免疫系統中的T細胞透過其受體識別特異性外來抗原，並激活免疫反應。T細胞受體 (TCR) 基因在V(D)J重組過程中，選擇並連接各種V、(D) 和J基因，所形成多樣的TCR序列能夠反映免疫系統的功能。為抓取各種TCR基因來研究免疫基因組，常用的多重PCR方法透過多種引子來放大所有可能的重組基因，但它有引子偏差的問題。要避免引子偏差可以使用5’ cDNA末端快速擴增 (5’ RACE) 的方法。然而，5’ RACE會產生非規則重組的TCR序列。現有的序列比對工具會誤把非規則重組的序列當成規則序列而導致錯誤的註解。因此我們開發了TRIg來正確分析5’ RACE數據。 TRIg將TCR序列與整個免疫基因比對，而不僅僅與V(D)J區域比對。有了準確的序列比對工具，我們在一個健康人樣本中比較多重PCR和5’ RACE方法，發現5’ RACE方法的可重複性比較高，而且偵測到的免疫基因組較均勻，顯示其較無引子偏差的優勢。另外，我們改良了5’ RACE方法，降低非規則重組序列的比例，使得大部份資料能有效用於免疫基因組的分析。這些成果提供有效率的5’ RACE實驗和計算分析流程以研究免疫基因組。

In the adaptive immune system, T cells are able to recognize a variety of foreign antigens because their T cell receptors (TCRs) appear in diverse structures, which are the results of complex V(D)J recombination of TCR genes. The recombined TCR gene sequences of all T cells can thus be used to characterize immune repertoire. To capture all possible V(D)J recombinations, a popular approach is applying multiple primers that target all possible V and/or J regions of TCR genes for amplification. This multiplex PCR (mPCR) approach, however, usually introduces primer bias. To avoid primer bias, a 5’ rapid amplification of cDNA ends (5’ RACE) approach can be used to ampify TCR genes. In the 5’ RACE data, however, both regularly and non-regularly recombined TCR sequences exist, and the later of which could not be used to characterize immune repertoire. Current tools may mistake non-regular TCR sequences as regular and report false V(D)J annotations. In this thesis, we developed a new computational tool, TRIg, to correctly handle both regular and non-regular TCR sequences in the 5’ RACE data. To promote the 5’ RACE approach, we further studied the difference between mPCR and 5’ RACE approach. We found that 5’ RACE achieved a higher consistency and captured more VJ recombination events than mPCR, suggesting less primer bias of the 5’ RACE approach. Finally, we improved a 5’ RACE method to reduce the proportion of non-regular TCR sequences via carefully controlling size of the PCR amplicons. This increased the fraction of useful data from <40% to >80%. With all these efforts, we provide an efficient experimental and computational pipeline for studying immune repertoire.

Alamyar, E., Giudicelli, V., Li, S., Duroux, P., and Lefranc, M.P. IMGT/HighV-QUEST: the IMGT(R) web portal for immunoglobulin (IG) or antibody and T cell receptor (TR) analysis from NGS high throughput and deep sequencing. Immunome Research 8, 26-36, 2012.

Alt, F.W., Oltz, E.M., Young, F., Gorman, J., Taccioli, G., and Chen, J. VDJ recombination. Immunology Today 13, 306-314, 1992.

Boehm, T., and Bleul, C. The evolutionary history of lymphoid organs. Nature Immunology 8, 131-135, 2007.

Bolger, A.M., Lohse, M., and Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114-2120, 2014.

Bolotin, D.A., Poslavsky, S., Mitrophanov, I., Shugay, M., Mamedov, I.Z., Putintseva, E.V., and Chudakov, D.M. MiXCR: software for comprehensive adaptive immunity profiling. Nature Methods 12, 380-381, 2015.

Boyd, S.D. Measurement and clinical monitoring of human lymphocyte clonality by massively parallel VDJ pyrosequencing. Science Translational Medicine 1, 12-23, 2009.

Brady, B.L., Steinel, N.C., and Bassing, C.H. Antigen receptor allelic exclusion: an update and reappraisal. Journal of Immunology 185, 3801-3808, 2010.

