Method and system for use of mutant mRNA in liquid biopsies to risk stratify and manage cancer

Abstract

Herein are the methods, systems, and devices for detecting and measuring messenger RNA transcripts that contain mutations, post-translational modifications, and, or polymorphisms (mut-mRNA) characteristic of diseased tissue that can be isolated from one tissue and / or from circulation; for example, blood, for the purpose of detecting and managing disease. The disclosure also relates to in vitro molecular diagnostics.

Description

DOCKET NO. BSBI-026-PCT PCT APPLICATION METHOD AND SYSTEM FOR USE OF MUTANT MRNA IN LIQUID BIOPSIES TO RISK STRATIFY AND MANAGE CANCER CROSS REFERENCE TO RELATED APPLICATION

[0001] This application claims the benefit of U.S. Provisional Patent Application No. 63 / 603,471, which is titled Reagents, Kits and Methods for Assessing the Likelihood and Risk of Developing a Disease, Disorder or Condition of the Liver, was filed November 28, 2023, and is incorporated herein by reference as if fully set forth. GOVERNMENT SUPPORT STATEMENT

[0002] This invention was made with government support under CA166111 and A00-2219- 5010 awarded by the National Institutes of Health and I01-CX-001933 and 01-CX-000988 awarded by the Veterans Administration. The government has certain rights in the invention. FIELD

[0003] The disclosure relates to detection, risk stratification, and management of disease, including liver cancer. Described herein are the methods, systems, and devices for detecting and measuring messenger RNA transcripts that contain mutations, post-translational modifications, and, or polymorphisms (mut-mRNA) characteristic of diseased tissue that can be isolated from tissue and / or from circulation; for example, blood, for the purpose of detecting and managing disease. The disclosure also relates to in vitro molecular diagnostics. BACKGROUND

[0004] In the case of hepatocellular carcinoma (HCC) and cholangiocarcinoma (CC) which we describe in detail in this patent application, early detection and molecular information that can guide therapy is of great value. Those at relatively high risk for HCC are a subpopulation including those with chronic viral hepatitis (HBV and HCV) or those who have been successfully “cured” of HCV, those with liver cirrhosis due to any cause, those with Metabolic liver diseases, those with alcoholic liver disease and those with a family history of liver cancer. These individuals should be screened and surveilled for liver cancer regularly, perhaps once or twice a year. However, current methods are deficient.

[0005] Hepatocellular carcinoma (HCC) is the 5thmost deadly cancer worldwide and is projected to become the 3rd leading cause of cancer-related deaths by 2030. Although HCC incidence has leveled off in the past 2 years, its decade-long rise has been attributed to theDOCKET NO. BSBI-026-PCT PCT APPLICATION increasing prevalence of chronic liver disease (CLD) due to metabolic-associated steatohepatitis (MASH), Chronic hepatitis C (CHC) and chronic hepatitis B (CHB) which can all progress to Liver Cirrhosis (LC). Most HCC occurs in a setting of LC, although importantly, as much as 30% does not.

[0006] Early HCC detection is critical to improve outcomes. 5-year survival of patients with HCC is ~18%, but is significantly influenced by the stage at which the cancer is detected. For example, it is >60 months when detected early, but <15 months when detected at an advanced stage. Early-stage patients are eligible for curative therapies, including resection, ablative therapies, and liver transplantation, whereas late-stage patients are generally only eligible for palliative systemic therapies with suboptimal response rates. But HCC is frequently not detected early.

[0007] The failure to detect HCC early is due partly to a lack of surveillance implementation but also due to the limited efficacy and practicality of the current surveillance and screening methods.

[0008] Current methods, including the formula that uses Gender, Age, serum L3, AFP and DCP protein levels, (GALADs), still miss 20-40% of Early HCC. Ultrasound (US) to detect HCC with or without serum alpha-fetoprotein (AFP) testing conducted every 6 months for screening is recommended for all LC patients as well as certain high-risk non-cirrhotic patients. US is operator dependent is not sensitive for early lesions. The performance of AFP varies widely and is used as a risk marker but not for diagnosis of HCC.

[0009] A diagnosis of HCC is usually made without biopsy, so improved imaging techniques, such as abbreviated MRI, supported by new non-invasive biomarkers are of great interest. Risk estimation models such as REACH B for those with CHB and The GALAD score (Gender, Age, AFP-L3, AFP, DCP), and the “Doylestown” Algorithm, combine simple demographic data with serum biomarkers. These are promising, but most still rely on AFP. Although different studies get different results, and specificities are usually good, the current and even most investigational approaches still miss as much as 35-40% of the cases and offer little information about the tumor, itself. Clearly, new non-invasive markers are needed. SUMMARY

[0010] In an aspect, the disclosure relates to a method. In some embodiments, the method comprises extracting analyte RNA comprising mRNA and long non-coding RNA from a liquid sample and determining whether the analyte RNA comprises one or more variant mRNA and / or the long non-coding RNA comprises one or more variant long non-coding RNA. The sampleDOCKET NO. BSBI-026-PCT PCT APPLICATION is from a subject. In some embodiments, the method is for determining whether the sample comprises one or more variant mRNA and / or one or more variant long non-coding RNA. In some embodiments, the method is for determining whether the sample comprises one or more variant mRNA and / or one or more variant long non-coding RNA associated with a disease or disorder state.

[0011] In an aspect, the disclosure relates to a method. In some embodiments, the method comprises extracting analyte RNA comprising mRNA and long non-coding RNA from a liquid sample from a subject, determining whether the analyte RNA comprises one or more variant mRNA and / or one or more variant long non-coding RNA, wherein the one or more variant mRNA and / or one or more long non-coding RNA are biomarkers indicative of a disease or disorder state. In some embodiments, the method further comprises identifying the subject as having the disease or disorder upon determining the analyte RNA comprises the one or more variant mRNA and / or the one or more variant long non-coding RNA.

[0012] In an aspect, the disclosure relates to a method. In some embodiments, the method comprises conducting the method of determining whether the sample comprises one or more variant mRNA and / or one or more variant long non-coding RNA herein. In some embodiments, the method comprises conducting the method of determining whether the sample comprises one or more variant mRNA and / or one or more variant long non-coding RNA associated with a disease or disorder state herein. In some embodiments, the method comprising conducting a method of diagnosis herein. In some embodiment the method is conducted on a liquid sample from a subject having been diagnosed with the disease or disorder or under treatment for the disease or disorder. In some embodiments, the disease or disorder state is cancer.

[0013] In some embodiments, the disclosure relates to a method method of treatment. In some embodiments, the method comprises conducting the method of determining whether the sample comprises one or more variant mRNA and / or one or more variant long non-coding RNA herein. In some embodiments, the method comprises conducting the method of determining whether the sample comprises one or more variant mRNA and / or one or more variant long non-coding RNA associated with a disease or disorder state herein. In some embodiments, the method comprising conducting a method of diagnosis herein. In some embodiments, the method further comprises administering a treatment matching a disease or disorder associated with the one or more variant mRNA and / or one or more variant long non-coding RNA.

[0014] In some embodiments, the disclosure relates to a composition comprising a liquid sample from a subject and any one or more primer herein.DOCKET NO. BSBI-026-PCT PCT APPLICATION

[0015] In some embodiments, the disclosure relates to a plasma-derived extracellular vesicle and one or more primer herein.

[0016] In some embodiments, the disclosure relates to a method of preparing a sample. In some embodiments, the method comprises precipitating extracellular vesicles from a liquid sample from a subject.

[0017] In some embodiments, the disclosure relates to a method for detecting an internal disease or disorder comprising (a) obtaining a biological sample from a subject; (b) isolating mRNA-derived transcripts that are normal or containing mutations, polymorphisms or post- translational modifications from the sample; (c) identifying the disease-associated mutations and (d) stratifying the subject's disease risk based on the presence of said mutations.

[0018] In some embodiments, the disclosure relates to a method comprising detection and or quantification of messenger Ribonucleic Acids (mRNA) or fragments thereof, or any group of mRNAs or groups of mRNA fragments in the blood for the purpose of disease detection as in claims 69–73, disease risk stratification of any disease, disease risk stratification of cancer, disease risk stratification of liver cancer, disease risk stratification of hepatocellular carcinoma, or disease risk stratification of cholangiocarcinoma.

[0019] In some embodiments, the disclosure relates to a kit comprising: a plurality of containers, wherein at least one of the plurality of containers contains a primer complementary to a first nucleic acid sequence proximal to an mRNA or long non-coding RNA variant position. In some embodiments, the primer is a sequencing primer configured to sequence a second nucleic acid sequence comprising the mRNA or long non-coding RNA variant position. In some embodiments, the primer is a first PCR primer configured to amplify the second nucleic acid sequence comprising the mRNA or long non-coding RNA variant position.

[0020] In some embodiments, the disclosure relates to a kit comprising: a plurality of containers, wherein at least one of the plurality of containers contains one or more primers complementary to one or more first nucleic acid sequence proximal to respective one of mRNA or long non-coding RNA variant position selected from a plurality of mRNA or long non- coding RNA variant positions. In some embodiments, at least one of the primers is a sequencing primer configured to sequence a respective second nucleic acid sequence comprising the mRNA or long non-coding RNA variant position. In some embodiments, at least two of the one or more primers comprise a forward PCR primer and a reverse PCR primer configured to amplify a respective second nucleic acid sequence comprising the mRNA or long non-coding RNA variant position.DOCKET NO. BSBI-026-PCT PCT APPLICATION BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The following detailed description of the preferred embodiment of the present invention will be better understood when read in conjunction with the appended drawings. For the purpose of illustrating the invention, there are shown in the drawings certain embodiments. It is understood, however, that the invention is not limited to the precise arrangements and instrumentalities shown. In the drawings:

[0021] FIGS.1A and 1B illustrate diversity and profiles of circulating mRNA variants detected in the circulation, circulating extracellular vesicles and tumors of HCC patients. FIG.1A. Bar charts representing proportion or frequency of occurrence (% age) in patient and control specimens; HCCMV: HCC circulating micro-vesicles (n=6); HCCT: HCC tumors (n=6); HCCP: HCC plasma (n=14); LC: liver cirrhosis plasma (n=8); NHCP: healthy control plasma (n=6). Separate bar graphs are shown to represent profiles by type, impact, and functional class of variants. Error bars represent the variation within samples. FIG.1B. Bar graphs representing the total number and number of variant counts corresponding to different categories in the same sample subsets as FIG.1A. The average number of variants per sample in RNA collected from different sources of subjects represented by the height of the bar, while the error bar showing the standard deviation within the group. Variant calling used a depth >=5 and QUAL value >=20. The 'QUAL' value for each called SNP is calculated as -log10(p) where p is the p value yielded from the statistical test carried out by ExactSNP. Therefore, a 'QUAL' value of 20 corresponds to a p value of 10^-20, which is extremely low.

[0022] FIGS. 2A and 2B illustrate a filtration summary for derivation of high-risk HCC- specific mRNA variants and concordance of detection between different sample subsets from HCC patients. FIG. 2A. The FASTQ files from NGS platform (illumina) were pre-processed to remove the residual of sequencing adapter in the files. The trimmed data were input into STAR, an aligner for RNA-Seq mapping, for alignment against human reference genome GRCh38. The alignments (BAM) were processed with GATK tools (v4.1.7.0) for spliting on reads with N cigar, base quality score recalibration, and variants calling by HaplotypeCaller. The variants reported by GTAK were filtered by depth (>=5) and quality (>=20) and annotated with snpEff for location on genes / transcripts, mutation type and putative biological impact. The number in the boxes indicate the total unique variants identified in samples of different groups. Variants occurred in multiple samples within the same group were counted once only. Only high-risk variants and those with highest frequency in tumors and HCC plasma were considered during enrichment. High-risk variants also detected in the circulation of liver cirrhosis patients and normal healthy individuals were excluded leading us to cancer-associated high-riskDOCKET NO. BSBI-026-PCT PCT APPLICATION variants referred to as tumor-centric variants. FIG.2B. Venn diagram showing the distribution and overlap of tumor-centric variants with total high-risk variants in various sample sources. The number of High-risk variants identified only in a single sample type either plasma, tumor and vesicles are 30,457, 25,109 and 18,894, repectively, reflecting the heterogeneity and difference in variant profiles attributed to the source of RNA. However, there are still 5,036 variants occurring in RNA from all three sources. Furthermore, 1,775 of them were among 5,480 tumor-related variants identified by tumor-control comparison, suggesting the plasma / vesicle RNA share abundant / significant transcripts carrying the tumor associated variants.

[0023] FIG.3 illustrates profile of top high-risk concordant variants detected selectively in the plasma and tumors of HCC patients. Indicated occurrence (light shading) of 1,501 high-risk variants identified in plasma of HCC patients but not in liver cirrhosis and healthy controls, with clustering dendrogram of samples on the top. Most of the tumor samples were clustered on the left part of the figure, while the vesicle samples on the right side. The liver cirrhosis and healthy controls not carrying the variants (dark shading) stay in the middle section.

[0024] FIG.4 illustrates liver specific transcripts in HCC patients reflect higher levels of high- risk variants than those from liver cirrhosis patients and healthy controls. The bar graphs represent the average counts of high-risk variants on 32 liver specific transcripts in several sample groups and error bar showing the standard deviation. Clearly plasma from HCC patients show significantly higher mutation load than that of LC patients.

[0025] FIGS. 5A–5C illustrates characterization of extracellular vesicles isolated from the plasma and profiles of high-risk tumor specific mRNA variants within the EVs of HCC patients. FIG. 5A. Plasma samples from HCC patients, LC patients without HCC and normal healthy controls were spun to remove the cellular debris before precipitation of EVs using ExoQuick kit followed by ultracentrifugation. followed by NanoSight tracking and Chip analysis. Dilutions of samples with PBS were carried out as shown in methods followed by Zetaview NTA analysis. 11 positions / frames were used to analyze each sample. Y-axes represent particles / ml and x-axes represent particle diameter in nm. The highest value on y axes reflects the number of particles / ml at the peak. FIG. 5B. Exoview chip analysis was carried out to evaluate tetraspanin receptor expression. EVs stained for CD63, CD81 and CD19 antibodies and anti CD41a and mIgG used as controls. Data is represented as pie charts to reflect the tetraspanin receptor profiles in EVs from two HCC, 1 LC and 1 CCA patients. LC patient derived EVs seem to have a higher expression of CD63 compared to HCC or CCA patients. FIG.5C. Heat map representing occurrence (light shading) of 1,369 high-risk variantsDOCKET NO. BSBI-026-PCT PCT APPLICATION identified in EVs of HCC patients but not in LC and NHC controls, with clustering dendrogram of samples on the top. Most of the EV samples are clustered on the right side, along with RNA from cancer patients (tissue and plasma).

[0026] FIGS.6A and 6B illustrate concordance of high-risk variants in three matching samples from same cancer patients. FIG.6A. Venn diagrams corresponding to 6 cancer patients (4 HCC, 2 CCA) with three matching specimens, EVs, tumor and plasma from each subject and three subjects with two matching specimens. The numbers represent the distribution and concordance of high-risk mRNA variants in multiple samples from same patients. FIG. 6B. Heat map representation of top genes carrying highest number of high-risk concordant variants. The number of high-risk variants, which were identified simultaneously in different types of samples (plasma, tumor, and / or vesicle) from same cancer patient, but not presented in any of liver cirrhosis or healthy control, were summarized by gene carrying them. The first 50 genes carrying the most of such high-risk concordant variants were selected and the numbers of variants on those genes were plotted against samples. UNC13D shown at the top, for example has the highest number of variants in HCC patient specimens.

[0027] FIGS. 7A and 7B illustrate high-risk concordant variants associated with cholangiocarcinoma. FIG. 7A. Pie charts representing profound synergy in high-risk variants between HCC and CCA patients. All 336 highrisk variants concordant in CCA samples (n=6) are also detected in HCC samples but none in LC and NHC controls. FIG. 7B. Heat map representing the profiles of concordant CCA variants in various samples.

[0028] FIGS. 8A–8C illustrate the KEGG pathway enrichment analysis conducted with R package cluster Profiler using “Over-representation analysis” based on hypergeometric distribution in the subset of genes with tumor-centric mutations. Over-representation of 578 genes with tumor-centric mutations in KEGG pathway / Gene Ontology (GO) terms.

[0029] FIG. 9. Illustrates the KEGG pathway / Gene Ontology enrichment analyses on top tumor-centric variants. Transcripts carrying tumor-related mutations show clustering of these genes in cancer related pathways and biological processes. Chord in the diagram indicate the connection between genes (blocks at left side) and pathways / processes (blocks on the right side). Some pathways / processes were merged for simplification. As can be seen, metabolism- related genes seem to be predominantly altered in HCC.

[0030] FIG. 10 illustrates inflammatory and toxic milieu in the liver influences the tumor microenvironment resulting in release of tumor derived transcripts in the circulation. Malignant tumor cells exhibit pervasive changes in DNA which consequently lead to a variety of changes in gene expression or genomic instability. Both functionally normal and tumor cells in liverDOCKET NO. BSBI-026-PCT PCT APPLICATION communicate with their surroundings through exosomes which are able to enter the loose endothelial vasculature in liver and land in the circulation. In addition to DNA, proteins and lipids, both free floating RNA and RNA within exosomes are found in circulation. Exosomes are vesicles of endosomal origin with tetraspanin receptors embedded in the protein lipid bilayer. Exosomes represent safe vehicles to protect nucleic acids and other cargo from degradation in circulation. We investigated RNA from three different samples from HCC / CCA patients by RNAseq, GATK and SNPeff analyses and identified high-risk RNA variants concordant in all cancer samples but not detected in noncancer liver cirrhosis patients and normal healthy controls. After characterization in a larger patient cohort, a mutant RNA signature can be derived which can be validated and used in HCC surveillance to accurately identify high risk patients and actionable targets and guide in patient management.

[0031] FIGS. 11A–11D illustrate variable approaches of isolating sEVs from human circulation for specific detection of circulating RNA. FIG. 11A. Tapestation Capillary electrophoresis gel showing sizes and quantities of RNA isolated from a single individual with different serum and four plasma preparations (EDTA, ACD, Na-Citrate and Na-Heparin). Ladder markers shoe fragment length in numbers of nucleotides. The bar chart displays the total amount of RNA in picograms, extracted from those different samples and quantified on a Tapestation 4200. FIG. 11B. sEV isolation using UC, ExoQuick, TM 1 and TM 2. Histogram plot of particle size vs particle density distribution obtained using NTA analysis using a ZetaView instrument from each sEV isolation method. FIG. 11C. Bar chart of copy number count of ALB, FTL and Actin-Beta transcripts from RNA extracted from isolated sEVs using four previously described methods, determined by qPCR. FIG. 11D. Bar chart showing the effects of DNase I on copy numbers of liver specific gene transcripts from RNA isolated from plasma-derived sEVs. Comparing the amount for each gene demonstrates the negligible amount of DNA captured during the RNA isolation protocol. A synthetic DNA ultramer spiked in samples was used to generate a standard curve to calculate copy numbers.

[0032] FIGS.12A and 12B. FIG.12A. Whole blood was drawn from one individual and serum and plasma was prepared from these samples. Serum samples were prepared by incubating at room temperature for 30 minutes and centrifuging the samples at 2000 x g at 4 degrees C for 10 minutes. Plasma was prepared by 4 different anti-coagulants (EDTA, ACD, Sodium-Citrate, and Sodium Heparin) and samples were centrifuged at 2000 x g for 15 minutes at 4 degrees C. Two 0.5 mL aliquots of each preparation were used to isolate RNA using the miRNeasy Serum / Plasma kit (Qiagen). Polynucleotide kinase (PNK) reaction was carried out in one of the replicates and other relicate was left untreated. A Tapestation 4200 instrument (Agilent)DOCKET NO. BSBI-026-PCT PCT APPLICATION with HSRNA Screentape was used to analyze and quantify the RNA content in each sample. FIG. 12B. Fresh or frozen plasma samples were processed for sEV isolation using either column (ExoRNAeasy Qiagen), Exoquick precipitation and / or ultracentrifugation and RNA extracted from sEVs using Qiagen serum / plasma miRNA isolation kit. sEV-derived RNA yield was measured by Tapestation and fresh and frozen plasma samples were compared.

[0033] FIGS.13A–13C illustrate circulating RNA as a robust analyte with potential for use as a stable biomarker. FIG. 13A. Table and Line Graph showing the increasing numbers of sEV particles recovered from increasing volumes of EDTA Plasma collected at the same time point from one individual using different sEV isolation methods. sEVs collected using UC, ExoQuick, and TM 1 and TM 2 from increasing volumes of plasma were quantified using NTA on the ZetaView instrument. FIG. 13B. Tapestation Capillary electrophoresis gel of RNA extracted from EVs using all four isolation methods with increasing starting amount of plasma. Ladder markers are expressed in number of nucleotides. The line graph shows the amount of RNA recovered in picograms from each isolation method and amount of plasma. FIG. 13C. Blood was drawn from one individual at three different timepoints: Days 1, 3, and 8. Plasma was created from these samples using EDTA, frozen and thawed, then total RNA was isolated from each sample. A capillary gel image (left panel) of RNA isolated at each time point and the quantity of RNA by Tapestation. Copy numbers of different liver specific transcripts (right panel) determined by RT-PCR.

[0034] FIG. 14 illustrates diversity and profiles of circulating mRNA variants detected in the plasma samples from non-cancer LC patients, early-stage HCC and late-stage HCC patients and HCC tumor tissues. Bar graphs representing the total number and number of variant counts corresponding to different categories in independent sample subsets. The counts of variants with different features (SNP / deletion / insertion / duplication), or impact (high / moderate / low- risk, or frameshift / stop-gained / missense / synonymous-sense) were plotted by the group, with the height as the average counts and error bar as standard deviation. The average number of variants per sample in RNA collected from different sources of subjects is represented by the height of the bar, while the error bar shows the standard deviation within the group. Variant calling used a depth ≥ 5 and QUAL value ≥ 20. The ‘QUAL’ value for each called SNP is calculated as -log10(p) where p is the p value yielded from the statistical test carried out by ExactSNP. Therefore, a ‘QUAL’ value of 20 corresponds to a p value of 10-20 which is extremely low.

[0035] FIGS.15A and 15B illustrate filtration summary for derivation of early- and late-stage HCC-specific circulating mRNA variants. FIG.15A. The FASTQ files from the NGS platformDOCKET NO. BSBI-026-PCT PCT APPLICATION (Illumina) were pre-processed to remove the residual bases of the sequencing adapter in the files. The trimmed data were input into STAR, an aligner for RNA-Seq mapping, for alignment against human reference genome GRCh38. The alignments (BAM) were processed with GATK tools (v4.1.7.0) for splitting on reads with N cigar, base quality score recalibration, and variants calling by HaplotypeCaller. The variants reported by GATK were filtered by depth (≥5) and quality (≥ 20). The number in the boxes indicates the total variants and average variants / sample identified in different sample subsets. Variants that occurred in multiple samples within the same group were counted once only. After the variants were annotated with snpEff for location on genes / transcripts, mutation type, and putative biological impact, only high-risk variants with the highest frequency in tumors and HCC plasma were considered during enrichment. FIG. 15B. Venn diagrams show the distribution and overlap of total variants (left panel) and high- risk variants (right panel) in four clinical subsets. One can see a significant number of variants uniquely associated with early or late-stage HCC samples.

[0036] FIG. 16 illustrates a binary heat map representing top 250 recurrent high-risk variant transcripts associated with early-stage and late-stage HCC patients. High-risk variants recurring from 4 to 12% HCC-plasma samples, including 25 early-stage HCC and 25 late-stage HCC plasma samples, are shown. The color intensity reflects mutant allele frequency (MAF). Among these 142 variants associated with early-stage HCC and 118 variants with late-stage HCC samples. None of these variants were detectable in one normal liver tissue and 31 LC samples without HCC. Color dendrogram / intensity represents allelic frequency of ctmutRNA variants.

[0037] FIGS. 17A and 17B illustrate a heat map representation of highly recurrent variants associated with liver cirrhosis plasma. Profiles of highly recurrent variants detected in HCC tumor tissues and cell lines. FIG.17A. A panel of 793 highly recurrent variants associated with both liver cirrhosis (0.32 to 77%) and HCC (0 to 80%) plasma samples with high MAF are depicted in the heat map and shown in supplementary table 5. FIG. 17B. Heat map representation of variants highly recurrent in 11 HCC tumor tissues and three cell lines using Targeted RNA Seq. None of these variants are detected in the normal liver tissue.

[0038] FIG. 18 illustrates dissecting out three ctmutRNA panels exhibiting high diagnostic performance. Diagnostic performance of variants expressed as a plot between number of variants on x axis and number of HCC patients identified on y-axis.The criteria for identifying panels are shown in Results section. As the variant number increases more HCC patients are identified such that a panel of 23 variants identify all HCC patients in our cohort. Variant panelsDOCKET NO. BSBI-026-PCT PCT APPLICATION can be reduced to 18 and 17 variants with compromised specificity by including 1 and 2 variants, respectively, detectable in LC patients.

[0039] FIGS. 19A and 19B illustrate novel mRNA fusion variants detected in the circulation of LC / HCC patients. Examples of relevant exon-exon links that are supported by the largest number of molecular tags are shown. Illustration to exemplify the relevant exon-exon links supported by the largest number of tags. The set of rectangles connected and sharing the same color codify the exons of the same transcript. The thickness of rectangle links represents the level of observed tags supporting the connection. Links of the same color as rectangles illustrate connections among exons belonging to the same transcript. Many genes have multiple reported splice variants. While the coordinates (on RNA level) for these fusion events are correct, the illustrated exon structure around it may represent only a subset of possible variants associated with the genes shown. The fusion plot visualizes all fusions between the reported transcripts: Green box - an exon in the 5' reported transcript; Blue box - an exon in the 3' reported transcript; Gray box - an exon (or portion) that is not in the reported transcript, may be present in other transcripts, or may represent a novel exon not seen in any transcript; Purple lines - fusion connections within different transcripts; Gray lines - connections due to alternative splicing between exons in the reported transcript, the number of reads splicing between the exons is shown on each line; Yellow vertical lines within green or blue boxes - indicate that fusion reads spliced > 12nt into the exon rather than at the exon boundary; Red lines - indicate fusions at the exon boundary. Grey boxes with nucleotide sequences illustrate Assembled fusion transcript consensus. Supporting reads for fusions of pair of genes were assembled by SPAdes. The resulting consensus contig is reported in the middle and the individual exons sharing that are reported above and below that and are highlighted with the same color code as in the rectangles above.

[0040] FIG.20 illustrates a schematic description of fusions

[0041] FIG.21 illustrates mRNA derived that transcripts in the blood come from many organs. DETAILED DESCRIPTION

[0015] Certain terminology is used in the following description for convenience only and is not limiting. The words “right,” “left,” “top,” and “bottom” designate directions in the drawings to which reference is made.

[0042] The words “a” and “one,” as used in the claims and in the corresponding portions of the specification, are defined as including one or more of the referenced item unless specifically stated otherwise. As used in the present disclosure and claims, the singular forms “a,” “an” andDOCKET NO. BSBI-026-PCT PCT APPLICATION “the” include plural forms unless the context clearly dictates otherwise. The phrase “at least one” followed by a list of two or more items, such as “A, B, or C” or “A, B, and C,” means any individual one of A, B or C as well as any combination thereof. Likewise, the phrase “one or more of” followed by a list of two or more items, such as “A, B, or C” or “A, B, and C,” means any individual one of A, B or C as well as any combination thereof. The term “and / or” as used in a phrase such as “A and / or B” herein includes both A and B, A or B, A (alone), and B (alone). Likewise, the term “and / or” as used in a phrase such as “A, B, and / or C” encompasses each of the following embodiments: A, B, and C; A, B, or C; A or C; A or B; B or C; A and C; A and B; B and C; A (alone); B (alone); and C (alone).

[0043] Unless defined otherwise, technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. For example, Singleton et al., Dictionary of Microbiology and Molecular Biology 2nd ed., J. Wiley & Sons (New York, NY 1994), provide one skilled in the art with a general guide to many of the terms used in the present application. Additionally, the practice of the present disclosure will employ, unless otherwise indicated, conventional techniques of molecular biology (including recombinant techniques), microbiology, cell biology, and biochemistry, which are within the skill of the art. Such techniques are explained fully in the literature, such as, “Molecular Cloning: A Laboratory Manual,” 2nd edition (Sambrook et al., 1989); “Oligonucleotide Synthesis” (M.J. Gait, ed., 1984); “Animal Cell Culture” (R.I. Freshney, ed., 1987); “Methods in Enzymology” (Academic Press, Inc.); “Handbook of Experimental Immunology,” 4th edition (D.M. Weir & C.C. Blackwell, eds., Blackwell Science Inc., 1987); “Gene Transfer Vectors for Mammalian Cells” (J.M. Miller & M.P. Calos, eds., 1987); “Current Protocols in Molecular Biology” (F.M. Ausubel et al., eds., 1987); and “PCR: The Polymerase Chain Reaction,” (Mullis et al., eds., 1994).

[0044] It is understood that wherever embodiments are described herein with the language “comprising” otherwise analogous embodiments described in terms of “consisting of” and / or “consisting essentially of” are also provided. It is also understood that wherever embodiments are described herein with the language “consisting essentially of” otherwise analogous embodiments described in terms of “consisting of” are also provided.

[0045] The term “about” as used herein when referring to a measurable value such as an amount, a temporal duration, and the like, is meant to encompass variations of ±20% from the specified value, as such variations are appropriate to perform the disclosed methods. Further embodiments herein comprise modification of any numerical value herein with ±10%, ±5%,, ±1%, or ±0.1%. For recitation of numeric ranges herein, each intervening number therebetweenDOCKET NO. BSBI-026-PCT PCT APPLICATION with the same degree of precision is explicitly contemplated. For example, for the range of 6– 9, the numbers 7 and 8 are contemplated in addition to 6 and 9, and for the range 6.0–7.0, the numbers 6.0, 6.1, 6.2, 6.3, 6.4, 6.5, 6.6, 6.7, 6.8, 6,9, and 7.0 are explicitly contemplated.

[0046] A subject, as used herein, is an animal. In some embodiments, the animal is a mammal. In some embodiments, the mammal is a human.

[0047] As used herein, a liquid sample is a bodily fluid of a subject. In some embodiments, the bodily fluid is blood, plasma, serum, urine, or saliva. In some embodiments, bodily fluid is free of cells. In some embodiments, bodily fluid is free of cells other than blood cells.

[0048] Liquid biopsy, as used herein, means molecular analysis of a bodily fluid, for example blood, plasma, serum, urine, or saliva. In some embodiments, the bodily fluid is free of cells. In some embodiments, the bodily fluid is free of cells other than blood cells.

[0049] mRNA means messenger RNA, fragments thereof, and alterations thereof occurring post-transcriptionally. A wild type mRNA may include full length transcripts or fragments of a full length transcript but would still retain the wt sequence in the fragments. A variant mRNA varies from wild type by including any of a number of variations, including but not limited to single nucleotide polymorphisms (SNPs), nucleotide insertions and deletions (called Indels), and splicing variants.

[0050] Long non-coding RNAs (long ncRNAs, lncRNA) means RNA transcripts more than about 200 nucleotides that are not translated into protein. Long ncRNAs are distinguished from microRNAs (miRNAs), small interfering RNAs (siRNAs), Piwi-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs), and other short RNAs. lncRNAs have no or limited coding capacity. A wild type lncRNA may include full length transcripts or fragments of a full length transcript but would still retain the wt sequence in the fragments. A variant lncRNA varies from wild type by including any of a number of variations, including but not limited to single nucleotide polymorphisms (SNPs), nucleotide insertions and deletions (called Indels), and splicing variants.

[0051] At certain points, the disclosure may discuss the sequence of an RNA or of a DNA. When discussion is made of an RNA with respect to a disclosed sequence containing T, it is understood that the RNA includes an RNA backbone and a U at the position listed as a T.

[0052] Embodiments herein comprise detection of internal diseases without obtaining portions of internal tissue. In some embodiments, a liquid biopsy platform is provided to detect, risk stratify and manage internal diseases, with cancer being the exemplary model.

[0053] Advantages of using RNA variants as non invasive markers may include one or more of the following. As with tumor derived DNA in the circulation, variant RNA present in theDOCKET NO. BSBI-026-PCT PCT APPLICATION blood does not require biopsy and provides a sampling of the entire tumor, not just a limited section that results from biopsy; examination of RNA allows for detection of gene products that may not be translated or secreted as protein; mRNA variants may be tumor selective and for many that we will pursue, provide information about the cancer pathobiology and drug sensitivity; DNA from the tumor is limited in copy number, whereas RNA is amplified and may allow for greater sensitivity; mRNA variants may be an excellent complement to miRNA and protein biomarkers, since they are from distinct pathways.

[0054] Some embodiments comprise detection of cancers or other disorders occurring by a simple, inexpensive assay using blood, plasma, urine, or saliva. In some embodiments, a signal indicating the probability of cancer or other disorder resulting from the assay on the easy-to- obtain body fluid would be followed by other confirmatory procedures, such as imaging or even biopsy.

[0055] Some embodiments comprise detection of hepatocellular carcinoma (HCC) or cholangiocarcinoma (CC). Early detection and molecular information that can guide therapy is of great value and embodiments herein may provide such early detection. The methods herein may apply to those at relatively high risk for HCC are a subpopulation including those with chronic viral hepatitis (HBV and HCV) or those who have been successfully “cured” of HCV, those with liver cirrhosis due to any cause, those with Metabolic liver diseases, those with alcoholic liver disease and those with a family history of liver cancer. In some embodiments, these individuals are screened and surveilled for liver cancer regularly, perhaps once or twice a year.

[0056] Embodiments herein comprise methods, systems, and devices for detecting and measuring messenger RNA transcripts (mRNA) that contain mutations, post-translational modifications, and, or polymorphisms (mut-mRNA) characteristic of diseased tissue that can be isolated from tissue and from circulation, such as blood for the purpose of detecting and managing disease. As used herein, mRNA-containing mutations, mut-mRNA, comprise one or more of mutations, post-transcriptional modifications, and polymorphisms. The mut-mRNA isolated from the circulation or other body fluids is called circulating mut-mRNA, or ct-mut- mRNA.

[0057] Embodiments provide a novel liquid biopsy-based assay for detecting early-stage liver cancer and assessing patient risk using circulating biomarkers. In some embodiments, the circulating biomarkers comprise mRNA isolated from body fluids such as the blood, plasma, urine, saliva, or other body fluids. In some embodiments, methods herein enables longitudinal monitoring of liver cancer progression and patient response to therapy.DOCKET NO. BSBI-026-PCT PCT APPLICATION

[0058] Embodiments herein comprise the unexpected discoveries of mutated mRNA and splicing variants in bodily fluids, mRNA in the blood from multiple organs. Assays for these analytes for detection, diagnosis, risk stratification, and disease management were heretofore unknown.

[0059] Methods herein, in some embodiments, are applicable to pathology internal organs. However, solid organ internal cancers and of HCC and CC are exemplified.

[0060] It is theorized that diseased organs in general, and cancers in particular, contain and shed or secrete into the circulation mRNA with mutations, post-transcriptional modifications, and or polymorphisms. mRNA, transcribed from DNA and then modified post- transcriptionally, is delivered into the extracellular spaces such as blood. When the gene specifying the RNA is mutated relative to the “germ line” sequence the individual was born with, or when the gene specifying the RNA contains a polymorphism that is rare in the general population, it will be represented in the RNA transcript. These transcripts may appear in a bodily fluid; for example, blood. In some cases, as outlined in the below Examples, the mRNA in the circulation is within vesicles, called exosomes. By obtaining samples of tissue, where possible, or of blood, where a less invasive approach is desired, the presence of cancer can be detected, or the level of cancer risk can be determined. In the case where tissue can be obtained, the cancer and its molecular nature can be confirmed. In some embodiments, total RNA in the blood or more efficiently, vesicles in the blood can then be isolated, and the RNA within them can be recovered and analyzed by Reverse Transcription (RT) PCR using primers and probes specific for the regions of interest, followed by product analysis for size, restriction enzyme profiling and, or nucleic acid sequencing.

[0061] In some embodiments methods herein comprises detecting a defined set of mut-mRNAs representing a set of different mutations, post-transcriptional modifications and or polymorphisms

[0062] In some embodiments, samples of blood are obtained. In some embodiments, other bodily fluids are obtained.

[0063] In some embodiments, the presence of specific mutations and polymorphisms, which are characteristic of cancer, are detected by methods that recognize and amplify mRNA, such as RT PCR or RNA seek, or targeted RNA seek.

[0064] In some embodiments, panels of specific mut-mRNAs found in the a bodily fluid, when present together, provide a strong indication of HCC. In some embodiments, the same mut- mRNAs found in tissue provide a strong indication of HCC.DOCKET NO. BSBI-026-PCT PCT APPLICATION

[0065] In some embodiments, panels of specific variant mRNAs found in the blood or tissue indicate the degree of likelihood of responding or not responding to specific medicines.

[0066] In some embodiments, a small sample of blood; for example, 1 ml, is taken from an individual by conventional phlebotomy. Either plasma or serum is used. In some embodiments, plasma is used so that extracellular vesicles can be recovered and RNA present in the vesicles is the analyte. If serum is used, total RNA is analyzed. In some embodiments, exosomes are isolated using commercial exosome recovery kits, as described herein. RNA is then isolated from the exosomes and subjected to targeted RNAseq or ELISA solution-type amplification as described in Methods, using primers specific for the mRNA sequences of interest.

[0067] In some embodiments, one or more biomarker indicative of disease is detected. The one or more biomarker, in some embodiments, relates to liver disorders and is chosen from the variants listed in Tables 7, 8, and 9 (Example 4). In some embodiments, the one or more biomarker relates to a disease or disorder variants listed in Tables 11–14. In some embodiments, the one or more biomarker is one or more variant selected from Tables 7–9 and 11–14.

[0068] In some embodiments, the disclosure relates to a method. In some embodiments, the method comprises extracting analyte RNA from a liquid sample. The analyte RNA may comprise mRNA and / or long non-coding RNA. In some embodiments, the method comprises determining whether the analyte RNA comprises one or more variant mRNA and / or one or more variant long non-coding RNA. In some embodiments, the sample is from a subject. In some embodiments, the method further comprises identifying the subject as having the disease or disorder upon determining the analyte RNA comprises the one or more variant mRNA and / or the one or more variant long non-coding RNA.

[0069] In some embodiments, the one or more variant mRNA and / or one or more long non- coding RNA are biomarkers indicative of a disease or disorder state In some embodiments, the determining comprises obtaining sequence information for the analyte RNA and comparing the sequence information to variant mRNA and variant non-coding mRNA sequences. In some embodiments, the method further comprises producing DNA from the extracted analyte RNA. In some embodiments, the DNA comprises one or more DNA molecules, each having a respective DNA sequence and the determining comprises identifying whether each respective DNA sequence comprises a biomarker sequence corresponding to the one or more variant mRNA and / or the one or more long non-coding RNA. In some embodiments, the determining comprises sequencing the DNA and comparing the respective DNA sequences to variant mRNA and variant non-coding mRNA sequences.DOCKET NO. BSBI-026-PCT PCT APPLICATION

[0070] In some embodiments, the subject is a mammal. In some embodiments, the subject is a human.

[0071] In some embodiments, the liquid sample is blood. In some embodiments, the method further comprises obtaining extracellular vesicles from the liquid sample. In some embodiments, the step of extracting mRNA comprises extracting the mRNA from the extracellular vesicles. In some embodiments, the method further comprises preparing plasma from the blood and the step of obtaining extracellular vesicles is performed on the plasma. In some embodiments, the step of preparing plasma comprises adding an anti-coagulant to the blood. In some embodiments, the anti-coagulant is one or more selected from EDTA, ACD, Sodium-Citrate, and Sodium Heparin.

[0072] In some embodiments, the one or more variant mRNA and / or one or more long non- coding RNA comprise one or more variant selected from Variant Nos.1–1061 from Tables 7– 9, and 11 and variants of Tables 12–14.

[0073] In some embodiments, the step of producing DNA from the analyte RNA comprises preparing DNA from the analyte RNA by reverse transcribing the analyte RNA. In some embodiments, the reverse transcribing comprises exposing the analyte RNA to one or more primer specific for the one or more variant mRNA and / or one or more long non-coding RNA, reverse transcriptase, and deoxynucleotides. In some embodiments, the one or more primer specific for the one or more variant mRNA and / or one or more long non-coding RNA is selected from Tables 10A and 10B. In some embodiments, the method further comprising conducting PCR on the DNA with one or more set of forward and reverse primers specific for one or more variant mRNA and / or one or more long non-coding RNA. In some embodiments, the one or more set of forward and reverse primers specific for one or more variant mRNA and / or one or more long non-coding RNA is selected from Tables 10A and 10B.

[0074] In some embodiments, the one or more variant mRNA and / or one or more long non- coding RNA are indicative of HCC and comprise one or more of Variant Nos. 1–255 from Tables 7–9, and the disease or disorder state is HCC. In some embodiments, the one or more variant mRNA and / or one or more long non-coding RNA are indicative of early-stage HCC and comprise one or more of Variant Nos. 310, 326, 328, 329, 332, 333, 338, 340, 343, 350, 355, 357, 359, 362, 366, 367, 368, 369, 370, 371, 374, 379, 380–386, 391–395, 397–399, 400, 402, 404, 405, 407–412, 415–418, 420–425, 431–433, 436–440, 448, 451, 474, 477, 479, 481, 482, 490, 491, 495, 508–510, 512, 515, 522, 527, 532, 533, 535, 543, 551, 554, 558, 575, 581, 582, 585, 586, 590, 605, 606, 614, 616, 640, 641, 643, 644, 647, 650, 660, 661, 664, 671–673, 675, 676, 679, 694–696, 705, 708, 709, 715, 835–840, and 847–971 from Tables 7–9, and theDOCKET NO. BSBI-026-PCT PCT APPLICATION disease or disorder state is early-stage HCC. In some embodiments, the one or more variant mRNA and / or one or more long non-coding RNA are indicative of late-stage HCC and comprise one or more of Variant Nos. 324, 330, 331, 337, 342, 345, 347, 349, 352–354, 356, 358, 360, 361, 363, 364, 365, 372, 373, 375–378, 387–390, 396, 401, 403, 406, 413, 414, 419, 426, 427–430, 434, 435, 441–445, 452, 455, 457, 458, 460, 464, 465, 470, 475, 476, 483, 485– 488, 494, 501, 504, 514, 517, 520, 521, 524, 526, 528, 531, 536, 540–542, 545, 547, 549, 553, 555, 556, 561, 563, 571–573, 576–580, 583, 584, 587, 592, 595, 597, 599, 602, 604, 607–609, 612, 615, 619, 620, 635, 636, 639, 649, 652, 654, 656, 658, 667, 674, 677, 678, 689–692, 697, 698, 700–702, 704, 706, 707, 710, 711, 716–834, and 841from Tables 7–9, and the disease or disorder state is late-stage HCC. In some embodiments, the one or more variant mRNA and / or one or more long non-coding RNA are associated with tumor tissues but are not detectable in normal liver tissue, and the disease or disorder state is presence of tumor tissue in the subject. In some embodiments, the one or more variant mRNA and / or one or more variant long non- coding RNA comprise transcripts of EPB41, M6PR, ARHGAP5, PRDX6, FASN, 346 ARCN1, SENP7, ECI1, IST1, ACOX1, or EIF3G variants, and the disease or disorder state is HCC. In some embodiments, the one or more variant mRNA and / or one or more long non-coding RNA are indicative of high-risk early stage HCC, and the disease or disorder state is high-risk early stage HCC. In some embodiments, the one or more variant mRNA and / or one or more long non-coding RNA are indicative of HCC and comprise one or more of Variant Nos. 298–309, 311–323, 325, 327, 334–336, 339, 341, 344, 346, 348, 351, 446, 447, 449, 450, 453, 454, 456, 459, 461–463, 466–469, 471–473, 478, 480, 484, 489, 492, 493, 496–500, 502, 503, 505–507, 511, 513, 516, 518, 519, 523, 534, 537–539, 624–634, 637, 638, 680–688, 693, 699, 703, 712– 714, and 842–846 from Tables 7–9, and the disease or disorder state is HCC.

[0075] In some embodiments, the one or more variant mRNA and / or one or more long non- coding RNA are indicative of cancer and comprise one or more of selected from Variant Nos. 1002–1061 (Table 11) and variants of Tables 12–14, and the disease or disorder state is cancer.

[0076] In some embodiments, the disclosure relates to a method of diagnosing a disease or disorder. In some embodiments, the method comprises extracting analyte RNA comprising mRNA and long non-coding RNA from a liquid sample from a subject. In some embodiments, the method comprises determining whether the analyte RNA comprises one or more variant mRNA and / or one or more variant long non-coding RNA. T In some embodiments, the one or more variant mRNA and / or one or more long non-coding RNA are biomarkers indicative of a disease or disorder state. In some embodiments, the method further comprises identifying the subject as having the disease or disorder upon determining the analyte RNA comprises the oneDOCKET NO. BSBI-026-PCT PCT APPLICATION or more variant mRNA and / or the one or more variant long non-coding RNA. In some embodiments, the method further comprises obtaining the liquid sample from the subject.

[0077] In some embodiments, the determining comprises obtaining sequence information for the analyte RNA and comparing the sequence information to variant mRNA and variant non- coding mRNA sequences.

[0078] In some embodiments, the method further comprises producing DNA from the extracted analyte RNA. In some embodiments, the DNA comprises one or more DNA molecules, each having a respective DNA sequence and the determining comprises identifying whether each respective DNA sequence comprises a biomarker sequence corresponding to the one or more variant mRNA and / or one or more variant long non-coding RNA. In some embodiments, the determining comprises sequencing the DNA and comparing the respective DNA sequences to variant mRNA and variant non-coding mRNA sequences.

[0079] In some embodiments, the subject is a mammal. In some embodiments, the subject is a human.

[0080] In some embodiments, the liquid sample is blood.

[0081] In some embodiments, the method further comprising obtaining extracellular vesicles from the liquid sample and the step of extracting mRNA comprises extracting the mRNA from the extracellular vesicles. In some embodiments, the method further comprises preparing plasma from the blood and wherein the step of obtaining extracellular vesicles is performed on the plasma. In some embodiments, the step of preparing plasma comprises adding an anti- coagulant to the blood. In some embodiments, the anti-coagulant is one or more selected from EDTA, ACD, Sodium-Citrate, and Sodium Heparin.

[0082] In some embodiments, the one or more variant mRNA and / or one or more long non- coding RNA comprise one or more variant selected from Variant Nos.1–1061 from Tables 7– 9, and 11 and variants of Tables 12–14.

[0083] In some embodiments, the step of producing cDNA from the extracted mRNA comprises preparing DNA from the mRNA by reverse transcribing the mRNA. In some embodiments, the reverse transcribing comprises exposing the mRNA to one or more primer specific for the one or more variant mRNA and / or one or more long non-coding RNA, reverse transcriptase, and deoxynucleotides. In some embodiments, the one or more primer specific for the one or more variant mRNA and / or one or more long non-coding RNA is selected from Tables 10A and 10B. In some embodiments, the method further comprises conducting PCR on the DNA with one or more set of forward and reverse primers specific for the one or more variant mRNA and / or one or more long non-coding RNA. In some embodiments, the one orDOCKET NO. BSBI-026-PCT PCT APPLICATION more set of forward and reverse primers specific for one or more variant mRNA and / or one or more long non-coding RNA is selected from Tables 10A and 10B.

