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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.
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 the 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 t Both 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 results of genetic 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.