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以晋大52为母本、晋大57为父本及其176个RIL群体后代为材料,应用WinQTLCart V2.0软件采用复合区间作图法对所选取对象(LOD>2.5)的生育期、开花日数、单株质量、单株粒重、单株粒数、单株荚数、百粒重、株高、茎粗、主茎节数、分枝数、结荚高度等12个农艺性状进行QTL定位分析。结果表明:效应最大的QTL可解释的遗传变异分别为md221.32%、fd248.11%、wp17.01%、swpp130.67%、nppp241.32%、spp18.56%、sw441.46%、ph152.51%、st135.14%、snn231.60%、bn225.43%、hp116.31%。检测到的30个QTL分布于山西农业大学大豆研究实验室建立的5个连锁群上,大多数性状聚集在c2(Dla)、c5(C2)、c7(M)等连锁群上,部分QTL在连锁群上的位置相同,即为同一位点,这类位点共有5个,除去重复计算部分,实际位点数为23个。
Using JinDa 52 as female parent, JinDa 57 as male parent and 176 RIL herds as the material, using WinQTLCart V2.0 software, the compound interval mapping method was used to select the object (LOD> 2.5) QTLs were performed on 12 agronomic traits such as number of days per plant, weight per plant, weight per plant, number of per plant, number of pods per plant, weight per plant, height of plant, diameter of stem, number of nodes of main stem, number of branches, pod height Positioning analysis. The results showed that the genetic variations explained by QTL with the most effect were md221.32%, fd248.11%, wp17.01%, swpp130.67%, nppp241.32%, spp18.56%, sw441.46%, ph152 .51%, st135.14%, snn231.60%, bn225.43%, hp116.31%. The detected 30 QTLs were located in 5 linkage groups established by Soybean Research Laboratory of Shanxi Agricultural University. Most of the traits were clustered in linkage groups c2 (Dla), c5 (C2) and c7 (M) The same location on the linkage group, that is the same site, a total of five such sites, excluding duplication of computing part of the actual number of sites 23.