to increase the concentration of one at the expense of the other. Soybean [Glycine max (L.) Merr.] is an important crop becauseHardiness, brittleness, and gumminess are important of its high oil and protein concentration. However, there is an inverse relationship between seed protein and oil concentration, making it physical properties, which determine the overall quality difficult to improve both traits simultaneously. Molecular breeding of tofu. Protein concentration, particularly glycinin, demay be helpful to facilitate a balanced accumulation of desirable termines these properties in tofu, whereas seed size dealleles. The objective of this study was to identify quantitative trait termines the quality of soy sprouts (Liu, 1997). Small loci (QTL) governing soybean protein, oil and seed size. To achieve seeded soybeans are generally desired for high quality this objective, 101 F 6 -derived recombinant inbred lines (RIL) from soy sprouts and natto production, and combining higher a population developed from a cross of N87-984-16 ϫ TN93-99 were protein with large seed size is desirable for tofu producused. Heritability estimates on an entry mean basis for protein and tion. Genomic regions for seed size along with protein oil concentrations, and seed size were 0.66, 0.54, and 0.71, respectively. and oil QTL could be used in marker-assisted selection A total of 585 simple sequence repeat (SSR) molecular genetic mark-(MAS) for desired soybean types for soy food appliers were screened and 94 were polymorphic in the RIL. Single factor ANOVA was used to identify candidate QTL, which were then con-cations. firmed by composite interval mapping. One novel molecular marker Despite moderately high heritabilities (Burton, 1987), (Satt570) on molecular linkage group (MLG) G associated with a it is difficult to improve seed traits, particularly protein protein QTL was detected. Novel molecular markers (Satt274, Satt420, and oil concentration, simultaneously. MAS might be useand Satt479) located on MLG D1b, O, and O respectively and a ful in achieving specific goals if genomic regions controlpreviously reported marker (Satt317) located on MLG H were associling protein and oil concentration and seed size could be ated with oil QTL in this study. Molecular markers Satt002 (MLG D2) identified to improve selection indices more precisely. and Satt184 (MLG D1a) associated with seed size QTL were verified Several researchers have paved the way toward this whereas Satt147 (MLG D1a) was novel. The individual QTL explained goal (Brummer et al., 1997; Chung et al., 2003; Diers et 20.2, 9.4-15, and 10 to 16.5% of the phenotypic variation for protein al., 1992;Lee et al., 2001; Lee et al., 1996c). Qiu et al. and oil concentrations, and seed size, respectively. Thus, we identified major loci for improving soybean seed quality.

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Soybean [Glycine max (L.) Merr.] is the single largest source of protein in animal feed. However, a major limitation of soy proteins is their deficiency in sulfur-containing amino acids, methionine (Met) and cysteine (Cys). The objective of this study was to identify quantitative trait loci (QTL) associated with Met and Cys concentration in soybean seed. To achieve this objective, 101 F(6)-derived recombinant inbred lines (RIL) from a population developed from a cross of N87-984-16 x TN93-99 were used. Ground soybean seed samples were analyzed for Met and Cys concentration using a near infrared spectroscopy instrument. Data were analyzed using SAS software and QTL Cartographer. RIL differed (P<0.01) in Met and Cys concentrations, with a range of 5.1-7.3 (g kg(-1) seed dry weight) for Cys and 4.4-8.8 (g kg(-1) seed dry weight) for Met. Heritability estimates on an entry mean basis were 0.14 and 0.57 for Cys and Met, respectively. A total of 94 polymorphic simple sequence repeat molecular genetic markers were screened in the RIL. Single factor ANOVA was used to identify candidate QTL, which were confirmed by composite interval mapping using QTL Cartographer. Four QTL linked to molecular markers Satt235, Satt252, Satt427 and Satt436 distributed on three molecular linkage groups (MLG) D1a, F and G were associated with Cys and three QTL linked to molecular markers Satt252, Satt564 and Satt590 distributed on MLG F, G and M were associated with Met concentration in soybean seed. QTL associated with Met and Cys in soybean seed will provide important information to breeders targeting improvements in the nutritional quality of soybean.

