Degree Type

Dissertation

Date of Award

2018

Degree Name

Doctor of Philosophy

Department

Agronomy

Major

Genetics

First Advisor

Patrick S. Schnable

Abstract

Genome-Wide Association Study (GWAS) have been widely used to detect the QTLs based on Linkage Disequilibrium (LD) relationships between SNPs and QTLs. However, in conventional GWAS false positive results cause serious concerns. In this research, we developed three different transcriptome-based GWAS approaches which are complementary to conventional SNP-based GWAS. The ability to identify trait-associated genes in these three different methods are supported by cross-validation, transposon knockout mutants, and the analysis of a gene regulatory networks. In summary, we provide novel methods of detecting trait associated loci to further understand the complex gene regulatory systems which will benefit plants, animals, and disease treatment development in the future.

Copyright Owner

Hung-Ying Lin

Language

en

File Format

application/pdf

File Size

140 pages

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