Genetic Composition Of Yield Heterosis Using An Ultrahigh Density SNP Bin Map In An "Immortalized F₂" Population

Heterosis, or hybrid vigor, refers to the superior performance of the hybrids relative to the parents. Utilization of heterosis has contributed tremendously to the increased productivity in many crops for decades. Although there have been a range of studies on various aspects of heterosis, the key to understanding the biological mechanisms of heterotic performance in crop hybrids is the genetic basis, much of which is still uncharacterized.We previously constructed an "immortalized F2"(IMF2) population by intercrossing recombinant inbred lines (RILs) derived from a cross between Zhenshan97and Minghui63, the parents of Shanyou63. The population allows identification of all the genetic components of heterosis, and research in this population showed epistasis plays an important role as the genetic basis of heterosis. More recently we resequenced the RILs and developed an algorithm for constructing ultra-high density bin map, which provided more precise information for genetic mapping. In this study, we used an ultrahigh density SNP bin map to dissect the genetic composition of yield and yield component traits in the IMF2population. The main results are summarized as follow:1. Using1619bin markers, we constructed an ultrahigh density SNP bin map for the IMF2population. Data for278crosses were obtained based on the210RILs, and genotype for each cross was deduced on the basis of the RILs that were used as the parents for crossing. There were three genotypes in each bin, a homozygote for each of the parental genotype (A and B), and a heterozygote (H), with frequencies equivalent to those in an F2population.2. A number of QTL were detected for yield and three yield component traits in1998and1999respectively. The accuracy of the ultra-high density bin map was evaluated with known genes. Because we did not have data for grain length or width, we thus assessed the quality of the IMF2bin map using related traits (grain weight for GS3and GW5/qSW5and grain number for GhdT). These QTL were successfully mapped to their known locations, showing the accuracy of the bin map.3. We estimated the additive and dominance effects in each of the1619bins for the four traits, based on the SNP bin map using the IMF2data collected in two years. In general, the data were consistent in two years that positive dominance was detected in much larger numbers of bins than the ones showing negative dominance for all four traits in both years. The only exception occurred in tillers per plant in1998, in which the number of bins showing positive dominance was slightly lower than ones exhibiting negative dominance.4. We used a h-statistic to identify bins that have statistically significant (P<0.05) dominant effects on the trait. The results of both years consistently showed that much greater numbers of bins demonstrated positive dominance than ones showing negative dominance. Then we attempted to merge the heterotic bins into clusters based on their physical positions which were distinguished by recombinantions between adjacent bins in RILs wherever possible. However this merge process might eliminate some of the adjacent ones that show similar effect, resulting in underestimation of the number and effects of heterotic bins. Given all that technological limitations, it is nonetheless clear that much greater numbers of bins exhibited positive dominance than ones showing negative dominance.5. We used mid-parent heterosis value to identify heterotic loci (HL). A number of HL was resolved for for all the traits in both two years. The heterosis loci distributed on all12chromosomes randomly.6. We also compared the HL with the QTL and the bins showed significant dominance that were resolved in the trait analysis of the same IMF2population. It seems that there was no necessary link between them. But there are some QTL also be a HL and showed significant dominance, revealing they played important role in both trait performance and heterosis.7. Interactions of all possible two-locus combinations were calculated using two-way ANOVA at P≤0.001. The total numbers of tests were1,248,255for1998and1,259,379for1999. We conducted a permutation test to reduce false positive followed by merging of interactions detected from adjacent two-locus combinations.8. We partitioned each of the significant interactions into four components using the orthogonal contrast test, according to the modes of gene actions at the two loci:additive (first locus) by additive (second locus), additive by dominance, dominance by additive and dominance by dominance. It was shown that additive by additive interactions occurred at the highest frequencies, making up over50%of total significant interactions, followed by additive by dominance (dominance by additive), and dominance by dominance interations occurred least frequently in both years.9. Interactions based on mid-parent heterosis value were also calculated. And the results were similar.10. To assess the relative contributions of the three types of genetic effects to heterosis in the F1hybrid, the heterotic bins were grouped according to the genetic effects: single-locus dominance, single-locus overdominance and digenic heterotic effects. We calculated the total effect of each group and the relative importance of these components. For yield overdominance is the most important contributor followed by DD. Overdominance also contributed the most to grains per panicle. DD effects were higher than overdominance for tillers per plant, but the heterotic effects of this trait were not consistent between years. For grain weight, the contribution of overdominance was also higher than DD and dominance, although the total amount of heterotic effect was relatively small.