Evidence map›Paper›PMID 30439982›Full record

ArticlePloS one2018

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

Yu Bai, David Wang, Wentian Li, Ying Huang, Xuan Ye, Janelle Waite, Thomas Barry, Kurt H Edelmann, Natasha Levenkova, Chunguang Guo and 4 more

Abstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Yu BaiRegeneron Pharmaceuticals, Tarrytown, New York, United States of America.ORCID 0000-0002-0371-8590
David WangDepartment of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York, United States of America.
Wentian LiRobert S. Boas Center for Genomics & Human Genetics, Feinstein Institute for Medical Research, Northwell Health, Manhasset, New York, United States of America.ORCID 0000-0003-1155-110X
Ying HuangRegeneron Pharmaceuticals, Tarrytown, New York, United States of America.
Xuan YeRegeneron Pharmaceuticals, Tarrytown, New York, United States of America.
Janelle WaiteRegeneron Pharmaceuticals, Tarrytown, New York, United States of America.
Thomas BarryRegeneron Pharmaceuticals, Tarrytown, New York, United States of America.
Kurt H EdelmannRegeneron Pharmaceuticals, Tarrytown, New York, United States of America.
Natasha LevenkovaRegeneron Pharmaceuticals, Tarrytown, New York, United States of America.
Chunguang GuoRegeneron Pharmaceuticals, Tarrytown, New York, United States of America.
Dimitris SkokosRegeneron Pharmaceuticals, Tarrytown, New York, United States of America.
Yi WeiRegeneron Pharmaceuticals, Tarrytown, New York, United States of America.
Lynn E MacdonaldRegeneron Pharmaceuticals, Tarrytown, New York, United States of America.
Wen FuryRegeneron Pharmaceuticals, Tarrytown, New York, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

AnimalsCD8-Positive T-LymphocytesColorectal NeoplasmsGenetic LociLymphocytic choriomeningitis virusMiceMice, Inbred C57BLReceptors, Antigen, T-CellRNASequence Analysis, RNASingle-Cell AnalysisSpleenTranscriptomeReceptors, Antigen, T-CellRNA

Identifiers

PMID30439982
PMCPMC6237323

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.