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DOI 10.1371/journal.pone.0207020

Медицинская библиотека · PloS one · 2018

Evaluation of the capacities of mouse TCR profiling from short read RNA-seq data.

Bai Yu, Wang David, Li Wentian, Huang Ying, Ye Xuan, Waite Janelle, Barry Thomas, Edelmann Kurt H, Levenkova Natasha, Guo Chunguang, Skokos Dimitris, Wei Yi, Macdonald Lynn E, Fury Wen

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Аннотация

Profiling T cell receptor (TCR) repertoire via short read transcriptome sequencing (RNA-Seq) has a unique advantage of probing simultaneously TCRs and the genome-wide RNA expression of other genes. However, compared to targeted amplicon approaches, the shorter read length is more prone to mapping error. In addition, only a small percentage of the genome-wide reads may cover the TCR loci and thus the repertoire could be significantly under-sampled. Although this approach has been applied in a few studies, the utility of transcriptome sequencing in probing TCR repertoires has not been evaluated extensively. Here we present a systematic assessment of RNA-Seq in TCR profiling. We evaluate the power of both Fluidigm C1 full-length single cell RNA-Seq and bulk RNA-Seq in characterizing the repertoires of different diversities under either naïve conditions or after immunogenic challenges. Standard read length and sequencing coverage were employed so that the evaluation was conducted in accord with the current RNA-Seq practices. Despite high sequencing depth in bulk RNA-Seq, we encountered difficulty quantifying TCRs with low transcript abundance (<1%). Nevertheless, top enriched TCRs with an abundance of 1-3% or higher can be faithfully detected and quantified. When top TCR sequences are of interest and transcriptome sequencing is available, it is worthwhile to conduct a TCR profiling using the RNA-Seq data.

Для цитирования: Bai Yu, Wang David, Li Wentian, Huang Ying, Ye Xuan, Waite Janelle, Barry Thomas, Edelmann Kurt H, Levenkova Natasha, Guo Chunguang, Skokos Dimitris, Wei Yi, Macdonald Lynn E, Fury Wen. Evaluation of the capacities of mouse TCR profiling from short read RNA-seq data.. PloS one. 2018. DOI: 10.1371/journal.pone.0207020.

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