PCR preference correction method and quantitative analysis method of immune repertoire

Abstract

The invention discloses a correction method of PCR (Polymerase Chain Reaction) preference, a DNA (Deoxyribose Nucleic Acid) artificially synthesized sequence combination of a TCR-beta immune repertoire, a primer combination for amplifying the TCR-beta immune repertoire, a quantitative analysis method of the TCR-beta immune repertoire of a gDNA sample, a detection kit and application of the detection kit. The PCR preference correction method can effectively correct the preference generated in the PCR amplification process, the DNA artificially synthesized sequence combination can effectively adjust the primer concentration ratio of the multiple PCR primer combination, and the primer combination can efficiently and quantitatively amplify a TCR-beta immune repertoire without mutual interference as much as possible. According to the method, the immune repertoire can be accurately and quantitatively analyzed at the DNA level.

Description

[0001] This application claims the priority of Chinese patent application CN202311838286.6, filed on December 28, 2023. This application cites the full text of the above Chinese patent application. Technical Field

[0002] The present invention belongs to the field of biological detection, and specifically relates to a PCR preference correction method, a DNA artificial synthesis sequence combination of a TCR-β immune repertoire, a primer combination for amplifying the TCR-β immune repertoire, a TCR-β immune repertoire quantitative analysis method of a gDNA sample, a detection kit and its application. Background Art

[0003] T cell receptors (TCR), B cell receptors (BCR) and the diversity of secreted antibodies constitute the core of a complex immune system and play a key role in protecting the body from viral and bacterial invasion and other pathogens. Among them, TCR is a protein on the surface of T cells that is responsible for the specific recognition of antigenic peptides bound to the major histocompatibility complex (MHC). When TCR binds to antigenic peptides and MHC, T lymphocytes are activated through signal transduction and initiate an immune response. In humans, TCR is composed of a heterodimeric αβ chain (about 95%, TRA, TRB) or a γδ chain (about 5%, TRD, TRG). Structurally, each chain can be divided into a constant region and a variable region. [1,2] , CDR1 and CDR2 are relatively conservative and are responsible for recognizing MHC; CDR3 is the TCR region that directly contacts the antigen. CDR3 is encoded by part of V, all D and J, and the junction between VD and DJ, so CDR3 has the highest degree of variation. Since the V (65 to 100 types), D (2 types), and J (13 types) gene segments themselves are diverse, in addition, during the rearrangement process, non-template nucleotides are often randomly inserted or deleted in the junction between VD and DJ, which further increases the diversity of the TCR CDR3 region, theoretically forming 2×10 18 TCR-αβ [3] Because lymphocytes are constantly generated, die, and proliferate upon stimulation, the TCR repertoire is dynamic and reflects the individual's immune potential and history, and it is important to develop precise methods to study the complete individual immune repertoire.

[0004] A large number of TCR immune repertoire sequencing and analysis methods have been developed. According to the research materials, they can be divided into DNA-based (gDNA) or RNA-based methods. The former can be divided into multiPCR using V and J primer sets or designed probe hybridization capture methods, and the latter can be divided into multiplex PCR or RACE-PCR methods (UMI can be optionally combined to limit PCR amplification bias and sequencing errors). Among them, the multiplex PCR method is compatible with both gDNA and RNA materials. DNA has higher stability, and the TCR DNA template of a single cell is single, which is convenient for quantification of a single TCR clone. Due to PCR preference, there is currently no mature quantitative method; at the RNA level, each cell may have multiple copies of TCR or BCR transcripts, so using RNA as a template will be more sensitive for identifying rarely expressed receptors and more complete for analyzing specific receptor variants, but quantification of a single TCR clone is extremely challenging. [4] . The target region capture method requires fewer PCR processes and has less PCR preference, but the TCR region itself is highly complex and variable, and it is difficult to design primers for hybridization capture. The RACE PCR method can usually retain the complete TCRVDJ region and avoid amplification preference. Since its method uses RNA as the starting material, it has relatively high operational requirements compared to other technologies, and the entire process is complicated, and repeatability may be affected.

[0005] In recent years, cell and gene therapy technologies have been widely used in the fields of genetic diseases, immune system diseases, tumor treatment, neurodegenerative diseases, etc. Among them, tumor-infiltrating lymphocytes (TILs) are an important cell therapy method. TILs are lymphocytes separated from tumor tissues. This lymphocyte population has the ability to infiltrate tumor tissues and specifically identify tumor cells. Usually, TIL cell therapy extracts lymphocytes from the patient's cancerous tissue, amplifies them in vitro, and then returns them to the patient. Since this process does not involve genetic modification, there is no difference between the gene sequence and protein expression of the amplified cells and the cells in the patient's body. After being injected into the patient's body, PCR and flow cytometry methods are almost completely unable to distinguish TIL from native cells, and it is even more impossible to detect the concentration, amplification and distribution of TIL injected into the body. Although there is currently no PK detection method for TIL, changes in the T cell receptor repertoire (TCR repertoire) can become a TIL detection method similar to PK, and it is also the only way to detect TIL today. However, the currently developed quantitative analysis methods for TCR immune repertoire sequencing are mainly for quantitative analysis of RNA. Due to the difference in gene expression, the RNA sequencing results cannot be directly associated with the number of cells. Each cell has only two copies of the TCR genome, so the gDNA method is a more appropriate choice for PK analysis of TILs.

[0006] Currently, there are patents in the public literature regarding primer compositions for amplifying TCR-β (patent application publication numbers CN103205420A, CN108602874A, etc.), which propose primer combinations that can amplify TCR-β CDR3 coding sequences. However, with the sequencing supplement of TCR sequences, primers need to be designed for new TCR types, and these patents cannot quantify different types of TCR-β immune repertoires. In addition, there are related products for detecting quantitative analysis of TCR immune repertoires. The patent (patent application publication number CN113122618A) introduces a molecular tag sequence containing random bases to eliminate the problem of uneven PCR amplification and achieve quantification of TCR clone clusters in DNA samples. However, the molecular tag sequence has a low binding efficiency and is mainly used for RNA quantitative analysis. Also due to the problem of binding efficiency, the use of the molecular tag sequence method to correct PCR bias will lead to the loss of rare clonal types. [5] .

