Identification of quantitative trait loci controlling sucrose content in soybean (Glycine max)

Sucrose is a primary constituent of soybean (Glycine max) seed; however, little information concerning the inheritance of seed sucrose in soybean is available. The objective of this research was to use molecular markers to identify genomic regions significantly associated with quantitative trait loci (QTL) controlling sucrose content in a segregating F₂ population. DNA samples from 149 F₂ individuals were analyzed with 178 polymorphic genetic markers, including RFLPs, SSRs, and RAPDs. Sucrose content was measured on seed harvested from each of 149 F_2:3 lines from replicated field experiments in 1993 and 1995. Seventeen marker loci, mapping to seven different genomic regions, were significantly associated with sucrose variation at P<0.01. Individually, these markers explained from 6.1% to 12.4% of the total phenotypic variation for sucrose content in this population. In a combined analysis these genomic regions; explained 53% of total variation for sucrose content. No significant evidence of epistasis among QTLs was observed. Comparison of our QTL mapping results for sucrose content and those previously reported for protein and oil content (the other major seed constituents in soybean), suggests that seed quality traits are inherited as clusters of linked loci or that `major' QTLs with pleiotropic effects may control all three traits. Of the seven genomic regions having significant effects on sucrose content, three were associated with significant variation for protein content and three were significantly associated with oil content.     

Interval mapping of quantitative trait loci for reproductive,morphological, and seed traits of soybean (Glycine max L.)

Quantitative trait loci (QTL) were mapped in segregating progeny from a cross between two soybean (Glycine max (L.) Merr.) cultivars: Minsoy (PI 27.890) and Noir 1 (PI 290.136). The 15 traits analyzed included reproductive, morphological, and seed traits, seed yield and carbon isotope discrimination ratios (¹³C/¹²C). Genetic variation was detected for all of the traits, and transgressive segregation was a common phenomenon. One hundred and thirty-two linked genetic markers and 24 additional unlinked markers were used to locate QTL by interval mapping and one-way analysis of variance, respectively. Quantitative trait loci controlling 11 of the 15 traits studied were localized to intervals in 6 linkage groups. Quantitative trait loci for developmental and morphological traits (R1, R5, R8, plant height, canopy height, leaf area, etc.) tended to be clustered in three intervals, two of which were also associated with seed yield. Quantitative trait loci for seed oil were separated from all the other QTL. Major QTL for maturity and plant height were linked to RFLP markers R79 (31% variation) and G173 (53% variation). Quantitative trait loci associated with unlinked markers included possible loci for seed protein and weight. Linkage between QTL is discussed in relation to the heritability and genetic correlation of the traits.     

RFLP analysis of soybean seed protein and oil content

Summary The objectives of this study were to present an expanded soybean RFLP map and to identify quantitative trait loci (QTL) in soybean [Glycine max (L.) Merr.] for seed protein and oil content. The study population was formed from a cross between a G. max experimental line (A81-356022) and a G. soja Sieb. and Zucc. plant introduction (PI 468916). A total of 252 markers was mapped in the population, forming 31 linkage groups. Protein and oil content were measured on seed harvested from a replicated trial of 60 F₂-derived lines in the F₃ generation (F₂₃ lines). Each F₂₃ line was genotyped with 243 RFLP, five isozyme, one storage protein, and three morphological markers. Significant (P<0.01) associations were found between the segregation of markers and seed protein and oil content. Segregation of individual markers explained up to 43% of the total variation for specific traits. All G. max alleles at significant loci for oil content were associated with greater oil content than G. soja alleles. All G. soja alleles at significant loci for protein content were associated with greater protein content than G. max alleles.     

