Genome-wide Association Analysis And Genome-wide Prediction Of Chilling Tolerance In Maize Seedling Stage

Low-temperature cold damage at the shoot stage is an important factor affecting maize production at high latitudes,and research on the genetic mechanism and genome-wide prediction of cold tolerance will provide an important basis for innovation of cold-tolerance resources and variety selection in maize.In this study,265 excellent maize inbred lines were used as materials,and were subjected to low temperature stress at the bud stage and seedling stage respectively,Various indicators related to cold tolerance at the sprout stage were determined,and analysis methods such as correlation analysis,principal component analysis and cluster analysis were used,Comprehensive evaluation of cold tolerance in maize sprout stage,and classification of cold tolerance of265 maize inbred lines according to D value of comprehensive cold tolerance;Using GBS-SNP genotype data and cold tolerance-related phenotypic traits,a variety of statistical models were used to conduct genome-wide association analysis to screen SNP markers associated with target traits.Based on the high-density markers covering the genome and phenotypic data at the sprout stage,a genome-wide prediction study of cold tolerance at the sprout stage of maize was carried out,which provided an important theoretical basis and technical support for the breeding of maize sprout stage cold tolerance.The main findings were as follows:1.A total of 14 maize cold tolerance indices were measured,including shoot germination rate,shoot length,root length,shoot fresh weight,root fresh weight,shoot dry weight,root dry weight and seedling conductivity,chlorophyll value,F0,Fm,Fv/Fm and Fv/F0.Five principal components were identified by principal component analysis,namely,shoot fresh weight principal component,PS? primary light energy conversion efficiency(Fv/Fm)principal component,maximum fluorescence(Fm)principal component,electrical conductivity principal component,and chlorophyll value principal component.The 265 maize inbred lines were classified into five cold tolerance levels by calculating the combined cold tolerance index(D)values at the shoot stage,there were 12 highly cold-sensitive materials,54 moderately cold-sensitive materials,85 cold-sensitive materials,105 moderately cold-resistant materials,and 9highly cold-resistant materials,of which No.83 had the strongest overall cold resistance of 0.79.2.15 chilling tolerance data and 281,396 SNP markers at the maize sprout stage were used to conduct genome-wide association analysis based on GLM model,MLM model,Farm CPU model and Blink model,A total of 605 SNP markers related to low temperature traits were co-localized,among which 221 significant loci in bud stage,357 significant loci in seedling stage and 27 significant loci in comprehensive cold tolerance D value were detected.Thirty-nine same significant loci were detected among different traits.3.The significant loci screened in this study according to the association analysis were associated with 71 genes,40 genes associated with bud stage traits,26 genes associated with seedling stage traits,and 5 genes associated with comprehensive cold tolerance D value indivual.4.A genome-wide prediction study of 15 indicators of cold tolerance at the sprouting stage of maize was conducted using the RR-BLUP model with a 5-fold cross-validation approach.The prediction accuracies,in descending order,were shoot length,germination index,germination percentage,shoot fresh weight,F0,D,Fm,root length,root fresh weight,shoot dry weight,root dry weight,conductivity,Fv/Fm,Fv/F0,and chlorophyll content.The training population size and marker density were optimized on the prediction accuracy for the shoot length index with the highest prediction accuracy and the chlorophyll content index with the lowest prediction accuracy,respectively,The results show that a good prediction can be achieved when the training population reaches 50% and the marker density is 500.