PRDM9 and Meiotic Regulatory Networks

PRDM9 和减数分裂调控网络

• 批准号: 8513497
• 负责人: Matthew Aaron Hibbs
• 金额: $ 32.53万
• 依托单位: JACKSON LABORATORY
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8513497
• 关键词: Alleles; Binding; Biological; Chromatin; Communities; Computer Simulation; DNA Binding; Data; Data Analyses; Data Sources; Development; Event; Evolution; Gametogenesis; Gene Expression; Gene Expression Profile; Genetic Recombination; Genetic Transcription; Genome; Genomics; Germ Cells; Goals; Histones; Hybrids; Imagery; Knockout Mice; Light; Literature; Machine Learning; Measures; Meiosis; Meiotic Recombination; Methyltransferase; Modeling; Molecular; Molecular Genetics; Mus; Outcome; Pattern; Proteins; Regulation; Resources; Role; Sequence Homology; Series; Site; Spermatogenesis; Sterility; Systems Biology; Techniques; Time; Transcriptional Activation; Variant; chromatin immunoprecipitation; chromatin modification; data integration; dosage; gene repression; human ZNF45 protein; mutant; novel; programs; transcriptome sequencing

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.

项目C