摘要： 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。

关键词: 大豆, RIL群体, 农艺性状, QTL

Abstract: TheQTL of some important agronomic traits analysis provides plant genetistsw ith a powerful tool for the analysis ofmolecular plant breeding structure and function. The materials of this research are a 176RIL popula - tions constructed from a cross between Jinda52 and Jinda57. W indowsQTL CartographerV2. 0, LOD> 2. 5were used to detectQTL concern to maturity date, flowering date, weight per plan, t weed weight per plan, t No. of pod per plan, t seeds per plan, t 100 -seedweigh, tPlant heigh, tste m thickness, No. of stem nods, No. of branch, height of 1st pod etc. 12 agronom ic traits. Results of these studies are as follows : the most effective QTLs of the 12 traits explained md2 21?32 %, fd2 48?11 %, wp1 7?01 %, swpp1 30?67 %, nppp2 41?32 %, spp1 8?56 %, sw4 41?46 %, ph1 52?51 %, st1 35?14 %, snn2 31?60 %, bn2 25?43 %, hp1 16?31 % of the total variation respectively. A ll 30QTLs distributed 5 link - age group of this tes, t most traits assembled the group c2( Dla), c5( C2), c7(M ), but part of the total 30QTLswas lo - cated on the same loc. i That suggested oneQTL could influencemore than one traits. Therewas 5 loci of thiskind. So the totalQTL was change from 30 to 23 if theQTLs located on the sa me locuswere counted as oneQTL.

Key words: Soybean, R IL population, Agronom ic traits, QTL

中图分类号: 

• S565.03