Methods and systems for preparing a sequencing library

Abstract

Described herein is a method for preparing a sequencing library. The method can comprise: ligating one or more adapters to nucleic acid molecules (e.g., DNA or RNA) in a ligation buffer; binding the nucleic acid molecules to a plurality of beads in the ligation buffer; separating from the ligation buffer, the plurality of beads bound to the nucleic acid molecules; suspending the plurality of beads in a solution comprising alcohol; and converting, using a bisulfite reaction, unmethylated cytosines in the nucleic acid molecules to uracil, to generate converted nucleic acid molecules.

Description

METHODS AND SYSTEMS FOR PREPARING A SEQUENCING LIBRARYCROSS-REFERENCE TO RELATED APPLICATION

[0001] This application claims the priority benefit of United States Provisional Patent Application Serial No. 63 / 609,017, filed December 12, 2023, the contents of which are incorporated herein by reference in its entirety.FIELD OF THE INVENTION

[0002] The present disclosure relates generally to methods and systems for preparing a sequencing library for methyl-sequencing, and more specifically, to methods and systems for preparing a sequencing library for methyl-sequencing via bisulfite conversion.BACKGROUND

[0003] Identifying the methylation patterns of nucleotide sequences has become increasingly important for diagnosing, monitoring, or determining the appropriate treatment for a disease, such as cancer. Previous methods for preparing sequencing libraries for methyl-sequencing via bisulfite conversion can often result in low yields of DNA and high dropouts of GC-rich regions. Improved methods are needed for preparing methyl-sequencing libraries via bisulfite conversion. Such methods would improve the overall efficiency and quality control of nucleic acid methyl-sequencing and analysis of biological samples.BRIEF SUMMARY OF THE INVENTION

[0004] Disclosed herein are methods and systems for preparing a sequencing library for methyl-sequencing via bisulfite conversion. The methods and systems comprise suspending a plurality of beads in a solution comprising alcohol. Previous protocols for preparing sequencing libraries using solid-phase beads state that the beads should not be disturbed when adding alcohol to the beads. See, for example, the user manual for NEBNext® Ultra™ II DNA Library Prep Kit for Illumina (NEB #E7645S / L, #37103S / L) by New England Biolabs (Ipswitch, MA). As further discussed herein, it has now been shown that suspending the plurality of beads in alcohol both increases the overall yield and reduces the dropout of GC-rich nucleic acid fragments, when compared to not disturbing the beads in the presence of alcohol. This sequencing library preparation protocol is in direct contrast to established protocols, which specifically instruct that disturbing the beads should be avoid. The increasein nucleic acid molecule yield and reduction in dropout of GC-rich fragments is shown for both genomic DNA and cell-free DNA (cfDNA). Further, the methods discussed herein may be applied to other nucleic acid molecules, such as RNA molecules. The reduction in dropout of GC-rich fragments is of special importance for preparing methyl- sequencing libraries via bisulfite conversion because the methylation of nucleic acid molecules (e.g., DNA) happens almost exclusively at CpG nucleotides. The methods disclosed herein may prove especially useful for the bisulfite conversion of cfDNA because of the inherently low amounts of cfDNA present in subjects.

[0005] In some aspects, disclosed herein is a method of preparing a sequencing library, comprising ligating one or more adapters to nucleic acid molecules (e.g., DNA or RNA) in a ligation buffer; binding the nucleic acid molecules to a plurality of beads in the ligation buffer; separating from the ligation buffer, the plurality of beads bound to the nucleic acid molecules; suspending the plurality of beads in a solution comprising alcohol; and converting, using a bisulfite reaction, unmethylated cytosines in the nucleic acid molecules to uracil, to generate converted nucleic acid molecules. In some embodiments, the nucleic acid molecules are cell- free DNA (cfDNA) molecules. In some embodiments, the nucleic acid molecules are RNA molecules.

[0006] In any of the embodiments herein, the method can comprise fractioning the nucleic acid molecules based on size. In any of the embodiments herein, the fractioning occurs after the ligating, and before the binding of the nucleic acid molecules to a plurality of beads in the ligation buffer. In any of the embodiments herein, the fractioning can comprise combining a second plurality of beads with the nucleic acid molecules, thereby allowing a first portion of the nucleic acid molecules to bind to the second plurality of beads; separating the second plurality of beads from a second portion of the nucleic acid molecules; and discarding the second plurality of beads and the first portion of the nucleic acid molecules.

[0007] In any of the embodiments herein, the converting can occur before the ligating. In any of the embodiments herein, the converting can occur after the suspending. In any of the embodiments herein, the method can comprise denaturing the converted nucleic acid molecules. In any of the embodiments herein, the method can comprise amplifying the converted nucleic acid molecules. In some embodiments, the amplifying can comprise performing a polymerase chain reaction (PCR) amplification or an isothermal amplification.

[0008] In any of the embodiments herein, the method can comprise blunting the ends of the nucleic acid molecules. In any of the embodiments herein, the method can comprisefragmenting the nucleic acid molecules. In some embodiments, fragmenting the nucleic acid molecules can comprise shearing the nucleic acid molecules. In some embodiments, shearing the nucleic acid molecules can comprise sonicating the nucleic acid molecules, nebulizing the nucleic acid molecules, applying a centrifugal force to the nucleic acid molecules, needle shearing the nucleic acid molecules, or enzymatically shearing the nucleic acid molecules. In any of the embodiments herein, the nucleic acid molecules can be phosphorylated at 5’ ends of the nucleic acid molecules. In any of the embodiments herein, the nucleic acid molecules can be adenylated at 3’ ends of the nucleic acid molecules.

[0009] In any of the embodiments herein, separating from the ligation buffer, the plurality of beads bound to the nucleic acid molecules, can comprise applying a magnetic field to the plurality of beads. In any of the embodiments herein, separating from the ligation buffer, the plurality of beads bound to the nucleic acid molecules, can comprise centrifuging the plurality of beads. In any of the embodiments herein, the alcohol can be ethanol, isopropanol, or a combination thereof. In any of the embodiments herein, the plurality of beads can comprise magnetic beads, beads can comprise a silica surface, beads can comprise a carboxyl surface, solid-phase reverse immobilization (SPRI) beads, or a combination thereof. In any of the embodiments herein, the methods can further comprise separating the nucleic acid molecules from the plurality of beads by eluting the nucleic acid molecules in a solvent. In some embodiments, the solvent can be water, a Tris-HCl solution, or a Tris-EDTA (TE) solution.

[0010] In any of the embodiments herein, the sample can comprise a tissue biopsy sample, a liquid sample, or a normal control. In some embodiments, the sample can be a liquid biopsy sample and can comprise blood, plasma, cerebrospinal fluid, sputum, stool, urine or saliva. In some embodiments, the sample can be a liquid biopsy sample and can comprise cfDNA. In some embodiments, the cfDNA can comprise circulating tumor DNA (ctDNA). In any of the embodiments herein, the nucleic acid molecules can comprise a mixture of tumor nucleic acid molecules and non-tumor nucleic acid molecules. In some embodiments, the tumor nucleic acid molecules can be derived from a tumor portion of a heterogeneous tissue biopsy sample, and the non-tumor nucleic acid molecules can be derived from a normal portion of the heterogeneous tissue biopsy sample. In some embodiments, the sample can comprise a liquid biopsy sample, and wherein the tumor nucleic acid molecules can be derived from a circulating tumor DNA (ctDNA) fraction of the liquid biopsy sample, and the non-tumornucleic acid molecules can be derived from a non-tumor, cell-free DNA (cfDNA) fraction of the liquid biopsy sample.

[0011] In any of the embodiments herein, one or more adapters can comprise amplification primers, flow cell adaptor sequences, substrate adapter sequences, or sample index sequences. In any of the embodiments herein, the captured nucleic acid molecules can be captured from the amplified nucleic acid molecules by hybridization to one or more bait molecules. In some embodiments, one or more bait molecules can comprise one or more nucleic acid molecules, each can comprise a region that is complementary to a region of a captured nucleic acid molecule.

[0012] In some aspects, disclosed herein is a method of sequencing the converted nucleic acid molecules, comprising: preparing the sequencing library, according to the method of any of the embodiments herein; sequencing, using a sequencer, the converted nucleic acid molecules. In any of the embodiments herein, the sequencing can comprise use of massively parallel sequencing (MPS), whole genome sequencing (WGS), whole exome sequencing, targeted sequencing, direct sequencing, or Sanger sequencing. In some embodiments, the sequencing can comprise massively parallel sequencing, and the massively parallel sequencing can comprise next generation sequencing (NGS). In any of the embodiments herein, the sequencer can comprise a next generation sequencer. In any of the embodiments herein, one or more of the plurality of sequencing reads can overlap one or more gene loci within one or more subgenomic intervals in the sample.

[0013] In some embodiments, the one or more gene loci comprise CpG sites within one or more gene promoter regions of interest. The CpG sites may include genomic regions with, for example, at least 200-500 base pairs having at least 50 bases in a CG sequence in the 5’ to 3’ direction (i.e., regions in the nucleic acid sequence, which comprise cytosine (C) followed by guanine (G)).

[0014] In some embodiments, the one or more gene loci comprises between 10 and 20 loci, between 10 and 40 loci, between 10 and 60 loci, between 10 and 80 loci, between 10 and 100 loci, between 10 and 150 loci, between 10 and 200 loci, between 10 and 250 loci, between 10 and 300 loci, between 10 and 350 loci, between 10 and 400 loci, between 10 and 450 loci, between 10 and 500 loci, between 20 and 40 loci, between 20 and 60 loci, between 20 and 80 loci, between 20 and 100 loci, between 20 and 150 loci, between 20 and 200 loci, between 20 and 250 loci, between 20 and 300 loci, between 20 and 350 loci, between 20 and 400 loci, between 20 and 500 loci, between 40 and 60 loci, between 40 and 80 loci, between 40 and100 loci, between 40 and 150 loci, between 40 and 200 loci, between 40 and 250 loci, between 40 and 300 loci, between 40 and 350 loci, between 40 and 400 loci, between 40 and 500 loci, between 60 and 80 loci, between 60 and 100 loci, between 60 and 150 loci, between 60 and 200 loci, between 60 and 250 loci, between 60 and 300 loci, between 60 and 350 loci, between 60 and 400 loci, between 60 and 500 loci, between 80 and 100 loci, between 80 and 150 loci, between 80 and 200 loci, between 80 and 250 loci, between 80 and 300 loci, between 80 and 350 loci, between 80 and 400 loci, between 80 and 500 loci, between 100 and 150 loci, between 100 and 200 loci, between 100 and 250 loci, between 100 and 300 loci, between 100 and 350 loci, between 100 and 400 loci, between 100 and 500 loci, between 150 and 200 loci, between 150 and 250 loci, between 150 and 300 loci, between 150 and 350 loci, between 150 and 400 loci, between 150 and 500 loci, between 200 and 250 loci, between 200 and 300 loci, between 200 and 350 loci, between 200 and 400 loci, between 200 and 500 loci, between 250 and 300 loci, between 250 and 350 loci, between 250 and 400 loci, between 250 and 500 loci, between 300 and 350 loci, between 300 and 400 loci, between 300 and 500 loci, between 350 and 400 loci, between 350 and 500 loci, or between 400 and 500 loci.

[0015] In any of the embodiments herein, the one or more gene loci can comprise ABL1, ACVR1B, AKT1, AKT2, AKT3, ALK, ALOX12B, AMER1, APC, AR, ARAF, ARFRP1, ARID1A, ASXL1, ATM, ATR, ATRX, AURKA, AURKB, AXIN1, AXL, BAP1, BARD1, BCL2, BCL2L1, BCL2L2, BCL6, BCOR, BCORL1, BCR, BRAF, BRCA1, BRCA2, BRIM, BRIP1, BTG1, BTG2, BTK, CALR, CARD11, CASP8, CBFB, CBL, CCND1, CCND2, CCND3, CCNE1, CD22, CD274, CD70, CD74, CD79A, CD79B, CDC73, CDH1, CDK12, CDK4, CDK6, CDK8, CDKN1A, CDKN1B, CDKN2A, CDKN2B, CDKN2C, CEBPA, CHEK1, CHEK2, CIC, CREBBP, CRKL, CSF1R, CSF3R, CTCF, CTNNA1, CTNNB1, CUL3, CUL4A, CXCR4, CYP17A1, DAXX, DDR1, DDR2, DIS3, DNMT3A, DOT1L, EED, EGFR, EMSY (Cllorf30), EP300, EPHA3, EPHB1, EPHB4, ERBB2, ERBB3, ERBB4, ERCC4, ERG, ERRFI1, ESRI, ETV4, ETV5, ETV6, EWSR1, EZH2, EZR, FAM46C, FANCA, FANCC, FANCG, FANCL, FAS, FBXW7, FGF10, FGF12, FGF14, FGF19, FGF23, FGF3, FGF4, FGF6, FGFR1, FGFR2, FGFR3, FGFR4, FH, FLCN, FLT1, FLT3, FOXL2, FUBP1, GABRA6, GATA3, GATA4, GATA6, GID4 (C17orf39), GNA11, GNA13, GNAQ, GNAS, GRM3, GSK3B, H3F3A, HDAC1, HGF, HNF1A, HRAS, HSD3B1, ID3, IDH1, IDH2, IGF1R, IKBKE, IKZF1, INPP4B, IRF2, IRF4, IRS2, JAK1, JAK2, JAK3, JUN, KDM5A, KDM5C, KDM6A, KDR, KEAP1, KEL, KIT, KLHL6, KMT2A (MLL), KMT2D (MLL2), KRAS, LTK, LYN, MAF, MAP2K1, MAP2K2,MAP2K4, MAP3K1, MAP3K13, MAPK1, MCL1, MDM2, MDM4, MED12, MEF2B, MEN1, MERTK, MET, MITF, MKNK1, MLH1, MPL, MRE11A, MSH2, MSH3, MSH6, MST1R, MTAP, MTOR, MUTYH, MYB, MYC, MYCL, MYCN, MYD88, NBN, NF1, NF2, NFE2L2, NFKBIA, NKX2-1, NOTCH1, NOTCH2, NOTCH3, NPM1, NRAS, NT5C2, NTRK1, NTRK2, NTRK3, NUTM1, P2RY8, PALB2, PARK2, PARP1, PARP2, PARP3, PAX5, PBRM1, PDCD1, PDCD1LG2, PDGFRA, PDGFRB, PDK1, PIK3C2B, PIK3C2G, PIK3CA, PIK3CB, PIK3R1, PIM1, PMS2, POLDI, POLE, PPARG, PPP2R1A, PPP2R2A, PRDM1, PRKAR1A, PRKCI, PTCHI, PTEN, PTPN11, PTPRO, QKI, RAC1, RAD21, RAD51, RAD51B, RAD51C, RAD51D, RAD52, RAD54L, RAFI, RARA, RBI, RBM10, REL, RET, RICTOR, RNF43, ROS1, RPTOR, RSPO2, SDC4, SDHA, SDHB, SDHC, SDHD, SETD2, SF3B1, SGK1, SLC34A2, SMAD2, SMAD4, SMARCA4, SMARCB1, SMO, SNCAIP, SOCS1, SOX2, SOX9, SPEN, SPOP, SRC, STAG2, STAT3, STK11, SUFU, SYK, TBX3, TEK, TERC, TERT, TET2, TGFBR2, TIP ARP, TMPRSS2, TNFAIP3, TNFRSF14, TP53, TSC1, TSC2, TYRO3, U2AF1, VEGFA, VHL, WHSCI, WHSC1L1, WT1, XPO1, XRCC2, ZNF217, ZNF703, or any combination thereof.

[0016] In some aspects, disclosed herein is a method of detecting one or more methylation signatures in a sample, comprising sequencing the converted nucleic acid molecules according to any of the embodiments disclosed herein; generating, by a sequencer, a plurality of nucleic acid molecules associated with the converted nucleic acid molecules; and determining, using one or more processors, one or more methylation signatures associated with the reads based on the plurality of sequence reads. In any of the embodiments herein, the methods can further comprise generating by the one or more processors, a report indicating the presences of tumor nucleic acid molecules based on the one or more methylation signatures. In some embodiments, the methods can further comprise transmitting the report to a healthcare provider. In some embodiments, the report can be transmitted via a computer network or a peer-to-peer connection.

[0017] In some aspects, disclosed herein is a method for detecting the presence of cancer, comprising: detecting one or more methylation signatures according to the method of some embodiments, wherein the methylation signatures are indicative of a cancer.

[0018] In some aspects, disclosed herein is a method for monitoring cancer progression or recurrence in a subject, the method comprising: detecting a first set of one or more methylation signatures using first isolated nucleic acid molecules in a first sample obtained from the subject at a first time point according to the method of some embodiments; detectinga second set of one or more methylation signatures using second isolated nucleic acid molecules in second sample obtained from the subject at a second time point; wherein the first time point can be before or after the second time point; and determining the progression of cancer by at least comparing the first methylation signature to the second methylation signature. In any of the embodiments herein, a cancer treatment can be administered to the subject after the first time point and before the second time point. In some embodiments, a determination can be made to maintain the cancer treatment based on the comparing.

[0019] In any of the embodiments herein, at least a portion of the method can be automated. In some embodiments, a system can comprise: one or more processors; and a memory communicatively coupled to the one or more processors and configured to store instructions that, when executed, by the one or more processors, can cause the system to control robotic components for automating: ligating one or more adapters to nucleic acid molecules in a ligation buffer; binding the DNA molecules to a plurality of beads in the ligation buffer; separating from the ligation buffer, the plurality of beads bound to the nucleic acid molecules; suspending the plurality of beads in a solution comprising alcohol; and converting, using a bisulfite reaction, unmethylated cytosines in the nucleic acid molecules to uracil, to generate converted nucleic acid molecules.INCORPORATION BY REFERENCE

[0020] All publications, patents, and patent applications mentioned in this specification are herein incorporated by reference in their entirety to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference in its entirety. In the event of a conflict between a term herein and a term in an incorporated reference, the term herein controls.BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Various aspects of the disclosed methods, devices, and systems are set forth with particularity in the appended claims. A better understanding of the features and advantages of the disclosed methods, devices, and systems will be obtained by reference to the following detailed description of illustrative embodiments and the accompanying drawings, of which:

[0022] FIG. 1 provides a non-limiting exemplary method for preparing a sequencing library for methyl- sequencing.

[0023] FIG. 2 provides another non-limiting exemplary method for preparing a sequencing library for methyl-sequencing.

[0024] FIG. 3 shows data indicating an increase in genomic DNA yield for methyl sequencing when preparing the sequencing library according to an exemplary sequencing library preparation method.

[0025] FIG. 4 shows data indicating a decrease in GC dropout in genomic DNA for methyl sequencing when preparing the sequencing library according to an exemplary sequencing library preparation method.

[0026] FIG. 5 shows data indicating an increase in the number of genomic DNA reads available for analysis when obtained by methylation sequencing using a sequencing library prepared according to an exemplary sequencing library preparation method.

[0027] FIG. 6 shows data indicating that a component in the ligation mix decreases genomic DNA yield, according to an exemplary sequencing library preparation method.

[0028] FIG. 7 shows data indicating that a component in the ligation mix increases GC dropout for genomic DNA according to an exemplary sequencing library preparation method.

[0029] FIG. 8 shows data indicating an increase in cfDNA yield when preparing a sequencing library according to an exemplary sequencing library preparation method.

[0030] FIG. 9 shows data indicating a decrease in GC dropout in cfDNA for methyl sequencings when preparing the sequencing library, according to an exemplary sequencing library preparation method.

[0031] FIG. 10 shows data indicating an increase in the number of cfDNA reads available for analysis when preparing the sequencing library according to an exemplary sequencing library preparation method.DETAILED DESCRIPTION

[0032] Previous methods for preparing methylation sequencing libraries via bisulfite conversion provide low nucleic acid molecule (e.g., DNA) yields and high dropouts of GC- rich nucleic acid sequences (i.e., GC dropouts). As a result, previous methods struggle to provide an adequate number of methylation sequencing reads for analyses. This challenge is especially relevant when preparing sequencing libraries from cell-free DNA (cfDNA), which are present in inherently low numbers in a subject, relative to genomic DNA. Methods and systems for preparing a sequencing library for methyl-sequencing, and more specifically for sequencing library prepared via bisulfite conversion, are described. The disclosed methodsinclude ligating one or more adapters to nucleic acid molecules (e.g., DNA molecules, such as cfDNA, or RNA molecules) in a ligation buffer. The nucleic acid molecules are then bound to beads in the ligation buffer, and the nucleic acid molecule-bound beads are separated from the ligation buffer. Importantly, the beads are suspended, e.g., via vigorous mixing, in a solution, and the solution can have alcohol. The unmethylated cytosines in the nucleic acid molecules are then converted, using a bisulfite reaction, to generate converted nucleic acid molecules.

[0033] Previous methods struggle to produce an adequate number of methylation sequencing reads for analyses, for example when a library is prepared by bisulfite conversion. For example, previous methods result in low overall nucleic acid yields for methylation sequencing. In addition, previous library preparation methods result in high levels of GC dropout. GC dropouts are especially problematic for methyl-sequencing because nucleic acid molecules are typically methylated at cytosine nucleotides, e.g., at CpG sites. A loss in GC- rich nucleic acid regions during library preparation thus results in a loss of a large proportion of the relevant nucleic acid sequences for methyl-sequencing. The loss of usable sequencing reads can be especially impactful, depending on the type of input nucleic acid used. Cell-free DNA (cfDNA), for example, is found in low amounts in a subject, relative to genomic DNA. The processing of low abundance DNA, such as cfDNA, via a protocol with low overall nucleic acid molecule yield and high GC dropout rates, can result in such limited amounts of usable sequencing reads, that in some cases, a consensus sequence cannot be derived.Methods that can output improved amounts of usable methylation sequencing reads are needed.

