Computational methods for modeling lineage-specific gene regulation

描述（由申请人提供）：复杂的感觉和信号传导途径最终以相互作用的调节RNA和蛋白质的复合物的形式聚集在DNA上，所述调节RNA和蛋白质结合特异性基因近端和远端调节元件以激活和抑制基因，从而建立和维持细胞类型特异性转录应答。这些调控元件具有静态和动态组分-前者在基因组序列本身中编码为转录因子结合位点序列基序的组合，后者是基因座和细胞类型特异性染色质可及性和表观基因组修饰以及远端调控元件与靶基因的动态连接的结果。此外，转录和转录后反馈和调控水平的调节 蛋白质和RNA也在动态细胞类型特异性基因调节中起关键作用。现代基因组学的核心挑战之一是了解基因组和表观基因组编码调控信息的规则。一个单一的基因组序列是如何在不同的时间点为不同类型的细胞编码精确而又高度独特的基因调控程序的？在任何特定条件下，决定任何给定DNA序列功能的关键序列决定因素和语法规则是什么？在这个项目中，我们试图使用来自路线图表观基因组学项目和ENCODE项目的公共数据，以在这些问题上取得进展。我们建议建立方法来解释共享和独特的监管功能，特别是包括转录因子结合，在相关的细胞类型。与此同时，我们将实施新的方法来识别高分辨率，上下文特定的动态调控元件，破译其潜在的调控序列语法和学习预测，转录调控的综合模型，以破译异质性调控成分对谱系特异性基因表达动态的影响，并为大量的策划和疾病相关基因集提供监管注释。

DESCRIPTION (provided by applicant): Complex sensory and signaling pathways ultimately converge on the DNA in the form of complexes of interacting regulatory RNAs and proteins that bind specific gene-proximal and distal regulatory elements to active and repress genes resulting in the establishment and maintenance of cell-type specific transcriptional responses. These regulatory elements have static and dynamic components - the former encoded in the genomic sequence itself as combinations of transcription factor binding site sequence motifs and the latter a consequence of locus and cell-type specific chromatin accessibility and epigenomic modifications as well as the dynamic linking of distal regulatory elements to target genes. In addition, transcriptional and post-transcriptional feedback and control of the levels of regulatory proteins and RNAs also play a key role in dynamic cell-type specific gene regulation. One of the central challenges in modern genomics is to learn these rules by which the genome and epigenome encode regulatory information. How does a single genome sequence encode the information for exquisitely precise, and yet highly distinctive programs of gene regulation for different cell types, and at different time points? What are the key sequence determinants, and grammatical rules that determine the function of any given DNA sequence under any particular set of conditions? In this project we seek to use public data from The Roadmap Epigenomics project and The ENCODE project to make progress on these questions. We propose to build methods for interpreting shared and distinctive regulatory features, including especially transcription factor binding, across related cell types. In parallel, we will implement novel methods for identifying high-resolution, context-specific dynamic regulatory elements, decipher their underlying regulatory sequence grammars and learn predictive, integrative models of transcriptional regulation to decipher the effects of heterogeneous regulatory components on lineage-specific gene expression dynamics and provide regulatory annotations for large collections of curated and disease-associated gene sets.