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BMC Genomics  2009 

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

DOI: 10.1186/1471-2164-10-184

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Abstract:

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.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.Gene density has been shown to vary widely by organism and genomic region and has been measured both in terms of mean interval between genes and genes per mega base pair of DNA [1,2]. It is known that gene density is positively correlated with G+C content [2] and that the heterochromatic regions surrounding centromeres and telomeres have a lower than average gene density [3-5]. In general, measurements of gene density have focused on correlations of gene density with chromosomal structure or base composition [2,6]. However, to our knowledge no one has looked at the correlation of gene density with Quantitative Trait Locus (QTL) density over the genome. Furthermore, gene density on its own is a fairly crude measurement of the functional role of specific genomic domains. It would be more informative to combine thi

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