Methods for sequencing immune repertoires

Abstract

The present invention provides a non-invasive technique for detecting and quantifying the immune repertoire in a biological sample containing multiple different cell populations. The method is performed using sequencing technology to detect and enumerate the immune repertoire in a heterogeneous biological sample.

Description

[0001] This application is a divisional application of the invention patent application with application number 201480016198.0, application date March 14, 2014, applicant is Lineage Biosciences, Inc., and invention name is "Method for Sequencing Immune Repertoires".

[0002] Related Applications

[0003] This application claims the benefit of and priority to U.S. Provisional Application No. 61 / 806,143, filed on March 28, 2013, and U.S. Provisional Application No. 61 / 801,785, filed on March 15, 2013, which are incorporated herein by reference in their entireties. Technical Field

[0004] The present invention relates to the field of quantitative nucleic acid analysis. More specifically, the present invention provides a method for determining immune repertoires using high-throughput sequencing. Background Art

[0005] The characteristic of adaptive immune response is the ability to produce a wide variety of binding molecules, such as: T cell antigen receptors and antibodies. Various molecular mechanisms can be used to produce initial diversity, including genetic recombination at multiple sites. Initial (naive) B cells and initial T cells are equipped with an initial repertoire of binding moieties, which circulate at a position that can contact with the antigen. When exposed to the antigen, positive selection can be performed, wherein the cells expressing the immune receptors with the desired binding properties are amplified, and further sequence modifications, such as somatic mutations, and additional recombination can be experienced. Negative selection can also be performed to eliminate the cells expressing the immune receptors with undesirable binding properties (e.g., self-reactivity). As a result of these selection processes, the repertoire with binding specificity in individual samples can provide a history of past antigen exposure, as well as information as inherent repertoire capabilities and limitations.

[0006] Adaptive immune receptors of interest include immunoglobulins or antibodies. This repertoire is highly adaptive and can be directed to produce antibodies with broad chemical diversity and high selectivity. There is still a good understanding of the potential diversity that can be obtained and the mechanisms of how this diversity is generated. Antibodies are composed of two types of chains (heavy and light), each type containing a highly diverse antigen binding domain (variable). The V, D and J gene segments of the antibody heavy chain variable region genes undergo a series of recombination events to produce new heavy chain genes. Antibodies are formed by recombination of gene segments, sequence diversification at the junctions of these segments, and a mixture of point mutations throughout the gene. The mechanisms are reviewed, for example, in Mzizels (2005) Annu. Revu. Genet. 39: 23-46; Jones and Gellert (2004) Immunol. Rev. 200: 233-248; Winter and Gearhart (1998) Immunol. Rev. 162: 89-96.

[0007] Another adaptive immune receptor of interest is the T cell antigen receptor (TCR), which is a heterodimer of two chains, each of which is a member of the immunoglobulin superfamily, with an N-terminal variable (V) domain and a C-terminal constant domain. The variable domains of the α chain and β chain of TCR have three hypervariable or complementary determining regions (CDRs). The β chain has an additional region of hypervariability (HV4) that is usually not in contact with antigens. The process for producing the diversity of TCR is similar to the process described for immunoglobulins. The TCR α chain is produced by VJ recombination, while the β chain is produced by V(D)J recombination. Similarly, the production of TCR γ chain involves VJ recombination, while the production of TCR δ chain occurs by V(D)J recombination. The intersection of these specific regions (V and J of α or γ chain, VD and J of β chain or δ chain) corresponds to the CDR3 region, which is important for antigen MHC recognition. It is the unique combination of segments in this region as well as the palindromic structure and random N- and P-nucleotide additions that results in the TCR binding repertoire.

[0008] While reference is made to binding specificity, and indeed a large number of serological assays are based on the physical interaction between antigen and receptor, the underlying cause of diversity lies in the gene sequences expressed by lymphocytes, which reflect the myriad processes of recombination, variation, and selection that have been imposed on the cells.

[0009] Methods to accurately determine the immune receptor repertoire of an individual or a sample of interest from an individual would have enormous implications for prognosis, diagnosis, and characterization. Summary of the invention

[0010] The present invention provides a method for monitoring immune repertoire. More specifically, the present invention provides a method for determining the immune repertoire in a subject, which is by isolating multiple RNAs from a biological sample containing multiple cell types from a subject; generating immunoglobulin chains or TCR chains cDNA from the RNA; adding homopolymeric tails, random molecular tags and universal sequences to the 3' end of the cDNA; amplifying the cDNA by using one or more immunoglobulin chains or TCR chains specific primers and universal sequence-specific primers containing flanking sequences specific to the sequencing platform to generate multiple molecularly labeled immunoglobulin chains or TCR chains nucleic acids; and sequencing the amplified immunoglobulin chains or TCR chains nucleic acids to generate multiple sequencing reads, thereby determining the immune repertoire of the subject. Optionally, the method also includes a data analysis step, such as grouping sequences with the same molecular markers read and clustered in the same group. In some aspects, the consensus sequence of each cluster is determined to generate a set of consensus sequences. The set of consensus sequences is used to determine the diversity of the immune repertoire.

[0011] The molecular marker is an oligomer. The oligomer is at least 9-mer. The biological sample is blood or a blood component. The blood is peripheral whole blood. The blood component comprises peripheral blood mononuclear cells. In certain aspects, the blood sample is classified based on extracellular or intracellular markers.

[0012] The immunoglobulin chain is a heavy chain or a light chain. The immunoglobulin heavy chain comprises the immunoglobulin VDJ and a constant region. The TCR chain is an α chain, a β chain, a γ chain or a δ chain. The TCR chain comprises VJ and a constant region. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 is a schematic diagram of the method of the present invention.

[0014] Figure 2 is a schematic diagram highlighting the difference between the method of the present invention and multiplex sequencing of immune repertoires.

[0015] Figure 3 It is shown that capture and PCR bias are eliminated by the method of the present invention.

[0016] Figure 4 is a schematic diagram detailing the sequencing of the immune repertoire according to the present invention.

[0017] Figure 5 is a schematic diagram detailing the sequencing of the immune repertoire according to the present invention.

[0018] Figure 6 is a schematic diagram detailing the molecular labeling steps of sequencing of the immune repertoire according to the method of the present invention.

[0019] Figure 7is a schematic diagram depicting the data analysis steps of the method according to the present invention.

[0020] Figure 8 is a graph showing the isotype distribution obtained from the same sample using multiplex PCR and the 5' RACE method of the present invention. Multiplex PCR skews the repertoire towards a more primitive bin.

[0021] Fig. 9 Graph showing the top 100 lineages for each sample and the corresponding representations in other samples. Bands connect identical lineages. The width of the segments represents the relative abundance of lineages in the sample. Several lineages visible with the method of the present invention are not present in the same sample prepared by multiplex PCR.

[0022] Fig.10 is a schematic diagram showing that multiplex PCR does not trigger lineages with mutations, resulting in the absence of highly mutated lineages in the multiplex PCR dataset. Fig.10 The sequence identifiers for each sequence in are SEQ ID NOs: 3-24 from top to bottom. DETAILED DESCRIPTION

[0023] The present invention provides an improved method for sequencing immune repertoires. Previous methods for determining immune repertoires, such as those described in WO 2011 / 140433 and WO 2012 / 083069, are based on multiplex PCR. Multiplex PCR has many limitations that make it particularly unsuitable for accurately determining the immune repertoire. (See Figure 2 )These limitations include capture bias and amplification bias due to PCR. The multiplex PCR technique of sequencing immune repertoires uses primers designed to trigger all framework regions of known V gene segments. When mutations occur at the priming position, capture bias occurs, and the mutated gene is under-amplified. PCR bias is generated due to uneven gene amplification caused by the relative amounts of each primer and PCR replicas with the same sequence. Therefore, PCR bias can lead to apparent clonality or lack of diversity. In general, the observed repertoire is inaccurate, or it is a linear representation of the actual repertoire.

[0024] To eliminate capture bias, the method of the present invention utilizes 5'RACE and universal PCR. PCR bias is eliminated by molecular markers. Figure 3 )

[0025] In addition, previous methods for sequencing immune repertoires require a population of specific immune cells (e.g., T cells or B cells) and require spatial isolation of such cells into single cells and / or single molecules of nucleic acids derived from these cells to form colonies. In contrast, the present method sequences immune repertoires directly from a heterogeneous population of cells derived from a heterogeneous mixture of nucleic acids.

