Systematically Differentiating Functions for Alternatively Spliced Isoforms through Integrating RNA-seq Data

Abstract

Integrating large-scale functional genomic data has significantly accelerated our understanding of gene functions. However, no algorithm has been developed to differentiate functions for isoforms of the same gene using high-throughput genomic data. This is because standard supervised learning requires ‘ground-truth’ functional annotations, which are lacking at the isoform level. To address this challenge, we developed a generic framework that interrogates public RNA-seq data at the transcript level to differentiate functions for alternatively spliced isoforms. For a specific function, our algorithm identifies the ‘responsible’ isoform(s) of a gene and generates classifying models at the isoform level instead of at the gene level. Through cross-validation, we demonstrated that our algorithm is effective in assigning functions to genes, especially the ones with multiple isoforms, and robust to gene expression levels and removal of homologous gene pairs. We identified genes in the mouse whose isoforms are predicted to have disparate functionalities and experimentally validated the ‘responsible’ isoforms using data from mammary tissue. With protein structure modeling and experimental evidence, we further validated the predicted isoform functional differences for the genes Cdkn2a and Anxa6. Our generic framework is the first to predict and differentiate functions for alternatively spliced isoforms, instead of genes, using genomic data. It is extendable to any base machine learner and other species with alternatively spliced isoforms, and shifts the current gene-centered function prediction to isoform-level predictions.

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.…”

Computational Inferences of the Functions of Alternative/Noncanonical Splice Isoforms Specific to HER2+/ER–/PR– Breast Cancers, a Chromosome 17 C-HPP Study

“…Hence, we used an integrated computational approach with tools for sequence alignment, 24 motif prediction, 25 structure prediction, 26 structure comparison, 27,17 and splice variant function prediction 28–30 to study the potential functions of the noncanonical splice proteins compared to those of the canonical proteins. GeneCards was used for gene level annotations (http://www.genecards.org/).…”

Quest for Missing Proteins: Update 2015 on Chromosome-Centric Human Proteome Project

“…This result is comparable to that of a previous study on the RNC-mRNA and MS data of Caco-2 cells: 52.6% of the protein entries with translation evidence were missing from the LC-MS/MS data acquired from institutions 54 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 18 commonly used in established databases. The genome-wide isoform analysis in mice has been reported 78 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Enlarging the analyzed chemical space…”