| Title: | Identification of QTLs associated with resistance to soybean cyst nematode races 2, 3 and 5 in soybean PI 90763 |
| Authors: | Guo, B., Sleper, D.A., Arelli, P.R., Shannon, J.G., Nguyen, H.T. |
| Source: | Theor. Appl. Genet. 2005, 103(8):1167-1173 |
| Abstract: | Abstract Root-knot nematodes (Meloidogyne spp.) can cause severe yield loss of soybean [Glycine max (L.) Merr.] in the southern production region of the USA. Planting root-knot nematode-resistant cultivars is the most effective method of preventing yield loss. DNA marker-assisted breeding may accelerate the development of root-knot nematode-resistant cultivars. RFLP markers have previously been used to identify quantitative trait loci (QTLs) conferring resistance to southern root-knot nematode [Meloidogyne incognita (Kofoid and White) Chitwood] (Mi) in a F2:3 soybean population created by crossing the resistant PI96354 and the susceptible ’Bossier.' A major QTL on linkage group (LG) O conditioning 31% of the variation in Mi gall number and a minor QTL on LG-G conditioning 14% of the gall variation were reported. With the development of SSR markers for soybean improvement, a higher level of mapping resolution and semi-automated detection has become possible. The objectives of this research were: (1) to increase the marker density in the genomic regions of the QTLs for Mi resistance on LG-O and LG-G with SSR markers; and (2) to confirm the effect of the QTLs in a second population and a different genetic background. With SSR markers, the QTL on LG-O was flanked by Satt492 and Satt358, and on LG-G by Satt012 and Satt505. Utilizing SSR markers flanking the two QTLs, marker-assisted selection was performed in a second F2:3 population of PI963542 Bossier. Results confirmed the effectiveness of marker-assisted selection to predict the Mi phenotypes. By screening the BC2F2 population of Prichard (3)2G93-9009 we confirmed that selection for the minor QTL on LG-G with flanking SSR markers would enhance the resistance of lines containing the major QTL (which is most-likely Rmi1). |