为进一步明确出仁率遗传基础,本研究以出仁率性状有显著差异的两亲本中花5号和ICGV 86699衍生的RIL群体为材料,以其表型数据结合栽培花生第一张基于SNP标记的高密度遗传图谱,采用Windows QTL Cartographer V.2.5软件的复合区间作图法,对3个单环境及联合环境下出仁率进行QTL定位,共检测到28个QTL。各QTL解释的表型变异为3.98%-13.77%,LOD值介于2.59-7.36之间,其中6个为贡献率大于10.0%的主效QTL。Meta-QTL分析鉴定出7个在不同环境下都能稳定表达的一致性QTL。其中一致性QTL cqSPA4b在3个单环境和联合环境中都能检测到,一致性QTL cq SPB6a在3个单环境中能检测到,且平均贡献率为11.86%。与前人的研究结果比较发现,cq SPA5b与另外两个不同群体鉴定出的A5染色体上出仁率QTL区间相似。本研究结果为出仁率QTL的精细定位及分子标记辅助育种奠定了良好基础。
Shelling percentage is an important factor influencing the peanut yield. In order to dissect the genetic basis of shelling percentage, a RIL population was used from the cross of Zhonghua 5 and ICGV 86699, both of which have high and low shelling percentage respectively. By combining the phenotypic data with the first SNP-based high density genetic map in cultivated peanut, we identified 28 QTLs in the conditions of 3 single-environments and joint cross environments using the CIM (composite interval mapping) method of Windows QTL Cartographer V. 2.5. The QTLs individually explained 3.98–13.77% of the phenotypic variation with LOD value of 2.59-7.36. Six QTLs which explained more than 10.0% phenotypic variation were considered as major loci. Through meta-QTL analysis,we identified seven consensus QTLs which were stable in multivariate conditions. Consensus QTL of cqSPA4b was found occurring in four conditions, and consensus QTL of cqSPB6a was detectable in three conditions with the average explained phenotypic variation of 11.86%. To compare with former research results, cqSPA5b was also found to be identical to similar QTL region on A5 chromosome in other two different populations. The results of this study contributed to QTL fine mapping and marker assisted breeding of shelling percentage.