[0084] In some embodiments, the one or more variant mRNA and / or one or more long non- coding RNA are indicative of HCC and comprise one or more of Variant Nos. 1–285 from Tables 7–9, and the disease or disorder state is HCC. In some embodiments, the one or more variant mRNA and / or one or more long non-coding RNA are indicative of early-stage HCC and comprise one or more of Variant Nos. 310, 326, 328, 329, 332, 333, 338, 340, 343, 350, 355, 357, 359, 362, 366, 367, 368, 369, 370, 371, 374, 379, 380–386, 391–395, 397–399, 400, 402, 404, 405, 407–412, 415–418, 420–425, 431–433, 436–440, 448, 451, 474, 477, 479, 481, 482, 490, 491, 495, 508–510, 512, 515, 522, 527, 532, 533, 535, 543, 551, 554, 558, 575, 581, 582, 585, 586, 590, 605, 606, 614, 616, 640, 641, 643, 644, 647, 650, 660, 661, 664, 671–673, 675, 676, 679, 694–696, 705, 708, 709, 715, 835–840, and 847–971from Tables 7–9, and the disease or disorder state is early-stage HCC. In some embodiments, the one or more variant mRNA and / or one or more long non-coding RNA are indicative of late-stage HCC and comprise one or more of Variant Nos. 324, 330, 331, 337, 342, 345, 347, 349, 352–354, 356, 358, 360, 361, 363, 364, 365, 372, 373, 375–378, 387–390, 396, 401, 403, 406, 413, 414, 419, 426, 427–430, 434, 435, 441–445, 452, 455, 457, 458, 460, 464, 465, 470, 475, 476, 483, 485– 488, 494, 501, 504, 514, 517, 520, 521, 524, 526, 528, 531, 536, 540–542, 545, 547, 549, 553, 555, 556, 561, 563, 571–573, 576–580, 583, 584, 587, 592, 595, 597, 599, 602, 604, 607–609, 612, 615, 619, 620, 635, 636, 639, 649, 652, 654, 656, 658, 667, 674, 677, 678, 689–692, 697, 698, 700–702, 704, 706, 707, 710, 711, 716–834, and 841 from Tables 7–9, and the disease or disorder state is late-stage HCC. In some embodiments, the one or more variant mRNA and / or one or more long non-coding RNA are associated with tumor tissues but are not detectable in normal liver tissue, and the disease or disorder state is presence of tumor tissue. In some embodiments, the one or more variant mRNA and / or one or more long non-coding RNA comprise transcripts of EPB41, M6PR, ARHGAP5, PRDX6, FASN, 346 ARCN1, SENP7, ECI1, IST1, ACOX1, or EIF3G variants, and the disease or disorder state is HCC. In some embodiments, the one or more variant mRNA and / or one or more long non-coding RNA are indicative of high-risk early stage HCC, and the disease or disorder state is high-risk early stage HCC. In some embodiments, the one or more variant mRNA and / or one or more long non- coding RNA are indicative of HCC and comprise one or more of Variant Nos. 298–309, 311– 323, 325, 327, 334–336, 339, 341, 344, 346, 348, 351, 446, 447, 449, 450, 453, 454, 456, 459, 461–463, 466–469, 471–473, 478, 480, 484, 489, 492, 493, 496–500, 502, 503, 505–507, 511, 513, 516, 518, 519, 523, 534, 537–539, 624–634, 637, 638, 680–688, 693, 699, 703, 712–714,DOCKET NO. BSBI-026-PCT PCT APPLICATION and 842–846 from Tables 7–9, and the disease or disorder state is HCC. In some embodiments, the one or more variant mRNA and / or one or more long non-coding RNA are indicative of cancer and comprise one or more variant selected from Variant Nos.1002–1061 (Table 11) and variants in Tables 12–14, and the disease or disorder state is cancer.

[0085] In some embodiments, the disclosure relates to a method of tracking disease or disorder progression comprising conducting a method of determining whether a sample comprises one or more variant mRNA or one or more variant long non-coding RNA herein or a method of diagnosis herein. In some embodiments, the method is conducted on a liquid sample from a subject having been diagnosed with the disease or disorder or under treatment for the disease or disorder, and the disease or disorder state is cancer. In some embodiments, the method further comprises detecting an amount of the mRNA comprising one or more disease biomarker sequence corresponding to the one or more variant messenger RNA sequence in the liquid sample. In some embodiments, the method is repeated two or more times. In some embodiments, the two or more times are separated by about one day, about one week, about one month, about one year, or about two years. In some embodiments, the method is conducted before a disease or disorder treatment is carried out on the subject. In some embodiments, the method further comprises conducting the method after a disease or disorder treatment is carried out on the subject.

[0086] In some embodiments, the disclosure relates to a method of treatment. In some embodiments, the method of treatment comprises conducting a method of determining whether a sample comprises one or more variant mRNA or one or more variant long non-coding RNA herein or a method of diagnosis herein. The method further comprises administering a treatment matching the disease or disorder discovered by the method of determining whether a sample comprises one or more variant mRNA or one or more variant long non-coding RNA herein or a method of diagnosis herein.

[0087] In some embodiments, the disclosure relates to a composition comprising a liquid sample from a subject and any one or more primer herein. In some embodiments, the any one or more primer is selected from Tables 10A and 10B.

[0088] In some embodiments, the disclosure relates to a composition comprising a plasma- derived extracellular vesicle and one or more primer herein. In some embodiments, the any one or more primer is selected from Tables 10A and 10B. In some embodiments, the composition further comprises one or more of reverse transcriptase, deoxynucleotides, and a heat-stable DNA polymerase. In some embodiments, the composition further comprises anDOCKET NO. BSBI-026-PCT PCT APPLICATION anticoagulant. In some embodiments, the anticoagulant comprises one or more of EDTA, ACD, Sodium-Citrate, and Sodium Heparin.

[0089] In some embodiments, the disclosure relates to a method of preparing a sample comprising precipitating extracellular vesicles from a liquid sample from a subject. In some embodiments, the liquid sample is blood. In some embodiments, the step of precipitating is preceded by preparing plasma from the blood and the step of precipitating is conducted on the plasma. In some embodiments, the step of preparing plasma comprises adding an anticoagulant to the blood. In some embodiments, the anti-coagulant is one or more selected from EDTA, ACD, Sodium-Citrate, and Sodium Heparin. In some embodiments, the method further comprises adding one or more primer selected from Tables 10A and 10B to the sample.

[0090] In some embodiments, the disclosure relates to a method for detecting an internal disease or disorder comprising (a) obtaining a biological sample from a subject; (b) isolating mRNA-derived transcripts that are normal or containing mutations, polymorphisms or post- translational modifications from the sample; (c) identifying the disease-associated mutations and (d) stratifying the subject's disease risk based on the presence of said mutations. In some embodiments, the internal disease or disorder is cancer. In some embodiments, the cancer is liver cancer. In some embodiments, the liver cancer liver is hepatocellular carcinoma. In some embodiments, the liver cancer is cholangiocarcinoma.

[0091] In some embodiments, the disclosure relates to a method comprising detection and or quantification of messenger Ribonucleic Acids (mRNA) or fragments thereof, or any group of mRNAs or groups of mRNA fragments in the blood for the purpose of disease detection as in claims 69–73, disease risk stratification of any disease, disease risk stratification of cancer, disease risk stratification of liver cancer, disease risk stratification of hepatocellular carcinoma, or disease risk stratification of cholangiocarcinoma.

[0092] Methods herein may be for the purpose of disease detection, disease risk stratification of any disease, disease risk stratification of cancer, disease risk stratification of liver cancer, disease risk stratification of hepatocellular carcinoma, or disease risk stratification of cholangiocarcinoma.

[0093] In some embodiments, the disclosure relates to a kit comprising: a plurality of containers. In some embodiments, at least one of the plurality of containers contains a primer complementary to a first nucleic acid sequence proximal to an mRNA or long non-coding RNA variant position. In some embodiments, the primer is a sequencing primer configured to sequence a second nucleic acid sequence comprising the mRNA or long non-coding RNA variant position. In some embodiments, the primer is a first PCR primer configured to amplifyDOCKET NO. BSBI-026-PCT PCT APPLICATION the second nucleic acid sequence comprising the mRNA or long non-coding RNA variant position.

[0094] In some embodiments, the primer is the first PCR primer and wherein at least one of the plurality of containers contains a second PCR primer. In some embodiments, the first PCR primer is a forward primer and the second PCR primer is a reverse primer, and the first and second primers are configured to amplify the second nucleic acid sequence comprising the mRNA or long non-coding RNA variant position. In some embodiments, the first PCR primer and the second PCR primer are selected from any PCR primer herein such that the first PCR primer and second PCR primer are matching forward and reverse primers configured to amplify the second nucleic acid sequence comprising the mRNA or long non-coding RNA variant position.

[0095] In some embodiments, the sequencing primer is selected from a sequencing primer herein.

[0096] In some embodiments, the variant is a variant herein. In some embodiments, the variant is a variant of Table 7–9 or 11–14.

[0097] In some embodiments, the kit further comprises an extracellular vesicle precipitant or device for precipitating extracellular vesicles as described in the below examples.

[0098] In some embodiments, the kit further comprises instructions to determine whether a liquid sample from a subject comprises a variant mRNA or variant long non-coding RNA.

[0099] In some embodiments, the disclosure relates to a kit comprising: a plurality of containers. In some embodiments, at least one of the plurality of containers contains one or more primers complementary to one or more first nucleic acid sequence proximal to respective one of mRNA or long non-coding RNA variant position selected from a plurality of mRNA or long non-coding RNA variant positions. In some embodiments, at least one of the primers is a sequencing primer configured to sequence a respective second nucleic acid sequence comprising the mRNA or long non-coding RNA variant position. In some embodiments, at least two of the one or more primers comprise a forward PCR primer and a reverse PCR primer configured to amplify a respective second nucleic acid sequence comprising the mRNA or long non-coding RNA variant position.

[0100] In some embodiments, forward PCR primer and the reverse PCR primer are selected from any PCR primer herein such that the forward PCR primer and reverse PCR primer are matching forward and reverse primers configured to amplify a respective second nucleic acid sequence. In some embodiments, at least four of the one or more primers comprise a plurality of forward PCR primers and a plurality of reverse PCR primers matched in respective pairs ofDOCKET NO. BSBI-026-PCT PCT APPLICATION forward and reverse PCR primers, each respective pair of forward and reverse PCR primers configured to amplify a respective second nucleic acid sequence. In some embodiments, each respective pair of forward and reverse PCR primers are selected from matching PCR primers herein.

[0101] In some embodiments, each sequencing primer is selected from any sequencing primer herein.

[0102] In some embodiments, the plurality of mRNA or long non-coding RNA variant positions comprise two or more variants herein. In some embodiments, the plurality of mRNA or long non-coding RNA variant positions comprise two or more variants of Tables 7–9 and 11–14.

[0103] In some embodiments, the kit further comprises an extracellular vesicle precipitant or device for precipitating extracellular vesicles as described in the below examples.

[0104] In some embodiments, the kit further comprises instructions to determine whether a liquid sample from a subject comprises an mRNA or long non-coding RNA comprising the mRNA or long non-coding RNA variant position. EXAMPLES

[0105] Example 1 — Circulating messenger RNA variants as a potential biomarker for surveillance of hepatocellular carcinoma

[0106] We report here the detection of high-risk mRNA variants exclusively in the circulation of HCC patients. Numerous genomic alleles such as single nucleotide polymorphisms (SNPs), nucleotide insertions and deletions (called Indels), splicing variants in many genes, have been associated with elevated risk of cancer. Our findings offer a novel non-invasive platform for HCC surveillance and early detection. RNAseq analysis was carried out in the plasma of 14 individuals with a diagnosis of HCC, 8 with LC and no HCC, and 6 with no liver disease diagnosis. RNA from 6 matching tumors and 5 circulating extracellular vesicle (EV) samples from 14 of those with HCC was also analyzed. Specimens from two cholangiocarcinoma (CCA) patients were also included in our study. HCC specific SNPs and Indels referred as “variants” were identified using GATK HaplotypeCaller and annotated by SnpEff to filter out high risk variants. The variant calling on all RNA samples enabled the detection of 5.2 million SNPs, 0.91 million insertions and 0.81 million deletions. RNAseq analyses in tumors, normal liver tissue, plasma, and plasma derived EVs led to the detection of 5480 high-risk tumor specific mRNA variants in the circulation of HCC patients. These variants are concurrently detected in tumors and plasma samples or tumors and EVs from HCC patients, but none ofDOCKET NO. BSBI-026-PCT PCT APPLICATION these were detected in normal liver, plasma of LC patients or normal healthy individuals. Our results demonstrate selective detection of concordant high-risk HCC-specific mRNA variants in free plasma, plasma derived EVs and tumors of HCC patients. The variants comprise of splicing, frameshift, fusion and single nucleotide alterations and correspond to cancer and tumor metabolism pathways. Detection of these high-risk variants in matching specimens from same subjects with an enrichment in circulating EVs is remarkable. Validation of these HCC selective ctmRNA variants in larger patient cohorts is likely to identify a predictive set of ctmRNA with high diagnostic performance and thus offer a novel non-invasive serology-based biomarker for HCC.

[0107] Hepatocellular carcinoma (HCC) represents the fourth most deadly cancer worldwide and projected to become the 3rd leading cause of cancer related deaths by 2030 (1-3). Rising HCC incidence has been attributed to increasing prevalence of chronic liver disease (CLD) specifically non- alcoholic steatohepatitis (NASH) and viral hepatitis (4-6), which can progress to liver cirrhosis (LC) detected in up to 90% of HCC patients (7). Development of cirrhosis significantly increases risk of HCC (8). Though traditionally HCC is known to arise in the context of hepatitis B (HBV) and hepatitis C (HCV) viral infections, metabolic associated fatty liver disease (MAFLD) and NASH are becoming more prominent risk factors for HCC (9-11). Because early-stage tumor diagnosis improves options for potentially curative therapy and thereby improves overall survival (12), AASLD guidelines recommend surveillance in CLD patients at risk for HCC (8, 13) with liver ultrasound (US) and serum alpha-fetoprotein (AFP) test conducted every 6 months (14). Ultrasound plus AFP remains relatively insensitive for early detection identifying only 63% of early-stage cancers (15). Alternative surveillance biomarkers, Lensculinaris agglutinin-reactive AFP, known more commonly as AFP-L3, and des-carboxy prothrombin (DCP), used in Japan for screening, are more specific but less sensitive biomarkers and therefore less utilized (16). Recently, GALAD score (Gender, Age, AFP-L3, AFP, DCP) has been proposed which combines simple demographic data with serum biomarkers and predicts the future probability of developing HCC in CLD patients (17,18). Despite these advances, surveillance is suboptimal not only due to low sensitivity of existing methods of early detection but also due to barriers in access to quality imaging and biomarkers (13,19-20). When ultrasound or AFP detect abnormalities, AASLD and EASL guidelines recommend magnetic resonance imaging (MRI) using extracellular or hepatobiliary contrast media or dynamic computed tomography as diagnostic testing using the Liver Imaging Reporting and Data Systems (LI-RADS) grading system (21). However, vascular imaging provides little information about tumor biology, patient prognosis or likelihood of response toDOCKET NO. BSBI-026-PCT PCT APPLICATION therapy. Since a diagnosis of HCC is most often made radiologically without a biopsy, key tumor molecular information rarely is available to optimize therapy. The limitations of testing lead to a critical need for improving HCC surveillance and early detection (15, 22-23). Cell- free DNA (cfDNA) in the blood provides a useful non-invasive diagnostic analyte for cancer although for early detection, both technical and biological factors introduce challenges to the detection of mutant DNA in plasma and its interpretation (24-26). Detection of tumors is also possible through analysis of circulating tumor cells (CTCs). However, density of CTCs in circulation has been observed to be very low presumably because only large tumors release CTCs (27). cfDNA analysis in cancer clinical trials has suggested promising results in early detection, real time monitoring and management (28). Fragmentation patterns of cfDNA combined with mutations in cfDNA has been reported to increase the sensitivity of cancer detection (29). However, the mechanisms of release and degradation of cfDNA, and the factors that affect the representation of circulating tumor DNA (ctDNA) in plasma, are poorly understood. Additionally there are challenges in differentiating between potential tumors within a mixed liquid biopsy due to the low allelic frequency have been reported (25,26). Circulating mRNA, without the copy number limitations of DNA, provides an alternative platform for use in cancer early detection and diagnostics. Cancer is a multistep process driven by cumulative acquisition of both germline (inherited) and somatic (not inherited) mutations leading to the transformation of normal hepatocytes into malignant clones. Genetic variants can be classified into several categories, including single nucleotide polymorphisms (SNPs), small insertions and deletions (Indels), and structural variants (30). SNPs account for >90% of allelic disparities scattered throughout the human genome and nonsynonymous SNPs alter the amino acid sequence as well as potentially affect protein structure and function (31,32). We have reported the detection of tumor specific mRNA transcripts in the circulation of HCC patients by RNAseq (33). Here we report the detection of high-risk variants comprising of both SNPs and indels in the circulating mRNA of cancer patients using RNAseq. Mutation profiling by NGS platforms can potentially lead to false-positive results due to errors introduced during library preparation and subsequent sequencing steps. These challenges have necessitated the use of multiple mutation-enrichment methods like GATK (34) and SNPeff tools (35,36). It has been suggested that comparison of paired tumor and plasma samples represents an important prerequisite to evaluate the diagnostic accuracy of analytical platforms, especially for variants with low allele frequency (37,38). Profiling the mutational landscape reflected in mRNA of the tumor in parallel with that of the circulation from same patient may identify critical concordant RNA variants which could potentially be used to develop a liquid biopsy platform forDOCKET NO. BSBI-026-PCT PCT APPLICATION surveillance and early HCC detection. Here we demonstrate the identification of high-risk HCCspecific mRNA variants present exclusively in tumors and plasma of HCC patients, but not detectable in LC patients without cancer or normal healthy individuals. These circulating tumorspecific mRNA variants are derived from RNAseq analysis of total RNA using GATK and SnpEff tools, further validation and characterization of these RNA variants is essential. Our study offers the promise of a novel analyte to be used in non-invasive detection of high- risk cancer specific mRNA variants and may facilitate effective surveillance and screening of ever increasing numbers of patients with chronic liver disease.

[0108] Materials and Methods:

[0109] Human Subjects: Samples were acquired from commercial vendor, Biochemed Inc and from our collaborators at The University of Pennsylvania (UPENN) and Capital Health Cancer research Institute. All samples were acquired before any therapeutic regimen was initiated. Patient plasma samples were collected at the time of diagnosis and acquired from treatment naïve adult consenting donors diagnosed with either hepatocellular carcinoma (HCC), cholangiocarcinoma or liver cirrhosis. Tumor tissues were harvested via biopsy or surgical resection before any treatment. HCC diagnosis was made by either 1) biopsy or 2) typical enhancement patterns on dynamic contrastenhanced CT or MRI (later codified as Li- RADS criteria). Staging performed per Barcelona Clinic Liver Cancer system (BCLC) (0 very early, A early, B intermediate, C advanced, D terminal). Patients with CCA were diagnosed by histopathology of the liver resection. Patients with LC underwent standard clinical surveillance for HCC development with abdominal ultrasound and AFP testing every 6 months (optimally) per AASLD surveillance guidelines. Patient details are shown in table 1. Normal human liver tissue was a kind gift from Dr. Ramilla Philip, Immunotope Inc.

[0110] Isolation and characterization of EVs. Plasma samples from HCC or CCA patients (1 to 1.5ml) were spun at 2,000g for 30 minutes to remove the cellular debris before purification of EVs using ExoQuick kit (System biosciences, Palo Alto CA). EVs were further purified by ultracentrifugation at 100,000g for 2 hours at 4C, pellet resuspended in 100ul PBS. followed by NanoSight tracking and Chip analysis. Dilutions of samples with PBS (Zetaview NTA) were carried out as 1:1000 (HCC001), 1:100 (HCC004, HCC006, HCC007, CCA005, NHC66), 1:20,000 (HCC014) and 1:10,000 (LC19, LC34). Dilutions for Exoview chip analysis were carried out in solution A (Exoview tetraspanin plasma kit analysis) 1:1000 (HCC001),1:100 (HCC004, CCA005), 1:100,000 (LC19). Manufacturer instructions were followed and EVs were stained for CD63, CD81 and CD19 at 1:1000 final working dilutions from the stock concentration. Antibodies against these markers are immobilized on chips called captureDOCKET NO. BSBI-026-PCT PCT APPLICATION probes. Once they encounter sample, tetraspanin receptor proteins on EVs bind to the antibodies on the chip and after washing, the chips are treated with fluorescently labeled antibodies against tetraspanin receptors, just like a sandwich ELISA. After washing, fluorescent labels are detected to evaluate particle counts and relative concentrations of tetraspanin receptors.

[0111] RNA extraction: Total RNA was isolated from human plasma samples, tumor and normal tissues and plasma-derived extracellular vesicles as reported earlier (33). Briefly, Total RNA from 1–2 ml plasma samples (spun at 2,000g for 5 minutes) was prepared using the Qiagen RNeasy Serum / Plasma Kit (Qiagen, Valencia, CA, USA) and quantified on a NanoDrop spectrophotometer. RNAseq analysis was carried out at Cancer Genomics Facility at Thomas Jefferson University (TJU), Philadelphia, PA, USA. RNA purity and integrity was assessed by Agilent 2100 BioAnalyzer. Also, Total RNA was extracted from HCC cell lines HepG2 and Huh7 and immortalized normal liver PH5CH cells using Qiagen miRNeasy Mini Kit (Qiagen, Valencia, CA, USA). Total RNA was also extracted from two Grade-2 HCC tumor tissues (HCC103T, HCC105T, BioChemed) and a normal liver tissue using mirVana miRNA Isolation Kit (Ambion, Austin, TX, USA). All kits were used by following manufacturer guidelines. Tumor samples corresponding to two plasma samples (HCC103P, HCC105P, BioChemed) were investigated by RNAseq and one of them (HCC103T) was also studied by RT-qPCR.100 mg tissue treated with RNAlater-ICE solution (Invitrogen, Carlsbad, CA, USA) was homogenized in a glass homogenizer, worked-up following kit protocol, and RNA eluted in 100 μl RNasefree water. Plasma (3 ml) from HCC101P (BioChemed) was spun at 2,000g for 15 minutes to remove cellular debris and supernatant was collected. Total RNA from extracellular vesicles (EVs) was extracted using the ExoMir Kit (BIOO Scientific Corp., Austin, TX, USA). RNA from the remaining EV-free flow-through plasma was extracted using the Qiagen RNeasy Serum / Plasma Kit (Qiagen, Valencia, CA, USA). RNA from plasma EVs, EV-free plasma, and liver tissues was sequenced at TJU as described above.

[0112] RNAseq analysis: For characterizing the circulating transcriptome, as shown in Table 1, plasma samples from HCC patients (n=14) representing both early and late stage, LC patients without HCC (n=8) and normal healthy individuals (n=6) were analyzed by RNAseq analysis. Within the HCC patient group, we also investigated matching tumors from 6 patients and plasma derived EVs from 5 patients in parallel. One normal human liver tissue was also included in the study. Total RNA was isolated and RNAseq was carried out on either Illumina NextSeq 500 platform using the SMARTer® Stranded Total RNA-Seq Kit v2-Pico Input Mammalian (Takara #634411) on a highoutput flow cell 2x75 bp as reported earlier (25) or onDOCKET NO. BSBI-026-PCT PCT APPLICATION the Illumina NovaSeq 6000 using a S1 Flow Cell with a paired end run, 2 x 150 cycles, generating more than 50 million reads each. Residual Pico v2 SMART adapters on paired end fastq files were trimmed. The expression of genes in each sample were called with RSEM with STAR (2.7.5a) as aligner against a human reference genome (GRCh38.p13).base quality recalibration and variants calling (Haplotype caller algorithm) were performed using Broad Institutes Genome Analysis Tool Kit (GATK) version 4.1.7.0. Variants with 20 or higher quality score as well as depth of 5 or more were considered as true positive. Filtration and annotation of high-risk variants was carried out using SnpEff analysis (version 4.3t) to identify high risk variants in all sample subsets. The SNPeff uses sequence and structure-based bioinformatics tools to predict the effect of protein coding SNPs on the structural phenotype of proteins. It includes intronic, untranslated region, upstream, downstream, splice site, or intergenic regions in its annotated genomic locations. It can predict coding effects such as synonymous or nonsynonymous amino acid replacement, start / stop codon gains or losses, or frame shift changes. Tumor-centric high-risk variants were sorted by concordant detection in tumors and plasma from HCC patients, proportion / frequency in samples, lack of detection in normal liver tissue and in the plasma of LC and NHC controls and established functional association with cancer. Pathway enrichment analysis was carried out using R package ClusterProfiler.

[0114] Statistics: The distinguishing high-risk variant transcripts were selected out of 5,480 tumor specific variants using Fisher’s exact test with multiple testing adjustment via Benjamini– Hochberg method.

[0115] Results:

[0116] Diversity of RNA variants and variant effects. Bioinformatic tools help determine the effect of variants (SNPs, indels, CNVs, structural variants) on genes, transcripts, proteinDOCKET NO. BSBI-026-PCT PCT APPLICATION sequences and regulatory regions. RNAseq variant analysis in 46 samples (Tumors, plasma, circulating EVs and normal liver tissue from 29 subjects) led to the detection of some 27.5M variant effects manifested due to 5.2 M SNPs, 0.91M insertions and 0.81 M deletions. Measuring by impact, 94.3% represented modifier variants, followed by high and low risk variants at 2.3% each and 1% of variants were of moderate risk. Among the effects by functional class, 62% represented missense variants, synonymous / silent 35% and stop gain / non-sense variants at 3%. Evaluating effects by type and region, 56% were detected in introns, upstream 12.5%, downstream 12.6%, intergenic 10.5%, exon 4.2%, splicing 2.5% and 0.05% are genic. No significant differences were observed when comparing these effects between sample groups. However, proportion of high and moderate risk, frame shift and missense variants was observed to increase as we moved from normal healthy, LC to HCC patients. Though the increase in sample subsets was not statistically significant, it did point to a possibility of progressive build-up of mutations during disease progression (FIG. 1A). FIG. 1B shows the average counts of variants corresponding to different categories in various clinical subsets.

[0117] Tumor-centric concordant variants. We then evaluated the occurrence of “high risk” variants in each category. Filtration and annotation of high-risk variants was carried out using SnpEff analysis to identify high risk variants in all sample subsets (FIG. 2A). “High risk” variants, derived by SnpEff are predicted to cause a significant effect on protein structure. As mentioned in methods, the SnpEff uses sequence and structure-based bioinformatics tools to predict the effect of proteincoding SNPs on the structural phenotype of proteins. High-risk variants in HCC tumors were further filtered to include variants detected in the plasma of HCC patients (concordant variants) and remove any variants detected in normal liver tissue and plasma samples of LC patients and NHC controls to derive a set of circulating tumor-centric RNA (ctRNA) variants. Analysis of 14 plasma and 6 corresponding tumors from HCC patients identified 5480 high-risk concordant ctRNA variants representing 3199 genes and detected in high frequency in both circulating plasma (7-50%) and tumors (30-100%). None of these tumor-centric variants are detected in the plasma of either LC patients (n=8) or NHC (n=6) controls. Most of the high-risk concordant variants involve splice donor / acceptor regions (4933), frameshift (2506) changes and splicing variations. Comparing tumor centric variants with all SnpEff derived high-risk variants identified in HCCT, HCCP and HCCMV sample subsets point to the concordant variants shared between the different sample subsets (FIG.2B).

[0118] Prominent altered genes corresponding to variant transcripts. FIG. 3 represents ctRNA variants detected in tumors and circulation of HCC patients in a clustering heat mapDOCKET NO. BSBI-026-PCT PCT APPLICATION comprised of splicing variants, SNPs, frameshift variants etc. Varaint Nos.1–200 represent top recurrent variants reported in FIG.3. Notable high-risk variants present in tumors and plasma (concordant) correspond to TP53, CTNNB1, FAH and SF3B1 genes, which are already known to harbor driver mutations (reviewed in 39). Concordant variant transcripts corresponding to complement cascade like C2, C4A, C4B, C1R, C5, C8G, KLKB1, KNG1, CFHR5, MASP2, etc. which are known to be liver enriched (40) are represented among tumor centric ctRNA variants. Additionally, among tumor-centric variants figure those ctRNA variants corresponding to coagulation factors F2, F11 and F12, which are not only liver enriched but also represent FDA approved drug targets (40).

[0119] Liver-derived transcripts reveal a high frequency of variants. With an interest to understand the variants in liver-associated transcripts, we calculated the number of total high- risk variants detected on these transcripts in various patient subsets. Some well-known liver- derived transcripts like FGL1, CYP2E1, SERPINA1, ALB, TF and SYCE1 display a huge variant load, particularly in the plasma and tumors from HCC patients. Several other liver- associated transcripts were observed to harbor significantly higher numbers of unique, high- risk variants in tumors, plasma or EVs of cancer patients compared to the levels detected in circulating plasma from LC patients and NHC controls. Bar graphs representing the total number of high-risk variants present in liver associated transcripts in various clinical subsets are shown in FIG. 4. Focusing on certain selective tissue specific transcripts with associated high-risk variants can potentially offer increased specificity and sensitivity to identify high- risk patients.

[0120] Characterization of extracellular vesicles (EVs) isolated from plasma: It was interesting to know if the variant mRNA transcripts were present in the circulation within extracellular vesicles (EVs) since (EVs) in circulation are known to contain nucleic acids. Therefore, in five HCC subjects we compared the variant mRNA profiles in whole plasma with matching plasma derived EVs by RNAseq. EVs were purified from HCC, HCC-free LC or NHC plasma samples and analyzed for size and density by zeta view (Ncsi Spectradyne) analysis. FIG. 5A shows the density peaks of circulating EVs from different patients and healthy control all centered around a 150 nm size. The EVs were further characterized for expression of tetraspanin receptors using Exoview chip arrays (FIG. 5B). Pie charts represent the expression profiles of CD9, CD81 and CD63 in percentage of circulating EV particles from representative cancer patients and LC control. CD41a is a platelet marker, antibody against which was used together with IgG control. Data shows that all EVs seem to reflect comparable expression of the tetraspanin receptors authenticating their EV phenotype.DOCKET NO. BSBI-026-PCT PCT APPLICATION

[0121] Common concordant variants selectively enriched in circulating EVs of HCC patients. RNAseq analyses of circulating EVs from five HCC patients were performed and the results were compared with RNAseq from their corresponding tumors. A set of concordant variants selectively enriched in EVs of these patients are highlighted in FIG 5C. Variant Nos. 1, 2, 3, 5, 17, 22, 46, 60, 171, and 178 reported in Tables 7, 8, and 9 are among those illustrated in FIG.5C. 218 high-risk concordant variants detected in tumors and plasma derived EVs of HCC patients were identified. Variants identified in this category correspond to some known HCC related transcripts like GOLGA2, ASAH1, ODC2, SAR1A, PIK3R1, CCNG1, MACF1, SERPINE1, CTNNB1, CREB3 and ADH5, among others. None of these EV-enriched variants are detected in the plasma of NHC controls or LC patients. The data indicates unique EV enrichment of these circulating variants.

[0122] Analyzing matching samples, whole plasma, circulating EVs and tumors from same cancer subjects indicated triple-concordant high-risk variants.

[0123] Significantly, comparing three different specimens from the same cancer subjects identified a set of triple concordant variants not detected in the circulation of LC patients or normal healthy controls. Hundreds of such triple concordant variants were detected in a set of 8 cancer patients with matched specimens (FIG.6A). Venn diagrams show the distribution of these variants in matching specimens from same subjects and strongly suggest an association of these high-risk variants with cancer. We sorted triple concordant high-risk variants from all patients and organized the corresponding genes based on number of variants to represent genes which exhibit highest number of mutations in HCC patients (FIG.6B). These are Variant Nos. 17, 24, 28, 37, 60, 74,109,110,168,169, 181 in Tables 7, 8, and 9. The heat map in FIG. 6B represents the distribution of top genes sorted based on high number of high-risk triple concordant variants. The data highlight the top altered genes mutated frequently at several critical regions and underscores the authenticity and functional relevance of these ctRNA variants. For example, UNC13D is a calcium dependent cytoplasmic protein involved in vesicular and endocytic transport essential for vesicle maturation and docking and also known as an unfavorable prognostic marker in renal, endometrial and pancreatic cancer (40). Nurobeachin like 2 (NBEAL2) plays a role in development and secretion of alpha granules containing growth factors and is a prognostic marker for head and neck cancer (40). MAP4K2 is a serine / threonine protein kinase and an essential component of MAP kinase signaling. It acts as an upstream activator of stress activated protein kinase / c-jun N-terminal kinase (SAP / JNK) and p38 pathways. MAP4K2 can be activated by TNFa and interacts with TRAF2. MAP4K2 is known as an unfavorable prognostic marker of liver cancer (40). The presence ofDOCKET NO. BSBI-026-PCT PCT APPLICATION multiple high-risk variants on these transcripts reflected in all three specimens from the same cancer subjects and the lack of detection in non-cancer control subjects highlights their role in cancer pathology.

[0124] Variants associated with CCA: Cholangiocarcinoma is a liver cancer of cholangiocytes, and not hepatocytes. It was therefore of interest and opportunistic to examine a set of specimens of matched plasma and tumor for high-risk mRNA transcripts. Matched CCA plasma, CCA EVs and tumors from CCA patients were studied as additional liver cancer controls to test the specificity of HCC-specific variants. Surprisingly, most of the highly frequent high-risk variants in HCC patients were also detected in CCA samples. We sorted variants on the basis of their proportion in CCA patients (FIGS.7A and 7B) Variant Nos.9, 23, 112, 113, 117, 120,153 in Tables 7, 8, and 9 are representative examples of such CCA specific variants. As in HCC, detection of high-risk variants in CCA patients was more frequent in tumors than plasma samples. EV-enriched HCC associated variants were also detected in the EVs of CCA patients. This concordance of ctRNA variations between HCC and CCA is interesting and underscores the functional relevance of such variants and validates their specificity in liver cancer.

[0125] Variants corresponding to transcripts involved in cancer and metabolic pathways suggest widespread metabolic alterations in HCC.

[0126] The high-risk mRNA variants we have identified are selectively present in the people with HCC. Given that the genes corresponding to these variants are well known players in tumor biology we hypothesize that these variants reflect the mutational environment of the tumor cells, from which we believe they are derived. To emphasize the importance of mutations in cancer biology, a multi-analyte blood test named as CancerSEEK based on circulating proteins and cfDNA mutations has been reported to detect 8 common cancers (41). Malignancies including HCC are characterized by the presence of mutated genes, possibly a result of altered tumor metabolism, DNA repair and splicing and our unique finding is that these genetic lesions can be detected in circulating transcripts. Though we have not characterized any NGS derived concordant tumor-centric variants, high-risk variants identified in HCC patients using GATK and SnpEff tools correspond to transcripts of EGFR, CTNNA1, PTPA, AKT1, MTOR, ARAF, RAF1, HRAS, CREB3, SREBF1, ACY1, STAT3, etc. These genes correspond to well-known cancer pathways. We carried out KEGG pathway enrichment analysis on 578 genes corresponding to tumor-centric variants (FIGS. 8A–8C) and were able to identify major pathways corresponding to variant genes. A profound and predominant representation of circulating tumor-centric variants correspond to genes involved inDOCKET NO. BSBI-026-PCT PCT APPLICATION metabolism suggesting some interplay in altered tumor metabolism (FIG. 9). Concordant variants of FASN, PC, SREBF1, ACADVL, PKLR, PCK1, ALDOC, PSAT1, MAT1A, MAT2A, GPT, etc. point to the altered genes associated with dysregulated tumor metabolism. In comparison, none of these tumor-centric variants were detected in the circulation of LC or NHC subjects. Variants corresponding to several other liver enriched transcripts like IDH2, PROC, PKLR, ACAA1, KLKB1, ACY1, ASL, MASP2, ECI1, ADH1A, ADH1B, ADH6, HADHA, etc. are well known metabolic enzymes facilitating tumor adaptation and some of these transcripts represent potential or FDA approved drug targets. Variants of GPT and PSAT1 are liver enriched and play role in glutamine metabolism and signaling. Variant transcripts associated with insulin signaling pathways (40) like PIK3R1, SLC2A2, SLC27A, PTPRF, OGT, NR1H, etc. are among the concordant ctRNA variants detected in both plasma and tumors of HCC patients. The preliminary data are exciting and provocative. Though the number of samples analyzed is small, the data illustrate a high mutation milieu in HCC patients and highlight the diagnostic potential of circulating HCC-specific mRNA variants detectable in a non-invasive manner.

[0127] Discussion: Detection of tumor-derived genetic material from peripheral blood offers a noninvasive platform with an additional advantage that a full spectrum of mutations in tumors can be detected compared to tumor biopsies that may miss variants not uniformly distributed due to tumor / nodular heterogeneity (42). Mutations are ubiquitous in cancer and the association between somatic mutations and cancer is well recognized (43). The inflammatory environment in hepatitis, MAFLD and cirrhosis may serve as a premalignant stage, the development of HCC requires progressive pre-neoplastic changes and further disease progression leads to enhanced tumor heterogeneity and increased mutation load (44-45). Mutational signature is known to be largely conserved across the liver (46,47).

[0128] An increasing number of studies demonstrate the potential use of cfDNA in diagnosis, prognosis, and monitoring of cancer. A multi-cancer early detection CancerSeek blood test based on specific DNA mutations and protein biomarkers when combined with PET-CT has shown progress in early detection (48). HCCscreen test (Genetron) claims detection of early- stage HCC with high sensitivity based on DNA mutations and protein biomarkers (49). Mutations within a tumor can be clonal or subclonal, and the amount of available genome copies is a limiting factor for the detection of variants of low allele frequency (50,51). Moreover, the tumor fraction of circulating DNA (ctDNA) varies between cancer types as well as between patients affected by the same cancer type (52). Even at the metastatic stage, some patients can yield a low amount of ctDNA (53,54). However, Challenges in the optimizationDOCKET NO. BSBI-026-PCT PCT APPLICATION and standardization of preanalytical steps, significant gaps in our understanding of its origin, physical properties, and dynamics in circulation call for alternative approaches which can address and overcome low allelic frequency and limited copy number of target variants (24,27,55-56).

[0129] The presence of mRNA sequences in the circulation has begun to be recognized (57- 60). We are the first to demonstrate mRNA as a powerful analyte with significant upregulation of HCC-specific transcripts in the circulation of HCC patients compared to high-risk patients without cancer (33). Another study using circulating EVs reported a ten-gene RNA expression signature, consistent with our data, exhibiting high sensitivity in distinguishing early-stage HCC from LC patients (61). We now provide evidence of specific high-risk mutations in tumor- derived liver transcripts in the circulation of HCC patients (62) and identify a panel of 9 ctmutRNA with high diagnostic performance (data not shown). Studies on circulating RNA (ctRNA) is an emerging field in diagnostics (63,64) and transcriptomics-based biomarkers are reported to exhibit higher efficiency than protein biomarkers of HCC (65).

[0130] Here, in this example, by profiling the mutational landscape of the tumor in parallel with that of circulation from HCC patients we identify some top highly frequent 1500 circulating high-risk mRNA variants concordant in tumors and plasma but not detected in the plasma of liver cirrhosis patients or normal healthy controls. GATK and SNPeff tools lead to the identity of high-risk variants comprised of both SNP’s and indels most of which seem to be reported in catalogue of somatic mutations in cancer (COSMIC) and dbSNP data bases. Several high-risk variants correspond to cancer driver genes and cancer signaling pathways. Some of these variants correspond to genes known as actionable targets with either potential or FDA approved therapies. Significantly, a large subset of HCC-specific high-risk variants were also detectable in the tumors, EVs and plasma of few cholangiocarcinoma patients but not in LC or normal healthy individuals.

[0131] Splicing variants represent a predominant category of high-risk mRNA variants detected in tumors, EVs and free plasma of cancer patients; none of these are detected in normal liver or plasma of LC patients and normal healthy individuals. Alternative isoforms and tumor- specific isoforms that arise from aberrant splicing during the liver tumorigenesis have been reported earlier (66) and long read RNA sequencing in liver cells and tumors have identified spliced variants corresponding to enzyme regulators, chromatin modifiers, RNA-binding proteins and receptors (67). A high level of differential splicing is known to occur in primary HCC tumor tissues compared with normal liver, and many of these changes have been shown to correlate with patient survival (68, 69). It is to be noted that any pathological changesDOCKET NO. BSBI-026-PCT PCT APPLICATION associated with transcription and RNA splicing / editing aberrations cannot be identified through ctDNA. Splicing and fusion variants in ctmRNA together with point mutations could be potentially more effective in identifying early stage and high-risk patients.

[0132] We demonstrate here is that plasma derived extracellular vesicles (EV) are enriched for a subset of high-risk cancer associated mRNA variants which were also detected in matching tumors. EVs provide a mechanism of how tumor-derived variants land in the circulation, are protected from ubiquitous nucleases and variant enrichment provides better chances of detection in circulation. Significantly, overall high-risk variant density was highest in tumors, followed by EVs and lower in free plasma. This suggests that EVs might work as better tools as repositories of mRNA variants compared to free plasma.

[0133] Profiling the mutational landscape of the liver through circulating RNA in patients is a paradigm shifting approach and potentially provide information about tumor biology, patient prognosis and likely response to therapy. Circulating variants of mRNA can offer a better understanding of genetic heterogeneity and if some constitutional variants predispose individuals to a specific molecular subtype of liver tumors. It could enable us to evaluate the exact function of the gene, if not already known, and the consequence of its loss of function in the liver. With regard to the efforts towards precision medicine in HCC, treatment decisions will become increasingly dependent upon genetic stratification and ctRNA variant profiles associated with different etiologies of chronic liver diseases could be very useful at the bedside. The identification of oncogenic activation of tyrosine kinases in some advanced NSCLC tumors, most notably mutations in the EGFR, ALK or ROS1 gene, has led to a paradigm shift and the development of specific molecular treatments for patients (70). Moreover, any pathological changes associated with transcription and RNA editing aberrations cannot be identified through DNA.It is becoming apparent that tumor biology (71) and treatment responses, even for immunotherapy (72), may be predictable based on mutational subtypes. Non-invasive and cost-effective access to these circulating mRNA variants could potentially revolutionize clinical management.

[0134] Since the fidelity of circulating RNA will be critical for clinical decision making, optimization and standardization of clinical sample collection, RNA isolation and analyses are critical for development of this platform. Our data clearly demonstrate the possibility of this platform to be used for clinical translation. Specific liver associated ctRNA biomarkers could potentially identify patients with liver cirrhosis, MAFLD and malignant pathology. Samples could be easily drawn linearly from patients and repeated for confirmation, at various timeDOCKET NO. BSBI-026-PCT PCT APPLICATION points of surveillance and treatment and treatment decisions could be tailored to mutational load of HCCspecific transcripts.

[0135] Though identification of these ctmRNA variants in HCC patients was carried out using next generation sequencing (NGS) analyses, further validation of these need to be carried out in larger patient cohorts and variants characterized by other technical approaches. In summary, we demonstrate that circulating mRNA variants can potentially offer a viable liquid biopsy platform which on its own or in combination with cfDNA or protein biomarkers can significantly aid in surveillance, early detection and patient management.

