Project description:Numerous genome-wide screens for polymorphisms that influence gene expression have provided key insights into the genetic control of transcription. Despite this work, the relevance of specific polymorphisms to in vivo expression and splicing remains unclear. We carried out the first genome-wide screen, to our knowledge, for SNPs that associate with alternative splicing and gene expression in human primary cells, evaluating 93 autopsy-collected cortical brain tissue samples with no defined neuropsychiatric condition and 80 peripheral blood mononucleated cell samples collected from living healthy donors. We identified 23 high confidence associations with total expression and 80 with alternative splicing as reflected by expression levels of specific exons. Fewer than 50% of the implicated SNPs however show effects in both tissue types, reflecting strong evidence for distinct genetic control of splicing and expression in the two tissue types. The data generated here also suggest the possibility that splicing effects may be responsible for up to 13 out of 84 reported genome-wide significant associations with human traits. These results emphasize the importance of establishing a database of polymorphisms affecting splicing and expression in primary tissue types and suggest that splicing effects may be of more phenotypic significance than overall gene expression changes. We evaluated 93 autopsy-collected cortical brain tissue samples with no defined neuropsychiatric condition and 80 peripheral blood mononucleated cell samples collected from living healthy donors. Affymetrix Human ST 1.0 exon arrays were used to assess exon and transcript expression levels for all samples used in the study. Replicate analyses were not performed. Exon array sample preparation from total RNA was conducted based on standard Affymetrix protocols. Data were normalized separately within PBMC and brain sets Affymetrix PLIER protocol with a sketch-quantile normalization procedure (Affymetrix Expression Console). Normalized files include brain core transcripts (NABRAINSETCOMBplier-gene-core.summary), brain all transcripts (NABRAINSETCOMBplier-gene-full.summary), brain core exons (NABRAINSETCOMBplier-exon-core.summary), brain all exons (NABRAINSETCOMBplier-exon-all.summary), PBMC core transcripts (NAPBMCfullsetplier-gene-core.summary), PBMC all transcripts (NAPBMCfullsetplier-gene-full.summary), PBMC core exons (NAPBMCfullsetplier-exon-core.summary), PBMC all exons (NAPBMCfullsetplier-exon-all.summary). all, full and core definitions are provided by Affymetrix.

Project description:Accurate and comprehensive de novo transcriptome profiling in heart is a central issue to better understand cardiac physiology and diseases. Although significant progress has been made in genome-wide profiling for quantitative changes in cardiac gene expression, current knowledge offers limited insights to the total complexity in cardiac transcriptome at individual exon level. To develop more robust bioinformatic approaches to analyze high-throughput RNA sequencing (RNA-Seq) data, with the focus on the investigation of transcriptome complexity at individual exon and transcript levels. In addition to overall gene expression analysis, the methods developed in this study were used to analyze RNA-Seq data with respect to individual transcript isoforms, novel spliced exons, novel alternative terminal exons, novel transcript clusters (i.e., novel genes) and long non-coding RNA genes. We applied these approaches to RNA-Seq data obtained from mouse hearts following pressure-overload induced by trans-aortic constriction. Based on experimental validations, analyses of the features of the identified exons/transcripts, and expression analyses including previously published RNA-Seq data, we demonstrate that the methods are highly effective in detecting and quantifying individual exons and transcripts. Novel insights inferred from the examined aspects of the cardiac transcriptome open ways to further experimental investigations. Our work provided a comprehensive set of methods to analyze mouse cardiac transcriptome complexity at individual exon and transcript levels. Applications of the methods may infer important new insights to gene regulation in normal and disease hearts in terms of exon utilization and potential involvement of novel components of cardiac transcriptome. Left ventricular tissues were collected from C57BL/6 mice after 1 week (hypertrophy stage, HY) and 8 weeks post trans-aortic constriction (TAC) procedure (heart failure stage, HF), respectively, and their corresponding Sham controls (Sham-HY, Sham-HF). To conduct RNA-Seq analysis, total RNAs from six TAC and Sham-operated mice at the HY stage and four TAC and corresponding Sham mice at the HF stage were obtained.

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Calcium-induced transcript variation in neuronal cells analyzed with exon microarrays.

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