[0026] The method of the present invention generally involves the following steps: obtaining a whole blood sample from peripheral blood of a subject, isolating RNA from the peripheral whole blood sample or its components (e.g., peripheral blood mononuclear cells), and reverse transcribing the isolated RNA using immunoglobulin heavy chain or TCR β chain specific primers to produce a transcript of cDNA of an immunoglobulin (e.g., heavy chain or light chain) or TCR (e.g., α, β, δ or γ chain). Short homopolymers are added to the ends of the cDNA by the inherent properties of the reverse transcriptase. A 5' flanking sequence oligonucleotide having a 3' sequence complementary to the homopolymer and a molecular tag comprising a universal sequence and composed of random nucleotides will be used as a template by the reverse transcriptase. As a result, the ends of each cDNA molecule are extended with a short homopolymer, a unique molecular tag and a universal sequence. This allows the amplification of unknown sequences between the gene-specific sequence and the 5' end of the mRNA. ( Figure 4-6 ). Because each cDNA molecule is labeled with a unique tag before amplification, differential amplification of each cDNA molecule can be corrected by counting each unique tag once, thereby providing an accurate and reliable measurement of the abundance of each species in the repertoire. Sequence replicates of each cDNA molecule determined with the same molecular tag can be used to construct a consensus sequence, thus allowing correction for amplification and sequencing errors.

[0027] Subjects

[0028] The methods of the present invention use biological samples from subjects or individuals. The subject can be a patient, for example, a patient with an autoimmune disease, an infectious disease or a cancer or a transplant recipient. The subject can be a human or non-human mammal. The subject can be a male or female subject of any age (e.g., a fetus, an infant, a child, or an adult).

[0029] sample

[0030] Samples used in the methods of the provided invention can include, for example, body fluids from a subject, including amniotic fluid surrounding a fetus, aqueous body fluids, bile, blood and plasma, cerumen (ear wax), Cowper's fluid or pre-ejaculatory fluid, chyle, chyme, female ejection, interstitial fluid, lymph, menstruation, breast milk, mucus (including nasal mucus and sputum), pleural fluid, pus, saliva, sebum (skin oil), semen, serum, sweat, tears, urine, vaginal lubrication, vomit, feces, internal body fluids including cerebrospinal fluid surrounding the brain and spinal cord, synovial fluid around bone joints, intracellular fluid (fluid inside cells), and vitreous humor (fluid in the eyeball).

[0031] In one embodiment, the sample is a blood sample, such as a peripheral whole blood sample, or a fraction thereof. Preferably, the sample is unseparated whole blood.

[0032] A blood sample may be about 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.080.09, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, or 5.0 milliliters.

[0033] The sample can be obtained by a health care provider, such as a physician, assistant physician, nurse, veterinarian, dermatologist, rheumatologist, dentist, paramedic or physician. The sample can be obtained by a technician in the study. More than one sample can be obtained from a subject.

[0034] The sample may include immune cells. Immune cells may include T cells and / or B cells. T cells (T lymphocytes) include, for example, cells expressing T cell receptors. T cells include helper T cells (effector T cells or Th cells), cytotoxic T cells (CTLs), memory T cells, and regulatory T cells. Samples may include individual cells in some applications (e.g., calibration tests to define related T cells) or more generally at least 1000, at least 10,000, at least 100,000, at least 250,000, at least 500,000, at least 750,000, or at least one million T cells.

[0035] B cells include, for example, plasma B cells, memory B cells, B1 cells, B2 cells, marginal zone B cells and follicular B cells. B cells can express immunoglobulins (antibodies, B cell receptors). Samples can include single cells in some applications (e.g., calibration tests to define related B cells) or more generally at least 1000, at least 10,000, at least 100,000, at least 250000, at least 500,000, at least 750000 or at least 1 million B cells.

[0036] The sample can include nucleic acids, such as DNA (e.g., genomic DNA or mitochondrial DNA) or RNA (e.g., messenger RNA or microRNA). The nucleic acid can be cell-free DNA or RNA. In the provided invention, the amount of RNA or DNA from the subject that can be analyzed includes, for example, as low as a single cell in some applications (e.g., calibration tests) and as many as tens of millions of cells or more, which translates into 6 picograms to 60 micrograms of DNA and about 1 picogram to 10 micrograms of RNA.

[0037] Amplification reaction

[0038] Polymerase chain reaction (PCR) can be used to amplify the region of interest from a collection of cells.

[0039] In some embodiments, the region to be amplified includes the entire clonal sequence or a subset of the clonal sequence, including the VD junction, DJ junction, the entire variable region of the immunoglobulin or T cell receptor gene, the antigen recognition region, or the CDR, for example, the complementarity determining region 3 (CDR3).

[0040] In some embodiments, the immunoglobulin sequence is amplified using primary and secondary amplification steps. Each different amplification step can include different primers. Different primers can introduce sequences that are not originally present in the immune gene sequence. For example, the amplification step can add one or more tags to the 5' and / or 3' ends of the amplified immunoglobulin sequence. The label can be a sequence that helps to subsequently sequence the amplified DNA. The label can be a sequence that helps to bind the amplified sequence to a solid support. The label can be a barcode or label that helps to identify the amplified immunoglobulin sequence.

[0041] Other methods of amplification may not employ any primers in the V region. Instead, specific primers may be used starting from the C segment and a universal primer may be placed on the other side (5'). Universal primers may be attached during cDNA synthesis by various methods, including the well-described strand switching method. Similarly, universal primers may be attached after cDNA formation by various methods, including ligation.

[0042] Other ways of amplifying nucleic acids that can be used in the methods of the invention include, for example, reverse transcription PCR, real-time PCR, quantitative real-time PCR, digital PCR (dPCR), digital emulsion PCR (dePCR), clonal PCR, amplified fragment length polymorphism PCR (AFLP PCR), allele-specific PCR, assembly PCR, asymmetric PCR (wherein a large excess of primers is used for the selected strand), colony PCR, helicase-dependent amplification (HDA), hot start PCR, inverse PCR (IPCR), in situ PCR, long PCR (extension of DNA greater than about 5 kilobases), multiplex PCR, nested PCR (using more than one pair of primers), single cell PCR, touchdown PCR, loop-mediated isothermal PCR (LAMP), and nucleic acid sequence-based amplification (NASBA). Other amplification schemes include: ligase chain reaction, branched DNA amplification, rolling circle amplification, circle-to-circle amplification, SPIA amplification, targeted amplification by capture and ligation (TACL) amplification, and RACE amplification.

[0043] The information in the RNA in the sample can be converted into cDNA using reverse transcription using techniques well known to those of ordinary skill (see, e.g., Sambrook, Fritsch and Maniatis, MOLECULAR CLONING: A LABORATORY MANUAL, 2nd Edition (1989)). Polyadenylic acid (polyA) primers, random primers and / or gene-specific primers can be used in the reverse transcription reaction.

[0044] Polymerases that can be used for amplification in the provided methods of the invention include, for example, Taq polymerase, AccuPrime polymerase, or Pfu. The choice of polymerase used can be based on whether fidelity or efficiency is preferred.

[0045] After amplification of DNA from the genome (or amplification of nucleic acid in the form of cDNA by reverse transcribing RNA), the amplicons are sequenced directly.

[0046] Sequencing

[0047] Any technique for sequencing nucleic acids known to those skilled in the art can be used in the methods of the invention provided. DNA sequencing techniques include classical dideoxy sequencing reactions (Sanger method) using labeled terminators or primers and gel separation in plates or capillaries, sequencing by synthesis using reversibly capped labeled nucleotides, pyrophosphate sequencing, 454 sequencing, allele-specific hybridization to libraries of labeled oligonucleotide probes, sequencing by synthesis using allele-specific hybridization to libraries of labeled clones followed by ligation, real-time monitoring of labeled nucleotide incorporation during the polymerization step, and SOLiD sequencing.

[0048] In certain embodiments, the sequencing technology used in the provided methods of the invention produces at least 100 reads per run, at least 200 reads per run, at least 300 reads per run, at least 400 reads per run, at least 500 reads per run, at least 600 reads per run, at least 700 reads per run, at least 800 reads per run, at least 900 reads per run, at least 1000 reads per run, at least 5000 reads per run, at least 10000 reads per run, at least 50000 reads per run, At least 100,000 reads per run, at least 500,000 reads per run, at least 1,000,000 reads per run, at least 2,000,000 reads per run, at least 3,000,000 reads per run, at least 4,000,000 reads per run, at least 5,000,000 reads per run, at least 6,000,000 reads per run, at least 7,000,000 reads per run, at least 8,000,000 reads per run, at least 9,000,000 reads per run, or at least 10,000,000 reads per run.