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Hum Mutat. 2000;15(1):45-51. doi: 10.1002 / (SICI)1098- 1004(200001)15:1<45::AIDHUMU10> 3.0.CO;2-T. PMID: 10612821. 32. Wu J, Jiang R. Prediction of deleterious nonsynonymous single-nucleotide polymorphism for human diseases. ScientificWorldJournal. 2013;2013:675851. doi: 10.1155 / 2013 / 675851. Epub 2013 Jan 30. PMID: 23431257; PMCID: PMC3572689. 33. Sayeed A, Dalvano BE, Kaplan DE, et al. Profiling the circulating mRNA transcriptome in human liver disease. Oncotarget.2020;11(23):2216-2232. 34. Vander Auwera GA. From fastq data to high confidence variant calls. The genome analysis tool kit best practices pipeline. Curr protocols in Bioinformatics 43(11) 10.2013. 35. Cingolani P, Platts A, Wang le L, Coon M, Nguyen T, Wang L, Land SJ, Lu X, Ruden DM. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly (Austin). 2012 Apr-Jun;6(2):80-92. doi: 10.4161 / fly.19695. 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The landscape of gene mutations in cirrhosis and hepatocellular carcinoma. Journal of Hepatology.2020.72;990-1002. 40. Nault JC. Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma. Cancer Genome Atlas Research Network. Hepatology 2020. 2020.71(1):164- 182.DOCKET NO. BSBI-026-PCT PCT APPLICATION 41. Cohen JD, Li L, Wang Y, Thoburn C, Afsari B, Danilova L, Douville C, Javed AA,et al. Detection and localization of surgically resectable cancers with a multi-analyte blood test. Science. 2018 Feb 23;359(6378):926-930. PMID: 29348365; PMCID: PMC6080308. 42. Parikh, A. R. et al. Liquid versus tissue biopsy for detecting acquired resistance and tumor heterogeneity in gastrointestinal cancers. Nat. Med.25, 1415–1421 (2019). 43. Martincorena I, Campbell PJ. Somatic mutation in cancer and normal cells. Science.2015; 25;349(6255):1483-9 Sep 24 PMID: 26404825 Review. 44. Bettegowda C, Sausen M, Leary RJ, et al. Detection of Circulating Tumor DNA in Earlyand Late-Stage Human Malignancies. Science Translational Medicine.2014;6(224). 45. Pelusi S, Baselli G, Pietrelli A, Dongiovanni P, et al. Rare Pathogenic Variants predispose to hepatocellular carcinoma in nonalcoholic fatty liver disease. Sci Rep 2019. 6;9(1):3682. 46. Blokzijl F, Ligt JD, Jager M, Sasselli V, et al. Tissue-specific mutation accumulation in human adult stem cells during life. Nature; 2016 Oct 13;538(7624):260-26 47. Brunner SF, Roberts ND, Wylie LA, Moore L, et al. Somatic mutations and clonal dynamics in healthy and cirrhotic human liver. Nature.2019 Oct;574(7779):538-542. 48. Lennon AM, Buchanan AH, Kinde I, Warren A, Honushefsky A, et al. Feasibility of blood testing combined with PET-CT to screen for cancer and guide intervention. Science. 2020 Jul 3;369(6499):eabb9601. doi: 10.1126 / science.abb9601. Epub 2020 Apr 28. PMID: 32345712; PMCID: PMC7509949. 49. Qu C, Wang Y, Wang P, Chen K, Wang M, Zeng H, Lu J,et al. Detection of early-stage hepatocellular carcinoma in asymptomatic HBsAg-seropositive individuals by liquid biopsy. Proc Natl Acad Sci U S A.2019 Mar 26;116(13):6308-6312. PMID: 30858324; PMCID: PMC6442629. 50. Guichard C, Amaddeo G, Imbeaud S, Ladeiro Y, et al. Integrated analysis of somatic mutations and focal copy-number changes identifies key genes and pathways in hepatocellular carcinoma.2012 May 6;44(6):694-8. 51. Adrian Ally, Cancer Genome Atlas Research Network. Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma. Cell. 2017. 15;169(7):1327- 1341.e23. 52. Nault JC. Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma. Cancer Genome Atlas Research Network. Hepatology 2020. 2020.71(1):164- 182. Leary RJ, Sausen M,Kinde I, Papadopoulos N, Carpten JD et al.DOCKET NO. BSBI-026-PCT PCT APPLICATION Detection of chromosomal alterations in the circulation of cancer patients with whole- genome sequencing. Sci Transl Med.2012 Nov 28;4(162):162ra154. 53. Leary RJ, Sausen M,Kinde I, Papadopoulos N, Carpten JD et al. Detection of chromosomal alterations in the circulation of cancer patients with whole-genome sequencing. Sci Transl Med.2012 Nov 28;4(162):162ra154. 54. McBride DJ, Orpana AK ,Sotiriou C, Joensuu H, Stephens PJ, et al., Use of cancer-specific genomic rearrangements to quantify disease burden in plasma from patients with solid tumors. Genes Chromosomes Cancer.2010 Nov;49(11):1062-9. 55. Ye Q, Ling S, Zheng S, Xu X. Liquid biopsy in hepatocellular carcinoma: circulating tumor cells and circulating tumor DNA. Mol Cancer.2019 Jul 3;18(1):114. 56. Su YH, Kim AK, Jain S. Liquid biopsies for hepatocellular carcinoma. Transl Res. 2018 Nov;201:84-97. 57. Mitchell PS, Parkin RK, Kroh EM, et al. Circulating microRNAs as stable blood-based markers for cancer detection. Proceedings of the National Academy of Sciences. 2008;105(30):10513-10518. doi:10.1073 / pnas.0804549105 58. Enache L, Enache E, Ramière C, et al. Circulating RNA Molecules as Biomarkers in Liver Disease. International Journal of Molecular Sciences. 2014;15(10):17644-17666. doi:10.3390 / ijms151017644 59. Vivian WX, Moon T, Cheung PT, Chan LLY, et al. Non-invasive Potential Circulating mRNA Markers for Colorectal Adenoma Using Targeted Sequencing. Scientific Reports 2019,9:12943 60. Akat KM, Lee YA, Hurley A, Morozov P, Klaas E.A. Max KEA, Brown M, Bogardus K, Sopeyin A, Hildner K, Diacovo T, Neurath MF, Borggrefe M, and Tuschl T Detection of circulating extracellular mRNAs by modified small-RNA-sequencing analysis. JCI Insight.2019;4(9).127317 61. Sun N, Lee YT, Zhang RY, Kao R, Teng PC, Yang Y, et al. Purification of HCC-specific extracellular vesicles on nanosubstrates for early HCC detection by digital scoring. Nat Commun.2020 Sep 7;11(1):4489. PMID: 32895384; PMCID: PMC7477161. 62. Sayeed A, Doria C, Kaplan D,et al.Detection of tumor derived mutant mRNA transcripts in the circulation of HCC patients. AASLD liver meeting, Abstract supplement, 1131, vol 74, Hepatology,2021. 63. Vivian WX, Moon T, Cheung PT, Chan LLY, et al. Non-invasive Potential Circulating mRNA Markers for Colorectal Adenoma Using Targeted Sequencing. Scientific Reports 2019,9:12943 | https: / / doi.org / 10.1038 / s41598-019-49445-xDOCKET NO. BSBI-026-PCT PCT APPLICATION 64. Akat KM, Lee YA, Hurley A, Morozov P, Klaas E.A. Max KEA, Brown M, Bogardus K, Sopeyin A, Hildner K, Diacovo T, Neurath MF, Borggrefe M, and Tuschl T. Detection of circulating extracellular mRNAs by modified small-RNA-sequencing analysis. JCI Insight.2019;4(9). doi:10.1172 / jci.insight.127317 65. Gupta R, Kleinjans J, Caiment F. Identifying novel transcript biomarkers for hepatocellular carcinoma (HCC) using RNA-Seq datasets and machine learning. BMC Cancer. 2021 Aug 27;21(1):962. PMID: 34445986; PMCID: PMC8394105. 66. Lee SE, Alcedo KP, Kim HJ, Snider NT. Alternative Splicing in Hepatocellular Carcinoma. Cell Mol Gastroenterol Hepatol. 2020;10(4):699-712. doi: 10.1016 / j.jcmgh.2020.04.018. Epub 2020 May 8. PMID: 32389640; PMCID: PMC7490524. 67. Chen H, Gao F, He M, Ding XF, Wong AM, Sze SC, Yu AC, Sun T, Chan AW, Wang X, Wong N. Long-Read RNA Sequencing Identifies Alternative Splice Variants in Hepatocellular Carcinoma and Tumor-Specific Isoforms. Hepatology. 2019 Sep;70(3):1011-1025. doi: 10.1002 / hep.30500. Epub 2019 Mar 22. PMID: 30637779; PMCID: PMC6766942. 68. Li S, Hu Z, Zhao Y, Huang S, He X. Transcriptome-Wide Analysis Reveals the Landscape of Aberrant Alternative Splicing Events in Liver Cancer. Hepatology. 2019 Jan;69(1):359- 375. doi: 10.1002 / hep.30158. Epub 2018 Dec 18. PMID: 30014619. 69. Zhu GQ, Zhou YJ, Qiu LX, Wang B, Yang Y, Liao WT, Luo YH, Shi YH, Zhou J, Fan J, Dai Z. Prognostic alternative mRNA splicing signature in hepatocellular carcinoma: a study based on large-scale sequencing data. Carcinogenesis. 2019 Sep 18;40(9):1077- 1085. doi: 10.1093 / carcin / bgz073. PMID: 31099827. 70. Jacqulyne P , Xiuning Le, John V. Heymach. Robichaux. Structure-based classification predicts drug response in EGFR-mutant NSCLC. Nature: 597,732–737 (2021) 71. Sia D, Villanueva A, Friedman SL, Llovet JM. Liver Cancer Cell of Origin, Molecular Class, and Effects on Patient Prognosis. Gastroenterology.2017 Mar;152(4):745-761. 72. Harding JJ, Nandakumar S, Armenia J, Khalil DN, Albano M, Ly M, Shia J,et al. Prospective Genotyping of Hepatocellular Carcinoma: Clinical Implications of Next- Generation Sequencing for Matching Patients to Targeted and Immune Therapies. Clin Cancer Res.2019 Apr 1;25(7):2116-2126.

[0137] Example 2 — Detection of circulating mRNA variants in Hepatocellular Carcinoma patients using Targeted RNAseqDOCKET NO. BSBI-026-PCT PCT APPLICATION

[0138] Mutations in circulating nucleic acids offer potential as biomarkers for the early detection and management of hepatocellular carcinoma (HCC). Although there is substantial literature about the use of circulating DNA and microRNA as biomarkers of cancer, there is relatively little information about circulating mRNA and circulating mRNA mutants (ctmutRNA), which may provide advantages over other analytes. Example 1 reveals 288 HCC selective ctmutRNA variants, called “candidates,” from a small cohort of HCC patients using Total RNAseq. The objective of this example 2 was to use targeted RNAseq to characterize and determine the presence or absence of these HCC selective variants in a new cohort of patients with liver cirrhosis (LC). Different methods to isolate small Extracellular Vesicles (sEVs) and amplify mRNA from the circulation were compared. RNA was isolated, and the primers and probes selective for the 288 regions of interest were used with RNA from HCC (n=50) and LC and no HCC (n=35) patients. HCC tumor tissues (n=11), a normal liver tissue and 3 cell lines were also studied. cDNA synthesis was followed by library construction using QIAseq RNA Fusion XP panel. 58 QC analysis was carried out with an Agilent Bioanalyzer before sequencing on a NextSeq 550 instrument. A GATK HaplotypeCaller was used for variant calling and annotation carried out using snpEff. Among the test panel of 288 ctmutRNA candidates in the original cohort, 75 were detected in the new 61 cohort of plasma samples. Moreover, 388 other variants in proximity to the original lesions were also found in multiple HCC but not LC plasma samples. A subset of 36 HCC selective variants were able to identify all HCC patients. The most common tumor specific variants were Indels and SNPs. Novel mRNA fusion variants, corresponding to SENP7, HYI, SAR1A, RASA2, TUBA transcripts, etc. were identified in HCC and LC patients. Circulating RNA are shown here to be a robust analyte for non-invasive early detection of HCC and ctRNA panels could work as powerful tools in the entire spectrum of clinical management.

[0139] INTRODUCTION

[0140] Certain high risk-groups, such as patients with Liver Cirrhosis (LC), chronic hepatitis B, and metabolic-dysfunction associated steatohepatitis (MASH) with advanced fibrosis, are recommended to undergo routine surveillance for hepatocellular carcinoma (HCC). Early detection of HCC in these patients greatly improves outcome (1,2). Ultrasound (US) to detect HCC with or without serum alpha-fetoprotein (AFP) testing conducted every 6 months for screening is recommended for all LC patients as well as certain high-risk non-cirrhotic patients (3-5). Both US and AFP, however, have limited sensitivity for early cancers; US is also limited by operator-dependence and access challenges for some patients, and utilization remains low.DOCKET NO. BSBI-026-PCT PCT APPLICATION A more sensitive blood test-based surveillance approach would be expected to improve uptake and increase the overall impact of HCC screening.

[0141] Liquid biopsy, utilizing blood or body fluids to search for cancer cells or other molecules such as DNA or RNA that are cancer-specific, is a promising platform to be utilized for HCC screening (6-8). However, technical challenges have limited broad application. For example, detection of low-frequency somatic mutations from circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) has proven challenging (9-11).

[0142] Circulating tumor RNA is an underexplored alternative approach to liquid biopsy that may offer better sensitivity for early cancer detection but needs further development. Using RNAseq on RNA isolated from plasma, we previously reported the detection of dysregulated mRNA transcripts in circulating exosomes also known as small Extracellular Vesicles (sEV) in the plasma of HCC patients (12). In Example 1, NGS and PCR-based tools were used to identify thousands of circulating mutated RNA (ctmutRNA) 88 / variants selectively detected in the plasma from HCC patients (n = 15) compared with samples from those 89 with LC without HCC or healthy subjects (n=15) (see also 13). A set of 288 variant transcripts were identified as those with the greatest promise as early detection markers of HCC because they were (i) exclusively detected in multiple HCC samples but not in any LC samples, (ii) detected in tumors and matching plasma and finally (iii) were “high impact” lesions that would be predicted to specify aberrant or dysfunctional polypeptides. However, although provocative, the single cohort and small sample sizes and difficulty in sEV preparation limited the conclusions that could be made.

[0143] In this example, we therefore optimized sample preparation and the approach that was used to determine the presence or absence of the 288 ctmutRNA variants in plasma from an entirely new cohort of age and gender-matched early-stage HCC (n=25), late-stage HCC (n=25), and non-cancer LC (n= 31) 98 patients. HCC tumor tissues (n=11), normal liver tissue (n=1) and liver cell lines (n=3) were also included. In the present example, deep sequence analysis was also conducted for regions flanking each of the 288 candidate variant transcripts isolated from the EVs from each patient sample.

[0144] A QIAseq RNA Fusion XP system was used, and the sequence files were analyzed using the GeneGlobe (QIAseq Qiagen), a cloud-based data analysis pipeline. Variants with annotations as SNPs, Indels and splice variants originally seen in the first samples sets were detected in many of the new patient samples. Several novel fusion transcripts associated with HCC were identified. In many cases, novel variants in the same transcript, flanking the original lesion (corresponding to the 288-test set) were detected. A panel with 36 variants was identifiedDOCKET NO. BSBI-026-PCT PCT APPLICATION that could identify all HCC samples. The specific identities of the transcripts most commonly mutated in the cancer sample, their possible pathogenic significance and use as early detection and management of HCC is discussed.

[0145] METHODS

[0146] Human subjects:

[0147] Plasma samples from diagnosed HCC patients were obtained from our collaborators at University of Pennsylvania under approved IRB protocols. HCC diagnosis was made by either (i) biopsy or (ii) typical enhancement patterns on dynamic contrast-enhanced CT or MRI (later codified as meeting Li-RADS 5 criteria). Staging was performed per the Barcelona Clinic Liver Cancer system (BCLC). We investigated separately 25 BCLC 0 or A samples (very early or early-stage HCC with single tumor or up to 3 lesions <3 117 cm) and 25 BCLC B or C (intermediate or late-stage HCC – exceeding stage A size criteria or with vascular 118 invasion or with metastatic disease) in order to investigate a possible discrimination between the earlier stages and the later stages of HCC. There were no stage D patients in the cohorts. Patient information is shown in Table 1A. Plasma samples from LC patients without HCC (n=31), HCC tumors (n=11), cell lines 121 (n=3) and 1 normal liver were used as controls. Demographic and clinical details of patients whose tumors were investigated are shown in Table 1B. All clinical specimens were acquired through our collaborators in the University of Pennsylvania, Philadelphia, PA, Mayo Clinic, Rochester, MN and Capital Health Cancer Center, Pennington, NJ using IRB approved protocols.0.5 mL plasma samples were processed using our optimized EV / RNA isolation protocol and RNA from tumors and cell lines was isolated 126 as reported earlier (12,13). Table 1AF6. 62.45 9.AP 1 3 249 3cauauau Ccau Ccau Re C.c. .C.caC.cpeC H / B+B+CAs sNHS eYesYeY dl- ieA A AsA Ahhgro sssass sasasasCupcSlClClClaClC C LeCgBatsA A ACA NOI 0N N0N NTegaN bt31 xpxN3b1 xb1 xA STpTpM0Tp xTpTpM0TMCIp 0L 6.4.3 6.4 2 2 16. 11P8 3 8.3.4.8.5.1P02m) 1ATuezm Tisc(CBP1el ay y yabts r r ryryryryryry y v7aa a a a a a a a araraorv4Ttemimimimimimim m m mcnMsisrPrPrPrPrPriPriPriPriPriPMIssisreovhirLri scesYeYoN? ? ? osNeYosNeYoN rom.uffD D D D D D D D TiD M WDPM W?W M WDPW gasiisCDon CC C C C C C C C C CHCHCHCHCHCHCHCHCHCHCHTeg8567951677070707562676CPA -620 x- eI SM M M M M M M M M MFBS sBf i8181819102026171717181.oso0rn202020202020202020202OaegaNYiDTEKtnTCe4Ti06T T T TT070131537 1T02T3T4T50000 0 0Ota0PDIH0CH0CH0H0H0HC C0C0C0C DC C C CM M M M MDOCKET NO. BSBI-026-PCT PCT APPLICATION

[0148] Serum and plasma comparison:

[0149] Whole blood was drawn, and serum and plasma were prepared. Serum samples were prepared by incubating at room temperature for 30 minutes and centrifuging the samples at 2000 g at 277 kelvins for 10 minutes. Plasma was prepared using 4 different anti-coagulants (EDTA, ACD, Sodium-Citrate, and Sodium Heparin) and samples were centrifuged at 2000 g for 15 minutes at 277 kelvins. Two 0.5 mL aliquots of each preparation were used to isolate RNA using the miRNeasy Serum / Plasma kit (Qiagen). A Tapestation 4200 instrument (Agilent) with HSRNA Screentape was used to analyze and quantify the RNA content in each sample.

[0150] sEV and RNA isolation from Plasma:

[0151] A combination of methods was used to isolate high quality RNA from plasma samples. 0.5 mL plasma samples were thawed and both sEV and sEV-free fractions corresponding to each sample were processed. sEVs were precipitated using ExoQuick (System Biosciences) precipitation followed by purification using ultracentrifugation (UC) as reported earlier. The sEV-free plasma was further subjected to RNA isolation using serum plasma miRNA isolation kit (Qiagen). sEV fraction from UC was also lysed and subjected to serum / plasma miRNA Qiagen column RNA isolation. RNA from sEV and sEV-free fractions was combined, and RNA samples were concentrated using a SpeedVac. QC analysis was conducted using Bioanalyzer.

[0152] sEV Isolation Methods comparison

[0153] EDTA Plasma was collected from one individual. Increasing volume aliquots from 0.5 mL to 2.0149 mL were used to isolate sEVs utilizing four different methods. Three methods using precipitation reagents, and one method is based on UC. All plasma samples were pre- cleared of any residual cellular debris by centrifugation at 3000 x g for 15 minutes.

[0154] UC was performed as previously reported (13) and the sEV pellet is resuspended in 0.5 mL of PBS. 153 sEV isolation using ExoQuick (Systems Biosciences) was performed according to the manufacturer 154 protocol. Polyethylene glycol (PEG) has been reported to enhance EV-derived nucleic acids (14). Test Matrix 1 and 2 are made of two different average molecular weight PEGs, 6000 and 8000 respectively, and 0.5M NaCl. A 2x stock solution is prepared and added in equal volume to the plasma samples and left to incubate overnight at 277 kelvins. Samples were centrifuged at 3250 g for 1 hour at 277 kelvins. The supernatant was aspirated, and the exosome pellet was resuspended in 0.5 mL of PBS. Nano Particle Tracking Analysis (NTA) was performed using a ZetaView (Particle Metrix) to determine the size distribution and particle count in the EV samples. RNA samples were run on the Agilent 4200 TapeStation using RNA ScreenTape. QIAseq RNA Fusion XP custom panel primers wereDOCKET NO. BSBI-026-PCT PCT APPLICATION designed using a propriety algorithm to flank the targeted SNP / Indel sites at either the 5ʹend, 3ʹend, or both so that 230 basepair (bp) read sequence contained sufficient endogenous sequence (≥25bp) from both directions.

[0155] qPCR on RNA isolated from sEVs

[0156] RNA was extracted from isolated sEVs using the miRNeasy Serum / Plasma kit (Qiagen) and quantified on a NanoDrop One (ThermoFisher).25 ng of cDNA was used for each reaction. DNase I digestion was followed with cDNA synthesis. qPCR was performed on a LightCycler 480 (BioRad) for 45 cycles using PowerSYBR Green Master Mix (ThermoFisher). A synthetic DNA ultramer was used to create a standard curve to calculate copy numbers.

[0157] RNA stability in linear longitudinal samples

[0158] Blood was taken from a healthy individual three times over an eight-day period and EDTA-prepped plasma was prepared from each sample. The plasma was stored at 193 kelvins for at least 1 day to ensure freeze and thaw consistency in results. Total RNA was isolated from linear 1.0 mL samples using the miRNeasy Serum / Plasma Kit (Qiagen) following the manufacturer’s protocols. Quantification and Quality analysis was performed for each time point’s RNA using the Tapestation 4200 instrument (Agilent) using HSRNA Screentape according to the manufacturer’s published protocols. RT-PCR was performed on a LightCycler 480 instrument (BioRad) using 25 ng of cDNA as a template and PowerSYBR Green Master Mix (Thermo Fisher) in a 24 µl reaction. Several gene targets with a synthetic DNA ultramer as an exogeneous control were studied to calculate copy numbers

[0012] .

[0159] Probes and primers

[0160] The 288 genomic targets referenced above include Variant Nos. 1–285 in Tables 7, 8, an 9, below.

[0161] To explore the 288 genomic targets of interest, 894 target specific primers were generated to ensure capturing all SNPs, splice variants and fusions. Primer design was based on GRCh38 genome build and designed using a proprietary algorithm to capture transcriptional variants. Briefly, QIAseq RNA Fusion XP custom panel primers were designed to flank the targeted SNP / indel site, at either the 5ʹend, 3ʹend, or both, depending on the target, so that the 230 bp read sequence contains sufficient endogenous sequence (≥25 bp) from both directions. High primer specificity within the Gencode Basic transcriptome model set was chosen. For SNPs and indels, chromosomal coordinates with 50 bp padding were targeted.

[0162] Targeted RNAseq:

[0163] QIAseq RNA Fusion XP targeted panels were used. These require just one gene-specific primer per target allowing for considerable flexibility for targeting splicing variants, fusionsDOCKET NO. BSBI-026-PCT PCT APPLICATION and SNP regions of interest. The QIAseq RNA Fusion XP Panels use single primer extension (SPE) and unique molecular index (UMI) technologies in NGS to help identify and characterize fusion gene events, gene expression, and SNP / Indel at the RNA level with high efficiency, sensitivity, and flexibility. The QIAseq RNA Fusion XP Panels rely on highly efficient RNA conversion, gene-specific single-primer enrichment, and molecular barcoding for sensitive fusion, gene expression, and RNA SNP / Indel detection. Total RNA was isolated from plasma samples using Qiagen miRNA serum / plasma kit and QC performed using Tapestation. Isolated total RNA (10 ng) was reverse transcribed with high efficiency into first strand and second- strand cDNA synthesis adaptor complexes containing unique molecular indices. Sample indices are incorporated into the dsDNA. Enrichment of targets was carried out using a single gene-specific primer and a universal forward primer and the libraries were amplified via fast universal PCR, in which a second index was added. Sequencing files were fed into the QIAseq pipeline (Qiagen), a cloud-based data analysis pipeline, which enables filter, map and align reads, as well as count unique molecular barcodes associated with targeted genomic regions, and call variants with a barcode-aware algorithm.

[0164] Unique Molecular Indices (UMIs)

[0165] UMIs also called “molecular barcoding” is applied prior to any amplification such each original 213 target molecule is “tagged by” a unique sequence “barcode”. This is accomplished by the ligation of double-strand cDNA with a sample index adapter containing a 12-base random sequence. Statistically, this provides 412 = 16,777,216 unique molecular tags for each adapter and each converted double-strand cDNA molecule in the sample receives a unique UMI sequence. The barcoded cDNA molecules are then amplified by SPE for target enrichment and library amplification. Due to intrinsic noise and sequence-dependent bias, barcoded cDNA molecules may be amplified unevenly between different enriched targets. Therefore, target transcripts can be better evaluated by counting the number of UMIs in the reads rather than counting the number of total reads for each transcript. Sequence reads having distinct UMIs represent different original molecules, while sequence reads having the same UMI are the results of PCR duplication from 1 original molecule and are counted together as 1 molecule (QIAseq RNAscan handbook).

[0166] Library preparation and sequencing

[0167] The QIAseq RNA Fusion XP Panels are provided as a single tube of primer mix, with up to 20,000 primers per tube (custom panel). RNA samples are initially converted to first- strand cDNA. A separate, second-strand synthesis is used to generate double-stranded cDNA (ds-cDNA). This ds-cDNA is then end-repaired and A-tailed in a single-tube protocol. TheDOCKET NO. BSBI-026-PCT PCT APPLICATION prepared ds-cDNAs are then ligated at their 5′ ends to a sequencing platform-specific adapter containing UMI and sample index. Adapter-ligated cDNA molecules are subject to limited target-barcode enrichment with SPE. This reaction ensures that intended targets are enriched sufficiently to be represented in the final library. A universal PCR is then carried out with highly efficient, low error rate, fast processing Taq enzyme to amplify the library.

[0168] Libraries were prepared using QIAseq RNA Fusion XP Panel (QIAGEN) according to manufacturer's instructions from 20 ng RNA for the tissue samples and 5 μl of the concentrated plasma samples (500 to 1000 pg). A total of 31 cycles were performed for the universal PCR amplification step. The libraries size distribution was validated, and quality inspected on a Bioanalyzer 2100, DNA7500 Chip (Agilent Technologies). Libraries were pooled in equimolar concentrations based on the bioanalyzer 6 automated electrophoresis system (Agilent Technologies). The library pool was quantified using qPCR and optimal concentration of the library pool used to generate the clusters on the surface of a flow cell before sequencing on a NextSeq550 instrument (Read 1: 229, Read 2: 69, Index 2 x 10) according to the manufacturer instructions (Illumina Inc.). Raw data was de-multiplexed and FASTQ files for each sample 242 were generated using the bcl2fastq software (Illumina inc.).

[0169] RNAseq Analysis

[0170] The QIAseq RNA Fusion XP Analysis workflow of GeneGlobe on https: / / geneglobe.qiagen.com / gb / was used for the analysis of the samples. Panel CJHS- 14875Z-894 was chosen with default parameters. Data was captured in terms of detected variants, gene expression and fusions. The filters are designed to catch false positive calls that have incorrectly high mutation likelihood for various reasons. A non-reference allele needs to pass the quality score threshold and all filters to be reported as a variant. smCounter2 uses a logistic regression classifier to determine if an indel in homopolymer is real. The filters in smCounter2 are: STAR Parameters Setting align SJoverhangMin:12; alignSJDBoverhangMin:12; chimSegmentMin:12; outFilterMultimapNmax:10; Filters Setting endogenous: 15; longest_must_be: 25; minmts <dynamic>; minreads <dynamic> as summarized in QIAseq Fusion XP SNV / Indel calling.

[0171] RESULTS.

[0172] Isolation of sEVs from the human circulation for detection of circulating RNA.

[0173] Optimizing sEV isolation is critical for harnessing their potential in cancer diagnosis and therapy. We first optimized methods to isolate EVs and RNA from human blood. Blood from the same healthy individual was drawn and processed with various anticoagulants or without any anticoagulant to extract serum. Total RNA was isolated from 0.5 mL plasma andDOCKET NO. BSBI-026-PCT PCT APPLICATION serum samples using Qiagen serum / plasma miRNA isolation kit and characterized using Tapestation. Comparable amounts of RNA from 10 to 20 ng were obtained FIG. 11A). Serum and EDTA, ACD, and Sodium-Citrate prepared Plasma have relatively the same amount of RNA, about 12.5 ng in 0.5 mL of sample. The Serum appears to have more RNAs in the 175 to 500 nucleotide (nt) range while most of the RNA in the plasma samples is in the 150 to 200 nt range. Regardless of sample type, the greatest amount of RNA is always in the small range, about 25 nt with the 75-150 nt species also prominent in plasma. While the sodium-heparin plasma appears to have much more RNA per sample, the extra steps that must be taken to make the RNA viable for downstream applications do make it a less enticing candidate.

[0174] RNA isolated from plasma and serum specimens was also treated with polynucleotide kinase, an enzyme known to stabilize circulating fragmented RNA (15). However, this did not result in any significant change in RNA yield (FIG.12A).

[0175] Since RNA in the circulation is mostly concentrated in sEVs, we evaluated various sEV isolation methods. In addition to an ExoQuick precipitation and UC for sEV isolation we also tested two matrices produced in our lab, we called matrix 1 and 2. sEVs were characterized by NTA (FIG. 12B). UC performed poorly in terms of particle count with a range of 4.1x1010 EVs in the 0.5 mL plasma sample to 2.0 x 1011 particles in 2.0 mL of plasma. Test Matrix 1 and 2 (TM1 and TM2) did result in a slightly wider range of sEV particle size, 50 to 300 nm, than ExoQuick which had a narrower distribution, but both did capture the most particles in the 100 nm range. To evaluate the effect of one cycle of freezing and thawing on sEV-derived RNA yield, fresh and frozen plasma samples were compared. As expected, freezing and thawing led to a 25 to 50% loss of RNA depending on the method of sEV isolation (FIG.12B).

[0176] All four sEV-isolation methods, however, show comparable levels of liver specific transcripts when tested by qPCR. beta actin transcript was used as a control (FIG.11C). DNA contamination in ctRNA is always an issue. In addition to EQ and UC, ExoRNeasy (Qiagen), another column-based method was investigated. ExoRNeasy columns work by trapping the EVs which are then lysed on the column to isolate RNA. To test the purity of ctRNA isolated by EQ, UC and ExoRNeasy approaches, ctRNA samples were either treated with DNase or left untreated before conversion to cDNA followed by analysis of liver specific transcripts using qPCR. Comparable copy numbers of both Alb and FTL transcripts were observed affirming the purity of ctRNA samples as DNase digestion did not affect the expression levels. (FIG.11D).

[0177] To test the reproducibility and precision of sEV and ctRNA isolation we sought to investigate the EV counts and RNA yield from increasing volume of plasma samples. All four isolation methods show a consistent increase in both particle count (FIG. 13A) and RNADOCKET NO. BSBI-026-PCT PCT APPLICATION amount (FIG.13B) directly proportional to the increasing volume of plasma used for isolation. Compared with the commercial precipitation reagent ExoQuick (Systems Biosciences), our in- lab PEG based solutions were as effective at capturing an equivalent number of particles and in total RNA recovered. The extent to which liver-associated circulating transcripts isolated in an individual vary from day to day was examined. RNA was isolated from the plasma of the same individual acquired at 3 time points over a period of 8 days. Linear longitudinal RNA samples corresponding to day 1, day 3 and day 8 were characterized by Tapestation, followed by investigating the levels of four liver specific transcripts using qPCR with the results shown in FIG. 13C. No substantial changes were detectable in transcript levels with respect to time. The amplified products are presented as relative copy numbers as a function of the day on which the blood was drawn. Importantly, the relative number of copies for each transcript did not vary by more than 3-fold for any given transcript. This suggests that the amount of these transcripts is consistent and does not vary significantly from day to day.

[0178] RNA variant profiles in clinical subsets using targeted RNAseq.

[0179] From the total RNAseq work of Example 1, we identified 288 ctmutRNA targets (including Variant Nos. 1 to 200, Tables 7, 8, and 9) that correlated with a diagnosis of HCC, that were concordant in plasma and tumors from HCC patients but were not present in LC or “Normal Healthy Controls” (NHC) plasma. These were classified as high-risk based on their “impact” and high prevalence among HCC samples. Since these variants were detected by RNAseq and from a relatively small number of patients, we sought to determine their detectability in a new cohort of liver disease patients (Table 1A) using a “targeted” RNAseq approach, which would characterize these variant lesions and provide more sequencing depth than did RNAseq.

[0180] Primers and probes specific for the 288 targets were produced. RNA was isolated from plasma-derived EVs in 81 patient samples. Additionally, RNA from 8 tumors, three cell lines and 1 liver tissue from a donor source who did not have liver disease (“normal liver”) was included. The investigation of 81 plasma samples using targeted seq analysis (QIAseq RNA- FusionXP, Qiagen) of the 288 specific lesions resulted in a total of 12,877 variants. Bar graphs representing the total number of variant counts corresponding to different clinical categories are shown in FIG.14. As shown in FIG. 14, SNPs are the largest class of circulating variants, followed by indels, a profile mirrored in tumors. Missense variants are the largest class by function, followed by synonymous and frameshift variants. On the basis of impact, the representation of high-risk variants in circulation is the lowest compared to low and moderate- risk variants.DOCKET NO. BSBI-026-PCT PCT APPLICATION

[0181] Variant calling used a depth ≥5, quality score Q≥20 meaning that variants of a quality score <20 and depth <5 reads were removed. 3,347 variants (165 per sample) were found in early-stage HCC, 3,362 (134 per sample) in late-stage HCC, and 386 variants were shared between the two HCC groups.5112 variants in total (165 per sample) were associated with LC samples and 1194 total (149 per sample) were found in tumor tissues. Distribution of variants in various sample subsets is shown in FIG.15A.

[0182] To further identify highly pathogenic or high-risk variants, SNPeff mediated annotation was carried out. Venn diagrams (FIG. 15B) show the distribution of high-risk variants in various clinical subgroups. 438 high-risk variants were exclusively detected in HCC plasma and 390 high risk variants exclusively with liver cirrhosis plasma samples. Among the high- risk variants in HCC plasma, 256 were associated with early-stage (Variant Nos.310, 326, 328, 329, 332, 333, 338, 340, 343, 350, 355, 357, 359, 362, 366, 367, 368, 369, 370, 371, 374, 379, 380–386, 391–395, 397–399, 400, 402, 404, 405, 407–412, 415–418, 420–425, 431–433, 436– 440, 448, 451, 474, 477, 479, 481, 482, 490, 491, 495, 508–510, 512, 515, 522, 527, 532, 533, 535, 543, 551, 554, 558, 575, 581, 582, 585, 586, 590, 605, 606, 614, 616, 640, 641, 643, 644, 647, 650, 660, 661, 664, 671–673, 675, 676, 679, 694–696, 705, 708, 709, 715, 835–840, and 847–971, Tables 7, 8, and 9), 255 with late-stage HCC (Variant Nos. 324, 330, 331, 337, 342, 345, 347, 349, 352–354, 356, 358, 360, 361, 363, 364, 365, 372, 373, 375–378, 387–390, 396, 401, 403, 406, 413, 414, 419, 426, 427–430, 434, 435, 441–445, 452, 455, 457, 458, 460, 464, 465, 470, 475, 476, 483, 485–488, 494, 501, 504, 514, 517, 520, 521, 524, 526, 528, 531, 536, 540–542, 545, 547, 549, 553, 555, 556, 561, 563, 571–573, 576–580, 583, 584, 587, 592, 595, 597, 599, 602, 604, 607–609, 612, 615, 619, 620, 635, 636, 639, 649, 652, 654, 656, 658, 667, 674, 677, 678, 689–692, 697, 698, 700–702, 704, 706, 707, 710, 711, 716–834, and 841, Tables 7, 8, and 9) and 59 were shared between the two groups (Variant Nos., Tables 7, 8, and 9). Some 110 high risk variants were associated with tumor tissues but not detectable in the normal liver tissue (Variant Nos., Tables 7, 8, and 9). In summary, a higher number of high-risk variants were identified compared to the original test set of 288 ctmutRNA targets, presumably because of the very high sequencing depth achieved.

[0183] Early- and late-stage HCC variants:

[0184] It was first of interest to know if any of the original exact variants from the list of 288 HCC-specific test candidates recur in the new cohort of HCC samples. A set of ~74 variants annotated to the same exact genomic location as in the 288-target panel and thus represent the same original mutation. That is, 74342 variants in the current cohort were identical to those found in the original cohort. Table 2, below, is a list of variants from the original test panel ofDOCKET NO. BSBI-026-PCT PCT APPLICATION 288 targets which are identical and validated in the new cohort of patients and thus represent HCC selective lesions in both studies. Of particular interest because of their biological significance are variants associated with the transcripts of EPB41, M6PR, ARHGAP5, PRDX6, FASN, 346 ARCN1, SENP7, ECI1, IST1, ACOX1, EIF3G, which had lesions identical in the original and current cohort samples of those with HCC and were not present in plasma from those without HCC. The variants of Table 2 include The variants of Table 2 correspond to Variant Nos.31, 48, 200, 202, 212, 215, 232, 239, 270, 717, and 734 in Tables 7, 8, and 9.DOCKET NO. BSBI-026-PCT PCT APPLICATION Table 2

[0185] A significant number of new variants close to and flanking the original test lesions were identified in all clinical subsets. Targeted RNAseq allowed for much greater sequencing depth than was possible with conventional RNAseq we employed earlier (13). Therefore, the possibility that recurrent high risk / high impact variants exclusively detected in HCC plasma in the vicinity of the initial 288 test lesions was also explored. High-risk / high impact variants exclusively detected in HCC plasma in at least 2 samples and not detected in any of the LCDOCKET NO. BSBI-026-PCT PCT APPLICATION patients (n=31) were identified. These variants are represented in a heat map shown in FIG.16. Each row shows a different variant, and each column shows a different sample. 256 recurrent (≥ 2 patients) high-risk variants were found to be associated with early-stage HCC patients (Variant Nos. Variant Nos. 310, 326, 328, 329, 332, 333, 338, 340, 343, 350, 355, 357, 359, 362, 366, 367, 368, 369, 370, 371, 374, 379, 380–386, 391–395, 397–399, 400, 402, 404, 405, 407–412, 415–418, 420–425, 431–433, 436–440, 448, 451, 474, 477, 479, 481, 482, 490, 491, 495, 508–510, 512, 515, 522, 527, 532, 533, 535, 543, 551, 554, 558, 575, 581, 582, 585, 586, 590, 605, 606, 614, 616, 640, 641, 643, 644, 647, 650, 660, 661, 664, 671–673, 675, 676, 679, 694–696, 705, 708, 709, 715, 835–840, and 847–971 in Tables 7, 8, and 9) and 255 high-risk variants associated with late-stage HCC patients (Variant Nos. 324, 330, 331, 337, 342, 345, 347, 349, 352–354, 356, 358, 360, 361, 363, 364, 365, 372, 373, 375–378, 387–390, 396, 401, 403, 406, 413, 414, 419, 426, 427–430, 434, 435, 441–445, 452, 455, 457, 458, 460, 464, 465, 470, 475, 476, 483, 485–488, 494, 501, 504, 514, 517, 520, 521, 524, 526, 528, 531, 536, 540– 542, 545, 547, 549, 553, 555, 556, 561, 563, 571–573, 576–580, 583, 584, 587, 592, 595, 597, 599, 602, 604, 607–609, 612, 615, 619, 620, 635, 636, 639, 649, 652, 654, 656, 658, 667, 674, 677, 678, 689–692, 697, 698, 700–702, 704, 706, 707, 710, 711, 716–834, and 841 in Tables 7, 8, and 9).113 variants were shared in both early- and late-stage patients (Variant Nos.298– 309, 311–323, 325, 327, 334–336, 339, 341, 344, 346, 348, 351, 446, 447, 449, 450, 453, 454, 456, 459, 461–463, 466–469, 471–473, 478, 480, 484, 489, 492, 493, 496–500, 502, 503, 505– 507, 511, 513, 516, 518, 519, 523, 534, 537–539, 624–634, 637, 638, 680–688, 693, 699, 703, 712–714, and 842–846 in Tables 7, 8, and 9).

[0186] Among the early-stage variants, 137 variants represent indels with frameshift mutations and 99 are SNPs representing stop gained mutation. 180 variants represent non-coding transcript exon variants containing regulatory elements. Among the late-stage variants, 111 represented indels and 104 variants belonged to SNPs. 159 late-stage variants represent non- coding transcript exon variants, containing regulatory elements. As in the case of early-stage high-risk variants, indels associated with late-stage variants represent frameshift mutations, while the SNPs predominantly represent stop-gained mutation. As the data demonstrates, several highly recurrent variant transcripts correspond to genes with established onco- pathological associations, such as EPB41, ARCN1, ECI1, CCAR1, HDAC5, SENP7 and ACOX1. The possible significance of this is considered further in the Discussion.

[0187] ctmutRNA variants detected in both HCC patients and LC patients without cancer. Annotation and proportions of highly recurrent LC-associated variants.DOCKET NO. BSBI-026-PCT PCT APPLICATION

[0188] To identify pure HCC specific variants our strategy of filtration and enrichment has excluded all variants which are detectable in non-cancer liver cirrhosis samples. However, since HCC often develops in the setting of LC it would be expected that some early markers of HCC would be present during LC. We, therefore, looked for ctmutRNA variants which are common in the circulation of both LC and HCC patients and HCC tumors but not detectable in normal liver tissue.

[0189] A set of 790 variants identified as shared between LC patients and HCC patients are represented in a heat map (FIG. 17A). The frequency of each of these variants ranged from 3 to 77% in LC patients, 2 to 80% in HCC patients and 0 to 80% in the tumor tissues. The most highly recurrent variant is the EIF3G SNP, (Chr19:101155880 A>G) noncoding transcript exon variant, with a recurrence of 80% in tumors, 77% 380 in LC plasma, and 80% HCC plasma samples. The variant minor allelic frequency (VMF) associated with this variant is very high in tumor and plasma samples, suggesting that it is a common variant. Similarly, an indel variant IST1 (Chr 16:71922608 AATGCCC>A, disruptive in frame deletion was recurrent in 67% LC plasma, 62% HCC plasma and 75% of tumors. Among these 790 variants prevalent in non- cancer LC and HCC patients, 335 variants were identified as high-risk with varying recurrences in LC, HCC, and tumor samples. In summary, we demonstrate the detectability of highly recurrent circulating variants shared between LC and HCC patients. The possibility that these recurrent variants offer potential in identifying high risk chronic liver disease patients is considered in the Discussion.

[0190] Apart from variants detected in circulation, we wanted to find out the most recurrent variants 390 associated with tumor tissues. 11 tumor tissues from HCC patients (Table 1B) were investigated by targeted seq analysis. All 288 ctmutRNA test candidates were observed to be concordant between HCC plasma samples and HCC tumor tissues (13). Therefore, in addition to plasma samples, 11 HCC tumors, 1 normal liver tissue, the hepatoblastoma HepG2, hepatoma Huh7 and “normal immortalized” liver PH5CH cell lines were also investigated using the targeted RNAseq panel. A set of 204 variants not detected in normal liver tissue and with ≥ 0.1% recurrence in tumors are represented in a heat map in FIG. 17B. As we have previously demonstrated, see Example 1, tumor tissues reflect a higher density of ctmutRNA variants than plasma samples from HCC patients. There are several variants that are enriched in tumors and HCC cell lines, yet not detectable in normal liver tissue. Some highly recurrent tumor tissue specific variants, also detectable in HCC and LC plasma samples, are summarized in Table 3 (those summarized in Table 3 include Variant Nos.726 and 787 in Tables 7, 8, and 9).DOCKET NO. BSBI-026-PCT PCT APPLICATION Table 3

[0191] Generating a panel of circulating ctmutRNA variants with high diagnostic precision to detect HCC patients.

[0192] In the previous analysis, we focused on identifying only high-risk variants or variants of highly pathogenic impact. Since the definition of “risk” (using snpEff annotation) is a judgment based on bioinformatic prediction, it is possible that variants not identified or “filtered” as “high risk” could also be significant and disease-correlative. We also observed that there are variants which are predominantly detectable in HCC plasma but also present in a few non-cancer LC plasma samples. We relaxed filtration frequency in order to investigate variants that are detectable in most of the HCC patients but rarely detected in LC samples. The ctmutRNA variants that were most common in and selective for the HCC samples, regardless of pre-determined “risk” or “impact” are represented, with their prevalence, in Table 4 (those summarized in Table 4 include Variant Nos. 52, 214, 313, 718, 973, 974, 977, 978, 993–996, 1000 in Tables 7, 8, and 9).DOCKET NO. BSBI-026-PCT PCT APPLICATION Table 4

[0193] The two SNPs corresponding to ASGR1 and MEX3C transcripts for example, were detected in 24% (or 12) of the HCC samples. The ASGR1 SNP was not detected in any of the LC samples but the SNP corresponding to MEX3C was present in 1 of the non-HCC (LC) samples. At the other extreme, a SNP in the CHMP2A transcript was present in only 3 HCC samples, but in none of the non-HCC (LC) samples.

[0194] In an effort to develop a panel with the highest diagnostic precision, we used various combinations of the ctmutRNA shown in Table 5 to generate 3 panels of variants that varied inDOCKET NO. BSBI-026-PCT PCT APPLICATION their sensitivity and specificity for distinguishing the HCC from LC patient samples. The results are shown in FIG.18. In summary, all 12877 variants are reduced to a panel of 36 in the following way. First, we enforce a specificity criterion that ≤ 0 / 31 LC patients and a sensitivity criterion that at least one early- or late-stage patient should be identified. Second, we remove the variants which identify the same set of early & late-stage patients as any other variants. Third, we sort the remaining variants in the decreasing order of the number of early- & late- stage patients they identify. Lastly, we go down this list of sorted variants and keep only those variants that identify additional patients than the variants higher up on this list. The panel with all 36 ctmutRNA candidates from Table 5 had 100% sensitivity (detected all 50 HCC patient samples) and 100% specificity (not detected in any of the 31 non-HCC samples). Table 5A, below, provides the variant sequence and will type sequence for each of the 36 panel members. The number of ctmutRNA candidates in the panel could be reduced to, for example, to 18 or 17, and though 100% of the HCC samples were still detected, specificity is compromised as 1 or 2 LC (non-HCC) samples, respectively, would also reflect the variants. In summary, we demonstrate a panel of circulating variants exhibiting high diagnostic specificity to identify HCC patients. Table 5A (V. No. – Variant No. Here in Table 5A, the Variant Nos. are from Table 7) V. Variant Sequence WT Sequence No. AGGATTCAGAAAGCCCAGGGTATGCCTGA AGGATTCAGAAAGCCCAGGGCATGCCTGA 973 AGGAGGTAATG AGGAGGTAATG GGCGTCCTAGATGCCTCTGCTAAAAAACAG GGCGTCCTAGATGCCTCTGCTAAAAAAACA 841 TGGTCCCTA GTGGTCCCTA GCCACCTGAGCAAGCTGAGCAAGAGCCCA GCCACCTGAGCAAGCTGAGCCAGAGCCCAC 974 CAGAAGCATGG AGAAGCATGG GGACGGCTGCCACGATGACCTCCACATTCC GGACGGCTGCCACGATGACCCCCACATTCC 975 GCTCCACTGC GCTCCACTGC AGCCCAGAACCTGTTGGGGGTATCATTTTT AGCCCAGAACCTGTTGGGGGCATCATTTTT 976 GGGGATCCGT GGGGATCCGT GCTTTCAAGCAGCGAATGATGTCATGCTTG GCTTTCAAGCAGCGAATGATCTCATGCTTG 977 TTCCGGCTAT TTCCGGCTAT CATATCCCGCAAGCCTGACCACAACTCCTG CATATCCCGCAAGCCTGACCTACAACTCCT 978 AATATACATC GAATATACATC AATAAGGGTTGAAGATCGATTAAAGGCT AATAAGGGTTGAAGATCGGTTAAAGGCT 313 TTGCCACAT TTGCCACAT AGTTCAGTGGGGGCCTGGAGTTGTCGGACT AGTTCAGTGGGGGCCTGGAGATGTCGGACT 979 TGTGAGGGAA TGTGAGGGAA GGTACTGTGGCTAACAAAAAAAGAAGAAG GGTACTGTGGCTAACAAAAAAGAAGAAGA 980 AAGATTTAGCAA AGATTTAGCAA ATGATGTCAAATGCTTTTGTAGTGATGGTG ATGATGTCAAATGCTTTTGTTGTGATGGTGG 981 GCTTGAGGTG CTTGAGGTG AGGTGTTCAGAGCCGTCAGAAAGGTAAAT AGGTGTTCAGAGCCGTCAGAGAGGTAAATA 982 AGGATCTTCTC GGATCTTCTCDOCKET NO. BSBI-026-PCT PCT APPLICATION AGAGATGCAGAGAGACAGGGAAAAAAAG AGAGATGCAGAGAGACAGGGCAAAAAAGC 983 CACCAGGATTTG ACCAGGATTTG GCAGTCCAGTCCTCCAGCAGGTGTAGAAA GCAGTCCAGTCCTCCAGCAGCTGTAGAAAG 718 GGGAACATCCT GGAACATCCT CTCTTCCACCCTGAGCAACTTATCACAGGC CTCTTCCACCCTGAGCAACTCATCACAGGC 984 AAGGAAGATG AAGGAAGATG ACGGTGCTGGCCACTCTGTATGCTGCTAAG ACGGTGCTGGCCACTCTGTACGCTGCTAAG 985 AAGTACATCG AAGTACATCG ATGAACCTGACTCTGTGGTCCTGGTAAGTT ATGAACCTGACTCTGTGGTCATGGTAAGTT 986 TATCCCAGAA TATCCCAGAA TTGTCAGCCATGATCTTGGGATGGGTGGTG TTGTCAGCCATGATCTTGGCATGGGTGGTG 987 ACATCCTGGG ACATCCTGGG TCACCCTGGGTGCTCAAGCCTTTGACCTGG TCACCCTGGGTGCTCAAGCCCTTGACCTGG 988 GCCTCCGTGC GCCTCCGTGC GGCTGTGGCTGAGATAGGTATTGCACTGCA GGCTGTGGCTGAGATAGGTACTGCACTGCA 989 GGGAATGCCG GGGAATGCCG GCCCGGGGAAAGGGTGGGGGTAGGAAGCA GCCCGGGGAAAGGGTGGGGGCAGGAAGCA 990 GCCGGCCTCCC GCCGGCCTCCC ATCCCCAAGACCGTTAAGGGAGGTAACGA ATCCCCAAGACCGTTAAGGGAGGATAGGTA 52 TCATG ACGATCATG CTTCAGGTGGAACCATTCAGAGGTGCCAGT CTTCAGGTGGAACCATTCAGTGGTGCCAGT 991 CTGTCGACAA CTGTCGACAA CGTACAGCACCCCCGCCGCCCCCGCCGCGG CGTACAGCACCCCCGCCGCCGCCGCCGCGG 992 CCGCCGCCTC CCGCCGCCTC CCAGGTTCACAAGTCATGGCAGCTCTCGAT CCAGGTTCACAAGTCATGGCCGCTCTCGAT 993 CTCAGACTCG CTCAGACTCG GAGTACACAGTGGCAGCTGGTTTAGTTGGT GAGTACACAGTGGCAGCTGGCTTAGTTGGT 994 GGACGGCCTG GGACGGCCTG GACCTCCCGCGGCGTGGGAGTCTGCGCGGC GACCTCCCGCGGCGTGGGAGGCTGCGCGGC 995 GATGCTGCAG GATGCTGCAG GAAGGATGAAATTTGGGGGTCTCCAGGGG GAAGGATGAAATTTGGGGGTGTCCAGGGGT 996 TCGTCTCTCAC CGTCTCTCAC TGTCAACCAGCTCGTCTTCCACGACCCCGA TGTCAACCAGCTCGTCTTCCCCGACCCCGA 997 GAAGCCCTGC GAAGCCCTGC GTGACCCCCCACTGGTGGACTCATCCTTCT GTGACCCCCCACTGGTGGACCCATCCTTCT 998 CCCTTCGTAG CCCTTCGTAG CAGGTTCTGGGTTGAGGTCCTGCTGCCACC CAGGTTCTGGGTTGAGGTCCCGCTGCCACC 999 GCTGCCTGCG GCTGCCTGCG CACCAGCAGCCACACTAAGCAAGCCCCCA CACCAGCAGCCACACTAAGCGAGCCCCCAG 1000 GTTGAGGGGAG TTGAGGGGAG TATTTTTTTCTGATTTCATCCTGTCTTGTCTT TATTTTTTTCTGATTTCATCATGTCTTGTCTT 1001 CATCTCTG CATCTCTG GCCGTATCCGCCTCTCCTCCTGCTCACGCA GCCGTATCCGCCTCTCCTCCCGCTCACGCAT 1002 TGGCCTTCTC GGCCTTCTC GCTGTTACCCTACATGACCAAGGCACTGCC GCTGTTACCCTACATGACCAGGGCACTGCC 1003 CAGTGGCTG CAGTGGCTG CTGCAACGACATCAAAGACAACTACAAAC CTGCAACGACATCAAAGACATCTACAAACG GCATGGCTGGC CATGGCTGGC

[0195] A subset of the tumor-selective variants are transcripts that have been modified by post- translational modifications, such as “editing,” where the nucleic sequence in the mRNA has been changed, and splice variants. Many of the RNA sequence variants detected in the blood of those with HCC are the products of post-translational modifications, such as editing,DOCKET NO. BSBI-026-PCT PCT APPLICATION splicing, splice variants, or both. Splice variants may result from alternative splicing or mutations that lead to errors in splicing.