SSR mapping and confirmation of the QTL from PI96354 conditioning soybean resistance to southern root-knot nematode

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 F_2:3 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 F_2:3 population of PI96354× Bossier. Results confirmed the effectiveness of marker-assisted selection to predict the Mi phenotypes. By screening the BC₂F₂ population of Prichard (3)×G93–9009 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). Received: 29 September 2000 / Accepted: 17 April 2001     

A Single-Nucleotide Polymorphism in an Endo-1,4-β-Glucanase Gene Controls Seed Coat Permeability in Soybean

Physical dormancy, a structural feature of the seed coat known as hard seededness, is an important characteristic for adaptation of plants against unstable and unpredictable environments. To dissect the molecular basis of qHS1, a quantitative trait locus for hard seededness in soybean (Glycine max (L) Merr.), we developed a near-isogenic line (NIL) of a permeable (soft-seeded) cultivar, Tachinagaha, containing a hard-seed allele from wild soybean (G. soja) introduced by successive backcrossings. The hard-seed allele made the seed coat of Tachinagaha more rigid by increasing the amount of β-1,4-glucans in the outer layer of palisade cells of the seed coat on the dorsal side of seeds, known to be a point of entrance of water. Fine-mapping and subsequent expression and sequencing analyses revealed that qHS1 encodes an endo-1,4-β-glucanase. A single-nucleotide polymorphism (SNP) introduced an amino acid substitution in a substrate-binding cleft of the enzyme, possibly reducing or eliminating its affinity for substrates in permeable cultivars. Introduction of the genomic region of qHS1 from the impermeable (hard-seeded) NIL into the permeable cultivar Kariyutaka resulted in accumulation of β-1,4-glucan in the outer layer of palisade cells and production of hard seeds. The SNP allele found in the NIL was further associated with the occurrence of hard seeds in soybean cultivars of various origins. The findings of this and previous studies may indicate that qHS1 is involved in the accumulation of β-1,4-glucan derivatives such as xyloglucan and/or β-(1,3)(1,4)-glucan that reinforce the impermeability of seed coats in soybean.     

Identification of quantitative trait loci for plant height, lodging, and maturity in a soybean population segregating for growth habit

The use of molecular markers to identify quantitative trait loci (QTLs) has the potential to enhance the efficiency of trait selection in plant breeding. The purpose of the present study was to identify additional QTLs for plant height, lodging, and maturity in a soybean, Glycine max (L.) Merr., population segregating for growth habit. In this study, 153 restriction fragment length polymorphisms (RFLP) and one morphological marker (Dt1) were used to identify QTLs associated with plant height, lodging, and maturity in 111 F₂-derived lines from a cross of PI 97100 and Coker 237. The F₂-derived lines and two parents were grown at Athens, Ga., and Blackville, S.C., in 1994 and evaluated for phenotypic traits. The genetic linkage map of these 143 loci covered about 1600 cM and converged into 23 linkage groups. Eleven markers remained unlinked. Using interval-mapping analysis for linked markers and single-factor analysis of variance (ANOVA), loci were tested for association with phenotypic data taken at each location as well as mean values over the two locations. In the combined analysis over locations, the major locus associated with plant height was identified as Dt1 on linkage group (LG) L. The Dt1 locus was also associated with lodging. This locus explained 67.7% of the total variation for plant height, and 56.4% for lodging. In addition, two QTLs for plant height (K007 on LG H and A516b on LG N) and one QTL for lodging (cr517 on LG J) were identified. For maturity, two independent QTLs were identified in intervals between R051 and N100, and between B032 and CpTI, on LG K. These QTLs explained 31.2% and 26.2% of the total variation for maturity, respectively. The same QTLs were identified for all traits at each location. This consistency of QTLs may be related to a few QTLs with large effects conditioning plant height, lodging, and maturity in this population.     

A novel major quantitative trait locus controlling seed development at low temperature in soybean (Glycine max)

Low temperature is among the critical environmental factors that limit soybean production. To elucidate the genetic basis for chilling tolerance and identify useful markers, we conducted quantitative trait loci (QTL) analysis of seed-yielding ability at low temperature in soybean (Glycine max), using artificial climatic environments at usual and low temperatures and recombinant inbred lines derived from a cross between two contrasting cultivars in terms of chilling tolerance. We identified a QTL of a large effect (LOD > 15, r ² > 0.3) associated with seed-yielding ability only at low temperature. The QTL was mapped near marker Sat_162 on linkage group A2, where no QTL for chilling tolerance has previously been identified. The tolerant genotype did not increase the pod number but maintained the seed number per pod and single seed weight, namely, the efficiency of seed development at low temperature. The effect of the QTL was confirmed in a segregating population of heterogeneous inbred families, which provided near-isogenic lines. The genomic region containing the QTL also influenced the node and pod numbers regardless of temperature condition, although this effect was not primarily associated with chilling tolerance. These results suggest the presence of a new major genetic factor that controls seed development specifically at low temperature. The findings will be useful for marker-assisted selection as well as for understanding of the mechanism underlying chilling tolerance in reproductive organs.     

