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.

抽象的 拟议研究的目标是系统地表征多个人类的蛋白质组变异 组织并改善人类基因组的注释。基因表达定量图谱 使用微阵列或RNA-seq的性状（eQTL）为人类生物学和 用于解释全基因组关联研究 (GWAS) 中的基因型-疾病关联结果。在 相比之下，检查蛋白质序列和丰度变化以及遗传基础的工作要少得多 蛋白质组变异的大部分仍未被探索。本研究的目的是量化 丰富的蛋白质，并使用先进的方法对至少五种人体组织中的蛋白质变体进行分类 基于定量质谱的平台。三个具体目标是 (1) 定量测量 五个组织中 100 个个体的蛋白质丰度，(2) 表征变异和功能 注释组织特异性人类翻译组； (3) 绘制影响蛋白质的遗传变异图谱 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域。经过 该项目优先选择多组织供体，最大限度地利用GTEx资源， 为量化个体之间和跨群体之间的蛋白质多样性和变异提供了独特的机会 组织。蛋白质组变异代表 RNA 表达下游的分子表型，可能 提供 RNA 表达和表型之间的关键联系。我们期望 pQTL 作图分析 可能捕获 eQTL 作图研究中未捕获的转录后调控机制。 总之，这项研究中产生的新数据将对生物学和生物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 转录组与翻译起始位点的位置、剪接异构体多样性和异等位基因有关 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 期望分子表型和注释的集合将提高我们预测的能力 个体的疾病易感性，也有助于设计个体化的预防和治疗 干预策略。