Identification of quantitative trait loci controlling nodulation and shoot mass in progenies from two Brazilian soybean cultivars

Abstract

Nitrogen (N) demand of soybean [ Glycine max (L.) Merrill] can be supplied via biological nitrogen fixation (BNF), however, higher yielding cultivars increase plant demand for N. Phenotypes differing for traits associated with biological nitrogen fixation result from the expression of the multiple genes of both the host plant and the microsymbiont, but limited studies have been done on the genetics of the soybean BNF. Integrated maps of soybean with simple sequence repeat (SSR) markers [Cregan, P.B., Jarvik, T., Bush, A.L., Shoemaker, R.C., Lark, K.G., Kahler, A.L., Kaya, N., Van Toai, T.T., Lohnes, D.G., Chung, J., Specht, J.E., 1999. An integrated genetic linkage map of the soybean genome. Crop Sci. 39, 1464–1491.] offer an excellent opportunity for the identification of traits related to BNF. This study aimed at the identification of quantitative trait loci (QTLs) controlling BNF and nodulation in an F 2 population of 160 plants derived from an intraspecific cross between two Brazilian cultivars, Embrapa 20 × BRS 133, previously identified as having good potential for mapping of QTLs [Nicolás, M.F., Arias, C.A.A., Hungria, M., 2002. Genetics of nodulation and nitrogen fixation in Brazilian soybean cultivars. Biol. Fertil. Soils 36, 109–117.]. From 252 SSR markers tested in the parental genotypes 45 were polymorphic with high heterozygotes resolution. Mapping was performed with those 45 SSR markers for nodulation [nodule number (NN) and nodule dry weight (NDW)] and plant growth [shoot dry weight (SDW)] phenotypes in F 2:3 lines. A total of 21 SSR loci were mapped with a likehood of odds (LOD) value of 3.0 and a maximum Haldane distance of 50 cM, and were distributed in nine linkage groups with coverage of 251.2 cM. The interval mapping analysis with Mapmaker/QTL revealed two genomic regions associated with NN and NDW, with a contribution of putative QTLs of 7.1 and 10%, respectively. The regression analysis identified 13 significant associations between the marker loci and QTLs due to additive effects, with some of them being significantly associated with more than one phenotypic trait. Effects were observed in all variables studied, ranging from 2 to 9%. A one-way analysis of variance (ANOVA) also detected 13 significant associations, related to dominance effects. A two-way-ANOVA showed six epistatic interactions among non-linked QTLs for SDW, NN and NDW, explaining up to 15% of the trait variation and increasing the phenotypic expression from 8 to 28%. The data obtained in this work establish the initial stage for additional studies of the QTLs controlling BNF and indicate that effective marker-assisted selection using SSR markers may be feasible for enhancing BFN traits in soybean breeding programs.