Deep RNA sequencing and proteomic analysis of a hybrid mouse diversity panel

描述(由申请人提供)： 这个项目将以高分辨率绘制产生明确的临床表型的遗传途径。我们将利用杂交小鼠多样性小组(HMDP)的力量，结合大规模RNA测序和蛋白质组学，追踪从DNA到RNA再到蛋白质的相互联系，并提供有关产生医学相关特征的分层信息。HMDP由100个自交系和重组自交系组成。该小组具有广泛的减数分裂断裂点，并已通过超过140,000个单核苷酸多态(SNPs)进行了密集的基因分型，从而可以非常精细地定位数量性状基因座(QTL)。此外，HMDP在遗传上是稳定的和可再生的，可以检测多种表型，产生累积的生物学信息。我们将扩展我们以前基于HMDP的代谢和行为障碍的研究，增加大规模RNA测序(RNA-Seq)和蛋白质组学来详细说明蛋白质表达的基因控制。我们的方法提供了定位已知途径以及变异的RNA和蛋白质物种的基因座的明显优势。(1)我们将在肝脏组织和海马区组织上进行RNA-SEQ，以阐明代谢性疾病，并研究学习和记忆的变化。(2)对大鼠海马区蛋白质组进行质谱分析。(我们关于肝脏蛋白质组学的数据已经发表。)(3)将使用强大的统计工具对组合数据集进行分析，以了解转录本和蛋白质表达的遗传调节。这些研究将绘制临床特征的遗传网络和组织间调控路径图，并提出新的、高度特异的治疗策略。

DESCRIPTION (provided by applicant): This project will chart with high-resolution the genetic pathways that give rise to defined clinica phenotypes. We will utilize the power of the hybrid mouse diversity panel (HMDP), combined with massive-scale RNA sequencing and proteomics, to trace the interconnections from DNA to RNA to protein and provide layered information on the production of medically relevant traits. The HMDP consists of 100 inbred and recombinant inbred strains. The panel has a wide array of meiotic breakpoints and has been densely genotyped with more than 140,000 single nucleotide polymorphisms (SNPs), allowing very fine mapping of quantitative trait loci (QTLs). In addition, the HMDP is genetically stable and renewable and can be assayed for multiple phenotypes, yielding cumulative biological information. We will expand our previous HMDP-based studies of metabolic and behavioral disorders, adding massive-scale RNA sequencing (RNA-Seq) and proteomics to detail genetic control of protein expression. Our approach offers the distinct advantage of mapping loci for known pathways as well as variant RNA and protein species. The following aims are proposed: (1) We will perform RNA-Seq on liver tissue to illuminate metabolic disease and on hippocampal tissue to investigate variations in learning and memory. (2) We will perform mass spectrometry to survey the proteome of the hippocampus. (Our data on liver proteomics has already been published.) (3) The combined datasets will be analyzed with powerful statistical tools to understand the genetic regulation of transcript and protein expression. These studies will map genetic networks and inter-tissue regulatory pathways for clinical traits and suggest new, highly specific therapeutic strategies.