[0049] In some embodiments, the number of sequencing reads per B cell sampled should be at least 2 times the number of B cells sampled, at least 3 times the number of B cells sampled, at least 5 times the number of B cells sampled, at least 6 times the number of B cells sampled, at least 7 times the number of B cells sampled, at least 8 times the number of B cells sampled, at least 9 times the number of B cells sampled, at least 10 times the number of B cells sampled. The read depth allows accurate coverage of the sampled B cells, facilitates error correction, and ensures that the library has been saturated with sequencing.

[0050] In some embodiments, the number of sequencing reads per sampled T-cell should be at least 2 times the number of sampled T cells, at least 3 times the number of sampled T cells, at least 5 times the number of sampled T cells, at least 6 times the number of sampled T cells, at least 7 times the number of sampled T cells, at least 8 times the number of sampled T cells, at least 9 times the number of sampled T cells, at least 10 times the number of sampled T cells. The read depth allows for accurate coverage of the sampled T cells, facilitates error correction, and ensures that the library has been saturated with sequencing.

[0051] In certain embodiments, the sequencing technology used in the provided methods of the invention can produce about 30bp, about 40bp, about 50bp, about 60bp, about 70bp, about 80bp, about 90bp, 100bp, about 110bp, about 120bp, about 150bp, about 200bp, about 250bp, about 300bp, 350bp, 400bp, 450bp, 500bp, 550bp, 600bp, 700bp, 800bp, 900bp, or about 1000bp per read. For example, the sequencing technology used in the methods provided herein can produce at least 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 150, 200, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700, 750, 800, 850, 900, 950, or 1000 reads per sequence.

[0052] True Single Molecule Sequencing

[0053] The sequencing technology used in the provided methods of the invention includes, for example, true single molecule sequencing (tSMS) by Helicos (Harris TD et al., (2008) Science 320: 106-109). In tSMS technology, a DNA sample is cut into chains of about 100 to 200 nucleotides, and a polyadenylic acid sequence is added to the 3' end of each DNA chain. Each chain is labeled by adding fluorescently labeled adenosine nucleotides. The DNA chains are then hybridized to a flow cell containing millions of capture sites of oligonucleotide-T fixed to the surface of the flow cell. The template can be at about 1 million templates / cm 2 The flow cell is then loaded into a tool, such as the HeliScope TM The sequencer is laser-irradiated on the surface of the flow cell, exposing the location of each template. A CCD camera can map the location of the template on the surface of the flow cell. The template fluorescent label is then cut off and washed away. The sequencing reaction is started by introducing DNA polymerase and fluorescently labeled nucleotides. Oligonucleotide-T nucleic acid serves as a primer. The polymerase binds the labeled nucleotides to the primer in a template-guided manner. The polymerase and unincorporated nucleotides are removed. The template with the directed incorporation of fluorescently labeled nucleotides is detected by imaging the surface of the flow cell. After imaging, a cleavage step removes the fluorescent label, and the process is repeated with other fluorescently labeled nucleotides until the desired reading length is reached. Sequence information is collected for each nucleotide addition step.

[0054] 454 sequencing

[0055] Another example of a DNA sequencing technique that can be used in the method of the present invention provided is 454 sequencing (Roche) (Margulies, M et al., 2005, Nature, 437, 376-380). 454 sequencing involves two steps. In the first step, DNA is sheared into fragments of about 300-800 base pairs, and the fragments are blunt-ended. Then oligonucleotide adapters are connected to the ends of the fragments. The adapters serve as primers for amplifying and sequencing the fragments. Using, for example, adapter B containing a 5'-biotin label, the fragments can be connected to capture beads (e.g., streptavidin-coated beads) of DNA. The fragments attached to the beads are PCR amplified in droplets of an oil-water emulsion. As a result, there are multiple copies of cloned amplified DNA fragments on each bead. In the second step, the beads are captured in a hole (picoliter size). Pyrophosphate sequencing is performed in parallel on each DNA fragment. The addition of one or more nucleotides produces a light signal recorded by a CCD camera in a sequencer. The signal intensity is proportional to the number of nucleotides incorporated.

[0056] Pyrosequencing utilizes pyrophosphate (PPi) that is released upon nucleotide addition. PPi is converted to ATP by ATP sulfurylase in the presence of adenosine 5' phosphosulfate. Luciferase uses ATP to convert luciferin to oxyluciferin, a reaction that produces light that is detected and analyzed.

[0057] Genome Sequencer FLX TM

[0058] Another example of a DNA sequencing technology that can be used in the methods of the present invention is the Genome Sequencer FLX System (Roche / 454). The Genome Sequencer FLX System (such as GS FLX / FLX+, GS Junior) provides high-quality reads of more than 1 million per run and a read length of 400 bases. These systems are well suited for de novo sequencing of whole genomes and transcriptomes of any scale, metagenomic characterization of complex samples, or resequencing studies.

[0059] SOLiD TM Sequencing

[0060] Another example of the DNA sequencing technology that can be used in the method of the present invention provided is SOLiD technology (Life Technologies). In SOLiD sequencing, genomic DNA is sheared into fragments, and adapters are connected to the 5' and 3' ends of the fragments to produce a fragment library. Alternatively, internal adapters can be introduced in the following ways: adapters are connected to the 5' and 3' ends of the fragments, circularized fragments, digested circularized fragments to produce internal adapters, and adapters are connected to the 5' and 3' ends of the produced fragments to produce a paired library. Then, a clone bead group is prepared in a microreactor containing beads, primers, templates, and PCR components. Following PCR, the template is denatured, and the beads are enriched to separate the beads with the extended template. The template on the selected bead is allowed to be attached to the 3' modification of the slide.

[0061] The sequence can be determined by sequential hybridization and partial ligation of random oligonucleotides to a centrally determined base (or base pair) labeled by a specific fluorophore. After the color is recorded, the ligated oligonucleotide is cleaved and removed, and the process is repeated.

[0062] Ion Torrent TM Sequencing

[0063] Another example of a DNA sequencing technology that can be used in the methods of the present invention provided is the IonTorrent system (Life Technologies). Ion Torrent uses a high-density array of micro-machined holes to perform the biochemical process in a massively parallel manner. Each hole holds a different DNA template. Below the hole is an ion-sensitive layer and below that is a proprietary ion sensor. If a nucleotide (e.g., C) is added to the DNA template and then incorporated into the DNA chain, a hydrogen ion will be released. The charge from the ion will change the pH of the solution, which can be detected by a proprietary ion sensor. The sequencer will call the base, directly from chemical information to digital information. The Ion Personal Genome Machine (PGM TM ) The sequencer then flushes the chip with nucleotide after nucleotide in sequence. If the next nucleotide flushed with the chip does not match, no voltage change will be recorded and no base will be called. If there are two identical bases on the DNA strand, the voltage will be doubled and the chip will record two identical bases called. Because this is direct detection - no scanning, no camera, no light - each nucleotide incorporation is recorded within seconds.

[0064] HiSeq TM and MiSeq TM Sequencing

[0065] Additional examples of sequencing technologies that can be used in the methods of the present invention include HiSEQ from Illumina TM System (e.g., HiSEQ2000 TM and HiSEQ1000 TM ) and MiSEQ TM System. HiSEQ TM The system is based on massively parallel sequencing of millions of fragments, using the attachment of randomly fragmented genomic DNA to a flat, optically transparent surface and solid-phase amplification to produce high-density sequencing flow cells with millions of clusters, each containing approximately 1,000 copies of template per square centimeter. These templates are sequenced using four-color DNA by synthetic sequencing technology. MiSEQ TM The system uses TruSeq, Illumina's reversible terminator-based sequencing by synthesis.

[0066] SOLEXA TM Sequencing

[0067] Another example of a sequencing technology that can be used in the method of the present invention is SOLEXA sequencing (Illumina). SOLEXA sequencing is based on the amplification of DNA on a solid surface using fold-back PCR and anchor primers. Genomic DNA is fragmented, and adapters are added to the 5' and 3' ends of the fragments. DNA fragments attached to the surface of the flow cell channel are extended and bridge amplified. The fragments become double-stranded, and the double-stranded molecules are denatured. Multiple cycles of solid phase amplification followed by denaturation can produce millions of clusters of about 1000 copies of single-stranded DNA molecules of the same template in each channel in the flow cell. Primers, DNA polymerase and 4 fluorophore-labeled, reversible terminator nucleotides are used to perform sequential sequencing. After nucleotide incorporation, a laser is used to excite the fluorophore, and an image is captured, recording the identity of the first base. The 3' terminator and fluorophore from each incorporated base are removed and the incorporation, detection and recognition steps are repeated.

