Quantitative trait locus analysis of molecular phenotypes in the GTEx cohort Pubblico

Abstract

Background: One of the main purposes of human genetic research is to understand the function of genetic variants. Expression quantitative trait loci (eQTL) analyses have been successfully carried out to identify variants that affect the expression level of their target gene. Due to computation cost, existing analyses focus on cis eQTLs, and only evaluate the variants effect on individual genes which may be affected by the excessive uncertainties and noise in the gene expression measurements.

Method: In this study, we study the impact of genetic variants on the overall expression levels of biological pathways using data from the Genotype-Tissue Expression (GTEx) consortium. We applied the GSVA and combined Z-score methods to transform the gene expression data to pathway-level expression scores. Then we utilized these scores instead of the raw expression data for QTL analysis to find the SNPs with significant association p-values, and their corresponding pathway and tissue.

Results: We found eight significant pathway/tissue pairs with genome-wide significant QTLs.: Folate Biosynthesis / Adipose Subcutaneous, Folate Biosynthesis / Muscle Skeletal, Sulfur Metabolism / Muscle Skeletal, Taste Transduction / Skin - Sun Exposed (Lower leg) for GSVA method, and Glycosaminoglycan Biosynthesis Chondroitin Sulfate / Brain Frontal Cortex BA9, Glyoxylate and Dicarboxylate Metabolism / Brain Frontal Cortex BA9, Folate Biosynthesis / Adipose Subcutaneous, Olfactory Transduction / Adrenal Gland for Z-score method.

Conclusion: Our analysis identified significant QTLs related to biological pathways in multiple tissues. Many of these QTLs are located in the coding regions of the gnome. These findings may help us to better understand the biological functions of genes, pathways and their connections with genetic variants.

Keywords: Pathway, Expression quantitative trait loci, Single Nucleotide Polymorphism

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School	Rollins School of Public Health
Department	Biostatistics
Subfield / Discipline	Biostatistics - MPH & MSPH
Degree	M.S.P.H.
Submission	Master's Thesis
Language	English
Research Field	Statistics
Parola chiave	Pathway, Expression quantitative trait loci, Single Nucleotide Polymorphism
Committee Chair / Thesis Advisor	Zhaohui Qin, Emory University
Committee Members	Xiangqin Cui, Emory University

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