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Genome-Wide Association Analysis For Genetic Basis Of Veins In Maize

Posted on:2020-12-24Degree:MasterType:Thesis
Country:ChinaCandidate:L L LiuFull Text:PDF
GTID:2393330590988545Subject:Biochemistry and Molecular Biology
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Maize is the largest food crop in the world and an important global feed crop and industrial raw material crop.Because of the adjustment of maize planting structure in China,improving the photosynthetic utilization efficiency of maize leaves,changing the leaf shape of maize leaves and enhancing the mechanical support of leaves are all important factors indirectly affecting the structure of maize industry.It has been reported that maize veins are a special form of vascular bundles,which not only plays an important role in the mechanical support of the leaves,but also is the main transport system for transporting water and mineral salts.The arrangement of leaf veins in the leaves not only affects the photosynthesis of the leaves,but also the factors affecting the transpiration of the leaves;the upper side of the maize veins is the phloem on the lower side of the xylem,the outer layer is surrounded by the vascular bundle sheath,and the chloroplasts in the sheath are distributed.Among them,this structure is more conducive to the photosynthesis of the leaves,and it is meaningful for the photosynthesis utilization rate of maize.It can be seen from the above that the predecessors' research mainly focused on the anatomy and physiology of maize veins,but did not advance into the molecular mechanism of understanding the leaf vein traits of maize and the molecular regulation of leaf vein morphogenesis,thus using genome-wide association analysis(GWAS)is meaningful for mining key genes that affect the development and morphogenesis of maize veins.In this study,the maize-related populations constructed from 508 inbred lines collected from the world were used to determine the maize vein traits in Liaoning Shenfu and Liaoning Tieling.Data were investigated and the GWAS analysis was performed on the width,thicknessness and depth of the veins.To excavate the genetic loci affecting the width,thicknessness and depth traits of maize veins in order to obtain candidate genes.The result is to improve the leaf vein traits of maize by molecular breeding methods,and to accelerate the cultivation of new maize varieties with independent intellectual property rights and high photosynthetic efficiency.Theoretical basis.The main findings are as follows:1.Genetic basis of vein width traits in associated populationsThe vein width was planted in the two environments of Shenfu and Tieling(both environments were tested in 2017,two repetitions in Shenfu,and three repetitions in Tieling).The survey data showed that the vein width satisfies the continuous positive distribution in both environments,and the generalized heritability is 0.59,showing a moderately upper level.When performing GWAS analysis on the data,we used a mixed linear model(MLM)to select the threshold location of the SNP locus 5 and analyze the independence of the SNP locus based on linkage disequilibrium.When above the threshold line,a total of 8 independent significant SNP loci were detected,located on chromosomes 3,5,6,7,and 10,respectively.The phenotypic contribution rate of independent significant SNP loci.4.68%,8 gene SNPs were detected for candidate gene function annotation and metabolic pathway analysis.A total of 8 were selected as candidate genes,which were mainly divided into signal transduction,metabolic pathway,redox pathway and transcriptional regulation.2.Genetic basis of vein thicknessness traits in associated populationsThe thicknessness of the veins was planted in the two environments of Shenfu and Tieling(both environments were tested in 2017,two repetitions of Shenfu,and three repetitions of Tieling).The results of the survey data show that the thicknessness of the veins still meets the continuous positive distribution in both environments,and the generalized heritability is 0.61,showing a high heritability level.When performing GWAS analysis on the data,we used a mixed linear model(MLM)to select the threshold location of the SNP locus 5 and analyze the independence of the SNP locus based on linkage disequilibrium.When above the threshold line,a total of 15 independent significant SNP loci were detected,except on chromosomes 2 and 10,which were not detected,and the distribution of SNP loci on the remaining 8 chromosomes,The phenotypic contribution rate of independent significant SNP loci was 3.34%.From the 11 SNP loci detected,candidate gene function annotation and metabolic pathway analysis were performed.A total of 12 were the final candidate genes,which were mainly divided into signal transduction.Five pathways,metabolic pathway,catalysis,cell cycle and transcriptional regulation.3.Genetic basis of vein depth traits in associated populationsThe vein depth was planted in the two environments of Shenfu and Tieling(both environments were tested in 2017,two repetitions of Shenfu,and three repetitions of Tieling).The results of the survey data show that the vein depth still satisfies the continuous positive distribution in both environments,and the generalized heritability is 0.33,showing a moderate genetic level.When performing GWAS analysis on the data,we used a mixed linear model(MLM)to select the threshold location of the SNP locus 5 and analyze the independence of the SNP locus based on linkage disequilibrium.When above the threshold line,a total of 18 independent significant SNP loci were detected,except on chromosomes 1 and 2,which were not detected,and the distribution of SNP loci on the remaining 8 chromosomes,the phenotypic contribution rate of independent significant SNP loci was 10.13%.From the 18 SNP loci detected,candidate gene function annotation and metabolic pathway analysis were performed.A total of 16 were selected as the final candidate genes,which were mainly divided into signal transductions.Guidance,metabolic pathways,gene editing,structural proteins and transcriptional regulation.
Keywords/Search Tags:maize, vein trait, genome-wide association analysis, candidate genes
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