QTL And Candidate Gene Mining Of Oil Content In Cottonseed Through Linkage And Association Analysis

Cotton is the fifth largest oil-bearing crop in the world,and cottonseed provides abundant oil resources.At present,most of the existing studies focus on fiber yield and quality traits,while relatively few researches on cottonseed quality were reported,which leads to a shortage of varieties with high fiber quality and high cottonseed oil content,resulting in the low utilization efficiency of cottonseed additional value.Two sets of high-quality upland cotton recombination inbred populations(CCRI70RILs of 250 F_5:8 populations constructed by two parents of sGKZhong156 and 901-001 for,and 0-153RILs of 196 F_6:9 populations constructed by two parents of sGK9708 and 0-153)and one natural populations of upland cotton（219accessions）were used to evaluate the oil content of cottonseeds in fourteen,eight,and four environments,respectively,and the oil content of cottonseeds was determined using nuclear magnetic resonance method.The interaction between genotype and environment type was analyzed in the study.Meanwhile,80K CHIP and SLAF-seq were chosen to genotype the above three populations,and stable QTLs/SNPs related to cottonseed oil content were identified by the strategies of QTL mapping and GWAS analysis,which combined RNA-seq technology to screen the candidate genes within the confidence intervals of QTLs/SNPs relate to cottonseed oil content.The main results of this study are as followed:（1）Correlation analysis results showed that oil content accumulation of the two sets of high fiber quality RILs depends on the common effects by genotype and environment.However,genotype effect was given priority to oil content accumulation of the upland cotton natural population,and the environment impact was relatively small.And in the different ecological zones,there was a trend on the holistic oil content of cottonseeds,just like as the highest recorded in the Yangtze river while the lowest recorded in the Yellow river.The results of structural equation analysis of CCRI70RILs showed that the direct effects of daily average rainfall and daily maximum temperature on cottonseed oil content,which could explain 19.60%of the cottonseed oil content variation,indicating that it could significantly affect cottonseed the oil content.The variation of meteorological factors was indirectly affected by geographical factors,and the accumulation of cottonseed oil content was then influenced.The CCRI70RILs were divided into three groups by systematic clustering method,of which GroupⅠconsisted of93 stains with an average oil content of 27.44%,and GroupⅡand GroupⅢincluded 106 stains with an average oil content of 33.36%and 54 stains with an average oil content of 30.71%,respectively.Comprehensive analyses on the above data,a total of twelve stains harboring ultra high-value oil content in different environments were selected and cultivated in this study.（2）CHIP and SLAF technologies were utilized to genotype the CCRI70RIL population for constructing the genetic linkage map,which combined the oil content data detected on cottonseeds from multiple environments to conduct QTL with composite interval mapping（CIM）method of Win QTL Cart 2.5 software.Seven and nineteen stable QTLs for cottonseed oil content were separately identified in more than three environments by the two genotyping methods,explaining 2.01～72.80%of the phenotypic variation.A total of twenty QTLs were detected by the two genotype methods,of which five common QTLs were detected.Based on the genotype results of 0-153RIL population with the integration of genetic linkage map using SSR,CHIP,and SLAF methods,a total of 21 QTLs were detected to be related to cottonseed oil content in more than two environments,explaining 4.87～13.02%of the phenotypic variation.Combined with the QTL mapping results of the two sets of RIL populations,31 QTLs for cottonseed oil content were totally detected,including 14 newly identified QTLs,among which qOC^slaf-c17-2 was an important QTL,explaining 30.64-54.03%of the phenotypic variation.Through SLAF genotyping of upland cotton natural population with combination of oil content data of cottonseeds from four environments,genome-wide association study（GWAS）analysis was conducted by GLM and MLM models,totally identifying fourteen multi-environment stable SNPs.There were seven common SNPs detected in the two models,chr05＿107481161 was detected simultaneously in the four environments,which is an important SNPs,and can explain 14.35%of phenotypic variation on average.Within the confidence intervals of the stable QTLs/SNPs,754 common encoding genes or transcription factors were screened from more than two environments,of which 58 candidate genes and seven transcription factors were found to be involved in lipid metabolism.Protein interaction analysis showed that these candidate gens could be divided into three modules,including thirteen Hub genes and five transcription factors,which mainly participated in carbon metabolism,coenzyme metabolism,fat biosynthesis,and cellular lipid metabolism.（3）Within the confidence intervals of the major QTLs qOC^Chip-C3-1,qOC^0-153-C3-2 for cottonseed oil content in chr3,and the natural population contains 20 haplotypes,Hub gene clusters related to lipid biosynthesis pathway were identified,including Ltn D,FER,PGK and RAV1.The flow of hexose or trisaccharide was regulated to transfer energy to seed fatty acid synthesis,and a group of regulators of oil synthesis,including LPLAT1 and PAH2,were found to coordinate key steps in the Lands cycle and Kennedy pathway that catalyze triacylglycerol synthesis.（4）Taken the parents of sGKzhong156 and 901-001 in CCRI70RIL population as the materials,24 ovule samples of 10,20,30,and 40 DPA during growth and development were selected for transcriptome sequencing.The RNA-seq results showed that two kinase genes,namely as GH＿A03G1075（NMT1）and GH＿D03G0968（CEL1）,and one transcription factor,namely as GH＿A11G2218（BHLH93）were identified within the confidence intervals of stable QTL,which might be involved in the process of lipid metabolism and synthesis.In this study,the oil content phenotype of cottonseeds in two sets of RIL populations and one set of natural population planted in multi-ecological environments,and the relationship between genotype and climate factors was preliminarily clarified.Combined with the genotyping results using SSR,CHIP,and SLAF methods,multi-environment stable QTLs and SNPs related to cottonseed oil content were explored by comprehensive analyses of QTL mapping and GWAS on the three populations and the interaction networks of proteins and the synthesis and accumulation model of cottonseed oil content were constructed.Transcriptome sequencing and q RT-PCR was further conducted to screen the candidate genes relevant to oil content.The results provide genetic basis and the candidate gene resources for breeding,introducing,and promoting the development of high oil-content varieties under different ecological conditions,which are greatly significant for the safety of edible vegetable oil and the sustainable development of the whole cotton industries around the world.