[0068] SMRT TM Sequencing

[0069] Another example of a sequencing technology that can be used in the methods of the present invention includes the single molecule, real-time (SMRT) sequencing technology from Pacific Biosciences. TM ) technology. TMIn the invention, each of the four DNA bases is attached to one of four different fluorescent dyes. These dyes are phosphorus-linked. A single DNA polymerase is fixed with a single molecule of a template single-stranded DNA at the bottom of a zero-mode waveguide (ZMW). The ZMW is a confining structure that enables the incorporation of a single nucleotide by a DNA polymerase to be observed against the background of fluorescent nucleotides that diffuse rapidly in and out of the ZMW (microseconds). It takes several milliseconds to incorporate the nucleotide into the growing chain. During this period, the fluorescent label is excited and produces a fluorescent signal, and the fluorescent label is cut off. The detection of the corresponding fluorescence of the dye indicates which base is incorporated. The process is repeated.

[0070] Nanopore sequencing

[0071] Another example of a sequencing technology that can be used in the methods of the present invention provided is nanopore sequencing (Soni GV and Meller A. (2007) Clin Chem 53: 1996-2001). A nanopore is a very small hole with a diameter of about nanometers. The nanopore is immersed in a conductive fluid and a potential is applied across the nanopore, resulting in a slight current due to the conductivity of ions passing through the nanopore. The amount of current flowing is sensitive to the size of the nanopore. As the DNA molecule passes through the nanopore, each nucleotide on the DNA molecule blocks the nanopore to a different extent. Therefore, the change in the current passing through the nanopore as the DNA molecule passes through the nanopore represents the reading of the DNA sequence.

[0072] Chemically sensitive field-effect transistor array sequencing

[0073] Another example of a sequencing technique that can be used in the provided methods of the invention includes using a chemically sensitive field effect transistor (chemFET) array to sequence DNA (e.g., as described in U.S. Patent Application Publication No. 20090026082). In one example of this technique, a DNA molecule can be placed in a reaction chamber, and a template molecule can be hybridized to sequence a primer bound to a polymerase. The incorporation of one or more triphosphates into a new nucleic acid chain at the 3' end of the sequencing primer can be detected by a chemFET according to a change in current. The array can have multiple chemFET sensors. In another example, a single nucleic acid can be attached to a bead, the nucleic acid can be amplified on the bead, and the single bead can be transferred to each reaction chamber on the chemFET array, each chamber having a chemFET sensor, and the nucleic acid can be sequenced.

[0074] Sequencing using electron microscopy

[0075] Another example of a sequencing technique that can be used in the methods of the invention provided includes the use of an electron microscope (Moudrianakis EN and Beer M. Proc Natl Acad Sci USA 1965 March; 53: 564-71). In one example of this technique, individual DNA molecules are labeled with metal tags that are distinguishable using an electron microscope. These molecules are then stretched on a flat surface and imaged with an electron microscope to measure the sequence.

[0076] Any of the sequencing techniques described herein can be used in the methods of the invention.

[0077] Digital counting and analysis

[0078] Sequencing allows the presence of multiple immunoglobulin genes to be detected and quantified in heterogeneous biological samples.

[0079] High-throughput sequencing provides very large data sets, which are then analyzed to build repertoires.

[0080] High-throughput analysis can be achieved using one or more bioinformatics tools, such as ALLPATHS (whole-genome shotgun assembly, which can produce high-quality assemblies from short reads), Arachne (a tool for assembling genome sequences from whole-genome shotgun reads, mainly forward and reverse pairs obtained by sequencing clone ends), BACCardl (a graphical tool for genome assembly validation, aiding genome organization and inter-genome comparison), CCRaVAT & QuTie (allows analysis of rare variants and quantitative trait association studies in large-scale case-control datasets), CNV-seq (a method for detecting copy number variation using high-throughput sequencing), Elvira (a collection of tools / procedures for high-throughput assembly of small genomes (e.g., viruses)), Glimmer (a system for finding genes in the genomes of microbial DNA, especially bacteria, archaea, and viruses), gnumap (a program designed to accurately map sequence data obtained from next-generation sequencing machines), Goseq (an R library for performing gene ontology and other class-based tests on RNA-seq data corrected for selection bias), ICAtoo (an R library for performing gene ontology and other class-based tests on RNA-seq data corrected for selection bias), ls (a collection of programs for medium to large-scale sequencing projects), LOCAS, a program for assembling short reads from second-generation sequencing technologies, Maq (builds assemblies by mapping short reads to a reference sequence), MEME (a motif-based sequence analysis tool), NGSView (allows visualization and manipulation of millions of sequences simultaneously on a desktop computer through a graphical interface), OSLay (optimized synteny for unfinished assemblies), Perm (efficient mapping of short sequencing reads with regular perfect sensitivity interval inoculation), Projector (automated contig mapping for gap closing purposes), Qpalma (alignment tool that targets concatenated reads generated by sequencing platforms such as Illumina, Solexa, or 454), RazerS (rapid read mapping with sensitivity control), SHARCGS (a short-read assembler based on powerful contig extension for genome sequencing); DNAAssembler (designed for de novo assembly of 25-40mer input fragments and deep sequence coverage), Tablet (next-generation sequence assembly visualization), and Velvet (sequence assembler for very short reads).

[0081] Figure 7 A non-limiting example of the data analysis steps is summarized in the flowchart of FIG.

[0082] Group reads with the same molecular marker: First match the sequences based on the same molecular marker.

[0083] A minimum spanning forest is constructed for each group: if the Hamming distance is greater than 5%, it is clustered into a subgroup (hair bundle).

[0084] For each subgroup (or tree), a vector of the sum of correct probabilities is created for each called base in each read.

[0085] A consensus read was created from the bases using the maximum sum in each position: the consensus read was used for mutation analysis and diversity measurement.

[0086] Diversity of VDJ lineages: VDJ usage is enumerated by the number of observed lineages falling into each VJ, VDJ, VJC, or VDJC (e.g., VDJ) combination at a given read depth.

[0087] VDJ and unique sequence abundance histograms: Histograms were plotted by binning the abundance of VDJ and unique sequences into logarithmically spaced bins (abundances were clustered or had been filtered and grouped by pedigree analysis).

[0088] Three-dimensional representation of VJ, VDJ, VJC, or VDJC (e.g., VDJ) usage: The repertoire is represented by applying V-, D-, J-, and / or C-segments to different axes on a three-dimensional plot. Bubbles of various sizes are used at each V / D / J / C coordinate to represent the total usage of that combination using abundance (usually number of reads, which can be bias-normalized) or observed lineage diversity.

[0089] Mutation vs. sequence abundance plot: After undergoing pedigree analysis, unique sequences are binned into logarithmically spaced bins by read count (or bias-normalized abundance). For a given abundance bin, the number of mutations per unique sequence is averaged to yield a mutation vs. abundance curve.

[0090] V, D, J, C, VJ, VDJ, VJC, VDJC, antibody heavy chain, antibody light chain, CDR3, or T cell receptor usage correlation measures (Pearson, KL divergence): The combination of VJ, VDJ, VJC or VDJC (e.g., VDJ) is considered as a vector with index components V,, weighted by the lineage diversity or abundance of the VDJ combination. The Pearson correlation, KL-divergence, between each pair of individuals is then calculated on the index.

[0091] The results analyzed herein may be referred to as the results of an analysis of an immune repertoire, which may be represented as a data set including sequence information, a representation of V, D, J, C, VJ, VDJ, VJC, VDJC, antibody heavy chain, antibody light chain, CDR3, or T-cell receptor usage, a representation of the abundance of V, D, J, C, VJ, VDJ, VJC, VDJC, antibody heavy chain, antibody light chain, CDR3, or T-cell receptor and unique sequences; mutation frequency, a representation of the relevant detection of VJ, V, D, J, C, VJ, VDJ, VJC, VDJC, antibody heavy chain, antibody light chain, CDR3, or T-cell receptor usage, etc. Such results may then be output or stored, for example, in a database for repertoire analysis, and may be used for comparison with test results, reference results, etc.

[0092] After obtaining the analysis results of the immune repertoire of the sample from the experiment, the repertoire can be compared with the reference repertoire or control group repertoire to make diagnosis, prognosis, drug effectiveness analysis or other required analysis. The reference repertoire or control group repertoire can be obtained by the method of the present invention, and will be selected to be relevant to the sample of interest. The test repertoire result can be compared with a single reference / control group repertoire result to obtain information about the immune ability and / or history of the individual from which the sample is obtained. Alternatively, the obtained repertoire result can be compared with two or more different reference / control group repertoire results to obtain more in-depth information about the characteristics of the test sample. For example, the obtained repertoire result can be compared with the positive and negative reference repertoire results to obtain confirmation information about whether the phenotype is of interest or not. In another example, two "test" repertoires can also be compared with each other. In some cases, the test repertoire is compared with a reference sample, and then the result is compared with the result obtained by the comparison between the second test repertoire and the same reference sample.

