Molecular markers provide the opportunity to identify marker-quantitative trait locus (QTL) associations in different environments and populations. Two soybean [Glycine max (L.) Merr.] populations, 'Young' x PI 416 937 and PI 97100 x 'Coker 237', were evaluated with restriction fragment length polymorphism (RFLP) markers to identify additional QTLs related to seed protein and oil. For the Young x PI 416937 population, 120 F4-derived lines were secored for segregation at 155 RFLP loci. The F4-derived lines and two parents were grown at Plains, G.a., and Windblow and Plymouth, N.C. in 1994, and evaluated for seed protein and oil. For the PI 97100 x Coker 237 population, 111 F2-derived lines were evaluated for segregation at 153 RFLP loci. Phenotypic data for seed protein and oil were obtained in two different locations (Athens, G.a., and Blackville, S.C.) in 1994. Based on single-factor analysis of variance (ANOVA) for the Young x PI 416937 population, five of seven independent markers associated with seed protein, and all four independent markers associated with seed oil in the combined analysis over locations were detected at all three locations. For the PI 97 100 x Coker 237 population, both single-factor ANOVA and interval mapping were used to detect QTLs. Using single-factor ANOVA, three of four independent markers for seed protein and two of three independent markers for seed oil were detected at both locations. In both populations, singlefactor ANOVA, revealed the consistency of QTLs across locations, which might be due to the high heritability and the relatively few QTLs with large effects conditioning these traits. However, interval mapping of the PI 97100 x Coker 237 population indicated that QTLs identified at Athens for seed protein and oil were different from those at Blackville. This might result from the power of QTL mapping being dependent on the level of saturation of the genetic map. Increased seed protein was associated with decreased seed oil in the PI 97100 x Coker 237 population (r = -0.61). There were various common markers (P[Symbol: see text]0.05) on linkage groups (LG) E, G,H,K, and UNK2 identified for both seed protein and oil. One QTL on LG E was associated with seed protein in both populations. The other QTLs for protein and oil were population specific.
Seed weight (SW) is a component of soybean, Glycine max (L.) Merr., seed yield, as well as an important trait for food-type soybeans. Two soybean populations, 120 F4-derived lines of 'Young'xPI416937 (Pop1) and 111 F2-derived lines of PI97100x'Coker 237' (Pop2), were mapped with RFLP makers to identify quantitative trait loci (QTLs) conditioning SW across environments and populations. The genetic map of Pop1 consisted of 155 loci covering 973 cM, whereas Pop2 involved 153 loci and covered 1600 cM of map distance. For Pop1, the phenotypic data were collected from Plains, GA., Windblow, N.C., and Plymouth, N.C., in 1994. For Pop2, data were collected from Athens, GA., in 1994 and 1995, and Blackville, S.C., in 1995. Based on single-factor analysis of variance (ANOVA), seven and nine independent loci were associated with SW in Pop1 and Pop2, respectively. Together the loci explained 73% of the variability in SW in Pop1 and 74% in Pop2. Transgressive segregation occurred among the progeny in both populations. The marker loci associated with SW were highly consistent across environments and years. Two QTLs on linkage group (LG) F and K were located at similar genomic regions in both populations. The high consistency of QTLs across environments indicates that effective marker-assisted selection is feasible for soybean SW.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.