基于高密度遗传图谱的芝麻籽粒品质相关性状QTL定位

QTL Mapping of Seed Quality Traits Based on High‑Density Genetic Map in Sesame

芝麻是我国重要的优质油料作物,对芝麻籽粒品质性状进行数量性状位点(QTL)定位对定向培育高品质芝麻品种具有重要意义。以豫芝4号为母本、孟加拉小籽为父本,分别构建F2、F2:3、BC1和BC1F2群体,结合特异位点扩增片段(SLAF)标记和简单重复序列(SSR)标记构建F2和BC1遗传图谱,以F2:3、BC1和BC1F23个群体的表型数据为基础,进行脂肪、蛋白质、芝麻素、芝麻林素含量等4个品质性状的QTL作图分析。结果表明,在F2:3群体中共检测到16个QTL,解释表型变异的5.08%~27.12%,其中仅有1个主效QTL qOC_10-1在2个环境中被重复检测到,分别解释表型变异的9.62%和27.12%。在BC1和BC1F2群体中共检测到35个QTL,其中3个主效QTL qOC_4-1、qOC_10-2和qSmin_7-2在3个环境中被重复检测到,分别解释表型变异的8.08%~12.42%、11.95%~12.60%和4.24%~10.56%;3个主效QTL qSmin_8、qSmol_5-2和qSmol_7-2在2个环境被重复检测到,分别解释表型变异的13.36%~26.75%、11.44%~14.33%和5.77%~12.38%。经过对2个图谱进行整合和比对分析,共发现10个QTL簇,其中QTL簇loci4、loci7、loci8和loci10均与多个性状相关联,并且均至少包含1个主效QTL,其对应的最大表型变异解释率分别为12.42%、12.38%、26.75%和27.12%。

Sesame(Sesamum indicum L.)is an important oilseed crop for the high oil content and quality.Understanding the genetic basis of seed quality trait is essential for improving the seed quality traits of sesame.To identify the QTLs associated with the seed oil,protein,sesamin,and sesamolin content in sesame,we developed F2,F2:3,BC1 and BC1F2 populations by crossing the Yuzhi 4 and BS lines to perform QTL mapping.A high‑density genetic map for the BC1 population was constructed using SLAF and SSR markers,and a genetic map for the F2 population was constructed using SSR markers.In the F2:3 population,16 QTLs for the seed oil,protein,sesamin,and sesamolin content were identified and explained 5.08%—27.12%of the phenotypic variations(PVs).Among these 16 QTLs,qOC_10‑1 was detected in two environments and explained 9.62%—27.12%of the PVs.In the BC1 and BC1F2 populations,35 QTLs for the seed oil,protein,sesamin,and sesamolin content were identified.Among these 35 QTLs,the major QTLs qOC_4‑1,qOC_10‑2,and qSmin_7‑2 were detected in three environments,explaining 8.08%—12.42%,11.95%—12.60%,and 4.24%—10.56%of the PVs,respectively.Three major QTLs qSmin_8,qSmol_5‑2,and qSmol_7‑2 were identified in two environments,explaining 13.36%—26.75%,11.44%—14.33%,and 5.77%—12.38%of the PVs,respectively.By integrating the two genetic maps,we identified 10 QTL clusters.It was worth noting that loci4,loci7,loci8,and loci10 harboring at least one major QTL and associating with more than two seed quality traits were identified,and the maximum explanation rates of phenotypic variation were 12.42%,12.38%,26.75%and 27.12%,respectively.