Glycinin (11S) and β-conglycinin (7S) are important seed storage proteins in soybean [Glycine max (L.) Merr.].A major limitation of soybean seed storage proteins is their low levels of the sulfur-containing amino acids, methionine and cysteine, which are important nutritional components of protein meal. Glycinin contains significantly more S-containing amino acids than does β-conglycinin. Thus, detection of quantitative trait loci (QTL) that govern 11S may provide marker-assisted selection (MAS) opportunities to improve soybean total S-containing amino acids. The objective of this study was to detect and map QTL governing 7S and 11S fractions of soybean seed storage proteins. To achieve this objective, 101 F 6 -derived recombinant inbred lines (RIL) developed from a cross of N87-984-16 × TN93-99 were used. Storage proteins were extracted from all RIL and separated in 10-20% linear gradient polyacrylamide gels. Dried gels were scanned for individual subunits of storage protein with a densitometer equipped with a He-Ne laser light source. Data were converted to concentration for each subunit component and analyzed using SAS software. A significant (P < 0.05) difference among genotypes was found for glycinin and β-conglycinin. A total of 94 polymorphic simple sequence repeat molecular genetic markers were used in screening all RIL. Three QTL for glycinin (Satt461, Satt292, and Satt156) were distributed on linkage group (LG) D2, I, and L, respectively, whereas two QTL for conglycinin (Satt461 and Satt249) were distributed on LG D2 and J. Phenotypic variation explained by individual QTL ranged from 9.5 to 22%. These QTL may provide useful MAS opportunities for improvement of nutritional quality in soybean.Soybean is a major source of protein and amino acids for human and animal feeds in the world (1). However, soy protein is not perfect because of its low levels of the sulfur-containing essential amino acids, methionine and cysteine. Enhancing the concentration of nutritionally essential amino acids in soybean would improve soy meal quality and boost its inclusion in diets for humans and animals.Soybean storage protein has two major fractions, β-conglycinin (7S) and glycinin (11S), accounting for more than 70% of the total proteins (2). β-Conglycinin is a trimer with subunits α, α′, and β, and a M.W. of about 180 kDa. Glycinin is a hexamer with a M.W. of 360 kDa, consisting of acidic and basic subunits. Glycinin constitutes about 35% of the total seed storage protein (3). Glycinin has three to four times more S-containing amino acids (particularly methionine) than does β-conglycinin (4). In addition, the β subunit of conglycinin is known to be void of methionine and cysteine. Hence, the glycinin fraction may be more desirable than the β-conglycinin fraction in developing improved amino acid balance in soy meal. Both 7S and 11S are components of total seed protein, and there is a typical inverse relationship between 7S and 11S concentrations (5). Thus, glycinin can be increased at the expense of β-conglycinin. Mutants ...

There continues to be improvement in seed yields of soybean by conventional breeding, but molecular techniques may provide faster genetic gains. The objective of this study was to identify quantitative trait loci (QTL) associated with the agronomic traits seed yield, lodging, plant height, seed filling period and plant maturity in soybean. To achieve this objective, 101 F 6 -derived recombinant inbred lines (RIL) from a population developed from a cross of N87-984-16 · TN93-99 were used. Experiments were conducted in six environments during 2002-2003. Heritability estimates on an entry mean basis from data combined across environments ranged from 0.12 to 0.65 for seed yield and seed filling period, respectively. Composite interval mapping detected one QTL for yield (near Satt076), two for lodging (near Satt225 and Satt593) and four for maturity (near Satt263, Satt292, Satt293 and Satt591) in this population. Additional environmentally sensitive QTL for these traits, and for seed filling period and plant height are also reported. The QTL associated with agronomic traits that we report and the recently released germplasm (PI 636460) from this population may be useful in soybean breeding programmes.