ABI Innovation: Computational Methods to Study Gene Transcription Initiation Patterns

该项目旨在开发计算方法和工具，以发现基因转录起始机制如何变化，以及它们对基因转录调控的功能影响。基因转录调控是指细胞调控其基因表达的任何过程。基因的适当调控表达对于确保生物过程准确进行至关重要，因为基因有助于发育、增殖、程序性细胞死亡（凋亡）、衰老和分化。当mRNA分子开始合成时，基因表达就开始了。为了理解基因表达的调控，必须发现不同条件下的转录起始机制，以及这些不同的机制如何导致不同的结果或表型。细胞中合成的完整RNA集的高通量测序已经产生了大数据集，但匹配大规模计算研究，以了解表型相关的转录起始机制仍处于早期阶段。该项目将研究转录起始和基因调控，目标是生成计算算法，捕获选择基因转录起始位点的规则和条件;然后将算法转换为软件工具。这些工具将作为开源软件包向科学界和感兴趣的公众免费提供。该研究将以预计将对各级教育产生重大影响的方式进行交流：它将被纳入面向研究生，本科生和K-12教育的讲座，实验室和研究机会。还将通过免费分发的计算工具和各种网络传播方式，向研究界和公众传播研究成果，以增进科学认识。此外，针对妇女和女孩的辅导和外联工作将有助于吸引更多妇女参与跨学科科学的研究经验。理解基因转录起始的潜在机制和功能后果对于理解基因调控是重要的。该项目旨在创建一套计算算法和统计方法，以发现转录起始和基因调控机制之间的关联，从而促进我们对基因转录调控的理解。通过大规模高通量转录组学、基因组学和表观基因组学数据集成，先进的基于图论的算法和基因转录起始和调控的概率模型有望揭示各种转录起始机制及其在基因转录调控和表型形成中的功能作用。该研究不仅有望促进对全球基因调控和表型发展的科学理解，而且还将激发人们在信息学研究领域开发和推进高效计算建模和数据集成方法的兴趣。研究信息和产品将通过项目网站（http：//hulab.ucf.edu/research/projects/TransInitiation/）提供。

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/).