Identification of QTLs Underlying Water-Logging Tolerance in Soybean

Soil water-logging can cause severe damage to soybean [Glycine max (L.) Merr.] and results in significant yield reduction. The objective of this study was to identify quantitative trait loci (QTL) that condition water-logging tolerance (WLT) in soybean. Two populations with 103 and 67 F_6:11 recombinant inbred lines (RILs) from A5403 × Archer (Population 1) and P9641 × Archer (Population 2), respectively, were used as the mapping populations. The populations were evaluated for WLT in manually flooded fields in 2001, 2002, and 2003. Significant variation was observed for WLT among the lines in the two populations. No transgressive tolerant segregants were observed in either population. Broad-sense heritability of WLT for populations 1 and 2 were 0.59 and 0.43, respectively. The tolerant and sensitive RILs from each population were selected to create a tolerant bulk and a sensitive bulk, respectively. The two bulks and the parents of each population were tested with 912 simple sequence repeat (SSR) markers to select candidate regions on the linkage map that were associated with WLT. Markers from the candidate regions were used to genotype the RILs in both populations. Both single marker analysis (SMA) and composite interval mapping (CIM) were used to identify QTL for WLT. Seventeen markers in Population 1 and 15 markers in Population 2 were significantly (p <0.0001) associated with WLT in SMA. Many of these markers were linked to Rps genes or QTL conferring resistance to Phytophthora sojae Kaufmann and Gerdemann. Five markers, Satt599 on linkage group (LG) A1, Satt160, Satt269, and Satt252 on LG F, and Satt485 on LG N, were significant (p <0.0001) for WLT in both populations. With CIM, a WLT QTL was found close to the marker Satt385 on LG A1 in Population 1 in 2003. This QTL explained 10% of the phenotypic variation and the allele that increased WLT came from Archer. In Population 2 in 2002, a WLT QTL was located near the marker Satt269 on LG F. This QTL explained 16% of the phenotypic variation and the allele that increased WLT also came from Archer.     

Determining the linkage of quantitative trait loci to RFLP markers using extreme phenotypes of recombinant inbreds of soybean (Glycine max L. Merr.)

An experimental test is described for linkages between RFLP markers and quantitative trait loci (QTL). Two hundred and eighty-four F₇-derived recombinant inbred lines (RIL) obtained from crossing the soybean cultivars (Glycine max L. Merr.) Minsoy and Noir 1 were evaluated for maturity, plant height, lodging, and seed yield. RIL exhibiting an extreme phenotype for each trait (earliest and latest plants for maturity, etc.) were selected, and two bulked DNA samples were prepared for each trait. A Southern transfer of the digested bulked DNA was hybridized with restriction fragement length polymorphism (RFLP) probes, and linkages with QTL were established by quantitating the amount of radioactive probe that bound to fragments defining alternative parental RFLP alleles. When an RFLP marker was linked to a QTL, one parental allele predominated in the bulked DNA from a particular phenotype; the other allele was associated with the opposite phenotype. When linkage was absent, radioactivity was associated equally with both alleles for a given phenotype (or with both phenotypes for a given allele). These results confirmed RFLP-QTL associations previously discovered by interval mapping on a smaller segregating population from the same cross. New linkages to QTL were also verified.     

Fine mapping of the FT1 locus for soybean flowering time using a residual heterozygous line derived from a recombinant inbred line