[0093] Determination or analysis of the difference (i.e., the difference between two repertoires) can be performed using any conventional method, a variety of which are known to those skilled in the art, such as by comparing digital images of the repertoire outputs, by comparing databases of usage data, etc.

[0094] A statistical analysis step may then be performed to obtain a weighted distribution of sequence prevalence, such as V, D, J, C, VJ, VDJ, VJC, VDJC, antibody heavy chain, antibody light chain, CDR3, or T cell receptor usage, mutation analysis, etc. For example, a nearest reduced centroid analysis as described in Tibshirani et al., (2002) PNAS 99: 6567-6572 may be applied to calculate the centroid for each class, and then the average squared distance between a given repertoire and each centroid is calculated, normalized by the within-class standard deviation.

[0095] Statistical analysis can include the use of statistical metrics (e.g., entropy metrics, ecological metrics, changes in abundance metrics, species abundance metrics, or measures of species heterogeneity) to characterize the diversity of the immune receptor set. Methods for characterizing ecological species diversity can also be used in the present invention. See, for example, Peet, Annu Rev Ecol. Syst. 5: 285 (1974). Statistical metrics can also be used to characterize changes in abundance or heterogeneity. Examples of methods for characterizing heterogeneity are based on information theory, particularly Shannon-weaver entropy, which summarizes the frequency distribution of a single quantity. See, for example, Peet, Annu Rev Ecol. Syst. 5: 285 (1974).

[0096] The classification can be defined probabilistically, and the cutoff can be empirically derived. In one embodiment of the invention, a probability of about 0.4 can be used to distinguish between individuals exposed and not exposed to the antigen of interest, more generally a probability of about 0.5, and a probability of about 0.6 or higher can be utilized. A "high" probability can be at least about 0.75, at least about 0.7, at least about 0.6, or at least about 0.5. A "low" probability can be no more than about 0.25, no more than 0.3, or no more than 0.4. In many embodiments, the above-mentioned information obtained is used to predict whether a host, experimenter, or patient should be treated with a therapy of interest, and to optimize the dosage therein.

[0097] Diagnosis and Prognosis

[0098] The present invention is used to prevent, treat, detect, diagnose, prognose, or study any condition or symptom of any condition including cancer, inflammatory diseases, autoimmune diseases, allergies, and infections in an organism. The preferred organism is a human subject, but can also be from a non-human subject (e.g., a non-human mammal). Examples of non-human mammals include (but are not limited to) non-human primates (e.g., apes, monkeys, gorillas), rodents (e.g., mice, rats), cows, pigs, sheep, horses, dogs, cats, or rabbits.

[0099] Examples of cancer include prostate, pancreatic, colon, brain, lung, breast, bone and skin cancers. Examples of inflammatory conditions include irritable bowel syndrome, ulcerative colitis, appendicitis, tonsillitis, dermatitis. Examples of atopic conditions include allergies, asthma, etc. Examples of autoimmune diseases include insulin-dependent diabetes mellitus (IDDM), rheumatoid arthritis (RA), multiple sclerosis (MS), systemic lupus erythematosus (SLE), Crohn's disease, Graves' disease, etc. Autoimmune diseases also include Celiac disease and dermatitis herpetiformis. For example, the determination of immune responses to cancer antigens, self-antigens, pathogenic antigens, vaccine antigens and the like is of interest.

[0100] In some cases, nucleic acid (e.g., genomic DNA, mRNA, etc.) is obtained from an organism after the organism has been challenged with an antigen (e.g., vaccination). In other cases, nucleic acid is obtained from an organism before the organism is challenged with an antigen (e.g., vaccination). Comparing the diversity of immune receptors present before and after the challenge can assist in analyzing the response of the organism to the challenge.

[0101] Also provided are methods for optimizing therapy by analyzing the immune repertoire in a sample and, based on this information, selecting appropriate therapies, dosages, treatment modes, etc. that are optimal for stimulating or suppressing a targeted immune response while minimizing undesirable toxicity. Therapy is optimized by selecting a treatment that minimizes undesirable toxicity while providing effective activity. For example, a patient may be assessed for the immune repertoire associated with an autoimmune disease, and a systemic or targeted immunosuppression regimen may be selected based on this information.

[0102] A signature repertoire of a condition can refer to immune repertoire results that indicate the presence of a condition of interest. For example, a history of cancer (or a particular type of allergy) can be reflected by the presence of immune receptor sequences that bind to one or more cancer antigens. The presence of an autoimmune disease can be reflected by the presence of immune receptor sequences that bind to autoantigens. A signature can be obtained from all or a portion of a data set, and typically a signature will include at least about 100 different immune receptor sequences, at least about 10 2 Different immune receptor sequences, at least about 10 3 Different immune receptor sequences, at least about 10 4 Different immune receptor sequences, at least about 10 5 Different immune receptor sequences, or more repertoire information. In the case of using a subset of the data set, the subset can include, for example, α-TCR, β-TCR, MHC, IgH, IgL, or a combination thereof.

[0103] The classification methods described herein are of interest as a means to detect the earliest changes along a disease pathway (eg, oncogenic pathways, inflammatory pathways, etc.), and / or to monitor the efficacy of various therapeutic and preventive interventions.

[0104] The methods disclosed herein can also be used to analyze the effects of reagents on cells of the immune system. For example, changes in the immune repertoire can be analyzed after exposure to one or more test compounds to analyze the effects of the test compounds on individuals. Such analysis can be used for a variety of purposes, such as in the development of immunosuppressive or immunoenhancing treatments.

[0105] The agents analyzed for potential therapeutic value can be any compound, small molecule, protein, lipid, carbohydrate, nucleic acid or other agent suitable for therapeutic use. Preferably, the testing is performed in vivo, for example using an animal model, to determine the effect on the immune repertoire.

[0106] Agents of interest for screening include known and unknown compounds covering many chemical classes, primarily organic molecules which may include organometallic molecules, genetic sequences, etc. An important aspect of the present invention is the evaluation of drug candidates, including toxicity assays;

[0107] In addition to complex biological agents, candidate agents include organic molecules containing functional groups necessary for structural interactions, especially hydrogen bonding, and generally include at least amine, carbonyl, hydroxyl or carboxyl groups, often at least two of the chemical functional groups. Candidate agents may contain cyclic carbon or heterocyclic structures and / or aromatic or polyaromatic structures substituted with one or more of the above functional groups. Candidate agents can also be found in biomolecules, including peptides, polynucleotides, carbohydrates, fatty acids, steroids, purines, pyrimidines, derivatives, structural analogs or combinations thereof. In some cases, the test compound may have a known function (e.g., reducing oxidative stress), but may also act through unknown mechanisms or on unknown targets. Included are pharmacologically active drugs, gene active molecules, etc. Compounds of interest include chemotherapeutic agents, hormones or hormone antagonists, etc. Exemplary agents suitable for use in the present invention are those described in the following references, "The Pharmacological Basis of Therapeutics", Goodman and Gilman, McGraw-Hill, New York, New York, (1996), 9th edition, in the sections: Water, Salts and Ions; Drugs Affecting Renal Function and Electrolyte Metabolism; Drugs Affecting Gastrointestinal Function; Chemotherapy of Microbial Diseases; Chemotherapy of Neoplastic Diseases; Drugs Acting on Hematopoietic Organs; Hormones and Hormone Antagonists; Vitamins, Skin Diseases; and Toxicology, all incorporated herein by reference. In addition, toxins, biological and chemical warfare agents are included, for example, see Somani, SM (ed.), "Chemical Warfare Agents," Academic Press, New York, 1992).

[0108] Test compounds include all the above-mentioned classes of molecules, and may further include samples with unknown contents. Of interest are complex mixtures of naturally occurring compounds from natural sources such as plants, fungi, bacteria, protists or animals. Although many samples will include compounds in solution, solid samples that can be dissolved in a suitable solvent may also be detected. Samples of interest include environmental samples such as groundwater, seawater, mining waste, biological samples such as lysates prepared from crops, tissue samples, etc.; manufacturing samples, such as time courses during drug preparation; and compound libraries prepared for analysis; etc. (e.g., compounds evaluated for potential therapeutic value, i.e., candidate drugs).

[0109] The sample or compound may also include additional components, such as components that affect ionic strength, pH, total protein concentration, etc. In addition, the sample may be processed to achieve at least partial fractionation or concentration. If care is taken to reduce the degradation of the compound, such as in a nitrogen atmosphere, freezing, or a combination thereof, the biological sample may be stored. The volume of the sample used is sufficient to allow measurable detection, such as a biological sample from about 0.1 ml to 1 ml may be sufficient.

