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

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 er...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6237323/
https://www.ncbi.nlm.nih.gov/pubmed/30439982
http://dx.doi.org/10.1371/journal.pone.0207020
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author 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
author_facet 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
author_sort Bai, Yu
collection PubMed
description 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.
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spelling pubmed-62373232018-12-01 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 PLoS One Research Article 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. Public Library of Science 2018-11-15 /pmc/articles/PMC6237323/ /pubmed/30439982 http://dx.doi.org/10.1371/journal.pone.0207020 Text en © 2018 Bai et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
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
title Evaluation of the capacities of mouse TCR profiling from short read RNA-seq data
title_full Evaluation of the capacities of mouse TCR profiling from short read RNA-seq data
title_fullStr Evaluation of the capacities of mouse TCR profiling from short read RNA-seq data
title_full_unstemmed Evaluation of the capacities of mouse TCR profiling from short read RNA-seq data
title_short Evaluation of the capacities of mouse TCR profiling from short read RNA-seq data
title_sort evaluation of the capacities of mouse tcr profiling from short read rna-seq data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6237323/
https://www.ncbi.nlm.nih.gov/pubmed/30439982
http://dx.doi.org/10.1371/journal.pone.0207020
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