Chaplin, D.D. Overview of the immune response. Journal of Allergy and Clinical Immunology 111, 442-459, 2003.

Delcher, A.L., Kasif , S., Fleischmann, R.D., Peterson, J., White, O., and Salzberg, S.L. Alignment of whole genomes. Nucleic Acids Research 27, 2369-2376, 1999.

Delcher, A.L., Phillippy, A., Carlton, J., and Salzberg, S.L. Fast algorithms for large-scale genome alignment and comparison. Nucleic Acids Research 30, 2478-2483, 2002.

Edgar, R.C. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nature Methods 10, 996-998, 2013.

Fang, H., Yamaguchi, R., Liu, X., Daigo, Y., Yew, P.Y., Tanikawa, C., Matsuda, K., Imoto, S., Miyano, S., and Nakamura, Y. Quantitative T cell repertoire analysis by deep cDNA sequencing of T cell receptor α and β chains using next-generation sequencing (NGS). Oncoimmunology 3, 968467-968479, 2015.

Fernandes, S., Chavan, S., Chitnis, V., Kohn, N., and Pahwa, S. Simplified fluorescent multiplex PCR method for evaluation of the T-cell receptor V beta-chain repertoire. Clinical and Diagnostic Laboratory Immunology 12, 477-483, 2005.

Freeman, J.D., Warren, R.L., Webb, J.R., Nelson, B.H., and Holt, R.A. Profiling the T-cell receptor beta-chain repertoire by massively parallel sequencing. Genome Research 19, 1817-1824, 2009.

Giannoni, F., Hardee, C.L., Wherley, J., Gschweng, E., Senadheera, S., Kaufman, M.L., Chan, R., Bahner, I., Gersuk, V., Wang, X., Gjertson, D., Baltimore, D., Witte, O.N., Economou, J.S., Ribas, A., and Kohn, D.B. Allelic exclusion and peripheral reconstitution by TCR transgenic T cells arising from transduced human hematopoietic stem/progenitor cells. Molecular Therapy 21, 1044-1054, 2013.

Hoebe, K., Janssen, E., and Beutler, B. The interface between innate and adaptive immunity. Nature Immunology 5, 971-974, 2004.

Hou, X., Wang, M., Lu, C., Xie, Q., Cui, G., Chen, J., Du, Y., Dai, Y., & Diao, H. Analysis of the Repertoire Features of TCR Beta Chain CDR3 in Human by High-Throughput Sequencing. Cellular Physiology and Biochemistry 39, 651-667, 2016.

Hung, S.J., Chen, Y.L., Chu, C.H., Lee, C.C., Chen, W.L., Lin, Y.L., Lin, M.C., Ho, C.L., and Liu, T. TRIg: a robust alignment pipeline for non-regular T-cell receptor and immunoglobulin sequences. BioMed Central Bioinformatics 17, 433-442, 2016.

Jennifer, M., and Hinrich, A. Melanoma Introduction. Melanoma - Current Clinical Management and Future Therapeutics. IntechOpen, United States of America, 11-12, 2015.

Klingenberg, R., Brokopp, C.E., Grivès, A., Courtier, A., Jaguszewski, M., Pasqual, N., Vlaskou Badra, E., Lewandowski, A., Gaemperli, O., Hoerstrup, S.P., Maier, W., Landmesser, U., Lüscher, T.F., and Matter, C.M. Clonal restriction and predominance of regulatory T cells in coronary thrombi of patients with acute coronary syndromes. European Heart Journal 36, 1041-1048, 2015.

Liu, X., Zhang, W., Zeng, X., Zhang, R., Du, Y., Hong, X., Cao, H., Su, Z., Wang, C., Wu, J., Nie, C., Xu, X., and Kristiansen, K. Systematic Comparative Evaluation of Methods for Investigating the TCRβ Repertoire. PLoS One 11, 152464-152482, 2016.

Mago, T., and Salzberg, S.L. FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics 27, 2957-2963, 2011.

