Deep learning of the splicing (epi) genetic code reveals a novel candidate mechanism linking histone modifications to ESC fate decision

doi:10.1093/nar/gkx870

NWIPB OpenIR

	Deep learning of the splicing (epi) genetic code reveals a novel candidate mechanism linking histone modifications to ESC fate decision
	Xu, Yungang 1,2; Wang, Yongcui 3; Luo, Jiesi 1; Zhao, Weiling 1; Zhou, Xiaobo 1,2
	2017-12-01
发表期刊	NUCLEIC ACIDS RESEARCH
ISSN	0305-1048
卷号	45 期号:21 页码:12100-12112
文章类型	Article
摘要	Alternative splicing (AS) is a genetically and epigenetically regulated pre-mRNA processing to increase transcriptome and proteome diversity. Comprehensively decoding these regulatory mechanisms holds promise in getting deeper insights into a variety of biological contexts involving in AS, such as development and diseases. We assembled splicing (epi) genetic code, DeepCode, for human embryonic stem cell (hESC) differentiation by integrating heterogeneous features of genomic sequences, 16 histone modifications with a multi-label deep neural network. With the advantages of epigenetic features, DeepCode significantly improves the performance in predicting the splicing patterns and their changes during hESC differentiation. Meanwhile, DeepCode reveals the superiority of epigenomic features and their dominant roles in decoding AS patterns, highlighting the necessity of including the epigenetic properties when assembling a more comprehensive splicing code. Moreover, DeepCode allows the robust predictions across cell lineages and datasets. Especially, we identified a putative H3K36me3-regulated AS event leading to a nonsense-mediated mRNA decay of BARD1. Reduced BARD1 expression results in the attenuation of ATM/ATR signalling activities and further the hESC differentiation. These results suggest a novel candidate mechanism linking histone modifications to hESC fate decision. In addition, when trained in different contexts, DeepCode can be expanded to a variety of biological and biomedical fields.
WOS标题词	Science & Technology ; Life Sciences & Biomedicine
DOI	10.1093/nar/gkx870
关键词[WOS]	EMBRYONIC STEM-CELLS ; TRANSCRIPTION FACTOR-BINDING ; NEURAL-NETWORKS ; INTEGRATIVE ANALYSIS ; SPEECH RECOGNITION ; RNA ; GENOME ; PROTEINS ; DNA ; RECRUITMENT
收录类别	SCI
语种	英语
项目资助者	National Institutes of Health(AR069395 ; 1R01GM123037 ; 1U01CA166886)
WOS研究方向	Biochemistry & Molecular Biology
WOS类目	Biochemistry & Molecular Biology
WOS记录号	WOS:000417691300011
出版者	OXFORD UNIV PRESS
引用统计	被引频次：56[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://210.75.249.4/handle/363003/23760
专题	中国科学院西北高原生物研究所
通讯作者	Zhou, Xiaobo
作者单位	1.Univ Texas Hlth Sci Ctr Houston, Sch Biomed Bioinformat, Ctr Syst Med, Houston, TX 77030 USA 2.Wake Forest Sch Med, Ctr Bioinformat & Syst Biol, Winston Salem, NC 27157 USA 3.Chinese Acad Sci, Northwest Inst Plateau Biol, Key Lab Adaptat & Evolut Plateau Biota, Xining 810008, Qinghai, Peoples R China
推荐引用方式 GB/T 7714	Xu, Yungang,Wang, Yongcui,Luo, Jiesi,et al. Deep learning of the splicing (epi) genetic code reveals a novel candidate mechanism linking histone modifications to ESC fate decision[J]. NUCLEIC ACIDS RESEARCH,2017,45(21):12100-12112.
APA	Xu, Yungang,Wang, Yongcui,Luo, Jiesi,Zhao, Weiling,&Zhou, Xiaobo.(2017).Deep learning of the splicing (epi) genetic code reveals a novel candidate mechanism linking histone modifications to ESC fate decision.NUCLEIC ACIDS RESEARCH,45(21),12100-12112.
MLA	Xu, Yungang,et al."Deep learning of the splicing (epi) genetic code reveals a novel candidate mechanism linking histone modifications to ESC fate decision".NUCLEIC ACIDS RESEARCH 45.21(2017):12100-12112.