Computational tools and resources to study alternative splicing and mRNA isoform variation

点击翻译按钮获取中文摘要

PROJECT SUMMARY The central objective of this project is to develop broadly applicable computational tools and resources for studying pre-mRNA alternative splicing (AS) and mRNA isoform variation. AS is a prevalent mechanism for generating regulatory and functional diversity. Almost all multi-exon genes in mammalian genomes undergo AS, resulting in mRNAs that vary in their exon composition. Widespread changes in AS occur in development, cell differentiation, and disease. However, many questions remain about the patterns, regulation, and functions of AS. Rapid accumulation of large-scale RNA-seq data in public repositories, emergence of new long-read sequencing strategies for transcriptome analysis, and recent advances in deep learning techniques create exciting opportunities for omics and big data approaches to uncover new regulatory and functional features of AS. To make full use of these powerful datasets and technologies, new computational tools are urgently needed. Our lab has an outstanding track record in developing and disseminating widely adopted algorithms and computational tools for characterizing AS and mRNA isoform variation. In this R01 project, building on that expertise, we will develop new computational tools and resources to study intron retention – a still poorly understood mechanism of gene regulation in human cells – and characterize genetically regulated intron retention events in the human population (Aim 1), and to delineate AS patterns and mRNA isoform variation using long-read RNA-seq data of bulk tissues (Aim 2) and single cells (Aim 3). The resulting user-friendly, scalable tools as well as associated data resources will substantially enhance the ability of biomedical researchers to study AS and transcriptome complexity using in-house and public datasets in diverse normal and diseased contexts. All software developed in this project will be made open source and freely available to the research community. We will leverage our extensive network of expert collaborators and broad user base to enhance the development, testing, and dissemination of these computational tools. Our efforts will be integrated with our long-standing interest in the biology of AS and mRNA isoform regulation, ensuring that our work addresses important biomedical questions and serves unmet technological needs. Importantly, in each aim the development of computational tools and resources will synergize with their applications to questions about the variation, regulation, and functions of AS. Overall, we expect that our proposed R01 project will provide powerful and widely used computational tools and resources for studying AS in mammalian transcriptomes.