PRDM9 and Meiotic Regulatory Networks

项目C PrDM9是一种多功能蛋白，在减数分裂过程中独特表达，调节减数分裂。 重组、转录和配子发生。我们知道PRDM9有能力创造 转录激活组蛋白H3K4me3染色质标记，具有潜在的抑制性KRAb和 SSXRD结构域，并与重组热点序列物理结合；但我们不知道如何 这些分子功能协同作用，实现了PrDM9‘S的多种生物学作用。 这个项目的总体目标是描绘PRDM9的S转录和转录的分子网络 H3K4三甲基转移酶活性的高通量测序，并分析这些数据在 结合其他计划项目数据构建F‘RDM9的计算系统生物学模型 功能。 在目标1中，我们将检测PRDM9依赖的基因表达变化和组蛋白H3K4me3标记 在整个减数分裂生殖细胞时间过程中的变化。我们将结合 B-Petkov项目的PRDMS-DNA结合数据及PRDMS-SET和-KRAB结构域的特征 项目D Handel的突变体，以区分PRDMS的直接和间接转录目标，并推断 可能的监管机制。 在目标2中，我们将通过检测基因来确定等位基因和剂量变异对Prdmq的影响。 从等位基因系列小鼠中分离的生殖细胞的表达和H3K4me标记图谱。我们将分析 这些数据与A Paigen和B Petkov项目对这些菌株的特征相结合 将每个等位基因与下游结果相关联，并检查等位基因干扰或显性模式。 在目标3中，我们将开发和应用统计机器学习方法来计算积分 所有计划项目数据，包括该项目的RNA-seq和Chlp-seq数据，具有高通量数据 从文献到PRDMS功能的综合模型。我们的集成模型将用于 预测新的PRDMS相互作用因子和减数分裂蛋白，并将作为生殖细胞的资源 社区通过一个公共的、在线的可视化界面。 最终，该项目将确定PRDMS转录和等位基因的时间和等位基因动态 染色质修饰作用，并将把这些数据放在PRDMS的多种功能的更广泛的上下文中 重组、减数分裂和配子发生。

PROJECT C PRDM9 is a multi-functional protein, expressed uniquely during meiosis, that regulates meiotic recombination, transcription, and gametogenesis. We know that PRDM9 has the capacity to create transcriptionally activating histone H3K4me3 chromatin marks, possesses potentially repressive KRAB and SSXRD domains, and physically binds to recombination hotspot sequences; but we do not understand how these molecular functions cooperate to achieve PRDM9's diverse biological roles. The overall goal of this project is to delineate the molecular networks of PRDM9's transcriptional and H3K4 trimethyltransferase activity through high-throughput sequencing, and to analyze these data in conjunction with other Program Project data to construct a computational systems biology model of F'RDM9 function. In Aim 1, we will determine PRDM9-dependent gene expression changes and histone H3K4me3 mark changes throughout a meiotic germ cell time course. We will analyze these data in conjunction with the PRDMS-DNA binding data of Project B Petkov and the characterization of PRDMS-SET and -KRAB domain mutants of Project D Handel, to distinguish direct from indirect transcriptional targets of PRDMS, and to infer the likely mechanisms of regulation. In Aim 2, we will determine the effects of allelic and dosage variation in PrdmQ by examining gene expression and H3K4me mark profiles from germ cells isolated from an allelic series of mice. We will analyze these data in conjunction with the characterization of these strains by Projects A Paigen and B Petkov to associate each allele with downstream outcomes and to examine allelic interference or dominance patterns. In Aim 3, we will develop and apply a statistical machine learning approach to computationally integrate all Program Project data, including the RNA-seq and ChlP-seq data of this project, with high-throughput data from the literature into a comprehensive model of PRDMS function. Our integrated model will be used to predict novel PRDMS interactors and meiotic proteins, and will serve as a resource for the germ cell community through a public, online visualization interface. Ultimately, this project will determine the temporal and allelic dynamics of PRDMS's transcriptional and chromatin modifying roles, and will place these data in the broader context of PRDMS's multiple functions in recombination, meiosis, and gametogenesis.