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.

Public Health Relevance

This project will produce the first large-scale multi-tissue characterization of normal proteomic variation in humans. The data generated in this project will provide a valuable resource for understanding the genetic basis of complex traits;an understanding of normal proteomic variation will also facilitate research aims to discover disease biomarkers.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project--Cooperative Agreements (U01)
Project #
3U01HG007611-01S2
Application #
8927754
Study Section
Special Emphasis Panel (ZRG1-IMST-M (50))
Program Officer
Volpi, Simona
Project Start
2014-04-24
Project End
2015-03-31
Budget Start
2014-09-22
Budget End
2015-03-31
Support Year
1
Fiscal Year
2014
Total Cost
$80,250
Indirect Cost
$30,250
Name
Stanford University
Department
Genetics
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305