Identification Loci Of Agronomic Traits Using Linkage And Linkage Disequilibrium Analysis In Wheat

Wheat(Triticum aestivum L.)is an important crop in the world,and the wheat grain is a major staple food for above third of the global human population.Wheat has been cultivated in China for more than four millennia and is now grown in 10 major agro-ecological zones.Modern wheat improvement is heavily based on crosses between elite varieties.Although conventional breeding has substantially facilitated the improvement of wheat varieties,it is time-consuming and has low efficiency.Marker-assisted selection(MAS)is considered to be an excellent approach for crop precision breeding,as it improves breeding efficiency and predictability,and thus accelerates breeding progress.Linkage analysis and genome-wide association study(GWAS)are two common way for detecting the correlation between traits and markers.In this study,a core of 723 wheat landraces,originated from 10 major agro-ecological zones of China,was genotyped by diversity arrays technology sequencing(DAr T-seq)markers.A GWAS was performed to identified loci associated with agronomic traits.Then,a recombinant inbred line(RIL)population,developed from the cross between the landrace Chinese Spring(CS)and the excellent line H461,was evaluated for agronomic traits in multi-environments.The RIL population was genotyped by 55 K SNP chip and used to construct a high-density genetic map.Linkage analysis was performed for detecting QTL of agronomic traits to validate the results of GWAS.The main results obtain from this study were listed as the following:1.Based on the high-throughput sequencing of 723 landraces from 10agro-ecological zones of China,polymorphism information content analysis revealed that landraces showed high genetic diversity.A total of 723 wheat accessions were genotyped using DAr T-seq markers.A total of52,303 polymorphism markers were gathered.Of these,25,439 markers were mapped on on the wheat consensus map version 3.0 with a total linkage distance of 5,977.88 c M.The average value of the polymorphism information content(PIC)for the 52,303 biallelic polymorphic markers was 0.31,ranging from 0.10 to 0.50.Population structure analysis revealed that 723 wheat accessions were divided into five sub-group(Gp1,Gp2,Gp3,Gp4 and Gp5).Gp1,Gp2,and Gp3 were predominantly included winter wheats,and Gp4 was mainly included spring wheats.Gp5 was consisted of both spring and winter wheats.PIC analysis based on the five sub-group indicated that Gp5 and Gp2 presented the highest(0.32)and lowest(0.22)average PIC values,respectively.Linkage disequilibrium(LD)analysis revealed that LD decay distance was the highest for the D subgenome(approximately 20 c M)and the lowest in the B subgenome(approximately 10 c M).The average LD decay distance of the A subgenome was approximately 15 c M,similarly to LD decay distance of the whole genome.2.Combined with phenotypic data of multi-environments,a large number of loci for agronomic traits were obtained using GWAS,and these loci broadened the application for MAS breeding in wheat.A total of 23 agronomic traits among 723 wheat accessions were evaluated in multi-environments.The heritability analysis showed that the heritability of grain width-length ratio was the lowest(0.43)and the heritability of heading date was the highest(0.98).Using phenotypic data collected from the different environments,11,915 significant markers were detected by general linear model(GLM)with 1.01-22.10%phenotypic variation explained(PVE).A total of 447 significant markers were detected by mixed linear model(MLM)with 2.60-13.98% PVE.A total of 376 significant markers were detected by both models for 22 agronomic traits,with the exception of plant height.Based on the best linear unbiased prediction(BLUP)values,9,385 significant markers were detected by GLM with 1.20-20.64% PVE.A total of 190 significant markers were detected by MLM with 2.51-11.87% PVE.A total of 149 significant markers were identified by both models for 21 agronomic traits,with the exception of plant height and tiller number.3.A high-density genetic map was constructed based on the RIL population using55 K SNP chip,combined with phenotypic data in multiple environments,four agronomic loci detecting by GWAS was confirmed by linkage analysis.The mutual verification and complementary agronomic loci detecting by linkage analysis and GWAS laid a foundation for the next step of wheat molecular assisted breeding.A RIL population was developed from the cross between the landrace CS and the excellent line H461.Both parents and the RIL population were genotyped using the wheat55 K SNP array.A high-density genetic map containing 21,197 SNPs was obtained.These markers covered each of the 21 chromosomes with a total linkage distance of 3,792.71 c M.Locations of these markers in this linkage map were highly consistent with their physical locations in the physical map of CS.The heritability analysis showed that all agronomic traits had high heritability.Combined with phenotypic data in multiple environments and the BLUP values,the linkage analysis revealed four agronomic loci were consistent with GWAS results,including:(1)a major loci for awn type(QAt.sicau-6B)was detecting in all environments with 33.18-71.43% PVE;(2)a major loci for heading date(QHd.sicau-2D-2)was detecting in all environments with 29.27-50.27% PVE;(3)a major loci for flowering date(QFd.sicau-2D-2)was detecting in all environments with 29.27-50.27% PVE;(4)a major loci for spikelet number(QSn.sicau-2D)was detecting in all environments with29.27-50.27% PVE.The mutual verification and complementary agronomic loci detecting by linkage analysis and GWAS laid a foundation for the next step of wheat molecular assisted breeding.