Tools for fundamental analysis functions of TCR repertoires: a systematic comparison

Zhang, Yanfang; Yang, Xiujia; Zhang, Yanxia; Zhang, Yan; Wang, Minhui; Ou, Jin; Zhu, Yan; Zeng, Huikun; Wu, Jiaqi; Lan, Chunhong; Zhou, Hongwei; Yang, Wei; Zhang, Zhenhai

doi:10.1093/bib/bbz092

Cited by 18 publications

(18 citation statements)

References 46 publications

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“…40 In the review of TCR sequencing software, the first study generated an in silico data set and assessed clonotype detection, CDR3 identification, error correction and gene segment assignment accuracy. 61 This study found that not all algorithms were able to run all four subanalyses and that the performances varied greatly across individual algorithms, particularly for gene assignment and error correction. The second study performed a similar analysis 62 and concluded that no single tool performed optimally for all types of analyses but recommended MiXCR 50 if limited to a single analysis.…”

Section: Variant Detection Workflowmentioning

confidence: 85%

Detecting pathogenic variants in autoimmune diseases using high‐throughput sequencing

Field

2020

Immunol. Cell Biol.

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Sequencing the first human genome in 2003 took 15 years and cost $2.7 billion. Advances in sequencing technologies have since decreased costs to the point where it is now feasible to resequence a whole human genome for $1000 in a single day. These advances have allowed the generation of huge volumes of highquality human sequence data used to construct increasingly large catalogs of both population-level and disease-causing variation. The existence of such databases, coupled with a high-quality human reference genome, means we are able to interrogate and annotate all types of genetic variation and identify pathogenic variants for many diseases. Increasingly, sequencing-based approaches are being used to elucidate the underlying genetic cause of autoimmune diseases, a group of roughly 80 polygenic diseases characterized by abnormal immune responses where healthy tissue is attacked. Although sequence data generation has become routine and affordable, significant challenges remain with no gold-standard methodology to identify pathogenic variants currently available. This review examines the latest methodologies used to identify pathogenic variants in autoimmune diseases and considers available sequencing options and subsequent bioinformatic methodologies and strategies. The development of reliable and robust sequencing and analytic workflows to detect pathogenic variants is critical to realize the potential of precision medicine programs where patient variant information is used to inform clinical practice.

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Section: Variant Detection Workflowmentioning

confidence: 85%

Detecting pathogenic variants in autoimmune diseases using high‐throughput sequencing

Field

2020

Immunol. Cell Biol.

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“…To increase the reliability of processed TCR sequences, multiple TCR extraction methods were used: CATT ( 22 ), MiXCR ( 23 ) and IMSEQ ( 24 ). These methods had demonstrated precise and sensitive performance on previous benchmarks ( 22 , 25 ). To reduce false positives, we used the intersection sets of TCR repertoire retrieved by three methods as the final result of a sample.…”

Section: Methodsmentioning

confidence: 99%

TCRdb: a comprehensive database for T-cell receptor sequences with powerful search function

Chen

Yue

Lei

et al. 2020

Nucleic Acids Research

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T cells and the T-cell receptor (TCR) repertoire play pivotal roles in immune response and immunotherapy. TCR sequencing (TCR-Seq) technology has enabled accurate profiling TCR repertoire and currently a large number of TCR-Seq data are available in public. Based on the urgent need to effectively re-use these data, we developed TCRdb, a comprehensive human TCR sequences database, by a uniform pipeline to characterize TCR sequences on TCR-Seq data. TCRdb contains more than 277 million highly reliable TCR sequences from over 8265 TCR-Seq samples across hundreds of tissues/clinical conditions/cell types. The unique features of TCRdb include: (i) comprehensive and reliable sequences for TCR repertoire in different samples generated by a strict and uniform pipeline of TCRdb; (ii) powerful search function, allowing users to identify their interested TCR sequences in different conditions; (iii) categorized sample metadata, enabling comparison of TCRs in different sample types; (iv) interactive data visualization charts, describing the TCR repertoire in TCR diversity, length distribution and V-J gene utilization. The TCRdb database is freely available at http://bioinfo.life.hust.edu.cn/TCRdb/ and will be a useful resource in the research and application community of T cell immunology.

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“…As shown in Figure 1, we obtained the candidate AUSs through the following six steps: i) V allele variant detection via IgDiscover with initial species-specific databases downloaded from IMGT/GENE-DB [7,26]. The newly discovered genes/alleles were merged with initial databases and carried on for downstream analyses; ii) the sequences from each sample were annotated and assembled via MiXCR (compared in Zhang et al [27]) and clonotypes were consequently extracted based on CDR3s and V and junctional (J) allele usages; iii) each sample were genotyped via a Bayesian method adapted from TIgGER; iv) the AUS in each clonotype was extracted and dimed as the initial AUS for that particular V allele; v) for each V allele, the consensus of all initial AUSs were calculated and defined as the final AUS(s). Alleles not in the genotype were excluded in this step; vi) a scoring-based method was employed to retain the most confident AUSs.…”

Section: Bioinformatics Pipeline For Obtaining High-quality Aussmentioning

confidence: 99%

Antibody Upstream Sequence Diversity and Its Biological Implications Revealed by Repertoire Sequencing

Zhu

Yang

et al. 2020

Preprint

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The sequence upstream of antibody variable region (Antibody Upstream Sequence, or AUS) consists of 5’ untranslated region (5’ UTR) and two leader regions, L-PART1 and L-PART2. The sequence variations in AUS affect the efficiency of PCR amplification, mRNA translation, and subsequent PCR-based antibody quantification as well as antibody engineering. Despite their importance, the diversity of AUSs has long been neglected. Utilizing the rapid amplification of cDNA ends (5’RACE) and high-throughput antibody repertoire sequencing (Rep-Seq) technique, we acquired full-length AUSs for human, rhesus macaque (RM), cynomolgus macaque (CM), mouse, and rat. We designed a bioinformatics pipeline and discovered 2,957 unique AUSs, corresponding to 2,786 and 1,159 unique sequences for 5’ UTR and leader, respectively. Comparing with the leader records in the international ImMunoGeneTics (IMGT), while 529 were identical, 313 were with single nucleotide polymorphisms (SNPs), 280 were totally new, and 37 updated the incomplete records. The diversity of AUSs’ impact on related antibody biology was also probed. Taken together, our findings would facilitate Rep-Seq primer design for capturing antibodies comprehensively and efficiently as well as provide a valuable resource for antibody engineering and the studies of antibody at the molecular level.

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Tools for fundamental analysis functions of TCR repertoires: a systematic comparison

Cited by 18 publications

References 46 publications

Detecting pathogenic variants in autoimmune diseases using high‐throughput sequencing

Detecting pathogenic variants in autoimmune diseases using high‐throughput sequencing

TCRdb: a comprehensive database for T-cell receptor sequences with powerful search function

Antibody Upstream Sequence Diversity and Its Biological Implications Revealed by Repertoire Sequencing

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