Fine-mapping of loci related to complex quantitative traits is essential for map-based cloning. A residual heterozygous line (RHL) of soybean (Glycine max) derived from a recombinant inbred line (RIL) was used for fine-mapping FT1, which is a major quantitative trait locus (QTL) responsible for soybean flowering time. The residual heterozygous line RHL1-156 was selected from the RILs that were derived from two distantly related varieties, Misuzudaizu and Moshidou Gong 503. The genome of RHL1-156 contains a heterozygous segment (approximately 17 cM) surrounding the FT1 locus but is homozygous in other regions, including three other loci affecting flowering time. A large segregating population of 1,006 individuals derived by selfing of RHL1-156 included two homozygous genotypes for the nearest marker of FT1 whose flowering time differed by 26 days. No continuous range of phenotypes was observed, in contrast to the F₂ population, suggesting that a single FT1 locus affected the flowering time in the RHL1-156 line. Linkage analysis revealed that the FT1 locus mapped as a single Mendelian factor between two tightly linked DNA markers, Satt365 and GM169, at distances of approximately 0.1 cM and 0.4 cM, respectively. Our results show that a RHL derived from RILs can be used to fine-map a QTL and that RHLs can be an efficient tool for a systematic fine-mapping of QTLs.     

Inheritance of polymorphic markers generated by DNA amplification fingerprinting and their use as genetic markers in soybean

DNA amplification fingerprinting (DAF) using a high primer-to-template ratio and single, very short arbitrary primers, was used to generate amplified fragment length polymorphic markers (AFLP) in soybean (Glycine max (L.) Merr.). The inheritance of AFLPs was studied using a cross between the ancestral Glycine soja PI468.397 and Glycine max (L.) Merr. line nts382, F1 and F2 progeny. The amplification reaction was carried out with soybean genomic DNA and 8 base long oligounucleotide primers. Silver-stained 5% polyacrylamide gels containing 7 M urea detected from 11 to 28 DAF products with primers of varying GC content (ranging from 50 to 100% GC). Depending on their intensity, AFLPs were classified into three classes. DAF profiles were reproducible for different DNA extractions and gels. Forty AFLPs were detected by 26 primers when comparing G. soja and G. max. Most AFLPs were inherited as dominant Mendelian markers in F1 and F2 populations. However, abnormal inheritance occured with about 25% of polymorphisms. One marker was inherited as a maternal marker, presumably originating from organelle DNA while another showed apparent paternal inheritance. To confirm the nuclear origin and utility of dominant Mendelian markers, three DAF polymorphisms were mapped using a F11 mapping population of recombinant inbred lines from soybean cultivars Minsoy × Noir 1. The study showed that DAF-generated polymorphic markers occur frequently and reliably, that they are inherited as Mendelian dominant loci and that they can be used in genome mapping.     

A PCR-based marker for a locus conferring aroma in vegetable soybean (<Emphasis Type="Italic">Glycine max</Emphasis> L.)

Vegetable soybean (Glycine max L.) is an important economic and nutritious crop in South and Southeast Asian countries and is increasingly grown in the Western Hemisphere. Aromatic vegetable soybean is a special group of soybean varieties that produce young pods containing a sweet aroma, which is produced mainly by the volatile compound 2-acetyl-1-pyrroline (2AP). Due to the aroma, the aromatic vegetable soybean commands higher market prices and gains wider acceptance from unfamiliar consumers. We have previously reported that the GmAMADH2 gene encodes an AMADH that regulates aroma (2AP) biosynthesis in soybeans (Arikit et al. 2010). A sequence variation involving a 2-bp deletion in exon 10 was found in this gene in all investigated aromatic varieties. In this study, a codominant PCR-based marker for the aroma trait in soybeans was designed based on the 2-bp deletion in GmAMADH2. The marker was verified in five aromatic and five non-aromatic varieties as well as in F₂ soybean population segregating for aroma. The aromatic genotype with the 2-bp deletion was completely associated with the five aromatic soybean varieties as well as the aromatic progeny of the F₂ population with seeds containing 2AP. Similarly, the non-aromatic genotype was associated with the five non-aromatic varieties and non-aromatic progeny. The perfect co-segregation of the marker genotypes and aroma phenotypes confirmed that the marker could be efficiently used for molecular breeding of soybeans for aroma.     