[0196] Circulating mRNA fusion variants detected in CLD patients.

[0197] QIAseq-RNA-FusionXP Targeted RNAseq allows enrichment and discovery of novel fusions using UMI’s and Single primer extension (SPE) technology. Digital sequencing with UMIs facilitates differentiation between true and false variants. A false variant, due to a PCR or sequencing error, would be detected in only some fragments carrying the same UMI. A true variant, however, will be present in all fragments carrying the same UMI. Also, a fusion variant where both the 5ʹ splice site and 3ʹ splice sites are annotated, or a novel junction is supported by sufficient evidence will be considered a true variant and not an artifact. Though the test panel of 288 targets was not designed to characterize any fusion variants, we identified novel fusion variants in the vicinity of 288 ctmutRNA targets in both LC as well as HCC samples (Table 6). Table 6

[0198] Two fusions that would be predicted to result in altered protein sequences were identified in the LC patient sample UPC021P. These are the MDP1 transcript from Chromosome (Chr.) 14 fused with the TRMT1 transcript from Chr. 19. The other fusion transcript from this patient’s sample is the PTPA207 transcript from Chr.9 fused to the CDK12DOCKET NO. BSBI-026-PCT PCT APPLICATION transcript from Chr.17. RNA from another LC Patient UPC036P, patient, also had two unique fusions, one between the SENP7 transcript from Chr.3 and the XRCC5 transcript from Chr.2 and the other between the CXCL3 transcript from Chr. 4 and the TNFSF13B transcript from Chr.13. Yet another LC patient (UPC028P) reflected a transcript fusion between the FAM217B transcript from Chr. 20 and the HNRNPLL transcript from Chr. 2 that would be predicted to produce a novel polypeptide. Schematic illustrations of these fusions are shown in FIG. 19A. The relevant exon-exon links that are supported by the largest number of molecular tags are shown. Many genes have multiple reported splice variants. While the coordinates (on RNA level) for these fusion events are correct, the illustrated exon structure around it may be only a subset of possible variants associated with the genes shown. A similar investigation of HCC samples led us to identify other protein-coding mRNA fusions. An intra chromosomal fusion variant on Chr.3 between SENP7 and RASA2 transcripts was detected in a tumor sample. We recall that a splicing variant corresponding to SENP7 was detected in HCC plasma as mentioned above. Protein coding fusions between UIMC1 (Chr. 15) and RGS10 (Chr. 10); FAM118A 459 (Chr. 22) and STK25(Chr. 13); SAR1A (Chr. 10) and RALY (Chr. 20) and SAR1A (Chr.10) and CDC42 (Chr.1) were detected in the plasma samples from HCC patients (FIG.19B). Another interesting observation was the presence of Alpha 1 tubulin mRNA fusions detected in liver cirrhosis plasma. Widespread mRNA fusion variants between tubulin α-1A and α-1β and α-1C isoforms were detected. The schematic description of these fusions is shown in FIG.20.

[0199] Discussion

[0200] In this example, we demonstrate detection and recurrence of high-risk circulating RNA variants in the circulation of HCC patients. Most of the ctmutRNA appear to reside within sEVs in the blood. This work confirms our earlier studies in which the observation of hundreds of mRNA variants in blood and tumors of HCC patients was first reported (13). It extends those findings by profiling of particular variants in a new cohort of early- and late-stage HCC patients with creation of a panel of variants that can be used to detect 100% of the cancer samples and distinguish them from the non-HCC samples.

[0201] We also describe a few simple and practical methods of isolation of the sEVs containing ctmutRNA. Importantly, RNA transcripts are generally stable in the circulation upon phlebotomy, carried out at different time points from the same individual. Freezing plasma samples after blood draw led to a marginal reduction in the RNA yield compared to fresh plasma. These data suggest that, surprisingly, RNA can be a robust blood derived analyte for analyzing both expression and mutation profiles.DOCKET NO. BSBI-026-PCT PCT APPLICATION

[0202] The main objective of this study was to validate the occurrence and detection of circulating HCC-specific RNA variants in the plasma of patients. The original panel of 288 ctmutRNA targets was derived from Example 1 in which total RNAseq was utilized to discover variants selectively detectable in the plasma and tumors of HCC patients compared to samples from individuals with LC without cancer and normal healthy controls (13). We sought to validate the detection of these ctmutRNA targets in a larger cohort of HCC and LC patients using targeted RNA seq.

[0203] In this example, at least 75 of the original 288 lesions distinguished in the first cohort were also detected in samples from the current cohort of 50 HCC patient samples. These ctmutRNA lesions were not present in any of the original cohort of non-cancer patient samples (Table 1B). However, there are some variants with high prevalence in our new cohort of HCC samples that are also detected with very low prevalence in new cohort of non-HCC subjects (Table 3). The most commonly occurring HCC selective variants that are exact matches with the original 288 variants with their prevalence in the HCC samples correspond to GOLGA2 ~20%; CHMP2A, ARCN1 and SLC25A39 ~16%; SIRT2 and 490 PTBP1~15%; HDAC5, GET3, PPP1R12C ~14%; EPB41, CXCL3, GPS2 and TRMT1 ~12%; FASN, 491 BIRC2, EIF3G, UBR4, GET3, TRIP12, NDUFS8 all at ~11%, etc. as shown in Table 3. Identification of these specific lesions may be critical for identifying high-risk patients.

[0204] The targeted RNAseq approach achieves higher sequencing depth, increasing the confidence in calling a variant at a specific location. It is particularly important when looking for rare variants or when sequencing heterogeneous samples like circulating nucleic acids and tumor tissues. For our purpose, targeted RNAseq allowed for the detection of a large number of additional variants within the vicinity of intended target lesions. Many of these are considered “high-risk” mutations, implying they cause a significant pathological impact on the expression or alter the structure of the corresponding protein.

[0205] Understanding basic aberrations in the early stages of cancer can reveal progressive changes from a healthy condition to a malignant state. Cumulative accumulation of these dysregulations mark the initiation of cancer. Aberrations associated with RNA processing and alternative splicing have been reported to contribute to cancer development and progression (16,17). Cataloguing these alterations in RNA may provide early-detection tools as well as highlight aberrant pathways and therapeutic vulnerabilities. Both SNPs and indels have been implicated in Mendelian and complex diseases. SNPs involve a single nucleotide change whereas an indel incorporates or removes one or more nucleotides. It is not clear whether indels in RNA are more likely to influence complex and pathogenic traits than the more abundantDOCKET NO. BSBI-026-PCT PCT APPLICATION SNPs. Since reading frames should be maintained to preserve protein function, coding indels are subject to stronger 510 purifying selection than SNPs (18,19). The cumulative contribution of indels compared with SNPs to oncological risk is not known.

[0206] Among the top six high-risk variants validated in early-stage HCC patients (each detectable in at least two patients) include three indels associated with MYO1C, CCAR1 and ARHGAP45 transcripts, all resulting in frameshift mutations. Three additional indels in ARHGAP45 flanking the original test lesion were exclusively detected in early-stage HCC samples leading to high-risk frameshift mutations. CCAR1 transcript, a prognostic marker in liver, ovarian and renal cancer (20) exhibited an additional high-risk variant known to cause a frameshift duplication in early-stage HCC. Early-stage HCC patients showed indels in SENP7 and TRIP12 resulting in high-risk frameshift mutations. Consistent with this, indels corresponding to SENP7 and TRIP12 were also detected in 75% and 12% tumor tissues, respectively. Three unique deletions leading to high-risk frameshift mutations corresponding to ATF2, a prognostic marker of liver cancer, are associated with early-stage HCC. Furthermore, four indels corresponding to RNF44, a known prognostic marker for endometrial and liver cancer (20), represent high risk frameshift mutations associated with early-stage HCC. Multiple high-risk and frameshift mutations in NUP54, a prognostic marker for liver and colorectal cancer (20), LRRFIP1, a known transcriptional repressor (21) and SLC25A39 a prognostic marker for liver and renal cancer (24) are associated with early-stage HCC. 526 HDAC5, a well-known prognostic marker in liver, renal and cervical cancer (20) shows four unique indels flanking each other associated with early-stage HCC. CDK4, a prognostic marker of liver and renal cancer (20) and HERC1, an E3 ubiquitin protein ligase member each show high-risk frameshift indels associated with early-stage HCC patients. Interestingly, differential expression analysis of HERC1 showed significant upregulation in early-stage HCC compared to late-stage HCC patients (data not shown). The top three high-risk SNP variants corresponding to POLR2E, ABTB1 and DBNL are stop gained and splice variants. Three additional SNPs corresponding to SH2B3, METTL26 and TRMT1 transcripts representing stop-gained variants were observed to be associated with early-stage HCC. A pair of indels each for POLR2E and MKNK2 are associated with early-stage HCC patients. Several other high-risk indels and frame shift variants corresponding to ARCN1, ABCD3, TPP1, SRP72, CUEDC2, PRDX6, PPP1R12C transcripts, known prognostic markers of liver and other cancers (20, 22,23,24) were observed to be associated with early-stage HCC patients. A transcription factor ZNF691, prognostic for liver, lung and pancreatic cancer (20, 25), shows a frameshift duplication associated with early-stage HCC. An enzyme, Fumaryl acetoacetateDOCKET NO. BSBI-026-PCT PCT APPLICATION hydrolase (FAH) known to play a role in metabolic reprogramming in cancer (23) shows a frameshift duplication in early-stage HCC. Similarly, KHSRP, a splicing regulatory gene and known to play critical role in lung, pancreatic, renal and breast cancer (20,24), shows a high risk indel associated with early-stage HCC. Yet another high-risk frame shift deletion detected in ODC1, an FDA approved drug target and involved in polyamine metabolism (20, 25) is associated with early-stage HCC. With further understanding of the role and physiological impacts of these high-risk variants on early cancer development, the findings are likely to have profound impact on current efforts towards development of early detection biomarkers for HCC.

[0207] Late-stage HCC patients exhibit some unique alterations compared to early-stage patients. Among the highly recurring high-risk variants in late-stage HCC patients is an indel corresponding to EPB41, annotated as a deletion and frame shift variant detected in three late- stage and one early-stage HCC patients. Four indels corresponding to PNRC1 and three indels corresponding to HNRNPL, a prognostic marker of liver, renal and pancreatic cancer (20) are associated with late-stage HCC. Similarly, MKNK2, EIF2S2, 552 RBM42, PTTG1IP all cancer prognostic markers (20) exhibit three unique indels associated with late-stage HCC. Two high- risk frameshift indels each corresponding to SRM, PRRC2C, ZNF691, RPF1, GDI1, 554 MAP4K2, SLC9A3R2, C16ORF72 and SLC9A3R2 are found uniquely associated with late- stage HCC. Among the prominent SNPs, a missense splice variant in M6PR and a stop gained variant corresponding to GPAA1 represent high-risk SNPs associated with at least two late- stage and one early-stage HCC patients. High-risk variants associated with SENP7, TRIP12, SH2B3, METTL26 and TRMT1 were selectively detectable in at least one early-stage and one late-stage patient. In addition to the utility as diagnostic tools, late-stage biomarkers can be used in the assessment of tumor response to therapy as it permits a prospective end-point evaluation and provides a guide for clinicians to make future treatment decisions. Both early detection and the ability to assess the tumor response to treatment are critical aspects in the field of cancer.

[0208] LC is the dominant risk factor for HCC and was associated with 2.4% of global deaths in 2019. The burden of cirrhosis remains substantial owing to under-diagnosis and under- treatment of chronic liver disease, and the number of deaths and cases of cirrhosis are projected to rise in the next decade (30). In this context it is imperative to focus on early detection of cirrhosis as well to reduce its global burden. Circulating ctmutRNA associated with LC offer a unique opportunity to address this. In this study analysis of circulating variants associated with both LC and HCC patients highlight some variants with high recurrence and allelic frequency.DOCKET NO. BSBI-026-PCT PCT APPLICATION Variants corresponding to EIF3G, IST1, P2RY11, EIF4EBP2, HNRNPL, CTSW and PRDX6 showed a recurrence between 48 to 77% in LC patients and 40 to 80% in HCC plasma and 50 to 100 % in tumor tissues. These overlapping variants in LC and HCC may not be critical as HCC biomarkers but one can speculate that they would serve as excellent circulating LC biomarkers because of high recurrence and high variant allele frequency.

[0209] Chromosomal rearrangements that juxtapose two different genes together can form a fusion gene. Fusion genes play a causal role in tumorigenesis, accounting for ~20% of human cancer morbidity (31). However, the prevalence of fusion genes varies widely across different cancers, and many fusion genes are specific to certain cancer sub-types (32,33). Rapid and accurate identification of fusion genes can characterize and stratify cancer diagnoses. Precise fusion gene diagnosis can also aid in selecting therapeutic treatment, with several drugs having been successfully developed to inhibit fusion genes, including imatinib mesylate for treating BCR-ABL1 and crizotinib for treating EML4-ALK fusion genes (34,35). Fusion gene diagnosis can also predict prognosis, patient survival and treatment response (33, 36). Targeted RNAseq has been proposed as a fusion gene diagnostic in solid tumors and lung cancer (37,38). In this study, we evaluated the diagnostic power of targeted RNAseq for fusion gene detection. RNA fusions were detected in LC and HCC patient plasma. Transcripts exhibiting SNP and indel variants corresponding to SAR1A, 584 SENP7, RALY, CDC42, XRCC5, HNRNPLL, TRMT1 transcripts were observed to be involved in RNA fusions.

[0210] Several fusion variants associated with tubulin alpha (TUBA) isoforms were detected in LC patients. TUBA participates in the formation of microtubules, structural proteins that participate in cytoskeletal structure (39). During cirrhosis, the regenerative nodules of hepatocytes are surrounded by fibrous connective tissue that bridges between portal tracts. It could be speculated that aberrations in the structural protein may likely impact hepatic architecture contributing to liver fibrosis and cirrhosis. All these point to a possibility of widespread tubulin changes in cancer and features of therapeutic selection depending on this factor

[0040] .

[0211] In conclusion, we demonstrate the detectability of HCC associated high-risk ctmutRNA variants in the circulation of HCC patients, which when validated in a larger set of patients could serve as exquisite non-invasive biomarkers for early detection of HCC.

[0212] Example 2 References 1. Yang JD, Hainaut P, Gores GJ, Amadou A, Plymoth A, Roberts LR, et al. A global view of hepatocellular carcinoma: trends, risk, prevention and management. Nature Reviews Gastroenterology & Hepatology.2019;16(10):589-604. doi:10.1038.DOCKET NO. BSBI-026-PCT PCT APPLICATION 2. McMahon B, Cohen C, Brown RS Jr, El-Serag H, Ioannou GN, Lok AS, Roberts LR, Singal AG, Block T. Opportunities to address gaps in early detection and improve outcomes of liver cancer. JNCI Cancer Spectr.2023 ;7(3):pkad034. doi: 10.1093 / jncics / pkad034. 3. Singal AG, Llovet JM, Yarchoan M, Mehta N, Heimbach JK, Dawson LA, et al. AASLD Practice Guidance on prevention, diagnosis, and treatment of hepatocellular carcinoma. Hepatology.2023;78(6):1922-1965. doi: 10.1097 / HEP.0000000000000466. 4. Angeli P, Bernardi M, Villanueva C, et al. EASL Clinical Practice Guidelines for the management of patients with decompensated cirrhosis. 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[0213] Example 3 — Exemplary Assays

[0214] Clinical laboratory assay development for Single Nucleotide Polymorphisms (SNPs) using qPCR

[0215] A predominant class of circulating variants correlating with HCC belong to single nucleotide changes. A regular primer based assay will not be able to detect single nucleotide change in a PCR product. SNP TaqMan assay relies on two competing probes corresponding to either wild type sequence or variant sequence. Duplexed competing hydrolysis probe assay (ThermoFisher) can be easily used to perform endpoint genotyping on the sample RNA for each SNP variant. RNA is DNased and converted to cDNA. PCR reaction is set up using a reaction mixture consisting of TaqMan Genotyping Master Mix, forward and reverse primers and two TaqMan Probes. Each TaqMan MGB Probe (FAM or VIC) anneals specifically to a complementary sequence, if present, between the forward and reverse primer sites. When the probe is intact, the proximity of the quencher dye to the reporter dye suppresses the reporter fluorescence. The exonuclease activity of DNA Polymerase cleaves only probes hybridized to the target. Cleavage separates the reporter dye from the quencher dye, increasing fluorescence by the reporter. The increase in fluorescence occurs only if the amplified target sequence is complementary to the probe. Thus, the fluorescence signal generated by PCR amplification identifies the specific allele in the sample. Artificially synthesized DNA strands corresponding to the wild-type and variant sequences for the particular SNP can be used to act as positiveDOCKET NO. BSBI-026-PCT PCT APPLICATION controls for the WT and VAR signals in the TaqMan assay. Given the need for sensitivity and quantification of these variant transcripts, a digital PCR platform is used to execute the same duplexed allele specific assay. Digital PCR allows to turn the qualitative genotyping assay into a quantitative assay enabling to count exact copy numbers of variant and wild type alleles for these SNPs. Absolute copy numbers of variant or wild type alleles can be detected in a sample facilitating the clinical prediction.

[0216] Validation of Tumor Specific Indel Variants

[0217] The RNA-seq analysis brought a striking number of indel (insertion or deletion) variants to prominence warranting further investigation. For clinical assay development, primer pairs can be designed to amplify a stretch of RNA around the indel junction in a qPCR or TaqMan PCR. TaqMan probe specifically recognizing and binding to the variant indel are used along with 2 primers located upstream and downstream to the indel in a qPCR reaction. If present in the sample, the TaqMan probe will bind to the indel and similar to SNP TaqMan assay described above, RNA polymerase activity will cleave the probe leading to increased fluorescence reflecting the indel detection.