[0007] In summary, the quantitative analysis of the immune repertoire, including TCR-β, has important research significance, and how to better quantify the immune repertoire still needs to be improved. Summary of the invention

[0008] In order to solve the technical problems of PCR bias in the quantitative analysis of T cell receptor β chain immune repertoire gDNA and the lack of a relatively accurate TCR-β immune repertoire gDNA quantitative analysis method, the present invention provides a PCR bias correction method, a DNA artificial synthesis sequence combination of TCR-β immune repertoire, a set of primer combinations for amplifying TCR-β immune repertoire, a TCR-β immune repertoire quantitative analysis method of a gDNA sample, a detection kit and its application. The PCR bias correction method can effectively correct the bias generated during PCR amplification, the DNA artificial synthesis sequence combination can effectively adjust the primer concentration ratio of a multiple PCR primer combination, the primer combination can amplify the TCR-β immune repertoire efficiently, quantitatively and without mutual interference as much as possible, and the method can quantitatively analyze the immune repertoire (such as TCR-β) relatively accurately at the DNA level.

[0009] In order to solve the above technical problems, the present invention provides a technical solution: a method for correcting the PCR bias of an immune repertoire, wherein the PCR bias correction algorithm is used to correct the PCR reaction bias of each unique CDR3 sequence number in an unknown sample (a unique CDR3 refers to a sequence in which the amino acid sequence of the CDR3 region of these sequences is consistent, and the corresponding V gene and J gene are also consistent) according to the corresponding VJ combination, and the correction method comprises the following steps: 1) analyzing the sequence number of each unique CDR3 (the unique CDR3 is recorded as CDR3i) in an unknown sample containing cell genomic DNA and recording it as N i,k (The number of sequences without bias correction is generally the direct data after sequencing, or the number of sequences after only removing low-quality data after sequencing, such as the number of sequences after removing primer dimers and polymers); 2) Obtain the V gene and J gene corresponding to each CDR3 i; 3) According to the baseline bias correction coefficient b of each VJ combination k The number of sequences for each CDR3 i was corrected according to the following formula:

[0010]

[0011] i, k, c are all integers greater than or equal to 1, i represents the corresponding CDR3 i, Correction N i,k represents the number of corrected sequences of the CDR3i, k represents the VJ combination corresponding to the CDR3i (also known as VJ combination k), b k represents the baseline bias correction coefficient corresponding to the VJ combination k, c represents the number of cycles of multiple PCR (multiPCR), b k c-1 It represents the bias correction coefficient corresponding to VJ combination k in round c of multiple PCR cycle;

[0012] The b k The results are obtained by the following steps: 1) DNA is extracted from all M training samples and c low 1) a first multiplex PCR amplification with low cycle number; 2) c low After rounds of multiplex PCR amplification, all products were divided into two parts, one of which was recorded as a low-cycle sample. The multiplex PCR amplification products of the low-cycle sample were subjected to second-generation sequencing to build a library, and the concentration after library construction was recorded as Con low The other product was subjected to multiple PCR amplification and recorded as the high-cycle sample. The total number of cycles of the high-cycle sample before and after the two amplifications was recorded as c high The multiplex PCR amplification products of the high cycle samples were subjected to second generation sequencing to build a library, and the concentration after library construction was recorded as Con high; 3) Sequencing high and low cycle samples, obtaining at least 6 million sequences for each sample; 4) Sampling the sequencing results of each high cycle sample and low cycle sample respectively, so that the proportion of the sampled data is consistent with Con high / Con low 5) Perform bioinformatics analysis on the sequencing results and obtain the N of the two amplified products i,k ; 6) Obtain the baseline preference correction coefficient b for each VJ combination k according to the following formula: k :

[0013]

[0014] m is an integer greater than 1 and less than M, representing one of the M training samples (including the training samples of cell genomic DNA), b m,k represents the preference correction coefficient of VJ combination k in sample m, b m,k Obtained by the following formula:

[0015]

[0016] B m,k c high -c low The total preference value of the round robin is obtained by the following formula:

[0017]

[0018] represents the number of sequences of all CDR3i corresponding to VJ combination k in sample m in low-cycle samples, represents the number of sequences of all CDR3 i corresponding to VJ combination k in sample m in high circulation samples, B m,k By pairing the vector and A linear fit with an intercept of zero is performed to obtain B m,k is the correlation coefficient of the fitting function of VJ combination k in sample m.

[0019] In the present invention, except Correction N i，k Except for the number of sequences that have been corrected for bias, all other sequence numbers are the number of sequences obtained by second-generation sequencing without bias correction (which may be processed by removing low-quality sequences, such as the number of sequences after removing primer dimers and polymers).

[0020] The correction method provided by the present invention uses the baseline preference correction coefficient b of each VJ combination k obtained from M training samples. k, the number of second-generation sequencing sequences of CDR3 i in the immune group library constructed by PCR can be corrected, that is, the same PCR reaction bias correction is performed on unknown samples. The correction method described in the present invention has a wide range of applicability, is not limited to a specific PCR primer, reaction system and reaction process, can correct the bias brought by the entire PCR reaction, and is also widely applicable to all sequence number databases obtained by second-generation sequencing.

[0021] In the present invention, CDR refers to the complementarity determining regions of an antibody or TCR.

[0022] In the present invention, the second generation sequencing refers to a high-throughput sequencing method that can rapidly sequence the base pairs of DNA or RNA samples, preferably using an Illumina sequencing instrument.

[0023] In the present invention, the immune repertoire refers to the sum of all functionally diverse B lymphocytes and T lymphocytes in the circulatory system of an individual at any specific time point, that is, the sum of all rearranged TCR and BCR encoding genes (clones) of the individual, including TCR-α, TCR-β, TCR-δ, TCR-γ, IGH and IGL.

[0024] Optionally, the sampling is to down sample the sequencing sequence of the sample using seqtk (v1, 4) to make the sequencing amount of the samples comparable.

