Histone posttranslational modifications predict specific alternative exon subtypes in mammalian brain

• Published in: PLoS computational biology Vol. 13; no. 6; p. e1005602
• Main Authors: Hu, Qiwen, Kim, Eun Ji, Feng, Jian, Grant, Gregory R, Heller, Elizabeth A
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.06.2017; Public Library of Science (PLoS)
• Subjects: Alternative splicing; Animals; Bioinformatics; Biology and life sciences; Brain; Brain - physiopathology; Chromatin; Cocaine; Cocaine-Related Disorders - genetics; Computation; Computational neuroscience; Computer Simulation; Drug abuse; Drug addiction; Epigenetics; Eukaryotes; Exons - genetics; Gene expression; Gene sequencing; Genomes; Histones; Histones - genetics; Immunoprecipitation; Learning algorithms; Machine learning; Medicine; Medicine and Health Sciences; Mental disorders; Mice; Models, Genetic; Narcotics; Nerve Tissue Proteins - genetics; Neural circuitry; Neurosciences; Nuclei; Nucleus accumbens; Observations; Pharmacology; Physical Sciences; Physiological aspects; Post-translational modifications; Protein Processing, Post-Translational - genetics; Psychiatry; Reinforcement; Ribonucleic acid; RNA; RNA Splice Sites - genetics; Roles; Splicing; Statistical methods; Studies; Transcription; United States > US
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1005602

A compelling body of literature, based on next generation chromatin immunoprecipitation and RNA sequencing of reward brain regions indicates that the regulation of the epigenetic landscape likely underlies chronic drug abuse and addiction. It is now critical to develop highly innovative computational strategies to reveal the relevant regulatory transcriptional mechanisms that may underlie neuropsychiatric disease. We have analyzed chromatin regulation of alternative splicing, which is implicated in cocaine exposure in mice. Recent literature has described chromatin-regulated alternative splicing, suggesting a novel function for drug-induced neuroepigenetic remodeling. However, the extent of the genome-wide association between particular histone modifications and alternative splicing remains unexplored. To address this, we have developed novel computational approaches to model the association between alternative splicing and histone posttranslational modifications in the nucleus accumbens (NAc), a brain reward region. Using classical statistical methods and machine learning to combine ChIP-Seq and RNA-Seq data, we found that specific histone modifications are strongly associated with various aspects of differential splicing. H3K36me3 and H3K4me1 have the strongest association with splicing indicating they play a significant role in alternative splicing in brain reward tissue.