东北大豆种质群体百粒重QTL-等位变异的全基因组解析

Genome-Wide QTL-Allele Dissection of 100-Seed Weight in the Northeast China Soybean Germplasm Population

【目的】对东北大豆种质群体百粒重性状进行全基因组关联分析,全面解析中国大豆主产区百粒重QTL-等位变异遗传构成,为东北地区大豆籽粒大小遗传改良提供理论基础。【方法】以东北地区育种和生产上常用的290份大豆材料作为试验群体,于2013和2014年在东北第二生态亚区的克山、牡丹江、佳木斯和长春4个地点进行百粒重表型鉴定试验。利用RAD-seq方法对试验群体进行基因组测序分析,对原始SNP数据进行过滤及填补缺失数据后,最终获得了82966个高质量的SNP标记。根据限制性两阶段多位点全基因组关联分析(restricted two-stage multi-locus genome-wide association analysis,RTM-GWAS)方法,首先构建获得15546个具有复等位变异的SNPLDB标记,然后使用两阶段多位点模型对百粒重性状进行全基因组关联分析。对检测到的百粒重关联SNPLDB标记位点附近(50 kb范围内)的基因进行分析,根据基因内SNP与SNPLDB标记位点之间关联性的卡方测验,筛选可能与百粒重性状相关的候选基因并进行功能注释。最后基于检测的百粒重QTL-等位变异体系分析了不同熟期组材料间的遗传分化。【结果】试验群体百粒重变异范围为18.3—20.7 g,性状遗传率为92.3%。RTM-GWAS方法共检测到76个与大豆百粒重性状关联的SNPLDB标记位点,其中15个位点主效不显著,另外61个主效显著位点解释了65.40%的表型变异;68个与环境互作效应显著的位点解释了17.46%的表型变异,另外8个位点与环境互作效应不显著。在检测到的76个位点中有34个位点与已报道的30个百粒重QTL重叠,另外42个位点为本研究新检测百粒重位点。基于检测的SNPLDB标记位点,共筛选到137个百粒重相关候选基因,功能注释显示这些候选基因不仅参与大豆百粒重的调节,还参与了初级新陈代谢、蛋白质修饰、物质运输、胁迫响应和信号转导等。对各熟期组间QTL-等位变异的遗传分化分析显示,尽管熟期组间百粒重差异不明显,但其QTL-等位变异遗传结构却发生了新生和汰除的变化。【结论】RTM-GWAS方法能相对全面地解析东北大豆种质群体百粒重QTL-等位变异遗传构成。东北大豆种质群体百粒重由大量QTL调控,且QTL与环境互作效应大,QTL存在丰富的复等位变异。由RTM-GWAS方法建立的QTL-等位变异矩阵为群体遗传及演化研究提供了新工具。

【Objective】A genome-wide association study in the Northeast China soybean germplasm population was conducted for a relatively thorough detection of the QTL-allele constitution of 100-seed weight,which may provide a theoretical basis for soybean breeding for seed size improvement.【Method】In the present study,a total of 290 soybean accessions that were frequently used for soybean breeding and production in the Northeast China were tested in 2013 and 2014 for 100-seed weight at four locations,including Keshan,Mudanjiang,Jiamusi and Changchun,which are all in the second sub-ecoregion of the Northeast China.RAD-seq(restriction site-associated DNA sequencing)was used for SNP genotyping,and 82966 high-quality SNPs were obtained after filtering and imputation.According to the RTM-GWAS(restricted two-stage multi-locus genome-wide association analysis)method,firstly a total of 15546 multi-allelic SNPLDBs were constructed,and then a multi-locus model was used for genome-wide association study of 100-seed weight.The genes near(within 50kb)the detected SNPLDBs were analyzed,and candidate genes for 100-seed weight were identified and annotated according to Chi-square test of independence between the SNPs within genes and the detected SNPLDBs.Finally,genetic differentiation among maturity groups were investigated based on the detected QTL-allele system of 100-seed weight.【Result】The 100-seed weight of the present population ranged from 18.3 to 20.7 g,and the trait heritability was 92.3%.A total of 76 SNPLDBs were detected to be associated with 100-seed weight,among which there were 15 SNPLDBs with non-significant main effect and the 61 SNPLDBs with significant main effect explained 65.40% phenotypic variation.There were 68 SNPLDBs that had significant interaction effect with environment and explained 17.46% phenotypic variation.In addition,34 out of 76 detected SNPLDBs overlapped 30 previously reported QTLs and 42 SNPLDBs were novel loci.A total of 137 candidate genes for 100-seed weight were annotated in the detected SNPLDB regions,and functional annotation showed that these genes were not only involved in regulation of 100-seed weight,but also involved in primary metabolism,translation,protein modification,material transport,stress response and signal transduction,etc.Although there was no obvious difference in the 100-seed weight among different maturity groups,genetic differentiation analysis showed varying changes of allele emergence and exclusion in QTL-allele structure of 100-seed weight among maturity groups.【Conclusion】The RTM-GWAS method used in the present study provided a relatively thorough detection of genome-wide QTLs and their multiple alleles for 100-seed weight in the Northeast China soybean germplasm population.The 100-seed weight of the Northeast China soybean germplasm population was controlled by a large number of QTLs with large significant interaction effect with environment,and there was also abundant multiple allelic variation in these QTLs.The QTL-allele matrix established from RTM-GWAS provided an efficient tool for population genetics and evolution study.