| Soybean[Glycine max(L.)Merr.],one of the most important food and oil crops in the world,provides abundant oil products protein for animals and humans.Seed yield has been frequently focused by human beings.Cultivating high yield and quality soybean varieties is always the aim for soybean breeders.Seed yield-related traits are complex quantitative traits and controlled by multiple genes.Wild soybean(Glycine soja Sieb.and Zucc.)is the progenitor of cultivated soybean and can be used as an essential genetic resource for yield improvement.In addition,as pod dehiscence leads to significant yield loss in soybean and may cause more damage to soybean production as climatic conditions become harsher,breeding soybean varieties with pod-dehiscence resistance is always one of the important goals for breeders.In order to explore the genetic mechanism of yield in soybean and MAS application in soybean,the QTLs and SNPs of yield-related traits in cultivated and wild soybean were identified using RIL-based linkage analysis and germplasms-based association mapping,respectively.GsCID1 related to seed weight in wild soybean and Glyma09g06290 related to pod dehiscence were detected based on GWAS results,respectively.In addition,the dCAPS markers were developed for GsCID1 and Glyma09g06290,respectively.The main results in this study are as follows:1.A high-density genetic map(bin-map)was constructed by re-sequencing 184 families in the RILs derived by Kefeng No.1 and Nannong 1138-2.The bin-map contains 3,420 bin markers and the total genetic distance is 1,904 cM.QTL mapping for 7 yield-related traits of RIL population in 3 environments was carried out by using this bin-map.The results showed that 44 QTLs were detected,17 of which could be detected in two or three environments.6 QTLs were detected in plant height,distributed on chromosome 5,6,10,11 and 12;7 QTLs were detected in the node number on main stem,distributed on chromosome 6,10,11,12,13 and 15;3 QTLs were detected in the branch number,distributed on chromosome 4,15 and 16;7 QTLs were detected in the pod number per plant,distributed on chromosome 6,10,11,12,13,18 and 19;8 QTLs were detected in the seed number per plant,distributed on chromosome 1,6,10,11,12,13,18 and 19;6 QTLs were detected on chromosome 4,6,11,16 and 17 for 100 seed weight;7 QTLs were detected on chromosome 3,6,10,11 and 17 for seed yield per plant.2.The association analysis was performed in 7 yield-related traits of a natural populations by using the NJAU 355K SoySNP across 3 environments.The results showed that there were significant differences among individuals,and significant differences was existed between experimental pots and years for the most traits,respectively.The highest heritability of plant height was 90.61%.266 SNPs associated with 7 traits were detected,25 of which were identified in 2 or 3 environments.147 SNPs for plant height,distributed on chromosome 1,2,3,5,6,7,9,11,12,13,15,16,19 and 20;29 SNPs for node number on main stem,distributed on chromosome 1,2,3,7,10,11,13,16 and 19;27 SNPs for branch number,distributed on chromosome 1,4,7,13,14,17,18 and 19;24 SNPs for pod number per plant,distributed on chromosome 2,4,6,9,13,14,15,18 and 19;9 SNPs for seed number per plant,distributed on chromosome 2 and 6;21 SNPs for 100 seed weight,distributed on chromosome 1,4,5,7,8,11,16,17 and 20;and 9 SNPs for seed yield per plant were detected,distributed on chromosome 2,5,14,15 and 18.3.Association analysis with NJAU 355K SoySNP array was performed to detected SNPs associated with pod dehiscence across five environments.A total of 128 SNPs were identified as significantly associated with pod dehiscence.Among these markers,112 SNPs that identified on chromosome 16 were located in the major QTL(qPDH1).1,10,3,1 and 1 SNPs were distributed on chromosome 1,8,9,11 and 18,respectively.Favorable SNPs and six haplotypes were identified based on 10 significant functional SNPs;Hap2 and Hap3 were considered as optimal haplotypes.In addition,two significant SNPs located on chromosome 9 were uncovered in two environments.Glyma09g06290 was identified as candidate gene based on these two significant SNPs.qRT-PCR results showed that the expression level of Glyma09g06290 was significantly increased in the late pod growth period,and exhibits significantly higher expression in the high-PPD varieties rather than that in the low-PPD varieties.This study sequenced the Glyma09g06290 gene in a subset of 20 accessions with high-PPD and 22 accessions with low-PPD and found 5 polymorphism sites,these 5 polymorphism sites were significantly associated with PPD.Correlation between the expression of Glyma09g06290 in extreme varieties and PPD value showed that Glyma09g06290 was positively correlated with the pod dehiscence(r=0.58,P<0.05).The above results confirmed that Glyma09g06290 was likely related to pod dehiscence in soybean.Furthermore,a functional dCAPS marker for Glyma09g06290 was developed4.By using association analysis in 96 wild soybean accessions with NJAU 355K SoySNP,SNPs associated with 5 yield-related traits were identified across multiple environments.A total of 41 SNPs were significantly associated with the yield-related traits in two or more environments,with 29,7,3,and 2 SNPs detected for 100-seed weight,maturity time,seed yield per plant and flowering time,respectively.BLAST search against the Glycine soja W05 reference genome was performed,20 candidate genes were identified based on these 41 significant SNPs.The expression patterns in different tissues and different stages of seed development indicated that the candidate gene GsCID1(Glysoja.04g010563)was highly expressed during seed development.Moreover,GsCID1 also harbored two significant SNPs-AX-93713187 and AX-93713188.The polymorphisms in this gene were associated with seed weight.By using the SNP within GsCID1,this study developed a dCAPS marker that was highly associated with seed weight and validated as a functional marker. |
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