[0034] The methods and systems described herein provide improved methylation sequencing outputs and are more suitable than existing methods for low abundance nucleic acid molecules, such as cfDNA. The key improvement of the methods described herein is the suspending, e.g., vigorous mixing, of the beads in a solution comprising alcohol, e.g., an 80% ethanol solution. Previous protocols for preparing sequencing libraries, such as the protocol for the NEBNext Ultra II DNA Library Prep Kit for Illumina by New England Biolabs (Ipswitch, MA), state that beads, such as paramagnetic beads, e.g., solid-phase reversible immobilization (SPRI) beads, should not be disturbed, when adding the alcohol solution to the beads. Contrary to protocols like the above, the methods described herein demonstrate that engaging in the opposite action, such as vigorously suspending the beads in the alcohol solution, yield improved amounts of usable sequencing reads for methylation sequencingwhen the sequencing library is prepared by bisulfite conversion. The present disclosure provides exemplary data suggesting that a reason for the increased number of usable sequence reads may be because a component in the ligation mix inhibits nucleic acid molecule yield and contributes to GC dropout, and the suspending the beads may contribute towards removing residual ligation mix, from the reaction. The suspending of the beads in an alcohol solution results in improved yield when preparing sequencing libraries for methylation sequencing via bisulfite conversion, for both genomic DNA and cell-free DNA inputs, or RNA molecule inputs.

[0035] In some aspects, disclosed herein is a method of preparing a sequencing library, comprising: ligating one or more adapters to nucleic acid molecules in a ligation buffer; binding the nucleic acid molecules to a plurality of beads in the ligation buffer; separating from the ligation buffer, the plurality of beads bound to the nucleic acid molecules; suspending the plurality of beads in a solution comprising alcohol; and converting, using a bisulfite reaction, unmethylated cytosines in the nucleic acid molecules to uracil, to generate converted nucleic acid molecules. The nucleic acid molecules may be, for example, DNA molecules. The DNA molecules can be cfDNA molecules. In another embodiment, the DNA molecules are genomic DNA molecules. In another example, the nucleic acid molecules are RNA molecules, such as mRNA molecules.Definitions

[0036] Unless otherwise defined, all of the technical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art in the field to which this disclosure belongs.

[0037] As used in this specification and the appended claims, the singular forms “a”, “an”, and “the” include plural references unless the context clearly dictates otherwise. Any reference to “or” herein is intended to encompass “and / or” unless otherwise stated.

[0038] 4‘About” and “approximately” shall generally mean an acceptable degree of error for the quantity measured given the nature or precision of the measurements. Exemplary degrees of error are within 20 percent (%), typically, within 10%, and more typically, within 5% of a given value or range of values.

[0039] As used herein, the terms “comprising” (and any form or variant of comprising, such as “comprise” and “comprises”), “having” (and any form or variant of having, such as “have” and “has”), “including” (and any form or variant of including, such as “includes” and“include”), or “containing” (and any form or variant of containing, such as “contains” and “contain”), are inclusive or open-ended and do not exclude additional, un-recited additives, components, integers, elements, or method steps.

[0040] As used herein, the terms “individual,” “patient,” or “subject” are used interchangeably and refer to any single animal, e.g., a mammal (including such non-human animals as, for example, dogs, cats, horses, rabbits, zoo animals, cows, pigs, sheep, and non- human primates) for which treatment is desired. In particular embodiments, the individual, patient, or subject herein is a human.

[0041] The terms “cancer” and “tumor” are used interchangeably herein. These terms refer to the presence of cells possessing characteristics typical of cancer-causing cells, such as uncontrolled proliferation, immortality, metastatic potential, rapid growth and proliferation rate, and certain characteristic morphological features. Cancer cells are often in the form of a tumor, but such cells can exist alone within an animal, or can be a non-tumorigenic cancer cell, such as a leukemia cell. These terms include a solid tumor, a soft tissue tumor, or a metastatic lesion. As used herein, the term “cancer” includes premalignant, as well as malignant cancers.

[0042] As used herein, “treatment” (and grammatical variations thereof such as “treat” or “treating”) refers to clinical intervention (e.g., administration of an anti-cancer agent or anticancer therapy) in an attempt to alter the natural course of the individual being treated, and can be performed either for prophylaxis or during the course of clinical pathology. Desirable effects of treatment include, but are not limited to, preventing occurrence or recurrence of disease, alleviation of symptoms, diminishment of any direct or indirect pathological consequences of the disease, preventing metastasis, decreasing the rate of disease progression, amelioration or palliation of the disease state, and remission or improved prognosis.

[0043] As used herein, the term “subgenomic interval” (or “subgenomic sequence interval”) refers to a portion of a genomic sequence.

[0044] As used herein, the term "subject interval" refers to a subgenomic interval or an expressed subgenomic interval (e.g., the transcribed sequence of a subgenomic interval).

[0045] As used herein, the terms “variant sequence” or “variant” are used interchangeably and refer to a modified nucleic acid sequence relative to a corresponding “normal” or “wildtype” sequence. In some instances, a variant sequence may be a “short variant sequence” (or “short variant”), i.e., a variant sequence of less than about 50 base pairs in length.

[0046] It is understood that aspects and variations of the invention described herein include “consisting” and / or “consisting essentially of’ aspects and variations.

[0047] When a range of values is provided, it is to be understood that each intervening value between the upper and lower limit of that range, and any other stated or intervening value in that states range, is encompassed within the scope of the present disclosure. Where the stated range includes upper or lower limits, ranges excluding either of those included limits are also included in the present disclosure.

[0048] Some of the analytical methods described herein include mapping sequences to a reference sequence, determining sequence information, and / or analyzing sequence information. It is well understood in the art that complementary sequences can be readily determined and / or analyzed, and that the description provided herein encompasses analytical methods performed in reference to a complementary sequence.

[0049] The section headings used herein are for organization purposes only and are not to be construed as limiting the subject matter described. The description is presented to enable one of ordinary skill in the art to make and use the invention and is provided in the context of a patent application and its requirements. Various modifications to the described embodiments will be readily apparent to those persons skilled in the art and the generic principles herein may be applied to other embodiments. Thus, the present invention is not intended to be limited to the embodiment shown but is to be accorded the widest scope consistent with the principles and features described herein.

[0050] The figures illustrate processes according to various embodiments. In the exemplary processes, some blocks are, optionally, combined, the order of some blocks is, optionally, changed, and some blocks are, optionally, omitted. In some examples, additional steps may be performed in combination with the exemplary processes. Accordingly, the operations as illustrated (and described in greater detail below) are exemplary by nature and, as such, should not be viewed as limiting.

[0051] The section headings used herein are for organizational purposes only and are not to be construed as limiting the subject matter described.Methods for preparing a sequencing library

[0052] The methods described herein are useful for preparing a sequencing library using nucleic acid molecules obtained from a sample. The sample may be, for example, a liquid sample or a solid tissue sample, such as blood or plasma. In some implementations, thesample is a cancer sample. Additional samples that may be used to obtain the nucleic acid molecules are further described herein. The nucleic acid molecules may be RNA molecules or DNA molecules. In some embodiments, the nucleic acid molecules are cfDNA molecules.

[0053] The nucleic acid molecules isolated from the sample may be used to construct a sequencing library. The disclosed methods for preparing a sequencing library includes suspending the plurality of beads bound to the nucleic acid molecules, to increase the output number of usable sequencing reads for methylation sequencing when the sequencing library is prepared by bisulfite conversion. Suspending the plurality of beads bound to the nucleic acid molecules may reduce, during library preparation, the carryover of the ligation mix, which when not washed and diluted, may contribute towards limiting the amount of usable sequencing reads. The suspending of the plurality of beads, according to the disclosed methods, result in both an increase in the overall yield of nucleic acid from the library preparation and a decrease in the GC dropout (i.e., loss of nucleic acid molecules comprising GC-rich sequences) from the library preparation. The disclosed methods apply to both genomic DNA and cfDNA, and my further be applied to RNA molecules.

[0054] FIG. 1 shows an exemplary schematic showing a general process 100 for preparing a sequencing library from a sample. The method of preparing the sequencing library can include: ligating one or more adapters to nucleic acid molecules in a ligation buffer (102); binding the nucleic acid molecules to a plurality of beads in the ligation buffer (104); separating from the ligation buffer, the plurality of beads bound to the nucleic acid molecules (106); suspending the plurality of beads in a solution comprising alcohol (108); and converting unmethylated cytosines in the nucleic acid molecules to uracil, to generate converted nucleic acid molecules (110). The nucleic acid molecules can be cell-free DNA (cfDNA) molecules. In another example, the nucleic acid molecules are RNA molecules.

[0055] In process 100, some blocks are, optionally, combined, and some blocks are, optionally, omitted. In some examples, additional steps may be performed in combination with the process 100. Accordingly, the operations as illustrated (and described in greater detail below) are exemplary by nature and, as such, should not be viewed as limiting.

[0056] Prior to 102 in FIG. 1, the nucleic acid molecules can be subjected to further processing, as part of preparing the sequencing library. For example, the processing can comprise denaturing the converted nucleic acid molecules, e.g., via subjecting the nucleic acid molecules to heat. The processing can also comprise amplifying the converted nucleic acid molecules. The amplifying can be any of a variety of specific or non-specific nucleicacid amplification methods known to those of skill in the art. In some instances, the nucleic acids are amplified, e.g., by a whole-genome amplification method such as random-primed strand-displacement amplification. The amplifying can comprise performing a polymerase chain reaction (PCR) amplification or an isothermal amplification. The result of the amplifying can include a plurality of nucleic acid molecules which can then be subject to the ligating of adapters in 102, as described below, or can be subject to further processing.

[0057] The method can comprise blunting the ends of the nucleic acid molecules, as part of processing the nucleic acid molecules prior to the ligating described in 102. Blunting the ends of the nucleic acid molecules can be achieved via amplifying the nucleic acid molecules, e.g., via PCR reaction, as stated above. Blunting the ends of the nucleic acid molecules can also be achieved via applying a polymerase or a portion of a polymerase, such as T4 DNA polymerase (e.g., T4 ligase), DNA polymerase I, or the large (Klenow) fragment of the DNA polymerase I. Blunting the ends of the nucleic acid molecules can also be achieved via applying an exonuclease, such as a 5' to 3' exonuclease, e.g., Mung Bean nuclease.

[0058] The method can comprise fragmenting the nucleic acid molecules, as part of processing the nucleic acid molecules prior to the ligating described in 102. Fragmenting the nucleic acid molecules can comprise shearing the nucleic acid. Shearing the nucleic acid molecules can comprise sonicating the nucleic acid molecules, nebulizing the nucleic acid molecules, applying a centrifugal force to the nucleic acid molecules, needle shearing the nucleic acid molecules, or enzymatically shearing the nucleic acid molecules.

[0059] The nucleic acid fragments can be subject to further processing steps, such as the blunting of the ends of the nucleic acid fragments or the amplifying of the nucleic acid fragments, as described above. The nucleic acid molecules can be phosphorylated at the 5' ends of the nucleic acid molecules, as part of processing the nucleic acid molecules prior to the ligating described in 102. The phosphorylating can be done via a kinase, for example, via a T4 polynucleotide kinase. The phosphorylating of the 5' ends of the nucleic acid molecules can be to prepare the nucleic acid molecules for downstream reactions, such as cloning, which can include ligating. The nucleic acid molecules can be adenylated at the 3' ends of the nucleic acid molecules, as part of processing the nucleic acid molecules prior to the ligating described in 102. The adenylating on the 3' ends can be done to prepare the nucleic acid molecules for use in cloning, such as TA cloning. An enzyme, such as a terminal transferase, can be used to adenylate the 3' ends.

[0060] At 102 in FIG. 1, one or more adapters to nucleic acid molecules in a ligation buffer are ligated. The ligation buffer, i.e., ligation mix, can comprise a ligase. The ligase can be T3 DNA ligase, T4 DNA ligase, human DNA ligase 3, T7 DNA ligase, PBCV-1 DNA ligase, or a portion thereof. The ligation buffer can comprise adenosine triphosphate (ATP). The ligation buffer can also comprise cofactors, such as magnesium chloride (MgCh), potassium chloride (KC1), NAD+, or ATP.

[0061] The one or more adapters to the nucleic acid molecules can include single stranded nucleic acid sequences that can hybridize or ligate to the nucleic acid molecules. The adapters can comprise sequences that are complementary to sequences of single- stranded nucleic acid molecules that are conjugated to substrates, such as a flow cell used for next-generation sequencing (e.g., flow cell adapters), or a bead used for enriching or purifying nucleic acid molecules, i.e., substrate adapters, such as a paramagnetic bead, e.g., a solid-phase reverse immobilization (SPRI) bead. The adapters can also include barcodes or indices, which can allow for multiplexing multiple sequencing reactions, during next-generation sequencing. Other examples of synthetic adapters, primers, and / or barcodes that can be optionally ligated to the nucleic acid molecules include amplification primers, sequencing adapters, and / or unique molecular identifier sequences.

[0062] At 104 in FIG. 1, the nucleic acid molecules are bound to a plurality of beads in the ligation buffer. The nucleic acid molecules can be bound to the plurality of beads in the ligation buffer via ligating or hybridizing against single stranded nucleic acid molecules that are conjugated to the surface of the beads on the plurality of beads. The plurality of beads can comprise magnetic beads, a silica surface, a carboxyl surface or a combination thereof. The beads can comprise solid-phase reverse immobilization (SPRI) beads. The binding of the nucleic acid molecules to the plurality of beads in the ligation buffer can allow for the enriching or purifying of nucleic acid molecules.

[0063] At 106 in FIG. 1, the plurality of beads bound to the nucleic acid molecules are separated from the ligation buffer. The separating of the plurality of beads bound to the nucleic acid molecules, from the ligation buffer, can be a part of purifying the nucleic acid molecules, e.g., by removing the ligation buffer, such that only the plurality of beads bound to the nucleic acid molecules remain. The plurality of beads bound to the nucleic acid molecules can, after suspending in a solution containing alcohol, as described in 108, ultimately be subjected to separating the plurality of beads from the nucleic acid molecules.

[0064] The separating the nucleic acid molecules from the ligation buffer can comprise fractioning the nucleic acid molecules based on size, i.e., size selection. The fractioning the nucleic acid molecules can include a left-side clean-up with the plurality of beads (i.e., the removal of small sequencing library fragments), e.g., the cleanup of a PCR reaction, such that nucleic acid molecules smaller than the expected size of the amplicons are not bound to the plurality of beads, and are instead left in the supernatant, when precipitating the plurality of beads. The fractioning the nucleic acid molecules based on size can be a function of the amount, e.g., the volume, of the beads that are bound to the nucleic acid molecules, e.g., the volume of the plurality of beads bound to the nucleic acid molecules in 104.

[0065] In addition to a left-side clean-up, the fractioning the nucleic acid molecules based on size can include right-side clean-up (i.e., the removal of large sequencing library fragments) or double-sided clean-up (i.e., comprising both a left-side clean-up and a right-side clean-up). The fractioning can comprise: combining a second plurality of beads with the nucleic acid molecules, thereby allowing a first portion of the nucleic acid molecules to bind to the second plurality of beads; separating the second plurality of beads from a second portion of the nucleic acid molecules; and discarding the second plurality of beads and the first portion of the nucleic acid molecules. The first portion of the nucleic acid molecules can include large sequencing library fragments that are larger than a target size of nucleic acid molecules. The fractioning the nucleic acid molecules based on size can be a function of the amount, e.g., the volume, of the second plurality of beads that are bound to the nucleic acid molecules, e.g., the volume of the second plurality of beads bound to the first portion of the nucleic acid molecules. The fractioning can occur after the ligating, and before the binding of the nucleic acid molecules to a plurality of beads in the ligation buffer. Other general forms of size selection can also be applied to the nucleic acid molecules, such as preparative gel electrophoresis, which can include running the gel electrophoresis, visualizing the results of the gel electrophoresis with a dye (e.g., ethidium bromide, or some other nucleic acid intercalator) and a specific wavelength distribution of light (e.g., light comprising ultraviolet (UV) light), physically excising the desired size of nucleic acid molecules, e.g., via a scalpel, and isolating the nucleic acid molecules from the gel components used in the gel electrophoresis. In some instances, however, the nucleic acid molecules, such as fragmented and / or adapter-ligated groups of nucleic acids, can be used without explicit size selection or amplification prior to hybridization-based selection of target sequences.

[0066] Separating from the ligation buffer, the plurality of beads bound to the nucleic acid molecules, can comprise applying a magnetic field to the plurality of beads. Applying the magnetic field can result in precipitating the plurality of beads and / or the second plurality of beads. The applying the magnetic field can be used to assist in fractioning the nucleic acid molecules, e.g., when fractioning the nucleic acid molecules based on size. The magnetic field can be used to attract the plurality of beads or the second plurality of beads, either of which can be magnetic or paramagnetic, such that the plurality of beads forms a precipitate, proximate to the source of the magnetic field. As a result, the remainder of the solution, i.e., the supernatant, can either be isolated for further analyses, e.g., during left-side clean-up, or can be discarded, e.g., during right-side clean-up.

[0067] Separating from the ligation buffer, the plurality of beads bound to the nucleic acid molecules, can comprise centrifuging the plurality of beads. A centrifuge can be set to spin at high speeds, such that a precipitate comprising the plurality of beads and / or the second plurality of beads can be formed, by pelleting higher molecular weight components in the library preparation solution, which can result in lower molecular weight components, e.g., components of the solution that are not the plurality of beads, to be in the supernatant. In the case of right-side clean-up, the precipitate comprising the plurality of beads and / or the second plurality of beads can be discarded, and the supernatant can be isolated for further processing and / or analyses. In the case of left-side clean-up, the precipitate comprising the plurality of beads and / or the second plurality of beads can be isolated for further processing and / or analyses, and the supernatant can be discarded.

[0068] At 108 in FIG. 1, the plurality of beads in a solution comprising alcohol are suspended. The alcohol can be ethanol, isopropanol, or a combination thereof. The suspending of the plurality of beads in the solution comprising alcohol can include the suspending of residual ligation buffer (i.e., ligation mix) in the alcohol solution. The suspending of the plurality of beads in the solution comprising alcohol can be a part of a washing, where the adding of the solution comprising alcohol can help dilute any residual amounts of ligation buffer. Multiple washes of the plurality of beads can be performed with a solution comprising alcohol. For example, a solution comprising alcohol can be added to the plurality of beads, and the resulting mixture can be suspended. The plurality of beads can then be precipitated, e.g., via the applying of a magnetic field, and the supernatant can be removed. The process of adding a solution comprising alcohol, followed by a precipitating of the plurality of beads, followed by a removing of the supernatant, can be considered awashing, and multiple washings can be performed. The solution comprising alcohol need not be the same solution for every washing. For example, a first wash can be performed with 80% ethanol, a second wash can be performed with 75% isopropanol, and a third wash can be performed with 90% ethanol. The suspending, e.g., mixing, of the plurality of beads in the solution comprising alcohol can result in the ligation buffer becoming more readily removable, because after mixing, the supernatant may more readily comprise both the alcohol and the residual ligation buffer.

[0069] At 110 in FIG. 1, unmethylated cytosines in the nucleic acid molecules are converted to uracil, to generate converted nucleic acid molecules. The converting of unmethylated cytosine to uracil can comprise a bisulfite reaction. The bisulfite reaction can comprise incubating the nucleic acid molecules with bisulfite at a high temperature. The high temperature incubation of the nucleic acid molecules with bisulfite can denature the nucleic acid molecules, such that any double- stranded nucleic acid molecules become singlestranded. As a result, the bisulfite can effectively react with the unmethylated cytosines of the nucleic acid molecules, and convert the unmethylated cytosines into uracil. The conversion of the unmethylated cytosines to uracil can comprise a deamination reaction, and the deamination reaction can occur at a low pH. The conversion of the unmethylated cytosines to uracil can also comprise a desulfonation reaction, and the desulfonation reaction can occur at a high pH.

[0070] The converting can occur before the ligating. For example, the nucleic acid molecules (DNA, e.g., genomic DNA or cfDNA, or RNA) can be subject to the bisulfite converting before preparing the methyl-sequencing library. Doing so can result in increased yield in recovered nucleic acid molecules compared to when the converting happens after preparing the methyl-sequencing library. Alternatively, the converting can occur after the suspending. For example, the nucleic acid (DNA, e.g., genomic DNA or cfDNA, or RNA) can be subject to the bisulfite converting after suspending the nucleic acid molecule-bound plurality of beads in the solution comprising alcohol. Doing so can result in retaining duplex strand sequence information, which may be lost if the converting occurs before the suspending.

[0071] The methods can further comprise separating the nucleic acid molecules from the plurality of beads by eluting the nucleic acid molecules in a solvent. The solvent can be water, a Tris-HCl solution, or a Tris-EDTA (TE) solution. Adding a hydrophilic solvent such as water, a Tris-HCl solution, or a TE solution, can result in the ionic components of the solvent favorably binding to the nucleic acid molecules bound to the plurality of beads. Thus,adding the solvent, such as a hydrophilic solvent, can elute i.e., release the nucleic acid molecules from the plurality of beads, into the supernatant of the solution. The plurality of beads can then be subjected to a magnetic field and precipitated. The precipitate can then be separated from the supernatant, and the supernatant can be isolated. The supernatant comprises the nucleic acid molecules.