Migalska, M., Sebastian, A., and Radwan, J. Profiling of the TCRβ repertoire in non-model species using high-throughput sequencing. Scientific Reports 8, 11613-11627, 2018.

Postow, M.A., Manuel, M., Wong, P., Yuan, J., Dong, Z., Liu, C., Perez, S., Tanneau, I., Noel, M., Courtier, A., Pasqual, N., and Wolchok, J.D. Peripheral T cell receptor diversity is associated with clinical outcomes following ipilimumab treatment in metastatic melanoma. Journal for ImmunoTherapy of Cancer 3, 23-26, 2015.

Robins, H. Immunosequencing: applications of immune repertoire deep sequencing. Current Opinion in Immunology 25, 646-652, 2013.

Rosati, E., Dowds, C.M., Liaskou, E., Henriksen, E., Karlsen, T.H., and Franke, A. Overview of methodologies for T-cell receptor repertoire analysis. BioMed Central Biotechnology 17, 61-77, 2017.

Rudolph, M.G., Stanfield, R.L., and Wilson, I.A. How TCRs bind MHCs, peptides, and coreceptors. Annual Review of Immunology 24, 419-466, 2006.

Ruggiero, E., Nicolay, J.P., Fronza, R., Arens, A., Paruzynski, A., Nowrouzi, A., Ürenden, G., Lulay, C., Schneider, S., Goerdt, S., Glimm, H., Krammer, P.H., Schmidt, M., and von Kalle, C. High-resolution analysis of the human T-cell receptor repertoire. Nature Communications 6, 8081-8088, 2015.

Thomas, N., Heather, J., Ndifon, W., Shawe-Taylor, J., and Chain, B. Decombinator: a tool for fast, efficient gene assignment in T-cell receptor sequences using a finite state machine. Bioinformatics 29, 542-550, 2013.

Tonegawa, S. Somatic generation of antibody diversity. Nature 302, 575-581, 1983.

Turner, F.S. Assessment of insert sizes and adapter content in fastq data from NexteraXT libraries. Frontiers in Genetics 5, 5-10, 2014.

Vettermann, C., and Schlissel, M.S. Allelic exclusion of immunoglobulin genes: models and mechanisms. Immunological Reviews 237, 22-42, 2010.

Viret, C., and Janeway, C.A. MHC and T cell development. Reviews in Immunogenetics 1, 91-104, 1999.

Wang, C.Y., Yu, P.F., He, X.B., Fang, Y.X., Cheng, W.Y., and Jing, Z.Z. αβ T-cell receptor bias in disease and therapy (Review). International Journal of Oncology 48, 2247-2256, 2016.

Warren, R.L., Freeman, J.D., Zeng, T., Choe, G., Munro, S., Moore, R., Webb, J.R., and Holt, R.A. Exhaustive T-cell repertoire sequencing of human peripheral blood samples reveals signatures of antigen selection and a directly measured repertoire size of at least 1 million clonotypes. Genome Research 21, 790-797, 2011.

Xianliang, H., Jianing, C., Lin, W., Yong, D., and Hongyan, D. Basic research and clinical application of immune repertoire sequencing. International Journal of Clinical and Experimental Medicine 9, 18868-18882, 2016.

Ye, J., Ma, N., Madden, T.L., and Ostell, J.M. IgBLAST: an immunoglobulin variable domain sequence analysis tool. Nucleic Acids Research 41, 34-40, 2013.

Yew, P.Y., Alachkar, H., Yamaguchi, R., Kiyotani, K., Fang, H., Yap, K.L., Liu, H.T., Wickrema, A., Artz, A., Besien, K., Imoto, S., Miyano, S., Bishop, M.R., Stock, W., and Nakamura, Y. Quantitative characterization of T-cell repertoire in allogeneic hematopoietic stem cell transplant recipients. Bone Marrow Transplant 50, 1227-1234, 2015.

Zhang, J., Kobert, K., Flouri, T., and Stamatakis, A. PEAR: a fast and accurate Illumina Paired-End reAd mergeR. Bioinformatics 30, 614-620, 2014.