Genome-wide association mapping and genomic prediction of stalk rot in two mid-altitude tropical maize populations

Maize stalk rot reduces grain yield and quality.Information about the genetics of resistance to maize stalk rot could help breeders design effective breeding strategies for the trait.Genomic prediction may be a more effective breeding strategy for stalk-rot resistance than marker-assisted selection.We performed a genome-wide association study(GWAS)and genomic prediction of resistance in testcross hybrids of 677 inbred lines from the Tuxpe?o and non-Tuxpe?o heterotic pools grown in three environments and genotyped with 200,681 single-nucleotide polymorphisms(SNPs).Eighteen SNPs associated with stalk rot shared genomic regions with gene families previously associated with plant biotic and abiotic responses.More favorable SNP haplotypes traced to tropical than to temperate progenitors of the inbred lines.Incorporating genotype-by-environment(G×E)interaction increased genomic prediction accuracy.

Genomic prediction of the performance of hybrids and the combining abilities for line by tester trials in maize

The two most important activities in maize breeding are the development of inbred lines with high values of general combining ability(GCA)and specific combining ability(SCA),and the identification of hybrids with high yield potentials.Genomic selection(GS)is a promising genomic tool to perform selection on the untested breeding material based on the genomic estimated breeding values estimated from the genomic prediction(GP).In this study,GP analyses were carried out to estimate the performance of hybrids,GCA,and SCA for grain yield(GY)in three maize line-by-tester trials,where all the material was phenotyped in 10 to 11 multiple-location trials and genotyped with a mid-density molecular marker platform.Results showed that the prediction abilities for the performance of hybrids ranged from 0.59 to0.81 across all trials in the model including the additive effect of lines and testers.In the model including both additive and non-additive effects,the prediction abilities for the performance of hybrids were improved and ranged from 0.64 to 0.86 across all trials.The prediction abilities of the GCA for GY were low,ranging between-0.14 and 0.13 across all trials in the model including only inbred lines;the prediction abilities of the GCA for GY were improved and ranged from 0.49 to 0.55 across all trials in the model including both inbred lines and testers,while the prediction abilities of the SCA for GY were negative across all trials.The prediction abilities for GY between testers varied from-0.66 to 0.82;the performance of hybrids between testers is difficult to predict.GS offers the opportunity to predict the performance of new hybrids and the GCA of new inbred lines based on the molecular marker information,the total breeding cost could be reduced dramatically by phenotyping fewer multiple-location trials.