Genomic Regions Associated with Amino Acid Composition in Soybean

Soybean [Glycine max (L.) Merr.] is the single largest source of protein in animal feed. However, few studies have been conducted to evaluate genomic regions controlling amino acid composition in soybean. It is important to study the genetics of amino acid composition to achieve improvements through breeding. The objectives of this study were to determine the ratios between essential to non-essential (E:NE) and essential to total (E:T) amino acids, and to identify genomic regions controlling essential and non-essential amino acid composition in soybean seed. To achieve these objectives, 101 F₆-derived recombinant inbred lines (RIL) developed from a cross of N87-984-16 × TN93-99 were used. Ground soybean seed samples were analyzed for amino acids using a near infrared spectroscopy (NIRS) instrument. A significant (p < 0.01) difference among the RIL was found for amino acid composition. Heritability estimates on an entry mean basis ranged from 0.13 for His to 0.67 for Tyr. A total of 94 polymorphic simple sequence repeat (SSR) molecular genetic markers were screened in DNA from progenies. Single factor ANOVA was used to identify candidate quantitative trait loci (QTL), which were then confirmed by QTL Cartographer. At least one QTL for each amino acid was detected in this population. QTL linked to molecular markers Satt143, Satt168, Satt203, Satt274 and Satt495 were associated with most of the amino acids. Phenotypic variation explained by an individual QTL ranged from 9.4 to 45.3%. QTL detected for amino acids in soybean in this experiment are expected to be useful for future breeding programs targeting development of improved soybean amino acid composition for human and animal nutrition.     

Identification of QTL underlying somatic embryogenesis capacity of immature embryos in soybean (Glycine max (L.) Merr.)

High embryogenesis capacity of soybean (Glycine max (L.) Merr.) in vitro possessed potential for effective genetic engineering and tissue culture. The objects of this study were to identify quantitative trait loci (QTL) underlying embryogenesis traits and to identify genotypes with higher somatic embryogenesis capacity. A mapping population, consisting of 126 F_5:6 recombinant inbred lines, was advanced by single-seed-descent from cross between Peking (higher primary and secondary embryogenesis) and Keburi (lower primary and secondary embryogenesis). This population was evaluated for primary embryogenesis capacity from immature embryo cultures by measuring the frequency of somatic embryogenesis (FSE), the somatic embryo number per explant (EPE) and the efficiency of somatic embryogenesis (ESE). A total of 89 simple sequence repeat markers were used to construct a genetic linkage map. Six QTL were associated with somatic embryogenesis. Two QTL for FSE were found, QFSE-1 (Satt307) and QFSE-2 (Satt286), and both were located on linkage group C2 that explained 45.21 and 25.97% of the phenotypic variation, respectively. Four QTL for EPE (QEPE-1 on MLG H, QEPE-2 on MLG G and QEPE-3 on MLG G) were found, which explained 7.11, 7.56 and 6.12% of phenotypic variation, respectively. One QTL for ESE, QESE-1 (Satt427), was found on linkage group G that explained 6.99% of the phenotypic variation. QEPE-2 and QESE-1 were located in the similar region of MLG G. These QTL provide potential for marker assistant selection of genotypes with higher embryogenesis.     

Identification of molecular markers linked to quantitative trait loci for soybean resistance to corn earworm

 One hundred and thirty nine restriction fragment length polymorphisms (RFLPs) were used to construct a soybean (Glycine max L. Merr.) genetic linkage map and to identify quantitative trait loci (QTLs) associated with resistance to corn earworm (Helicoverpa zea Boddie) in a population of 103 F₂-derived lines from a cross of ‘Cobb’ (susceptible) and PI229358 (resistant). The genetic linkage map consisted of 128 markers which converged onto 30 linkage groups covering approximately 1325 cM. There were 11 unlinked markers. The F₂-derived lines and the two parents were grown in the field under a plastic mesh cage near Athens, Ga., in 1995. The plants were artificially infested with corn earworm and evaluated for the amount of defoliation. Using interval-mapping analysis for linked markers and single-factor analysis of variance (ANOVA), markers were tested for an association with resistance. One major and two minor QTLs for resistance were identified in this population. The PI229358 allele contributed insect resistance at all three QTLs. The major QTL is linked to the RFLP marker A584 on linkage group (LG) ‘M’ of the USDA/Iowa State University public soybean genetic map. It accounts for 37% of the total variation for resistance in this cross. The minor QTLs are linked to the RFLP markers R249 (LG ‘H’) and Bng047 (LG ‘D1’). These markers explain 16% and 10% of variation, respectively. The heritability (h²) for resistance was estimated as 64% in this population. Received: 15 October 1997 / Accepted: 4 November 1997     

RFLP markers associated with soybean cyst nematode resistance and seed composition in a ‘Peking’בEssex’ population