[0110] Compounds comprising candidate agents are obtained from a variety of sources including synthetic or natural compound libraries. For example, many methods can be used for random and directed synthesis of a variety of organic compounds including biomolecules, including the expression of randomized oligonucleotides and oligopeptides. Alternatively, libraries of natural compounds in the form of bacteria, fungi, plants and animal extracts are available or easily produced. In addition, natural or synthetically produced libraries and compounds are easily modified by traditional chemical, physical and biochemical methods, and can be used to produce combinatorial libraries. Known pharmacological agents can undergo directed or random chemical modifications, such as acylation, alkylation, esterification, amidation, etc., to produce structural analogs.

[0111] Some formulations do not include additional components that may have a significant effect on the overall formulation, such as preservatives. Thus, such formulations consist essentially of the biologically active compound and a physiologically acceptable carrier (e.g., water, ethanol, DMSO, etc.). However, if the compound is a solvent-free liquid, the formulation may consist essentially of the compound itself.

[0112] Expression library database and data analysis

[0113] Also provided is a database of immune repertoires or a database of immune receptor sets. These databases may generally include repertoire results derived from various individual conditions, such as individuals exposed to vaccines, cancer, individuals with autoimmune diseases of interest, individuals infected with pathogens, and the like. Such databases may also include sequences of immune receptors from synthetic libraries or other artificial methods. The repertoire results and their databases may be provided in various media to facilitate their use. "Medium" refers to a product containing information of the expression repertoire of the present invention. The database of the present invention may be recorded in a computer-readable medium, such as any medium that can be read and directly accessed by a computer. Such media include, but are not limited to: magnetic storage media, such as floppy disks, hard disk storage media, and magnetic tapes; optical storage media, such as optical disks; electrical storage media, such as RAM and ROM; and mixtures of these categories, such as magnetic / optical storage media. A person skilled in the art can readily understand how any currently known computer-readable medium can be used to create a record of the information of the current database. "Recorded" refers to the process of storing information on a computer-readable medium using any such method as known in the art. Any convenient data storage structure may be selected depending on the manner in which the stored information is accessed. Various data processor programs and formats are available for storing, for example, word processing text files, database formats, and the like.

[0114] As used herein, "computer-based system" refers to hardware devices, software devices, and data storage devices used to analyze the information of the present invention. The minimum hardware of the computer-based system of the present invention includes a central processing unit (CPU), an input device, an output device, and a data storage device. A skilled person can easily understand that any of the currently available computer-based systems is suitable for use in the present invention. The data storage device can include any article of manufacture that includes a record of the above-mentioned existence information, or a memory access device that can access such an article of manufacture.

[0115] A variety of structural formats of input and output devices can be used to input and output information in the computer-based system of the present invention.The above statements provide one skilled in the art with a level of similarity and determine the degree of similarity contained in the test expression set library.

[0116] Data analysis can also take a scaling approach. For example, the Pearson correlation of the repertoire results can provide a quantitative score reflecting the signature of each sample. The higher the correlation value, the more similar the sample is to the reference repertoire. A negative correlation value indicates the opposite behavior. The threshold for classification can be moved up or down from zero depending on the clinical goal.

[0117] To provide a significance ranking, the false discovery rate (FDR) can be determined.

[0118] First, a null distribution set of different values ​​is generated. In one embodiment, the values ​​of the observed repertoire are arranged to generate a sequence of distributions of correlation coefficients obtained from chance, thereby generating a null distribution set of appropriate correlation coefficients (see Tusher et al. (2001) PNAS 98, 51 18-21, which is incorporated herein by reference). The null distribution set is obtained by the following steps: the value of each repertoire is arranged for all available repertoires; the paired correlation coefficients are calculated for all repertoire results; the probability density function of the correlation coefficient is calculated for the arrangement; and the step is repeated N times, where N is a large number, typically 300. Using N distributions, we calculate appropriate measurements (means, medians, etc.) of the counts of correlation coefficient values, and their values ​​exceed the (similarity) values ​​obtained from the distribution of similarity values ​​observed experimentally at a given significance level.

[0119] The FDR is the ratio of the expected number of falsely significant correlations (estimated from correlations greater than the selected Pearson correlation in the set of randomized data) to the number of correlations greater than the selected Pearson correlation in the empirical data (significant correlations). This cutoff correlation value can be applied to correlations between experimental repertoires.

[0120] Using the above distribution, a confidence level is selected for significance. This is used to determine the lowest value of the correlation coefficient that exceeds the result that would be obtained by chance. Using this method, a threshold for positive correlation, negative correlation, or both can be obtained. Using this threshold, the user can filter the observations of the pairwise correlation coefficients and eliminate those that do not exceed the threshold. In addition, an estimate of the false positive rate can be obtained for a given threshold. For each individual "random correlation" distribution, it can be found how many observations fall outside the threshold range. This process provides a sequence of counts. The mean and standard deviation of the sequence provide the average number of potential false positives and their standard deviation.

[0121] The data can be subjected to unsupervised hierarchical clustering to reveal relationships between repertoires. For example, hierarchical clustering can be performed where Pearson correlation is used as the clustering metric. Clustering of correlation matrices such as those using multidimensional scaling enhances visualization of homology similarities and dissimilarities. Multidimensional scaling (MDS) can be applied in one, two, or three dimensions.

[0122] This analysis can be realized with hardware or software, or a combination of the two. In one embodiment of the invention, a machine-readable storage medium is provided, the medium includes data storage materials encoded with machine-readable data, wherein, when using a machine programmed with instructions for using the data, the machine-readable data can display any data set and data comparison of the present invention. Such data can be used for a variety of purposes, such as drug development, analysis of the interaction between cellular components, and the like. In some embodiments, the present invention is implemented in a computer program executed on a programmable computer, and the programmable computer includes a processor, a data storage system (including volatile and non-volatile memory and / or storage element), at least one input device, and at least one output device. Program code is applied to input data to perform the above functions and generate output information. Output information is applied to one or more output devices in a known manner. The computer can be, for example, a personal computer, a microcomputer, or a workstation of conventional design.

[0123] Each program can be implemented in a high-level procedural or object-oriented programming language to communicate with a computer system. However, if necessary, the program can be implemented in assembly or machine language. In any case, the language can be a compiled language or an interpreted language. Each such computer program can be stored on a storage medium or device (e.g., ROM or floppy disk) readable by a general or special programmable computer, and is used to configure and operate the computer when the storage medium or device is read by the computer to execute the program described herein. The system can also be considered to be implemented as a computer-readable storage medium configured with a computer program, wherein the storage medium so configured causes the computer to operate in a specific and predetermined manner to perform the functions described herein. Input and output devices of various structural formats can be used to input and output information in the computer-based system of the present invention. A format for outputting a test data set with different degrees of similarity to a trustworthy group library. The above statement provides a level of similarity to those skilled in the art, and determines the degree of similarity contained in the test group library.

[0124] Storing and transmitting data

[0125] Also provided herein is a method for storing and / or sending sequences and other data collected by the methods disclosed herein by a computer. Any computer or computer attachment including but not limited to software and storage devices can be used to implement the present invention. Sequences or other data (for example, analysis results of immune repertoires) can be directly or indirectly input into a computer by a user. In addition, any device that can be used for sequencing DNA or analyzing DNA or analyzing immune repertoire data can also be connected to a computer so that data is transferred to a computer and / or a storage device compatible with a computer. Data can be stored on a computer or an appropriate storage device (for example, an optical disk). Data can also be transmitted from a computer to another computer or data collection point by methods known in the art (for example, the Internet, ground mail, airmail). Therefore, the data collected by the methods described herein can be collected and sent to any other geographical location at any point or geographical location.

[0126] Reagents and Kits

[0127] Also provided are reagents and kits for implementing one or more of the above methods. Subject reagents and kits can vary greatly. Reagents of interest include reagents designed specifically for producing the above-mentioned immune repertoire analysis. For example, reagents may include primer sets for cDNA synthesis, PCR amplification and / or for high-throughput sequencing of a class or subtype of immune receptors. Gene-specific primers and methods using the gene-specific primers are described in U.S. Patent No. 5,994,076, the disclosure of which is incorporated herein by reference. Gene-specific primer sets may include only primers for immune receptors, or they may include primers for additional genes (e.g., housekeeping genes, controls, etc.).