[0218] Example 4 — Variant Tables

[0219] The below Tables 7, 8, and 9 report 1001 variants of embodiments herein.97 9406 1951167 89 7 1 2 9 7 0 3 6 1 9453 122 699 42155301619258919238987 0 863232683329550 8 3 7 2 5 4 2 5 5 4 137484S50 55856536676 7 8 3 4 2 2 6 9 0 3 256323OP7 3743572 8591052539390131418226 217 01435 6576911313131313151717 41262624 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6MN OORIHTCACII-2 6 4 5- -1 2 3 1 1 2 1 1 2LN2S 11 .6D SPFA2 OP, CTS3_P ECCHCP1 B 1.T3C6TXfr 2S_3_3PI_1_ 1 21BAPSIH_3SI_3RO6 RFAUIB1ACS3 C, 1MC,TIoP5A-6RTRTNTM M NI 31 D,F TDS HP,DSPA M D,A3L7I3 CD K N DP676D ALS 216f,r4.C,966A AP PPR1A1Af N N M MEH12H H12TNEKCN NC oA5 P rS TC67o5 SI1TTH SI1TPA2 CH H423 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 7tn05050505050 0 0 1 1 1 1 1 1 1 1 1 1 2 2 2 2ai.5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5ro7 aN elV baT15 299 486 949 108 921 503 10670 08 95 208 7 5 1 5 6647 2892 2978 84142 0 8 9 9 6 28S5 7984762 99 02 63486 168435416096O9 550 20 982 006 4 96029 6 39030 03 3 0 3 2 3382 8 5167 4410 032906 195 71024 4 14 856013257969P1 1 3 4 741 7 1 1 5 1 451 9 82111 1 691 1 8 6 86171 4 871919 9 2 9M1 1 2 1OTRCHP- C620-I11.BS E SA2-OBM0 2 6 2.A1A O NRMG1 0H4D20L12BR633R31_53D23A 1 11K D1K2- A9CL 1 144T R65TSNT LD DPNROAAR PK1UPDCAC FAC CMP PA M GSAHCM MPPM1F TORSTCLSDXNL R P E RTHCM US T P S REKtn 1 2 3 4 5 6 7 8 90 1 2 3 4 5 6 7 8ai.1 1 1 1 1 1 1 1 191021222C OroaN D V9587495302 0775264 1 45 6 2 6 40 4 6 7 0131 5 6 28 4 3543969 7 8 7 9 0846011111474 4 6 65 2685184713 485327536523 57966133698 6 6 0 5296299664 5 1 6 9 21323233393 96094229361572696 719 5 1 2 90813305311 1 1 1 1 1 3 4 9 901010101216 6 6 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7NOITACI6, -2 2-- 9379 8 7202- 2-1 3111 65 6LYCP L, 5 ca 2PB Gb ._1Aca.5 KNC1K1PX_ 1PL ca.AA,411 .2R,5AL PF E,0- A3X2 A E2 1TX3JBLHbX1D6PKIK,A ATSB1 C yX_7.5P1R.K7ABF RE1.W 6VCUU CL TN A26Y X23 RX,64 61G DI T,X,C70,R7308GI T6R CMS,M K W K GD- 2HR1253 4M52TNL,BP ABK OGNRA3RS6X00H500 70 CC SP C5 B LG H DPBCAP BK GHYC C0M T A ACSAP545 6 7 8 9 0 1 2 3 4 722 2 2 25 6 7 8 9 0 1 2 3 45 5 5 5 52535353535353535353535454545454517753 728 8 3656 174 4 935 0 1 6 31373231121 752 2 908 6 0 433 1 1 6 1 254417 5 6 7183718098181039620456461 5 1 4865 2541 3 744 5 6 072 7 9 9 7 38010 172606304144 1 436 3 6 141 3 8 0 9 09 1911 8 9 8 2 3 0 4 8 5 01551 1 571 7 6 8 4 3 5 2 4412010111217191X1 3 50111517171919122X5TCP-620-I-B 1 1S1 11P 2 9_B_1 2CA291 211BR 2._C3CA2 111_5 3.O1A C1 C 1 A2 1 P14 BAJ&39 1 522 R1 R 4RMIDR LOPPO Y MIRHAAL H7H O YCTRP TDLNOASNPT TA MHCD GBUDP IN KT9 A L I P ZBTD A6 FMS S P LW AEK324252627282920313233343536373839304142434CO D8287155534 394 8 3 6 1 2 2 7 8 16 17 4 5 090 5 1 4293310714303 0 3 4 62427 0 3 8 278089125712 133 7 9 5 4045044516345018521798708289 51072252 48310929228897256 98719 4 5 3273 7 4 2 222 4 4 41 2 283047474153585163 8 1 3 511 1 1 1 141 1 2 3 37 7 7 7 7 8 8 8 8 8 8 8 8 8 8 8 8 8 9 9 9 9NOITACI1 3 2-6 5 5-1 9 1 2 1 2 1 2 1 -LDOBF _P N211PR VOP S11.5PS552L1O_ _ D _ 11.6A,1HP L10177P F 01L 1A1GB3P S PN UPTTDRN, ,62 S S.S RP0 P, RE,9AC DI R45 DR T4NS IDPIPMA1D.4CE619S20FRH,N 5Z S,TNF AB1C15.MINA,F B 11L5PR,H 3 WS S PCT7-09 PK 71A UTA H4SS BED1 0PJDC R PE1 RPZ1PCA92AP B 1 P F RA M4656 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 744 4545455555555553 4 5 65 5 55555555555656565656565657343 4705 8471 14 54 196491491987 48 3 1 6 1 3 171388 07 2228 6 5 1 1 94 534986498276 113244 556009181 574 91 954 491 5 5 6 3302521805843 8 032 9 1 8 2030862827 88080 845 3624011 8 2950 058563744 6 517 4 9 43504 011 1 1 1 1 4 341 9 6 4 5 5 47 91111112131417171919112 1 5 9112121517191TCP-620-IBS1B 01_1254.ELCAPP NJ 1RN2C3B462D2 4TB4IH1G01 84HP12CKC41AP 1 _5PA PA NRGCGONEN MTP PCTPAR 2KBKP C 3 TKACIBHSTSTBDPESBTCZTPTS ID C ABU NPA C DHRTDCMTHCH AEK44546474849405152535455565758595061626364656CO D695903 036212312 09 0 4 4 1 6 7 5 3 3 4 5 91 5 10 1 2 86451 69929238317 2 3 0 0 2 7 7759 80 3 8 8 71 6 6 8 8265985842964466177384 5 2 3 2 3772516168 8 5 6 1 4 9 5 4 35 9 6 7282258853054 8 8227 9 3 2 4 0 0 3 03 8 92 2 2 2 3 31 1 1 5868696273757874 711 1 1 1 1 9 99 9 9 9 9 9 9 9 901010101010101010101010101NOITACI4-1 1 1 2 1 8 4 1LR,511. D4 B6AP LLCP E181.3U2OT LMB7_PP 3 6_G1 26 KS _112S KAA NBCM D2L3 TIPGJR2A 1 MH,1RDE BOP BAPRR1 PS,,N56S, TF1ML01N NRA O MUP- X 1RD H,61R_3ASPS,PCSUS,1A DCYPP31 ROLNSA,T P 1-1 S 41C5KTAA CP,A DFN N GCA1PSC MS1A PD PY A K NCC UPMC SRH KPA D777686960717273747576 7 8 9 0 1 2 3 4 5 6 7 85 5 5 5 5 5 5 5 5757575758585858585858585856960 5 71 7 94 5 0 5 6 1 5 14 0 9 3 80540 2 4 8652910 2 2 2 8 8 5 7 68930079 62343 5703767 6980512121868824 0 922740 9 5728748 0 8 1 1 3 8 8 19541695762667 384 5673762 7 8 8 4 4 6 0 2565 3 6 50374852 6 464656919176285358 6 2 9911 171811112 49191919191 3 6 71111113131617102 1 1 1 2 2 3TCP-620-ITS1_2U 2_2DB&2 3 P PNS4B._2_25151.0 9 01&3O1P-1H42P B1A M 10 3K P2EBT 1H4K P4 APW5A252 F N 6E 22 A01D Xfr 2LS RL3NIR D TT1C23 BFXIA Y NBUB PY A ASACTTTM MTC C CCLSLSTS FCA IAo1RPCLBAFATF ENC T SO DFEK66768696071727374757677787970818283848586878CO D918785 70 53 713 4 0 1 3 4 58 0 9 6 976 312569 6708495460845 2 2460753385355 04456346 49 77 5 7 7 08024249 2 6 8 2 234 3877284 15241692556988282 4 5 5 5 102 47 40042014 7 1 5 5 5 7 7 9408147896 444111111 1 1 6 6 6 6 6 601011111 1 201010111111111111111111111111111112121212121NOITACI-820161 1 1 1 2 4 6-27L11M_ 2A1HCNA2R, 7.2 1LLEABIL G,_ G,_ P 5L61XAP711 A615frU13.PIP PI 7CT13R MITNU OP C13H1PYR,PIF,BSOD32KD32KSAUCBTDW,8 HSPCo2N42 F ,1P1P R TA, B5RVR,2M,2 SKI TF,0C1S98S, 58F,1DR 1DR CBDRLZL1R1S,C,697TAD XBET.8SCASAP 1 8- 4AP1 4 C R R 1 2.3,1N4PU OP7D2PTS14TPAEPRID C K K X N N DI3NTT, RBMCA A D82AP1,-7YP890 1 2 3 4 5 6 7 789 9 9 9 9 9 9 989990010203040506 7 8 9 05 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6060606061679 60 66 20215 50 48 86 1 157 406 8 6001174 61203058 17 10 5 24 4806 403 30632 1 98 147 241 68 39899 33 352 3371073 5 422 8 2 7 1 9 9 64184713020852479145916 8 5 56 5577 5 04347 428 222 8 0 25 9 0 41 74141 201 6 4 7 1 1458574748411344 5 7 8 8010111616171719191919191X X X1 1TCP-620-IBSB. 21128AO74 1 8 CS83 D14 4382 11_P1X AF 1NPRBDE FUME1T IPLP3N M1 FAP_ITSDRADOP P SGPCARUCD NMIAMTCETS F B RTATPME E IAGSTRT BAURIARM Y GRSHEK889809192939495969798999 001 2 3 4 5 6 7 8 91010101010 0 0 0 0C1 1 1 1 1O D82146039426 2 2 4 2 7 93 9 2 4 8 6046 690 1722 4 1 7 423127580708 0152636971877 2 4 4683 4 1 9 3 4 8 2 224733 8 8 1 5 3 1785491175710752377554192845 5 7 29 9 9 5 5 23 4 6 7 3 38 1 2 8 9 6 22 2 452813434866033 478 553 9 73 4 4 4 4 5 6469659 969111111112121 237 7976802212121212121212121212121212121212121313131313141NOITACI 8 -- - -L P 4NHP 1B74112.7 SR11T51 1K6FTZ2P121.1 5K1_2_2T1P1O3F 1 1.41 3L6203DPDPH URZP, RRCI PRD9 CYPSSBSTPEA VTPRJ4 P 5 5 FA X X NBA NIT1P 1RH7PRHC M40D 0E, 3PL 15 ZM,,7M,EUC E, 93B B RCBSM, ,5 BCAM ACDP87,1 61053M3KKP T T ,KA21 1U,3 RN3TR N YHLAR 3F FCI L CDNCEM HTL.8ILM K G DPM A K G92DE912 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 711 1 1 1 1 1616162626262623 46 6 6 6 6 6 6262626262636363636367417406644 7905 58 159599 43 84 03 9258 99262471 9058 4 18 5 1 50 3 8 2 3 0 7 0 9 5 2 21 9 0 188918 1 6 2 3 3 0 75 1 1 7 8326263395 056 53245 1 7 8 93680 7 5436 6 7941 8 851 1 8 663 207 8 243491477809434568849 55585 2 96439 20 6 7 7 33740 0122 3315122 581 44121 7 6 5 51101 9 91 1 1 1 1 1 1 2 2 2 2 3 3 6 7 90111212131415151TCP-620-IBSB1AL1P. 2 F 2 31 A 2DA 306LPA22 _ 8H1 P 1A5 M NG3M2102 2R63A2BE1L 41PNI2O_IRPRPNCC E R BAPIML PB H34 P 1PKT 2F RNNY HTPELKP BALSMNA T R A O RRCFIRR DRN UATTHR S T F P RKR EML CGI FMEK011 2 3 4 5 6 7 8 9 0 11111111111111111111212223242526272829203132333C1 1 1 1 1 1 1 1 1 1 1 1 1O D7823955446 06 0 3 5 9 902 3 3 51 7 32 8 5 45 3 2 7 32 85923666 4166902 0537 1 4 1 1220 0 8 77476083503 8 926 4 8 6 4 9 2763 9 9 2 316118789109700 4865 73287289220343951 4750 3 3 3 8 9 6 60337142 8185518812 2 4 4 6 7 8 9 1 1 2 2414141414141515151515151515161616161616161NOITACI2 15 211 11 4 042 1,3-- 41-51LA,R 7TDAP3P.,10 RVD 171.0C, PILR,PP60 P C ECREC85DN2N IP B C11 11.2DANP L .9 A5T,FCZAC 1D7. R6AE81 AFHS L PN G AI1HC XB SPC, PR PR2J51LTCO1 2FNPA66.16CDS BD C1645C6,0GL,L AS7M1CLS,1AU NS 9,5 ,fF ,3.17SR,2. 13 TAT006RC 2- 8C 00T 28frOGLN DI L 2rEo 22 3-BP E 0A0 ,1E CP 9AR Lo4GOE BGM61 J5D2A G AE C177 T9C0 56 7 8 9 0 1 2 3 4 5 6 7 83363636364648 9 0 1 2 3 4 56 646464646464646465656565656560098 736562 2635 488374155748339588809392 796237311 0853566 9 159 9823 5396104 3 3 8 9 4 0 9 3 228639073047 6 4 4 2 6 39061737 346 60 71 9 4 6 8735932925513827 440518 1 6012141538304142424344493 111151717171717191919191919191919191919112 1 1 2TCP-620-IBSB 1.1 3 E8A C20A932 L4P1NCA_11CFA1ORG2S N CSRL 1R G3 SR X MR 3AB 3CL C1P _1NSAP R BGOP FI ADBN DL A KS CIRKFAAFITG G A HPGE FDRHP RGCXPMR REK435 6 7 8 9 0 1131313131314142143144454647484940515253545C1 1 1 1 1 1 1 1 1 1 1 1O D137391 2234 009414938 3 5 0 0 0 6 6 0 3 93 2 90 69 8 4 69095114436201718337558 7 1 6 6 5 5 0 8 4 5 8 9 178 6 8 42780 7 7 43 0 3 9949 908 4 6 4391821658332803615217361798 5355181825304243406165767671863946161617171717171717171717171717171718181NOITACI 13P,L 1CP 1 6AC S H 3K31 2- -A6-1 -X25R N 1- 32. 6PHLPD1 10DL13.13CK 3 FIE .B22G9S,36 1N,2.2T N R 1111 S 6 P 11 1P B _1 8P L C C311P0 AM 9 Y KA95 L, L 1.1TP F 13R CEBNPRPRPR,PRR,T,5SA A UGAA ZN PRR, 2D3DAPGF 3A9R0,18 148 0P6C67ULS 21014B,1,30.4.,30 AS3.8.8 -2N,,37 ,2 L, 1C8181A1 .066 CLA1 1H ACG OGT27- STCC PAT 0E ECH2G6 CDPA URN KC CRA AB5151 B 23333GXET6SA67167 8 9 0 1 2 3 4 5 85656565666666666666666766866966067167267367467567640 0606771 1834 7046 1425 54 33 93 6849 5119 26 1163918417 28235 4 655 1792 2374 3 841 2989 9 075 59 0 7 950 8989 6118 363 25 273709190 0144708 8556 9143 5641 04 38 12 0404 3927 911 1 1 7 8 2437171 3 334224 4101 6 63 3 4 4 4 5 6 6 6 7 7 7 8 8 8 9 9 91111TCP-620-I9.3B11.2.SD721B.2N.NC41B 22. 2R 9 5 1 0 I IAL 4. 3 3549K H6 P PD3ACO ABDLCXT -1 4F 11 3P 1SLND1 R RN1NJA3N AM TALXCN1APRNK RTFSHATPMNI B PM DM AA H A HNESPN T N HSTI F S SD VCDSEK556 7 81515159150161162163164656667686960717273747C1 1 1 1 1 1 1 1 1 1 1 1O D09321770326113081543 61 94 3 626 55 7 6 93 44217 7 7 2 463 7 4 1 0 9 4 9 0 7 4 5 0 00620422440268519 5 0 6 87901 0 7 7 5 6522 2 9 6 2 5 947512333052 06571920421710213531414344454649445 11371435354749191919191919191919191919102020202020202NOITACI- TLDC242 16 4 2-31-531, -D 2 2 P HX1 - 26 0 4 8TM, TOP2NZ,_9L. .E6 9VD.T322114F LDP01. 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AP05,RAbC2.O81X,0 a1.BDP876,01X1.b 42KZ,C 1 1.LP P 5PR,R,1IU NPR8 7 L,1FH30 411SRPR075.9D9075.9D2L 91NL ,L4X 2P48.H A14F 1 0180R, P558CVP PA2 TNDT 3STM32ND00 ,66S1,5 OC6RP4441ADI 0R,Y. 50 ZO G K01 B 51073MC A5M350S 0P F11AF11 P01 C 44B96 00LAPRPM GPCI8 3PA D DB21 CAF05 E3 67 8 9 0 1 2 3 899 9 9 04 5 6 7 8 9 0 16 6 6 6 7070707070707070707171725 0365 559186574 766 3 80 9 19875 4 252 1 521117 7 4 7 3 6 6939 95 307203440059846699121941677 2977629 898 81 229943051212 4 1 7 548 9 1 87989 74 181 4 4 5 7 6 83131 221XX1 1 1 181 19101 661 4 4 6 4TCP-620-IBS 21 1S1 1 2B._5 _40 1 0 A_ _3_3 BOR 1N2 9622 C3N -2 1R1 L L 26f 1PND A ARGNF F FXEXLA N D1TM M A Aro RW N A MN NEM C S 6 ATZ RM NE CMIM MC LEK5961971981991901010203040506070809001C2 2 2 2 2 2 2 2 2 2 2O D69716 2175848 006 00046 42 1 44 24 6 9 09754 831389 080 23 303 05 76104750555 400 507 1750502 273 242 1 200401111 05541 2 2 35 604389 96974360 9159550500 004046 3060585976 7 049 0 0 4 8 4 5 581163 1025 5 92 8 44 18 44139 11 1 21 19 9 2 261 1 1 1 111 12201 1 1 17171 2 2 4 4X X X X X121 871 8216191 2 3 1 1 1 1 1 1 1 1 1 1NOITACI -- -L S11PHP.8 74R- A34P5.51G2P 14RP1ASGNI 3B621T217PM M2NC2C2 1414 1919 22PN, R,N S1S0P6A,F3XXCR, 1M1SKA 5S CE BCP6MEMAPHPR2LHTMPINR RG AST RTRTES S FCS MRCB B6 6LRRP PF FPRE EN NRA H AC CA45HES P P Z ZTNMMCRPA 4 23 4 5 6 7 811 1 1 1 181910212223 4 5 6 7 8 9 0 1 2 3 4 5 67 7 7 7 7 7 7 7 7 7 7272727272727273737373737373738 667 1740 28 209080456292 1157 6 17849 042 2 5410523 719799571719552 597588 09 29 03 2449 27 4869706 428 5 789 2 8 030231 3 9 857 892 7 879 3 2 767 170 51409 43 35955455959888 2 8759 049915892 52 568 71 917534 16 9191380312 271 9 1 2 9 5 5 8 7 291 221 9 7 1 4 5X0101 1 101 1013191517181 671 4 171 3 381 1111141TCP-620-I 1 2 3B _ .1_5S211P2PB.A1 61PSA2ALF2PV1P 1 1 51B21_ 82J 63O XN R3G T D4XB NGSDHA AR BDR EHAPERPOSPS R 9D MMTA B CX31GGAMTHCLS C L ROAARNP CABSG APLAPD22VR-1ONINLPAPT1PTA GR SG MC RNP REK112 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8212121212121212122222222 2 2 2 2 292031323334353C2 2 2 2 2 2 2 2 2 2 2 2 2O D176903358 65 7 2 153 6 9 753 3 0 19 6 7 5 40 60016261 2 806 8859531 9 019 8 281428911 4 633 8 137478938 512687949 289 05701061 498 8 2 7 428 8 7 382 3 8 0 515494636364 6 23030 8444 7 715 5 751 2 7 86 343462919 2 0 36291 1 958486888 01 4 4 888 4 4 466 6 9 78 5 202227 112 2 611 4 6 6 6 6 6 4 501 6 7 9 9821 1 1 1010101011111111111111111212121416161616161616171NOITACI 1F1F 1B2N3D1212 1R1 JNR4C2K2K1P 1111 C11P R 6 2R2R1IFC1T 27275LP PRPRLPG K3PDP PA A A A G GC CP JC RT 4 4 PL LAPA NPAPATPRPRABR PL6DMBT3BA3C9A9ETCSIfrforG 6o16A 1PSAH H HD M M M MUT CLCLC CT S RARAS SCP578 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 833 3 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 585950616263 47 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7676747 49 36 29 86826320 755 985 9 4 12 9 8 08 8 9 82 8 5 875 8 15460 888440001 8 7 1 055910030 8 1 9 302 2 2824 3 3800182192730 434 6730 335 35871969 433261709994 02822436 028898217 5 3 2 1 019 3 3 5 9 42 1 95 9 5 2 691 9 0 1 1 3 5 49 5 05 67 23 81 75750367 986 1 3 79 6 4 29 2 1 14 5 5 211 47101 431417101 3 3 3 621317151 8 4 4 371 5 91121417131 2X6102 5 5 5 7 13141 2 9 9 1 2 1213141TCP-620-IBS 0B 0. 11 S23R1M5 11H2 2 2F F11L 4 7fr E 5__5PD4 R 1F 01C22113A GOMNE CON MMTI PCDC P 3 2 LUOT RH A3ORRXE SHENCZ FSNCoG 6 A1 FCRA1FB1 C 2 6P A X C_1 1FAMSNEPRRC BA G XB P T R FH MP N H T E R IFPA GHC ORTS S E P S P R R S CAEK637 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 62323232424242424242424242425 5 5 5 5 5 575859506162636C2 2 2 2 2 2 2 2 2 2 2 2 2 2O D634960436 74 20 464 67 2 4 6 96 8 1 3 2 9 3 6 81 719 2997243730030 915 4004646 8 2702542 325641616 123 5 9 2 6 8 797374765303 8 8 65718 9 9 2 5 67023 9 611 5 080824242430 3 6 8460034044044344344 14727 85671 51 20 0 0636362148484859088 90101 1 1 20202535353638383831 14531717171717171717171718191919191919191919191919191919191 2NOITACI 1L P5C5C5C93N 1RLD3 SG1PG3 4L 54542K2K2K242424B LPLPLP1C1P 1PP RSA A AARV GGD1HBFPI PP PN N N M M MCBN N N ABA N D D D52SAC L E RA A G G K K KB B BT R R R BTPG3A H H HCA NAM LC R R RN N NAA URHRHM M M H H HR BT S RACA ARP656 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 866 6 6 6 7 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8788898091927 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 79728 50 8945 2289 27 174871 36 3 2 570 3 0 62 19 7 3 5 8 8159 96 833 2 7 13 845 0 844 1 6 9 25130 0 1 2 4 4 739 30 8512 6249 04 423967 64 116674865164 36 559329463641 6675 4464464266268805 14 4 34 257 6 594 6 2 778 9 1 35 40 0 053530973 1093 4433 17 6 7 680 8 8 773 2 6 98 28 8 8 1 1 011 1 1 8 1 9 3 5 4 132 5 6 7 11111 1 1 1 3 3 5202 3 5 6 9 1 1010121315161 2 2 2 2 4 9X7 8 8 8 6 641TCP-620-IBSB12__ 1 1.2 73B _ C3 0RLC2 L F1B1 1 2 411 1_2_3_ 1_2M2P6 PI_1 4D1K_1 1 1 1B_B O2N FST2PFNT5AC 1XC GMSAIEESMDC F R 3A9 RP6G A M D NCFREP 5MB PN UNNRPHSTSMTM H AOLMSRLSPHE E CDH H H- - LORAFSASASALALG YTN D DIA A A H HPEK465 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 42626262626272727272727272727 7 8 8 8 8 858687888980919C2 2 2 2 2 2 2 2 2 2 2 2 2 2O D476308 0186153 7 3526 7 1 1 9 5 9 4 0 4 7503 654 5 0 9 160 29709927594053500269591 6 0119153 563305243651250 919 3 3 3 8 3 3 1 9 34259358977 1041842135858 86 38 5 8 8 7 8 8 9 228211 2 874791651519119190 5 9 54 0 072 33 3534444442 853 4 4 4 4 437676777 3 3 912 2 1 1 1 1 1 1 1 1 1 1 1 3 4 82 2 2020202121212 3 3 3 5 5 5 5 5 5 5 5 5 5 6 6 6NOITACI2 1 3 5 1 1 4 3 3 4 6 1LF 2PT 1PIPI2FS22S62FIL PKIPI 1F1 1 B BT H A D1 F 4 1D AHPHP FMIMI RBF C141XFH3PCRPART R FIFEIEE PGTGT BDAPATM AIAINRLBLBEN MRR IDPRU DRNPARLTPTP SD D A ACTCP734 5 6 7 8 9 0 1 2 3 4 5 6 7 899 9 9 9 9 98 9 0 1 2 3 4 5 6 77 7 7 7 7 7 70808080808080808080818181818181818184838 75 25 968987 87 789035233734 912 8 29 9 9 6 006 2 8 137 4049 95 4 8 0 508 40227 436 72 036194596 14 334172299615033127 98 6 1 825 640332 4685288573 426942 044 3 2 834 5 7 5 1 9 5884 6 691779643081 817 5573659 24725462240700 7 57 8 4 1 841 1 1 711 5515102 3 9 6 6 92181 7 8 25102 5 3 422 1 6 8112191 1 1 1 3 3 7 8 8 9TCP-620- AIM1A TS05B ,.271N,I2H,-2S2 1-B1 4.71.2-L1LI S33AL LP3H5.0E1 P.D2R 821P21G1V,-6 PR,R,R_1_1H3 1 9 1 784282A 3-5H1, .D61 3K K NR,12.8 3 2 1P08 R,L L4PSA7112 L 8SN 53O KD N GNP 001 8P 153TB CO AL K D -3.DG 1F TCPRNRAS RCNPCK NPT 1 LSI 21ORS 5 L R 4K6 3V ARDTAFIACS C RA3P CAPRAPSHH122HHSK64KPRPRLEB6TCTSNZLCM AW,EK293 4 5 6 7 8 9 0 1 2 3 42929292929292920303030 0506070809001112131415161C3 3 3 3 3 3 3 3 3 3 3 3 3 3O D413339 19 12 27 923856 0 4 94 6 0666 7 639 9 0961 755 944147336 0 1 252 2236908 4383 4639 49690 224 2 2 2 0761250 310 0 7 6908080 489 95050 245 7 3 4 4658 5778 9 759 9 9 625 048 1969934444 9 841 7010167 08 8 8 741812137 8 4 8 412 01515151 4 4 4 621 46 6 6 7 7 8 8 8 9 9X X X X X X1271019191 3 7NOITACI1 1 1 3 RLC C CHO NI 1 1A S 4 0 1PH HP R LS1 I1I F1PI C 15E 1LA D DAPA1 1 R4P 2RBNPRNRNRYP RASASTPOP CA G GR PGO A ALTBBP P PNPTTA H A AOA AITYCG T NRTPMCH OD P AASGT RCAP889 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 811 2 2 2 2 28282828282839 08 8 8 8 8 8 838383838383838383848715040447161 244817 92 3302824858461565 1566 48 3581 31 9 0 4 7 1 1 1 4 7 0 8 69 869812647095 5 6 10 7 6885279766251515539702 1 794 4 9869633013940 6 8 663 8 6 0 0 9 7 9 3666283730934872365 552 590 5 0 0 0 6 0 58 6 098 915121 70111416161510121 2 211 6 6414151710202 1 2 3 5 5 5 5 5 5 6 7 7 801012121TCP-620-I-152CSC - D -111P2.09.- -11B1 C ZSPBRL.,S,5,4FT 1PR, 1J 2A11.611 11PPAP C R, R, 8.A45.641F _7 H6 R-1. ,1R,2.O132.3KCN11 1 6SGB962CRB 73T 34 0 PNA1D4F7P 81 4PB D 3- _1U1P1S3D_2 BN 1_11 2D5IN0 30L 1-T3A2.3M2PIO312BGPF F1R18182APRUTN AN FTIKCN0 P 9 1G1FE45RPN 7 A PP ,KCTCTRACX1PFID11 A88TE 3 P RAI T TAZAE R EM6 R 5EK718 9 0 1 2 3 4 5 6 731313232323232323232829203132333435363738393C3 3 3 3 3 3 3 3 3 3 3 3 3O D40 406000 004513 38 12610 8 9 7 20 3 9 123 0 4 47 5 87424 76 635479978860751385905945784 5 5 974 360129 8 3 374 4382 9 9 9 0 89831 2929849494 234244251292 109211 3151 37 6393 67 7 4 4 42 2 0101 2 1 1 7 7 8 9 9010111111 3 2216191 1 1 1 1 1 1 1 1 1 101010101NOITACI1L4 7P21 3B621TN6 1 2 3 3 3 3EX04F 2N X N1FD D2C2CD DPBPPNPEEI 2LSRTMPD K THST RSTRPTC LSAPEXEPRC C D DD D MRN NBAB E EAU UA AAE C CTMCP912 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 84848484848484848485858585858585858585868435 1 2 7 7 0 4 5 3 9 5 05 19 8 6 72501265001186167 7 6 0 3 93097 8 3 5 59950 6 7 5 2 55344677650425 6 05085261228112808193301136503 4 68 87 7 4 430256679158042628229845850152 525136 10742867 231 2 4 4 79151515161617171719191910222X1 1 1 1 1 1TCP-620-I 36.24.A A - 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SP,AN5D973M,O -1N1X,A6-11A21 C 94,78.8.81P4S 42L.261 22 G2-911 R,183 S,B RA5LS37 PPPRLF 1CTE 6P ERS PDED GOTMCF B1 1 1CNZGB B BRC000LA C6PVLLG,10ES0TNN23LPAL1FP961PDO R83NSCL7N3CDRST6 6 6NBXI 63 I 4 R P R 2A O D, S R Z C _EK041 2 33434344345346347348349405152535455565758595C3 3 3 3 3 3 3 3 3 3 3 3O D66999184 69 8436 65 2 6 0 8 1 7 3 4 5 9 7122 6230 4 08591 1345 5363631 0 0 4 9 4 9 9 5085095 1 932 657 7 7772399302941987812166857793 83281513 3 3 0 3 6 1 4 6 1 1 7 633 307142865 5981 415 6666 464646370829377740557310 02 6191 6 6 6 6 6 6 6 4 5 5 3 4 6 8010101011111111111111111111121212131315151616161NOITACI1 1 4 1 1 1 1 3 8LMPA2 1PR1SN AB C C 1JNP P1PPP 1L1L1LHS SFC1 2 41AM K DB 3G1GCH26R A R3 2 2L7frPTSA GCR RAAT TPRPRPRSUBDCOFMC EATo6AHCOA NCDUH3H9 TE1RSD M M M NT RHCL MCTASCP012 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 96868686868686868687878787878787878787888888888883334 0926360501 742511277712 22 437802 262828 96 632779868 72 7 7 6 4 2 5 3 7 6 5085 4897973790 411676133159 00 1 1 2 2 0 784166 6 6 866 6 7 42398 568868110602757983101 5395 927987 797078 5051491323279891 6 756 1 11161217181010141 711 2 3 32 2 2 2 2 2 2 2 2 2 3 3 3 4 4 4 4 5 5 5 5 6 6 6TCP-620- 1I C5 -6A A0H91cab7BTU GPGP 5C CT0 1_2 F_CTX1.X5SB 2N,N.R, ,63N3P,57A2 1P 11111T2 C1,1 ,M6AB1,4 B1P 21BD_22D_ DR U,5KT T3N22 1LK L2M 11AC C _BGG H H H1 1 R BC -2 FC11OCNSOCSB5T MTH561AN-B DR21 TP61AA MTP1K A NRE L 2 L3 FAHA M AOCM GLPK3YCHC EMK2FAHLRH D HADC SB3TPSIH CC, ,21SGPBTD MPMTNPAZ Z TA HC CA -EK061 2 3 4 5 6 7 8 9 0 1 23636363636363636363737 73747576777879708182838C3 3 3 3 3 3 3 3 3 3 3 3 3O D40902176989899991 3 6 2 4 9 858 19 9 5 6 3434 4 4 0 0 0 00152621 2 9 452 6 6031343294993 3 3 0 0 0 0 0 0 0405031093 3 50909090232323232323232 5 5 11 2525 08080898094444444444444444444443443443 5544447 9 2020101 1010101017171717171717171717171717171818191919191919191NOITACI 5 5 5 5 9 9 9 9 9 9 9 9L C C C C 3 3 3 3 3 3 3 3N 2 1 4 45 5 5E EPRNRP P LPLP 4P4P4P 2 2A A A AA5A5A5A5A5A5A5A5G G DBPD D D DL R RA A AR RH H H H2C2 2 2 2 2 2 2 NL LCAM M G G GO OALCSLCSLC C C C C RSLSLSLSLSL HRHRHRP PT SCA A AP156 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 988 8 8 8 9 9 9 989898989898978 8 8 8 8 8 8 8 8090909090909090999501 61 15 300987 59798 078 8 4 4 2 6 9 60 37456 454 2 6 949 453 4 8 0 8 6 3 92 718484844 10703451 9 5 5 06 358 8 664 2212281 1 1 8 720 9 653922 8 74483 05206378 9 716 27 0730442 0 0 0 942 8 5 6 93891536 6 54434343435 90 124 6 4 2 9 3 72 6011 1 1 1 3 9 2 3 5 6 90111 16 6 6 7 7 7 7 8 8 8 8 8 9 9 90101010101010111TCP-620-I 122 I - -,7__PB- F1 1 1A3_8BS 1K BSB7 0U1P 11P 21PN1MI1 D7-6 R,_. R5R,_ R3,_ 1 1FI,C 2PR 2PDN7O -RN A,2 B1 CN -3. 35. 35._ LD,5VK0K0K01 108115P02B4A G1 6 CT1 2-,5. RP 3D L ARHGD WHFVBC90WYT LA KRBRB1_RTTO2,5OP8O2OP8O2OP8AED H A1NWMCH9 9 9 C K F N A D HB CRG DDJ1P1T C M R1 8IPP A7LN MT5H5H5 T P I F F CAI C J R R 41 PAEK485 6 7 8 9 0 1 23838383838393939339439596979899900102030405060C3 3 3 3 3 3 4 4 4 4 4 4 4O D74 2494 920128498 4 5 0 12 84838 2 3 140 6 83 5 4 59170875829408 6218125543294204 7 5 9 4 4 2 8 8913 30 362178329294909055 134 85033844 939799521 2 25 436383242474555585 6760 01507505891717122919191919191919191919191919191 2 2 2 2 2NOITACIA2 22LSK K4B2T ACI A C CAP01 1P 12F2F2F 21PRMCPAN NR 3 C P 2121 2PRSPK KB BTISKSAI B CDT T TPINR1R1M HR TO A A ARAFM MRGPPPP HKT P TCT P PCP289 0 1 2 900 1 1 13141516171819102122 3 4 5 6 79 9 9 9 9 9 9 9 9 9 9 9 9 929292929292922493034 51 301935 43 86 08 4 3 8 78 5 5 3 8183 4 789 9 830 41 07504526 2 3388173931126 349 0 2 706 719 4 5 7 2 2698664138837420 6611351 100 567861958671144477 81 721 08734 034 044353971 3 411 711 2 9 51111111111212121213131414141516161717171TCP-6202- 1IPN AR,341. - -c1DR2ABD- MBRS,I 2AN39 PS L .19111 61 L,HW, 11MT CK-BX6.R .P6 94D1T,024. 4SS 1X P29B2EE13 F,642 L0 P1R,3.A3647 L, 1 R.,9.1PBR,S81 11UI ,A ,5. P0SB 1, 3O1POG3NR1C- 1 N1 21D RB SK52 2 -1 H1 RM1 TD2AVR R,M-1I1LPAPR5481DPIOCGMFTPPV U O O MAN- FTL11C 1PCH 4O92PPPDRJDM31-Dc3S1,GI1 4 O72 PS PRTN3BTC PMR C 8 P T J 363 L 2 R 1 2AT CAEK708 9 0 1 240404141413414415416171819102122232425262C4 4 4 4 4 4 4 4 4 4 4 4O D00748410 14846676 2 3 70 9 4 04 5 4594 4 56 2 2 2 208608 81735206400895363636 5 4 6 6997798 4 4 426381 78 7 7 7 988258583 6 7 74743131190492737373 35534441 7 96 6 6 69 3362 2 2 2 40121 5 5 7 74171712 2 2 2 2021212 3 3 3 4 4 4 4 5 5 5NOITACI 2L 1 1P1P1P 4E6F PIPI 7P1B3A272745453F 19P PI IPR FIRFIRF IR MSE 1G1N TGTE TDP P P PMI RB11S BA RSRSU U N NLBEAATRLRLRL PTPTPATARCAITKCP389292031323334353637 8 9 0 1 2 3 4 59 9 9 9 9 9 9 9 93939394949494949493191589975 19 17186 6 2 64 4 9 03 53 6 5 8 556 884980116 11713242 8398 8 7 5 4 6 5 9 6 0 4 156 8 7 2032489393 6303 629515 0521122347370 8 8742516860597 8219345927182 1 1813152717171818191919191122222.111 1 1 1 1 17T07C 2IP- K620,- A78-12 TCP2,007PI R21.- 1 XO4 F 9RB T, LS7 P 211PRBT 2 M, TMCP2N SP 1.SRB.4R F2M3P ,9R,3. ,5. 87411 1.,67T2M,DZ, RN0 , 4 ,3172951 226..M,891 1NE -381S 1811_1 0CB9M-1JP672 T2P 4 B 20R H K41f _ _4r 1 1M-2O90C1PPM1EPAH HRC22 SN2B3333A-IEPL MTAD2AR T9P1TP1M,A7IP1 _K ALICA DIEH2Co1BNBN D R3NP56TP C 2A O2 P 9 P L B B CACG GP R 41EK728 9 042424314324334344353637383930414243444C4 4 4 4 4 4 4 4 4 4 4O D458923673693 8 704 2 06 1 0 5246 74 41 755 7 7 5 4 039 1 219295124 760 0 20165 1 39295292922829 65149349498 8 9 6 594 5666290765656569656 714805050 909 9 054040414 0 58 1 1 23239 623 39393 1 577 7 7 7 3 42339844444 4 4 4 812 91915 7 711 1 1 1 1 1 1 1 1 1 151 4 45 5 5 5 5 6 6 6 6 7 7 8 8 8 8 8 9 9 9X X X XNOITACI4 4 4 415 21111 20 01 FL4PF4F4F4F CK6M 3f FCL LNININI FHH C4C4 1 1A AProHRNBNBPRPRPAA3D D A AB RPNRNRNRNRIU A6PND D A ARA MSCRN N A A U AAC PA N N MH H H NENET S S SD DCP467 8 9 0 944 4 4 5152535455565758 9 0 1 2 3 4 5 6 7 89 9 9 9 9 9 9 9 9 9 9 95959696969696969696969079091746 451 6 5 3 6 9 7 8 6 6 3 1 00899715501264805224626510 3 10 70 9605511220114 0 4 9 5 7 5 9 6 23 8 982 84317053308 42 9 8 9 1 4 7 5 6 0795695194 054 8 768 712257588 83433565568590515621724 0 0 2970328208 5234 7 23636497 2 311 1 1 1 1 1 1 2 2 2 2 2 2 2 3 31 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2TCP-620-IU,D -P1PES5-AB 25-1NSD1X1B N - G F1,11.X U,03f5rP CTB.C, PT,AP,P 1A 8N3L ,P o1 R,22.1RK1PO111R,42.8 D,11218R,2. 1N MFAG4415H6A L GO81 1C,T1N 81TL2,P27BR721PI N1AX I1B TA2K191BCA1DSNPAKP B00 BI6N41SH93R31 LCAT RHACF R1CUSG2 PRSIFRLAO6R5T SYN3HAS1TNF,3CTBTTAF S R CD A G9MC SAI P T LEK546 7 8 9 0 1 2 3 4 5 644444444454545454545 57585950616263646566676C4 4 4 4 4 4 4 4 4 4 4 4 4O D46551620 79656532 44 38 0 0 2 31 8371 52468 8 79 3 3 73 78 5305923246547 196 5 53777 7 460707066 73183898 99 015 252 3 5223 8 159 41719290505852 8 911 42955 994949477 758518797 320 5 9 4 0 51040 251 8 90111 401 1 5 2 4 14141 101 7 561X X X X711111 3X119191 11291 5 821416191 1NOITACI5L4545X11C3 1 24 C1 PI 41N 11 61ARPRDR4DRRRN1AA CLDTGSCRAB DB RP21 4B 1 LP HIP Y DTS 211UIR RP GR PAR R BTI PMFPA A AABM1E TMIA2A W W WUT T PP TPDHP BHCT P SCP590 1 2 3 4 5 6 9677 8 9 0 1 2 3 4 5 6 7 8 9 09 97979797979797979798989898989898989898999579 9 9 2 51 9 6 4 6 1 0 9 39 9 4 5 698 5 9 6 29 6493429125161 86487624481403117 6 2483 440 7 0 3 1 4302684579022933341447 82 3 9 136513714535 6 3 6 1 6 6555351747552858 163947677719314168 0 1 6 8 4 0 2016 5 5 2 2 9 01912232324242 1 1 4 4 4 5 52 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3TCP-620-ICCCB ,8 CS78APTP 21 - 7CBPA 8P11R,S. ,B8 80.1NN MO AP,21 22R -P R,P 1ATME5. 3182_532HR_P ,S3R_YV,2B -6_1 1N _2_ ,15P 44PY1R,NC S,R1.C,X3. 6CI T, BO1A0821AD 8 O N O,P5PHU N1 3PD8f I4FC 2P2P22SA6,R322RO B42.3N,8.37 6A1SNC8AC0DC8ACHPK3MKR GD MTM1RLE1LAE , IPVLPEEPP Sro2RA R DRARH A UPSR LOTKB3K1CRKC,- 6M31 T4 M-J19MA4 BME- BTHC LHF F SMCN6A1 1 1 1A1 9 R S 3EK869 0 1 2 3 4464747474747547647747879708182838485868788898C4 4 4 4 4 4 4 4 4 4 4 4 4O DTL A GT TG A G 44 7445267 8479 190932 786G TC C A3 2165776 3240 842326 57241 AA CC TT TGCATA 33 4 98 89 9 54 57 857 1572115 1041 006784 4461ACAG TCTTTG G 15 1 451 C TGT TG CTACTTACCTGCACTTGGACGCTGGT C77 9 8 9 7 0 1 7A A GC5 G G GC1 1 1 1 1 1 1 2X1ATTA A A GNATCCCOT TAACG G AGTTTITTTT CACT ACA CC A CGCC GC TCAGTA G ACI2LS DA AT33AG TC3 1H54PP PLPMPI11I 8 CACCDF C C A TC CPG1C EGXNE PA ANA RT GP T CTGR G CC TCG TCC CGA U MID G H NSTP C C C CRHPAAGCG GTG C ATTTGCTAGCAAGGC8 TCACCGCP elbACA TTA TAT GTC61992993994 5 6 7 8 909999999999999 0100a ATCGAT TGA CCCTTGCGCCA 101ACGCG GCF AG TCG GTE A GGT CTGCRACAGAA GAT GCA ATAC CGCCAG GG 66653081330 04877 17 3 9 GTACTCCAG AGG A CGC466495297 8 75314 598080GTG G G GTAACTCTG 24848632603549344 968241CC ATCCCC CGTG 2535854068 3905048772 384357A 13191 4 5 6CTTATTATATCCCGTAC TTCACTCTGG CCA G GACGG ATTACCAC CAAAG AG CC33 3 3 3 3 3 3 4 4 4 4T CCT CTACTG C GTC TAC TCCAG AAACCTGAG T A GACAAAATA GTA GCGCAGATAGAGCCGTG GAPACATATGGA TGC- A6 TAAGCGGGG GTGTCTCGTTGTTACTGTA AG20- G A A A ATATAATITAAA- B -ACAAATGCCTCGACB4 RSH 711 91G P AATA CCTACCTGCTBIT-CGG TTGCTAGI56. LI,ST32R,3.GTCCTAACGTGTCCC.,O4 PN H R, 1H MRR3 3 2N 1 8I1 MD1CK AB 26PHCPI I L1 CPG GCAA AGTAACGCAG GG N GCGAATGCTACTS 66 H XD ATIE R NALPI13 EATGGG ACTTTAATCGG GCTIA9 C PA G NC L T S F 2 CTCA A ATGTTTTCTTCTCE 0919293 4 5 6 7 8 9 0 1G ACTGCTG GCG A AGTCGCC K4 4 494949494949 9 0 0C4 4 5 5..1 2 3 4 5 6O VoN DG G A GC TA GTGCACG G A GT T TC ACC G C C C A A C T CGACAA CTGCCCCGCG G GTCGCGCCC GCA G A ATGCCG GTA A ACT C CG TCCAC ACGTG TA GTA C AGCGT CC T G A G G GCT CC GTCCCTCT CA A GT ACCACATCGCTGC T G TGTCG G A A GCGCGC C T CA ATAGCTCG A TCTTGGACG GA CGCAG CT CCG C AT TCCCC ATACTA A GCATG A AA TT CGCCG GT A TTG CCCC CCG GTCG AC TGA CCT TATA G AACG G G GTG TTGANGTCCCC G T GC T GT CC GTG A A GAAATTCTCOTA GCTTACG ACCTT GCGCGIGGTG GCACCAG GA GACACAACA C GC CCC ACG ACC GCTTTC ATTATA CC ATCG A ACG CACACCGCC ACCCC ATCT CGTCTAG CTATATC CCC G GTCAC TTA ATATGCCI CL CTTT CCAAACAC CGG CCGTTG A G GC A C AC G APCC ATCACTCA CGG A GC TA G GT CTCGCT TCATG GTA AACAGATCTPGGC CG GCATG AAA ATGATG GGCG ATCTCGC GCTAC GCCA GCACCAATATCCACAC CA G GGG G G GCGTG A CC TAA CTA ACGC TGCGP CAAAC GCTTAA ATGGCGTG ACGC GCCGTGCC CATCAAC G A TTGCCCCTC CTCATG CAAC7C CCTACG CTCC A AGTCCG GCC G G GTTTCG G GTCTCTTTG AAGA GACC9GCCA G GTCGCCTCT CAT C ATCTAGA GTGTCC ACCC ACG GC TCAAGTACTG AAG TGG ACA G A G G GC TA C A GCGGCCGCAGGGTAGCTCCAACTAACC TGCC CCTAGCTTGCGCAGTA GCCATACG G GCACCCAGCAGTCCTGCGAGG GTCTC A GGTA GAGT GT TCCG GTCTTCAGTCCC GAGG GATA GGGC CTGTAA CCTA GTC GCGCCGATGTACACTA GTG AGC CTC GTC CC CCCTC GGGC CCCC GCTATGCGA CGGGAGTGGTCG TTTGTACA A AAAACTCTACCCTATATA TCGAACAGC CAGGC TATTATGAGAGCTA CACGTAGC CTCAGCTGCAAGCGCC CAGAATA GCTTG GA TTAA CGCCCGCC G G GGTCCCCCCTCTACCTATCGTTTTGTACA CCA TTCCCTA GCCTC TTC TA ATATTCAC CG ACG CGCAAG GAAGGCTGT G GTT CGGAAAAGATCG GAGC CCGTACGTATTAAAGC CTAACAGA CGAGGC ATAACATCGACCCGA CGAGATCTG AGTG GACTTTGGA ATATGGA AC CACG G GGCGCAGG GGGAGT A CTTCCG GACG GCGCCCATGTA ATTGGGTACTTTAGCCACCGA AGACCGT CAAGC CACTCCG AGTGTATCA GTGCTGTGTTGTG AGATAAAGAGT GACTAAPCGATCAA CAA ATAAC AACCAGGGTGTCA CCGACGACCCGCGCTA ACGC TATCTCGTAC- AG ACG6G GCACATA A AACG GCGTGCGCAGTCG ACCG CTATA CGGCTT CAAA GGCAAACG ACATTG2GGAC0 TTAA AGAA ATCACG TG GTGTGGAG AGGGACCG TAGAAG GGGG GCATAAATAAGGTTTC - AIGCA GCACATC CA AC CAACCTAAATG CC CAGCGC AGGC TTCTGCAAA CCACTAACAG GACCBACAGAGCGA GTGA T GACGCCG ACCTCASAAGAAAACGCACCTG AAAGCGGTGTACA AACG AAAG ATCCGATG GGGAGTCGTCG AGG GCCACG A ATGGCGCGACCTGCGC CCTG ACATAGCGCGAGTBGGGAA G AG GCAGCGGTC CA GG GAGAAGGTAC.AAAG GAGCGGATATGC GTTGCAA GGATAATATOCNTCGTG GATGCGTTT TTGCA ATTACAG AGGGTCGTCAC TGGGCTCGAATA TACCGGAAA ACTA GCA ATCCCG TACCAAACG GCG TCGTGTGGC TCCCGTTTCCGG ATGGCTG TACG TTCTA GTGTTCTE CCCC CGAGTAAACCCCCGCGTGC C CAC C C CGG G A GC CAC CGC CG ACTGCG G A G GCTGCTA ACGCCTTCC TCC C CGCTGGTGTCTCCK C7 8 901112 3 4 5 6 7 8 9 0 1 2 3 4 5 6O1 1 1 1 1 1 1 1 2 2 2 2 2 2 2DA CC TG AA CTACGAACA A AA CGGTA A ATATATGT TG GT C C TTGCC A A G C CCG G A T GT A CCAG C CTTC CC CA TGA A A GAA TCAT T TAT C TCCCGT CTGCGCGCCTG TCG GCTTTTGCC CCG G GCTATG T A GTCCTA AGCG G C A A ATTCGTGA TG GT C CGTA GTTTCCAC TG A G AC CAC TA AATATA GCTCGGC C TCGGCA G GACTA GTAC T CG CTGTTTACG GAGC TC CAGGCGTG GCG TCG GCAGTAC G TT TA A GC CCCCATA A A G G G A GGTCACG CAAG GAATT CGACACCACA G G G G ATTNCGCAGTCTTTGTTATGTAAG AC CC G G G A G G G G AOCIGCTTAC CG ATATA G G GTGCC CGTTCGCC A ATAAGCCAAG CGTAGC A G ACTAC ACC A GATAG ACCAC G G CTCTGGGCI TCGAATCCTCG AAA CCGACGC CGGCACAL C CACCG GCTC CATACTAGCTCCGATTCGTCGGG GGCCTC ATATACACGCTGCG GATTATPPG GAA GCG GTATGGTCGCA TGG ACTC GTAAGAT CGCGTGTA ACCCACACTGGCGCTAA CGAAATAAA G AGATG A AA GCG AC TTTG C GTCTTTTG GCGCATTGAAGGACC GAAG A A ATAGC TAGTC C GTC ATACCGCCPGC GGCTCTTCAGTATATG GCACC C CGACACGC TAA A CTTCCCGACCGCGCA CGT TGTACGGTCAC GAAAGGGTATTCA ATGC TGGCCAA AGA GCAA89TTGGACACGCTGGAGTTGG ATGA G ATCTC C CCGGGCTCGGAA GCACTGAACGG GGTGA GCGTATGTG C G C AGGGGTCT GAGTGCTGTAAGAGCT TTATG GCGTTCAAGGCCGG ATGGAAACG G G TGGC AGC TCCTTC ACTCGATACTGGGC GCGT TCGGA T ACCAG CGTGTTTCCCTG GCGGC CGTTA A AGGCG TAG GC GCCA TAA AGCCACAGCAAC CAG C CGAC GAT TGCA A GAGAGTCC TCTTGGAAATT T TTTC TGTGTGTTACGGGAACCTGA TCGAGATTTG G GCGC CCGGTTTTCGG GT GGGC CTT TTGGTTG GGG G GGGCACC CCGGCTACTC TGGACGTGAGGGGGCGTC TGGATTTGCTTTTTG CGGAG AG CG AAGG TGGTCCGC TA TAGTG C GGGTGTCACGTACTACGGGTA ACAC CGCAGCA C GTA GCAGGC CCA AATCATTTCC CAATCCTACTTGTG GGCG ATGGG GGCCTGGA TTA TAGG TAGA GACTTTC TCTTGGT TG CGGGCTGCACTCAAG GCGGTATG AGA T GC GTA TATTGCA ACCCGTTGTTCTCATCGTG TGGTAAGGTCAC TC TGCTGC CATATGG CTGCAA CTC TCCTG CATTCCCCAACCTTGTTCGCATG CAG ATTACTACCG CACG GGACCCCACATA A AGTA G GCGGGGGCACA ATCGTTACTTCGCGGGGCTGAGGAGTTG GTGATTACTGCG AGGTCACGCA A CTTTGCG AAPG CTGG GGATACGGTTTA GTGTAGTTCTAGATGTCACCACGTGGCC CTATAACCTGG GGCATGT-T CGC6G GAGCGATGCCGGAA2TGGTGCA AGAAAC CTGGG GAGCA ACGGATTAGTGGA AGACT CCTG A0G GC- G AGGGGGACATGTTACG ATCCG GATGA GTCCGAGC TCACGGAA AGGACAATATCIT G CGGTATCBTGGG AACAAG TT CATCAC CACAT GGC AGTGTGC TTGCCAAACCATTAAGAGTCCGAGCAGCTCAGCGGCACTATG GGA CCCGCAG GG CTGGGAASGC TGGCCCAGACGCATAC TCTATGGGCGTGGGAB G. TTA GGGCTGTAAGCACCGGGGAGGGAC CAA CAATACGGTTTA CA CGTGTTGG GACGCGCG CAAG CG GGA TGG GGTCCGCGGTTTGTTAATCGCATCATO A GGACTATGTTTCCCCACAAGGGCAGCGCTA GTN AGTTG TAGTCGTAG CTACCTA TTAACG CAC GTCTTCACTCACCGAG GTCCGTTGTATTGG TGGCTTTEGGCC TGGGCAAATCGTTTAT TTGC T T TCACGTC TACGC TGCCAC C T TATC ATTCTG A GCTCTA AC C CTG G AC CGCCCCCTCG A G ATCCGTTK C728292031 2 3 4 5 6 7 8 9 0 1 2 3 4 5O3 3 3 3 3 3 3 3 3 4 4 4 4 4 4DTATG TTTTTA A A G A A A GTGC T CA G GTA GC TA TTTGT A G C GAC C G A T CTTAA A C TTCTGTAA GGCTATTCCACGC CGCCGCA GCCG GTTGC G CCA TC CTCTTA G TCGCTGTG G GA T G GTG G TT TAA C TCAGACC TG T G CTGC C CTTCG GTGGTTCTG ACG TCCT CCA G G G GCCTCTGCAT TT C AGTAC G TTACTA GCGGG GTA CGCTACAG A GGTG CCG GTATAGTACCGTTATTGCCTCGTTACACG GTCGC TC AGCCCTGAG TC TT ATTACCTTA GT C CCG GCA GGCGTGTTTGC CCC TNOC CACCIG T GTACTCG AA GTTA T G ACGC A CCA G AGGTG A CACG ACCGCCTTGTG A GTCGT GG G A A GCCCGCCCGGCCTGACGTATGCTGA TG GTCCCGA GCACTGIG AA GA AGGAC CCAAGTGTTC CA ACCTGCG A C A GCCTCCACAGTLPCGTACCCTG AAA CCAATC TGCGAGTGGCTCPTTGACG T GTA A G AC TTCGC CCCCCTC CA GACTCTCAG TTTGCCG A GC C TACGCG AC GCTTTA AACCATAAG T GC TTC TGG TTTCCGGCG GTTTGCCTACPACGC CTGTCG GCCGACA A GTTA GTCCTCCT CGCCAGCCC CTTTCTTC C CCC G C GTTAT G TCG CCCC GC CTCC TC T CCG99ACGAATATATCC TCGAGCTAGACCCTGTGCTTC TCC T TGCTGC CCCACGCG G GGCGC TCGTTG GCCCTCC C GGCATGTGG CGCGTTA GC TTGGTGA TAACT C TGA CCGCGGA GACCC AGTACCGGCTG GC TCCGGTCGTACGCC ATGTTGGCT TCTGTGGGTAT GG GCAG TAGC CCCGCTACGTTT TCTCGTGGC TTGCCCTTATGA GTCTTTCT TTGTGGTTTGCGC CC TAACA CCGTA GTTGTCCACATCTGTACCAG GTTC CTC GCTTAC GACTTGT T CC GCT CTGGGCATAGTGAGGTTCAAGTG CTATTCCCTAGC TC TCTTG GCATACCCTTGCTGCTACGCA CAGAA G TGGGCCCG GTC CCCTGTAAAG G GACAGG TT CCGG AGGGCGAG C GGCGTCC CTCCT A GCCCCGTGCGTCGT CCC G CC CAGAG AC GCGC TTGCCCGCACTTA AAAGATGACTAAGC CCATTGCGCA TATGGA C AGCC AAACTCTGCCCTG CAGCGG GTATCC AA ACTCCTCCTT CT GAG GCTCTTG GCTTTCG GCTCCAATACACAG ACCCCGCATGTA GA A C GT GC CCCTGATC TTTGTCCCCTGCTCT TGTG GGTTCGGCCTGCCGCGT TGATTAAGGGCATAACCGC CTTCGCCGGCGCTC CA ACTTGAPGTG AA GACT-CAGCACGG CGG G AATTTTCACTG GTGGCCG AATA AGCCGTC TAAAGGGGG6ATTTTTATA2TCACA G GC GCA TTAGG AATGTA C ACGTC TATGG TCTC TAAAA AGCAC0GCAC- G GCA GATTCACGCCG ACG G GCGCACGCGC GCCTCCIGGTCATTCATG GGTCCCGTGG GBGTTGCTCCGTTAG ATG AACGATTACCCGGTGTT GCC TTAGTCAGGCATGTAAGTTCSGGGCB TGATATT ATTCGCT CGGCGCGA ACATGAATCGG AGAAAACG GCGTCAGCAG ACAACTCGG GCGATC GAAGGCAGAGATGCA. TAGGTCGTAAGC GG GCACGTTATGGCGTTAO GNAGAGGATAGATATCGGTGC ACCCACGGTGTC A GGT CG G AGG GGGATAACGC AGAAATG GTTTGTA GGTG TGATG GGG T GGA CACTCTCG TTCG TTCTCTGTCGTTATCCGTCG GGGCTEGTTCTG AACG GTAG A A A G A ACC ATGCTCGG A G ACCCG ACCCACGCG G GGTGCGTAT AT GTGCCG GGTGAA G A GK C647484940515253 4 5 6 7 8 9 0 1 2 3 4 5 6O5 5 5 5 5 5 5 6 6 6 6 6 6 6DAC A A ATGCACGT CG GTCC G A GT T T C TC C G C T G G A A C TTCCG G G GCCC GGCCG G T G G GTC A G G G GCAGG GCGTACCCTC G GTGTTCGCA G TGC TT GT TGG TTTCTGCG ACGG ATA GCCGT TGC GGTTGCC G T CCCTC T T TAC G GCT CGCAGACCG G T GCGCCGC G G ACC G ACCTG GCG G GACA T AACTCTCG GT ACTCG GTTTA CCC GGTG GTG A GCTG G G GAG GCGCTT CTGGTGCACCATCGNCACGTG GCA GCAOITCGCGCTCG ATATC GCACTGT TTGCCCG G T GC G GCC CG CCTA GCCA ATCGA TCCGTIA GC C CLCGCCC TGACC AT TTAT CCGTC CG GCG GCCCG G GCGCAACPCGCG GCGA CCCA CCTCG ATGGTGCGPCC GTG G G A GTT TGCCTCTACC GCCA ACG A A G GCTAC G G GCC C TG A GGGTTA C GGCTGCGTG GGCGCAG GACACGCATCCCC