RNA sequencing of transcriptomes in human brain regions: protein-coding and non-coding RNAs, isoforms and alleles

BMC Genomics

Research Article

Rachel F. Tyndale¹  Leslie C. Newman²  Audrey C. Papp²  Samuel K. Handelman²  Amanda Curtis²  Amy Webb³  Wolfgang Sadee⁴  Maciej Pietrzak⁵  Deborah C. Mash⁶  Caryn Lerman⁷  John R. Kelsoe⁸  Grzegorz A. Rempala⁹  Michal Seweryn⁹  Erica Graziosa^1,10  Daqing Wang^1,10 

[1] Center for Addiction and Mental Health and Departments of Psychiatry and Pharmacology & Toxicology, University of Toronto, Toronto, Ontario, Canada;Center for Pharmacogenomics, College of Medicine, The Ohio State University, 43210, Columbus, OH, USA;Center for Pharmacogenomics, College of Medicine, The Ohio State University, 43210, Columbus, OH, USA;Department of Biomedical Informatics, College of Medicine, The Ohio State University, 43210, Columbus, OH, USA;Center for Pharmacogenomics, College of Medicine, The Ohio State University, 43210, Columbus, OH, USA;Departments of Pharmacology, College of Medicine; Colleges of Pharmacy and Environmental Health Sciences, The Ohio State University, Columbus, OH, USA;Departments of Psychiatry, College of Medicine; Colleges of Pharmacy and Environmental Health Sciences, The Ohio State University, Columbus, OH, USA;Departments of Human Genetics/Internal Medicine, College of Medicine; Colleges of Pharmacy and Environmental Health Sciences, The Ohio State University, 5078 Graves Hall, 333 W. 10th Avenue, 43210, Columbus, OH, USA;Center for Pharmacogenomics, College of Medicine, The Ohio State University, 43210, Columbus, OH, USA;Division of Biostatistics, College of Public Health, and Mathematical Biosciences Institute, The Ohio State University, Columbus, OH, USA;Department of Neurology, Miller School of Medicine, University of Miami, 33136, Miami, FL, USA;Department of Psychiatry, Annenberg School for Communication, and Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA;Department of Psychiatry, Laboratory of Psychiatric Genomics, University of California, San Diego, USA;VA San Diego Healthcare System, La Jolla, San Diego, CA, USA;Division of Biostatistics, College of Public Health, and Mathematical Biosciences Institute, The Ohio State University, Columbus, OH, USA;Thermo Fisher Scientific, 94080, South San Francisco, CA, USA;

关键词: RNA sequencing;    Brain regions;    Differential expression;    Allelic expression imbalance;    Isoform fraction;    Non-coding RNA;   

DOI  :  10.1186/s12864-015-2207-8

 received in 2015-02-20, accepted in 2015-11-12,  发布年份 2015

来源: Springer

【 摘 要 】

BackgroundWe used RNA sequencing to analyze transcript profiles of ten autopsy brain regions from ten subjects. RNA sequencing techniques were designed to detect both coding and non-coding RNA, splice isoform composition, and allelic expression. Brain regions were selected from five subjects with a documented history of smoking and five non-smokers. Paired-end RNA sequencing was performed on SOLiD instruments to a depth of >40 million reads, using linearly amplified, ribosomally depleted RNA. Sequencing libraries were prepared with both poly-dT and random hexamer primers to detect all RNA classes, including long non-coding (lncRNA), intronic and intergenic transcripts, and transcripts lacking poly-A tails, providing additional data not previously available. The study was designed to generate a database of the complete transcriptomes in brain region for gene network analyses and discovery of regulatory variants.ResultsOf 20,318 protein coding and 18,080 lncRNA genes annotated from GENCODE and lncipedia, 12 thousand protein coding and 2 thousand lncRNA transcripts were detectable at a conservative threshold. Of the aligned reads, 52 % were exonic, 34 % intronic and 14 % intergenic. A majority of protein coding genes (65 %) was expressed in all regions, whereas ncRNAs displayed a more restricted distribution. Profiles of RNA isoforms varied across brain regions and subjects at multiple gene loci, with neurexin 3 (NRXN3) a prominent example. Allelic RNA ratios deviating from unity were identified in > 400 genes, detectable in both protein-coding and non-coding genes, indicating the presence of cis-acting regulatory variants. Mathematical modeling was used to identify RNAs stably expressed in all brain regions (serving as potential markers for normalizing expression levels), linked to basic cellular functions. An initial analysis of differential expression analysis between smokers and nonsmokers implicated a number of genes, several previously associated with nicotine exposure.ConclusionsRNA sequencing identifies distinct and consistent differences in gene expression between brain regions, with non-coding RNA displaying greater diversity between brain regions than mRNAs. Numerous RNAs exhibit robust allele selective expression, proving a means for discovery of cis-acting regulatory factors with potential clinical relevance.

【 授权许可】

CC BY   
© Webb et al. 2015