| Soybean is one of the important sources of human plant protein,edible oil and fodder.It originated in China and is the most important grain and oil crop and cash crop in China's national economy.Soybean industry is related to national food security,but more than 80%of the gap between production and demand depends on imports.To further dig the potential of soybean high yield and improve the level of soybean yield per unit area is an urgent task and goal for soybean breeders.Modern molecular breeding technology can speed up the breeding process and improve the efficiency of variety selection.Using molecular marker technology to locate QTL for important yield traits and mine related genes have important theoretical and practical significance for breeding high-yield soybean varieties.Plant height(PH)and node number in main stem(NNMS)are key agronomic traits that positively related with seed yield,they are controlled by genotype and influenced by environment,such as density.In this study,a four-way recombinant inbred lines(FW-RIL)with 144 families derived from Kenfeng 14,Kenfeng 15,Heinong 48,Kenfeng 19 was used as experimental materials,based on a constructed SNP genetic map of the population,QTL/QTN for PH and NNMS and their response to density under 2.2×10~5plant/ha and 3×10~5plant/ha in five environments were identified by linkage analysis and GWAS.Then the selected stable QTL/QTN(could identified in two densities or multiple environment or multiple methods or co-location with QTL)were used to predict potential genes related to PH and NNMS through Kyoto Encyclopedia of Genes and Genomes combined with GO number and NCBI database.Finally,the candidate genes were verified by RT-q PCR.This research will enrich the QTL of PH and NNMS,and improve the precision of gene mining,as well as reveal the molecular mechanisms of PH and NNMS in response to density,subsequently lay the foundation for marker-assisted selection breeding to increase soybean yield.The main results as follows:(1)Through analyzing phenotypic data of 4 parents and 144 strains of FW-RIL in PH and NNMS under two densities in five environments,the results showed that there were significant difference of PH and NNMS in population,showing a strong bilateral transgressive segregation,and displaying a typical normal distribution,the variance of genotype was significant,indicating that there were real and abundant genetic variation in the population,FW-RIL were suitable for mapping QTL controlling PH and NNMS.The results of variance analysis also showed that the variance of genotype×density,genotype×environment and genotype×density×environment of PH and NNMS were significantly different(P<0.01),indicating that PH and NNMS were specific for different environments and densities.When the density increased from D1 to D2,PH and NNMS of most strains increased,and the extreme difference of heritability between joint and single environment showed the response of genotype to change of density among environments.(2)Through linkage analysis,55 QTL controlling PH were detected under two densities in five environments,26 and 20 were identified specifically in D1 and D2,respectively,and 9 were discovered commonly in D1 and D2.As far as five environments,17,5,12,2 and 11 QTL for PH were detected solely in E1,E2,E3,E4 and E5,respectively,and 8 QTL for PH were repeatedly found in more than two environments.14 QTL were identified both by IM and ICIM.That is to say,a total of 15 stable QTL for PH were identified(in multiple densities or environments or methods).Eighteen QTL for PH response to density(RD)were detected under two densities in five environments(8 were associated with QTL under D2),4 RD QTL were identified by both IM and ICIM,which could be called stable RD QTL for PH.