[0025] Preferably, M is a positive integer, for example, a positive integer greater than 2, greater than 3, greater than 4, greater than 5, greater than 6, greater than 7, greater than 8, greater than 9 or greater than 10. When M is larger, the obtained b k When M is small, a higher sequencing depth can be used to compensate for it and obtain more representative b k value.

[0026] Preferably, the linear fitting is performed using least squares approximation.

[0027] Preferably, the 5' ends of the primers used in the multiplex PCR all contain the same linker. Preferably, the linker of the V region primer contains the sequence shown in SEQ ID NO: 1 (TCGTCGGCAGCGTCAGATGTGTATAAGAGAC AG), and the linker of the J region primer contains the sequence shown in SEQ ID NO: 49 (GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG).

[0028] Preferably, the primer combination used in the multiplex PCR is the primer combination described below in the present invention.

[0029] Preferably, the ratio of primer combination concentration in multiplex PCR is optimized using artificially synthesized TCR-β DNA artificially synthesized sequence. Preferably, the artificially synthesized TCR-β DNA is a combination of artificially synthesized DNA sequences as described below in the present invention.

[0030] Preferably, the immune repertoire is a TCR-β immune repertoire.

[0031] Optionally, the unknown sample and / or the training sample are obtained by conventional methods such as a magnetic bead method or a column method.

[0032] Preferably, the bioinformatics analysis includes: 1) removal of data adapters after sampling; 2) splicing of double-end sequencing data read1 and read2; 3) TCR-βV / J gene annotation and CDR3 region identification; 4) removal of primer dimers and multimers; 5) CDR3 i sequence number statistics.

[0033] Optionally, the adapter removal uses trim_galore software, and the beneficial effect of this step is that some primer dimers or polymers can be removed.

[0034] Optionally, the splicing uses flash software, and the beneficial effect of this step is that the full-length CDR3 region sequence can be obtained.

[0035] Optionally, the TCR-β V / J gene annotation and CDR3 region identification are performed using igblast software.

[0036] Optionally, the CDR3 i sequence number statistics are obtained by the following steps: 1) using the V region and J region genes in the IMGT database as reference sequences for splicing and comparing the sequence lengths of the reference genome, while referring to the length of the primer combination used in the multiplex PCR; 2) eliminating spliced ​​sequences that are too short in length when compared to the reference genome.

[0037] In order to solve the bias of multiple PCR primer combinations due to problems such as primer binding efficiency, the present invention provides a set of artificially synthesized DNA sequence combinations of TCR-β immune repertoires, wherein the artificially synthesized DNA sequence combination comprises multiple nucleotide sequences, each of which comprises the following components: (1) a partial sequence of a V gene, including the entire V region in the CDR3 region and all V gene regions amplified by the multiple primer combination; (2) a complete sequence of a J gene, including the entire J region in the CDR3 region and all J gene regions amplified by the multiple primer combination; (3) a complete sequence of a D gene; and (4) a tag sequence.

[0038] Preferably, the synthetic DNA sequence combination comprises two parts, wherein the 5' end of one part of the synthetic DNA sequence is a partial sequence of the same V gene, and the V gene is denoted as V high frequency The 3' end is the complete sequence of all J genes; the 5' end of the other part of the artificially synthesized DNA sequence is the partial sequence of all V genes, and the 3' end is the complete sequence of the same J gene. This J gene is denoted as J high frequency Theoretically, any V gene and any J gene can be used as V high freq uency and J high frequency Preferably, the V high frequency and J high frequency They are V28 (NCBI Accession number: NC_000007.14: 142720874-142721160) and J2-7 (NCBI Accession number: NC_000007.14: 142797456-142797502), respectively. Preferably, the V28 comprises the nucleotide sequence shown in NCBI Accession number: NC_000007.14: 142720874-142721160, and / or the J2-7 comprises the nucleotide sequence shown in NCBI Accession number: NC_000007.14: 142797456-142797502.

[0039] Preferably, the tag sequence is AAACCTGAGAAACCA (SEQ ID NO: 125), located between the V gene and the D gene.

[0040] More preferably, the artificially synthesized DNA sequence combination comprises the following nucleotide sequence:

[0041]

[0042]

[0043]

[0044] Taking SEQ ID NO:63 as an example, the sequence "CTCCCTGATTCTGGAGTCCGCCAGCACCAACCAGACATCTATGTACCTCTGTGCCAGCAGTTTATG" (SEQ ID NO:124) is a partial sequence of a V gene, the sequence "AAACCTGAGAAACCAT" (SEQ ID NO:125) is a tag sequence, the sequence "GGGACAGGGGGC" is a complete sequence of a D gene, and the sequence "TGAACACTGAAGCTTTCTTTGGACAAGGCACCAGACTCACAGTTGTAG" (SEQ ID NO:126) is a complete sequence of a J gene.

[0045] In order to solve the above technical problems, the present invention provides a set of primer combinations for amplifying the TCR-β immune repertoire, wherein the primer combination comprises the following nucleotide sequences:

[0046]

[0047]

[0048]

[0049] Preferably, the usage of each primer in the primer combination is as follows:

[0050] Primers Number of copies Primers Number of copies TRBV2 2 TRBV15 2 TRBV3-1 2 TRBV16 2 TRBV4-1 2 TRBV17 2 TRBV(4-2,4-3) 2 TRBV18 2 TRBV5-1 2 TRBV19 2 TRBV5-3 2 TRBV20-1 2 TRBV(5-4,5-5,5-6,5-7,5-8) 2 TRBV23-1 2 TRBV6-1 2 TRBV24-1 2 TRBV(6-2,6-3) 2 TRBV25-1 2 TRBV6-4 2 TRBV27 2 TRBV6-5 2 TRBV28 2 TRBV6-6 2 TRBV29-1 2 TRBV6-7 2 TRBV30 2 TRBV6-8 2 TRBV3-1*02 2 TRBV6-9 2 TRBV20-OR9-2 2 TRBV7-1 2 TRBV23 / OR9-2*02-2 2 TRBV7-2 2 TRBJ1-1 6.5 TRBV7-3 2 TRBJ1-2 6.5 TRBV7-4 2 TRBJ1-3 6.5 TRBV7-6 2 TRBJ1-4 6.5 TRBV7-7 2 TRBJ1-6 6.5 TRBV7-8 2 TRBJ2-1 6.5 TRBV7-9 2 TRBJ2-2 6.5 TRBV9 2 TRBJ2-3 6.5 TRBV10-1 2 TRBJ2-4 6.5 TRBV10-2 2 TRBJ2-5 8.8 TRBV10-3 2 TRBJ2-6 6.5 TRBV(11-1,11-3) 2 TRBJ2-7 6.5 TRBV11-2 2 TRBJ1-5*01-1 19.5 TRBV(12-3,12-4,12-5) 3 TRBJ2-2P*01-2 6.5 TRBV13 2 TRBV14 2 .

