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Unconstrained mining of transcript data reveals increased alternative splicing complexity in the human transcriptome.

ABSTRACT: Mining massive amounts of transcript data for alternative splicing information is paramount to help understand how the maturation of RNA regulates gene expression. We developed an algorithm to cluster transcript data to annotated genes to detect unannotated splice variants. A higher number of alternatively spliced genes and isoforms were found compared to other alternative splicing databases. Comparison of human and mouse data revealed a marked increase, in human, of splice variants incorporating novel exons and retained introns. Previously unannotated exons were validated by tiling array expression data and shown to correspond preferentially to novel first exons. Retained introns were validated by tiling array and deep sequencing data. The majority of retained introns were shorter than 500 nt and had weak polypyrimidine tracts. A subset of retained introns matching small RNAs and displaying a high GC content suggests a possible coordination between splicing regulation and production of noncoding RNAs. Conservation of unannotated exons and retained introns was higher in horse, dog and cow than in rodents, and 64% of exon sequences were only found in primates. This analysis highlights previously bypassed alternative splice variants, which may be crucial to deciphering more complex pathways of gene regulation in human.

SUBMITTER: Mollet IG

PROVIDER: S-EPMC2919708 | biostudies-literature | 2010 Aug

REPOSITORIES: biostudies-literature

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Unconstrained mining of transcript data reveals increased alternative splicing complexity in the human transcriptome.

Mollet I G IG Ben-Dov Claudia C Felício-Silva Daniel D Grosso A R AR Eleutério Pedro P Alves Ruben R Staller Ray R Silva Tito Santos TS Carmo-Fonseca Maria M

Nucleic acids research 20100412 14

Mining massive amounts of transcript data for alternative splicing information is paramount to help understand how the maturation of RNA regulates gene expression. We developed an algorithm to cluster transcript data to annotated genes to detect unannotated splice variants. A higher number of alternatively spliced genes and isoforms were found compared to other alternative splicing databases. Comparison of human and mouse data revealed a marked increase, in human, of splice variants incorporatin ...[more]

PMID: 20385588

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Project description:Alternative splicing (AS) plays pivotal roles in regulating plant growth and development, flowering, biological rhythms, signal transduction, and stress responses. However, no studies on AS have been performed in Liriodendron chinense, a deciduous tree species that has high economic and ecological value. In this study, we used multiple tools and algorithms to analyze transcriptome data derived from seven tissues via hybrid sequencing. Although only 17.56% (8,503/48,408) of genes in L. chinense were alternatively spliced, these AS genes occurred in 37,844 AS events. Among these events, intron retention was the most frequent AS event, producing 1,656 PTC-containing and 3,310 non-PTC-containing transcripts. Moreover, 183 long noncoding RNAs (lncRNAs) also underwent AS events. Furthermore, weighted gene coexpression network analysis (WGCNA) revealed that there were great differences in the activities of transcription and post-transcriptional regulation between pistils and leaves, and AS had an impact on many physiological and biochemical processes in L. chinense, such as photosynthesis, sphingolipid metabolism, fatty acid biosynthesis and metabolism. Moreover, our analysis showed that the features of genes may affect AS, as AS genes and non-AS genes had differences in the exon/intron length, transcript length, and number of exons/introns. In addition, the structure of AS genes may impact the frequencies and types of AS because AS genes with more exons or introns tended to exhibit more AS events, and shorter introns tended to be retained, whereas shorter exons tended to be skipped. Furthermore, eight AS genes were verified, and the results were consistent with our analysis. Overall, this study reveals that AS and gene interaction are mutual-on one hand, AS can affect gene expression and translation, while on the other hand, the structural characteristics of the gene can also affect AS. This work is the first to comprehensively report on AS in L. chinense, and it can provide a reference for further research on AS in L. chinense.

Dataset Information

Unconstrained mining of transcript data reveals increased alternative splicing complexity in the human transcriptome.

Publications

Unconstrained mining of transcript data reveals increased alternative splicing complexity in the human transcriptome.

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