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Bai Y, Wang D, Li W, Huang Y, Ye X, Waite J, Barry T, Edelmann KH, Levenkova N, Guo C, Skokos D, Wei Y, Macdonald LE, Fury W. Evaluation of the capacities of mouse TCR profiling from short read RNA-seq data. PLoS One 2018; 13:e0207020. [PMID: 30439982 PMCID: PMC6237323 DOI: 10.1371/journal.pone.0207020] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2018] [Accepted: 10/22/2018] [Indexed: 11/18/2022] Open
Abstract
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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Affiliation(s)
- Yu Bai
- Regeneron Pharmaceuticals, Tarrytown, New York, United States of America
- * E-mail: (YB); (WF)
| | - David Wang
- Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York, United States of America
| | - Wentian Li
- Robert S. Boas Center for Genomics & Human Genetics, Feinstein Institute for Medical Research, Northwell Health, Manhasset, New York, United States of America
| | - Ying Huang
- Regeneron Pharmaceuticals, Tarrytown, New York, United States of America
| | - Xuan Ye
- Regeneron Pharmaceuticals, Tarrytown, New York, United States of America
| | - Janelle Waite
- Regeneron Pharmaceuticals, Tarrytown, New York, United States of America
| | - Thomas Barry
- Regeneron Pharmaceuticals, Tarrytown, New York, United States of America
| | - Kurt H. Edelmann
- Regeneron Pharmaceuticals, Tarrytown, New York, United States of America
| | - Natasha Levenkova
- Regeneron Pharmaceuticals, Tarrytown, New York, United States of America
| | - Chunguang Guo
- Regeneron Pharmaceuticals, Tarrytown, New York, United States of America
| | - Dimitris Skokos
- Regeneron Pharmaceuticals, Tarrytown, New York, United States of America
| | - Yi Wei
- Regeneron Pharmaceuticals, Tarrytown, New York, United States of America
| | - Lynn E. Macdonald
- Regeneron Pharmaceuticals, Tarrytown, New York, United States of America
| | - Wen Fury
- Regeneron Pharmaceuticals, Tarrytown, New York, United States of America
- * E-mail: (YB); (WF)
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