[0128] The kit of the subject invention may include the above-mentioned gene-specific primer set. The kit may also include a software package for statistical analysis, and may include a reference database for calculating the probability of matching between two groups of libraries. The kit may include reagents used in various methods, such as primers for generating target nucleic acids, dNTPs and / or rNTPs, which may be premixed or separate, one or more uniquely labeled dNTPs and / or rNTPs, such as biotinylated or Cy3 or Cy5 labeled dNTPs; gold or silver particles with different scattering spectra; or other reagents labeled after synthesis, such as chemically active derivatives of fluorescent dyes; enzymes, such as reverse transcriptase, DNA polymerase, RNA polymerase, and the like; various buffer media, such as hybridization and washing buffers; prefabricated probe arrays, labeled probe purification reagents and components, such as spin columns, etc.; signal generation and detection reagents, such as streptomycin-alkaline phosphatase conjugates, chemiluminescent or chemiluminescent substrates, and the like.

[0129] In addition to the above-mentioned components, the kit of the present invention will further include instructions for implementing the inventive method. These instructions can be present in the kit of the present invention in various forms, wherein one or more can be present in the kit. Wherein a form in which these instructions can exist is as information printed on a suitable medium or substrate, for example, one or more pages of paper on which information is printed, in the packaging of the kit, in a packaging insert, etc. And another tool is a computer-readable medium on which information has been recorded, for example, a floppy disk, a CD, etc. Another tool that can also exist is a website address, which can be used to access information at a removed site through the Internet. Any convenient tool can be present in the kit.

[0130] The above-mentioned analysis method can be embodied as a program of instructions executed by a computer to perform different aspects of the present invention. Any of the above-mentioned techniques can be performed by a device loaded into a software component of a computer or other information device or digital device. When so enabled, a computer, a device or equipment can then perform the above-mentioned techniques to assist in the analysis of the value set associated with a plurality of genes in the above-mentioned manner, or for comparing such correlation values. The software component can be loaded from a fixed medium or accessed by a communication medium such as the Internet or other types of computer networks. The above-mentioned features are embodied in that one or more computer programs can be performed by one or more computers running such a program.

[0131] The software product (or component) may be tangibly embodied in a machine-readable medium and may include instructions operable to cause one or more data processing devices to perform the following operations, including: a) clustering sequence data from a plurality of immune receptors or fragments thereof; and b) providing a statistical analysis output of the sequence data. Also provided herein is a software product (or component) tangibly embodied in a machine-readable medium and may include instructions operable to cause one or more data processing devices to perform the following operations, including: storing more than 10 2 , 10 3 , 10 4 , 10 5 , 10 6 , 10 7 , 10 8 , 10 9 , 10 10 , 10 11 , or 10 12 Immune receptors or more than 10 2 , 10 3 , 10 4 , 10 5 , 10 6 , 10 7 , 10 8 , 10 9 , 1010 , 10 11 , or 10 12 Sequence data of sequence reads.

[0132] In certain embodiments, software product (or component) comprises for distributing sequence data to V, D, J, C, VJ, VDJ, VJC, VDJC, or VJ / VDJ pedigree use category or for displaying the instruction of analysis output in multidimensional figure.In some cases, multidimensional figure enumerates all possible values ​​for one of following items: V, D, J or C (for example, three-dimensional figure, it comprises an axis enumerating all possible V values, enumerates the second axis of all possible D values, and enumerates the third axis of all possible J values).In some cases, software product (or component) comprises for identifying one or more unique patterns from the single sample relevant to condition.Software product (or component) can also comprise for normalizing instruction for amplification preference.In certain embodiments, software product (or component) can comprise for using control data to normalize for sequencing error or for using clustering process to reduce sequencing error instruction.Software product (or component) can also comprise for using two independent primer sets or PCR screeners to reduce sequencing error instruction.

[0133] Incorporation by reference

[0134] Other documents such as the contents of patents, patent applications, patent publications, journals, books, newspapers, websites, etc. have been referenced and cited throughout this disclosure. All of these documents are hereby incorporated by reference in their entirety for all purposes.