 Soybean cyst nematode (SCN), Heterodera glycines Ichinohe, causes severe damage to soybean [Glycine max (L.) Merr] throughout North America and worldwide. Molecular markers associated with loci conferring SCN resistance would be useful in breeding programs using marker-assisted selection (MAS). In this study, 200 F_2:3 families derived from two contrasting parents, SCN-resistant ‘Peking’ with relatively low protein and oil concentrations, and SCN-susceptible ‘Essex’ with high protein and oil concentrations, were used to determine loci underlying the SCN resistance and seed composition. Three different SCN Race isolates (1, 3, and 5) were used to screen both parents and F_2:3 families. The parents were surveyed with 216 restriction fragment length polymorphism (RFLP) probes with five different restriction enzymes. Fifty-six were polymorphic and contrasted with trait data from bioassays to identify molecular markers associated with loci controlling resistance to SCN and seed composition. Five RFLP markers, A593 and T005 on linkage group (LG) B, A018 on LG E, and K014 and B072 on LG H, were significantly linked to resistance loci for Race 1 isolate, which jointly explained 57.7% of the total phenotypic variation. Three markers (B072 and K014, both on LG H; T005 on LG B) were associated with resistance to the Race 3 isolate and jointly explained 21.4% of the total phenotypic variation. Two markers (K011 on LG I, A963 on LG E) associated with resistance to the Race 5 isolate together explained 14.0% of the total phenotypic variation. In the same population we also identified two RFLP markers (B072 on LG H, B148 on LG F) associated with loci conferring protein concentration, which jointly explained 32.3% of the total phenotypic variation. Marker B072 was also linked to loci controlling the concentration of seed oil, which explained 21% of the total phenotypic variation. Clustering among quantitative trait loci (QTLs) conditioning resistance to different SCN Race isolates and seed protein and oil concentrations may exist in this population. We believe that markers located near these QTLs could be used to select for new SCN resistance and higher levels of seed protein and oil concentrations in breeding improved soybean cultivars. Received: 3 March 1998 / Accepted: 18 August 1998     

Genetic control of soybean seed oil: I. QTL and genes associated with seed oil concentration in RIL populations derived from crossing moderately high-oil parents

Soybean seed is a major source of oil for human consumption worldwide and the main renewable feedstock for biodiesel production in North America. Increasing seed oil concentration in soybean [Glycine max (L.) Merrill] with no or minimal impact on protein concentration could be accelerated by exploiting quantitative trait loci (QTL) or gene-specific markers. Oil concentration in soybean is a polygenic trait regulated by many genes with mostly small effects and which is negatively associated with protein concentration. The objectives of this study were to discover and validate oil QTL in two recombinant inbred line (RIL) populations derived from crosses between three moderately high-oil soybean cultivars, OAC Wallace, OAC Glencoe, and RCAT Angora. The RIL populations were grown across several environments over 2 years in Ontario, Canada. In a population of 203 F_3:6 RILs from a cross of OAC Wallace and OAC Glencoe, a total of 11 genomic regions on nine different chromosomes were identified as associated with oil concentration using multiple QTL mapping and single-factor ANOVA. The percentage of the phenotypic variation accounted for by each QTL ranged from 4 to 11 %. Of the five QTL that were tested in a population of 211 F_3:5 RILs from the cross RCAT Angora × OAC Wallace, a “trait-based” bidirectional selective genotyping analysis validated four QTL (80 %). In addition, a total of seven two-way epistatic interactions were identified for oil concentration in this study. The QTL and epistatic interactions identified in this study could be used in marker-assisted introgression aimed at pyramiding high-oil alleles in soybean cultivars to increase oil concentration for biodiesel as well as edible oil applications.     

