Utilizing Whole Genome Sequence Information in Swine Breeding: Where next for Application?

Abstract Text: Simulated results predict an increase in genomic prediction accuracy through inclusion of whole genome sequence data. Very initial results indicate that improvements obtained using real data do not match those predicted using simulated data. However, results from beef cattle simulated data showed that differences in how the reference population was chosen, the number of animals sequenced and the fold coverage of the sequence influenced the genomic prediction accuracy. More complete knowledge of the underlying genetic architecture for a given trait could lead to more comprehensive genetic evaluation models and the ability to predict the influence of non-genetic effects on animal phenotypes. Increased data storage needs, more comprehensive evaluation models, and increased phenotyping will increase costs however these need to be balanced against the benefits. Sensitivity analysis using the cost-benefit models can assist organizations in addressing the uncertainty in key inputs and outputs.

Keywords:

swine

genome sequence

genetics