A Block Mixture Model To Map Eqtls For Gene Clustering

Open Access
Author:
Wang, Ningtao
Graduate Program:
Statistics
Degree:
Doctor of Philosophy
Document Type:
Dissertation
Date of Defense:
June 05, 2015
Committee Members:
  • Rongling Wu, Dissertation Advisor
  • Runze Li, Dissertation Advisor
  • Lingzhou Xue, Committee Member
  • John Edward Carlson, Committee Member
Keywords:
  • block mixture model
  • eQTL
  • gene cluster
Abstract:
To study how genes function in a cellular and physiological process, a general procedure is to classify gene expression profiles into categories based on their similarity and reconstruct a regulatory network for functional elements. However, genetic mechanisms that underlie the organization of gene clusters and networks remain unexplored, despite a considerable body of efforts made to map expression quantitative trait loci (eQTLs) that affect the expression of individual genes. Here we address this issue by developing a block mixture based approach that integrates gene clustering and reconstruction with genetic mapping into a unifying framework. The approach can not only identify specific eQTLs that control how genes are clustered and organized toward biological functions, but also enable the investigation of the biological mechanisms how eQTLs perturb in a signaling pathway. We applied the approach to characterize the effects of eQTLs on the structure and organization of gene clusters, and extended it aiming at specific characteristics of different eQTL studies. These studies provide the first characterization, to our knowledge, of the effects of genetic variants on the regulatory network of gene expression. Moreover, the approach developed can facilitate the genetic dissection of other dynamic processes, including development, physiology and disease progression in any organisms.