QTL associated with horizontal resistance to soybean cyst nematode in Glycine soja PI464925B

Soybean cyst nematode (Heterodera glycines Ichinohe; SCN) is the primary disease responsible for yield loss of soybean [Glycine max (L.) Merr.]. Resistant cultivars are an effective management tool; however, the sources currently available have common resistant genes. Glycine soja Sieb. and Zucc., the wild ancestor of domesticated soybean, represents a diverse germplasm pool with known SCN resistance. The objectives of this research were to: (1) determine the genetic variation and inheritance of SCN resistance in a G. max (‘S08-80’) × G. soja (PI464925B) F _4:5 recombinant inbred line (RIL) population; and (2) identify and evaluate quantitative trait loci (QTL) associated with SCN resistance. Transgressive segregation for resistance was observed, although neither parent was resistant to the Chatham and Ruthven SCN isolates. Broad sense heritability was 0.81 for the Ruthven and 0.91 for the Chatham isolate. Root dry weight was a significant covariate that influenced cyst counts. One RIL [female index (FI) = 5.2 ± 1.11] was identified as resistant to the Chatham isolate (FI < 10). Seventeen and three RILs infected with Chatham and Ruthven isolates, respectively, had mean adjusted cyst counts of zero. Unique and novel QTL, which derived resistance from G. soja, were identified on linkage groups I, K, and O, and individually explained 8, 7 and 5% (LOD = 2.1–2.7) of the total phenotypic variation, respectively. Significant epistatic interactions were found between pairs of SSR markers that individually may or may not have been associated with SCN resistance, which explained between 10 and 15% of the total phenotypic variation. Best-fit regression models explained 21 and 31% of the total phenotypic variation in the RIL population to the Chatham and Ruthven isolates, respectively. The results of this study help to improve the understanding of the genetic control of SCN resistance in soybean caused by minor genes resulting in horizontal resistance. The incorporation of the novel resistance QTL from G. soja could increase the durability of SCN-resistance in soybean cultivars, especially if major gene resistance breaks down.     

Loci underlying resistance to Race 3 of soybean cyst nematode in Glycine soja plant introduction 468916

Soybean cyst nematode (SCN) (Heterodera glycines Ichinohe) is an important soybean [Glycine max (L.) Merr.] pest in the U.S. and throughout the world. Genetic resistance is the primary method for controlling SCN and there is a need to identify new resistance genes. Glycine soja Sieb. and Zucc. is the wild ancestor of domesticated soybean and is a potential source of new SCN resistance genes. The goal of this research was to map quantitative trait loci (QTLs) that provide resistance to SCN Race 3 from the G. soja plant introduction (PI) 468916. Fifty seven F₂-derived lines from a cross between the G. soja PI 468916 and the G. max experimental line A81-356022 were tested for resistance to an SCN population with a Race-3 phenotype. These lines were also genotyped with 1,004 genetic markers and resistance genes were mapped by composite interval mapping with the computer program QTL-Cartographer. In the F₂ population, three significant (LOD > 3.0) QTLs were detected that explained from 5% to 27% of the variation for Race-3 resistance. The two most significant QTLs identified in the F₂ population were tested in a population of 100 BC1F₂ plants developed by crossing A81-356022 to a line from the F₂ population that carried the two resistance QTLs from G. soja. In the backcross population, both Race-3 resistance QTLs were significant, which confirms the existence of these QTLs. The QTLs identified in this experiment map to positions where SCN resistance genes have not been previously identified, suggesting that these are novel genes that could be useful for diversifying the resistance genes currently used in cultivar development. Received: 7 August 2000 / Accepted: 4 December 2000     

Genome-Wide Association Studies Identifies Seven Major Regions Responsible for Iron Deficiency Chlorosis in Soybean (Glycine max)

Iron deficiency chlorosis (IDC) is a yield limiting problem in soybean (Glycine max (L.) Merr) production regions with calcareous soils. Genome-wide association study (GWAS) was performed using a high density SNP map to discover significant markers, QTL and candidate genes associated with IDC trait variation. A stepwise regression model included eight markers after considering LD between markers, and identified seven major effect QTL on seven chromosomes. Twelve candidate genes known to be associated with iron metabolism mapped near these QTL supporting the polygenic nature of IDC. A non-synonymous substitution with the highest significance in a major QTL region suggests soybean orthologs of FRE1 on Gm03 is a major gene responsible for trait variation. NAS3, a gene that encodes the enzyme nicotianamine synthase which synthesizes the iron chelator nicotianamine also maps to the same QTL region. Disease resistant genes also map to the major QTL, supporting the hypothesis that pathogens compete with the plant for Fe and increase iron deficiency. The markers and the allelic combinations identified here can be further used for marker assisted selection.