Genetic Basis Of The Agronomic Traits Revealed By Association Mapping Based On Germplasm And Magic Population

Upland cotton(Gossypium hirsutum L.)provides the most natural fibre for the manufacture of textiles worldwide.And it is one of the most important economic crop in China.The growth period,plant type,yield,and fiber quality are important agronomic traits that decide the economic value and planting pattern of upland cotton.They are are quantitative traits with a complex genetic basis that are controlled by multi-genes with small effects.Therefore it is difficult to improve them based on traditional breeding methods.Revealing the genetic basis of these agronomic traits will promote the development of high-efficiency molecular breeding in upland cotton.Association mapping is a powerful and widely used tool for detecting QTLs.To understand the genetic architecture of upland cotton growth period,plant type,yield,and fiber quality traits in upland cotton,association mapping based on two populations was implemented in this study as follows.1 Genetic basis of the agronomic traits revealed by a genome-wide association study based on 503 upland cotton accessionsA population containing 503 upland cotton accessions was collected from the nation-wide cultured germplasms.A total of 11,975 quantified polymorphic single-nucleotide polymorphisms(SNPs)were obtained for genotyping the 503 accessions by using the CottonSNP63 K array and a published high-density map based on this array.The average PIC and gene diversity index of all SNPs were 0.332 and0.391,respectively.The genome-wide LD decay distance of the population was 6.1cM when the r~2 attenuated 0.1.Based on the genotyping,the 503 upland cotton accessions were divided into 3 obvious subpopulations by STRUCTURE simulation analysis,PCA and drawing the Neighbor-Joint tree.The 503 accessions were planted in four places in two years for phenotyping.Effective phenotypic data of 16 important agronomic traits were obtained.Using 11975 SNPs and BLUPed phenotypic value,the marker-traits association were performed.A total of 324 SNPs were identified significantly associated with the 16 target traits.The phenotypic variation explained by the identified SNPs were ranged from 3.17%to 9.04%.In addition,based on the confidence interval set by LD decay distance,a total of 160 QTLs were identified from the 324 significant SNPs.Seven QTLs were reported with the same trait controlling in recent researches.There were 28 QTL regions and 11 closely linked QTLs associated with two or more traits.A network was established for pleiotropic in QTLs and inter associations among traits.Furthermore,336 and 18 genes were screened as the priori candidate genes base on preferential expression pattern and the information of gene function studied clearly,respectively.In a lint percentage(LP)QTL region which evaluated with fast LD decay,one gene(Gh_D08G2376)was speculated as the candidate gene controlling the LP.2 Genetic basis of the agronomic traits revealed by association mapping based on503 upland cotton accessions using an 8-way MAGIC populationIn this study,a MAGIC population containing 960 lines(MLs)was developed based on 8 diverse parents(PMs).A multi-environment field experiment in three locations from 2013 to 2015 was designed for phenotyping.Fourteen agronomic traits were investigated in five environments.Phenotypic analysis showed that the PMs have wider variation than the MLs.In early of this study,the SSR markers were used to genotype the MLs.A total of 284 SSR markers showed high quality and good polymorphism were screened by 8PMs from a high-density interspecific(G.hirsutum×G.barbadense)genetic map.The genetic characteristics of MLs were mined based on the 284 SSR markers.The gene diversity index were 0.415 and 0.463 in PMs and MLs,respectively.Statistical analysis of gene diversity confirmed the more genetic variations in MLs than PMs.The MLs were revealed without population structure by PCA analysis.In addition,the MLs population showed fast LD decay that the distance were 0.76 cM when r~2dropped to 0.1.Marker-trait association were performed using BLUPed value of 14 traits and 284 SSR markers.There were 139 loci significantly associated with 14 traits under the p<0.01.The percentage of phenotypic variation explained by the identified loci ranged from 0.71%-7.23%.The 139 loci were covered by 96 SSR markers on genetic map.Forty SSR markers were reported in recent studies,while 6of them were consistent with our results.In addition,26 SSR markers that were associated with more than one trait demonstrated the pleiotropism.Furthermore,9 hot pleiotropic loci were explored with valuable information for further genetic research and cotton breeding.To deeply genotype the MAGIC population,a subset population contains 372lines(SMLs)was selected from 960 MLs by phenotype and SSR genotype.The SMLs were reinforced phenotype data investigated in 2016.A total of 60495 pleomorphic SNPs were obtained by SLAF-seq.The LD decay distance of SMLs was600 kb(r~2=0.1)that showed similarity result calculated by SSR markers.The GWAS were performed using 60495 SNPs and phenotyping data of SMLs.Base on the phenotype of 6 environments and BLUP,975 SNPs were identified significantly associated with 14 agronomic traits.And the identified SNPs were divided in 400 QTLs.The QTLs could explained 5.08%to 53.80%of phenotypic variation.Among the 400 QTLs,30 QTLs could identified stably in multiple environments.In addition,88 QTL regions were proved with pleiotropism that associated with multiple traits.In QTLs regions,271 genes,which preferential expressed in correlated tissues,and 18 genes with known functions were screened out as the priori candidate genes.