[0072] FIG. 2 shows an exemplary schematic showing a general process 200 for preparing a sequencing library from a sample, that can be done alternatively to the general process 100. The method of preparing the sequencing library can include: ligating one or more adapters to nucleic acid molecules in a ligation buffer (202); binding the nucleic acid molecules to a plurality of beads in the ligation buffer (204); separating from the ligation buffer, the plurality of beads bound to the nucleic acid molecules (206); combining a second plurality of beads with the nucleic acid molecules, thereby allowing a first portion of the nucleic acid molecules to bind to the second plurality of beads (208); separating the second plurality of beads from a second portion of the nucleic acid molecules (210); suspending the plurality of beads in a solution comprising alcohol (212); discarding the second plurality of beads and the first portion of the nucleic acid molecules (214); and converting unmethylated cytosines in the nucleic acid molecules to uracil, to generate converted nucleic acid molecules (216). Like in process 100, the nucleic acid molecules can be cell-free DNA (cfDNA) molecules, genomic DNA molecules, or RNA molecules. The separating from the ligation buffer, the plurality of beads bound to the nucleic acid molecules (206), can comprise isolating the plurality of beads bound to the nucleic acid molecules and removing small nucleic acid molecules found in the supernatant, as a part of a left-side clean-up. The isolated nucleic acid molecules bound to the plurality of beads can include large nucleic acid molecules. In 208-214, the combining, separating, suspending, and discarding can comprise a right-side clean-up, where large nucleic acid molecules are removed. That is, the first portion of the nucleic acid molecules can bind to the second plurality of beads, where the first portion of the nucleic acid molecules can include the large nucleic acid molecules, and the second plurality of beads can include a large volume of beads that corresponds to the removal of the large nucleic acid molecules, i.e., the first portion of the nucleic acid molecules. The result of performing 202-214 is the isolation (e.g., elution) of intermediate size nucleic acid molecules, because of both the rightside clean-up and the left-side clean-up.

[0073] The isolated intermediate size nucleic acid molecules can then be subject to bisulfite conversion, for example, as indicated in 110 or 216 (for processes 100 or 200, respectively),provided that the bisulfite conversion has not yet happened. In the case that the bisulfite conversion is done after the supernatant has been isolated, duplex strand sequence information can be retained, which can otherwise be lost if the converting has occurred before the preparing of the sequencing library. Bisulfite conversion need not happen both before beginning to prepare the sequencing library, and after the preparing of the sequencing library. Bisulfite conversion happens only once: either before beginning to prepare the sequencing library, or after. Once the nucleic acid molecules have been isolated from the supernatant, and the nucleic acid molecules have been bisulfite converted, the nucleic acid molecules can be amplified, and adapters, such as sequencing adapters, can be added to the ends of the nucleic acid molecules by, for example, amplification. Once the adapters have been added to the nucleic acid molecules as part of the processing of the sequencing library, the sequencing library can be sequenced. The sequencing of the sequencing library results in sequencing data. The sequencing data can be analyzed, for example, by aligning the sequencing reads that can constitute the sequencing data, by calling mutations that may be indicated by the sequencing data, and / or by calling methylation patterns that can be associated with some sequences in the sequencing data.Sample preparationSamples

[0074] The disclosed methods and systems may be used with any of a variety of samples (also referred to herein as specimens) comprising nucleic acids (e.g., DNA or RNA) that are collected from a subject (e.g., a patient). Examples of a sample include, but are not limited to, a tumor sample, a tissue sample, a biopsy sample (e.g., a tissue biopsy, a liquid biopsy, or both), a blood sample (e.g., a peripheral whole blood sample), a blood plasma sample, a blood serum sample, a lymph sample, a saliva sample, a sputum sample, a urine sample, a gynecological fluid sample, a circulating tumor cell (CTC) sample, a cerebral spinal fluid (CSF) sample, a pericardial fluid sample, a pleural fluid sample, an ascites (peritoneal fluid) sample, a feces (or stool) sample, or other body fluid, secretion, and / or excretion sample (or cell sample derived therefrom). In certain instances, the sample may be frozen sample or a formalin-fixed paraffin-embedded (FFPE) sample.

[0075] In some instances, the sample may be collected by tissue resection (e.g., surgical resection), needle biopsy, bone marrow biopsy, bone marrow aspiration, skin biopsy, endoscopic biopsy, fine needle aspiration, oral swab, nasal swab, vaginal swab or a cytology smear, scrapings, washings or lavages (such as a ductal lavage or bronchoalveolar lavage), etc.

[0076] In some instances, the sample is a liquid biopsy sample, and may comprise, e.g., whole blood, blood plasma, blood serum, urine, stool, sputum, saliva, or cerebrospinal fluid. In some instances, the sample may be a liquid biopsy sample and may comprise circulating tumor cells (CTCs). In some instances, the sample may be a liquid biopsy sample and may comprise cell-free DNA (cfDNA), circulating tumor DNA (ctDNA), or any combination thereof.

[0077] In some instances, the sample may comprise one or more premalignant or malignant cells. Premalignant, as used herein, refers to a cell or tissue that is not yet malignant but is poised to become malignant. In certain instances, the sample may be acquired from a solid tumor, a soft tissue tumor, or a metastatic lesion. In certain instances, the sample may be acquired from a hematologic malignancy or pre-malignancy. In other instances, the sample may comprise a tissue or cells from a surgical margin. In certain instances, the sample may comprise tumor-infiltrating lymphocytes. In some instances, the sample may comprise one or more non-malignant cells. In some instances, the sample may be, or is part of, a primary tumor or a metastasis (e.g., a metastasis biopsy sample). In some instances, the sample may be obtained from a site (e.g., a tumor site) with the highest percentage of tumor (e.g., tumor cells) as compared to adjacent sites (e.g., sites adjacent to the tumor). In some instances, the sample may be obtained from a site (e.g., a tumor site) with the largest tumor focus (e.g., the largest number of tumor cells as visualized under a microscope) as compared to adjacent sites (e.g., sites adjacent to the tumor).

[0078] In some instances, the disclosed methods may further comprise analyzing a primary control (e.g., a normal tissue sample). In some instances, the disclosed methods may further comprise determining if a primary control is available and, if so, isolating a control nucleic acid (e.g., DNA) from said primary control. In some instances, the sample may comprise any normal control (e.g., a normal adjacent tissue (NAT)) if no primary control is available. In some instances, the sample may be or may comprise histologically normal tissue. In some instances, the method includes evaluating a sample, e.g., a histologically normal sample (e.g., from a surgical tissue margin) using the methods described herein. In some instances, thedisclosed methods may further comprise acquiring a sub-sample enriched for non-tumor cells, e.g., by macro-dissecting non-tumor tissue from said NAT in a sample not accompanied by a primary control. In some instances, the disclosed methods may further comprise determining that no primary control and no NAT is available, and marking said sample for analysis without a matched control.

[0079] In some instances, samples obtained from histologically normal tissues (e.g., otherwise histologically normal surgical tissue margins) may still comprise a genetic alteration such as a variant sequence as described herein. The methods may thus further comprise re-classifying a sample based on the presence of the detected genetic alteration. In some instances, multiple samples (e.g., from different subjects) are processed simultaneously.

[0080] In some instances, the sample may comprise a tissue biopsy sample, a liquid biopsy sample, or a normal control. In some instances, the sample may be a liquid biopsy sample and may comprise blood, plasma, cerebrospinal fluid, sputum, stool, urine, or saliva. In some instances, the sample may be a liquid biopsy sample and may comprise circulating tumor cells (CTCs). In some instances, the sample may be a liquid biopsy sample and may comprise cell-free DNA (cfDNA), circulating tumor DNA (ctDNA), or any combination thereof.

[0081] The disclosed methods and systems may be applied to the analysis of nucleic acids extracted from any of variety of tissue samples (or disease states thereof), e.g., solid tissue samples, soft tissue samples, metastatic lesions, or liquid biopsy samples. Examples of tissues include, but are not limited to, connective tissue, muscle tissue, nervous tissue, epithelial tissue, and blood. Tissue samples may be collected from any of the organs within an animal or human body. Examples of human organs include, but are not limited to, the brain, heart, lungs, liver, kidneys, pancreas, spleen, thyroid, mammary glands, uterus, prostate, large intestine, small intestine, bladder, bone, skin, etc.

[0082] In some instances, the nucleic acids extracted from the sample may comprise deoxyribonucleic acid (DNA) molecules. Examples of DNA that may be suitable for analysis by the disclosed methods include, but are not limited to, genomic DNA or fragments thereof, mitochondrial DNA or fragments thereof, cell-free DNA (cfDNA), and circulating tumor DNA (ctDNA). Cell-free DNA (cfDNA) is comprised of fragments of DNA that are released from normal and / or cancerous cells during apoptosis and necrosis, and circulate in the blood stream and / or accumulate in other bodily fluids. Circulating tumor DNA (ctDNA) is comprised of fragments of DNA that are released from cancerous cells and tumors that circulate in the blood stream and / or accumulate in other bodily fluids. In some instances, thenucleic acid molecules extracted from a sample may comprise a mixture of tumor nucleic acid molecules and non-tumor nucleic acid molecules. In some instances, the tumor nucleic acid molecules may be derived from a tumor portion of a heterogeneous tissue biopsy sample, and the non-tumor nucleic acid molecules may be derived from a normal portion of the heterogeneous tissue biopsy sample. In some instances, the sample may comprise a liquid biopsy sample, and the tumor nucleic acid molecules may be derived from a circulating tumor DNA (ctDNA) fraction of the liquid biopsy sample while the non-tumor nucleic acid molecules may be derived from a non-tumor, cell-free DNA (cfDNA) fraction of the liquid biopsy sample.

[0083] In some instances, nucleic acid molecules are extracted from nucleated cells from the sample. In some instances, a sample may have a low nucleated cellularity, e.g., when the sample is comprised mainly of erythrocytes, lesional cells that contain excessive cytoplasm, or tissue with fibrosis. In some instances, a sample with low nucleated cellularity may require more, e.g., greater, tissue volume for nucleic acid extraction.

[0084] In some instances, the nucleic acids extracted from the sample may comprise ribonucleic acid (RNA) molecules. Examples of RNA that may be suitable for analysis by the disclosed methods include, but are not limited to, total cellular RNA, total cellular RNA after depletion of certain abundant RNA sequences e.g., ribosomal RNAs), cell-free RNA (cfRNA), messenger RNA (mRNA) or fragments thereof, the poly(A)-tailed mRNA fraction of the total RNA, ribosomal RNA (rRNA) or fragments thereof, transfer RNA (tRNA) or fragments thereof, and mitochondrial RNA or fragments thereof. In some instances, RNA may be extracted from the sample and converted to complementary DNA (cDNA) using, e.g., a reverse transcription reaction. In some instances, the cDNA is produced by random-primed cDNA synthesis methods. In other instances, the cDNA synthesis is initiated at the poly(A) tail of mature mRNAs by priming with oligo(dT)-containing oligonucleotides. Methods for depletion, poly(A) enrichment, and cDNA synthesis are well known to those of skill in the art.

[0085] In some instances, the sample may comprise a tumor content e.g., comprising tumor cells or tumor cell nuclei), or a non-tumor content (e.g., immune cells, fibroblasts, and other non-tumor cells). In some instances, the tumor content of the sample may constitute a sample metric. In some instances, the sample may comprise a tumor content of at least 5-50%, 10- 40%, 15-25%, or 20-30% tumor cell nuclei. In some instances, the sample may comprise a tumor content of at least 5%, at least 10%, at least 20%, at least 30%, at least 40%, or at least50% tumor cell nuclei. In some instances, the percent tumor cell nuclei (e.g., sample fraction) is determined (e.g., calculated) by dividing the number of tumor cells in the sample by the total number of all cells within the sample that have nuclei. In some instances, for example when the sample is a liver sample comprising hepatocytes, a different tumor content calculation may be required due to the presence of hepatocytes having nuclei with twice, or more than twice, the DNA content of other, e.g., non-hepatocyte, somatic cell nuclei. In some instances, the sensitivity of detection of a genetic alteration, e.g., a variant sequence, or a determination of, e.g., micro satellite instability, may depend on the tumor content of the sample. For example, a sample having a lower tumor content can result in lower sensitivity of detection for a given size sample.

[0086] In some instances, as noted above, the sample comprises nucleic acid (e.g., DNA, RNA (or a cDNA derived from the RNA), or both), e.g., from a tumor or from normal tissue. In certain instances, the sample may further comprise a non-nucleic acid component, e.g., cells, protein, carbohydrate, or lipid, e.g., from the tumor or normal tissue.Subjects

[0087] In some instances, the sample is obtained (e.g., collected) from a subject (e.g., patient) with a condition or disease (e.g., a hyperproliferative disease or a non-cancer indication) or suspected of having the condition or disease. In some instances, the hyperproliferative disease is a cancer. In some instances, the cancer is a solid tumor or a metastatic form thereof. In some instances, the cancer is a hematological cancer, e.g., a leukemia or lymphoma.

[0088] In some instances, the subject has a cancer or is at risk of having a cancer. For example, in some instances, the subject has a genetic predisposition to a cancer (e.g., having a genetic mutation that increases his or her baseline risk for developing a cancer). In some instances, the subject has been exposed to an environmental perturbation (e.g., radiation or a chemical) that increases his or her risk for developing a cancer. In some instances, the subject is in need of being monitored for development of a cancer. In some instances, the subject is in need of being monitored for cancer progression or regression, e.g., after being treated with an anti-cancer therapy (or anti-cancer treatment). In some instances, the subject is in need of being monitored for relapse of cancer. In some instances, the subject is in need of being monitored for minimum residual disease (MRD). In some instances, the subject has been, oris being treated, for cancer. In some instances, the subject has not been treated with an anticancer therapy (or anti-cancer treatment).

[0089] In some instances, the subject (e.g., a patient) is being treated, or has been previously treated, with one or more targeted therapies. In some instances, e.g., for a patient who has been previously treated with a targeted therapy, a post-targeted therapy sample (e.g., specimen) is obtained (e.g., collected). In some instances, the post-targeted therapy sample is a sample obtained after the completion of the targeted therapy.

[0090] In some instances, the patient has not been previously treated with a targeted therapy. In some instances, e.g., for a patient who has not been previously treated with a targeted therapy, the sample comprises a resection, e.g., an original resection, or a resection following recurrence (e.g., following a disease recurrence post-therapy).Cancers

[0091] In some instances, the sample is acquired from a subject having a cancer. Exemplary cancers include, but are not limited to, B cell cancer (e.g., multiple myeloma), melanomas, breast cancer, lung cancer (such as non-small cell lung carcinoma or NSCLC), bronchus cancer, colorectal cancer, prostate cancer, pancreatic cancer, stomach cancer, ovarian cancer, urinary bladder cancer, brain or central nervous system cancer, peripheral nervous system cancer, esophageal cancer, cervical cancer, uterine or endometrial cancer, cancer of the oral cavity or pharynx, liver cancer, kidney cancer, testicular cancer, biliary tract cancer, small bowel or appendix cancer, salivary gland cancer, thyroid gland cancer, adrenal gland cancer, osteosarcoma, chondrosarcoma, cancer of hematological tissues, adenocarcinomas, inflammatory myofibroblastic tumors, gastrointestinal stromal tumor (GIST), colon cancer, multiple myeloma (MM), myelodysplastic syndrome (MDS), myeloproliferative disorder (MPD), acute lymphocytic leukemia (ALL), acute myelocytic leukemia (AML), chronic myelocytic leukemia (CML), chronic lymphocytic leukemia (CLL), polycythemia Vera, Hodgkin lymphoma, non-Hodgkin lymphoma (NHL), soft-tissue sarcoma, fibrosarcoma, myxosarcoma, liposarcoma, osteogenic sarcoma, chordoma, angiosarcoma, endotheliosarcoma, lymphangiosarcoma, lymphangioendotheliosarcoma, synovioma, mesothelioma, Ewing's tumor, leiomyosarcoma, rhabdomyosarcoma, squamous cell carcinoma, basal cell carcinoma, adenocarcinoma, sweat gland carcinoma, sebaceous gland carcinoma, papillary carcinoma, papillary adenocarcinomas, medullary carcinoma,bronchogenic carcinoma, renal cell carcinoma, hepatoma, bile duct carcinoma, choriocarcinoma, seminoma, embryonal carcinoma, Wilms' tumor, bladder carcinoma, epithelial carcinoma, glioma, astrocytoma, medulloblastoma, craniopharyngioma, ependymoma, pinealoma, hemangioblastoma, acoustic neuroma, oligodendroglioma, meningioma, neuroblastoma, retinoblastoma, follicular lymphoma, diffuse large B-cell lymphoma, mantle cell lymphoma, hepatocellular carcinoma, thyroid cancer, gastric cancer, head and neck cancer, small cell cancers, essential thrombocythemia, agnogenic myeloid metaplasia, hypereosinophilic syndrome, systemic mastocytosis, familiar hypereosinophilia, chronic eosinophilic leukemia, neuroendocrine cancers, carcinoid tumors, and the like.

[0092] In some instances, the cancer comprises acute lymphoblastic leukemia (Philadelphia chromosome positive), acute lymphoblastic leukemia (precursor B-cell), acute myeloid leukemia (FLT3+), acute myeloid leukemia (with an IDH2 mutation), anaplastic large cell lymphoma, basal cell carcinoma, B-cell chronic lymphocytic leukemia, bladder cancer, breast cancer (HER2 overexpressed / amplified), breast cancer (HER2+), breast cancer (HR+, HER2- ), cervical cancer, cholangiocarcinoma, chronic lymphocytic leukemia, chronic lymphocytic leukemia (with 17p deletion), chronic myelogenous leukemia, chronic myelogenous leukemia (Philadelphia chromosome positive), classical Hodgkin lymphoma, colorectal cancer, colorectal cancer (dMMR and MSI-H), colorectal cancer (KRAS wild type), cryopyrin- associated periodic syndrome, a cutaneous T-cell lymphoma, dermatofibrosarcoma protuberans, a diffuse large B-cell lymphoma, fallopian tube cancer, a follicular B-cell nonHodgkin lymphoma, a follicular lymphoma, gastric cancer, gastric cancer (HER2+), a gastroesophageal junction (GEJ) adenocarcinoma, a gastrointestinal stromal tumor, a gastrointestinal stromal tumor (KIT+), a giant cell tumor of the bone, a glioblastoma, granulomatosis with polyangiitis, a head and neck squamous cell carcinoma, a hepatocellular carcinoma, Hodgkin lymphoma, juvenile idiopathic arthritis, lupus erythematosus, a mantle cell lymphoma, medullary thyroid cancer, melanoma, a melanoma with a BRAF V600 mutation, a melanoma with a BRAF V600E or V600K mutation, Merkel cell carcinoma, multicentric Castleman's disease, multiple hematologic malignancies including Philadelphia chromosome-positive ALL and CML, multiple myeloma, myelofibrosis, a non-Hodgkin’s lymphoma, a nonresectable subependymal giant cell astrocytoma associated with tuberous sclerosis, a non-small cell lung cancer, a non-small cell lung cancer (ALK+), a non-small cell lung cancer (PD-L1+), a non-small cell lung cancer (with ALK fusion or ROS1 gene alteration), a non-small cell lung cancer (with BRAF V600E mutation), a non-small cell lungcancer (with an EGFR exon 19 deletion or exon 21 substitution (L858R) mutations), a nonsmall cell lung cancer (with an EGFR T790M mutation), ovarian cancer, ovarian cancer (with a BRCA mutation), pancreatic cancer, a pancreatic, gastrointestinal, or lung origin neuroendocrine tumor, a pediatric neuroblastoma, a peripheral T-cell lymphoma, peritoneal cancer, prostate cancer, a renal cell carcinoma, rheumatoid arthritis, a small lymphocytic lymphoma, a soft tissue sarcoma, a solid tumor (MSI-H / dMMR), a squamous cell cancer of the head and neck, a squamous non-small cell lung cancer, thyroid cancer, a thyroid carcinoma, urothelial cancer, a urothelial carcinoma, or Waldenstrom's macroglobulinemia.