(3)Through GWAS,35 QTN controlling PH were detected under two densities in five environments,13 and 21 were identified specifically in D1 and D2,respectively,and 1 were discovered commonly in D1 and D2.As far as five environments,7,8,9,9 and 3 QTN for PH were detected solely in E1,E2,E3,E4 and E5,respectively,and 1 QTN for PH were repeatedly found in more than two environments.ISIS EM-BLASSO,p LARm EB,FASTmr EMMA,mr MLM,FASTmr MLM were used to detected QTN for PH,9 QTN were identified by more than two methods.Consequently,a total of 9 stable QTL for PH were identified(in two densities or multiple environments or more than two methods).Seven RD QTN for PH were detected under two densities in five environments(5 were associated with PH under D2),2 RD QTL were identified by more than two multiple locus GWAS methods,which could be called stable RD QTL for PH.Six QTN,co-located in the interval of QTL with a longer genome length over 3000 kb.(4)Through linkage analysis,31 QTL controlling NNMS were detected under two densities in five environments,16 and 10 were identified specifically in D1 and D2,respectively,and 5 were discovered commonly in D1 and D2.As far as five environments,10,3,5,7 and 10 QTL for NNMS were detected solely in E1,E2,E3,E4 and E5,respectively,and 3 QTL for NNMS were repeatedly found in more than two environments.Eleven QTL were identified both by IM and ICIM.That is to say,a total of 11 stable QTL for NNMS were identified(in multiple densities or environments or methods).Fourteen RD QTL for NNMS were detected under two densities in five environments(7 were associated with QTL for NNMS),6 RD QTL were identified by both IM and ICIM,which could be called stable RD QTL for NNMS.(5)Through GWAS,52 QTN controlling NNMS were detected under two densities in five environments,34 and 18 were identified specifically under D1 and D2,respectively.As far as five environments,11,14,14,6 and 7 QTN for NNMS were detected solely in E1,E2,E3,E4 and E5,respectively.ISIS EM-BLASSO,p LARm EB,FASTmr EMMA,mr MLM,FASTmr MLM were used to detected QTN for NNMS,17 QTN were identified by more than two methods.Consequently,a total of 17 stable QTN for NNMS were identified(in two densities or multiple environments or more than two methods).Thirty-four RD QTN for NNMS were detected under two densities in five environments(5 were associated with QTN under D2),one RD QTL were identified by more than two environments and 8 RD QTL were identified by more than two multiple locus GWAS methods,which could be called stable RD QTL for NNMS.Among all the QTN,twenty-four QTN were co-located in the interval of QTL detected by linkage analysis,15 of which could explain phenotypic variation more than 10%.(6)Combining the results of linkage analysis and GWAS,genome interval of 8 QTL(ql PH-5-4,ql PH-6-2,ql PH-6-3,ql PH-9-2,ql PH-15-1,ql PH-16-6,ql PH-18-2,ql RDPH-3-4)and the interval of 100 kb on either side of 16 QTN(qn PH-1-2,qn PH-4-2,qn PH-6-2,qn PH-7-1,qn PH-9-3,qn PH-10-1,qn PH-11-1(qn RDPH-11-1),qn PH-13-1,qn RDPH-13-1,qn PH-15-1,qn PH-18-2,qn PH-19-1,qn PH-19-2(qn RDPH-19-1),qn RDPH-19-2,qn RDPH-19-3,qn PH-20-2)were used to select potential genes related to PH.The results showed that 6 genes were considered as potential candidate genes regulating PH,which were Glyma.04G242200,Glyma.06G101500,Glyma.07G056900,Glyma.10G158000,Glyma.13G371400,Glyma.19G182600.The result of RT-q PCR showed that the genes related with the difference of plant height.(7)Combining the results of linkage analysis and GWAS,genome interval of 5 QTL(ql NN-6-1,ql NN-6-2,ql NN-17-1,ql NN-19-1,ql RDNN-3-1)and the interval of 100 kb on either side of 27QTN(qn NN-1-1,qn NN-1-3,qn NN-4-1(qn RDNN-4-1),qn NN-4-2,qn NN-4-3,qn NN-6-2,qn NN-7-2,qn NN-7-4,qn NN-9-1,qn NN-9-4,qn NN-10-2,qn NN-11-1,qn NN-12-1,qn NN-13-2,qn NN-13-3(qn RDNN-13-3),qn NN-13-4,qn NN-15-1,qn NN-18-2,qn NN-18-3,qn NN-19-2,qn RDNN-5-1,qn RDNN-5-3,qn RDNN-7-1,qn RDNN-9-1,qn RDNN-9-2,qn RDNN-13-1,qn RDNN-14-1)were used to select potential genes related to NNMS.The results showed that 4genes were were speculated as potential candidate genes regulating NNMS,which were Glyma.06G094400,Glyma.06G147600,Glyma.19G160800 and Glyma.19G161100.The result of RT-q PCR showed that the genes related with the difference of node number in main stem. |
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