title: High-resolution functional annotation of human transcriptome: predicting isoform functions by a novel multiple instance-based label propagation method.
abstract: Alternative transcript processing is an important mechanism for generating functional diversity in genes. However, little is known about the precise functions of individual isoforms. In fact, proteins (translated from transcript isoforms), not genes, are the function carriers. By integrating multiple human RNA-seq data sets, we carried out the first systematic prediction of isoform functions, enabling high-resolution functional annotation of human transcriptome. Unlike gene function prediction, isoform function prediction faces a unique challenge: the lack of the training data--all known functional annotations are at the gene level. To address this challenge, we modelled the gene-isoform relationships as multiple instance data and developed a novel label propagation method to predict functions. Our method achieved an average area under the receiver operating characteristic curve of 0.67 and assigned functions to 15 572 isoforms. Interestingly, we observed that different functions have different sensitivities to alternative isoform processing, and that the function diversity of isoforms from the same gene is positively correlated with their tissue expression diversity. Finally, we surveyed the literature to validate our predictions for a number of apoptotic genes. Strikingly, for the famous 'TP53' gene, we not only accurately identified the apoptosis regulation function of its five isoforms, but also correctly predicted the precise direction of the regulation.
authors.affiliation: Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA, Institute of Genomics and Bioinformatics, National Chung Hsing University, Taiwan 40227, Republic of China, National Center for Mathematics and Interdisciplinary Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China and Department of Computer Science, University of Southern California, Los Angeles, CA 90089, USA.
authors.forename: Wenyuan
authors.initials: W
authors.lastname: Li
authors.forename: Shuli
authors.initials: S
authors.lastname: Kang
authors.forename: Chun-Chi
authors.initials: CC
authors.lastname: Liu
authors.forename: Shihua
authors.initials: S
authors.lastname: Zhang
authors.forename: Yi
authors.initials: Y
authors.lastname: Shi
authors.forename: Yan
authors.initials: Y
authors.lastname: Liu
authors.forename: Xianghong Jasmine
authors.initials: XJ
authors.lastname: Zhou
mesh_terms: D017209:Apoptosis; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D006801:Humans; D058977:Molecular Sequence Annotation; D020033:Protein Isoforms / Q000235:genetics / Q000378:metabolism / Q000502:physiology*; D059368:RNA Isoforms / Q000378:metabolism; D017423:Sequence Analysis, RNA
chemical_list: D020033:Protein Isoforms; D059368:RNA Isoforms