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Meta-analysis of transcriptomic variation in T-cell populations reveals both variable and consistent signatures of gene expression and splicing

Human CD4(+) T cells are often subdivided into distinct subtypes, including Th1, Th2, Th17, and Treg cells, that are thought to carry out distinct functions in the body. Typically, these T-cell subpopulations are defined by the expression of distinct gene repertoires; however, there is variability b...

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Autores principales: Radens, Caleb M., Blake, Davia, Jewell, Paul, Barash, Yoseph, Lynch, Kristen W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7491319/
https://www.ncbi.nlm.nih.gov/pubmed/32554554
http://dx.doi.org/10.1261/rna.075929.120
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author Radens, Caleb M.
Blake, Davia
Jewell, Paul
Barash, Yoseph
Lynch, Kristen W.
author_facet Radens, Caleb M.
Blake, Davia
Jewell, Paul
Barash, Yoseph
Lynch, Kristen W.
author_sort Radens, Caleb M.
collection PubMed
description Human CD4(+) T cells are often subdivided into distinct subtypes, including Th1, Th2, Th17, and Treg cells, that are thought to carry out distinct functions in the body. Typically, these T-cell subpopulations are defined by the expression of distinct gene repertoires; however, there is variability between studies regarding the methods used for isolation and the markers used to define each T-cell subtype. Therefore, how reliably studies can be compared to one another remains an open question. Moreover, previous analysis of gene expression in CD4(+) T-cell subsets has largely focused on gene expression rather than alternative splicing. Here we take a meta-analysis approach, comparing eleven independent RNA-seq studies of human Th1, Th2, Th17, and/or Treg cells to determine the consistency in gene expression and splicing within each subtype across studies. We find that known master-regulators are consistently enriched in the appropriate subtype; however, cytokines and other genes often used as markers are more variable. Importantly, we also identify previously unknown transcriptomic markers that appear to consistently differentiate between subsets, including a few Treg-specific splicing patterns. Together this work highlights the heterogeneity in gene expression between samples designated as the same subtype, but also suggests additional markers that can be used to define functional groupings.
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spelling pubmed-74913192021-10-01 Meta-analysis of transcriptomic variation in T-cell populations reveals both variable and consistent signatures of gene expression and splicing Radens, Caleb M. Blake, Davia Jewell, Paul Barash, Yoseph Lynch, Kristen W. RNA Bioinformatic Human CD4(+) T cells are often subdivided into distinct subtypes, including Th1, Th2, Th17, and Treg cells, that are thought to carry out distinct functions in the body. Typically, these T-cell subpopulations are defined by the expression of distinct gene repertoires; however, there is variability between studies regarding the methods used for isolation and the markers used to define each T-cell subtype. Therefore, how reliably studies can be compared to one another remains an open question. Moreover, previous analysis of gene expression in CD4(+) T-cell subsets has largely focused on gene expression rather than alternative splicing. Here we take a meta-analysis approach, comparing eleven independent RNA-seq studies of human Th1, Th2, Th17, and/or Treg cells to determine the consistency in gene expression and splicing within each subtype across studies. We find that known master-regulators are consistently enriched in the appropriate subtype; however, cytokines and other genes often used as markers are more variable. Importantly, we also identify previously unknown transcriptomic markers that appear to consistently differentiate between subsets, including a few Treg-specific splicing patterns. Together this work highlights the heterogeneity in gene expression between samples designated as the same subtype, but also suggests additional markers that can be used to define functional groupings. Cold Spring Harbor Laboratory Press 2020-10 /pmc/articles/PMC7491319/ /pubmed/32554554 http://dx.doi.org/10.1261/rna.075929.120 Text en © 2020 Radens et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society http://creativecommons.org/licenses/by-nc/4.0/ This article is distributed exclusively by the RNA Society for the first 12 months after the full-issue publication date (see http://rnajournal.cshlp.org/site/misc/terms.xhtml). After 12 months, it is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Bioinformatic
Radens, Caleb M.
Blake, Davia
Jewell, Paul
Barash, Yoseph
Lynch, Kristen W.
Meta-analysis of transcriptomic variation in T-cell populations reveals both variable and consistent signatures of gene expression and splicing
title Meta-analysis of transcriptomic variation in T-cell populations reveals both variable and consistent signatures of gene expression and splicing
title_full Meta-analysis of transcriptomic variation in T-cell populations reveals both variable and consistent signatures of gene expression and splicing
title_fullStr Meta-analysis of transcriptomic variation in T-cell populations reveals both variable and consistent signatures of gene expression and splicing
title_full_unstemmed Meta-analysis of transcriptomic variation in T-cell populations reveals both variable and consistent signatures of gene expression and splicing
title_short Meta-analysis of transcriptomic variation in T-cell populations reveals both variable and consistent signatures of gene expression and splicing
title_sort meta-analysis of transcriptomic variation in t-cell populations reveals both variable and consistent signatures of gene expression and splicing
topic Bioinformatic
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7491319/
https://www.ncbi.nlm.nih.gov/pubmed/32554554
http://dx.doi.org/10.1261/rna.075929.120
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