[0093] In some instances, the cancer is a hematologic malignancy (or premaligancy). As used herein, a hematologic malignancy refers to a tumor of the hematopoietic or lymphoid tissues, e.g., a tumor that affects blood, bone marrow, or lymph nodes. Exemplary hematologic malignancies include, but are not limited to, leukemia (e.g., acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), chronic lymphocytic leukemia (CLL), chronic myelogenous leukemia (CML), hairy cell leukemia, acute monocytic leukemia (AMoL), chronic myelomonocytic leukemia (CMML), juvenile myelomonocytic leukemia (JMML), or large granular lymphocytic leukemia), lymphoma (e.g., AIDS-related lymphoma, cutaneous T-cell lymphoma, Hodgkin lymphoma (e.g., classical Hodgkin lymphoma or nodular lymphocyte-predominant Hodgkin lymphoma), mycosis fungoides, non-Hodgkin lymphoma (e.g., B-cell non-Hodgkin lymphoma (e.g., Burkitt lymphoma, small lymphocytic lymphoma (CLL / SLL), diffuse large B-cell lymphoma, follicular lymphoma, immunoblastic large cell lymphoma, precursor B -lymphoblastic lymphoma, or mantle cell lymphoma) or T-cell non- Hodgkin lymphoma (mycosis fungoides, anaplastic large cell lymphoma, or precursor T- lymphoblastic lymphoma)), primary central nervous system lymphoma, Sezary syndrome, Waldenstrom macroglobulinemia), chronic myeloproliferative neoplasm, Langerhans cell histiocytosis, multiple myeloma / plasma cell neoplasm, myelodysplastic syndrome, or myelodysplastic / myeloproliferative neoplasm.Nucleic acid extraction and processing

[0094] DNA or RNA may be extracted from tissue samples, biopsy samples, blood samples, or other bodily fluid samples using any of a variety of techniques known to those of skill in the art (see, e.g., Example 1 of International Patent Application Publication No. WO 2012 / 092426; Tan, et al. (2009), “DNA, RNA, and Protein Extraction: The Past and TheZ1Present”, J. Biomed. Biotech. 2009:574398; the technical literature for the Maxwell® 16 LEV Blood DNA Kit (Promega Corporation, Madison, WI); and the Maxwell 16 Buccal Swab LEV DNA Purification Kit Technical Manual (Promega Literature #TM333, January 1, 2011, Promega Corporation, Madison, WI)). Protocols for RNA isolation are disclosed in, e.g., the Maxwell® 16 Total RNA Purification Kit Technical Bulletin (Promega Literature #TB351, August 2009, Promega Corporation, Madison, WI).

[0095] A typical DNA extraction procedure, for example, comprises (i) collection of the fluid sample, cell sample, or tissue sample from which DNA is to be extracted, (ii) disruption of cell membranes (i.e., cell lysis), if necessary, to release DNA and other cytoplasmic components, (iii) treatment of the fluid sample or lysed sample with a concentrated salt solution to precipitate proteins, lipids, and RNA, followed by centrifugation to separate out the precipitated proteins, lipids, and RNA, and (iv) purification of DNA from the supernatant to remove detergents, proteins, salts, or other reagents used during the cell membrane lysis step.

[0096] Disruption of cell membranes may be performed using a variety of mechanical shear (e.g., by passing through a French press or fine needle) or ultrasonic disruption techniques. The cell lysis step often comprises the use of detergents and surfactants to solubilize lipids the cellular and nuclear membranes. In some instances, the lysis step may further comprise use of proteases to break down protein, and / or the use of an RNase for digestion of RNA in the sample.

[0097] Examples of suitable techniques for DNA purification include, but are not limited to,(i) precipitation in ice-cold ethanol or isopropanol, followed by centrifugation (precipitation of DNA may be enhanced by increasing ionic strength, e.g., by addition of sodium acetate),(ii) phenol-chloroform extraction, followed by centrifugation to separate the aqueous phase containing the nucleic acid from the organic phase containing denatured protein, and (iii) solid phase chromatography where the nucleic acids adsorb to the solid phase (e.g., silica or other) depending on the pH and salt concentration of the buffer.

[0098] In some instances, cellular and histone proteins bound to the DNA may be removed either by adding a protease or by having precipitated the proteins with sodium or ammonium acetate, or through extraction with a phenol-chloroform mixture prior to a DNA precipitation step.

[0099] In some instances, DNA may be extracted using any of a variety of suitable commercial DNA extraction and purification kits. Examples include, but are not limited to,the QIAamp (for isolation of genomic DNA from human samples) and DNAeasy (for isolation of genomic DNA from animal or plant samples) kits from Qiagen (Germantown, MD) or the Maxwell® and ReliaPrep™ series of kits from Promega (Madison, WI).

[0100] As noted above, in some instances the sample may comprise a formalin-fixed (also known as formaldehyde-fixed, or paraformaldehyde-fixed), paraffin-embedded (FFPE) tissue preparation. For example, the FFPE sample may be a tissue sample embedded in a matrix, e.g., an FFPE block. Methods to isolate nucleic acids (e.g., DNA) from formaldehyde- or paraformaldehyde-fixed, paraffin-embedded (FFPE) tissues are disclosed in, e.g., Cronin, et al., (2004) Am J Pathol. 164(1):35— 42; Masuda, et al., (1999) Nucleic Acids Res.27(22) :4436-4443; Specht, et al., (2001) Am J Pathol. 158(2):419— 429; the AmbionRecoverAll™ Total Nucleic Acid Isolation Protocol (Ambion, Cat. No. AM1975, September 2008); the Maxwell® 16 FFPE Plus LEV DNA Purification Kit Technical Manual (Promega Literature #TM349, February 2011); the E.Z.N.A.® FFPE DNA Kit Handbook (OMEGA bio- tek, Norcross, GA, product numbers D3399-00, D3399-01, and D3399-02, June 2009); and the QIAamp® DNA FFPE Tissue Handbook (Qiagen, Cat. No. 37625, October 2007). For example, the RecoverAll™ Total Nucleic Acid Isolation Kit uses xylene at elevated temperatures to solubilize paraffin-embedded samples and a glass-fiber filter to capture nucleic acids. The Maxwell® 16 FFPE Plus LEV DNA Purification Kit is used with theMaxwell® 16 Instrument for purification of genomic DNA from 1 to 10 pm sections of FFPE tissue. DNA is purified using silica-clad paramagnetic particles (PMPs), and eluted in low elution volume. The E.Z.N.A.® FFPE DNA Kit uses a spin column and buffer system for isolation of genomic DNA. QIAamp® DNA FFPE Tissue Kit uses QIAamp® DNA Micro technology for purification of genomic and mitochondrial DNA.

[0101] In some instances, the disclosed methods may further comprise determining or acquiring a yield value for the nucleic acid extracted from the sample and comparing the determined value to a reference value. In some instances, the disclosed methods may further comprise determining or acquiring a value for the size (or average size) of nucleic acid fragments in the sample, and comparing the determined or acquired value to a reference value, e.g., a size (or average size) of at least 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1000 base pairs (bps). In some instances, one or more parameters described herein may be adjusted or selected in response to this determination.

[0102] After isolation, the nucleic acids are typically dissolved in a slightly alkaline buffer, e.g., Tris-EDTA (TE) buffer, or in ultra-pure water. In some instances, the isolated nucleicacids (e.g., genomic DNA) may be fragmented or sheared by using any of a variety of techniques known to those of skill in the art. For example, genomic DNA can be fragmented by physical shearing methods, enzymatic cleavage methods, chemical cleavage methods, and other methods known to those of skill in the art. Methods for DNA shearing are described in Example 4 in International Patent Application Publication No. WO 2012 / 092426. In some instances, alternatives to DNA shearing methods can be used to avoid a ligation step during library preparation.Methods of using the prepared sequencing library

[0103] In some instances, the disclosed methods may further comprise one or more of the steps of: (i) appending or adapting the nucleic acid molecules extracted from the sample as a part of configuring the nucleic acid molecules for targeting gene loci for analysis, such as by hybridizing to a substrate (e.g., flow cells) and / or to provide indexing, (ii) capturing nucleic acid molecules from the amplified nucleic acid molecules (e.g., by hybridization to one or more bait molecules, where the bait molecules each comprise one or more nucleic acid molecules that each comprising a region that is complementary to a region of a captured nucleic acid molecule), (iii) sequencing the nucleic acid molecules extracted from the sample (or library proxies derived therefrom) using, e.g., a next-generation (massively parallel) sequencing technique, a whole genome sequencing (WGS) technique, a whole exome sequencing technique, a targeted sequencing technique, a direct sequencing technique, or a Sanger sequencing technique) using, e.g., a next-generation (massively parallel) sequencer, and (iv) generating, displaying, transmitting, and / or delivering a report (e.g., an electronic, web-based, or paper report) to the subject (or patient), a caregiver, a healthcare provider, a physician, an oncologist, an electronic medical record system, a hospital, a clinic, a third- party payer, an insurance company, or a government office. In some instances, the report comprises output from the methods described herein. In some instances, all or a portion of the report may be displayed in the graphical user interface of an online or web-based healthcare portal. In some instances, the report is transmitted via a computer network or peer-to-peer connection.Targeting gene loci for analysis

[0104] The methods described herein can be used in combination with, or as part of, a method for evaluating a plurality or set of subject intervals (e.g., target sequences), e.g., from a set of genomic loci (e.g., gene loci or fragments thereof), as described herein. For example, the methods of preparing a nucleic acid library described herein can be used to provide nucleic acid molecules, from which some DNA sequences can be sequenced and / or the methylation patterns of the nucleic acid sequences can be analyzed.

[0105] The targeted gene may include coding and / or noncoding portions of the gene. Noncoding portions of the gene may include, for example, introns or one or more regulatory elements (e.g., promoters, etc.) of the gene. By way of example, in some embodiments, one or more CpG sites of a gene promotor region is targeted, e.g., for analysis according to the methods described herein.

[0106] In some instances, the set of genomic loci evaluated by the disclosed methods comprises a plurality of, e.g., genes, which in mutant form, are associated with an effect on cell division, growth or survival, or are associated with a cancer, e.g., a cancer described herein. In some instances, the mutant form of the genes associated with effects on biological processes (e.g., cell division, growth, or survival, or are associated with a cancer, e.g., a cancer described herein), can correspond to a methylation pattern or a methylation signature that is less commonly found (e.g., not commonly found) in health subjects.

[0107] In some instances, the set of gene loci evaluated by the disclosed methods comprises at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 20, at least 30, at least 40, at least 50, at least 60, at least 70, at least 80, at least 90, at least 100, or more than 100 gene loci.

[0108] In some instances, the selected gene loci (also referred to herein as target gene loci or target sequences), or fragments thereof, may include subject intervals comprising non-coding sequences, coding sequences, intragenic regions, or intergenic regions of the subject genome. For example, the subject intervals can include a non-coding sequence or fragment thereof (e.g., a promoter sequence, enhancer sequence, 5’ untranslated region (5’ UTR), 3’ untranslated region (3’ UTR), or a fragment thereof), a coding sequence of fragment thereof, an exon sequence or fragment thereof, an intron sequence or a fragment thereof. The noncoding regions can comprise non-coding regions that can correspond to methylation patterns,e.g., GC-rich non-coding regions such as LI non-coding regions, promoter regions, and enhancer regions.Target capture reagents

[0109] The methods described herein may comprise contacting a nucleic acid library with a plurality of target capture reagents to select and capture a plurality of specific target sequences (e.g., gene sequences or fragments thereof) for analysis. In some instances, a target capture reagent (i.e., a molecule which can bind to and thereby allow capture of a target molecule) is used to select the subject intervals to be analyzed. For example, a target capture reagent can be a bait molecule, e.g., a nucleic acid molecule (e.g., a DNA molecule or RNA molecule) which can hybridize to (i.e., is complementary to) a target molecule, and thereby allows capture of the target nucleic acid. In some instances, the target capture reagent, e.g., a bait molecule (or bait sequence), is a capture oligonucleotide (or capture probe). In some instances, the target nucleic acid is a genomic DNA molecule, an RNA molecule, a cDNA molecule derived from an RNA molecule, a microsatellite DNA sequence, and the like. In some instances, the target capture reagent is suitable for solution-phase hybridization to the target. In some instances, the target capture reagent is suitable for solid-phase hybridization to the target. In some instances, the target capture reagent is suitable for both solution-phase and solid-phase hybridization to the target. The design and construction of target capture reagents is described in more detail in, e.g., International Patent Application Publication No. WO 2020 / 236941, the entire content of which is incorporated herein by reference.

[0110] The methods described herein provide for optimized sequencing of a large number of genomic loci (e.g., genes or gene products (e.g., mRNA), micro satellite loci, etc.) from samples (e.g., cancerous tissue specimens, liquid biopsy samples, and the like) from one or more subjects by the appropriate selection of target capture reagents to select the target nucleic acid molecules to be sequenced. In some instances, a target capture reagent may hybridize to a specific target locus, e.g., a specific target gene locus or fragment thereof. In some instances, a target capture reagent may hybridize to a specific group of target loci, e.g., a specific group of gene loci or fragments thereof. In some instances, a plurality of target capture reagents comprising a mix of target- specific and / or group- specific target capture reagents may be used.

[0111] In some instances, the number of target capture reagents (e.g., bait molecules) in the plurality of target capture reagents (e.g., a bait set) contacted with a nucleic acid library to capture a plurality of target sequences for nucleic acid sequencing is greater than 10, greater than 50, greater than 100, greater than 200, greater than 300, greater than 400, greater than 500, greater than 600, greater than 700, greater than 800, greater than 900, greater than 1,000, greater than 1,250, greater than 1,500, greater than 1,750, greater than 2,000, greater than 3,000, greater than 4,000, greater than 5,000, greater than 10,000, greater than 25,000, or greater than 50,000.

[0112] In some instances, the overall length of the target capture reagent sequence can be between about 70 nucleotides and 1000 nucleotides. In one instance, the target capture reagent length is between about 100 and 300 nucleotides, 110 and 200 nucleotides, or 120 and 170 nucleotides, in length. In addition to those mentioned above, intermediate oligonucleotide lengths of about 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220, 230, 240, 250, 300, 400, 500, 600, 700, 800, and 900 nucleotides in length can be used in the methods described herein. In some embodiments, oligonucleotides of about 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220, or 230 bases can be used.

[0113] In some instances, each target capture reagent sequence can include: (i) a targetspecific capture sequence (e.g., a gene locus or micro satellite locus-specific complementary sequence), (ii) an adapter, primer, barcode, and / or unique molecular identifier sequence, and (iii) universal tails on one or both ends. As used herein, the term "target capture reagent" can refer to the target- specific target capture sequence or to the entire target capture reagent oligonucleotide including the target- specific target capture sequence.

[0114] In some instances, the target- specific capture sequences in the target capture reagents are between about 40 nucleotides and 1000 nucleotides in length. In some instances, the target- specific capture sequence is between about 70 nucleotides and 300 nucleotides in length. In some instances, the target- specific sequence is between about 100 nucleotides and 200 nucleotides in length. In yet other instances, the target- specific sequence is between about 120 nucleotides and 170 nucleotides in length, typically 120 nucleotides in length. Intermediate lengths in addition to those mentioned above also can be used in the methods described herein, such as target- specific sequences of about 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220, 230, 240, 250, 300, 400, 500, 600,700, 800, and 900 nucleotides in length, as well as target- specific sequences of lengths between the above-mentioned lengths.

[0115] In some instances, the target capture reagent can comprise a gene panel that is configured to capture and / or identify specific sequences, such as genes, although non-coding sequences can also be captured and / or identified in the nominally referred to gene panel. The gene panel may comprise at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 20, at least 30, at least 40, or more than 40 genes.

[0116] In some instances, the disclosed methods may comprise target capture reagents configured to capture and / or identify specific sequences, such as variants in the ABL1, ACVR1B, AKT1, AKT2, AKT3, ALK, ALOX12B, AMER1, APC, AR, ARAF, ARFRP1, ARID1A, ASXL1, ATM, ATR, ATRX, AURKA, AURKB, AXIN1, AXL, BAP1, BARD1, BCL2, BCL2L1, BCL2L2, BCL6, BCOR, BCORL1, BCR, BRAF, BRCA1, BRCA2, BRD4, BRIP1, BTG1, BTG2, BTK, CALR, CARD11, CASP8, CBFB, CBL, CCND1, CCND2, CCND3, CCNE1, CD22, CD274, CD70, CD74, CD79A, CD79B, CDC73, CDH1, CDK12, CDK4, CDK6, CDK8, CDKN1A, CDKN1B, CDKN2A, CDKN2B, CDKN2C, CEBPA, CHEK1, CHEK2, CIC, CREBBP, CRKL, CSF1R, CSF3R, CTCF, CTNNA1, CTNNB1, CUL3, CUL4A, CXCR4, CYP17A1, DAXX, DDR1, DDR2, DIS3, DNMT3A, DOT1L, EED, EGFR, EMSY (Cllorf30), EP300, EPHA3, EPHB1, EPHB4, ERBB2, ERBB3, ERBB4, ERCC4, ERG, ERRFI1, ESRI, ETV4, ETV5, ETV6, EWSR1, EZH2, EZR, FAM46C, FANCA, FANCC, FANCG, FANCL, FAS, FBXW7, FGF10, FGF12, FGF14, FGF19, FGF23, FGF3, FGF4, FGF6, FGFR1, FGFR2, FGFR3, FGFR4, FH, FLCN, FLT1, FLT3, FOXL2, FUBP1, GABRA6, GATA3, GATA4, GATA6, GID4 (C17orf39), GNA11, GNA13, GNAQ, GNAS, GRM3, GSK3B, H3F3A, HDAC1, HGF, HNF1A, HRAS, HSD3B1, ID3, IDH1, IDH2, IGF1R, IKBKE, IKZF1, INPP4B, IRF2, IRF4, IRS2, JAK1, JAK2, JAK3, JUN, KDM5A, KDM5C, KDM6A, KDR, KEAP1, KEL, KIT, KLHL6, KMT2A (MLL), KMT2D (MLL2), KRAS, LTK, LYN, MAF, MAP2K1, MAP2K2, MAP2K4, MAP3K1, MAP3K13, MAPK1, MCL1, MDM2, MDM4, MED12, MEF2B, MEN1, MERTK, MET, MITF, MKNK1, MLH1, MPL, MRE11A, MSH2, MSH3, MSH6, MST1R, MTAP, MTOR, MUTYH, MYB, MYC, MYCL, MYCN, MYD88, NBN, NF1, NF2, NFE2L2, NFKBIA, NKX2-1, NOTCH1, NOTCH2, NOTCH3, NPM1, NRAS, NT5C2, NTRK1, NTRK2, NTRK3, NUTM1, P2RY8, PALB2, PARK2, PARP1, PARP2, PARP3, PAX5, PBRM1, PDCD1, PDCD1LG2, PDGFRA, PDGFRB, PDK1, PIK3C2B, PIK3C2G, PIK3CA, PIK3CB, PIK3R1, PIM1, PMS2, POLDI, POLE, PPARG, PPP2R1A, PPP2R2A,PRDM1, PRKAR1A, PRKCI, PTCHI, PTEN, PTPN11, PTPRO, QKI, RAC1, RAD21, RAD51, RAD51B, RAD51C, RAD51D, RAD52, RAD54L, RAFI, RARA, RBI, RBM10, REL, RET, RICTOR, RNF43, ROS1, RPTOR, RSPO2, SDC4, SDHA, SDHB, SDHC, SDHD, SETD2, SF3B1, SGK1, SLC34A2, SMAD2, SMAD4, SMARCA4, SMARCB1, SMO, SNCAIP, SOCS1, SOX2, SOX9, SPEN, SPOP, SRC, STAG2, STAT3, STK11, SUFU, SYK, TBX3, TEK, TERC, TERT, TET2, TGFBR2, TIP ARP, TMPRSS2, TNFAIP3, TNFRSF14, TP53, TSC1, TSC2, TYRO3, U2AF1, VEGFA, VHL, WHSCI, WHSC1L1, WT1, XPO1, XRCC2, ZNF217, or ZNF703 gene locus, or any combination thereof.

[0117] In some instances, the disclosed methods may comprise target capture reagents configured to capture and / or identify variants in the ABL, ALK, ALL, B4GALNT1, BAFF, BCL2, BRAF, BRCA, BTK, CD19, CD20, CD3, CD30, CD319, CD38, CD52, CDK4, CDK6, CML, CRACC, CS1, CTLA-4, dMMR, EGFR, ERBB1, ERBB2, FGFR1-3, FLT3, GD2, HDAC, HER1, HER2, HR, IDH2, IL-1 , IL-6, IL-6R, JAK1, JAK2, JAK3, KIT, KRAS, MEK, MET, MSI-H, mTOR, PARP, PD-1, PDGFR, PDGFRa, PDGFRp, PD-L1, PI3K5, PIGF, PTCH, RAF, RANKL, RET, ROS1, SLAMF7, VEGF, VEGFA, or VEGFB gene locus, or any combination thereof.

[0118] In some embodiments, the one or more gene loci comprise CpG sites within one or more gene promoter regions of interest. The CpG sites may include genomic regions with, for example, at least 200-500 base pairs having at least 50 bases in a CG sequence in the 5’ to 3’ direction (i.e., regions in the nucleic acid sequence, which comprise cytosine (C) followed by guanine (G)).

[0119] In some instances, the target capture reagent may be designed to select a subject interval containing one or more rearrangements, e.g., an intron containing a genomic rearrangement. In such instances, the target capture reagent is designed such that repetitive sequences are masked to increase the selection efficiency. In those instances where the rearrangement has a known juncture sequence, complementary target capture reagents can be designed to recognize the juncture sequence to increase the selection efficiency.

[0120] In some instances, the disclosed methods may comprise the use of target capture reagents designed to capture two or more different target categories, each category having a different target capture reagent design strategy. In some instances, the hybridization-based capture methods and target capture reagent compositions disclosed herein may provide for the capture and homogeneous coverage of a set of target sequences, while minimizing coverage of genomic sequences outside of the targeted set of sequences. In some instances,the target sequences may include the entire exome of genomic DNA or a selected subset thereof. In some instances, the target sequences may include, e.g., a large chromosomal region (e.g., a whole chromosome arm). The methods and compositions disclosed herein provide different target capture reagents for achieving different sequencing depths and patterns of coverage for complex sets of target nucleic acid sequences.