[0051] In order to solve the above technical problems, the present invention provides a quantitative analysis method of an immune repertoire, which comprises performing second-generation sequencing on an immune repertoire library constructed based on multiplex PCR, and correcting the number of sequencing sequences of the second-generation sequencing using the correction method described in the present invention.

[0052] Preferably, the immune repertoire is a T cell receptor β chain immune repertoire of a DNA sample.

[0053] Preferably, the primers used in the second generation sequencing are the primer combination described in the present invention.

[0054] More preferably, the quantitative analysis method further comprises using a Jurkat cell line to verify the results of the second generation sequencing corrected by the correction method described in the present invention.

[0055] Further preferably, in the verification, the genomic DNA extract of Jurkat cell line is compared with CD3 +The genomic DNA extracts of T cells were mixed at different mass ratios to obtain mixed samples, and each mixed sample was subjected to PCR amplification and second-generation sequencing as defined in the correction method of the present invention, and the Correction N of the Jurkat cell line CDR3 i in each mixed sample was calculated according to the correction method. i,k , and compare and verify the ratio of this value with the mixed concentration.

[0056] To solve the above technical problems, the present invention provides a detection kit, which includes the DNA artificial synthesis sequence combination and / or the primer combination as described in the present invention. Preferably, the detection kit also includes a reagent for second-generation sequencing.

[0057] To solve the above technical problems, the present invention provides an application of the artificially synthesized DNA sequence combination and / or primer combination as described in the present invention in quantitative analysis of T cell receptor β chain immune repertoire. Preferably, the application is for non-diagnostic or therapeutic purposes.

[0058] In the present invention, T cell receptor β chain and TCR-β can be used in combination.

[0059] On the basis of being in accordance with the common sense in the art, the above-mentioned preferred conditions can be arbitrarily combined to obtain the preferred embodiments of the present invention.

[0060] The reagents and raw materials used in the present invention are commercially available.

[0061] The positive and progressive effects of the present invention are:

[0062] The PCR preference correction method provided by the present invention can effectively correct the preference generated during the PCR reaction, making the quantitative analysis of the gDNA immune group library based on multiple PCR library construction and second-generation sequencing more accurate. Further, using a group of DNA artificial synthesis sequence combinations of the TCR-β immune group library designed by the present invention, the primer concentration of PCR can be effectively optimized, and the effectiveness of PCR primers can be verified, and the preference caused by the primer amplification efficiency in PCR can be further corrected, helping to more accurately quantitatively analyze the TCR-β immune group library. The primer combination for amplifying the TCR-β immune group library designed by the present invention can also improve the accuracy of the quantitative analysis of the TCR-β immune group library. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 Optimize the concentration of the pre-product for the primers.

[0064] Figure 2 The concentration of the product after primer optimization.

[0065] Figure 3 This is the distribution diagram of the library product fragments before and after purification in Example 2.

[0066] Figure 4 Result graph for optimization of primer dimers and polymers removal. DETAILED DESCRIPTION

[0067] The present invention is further described below by way of examples, but the present invention is not limited to the scope of the examples. The experimental methods in the following examples without specifying specific conditions are carried out according to conventional methods and conditions, or selected according to the product specifications.

[0068] The multiPCR enzyme reaction system used in the present invention ( Multiplex PCR Kit #206143) was purchased from Qiagen, and the library construction PCR enzyme reaction system (KAPA HiFi HotStart ReadyMix (2x) #KK2601) was purchased from Roche; other instruments, reagents and consumables, unless otherwise specified, are conventional commercial products; the experimental methods involved, unless otherwise specified, are conventional methods.

[0069] Example 1 Design of primers and synthetic DNA sequences

[0070] 1. Design and synthesis of multiplex PCR primers

[0071] In this embodiment, multiple PCR primers were designed and synthesized for all functional genes and ORFs in the V and J regions in the IMGT database. Among them, the forward primers TRBV3-1*02, TRBV20-OR9-2, TRBV23 / OR9-2*02 and the reverse primers TRBJ1-5*01, TRBJ2-2P*01 were designed based on the newly discovered V-3-1*02, V20-OR9-2, V23 / OR9-2*02 and J1-5*01, J2-2P*01 in recent years; in summary, 48 V region forward primers and 14 J region reverse primers are included, as shown in Table 1.

[0072] Table 1 Detailed information of 48 V region forward primers and 14 J region reverse primers

[0073]

[0074]

[0075]

[0076] 2. Design and synthesis of artificial DNA sequences

[0077] In this embodiment, VDJ DNA artificial synthesis sequences were designed and synthesized for some V and J combinations, which were used to adjust the concentration of multiple PCR primers: 1) According to the VJ combination frequency of the healthy cohort in the TCRdb database, the V28 and J2-7 sequences with high frequency combinations were selected and combined with all or part of the remaining V and J gene sequences; 2) A D gene sequence was randomly inserted in the middle; 3) A tag sequence (AAACCTGAGAAACCAT, SEQ ID NO: 124) was inserted between the VD sequences to distinguish the DNA artificial synthesis sequence from the TCR-β sequence in the sample in the subsequent sequencing results. 61 artificially designed and synthesized VDJ DNA sequences are shown in Table 2, and the V / J sequences therein can correspond to all the above primers.

