In silico simulation of future hybrid performance to evaluate heterotic pool formation in a self-pollinating crop.

Hybrid vigour has the potential to substantially increase the yield of self-pollinating crops such as wheat and rice, but future hybrid performance may depend on the initial strategy to form heterotic pools. We used in silico stochastic simulation of future hybrid performance in a self-pollinating crop to evaluate three strategies of forming heterotic pools in the founder population. The model included either 500, 2000 or 8000 quantitative trait nucleotides (QTN) across 10 chromosomes that contributed to a quantitative trait with population mean 100 and variance 10.

A hybrid method for the imputation of genomic data in livestock populations.

Background: This paper describes a combined heuristic and hidden Markov model (HMM) method to accurately impute missing genotypes in livestock datasets. Genomic selection in breeding programs requires high-density genotyping of many individuals, making algorithms that economically generate this information crucial. There are two common classes of imputation methods, heuristic methods and probabilistic methods, the latter being largely based on hidden Markov models.