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以高密度遗传图IBM2Neighbors整合公开发表的、控制68个性状的1201个玉米QTL,构建了用于分子标记发掘、QTL定位、基因克隆及分子标记辅助选择的综合图谱,并将结果融入本地化数据库CMap软件.利用CMap比较玉米QTL综合图和水稻QTL图谱发现,玉米和水稻QTL成簇分布具有普遍性;22个玉米株高QTL与64个水稻株高QTL位于标记水平上的共线性区域,43个玉米产量QTL与7个水稻QTL位于标记水平上的共线性区域.以控制玉米株高的QTL为例,利用overview的分析方法对127个QTL进行优化,定位了40个“真实”QTL,提高了QTL定位的准确性和有效性,发现了玉米和水稻株高相关QTG(quantitativetraitgene)的候选基因.本研究为大量玉米QTL信息的有效利用搭建了重要的生物信息学平台.
A total of 1201 maize QTLs with 68 traits were published in a high-density genetic map IBM2Neighbors. A comprehensive map for molecular marker mining, QTL mapping, gene cloning and molecular marker-assisted selection was constructed and integrated into the localization database CMap software.Comparison of CMap map and QTL map of rice showed that the QTL clustering distribution of maize and rice was universal. CMt of 22 maize lines shared the collinearity with 64 QTLs at marker level Maize QTLs and seven rice QTLs located at the marker level were co-linear.With the QTL controlling plant height as an example, we analyzed 127 QTLs using overview analysis and mapped 40 “true” QTLs The accuracy and validity of QTL mapping and the discovery of QTG (candidate genes for QTL related to QTG in maize and rice were also investigated.) This study constructed an important bioinformatics platform for effective utilization of QTL information in large numbers of maize.