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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 cq SPA4b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。
In order to further clarify the genetic basis of kernel rate, we used the RIL population derived from ICGV 86699, an amphiploid of Zhongmu 5 with significant difference in kernel rate, with its phenotypic data and the first peanut-based SNP marker QTL mapping was carried out on kernels of three single enviroment and joint endemism using QTL Cartographer V.2.5 software, and a total of 28 QTLs were detected. The phenotypic variation explained by each QTL ranged from 3.98% to 13.77%, and the LOD values ranged from 2.59 to 7.36, of which 6 were major QTLs contributing more than 10.0%. Meta-QTL analysis identified seven consistent QTLs that were stably expressed in different environments. Consensus QTL cq SPA4b was detected in three single environments and united environments. Consistent QTL cq SPB6a was detected in three single environments with the average contribution rate of 11.86%. Compared with the results of previous studies, cq SPA5b was similar to the QTL interval of the outgrowth rate on A5 chromosome identified by two different groups. The results of this study laid a good foundation for the fine mapping of QTL for kernel rate and molecular marker-assisted breeding.