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

被引:5
|
作者
Yu, Peng [1 ,2 ]
Li, Jin [3 ]
Deng, Su-Ping [4 ]
Zhang, Feiran [5 ]
Grozdanov, Petar N. [6 ]
Chin, Eunice W. M. [7 ]
Martin, Sheree D. [8 ,9 ]
Vergnes, Laurent [10 ]
Islam, M. Saharul [11 ,12 ]
Sun, Deqiang [3 ]
LaSalle, Janine M. [11 ,12 ]
McGee, Sean L. [8 ,9 ]
Goh, Eyleen [7 ]
MacDonald, Clinton C. [6 ]
Jin, Peng [5 ]
机构
[1] Sichuan Univ, West China Hosp, West China Biomed Big Data Ctr, Chengdu, Peoples R China
[2] Sichuan Univ, Med Big Data Ctr, Chengdu, Peoples R China
[3] Texas A&M Univ, Coll Med, Ctr Epigenet & Dis Prevent, Inst Biosci & Technol, Houston, TX 77030 USA
[4] Suzhou Univ Sci & Technol, Sch Elect & Informat Engn, Suzhou 215009, Jiangsu, Peoples R China
[5] Emory Univ, Sch Med, Dept Human Genet, Atlanta, GA USA
[6] Texas Tech Univ, Dept Cell Biol & Biochem, Hlth Sci Ctr, Lubbock, TX 79430 USA
[7] Duke NUS Med Sch, Neurosci Acad Clin Programme, NA, Singapore, Singapore
[8] Deakin Univ, Metab Reprogramming Lab, Metab Res Unit, Sch Med, Geelong, Vic, Australia
[9] Deakin Univ, Ctr Mol & Med Res, Geelong, Vic, Australia
[10] Univ Calif Los Angeles, David Geffen Sch Med, Dept Human Genet, Los Angeles, CA 90095 USA
[11] Univ Calif Davis, Dept Med Microbiol & Immunol, Genome Ctr, Davis, CA 95616 USA
[12] Univ Calif Davis, MIND Inst, Davis, CA 95616 USA
基金
美国国家卫生研究院;
关键词
ARGININE METHYLTRANSFERASE; GENE-EXPRESSION; BROWN; TRANSCRIPTION; DYSFUNCTION; STRESS; MECP2;
D O I
10.1038/s41597-020-0514-7
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页数:16
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