An updated object oriented bovine QTL viewer and genome-wide bovine meta-analysis

• Main Author: Salih, Hanni
• Other Authors: Adelson, David
• Format: Others
• Language: en_US
• Published: 2010
• Subjects: Bovine; Genome-Wide; QTL
• Online Access: http://hdl.handle.net/1969.1/ETD-TAMU-2969; http://hdl.handle.net/1969.1/ETD-TAMU-2969

Waves of bovine genomic data have been produced as a result of the bovine genome sequencing projects. In addition to the massive amounts of genomic sequence, significant annotation including single nucleotide polymorphisms, sequence tagged sites and haplotype blocks have been produced by the Bovine HapMap Project. Furthermore, many agriculturally significant traits in cattle such as milk yield and carcass weight are measured on a quantitative scale and have been genetically mapped as quantitative trait loci (QTL). QTL data can be used to generate another form of bovine annotation linking phenotype to genotype. However, it is impossible for humans to be able to analyze genomic scale data without computer based tools. Bioinformatic tools have been shown to greatly increase productivity and improve efficiency when dealing with large data sets. My dissertation presents an integrated, extensible database that houses SNPs, STSs, haplotypes, and QTL. The database is presented to researchers through a restructured, object oriented Bovine QTL Viewer that displays multiple levels of bovine annotation synergistically. Evaluation of use of the viewer was performed using a survey based approach and measured quantitatively. In addition, the QTL data from the database was used to analyze the frequency of gene ontology (GO) annotations within QTL regions. QTL regions were divided into 8 trait based groups. GO terms were counted within each category of QTL and in non- QTL regions of the genome. Top level GO term frequencies were generated from the counts and these frequencies were compared between QTL and non-QTL portions of the genome. Furthermore, specific sets of GO terms believed to be related to QTL categories were also used to determine if QTL regions were enriched for genes annotated with such GO terms. As a result, we determined that gene density varied significantly across QTL regions and that many QTL categories showed GO term frequency differences that could be related to the trait’s biology. Furthermore, our selected GO term sets were shown to be significantly enriched in some QTL categories.