Nextflow管道用于t细胞受体库重建和RNA测序数据分析

Teresa Rubio , Maria Chernigovskaya , Susanna Marquez , Cristina Marti , Paula Izquierdo-Altarejos , Amparo Urios , Carmina Montoliu , Vicente Felipo , Ana Conesa , Victor Greiff , Sonia Tarazona
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引用次数: 3

摘要

t细胞受体(TCR)分析对免疫系统疾病的研究具有重要意义。TCR的表达通常通过靶向测序方法来测量,其中TCR基因被选择性扩增。然而,许多非靶向RNA-seq实验也包含TCR基因的reads,这可以用于TCR表达分析,同时减少样品需求和成本。此外,转录组RNA-seq读取的一步一步的传递免疫库数据的管道是缺失的,这些类型的分析通常不包括在免疫条件的RNA-seq研究中。这意味着错过了通过分析免疫储备来补充它们的机会。我们提出了一个Nextflow管道,用于t细胞受体库重建和RNA测序数据分析。我们使用了一个案例研究,从对照患者,无肝性脑病和轻度肝性脑病(MHE)的肝硬化患者分离的CD4 T细胞的大量rna测序中恢复TCR库谱。MHE是一种由外周炎症介导的神经精神综合征,可影响肝硬化患者。在每位患者恢复498- 1114个不同的TCR β链后,对患者进行全库分析,发现很少有公共克隆,多样性高,全库内序列相似性升高,与免疫状态无关。此外,与乳糜泻和炎症性肠病相关的tcr在MHE患者谱中被显著高估。提供的计算管道作为一种资源,可以促进从RNA-seq数据中分析TCR,从而促进免疫疾病的免疫表型分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Nextflow pipeline for T-cell receptor repertoire reconstruction and analysis from RNA sequencing data

T-cell receptor (TCR) analysis is relevant for the study of immune system diseases. The expression of TCRs is usually measured with targeted sequencing approaches where TCR genes are selectively amplified. However, many non-targeted RNA-seq experiments also contain reads of TCR genes, which could be leveraged for TCR expression analysis while reducing sample requirements and costs. Moreover, a step-by-step pipeline for the processing of transcriptome RNA-seq reads to deliver immune repertoire data is missing, and these types of analyses are usually not included in RNA-seq studies of immunological conditions. This represents a missed opportunity for complementing them with the analysis of the immune repertoire.

We present a Nextflow pipeline for T-cell receptor repertoire reconstruction and analysis from RNA sequencing data. We used a case study where TCR repertoire profiles were recovered from bulk RNA-seq of isolated CD4 T cells from control patients, cirrhotic patients without and with Minimal Hepatic Encephalopathy (MHE). MHE is a neuropsychiatric syndrome, mediated by peripheral inflammation, that may affect cirrhotic patients. After the recovery of 498-1,114 distinct TCR beta chains per patient, repertoire analysis of patients resulted in few public clones, high diversity and elevated within-repertoire sequence similarity, independently of immune status. Additionally, TCRs associated with celiac disease and inflammatory bowel disease were significantly overrepresented in MHE patient repertoires. The provided computational pipeline functions as a resource to facilitate TCR profiling from RNA-seq data boosting immunophenotype analyses of immunological diseases.

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来源期刊
Immunoinformatics (Amsterdam, Netherlands)
Immunoinformatics (Amsterdam, Netherlands) Immunology, Computer Science Applications
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