[0078] Table 2 Detailed information of VDJ DNA synthetic sequence

[0079]

[0080]

[0081]

[0082] Example 2 Optimizing the primer concentration ratio of multiple PCR primer combination based on artificially synthesized DNA sequence

[0083] Human peripheral blood was obtained and stored in sterile blood collection tubes containing anticoagulants at 2-8°C for transportation and storage (valid for 5 days). Genomic DNA from peripheral blood was extracted. Specifically, a magnetic bead method based on proteinase K digestion was used ( Genomic DNA was extracted using Blood Genomic DNA Kit #EC101).

[0084] 1. Multiplex PCR Primer Concentration Optimization

[0085] In this example, the artificially synthesized DNA sequence in Example 1 was used to adjust the primer concentration to correct the PCR preference caused by the difference in primer amplification efficiency.

[0086] The artificially synthesized DNA sequence is used as a PCR reaction template, and the primers in the primer library are used for PCR amplification. Each artificially synthesized DNA sequence reaction system includes: a multiplex PCR enzyme reaction system, an artificially synthesized DNA sequence combination, and an amplification primer combination corresponding to the V region and the J region in the artificially synthesized DNA sequence combination.

[0087] The concentration of the amplified product was measured using Qubit. The primer amplification efficiency was positively correlated with the product concentration. The product concentration was recorded as Con s , and then the average product concentration is obtained according to the following formula, recorded as

[0088] Through experience and experimental exploration, Con s and By comparison, samples with abnormal amplification efficiency are obtained, and relevant formulas are established to achieve uniform primer amplification efficiency. If the difference between the product concentration and the average product concentration is greater than 20%, the sample is judged to have abnormal amplification efficiency. The specific screening is carried out according to the following formula. If f(s) is less than 0, the sample amplification efficiency is too low, and the primer concentration needs to be increased until f(s) is greater than or equal to 0.

[0089]

[0090]

[0091] Prepare 10x primer mix according to the optimized primer concentration ratio. The specific preparation is shown in Table 3:

[0092] Table 3 Ratio of different primer concentrations

[0093]

[0094]

[0095] The comparison of primer concentration before and after optimization is as follows Figure 1 and Figure 2 As shown, it can be seen that the consistency of the product is significantly improved after optimization.

[0096] Example 3 Obtaining Baseline Preference Correction Coefficients by Analyzing Training Samples

[0097] 1. High- and low-cycle multiplex PCR reaction and sequencing library construction

[0098] In this example, the above primer library is used to capture and enrich the target fragments of the DNA extraction sample. The overall process is as follows: 1) one round of multiplex PCR amplification; 2) two rounds of multiplex PCR amplification; 3) multiplex PCR product magnetic bead purification; 4) multiplex PCR product library construction; 5) library magnetic bead purification; 6) library quality control. The details are as follows:

[0099] In multiplex PCR amplification, the specific PCR reaction system is shown in Table 4. In this embodiment, QIAGEN Multi PCR Master Mix ( Multiplex PCR Kit #206143) was used as the PCR Reaction Mix.

[0100] Table 4 PCR reaction system

[0101] Components / Tube volume PCR Reaction Mix 25μl 10x Primer Mix 4μl Enzyme-free Nuclease-free Water 21μl-x Template DNA (1 μg) x Total volume 50μl

[0102] The first PCR reaction program is shown in Table 5. The number of cycles of the first PCR reaction is denoted as c low :

[0103] Table 5. First PCR reaction procedure

[0104]

[0105] The product after the first PCR amplification was divided into two parts. One part of the product skipped step 2 and directly performed multiple PCR product magnetic bead purification. The other part of the product continued to perform the second multiple PCR amplification. The total number of cycles of the two amplifications was recorded as c high The specific reaction procedure is shown in Table 6:

[0106] Table 6 Multiplex PCR reaction program

[0107]

[0108] In this example, the steps of magnetic bead purification of multiple PCR products and library magnetic bead purification are the same, and both use conventional methods in the field: DNA sorting magnetic beads for single-side DNA purification to achieve the purpose of removing small fragment impurities within 100 bp such as primers and primer dimers. The volume of the two samples must be the same for each purification.

[0109] After the first purification, the multiple PCR amplification products were all subjected to second generation sequencing library construction using sequencing adapter primers (i.e., Nextera XT (IDT)) that were partially complementary to the universal adapter. In this embodiment, KAPA HiFi HotStart ReadyMix (KAPA HiFi HotStart ReadyMix (2x) # KK2601) was selected as the PCR Reaction Mix, and Nextera XT (IDT) primer was selected as the library construction primer for library construction. The specific library construction reaction system is shown in Table 7 below:

[0110] Table 7 Library construction reaction system

[0111] Components volume DNA 5μl Library Construction Primer 5 5μl Library Construction Primr 7 5μl PCR Reaction Mix 25μl ddWater 10μl Total volume 50μl

[0112] The library construction reaction program is shown in Table 8 below:

[0113] Table 8 Library construction reaction program

[0114]

[0115] After library construction, the concentration of the product library after only one round of multiPCR is recorded as Con lowThe concentration of the product library after two rounds of multiPCR is recorded as Con high .

[0116] In this example, the purified product was quality controlled, specifically, quantified using Qubit and fragment distribution analyzed using Qsep100. The present invention recommends that the concentration of the library product be no less than 3 ng / μL, the total volume be no less than 15 μL, the peak of the target fragment of the library product be dispersed, the main peak is concentrated around 250-300 bp, and there is basically no distribution within 100 bp. The fragment distribution of the library product before and after purification is as follows Figure 3 As shown (the upper figure is before purification, the lower figure is after purification), if the library product still has obvious distribution within 100 bp after purification, add a magnetic bead purification step to remove the fragments within 100 bp.

[0117] 2. Sequencing

[0118] The DNA fragments of the sequencing library are loaded onto the sequencing chip, and the second-generation sequencer is used for sequencing while synthesis. In this embodiment, the second-generation sequencer uses Illumina Nova-seq, and the sequencing strategy selects PE150 double-end sequencing. To ensure that at least 6 million sequences are obtained for both high- and low-cycle samples, the data volume of a single sample is not less than 3G. Considering the special sample distribution of multiplex PCR, it is recommended that the data volume of a single sample sequencing machine is not less than 8G.

