Quantitative Trait Locus Analysis On The Protein And Oil Contents In Soybean(Glycine Max[L.]Merri.)in Response To Planting Density

Soybean varieties suitable for high planting density allow greater yields.However,the seed protein and oil contents,which determine the value of this crop,can be influenced by planting density.Thus,it is important to understand the genetic basis of the responses of different soybean genotypes to planting density.In this study,the four-way recombinant inbred line population(FW-RILs,F_2:8)constructed by（Kenfeng 14×Kenfeng 15）×（Heinong 48×Kenfeng 19）was used as the test material,with 2.15×10⁵plants/ha（D1）and 3×10⁵plants/ha（D2）are planted for four partent and FW-RILs.The test sites were Harbin（2015 and 2016）,Keshan（2015）,Acheng（2016）and Shuangcheng（2016）.The field experiments were arranged in a split-plot design with three replications,obtain phenotypic data of protein and oil content.Using the advantages of the four-way recombination inbred line population,combined with SSR markers and SNP markers to construct genetic linkage maps for QTL mapping of protein and oil content.In addition,to predict the potential candidate genes affected by planting density to control protein and oil content based on the major-QTL mapped by the high-density genetic map.The results of this study are as follows:（1）Variance analysis show that genotype and genotype×density interaction effects are significant（P≤0.01）.The response of density also reached a significant level under different environment（P≤0.01）.（2）QTL were detected for protein and oil content based on SSR markerThe genetic map was constructed using 275 SSR marker.A total of 94 QTLs were detected on 19 of the 20 linkage groups in soybean.Of these,25 QTLs and 17 QTLs were located for protein content in2.15×10⁵ plants/ha and 3×10⁵ plants/ha,respectively.A single QTL accounted for 3.14%～13.36%of phenotypic variance,three QTLs were detected in two densities.The 17 remaining QTLs and 13 QTLs for oil content were detected in 2.15×10⁵ plants/ha and 3×10⁵ plants/ha,resectively.The explainable phenotypic variance were between 3.48%～12.82%,one QTL was detected in both densities.We identified 22 QTLs for protein and oil content under the response of density.Briefly,12 QTLs for protein content were identified on different linkage groups,including B2,C2,D1a,D1b,D2,H,J,K,M,and N,accounting for a phenotypic variance of 3.46%～18.20%.Moreover,10 QTLs for oil content were located on linkage groups A1,A2,B1,B2,D2,F,L,and N.The explainable phenotypic variations of single QTLs for oil content ranged from 3.87%～12.64%.83 of the 94 QTLs detected in the current study were also found in previous studies,and 10 QTLs（qPC-D1a-1,qPC-D2-2,qPC-J-1,qPC-M-3,q OC-A1-1,q OC-C1-3,q OC-D2-4,q RDOC-A1-1,q RDPC-D1a-1 and q RDPC-M-1）were newly located.（3）QTL were detected for protein and oil content based on SNP markerThe high-density map were constructed by 2332 SNP marker.65 QTLs were located at different densities.Among them,14 QTLs with and 14 QTLs were located for protein content under the 2.15×10⁵plants/ha and 3×10⁵ plants/ha,respectively,a single QTL explained a phenotypic variation of 5.22%～25.05%.20 QTLs and 17 QTLs for oil content were identified under 2.15×10⁵ plants/ha and 3×10⁵plants/ha,respectively,The explainable phenotypic variations of single QTLs for oil content ranged from4.77%～16.95%.A total of 49 QTLs were detected under the response of density,which 20 QTLs were detected for protein content,and a single QTL accounted for 3.64%～33.26%of phenotypic variation;18QTLs were located for oil content,with a single QTL accounted for 5.88%～24.68%of phenotypic variance.Among the all QTL detected,we found that 65 QTLs were in agreement with previous reports,17 QTLs for protein content（qPC-1-1,qPC-5-2,qPC-10-4,qPC-3-1,qPC-5-1,qPC-8-2,qPC-12-1,qPC-12-2,qPC-14-1,q RDPC-1-1,q RDPC-3-1,q RDPC-3-2,q RDPC-6-2,q RDPC-7-2,q RDPC-12-1,q RDPC-15-1,q RDPC-19-1）and 16 QTLs for oil content（q OC-7-1,q OC-10-1,q OC-12-2,q OC-18-2,q OC-19-2,q OC-8-2,q OC-9-2,q OC-13-2,q OC-18-1,q RDOC-5-2,q RDOC-5-3,q RDOC-6-1,q RDOC-6-2,q RDOC-13-1,q RDOC-13-2,q RDOC-19-1）were newly identified.This result laying the foundation for predicting candidate genes that control protein and oil content in the next step（3）In this study,fourty-three QTLs account for over 10%of the phenotypic variation under high density linkage mapping,based on 23 QTLs of a marker interval distance around 700 Kb detected under different densities and density responses.Pathway analysis revealed f our candidate genes involved in protein and oil biosynthesis/metabolism.These results improve understanding of the genetic underpinnings of protein and oil biosynthesis in soybean,laying the foundation for enhancing protein and oil contents and increasing yields in soybean.