Genetic Dissection of Resistance to Pseudomonas amygdali pv. tabaci in Soybean [Glycine max (L.) Merr.] by Linkage Analysis.

Soybeans [Glycine max (L.) Merr.] are susceptible to many diseases including fungal diseases such as soybean sudden death syndrome (SDS). Several studies reported SDS resistance quantitative trait loci (QTL) on the soybean genome using different recombinant inbred line (RIL) populations and low density genetic linkage maps. High density exclusively single nucleotide polymorphisms-based (SNP-based) maps were not yet reported in soybean. The objectives of this study were (1) to construct a high density SNP-based genetic linkage map of soybean using the ‘PI438489B’ by ‘Hamilton’ (PIxH, n=50) recombinant inbred line population, and (2) to map QTL for SDS resistance using this high-density reliable genetic SNP-based map. The PI438489B by Hamilton high-density SNP-based genetic map was a high density map composed of 31 LGs, 648 SNPs, and covered 1,524.7 cM with an average of 2.37 cM between two adjacent SNP markers. Fourteen significant QTL were identified for SDS resistance using interval mapping (IM) and composite interval mapping (CIM) with LOD scores that ranged between 2.6 and 5.0. Twelve QTL were identified for foliar disease severity (FDS) and three QTL for root rot severity (RRS) of which one QTL underlain both FDS and RRS. The fourteen QTL were mapped onto ten separate chromosomes of the soybean genome. Seven of the intervals encompassing the QTL had been identified previously (on LGs C1, C2, D1b, G, L, N and O) associated with resistance to SDS but seven were novel (LGs A2 (2), B1, C2, D1a, D1b and O). We constructed the first PI438489B by Hamilton exclusively SNP-Based map and identified fourteen QTL that underlie SDS resistance including both resistances to foliar and root rot symptoms caused by Fusarium virguliforme infection. The QTL discovered here for SDS resistance could be useful to include in breeding programs in developing soybean cultivars resistant to SDS.

Soybeans [Glycine max (L.) Merr.] are susceptible to many diseases including fungal diseases such as soybean sudden death syndrome (SDS). Several studies reported SDS resistance quantitative trait loci (QTL) on the soybean genome using different recombinant inbred line (RIL) populations and low density genetic linkage maps. High density exclusively single nucleotide polymorphisms-based (SNP-based) maps were not yet reported in soybean. The objectives of this study were (1) to construct a high density SNP-based genetic linkage map of soybean using the ‘PI438489B’ by ‘Hamilton’ (PIxH, n=50) recombinant inbred line population, and (2) to map QTL for SDS resistance using this high-density reliable genetic SNP-based map. The PI438489B by Hamilton high-density SNP-based genetic map was a high density map composed of 31 LGs, 648 SNPs, and covered 1,524.7 cM with an average of 2.37 cM between two adjacent SNP markers. Fourteen significant QTL were identified for SDS resistance using interval mapping (IM) and composite interval mapping (CIM) with LOD scores that ranged between 2.6 and 5.0. Twelve QTL were identified for foliar disease severity (FDS) and three QTL for root rot severity (RRS) of which one QTL underlain both FDS and RRS. The fourteen QTL were mapped onto ten separate chromosomes of the soybean genome. Seven of the intervals encompassing the QTL had been identified previously (on LGs C1, C2, D1b, G, L, N and O) associated with resistance to SDS but seven were novel (LGs A2 (2), B1, C2, D1a, D1b and O). We constructed the first PI438489B by Hamilton exclusively SNP-Based map and identified fourteen QTL that underlie SDS resistance including both resistances to foliar and root rot symptoms caused by Fusarium virguliforme infection. The QTL discovered here for SDS resistance could be useful to include in breeding programs in developing soybean cultivars resistant to SDS.

