Meta-analysis to refine map position and reduce confidence intervals for delayed-canopy-wilting QTLs in soybean

Slow canopy wilting in soybean has been identified as a potentially beneficial trait for ameliorating drought effects on yield. Previous research identified QTLs for slow wilting from two different biparental populations, and this information was combined with data from three other populations to identify nine QTL clusters for slow wilting on Gm02, Gm05, Gm11, Gm 14, Gm17, and Gm19. The QTL cluster on Gm14 was eliminated because these QTLs appeared to be false positives. In the present research, QTLs from these remaining eight clusters were compiled onto the soybean consensus map for metaQTL analysis. Five model selection criteria were used to determine the most appropriate number of metaQTLs at these eight chromosomal regions. For a QTL cluster on Gm02, two meta-QTLs were identified, whereas for the remaining seven QTL clusters the single meta-QTL model was most appropriate. Thus, the analysis identified nine meta-QTLs associated with slow wilting. Meta-analysis decreased the confidence intervals from an average of 21.4 cM for the eight QTL clusters to 10.8 cM for the meta-QTLs. Averaged R-2 values of the nine meta-QTLs in eight QTL clusters were 0.13 and ranged from 0.09 to 0.22. Meta-QTLs on Gm11 and Gm19 had the highest R-2 values (0.22 and 0.20, respectively).