[0119] 3. Data Analysis

[0120] The sequencing results of the multiplex PCR high and low cycle samples were analyzed according to the following data analysis steps:

[0121] Step A, sample the sequencing results of high and low cycle samples respectively to keep the data volume ratio consistent with Con high / Con low Consistent, sampling was done using the software seqtk (v1,4); Con high 、Con low Obtained by the above steps.

[0122] Step B: trim the sequencing reads using trim_galore (Version 0.6.4) [6] The software removed low-quality bases and adapters with the following parameters (-q 25--phred33--length 36--stringency 3--paired).

[0123] Step C, use FLASH (Fast Length Adjustment of Short reads) [7]The software splices read1 and read2 after removing the linker to obtain the full-length CDR3 region sequence.

[0124] Step D, using IgBLAST (1.13.0) [8] The software annotates the V / J genes and identifies the CDR3 region of TCR-β, and then uses the V and J region genes in the IMGT database as reference sequences. At the same time, it refers to the primer length in the above multiple PCR primer combination, and compares the sequence length of the reference genome after splicing. The splicing sequence with a too short alignment length is removed to remove primer dimers and polymers. The results of the optimization of removing primer dimers and polymers are shown in Figure 2. Figure 4 As shown, Figure 4 The upper half of the bar graph shows the sequence length distribution without removing dimers and polymers. Figure 4 The lower half of the bar graph shows the sequence length distribution after dimers and multimers are removed.

[0125] 4. Calculation of Baseline Bias Correction Coefficient

[0126] For each CDR3 i (i.e., unique CDR3, unique CDR3 means that the amino acid sequence of the CDR3 region of these sequences is consistent, and the corresponding V gene and J gene are also consistent) sequence number, PCR bias correction is performed according to its corresponding VJ combination, specifically including the following steps: 1) Analyze the number of each CDR3 i in the training sample and record it as N i,k ; 2) Obtain the V gene and J gene corresponding to each CDR3 i. 3) Obtain the baseline preference correction coefficient of VJ combination k according to the number of high and low cycle sequences of each CDR3 i in the training sample, and the formula is as follows.

[0127]

[0128] m is one of the M DNA training samples, k represents the VJ combination corresponding to the CDR3 i, b m,k represents the preference correction coefficient of VJ combination k in sample m, b m,k Obtained by the following formula:

[0129]

[0130] B m,k c high -c low The total preference coefficient of the round robin is obtained by the following formula:

[0131]

[0132] represents the number of all CDR3i sequences with VJ combination k in low cycle sample m, represents the number of high-cycle sample sequences corresponding to all CDR3 i with VJ combination k in sample m, B m,k By pairing the vector and A linear fit with an intercept of 0 is performed to obtain B m,k is the correlation coefficient of the fitting function with VJ combination k in sample m;

[0133] The fitting function parameters of each VJ combination k of the training sample are shown in Table 9. In the table, k is a different VJ combination, B k is the slope of the fitting function of VJ combination k in the sample, r-square is the R square value of the linear fitting function, and p-value is the p value of the correlation coefficient of the fitting curve. Results VJ combination k with CDR3 i number greater than 10, r-square greater than 0.9, and p-value less than 0.01 was screened.

[0134] Table 9 Fitting function parameters for each VJ combination k of training samples

[0135]

[0136]

[0137]

[0138]

[0139]

[0140]

[0141]

[0142]

[0143] Finally, the baseline preference correction coefficient of each VJ combination k is shown in Table 10 below. NA in the table means that the corresponding VJ combination was not detected in this embodiment, so the preference coefficient corresponding to the VJ combination cannot be provided:

[0144] Table 10 Baseline preference correction coefficients for each VJ combination k

[0145]

[0146]

[0147] Example 4 Correction of PCR bias according to baseline bias correction coefficient and quantitative analysis of T cell lines

[0148] 1. DNA Extraction from Jurkat Cell Line

[0149] In this example, a magnetic bead method based on proteinase K digestion was used ( The genomic DNA of Jurkat (Precella, CL-0129) cell line was extracted using Blood Genomic DNA Kit #EC101. Specifically, the Jurkat cell line is a human T lymphocyte leukemia cell (Clone E6-1), and the V and J genes of the Jurkat cell line are TRBV12-3 (NCBI Accession number: NC_000007.14: 142560642-142560931) and TRBJ1-2 (NCBI Accession number: NC_000007.14: 142787017-142787064).

[0150] 2. Human peripheral blood PBMC CD3 + T cell sorting and DNA extraction

[0151] In this example, flow cytometry was used to sort the cells. TM CD3 was isolated from human peripheral blood PBMC by using Fusion + T cells, sorted CD3 + T cells, using a proteinase K-digestion-based magnetic bead method ( Genomic DNA was extracted using Blood Genomic DNA Kit #EC101).

[0152] 3. In CD3 + Different concentrations of Jurkat cell line genomic DNA were added to the T cell DNA

[0153] 100ng CD3 + Jurkat T cell DNA at different mass ratios (10%, 1%, 0.1%, 0.01%) was added to the T cell DNA sample to obtain various mixed samples.

[0154] 4. Multiplex PCR reaction and sequencing library construction

[0155] The primer library was used to capture and enrich the target fragments added to the mixed samples. The specific experimental steps and reaction procedures were consistent with those in Example 3.

[0156] In this example, the steps of magnetic bead purification of multiple PCR products and magnetic bead purification of libraries are the same, both of which are consistent with Example 3.

[0157] After the first purification, the multiplex PCR amplification products were all subjected to second generation sequencing library construction using sequencing adapter primers that were partially complementary to the universal adapter. The reagents used and the specific library construction reaction system were consistent with those in Example 3.

[0158] 5. Sequencing

[0159] The DNA fragments of the sequencing library are loaded onto the sequencing chip, and the second-generation sequencer is used for sequencing by synthesis. In this embodiment, the second-generation sequencer is Illumina Nova-seq, and the sequencing strategy is PE150 double-end sequencing. At least 6 million sequences are obtained for each sample, and the amount of data for a single sample is not less than 3G.

