ABI Innovation: Computational Methods to Study Gene Transcription Initiation Patterns

点击翻译按钮获取中文摘要

This project aims to develop computational methods and tools to discover how gene transcription initiation mechanisms vary, and their resulting functional consequences on gene transcriptional regulation. Gene transcriptional regulation refers to any process by which a cell regulates its genes expression. Properly regulated expression of genes is crucial for ensuring that biological processes are accurately carried out, for genes contributing to development, proliferation, programmed cell death (apoptosis), aging, and differentiation. Gene expression begins when mRNA molecules start to be synthesized, at the point on the gene where they initiate. To understand the regulation of gene expression, it is essential to discover the transcription initiation mechanisms under various conditions, and how these varied mechanisms lead to different outcomes, or phenotypes. High throughput sequencing of complete RNA sets synthesized in cells has produced large datasets, but matching large-scale computational studies, to understand phenotype-relevant transcription initiation mechanisms are still at its early stage. This project will study transcription initiation and gene regulation, with the goal of generating computational algorithms that capture the rules and conditions for selection of the transcription initiation site on a gene; the algorithms will then be converted into software tools. These tools will be released as open-source and freely available software packages to the scientific community and interested public. The research will be communicated in ways expected to have a great impact on education at many levels: it will be incorporated into lectures, labs, and research opportunities geared towards graduate, undergraduate and K-12 education. The research will also be disseminated to the research community and the public to enhance scientific understanding, through freely distributed computational tools and various modes of web dissemination. In addition, mentoring and outreach efforts targeted towards women and girls will help attract more women into engaging in research experiences in interdisciplinary science. Understanding the underlying mechanisms and functional consequences of gene transcription initiation is important to understand gene regulation. The project seeks to create a set of computational algorithms and statistical methods to discover the associations between transcription initiation and gene regulation mechanisms towards advancing our understanding of gene transcriptional regulation. The advanced graph theory-based algorithms and probabilistic models of gene transcription initiation and regulation through large-scale high-throughput transcriptomics, genomics and epigenomics data integration have the promise to unveil various transcription initiation mechanisms and their functional roles in gene transcriptional regulation and phenotype formulation. The research is expected to not only advance scientific understanding of global gene regulation and phenotype development, but also stimulate interest in developing and advancing efficient computational modeling and data integration methods in the informatics research field. The research information and products will be made available through the project website (http://hulab.ucf.edu/research/projects/TransInitiation/).