An Integrated QTL Map of Fungal Disease Resistance in Soybean (Glycine max L. Merr):A Method of Meta-Analysis for Mining R Genes  

作　　者：WANG Jia-lin LIU Chun-yan WANG Jing QI Zhao-ming LI Hui HU Guo-hua CHEN Qing-shan 

机构地区：[1]College of Agriculture, Northeast Agricultural University, Harbin 150030, P.R.China [2]Land Reclamation Research ＆ Breeding Centre of Heilongjiang, Harbin 150090, P.R.China [3]The National Research Center of Soybean Engineering and Technology, Harbin 150050, P.R.China [4]College of Science, Northeast Agricultural University, Harbin 150030, P.R.China

出　　处：《Agricultural Sciences in China》2010年第2期223-232,共10页中国农业科学（英文版）

基　　金：supported by the funding from the National Natural Science Foundation of China(30971809);the National 973 Program of China(2004CB 117203-5);the National 948 Project of China[(2006-G1(A)];the National High-Tech R&D Program of China(863 Program, 2006AA100104-3);the Heilongjiang Foundation for University Key Teachers,China(1152G007)

摘　　要：Diseases caused by fungal pathogens account for approximately 50% of all soybean disease losses around the world. Conflicting results of fungal disease resistance QTLs from different populations often occurred. The objectives of this study were to： （i） evaluate evidence for reported fungal disease resistance QTLs associations in soybean and （ii） extract relatively reliable and useful information from the ＂real＂ QTLs and mine putative genes in soybean. An integrated map of fungal disease resistance QTLs in soybean was established with soymap 2 published in 2004 as a reference map. QTLs of fungal disease resistance developed from each of separate populations in recent 10 years were integrated into a combinative map for gene cloning and marker assisted selection in soybean. 107 QTLs from different maps were integrated and projected to the reference map with the software BioMercator 2.1. A method of meta-analysis was used to narrow down the confidence interval, and 23 ＂real＂ QTLs and their corresponding markers were obtained from 12 linkage groups （LG）, respectively. Two published R genes were found in these ＂real＂ QTLs intervals. Sequences in the ＂real＂ QTLs intervals were predicted by GENSCAN, and these predicted genes were annotated in Goblet. 228 resistance gene analogs （RGAs） in 12 different terms were mined. The results will lay the foundation for a bioinformatics platform combining abundant QTLs, and offer the basis for marker assisted selection and gene cloning in soybean.Diseases caused by fungal pathogens account for approximately 50% of all soybean disease losses around the world. Conflicting results of fungal disease resistance QTLs from different populations often occurred. The objectives of this study were to： （i） evaluate evidence for reported fungal disease resistance QTLs associations in soybean and （ii） extract relatively reliable and useful information from the ＂real＂ QTLs and mine putative genes in soybean. An integrated map of fungal disease resistance QTLs in soybean was established with soymap 2 published in 2004 as a reference map. QTLs of fungal disease resistance developed from each of separate populations in recent 10 years were integrated into a combinative map for gene cloning and marker assisted selection in soybean. 107 QTLs from different maps were integrated and projected to the reference map with the software BioMercator 2.1. A method of meta-analysis was used to narrow down the confidence interval, and 23 ＂real＂ QTLs and their corresponding markers were obtained from 12 linkage groups （LG）, respectively. Two published R genes were found in these ＂real＂ QTLs intervals. Sequences in the ＂real＂ QTLs intervals were predicted by GENSCAN, and these predicted genes were annotated in Goblet. 228 resistance gene analogs （RGAs） in 12 different terms were mined. The results will lay the foundation for a bioinformatics platform combining abundant QTLs, and offer the basis for marker assisted selection and gene cloning in soybean.

关 键 词：SOYBEAN fungal disease QTL META-ANALYSIS resistance gene analogs 

分 类 号：S572.034[农业科学—烟草工业] O177.91[农业科学—作物学]