QTL global meta-analysis: are trait determining genes clustered?

Background: A key open question in biology is if genes are physically clustered with respect to their known functions or phenotypic effects. This is of particular interest for Quantitative Trait Loci (QTL) where a QTL region could contain a number of genes that contribute to the trait being measured. Results: We observed a significant increase in gene density within QTL regions compared to non-QTL regions and/or the entire bovine genome. By grouping QTL from the Bovine QTL Viewer database into 8 categories of non-redundant regions, we have been able to analyze gene density and gene function distribution, based on Gene Ontology (GO) with relation to their location within QTL regions, outside of QTL regions and across the entire bovine genome. We identified a number of GO terms that were significantly over represented within particular QTL categories. Furthermore, select GO terms expected to be associated with the QTL category based on common biological knowledge have also proved to be significantly over represented in QTL regions. Conclusion: Our analysis provides evidence of over represented GO terms in QTL regions. This increased GO term density indicates possible clustering of gene functions within QTL regions of the bovine genome. Genes with similar functions may be grouped in specific locales and could be contributing to QTL traits. Moreover, we have identified over-represented GO terminology that from a biological standpoint, makes sense with respect to QTL category type.Hanni Salih and David L Adelso

Bovine Genome Database: integrated tools for genome annotation and discovery

The Bovine Genome Database (BGD; http://BovineGenome.org) strives to improve annotation of the bovine genome and to integrate the genome sequence with other genomics data. BGD includes GBrowse genome browsers, the Apollo Annotation Editor, a quantitative trait loci (QTL) viewer, BLAST databases and gene pages. Genome browsers, available for both scaffold and chromosome coordinate systems, display the bovine Official Gene Set (OGS), RefSeq and Ensembl gene models, non-coding RNA, repeats, pseudogenes, single-nucleotide polymorphism, markers, QTL and alignments to complementary DNAs, ESTs and protein homologs. The Bovine QTL viewer is connected to the BGD Chromosome GBrowse, allowing for the identification of candidate genes underlying QTL. The Apollo Annotation Editor connects directly to the BGD Chado database to provide researchers with remote access to gene evidence in a graphical interface that allows editing and creating new gene models. Researchers may upload their annotations to the BGD server for review and integration into the subsequent release of the OGS. Gene pages display information for individual OGS gene models, including gene structure, transcript variants, functional descriptions, gene symbols, Gene Ontology terms, annotator comments and links to National Center for Biotechnology Information and Ensembl. Each gene page is linked to a wiki page to allow input from the research community

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

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

A physical map of the bovine genome

A new physical map of the bovine genome has been constructed by integrating data from genetic and radiation hybrid maps, and a new bovine BAC map, with the bovine genome draft assembly