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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 WM, Martin, Sheree D, Vergnes, Laurent, Islam, M Saharul, Sun, Deqiang, LaSalle, Janine M, Mcgee, Sean L, Goh, Eyleen, MacDonald, Clinton C and Jin, Peng 2020, Integrated analysis of a compendium of RNA-Seq datasets for splicing factors, Scientific data, vol. 7, no. 1, pp. 1-16, doi: 10.1038/s41597-020-0514-7.

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Title Integrated analysis of a compendium of RNA-Seq datasets for splicing factors
Author(s) Yu, Peng
Li, Jin
Deng, Su-Ping
Zhang, Feiran
Grozdanov, Petar N
Chin, Eunice WM
Martin, Sheree D
Vergnes, Laurent
Islam, M Saharul
Sun, Deqiang
LaSalle, Janine M
Mcgee, Sean LORCID iD for Mcgee, Sean L orcid.org/0000-0001-6953-106X
Goh, Eyleen
MacDonald, Clinton C
Jin, Peng
Journal name Scientific data
Volume number 7
Issue number 1
Article ID 178
Start page 1
End page 16
Total pages 16
Publisher Nature Publishing Group
Place of publication London, Eng.
Publication date 2020
ISSN 2052-4463
2052-4463
Keyword(s) Science & Technology
Multidisciplinary Sciences
Data integration
Data mining
Summary Abstract 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.
Language eng
DOI 10.1038/s41597-020-0514-7
Indigenous content off
HERDC Research category C1 Refereed article in a scholarly journal
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30139530

Document type: Journal Article
Collections: Faculty of Health
School of Medicine
Open Access Collection
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.