GCCTACG A G GGG GCAG CC GCPCCG CGAT T CAGGATGCCCGTATGAGT0CTCA C CCCCCG GC TCG TAC TT CCA GCGGCCCCGCTGTGCGT0T G A TTC1GCCCT T TGC CCC CGAGAGCGTA G ACCG CTACG GCCG CG GCACT GCGGGCCGGAC CGTG CGTCTA A GTCCGC CGCCCA CG CTACA GAGT CCG GCGCG GGAGCG A AT T CGTATGAACCCTG AGCG C CAA GCAC C TGCCCCTGATG GCGCC T CTA GACCCCA GGCCGCGCGGTGGG TG G AC CCAAGGTCG GTGCCA TGCCC A TTAGTCCG GCGTA CA G GTCGG CGCAACGGC CGCTCGCGGCTGGCAT GCC CG ATTTCA CCG GCGA A CCTA GAGCGA GTCGCTGCCC CAACTGGGATA A TCTCA CTTACG ACCGCGG A AATGCG A AC CCGCGGG G GGCG GGGCGTGTACTCTCCTACACGTGCCC GA GC TG ATCC G ACCGTC GGGAGGGTG GG GGGGA TGC GGTATTC ATGCTCG G GCACG A ACGGAGTTCTGGCCGGACGGC TC GTC TG GTGC CCGAGAGGATTT CCCCCATGCGTGG G G ACTCGAGTTAG GTGCG GACA GTAGCCCCCGG AGCACGTGTCGAAACCAGGPGTGTAGCCGTGTACG ATC GCTGCGCCTG ATCG GGG ACAGCC-TTA G G A ATG6GGA GC TCACGTG G GGGGCTG T GGA GGC CCTGTT CCTTACCCCC20GTG G GCCCCTG CGGGA TAGGCCACTCGTCGA TGG CT TGA ATGACAG- GTCTG A ATG GCAGTCCCGGG T G A GCGCGG GG ACC GCCAA AA AGGTTGCITCACC GGCGGG ACGACACA GGCCGGBCCGTC TGTG A GAGGCATTGTGTGTGSGG GCGCG A AAATTGC CGATTTATGB G. TAGGGOGCA TGCT GTGAGCGAGG GCAACCGATGGCTGGC GTGG AGTGA G TCGCCG ACGAA A AAG TATGCGACG ATCNTGCGCTTGCCGTGGCGG A GGGCTGCAGTCGTGC TG GAATTGTTGG GGTTCTGATAGCCTCCAAGG AA GCGTTATCCATGCCTCTGCTG ACATAGTTTCGGCETCTCCCC AAC A G GTGCCTG A GCG G ACC A G GC TTAT TCCCG AT TATGA C G C GTAGTGK C768696071727374757677 8 9 0 1 2 3 4 5 6 7O7 7 7 8 8 8 8 8 8 8 8DATA GTATG GC TA GC T TAT TCTCC TT TG TT A G G GT CG GTG T GCTA GTG AC GCCT CGAC GT GCAGTGTAC CC G GCA GCA CCC TC ACA GCTT ACCA A ATACG G GCAGTG GGTC A CTG G A T A ACC G TC AC TG AACTCGC C CCCTTAC G GCC C C CC G GT TTCTTGAGCG GCTCC G G GGG GTTGTTC GA CG G TGCAG CT CA GGCGC T TC G GCC TGGCGAGTG G GTATACT CT CGCCTC GT C CGTCTAG G C G GGC G G GCT GCT CATTTANAG G ATCGTACG GCAACCGCTCGCTG GCCOT TCCG GCT CGTAITTTCGCGTCTCGCGGTG ATCG A G GAG A GAG GACGT AA C A G AC ACAATAACG G A A T GCC G A AG G CT TCAAG C A CTGTAI AG A GTA TT CGCTGC T C TACGGG G G GTACC GGCTCT CA GC CCTACTTG AACGCL TP T CGCA TTTCGG G G G G GCG G G AAG G GCGCP T CG G GCGA C CCAC TTGTG G GA GTG ACAATG AGTAC C CAACCCCC AG G G GC TCAG TCTATCGC CACC G A G G GC CTAC G A GTGC T T CCPTTTAG GTCGTA GGG GCCACCTTG AGTA ATACCTTGTG A GGT TTT GT TTATG A A GCCAT1T CC CGG G GAGTA TG GC CGTG G G A G G GACGC01A T GGG GC TG G GCTGCG G G ATCCCG A T GATA GCAGGTTTC G G G GTACGA GTG GCAGCATCACAGT TAGCA C CCA GA GGGCA G ATGTACAT CGC CC GGTTG G GTT CG G G GCA A G GCATTAATACACCA T A GG GC CCTTGACGG GCG GG GGG GTGCGTTAGG G A AC TTGGT CGCCTCGTG AGTTTGA G GGTAG G G GCG CGGTA GCGCCGTGCAGTC AAA AGG ACGCGTGTG ACAG C GGCG GCGCGCG G GT TGT TGGCG GTG GTATGC CGC T TGATA AC TGATGACG GGCC A GGA GGT AGAGT TGTCTGAAGCTACTCGTG GGCG GGA ACCGCTAGGTGGAGGATATCG ACTC TGGTAAA ACC AGCATGCGGCGCGGCC GTTGTGCGTCGTG GT CAA G GTC T TCTACC CCAAAGACCG TGTG CCGTG GTCAACAGTCC GGAGGCAGGCC C CA CCACGCA ATA GTAT ATCGAGACACGCTG GGG GTCCTGGCCG GCG ATAGTGA T GGCGTACGTCCG GTA GC CCGTGCTGGCG GG GC GGCGCCTGTGCCCC TT TGAGC AC C TCGGTAGGCCGCACAAGGC CCGP- GGCGCAGGCG A GACA G G G GCCGACTGCAGG GTGGTGCG G GGTGGATGGGCTGCACG6 TG2 GTACGTAAA0 TGGGCGAA TCG GACGA CACGAAGATCGGTGGTTCTGTTCCCATCAGTG- TAGGTG GGGCAGGCCCG A G CCTACG ATAGCCGAAGCCCACGGCGG CTCCCCA CGTCTTCGC TCCGCCCG GAGACTCCA GTCI CACCGCCAA ACC CGCATGGGC GG CCGACBSCTG GACAAGTG GAA ACAC TACG CAGATTA G AACCGG AGGGC TAGTG GATCAG GTCCCB ATAGCCG ACCCGAG GTAGACTCGCCGACATG GGATCA GGAAGG TCGA CGCATGTC T.GCGA O AGAGGT CAGGGGGAACGTC TGCA AG AGGN GGTGGTA CTGAGC TGAGGGCGT TCG CGCAACGGA GGTTTGACGTCG ATGTGTG GGGTA ATGTATCG A AGC TAATTGGTATCGTTTGGG GC TGAACGTGC CCCG GCACCACCCTCCCATCGCGGCAGCGTCTGGGCCATCGEACCCTA A A GCCCTG ATATCC GCCCG G GCCCCCTGCA ATTG GTGCCTTGTCCGTGA A ACCGTCGGTACK C8 9 0 1 2 3 4 5 6 7 80 1 2 3 4 5 6O8 8 9 9 9 9 9 9 9 9 99901010101010101DTGTG A A AC T TG AT TG A GCTC GTC C C C G C TA TG CTGCAA ATACT CGTTT TG TT T ACC A A CCGCGC TAGCA GGA C GCACAT TATG T TTCGATC CGCA AGTTC G CA CGT CTATA TTA GTCCGATGCACA A GC CCCC G AAA ATGGG A GCACCTATG A GTTC GATATG A A ATTCA GTT TT CCA GTTGTATA ATA CCA C GG A CCCTTG GTAGACC TCCGTA AT ACG AC CCC GTTA AGTTTCGCT GCGA TT T TCCGT TTGGG A A AT TTC C TAT T C TATCC TANCGG AAT CACG AGTCO GI T CCT AATGT T TA CCA A A AGTCC TATCATATT TTATA ATTT TGTA AGAAT TTATCG TA CGCG GG CGTCAAGCCAAATACAACAC C T CA A CCACCTATTTG GTAAATCG TTG ACACILAAP GGCT CTGTTCTC ATTT T C TA A ACGATGA ATATTT AC AAG GCTA ACCTAA A ATATTPCC TACAGCAC GTATT T ATGTCTTT CGTC GTGAATT GG AT C TAGTTTTTACTG TAT CTGCG TCG CCCAT CAC GT CGGGTA A GCTTTTGTCC TAT T CTTG A GTA GCAC C TTCTTATPGGCGTCGA TG ATGGC CCC CA ATTTACA ATTTA T GG A CTCTTA GTT C CACA C GTGGT20AATGCG C A GAATACCTGT TACCCTCCTTTGTGCGGG GT CA1ACG GAA ACTTCGTT AGGG G G ATCCATG GCCAT CGA A GAATT CC CGTCGTCAA CTTCCCGGTA A A A AACA TTTAATC TAA GCTGTGACGCGTAA GTATT ATTTGC CC CG GTACAT TG GTGTGTCTTACATC CTGGCAA ACTTGTA G G GC CGCG A CAAGTATGGCAACAC AC G ATC A GG ACGAA GCAA AATTAGGCGCTTTTTGG ATACCAG CTA G ACT TTTG A GTTCCTTTTT TGGTCACGATAA G GG G GCTA A G GC TTAGT ATCCTGCTAA ATA TA A G TGG GCCGCGC GT CA GC TTTC CA AT TG A AACTG ACATGTTGTCGGCCGTTGTTTA GAG T AG CTTATA A GG ATTGGATATT ATAATGCGTTTTGCCTTAGTGTGAACTTTGTA ACACTGGAGGTCCAC TATGTGTAC CA A AGAC AG AGACGCTAATAGGG ATGGGTAC T CA TA AA CGCA ACAAATCATG CGTA ATCATAACA AG GGCTG GATCTTGGTC T CCGCTAGCGCCAAGAGCGCGCG TAATTAATGAT TTGA ACCACTACGAGAGC TCGCTGAGAGTGAT T CGA AACCTATATTATAATGCGCGATTAA AATGGTP- GA6AGGTA GCCG CG GG2TTTA AAACCAA0AGTTG TAG G CACCAGCAG A ATTACTTGTA GGTAA- ACG GTA AGGCCCGTACAATTCCCTC CCATTA A A AGGATGTATA A A G GTC AA GCAIGGTABACG G AG A GGTCG GGCA AATTACG GA ATC AC TTTT AG TACGCGTTA ACGTA G GCTSGGG AAAGGTACAATG ATCATTAA CACCA CGAGTGA GATC A AAACCA A GG ACCBGCG A G GTGCGTACGCGTATTTGATTTCGTTATATATTGATTATAC TGA GTAGTATAT.GOTATGAGTCAG GGNGTG ACA TCTATTGTGTCCA TATGCATCCCGA TA AGA AAAACCATATATATG GTTG G CTGGGAGTGA TAAAGATA GG TTCTGAAAA A TG GTCTTAGTATTTTTTCCCCCACCTCACGGG AGAC TGACCTTTGTCTTCA ATCA GTCTCCG GTTGG GCCA A AECTCTGCCTTTG A A A ATTA ACAGTGTCTCC G A ATTCTAC G AATG GAC ACG ATTK C7080900111213141516171819 0 1 2 3 4 5 6O1 1 1 1 1 1 1 1 1 1 1 11121212121212121DCG GTGT C TACA G A GC CGT TT CTCCCG GGG G C GCTTTC A G C A C G GTTAGA G GTA A GATAA A TGCTCG G G G GCACGTC CCG ACT TACG ATGG ACTCG G GTGGCTCG T GCCA G G A CGG T GT CCTTCC GTG A C G TAA CGCGTA A GTCG GCAG GTCCCCGCG CACC CCG CTGCTCACCC G G A AACG G GCCCCG AGCG ATG AATCC GTTATCCGCC CA GCAT CA GCGGG ACGCGTC AC CA GCG A G A G GGCCCGTG TT CCAGCTTAA TCAC CGC CTG GTCAGT CGCAACCCGNAOC TC GCTGCATCT C CCC G GATGCA CT CTAGCICCGTCC GGGG G G G GCATG TCGCA GTG AATCG CCCAGCGTG TC TCTG G GTG GTCACGCCGTCGA C CACCTGCA T GGA G C A A AAG GTCG G ACGCGGCIG ACCCGTGCGT CGACA G GCG GGTT GTGTA GLG GCPPGTAACAG GCA GCTTCCGACTCCG CGGTT CGGATGCCGCAA TCCG G GTTTACAC CC TGTC AAC ATCTT CCAGCCGCTCTT CTACA A GCCC GACACACCC CCC C TGTCCG G G G A GA GCG CCG GGTCC TCPC ATCTCATTTG TTCG GGGCT TG CG GACG GGTCGCGTCT TTGCA GTG G G G GTCG G G GC TT GCGT 3CAC TCTC GTGTTGCG G G GC CAG GGC A AA 0CATTCG G AAA A C A A G G T G GGACG G G GC 1GCGACCTTGTG GC CA A GCTCTTGCA G ATC G ATTCATCTAAACCA GGATC GGCG GGGCGGCA A GCC A ACTTAC CAAACTG ATGC C TGCGCTTA GC CGTGCGCAGCG CCTTC CC A A A G GCCG GC TG AGGG GGTTTTCGACACGTGCG G GTCG GCCC CG G G ACGTGGCCCGTCCTAACGAAGCG G GCTGA AC GCCGCCAGAGCCATCCGCTGGCGTATGCGCCGTGATGG G TTG GAGCCGCGACTG GCT T CA A G G GCC ACTCGAGGGTCCGGAACTACAGCAATCG A G ACC GGGGCC CCATAGACC GTTACGGCGCCGC CGA T AGAAGCAGTAAC CA GTA G G AGGCG G G G G GA T C GGCCG T GATTCCG CCAG CAGTT GCGC T TGTGCGGTGGTTGCGACG ATGG GACGTGGCG GCAG C GCGCGAC CCGCTGTGAGCGTGG GTCCAGA GG G GCG TAGCTGGTACA GTC AA AAGC TGGGTA AG G G TTCCGAGCCGGCCGCAC CCAGTGGTTG G GA G GTTTG A GCTCAGCA ATCTGAG GACCAGGGGC GTA G A GGCG GGCGCGTG AGCCG AGGAGCGAG ACTAGAA GGAAAGG GGATAACG GTGGCG GGGGAGGCGAGTCC GAGGTGACTA GCGGATACG ACGCCCA AGG GAG AA G AAAGA GGACGTCATT GAGCGCGTAC CAA GCGGCCCG GCG A GACCCACG ACTP- AGGG6G GCGAGGG GTGA GG GC TGCATG G ATGACAGTT2GAAAC TGGTGGCGGTA ACGACAAAC TCAG A ACGTACA GCCGGGGTGTCCA AG GGTTCG TGACTGC GCACGCCTTGCAAGTCCCCG TGG0-IATTCTGAACCCC CCCTTCTCGA G G GA GACG GGGGG TTACGCG GGTGGGAG GGACGCBGCGGGC TGTG GSGCCGGTGTTAGA ACCGTGTG TATG ACA CGAAGGGGTGAATG GGAG CACCGAACCGTAC ACTCCGG GACAACCC CGGTC CGGCTGTGABAGT.GGGOTAGG G A GAGGG GA GATAATGGCGCGGC TCGCGGCTGCGAACGTAACCGAGCGGTGCGT GGGCAGGAGCTAC TGCA AG GCTCTCG GCGGNGTCCATCGTTGC TG GGGACTTGGCGCCTCGGTTGGGCG CGCGCA GTCCGCCCCCG GGCGTCCGATCCG GTG GTCTCCTCCCGGGGATAGTG GCC CTGG ACAGCACG TGCTCTCCG AATGGATCGTECCATG G G ACTA GGTGTAAC GCTGC ACTCC A G AACCGCGCACA G GCCCCG ACCCCCG G GGTA GCTACK C72829203132333435 6 7 8 9 0 1 2 3 4 5O1 1 1 1 1 1 1 13131313131414141414141DC TA G GCAC TA GTG G G G G G G G GA TA T GCT A C T G G AC CGCG TT TTA G GTACCG G ACGTAC AG A GCCC TTCAC TGCTA CTC A A CCAC ATC AGT CCACA A G CT TA GCT A ACACCGCA CC G GTAC CG C GTCGGG ATATTGC C AGTAC CCGT CGTGTCCCG A C GAGTACACGCATC G ATATCCA A ACGGTG ACTCGTTCACT C TGCTTCA A G GAG CG GG C TTA CG G A ACTA C G A A ATGCA G T GAT TG A CCCCT CGTG G GGT TACCCTCGACCTGCATG GCCTA GCGTCCG ACGN GA T C T GG GTTAA GGOIGC CGCTGCCATACTCATGCTG ACTA ATACACG TTC AAA C AC C CG CCGCTA A G G ATG A G ATAG ATA CA AGTACACATGACCC GGTACTCACICCAC CC GTCC GCCGCT A A G G A ACG G GACG GATG GCA AA AG ACG AL CAGCT T CG GCT CAGPACPGC CTGCG G CAAC T AC G AATG GC GTAA GCGAACGTT CTCAC C TG ACGCTA GG GCACA GGCTG TCG G ACG A GAAT TA G AATAG A GG ACCCACTG G GTPGG C ACTACCCG G G GGCGTATG A GCCGTT ACC TTT TATTCG GCGTG GTG A GCG A4GCTG GTCCTAATCGTATGGCGCG ACGCC0GCG GC CTCTTGCG GCGTAG G GC A AT CCGA1GAACG G AT CGCCTGTGCG AGGTTCACACGG G GGAC TAGT CA GTGG GTGA GGTGACGCTTAGG AT CG C GCACTGT CCTGAACC GCGC T CCGCG ACGT TTTA ATTG A GGAC CCTGGTTCCGCG GCT G G GCCACAAGCG A A GCTGACGCAA G CTCATC GCTC TCGTGTAGA ATGC CTGTTCTCC CAA GT TACACATTG C G GG GATG GAGATACCCGCG TCCC GATATCG GGAAGC G GTTGCGCTCA TCA GACCCA CT TGTCTCG GCTTTATAACCGGG ATCCTTATAGACAGTTTATTACAG GTCCGCG G GCTGCGCGAG GCAGTTTTATG AATTCG GCGGCGGGTA C GC GA AGAACTGCGTTGTC TGCGTG G GC TA CTCGTGGAGAG GCGTA G GCA GTAGAAC CC CGTACATAA G GACGGGTTAACCGCCCCATTGCG G ACGC TTGATGTATTATTGCGAG GATA CGAAC CCACG CGTTCCCTATGCCG CTC CCAGACAATGGG G GTTT TAG GCATAC CGAC CGTTGGG ACGTCTCATAGCG GCCTGTATTACACCGCGGGACC TGC CATCTG GTG TGTCA AAGCACG AA GCG A ACTACGTCGACGCCCTCCPGCG G GGCG AG A GG GTT-TTT TTTG AATTAAG GGG GCG C GAACGTGGCTGCGTGGACTCT6AA CCT2G0TC CACTG CTGTCCCGATTTCGC CCGTA CGTGGGTTG GTACGGTGGCGCTAGG AGCTCTG -TCAAACAC G GGGAGCTAATGGATCTGTGG GGTCCACCCGCA ACAGCTGAAC G GGTCTACACTTCTGCTCTTAAGGCCCTGGICGACGCGCGAAGCTG AA GACTGTAGCCGTBTSGTA GTA CAAA CGCA GGTAAATAAA CAGA GACAAG GGCATACCCCAGGCACGAAGCCACGBTA.GTGAGC CGGCGTGGGGO ATCATCAC TGTTG CTGAAGGACCGT GCTTCAA TCG ATCA ATGGTACTC GCGCGTTGGCTGAN GTGATCCGTCT TAG ACG TA ATCG ACG AATGCGGCCAGG TAGAGCCGCA GGTATTA GCTCGTGGTCCCTCCG GCCGATA AGTGG GACGGCTAA GCG GGAATGGTTCCCTCACGGGTT GCTCTGCG AG ATTGAACAT GCC TG GCCCTCCGCCGATCCTACGEGC GCTA A A GCTGCGC G A GACGTA A A GCCCTG G A A GTACGCCAA G ACGCCCGGA G A G GK C64748494051525354555657 8 9 0 1 2 3 4 5O1 1 1 1 1 1 1 1 1 1 1515151616161616161DATA GCATA GTGTATGCATG A C C CTT T T CC CCC CACTGT TA C C A G A T G A GC CTC T GACACAAA GTG G G A G A GC CCCTCCTGATGTGGCGGCG CCCCT TTTGTG GCA GTTCGCCTT TATAG TCAGG ATC AT ACGA G ATG GTGC C CA CT CATGCA T C T A CTCCC GTTC A A ATG AACGC T TCCT C C CGCTC C T GTGCC G GTGGAT CA A A AAG GCCG GTCGCGTC A ATTATGC TTTCCAA TCNACT TGTA TTT TG GTTACGGTG GCCGOC C CCTCC TA G A GICTA C G GTCTATCC C TTCCC TTGTAT TGTA ACCCGA CT CTATCT CT TG AGTA GCTG A GC AA GCA GGC GCGC TA AC CATG GCATGCCTC GTC ACI AC CL CACG ATG AATGTGCA GCA C G G TP C ACCCGG A A G G G A G A A G A ACGCGT CP CG CTA A G GT TG GATGC G AC GAC ACCACC CTC C C T TGTA G ACGTACG G G GTTCCCCCCATTCT TC GCA CCTACGT CGCCPAACCGG A G ACTG A GCGTAC TTGTCCGC GTCTATGTT T CT CG GAC CGC CT 50G A CAT T TA G G G ATAGTTTCGTCCC 1T TTCGCC A G AA TCG A A AACGTG AACG GC TAAGC CGCCGG AT TG AC CTC TGCTAT CCCTTTGTTC CG C GCTG GTGCGCGCCA GT CA A ATACGCCAATG GTG G A CGGGTTATGTCG ATTT CGCA A GATACTG A C CCCG GTGT TAATTA CCA C GG GTG A ATAC CCTA CCG A G G G GG CA AC T CG G G A A A G CAACT CTTA A GCCTTCG G AG AACG T ACCAC CTATTCGG GGG A TTCCTTT TG TTTATGGG GTGAT T CCT C CG A C ACGGG CCCGCAC T C TTTA TGGA GACTGTG ATAGA GTA ACTTCGCGCGG G A GTG GAG GTTA CGG GTTTC TCTC T TACA A CAAAG ACA A ACGT ACG G ATAT CG GGGATGTGTTCATGTC TCCA G GCGC CAGGTACGGG A TCTCGTGTA ACG AACAATAACGTTG TCCGTG AAT T CG G GG GCA GGAACGCGTACCCTCAATT T CGTGTCA ATGGG ATGTCGTCGCATPGCGCTA A ATATG TATTGGTCGCTCA GCGGTACG GCCTAACGTCA - GTTGCGG G A GTGA GCT CCAG CACCGGTA TC CGGCTGGGCAGCCGGTTG CG6AAG20ACCTG CA GCG AGTTATG -C TG ACGCA G AC CTATCGTATACG G GAGCG AG AIGACCAATG A G GCACGTTTA ATCTTG GACG ACA G ACGA GCGTCCCGTCCACBGGAGG ACAC TTTTCTA GC GCTGGA AATGCTATTGTCGCG CGCCGCGCTGGSGTACA GCCG G GGTGTTAAAACGGTACGTA CACCA GG ACA GGTTTTTTGTTTAB.GCTGTTG GGACCAA GGGTATTCGA AGGC CCTA G AACG GC CCGTCGCGATCOACCCG AGGTTGCCATCAAATTCGTCGGTTCGTCA GATT CCCGATATCTC CCCNA TTAAGCCGGCTG GTATCA TTGCCTG GGGGCCGATG TTCGAGGC CTCGTACTE CAATCGTTCAG A ATTCCG G AAA CATGA AACTCG TGATCTATCGATG GCG TGTATGCTCCTGCCA GCTCTACCGCAGTCCCACACCTCGTCCT CK C6676869607172737475767778797081 2 3 4 5O1 1 1 1 1 1 1 1 1 1 1 1 1 1 18181818181DGTGT TG GT T TGCGACT CA GTAT TG A G A C G C C C T C G G GA CCGG AT C GTCGGACTGT CT TTC ACACA G GTATG GTCCC G GC CACGCCC G G G GG CACGTGACC CGCACGCGCTA GTACAA AACT TCACCCG C A A GTCGGTTTCACCCA AAA GTG A CC CGTGC CACG CT T CTTTG AC T TCCCGC C TC A GAACT TGCACTG C GCTTCCACCGCCTA A AAC ANOIAG CGC GCTCA CTCG CCG A G G G GCG ACCTG G A AACA ACCG GTA CCC TGC CCG CC C GC CCCGCGCGT CCC C CGCACCA A GTCCGTILGCG C TACGGCP TC GT CGCCGG GTPGC TGT CA GC TA GTG GC CG GCAT CCT C CC CTA GGC CCGGCACCA C A ATCGTCGC CCT TG G TCGGCPGTTCACTCCC TCG GCCC GTG GTGAGCCAC CGCGCCG G ACG C6GTTTG G G ACC A G G G G G G ACTGAAC T01G G GGTCG ATG GCATCG A A GCAAT GCGT ATTCG G GCTCC TG ACCGCT CGCTGGTG G ACCGA GC CACACGGCGGGCAATGCCTCGT GGTAG GGT TCAGAGTCC C GT C TCTGTCG A G A GGCGGCCGCG A GCCATGACCGGGACGTTCTG TGCTCACG ACG GTATTGTCAC CTCTGATCCTATCGTCGCCA G G GTATGGGCG GTACGCGCCCA G C G ACCCTGGG GGTGCGAGCGCG T G G GTCG A A GGCCTG G G TAG TTTG GTATGG GGGGGGTTTCGCGG GACTC ACACGTTTTGTGTGT TCCTCTGTGGCCA GGCT GCTGG GTGCCTCCCGTGTCAGCGTCG G A ACTTG GGATG ACGTGATCA GCCAGCATCG G GGGAACCG CCT CG G G GTCCCGCG ACGCCCGT CCCCPGCTGCACAC CGC-T CGTTCG G A A TGCA G GCGACAAGCAA C AG6GCG2GCGCAGG G AACGGTGTAAGGG AGCGTGTG CAA GCG ATG0- GCCACTTCG A A GAGTIAGCCCACA GGA GAGCAAAGATAA G AGBAGGCSAGGCG GTACA ATGTAAGCTAGGTGCTGAACGCTC A GAGATCGGTAACCAGCTGGGAAAAC AAGGTCC TCGCT CCAT CB.GCCGGG G GGGCGCCTAG AGGAGC GTGGACGTCGTATGCC G CCO GGNGCATGCGTACGAGCGCACCGACTCTGGGGTGCGGTATG GCGGTGCGCA CGAGTA GAT CGCGCGGTTGCTCGGT TGT TATC CCGT T GE CATGTCCGTCCTCCCCCTGCCCGTCTCACACGCCAGC C TGCCCTGC GACCTGGTTC G GCGCCCTCTGTTCCTCCCGCTGCTCTGCGTG GGC A G GTG ACGK C68788 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7O1 18181919191919191919191910202020202020202DTTC A GTC A GTCATACTC A GTC A GTCTC A A A G G GTGTACTGTA G GCTTCACACCNOITACILPPATCP 701TCP-620-I CGBSTCBG.TOCNGTTCEGT CGCGC T C CGCGC CG G G G ACG G GT C C C TK C809001112 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5O2 2 2 2121212121212121222222222222222222222323232323232DATTCTAACTGTC A GTGTGTCATA GATA A G GACATTCTCACACTC A A G GAT TGATAC NOITACILPPATCP 801TCP-620-IBSB.ONTE T CACGCG G GC TGTG GC T C C C C CG GTGT CK C6373839304142 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3O2 2 2 2 2 242424242424242425252525252525252525262626262DTCTGTA GA A A A A TTTTATATA T AA ACTA GT C C T C CGCGCG G GC C CG GCAT TG G NOITACILPPATCP 901CTT CCCCP- T6 C2 C0-CIABCSCBCG.TONC CTG GTTTEG ACCG G GT C C T C CGCGCG G GC C CG GTC ACTCTG GK C4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1O62626262626272727272727272727272828282828282828282829292DACATTCTTC A GTA ATAAC ATACAC T C TAC C TA GCNOITACILPPATCP 011TCP-62G0A -ICBTSABT.TTO ANA ATCE C T CTT CG G GCA GCGCGTGT CACCGTA A GC TK C29394959697989990 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9O2 2 2 2 2 2 2 20303030303030303030313131313131313131313DG A GTTC ATAT TA ATA A A ATG AT TATATGTC A A NOITACILPPATCP 111TCP-620-IBSB.O ANGTAE TG A GCG GCAT CGTA G G G G GT C C CACAC TGK C02122232425262728292031 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7O3 3 3 3 3 3 3 3 3 3 33333333333333333334343434343434343DG AT C T C TA AAT T CA AT T TG G A GT T C TG GCATG NOITACILPPATCP 211TCP-620-IBSB.ONTE TGCACACT TA GTGTGC CGC T CGTAC C TGCA G GK C84940515253545556575859 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5O3 3 3 3 3 3 3 3 3 3 35363636363636363636363737373737373DTAC T T TA ATCTGCATAA A CTA A AC CACT TG GCTCTGTGCNOITACILPPATCP 311TCP-620-IBSB.ONTTTTETA CCGCC GC CGT TG A GCG ACG AT CA G GCTCCG G AK C67778797081828384 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3O3 3 3 3 3 3 3 38383838383839393939393939393939304040404DA ACA GTACATG G G ATAAGCAC A A ACA G G A GT C CGCT CG G NOITACILPPATCP 411TCP-620-IBSGBA.COTNG GTEGT C TA T G G ACACC A G ACG G GTA GCG GC CG A GTGTK C405060708090011 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1O4 4 4 4 4 4 4141414141414141414242424242424242424243434DCA GCG G G A A AT CAT TA GCATATGCT C T C TA A GTAAC NOITACILPPATCP 511TCP-6T20 C- AIABCSTBC.GOCAN CTCE TG GCGTGT TG GTTCCTC G ATA G G G G AC T T TA A G A ACK C2333435363738 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9O4 4 4 4 4 434344444444444444444444454545454545454545454DA A CCACC TAC TTCTC ATGT TG A GATTCTATA A G A G GACC TNOITACILPPATCP 611TCP-620-IBSB.ONTETAAC AACT CA G G GC CGCG G GT C C T TGCGTATGCTC AK C06162636465666768 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7O4 4 4 4 4 4 4 46464747474747474747474748484848484848484DA AG ACTGTA G GT T TA A A G A GCA A AC T C C CA AG G G A G GTCC TGTNOITACILPPATCP 711TCP-620-IBSB.ONGTATEGT C CATAC ACACCACT T TG G GTT TAAG G G G GTGCACCG GK C8898091929394 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5O4 4 4 4 4 494949494949405050505050505050505151515151515DTA AT T TTCAC TG ATG AC CAC A A G G ATA G G G GC CA A A ATAC G NOITACILPPATCP 811TCP-620-IBS CB T. COANTGT AEA G G AGT CG G A GT T CTC G G G GGCT CG G GCAGT CGK C617181910212223 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3O5 5 5 5 5 5 5252525252525253535353535353535353545454545DCCACGT TA A GT TA A A G A A AC TG G G G ATATC GC C C C T CG GTCTG NOITACILPPATCP 911TCP-620-IBSB.ONTEG ACGTCTATG G G GTGTATT C CGACACTCTC GTG GCGK C445464748494051 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1O5 5 5 5 5 5 5555555555555555555656565656565656565657575DTGTTC CATC C CA G GTTGAT TG GCGC CA A G AT TGTAGC NOITACILPPATCP 021TCP-620-IBSB.OANTE TA ATTG GGT CGC C C TTTA G GT CGTCGCTAT TA G A A AC CGT T CK C273747576777879 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9O5 5 5 5 5 5 5758585858585858585858595959595959595959595DTC TA AA A A A ATGTA A G AT CG AT CA ATG G G G G G A G G G A NOITACILPPATCP 121TCP-620-IBSB.O ANACTA AGECTGT CA GCGT C TG GT C T TG G ATG G G GCGCG G ATG GG G AK C001020304050607 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7O6 6 6 6 6 6 6060606161616161616161616162626262626262626DCG A C G ACACT TA G ATATTTTCC T TA G ATGCATA GCA A G G A ATC A ATG G ATTCT C TNOITACILPPATCP 221TCP-620-IBSB.ONTEG ACGCG G G GCACA G A ACA GCGTG G GC CTC GK C8292031323334 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5O6 6 6 6 6 636363636363646464646464646464646565656565656DA T A ATTCCA A G GTA A A A G ATGTGT C C CATCT TA NOITACILPPATCP 321CG G C G A C C C G A C C C A T CTCCCPA -6A2 C0 C-ICBCASCBC.G OANCCTCAE C C TGTG GCTG G GTGCA A A G GT C C CGCAACT T CCTA GK C657 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3O6565656666666666666666666667676767676767676767686868686DT T T C TA G AC TA A G ACGC TGGCCA GCG A AC TG G GAC GTNOITACILPPATCP 421TCP-620-IBSB.ONTE CGTACT CCT TAT TG GAC ATC GCC GCAC GTACC CG A GC TGK C48586878889809192 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1O6 6 6 6 6 6 6 69696969696969696070707070707070707071717DGTCTCT CGTG ATA ATATTTTCCTA G A A G ACA ACATAC CNOITACILPPATCP 521TCP-620-IBSB.ONATG G AEACA GTAT C CATGCGT T CGT TG AAC A AAC ACTA AGCTCK C213141516171819 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9O7 7 7 7 7 7 7172727272727272727272737373737373737373737DC TA AT C T T T C T CAC GCG GCA A ATT TA A A AAC A ATCC NOITACILPPATCP 621TCP-620-IBS TBA.GOANTATTEAC CA GGTG CCTAATACATGTATTCGTTCC TGACCA G GGC G ACG A ATGTA ACAGT CK C0414243 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7O7 7 747474747474747575757575757575757576767676767676767DG A A GTG G A GC T CTTGCT TG GCAT T T CGTGTGTTTTTGCNOITACILPPATCP 721TCGPA -6G2C0G-ICBCSCCBG.TOCNG ATE CGGT CGCG A GGCGTGCT CGCTCTGT GCC CAGTGTGTG GGT T CGG CTT T TGACK C869 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5O7677777777777777777777787878787878787878787979797979797DCTACCT CGCC CACCTA A G G A A AT TG GCA A G GCCT C T C CA NOITACILPPATCP 821TCP-620-IBSB.ON TTT TE T TA GTTTTCCACTC AACTA G G A ATAGTGTA G GTCCATACA G GCCTACGTGC AK C697989990 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3O7 7 7 7080808080808080808081818181818181818181828282828DAC ACA G G A TTGCCA AAC A A G G A GGTTTA A A ACG A A GTTTTTTA A A ATA A A ACA NOITACILPPATCP 921TCP-620-IBSB.ONTE T CAC AC CGTG ATATGT TA A GT C CAT T TGCG A A ACCTAK C42526272829 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1O8 8 8 8 82838383838383838383838484848484848484848485858DCA A G ATT TA A A GT CGT TA A A GTGCTTACC T T CTTAC TNOITACILPPATCP 031TCP-6G2C0G-IAA CBC CSC CBT T.A COTN ACTGTEG A A A ATG AT TGT CGT TA A ACGT TGGCCAG C A C A GGTCT CTCGTGTACT TATCATK C2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9O58585858585858586868686868686868686878787878787878787878DTCTTTC A G ATGTT T CG G GT TATTC A ATCC TGCG GCG GCC G NOITACILPPATCP 131TCP-T62A0A -IABTGSABA.TOC CNA GCTTTET GCT C CAGTGTGA TC AC GCGGA TG CTTG G A AGT CACACGTA GGCCCGCG GTAGC CGK C0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7O88888888888888888888989898989898989898980909090909090909DCCC T T TG AG TA CTTA A GC T TATA ATAC C CGTG A GC C T CNOITACILPPATCP 231TAC GP-C6G2G0G-I TB GTSCBC.CONT T CA G G GCC GCECCTG TGCAGTA TGTACACGC TCT CA G ATTATAT CATCTA CTCCAAGTG ATGTCGTCCTCCK C8090011121314151617181910212223242526272829203132333435O9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 939DTTTTT T C CA A A A AC TTCTA A A GT CATAC CGT C T TA A NOITACILPPATCP 331TCP-620-IBSB.OTNA TTECT T TGTACTC GT TG G CT C TA G A A A AC A CGCTAC ACTAACACCGGTACGTCTG A AK C637383930 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3O9 9 9 9494949494949494949495959595959595959595969696969DA G A A G A AC C TG G T A ATA AC TAC TATNOITACILPPATCP 431TCP-620-IBSB.ONT GTEACGCATAACTCCTG GKCG GCGTGC CA GTA C4O6596696796896996097197297979379479579679779879989089 189289389 4895DEC N E U TT CA AT TA ACG A G ATA G Q ESTN AIR A V NOITACILPPATC9P elb 5aE31TC NER E F E REPY T D LIWTCP-620-IBSB.DTIONATG GEKC C CA A GC C T CGCG AC TA C868 78 88 99 09 1 ..O9 9 9 9 9 9 99299399499599699 799899901000110VoD NGTTCCCGCTTTTCCT GTCTCC TCCCTTA AGACATGTCTG ACCATG TTAGTCTCTC TGC A GTT AT GG G ATTTCCTAGTATGCCCTCAATCACTA TCAACCCCTGTA TTAGCGATA GTACCG AC CCCTTGTGAAAGGCATGAA ATCACCTTAGGGTACCGTGTAACCTGGTGTAGCCCGCTATATTTAATCGCCAATGTGCACCTTTAAAACTATGCG TGATTC CTGAG TAACCAG GGGACTGA TGGAGCCCTGC TCTCA A G CTCCTGTGTTGA TACCCCG A CGAGACCT A GGTAGCTTGGT TGG GCTGCGCGTAAATGCCTCGCA ACCG A GCGTC CTCACCACTCCGAGCA ACTA AATCTATCC T CATGGCAAAGG AGAGTTGGTGGGCGTTA CGACTAGAATTGCA TACTG GTG AAC TATAACTTGATTA A GACCCATGG GGTAAG ACGTC CGA TCTA AGGTGAACCCCGGCCGTGAGGCAGTCCCAGGTATACCCCAACACGTTA GTGCATGGTGACG C GGTACACC CACATACCCTGAATCTCCTTCATGCCCAT TGCCGACGG ATA G ATTCGTCGCTGGGCG AG GAACACCCCAGAGAGCCT CATATC TCTATTTCAAGTGTAGTCTACCACGCCGA GCGCGGCCAG AA ATATG AGTCGTGGATCAATGCTAGG CCAATTGTCTATCC AAG GCCAGCGCGCAATG ATCCCTTCCA AA AGTG T GTCGCGGTATCGTTATAC TATGTATCCGATTAGGGTACA CG TGCCCGCTGCTAA AG CAG AGA GCTA GA GTCTTCTTATGATACGCGCCTAAGGTACACCCACGGCG GGCCAGCATGCTCC GG CATACAAGCCGCG GAC GG TACTAATCAG CACTCAC GCG CGATTCCCTGCAAGTCACTTTCACC TCGTCTAATGACATGCCACCCCCCTATCC GTG CTCTTTCTACCATCTCGGAG A ACTATGGTCGTGCTTCCAAAAGGGACTG GGC CCC TGTCGAACCAATACGGGG ATGCAATTACCG GACTC TG GTCTCCTGCCAATCTCAGTACAGTATACGGTTTTGTGA CACTTCCA TTTACGCACTGG CTGCGA GTCTCANCOGACA AATIGCT CATCCAACA CGATATCTTTCGCACTTCCCTCGTG AGTGT TGCGGCA TCGTG ATAG ATGCTAA CTAAATGCCGAATTCACTCATCCCATGCGACATCTTATC TATTCGAG AGTCTAG CGTCCTGCTTCATCCGCACTCACTTG AACCGTCA AGCCGGAA ACATA ATGATGGTCGGCG ATGC CGGGTCATTG ACGTGC ATCGCCGGCTG A TAAA CC A G G AC C CGC C TGC CILPTA CPGA GC CTGA ATC TCTGA AAGCAC CCTG GC CCCGTG TAT TCTT CCTATAATC ATAAC T CACATCTG GTA ACACA ACCGC TP TCCGCTGG CCCCG TGTT TG CAAAT TCCT GTCGACC TAG GC 6CCACACATAGA TG GG ACGCGGA31GCT CCCCACATT CTTAA ACATCACCTCGA GCC TTCTCTCAA ATCCGG ACG A ATCGTA GTGTA CCTTC ATCGT ACTATA A ATTC CAACGCTGGTA CCTGCTCCC ACCTTAATTCTACAGTTG GG GGCG GAACGC CCTGCC CGAA ACTGT CTATG GGCTGCGGTAT TACCC ATATCGAACT TAGCTAG G GG GTTGAGTCTGTTGGAA CTGATCAGTA CTGCACCTTCAATG GTCTACA ACGCTCGA GCTTA G GGAGCCGTCGAGATCGT TG AA TA CATCCTG CTA TGT CTATCCA ACTGGGTGTGCGCTAG T ACA GCAGTCGCG TCTAATGCGCTTCTT CCGCTTCG AAA GGATATTACACGCGCCAAG CCTG AA C GATG GTGATCTCG CG C GTAACTT TCCGTGG ACAGTGCCC TAGTCCA GCGTTAG AACTTGTGTTCGTTCTGCC TTTACAGCTGTACCTG AA CTTTGTTAGG AGA GCTAATGTTCACA GGCCCGCCCTACACGTGTCGCTG GA GTGP- G G AATCTGTGCGTTTA A G G A AACCCGTTTG G620-IBSB.ONTEK. . . . . . .C O1 2 3 4 5 6 7DG T G GGC CGTCCT GTCAA CAA CGC C C GGAG A AAGGCAGCTCG AACTATCACAAGA GAGGA A GAGG T AGGGGCAA GACAAT CACTTA GTTTGGCAAAA ACCAACCGCCAG ACCCGATCGTTTTAACAGAAATGCAACATAATC CCGACCCG TTCCGATATCCTCGGTGAAAAA ACAGAGCTGTGCA CCTGCA GC GTCCACCTGTA G GCTTAATAATAATA AAGG ACCCTACGGATTCACTACTC T GCGTCCTGCAAACATCAAC TAACTAATGTTCA GCTCCG TGACGGGATCGCGGGGCG ACGCATCA AGTACACCGGAT TATGCACCA TTGA TGACTCACATGATGTCTATGTGG GCTCGTTGGCAACGACGCCCACACGCATCGTACATG GGCAACG TCGCCGCTCCCGACGTCCGTGTGTAAGG GGAAATCCAACGCAGGCA T GGACTGA TTA AGT CAAGC TGGTCCCGTCGGCCA C GCGTGGGCGTGCG GATCA AATTTCA GATTGTTATGTA GAA ATG CGG GTTGG GCGGGCTAAACGTACGAA GACAATAATA GTTC TGCCCGCGTAACACACACGAGCG AAAAG GC CACCCTCGGGTCGCGTCTCGTA AATCGGGGAGCAA TTAGT CTGAAAGTTTCG GTCCTCT GAC TCGTCCG GCG CGCTCGCGCA ACAGG GACATCCCATA TATCACA ACGCCAGGAG AAGAA CCGTG GGG GAGATG GGTTAA CTAGGA TTACGG CCCA TCTTAA AGTCAG GCCGCCCTCGACTCCCAACATATGCTCCCCACATGCTCCGCGTACACTCAAATAAAACG AGCTTTCA CACTTCCCG GTCCTCGG GGCTTGCTTTCCGGGGGTTCG GGTGCTTTATATTA G TA GCGA A A GGAATCGG CGGTGGTACATTCGCG GTGACCGG ACACCGTCTAACTATTTGAAACGACACGGTGTGTCGGGTTGGCCCCAG CGCTCAAA ACACCCATCATTCCATTG AGGT TGAGGCGAATACGGGCCNCACAGTG GACCCCATCGCGTATA AATTA G ACATCCA GGTGCGTTGAAG GGCCCCAGTCCOI TATGG GGTGTCACTCTCCG GCTACG GCACCTTTATCTGTTGGAAACACGTGAACCG ATCTACGGTG TTGCATCATGTTCCCCCTCTCA AAACG GCCCTTAC TGA GCTACC ACCTGATTTGCTGTACATCATA GTTACTTAC ATCTTCCCAA GCACCCAGTTGA A AGCACGTGTCCGTCTG G A GTG GILPG T CCGACCCA AGTCAGGGPACAC CTACTCCA CGATTGGCTTACCCCTCT TC TGTA TP CA AC TCTACTGAACA GG ACCATAGA GACGCACCTTTA TGGAA CTGACTGC 73CGA A CGCTTTTTCATA GGCC TCGGGTTA1CAC A CGAGGGGCGTCTCC CGC C TTCGGATCTGTTA G TACGCTTCACCCTTTCTTGCG G GTCC CGTTCG A GG AA AACG AAGTTCCTCGTGTTTTAGCCGTTTACCATTTAG TCCCGTGGG AG GTGCTACC GTACTCTA AGG GTGCTCGG AA GTTATCGG CCGACC GTTCTACTA CAGGCGCCG TTAGAGTCGTCTGTAC TCATCAGACTG ACCTGCACCGTTTAA ACACTTCAGTCTCTTTAA CGACATCG G ACAATAACCCGATGATCCC TCC T G TTCG ATCAAG CTG CGT TTCCACAGCTG GGG GCCA A GATATTGTGAACC CTGGGGCTGG G GTTGTGC TCT CGGATTATA ACAAACTGTG A CACGTCGCG AGTGA AG GGGACCGCA GTGTGCCCCGTATG AACA GTTGCAGA CTCATCAACGCTTACCCTTCPTCG ACTGA ATGCGAC-T TA GCTTA G A ACATACCTGCA620-IBSB.ONTEK. . . . . . .C O8 90111213141DACC G AATCGCGG GGTTCT CCTGCGGGGTA ACCCT GGGGATGCTA GCCTA CGGGCCCGGCGCAAGTCCGA GGC TTGCC ATGTC TATTCCTAGGCCCTTTACGCCCCCGG A CAACGCT TCGCTCCG AGCTAAT TTGAGCC CGCCTACCCCAACGTT TACCTACAA CGCCGCA CCGTGCGCCTCGTG GA G GGCG GGCTGGCGAT AGCCCTGGATAGTCTAGCAGCCGCGTCATGGC TCTAC GACCGCCGGC TGTCGGGTGA ATAG GACG GGGACGCCAGACAATTTG A GTTTTTAGCCCTCGGT CACCT TA AACG GGGTGGTG CGGATAA CGGAG TGCCGTA GCCGT AACTC CCCACTTTGTCGAACTCCG TGTAG TCAGT TCAAGGAG CCGAGGA TGGAGCG ATTCA GA GACAAGCGACACGCAG CGGTTACG CGCCCACCCGGG GGGCTC CCTCCTCTGCCCGGCTCGTGG GTCACT CCA GGCTCGTAG ATTCT TCACCCCCC CCCGTCTCGCGTCCGTGGA A CGCAG AGCGAGGGCCAACTG ATC CGAACCCGGT CCCTG GCATGCCAATGCG TA GGGCGGTAG GA A TGG CCTGCA CCCCCGGTCGCTCA GTGG AGGTTGTCAGCTACGT TATGTCGT TGAGTTGTTTG CG GTG AGACGGGGTATAGAATTCCCGGGTGCTACGGGAGCCGCCGC GTTCTCCTCCGCGTTCGCCAGCCC CGACAACCCG GCTTGCCAC GGGAC TGCCTTCGGGGTAGACACGGAGTGTCCC TA CCGCGG GCTGCGCGCCCGACCTCCCCGGTGTGGTCCCTTG G AGTCCACCCGTCCCGCCG GCCCTG CCATCGGGTTAG GGGCTCCGCGG AGGGGCTG CATCGTCTTA GGA G GCGCTCG GG AGACCTGCTTCAAA GGCCTTG GGCCTGTAGA CATCGCTATGCTGGTCG GCCGTGGCTCGGGTCTATATCTTCACTCTAAGTGCTCGCCCC TTGACCTGCCG TGGTGTCG ACGGTGCGGC ACCCGTACGTGGACCACCCACGGAGAGTNAA CACGCA AGCCCCGCGAC CG ACACCGAG TAGTCG GTAGCCCCCGCA AGTCCTGG GTAGTCATCAOCIGTCGTCCGG AAATGTGATCAGCCCACTGTC ACGCCTGCTCAGGG AGCGCCTTCCGTACGCG GGTCAACGTCAGCCACCCCGGCCCTACG GCCCCTAAGTCCCG GATCGGAG GCTTGTGCGCATCCCAGG CTGGTACAGTG ATCCGGTG A GGTCTAG CTCGTAACGCGAGTTTTG CGG TCGGGAG TACGAGGC GC CAC T C T CGT T CG GCAC CA GCG G GILP ATGAP CTGC GC G GATG GG CTGCGCATG ATTCCTTCCATGTG AG GA TCCTCT CTCA GC CCA GG ATTA TCAGCCC CTGGGCGCGGCTCTAAG TACA GTGGG ATPGCGAAGCCCACA G ATACCTGG GGTATTTAGCTCTTAGAG83GAGGTG ATTCCACAG CGTG T GATC1CGGTGTAACGGTACCAGC TCGGGACCCAGCGCCG G AAG GAATCTCTACCGTTGTCCTCGCG TCACT CCA GGC TGATGCGCCCACCTAGTTCTCTTCG CGCGGCGTGTGGCGG CTG CA C G ACCAC TCGGATGA GGC CGGTTG GG GCAGCAATCTGCTTGGAGGCGAG G C AGT TCCTCCTGTTAGACACAACGCTTATCCTACCGCCCG GCCGTG GCGTGT GCCC GCCTATA GGTGACTCA AGTG GTT TCCC TGTGGGCGT TCTCCCCCGCATTGTTAG GGGTCTCCT CCGGCGCA GTTGAGCGGAATTAG GTC CACTTGAGGGAGTGAATTTCG GCT TCGCTACCGTGCTGTCGCACGGCG GCCCGTTACTCTTGATGCA G GCGGTGATA CA CAACGCCCCGACT CCATG ATGTTA ACCC ATCCTAGA TG GGCCTCGGA GCGCA GCGCTA C ACG GTTCCAA A CCPCGTCCTTCATAGGCATTTA G GCGGGGCCGGATGCATCTC GCCATTCTGTGAGCATT-CG GCAGT C CG A A A G G GCATCGCG G620-IBSB.ONTEK. . . . . . .C O51617181910212DGTCTCGACATCCGGGCCC TTA ACACCATACAGGAGACGT CGTGTTCA GCTG AAG GGGCAC GGT GG GGCG CCTGGCACTGGGCTCGCCTTTTATGG GCAGACGGTCTA ATGACCT TTG ATG GATGTG GGGAATCCTATTAC CACG GAGTC TCACG ACACACAAGTCTTTATATGGCCG GTAC CGCGAGCCCTCAAATTATTGCAAAC AGCCATGGTTCCAAC GAA AATTACCGA ATAT CTG GTCGGTA ATGTGCTCG CATGTAAGATAACTGA AAC C CGAAC TGTGGTATGTTAGGACCTAGTGTTCCTGTTCTTG GG ACACCCG CTACA AATCCAAAA ATCTAT TGACTGGATGGTTCCATA GCGGGAGCCG ACAACCCTTCGTTAACCGCAACCAAAA AGAAAG AACA GCACAAG GCGCAATA CTG CGATCGGGAAG ATCAATACT TACCTAAGTA GCTA TGGTTGCAGCCGCTGATACTAGC TTGGA AAGGTTCCTG G ACGCCGCCA AAGG AT TGCACAA GAAG GTCGTG ATAATAAACCCCAACG GA CTTG GGA GCAC ACCCTGCTATTTCCGTGATAGA A AAAAGTA GATATTCGCGACTGACCTCC CAATATGCGTTCAGCCTCC TG CGCGTATCTCGATATCGG AATCAGG GA GTG AGGCGACCC CGCCACTCGA G GG GG CAGTGACCTCTGTCTGCGCTCCTG GACG GG TA CTCCCGTGGCTCTCATCGTATTTTGTCCTTCACA ACCG AAC CCACGGAG AATACCACTCTGA AA GCA AGCCGATTCTCGTCCGCACAGCG CTGTGCCCAATGAAATACTAGA AG ACTA GG GG GGGTGTG TGGCGTCGAAA GCTA CTCCCA GTAACGA CTTCACCGGTCGATC GCGCA TGCCACA GCCCTCATG C AA AGACG AACTTTCCCATCGCCCCA G CCTGAATGTA GAAGCTATGTAA CG TGCGGCG GGATAAACTCCAGTGTATATCTTAGNCTTCCTG GTCTCCGAGGGAA TCAA TGTTTTTTCGAG GCCGGG GTAACCCATCTCCCCTCG CACGGTTTCCACGTCATCA TTCATTTACAA AATC CACTTTTTTGGCGTAACAC TCG CAGCCCOIA CCTCGG CCCGCTCTACCACCCTACA CACCTAAATAGGCTGGTTCGTA TGTGAAGTACAATCAACGTGCTAATGGCAAGAGTTTGCGATACGAGTTTTTCAATTGCGTG ATAACAG ACGTTTCTCTA GTGTAG TACCAACACACCACGGAAA CGGTGCCC ACTG AT T C A C CG GC GC GC GC GCCCA A ACGCGTACG G GT TGT C T TGT CGT TGT T TILPCCPGG CCT AC CG CAGTACGTGA AGTACA GTTTGGCTCGGAG G CAACTAGCG TG G GT CCCC CGCTTCAP TGATGGTACGTA AAAAGTA GC CAA CCTCCACA CCA9CTA GA AGTTCC CGT T3TCGG G CAG CGACAATCG GGG GGA ACTG GTC 1CAGG AGATA G ATAAA T AA AAAGACCGATCTCA GGTGCGGCATATCA A A GCGTA TGTACTA CG CCTGCA AACGACCCT GGGAACGATATGCAC CTCCACCT CTCCATAGCA GG TG GTGGACTA C ATG GCTCGTAG G GTCTGTACACA GA GG GTCCCCTTCTGTGTCCCCTCCTG GCG GGCA CTCACG ATA G CGG AACA ACACA GTCG AGG GCCG ATTG CAACGTCA GGGG CAAAGATTC TG GCACATACG ATCAGCGCTTT CCCAG A GGCT CTCGGTCGCCTCTTCACACTCTTA ATT CACG CGGTCATTCCGGTTACGCGAT TG ATCTCC TTA G CAACGTAGCGCTCCA CGGATCC C TG GGC GA AGCCCC TTT TAGCTG GCTAT CGTTAAA CTG ATGC TCA ACTCTPGG CTATTTCTT TCTAACACTG GCACCGA A -T C CA G ACGGTGCCTGTTTAGTCTG620-IBSB.ONTEK. . . . . .C O223242526272DC ATC TTTTGCC ACTTGGACC CCTTCA CTATA CCATCCTGCTTCC CTC GCTTCTTAGTC CCTCT CGTTA GCTACCCGACTGCTGGAGACTGCCGCGG TCGCTTCAACTTCTTTATACA GA GGTGGCTTACATCGCG G A GGTGCGTA GA GGGGGTGTGCTTTTCGCACTC GA G ACTGATAAA CCTCCTTCCTGG GCA GGG GATCACCTCTGTAGTGT CG ACTGGTCAGTCATGGTTTTGCCTCTCCTGGCAAGCGGCGCT CTG GGG GCCCGT GGGTTTAGTGCCTCTATAG ACCGATCGATCACGATATTTAGGGCGGGTAG GGA GCAAGTTG GGAG CTGGAA GTGACCGGTCGTAGATG CATGTG ACGTC AAACAG AAGGTA G GTAATAATTTA CGAAGTCCTCAACCA GCAGCATCACCCGCGTCTA G CCCGACTCGACGG GCGGTCCATACCCCTTTGCCGTACATATTGA CTATCTAAAACTCAACACTGCCTA AA TTTCC CGCAG AGCG GCCCCCAA C GAGCCCGCAGTA ACTGAAAGCGATCTGGCCGCCGCGGCA CCAGG CAGCG G CA GG AGGCAGCC GTACAAGTTGTCAATTTGTCG ATAG CCG CGG GAG CGGCGGCTTGTTT CTGT CGGAGCTG GGTATGG AGTCTCATTGTCA TTCTCTCAA GTACATTAA CGTACGCGGGTCGTGG GCCA A G ACCCA CTGACTCCCG GTTCTTCCCAGTTG TA TAG TACTCACACTA G CGGCGGCAA T A GTGGAAGGTGCTATCTTCTAAACTAA A AGTGTGCGAGCTTAGTGTGGGTA AACAG AGAAGCACATCGGACAGAAGTGGACT CCCGAATTTCAAGCT CGGTCGCCGGTCGGGA ACTGTGA CGATGTG GTGCCTCCCTATCACTAG GA G AACTATTCCTGCCG TCTGAAGGG GCA GGGCGCG CACA GGCGCTCTATTG TTCCACGA AGCATGATTGGTG GACACGTTC TAG AGAAACCGCCT TTTA AGG ACGGGCCGGAGAGGCAATGTGCTGTCGC TGCNGGGTCTCA AGTA GGAGTCAG AGATTGCCTGT CCGTGCCTCTGCCTGCAATGTG GGTATGTCOCGG GTIGTAACGCGACGTGGTTTACG GGGAAAGACGGCGAACCTA CACCGTGCGAAA ATA AAA ATA GTCGTTGGGGCCACGTAGAACACGGCCA CGTTTGTGGGTA GAAATTACTACG GAACGTG G A GTCCCCAGCTCACA GACTTCATAGTCAG G A ATGTAA A GTTGAGGCTTA CGCATGC GC CA ATG ACGC C T TGT TGILPCACC GTCT CPAACACG GT TCG TCC CG TCCGTCCCTTAGA GTTCTCCCGATAPAG ATGGCG TCACTTAAA CTGTTA GGTGTTCGC CGCGTAAGGTTGCCA GTT 0CTAA GTGCCTTACA G ACGTATC ACC TCCCTCAT41ATG G GTA GAGGTTTCACATCCTCATGCCTTACGCGACTTTTCTTGCTT CCA ACTTGCA GG T GACCCTGTGTT TGACGCTACGCTCCTGCTTCGC CGTA A GTG GGG GATGATG A GATCACGCACA G GGTGTGTTC TTG TCGACGTGG CA GGGCACATG G AGACC CTGTA GGG ATACTACGG CGTCATAG TCA TCGCTCATACACCCCCG GTGC GGTA GA GA G GAA TACT CCCTA AC TA T GTA C A CG ACGTTATT CTG T A ATCCGCGAATGACG GCGGT TTAACCCCAGCGCAGATATCGCG AACTGCAGCGATG GCGA GCCTAACTAAG AACACCCG ACG C GTTCGACCCTTCTC GCGG G CGTA GGTTGCTAACACTTTGTCCAG CATGTGACTTTA G ACCGCTA GG ATTTGCCA ATGCTTCGCACG GTPTAA ACGAT TATCTA GACG GCGA G - G A GC CATGTA G G GCC G A GCTGTG620-IBSB.ONTEK. . . . . .C O829203132333DGC C AT TG TCT AGGG CCA T GC TGAAGTAAATGTGTTGAA G ATAAAATCGTGTTAACCAGGACTGAC TCACGCCTAGCGG AAGTCGCCGCG TG GGAACTCAATGCCATCGA ATTTGTGACCAGGCAGAATTCAGGGGTTGACTAC ATGCATTATAACCCC CAGC TTAGTGACAGG ACACGCCC GGGG GAGGAG ATATTA AAATA G TCGCCTA TGGGCGAGCGGAGCG CGAAG C GTA GGCGCTACG CCAA GTACCGCA CACTATCCAGTGAACTTCCGTGGTGACCC GACAACCCTCGTAGACGTACTGACAA CTA AGAATGTA AACCCGCGCCTCGG GTGGACG ATCAGCGTC CCTCAG GGCCG AGGTGAACCGGCCTCAGGA GGGA CGTCAT TAATCCCCTTCCCAGCGTCGCGGG GGCTCCTCACGG TATG CA TAG CCTGTATTTAAGAGATCGGGGGCTAGGGTCCCGTG GGG AA GCTG AACCGCC GTTAGTA A CATACGGATTG ATCTG AATAGGCCTCGGGGAGG CATGCCGGCTTAGCG ATCCGTCG AACCGC TGTTA TTAATAG ACTCTCCGGAGTGAGTCCA GGCGCACCTGA TG GACGCG TTTAGA G TA GACACGTAGGCCG ATCCG AGGCCGCCGGATCGTCCTCGCCGGG TAGTA A GTGCGG GCAGTAA TACTACGT GGGTG AT TGACCTG ACGCATCCAGG GGCCGTCGGTAGCGGACACG TACTGACCA ATTGATTATACCCACTAA CTC CGGTCCCTACAG AACTCTCTTTCGGG A GGCTAATTTG AGC TTTCTATA AC CGCTTATCGTATGGGCCGA GCTCCAGCA CGG GGCT GGG TTACGC CCTCGTCATAACGGCGG GCT TC CCTATCCTTGG GGGTCCCGGTTG AGAGTCACTTGGTCCG GTGCGT TACAGTAGTCA AGGG GGA AGGG CCGCCACCA G GAGCACC TCC TGGGGACATCGGTCTTATTTTAC CTGTCTTGCTTCCG TGCTG CGTG GGGCGTA AAAGG AG GANTAA TGCCGTCCGTCAACTTAAG GGCCG GTGGTTTCGTAGTA A TCACCTGCCCAG GCACTOI TCATCTTG GGCGG ACGATCTAATCG AGTA ATTCTCCCTG G AGCCGC TAGCTCCG G GTCTTA GATA CGAGTAGTGACATCGACATACCTTGTGTCAGC T GGCGCGCTCTTGCCGACGCCCAGTTCGTGTC G AGTGTATATCTC GGTGTG ATTG GGCACCCTCCTTCTAGCACC TTACATGCCGCG AC CACILPG T TCA G C AG GG GCTG ACP TGGATAGGCAGT AGA GCTTGCTAGGTT CACTCCCC TGCA G ATGAT CTAGGTTCCCCG A GTCPG GAG A CACAG TT GATACCGCCAG GTCCGC 1GGACCGCCTTGT AGG GTGGGGCAGGCA GAC41AGTAA CACACCTGCCTTTCCCGGCTCCAA TT GGCAGCGTCATCATACTG ACGACCAAGACCGGCTTC G GCCA GGCG G GGTGACTCCCG GAG AAA A ACAG AGGG GCTCCGCTCGCGTCTTTCGTG GAG AA GATA GGCA G GTCCT TAGCG AAA A TCTCGCGCACCG TA GGACACCT AG GTTGTG GGT GTTCG CTTTCG GGCAGCG AGGTCCCACTCTTTA A AAGTACGGTACACCTCTTCTAGGGTTCA GCCGTTC GTGG GAT GGCGGG TCAGGTTACCCTTACCATC GGCGTTACCAG ATG CGATT CGA GTC ATGGCCCC A GGCTTCCGG GCTAGGCTAACCCA TTGACA TTCCTTTG ACATA AACA ACCACA GA T AGACTTCGCA C A ATGATCAGTGTGGCCCCG CAAC ACCCGTTCGCGTCCGPGTCCTGTTATGTCC A GGCC GACGTCTG