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: 9062502
• 负责人: MICHAEL P. SNYDER
• 金额: $ 80万
• 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 2018-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9062502
• 关键词: Amino Acid Sequence; Area; Biological Markers; Biomedical Research; Brain; Cataloging; Catalogs; Cells; Communities; Complex; DNA; Data; Dimensions; Disease; Disease susceptibility; Gene Expression; 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; individualized prevention; mRNA Transcript Degradation; molecular phenotype; programs; research study; trait; transcriptome; transcriptome sequencing

DESCRIPTION (provided by applicant): 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.

描述（由申请人提供）：拟议研究的目标是系统地表征多个人体组织中的蛋白质组变异并改进人类基因组的注释。使用微阵列或 RNA-seq 绘制基因表达数量性状 (eQTL) 为人类生物学和解释全基因组关联研究 (GWAS) 的基因型与疾病关联研究结果提供了丰富的信息来源。相比之下，检查蛋白质序列和丰度变异的工作要少得多，并且蛋白质组变异的遗传基础在很大程度上仍未被探索。这项研究的目的是量化蛋白质的丰度并对蛋白质变体进行分类 使用先进的定量质谱平台对至少五种人体组织进行检测。三个具体目标是 (1) 定量测量 5 个组织中 100 个个体的蛋白质丰度，(2) 表征变异并对组织特异性人类翻译组进行功能注释； (3) 绘制影响蛋白质丰度 (pQTL) 的遗传变异图。质谱数据将用于验证先前预测的编码蛋白质的基因间和内含子区域，并更好地注释人类基因组的翻译区域。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，并为量化个体之间和组织之间的蛋白质多样性和变异提供了独特的机会。蛋白质组变异代表 RNA 表达下游的分子表型，并可能提供 RNA 表达和表型之间的关键联系。我们期望 pQTL 作图分析可以捕获 eQTL 作图研究中未捕获的转录后调控机制。总之，这项研究产生的新数据将对生物学和生物医学研究产生重要的积极影响，因为它们为解释通过全基因组关联研究确定的基因型-表型相关性提供了重要线索。他们还将验证人类转录组在翻译起始位点位置、剪接异构体多样性、异等位基因和编辑表达方面的注释。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个体疾病易感性的能力，并有助于设计个体化的预防和干预策略。