[0121] Typically, DNA molecules are used as target capture reagent sequences, although RNA molecules can also be used. In some instances, a DNA molecule target capture reagent can be single stranded DNA (ssDNA) or double-stranded DNA (dsDNA). In some instances, an RNA-DNA duplex is more stable than a DNA-DNA duplex and therefore provides for potentially better capture of nucleic acids.

[0122] In some instances, the disclosed methods comprise providing a selected set of nucleic acid molecules (e.g., a library catch) captured from one or more nucleic acid libraries. For example, the method may comprise: providing one or a plurality of nucleic acid libraries, each comprising a plurality of nucleic acid molecules (e.g., a plurality of target nucleic acid molecules and / or reference nucleic acid molecules) extracted from one or more samples from one or more subjects; contacting the one or a plurality of libraries (e.g., in a solution-based hybridization reaction) with one, two, three, four, five, or more than five pluralities of target capture reagents (e.g., oligonucleotide target capture reagents) to form a hybridization mixture comprising a plurality of target capture reagent / nucleic acid molecule hybrids; separating the plurality of target capture reagent / nucleic acid molecule hybrids from said hybridization mixture, e.g., by contacting said hybridization mixture with a binding entity that allows for separation of said plurality of target capture reagent / nucleic acid molecule hybrids from the hybridization mixture, thereby providing a library catch (e.g., a selected or enriched subgroup of nucleic acid molecules from the one or a plurality of libraries).

[0123] In some instances, the disclosed methods may further comprise amplifying the library catch (e.g., by performing PCR). In other instances, the library catch is not amplified.

[0124] In some instances, the target capture reagents can be part of a kit which can optionally comprise instructions, standards, buffers or enzymes or other reagents.Hybridization conditions

[0125] As noted above, the methods disclosed herein may include the step of contacting the library (e.g., the nucleic acid library) with a plurality of target capture reagents to provide aselected library target nucleic acid sequences (i.e., the library catch). The contacting step can be effected in, e.g., solution-based hybridization. In some instances, the method includes repeating the hybridization step for one or more additional rounds of solution-based hybridization. In some instances, the method further includes subjecting the library catch to one or more additional rounds of solution-based hybridization with the same or a different collection of target capture reagents.

[0126] In some instances, the contacting step is effected using a solid support, e.g., an array. Suitable solid supports for hybridization are described in, e.g., Albert, T.J. et al. (2007) Nat. Methods 4(1 l):903-5; Hodges, E. et al. (2007) Nat. Genet. 39(12): 1522-7; and Okou, D.T. et al. (2007) Nat. Methods 4( 1 l):907-9, the contents of which are incorporated herein by reference in their entireties. In some instances, the solid support for the contacting step can comprise a plurality of beads, such as beads comprising a silica surface, beads comprising a carboxyl surface, solid-phase reverse immobilization (SPRI) beads, or a combination thereof.

[0127] Hybridization methods that can be adapted for use in the methods herein are described in the art, e.g., as described in International Patent Application Publication No. WO 2012 / 092426. Methods for hybridizing target capture reagents to a plurality of target nucleic acids are described in more detail in, e.g., International Patent Application Publication No. WO 2020 / 236941, the entire content of which is incorporated herein by reference.Sequencing methods

[0128] The methods and systems disclosed herein can be used in combination with, or as part of, a method or system for sequencing nucleic acids (e.g., a next-generation sequencing system) to generate a plurality of sequence reads that overlap one or more gene loci within a subgenomic interval in the sample and thereby determine, e.g., gene allele sequences at a plurality of gene loci. “Next-generation sequencing” (or “NGS”) as used herein may also be referred to as “massively parallel sequencing” (or “MPS”), and refers to any sequencing method that determines the nucleotide sequence of either individual nucleic acid molecules (e.g., as in single molecule sequencing) or clonally expanded proxies for individual nucleic acid molecules in a high throughput fashion (e.g., wherein greater than 103, 104, 105or more than 105molecules are sequenced simultaneously).

[0129] Next-generation sequencing methods are known in the art, and are described in, e.g., Metzker, M. (2010) Nature Biotechnology Reviews 11:31-46, which is incorporated herein byreference. Other examples of sequencing methods suitable for use when implementing the methods and systems disclosed herein are described in, e.g., International Patent Application Publication No. WO 2012 / 092426. In some instances, the sequencing may comprise, for example, whole genome sequencing (WGS), whole exome sequencing, targeted sequencing, or direct sequencing. In some instances, sequencing may be performed using, e.g., Sanger sequencing. In some instances, the sequencing may comprise a paired-end sequencing technique that allows both ends of a fragment to be sequenced and generates high-quality, alignable sequence data for detection of, e.g., genomic rearrangements, repetitive sequence elements, gene fusions, and novel transcripts.

[0130] The disclosed methods and systems may be implemented using sequencing platforms such as the Roche 454, Illumina Solexa, ABI-SOLiD, ION Torrent, Complete Genomics, Pacific Bioscience, Helicos, and / or the Polonator platform. In some instances, sequencing may comprise Illumina MiSeq sequencing. In some instances, sequencing may comprise Illumina HiSeq sequencing. In some instances, sequencing may comprise Illumina NovaSeq sequencing. Optimized methods for sequencing a large number of target genomic loci in nucleic acids extracted from a sample are described in more detail in, e.g., International Patent Application Publication No. WO 2020 / 236941, the entire content of which is incorporated herein by reference.

[0131] In certain instances, the disclosed methods comprise one or more of the steps of: (a) acquiring a library comprising a plurality of normal and / or tumor nucleic acid molecules from a sample; (b) simultaneously or sequentially contacting the library with one, two, three, four, five, or more than five pluralities of target capture reagents under conditions that allow hybridization of the target capture reagents to the target nucleic acid molecules, thereby providing a selected set of captured normal and / or tumor nucleic acid molecules (i.e., a library catch); (c) separating the selected subset of the nucleic acid molecules (e.g., the library catch) from the hybridization mixture, e.g., by contacting the hybridization mixture with a binding entity that allows for separation of the target capture reagent / nucleic acid molecule hybrids from the hybridization mixture, (d) sequencing the library catch to acquiring a plurality of reads (e.g., sequence reads) that overlap one or more subject intervals (e.g., one or more target sequences) from said library catch that may comprise a mutation (or alteration), e.g., a variant sequence comprising a somatic mutation or germline mutation; (e) aligning said sequence reads using an alignment method as described elsewhere herein; and / or (f) assigning a nucleotide value for a nucleotide position in the subject interval (e.g.,calling a mutation using, e.g., a Bayesian method or other method described herein) from one or more sequence reads of the plurality.

[0132] In some instances, the library (or a portion thereof) may comprise one or more subgenomic intervals. In some instances, a subgenomic interval can be a single nucleotide position, e.g., a nucleotide position for which a variant at the position is associated (positively or negatively) with a tumor phenotype. In some instances, a subgenomic interval comprises more than one nucleotide position. Such instances include sequences of at least 2, 5, 10, 50, 100, 150, 250, or more than 250 nucleotide positions in length. Subgenomic intervals can comprise, e.g., one or more entire genes (or portions thereof), one or more exons or coding sequences (or portions thereof), one or more introns (or portion thereof), one or more micro satellite region (or portions thereof), or any combination thereof. A subgenomic interval can comprise all or a part of a fragment of a naturally occurring nucleic acid molecule, e.g., a genomic DNA molecule. For example, a subgenomic interval can correspond to a fragment of genomic DNA which is subjected to a sequencing reaction. In some instances, a subgenomic interval is a continuous sequence from a genomic source. In some instances, a subgenomic interval includes sequences that are not contiguous in the genome, e.g., subgenomic intervals in cDNA can include exon-exon junctions formed as a result of splicing. In some instances, the subgenomic interval comprises a tumor nucleic acid molecule. In some instances, the subgenomic interval comprises a non-tumor nucleic acid molecule.

[0133] Examples of nucleic acid library preparation techniques for next-generation sequencing, including those already described herein, can be found in, e.g., van Dijk, et al. (2014), Exp. Cell Research 322:12 - 20, and Illumina’s genomic DNA sample preparation kit.

[0134] In some instances, the resulting nucleic acid library may contain all or substantially all of the complexity of the genome. The term “substantially all” in this context refers to the possibility that there can in practice be some unwanted loss of genome complexity during the initial steps of the procedure. The methods described herein also are useful in cases where the nucleic acid library comprises a portion of the genome, e.g., where the complexity of the genome is reduced by design. In some instances, any selected portion of the genome can be used with a method described herein. For example, in certain embodiments, the entire exome or a subset thereof is isolated. In some instances, the library may include at least 95%, 90%, 80%, 70%, 60%, 50%, 40%, 30%, 20%, 10%, or 5% of the genomic or cell-free DNA. Insome instances, the library may consist of cDNA copies of genomic DNA that includes copies of at least 95%, 90%, 80%, 70%, 60%, 50%, 40%, 30%, 20%, 10%, or 5% of the genomic DNA. In certain instances, the amount of nucleic acid used to generate the nucleic acid library may be less than 5 micrograms, less than 1 microgram, less than 500 ng, less than 200 ng, less than 100 ng, less than 50 ng, less than 10 ng, less than 5 ng, or less than 1 ng.

[0135] In some instances, a library (e.g., a nucleic acid library) includes a collection of nucleic acid molecules. The nucleic acid molecules of the library can include a target nucleic acid molecule (e.g., a tumor nucleic acid molecule, a reference nucleic acid molecule and / or a control nucleic acid molecule; also referred to herein as a first, second and / or third nucleic acid molecule, respectively). The nucleic acid molecules of the library can be from a single subject or individual. In some instances, a library can comprise nucleic acid molecules derived from more than one subject (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30 or more subjects). For example, two or more libraries from different subjects can be combined to form a library having nucleic acid molecules from more than one subject (where the nucleic acid molecules derived from each subject are optionally ligated to a unique sample barcode corresponding to a specific subject). In some instances, the subject is a human having, or at risk of having, a cancer or tumor.

[0136] In some instances, acquiring sequence reads for one or more subject intervals may comprise sequencing at least 1, at least 5, at least 10, at least 20, at least 30, at least 40, at least 50, at least 100, at least 150, at least 200, at least 250, at least 300, at least 350, at least 400, at least 450, at least 500, at least 550, at least 600, at least 650, at least 700, at least 750, at least 800, at least 850, at least 900, at least 950, at least 1,000, at least 1,250, at least 1,500, at least 1,750, at least 2,000, at least 2,250, at least 2,500, at least 2,750, at least 3,000, at least 3,500, at least 4,000, at least 4,500, or at least 5,000 loci, e.g., genomic loci, gene loci, micro satellite loci, etc. In some instances, acquiring a sequence read for one or more subject intervals may comprise sequencing a subject interval for any number of loci within the range described in this paragraph, e.g., for at least 2,850 gene loci.

[0137] In some instances, acquiring a sequence read for one or more subject intervals comprises sequencing a subject interval with a sequencing method that provides a sequence read length (or average sequence read length) of at least 20 bases, at least 30 bases, at least 40 bases, at least 50 bases, at least 60 bases, at least 70 bases, at least 80 bases, at least 90 bases, at least 100 bases, at least 120 bases, at least 140 bases, at least 160 bases, at least 180 bases, at least 200 bases, at least 220 bases, at least 240 bases, at least 260 bases, at least 280 bases,at least 300 bases, at least 320 bases, at least 340 bases, at least 360 bases, at least 380 bases, or at least 400 bases. In some instances, acquiring a sequence read for the one or more subject intervals may comprise sequencing a subject interval with a sequencing method that provides a sequence read length (or average sequence read length) of any number of bases within the range described in this paragraph, e.g., a sequence read length (or average sequence read length) of 56 bases.

[0138] In some instances, acquiring a sequence read for one or more subject intervals may comprise sequencing with at least lOOx or more coverage (or depth) on average. In some instances, acquiring a sequence read for one or more subject intervals may comprise sequencing with at least lOOx, at least 150x, at least 200x, at least 250x, at least 500x, at least 750x, at least l,000x, at least 1,500 x, at least 2,000x, at least 2,500x, at least 3,000x, at least 3,500x, at least 4,000x, at least 4,500x, at least 5,000x, at least 5,500x, or at least 6,000x or more coverage (or depth) on average. In some instances, acquiring a sequence read for one or more subject intervals may comprise sequencing with an average coverage (or depth) having any value within the range of values described in this paragraph, e.g., at least 160x.

[0139] In some instances, acquiring a read for the one or more subject intervals comprises sequencing with an average sequencing depth having any value ranging from at least lOOx to at least 6,000x for greater than about 90%, 92%, 94%, 95%, 96%, 97%, 98%, or 99% of the gene loci sequenced. For example, in some instances acquiring a read for the subject interval comprises sequencing with an average sequencing depth of at least 125x for at least 99% of the gene loci sequenced. As another example, in some instances acquiring a read for the subject interval comprises sequencing with an average sequencing depth of at least 4,100x for at least 95% of the gene loci sequenced.

[0140] In some instances, the relative abundance of a nucleic acid species in the library can be estimated by counting the relative number of occurrences of their cognate sequences (e.g., the number of sequence reads for a given cognate sequence) in the data generated by the sequencing experiment.

[0141] In some instances, the disclosed methods and systems provide nucleotide sequences for a set of subject intervals (e.g., gene loci), as described herein. In certain instances, the sequences are provided without using a method that includes a matched normal control (e.g., a wild-type control) and / or a matched tumor control (e.g., primary versus metastatic).

[0142] In some instances, the level of sequencing depth as used herein (e.g., an X-fold level of sequencing depth) refers to the number of reads (e.g., unique reads) obtained afterdetection and removal of duplicate reads (e.g., PCR duplicate reads). In other instances, duplicate reads are evaluated, e.g., to support detection of copy number alteration (CNAs).Alignment

[0143] Alignment is the process of matching a read with a location, e.g., a genomic location or locus. In some instances, NGS reads, such as those used for identifying sequences corresponding to methylation patterns, may be aligned to a known reference sequence (e.g. , a wild-type sequence). In some instances, NGS reads may be assembled de novo. Methods of sequence alignment for NGS reads are described in, e.g., Trapnell, C. and Salzberg, S.L. Nature Biotech., 2009, 27:455-457. Examples of de novo sequence assemblies are described in, e.g., Warren R., et al., Bioinformatics, 2007, 23:500-501; Butler, J. et al., Genome Res., 2008, 18:810-820; and Zerbino, D.R. and Birney, E., Genome Res., 2008, 18:821-829. Optimization of sequence alignment is described in the art, e.g., as set out in International Patent Application Publication No. WO 2012 / 092426. Additional description of sequence alignment methods is provided in, e.g., International Patent Application Publication No. WO 2020 / 236941, the entire content of which is incorporated herein by reference.

[0144] Misalignment (e.g., the placement of base-pairs from a short read at incorrect locations in the genome), e.g., misalignment of reads due to sequence context (e.g., the presence of repetitive sequence) around an actual cancer mutation can lead to reduction in sensitivity of mutation detection, can lead to a reduction in sensitivity of mutation detection, as reads for the alternate allele may be shifted off the histogram peak of alternate allele reads. Other examples of sequence context that may cause misalignment include short-tandem repeats, interspersed repeats, low complexity regions, insertions - deletions (indels), and paralogs. If the problematic sequence context occurs where no actual mutation is present, misalignment may introduce artifactual reads of “mutated” alleles by placing reads of actual reference genome base sequences at the wrong location. Because mutation-calling algorithms for multigene analysis should be sensitive to even low-abundance mutations, sequence misalignments may increase false positive discovery rates and / or reduce specificity.

[0145] In some instances, the methods and systems disclosed herein may integrate the use of multiple, individually-tuned, alignment methods or algorithms to optimize base-calling performance in sequencing methods, particularly in methods that rely on massively parallel sequencing (MPS) of a large number of diverse genetic events at a large number of diversegenomic loci. In some instances, the disclosed methods and systems may comprise the use of one or more global alignment algorithms. In some instances, the disclosed methods and systems may comprise the use of one or more local alignment algorithms. Examples of alignment algorithms that may be used include, but are not limited to, the Burrows-Wheeler Alignment (BWA) software bundle (see, e.g., Li, et al. (2009), “Fast and Accurate Short Read Alignment with Burrows-Wheeler Transform”, Bioinformatics 25:1754-60; Li, et al. (2010), Fast and Accurate Long-Read Alignment with Burrows-Wheeler Transform”, Bioinformatics epub. PMID: 20080505), the Smith-Waterman algorithm (see, e.g., Smith, et al. (1981), "Identification of Common Molecular Subsequences", J. Molecular Biology 147(1): 195-197), the Striped Smith- Waterman algorithm (see, e.g., Farrar (2007), “Striped Smith-Waterman Speeds Database Searches Six Times Over Other SIMD Implementations”, Bioinformatics 23(2): 156- 161), the Needleman-Wunsch algorithm (Needleman, et al. (1970) "A General Method Applicable to the Search for Similarities in the Amino Acid Sequence of Two Proteins", J. Molecular Biology 48(3):443— 53), or any combination thereof.

[0146] In some instances, the methods and systems disclosed herein may also comprise the use of a sequence assembly algorithm, e.g., the Arachne sequence assembly algorithm (see, e.g., Batzoglou, et al. (2002), “ARACHNE: A Whole-Genome Shotgun Assembler”, Genome Res. 12:177-189).

[0147] In some instances, the alignment method used to analyze sequence reads is not individually customized or tuned for detection of different variants (e.g., point mutations, insertions, deletions, and the like) at different genomic loci. In some instances, different alignment methods are used to analyze reads that are individually customized or tuned for detection of at least a subset of the different variants detected at different genomic loci. In some instances, different alignment methods are used to analyze reads that are individually customized or tuned to detect each different variant at different genomic loci. In some instances, tuning can be a function of one or more of: (i) the genetic locus (e.g., gene loci, micro satellite locus, or other subject interval) being sequenced, (ii) the tumor type associated with the sample, (iii) the variant being sequenced, or (iv) a characteristic of the sample or the subject. The selection or use of alignment conditions that are individually tuned to a number of specific subject intervals to be sequenced allows optimization of speed, sensitivity, and specificity. The method is particularly effective when the alignment of reads for a relatively large number of diverse subject intervals are optimized.

[0148] In some instances, the method includes the use of an alignment method optimized for rearrangements in combination with other alignment methods optimized for subject intervals not associated with rearrangements.

[0149] In some instances, the methods disclosed herein further comprise selecting or using an alignment method for analyzing, e.g., aligning, a sequence read, wherein said alignment method is a function of, is selected responsive to, or is optimized for, one or more of: (i) tumor type, e.g., the tumor type in the sample; (ii) the location (e.g., a gene locus) of the subject interval being sequenced; (iii) the type of variant (e.g., a point mutation, insertion, deletion, substitution, copy number variation (CNV), rearrangement, or fusion) in the subject interval being sequenced; (iv) the site (e.g., nucleotide position) being analyzed; (v) the type of sample (e.g., a sample described herein); and / or (vi) adjacent sequence(s) in or near the subject interval being evaluated (e.g., according to the expected propensity thereof for misalignment of the subject interval due to, e.g., the presence of repeated sequences in or near the subject interval).

[0150] In some instances, the methods disclosed herein allow for the rapid and efficient alignment of troublesome reads, e.g., a read having a rearrangement. Thus, in some instances where a read for a subject interval comprises a nucleotide position with a rearrangement, e.g., a translocation, the method can comprise using an alignment method that is appropriately tuned and that includes: (i) selecting a rearrangement reference sequence for alignment with a read, wherein said rearrangement reference sequence aligns with a rearrangement (in some instances, the reference sequence is not identical to the genomic rearrangement); and (ii) comparing, e.g., aligning, a read with said rearrangement reference sequence.

[0151] In some instances, alternative methods may be used to align troublesome reads. These methods are particularly effective when the alignment of reads for a relatively large number of diverse subject intervals is optimized. By way of example, a method of analyzing a sample can comprise: (i) performing a comparison (e.g., an alignment comparison) of a read using a first set of parameters (e.g., using a first mapping algorithm, or by comparison with a first reference sequence), and determining if said read meets a first alignment criterion (e.g., the read can be aligned with said first reference sequence, e.g., with less than a specific number of mismatches); (ii) if said read fails to meet the first alignment criterion, performing a second alignment comparison using a second set of parameters, (e.g., using a second mapping algorithm, or by comparison with a second reference sequence); and (iii) optionally, determining if said read meets said second criterion (e.g., the read can be aligned with saidsecond reference sequence, e.g., with less than a specific number of mismatches), wherein said second set of parameters comprises use of, e.g., said second reference sequence, which, compared with said first set of parameters, is more likely to result in an alignment with a read for a variant e.g., a rearrangement, insertion, deletion, or translocation).

[0152] In some instances, the alignment of sequence reads in the disclosed methods may be combined with a mutation calling method as described elsewhere herein. As discussed herein, reduced sensitivity for detecting actual mutations may be addressed by evaluating the quality of alignments (manually or in an automated fashion) around expected mutation sites in the genes or genomic loci (e.g., gene loci) being analyzed. In some instances, the sites to be evaluated can be obtained from databases of the human genome (e.g., the HG19 human reference genome) or cancer mutations (e.g., COSMIC). Regions that are identified as problematic can be remedied with the use of an algorithm selected to give better performance in the relevant sequence context, e.g., by alignment optimization (or re-alignment) using slower, but more accurate alignment algorithms such as Smith-Waterman alignment. In cases where general alignment algorithms cannot remedy the problem, customized alignment approaches may be created by, e.g., adjustment of maximum difference mismatch penalty parameters for genes with a high likelihood of containing substitutions; adjusting specific mismatch penalty parameters based on specific mutation types that are common in certain tumor types (e.g. C~^T in melanoma); or adjusting specific mismatch penalty parameters based on specific mutation types that are common in certain sample types (e.g. substitutions that are common in FFPE).