Khanal, R., Navabi, A. and Lukens, L. 2015. Linkage map construction and quantitative trait loci (QTL) mapping using intermated vs. selfed recombinant inbred maize line (Zea mays L.). Can. J. Plant Sci. 95: 1133–1144. Intermating of individuals in an F2 population increases genetic recombination between markers, which is useful for linkage map construction and quantitative trait loci (QTL) mapping. The objectives of this study were to compare the linkage maps and precision of QTL detection in an intermated recombinant inbred line (IRIL) population and a selfed recombinant inbred line (RIL) population. Both, IRIL and RIL, populations were developed from Zea mays inbred lines CG60 and CG102. The populations were grown in two environments to evaluate traits, and inbred lines from each population were genotyped with SSR and SNP markers for linkage map construction and QTL identification. In addition, we simulated RIL and IRIL populations from two inbred parents to compare the precision of QTL detection between simulated RIL and IRIL populations. In the empirical study, the linkage map was longer in RIL as compared with IRIL, and the average QTL support interval was reduced by 1.37-fold in the IRIL population compared with the RIL population. We detected 16 QTL for flowering time, plant height, leaf number, and stay green in at least one recombinant inbred line population. Two out of 16 QTL were shared between two recombinant inbred line populations. In the simulation study, the QTL support interval was reduced by 1.66-fold in the IRIL population as compared with the RIL population and linked QTL were identified more frequently in IRIL population as compared with RIL population. This study supports the utility of intermated RIL populations for precise QTL mapping.

The relatively low genomic variation of current U.S. soybean [Glycine max (L.) Merill] cultivars constrains the improvement of grain yield, seed quality, and other agronomic traits within soybean breeding programs. Recently, a substantial effort has been undertaken to introduce novel genetic diversity present in wild soybean (Glycine soja Siebold and Zucc.) into new elite cultivars, in both public and private applied soybean breeding programs. The objectives of this research were to evaluate the phenotypic diversity within a core collection of 80 G. soja plant introductions (PIs) in the United States Department of Agriculture National Genetic Resources Program that were collected in China, Japan, Russia, and South Korea, and to analyze the correlations between agronomic and seed composition traits. Field tests were conducted in Missouri and North Carolina during three years, 2013, 2014, and 2015, in a randomized complete block design (n=3). The phenotypic data collected included plant maturity date, seed weight, and the seed concentration of protein, oil, essential amino acid, fatty acid, and soluble carbohydrates. Analyzing the data from six environments, we found genotype was a significant (p less than 0.0001) source of variation for maturity date, seed weight, seed protein and amino acids, seed oil and fatty acids, and seed carbohydrates. Significant correlations were observed between numerous traits. The core collection had lower seed weight, higher seed content of protein, linolenic acid, raffinose and stachyose but lower seed content of oil and oleic acid than those of the cultivated soybean lines that were used as checks. The amino acid profile of the core collection was significantly different from that of the checks. An association analysis revealed 19 SNP that were significantly associated with maturity, seed weight, and seed contents of aspartic acid, glutamine, palmitic acid, oleic acid, and linoleic acid. The information and data collected in this study will be invaluable in guiding soybean breeders and geneticists in selecting promising Glycine soja plant introductions for research and cultivar improvement. In addition the identification of quantitative trait loci (QTLs) associated with the contents of seed protein and oil, maturity, branching traits, height, lodging, and yield in a recombinant inbred line (RIL) population developed from one single F2 plant from the cross between Osage and PI593983 was carried out. The mapping population in this study included 164 F4:6 recombinant inbred lines (RILs) derived from a cross between Osage, a cultivated soybean variety, and PI593983, a wild soybean accession. Field tests were carried out in Missouri for two years during 2016 and 2017, in a randomized complete block design (n=2). Both protein and oil contents showed high heritabilities. Seed protein and seed oil were negatively correlated (-0.77). A total of 4,374 polymorphic markers were used to construct a genetic linkage map, and nine QTLs for protein content, explained 7.6 to 36.7% of variance, and seven QTLs for oil content, explained for 7.8 to 29.7% of variance, were detected using composite interval mapping. addition we identified eight novel QTLs and confirmed sixteen QTLs associated with maturity (R2 = 6.4 to 26.3%), plant height (R2 = 7.4 to 15.5%), and total branch length (R2 = 9.3% and 14.5%) in individual and across environments, and the ratio of total branch length to plant height (R2 = 11.8%), yield (R2 =12.8 and 15.7), and lodging (R2 = 12.1 and 13.4) in individual studied environments. Sixteen QTLs for maturity, yield, and plant height confirmed previously reported QTLs, and eight QTLs have not been reported before. The results of this study will facilitate the identification of the causative genes for seed protein and oil, maturity, height, lodging, and branching traits, and will help soybean breeder improve soybean performance by developing markers for marker-assisted selection.