[0135] Equivalent

[0136] The present invention may be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the aforementioned embodiments are illustrative in all aspects rather than limiting the present invention described herein. Therefore, the scope of the present invention is indicated by the appended claims rather than by the aforementioned description, and therefore all changes within the meaning and equivalent range of the claims are intended to be included therein. Sequence Listing <110> Lineage Biosciences <120> Methods for sequencing immune repertoires <130> 097155-0955694-000210US <140> US 14 / 776,141 <141> 2015-09-14 <150> PCT / US2014 / 029241 <151> 2014-03-14 <150> US 61 / 806,143 <151> 2013-03-28 <150> US 61 / 801,785 <151> 2013-03-15 <160> twenty four <170> Patent version 3.5 <210> 1 <211> 16 <212> DNA <213> Artificial sequence <220> <223> Synthetic oligonucleotide tags <220> <221> misc_features <222> (1)..(9) <223> n is a, c, g, t or u <220> <221> misc_features <222> (14)..(16) <223> Probably ribonucleotide <400> 1 nnnnnnnnna cgcggg 16 <210> 2 <211> 15 <212> DNA <213> Artificial sequence <220> <223> Synthetic oligonucleotide tags <220> <221> misc_features <222> (7)..(15) <223> n is a, c, g, or t <400> 2 cccgcgnnnn nnnnn 15 <210> 3 <211> 170 <212> DNA <213> Artificial sequence <220> <223> Synthetic amplification of immunoglobulin sequences by PCR products <400> 3 gagccccagc cctgggattc ccaggtgttt ctgcttgctg atcaggactg cacacagaga 60 actcaccatg gagtttgggc tgcgctgggt tttccttgtt actattttaa aaggtgtcca 120 gtgtgagatg cactaggtgg agtctggggg aggcttggtc cagcctgggg 170 <210> 4 <211> 169 <212> DNA <213> Artificial sequence <220> <223> Synthetic amplification of immunoglobulin sequences by PCR products <400> 4 ggccccagcc ctgggattcc caggtgtttc tgcttgctga tcaggactgc acacagagaa 60 ctcaccatgg agtttgggct gagctgggtt ttctttgtta ctattttaaa aggtgtccag 120 tgtgagatgc acttggtgga gtctggagga ggcttgatcc agcctgggg 169 <210> 5 <211> 170 <212> DNA <213> Artificial sequence <220> <223> Synthetic amplification of immunoglobulin sequences by PCR products <400> 5 gagccccagc cctgggattc ccaggtgttt ctgcttgctg atcaggactg cacacagaga 60 cctcaccatg gagtttgggc tgagctgggt tttccttgtt actattttaa aaggtgtcca 120 gtgtgagatg catttggtgg agtctggagg aggcttgatc cagcctgggg 170 <210> 6 <211> 171 <212> DNA <213> Artificial sequence <220> <223> Synthetic amplification of immunoglobulin sequences by PCR products <400> 6 ggagccccag ccctgggatt cccaggtgtt tctgcttgct gatcaggact gcacacagag 60 aactcaccat ggagtttggg ctgagctggg ttttccttgt tactatttta aaagttgtcc 120 agtgtgagat gcacttggtg gagtctggag gaggcttgat ccagcctggg g 171 <210> 7 <211> 172 <212> DNA <213> Artificial sequence <220> <223> Synthetic amplification of immunoglobulin sequences by PCR products <400> 7 aggagcccca gccctgggat tcccaggtgt ttctgcttgc tgatcaggac tgcacacaga 60 gaactcacca tggagtttgg gctgagctgg gttttccttg ttactatttt aaaagttgtc 120 cagtgtgaga tgcaactggt ggagtctgga ggaggcttga tccagcctgg gg 172 <210> 8 <211> 103 <212> DNA <213> Artificial sequence <220> <223> Synthetic amplification of immunoglobulin sequences by PCR products <400> 8 atggagtttg ggctgagctg ggttttcctt gttgctattt taaaaggtgt ccagtgtgag 60 gtgcagctgg tggagtctgg gggaggtgtg gtacggcctg ggg 103 <210> 9 <211> 170 <212> DNA <213> Artificial sequence <220> <223> PCR products of immunoglobulin sequences <400> 9 gagcccaagc cctgggattc ccgggtgttt ctgcttgctg atcaggactg cacacagaga 60 actcaccatg gagtttgggc tgagctggct tttctttgtt cctattttaa ccgtcgtctg 120 gtgtgagatg cgtttggtgg agtctggggg aggtgtggta cggcctgggg 170 <210> 10 <211> 171 <212> DNA <213> Artificial sequence <220> <223> Synthetic amplification of immunoglobulin sequences by PCR products <400> 10 ggagccccag ccctgggatt cccaggtgtt tctgcttgct gatcaggact gcacacagag 60 aactcaccat ggagtttggg ctgagctggg ttttccttgt tactatttta aaaggtgtcc 120 agtgtgagat gcacttggtg gagtctgggg gaggtgtggt acggcctggg g 171 <210> 11 <211> 172 <212> DNA <213> Artificial sequence <220> <223> Synthetic amplification of immunoglobulin sequences by PCR products <400> 11 gggagcccca gccctgggat tcccaggtgt ttctgcttgc tgatcaggac tgcacacaga 60 gaactcacca tggagtttgg gctgagctgg gttttccttg ttactatttt aaaaggtgtc 120 cagtgtgaga tgcatctggt ggagtctggg ggaggtgtgg tacggcctgg gg 172 <210> 12 <211> 171 <212> DNA <213> Artificial sequence <220> <223> Synthetic amplification of immunoglobulin sequences by PCR products <400> 12 ggagccccag ccctgggatt cccaggtgtt tctgcttgct gatcaggact gcacacagag 60 aactcaccat ggagtttggg ctgagctggg ttttccttgt tactatttta aaaggtgtcc 120 agtgtgagat gcatttggtg gagtctgggg gaggtgtggt acggcctggg g 171 <210> 13 <211> 170 <212> DNA <213> Artificial sequence <220> <223> Synthetic amplification of immunoglobulin sequences by PCR products <400> 13 gagccccagc cctgggattc ccaggtgttt ctgcttgctg atcaggactg cacacagaga 60 actcaccatg gagtttgggc tgagctgggt tttccttgtt actattttaa aaggtgtcca 120 gtgtgagatg catttggtgg agtctggggg aggtgtggta cggcctgggg 170 <210> 14 <211> 126 <212> DNA <213> Artificial sequence <220> <223> Synthetic amplification of immunoglobulin sequences by PCR products <400> 14 atgaaacacc tgtggttctt cctcctcctg gtggcagctc ccagatgggt cctgtcccag 60 gtgcagctac agcagtgggg cgcaggactg ttgaagcctt cggagaccct gtccctcacc 120 tgcgct 126 <210> 15 <211> 162 <212> DNA <213> Artificial sequence <220> <223> Synthetic amplification of immunoglobulin sequences by PCR products <400> 15 ggctttctga gagtcatgga cctcctgcac aagaacatga gacacctgtg gctcttcctc 60 ctcctggtgg cagctcccag ctgggtcctg tcccaggtgc ggttacatct gtggggcgcg 120 gtacagctga agccctcgga gaccctgtcc ctcacctgcg ct 162 <210> 16 <211> 162 <212> DNA <213> Artificial sequence <220> <223> Synthetic amplification of immunoglobulin sequences by PCR products <400> 16 ggctttctga gagtcatgga cctcctgcac aagaacatga gacacctgtg gctcttcctc 60 ctcctggtgg cagctcccag ctgggtcctg tcccaggtgc agttccatcc gtggggcgca 120 gtacagctga agccctcgga gaccctgtcc ctcacctgcg ct 162 <210> 17 <211> 164 <212> DNA <213> Artificial sequence <220> <223> Synthetic amplification of immunoglobulin sequences by PCR products <400> 17 agtgctttct gagagtcatg gacctcctgc acaagaacat gagacacctg tggctcttcc 60 tcctcctggt ggcagctccc agatgggtcc tgtcccaggt gcagttacat cagtggggcg 120 caggacagct gaagccttcg gagaccctgt ccctcacctg cgct 164 <210> 18 <211> 165 <212> DNA <213> Artificial sequence <220> <223> Synthetic amplification of immunoglobulin sequences by PCR products <400> 18 gagtgctttc tgagagtcat ggacctcctg cacaagaaca tgagacacct gtggctcttc 60 ctcctcctgg tggcagctcc cagatgggtc ctgtcccagg tgcagttaca tcagtggggc 120 gcaggacagc tgaagccttc ggagaccctg tccctcacct gcgct 165 <210> 19 <211> 164 <212> DNA <213> Artificial sequence <220> <223> Synthetic amplification of immunoglobulin sequences by PCR products <400> 19 ggtgctttct gagagtcatg gacctcctgc acaagaacat gagacacctg tggctcttcc 60 tcctcctggt ggcagctccc agatgggtcc tgtcccaggt gcagttacat cagtggggcg 120 caggccagct gaagccttcg gagaccctgt ccctcacctg cgct 164 <210> 20 <211> 164 <212> DNA <213> Artificial sequence <220> <223> Synthetic amplification of immunoglobulin sequences by PCR products <400> 20 ggtgctttct gagagtcatg gacctcctgc acaagaacat gagacacctg tggctcttcc 60 tcctcctggt ggcagctccc agatgggtcc tgtcccaggt gcagttacat cagtggggcg 120 caggacagct gaagccttcg gagaccctgt ccctcacctg cgct 164 <210> twenty one <211> 162 <212> DNA <213> Artificial sequence <220> <223> Synthetic amplification of immunoglobulin sequences by PCR products <400> twenty one ggctttctga gagtcatgga cctcctgcac aagaacatga gacacctgtg gctcttcctc 60 ctcctggtgg cagctcccag atgggtcctg tcccaggtgc agttacatca gtggggcgcg 120 ggccagctga agccctcgga gaccctgtcc ctcacctgcg ct 162 <210> twenty two <211> 162 <212> DNA <213> Artificial sequence <220> <223> PCR products of immunoglobulin sequences <400> twenty two ggctttctga gagtcatgga cctcctgcac aagaacatga gacacctgtg gctcttcctc 60 ttcttggtgg cagctcccag atgggtcctg tcccaggtgc agttacatca gtggggcgca 120 ggacagctga agccctcgga gaccctgtcc ctcacctgcg ct 162 <210> twenty three <211> 162 <212> DNA <213> Artificial sequence <220> <223> Synthetic amplification of immunoglobulin sequences by PCR products <400> twenty three ggctttctga gagtcatgga cctcctgcac aagaacatga gacacctgtg gctcttcctc 60 ctcctggtgg cagctcccag atgggtcctg tcccaggtgc agttacatca gtggggcgca 120 ggacagctga ggccctcgga gaccctgtcc ctcacctgcg ct 162 <210> twenty four <211> 161 <212> DNA <213> Artificial sequence <220> <223> Synthetic amplification of immunoglobulin sequences by PCR products <400> twenty four gctttctgag agtcatggac ctcctgcaca agaacatgag acacctgtgg ctcttcctcc 60 tcctggtggc agctcccaga tgggtcctgt cccaggtgca gttacatcag tggggcgcag 120 gacagctgag gccctcggag accctgtccc tcacctgcgc t 161

Claims

1. A method for determining the immune repertoire of a subject, comprising: (a) reverse transcribing mRNA obtained from a biological sample comprising a plurality of cell types of a subject using immunoglobulin chain-specific primers and a reverse transcriptase to generate immunoglobulin chain cDNA comprising a 3' homopolymer tail; (b) adding a random molecular tag and a universal sequence to the 3' end of the immunoglobulin chain cDNA by using a reverse transcriptase and an oligonucleotide to form an extended cDNA, the oligonucleotide comprising a 3' sequence complementary to the homopolymer tail and a 5' flanking sequence comprising: the universal sequence and the random molecular tag, the random molecular tag being an oligomer of at least 9-mers, wherein each extended cDNA comprises a unique random molecular tag; (c) amplifying the extended cDNA by using one or more immunoglobulin chain-specific primers and a universal sequence-specific primer comprising flanking sequences specific to a sequencing platform to produce a plurality of molecularly tagged immunoglobulin chain nucleic acids; (d) sequencing the plurality of molecularly tagged immunoglobulin chain nucleic acids to generate a plurality of sequencing reads; (e) digitally counting the number of unique random molecular tags associated with each immunoglobulin chain nucleic acid sequence, wherein the number of unique random molecular tags associated with each immunoglobulin chain nucleic acid sequence is a measure of the abundance of each immunoglobulin chain nucleic acid species in the immune repertoire, thereby determining the immune repertoire of the subject.

2. The method of claim 1, further comprising a data analysis step after step (d) and before step (e), wherein the data analysis comprises grouping sequencing reads having the same molecular tag and clustering sequences within the same group to form a plurality of clusters. 3 . The method of claim 2 , further comprising establishing a consensus sequence for each of the plurality of clusters to generate a set of consensus sequences.

4. The method of claim 3, wherein the collection of consensus sequences is used to determine the diversity of the immune repertoire. The method of claim 1 , wherein the biological sample is a whole blood sample or a blood component.

6. The method of claim 5, wherein the whole blood is peripheral whole blood.

7. The method of claim 5, wherein the blood component comprises peripheral blood mononuclear cells.

8. The method of claim 5, wherein the whole blood sample is classified into blood components based on extracellular or intracellular markers.

9. The method of claim 1, wherein the immunoglobulin chain is a heavy chain or a light chain.

10. The method of claim 9, wherein the immunoglobulin heavy chain comprises the immunoglobulin VDJ and constant region.

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