[0153] Reduced specificity (increased false positive rate) in the evaluated subject intervals due to misalignment can be assessed by manual or automated examination of all mutation calls in the sequencing data. Those regions found to be prone to spurious mutation calls due to misalignment can be subjected to alignment remedies as discussed above. In cases where no algorithmic remedy is found possible, “mutations” from the problem regions can be classified or screened out from the panel of targeted loci.Alignment of Methyl-Seq Sequence Reads

[0154] In some instances, the methods may include the use of an alignment method optimized for aligning sequence reads for DNA that has been converted using, e.g., a bisulfite reaction, to convert unmethylated cytosine residues to uracil (which is interpreted as athymine in sequencing results). In some instances, sequence reads may be aligned to two genomes in silico, e.g., converted and unconverted versions of the reference genome, using such alignment tools. Methylation occurs primarily at CpG sites, but may also occur less frequently at non-CpG sites (e.g., CHG or CHH sites).

[0155] In some instances, the sequence read data may be obtained using a nucleic acid sequencing method comprising the use of Methylated DNA Immunoprecipitation (MeDIP).

[0156] Examples of alignment tools optimized for aligning sequence reads for converted DNA include, but are not limited to, NovoAlign (Novocraft Technologies, Selangor, Malaysia), and the Bismark tool (Krueger, et al. (2011), “Bismark: A Flexible Aligner and Methylation Caller for Bisulfite-Seq Applications”, Bioinformatics 27(11): 1571- 1572).Mutation calling

[0157] Base calling refers to the raw output of a sequencing device, e.g., the determined sequence of nucleotides in an oligonucleotide molecule. Mutation calling refers to the process of selecting a nucleotide value, e.g., A, G, T, or C, for a given nucleotide position being sequenced. Typically, the sequence reads (or base calling) for a position will provide more than one value, e.g., some reads will indicate a T and some will indicate a G. Mutation calling is the process of assigning a correct nucleotide value, e.g., one of those values, to the sequence. Although it is referred to as “mutation” calling, it can be applied to assign a nucleotide value to any nucleotide position, e.g., positions corresponding to mutant alleles, wild-type alleles, alleles that have not been characterized as either mutant or wild-type, or to positions not characterized by variability. Mutation calling can be used to assign correct nucleotide values for nucleotide sequences relating to methylation patterns. For example, mutation calling can be used to identify mutant or wild-type alleles that correlate to particular methylation patterns.

[0158] In some instances, the disclosed methods may comprise the use of customized or tuned mutation calling algorithms or parameters thereof to optimize performance when applied to sequencing data, particularly in methods that rely on massively parallel sequencing (MPS) of a large number of diverse genetic events at a large number of diverse genomic loci (e.g., gene loci, microsatellite regions, etc.) in samples, e.g., samples from a subject having cancer. Optimization of mutation calling is described in the art, e.g., as set out in International Patent Application Publication No. WO 2012 / 092426.

[0159] Methods for mutation calling can include one or more of the following: making independent calls based on the information at each position in the reference sequence (e.g., examining the sequence reads; examining the base calls and quality scores; calculating the probability of observed bases and quality scores given a potential genotype; and assigning genotypes (e.g., using Bayes’ rule)); removing false positives (e.g., using depth thresholds to reject SNPs with read depth much lower or higher than expected; local realignment to remove false positives due to small indels); and performing linkage disequilibrium (LD) / imputation- based analysis to refine the calls.

[0160] Equations used to calculate the genotype likelihood associated with a specific genotype and position are described in, e.g., Li, H. and Durbin, R. Bioinformatics, 2010; 26(5): 589-95. The prior expectation for a particular mutation in a certain cancer type can be used when evaluating samples from that cancer type. Such likelihood can be derived from public databases of cancer mutations, e.g., Catalogue of Somatic Mutation in Cancer (COSMIC), HGMD (Human Gene Mutation Database), The SNP Consortium, Breast Cancer Mutation Data Base (BIC), and Breast Cancer Gene Database (BCGD).

[0161] Examples of LD / imputation based analysis are described in, e.g., Browning, B.L. and Yu, Z. Am. J. Hum. Genet. 2009, 85(6):847-61. Examples of low-coverage SNP calling methods are described in, e.g., Li, Y., et al., Annu. Rev. Genomics Hum. Genet. 2009, 10:387- 406.

[0162] After alignment, detection of substitutions can be performed using a mutation calling method (e.g., a Bayesian mutation calling method) which is applied to each base in each of the subject intervals, e.g., exons of a gene or other locus to be evaluated, where presence of alternate alleles is observed. This method will compare the probability of observing the read data in the presence of a mutation with the probability of observing the read data in the presence of base-calling error alone. Mutations can be called if this comparison is sufficiently strongly supportive of the presence of a mutation.

[0163] An advantage of a Bayesian mutation detection approach is that the comparison of the probability of the presence of a mutation with the probability of base-calling error alone can be weighted by a prior expectation of the presence of a mutation at the site. If some reads of an alternate allele are observed at a frequently mutated site for the given cancer type, then presence of a mutation may be confidently called even if the amount of evidence of mutation does not meet the usual thresholds. This flexibility can then be used to increase detection sensitivity for even rarer mutations / lower purity samples, or to make the test more robust todecreases in read coverage. The likelihood of a random base-pair in the genome being mutated in cancer is ~le-6. The likelihood of specific mutations occurring at many sites in, for example, a typical multigenic cancer genome panel can be orders of magnitude higher. These likelihoods can be derived from public databases of cancer mutations (e.g., COSMIC).

[0164] Indel calling is a process of finding bases in the sequencing data that differ from the reference sequence by insertion or deletion, typically including an associated confidence score or statistical evidence metric. Methods of indel calling can include the steps of identifying candidate indels, calculating genotype likelihood through local re-alignment, and performing LD-based genotype inference and calling. Typically, a Bayesian approach is used to obtain potential indel candidates, and then these candidates are tested together with the reference sequence in a Bayesian framework.

[0165] Algorithms to generate candidate indels are described in, e.g., McKenna, A., et al., Genome Res. 2010; 20(9): 1297-303; Ye, K., et al., Bioinformatics, 2009; 25(21):2865-71 ; Lunter, G., and Goodson, M., Genome Res. 2011; 21(6):936-9; and Li, H., et al. (2009), Bioinformatics 25(16) :2078-9.

[0166] Methods for generating indel calls and individual-level genotype likelihoods include, e.g., the Dindel algorithm (Albers, C.A., et al., Genome Res. 2011;21(6):961-73). For example, the Bayesian EM algorithm can be used to analyze the reads, make initial indel calls, and generate genotype likelihoods for each candidate indel, followed by imputation of genotypes using, e.g., QCALL (Le S.Q. and Durbin R. Genome Res. 201 l;21(6):952-60). Parameters, such as prior expectations of observing the indel can be adjusted (e.g., increased or decreased), based on the size or location of the indels.

[0167] Methods have been developed that address limited deviations from allele frequencies of 50% or 100% for the analysis of cancer DNA. (see, e.g., SNVMix -Bioinformatics. 2010 March 15; 26(6): 730-736.) Methods disclosed herein, however, allow consideration of the possibility of the presence of a mutant allele at frequencies (or allele fractions) ranging from 1% to 100% (i.e., allele fractions ranging from 0.01 to 1.0), and especially at levels lower than 50%. This approach is particularly important for the detection of mutations in, for example, low-purity FFPE samples of natural (multi-clonal) tumor DNA.

[0168] In some instances, the mutation calling method used to analyze sequence reads is not individually customized or fine-tuned for detection of different mutations at different genomic loci. In some instances, different mutation calling methods are used that are individually customized or fine-tuned for at least a subset of the different mutations detectedat different genomic loci. In some instances, different mutation calling methods are used that are individually customized or fine-tuned for each different mutant detected at each different genomic loci. The customization or tuning can be based on one or more of the factors described herein, e.g., the type of cancer in a sample, the gene or locus in which the subject interval to be sequenced is located, or the variant to be sequenced. This selection or use of mutation calling methods individually customized or fine-tuned for a number of subject intervals to be sequenced allows for optimization of speed, sensitivity and specificity of mutation calling.

[0169] In some instances, a nucleotide value is assigned for a nucleotide position in each of X unique subject intervals using a unique mutation calling method, and X is at least 2, at least 3, at least 4, at least 5, at least 10, at least 15, at least 20, at least 30, at least 40, at least 50, at least 60, at least 70, at least 80, at least 90, at least 100, at least 200, at least 300, at least 400, at least 500, at least 1000, at least 1500, at least 2000, at least 2500, at least 3000, at least 3500, at least 4000, at least 4500, at least 5000, or greater. The calling methods can differ, and thereby be unique, e.g., by relying on different Bayesian prior values.

[0170] In some instances, assigning said nucleotide value is a function of a value which is or represents the prior (e.g., literature) expectation of observing a read showing a variant, e.g., a mutation, at said nucleotide position in a tumor of type.

[0171] In some instances, the method comprises assigning a nucleotide value (e.g., calling a mutation) for at least 10, 20, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1,000 nucleotide positions, wherein each assignment is a function of a unique value (as opposed to the value for the other assignments) which is or represents the prior (e.g., literature) expectation of observing a read showing a variant, e.g., a mutation, at said nucleotide position in a tumor of type.

[0172] In some instances, assigning said nucleotide value is a function of a set of values which represent the probabilities of observing a read showing said variant at said nucleotide position if the variant is present in the sample at a specified frequency (e.g., 1%, 5%, 10%, etc.) and / or if the variant is absent (e.g., observed in the reads due to base-calling error alone).

[0173] In some instances, the mutation calling methods described herein can include the following: (a) acquiring, for a nucleotide position in each of said X subject intervals: (i) a first value which is or represents the prior (e.g., literature) expectation of observing a read showing a variant, e.g., a mutation, at said nucleotide position in a tumor of type X; and (ii) asecond set of values which represent the probabilities of observing a read showing said variant at said nucleotide position if the variant is present in the sample at a frequency (e.g., 1%, 5%, 10%, etc.) and / or if the variant is absent (e.g., observed in the reads due to basecalling error alone); and (b) responsive to said values, assigning a nucleotide value (e.g., calling a mutation) from said reads for each of said nucleotide positions by weighing, e.g., by a Bayesian method described herein, the comparison among the values in the second set using the first value (e.g., computing the posterior probability of the presence of a mutation), thereby analyzing said sample.

[0174] Additional description of exemplary nucleic acid sequencing methods, mutation calling methods, and methods for analysis of genetic variants is provided in, e.g., U.S. Patent No. 9,340,830, U.S. Patent No. 9,792,403, U.S. Patent No. 11,136,619, U.S. Patent No.11,118,213, and International Patent Application Publication No. WO 2020 / 236941, the entire contents of each of which is incorporated herein by reference.Methylation Status Calling

[0175] In some instances, the methods described herein may comprise the use of a methylation status calling method, e.g., to call the methylation status of the CpG sites based on the sequence reads and fragments (complementary pairs of forward and reverse sequence reads) derived from DNA that has been subjected to a chemical or enzymatic conversion reaction, e.g., to convert unmethylated cytosine residues to uracil (which is interpreted as a thymine in sequencing results). Examples of such methylation status calling tools include, but are not limited to, the Bismark tool (Krueger, et al. (2011), “Bismark: A Flexible Aligner and Methylation Caller for Bisulfite-Seq Applications”, Bioinformatics 27(11): 1571-1572), TARGOMICS (Garinet, et al. (2017), “Calling Chromosome Alterations, DNA Methylation Statuses, and Mutations in Tumors by Simple Targeted Next-Generation Sequencing - A Solution for Transferring Integrated Pangenomic Studies into Routine Practice?”, J.Molecular Diagnostics 19(5):776-787), Bicycle (Grana, et al. (2018) “Bicycle: A Bioinformatics Pipeline to Analyze Bisulfite Sequencing Data”, Bioinformatics 34(8): 1414— 5), SMAP (Gao, et al. (2015), “SMAP: A Streamlined Methylation Analysis Pipeline for Bisulfite Sequencing”, Gigascience 4:29), and MeDUSA (Wilson, et al. (2016), “Computational Analysis and Integration of MeDIP-Seq Methylome Data”, in: Kulski JK, editor, Next Generation Sequencing: Advances, Applications and Challenges. Rijeka: InTech,p. 153-69). See also, Rauluseviciute, et al. (2019), “DNA Methylation Data by Sequencing: Experimental Approaches and Recommendations for Tools and Pipelines for Data Analysis”, Clinical Epigenetics 11:193.

[0176] In some instances, the disclosed methods may be used to assess methylation patterns and their corresponding sequences in at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 20, at least 30, at least 40, or more than 40 gene loci.

[0177] In some instances, the disclosed methods for preparing a sequencing library may be used to diagnose (or as part of a diagnosis of) the presence of disease or other condition (e.g., cancer, genetic disorders (such as Down Syndrome and Fragile X), neurological disorders, or any other disease type where detection of variants, e.g., copy number alternations, are relevant to diagnosing, treating, or predicting said disease) in a subject (e.g., a patient). In some instances, the disclosed methods may be applicable to diagnosis of any of a variety of cancers as described elsewhere herein.

[0178] In some instances, the disclosed methods for preparing a sequencing library may be used to predict genetic disorders in fetal DNA. (e.g., for invasive or non-invasive prenatal testing). For example, sequence read data obtained by sequencing fetal DNA extracted from samples obtained using invasive amniocentesis, chorionic villus sampling (cVS), or fetal umbilical cord sampling techniques, or obtained using non-invasive sampling of cell-free DNA (cfDNA) samples (which comprises a mix of maternal cfDNA and fetal cfDNA), may be processed according to the disclosed methods to identify variants, e.g., copy number alterations, associated with, e.g., Down Syndrome (trisomy 21), trisomy 18, trisomy 13, and extra or missing copies of the X and Y chromosomes.

[0179] In some instances, the disclosed methods for preparing a sequencing library may be used to determine methylation profiles to ultimately select a subject (e.g., a patient) for a clinical trial based on the methylation sequences determined for one or more gene loci. In some instances, patient selection for clinical trials based on, e.g., identification of methylation patterns at one or more gene loci, may accelerate the development of targeted therapies and improve the healthcare outcomes for treatment decisions.

[0180] In some instances, the disclosed methods for preparing a sequencing library may be used to determine methylation profiles to ultimately select an appropriate therapy or treatment (e.g., an anti-cancer therapy or anti-cancer treatment) for a subject. In some instances, for example, the anti-cancer therapy or treatment may comprise use of a poly(ADP-ribose) polymerase inhibitor (PARPi), a platinum compound, chemotherapy, radiation therapy, a targeted therapy (e.g., immunotherapy), surgery, or any combination thereof.

[0181] In some instances, the targeted therapy (or anti-cancer target therapy) may comprise abemaciclib (Verzenio), abiraterone acetate (Zytiga), acalabrutinib (Calquence), ado- trastuzumab emtansine (Kadcyla), afatinib dimaleate (Gilotrif), aldesleukin (Proleukin), alectinib (Alecensa), alemtuzumab (Campath), alitretinoin (Panretin), alpelisib (Piqray), amivantamab-vmjw (Rybrevant), anastrozole (Arimidex), apalutamide (Erleada), asciminib hydrochloride (Scemblix), atezolizumab (Tecentriq), avapritinib (Ayvakit), avelumab (Bavencio), axicabtagene ciloleucel (Yescarta), axitinib (Inlyta), belantamab mafodotin-blmf (Blenrep), belimumab (Benlysta), belinostat (Beleodaq), belzutifan (Welireg), bevacizumab (Avastin), bexarotene (Targretin), binimetinib (Mektovi), blinatumomab (Blincyto), bortezomib (Velcade), bosutinib (Bosulif), brentuximab vedotin (Adcetris), brexucabtagene autoleucel (Tecartus), brigatinib (Alunbrig), cabazitaxel (Jevtana), cabozantinib (Cabometyx), cabozantinib (Cabometyx, Cometriq), canakinumab (Haris), capmatinib hydrochloride (Tabrecta), carfilzomib (Kyprolis), cemiplimab-rwlc (Libtayo), ceritinib (LDK378 / Zykadia), cetuximab (Erbitux), cobimetinib (Cotellic), copanlisib hydrochloride (Aliqopa), crizotinib (Xalkori), dabrafenib (Tafinlar), dacomitinib (Vizimpro), daratumumab (Darzalex), daratumumab and hyaluronidase-fihj (Darzalex Faspro), darolutamide (Nubeqa), dasatinib (Sprycel), denileukin diftitox (Ontak), denosumab (Xgeva), dinutuximab (Unituxin), dostarlimab-gxly (Jemperli), durvalumab (Imfinzi), duvelisib (Copiktra), elotuzumab (Empliciti), enasidenib mesylate (Idhifa), encorafenib (Braftovi), enfortumab vedotin-ejfv (Padcev), entrectinib (Rozlytrek), enzalutamide (Xtandi), erdafitinib (Balversa), erlotinib (Tarceva), everolimus (Afinitor), exemestane (Aromasin), fam-trastuzumab deruxtecan-nxki (Enhertu), fedratinib hydrochloride (Inrebic), fulvestrant (Faslodex), gefitinib (Iressa), gemtuzumab ozogamicin (Mylotarg), gilteritinib (Xospata), glasdegib maleate (Daurismo), hyaluronidase-zzxf (Phesgo), ibrutinib (Imbruvica), ibritumomab tiuxetan (Zevalin), idecabtagene vicleucel (Abecma), idelalisib (Zydelig), imatinib mesylate (Gleevec), infigratinib phosphate (Truseltiq), inotuzumab ozogamicin (Besponsa), iobenguane 1131 (Azedra), ipilimumab (Yervoy), isatuximab-irfc (Sarclisa), ivosidenib (Tibsovo), ixazomib citrate (Ninlaro), lanreotide acetate (Somatuline Depot), lapatinib (Tykerb), larotrectinib sulfate (Vitrakvi), lenvatinib mesylate (Lenvima), letrozole (Femara), lisocabtagene maraleucel (Breyanzi), loncastuximab tesirine-lpyl (Zynlonta), lorlatinib (Lorbrena), lutetium Lu 177-dotatate (Lutathera), margetuximab-cmkb (Margenza),midostaurin (Rydapt), mobocertinib succinate (Exkivity), mogamulizumab-kpkc (Poteligeo), moxetumomab pasudotox-tdfk (Lumoxiti), naxitamab-gqgk (Danyelza), necitumumab (Portrazza), neratinib maleate (Nerlynx), nilotinib (Tasigna), niraparib tosylate monohydrate (Zejula), nivolumab (Opdivo), obinutuzumab (Gazyva), ofatumumab (Arzerra), olaparib (Lynparza), olaratumab (Lartruvo), osimertinib (Tagrisso), palbociclib (Ibrance), panitumumab (Vectibix), panobinostat (Farydak), pazopanib (Votrient), pembrolizumab (Keytruda), pemigatinib (Pemazyre), pertuzumab (Perjeta), pexidartinib hydrochloride (Turalio), polatuzumab vedotin-piiq (Polivy), ponatinib hydrochloride (Iclusig), pralatrexate (Folotyn), pralsetinib (Gavreto), radium 223 dichloride (Xofigo), ramucirumab (Cyramza), regorafenib (Stivarga), ribociclib (Kisqali), ripretinib (Qinlock), rituximab (Rituxan), rituximab and hyaluronidase human (Rituxan Hycela), romidepsin (Istodax), rucaparib camsylate (Rubraca), ruxolitinib phosphate (Jakafi), sacituzumab govitecan-hziy (Trodelvy), seliciclib, selinexor (Xpovio), selpercatinib (Retevmo), selumetinib sulfate (Koselugo), siltuximab (Sylvant), sipuleucel-T (Provenge), sirolimus protein-bound particles (Fyarro), sonidegib (Odomzo), sorafenib (Nexavar), sotorasib (Lumakras), sunitinib (Sutent), tafasitamab-cxix (Monjuvi), tagraxofusp-erzs (Elzonris), talazoparib tosylate (Talzenna), tamoxifen (Nolvadex), tazemetostat hydrobromide (Tazverik), tebentafusp-tebn (Kimmtrak), temsirolimus (Torisel), tepotinib hydrochloride (Tepmetko), tisagenlecleucel (Kymriah), tisotumab vedotin-tftv (Tivdak), tocilizumab (Actemra), tofacitinib (Xeljanz), tositumomab (Bexxar), trametinib (Mekinist), trastuzumab (Herceptin), tretinoin (Vesanoid), tivozanib hydrochloride (Fotivda), toremifene (Fareston), tucatinib (Tukysa), umbralisib tosylate (Ukoniq), vandetanib (Caprelsa), vemurafenib (Zelboraf), venetoclax (Venclexta), vismodegib (Erivedge), vorinostat (Zolinza), zanubrutinib (Brukinsa), ziv-aflibercept (Zaltrap), or any combination thereof.