Modern soybean [Glycine max (L.) Merr] cultivars have low overall genetic variation due to repeated bottleneck events that arose during domestication and from selection strategies typical of many soybean breeding programs. In both public and private soybean breeding programs, the introgression of wild soybean (Glycine soja Siebold and Zucc.) alleles is a viable option to increase genetic diversity and identify new sources for traits of value. The objectives of our study were to examine the genetic architecture responsible for seed protein and oil using a recombinant inbred line (RIL) population derived from hybridizing a G. max line (‘Osage’) with a G. soja accession (PI 593983). Linkage mapping identified a total of seven significant quantitative trait loci on chromosomes 14 and 20 for seed protein and on chromosome 8 for seed oil with LOD scores ranging from 5.3 to 31.7 for seed protein content and from 9.8 to 25.9 for seed oil content. We analyzed 3,015 single F4:9 soybean plants to develop two residual heterozygotes derived near isogenic lines (RHD-NIL) populations by targeting nine SNP markers from genotype-by-sequencing, which corresponded to two novel quantitative trait loci (QTL) derived from G. soja: one for a novel seed oil QTL on chromosome 8 and another for a novel protein QTL on chromosome 14. Single marker analysis and linkage analysis using 50 RHD-NILs validated the chromosome 14 protein QTL, and whole genome sequencing of RHD-NILs allowed us to reduce the QTL interval from ∼16.5 to ∼4.6 Mbp. We identified two genomic regions based on recombination events which had significant increases of 0.65 and 0.72% in seed protein content without a significant decrease in seed oil content. A new Kompetitive allele-specific polymerase chain reaction (KASP) assay, which will be useful for introgression of this trait into modern elite G. max cultivars, was developed in one region. Within the significantly associated genomic regions, a total of eight genes are considered as candidate genes, based on the presence of gene annotations associated with the protein or amino acid metabolism/movement. Our results provide better insights into utilizing wild soybean as a source of genetic diversity for soybean cultivar improvement utilizing native traits.

Soybean [Glycine max (L.) Merr] cultivars have low genetic variation due to domestication, founder events, and selection strategies for modern plant breeding. There is a need to introduce genetic diversity into soybean cultivars for long-term improvement of agronomic and seed compositional traits. In both public and private soybean breeding programs, the introgression of wild soybean (Glycine soja Siebold and Zucc.) genes has been utilized to incorporate novel genetic diversity. In our study, 3,015 single F[subscript 4:9] soybean plants were genotyped for nine genotype-by-sequencing markers from a previous genetic mapping study on recombinant inbred lines (La, 2018) to create two residual heterozygotes derived near isogenic lines (RHD-NIL) populations. The first RHD-NIL population was selected for a novel oil quantitative trait loci (QTL) on chromosome 8 and the second RHD-NIL population was selected for a novel protein QTL on chromosome 14. Both novel QTL derived from the wild soybean accession PI 593983. The objective of this research is to validate these QTL, reduce the QTL interval, and fine map the two novel QTL for candidate gene identification. Single marker analysis and linkage analysis was conducted using SoySNP6K BeadChip markers for QTL validation. The chromosome 8 oil QTL was not advanced for fine mapping because the QTL was not validated in a subsequent field and greenhouse study. Whole genome resequencing was leveraged to reduce the QTL from 16.5 Mbp to approximately 4.6 Mbp and to fine map 50 high protein RHD-NIL, which have segregated for the validated chromosome 14 QTL to permit candidate gene identification. A total of 55 potential candidates was identified in a physical interval of 8,059,955 to 12,648,760 bp. Our results provide a better insight of utilizing wild soybean as a source of genetic diversity for soybean cultivar improvement. In addition to the fine mapping and candidate gene identification study, we conducted linkage analysis for a recombinant inbred line (RIL) mapping population for plant biomass content, whole plant carbon content, whole plant nitrogen content, seed oil content, and seed protein content. Soybean seeds require a large amount of nitrogen because of its high protein content. Through a symbiotic association between soil microorganisms and soybean root nodules, soybean is able to fix atmospheric dinitrogen for nitrogen uptake. Plant biomass was collected by bulking five soybean shoot samples per plot from 262 plots in four locations and bulking three soybean shoots samples per plot from 262 plots in one location. Plant materials were dried and weighed for whole plant biomass weight. Whole plant carbon content, whole plant nitrogen content, seed oil content, and seed protein content was analyzed via near infrared spectroscopy. The objective of this study was to examine nitrogen mobilization from a mapping population from the cross PI 361103 (contains high shoot N content and low seed N content) x PI 567572B (contains high seed N content and low shoot N content), identify QTL for plant biomass, whole plant carbon content, whole plant nitrogen content, and seed composition, and study maternal effects of cytoplasmic inheritance of the five traits from the reciprocal parental cross. Linkage analysis was conducted using BARCSoySNP50K markers. We identified six QTL for plant biomass, two QTL for whole plant carbon content, three QTL for whole plant nitrogen content, three QTL for seed oil content, and five QTL for seed protein content, with multiple traits having overlapping QTL intervals. Our results indicate QTL associated with multiple traits demonstrating the potential of pleiotropic effect in our mapping population.

