Prioritization of candidate genes for cattle reproductive traits, based on protein-protein interactions, gene expression, and text-mining

Abstract

Reproduction is of significant economic importance in dairy cattle. Improved understanding of mechanisms that control estrous behavior and other reproduction traits could help in developing strategies to improve and/or monitor these traits. The objective of this study was to predict and rank genes and processes in brain areas and pituitary involved in reproductive traits in cattle using information derived from three different data sources: gene expression, protein-protein interactions, and literature. We identified 59, 89, 53, 23, and 71 genes in bovine amygdala, dorsal hypothalamus, hippocampus, pituitary, and ventral hypothalamus, respectively, potentially involved in processes underlying estrus and estrous behavior. Functional annotation of the candidate genes points to a number of tissue-specific processes of which the "neurotransmitter/ion channel/synapse" process in the amygdala, "steroid hormone receptor activity/ion binding" in the pituitary, "extracellular region" in the ventral hypothalamus, and "positive regulation of transcription/metabolic process" in the dorsal hypothalamus are most prominent. The regulation of the functional processes in the various tissues operate at different biological levels, including transcriptional, posttranscriptional, extracellular, and intercellular signaling levels.

Associations of SNPs located at candidate genes to bovine growth traits, prioritized with an interaction networks construction approach

“…The networks derived from a single source of information exhibit a low level of predictive power, low coverage and a reduced number of interactions relative to the networks generated through the integration of diverse biological data. The coverage (27 %) obtained by Hulssege et al [ 10 ] is noteworthy because the coverage was greater than that achieved in previously reported networks and exhibited greater predictive power than STRING (AUC 0.51) in this study, which was similar to the performance obtained in the integrated network BosNet (AUC 0.64). These results were expected because the interactions in STRING were generated using an integrative method that is conceptually similar to the methodology applied in the present study [ 12 ].…”

“…Similarly, Hulsegge et al [ 10 ] prioritized candidate genes for reproductive characteristics in cattle based on PPIs reported for existing orthologous genes between B. taurus and H. sapiens in the STRING database. The genes were prioritized using the average of two calculated scores.…”

“…Currently, the availability of different types of biological data, such as functional annotations for B. taurus genes, is limited compared with the information available for more thoroughly studied organisms, such as H. sapiens [ 10 ].…”

“…Hence, animal science has begun to utilize bioinformatics to model and generate interaction networks that represent the architectural genetics of complex traits in bovines, such as marbling, age at puberty and reproductive characteristics [ 7 , 9 , 10 ]. The objectives of this work were to develop BosNet as a tool for the identification and prioritization of genes associated with complex traits and to assess the efficiency of the BosNet tool in associating SNPs located on BosNet-prioritized genes with bovine growth traits.…”

Genetics of cattle temperament and its impact on livestock production and breeding – a review

“…In cattle, putative candidate genes that affect behavioural traits in distinct situations such as oestrus and feeding behaviour have been reported (Nkrumah et al, 2005;Kommadath et al, 2011;Hulsegge et al, 2013). One example for a positional and functional candidate gene for cattle temperament is the tyrosinase gene (TYR), which is generally known for its function in the dilution of coat colour in cattle (Schmidtz et al, 2001), and is located in a QTL for temperament during milking on BTA29 (Hiendleder et al, 2003).…”