[0182] In some instances, the disclosed methods for preparing a sequencing library may be used to determine methylation profiles for ultimately treating a disease (e.g., a cancer) in a subject. For example, in response to determining a methylation profile using any of the methods disclosed herein, an effective amount of an anti-cancer therapy or anti-cancer treatment may be administered to the subject.

[0183] In some instances, the disclosed methods for preparing a sequencing library may ultimately be used for monitoring disease progression or recurrence (e.g., cancer or tumor progression or recurrence) in a subject. For example, in some instances, the methods may be used to determine a methylation profile in a first sample obtained from the subject at a firsttime point, and used to determine a methylation profile in a second sample obtained from the subject at a second time point, where comparison of the first determination of a methylation profile and the second determination of a methylation profile allows one to monitor disease progression or recurrence. In some instances, the first time point is chosen before the subject has been administered a therapy or treatment, and the second time point is chosen after the subject has been administered the therapy or treatment.

[0184] In some instances, the disclosed methods may be used for adjusting a therapy or treatment (e.g., an anti-cancer treatment or anti-cancer therapy) for a subject, e.g., by adjusting a treatment dose and / or selecting a different treatment in response to a change in the determination of a methylation profile, which can derive from preparing a sequencing library in accordance with the methods described herein.

[0185] In some instances, the methylation profile derived from preparing a sequencing library using the disclosed methods may be used as a prognostic or diagnostic indicator associated with the sample. For example, in some instances, the prognostic or diagnostic indicator may comprise an indicator of the presence of a disease (e.g., cancer) in the sample, an indicator of the probability that a disease (e.g., cancer) is present in the sample, an indicator of the probability that the subject from which the sample was derived will develop a disease (e.g., cancer) (i.e., a risk factor), or an indicator of the likelihood that the subject from which the sample was derived will respond to a particular therapy or treatment.

[0186] In some instances, the disclosed methods for preparing a sequencing library may be implemented as part of a genomic profiling process that comprises identification of the presence of variant sequences at one or more gene loci in a sample derived from a subject as part of detecting, monitoring, predicting a risk factor, or selecting a treatment for a particular disease, e.g., cancer. In some instances, the variant panel selected for genomic profiling may comprise the detection of variant sequences at a selected set of gene loci. In some instances, the variant panel selected for genomic profiling may comprise detection of variant sequences at a number of gene loci through comprehensive genomic profiling (CGP), which is a nextgeneration sequencing (NGS) approach used to assess hundreds of genes (including relevant cancer biomarkers) in a single assay. Inclusion of the disclosed methods for preparing a sequencing library as part of a genomic profiling process (or inclusion of the output from the disclosed methods for preparing a sequencing library as part of the genomic profile of the subject) can improve the validity of, e.g., disease detection calls and treatment decisions,made on the basis of the genomic profile by, for example, independently confirming the presence of a methylation profile in a given patient sample.

[0187] In some instances, a genomic profile may comprise information on the presence of genes (or variant sequences thereof), copy number variations, epigenetic traits, proteins (or modifications thereof), and / or other biomarkers in an individual’s genome and / or proteome, as well as information on the individual’s corresponding phenotypic traits and the interaction between genetic or genomic traits, phenotypic traits, and environmental factors.

[0188] In some instances, a genomic profile for the subject may comprise results from a comprehensive genomic profiling (CGP) test, a nucleic acid sequencing-based test, a gene expression profiling test, a cancer hotspot panel test, a DNA methylation test, a DNA fragmentation test, an RNA fragmentation test, or any combination thereof.

[0189] In some instances, the method can further include administering or applying a treatment or therapy (e.g., an anti-cancer agent, anti-cancer treatment, or anti-cancer therapy) to the subject based on the generated genomic profile. An anti-cancer agent or anti-cancer treatment may refer to a compound that is effective in the treatment of cancer cells. Examples of anti-cancer agents or anti-cancer therapies include, but not limited to, alkylating agents, antimetabolites, natural products, hormones, chemotherapy, radiation therapy, immunotherapy, surgery, or a therapy configured to target a defect in a specific cell signaling pathway, e.g., a defect in a DNA mismatch repair (MMR) pathway.Systems

[0190] Also disclosed herein are systems designed to implement any of the disclosed methods for preparing a sequencing library from a sample from a subject. The systems can be used to automate the methods of preparing a sequencing library, such as a sequencing library formed by bisulfite conversion used for methylation sequencing. The systems may comprise, e.g., one or more processors, and a memory unit communicatively coupled to the one or more processors and configured to store instructions that, when executed by the one or more processors, cause the system to control components, such as robotic components, that can: ligate one or more adapters to nucleic acid molecules in a ligation buffer; bind the nucleic acid molecules to a plurality of beads in the ligation buffer; separate from the ligation buffer, the plurality of beads bound to the nucleic acid molecules; suspend the plurality of beads in a solution comprising alcohol; and convert, using a bisulfite reaction, unmethylated cytosines in the nucleic acid molecules to uracil, to generate converted nucleic acid molecules.

[0191] The disclosed systems can comprise components such as robotic modules for automating sample processing. For example, the disclosed systems can comprise components such as robotic library preparation workstations, microplate-handling robotics, fluiddispensing systems, temperature control modules, environmental control chambers, additional data storage modules, data communication modules (e.g., Bluetooth®, WiFi, intranet, or internet communication hardware and associated software), display modules, one or more local and / or cloud-based software packages (e.g., instrument / system control software packages, sequencing data analysis software packages), etc., or any combination thereof. In some instances, the systems may comprise, or be part of, a computer system or computer network as described elsewhere herein.

[0192] In some instances, the disclosed systems may further comprise a component, such as a sequencer, e.g., a next generation sequencer (also referred to as a massively parallel sequencer) to ultimately sequence the sequencing library generated from, for example, the robotic system used to automate the preparing of the sequencing library. Examples of next generation (or massively parallel) sequencing platforms include, but are not limited to, Roche / 454’s Genome Sequencer (GS) FLX system, Illumina / Solexa’ s Genome Analyzer (GA), Illumina’s HiSeq® 2500, HiSeq® 3000, HiSeq® 4000 and NovaSeq® 6000 sequencing systems, Life / APG’s Support Oligonucleotide Ligation Detection (SOLiD) system, Polonator’s G.007 system, Helicos BioSciences’ HeliScope Gene Sequencing system, ThermoFisher Scientific’s Ion Torrent Genexus system, or Pacific Biosciences’ PacBio® RS system.

[0193] In some instances, the disclosed systems may be used for preparing a sequencing library for any of a variety of samples as described herein (e.g., a tissue sample, biopsy sample, hematological sample, or liquid biopsy sample derived from the subject).

[0194] In some instances, the plurality of gene loci for which sequencing data is processed to determine a methylation profile may comprise at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or more than 10 gene loci.

[0195] In some instance, the nucleic acid sequence data is acquired using a next generation sequencing technique (also referred to as a massively parallel sequencing technique) having a read-length of less than 400 bases, less than 300 bases, less than 200 bases, less than 150 bases, less than 100 bases, less than 90 bases, less than 80 bases, less than 70 bases, less than 60 bases, less than 50 bases, less than 40 bases, or less than 30 bases.

[0196] In some instances, the determination of a methylation profile deriving from a sequencing library in accordance with the methods described herein is used to select, initiate, adjust, or terminate a treatment for cancer in the subject (e.g., a patient) from which the sample was derived, as described elsewhere herein.EXEMPLARY EMBODIMENTS

[0197] The following embodiments are exemplary and are not intended to limit the scope of any claims.

[0198] Embodiment 1. A method of preparing a sequencing library, comprising: ligating one or more adapters to nucleic acid molecules in a ligation buffer; binding the nucleic acid molecules to a plurality of beads in the ligation buffer; separating from the ligation buffer, the plurality of beads bound to the nucleic acid molecules; suspending the plurality of beads in a solution comprising alcohol; and converting, using a bisulfite reaction, unmethylated cytosines in the nucleic acid molecules to uracil, to generate converted nucleic acid molecules.

[0199] Embodiment 2. The method of embodiment 1, wherein the nucleic acid molecules are DNA molecules.

[0200] Embodiment 3. The method of embodiment 2, wherein the DNA molecules are cell- free DNA (cfDNA) molecules.

[0201] Embodiment 4. The method of embodiment 1, wherein the nucleic acid molecules are RNA molecules.

[0202] Embodiment 5. The method of any one of embodiments 1-4, wherein the method comprises fractioning the nucleic acid molecules based on size.

[0203] Embodiment 6. The method of any of embodiments 1-5, wherein the fractioning occurs after the ligating, and before the binding of the nucleic acid molecules to a plurality of beads in the ligation buffer.

[0204] Embodiment 7. The method of embodiment 5 or 6, wherein the fractioning comprises: combining a second plurality of beads with the nucleic acid molecules, thereby allowing a first portion of the nucleic acid molecules to bind to the second plurality of beads; separating the second plurality of beads from a second portion of the nucleic acid molecules; anddiscarding the second plurality of beads and the first portion of the nucleic acid molecules.

[0205] Embodiment 8. The method of any of embodiments 1-7, wherein the converting occurs before the ligating.

[0206] Embodiment 9. The method of any of embodiments 1-8, wherein the converting occurs after the suspending.

[0207] Embodiment 10. The method of any of embodiments 1-9, wherein the method comprises denaturing the converted nucleic acid molecules.

[0208] Embodiment 11. The method of any of embodiments 1-10, wherein the method comprises amplifying the converted nucleic acid molecules.

[0209] Embodiment 12. The method of embodiment 11, wherein the amplifying comprises performing a polymerase chain reaction (PCR) amplification or an isothermal amplification.

[0210] Embodiment 13. The method of any of embodiments 1-12, wherein the method comprises blunting the ends of the nucleic acid molecules.

[0211] Embodiment 14. The method of any of embodiments 1-13, wherein the method comprises fragmenting the nucleic acid molecules.

[0212] Embodiment 15. The method of embodiment 14, wherein fragmenting the nucleic acid molecules comprises shearing the nucleic acid molecules.

[0213] Embodiment 16. The method of embodiment 15, wherein shearing the nucleic acid molecules comprises sonicating the nucleic acid molecules, nebulizing the nucleic acid molecules, applying a centrifugal force to the nucleic acid molecules, needle shearing the nucleic acid molecules, or enzymatically shearing the nucleic acid molecules.

[0214] Embodiment 17. The method of any of embodiments 1-16, wherein the nucleic acid molecules are phosphorylated at 5’ ends of the nucleic acid molecules.

[0215] Embodiment 18. The method of any of embodiments 1-17, wherein the nucleic acid molecules are adenylated at 3’ ends of the nucleic acid molecules.

[0216] Embodiment 19. The method any one of embodiments 1-18, wherein separating from the ligation buffer, the plurality of beads bound to the nucleic acid molecules, comprises applying a magnetic field to the plurality of beads.

[0217] Embodiment 20. The method of any of embodiments 1-19, wherein separating from the ligation buffer, the plurality of beads bound to the nucleic acid molecules, comprises centrifuging the plurality of beads.

[0218] Embodiment 21. The method of any of embodiments 1-20, wherein the alcohol is ethanol, isopropanol, or a combination thereof.

[0219] Embodiment 22. The method of any of embodiments 1-21, wherein the plurality of beads comprises magnetic beads, beads comprising a silica surface, beads comprising a carboxyl surface, solid-phase reverse immobilization (SPRI) beads, or a combination thereof.

[0220] Embodiment 23. The method of any of embodiments 1-22, further comprising separating the nucleic acid molecules from the plurality of beads by eluting the nucleic acid molecules in a solvent.

[0221] Embodiment 24. The method of embodiment 23, wherein the solvent is water, a Tris- HC1 solution, or a Tris-EDTA (TE) solution.

[0222] Embodiment 25. The method of any of embodiments 1-24, wherein the sample comprises a tissue biopsy sample, a liquid sample, or a normal control.

[0223] Embodiment 26. The method of embodiment 25, wherein the sample is a liquid biopsy sample and comprises blood, plasma, cerebrospinal fluid, sputum, stool, urine or saliva.

[0224] Embodiment 27. The method of embodiment 25, wherein the sample is a liquid biopsy sample and comprises cfDNA.

[0225] Embodiment 28. The method of embodiment 27, wherein the cfDNA comprises circulating tumor DNA (ctDNA).

[0226] Embodiment 29. The method of any of embodiments 1-28, wherein the nucleic acid molecules comprise a mixture of tumor nucleic acid molecules and non-tumor nucleic acid molecules.

[0227] Embodiment 30. The method of embodiment 29, wherein the tumor nucleic acid molecules are derived from a tumor portion of a heterogeneous tissue biopsy sample, and the non-tumor nucleic acid molecules are derived from a normal portion of the heterogeneous tissue biopsy sample.

[0228] Embodiment 31. The method of embodiment 29, wherein the sample comprises a liquid biopsy sample, and wherein the tumor nucleic acid molecules are derived from a circulating tumor DNA (ctDNA) fraction of the liquid biopsy sample, and the non-tumor nucleic acid molecules are derived from a non-tumor, cell-free DNA (cfDNA) fraction of the liquid biopsy sample.

[0229] Embodiment 32. The method of any of embodiments 1-31, wherein the one or more adapters comprise amplification primers, flow cell adaptor sequences, substrate adapter sequences, or sample index sequences.

[0230] Embodiment 33. The method of any of embodiments 1-32, wherein the captured nucleic acid molecules are captured from the amplified nucleic acid molecules by hybridization to one or more bait molecules.

[0231] Embodiment 34. The method of embodiment 33, wherein the one or more bait molecules comprise one or more nucleic acid molecules, each comprising a region that is complementary to a region of a captured nucleic acid molecule.

[0232] Embodiment 35. A method of sequencing the converted nucleic acid molecules, comprising: preparing the sequencing library, according to the method of any of embodiments 1- 34; and sequencing, using a sequencer, the converted nucleic acid molecules.

[0233] Embodiment 36. The method of any of embodiments 1-35, wherein the sequencing comprises use of massively parallel sequencing (MPS), whole genome sequencing (WGS), whole exome sequencing, targeted sequencing, direct sequencing, or Sanger sequencing.

[0234] Embodiment 37. The method of embodiment 36, wherein the sequencing comprises massively parallel sequencing, and the massively parallel sequencing comprises next generation sequencing (NGS).

[0235] Embodiment 38. The method of any of embodiments 1-37, wherein the sequencer comprises a next generation sequencer.

[0236] Embodiment 39. The method of any of embodiments 1-38, wherein one or more of the plurality of sequencing reads overlap one or more gene loci within one or more subgenomic intervals in the sample.

[0237] Embodiment 40. The method of embodiment 39, wherein the one or more gene loci comprises between 10 and 20 loci, between 10 and 40 loci, between 10 and 60 loci, between 10 and 80 loci, between 10 and 100 loci, between 10 and 150 loci, between 10 and 200 loci, between 10 and 250 loci, between 10 and 300 loci, between 10 and 350 loci, between 10 and 400 loci, between 10 and 450 loci, between 10 and 500 loci, between 20 and 40 loci, between 20 and 60 loci, between 20 and 80 loci, between 20 and 100 loci, between 20 and 150 loci, between 20 and 200 loci, between 20 and 250 loci, between 20 and 300 loci, between 20 and 350 loci, between 20 and 400 loci, between 20 and 500 loci, between 40 and 60 loci, between40 and 80 loci, between 40 and 100 loci, between 40 and 150 loci, between 40 and 200 loci, between 40 and 250 loci, between 40 and 300 loci, between 40 and 350 loci, between 40 and 400 loci, between 40 and 500 loci, between 60 and 80 loci, between 60 and 100 loci, between 60 and 150 loci, between 60 and 200 loci, between 60 and 250 loci, between 60 and 300 loci, between 60 and 350 loci, between 60 and 400 loci, between 60 and 500 loci, between 80 and 100 loci, between 80 and 150 loci, between 80 and 200 loci, between 80 and 250 loci, between 80 and 300 loci, between 80 and 350 loci, between 80 and 400 loci, between 80 and 500 loci, between 100 and 150 loci, between 100 and 200 loci, between 100 and 250 loci, between 100 and 300 loci, between 100 and 350 loci, between 100 and 400 loci, between 100 and 500 loci, between 150 and 200 loci, between 150 and 250 loci, between 150 and 300 loci, between 150 and 350 loci, between 150 and 400 loci, between 150 and 500 loci, between 200 and 250 loci, between 200 and 300 loci, between 200 and 350 loci, between 200 and 400 loci, between 200 and 500 loci, between 250 and 300 loci, between 250 and 350 loci, between 250 and 400 loci, between 250 and 500 loci, between 300 and 350 loci, between 300 and 400 loci, between 300 and 500 loci, between 350 and 400 loci, between 350 and 500 loci, or between 400 and 500 loci.

[0238] Embodiment 41. The method of embodiment 39 or 40, wherein the one or more gene loci comprise ABL1, ACVR1B, AKT1, AKT2, AKT3, ALK, ALOX12B, AMER1, APC, AR, ARAF, ARFRP1, ARID 1 A, ASXL1, ATM, ATR, ATRX, AURKA, AURKB, AXIN1, AXL, BAP1, BARD1, BCL2, BCL2L1, BCL2L2, BCL6, BCOR, BCORL1, BCR, BRAF, BRCA1, BRCA2, BRD4, BRIP1, BTG1, BTG2, BTK, CALR, CARD11, CASP8, CBFB, CBL, CCND1, CCND2, CCND3, CCNE1, CD22, CD274, CD70, CD74, CD79A, CD79B, CDC73, CDH1, CDK12, CDK4, CDK6, CDK8, CDKN1A, CDKN1B, CDKN2A, CDKN2B, CDKN2C, CEBPA, CHEK1, CHEK2, CIC, CREBBP, CRKL, CSF1R, CSF3R, CTCF, CTNNA1, CTNNB1, CUL3, CUL4A, CXCR4, CYP17A1, DAXX, DDR1, DDR2, DIS3, DNMT3A, DOT1L, EED, EGFR, EMSY (Cllorf30), EP300, EPHA3, EPHB1, EPHB4, ERBB2, ERBB3, ERBB4, ERCC4, ERG, ERRFI1, ESRI, ETV4, ETV5, ETV6, EWSR1, EZH2, EZR, FAM46C, FANCA, FANCC, FANCG, FANCL, FAS, FBXW7, FGF10, FGF12, FGF14, FGF19, FGF23, FGF3, FGF4, FGF6, FGFR1, FGFR2, FGFR3, FGFR4, FH, FLCN, FLT1, FLT3, FOXL2, FUBP1, GABRA6, GATA3, GATA4, GATA6, GID4 (C17orf39), GNA11, GNA13, GNAQ, GNAS, GRM3, GSK3B, H3F3A, HDAC1, HGF, HNF1A, HRAS, HSD3B1, ID3, IDH1, IDH2, IGF1R, IKBKE, IKZF1, INPP4B, IRF2, IRF4, IRS2, JAK1, JAK2, JAK3, JUN, KDM5A, KDM5C, KDM6A, KDR, KEAP1, KEL, KIT,KLHL6, KMT2A (MLL), KMT2D (MLL2), KRAS, LTK, LYN, MAF, MAP2K1, MAP2K2, MAP2K4, MAP3K1, MAP3K13, MAPK1, MCL1, MDM2, MDM4, MED12, MEF2B, MEN1, MERTK, MET, MITF, MKNK1, MLH1, MPL, MRE11A, MSH2, MSH3, MSH6, MST1R, MTAP, MTOR, MUTYH, MYB, MYC, MYCL, MYCN, MYD88, NBN, NF1, NF2, NFE2L2, NFKBIA, NKX2-1, NOTCH1, NOTCH2, NOTCH3, NPM1, NRAS, NT5C2, NTRK1, NTRK2, NTRK3, NUTM1, P2RY8, PALB2, PARK2, PARP1, PARP2, PARP3, PAX5, PBRM1, PDCD1, PDCD1LG2, PDGFRA, PDGFRB, PDK1, PIK3C2B, PIK3C2G, PIK3CA, PIK3CB, PIK3R1, PIM1, PMS2, POLDI, POLE, PPARG, PPP2R1A, PPP2R2A, PRDM1, PRKAR1A, PRKCI, PTCHI, PTEN, PTPN11, PTPRO, QKI, RAC1, RAD21, RAD51, RAD51B, RAD51C, RAD51D, RAD52, RAD54L, RAFI, RARA, RBI, RBM10, REL, RET, RICTOR, RNF43, ROS1, RPTOR, RSPO2, SDC4, SDHA, SDHB, SDHC, SDHD, SETD2, SF3B1, SGK1, SLC34A2, SMAD2, SMAD4, SMARCA4, SMARCB1, SMO, SNCAIP, SOCS1, SOX2, SOX9, SPEN, SPOP, SRC, STAG2, STAT3, STK11, SUFU, SYK, TBX3, TEK, TERC, TERT, TET2, TGFBR2, TIP ARP, TMPRSS2, TNFAIP3, TNFRSF14, TP53, TSC1, TSC2, TYRO3, U2AF1, VEGFA, VHL, WHSCI, WHSC1L1, WT1, XPO1, XRCC2, ZNF217, ZNF703, or any combination thereof.

[0239] Embodiment 42. The method of any one of embodiments 39-40, wherein the one or more gene loci comprises one or mor CpG sites.