Common bacterial blight (CBB) is a major disease of common bean (Phaseolus vulgaris L.) worldwide. Genetic resistance is the most effective and environmentally safe approach for controlling CBB, and identification of resistance quantitative trait loci (QTL) can improve response to selection when breeding for CBB resistance. Interactions of CBB resistance QTL and pathogen isolates with different levels of aggressiveness were studied using an F4:5 recombinant inbreed line (RIL) population, derived from a cross between the susceptible cultivar “Sanilac” and the resistant breeding line “OAC 09-3.” Disease phenotyping was performed under field and growth room conditions using multiple bacterial isolates with differential levels of aggressiveness. QTL analysis was performed with 237 molecular markers. The effect of pathogen isolate on the average phenotypic value in the RIL population and the interaction of RILs and the pathogen isolates were highly significant. Two QTL underlying CBB resistance were detected on Pv08 and Pv03. A major QTL (R2p between 15 and 56%) was identified in a 5-cM (380 kbp) interval in the distal end of the long arm of Pv08. This genomic region was significantly associated with multiple disease evaluation traits in field and growth room assays and against different isolates of the pathogen, which included the previously known CBB marker SU91. A new QTL on Pv03 (Xa3.3SO), associated with the PvSNP85p745405 allele from the susceptible parent, Sanilac, appeared to be an isolate-specific QTL against the aggressive fuscans isolate ISO118. Interaction between the SU91 and Xa3.3SO QTL resulted in a significant reduction in mean disease severity for almost all disease evaluation traits after plants were challenged with the isolate ISO118. The 7.92 and 7.79% diseased areas in RILs with both QTL, compared with 14.92 and 13.81% in RILs without either in test1 and in test2 quantified by image analysis, showed a 44 and 47% reduction of percent diseased areas, indicating that the two QTL interact to limit the expansion of CBB symptoms after infection by ISO118. The information obtained in this study indicates that while the broad-spectrum SU91 QTL is useful in breeding programs, isolate-specific QTL, such as Xa3.3SO, will aid in breeding bean varieties with enhanced resistance against aggressive regional isolates.

To identify quantitative trait loci (QTLs) conditioning salt tolerance in soybean (Glycine max (L.) Merr.), two recombinant inbred line (RIL) populations derived from crosses of FT-Abyara × C01 and Jin dou No. 6 × 0197 were used in this study. The FT-Abyara × C01 population consisted of 96 F7 RILs, and the Jin dou No. 6 × 0197 population included 81 F6 RILs. The salt tolerant parents FT-Abyara and Jin dou No. 6 were originally from Brazil and China, respectively. The QTL analysis identified a major salt-tolerant QTL in molecular linkage group N, which accounted for 44.0 and 47.1% of the total variation for salt tolerance, in the two populations. In the FT-Abyara × C01 population, three RILs were found to be heterozygous around the detected QTL region. By selfing the three residual heterozygous lines, three sets of near isogenic lines (NILs) for salt tolerance were developed. An evaluation of salt tolerance of the NILs revealed that all the lines with FT-Abyara chromosome segment at the QTL region showed significantly higher salt tolerance than the lines without the FT-Abyara chromosome segment. Results of the NILs validated the salt tolerance QTL detected in the RIL populations.

