Guan Lab

Department of Computational Medicine & Bioinformatics
Sat, 09/06/2014 - 04:06 -- gyuanfan
TitleThe emerging era of genomic data integration for analyzing splice isoform function.
Publication TypeJournal Article
Year of Publication2014
AuthorsLi H-D, Menon R, Omenn GS, Guan Y
JournalTrends Genet
Volume30
Issue8
Pagination340-347
Date Published2014 Aug
ISSN0168-9525
Abstract

The vast majority of multi-exon genes in humans undergo alternative splicing, which greatly increases the functional diversity of protein species. Predicting functions at the isoform level is essential to further our understanding of developmental abnormalities and cancers, which frequently exhibit aberrant splicing and dysregulation of isoform expression. However, determination of isoform function is very difficult, and efforts to predict isoform function have been limited in the functional genomics field. Deep sequencing of RNA now provides an unprecedented amount of expression data at the transcript level. We describe here emerging computational approaches that integrate such large-scale whole-transcriptome sequencing (RNA-seq) data for predicting the functions of alternatively spliced isoforms, and we discuss their applications in developmental and cancer biology. We outline future directions for isoform function prediction, emphasizing the need for heterogeneous genomic data integration and tissue-specific, dynamic isoform-level network modeling, which will allow the field to realize its full potential.

DOI10.1016/j.tig.2014.05.005
Alternate JournalTrends Genet.
PubMed ID24951248
PubMed Central IDPMC4112133
Grant ListR21 NS082212 / NS / NINDS NIH HHS / United States