A -T CGGTACGTA G GCGTCGGT CG A620-IBSB.ONTEK. . . . . .C O435363738393DGGG CG CGAGTCGTACGCCC C GGCTTC AGC AGGGTGAG AC AATA AACGAGTTATA CTTATG ACCTGAGCCGGTTCCGCCCCCTCGTTG G AGCAGAGCACA GATAGTAA ATCTA ATGCCTGAGCCTTGGCCTCACCAACG ACGTAGACCTCTACCG A GGCGGGCAATCAATCGCTTGTTG TATGGCCGTG GATCTAG AGCACCCCGTG GG T G GGCATTT TCAACTCGAGG ATATCGATA GACTGCCCCT CCG ACGGCTAGGCAGGGTATTGATTTAGTA G AGCACATTTTCTTG A TCACTTAACAG CCCC TGGCAGTG ACGCTAGAGTGGTAA GCTCCCCAAA CCCA ACG AGTCCA GTG CATTCTGTATGGGTCCACG GG AACTGGTTCCTGAGCGGGTTATA GTACA ATGGGTGTGCGGTCCCGCTC AGCACCCCCTGGCTGCGG G ACA AGA GCGAGTA GAAACATGATAA AGAG TGAG CCCGGCCCA GGGA GTGTTCT AG TCGGTCGTTATC GTCA CCG CC TG AAAA GTAG ATAG GTGA CTGCA AG AGCTATGCTGGTAGGGCTCA TAGGGTC CA AAATTA ATGCG AATAGTG CTG ACCGCTCCG GACCA CATTGTCCGTCGCCGTA GGTTT AAATA ACCC TGGCGAAATTGTGCGCCTTCCGCCG TCACCACTGCCA GATACGTTTCCAGGTTACCTTTTCTATA TGTCGCGGCTCCGTCCATCC TCCTCC CGG GCGG GAGCCA AAGCGGATCCTG A CCAGCTCTTCTCGAAGTCTTAC TTTTAACTTAAAACCGTC CTACCTGGTACACGTGACTGGATATATCGTGACTG TCCTGTCCCGTTCCGCG AATGCGCCGCGTA CCTCTTCTTG GATTACGTCAATACTACATCTGA CCGCTG GGATA GTACCCCTCCGTCCCACAATCTTTAA GCCTATCTCGCGTTNCCCCGTCGCAGCG G GCT C TCGGGACCGC A GATTGA GCAATGTGTTAGGGGCAAG CTTTCOCGAGTCCIGC CCG GACTG GATCCAGTTCAGG T AAAG GTCTCGTGCTATAAG CACCTACATTCCACG AGCCCTCTTAA CCCCAGCGGCTGC TGGGGGG TGACGCAACGGCAT TCACTTGCTAACC GTTGTGGGACTCGTTG AGGCTCGCACTA GGG GTAGTTATAATAA GGCCGGA CG G GCG GC C CG G G ACA AA GGAAT A C C ATCC CA G ATAC C C C TGTGTATGC TILPG CTCAGA T GGTCAT TTAAAP CCA GACTG ACGCAGA GTC AGT TC CACACTA AC CGGGGGACAC CTAA AP TTGCGAGCCCCCGTAGGCATCCGTG ATTAAACGA CCAG GGAATCC TAGCTTCA CTA AA24GCTGC TACA G GCAACCCTGGCCG C1GTCCGG AGCTCGG GTCGTTG A A ACGAGGTCA GGTC G ACCCATTGCACAGCTG AGATACATGATCCCAG AGAA GCCATA GA GTAGTCA GCTCGTG CCTCCGATG GAGAAGGGCCCCTAGCCTCACCTCAGCGATTTGTA CAG ATAACCATCA ACTG GCCGTGCGTCAATGTTAAG GCGG GCGCG CTCAT CG C AATAAG TTTCTGA GGTTTCCGTG CGCG GGCCCCTTCG ACTGTCATTATATACACCCTAAGCTCTA ATA GGCACGAC ACCG TGTA G GCTCCCTCCCTCTACATAA TCCTCACG GAA GAAC GTCTCG CCACTTA GCCACCCGGCCCGCACGGCG CCG A AA GA A AGA GGTCAACTG CACCTCCCGGC TCA A GGTATTGCCCTPCTTAGG CTC G GGATAC TGGCCCTTAGCACACA CTGA TTTTG GAA TATTA GCCCT-CGC CG G AT CG AC CA ATGTT620-IBSB.ONTEK. . . . . . .C O04142434445464DTTA TGGCACG GCGATCAGT CA TAATGCGGATCTC AT TAG GCGCG TACCCTCACCCGTCATG AAGTGGCGG CGGGTTAGACTA AGCGTAATGCGCCG GCGCTCAGAAAACG AG ACCCCTGCG GCCCT GTGCTTGA TTCCCCGCCCTTCTA GGGAATAGTGCTGCGCG GCA GGCTGTTGTATAGGACA ACTGAACGCAGGGGG A AAG A ACACGTTTCAATCG GCATC CCAGGAAACAGA G G ACCTG CGTCGACTTCGAATTTA T GCCCGCCAGCGCTCCTA TCGG ATATCCTAAT AGTA C AA CAGGG GGG GGTTA ATATTGGCTAAACAGTG G GGG GCCGCA TT CA CGTCCGTGTAGTCG CGCGGCATCACACCGCCTTTA TCATCAGCTCA GG GACACCGGT TTACTC AGTTG ACTTTCCCAGTCGACTAG GACGAATTTTCCTG TCCTCGTAGGCACTGAGAATTCGTA ACAGTACAACTGTCG CTGCGCGCGATGTCCGCTGCGGCCGTACCGGCGTGTGACG ATACAGGCTGTTCC ATTCACCGCG GG A GAATTAGACGTCGGGCGCGGACTTCA CCTCCTAACG TCCGCTGACG T CTTGTTA CGTCA CTATTTATA GGAAAAGTTACCCG GG CGCTCGTAGCCAATGACGCCAGGAGTCGTTCGGCGACCCTGTCCTTGTG G AAGCAGCGTTC CAGGAGGCTACCCCGGGA GG GGG AAACA CCTG CGT AGTAATTGTA CGTAATTCGACGCCGCCTCATTAAACAG CTTTG AGTTAACCTTTGCTCCTTGTATGACCACATTCCTGTACGTACTCTTA GGG GCCTAGTGCGTCACGTTCCCCCGTTATTACGTGTACATACAGG CCCCGCGCTTCTTGTCGCTTG GTATTTAGATAG GTATGGTCATTG TACGCGGACTTTCGTGG A ATCTATTGTCGGCACGCTCTTACTAACAN AC CTCCAC CG TG CCATTTGTG AATCCGTGCTCACC CTCAAGCC A GTCCTCCGGCAAGTGTGCTACGCATTA TTTGTAGTCCCTTAACACGTCCAGCGTCGCTGTTTATTA GGCOI CCGTG CG ACGTTTTGTTTTGACTGTCCCGT AGTG GTCGGGTTCAA GCTTCCG GGAGTTTTCA GATTATGTA GAA CCTACGCGTGTGTG A G A GACGCAA CATCTGGGCGCGCACGCG GGCTG GCGACCTTACATCTTCGG TG GCTGCC G A A G AC T T C C TG G G AC CGT C T CGILP TCTCPGG TACAAC G GG C TCC GG GACG GGCAA CCATCC TATCG GATGTAG ACCGC CA GCC TCT TCGAP CTCCCA CGGAGTGG GCG ATAA AGC CATAGGGCGAGG GTAGCCA GG AGATGTAGCG34GCGGTATTG GCG ACGGGGCCGGTAGTC 1CGGTAGTCGTCTTAG GGCGACGTATTTAAGATA GACGTA GCCTA TG GCTTC TCATCCTGTA GATAA TCCATT CCCAGCGCTTGTCTG GTGTCACG ACCTGTA GCCAGTT TTTGT CTGACC CTG GA CGG CG GCGGA GC CTGACTGTGTAA C GGGTTTACGGACCACGACCATTTGTCGCA GAAC CGGG CA CGTGAGCGG TATTGTG G GGG CCCGGT TGATAGCCCGACATAAG ATTTAA AGGCGGCATCTGC GCATTTTAG GCGGTATCCGAG TGTGAGACTATTGTGCCCCCTGTCTTCTCACGG T GAGTATGCATTACGCTACG AA ACC CAGTC CCTGCAA AGTGCTTCCATG GCAAG GGT TTTTTT CTTGTCGTCC GCTA GTCGCTCA ACCGTTTTGAG G AGT AGT GCTCTG GGTTCCPG-TG ACGGCG A GGTG AACCGCTGTCGCA ATAG G ACG TTG CGCTAT620-IBSB.ONTEK. . . . . . . .C O7484940515253545DC C AA CTAGCTA GCT CCCCAGGGT CTGAAAC GATCTA CC GTCGCT CTCACGCTATGGTTCCCGCGCTGAGTCTG GCCA TGC CGG ATCTGCGGGTCACTTCCTCA G GTCGTAATACGTGACCCGCCATCCCGTGGTGTG CGAGG CGGACCTCAATGTGCACCC A ATTTAA ACC ACTCCTCAC TTGTCCGCGCGCTGACGTGG CCAAAACGCCATATTCTCAA ACACGCTGGGTCGTATTGTC CCT TGCA CA CGCCCCG ACTATGATGCGCCCCTGG GCCA GCGACGTTG CACCC CATTTCCAATAGGGGACCAGTCCCACTA TCCATAAT TCGGTTCACCCG CAGGGCCCTCGGCCCGTAAT GGGT CGG GCCTG GATAACCCGGGTGTCGGTCTA GCCTAGCATAACCGTTCCAGC GG GG GCTCGGCTTGTTGACGTTG GGTAA CA CGTG CACACTAGTG GGCGCTGGGCGCACCTG CATG GTCTCG TCTTTGAA TATCTTAGGTTGTG TGCGCGCCGAAGCCTCCGTGACTC GCGGCAGCACGCACCATGAATCGTACTCCTCCCGGTGTGGTCCACTCGTGGTCCG GGGTGTGCTTGAAGTG GTTTGGAAGCG ACGACACGCG GGGCCCCGGTTGAGTCGGGGCTGCGCGGCCCGCTGATTCA GCCCCCCATCA CCGGCGTCGTG GATCTGCGGTAG G GC CTGCCTTGA GAA ACTGG G TGTGTGCCCG GC CACCTG AGACCGACG G G ACGGCCCCCTA ACCTGATG GGATAAGCCATGTCTT TTGGCCGCCTAC TATGTTCACAACCGG G A ACGCCTCT TGCAGCGAATCCTTTGTG ATCTTCTCTACGTCCAGTCGGCGTTGCCG GGGTGCTCACGACAGCTCTTCCCCGGCGGCGTGG GTAAGAGATG CTGTAGCTACT TCATGCACGTGC TCATA GCN ACTACCGTCTGCT CCCCAG GCACGT GTGTAGCCCC CAAG GCGA CCTGTCTTAGCOGTATTCTCCTATIGAGGG T G AAGCCCA TGTTCGG GGCGCG TACCGTGCCTCG ATCGTTTTC ACGCCTTCCCA GGCCA GCGAA TG AG GGCAG GC CAAGATGCGGCCGACGG TCCTCTAGTTTA ATA AGGTACCACA A TACGCCCTGCAA GAACCTTCGCCGCTTAAC C CG AC C CTTG A G GCGG G A CT A TTTCT C TA GC TG GC T CG ACAT C TILPAG GGGTGPCACTTGTC CGTCAGTCAA TCATCGGTGCTCTTC GTA AG AC CTGAG GCCGG AG AGP CGTTC CTA G CACGG G TTCGG ATTA C GGGCTT CCCG4AGTGCGCCATCTGCTACTCCA AATAGT4G1AGTCTT CGTGAGATGCTAACCGGCCGATGTCC CGAATTGTATGCCAG CCTAGAGGCCAG GTGA G GCATGCGGGTTTC CGG A CA AA GTGACACA ATCTCTA G ATCGTCTAGCTTG G T GGG TCATAA A GCTTA GCGACGCCCCG CACGG GAAAA CCGTCTGGCTCAAA TCGGCAGT CCTCG A CG CATCCTCT CGGCT TGC CATT GG TAGTCT TCACA GTCCGG TTATTTTGC TTAATTC CGA TAG GCGCCGGACTCCGTG ACG GGCCCA CACTCC CCTTGGTCCACCAA CTGTATTG CGGA AACTCTGG G ACCCGCATTTTACGCGCCAGCGCCG CACCG GCAC ATCACCPCG -CGCA A G GAACCA GTA CGCTCTGACG GACTACGCACC620-IBSB.ONTEK. . . . . . . .C O5565758595061626DCCTGA GTGGC TGGCGTC GCTGAACCGCTG A TA CGATCCGCCCGC TCCACAGG AAGCG A A ATTGGATG AAGAG ACGTGCGCGCC CCTG AGGCGACAAGTCCGCTGCTGG TAGTGGACTCGGCC G GAA AAAACCGTCGCCTCCCGTACTTACGTAGGTGCGGGAA GGTAAAAGAACATCGCTTTCAG CGTCTG CAGTTAG GAAG CTGG GGCTCCCGG CGG GG G ACGTCCCGTC CACGGATT TCG CG AA ATGTAAGACCGGG GCGTCAGTGTACCG GTGAGACGACG AGGAACGCTTGG GAGGGTGGTAT CGTTG GTG GTGCTGTCGTCGTGACTCACGA TCCGAGCTTATC CTAAGG CCGA AGTGCA ATCTGAACGTCTCGCAGCG AAGCTG GGA ATGTGCATTC TAGCAGATCCGGAGGGC GGAACTA TTAGA GAGCCG ACGATCTGTATA GGAA ACAGCGTCGATACAAGG GCCTACG GGCGGTTGCA GTG ATG ACGTGGCCA GCTTT CGGTGG GGCAATGGAGCCCGTTGG GAGACGGCATTTGCTTA GAG GGCAGCC ACCACTTCG GGATTG CGCCA ATCTCCCTTAGAA CGGCCTCGCTCTCG AGTG GACCACTTCTGACGCCTTCGCGA GCGTTA ACGAG GGA GGCACTTCCCCTCG GACCAGTCTCCCGCTGCAG GAG GCAGCCTAAG GGTGG TTTA ACTTTACGTCCCGATA CTTCGA GTA AA TATTCTTCGTA CATAACCGTTCACCGTGCTAGA GGTAGGTTAGGCACTC CCTCCG TACCTA CGTTTG CA CAG AGCGACGCCG GAGGATA AGGGG AGCCCGCATA AAGATTCGC AGGGCAGTTG AA CG GACG GGGTGCCGCACG TCCAGGGTGACCTA GGTCATCCCCGAAAGC CTCTGGGTCTTGACTGTTA C G GAGACACGG GGTACCGTGCTGGG GGG AACGTTACAA CA CGGG GCGGCGG GGCTGGGTCGTCA CCGTCCTGGATG AGTTCGCCGG AGGCTCCCAGA GAGG TTA GAGNCATTAGAAA A GACCGCCTCCCGCA AGGGG ATCGCCTGGCGCCTGG AACGTGGACTGAGATOITTTTTGA CCGGGGAAGTGG GACCCCA CGCCCCTATCCCTCG GGCTGGCATAGCTAGTCAACACGTGCCGAA CTAAG ATAG TG CGAG CAT TTGACACCGTTTC TGGGCCC CTATAGGC C TAGACTC G GAC A G ACTGTTCGTACTCTC A GTGCTCACGG A A GGTCCCCTA G GTCTC CAGGGC GC T CG GTILP TP TG CC CACC AAG GG AC CC CGTA ACTCGAC ACTCC TGGTGCTC AAC CTGTTGC ACCACGCCGCGA GAAACCAACG CATACCP CATTTAGGTT CACAGCA CCTGGCGTG CC 5CACGG AGA G GA CTA AGCGCCAACGCTG ATGTTATTG CTG4CCG1G GGTTTGTCAGCATACGTT TG GATCTAGTTAA ACAC CGATGCTTCG A GTGT CACG ATAAG GTG A A ATTCA GACGT CGAAGGAGCCCGTGCGCA AATA AAG G AGTCGGGGG CTG ACTGAGG AGGAG GCATGCTTCACTTGACTCCTCGCCTCGAGACACG AACAT CCCA CGAGCG TCGCTA C AA GAGGG TTGCTCTTATGCTTTGGCCTT AATACCAT TG AT TCCACGA GAGTGGCCTCG GCATA AGG CTTG G AAATCG AAGTAG GTTTAACCAGGTAA GCGCA ACCGGCGACACC GA CCGGCTTG A CG AGCCA GGCCTTTGTGCCCA AAA AGCCGACCG G GCCATGCTGA TAT CGGTG G GCA GCGTG AGATCG CGCGTTGT CG ACATGCAAAGAGGT CGTT TGCA AAACATTATG GCTG G GTATCCCG ACTATGGCACGCP-CGCA GC CACACA G G ACTAAT620-IBSB.ONTEK. . . . . . .C O36465666768696DGA TACCA GGGCC AGACTTCC TGG TCCG C AGCGGGATACCCCCTGCTG C GG CG GTTG GA AA A GCGGTGGCACCAA TACCCC GTGTGTTCCTGGGCGACGCGGCTTA G GGG AACCTAATCGACGTTCTGCCCG CAGAGCG CGCGCGGGATAATCCATGCTCGTGCGAATGAC GGCTC CGCA GTCCCTAGCATGGTCTGGAG GCCTCG AAGGCTA CGGCAGCTG CGCC GGCATCAGCACCCCTTCGT TGGG GGCGCG GGAG TGGGCAAC GCA GCTTGAGCGCGG GTCGCGCT TCGTCCGATGGTCTGGCGCGCAAA GGACTAGGGTATGAGCGGGA TGG GCTACC TTGCTG GC TCGACAGGGGC CCG TTCGCGGTGTGGGGG AAGAGATAGGGCGGA CGGGA CGTATC TTTAAGGCCGCCCAG GTCCGCGCTATGCCA GACCGAATAACAGG T ATCGGTG ACCCTCCGGCTCGCGA GCGTGTGTGCGC GG GGACTGCCGGCGCG TGCTTCGGCTCGGCAGCTTTTCCGCCGG G CGAGCCATTTATTTCGTACTGACCTC TGGG TACATACGAG CCGCAGTCG GGAA GCCAACCG GGCGGCT GGATG GGG TGTG CAAG AGTCCCTCACA TATCGTA ACCACCG ACCGGG GTG GGTGTTCCATACGGCGCCG TC CG AGGAGTGTCGGTTCCCTCCCGACCGCTCTGGACA AGCTTCGG GTTCCGCG GCCGT GTACTG TTGCCCC CGAA CCAG ATCCTG TTGG GCGCTG GCTA GGGCTAGTGCGCA GG A GG GGTGTACCCTCAAAGCGCGTC CGG GTCCTT CGTGGAAGATCTTTAG ATG TG GG GTT GCACCGGTCG GTGG GCGTTATCCAGATCAGAA GGCCCTGCGTCTATCGG G GA CCTNTTA AACCOACATCCTCGCCTCTCCAGCGGCACGGTTAGCG CCGTCACA CTG GA GTTCTCTG GAGGGTCCGTCCA GA GGCGCTCCTTGGG ATGAGC TGCAG A ATCAGAA CCCI CGTGTGTCCGTCCAGGC CGC TGCC TGGTG A ACGCTCTCCTACCAGGATCC CGACGAGGC AGTTCTC G GCCCGGTG AGCGCGGG G G GCGTGTTCCG GCTCATATATGGACAGC A G G AT C TILP GTAACG T AG CTG AA G GCPAA GA CGCG CA G GGACA TC TG GC TGAG GT TCCAACG ATGCGCGCCGTTTAACTCTCGAA TGTGATGCTGCPGAGTGGCTGC CG6GA GGG ACGGTC TG AGCA GGG TG GATGACTCAC G TGCCGG A41GTGGGGT TACGCGCGCTAGTTCTGATTAGGCG GCCTGTGGTCG ATC T G ATA TGTGA ACCCCA T AGACGCGCA CC TGCGCCGGAGTAGATCC CTCCC TGAGCCAGCTTCGCA G GTGGTGTTCGGTCCCTTCGTTCATCCGT GCGCATGTGCA CCGGTG C AACGCAGG GTG G GGC GTTCCGTCCCGGGCCAGTT CGCA A CCCAT CGCGTCACAACGTCATCGTCTG CCGG TCGAGCGTCCAGAAGTC T TGG AAACGACGG ACGTTG GCTTTCTCTCCCACGCTCCG GATC CATTATCCG GGG GT G GTTG AATGTTG GCGTG G GCCTCTACTCCT TCCGG GTATC AACG GTTCTAAATCTCTC CCA ACCATGGC CCGC C T TGG G G ACCGCGCTTC G CA CT TGACTAACTGTCA ATTCTCACCCTCAT GCGCGTG AAGCGGCTCG GGTGCGC ATTCTA ATAAA CCCP-C C T CG620-IBSB.ONTEK. . . . . . . . . . .C O0717273747576777879708DAA TCGGG CCAGTAG AG GTCGCA TCGCGTAAGGCAGAATTG TTTTG CT GTCTCCTCCA CCC CCCCAGCCCTACAAGG GGCGGGGCCAA GTATG CATTACGTGACA G AAGA ACGA GCCGCGCG GCACCGG GCCGTATAG GTTCACGCTGCCTGG G GACCAAATAG ACAATAATATGGTTTGCGG GAG TCCC CGCTGTCTCGTGGCCGG TGGAATTATA AAAGCCCCCCCGTCGCTCGCCGACCCTCACACTCCCTTCAG C GGGGGGCGCGTTG AAGTATTGGTGTCTGAGTCCCACGCCGCCGG GTAA CCGGTA ATCTCGAAAATGCGCGCGTCGCTCCAATGCGAATTTATAAG GC CGCGGAGCATG CAGAACCGCG ACGACACCCGACTT TCATTTAGAGGGATGAGACTCGTCCGGCTC TGCGCCGCC TGGCAGGACCCTCGCG AATTA CTCTTCG TATGTTCGG ACGTGCGTCACGTTCGG GCC C CGC GG GACCCGG GA GGG GACA TTGTA GACCTGTTAGGATTGA A CAGCACCAC CTCG GCTTTGG GTCGGCCTA TGCCGATCGCTACA GACGTAGAAAA GGTG TACTG CACGGGCCG CAACTCCGGGGGGTGCTGTCG ACTC AAGCCG GCAAGGATGCATTTTTA GTG GATG TGATG GTAG GGCGTTCTCCACCTATAG GCTTGTTAA TATATATTGCTTTGCTCCGACTCTAGCCCAGGGCGA CTCGCCCCAGTGCCGGAGTCA GTA GCGCTCATAC CTGG AATC TGGCGCTCGCCGTCCGGTGCCGGAGGCCACAGCG GCGCCCCCGG GCA ATTCAGG GGACGA G GCTTAAGACA ACCCCGCCCC GAGA GG CACCTTAGGT CCGGGTCCGACCGTCCCCTCTGCCG GACCTG GGTGTTATACCGAC CGCCGCATCTGTCATCTCGTCGTG CGTGG GG ATGGTGG CCTTGTTA GTGGTTG G GTCCTCCCGGTGCTCCG GA GACATCCCCGGGCCCCGAGCGTATTTTTTCGCCCTT CTCGAACCGNCCGGTATCCG G ACG ATCGGA CGCCCGATAAGTTA CCTTACGTCCAC AACCTCACGTGCGCOI CCGTGGCGCGTA GATCTG GTGTCCACG G GCTTTTTCG ATCGA GACTTAGCAACGTTTAACCC GTGAG TG TCGGGCGTGGTCG GGT T CGCACACTGCATTATTTATCCCTACGGTGGCCCAACCCC ATCGTCCCCTTTTG G G G ACCATCTATAC ATCA GCTTTGG G GTTGCATTCCCTCGCC CGTGC CG GILPGCC CG G ATTTAGCCCCTPA GGAGAA GT ATGGGCAAACGC TT CC ACGCCTGG ACGT GCACG G ACCTACG GTTG TTGTGGC CCT CGTACTG GG TGP TTG GC CA GCCACAT 7ACTTG G TGAATG TGTA AACGCACGGCGAT41GTT TG GG AGATATACGCGCG ATTAGATTCGGTTAGTCAGCAAGTGCTTAA G G GTA CTGTCTC TCGCCGGG GGACAGAG GATG GCTAGCGG A GAAGA A GTTCAGTACTG ACAA GAGGCGTCCGC GGG GCTTTCTTAATTTA ATCT CTTTCCCCCA ACACACG AACGTA GG GTGGTCCCCAGGTCAATCGTT TCTTCTTTT CAAACCG CGGCGA CCG A ACG GCT CACGTG AA CC CA ATA ACGGG GCGGACG C G GATGTGTCGAACTGGT GTTGCTGG A TCGTCCCGCCCG TAATGATCT CAAATG GGTCA GGGCC TCGTCCCCC GGACAC TGCCCGTCCG GA CCGCACCCCGG GCACGGAC CG AGC ACCT CTG A GGCAG A CG AACGTCTG ATTGTCTG AGG G GCTCPTCCTGGTTG TCTGT CCTAGCTTGGTTTTGG CCAAGT TTGGT CCGGCTCG CCG - AC TG GC TCTACA ATT CA GCG620-IBSB.ONTEK. . . . . . .C O18283848586878DC GCTCTTGATG CCAA CGTT TTGCG GTTT A GATGCACTATCCCGCG CGCGTCTGA TTA GTTGACGCTGGCACACGATACAGGC TCAG TTTGACCACCTACCAGCGGCC TCGCGG ACATTGATAAGTTCCCG GGT TGGTTAACTTG AGGTAGGATGCGACCCAGGGCGAGC TTG GA ACCGGACC TGCGCCGGGTGATC CACAG CCGTCAGGCGC TGCGA GGCACTTT GGTAA G GTAGTAA TATG AAC CTGCACT CCG GTG GTACTA GCGCGCGGGATCCCGTACTTGTA G ATCAGC TTCGATGGGCA TA GT CGA AGCGA CATTAG TGGGCTG CC CCGTATGCAGCGCGGCCCTCAGTGCA GGA TGCGT TGAGCCCG A A ACGCAAACG A GCCGGATCACCCG AAATATCTCGACTG ATCGCGAAGCCAGT CAG AGGCA GGCTCGTA GCGCCCAG CAA TGTACGAGTCATTCG GTCCGA TAAAGCCCTCCAA GTCA CAT GCG AGGCG CGTAGTA ACGA AGA ATTG GATG TGCGTA GGCGCGCGTTTTGCCCGGGGCGGTTTTCAACGTG G GGATTTGTTGTA TGTATCTCA AGG CGGGA GACGGAACTCGTGG GCA G CG CGAGT ATCAC CGTG AAA CTGG ATAT CACAGTCGG TGACGCAA CAGTACTGTTGGCTTTTGCG CACCACAATA GATTGCTCG GCACTCTGGA ATTCACCACTCAG GAG CCT CAACACCTCGCGGTCG CATCCCCGGGCTTCCACG ATTATTG C AATTCGCACGATTTGTC TGACGCAAGG GGGTCG ACTTG GCGGA CTTGTCTCACG AG GACTTC CCAG TGCCGGAA GATG GC CCCGGTA A G GTTGATG ATAGTTA ACCTC TCTGCAC C CGTAGAATA GCATTCGAA GGCACGGGGC TCGGAG GGACAG AN GGTG AATGGTTCGCCGCG ACACGGAGTCGCAGCTGTGTAA GCA AATTGCACATAGTO GTTTACG AGA ATG CAGGGAGTGAGATTCGTACG GCGGCCCGGCCCTATTTTCGAITCCGGCACA ATTAAACC GCGAGACC TCTTGGTGGTGA GGAGCGCACCTCGGTTAG GACCACCGAGTGAGGCGCCTGA TAACTA TAACC G AC T CA AAC CCTTCGTGATGTCAGAGC GCACGT CA G G GCA GC CG G A A GCG AC TG G ACA G GCAILPG G A APGAAC C TGCG ACGCTCGTCGCGTGATACTATCGTTGTCCTCGTTAAC ACG GGCCTTAGCCCCA AGG GTC TCAAP CCGTCG AATCACCCGA G GTCTC GCGTCTCC GAA TGTGCAA8GTTGCGGCT TGATA4A AGATCGTTCGCTCGTGG1GGCGCAGTAC CCCTGCG ACTATTGTG ACCG CTA G ACCG A A ATACCTTGGCCCTG C GGTACG A GCAAGGCACCA GCAACAGCATCGTCG ACTCGT TGATT GATCACCCT CCGAT TTAC CCTGCCC ATGT CGC AA TC TGTA TGGCT CGGG GTT AGA TA GGTAGCAGGGA G AGTGG CTATTCCGCAA AAC GCTAATGCAATTGCG GCTGGTGATTCGCGTATCCG AC TATCG CTACCTCG GTAGCCTACCCCTTCACCCA GTGGGTCG ACTG C GGGTTCAGT CTCG G GACG ACGCC A GAG A AGCTACCGGACTGGTGA A ACGGCGG AA A AAGTAA GTTCGCCA C GG GACC CACAGTCATTACATACGGTGG AGTACACCGCAATAA ATCCA AC CGGGGTGA GA GGA G G AAC TA G GAA AAGTCA CGGACGAT CCCCTTGTGA TCGGCP- A G AT T TA GCA AC CTT CA GAT620-IBSB.ONTEK. . . . . .C O889809192939DC GGCTGGTGGTCTTGGG GGCGCGGCCTGTCA CG GTCCACGTC TGG A GCTC GGA GTAGGGA GAGCGCGTG GGTG TTGGG T AGCTGG T GCGGCCCGGGT CGCCGTACTCCCCAGTTTATGTGGTG TGCAGGCCCCCAATCCGGTGGTGTCT TCCG C AAGCACCTCGCGGTCCATCACATCG GTGTACGA GGCGC CA GGGTTCCGCGC TACTCCACCA T GGGAGAGTCGGCCGCCG A GACCTGTGACACTGAACTCGG GTCGCG T TCTCTCCGCGG CGGACCGCG CGACG GGGACG G CCCAACCAGATGGTGC TAGTTGGGCCT GCGGAACTG G ACTGATCAA CA AGACCCCG GCCCGCGATCGGAGGGCCGGGACTC CTTCCTTACGTGGG GTAACGCCCGGAGCCCCCAGAG GCGCTTGGGCGGTTCT TTA ACCTTTAAGGCCGGGAGTG GGGCG GTAACTCATT CTCTAGGCCC AG GATTACACGA CAG TTGCAA ACA GGGCGTGTCCCTCATAA CCGGCGCTGCATTCGCGCCTGCGTCAATGGGG GCTGCCGA GCGTAAAGGTCGGAGATGACGAG TTAGCTGGGCATGGGCGTGG GGCGGCTATTGCTGTGA ATGACGTTTGCGGATTCGTTGCGAGGTCAAGACACT CGGCG AAGC CCCCGCCTATAAAACTATGCTCCCTGG TA CCCC GAGGCCGCCGTACCCGGGTGCGG GTCCCCAC G GA GCCCCGCGTCAGTTGCCCCCAGGCGG C ATGCGAAAGG GCGATTTGCG CTGGTGGCTAGT CCAC CCGGAAG CTGGCCACGGCGGCCGCTCG CTCAGTGGCGGTTCTCCCCGGCG GGCCCATCCG A ATGTGGTCCGCCA GGGCGTCCG GTCCCGCCA AGAGAG GTGCTGCGACGGTGAACG AGGCGTGTCCGTAG GACGTTCAGCGGTGACCAGCCTGCGGC TCATA ATTATATAGA GTAGGGTA GCAGCGCG TCCTACTCTC ACGAGC T GGGCGATGCC CCGTTCCACGTTGCTCG ACGGGTCCCCGGACGGTG GNGGGAAGAGGCGAGCGGTGCATCGCG GGGG ACICACA GCCGTAGG AACA GTCGGGCTTA GGGCCTACCGCATAATCAAG GACTGAG GCGCTAATOCCG GGCGAGGGGCACGCAG ATATAC CGGCCGCTGCTAG AAA ATAACCAGCCG GACCCCGTAGCGGCGGCAA CCCAGTGA TGACG AGACTATA GCAGCTC GATGTCCA G GTAGG G G G GCGCCA GGCACG G AGTGCCCCA GCCGCGATGCA CGGGGTTAAACCC G A G ACA ATACG ATG AC C CILPCTGG C TT CT GGPGCCT A GG GA GTTCGCC T GGGA CCCGC TG GTCCATTG GCGCGCCPTACA AGCT CATGACTGTACCA C GA GTCATACGGCCGG AGCCGCTATTTAGCTACCGGCTTCGTTG CCCA GCG GGTATTCA G GCCG94AAGCAA CCTA CGGGA GGTAGCGTCATGTAC 1GGA GATGCCGCA A AGTGCGCGTG GCATCCCG ACTCATCGGCTACGGCGTCT C CATG CTTAGCCA G AGACTCGTCA G GTGCGGCATCAC GTG TGCA GCCGTTCCC CCGTG G AC TGCGC CCG A GACGCGTACGTTCG GCC GCCTTGCACTGGC ACG ACG GA CA ATGCGACCGTGA G ACA ATG GAGCT CCATAT TGG GCTAG G GA GA GCGC CTCCG GTCG G GACAAACCGG GTGTGCG GTG GG AGCCCGACATTTA GGT CTCGC CTTTCCCTG CCACGCGG CCAG GTA GCGGCGACATATCCCA CGGCCCG CCTCCAG GTGG AACCG GCGTCG CTTTTGGG GCC TATATCA A A ACG GCTGAT CC CTCAGGTCTGAACCCGA AGGTA CACGTGGACGG GACGAG GGGTTGCCACGGA ATCACG A G CATCCC TG GTCACGG GGG GA CGCAAA GGCCAA CACTGCG ACATCATPAACTGCG ACC CCCCG ACGGTG CCCGCCATAGC TA AATGCAGATTGG CTA AACG - GTCTG G A GCGCG G G A G ACCTACG620-IBSB.ONTEK. . . . . . .C O495969798999 00D1C A T GCG CTGACCA ACCGCGAACC G TAATCGTGA TATAGTGACGACGACCACGTGTCGCTGCCTATCGCGCGCT GTCGAGCG TGGTAGT CGA ACCGCG CGCTCACG GGCCTACG GCACCTCA A AATG CCAGCCAGCTGTGGG CGTAGCCG G ACCGCGGAG TA GTCTA GGTCAGCTGGACCGGGACGAGACGGTCA CGGCATCAGGAGCGCATAGTAGAGCAGTGCCGCGG A ACGGGT TTGTTGGTACCCTC GCAAGA GTCT CAA C GGGTGG A GAGTCACTGCCCCGTG GGTAG GCGGCCCTCCCGA TCG ACAGGCGTCA AGG ACCA GGGCGGCCCG GCCGC CTGACCT GGT CCGTGTACACCAGGA CA GCGAGG TATAGCATACTCTCCTA CATC GGG CGTTCTAGCGTA GTACAA GGCG CGCACC CTACGTGTCCTCTG GGGCGATCAGTTCCCCTGA CTTACG GACCCCCCGTGCCCCACTCTGCA CGCAG G GA GGACCGCCGTACTTCGG ACGGCCG AC CGTGGACTAA C ATAGGACGGAGGTTTATG GATGTC A GTACGTGGCTGAG CATACCCGTTGCGTCGAGG A GGACA AATTCACATGTGTAAGCTATACCGGGG GTCGGGGCGCCGGTGGCGGGACGCAGCGCTGGTG CTCACA CGCTACTATGTGTCGAG GGCGA GTA TGTTGTCGACCAGTACGTCTCGAG TTCTGAGA GCTA GCGTA GTGCCTGCTCGGA G GTCTTGACACAGCG ATCATCGGCAGGGTATGCCCCGCGCCTCCG A CGCCGG CAACAGCCCCGG TTA GCGCGTGGTGCCTA GACA GTGAAAGCTATCTACGACCCCTTG CCGCTCCA AATGGCTG GTCCACCCTTCG AGTGAA GCTAAG TGA G AGGACTGGGG GGACG TTCCGCTCCGGCGGCGCTCCCTCT GGCA GCTGTC CGGTTCATTCCACTTTGCG CAG AGTAC CGTG ATG GTAA GGGGGCGAGGCC C TCTCGCCCA TGACAATTCTTA CTCCCAAC GACTGAACTTATCCTGC TCCAACTG ANCGTCAGATGCTTGGCCTCTCCGAA ACGCA ACCATGCCTCGAG CGGGTCCCCCGGTGCG GTGCACGG CGAATGGGATGCGCGCACCG CGGCTCCCATOAACCTAGTTACGCGCGTACACGCGCCTCTGTGIGTGCGGGAGGG C CGCCA CT CAGTC CTACATGG A GG A GTCGTCGTCGCAACGGATTAGAAC TGTGCTTCG GTCGCGG GA A GGTA GACG GCCACGTGCCTCTA ATTCTAGCCGTAGTATTCGAAGTTCTAGCCCG AC C TG GTATGC TGC TGILTP TCC AGCGGTG G GGTTCTCCA GGACGPA GGCCT CGCG GGAACGTTGTTC G C AAAA GG G C GAGTA GTCAC CGTA GAAC CP CCGCC CTT ATCACTACG A GGGCCCG T GAG ACTGTCGTA GTTCTTCGCCCACAGG TCGC CCCGG05GAACAGTGCACCAG GTGG GTAGATCCAGC CTCGTGT1ATACGAG A CACAATTACTG ACTCCGCGGCCC CACGTC CGTGCCTGGAC CG GC AGCTAC TGCCGCC CGT CCA GGCCACGCATTG AG GGCA TCCC GGACTACGT CTCACGTG GTGGTACTCG G ATTTGGGCGCAGCCGCCCCTGAAACATACTCGG G GCCG CAG CTA GTTGCGT GTG GTGGG ATCTG G C ATCGCTGCG GCTA GCGCGCACC ATACC TCTGCCCCCCGGCCCCATT CA CAGGCACCTCGGCT CTCCACTTTG CCC CGCG ATGCG ACTC TAGCC TGCGCCTCCATGGTGCGGAGTG A CAG AGTCCAGGCTCCCATACG CC CGGTTCTCGCA ATTACCG AA G GTGCGCACCAA GCGTATTGACGACGGCAGTCG GG TCTCTG GAG A TA GCTCGTCA ACC CCA GG ATG CATACCG ACG A A GTGTGACCGTGTTACAT CTCTGCGTGACT CCG GGA GAACPTTCCGGCCTAA C G A ATACTTTTCTT-CGCG A G GCAGCGG CCA TCCGCCGCGATCTCCA GGTGG AATAG CTTCCT620-IBSB.ONTEK. . . . . . .C O10203040506070D1 1 1 1 1 1 1GCGTCCGCG GTTA G GGT ATGCTATAT ATAATTCGACC TAGCT CGTGGTACCTTCC GACA GTGATGGCACCCAT CCCGTCATGTCC CG TAACGCCAA CTGGGAGACTA GAAAACGCTTTGCG GA ATGTG CCGCAAATATGTGA AGGCGATCGACG ACCG GACG CAAATA CTTCACGATAATA G TCCCC GAA CAGTCC AATCCATCGCAGAAACTCTA GTCGGAA CATTTCTTAAATG CAGTCA AACGGGGTGTCCGTGCCATGTGTGTTCCTG CACG GT TGGGATC TTCACGTAG AACG AA CTGTGTATGCATCTCAT TGCCCC CGTCAATACG CA CCGGAGCTATG GGCTCGAGAGAATTAATA GACTCGCA G G GGCAA GC CGTG CA AG ATAGGG GTGG GG ACGGAAACG ATAG ACG AAACTTTA C CCGCGTTGGATGGCCTTCCGCA TACCCCAATCTGAGGACGTATCGG A AGGTCCGTCCCC GA CGGTCGTGAGATTAATTTACTAAATTTA CGGGAGTGGTTGGCCTGCGCATACGATTGA ATGTGCCTGAGGTACGGCGCTCCGA G GGAG TAGGG GTGATGACCTATTTTCAGTGGAATTGTGATCCGTTG GCGG CCAACTCATTTTA A GG GGGA GAACA T GG GGCAGACCTTGTAACTAAA A CTGTGCCG CTTCGCAGTCGCCG GCCGTCAAGAAC CACGTTTAGACGTT CTGATGTAAACTTTCAG GTCGCCCGCCT TTATTATA AGCACAG GGCGATCGCCTG TA ATGAAATCGAAA ATATCG GTAGTCCG GGCGTCGCCCGCTCCACCCCTTGAACTTCTAATCTAGGTAGTGATCA GG CT CAGGACCACCCTGCGTGGG A AAT TAAAAA CG GA GCTCATGAATTACCTTCTATGA GGGTAACCCAGAACCTTA GATATTCCTATGTAA A GTGAGGTT C TC C ACATTGGCCTCGATATAATACTCTAG GGNCCCAGCTCG GCTA GCAATTG GTGGTG AGCTGA ACTTCCCCTAGTAAATTTCTTAG ATTTGGTACCGAGGGGAGTTG CA GGTGCCGACTCGG GGTTTG TCTG AAAG CGATATOI CTTCGGATCGTGTTCG GCC GAGTGAAG TTTA G GCAGGCG GAGTCCCCATTAGTCGGTGA AGTTCTCC GC CAACGGCAGCGCTA GAAGCAGGCGGTCCGCTCACTTGTGTGTGATTTACAACCCGTC CCCA CCC CA T GG CA GTCTTA A AATTTGG AT T T T CGC C TG GC TG GCGT TG AC CATA A ATG GILPCPGC TG AGCGTCGCCA GGTG AGTAC TT TG GAATTG AT TACCCCCCAC CA A AACCGGCGGCPGTGTGCCCTGCA G ATCC CG AGATTATGAA CG TAC ATGTTGA TGATGA ATCTAG1CAG CCTGTCCTTGCGCGTGA TCCCCCCGCA GAATATGA AA51CATA T TGG GG AGA GAA GCCGGGC CA ACCAC TTGCGG AGC TTGGGGTGCACAG ACTTTA AGTGGGGGCACCTCG AATGGCTTCGTTTA GTCGTG GG TTA ACGAACCC GG GTTGTG GTG G A ATGTTGGTA CCTTTG A GTCA G CGAACATTGCTGG AATTGG A A AT ACGG G ACCGCTCCGTTG GCG GACCACCG GATATATCATTGCG GTGAGTTA C GCCT TTGA TC TAAGGG A AGCCATTGCTGGCCGCCTATATAGTACA C GCCGTTTACTTCG GGTA GTGAGTTTGTTATCTTG A AATACAGG G GA AACTCGAG GA ATCCTGCAGTGTCTGGTG T ACACA GGTGTGTAG GTAATGTACCGAG ACA ACGGCGACACATTAGATTCCAACGAT TGCCT TATCCTAAG GG GC TGC TCATTGTAA GACTC CC C CTAGTGTTATAAP-T TACG GCG ATA G ATA A A A620-IBSB.ONTEK. . . . . .C O809001112131D1 1 1 1 1 1AT AGTCAATTCTGTAGCC GGCTTATTC AAGTCATTTCG TCTGCGCATAAATTGCGCT AACAG G G GGTTTTA CGACGTGCTTTTG ACCCG GGAA ATTTCAACGTGTATTCG GTAA CA GCATAAC ATAAATCTTCC TACAG GCTTGGCTGGCATA AATTATAA GA GT CTATTAAAA CGAG AAACTC GTCCACAGTGGTCTGAGGCCGGTATATACA CGA CT TAACTG GCG GTG ATTGAA AG AATATTGCCCT TGT CAAATCTTTTCCAGAG A ATAT CGGTTACCC CAACCAGGTTGCACATAGCTCC TTG TCTTA TTCTGTTCGCCATACAGCTTAAAGTTG ACCTGTCTTAATATTTATCA CATCGGCTGCTA GA A GACAGGCGTC TAGAG CAA CTTACTTC CA GTTGCA GGCAAA GGCTTA ACTAAATTGGCAAG ACA TCACG TCCGCTTAGAC CTGATT TTAGTCATCA AAACATACA AATTTTTGTA TACACTATTACCGTCTCGTAAAA TTAC CGCTACATTG TTATTATTATTCA TGTCGCCTATTG CCAGTTTTCCTAGATCCTCG TGAGTAGTAACGA CTTCAAACAACA GACCACTCCACTGGTATACAGCTGTATCT GCCAAAGCTT C TCCAGTGTACTTCTTAG TAATCATCTGTTCCAGGGACGGTATCCCCCTCCATCGTTATAGAT TG ATTTACCCATCCGAATA CTTTCAA CTA AAG GTT TGTAGGAATC CTC CTGTCGCGCA ACCCAGAGGGCTTTTATTTTATACA G GGGTGCGTACCGTCAATCCTGTTTCA GAC CCCAACGTCCATGTAGGGATATTTTCA CTAGTCCTCATG ATTGTTTCTTCGTGA ACG GTTTCGCCTGTCGTATATTATATAGATCCTCATTTGATA GCTGTTCAACTGGGG ACCCATCCAAGTTATAAACACGGCAGTACTTCGAATGCCCTN A GTTTTTTCCTTCAG TGACCTCG GA GCGTTATGGAG CAGTTG AACGACTACTTCACATACTTAA GCCGGACATTATATCCA AATACTATACG ATATCAGCA TATGTATTAA GAOIGTTATCGTGTGTCCACATGCTG A GGCAGG ATGACCTCTATCTTAGTATCATCAATGGTTTTTTAAG GACTTAAAG A ACGGCA GCGTG GTAGTTCGTCATATTCCGC TTA ACTATTG ACATTAATCTA ACGGTCT CCTAGC T G A AT TT TCT CG A ATATA ACG A A GC CAC TG A GCILPAC GT T GPACA TTCG AC CAA GCAATAA GTGTGCA GACGAT TA ATT ATAG GTC TACG AGCGGG ACCGTPAACAATTGC GACG ATTTCTG AG GATCA ACAAA CCTTTCTT CACCATA ACCCT C2CA5GTTTTATTTTTGCCGCTCTCGCACGAATCA1CCT TTCA GCCGCGATAG CGTATACGCACCCCTATTG GACATCCG AGAATTT TAA AATAATGCTCCAGAA CTCAGGTCTTC CTTCGCCAA TGAATCTTTTCCATCTGACATACGTCTTTCAA CCGTCCTACCA CTGTACATGTTACCTACAT TGG CGTCTAA TA TTCACCCGCG GCA TGACA CCGGCGTT TCTTCTGC TTACTTACTTTTTA GTGTAATCTCACAGTG ATA GGCTTCACCGCGCTGTTGTA ATTT AGA ATGCAGTCTGTTTTAT TCATC CGCA CCACTA ATACAA GTA G GTCACATG GCA AGGCTGCAC TA GAG G ATTTAGTGTC TACCCCC CCCTAACGAA AA GGTCCCTGAA GC TTACGGATGAACCCATGGTTACTTTTGTACCTPTTTA GACGTTTGTTTACTACTTG G -TAGCATTTCG AGCCCTA AACG ATAGTACA GATACATCAC620-IBSB.ONTEK. . . . . . .C O41516171819102D1 1 1 1 1 1 1T AGAG CACATTACA TT TT TAGGTTCTA AC ATA G ACAACG GGTACA CGG GTT TCT CGC TG ATTATATTAA ATTTG GGTACCATAACCA GATG AAGACC AG ACTCTGGGCATGGTACCG C ACTACAACCTTAG ACAACCTATTAACCGGTGGCCTGCTAACTTG AATCCCACA GAATT CAACCTCGCG T GGAACG GTTTGCGATTA CTGGGTAACATTGTGAGATGCACCCGCGGG GATGTTTAA ACATTAGCGGTAACCTGCGTTAAGGAACGGAGTCGGTA GGGAGCAAAACCA GAATTTTACAATGGGTA AGA GTACCAT TCATAA GGGGTGA AATCTTGGTC GTATCCAC GA AGCG TAGA TCTATTTTCGATAT CATCGCTACTCTA CGTGTATACGCTTAGCAAGCACT CATCTGTCG GCCG TAGCGTGGTGCTTA AA ACTCATTTT AGCATACGTA TGCCC CTATCTATGTCGTGTGCGTTTCTAACCAGGGCCTTCAATCAGCA GCG TGGCACGCATGACCA AATCCCCAGAATTATTAGACTCAACTGGGGGGTGCTTACTGGTATGTCTCCC G AATAGCCCCGTTGGTCATTG GTTTA GCGTTGTA G CCGTA CTACATAACAAGTCTGCTCCTGTGGGTATG ACACA CATCGTTTGA TCAACCAGATTGGTCCCATTCACTCCCAGA TAGGAG GCCG G AACCATAA TATGATTTTCCGACATACTTATAG CGTA TAGTATCTATTACTA CC CAGTGGTAAATTTAACCGGAAATG GTATATGGGCAGTCAATGCACATTTGGTTTCATCTCACCCAAA CAATTCA GGTATCA ATAATTA GCGA A ACTATGG CTT TCTTTTGATCGCAA GACCCG TCTTCATTC TAAA GTCTTCTA AGGCTGCTTA CCTCGTTCA ACTCTTCGGCA CCTTCGTCGCCCGTCACATGGAA GG G AGGG TTGCTGCCTGTGTATTG A A AACCCTGCCTGG AAGANOTTA TTTATGATTAAG AACGCTTTGCGGCICTTAT CTCT ACGC GGTCTCCTCC CTGGGGTTTGACAA A AAGTTGCACA ATTTCGCGCCAGATG ATTAGTCTCGTTGTAAA CGTACTATCG A GGTCTTG AGATGAG AGGTCACTCACATTCTATA A TG T TGTCTGCCAGGCGGCCAGC ATATAC CA A G GTA ATG A A ACGC CG GCAT TGC C T CILP A TCGT TCT TGC TCTTGTG GCPAAGTG A GCATCTAATATAGACCAGCCGGTAC AGATACP CTTGTTA GTGGCCGACAA AC TACGATTTG GCATAACAG ACTTCACTGT 3T CCTAACCATA AAGGTCT GG GGT CG GTAC51GCAG ATTTGAAATTGC CGTTAGG CA GCG GGG AGC T TA ACA A GACGAGTCGG CACCGATCAGTATGAATTGACC TCGGT TTGTGCGTG ATTGATGTCATTACT TTCACTTACCCCG C AATA C GA GACCCTTCCGA TGGTGTTGCATA TCCTGATGTAG CGTTG G GCT ATA CC GTGG TCTCTTG GTGAT CAATCGC CACAAA CAAC TGG ACCGTTGGCTCGACTCAGAT CATTC CGTACCAA ATTTACAA CAAATCCTGT CTG GTCATTATCGCTTATCATCCA ACCAG ATCCTC CGA TTTA CTTGAAAT TTACTA G A C ACCGC TCCCG GACTCA GCCTCATG GACTTAC TGA TTTTG GGTATAGCT CTA GGGACCT CC CTTGGTATC TACCGAACCA AG GGTACCGGT CTGT TGCCCGCCAAG TAAGTA GTCA GAG A AGGCPT-TTTTTTA AATTA A ATGACCAA G A AGCCGCTCTGTGT620-IBSB.ONTEK. . . . . . . .C O12212324252627282D1 1 1 1 1 1 1ATGATA AAGCC AATTTTC TT ACCCGC CGCGCGC GCGGGCAGCCG CGGTTAAGGGCTGGGC T CACGA GTATAGTCAAATT GG CAG CCCGCG GGG CCCTGG GGTCGTTT CCCAGTGTTA CGTTACCCATCTACGG GG TGCATCGGGTCA GTGA GG GCGGGACAATCCG TCCAGATGTCCGA GAGGGACCTTCGTG CAGAA CACTG GA ACCCGCACGGTGC TCTGGG AGA AGGG CGCAAC CGGGGGCG AA AGACAGCTAACCCGGGAG TGCCCTACGGCCC CGC CGGCCGGTATTTCTTAAG CATGCG AG TCAG GCGCAT CATCAGTTGCGTCCGGCGG ACACCCTTG GG CTG CACG CGGCCGGATGTGC TCTCAACCCACCCCACTCATCCTTTGC GCTA ACCACCGCG GC TCAGTAAGGGTAATCAGA GGG GGCTTACACCGGGGGTA GGG C TGGCCG CCGGGG AGTGT TA GGGG GTA AATCGC TGGAGACGCCATG C CG GTG GTATC CTCCACCGG ATG GGTCTGGTAACTAGGGA GGGTGCGT TGGTGACAGCCTCACG GACG GTCGTACGGTGGGCGCACGAGCTCTGCAGGAA GGTA CTCCCTGGGCTA GTACCGTTAGGGCAGG GAGCTTTACGGTATTAGAT CTGGCTCATGTTTCA AGCC TATT CG GTGGCGAGGC AGGCCGCCCC TCA G CTTTATGACGGAGC CGATTG GC CGGAA GCCC T GTCCGCCAA CATTAG GCCTACACCAC CA AGCGGTG AACGTG AAA GGTATA GGTCAA GTCCCA GTCATA TGTAAGCA GGAATA GAGGCGTCG CACCGA GTACGGTTTGCCCCTG GGCCG CA GCCTCCCCGTA GA G CCTGTGA GCTATAGCTCCGA CACCGACGGG GAGTTTTCGCA ATCACAAAAGTTCCCG CGAG GCTGA ATAG AGAA AACGTGCCG GCGGTACG GTTA C AA GACCCTCCG AAGGG T G GGGTTGGACCCGTAAGCGTAAGCGAACGTCCCGCG GCGCAGGGGGGGCGTC CCTTGAACTGTA GATCG AGCCACTTACCCCTG TA G GCCACGATCCCC GGCCCGCCCGAA GCCGATCTGGGTCA AATACCG GA AAA ACCTACGCGCATCGAN GGCATATGAGG GAGA A GA TAACCGCACCGGTGOT CTTT CCC CGGGTCGTAC GCGATAATCCCTGTIATCAGCGG GGACATTGCGGGCAATCCCGCCGAGCCGCA AAA GGCCCCTGTCTGCTGCGCGTCTTATGTACACATGGTGCGCTCTCCTTCCTCACA CGTAG GTC G GAC G GCTG GC T CC T T TTATAGTGGCGCAC GTA GCAC CATGCG A GC C CA AC T T CACA ACILPGPTACCC AA ACGCGGCGGGCATACATACCGTGTT CGCTTGCA TTTAA CGT CTACCGTCG AGGACCGGG CTT CGTCCTTCGTCGCCPCCG GG CCT CGCTCA GGTTCACCGCCCTCCA CACGAACCTCGAG GCG4AG CTGCA GGCGCCCTCCCG AGTG AA TATT CTG 51TTTG GCG ACCTTTC A AGCGAC CA AAA CG GG ATGTAACGTTGCTC GATA G G AACA GCGGCTTACCCAGTCGGTAACGG GGACGTAACA AGCTCGACC GGGA ATCCG GA GCATGGGTA GTA ACATGCATT CTG GCACG GG TATCGGT GGG GA G ACCTGTCGTTGCG GTTATCACG AG CATCCACACGACTCGCTG TTCCTG CTGTA T GCTGCCGC TAGTCCGG AG ACCTTCAACCG TATCTAGTAG CAA ACAATCCA GCAG G GCCGA ACG G A GCA CACT CGG GTTG GCCCAGTTCGT TCGAC AAGCTTGC C TG GCCTAA A AAGACACCGTG AACTAA CGCGTACCCGGGGCCAGTCGGCA ATC CGGACGCTTGGCCG GAACGA AAA AG GTCTTCCTGTTA GCGCGGAGCAG AGGGGA GATTACCCCTACC TCGCCG GTGGCACAA GTCA GAGACATCTAG CGGTGGTACCGCTGCGCCAG GACGCTGCGGGATCTG GGTTTATCATTCCGTACA CGTGC ATTGGTA GTCGCGP- A G G ATA ACAC TGC C T T CA A A620-IBSB.ONTEK. . . . . . .C O92031323334353D1 1 1 1 1 1 1CATTGCC GCGC AT G G GAGGAGGT C C CGCCG CTGAGCG GCGAT TAAAGATGTTAGCGCG AGAAAGGGAT TC CGAACGGTAACATG ATAGT TTCCG T A G GGTTGG GG AGAGGGTCGCG ACAGGCGTAGGTCATCTGGCG TGCGA A GCTGGAGCCAA GGGAGCGACGGCCCCAGGAAGGCC GGAGCTC TGATAACTGGGGCAGGGG ACGCC TGTTTTA CACTCACCAG TTCCTCGGT GGTTA GGCCG GTC CGG TGAGA G GGGTCTCACCTAGGCTCGTGGGT TCGGAAACAGTCCCTGTGGCGCCCTTAGGT CTCAG GA A GCGGATGTTCGA A AGTCG G AAGTCCCGACG CG ATTGCTA CGACGGAGGTCTGC GTGTAGGCA GCG ATGTCCA T GGGGC CGGCA CCGTGCC AGCGACCCGCGG GG GACGCCGTCG AAG AGATGGTCAAGAAGATGCGGCTCCGACAGGTGTTCCTCT GGCGGCGAG CGGCATA CGGG TTAGCA CGGCCGAGGC CGCTC TGACG GTCCTA GTAGACTCCTCGC CTGATAGAGC C CCATCTCCAGGTAGGCTTGATG TCCGGTCCGAGTGCGAGA AG CCGGCGTACGATCGACCCTTAGGTTGTGCCA GCC C TTGCCTTTTTGCGA CATGACTGGCATAGCC CGTGGGCGCC ACGG G CTA AAGG CG GGCTGAACCACCCG G GGCGGGTGCTTTTCCGGCCCGGT GCCA GGC CTCCCGCCA TAGA CTG GTCGCA GA GGCCA GCAAACTGTTCCATCCG GACTG CGCCGACTCAG ACATAG G ACGGGTCA CGGGATCGGTTGCAC TTACGGTGCCTCGACCGTA CCGACGTCGCCTGAAAGGCAGTTGCGGGTACGACTAGGCCGAAGTAG AAGTGTGCTGACCTGGGG AGGACCCCCTCGCC CACGCCG TGTAGGCCGACTGTCTGTGATG ACCTGGGCTGGA GGAACAGGGCGGTTG AGGG ACGTCGATTCGTTTATGCCAG GATCCTCCA CG GGTG AGCTCACCGCAGGGGCCTCTGCC CAGCN AA GGTCTGCTGGTGCTTTAAAGGGGATTCGGGGACTAGG GCGCGGGCCCTA AAAGGAGCTOGIATCC CCA GGCTCGGCTGTGATGCCTG TGCGCACA CACCACCCGGGACCAGTCCAGTGTG CGTCG G GCTCG GCTGTTTTCGGTGGGCCCGGACGCTCGGTGG G GGGCGG TG TAAATGCGAATCGTGCTG G G A ATTG ATCG GACACTACCA ATGCGTTTAGTA GCTCATCCG GCCAAGGATCC G A GC C TG AC CILPGC GTC GCTGGT G AT GTPGA A G GGTATTATTA AG GA AA G AGCCGGCAGTGCTACCCGTCGGA GTTG T AA GA TGGACAA GCGCGC GTTGTG AGTP CTGTGCAGGATTGCA5CTTC GTACAG GTAC G GCCAA GACGCCGG A51GCGCGTTG ACACGG TTAGTGTGA GG GG GTG GTGCTGACCCGAC TG T ACTCGAGG GTCCCGGCGTGTG GTGTACGCGTAGACTTCATGCA GCGC CGCACGGGCA TGGCTTCA CTTTCG GG G AGCC CA AGTTCCTTTA GGCTCCGATTGGTC TG GG TGTGAG ACGGCTCCCCCATGCCCCATCCTACATTAACT CGTGAA GTAGTCAACACCACCGCGGG GCGGGG AA GCCCTTTGTGCGT ACAG A TCTGC TGGC CCAG CAGCCGGTA CCCA TGACG TTG GT TAGC TCT CCCCATCGAGTTAT CGC GGG GCCGATCAGTCGACCCTCG GGC TGGC TGCACGATCCTA A ACGAGCT CT AA TC CTGCATGCCGAACGCA C GGA GCTAC GCGCCT CCAGGTCTAGCCTGGCGTTTGCG ATGGPCCGG G TGTA ATACCAGCCTTCGAATATGAGTCCCC A AGTTT -T TATGC CA A G GC CGC C C C620-IBSB.ONTEK. . . . . .C O637383930414D1 1 1 1 1 1CTGCC CTTACTC GATCTCG CCCGA A GGAG CAC GGG A C CG GTAAGTTGTTTTCACCG GGCCA GGCCCCGGCACCGTTACCGTG CCGGCTTG CCGAATAG GTG GAAC TTCCG AACAG CA GACTCACTACGTGA CATAAGCG GCCGAC GGCGCGCT CCAAGCGCTCGCCCAAGT CCGA GTGCT CAACCCC CGCACGCCGGGGT GATAAGCACG AG GGGCCA GGCGC CGCCTATCC TGGC TTAACGAGGTTGAAAACCAC CTCACAGTGTAACACTATGCGGTCCGCCTCCTTCTCGCACGGAGTTGA GCACCCG GCACGTCCGGCCACACCCGAA CGGCTGCACG GCAGCGTCG CGGGCGGTCGATGTTTGTACGTGTACCCGGTCACACGAGG GGCGC ACCACACACTGCTTGACCGTTATTGA AGTTCTC ACAAC CTCTGTCTGATCCTG A GG TAGG A CCGCG AGCTGCGGA ATGCG AGCCGGGGGTGTCTCGGCCTTAATG GTACCCG TATGTTGATGCGG GGACACGGTGCG AG AGCTACTAG TCAGGCTCAGGCTGGGGGGCCCG GCGAAGCTCTCCC ACGTCGTGCG ACGTC CTCGTGCCG G AGG CTGCCGGATG CTGAGCGAG CGTGCCACCG GGTCG TCG A GGTGCGGCACG CACCG CTCAGCCGC CGACATCACCCGTTACCGAGG AGTACACACACCAGGTCCCCGTAAGCACGCG AGC CGGC CGCC CTGAGTCG GCATGCGAG AG G TACCAGCTGAGCGGTCCTAG GCAACCA CTAGGGGG CGG AGG TGCCACA CGGTTAAGGACTA GGGTGCC CTTCCCGCCCGCGATCA GCCAAG CGGCACGGAC TGCCG GGTAAATCCGGGGATGCATGCC TATTCATCCCCGAGCAAAG GTCTCTTACGCGTACCC A GGG TCCCGAAG GA GGGTACGGGCG G GGCAATA GCA CGGGCTG GACCCA G GTCGCTA G CTATCGCAAGGCCGTGGGCCTG G AACGGAGA GACAC CCAC TCTG CCAACGTGAG CTGCA CCGGCNCCCCCAACCG GGTA AGCCCGGAACGTTTTGCGGTCIC GGCTGTAGGTTTGGTCGGGGCGGGTGTA C CGCCCTCCAAA GACCCCGGA ATGGACCAAG CAOCTG AATCCCCGCTGGTCCACC TCCCAGGCTGGGTCGAAGGCTACGCCCAGTCTAA CGAGCATACAGCGACCGCGGCTGCTCA CGCCAG A ACATTTACTAGTACCTAC GGTGCCCCG GTGTA A GCCG ACG G GCCAGA G G GGTCGGCG GCCACCACGAGCGCC GC CG AC CA ACA GTILP CTG T GCCC CT AG TG GPCGTACGTCCGTGCG ACCTGGTAG CCGTTCGC TGTAGCCA AA CGCTCAGA GCTCA T AGCGGCCA GCGCPTCGCG CA T GG TGATGGTGTGCTGAG AAGCCAG A GCATATG GCGGG GTCGTGTCCGGATCGC 65CAGCTCACCGTT CTGTGG GTGGCTAAGAACG G GCA1CTCG A TTGTGTCA GCGCACC TCA GTACGG CCGCA A C ACACATACATG GCCG GGCCA G ACGTAATATCACG A GGGATCTTATTCGGCATA AACG ACCG GCTG GCA AA GTCTG ACACGACG ACCCCCTGA GCTGTCCG AGG AGTATCCAAGGCG ACG GGG TCT CGGCCGCCG GAAAGCG AGCG ACA ACCATG CAGCTCCGGTCTCGCTCCTCACG ATCCGCA GACACTCCGG AACA AACTACTCGCTA G G AAGAACTCTCGACCGC GGTT TCG CGCCG GGTGTCTG GTGTATCCCA GC CGTGG AAGCGGCAATCGGCATTTG G GGCA GTGTAGACGG G A ACAGCCTG GCA GCAGCCTCGAG GCACTA GA CAG GGCTATT CTAGCATG C CCA A CCTCTCGGTCATGT CTT TGGCA CGTA CG CGGTCCCA ACCCC CACAAC GGGA CT CAG AAA GTCCCCGTCA CAG AGCGGCTTCCCCCCACGACCCGCCATCCCA G G ACCGC CTAC TC A CC ACAC GAAP-CGC CGCG GC CG ACG GC CG G620-IBSB.ONTEK. . . . . . .C O24344454647484D1 1 1 1 1 1 1CTG G ACCCTTA G GC GGGACCGCTTCCAGACTT ATTTAAATTG GACGTGA AACTTGCGGGGG AACA G GGCAA CG GATCTTTTACAAGTG CGGGGATTTTTGGCGGCGCCCTTAATTCATTAAAA CCGA ACTTAGAAATTCG GCACTTTA AGGTG CGCT TGGGG CT TCTGATTAGGACTC AGGCC CGAA CGTTTTCTTCGTGGAACTTT CTGCGCTCT TTGCCGTCTCCTAAGCCCTA GTG CTAGTA GATTA GCCCGACCTCGCTCC GGTATCTAACAT CCGATAATTGTCAGGCCTGCCCACGCCGA CGAGAAC TTATTATTCCAA AG ACTGTCCCGCTCGGT C TTACACACGCCC TGTAACCCAACGG ACGCGCGCCG GGCA G GGTAGAGTGGGGAGTGAAGTGCAGGAGCTTACCGG G TCCGCTTTACTGTAA ATGACCCCA T AGCA TTGTG ATAAGAGACG GATC TGGCAG CCGGTT CGCGGGTTCTGATCT TTTAT ACG A GGTCAGCGGGGCCAAAATAGATTTTCGGG G GATCAGTAACTTGTTGGACAAGTGC CTTG GTGGAC CGGGGCTG AGTGTGCATTGCGTTA G GTGA GTG TCGCC CACTGTCCATCTCCG AG G GGCCTTTAGGCATC TGCTCACTCGGCCGA TG TCGGTTCCTAGTCTTGACGCCGTGTCAA CAA ACTTCTG A GT TAGTCCA AGTA ACCCTC TCAGTCCA A G ACGGGACTCG A CGCTCAAGGTGCGCG CTG GGAGA CGAGAATTGTCAATTAACA AAT TAATTA ACGG CTCAGAGAACACCATGTGTCCGACTCGTCATATAGG GCGAGCA GTTTCTATG GCGTAAAATG G GACGCG GAGTG ACCTTG AA ACTAAGAA GA CTCCAACG CG GAGCACCGCGGG C GTCACTG TTTGTGGAACGAAATCTTTGCTCAATTTTGCCTCCTCCGTNC CAOTG GTA GC TTCA TCGCG AGGCTTG TGTGTGGGCTTGGTCTAG GGTCACGCACCGAGGACGIACA AGTCCACCTCTA GCCCATCTCGCTTTCAA ACA GTTCTGTTTTG TGGACACC ACCGGACGTTA GCA GGAGTTCAGGGTGTT GCGTCTTAT TATGAATATGGCCTTCTTAACA ACGAC TGCGGTTGATGCAAGAGCTA AACCTG ACCGTACGTTTAG GG G ACTGTG ACG G GGTTCG GCCCAGCACTCTTTATACCGCT CG A G G A GTA G A GTGILPGAGC G CCTACAGPA AGA GC TTGCGTGTGTCCTGTCTTG AACGTACTACCTCCAACG GG CATGACCTCTAGCP CAGCG ACTCGCTG ACTGCGT CTAACTTA CGGT 7CACTTCACACACTG TGCGG GTGTCTAGTGGG C5CACG G GGTGTTTA TAGTTCT 1ATTTTG ACCG CACGACGTG TTGTAA ATA A GCGACTGACTTTG AGCG GG AGGCTAGTTTCGG C AACGTGAAA GGCCGGCGA GTGGA GC AG GTGCCA AAGTGGG GTATAACT CTATACCGTGCG G ACGCGTACTCA A AGA GACGCATACCGCCGACTGCCTTG TG ACCAGA AATAG GA TCG ACCCA ACAAATAGGCGCGGTTCTTT CATA AACGG GAGACGTG GAGCCTA AAT TG GCTG CCCCGGCAC TATCCG CCTTGATGTGT CAAG GTGCCTCGTGTA GGCC G AAA AAAGCAGCGTGAA GCCCATTTGAC AG GATGTGCGGACTTCA CGCCACTTTCG A CCAGTTA G GTTAGTCTGTACCCTAA A GCTG CTTCGTG A TGGGGTAT CG AGATAG GGGCGT TCGTGT TCCTGCA CGTTGCTATGGCGT ACPCT-TA GTTGCCGACG G GACA ATA A ATGAC620-IBSB.ONTEK. . . . . . .C O94051525354555D1 1 1 1 1 1 1GACGGACGCGTTGAACTG G ATG ACTTC TAA ACTTTCCGGTCGA C GG GAAAGCTGGATACA GGGATCTGATAGGA GT CAACCGCTCGCT CAC ACCCTTCTCAA AAATGCTC CAGCCAGGCCAA CGACG CA ATCTTA ATGG GAA CCGG AG CCAGT CACGGCCTCGTGAATCGGGG C GAGCCCCGCTCGCTGGTGCGGGCTCGGCA ATGTTTCAGTGATCG ATCAG A AGATG GCGGTGG TAGTCCTC AATCGTGGG TGAGTCACGGTGTAAAACCGCTG GGCG GGTCCCCGCTGCC GTAGTGCCACGTCATCGT CA ACACACAAA AGCG AACGTAG GCGGGCTT TGA CCGTTCGCAATTACCACTTATTAAACG G GGTTA CGAAGGA AAGCTATCCG AAGTTGAGTTCT CGATC CTCGCAGGCC TACCAATGGCCG AG G GGTACGACTGACCTTG GC CGGCCC CGTGCT TTCC CA CTTTGGGTCGG TAGTCCC AA GGTCCATAAGGCACTGGGTCTACTCCGTGCGG T GGCCGTCG TAGTCTTCTGAGCG GGCG T AACATGA A CGAAGAGTCACGG GGCAGTGCGGGATCGGCGTAG TAA CCCGG AG TTCGCCTGTCGG GGGAGTTGACACTCGTTTG GTCG AGCTA GA CT ACCCCAAGCATAG GTCTCCGT...