[0160] 6. Data Analysis

[0161] The sequencing results of the multiplex PCR high and low cycle samples were analyzed according to the following data analysis steps:

[0162] In step A, the sequencing reads were trimmed to remove low-quality bases and adapters using trim_galore (Version 0.6.4) [6] software with the following parameters (-q 25 --phred 33 --length 36 --stringency 3-paired).

[0163] Step B, use FLASH (Fast Length Adjustment of Short reads) [7] The software splices read1 and read2 after removing the linker to obtain the full-length CDR3 region sequence.

[0164] Step C, using IgBLAST (1.13.0) [8] The software annotated the V / J genes and identified the CDR3 region of TCR-β, and then used the V and J region genes in the IMGT database as reference sequences. At the same time, the primer lengths in the above-mentioned multiple PCR primer combination were referred to, and the sequence lengths of the reference genome were compared after splicing. The splicing sequences with too short alignment lengths were eliminated to remove primer dimers and polymers.

[0165] 7. Back-calculate the proportion of Jurkat cell lines in each mixed sample

[0166] 1) Analyze the number of CDR3 i sequences in each mixed sample and record it as N i,k(The number of sequences without bias correction is generally the direct data after sequencing, or the number of sequences after only removing low-quality data after sequencing, such as the number of sequences after removing primer dimers and polymers); 2) Obtain the V gene and J gene corresponding to each CDR3 i; 3) According to the baseline bias correction coefficient b of each VJ combination k The number of sequences for each CDR3 i was corrected according to the following formula:

[0167]

[0168] i, k, c are all integers greater than or equal to 1, i represents the corresponding CDR3 i, Correction N i,k represents the number of corrected sequences of the CDR3i, k represents the VJ combination corresponding to the CDR3i (also known as VJ combination k), b k represents the baseline bias correction coefficient corresponding to the VJ combination k, c represents the number of cycles of multiple PCR (multiPCR), b k c-1 It represents the bias correction coefficient corresponding to VJ combination k in round c of multiple PCR cycle;

[0169] The proportion of Jurkat cell lines in each sample was calculated based on the corrected CDR3 i sequence number. The results are shown in Table 11:

[0170]

[0171]

[0172] In the table, the proportion of reads aligned to Jurkat in the mixed sample sequencing results with a Jurkat T cell DNA mass ratio of 10% is 7.1%-8.4%; the proportion of reads aligned to Jurkat in the mixed sample sequencing results with a Jurkat T cell DNA mass ratio of 1% is 1.3%-1.7%; the proportion of reads aligned to Jurkat in the mixed sample sequencing results with a Jurkat T cell DNA mass ratio of 0.1% is 0.1%-0.2%; the proportion of reads aligned to Jurkat in the mixed sample sequencing results with a Jurkat T cell DNA mass ratio of 0.01% is 0.02%-0.04%. It can be seen from the experimental data that under different incorporation ratios such as 10%, 1%, 0.1% and 0.01%, the detection value has a good correspondence with the actual incorporation ratio (CV<20%, RE<50%). Under the condition of the lowest concentration of 0.01%, this method can still detect the target cells.

[0173] The above verification shows that when the CDR3 frequency is greater than 0.1%, the method established in this study can accurately detect the content of Jurkat cells in T cells at different proportions (CV<20%, RE<50%), and when the CDR3 frequency is greater than 0.01%, this research method can detect CDR3. The experimental parallelism is good and the results are stable and reliable, indicating that this method has good accuracy and sensitivity and can be used for quantitative analysis of a small number of specific cells in sample cells.

[0174] References

[0175] [1] Lefranc MP, Lefranc G, 2001a The Immunoglobulin Factsbook. Academic Press: London; 448 pages.

[0176] [2] Lefranc MP, Lefranc G, 2001b The T cell receptor Factsbook. Academic Press: London; 384 pages.

[0177] [3] Robins HS, Campregher PV, Srivastava SK, et al. Comprehensiveassessment of T-cell receptor beta-chain diversity in alphabeta T cells. [J]. Blood, 2009, 114(19): 4099-4107. DOI: 10.1182 / blood-2009-04-217604.

[0178] [4] Rosati, E., Dowds, CM, Liaskou, E. et al. Overview of methodologies for T-cell receptor repertoire analysis. BMC Biotechnol 17, 61 (2017). https: / / doi.org / 10.1186 / s12896-017-0379-9

[0179] [5]Barennes,P.,Quiniou,V.,Shugay,M.et al.Benchmarking of T cellreceptor repertoire profiling methods reveals large systematic biases.NatBiotechnol 39,236–245(2021).https: / / doi.org / 10.1038 / s41587-020-0656-3

[0180] [6]https: / / www.bioinformatics.babraham.ac.uk / projects / trim_galore /

[0181] [7]FLASH:Fast length adjustment of short reads to improve genomeassemblies.T.Magoc and S.Salzberg.Bioinformatics 27:21(2011),2957-63.

[0182] [8]Ye J,Ma N,Madden TL,Ostell JM.IgBLAST:an immunoglobulin variabledomain sequence analysis tool.Nucleic Acids Res.2013 Jul;41(Web Serverissue):W34-40.doi:10.1093 / nar / gkt382.Epub 2013 May 13.PMID:23671333;PMCID:PMC3692102。

