Improving hybrid rice breeding programs via stochastic simulations: number of parents, number of hybrids, tester update, and genomic prediction of hybrid performance.

Schemes that use genomic prediction outperform others, updating testers increases hybrid genetic gain, and larger population sizes tend to have higher genetic gain and less depletion of genetic variance One of the most common methods to improve hybrid performance is reciprocal recurrent selection (RRS). Genomic prediction (GP) can be used to increase genetic gain in RRS by reducing cycle length, but it is also possible to use GP to predict single-cross hybrid performance. The impact of the latter method on genetic gain has yet to be previously reported.

Genomic Prediction of Yield Traits in Single-Cross Hybrid Rice ( L.).

Hybrid rice varieties can outyield the best inbred varieties by 15 - 30% with appropriate management. However, hybrid rice requires more inputs and management than inbred rice to realize a yield advantage in high-yielding environments. The development of stress-tolerant hybrid rice with lowered input requirements could increase hybrid rice yield relative to production costs.

Genome-wide association study of outcrossing in cytoplasmic male sterile lines of rice.

Stigma exsertion and panicle enclosure of male sterile lines are two key determinants of outcrossing in hybrid rice seed production. Based on 43,394 single nucleotide polymorphism markers, 217 cytoplasmic male sterile lines were assigned into two subpopulations and a mixed-group where the linkage disequilibrium decay distances varied from 975 to 2,690 kb. Genome-wide association studies (GWAS) were performed for stigma exsertion rate (SE), panicle enclosure rate (PE) and seed-setting rate (SSR).