[0240] Embodiment 43. A method of detecting one or more methylation signatures in a sample, comprising: sequencing, by a sequencer, the converted one or more gene loci molecules according to any of embodiments 35-42; generating, by the sequencer, a plurality of one or more sequence reads associated with the converted one or more gene loci molecules; and determining, using one or more processors, one or more methylation signatures associated with the sequence reads based on the plurality of sequence reads.

[0241] Embodiment 44. The method of any of embodiments 1-43, further comprising generating by the one or more processors, a report indicating the presences of tumor DNA based on the one or more methylation signatures.

[0242] Embodiment 45. The method of embodiment 44, further comprising transmitting the report to a healthcare provider.

[0243] Embodiment 46. The method of embodiment 44, wherein the report is transmitted via a computer network or a peer-to-peer connection.

[0244] Embodiment 47. A method for detecting the presence of cancer, comprising: detecting one or more methylation signatures according to the method of embodiment 43, wherein the methylation signatures are indicative of a cancer.

[0245] Embodiment 48. A method for monitoring cancer progression or recurrence in a subject, the method comprising: detecting a first set of one or more methylation signatures using first isolated nucleic acid molecules in a first sample obtained from the subject at a first time point according to the method of embodiment 43; detecting a second set of one or more methylation signatures using second isolated nucleic acid molecules in second sample obtained from the subject at a second time point, wherein the first time point is before or after the second time point; and determining the progression of cancer by at least comparing the first methylation signature to the second methylation signature.

[0246] Embodiment 49. The method of embodiment 47 or 48, wherein a cancer treatment is administered to the subject after the first time point and before the second time point.

[0247] Embodiment 50. The method of embodiment 49, wherein a determination is made to maintain the cancer treatment based on the comparing.

[0248] Embodiment 51. The method of any of embodiments 1-50, wherein at least a portion of the method is automated.

[0249] Embodiment 52. A system comprising: one or more processors, and a memory communicatively coupled to the one or more processors and configured to store instructions that, when executed by the one or more processors, cause the system to control robotic components for automating: ligating one or more adapters to nucleic acid molecules in a ligation buffer; binding the nucleic acid molecules to a plurality of beads in the ligation buffer; separating from the ligation buffer, the plurality of beads bound to the nucleic acid molecules; suspending the plurality of beads in a solution comprising alcohol; and converting, using a bisulfite reaction, unmethylated cytosines in the nucleic acid molecules to uracil, to generate converted nucleic acid molecules.

[0250] Embodiment 53. A method of detecting a likely presence of cancer in a subject, comprising:ligating one or more adapters to nucleic acid molecules in a ligation buffer; binding the nucleic acid molecules to a plurality of beads in the ligation buffer; separating from the ligation buffer, the plurality of beads bound to the nucleic acid molecules; suspending the plurality of beads in a solution comprising alcohol; converting, using a bisulfite reaction, unmethylated cytosines in the nucleic acid molecules to uracil, to generate converted nucleic acid molecules; sequencing, by a sequencer, the converted nucleic acid molecules to generate a plurality of sequence reads; analyzing, by one or more processors, the plurality of reads to identify one or more methylation patterns in the plurality of sequence reads; and based on the one or more methylation patterns, detecting the presence of cancer in the subject.

[0251] Embodiment 54. The method of embodiment 53, wherein the nucleic acid molecules are DNA molecules.

[0252] Embodiment 55. The method of embodiment 53, wherein the nucleic acid molecules are RNA molecules.

[0253] Embodiment 56. A system comprising: one or more processors, and a memory communicatively coupled to the one or more processors and configured to store instructions that, when executed by the one or more processors are configured to: determine that one or more sequence reads received from a sequencer includes one or more methylation patterns indicating a likely presence of cancer in a subject, wherein the sequence reads are derived from one or more nucleic acid molecules that have been subjected to a conversion process, the conversion process including: ligating one or more adapters to nucleic acid molecules in a ligation buffer, binding the nucleic acid molecules to a plurality of beads in the ligation buffer, separating from the ligation buffer, the plurality of beads bound to the nucleic acid molecules, suspending the plurality of beads in a solution comprising alcohol, and converting, using a bisulfite reaction, unmethylated cytosines in the nucleic acid molecules to uracil, to generate converted nucleic acid molecules; andbased on the methylation patterns, detecting, by the one or more processors, the likely presences of cancer in the subject.EXAMPLES

[0254] This section provides non-limiting examples of the methods described herein.Example 1

[0255] DNA molecules were derived from samples from a cell line was acoustically sheared to approximately 170 bases in length. The resulting DNA molecules were used to prepare a sequencing library. The sequencing library preparation first involved shearing the DNA in a solution of lx TE buffer, to generate DNA fragments. The fragmented DNA molecules were then aliquoted into an amount of 500 pg to 1 pg. The ends of the fragmented DNA molecules were then blunted via an end-repair reaction, such that the DNA fragments comprised blunt ends instead of jagged ends. In the same end-repair reaction, the DNA fragments were phosphorylated on their 5’ ends and adenylated on their 3’ ends.

[0256] After the ends of the DNA fragments were modified, adapters were ligated onto the DNA fragments, in a ligation buffer. The ligation reaction was then cleaned up with the use of a SPRI beads solution. The SPRI beads solution was vortexed and then added to the adapter ligation reaction. The resulting mixture of the SPRI beads solution, the ligation enzymes, the ligation buffer, and the DNA fragments ligated to the adapters were mixed together and incubated for 5 minutes at room temperature, so that the DNA fragments could bind to the SPRI beads via the adapter sequences. The resulting mixture was then subject to a magnetic stand that separated the SPRI beads bound to the DNA fragments, from the other contents of the mixture, such as the ligation buffer. The magnetic stand applied a magnetic field to the mixture, such that the SPRI beads and its bound DNA fragments were pelleted and affixed to the bottom of the mixture. The supernatant was then removed, thereby isolating the SPRI beads and its bound DNA fragments.

[0257] Freshly prepared 80% ethanol was then added to the isolated SPRI beads and its bound DNA fragments. In contrast to traditional methods, which do not disturb the beads when adding the 80% ethanol, the beads and its bound DNA fragments were vigorously suspended, to completion, in the ethanol. The ethanol and SPRI beads solution was then subjected to a magnetic field, such that the beads were pelleted to the bottom of the mixture,and the supernatant was removed. The addition of the 80% ethanol, the vigorous suspension of the beads and ethanol, the pelleting of the beads, and the removal of the supernatant, were then repeated two more times. The beads were then air-dried for 5 minutes, while the beads were subjected to a magnetic field. A Tris-EDTA solution was then added to the beads and the resulting solution was suspended, to elute (i.e., release) the DNA fragments from the SPRI beads. A magnetic field was then applied to the solution, such that the beads were pelleted to the bottom of the mixture, and the supernatant, which comprised the eluted DNA fragments, was transferred to a new tube. Following the DNA library preparation, the isolated DNA fragments were subjected to a bisulfite conversion reaction, which converted the unmethylated cytosines in the DNA fragments into uracil.

[0258] The isolated DNA fragments that were prepared with the vigorous suspension in ethanol, while bound to the beads, resulted in a higher yield of DNA fragments, when compared to DNA fragments that were isolated without being subject to the vigorous suspension in 80% ethanol. FIG. 3 illustrates the comparison. On the left side of FIG. 3 is a bar glyph indicating a mean of approximately 75 ng of isolated DNA fragments (when measured by a fluoremeter) when the library preparation protocol did not comprise the vigorous suspension of the DNA-bound beads in 80% ethanol. In contrast, on the right side of FIG. 3 is a bar glyph indicating a mean of approximately 300 ng of isolated DNA fragments (when measured by a fluoremeter) when the library preparation protocol did comprise the vigorous suspension of the DNA-bound beads in 80% ethanol. Thus, when the DNA-bound beads were subject to the vigorous suspension in 80% ethanol, the yield was improved by approximately 4.4-fold.

[0259] Furthermore, the isolated DNA fragments that were prepared with the vigorous suspension in ethanol, while bound to the beads, also resulted in reduced GC dropout, when compared to DNA fragments that were isolated without being subject to the vigorous suspension in 80% ethanol. FIG. 4 illustrates the comparison. GC dropout refers to a Picard metric, in percentage, that quantifies the extent to which high-GC regions are underrepresented by the sequencing reads, relative to the mean. Of note, only 19% of the human genome is high GC, and thus, the max value of the GC dropout is 19%. On the left side of FIG. 4 is a bar glyph indicating an approximate mean GC dropout value of 6.8, when the library preparation protocol did not comprise the vigorous suspension of the DNA-bound beads in 80% ethanol. On the right side of FIG. 4 is a bar glyph indicating an approximate mean GC dropout value of 1.1 , when the library preparation protocol did comprise thevigorous suspension of the DNA-bound beads in 80% ethanol. Thus, when the DNA-bound beads were subject to the vigorous suspension in 80% ethanol, the GC dropout was reduced by about 7-fold.

[0260] The reduced GC dropout levels from when the DNA fragments were prepared with the vigorous suspension in 80% ethanol resulted in an improved number of reads that pass the quality filtering steps of the analysis pre-processing pipeline, as indicated in FIG. 5. White circuls in FIG. 5 corresponding to the “control” label in the legend represents a sample of isolated DNA fragments that were not subject to the suspension in 80% ethanol. Each black circle in FIG. 5 corresponding to the “vigorous suspension in 80% ethanol” label in the legend represents a sample of isolated DNA fragments that were subject to the suspension in 80% ethanol. On the y-axis of FIG. 5 is the coverage-normalized number of reads that pass the quality filter. On the x-axis of FIG. 5 is the GC dropout level. As was depicted in FIG. 4, the DNA-bound beads that were subject to the vigorous suspension in 80% ethanol exhibit much lower GC dropout when compared to the DNA-bound beads that were not subject to the vigorous suspension. As seen by the y-axis values, the samples subject to the vigorous suspension of the DNA-bound beads in 80% ethanol also resulted in a high normalized number of reads that pass filter (approximately 5500 reads, on average). In contrast, the samples not subject to the vigorous suspension resulted in a much lower normalized number of reads that pass filter (on average approximately 2600 reads). Thus, when the DNA-bound beads were subject to the vigorous suspension in 80% ethanol, the GC dropout was reduced by about 7-fold, which corresponded to an approximately 2.1 -fold increase in the normalized number of reads that pass the quality filter.Example 2

[0261] The isolated DNA fragments for this example were subject to the same sequencing library preparation protocol used for the isolated DNA fragments in Example 1. That is, the DNA fragments were subject to the vigorous suspension in 80% ethanol during library preparation. In the present example, however, the vigorously 80% ethanol-suspended DNA fragments were then spiked with one of various components from the sequencing library preparation protocol. By spiking in a component (e.g., end-repair / A-tailing buffer, ligation mix, or ligation enhancer) from the sequencing library preparation protocol prior to bisulfite conversion, components from the library preparation protocol could be tested for negative impacts they may have had on the isolated DNA molecules, following bisulfite conversion.

[0262] The isolated DNA molecules were spiked with either no components from the library preparation protocol (1st bar glyph from the left in FIG. 6), end-repair / A-tailing (ER / AT) buffer (2nd bar glyph from the left in FIG. 6), the ligation mix, which includes at least polyethylene glycol, ligase, salts, and ATP (3rd bar glyph from the left in FIG. 6), or the ligation enhancers, which comprises ancillary enzymes and cofactors (4th bar glyph from the left in FIG. 6). As seen in FIG. 3, the spiking in of the ER / AT buffer or the ligation enhancers prior to bisulfite conversion, resulted in similar amounts of DNA fragment yield as not spiking in any components from the library preparation protocol, as measured by a fluoremeter, following bisulfite conversion, at approximately 380 to 430 ng. In sharp contrast, however, the spiking in of the ligation mix, prior to bisulfite conversion, resulted in a large decrease in the DNA yield, following bisulfite conversion, at approximately 60 ng. Thus, one or more components in the ligation mix used for ligating adapters onto the DNA fragments, not found in neither the ER / AT buffer nor the ligation enhancer buffer, reduced the final amount of DNA isolated after bisulfite conversion.

[0263] The spiking experiment was performed also with respect to the GC dropout effects. That is, the isolated DNA molecules were spiked with either no components from the library preparation protocol (1st bar glyph from the left in FIG. 7), ER / AT buffer (2nd bar glyph from the left in FIG. 7), the ligation mix, which includes at least polyethylene glycol, ligase, salts, and ATP (3rd bar glyph from the left in FIG. 7), or the ligation enhancers, which comprises ancillary enzymes and cofactors (4th bar glyph from the left in FIG. 7). As seen in FIG. 7, the spiking in of the ER / AT buffer or the ligation enhancers prior to bisulfite conversion, resulted in similar levels of GC dropout as not spiking in any components from the library preparation protocol, following bisulfite conversion, at approximately levels of 2.0 to 2.8. In sharp contrast, however, the spiking in of the ligation mix, prior to bisulfite conversion, resulted in a large increase in GC dropout, following bisulfite conversion, at approximately levels of 8.5. Thus, one or more components in the ligation mix used for ligating adapters onto the DNA fragments, not found in neither the ER / AT buffer nor the ligation enhancer buffer, increased the amount of GC dropout, following bisulfite conversion.Example 3

[0264] The isolated DNA fragments for this example were subject to the same sequencing library preparation protocol used for the isolated DNA fragments in Example 1. That is, the DNA fragments were subject to the vigorous suspension in 80% ethanol during librarypreparation. In the present example, however, the vigorously 80% ethanol-suspended DNA fragments were then spiked with one of various components from the sequencing library preparation protocol. By spiking in a component from the sequencing library preparation protocol prior to bisulfite conversion, components from the library preparation protocol could be tested for negative impacts they may have had on the isolated DNA molecules, following bisulfite conversion. For this example, cell-free DNA (cfDNA) extracted from plasma obtained from a late-stage prostate cancer patient with 47% tumor fraction was used as the starting DNA for library preparation, instead of genomic DNA.

[0265] The isolated DNA fragments that were prepared with the vigorous suspension in ethanol, while bound to the beads, resulted in a higher yield of cfDNA fragments, when compared to cfDNA fragments that were isolated without being subject to the vigorous suspension in 80% ethanol. FIG. 8 illustrates the comparison. On the left side of FIG. 8 is a bar glyph indicating a mean of approximately 385 ng of isolated cfDNA fragments (when measured by a fluoremeter) when the library preparation protocol did not comprise the vigorous suspension of the cfDNA-bound beads in 80% ethanol. In contrast, on the right side of FIG. 8 is a bar glyph indicating a mean of approximately 515 ng of isolated cfDNA fragments (when measured by a fluoremeter) when the library preparation protocol did comprise the vigorous suspension of the DNA-bound beads in 80% ethanol. Thus, when the cfDNA-bound beads were subject to the vigorous suspension in 80% ethanol, the yield was improved by approximately 34%.

[0266] Furthermore, the isolated cfDNA fragments that were prepared with the vigorous suspension in ethanol, while bound to the beads, also resulted in reduced GC dropout, when compared to cfDNA fragments that were isolated without being subject to the vigorous suspension in 80% ethanol. FIG. 9 illustrates the comparison. GC dropout refers to a Picard metric, in percentage, that quantifies the extent to which high-GC regions are underrepresented by the sequencing reads, relative to the mean. Of note, only 19% of the human genome is high GC, and thus, the max value of the GC dropout is 19%. On the left side of FIG. 9 is a bar glyph indicating an approximate mean GC dropout value of 7.7, when the library preparation protocol did not comprise the vigorous suspension of the DNA-bound beads in 80% ethanol. On the right side of FIG. 9 is a bar glyph indicating an approximate mean GC dropout value of 3.0, when the library preparation protocol did comprise the vigorous suspension of the DNA-bound beads in 80% ethanol. Thus, when the DNA-boundbeads were subject to the vigorous suspension in 80% ethanol, the GC dropout was reduced by about 2.6-fold.

[0267] The reduced GC dropout levels from when the DNA fragments were prepared with the vigorous suspension in 80% ethanol resulted in an improved number of reads that pass the quality filtering steps of the analysis pre-processing pipeline, as indicated in FIG. 10. White circles in FIG. 10 corresponding to the “control” label in the legend represents a sample of isolated DNA fragments that were not subject to the suspension in 80% ethanol. Dark circles in FIG. 10 corresponding to the “vigorous suspension in 80% ethanol” label in the legend represents a sample of isolated DNA fragments that were subject to the suspension in 80% ethanol. On the y-axis of FIG. 10 is the coverage-normalized number of reads that pass the quality filter. On the x-axis of FIG. 10 is the GC dropout level. As was depicted in FIG. 10, the DNA-bound beads that were subject to the vigorous suspension in 80% ethanol exhibit much lower GC dropout, when compared to the DNA-bound beads that were not subject to the vigorous suspension. As seen by the y-axis values, the samples subject to the vigorous suspension of the DNA-bound beads in 80% ethanol also resulted in a high normalized number of reads that pass filter (approximately 3200 reads, on average). In contrast, the samples not subject to the vigorous suspension resulted in a much lower normalized number of reads that pass filter (approximately 1600 reads, on average). Thus, when the DNA-bound beads were subject to the vigorous suspension in 80% ethanol, the GC dropout was reduced by about 2.6-fold, which corresponded to an approximately 2-fold increase in the normalized number of reads that pass the quality filter..It should be understood from the foregoing that, while particular implementations of the disclosed methods and systems have been illustrated and described, various modifications can be made thereto and are contemplated herein. It is also not intended that the invention be limited by the specific examples provided within the specification. While the invention has been described with reference to the aforementioned specification, the descriptions and illustrations of the preferable embodiments herein are not meant to be construed in a limiting sense. Furthermore, it shall be understood that all aspects of the invention are not limited to the specific depictions, configurations or relative proportions set forth herein which depend upon a variety of conditions and variables. Various modifications in form and detail of the embodiments of the invention will be apparent to a person skilled in the art. It is therefore contemplated that the invention shall also cover any such modifications, variations and equivalents.

Claims

CLAIMSWhat is claimed is:

1. A method of preparing a sequencing library, comprising: ligating one or more adapters to nucleic acid molecules in a ligation buffer; binding the nucleic acid molecules to a plurality of beads in the ligation buffer; separating from the ligation buffer, the plurality of beads bound to the nucleic acid molecules; suspending the plurality of beads in a solution comprising alcohol; and converting, using a bisulfite reaction, unmethylated cytosines in the nucleic acid molecules to uracil, to generate converted nucleic acid molecules.

2. The method of claim 1, wherein the nucleic acid molecules are DNA molecules.

3. The method of claim 2, wherein the DNA molecules are cell- free DNA (cfDNA) molecules.

4. The method of claim 1, wherein the nucleic acid molecules are RNA molecules.

5. The method of claim 1, wherein the method comprises fractioning the nucleic acid molecules based on size.

6. The method of claim 5, wherein the fractioning occurs after the ligating, and before the binding of the nucleic acid molecules to a plurality of beads in the ligation buffer.

7. The method of claim 5, wherein the fractioning comprises: combining a second plurality of beads with the nucleic acid molecules, thereby allowing a first portion of the nucleic acid molecules to bind to the second plurality of beads; separating the second plurality of beads from a second portion of the nucleic acid molecules; and discarding the second plurality of beads and the first portion of the nucleic acid molecules.

8. The method of claim 1, wherein the converting occurs before the ligating.

9. The method of claim 1, wherein the converting occurs after the suspending.

10. The method of claim 1, wherein the method comprises denaturing the converted nucleic acid molecules.

11. The method of claim 1 , wherein the method comprises amplifying the converted nucleic acid molecules.

12. The method of claim 1, wherein the method comprises blunting the ends of the nucleic acid molecules.

13. The method of claim 1, wherein the method comprises fragmenting the nucleic acid molecules.

14. The method of claim 13, wherein fragmenting the nucleic acid molecules comprises shearing the nucleic acid molecules.

15. The method claim 1, wherein the nucleic acid molecules are phosphorylated at 5’ ends of the nucleic acid molecules or the nucleic acid molecules are adenylated at 3’ ends of the nucleic acid molecules.

16. The method of claim 1, wherein the alcohol is ethanol, isopropanol, or a combination thereof.

17. The method of claim 1, further comprising separating the nucleic acid molecules from the plurality of beads by eluting the nucleic acid molecules in a solvent.

18. A method of sequencing the converted nucleic acid molecules, comprising: preparing the sequencing library, according to the method of claim 1 ; and sequencing, using a sequencer, the converted nucleic acid molecules.

19. A method of detecting one or more methylation signatures in a sample, comprising: sequencing, by a sequencer, the converted one or more gene loci molecules according claim 18; generating, by the sequencer, a plurality of one or more sequence reads associated with the converted one or more gene loci molecules; and determining, using one or more processors, one or more methylation signatures associated with the sequence reads based on the plurality of sequence reads.

20. A method of detecting a likely presence of cancer in a subject, comprising: ligating one or more adapters to nucleic acid molecules in a ligation buffer; binding the nucleic acid molecules to a plurality of beads in the ligation buffer; separating from the ligation buffer, the plurality of beads bound to the nucleic acid molecules; suspending the plurality of beads in a solution comprising alcohol; converting, using a bisulfite reaction, unmethylated cytosines in the nucleic acid molecules to uracil, to generate converted nucleic acid molecules; sequencing, by a sequencer, the converted nucleic acid molecules to generate a plurality of sequence reads; analyzing, by one or more processors, the plurality of reads to identify one or more methylation patterns in the plurality of sequence reads; and based on the one or more methylation patterns, detecting the presence of cancer in the subject.

Images