Two genetic linkage maps based on doubled haploid (DH) and recombinant inbred lines (RILs) populations, derived from the same indica-japonica cross ‘Samgang × Nagdong’, were constructed to analyze the quantitative trait loci (QTLs) affecting agronomic traits in rice. The segregations of agronomic traits in RILs population showed larger variations than those in DH population. A total of 10 and 12 QTLs were identified on six chromosomes using DH population and seven chromosomes using RILs population, respectively. Three stable QTLs including pl9.1, ph1.1, and gwp11.1 were detected through different years. The percentages of phenotypic variation explained by individual QTLs ranged from 8 to 18% in the DH population and 9 to 33% in the RILs population. Twenty-three epistatic QTLs were identified in the DH population, while 21 epistatic QTLs were detected in the RILs population. Epistatic interactions played an important role in controlling the agronomic traits genetically. Four significant main-effect QTLs were involved in the digenic interactions. Significant interactions between QTLs and environments (QE) were identified in two populations. The QTLs affecting grain weight per panicle (GWP) were more sensitive to the environmental changes. The comparison and QTLs analysis between two populations across different years should help rice breeders to comprehend the genetic mechanisms of quantitative traits and improve breeding programs in marker-assisted selection (MAS).

ABSTRACTOil is one of the major chemical constituents that affect the quality of soybean [Glycine max (L.) Merr.] products. Soybean seed with high oil content is a valuable source for cooking oil and biodiesel production. The objective of this study was to identify quantitative trait loci (QTL) for oil content to advance soybean breeding efforts. Two F2–derived recombinant inbred line (RIL) populations, consisting of 242 and 214 individuals from the cross of R05–638 × R05–1415 (Population 1) and R05–4256 × V97–1346 (Population 2), respectively, were used for QTL mapping. The F2 plants from the mapping populations were genotyped by simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers. Seeds from F2:3, F2:4, and F2:5 lines were tested for oil content using near infrared transmittance technique based on 13% moisture. Six oil QTL regions located on chromosomes 5, 6, 14, 15, and 20 were identified. Among the QTL identified, a major oil QTL (14–40%) on chromosome 20 linked with eight SNP markers was confirmed across genetic populations, locations, and years; this QTL had negative effect on seed protein content. In Population 2, two novel QTL located on chromosomes 6 and 14 accounting for between 11 and 15% and 8 and 15% of the variation in seed oil content, respectively, were detected. These QTL with linked markers can be used for marker‐assisted selection for increased seed oil content in soybean breeding programs.

Seed size and shape traits are important determinants of seed yield and appearance quality in soybean [Glycine max (L.) Merr.]. Understanding the genetic architecture of these traits is important to enable their genetic improvement through efficient and targeted selection in soybean breeding, and for the identification of underlying causal genes. To map seed size and shape traits in soybean, a recombinant inbred line (RIL) population developed from K099 (small seed size) × Fendou 16 (large seed size), was phenotyped in three growing seasons. A genetic map of the RIL population was developed using 1,485 genotyping by random amplicon sequencing-direct (GRAS-Di) and 177 SSR markers. Quantitative trait locus (QTL) mapping was conducted by inclusive composite interval mapping. As a result, 53 significant QTLs for seed size traits and 27 significant QTLs for seed shape traits were identified. Six of these QTLs (qSW8.1, qSW16.1, qSLW2.1, qSLT2.1, qSWT1.2, and qSWT4.3) were identified with LOD scores of 3.80–14.0 and R2 of 2.36%–39.49% in at least two growing seasons. Among the above significant QTLs, 24 QTLs were grouped into 11 QTL clusters, such as, three major QTLs (qSL2.3, qSLW2.1, and qSLT2.1) were clustered into a major QTL on Chr.02, named as qSS2. The effect of qSS2 was validated in a pair of near isogenic lines, and its candidate genes (Glyma.02G269400, Glyma.02G272100, Glyma.02G274900, Glyma.02G277200, and Glyma.02G277600) were mined. The results of this study will assist in the breeding programs aiming at improvement of seed size and shape traits in soybean.

Partial resistance to Phytophthora sojae in soybean is controlled by multiple quantitative trait loci (QTL). With traditional QTL mapping approaches, power to detect such QTL, frequently of small effect, can be limited by population size. Joint linkage QTL analysis of nested recombinant inbred line (RIL) populations provides improved power to detect QTL through increased population size, recombination, and allelic diversity. However, uniform development and phenotyping of multiple RIL populations can prove difficult. In this study, the effectiveness of joint linkage QTL analysis was evaluated on combinations of two to six nested RIL populations differing in inbreeding generation, phenotypic assay method, and/or marker set used in genotyping. In comparison to linkage analysis in a single population, identification of QTL by joint linkage analysis was only minimally affected by different phenotypic methods used among populations once phenotypic data were standardized. In contrast, genotyping of populations with only partially overlapping sets of markers had a marked negative effect on QTL detection by joint linkage analysis. In total, 16 genetic regions with QTL for partial resistance against P. sojae were identified, including four novel QTL on chromosomes 4, 9, 12, and 16, as well as significant genotype-by-isolate interactions. Resistance alleles from PI 427106 or PI 427105B contributed to a major QTL on chromosome 18, explaining 10-45% of the phenotypic variance. This case study provides guidance on the application of joint linkage QTL analysis of data collected from populations with heterogeneous assay conditions and a genetic framework for partial resistance to P. sojae.

