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Genome-Wide Dissection Of Genetic Differences In Ear Traits Of Maize Cultivars In Different Ecological Regions

Posted on:2021-04-22Degree:MasterType:Thesis
Country:ChinaCandidate:Y SunFull Text:PDF
GTID:2543306029466464Subject:Bioinformatics
Abstract/Summary:PDF Full Text Request
China is the country with the largest corn acreage in the world,and it is grown all over the country,but the yield of corn is much lower than that of the United States.Therefore,increasing yield is still an important goal of maize breeding.Corn ear traits are directly related to yield.In the long-term corn breeding process,due to differences in ecology,germplasm and breeding goals,continuous breeding manual selection has caused genetic differences in corn ear traits in different ecological regions of China,which has led to this genetic The molecular basis of the difference is unclear.In this study,a mixed linear model that can detect genotype effects and environmental interaction effects was used.The phenotypic data of 4 larvae traits of 554 maize regional test varieties and 200 K SNP were used in the three major maize ecological regions in China,including Donghuabei,Huanghuaihai and Xinan.The data were used for genome-wide association analysis,to analyze the genetic structure differences of ear traits in different regions,to discover significant SNP loci and candidate genes,to analyze the molecular basis of genetic differences in ward traits in different regions,to predict good genotypes,and for different ecological regions.Maize ear trait gene selection and high-yielding breeding provide theoretical basis.The main results are as follows:1.The study found that the heritability of additive and dominant effects of ear length,ear line number,100-kernel weight and line number explained a total of 60.13%-94.84%of phenotypic variation.This implies that the genetic structure of maize ear traits is mainly additive and dominant effects.The ear line number in the Xinan and the line number in the Huanghuaihai region shows a large genotype environment interaction effect.2.A total of 101 significant SNP loci were identified for the four ear traits in the three major maize ecological regions,among which ear length,ear line number,100-grain weight,and line number were 24,28,33,and 16,respectively.The number,position and effect of the SNP loci that are significantly associated with the same trait in different ecological regions are obviously different.The same SNP locus in the same ecological trait is not found in different ecological regions.This reflects the significant genetic differences in ear traits in different ecological regions.3.Through analysis and identification of related candidate genes in the 50 Kb segment around the significant SNP with ear traits in the three major maize ecological regions,40 candidate genes related to ear development were screened,such as the grain weight Zm00001d011559(emp16)gene.These candidate genes mainly involved 7 gene families related to ear development,including PPR,b HLH,LRR,F-box,myb and SM.Some genes with the same trait genetic differences between different ecological regions mostly belong to a family or genes with similar functions in different families.This shows that the genetic differences of the traits in different ecological regions may be the result of different selections of different genes with similar functions..4.The breeding values and excellent allele types of four ear traits SH and F1 in the three ecological regions were predicted,and excellent SNP loci and allele types of ear traits in different regions were obtained.The genetic effect is negative,and the number of ear rows and row grains is positive.In the southwest ecoregion,the result is quite the opposite.This shows the differences in the breeding potential and selection effects of corn ear traits in different ecological regions,and also provides an important theoretical basis for the selection and aggregation of excellent allelic maize breeding in different ecological regions.
Keywords/Search Tags:maize, ear length, genetic difference, genome-wide association analysis, Genetic effects, candidate genes
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