The emerging era of genomic data integration for analyzing splice isoform function

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. Now deep sequencing of RNA provides an unprecedented amount of expression data at the transcript level. We describe here emerging computational approaches that integrate such large-scale RNA-seq data for predicting 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.

Comparative analysis of the liver tissue transcriptomes of Mongolian and Lanzhou fat-tailed sheep

“…Computational approaches need to be developed to analyze differential expression levels in cell lineages and tissues (Huang et al, 2012;Li et al, 2014). Although measuring the concentration of mRNA is still a useful method, in order to analyze gene expression, gene coverage should be calculated.…”

Genome-wide peripheral blood transcriptome analysis of Arab female lupus and lupus nephritis

“…Despite being the hotspot area, not much is known regarding the expression spectrum of alternatively spliced genes and it role in diseases progression. Very limited studies have characterized the functional role of splice variants with majority being centered on algorithm based computational methods and RNA-seq technology (Li et al, 2014a(Li et al, , 2014bEksi et al, 2013;Wang et al, 2008). In the present study, we aimed to investigate the genome-wide peripheral blood transcriptome of Arab female lupus and LN cases compared to healthy control.…”

The Current Status and Challenges in Computational Analysis of Genomic Big Data

“…Precise measure differential expressed isoforms is also a difficult task nowadays [36]. More recently, "Single-Cell RNA-Seq" [37] was developed to measure the precise differences between transcripts in each single cell.…”