Genotype-Tissue-Protein: proteomic variation and quantitative trait loci (pQTL)

基因型-组织-蛋白质：蛋白质组变异和数量性状位点 (pQTL)

• 批准号: 8643009
• 负责人: MICHAEL P. SNYDER
• 金额: $ 147.56万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-04-24 至 2017-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8643009
• 关键词: Amino Acid Sequence; Area; Biological Markers; Biomedical Research; Brain; Cataloging; Catalogs; Cells; Communities; Complex; DNA; Data; Dimensions; Disease; Disease Association; Disease susceptibility; Gene Expression; Gene Expression Profile; Genetic; Genetic Transcription; Genetic Variation; Genome; Genotype; Goals; Health; Heart; Human; Human Biology; Human Genetics; Human Genome; Individual; Intervention; Link; Liver; Location; Lung; Maps; Mass Spectrum Analysis; Measures; Molecular; Molecular Biology; Outcome; Pancreas; Peptide Sequence Determination; Peptides; Phenotype; Prevention strategy; Protein Databases; Protein Isoforms; Proteins; Proteome; Proteomics; Quantitative Trait Loci; RNA; RNA Splicing; Regulation; Research; Resources; Site; Source; Surveys; Time; Tissue Donors; Tissues; Transcriptional Regulation; Translating; Translations; Variant; Work; base; biological research; design; disorder risk; experience; frontal lobe; genetic variant; genome annotation; genome wide association study; human tissue; improved; mRNA Transcript Degradation; molecular phenotype; programs; research study; trait; transcriptome sequencing

Abstract The goals of the proposed research are to systematically characterize proteomic variation in multiple human tissues and improve the annotation of the human genome. The mapping of gene expression quantitative traits (eQTL) using microarray or RNA-seq has provided a rich source of information for human biology and for interpreting genotype-disease association findings from genome-wide association studies (GWAS). In contrast, much less work has examined variation in protein sequence and abundance, and the genetic basis of proteomic variation remains largely unexplored. The objective of this research is to quantify the abundance of proteins and to catalog protein variants in at least five human tissues using an advanced quantitative mass-spectrometry-based platform. The three Specific Aims are to (1) Quantitatively measure protein abundance in 100 individuals across five tissues, (2) Characterize variation and functionally annotate the tissue-specific human translatome; and (3) Map genetic variation that influences protein abundance (pQTL). Mass spectrometry data will be used to verify previously predicted intergenic and intronic regions that encode protein, and to better annotate the translated region of the human genome. By preferentially selecting multi-tissue donors, this project maximizes the utilization of the GTEx resource and provides a unique opportunity for quantifying protein diversity and variation between individuals and across tissues. Proteomic variation represents a molecular phenotype downstream of RNA expression and may provide a critical link between RNA expression and phenotypes. We expect that the pQTL mapping analysis may capture post-transcriptional regulatory mechanisms that are not captured in eQTL mapping studies. Together, the new data generated in this research will have an important positive impact on biological and biomedical research, because they offer important clues for interpreting genotype-phenotype correlation identified through genome-wide association studies. They will also validate the annotation of the human transcriptome with regards to location of translation start sites, splice isoform diversity and heteroallele and editing expression. They will provide a rich resource for the human genome community. Ultimately, we expect the ensemble of molecular phenotypes and annotation will improve our ability for predicting an individual's disease susceptibility, as well as contribute to the design of individualized prevention and intervention strategies.

摘要 该研究的目的是系统地描述多个人类基因组中蛋白质组的变异， 组织和改善人类基因组的注释。基因表达定量作图 使用微阵列或RNA-seq的eQTL（eQTL）已经为人类生物学提供了丰富的信息来源， 用于解释全基因组关联研究（GWAS）的基因型-疾病关联结果。在 相比之下，研究蛋白质序列和丰度变化以及遗传基础的工作要少得多 蛋白质组学变异的研究还很不深入。本研究的目的是量化 丰富的蛋白质，并使用先进的 基于定量质谱的平台。三个具体目标是：（1）定量测量 在100个个体的五种组织中的蛋白质丰度，（2）表征变异和功能 注释组织特异性人类翻译组;和（3）绘制影响蛋白质的遗传变异图 丰度（pQTL）。质谱数据将用于验证先前预测的基因间和 编码蛋白质的内含子区域，并更好地注释人类基因组的翻译区。通过 优先选择多组织供体，该项目最大限度地利用了GTEx资源， 提供了一个独特的机会，量化蛋白质的多样性和变异之间的个人和跨 组织中蛋白质组变异代表RNA表达下游的分子表型， 提供了RNA表达和表型之间的关键联系。我们希望pQTL定位分析 可以捕获在eQTL定位研究中未捕获的转录后调控机制。 总之，这项研究产生的新数据将对生物学和医学产生重要的积极影响。 生物医学研究，因为它们为解释基因型-表型相关性提供了重要线索 通过全基因组关联研究确定。他们还将验证人类的注释 转录组的翻译起始位点的位置，剪接异构体多样性和异等位基因， 编辑表达式。它们将为人类基因组界提供丰富的资源。最终我们 预期分子表型和注释的集合将提高我们预测一个 个人的疾病易感性，并有助于设计个性化的预防和 干预策略。