Claims

1. A method for correcting the PCR bias of an immune repertoire, characterized in that: The calibration method comprises the following steps: 1) analyzing the number of each unique CDR3 sequence in an unknown sample containing cell genomic DNA and recording it as N i,k , the unique CDR3 is recorded as CDR3 i; 2) obtaining the V gene and J gene corresponding to each CDR3 i; 3) According to the baseline preference correction coefficient b of each VJ combination k The number of sequences for each CDR3 i was corrected according to the following formula: i, k, c are all integers greater than or equal to 1, i represents the corresponding CDR3 i, Correction N i,k represents the number of corrected sequences of the CDR3i, k represents the VJ combination k corresponding to the CDR3i, b k represents the baseline bias correction coefficient corresponding to the VJ combination k, c represents the number of cycles of multiplex PCR, b k c-1 It represents the bias correction coefficient corresponding to VJ combination k in round c of multiple PCR cycle; The b k The results are obtained by the following steps: 1) DNA is extracted from all M training samples and c low 1) a first multiplex PCR amplification with low cycle number; 2) c low After rounds of multiplex PCR amplification, all products were divided into two parts, one of which was recorded as a low-cycle sample. The multiplex PCR amplification products of the low-cycle sample were subjected to second-generation sequencing to build a library, and the concentration after library construction was recorded as Con low The other product was subjected to multiple PCR amplification and recorded as the high-cycle sample. The total number of cycles of the two amplifications before and after the high-cycle sample was recorded as c high The multiplex PCR amplification products of the high cycle samples were subjected to second generation sequencing to build a library, and the concentration after library construction was recorded as Con high ; 3) Sequencing high and low cycle samples, obtaining at least 6 million sequences for each sample; 4) Sampling the sequencing results of each high cycle sample and low cycle sample respectively, so that the proportion of the sampled data is consistent with Con high / Con low Consistency; 5) Perform bioinformatics analysis on the sequencing results and obtain the N of the two amplified products. i,k ; 6) Obtain the baseline preference correction coefficient b for each VJ combination k according to the following formula: k : m is an integer greater than 1 and less than M, representing one of the M training samples, b m,k represents the preference correction coefficient of VJ combination k in sample m, b m,k Obtained by the following formula: B m,k c high -c low The total preference value of the round robin is obtained by the following formula: represents the number of sequences of all CDR3i corresponding to VJ combination k in sample m in low-cycle samples, represents the number of sequences of all CDR3 i corresponding to VJ combination k in sample m in high circulation samples, B m，k By pairing the vector and A linear fit with an intercept of zero is performed to obtain B m,k is the correlation coefficient of the fitting function of VJ combination k in sample m.

2. The calibration method according to claim 1, characterized in that: The sampling is to down sample the sequencing sequence of the sample using seqtk (v1,4) to make the sequencing amount of the samples comparable; And / or, M is a positive integer; And / or, the linear fitting is performed using least squares approximation; and / or, the 5' ends of the primers used in the multiplex PCR all contain the same adapter; and / or, the ratio of primer combination concentrations in multiplex PCR is optimized using an artificially synthesized sequence of artificially synthesized TCR-β DNA; And / or, the immune repertoire is a TCR-β immune repertoire; And / or, the unknown sample and / or the training sample are obtained by a magnetic bead method or a column method.

3. The calibration method according to claim 1 or 2, characterized in that: The bioinformatics analysis includes: 1) removal of data adapters after sampling; 2) splicing of double-end sequencing data read1 and read2; 3) TCR-βV / J gene annotation and CDR3 region identification; 4) removal of primer dimers and multimers; 5) CDR3 i sequence number statistics.

4. The calibration method according to claim 3, characterized in that: The trim_galore software is used for the removal of the linker; and / or, the flash software is used for the splicing; and / or, the TCR-β V / J gene annotation and CDR3 region identification are completed using the igblast software; and / or, the CDR3 i sequence number statistics are obtained by the following steps: 1) using the V region and J region genes in the IMGT database as reference sequences for splicing and then comparing the sequence length statistics on the reference genome, while referring to the length of the primer combination used in the multiplex PCR; 2) eliminating the spliced ​​sequences that are too short in length when compared to the reference genome.

5. A set of synthetic DNA sequences of a TCR-β immune repertoire, characterized in that: The synthetic DNA sequence combination comprises a plurality of nucleotide sequences, each of which comprises the following components: (1) a partial sequence of a V gene, comprising the entire V region in the CDR3 region and the entire V gene region amplified by the multiple primer combination; (2) The entire sequence of a J gene, including the entire J region in the CDR3 region and the entire J gene region amplified by the multiple primer combination; (3) The entire sequence of a D gene; (4) The tag sequence.

6. The artificially synthesized DNA sequence combination according to claim 5, characterized in that: The synthetic DNA sequence combination comprises two parts, wherein the 5' end of one part of the synthetic DNA sequence is a partial sequence of the same V gene, and the V gene is denoted as V highfrequency The 3' end of the other part of the DNA artificially synthesized sequence is the partial sequence of all V genes, and the 3' end is the complete sequence of the same J gene. This J gene is denoted as J highfrequency Preferably, the V highfrequency and J highfrequency They are V28 and J2-7 respectively; Preferably, the tag sequence is the amino acid sequence shown in SEQ ID NO: 125, which is located between the V gene and the D gene; More preferably, the artificially synthesized DNA sequence combination comprises the following nucleotide sequence:

7. A set of primer combinations for amplifying the TCR-β immune repertoire, characterized in that: The primer combination includes the following nucleotide sequence: Preferably, the usage of each primer in the primer combination is as follows: 。 8. A quantitative analysis method of immune repertoire, characterized in that: The quantitative analysis method comprises performing second-generation sequencing on the immune repertoire library constructed based on multiplex PCR, and correcting the number of CDR3 sequencing sequences of the second-generation sequencing using the correction method as described in any one of claims 1 to 4; Preferably, the immune repertoire is a T cell receptor β chain immune repertoire of a DNA sample; More preferably, the primers used in the second generation sequencing are the primer combination as claimed in claim 7; Further preferably, the quantitative analysis method further comprises using a Jurkat cell line to verify the result of the second generation sequencing corrected by the correction method as described in any one of claims 1 to 4.

9. A detection kit, characterized in that: The detection kit comprises the artificially synthesized DNA sequence combination as described in claim 5 or 6 and / or the primer combination as described in claim 7; preferably, the detection kit also comprises reagents for second-generation sequencing.

10. Use of the artificially synthesized DNA sequence combination according to claim 5 or 6 and / or the primer combination according to claim 7 in quantitative analysis of T cell receptor β chain immune repertoire; preferably, the use is for non-diagnostic or therapeutic purposes.

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