Claims

DOCKET NO. BSBI-026-PCT PCT APPLICATION We claim:

1. A method comprising: extracting analyte RNA comprising mRNA and long non- coding RNA from a liquid sample and determining whether the analyte RNA comprises one or more variant mRNA and / or one or more variant long non-coding RNA, wherein the sample is from a subject.

2. The method of claim 1, wherein the one or more variant mRNA and / or one or more long non-coding RNA are biomarkers indicative of a disease or disorder state.

3. The method of claim 1 or 2, wherein the determining comprises obtaining sequence information for the analyte RNA and comparing the sequence information to variant mRNA and variant non-coding mRNA sequences.

4. The method of claim 1 or 2 further comprising producing DNA from the extracted analyte RNA, wherein the DNA comprises one or more DNA molecules, each having a respective DNA sequence and the determining comprises identifying whether each respective DNA sequence comprises a biomarker sequence corresponding to the one or more variant mRNA and / or the one or more long non-coding RNA.

5. The method of claim 4, wherein the determining comprises sequencing the DNA and comparing the respective DNA sequences to variant mRNA and variant non-coding mRNA sequences.

6. The method of any of claims 1–5, wherein the subject is a mammal.

7. The method of any of claims 1–5, wherein the subject is a human.

8. The method of any one of claims 1–7, wherein the liquid sample is blood.

9. The method of claim 8 further comprising obtaining extracellular vesicles from the liquid sample and wherein the step of extracting mRNA comprises extracting the mRNA from the extracellular vesicles.DOCKET NO. BSBI-026-PCT PCT APPLICATION 10. The method of claim 9 further comprising preparing plasma from the blood and wherein the step of obtaining extracellular vesicles is performed on the plasma.

11. The method of claim 10, wherein the step of preparing plasma comprises adding an anti-coagulant to the blood.

12. The method of claim 11, wherein the anti-coagulant is one or more selected from EDTA, ACD, Sodium-Citrate, and Sodium Heparin.

13. The method of any one of claims 1–12, wherein the one or more variant mRNA and / or one or more long non-coding RNA comprise one or more variant selected from Variant Nos.1–1061 from Tables 7–9, and 11 and variants of Tables 12–14.

14. The method of any one of claims 3–13, wherein the step of producing DNA from the analyte RNA comprises preparing DNA from the analyte RNA by reverse transcribing the analyte RNA.

15. The method of claim 14, wherein the reverse transcribing comprises exposing the analyte RNA to one or more primer specific for the one or more variant mRNA and / or one or more long non-coding RNA, reverse transcriptase, and deoxynucleotides.

16. The method of claim 15, wherein one or more primer specific for the one or more variant mRNA and / or one or more long non-coding RNA is selected from Tables 10A and 10B.

17. The method of any one of claims claim 14–16 further comprising conducting PCR on the DNA with one or more set of forward and reverse primers specific for one or more variant mRNA and / or one or more long non-coding RNA.

18. The method of claim 16, wherein the one or more set of forward and reverse primers specific for one or more variant mRNA and / or one or more long non-coding RNA is selected from Tables 10A and 10B.DOCKET NO. BSBI-026-PCT PCT APPLICATION 19. The method of any one of claims 1–18, wherein the one or more variant mRNA and / or one or more long non-coding RNA are indicative of HCC and comprise one or more of Variant Nos.1–255 from Tables 7–9, and the disease or disorder state is HCC.

20. The method of any one of claims 1, wherein the one or more variant mRNA and / or one or more long non-coding RNA are indicative of HCC and comprise one or more of Variant Nos.1–255 from Tables 7–9, and the disease or disorder state is HCC.

21. The method of any one of claims 1–18, wherein the one or more variant mRNA and / or one or more long non-coding RNA are indicative of early-stage HCC and comprise one or more of Variant Nos.310, 326, 328, 329, 332, 333, 338, 340, 343, 350, 355, 357, 359, 362, 366, 367, 368, 369, 370, 371, 374, 379, 380–386, 391–395, 397–399, 400, 402, 404, 405, 407– 412, 415–418, 420–425, 431–433, 436–440, 448, 451, 474, 477, 479, 481, 482, 490, 491, 495, 508–510, 512, 515, 522, 527, 532, 533, 535, 543, 551, 554, 558, 575, 581, 582, 585, 586, 590, 605, 606, 614, 616, 640, 641, 643, 644, 647, 650, 660, 661, 664, 671–673, 675, 676, 679, 694– 696, 705, 708, 709, 715, 835–840, and 847–971 from Tables 7–9, and the disease or disorder state is early-stage HCC.

22. The method of claim 1, wherein the one or more variant mRNA and / or one or more long non-coding RNA are indicative of early-stage HCC and comprise one or more of Variant Nos.310, 326, 328, 329, 332, 333, 338, 340, 343, 350, 355, 357, 359, 362, 366, 367, 368, 369, 370, 371, 374, 379, 380–386, 391–395, 397–399, 400, 402, 404, 405, 407–412, 415–418, 420– 425, 431–433, 436–440, 448, 451, 474, 477, 479, 481, 482, 490, 491, 495, 508–510, 512, 515, 522, 527, 532, 533, 535, 543, 551, 554, 558, 575, 581, 582, 585, 586, 590, 605, 606, 614, 616, 640, 641, 643, 644, 647, 650, 660, 661, 664, 671–673, 675, 676, 679, 694–696, 705, 708, 709, 715, 835–840, and 847–971 from Tables 7–9, and the disease or disorder state is early-stage HCC..

23. The method of any one of claims 1–18, wherein the one or more variant mRNA and / or one or more long non-coding RNA are indicative of late-stage HCC and comprise one or more of Variant Nos.324, 330, 331, 337, 342, 345, 347, 349, 352–354, 356, 358, 360, 361, 363, 364, 365, 372, 373, 375–378, 387–390, 396, 401, 403, 406, 413, 414, 419, 426, 427–430, 434, 435, 441–445, 452, 455, 457, 458, 460, 464, 465, 470, 475, 476, 483, 485–488, 494, 501, 504, 514, 517, 520, 521, 524, 526, 528, 531, 536, 540–542, 545, 547, 549, 553, 555, 556, 561,DOCKET NO. BSBI-026-PCT PCT APPLICATION 563, 571–573, 576–580, 583, 584, 587, 592, 595, 597, 599, 602, 604, 607–609, 612, 615, 619, 620, 635, 636, 639, 649, 652, 654, 656, 658, 667, 674, 677, 678, 689–692, 697, 698, 700–702, 704, 706, 707, 710, 711, 716–834, and 841from Tables 7–9, and the disease or disorder state is late-stage HCC.

24. The method of claim 1, wherein the one or more variant mRNA and / or one or more long non-coding RNA are indicative of late-stage HCC and comprise one or more of Variant Nos.324, 330, 331, 337, 342, 345, 347, 349, 352–354, 356, 358, 360, 361, 363, 364, 365, 372, 373, 375–378, 387–390, 396, 401, 403, 406, 413, 414, 419, 426, 427–430, 434, 435, 441–445, 452, 455, 457, 458, 460, 464, 465, 470, 475, 476, 483, 485–488, 494, 501, 504, 514, 517, 520, 521, 524, 526, 528, 531, 536, 540–542, 545, 547, 549, 553, 555, 556, 561, 563, 571–573, 576– 580, 583, 584, 587, 592, 595, 597, 599, 602, 604, 607–609, 612, 615, 619, 620, 635, 636, 639, 649, 652, 654, 656, 658, 667, 674, 677, 678, 689–692, 697, 698, 700–702, 704, 706, 707, 710, 711, 716–834, and 841from Tables 7–9, and the disease or disorder state is late-stage HCC.

25. The method of any one of claims 1–18, wherein the one or more variant mRNA and / or one or more long non-coding RNA are associated with tumor tissues but are not detectable in normal liver tissue, and the disease or disorder state is presence of tumor tissue in the subject.

26. The method of claim 1, wherein the one or more variant mRNA and / or one or more long non-coding RNA are associated with tumor tissues but are not detectable in normal liver tissue, and the disease or disorder state is presence of tumor tissue in the subject. 27 The method of any one of claims 1–18, wherein the one or more variant mRNA and / or one or more variant long non-coding RNA comprise transcripts of EPB41, M6PR, ARHGAP5, PRDX6, FASN, 346 ARCN1, SENP7, ECI1, IST1, ACOX1, or EIF3G variants, and the disease or disorder state is HCC.

28. The method of claim 1, wherein the one or more variant mRNA and / or one or more long non-coding RNA comprise transcripts of EPB41, M6PR, ARHGAP5, PRDX6, FASN, 346 ARCN1, SENP7, ECI1, IST1, ACOX1, or EIF3G variants, and the disease or disorder state is HCC.DOCKET NO. BSBI-026-PCT PCT APPLICATION 29. The method of any one of claims 1–18, wherein the one or more variant mRNA and / or one or more long non-coding RNA are indicative of high-risk early stage HCC, and the disease or disorder state is high-risk early stage HCC.

30. The method of claim 1, wherein the one or more variant mRNA and / or one or more long non-coding RNA are indicative of high-risk early stage HCC, and the disease or disorder state is high-risk early stage HCC.

31. The method of any one of claims 1–18, wherein the one or more variant mRNA and / or one or more long non-coding RNA are indicative of HCC and comprise one or more of Variant Nos. 298–309, 311–323, 325, 327, 334–336, 339, 341, 344, 346, 348, 351, 446, 447, 449, 450, 453, 454, 456, 459, 461–463, 466–469, 471–473, 478, 480, 484, 489, 492, 493, 496– 500, 502, 503, 505–507, 511, 513, 516, 518, 519, 523, 534, 537–539, 624–634, 637, 638, 680– 688, 693, 699, 703, 712–714, and 842–846 from Tables 7–9, and the disease or disorder state is HCC.

32. The method of claim 1, wherein the one or more variant mRNA and / or one or more long non-coding RNA are indicative of HCC and comprise one or more of Variant Nos. 298– 309, 311–323, 325, 327, 334–336, 339, 341, 344, 346, 348, 351, 446, 447, 449, 450, 453, 454, 456, 459, 461–463, 466–469, 471–473, 478, 480, 484, 489, 492, 493, 496–500, 502, 503, 505– 507, 511, 513, 516, 518, 519, 523, 534, 537–539, 624–634, 637, 638, 680–688, 693, 699, 703, 712–714, and 842–846 from Tables 7–9, and the disease or disorder state is HCC.

33. The method of any one of claims 1–18, wherein the one or more variant mRNA and / or one or more long non-coding RNA are indicative of cancer and comprise one or more of selected from Variant Nos. 1002–1061 (Table 11) and variants of Tables 12–14, and the disease or disorder state is cancer.

34. The method of claim 1, wherein the one or more variant mRNA and / or one or more long non-coding RNA are indicative of cancer and comprise one or more variant selected from Variant Nos. 1002–1061 (Table 11) and variants of Tables 12–14, and the disease or disorder state is cancer.DOCKET NO. BSBI-026-PCT PCT APPLICATION 35. A method of diagnosing a disease or disorder comprising extracting analyte RNA comprising mRNA and long non-coding RNA from a liquid sample from a subject, determining whether the analyte RNA comprises one or more variant mRNA and / or one or more variant long non-coding RNA, wherein the one or more variant mRNA and / or one or more long non- coding RNA are biomarkers indicative of a disease or disorder state, the method further comprising identifying the subject as having the disease or disorder upon determining the analyte RNA comprises the one or more variant mRNA and / or the one or more variant long non-coding RNA.

36. The method of claim 35 further comprising obtaining the liquid sample from the subject.

37. The method of claim 35 or 36, wherein the determining comprises obtaining sequence information for the analyte RNA and comparing the sequence information to variant mRNA and variant non-coding mRNA sequences.

38. The method of claim 35 or 36 further comprising producing DNA from the extracted analyte RNA, wherein the DNA comprises one or more DNA molecules, each having a respective DNA sequence and the determining comprises identifying whether each respective DNA sequence comprises a biomarker sequence corresponding to the one or more variant mRNA and / or tone or more variant long non-coding RNA.

39. The method of claim 38, wherein the determining comprises sequencing the DNA and comparing the respective DNA sequences to variant mRNA and variant non-coding mRNA sequences.

40. The method of any one of claims 35–39, wherein the subject is a mammal.

41. The method of any one of claims 35–39, wherein the subject is a human.

42. The method of any one of claims 35–39, wherein the liquid sample is blood.DOCKET NO. BSBI-026-PCT PCT APPLICATION 43. The method of claim 42 further comprising obtaining extracellular vesicles from the liquid sample and wherein the step of extracting mRNA comprises extracting the mRNA from the extracellular vesicles.

44. The method of claim 43 further comprising preparing plasma from the blood and wherein the step of obtaining extracellular vesicles is performed on the plasma.

45. The method of claim 44, wherein the step of preparing plasma comprises adding an anti-coagulant to the blood.

46. The method of claim 45, wherein the anti-coagulant is one or more selected from EDTA, ACD, Sodium-Citrate, and Sodium Heparin.

47. The method of any one of claims 35–46, wherein the one or more variant mRNA and / or one or more long non-coding RNA comprise one or more variant selected from Variant Nos.1–1061 from Tables 7–9, and 11 and variants of Tables 12–14.

48. The method of claim 47, wherein the step of producing cDNA from the extracted mRNA comprises preparing DNA from the mRNA by reverse transcribing the mRNA.

49. The method of claim 48, wherein the reverse transcribing comprises exposing the mRNA to one or more primer specific for the one or more variant mRNA and / or one or more long non-coding RNA, reverse transcriptase, and deoxynucleotides.

50. The method of claim 41, wherein one or more primer specific for the one or more variant mRNA and / or one or more long non-coding RNA is selected from Tables 10A and 10B.

51. The method of any one of claims claim 40–42 further comprising conducting PCR on the DNA with one or more set of forward and reverse primers specific for the one or more variant mRNA and / or one or more long non-coding RNA.

52. The method of claim 50, wherein the one or more set of forward and reverse primers specific for one or more variant mRNA and / or one or more long non-coding RNA is selected from Tables 10A and 10B.DOCKET NO. BSBI-026-PCT PCT APPLICATION 53. The method of any one of claims 35–52, wherein the one or more variant mRNA and / or one or more long non-coding RNA are indicative of HCC and comprise one or more of Variant Nos.1–285 from Tables 7–9, and the disease or disorder state is HCC.

54. The method of any one of claims 35–52, wherein the one or more variant mRNA and / or one or more long non-coding RNA are indicative of early-stage HCC and comprise one or more of Variant Nos.310, 326, 328, 329, 332, 333, 338, 340, 343, 350, 355, 357, 359, 362, 366, 367, 368, 369, 370, 371, 374, 379, 380–386, 391–395, 397–399, 400, 402, 404, 405, 407– 412, 415–418, 420–425, 431–433, 436–440, 448, 451, 474, 477, 479, 481, 482, 490, 491, 495, 508–510, 512, 515, 522, 527, 532, 533, 535, 543, 551, 554, 558, 575, 581, 582, 585, 586, 590, 605, 606, 614, 616, 640, 641, 643, 644, 647, 650, 660, 661, 664, 671–673, 675, 676, 679, 694– 696, 705, 708, 709, 715, 835–840, and 847–971from Tables 7–9, and the disease or disorder state is early-stage HCC.

55. The method of any one of claims 35–52, wherein the one or more variant mRNA and / or one or more long non-coding RNA are indicative of late-stage HCC and comprise one or more of Variant Nos.324, 330, 331, 337, 342, 345, 347, 349, 352–354, 356, 358, 360, 361, 363, 364, 365, 372, 373, 375–378, 387–390, 396, 401, 403, 406, 413, 414, 419, 426, 427–430, 434, 435, 441–445, 452, 455, 457, 458, 460, 464, 465, 470, 475, 476, 483, 485–488, 494, 501, 504, 514, 517, 520, 521, 524, 526, 528, 531, 536, 540–542, 545, 547, 549, 553, 555, 556, 561, 563, 571–573, 576–580, 583, 584, 587, 592, 595, 597, 599, 602, 604, 607–609, 612, 615, 619, 620, 635, 636, 639, 649, 652, 654, 656, 658, 667, 674, 677, 678, 689–692, 697, 698, 700–702, 704, 706, 707, 710, 711, 716–834, and 841 from Tables 7–9, and the disease or disorder state is late-stage HCC.

56. The method of any one of claims 35–52, wherein the one or more variant mRNA and / or one or more long non-coding RNA are associated with tumor tissues but are not detectable in normal liver tissue, and the disease or disorder state is presence of tumor tissue.

57. The method of any one of claims 35–52, wherein the one or more variant mRNA and / or one or more long non-coding RNA comprise transcripts of EPB41, M6PR, ARHGAP5, PRDX6, FASN, 346 ARCN1, SENP7, ECI1, IST1, ACOX1, or EIF3G variants, and the disease or disorder state is HCC.DOCKET NO. BSBI-026-PCT PCT APPLICATION 58. The method of any one of claims 35–52, wherein the one or more variant mRNA and / or one or more long non-coding RNA are indicative of high-risk early stage HCC, and the disease or disorder state is high-risk early stage HCC.

59. The method of any one of claims 35–52, wherein the one or more variant mRNA and / or one or more long non-coding RNA are indicative of HCC and comprise one or more of Variant Nos. 298–309, 311–323, 325, 327, 334–336, 339, 341, 344, 346, 348, 351, 446, 447, 449, 450, 453, 454, 456, 459, 461–463, 466–469, 471–473, 478, 480, 484, 489, 492, 493, 496– 500, 502, 503, 505–507, 511, 513, 516, 518, 519, 523, 534, 537–539, 624–634, 637, 638, 680– 688, 693, 699, 703, 712–714, and 842–846 from Tables 7–9, and the disease or disorder state is HCC.

60. The method of any one of claims 35–52, wherein the one or more variant mRNA and / or one or more long non-coding RNA are indicative of cancer and comprise one or more variant selected from Variant Nos.1002–1061 (Table 11) and variants in Tables 12–14, and the disease or disorder state is cancer.

61. A method of tracking disease or disorder progression comprising conducting the method of any one of claims 1–60 on a liquid sample from a subject having been diagnosed with the disease or disorder or under treatment for the disease or disorder, and the disease or disorder state is cancer.

62. The method of claim 61 further comprising detecting an amount of the mRNA comprising one or more disease biomarker sequence corresponding to the one or more variant messenger RNA sequence in the liquid sample.

63. The method of tracking disease or disorder progression of claim 62 comprising repeating the method at two or more times.

64. The method of claim 62, wherein the two or more times are separated by about one day, about one week, about one month, about one year, or about two years.DOCKET NO. BSBI-026-PCT PCT APPLICATION 65. The method of claims 62 comprising conducting the method before a disease or disorder treatment is carried out on the subject.

66. The method of claim 65 further comprising conducting the method after a disease or disorder treatment is carried out on the subject.

67. A method of treatment comprising conducting the method of any one of claims 1– 34 and administering a treatment matching the disease or disorder.

68. A method of treatment comprising conducting the method of any one of claims 35– 60 and upon a determination that the subject has the disease or disorder administering a treatment matching the diagnosis.

69. A composition comprising a liquid sample from a subject and any one or more primer selected from Tables 10A and 10B.

70. A composition comprising a plasma-derived extracellular vesicle and one or more primer selected from Tables 10A and 10B.

71. The composition of claim 69 or 70 further comprising one or more of reverse transcriptase deoxynucleotides, and a heat-stable DNA polymerase.

72. The composition of any one of claims 69–71 further comprising an anticoagulant.

73. A method of preparing a sample comprising precipitating extracellular vesicles from a liquid sample from a subject.

74. The method of claim 73, wherein the liquid sample is blood.

75. The method of claim 74, wherein the step of precipitating is preceded by preparing plasma from the blood and the step of precipitating is conducted on the plasma.

76. The method of claim 75, wherein the step of preparing plasma comprises adding an anticoagulant to the blood.DOCKET NO. BSBI-026-PCT PCT APPLICATION 77. The method of claim 76, wherein the anti-coagulant is one or more selected from EDTA, ACD, Sodium-Citrate, and Sodium Heparin.

78. The method of any one of claims 73–77 further comprising adding one or more primer selected from Tables 10A and 10B to the sample.

79. A method for detecting an internal disease or disorder comprising (a) obtaining a biological sample from a subject; (b) isolating mRNA-derived transcripts that are normal or containing mutations, polymorphisms or post-translational modifications from the sample; (c) identifying the disease-associated mutations and (d) stratifying the subject's disease risk based on the presence of said mutations.

80. The method of claim 79, wherein the internal disease or disorder is cancer.

81. The method of claim 80 wherein the cancer is liver cancer.

82. The method of claim 81 wherein the liver cancer liver is hepatocellular carcinoma.

83. The method of claim 81 wherein the liver cancer is cholangiocarcinoma.

84. A method comprising detection and or quantification of messenger Ribonucleic Acids (mRNA) or fragments thereof, or any group of mRNAs or groups of mRNA fragments in the blood for the purpose of disease detection as in claims 69–73, disease risk stratification of any disease, disease risk stratification of cancer, disease risk stratification of liver cancer, disease risk stratification of hepatocellular carcinoma, or disease risk stratification of cholangiocarcinoma.

85. The method of any one of claims 1–66 for the purpose of disease detection, disease risk stratification of any disease, disease risk stratification of cancer, disease risk stratification of liver cancer, disease risk stratification of hepatocellular carcinoma, or disease risk stratification of cholangiocarcinoma.DOCKET NO. BSBI-026-PCT PCT APPLICATION 86. A kit comprising: a plurality of containers, wherein at least one of the plurality of containers contains a primer complementary to a first nucleic acid sequence proximal to an mRNA or long non-coding RNA variant position, and wherein the primer is a sequencing primer configured to sequence a second nucleic acid sequence comprising the mRNA or long non-coding RNA variant position, or wherein the primer is a first PCR primer configured to amplify the second nucleic acid sequence comprising the mRNA or long non-coding RNA variant position.

87. The kit of claim 86, wherein the primer is the first PCR primer and wherein at least one of the plurality of containers contains a second PCR primer, and wherein the first PCR primer is a forward primer and the second PCR is a reverse primer, and the first and second primers are a configured to amplify the second nucleic acid sequence comprising the mRNA or long non-coding RNA variant position.

88. The kit of claim 87, wherein the first PCR primer and the second PCR primer are selected from any PCR primer herein such that the first PCR primer and second PCR primer are matching forward and reverse primers configured to amplify the second nucleic acid sequence comprising the mRNA or long non-coding RNA variant position.

89. The kit of claim 86, wherein the sequencing primer is selected from a sequencing primer herein.

90. The kit of any one of claims 86–89, wherein the variant is a variant herein.

91. The kit of any one of claims 86–90, wherein the variant is a variant of Table 7–9 or 11––14.

92. The kit of any one of claims 86–91 further comprising an extracellular vesicle precipitant.

93. The kit of any one of claims 86–92 further comprising instructions to determine whether a liquid sample from a subject comprises an mRNA or long non-coding RNA comprising the mRNA or long non-coding RNA variant position.DOCKET NO. BSBI-026-PCT PCT APPLICATION 94. A kit comprising: a plurality of containers, wherein at least one of the plurality of containers contains one or more primers complementary to one or more first nucleic acid sequence proximal to respective one of mRNA or long non-coding RNA variant position selected from a plurality of mRNA or long non-coding RNA variant positions, and wherein at least one of the primers is a sequencing primer configured to sequence a respective second nucleic acid sequence comprising the mRNA or long non-coding RNA variant position, and / or wherein at least two of the one or more primers comprise a forward PCR primer and a reverse PCR primer configured to amplify a respective second nucleic acid sequence comprising the mRNA or long non-coding RNA variant position.

95. The kit of claim 94, wherein the forward PCR primer and the reverse PCR primer are selected from any PCR primer herein such that the forward PCR primer and reverse PCR primer are matching forward and reverse primers configured to amplify a respective second nucleic acid sequence.

96. The kit of claim 94, wherein at least four of the one or more primers comprise a plurality of forward PCR primers and a plurality of reverse PCR primers matched in respective pairs of forward and reverse PCR primers, each respective pair of forward and reverse PCR primers configured to amplify a respective second nucleic acid sequence. 97.The kit of claim 96, wherein each respective pair of forward and reverse PCR primers are selected from matching PCR primers herein.

98. The kit of claim 94, wherein each sequencing primer is selected from any sequencing primer herein.

99. The kit of any one of claims 94–98, wherein the plurality of mRNA or long non- coding RNA variant positions comprise two or more variants herein.

100. The kit of any one of claims 94–99, wherein the plurality of mRNA or long non- coding RNA variant positions comprise two or more variants of Tables 7–9, 11–13, 15, or 16.

101. The kit of any one of claims 94–100 further comprising an extracellular vesicle precipitant.DOCKET NO. BSBI-026-PCT PCT APPLICATION 102. The kit of any one of claims 94–101 further comprising instructions to determine whether a liquid sample from a subject comprises an mRNA or long non-coding RNA comprising the mRNA or long non-coding RNA variant position.

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