Yield is a multi-factorial trait determined by several genetic traits and highly correlated with important agronomic traits in many crops including soybean. [Glycine max (L.)]. Plant height, seed and pod numbers, and seed weight are all components of yield and polygenic in nature. The objective of this study was to identify quantitative trait loci (QTL) for days to germination, days to flowering, plant height, pod number, seed number, 100-seed weight, and total seed weight in soybean using the using the PI 438489B by ‘Hamilton’ recombinant inbred line (RIL) population (PIxH, n=50). A total of 18 QTL were found on 10 different chromosomes. Three QTL for days to germination (qDG001-qDG003) have been identified on chromosomes 5b, 6, and 13b. Two QTL (qDF001 and qDF002) have been identified on chromosomes 9 and 13b, respectively. On QTL for plant height (qPH001) have been identified on chromosome 6. Four QTL for pod number (qPN001-qPN004) had been identified on chromosomes 2, 6, and 8 (2 QTL), respectively. Two QTL for seed number (qSN001 and qSN002) have been identified on chromosomes 5b and 11b, respectively. Five QTL for 100-seed weight (qSW001 to qSW005) have been identified on chromosomes 5a, 6, 8, 9, and 11c, respectively. Two QTL for total seed weight (qTSW001 and qTSW002) have been identified on chromosomes 5b and 17c, respectively. The QTL identified here may be introduced in breeding programs to develop soybean cultivars with high yield potential.

Phomopsis seed decay (PSD), primarily caused by Phomopsis longicolla, is a major contributor to poor soybean seed quality and significant yield loss, particularly in early maturing soybean genotypes. However, it is not yet known whether PSD resistance is associated with early maturity. This study was conducted to identify quantitative trait loci (QTLs) for resistance to PSD and days to maturity using a recombinant inbred line (RIL) population derived from a cross between the PSD-resistant Taekwangkong and the PSD-susceptible SS2-2. Based on a genetic linkage map incorporating 117 simple sequence repeat markers, QTL analysis revealed two and three QTLs conferring PSD resistance and days to maturity, respectively, in the RIL population. Two QTLs (PSD-6-1 and PSD-10-2) for PSD resistance were identified in the intervals of Satt100-Satt460 and Sat_038-Satt243 on chromosomes 6 and 10, respectively. Two QTLs explained phenotypic variances in PSD resistance of 46.3 and 14.1%, respectively. At the PSD-6-1 QTL, the PSD-resistant cultivar Taekwangkong contributed the allele with negative effect decreasing the infection rate of PSD and this QTL does not overlap with any previously reported loci for PSD resistance in other soybean genotypes. Among the three QTLs for days to maturity, two (Mat-6-2 and Mat-10-3) were located at positions similar to the PSD-resistance QTLs. The identification of the QTLs linked to both PSD resistance and days to maturity indicates a biological correlation between these two traits. The newly identified QTL for resistance to PSD associated with days to maturity in Taekwangkong will help improve soybean resistance to P. longicolla.

Isoflavones from soybeans [ Glycine max (L.) Merr.] have a significant impact on human health to reduce the risk of several major diseases. Breeding soybean for high isoflavone content in the seed is possible through marker-assisted selection (MAS) which can be based on quantitative trait loci (QTL). The objective of this study was to identify QTL controlling isoflavone content in a set of 'MD96-5722' by 'Spencer' recombinant inbred line (RIL) populations of soybean. Wide variations were found for seed concentrations of daidzein, glycitein, genistein, and total isoflavones among the RIL populations. Three QTL were identified on three different linkage groups (LG) represented by three different chromosomes (Chr). One QTL that controlled daidzein content was identified on LG A1 (Chr 5), and two QTL that underlay glycitein content were identified on LG K (Chr 9) and LG B2 (Chr 14). Identified QTL could be functional in developing soybean with preferable isoflavone concentrations in the seeds through MAS.