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Integrated analysis of a compendium of RNA-Seq datasets for splicing factors

A vast amount of public RNA-sequencing datasets have been generated and used widely to study transcriptome mechanisms. These data offer precious opportunity for advancing biological research in transcriptome studies such as alternative splicing. We report the first large-scale integrated analysis of...

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Autores principales: Yu, Peng, Li, Jin, Deng, Su-Ping, Zhang, Feiran, Grozdanov, Petar N., Chin, Eunice W. M., Martin, Sheree D., Vergnes, Laurent, Islam, M. Saharul, Sun, Deqiang, LaSalle, Janine M., McGee, Sean L., Goh, Eyleen, MacDonald, Clinton C., Jin, Peng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7297722/
https://www.ncbi.nlm.nih.gov/pubmed/32546682
http://dx.doi.org/10.1038/s41597-020-0514-7
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author Yu, Peng
Li, Jin
Deng, Su-Ping
Zhang, Feiran
Grozdanov, Petar N.
Chin, Eunice W. M.
Martin, Sheree D.
Vergnes, Laurent
Islam, M. Saharul
Sun, Deqiang
LaSalle, Janine M.
McGee, Sean L.
Goh, Eyleen
MacDonald, Clinton C.
Jin, Peng
author_facet Yu, Peng
Li, Jin
Deng, Su-Ping
Zhang, Feiran
Grozdanov, Petar N.
Chin, Eunice W. M.
Martin, Sheree D.
Vergnes, Laurent
Islam, M. Saharul
Sun, Deqiang
LaSalle, Janine M.
McGee, Sean L.
Goh, Eyleen
MacDonald, Clinton C.
Jin, Peng
author_sort Yu, Peng
collection PubMed
description A vast amount of public RNA-sequencing datasets have been generated and used widely to study transcriptome mechanisms. These data offer precious opportunity for advancing biological research in transcriptome studies such as alternative splicing. We report the first large-scale integrated analysis of RNA-Seq data of splicing factors for systematically identifying key factors in diseases and biological processes. We analyzed 1,321 RNA-Seq libraries of various mouse tissues and cell lines, comprising more than 6.6 TB sequences from 75 independent studies that experimentally manipulated 56 splicing factors. Using these data, RNA splicing signatures and gene expression signatures were computed, and signature comparison analysis identified a list of key splicing factors in Rett syndrome and cold-induced thermogenesis. We show that cold-induced RNA-binding proteins rescue the neurite outgrowth defects in Rett syndrome using neuronal morphology analysis, and we also reveal that SRSF1 and PTBP1 are required for energy expenditure in adipocytes using metabolic flux analysis. Our study provides an integrated analysis for identifying key factors in diseases and biological processes and highlights the importance of public data resources for identifying hypotheses for experimental testing.
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spelling pubmed-72977222020-06-19 Integrated analysis of a compendium of RNA-Seq datasets for splicing factors Yu, Peng Li, Jin Deng, Su-Ping Zhang, Feiran Grozdanov, Petar N. Chin, Eunice W. M. Martin, Sheree D. Vergnes, Laurent Islam, M. Saharul Sun, Deqiang LaSalle, Janine M. McGee, Sean L. Goh, Eyleen MacDonald, Clinton C. Jin, Peng Sci Data Analysis A vast amount of public RNA-sequencing datasets have been generated and used widely to study transcriptome mechanisms. These data offer precious opportunity for advancing biological research in transcriptome studies such as alternative splicing. We report the first large-scale integrated analysis of RNA-Seq data of splicing factors for systematically identifying key factors in diseases and biological processes. We analyzed 1,321 RNA-Seq libraries of various mouse tissues and cell lines, comprising more than 6.6 TB sequences from 75 independent studies that experimentally manipulated 56 splicing factors. Using these data, RNA splicing signatures and gene expression signatures were computed, and signature comparison analysis identified a list of key splicing factors in Rett syndrome and cold-induced thermogenesis. We show that cold-induced RNA-binding proteins rescue the neurite outgrowth defects in Rett syndrome using neuronal morphology analysis, and we also reveal that SRSF1 and PTBP1 are required for energy expenditure in adipocytes using metabolic flux analysis. Our study provides an integrated analysis for identifying key factors in diseases and biological processes and highlights the importance of public data resources for identifying hypotheses for experimental testing. Nature Publishing Group UK 2020-06-16 /pmc/articles/PMC7297722/ /pubmed/32546682 http://dx.doi.org/10.1038/s41597-020-0514-7 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Analysis
Yu, Peng
Li, Jin
Deng, Su-Ping
Zhang, Feiran
Grozdanov, Petar N.
Chin, Eunice W. M.
Martin, Sheree D.
Vergnes, Laurent
Islam, M. Saharul
Sun, Deqiang
LaSalle, Janine M.
McGee, Sean L.
Goh, Eyleen
MacDonald, Clinton C.
Jin, Peng
Integrated analysis of a compendium of RNA-Seq datasets for splicing factors
title Integrated analysis of a compendium of RNA-Seq datasets for splicing factors
title_full Integrated analysis of a compendium of RNA-Seq datasets for splicing factors
title_fullStr Integrated analysis of a compendium of RNA-Seq datasets for splicing factors
title_full_unstemmed Integrated analysis of a compendium of RNA-Seq datasets for splicing factors
title_short Integrated analysis of a compendium of RNA-Seq datasets for splicing factors
title_sort integrated analysis of a compendium of rna-seq datasets for splicing factors
topic Analysis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7297722/
https://www.ncbi.nlm.nih.gov/pubmed/32546682
http://dx.doi.org/10.1038/s41597-020-0514-7
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