Genome-Based Identification of Heterotic Patterns in Rice

Abstract Background Hybrid rice breeding facilitates to increase grain yield and yield stability. Long-term success of hybrid breeding depends on the recognition of high-yielding complementary heterotic patterns, which is lacking in crops like rice. Result The main goal of this study was to evaluate the potential and limits to use genomics for establishing heterotic patterns in rice. For this purpose, data of a commercial hybrid rice breeding program targeted to India was analyzed, including 1,960 phenotyped hybrids from three market segments and 262 genotyped parental lines. Our cross-validation study revealed that grain yield of all potential single-crosses can be accurately predicted. Based on the full matrix of hybrid performances, high-yielding heterotic patterns were identified. These heterotic patterns increased grain yield up to 9% compared to the currently employed groups. Heterotic groups of around 14 individuals reflect a good compromise between long-term and short-term selection response. Conclusions Our findings clearly underlined the benefits of a genome-based establishment of heterotic patterns in rice as a requirement for a sustainable long-term success of hybrid rice breeding

Additional file 1: of Genome-Based Identification of Heterotic Patterns in Rice

for Genome-based identification of heterotic. Figure S1. Decay of linkage disequilibrium measured using r2 with physical map distance. Figure S2. Principal coordinate analysis of all parental lines for market segments LS, MM, and SS. Figure S3. Applied cross validation scenario exemplifying the selected fractions for market segment MM. Figure S4. Unbalanced factorial crossing designs for market segment (A) LS, (B) MM, and (C) SS. Figure S5. Venn diagram of overlapping parental lines of the hybrid evaluation trials in market segments LS, MM, and SS. Figure S6. Experimental design and distribution of checks for hybrid experiment of market segment MM at location HYD. Orange and black lines represent the size of trials and blocks, respectively. White plots were not phenotyped. Table S1. Composition of heterotic groups selected with the simulated annealing algorithm as well as the average hybrid performance between both heterotic groups (Inter) for the market segments LS, MM, and SS. Table S2. Composition of estimation and test populations for market segment LS, MM, and SS. (DOCX 1811 kb

Additional file 2: of Genome-Based Identification of Heterotic Patterns in Rice

Best linear unbiased estimations for hybrid grain yield experiments in market segments LS, MM, and SS. (XLSX 76 kb