Fine mapping and identification of candidate genes controlling the resistance to southern root-knot nematode in PI 96354

Meloidogyne incognita (Kofoid and White) Chitwood (Mi) is the most economically damaging species of the root-knot nematode to soybean and other crops in the southern USA. PI 96354 was identified to carry a high level of resistance to galling and Mi egg production. Two Quantitative Trait Locus (QTLs) were found to condition the resistance in PI 96354 including a major QTL and a minor QTL on chromosome 10 and chromosome 18, respectively. To fine map the major QTL on chromosome 10, F_5:6 recombinant inbred lines from the cross between PI 96354 and susceptible genotype Bossier were genotyped with Simple Sequence Repeats (SSR) markers to identify recombinational events. Analysis of lines carrying key recombination events placed the Mi-resistant allele on chromosome 10 to a 235-kb region of the ‘Williams 82’ genome sequence with 30 annotated genes. Candidate gene analysis identified four genes with cell wall modification function that have several mutations in promoter, exon, 5′, and 3′UTR regions. qPCR analysis showed significant difference in expression levels of these four genes in Bossier compared to PI 96354 in the presence of Mi. Thirty Mi-resistant soybean lines were found to have same SNPs in these 4 candidate genes as PI 96354 while 12 Mi-susceptible lines possess the ‘Bossier’ genotype. The mutant SNPs were used to develop KASP assays to detect the resistant allele on chromosome 10. The four candidate genes identified in this study can be used in further studies to investigate the role of cell wall modification genes in conferring Mi resistance in PI 96354.     

DNA marker analysis of loci conferring resistance to peanut root-knot nematode in soybean

 Peanut root-knot nematode [Meloidogyne arenaria (Neal) Chitwood] (Ma) is a serious pathogen of soybean, Glycine max L. Merrill, in the southern USA. Breeding for root-knot nematode resistance is an important objective in many plant breeding programs. The inheritance of soybean resistance to Ma is quantitative and has a moderate-to-high variance-component heritability on a family mean basis. The objectives of the present study were to use restriction fragment length polymorphism (RFLP) markers to identify quantitative trait loci (QTLs) conferring resistance to Ma and to determine the genomic location and the relative contribution to resistance of each QTL. An F₂ population from a cross between PI200538 (Ma resistant) and ‘CNS’ (Ma susceptible) was mapped with 130 RFLPs. The 130 markers converged on 20 linkage groups spanning a total of 1766 cM. One hundred and five F_2:3 families were grown in the greenhouse and inoculated with Ma Race 2. Two QTLs conferring resistance to Ma were identified and PI200538 contributed the alleles for resistance at both QTLs. One QTL was mapped at 0-cM recombination with marker B212V-1 on linkage group-F (LG-F) of the USDA/ARS-Iowa State University RFLP map, and accounted for 32% of the variation in gall number. Another QTL was mapped in the interval from B212D-2 to A111H-2 on LG-E, and accounted for 16% of the variation in gall number. Gene action for the QTL located on LG-F was additive to partially dominant, whereas the gene action for the QTL on LG-E was dominant with respect to resistance. The two QTLs, when fixed on the framework map, accounted for 51% of the variation in gall number in a two-QTL model. The two QTLs for Ma resistance were found in duplicated regions of the soybean genome, and the major QTL for Ma resistance on LG-F is positioned within a cluster of eight diverse disease-resistance loci. Received: 10 June 1996 / Accepted: 18 April 1997     

Identification of a new major QTL associated with resistance to soybean cyst nematode (Heterodera glycines)

Resistance of soybean [Glycine max (L.) Merr.] to cyst nematode (SCN) (Heterodera glycines Ichinohe), one of the most destructive pathogens affecting soybean, involves a complex genetic system. The identification of QTLs associated with SCN resistance may contribute to the understanding of such system. The objective of this work was to identify and map QTLs for resistance to SCN Race 14 with the aid of molecular markers. BC₃F_2:3 and F_2:3 populations, both derived from an original cross between resistant cv. Hartwig and the susceptible line BR-92–31983 were screened for resistance to SCN Race 14. Four microsatellite (Satt082, Sat_001, Satt574 and Satt301) and four RAPD markers (OPAA-11₇₉₅, OPAE-08₈₃₇, OPR-07₅₄₈ and OPY-07₂₀₃₀) were identified in the BC₃F_2:3 population using the bulked segregant analysis (BSA) technique. These markers were amplified in 183 F_2:3 families and mapped to a locus that accounts for more than 40% of the resistance to SCN Race 14. Selection efficiency based on these markers was similar to that obtained with the conventional method. In the case of the microsalellite markers, which identify homozygous resistant genotypes, the efficiency was even higher. This new QTL has been mapped to the soybean linkage group D2 and, in conjunction with other QTLs already identified for SCN resistance, will certainly contribute to our understanding of the genetic basis of resistance of this important disease in soybean. Received: 12 October 1999 / Accepted: 14 April 2000     

QTL analysis of root traits as related to phosphorus efficiency in soybean

Background and Aims

Low phosphorus (P) availability is a major constraint to soybean growth and production, especially in tropical and subtropical areas. Root traits have been shown to play critical roles in P efficiency in crops. Identification of the quantitative trait loci (QTLs) conferring superior root systems could significantly enhance genetic improvement in soybean P efficiency.

Methods

A population of 106 F₉ recombinant inbred lines (RILs) derived from a cross between BD2 and BX10, which contrast in both P efficiency and root architecture, was used for mapping and QTL analysis. Twelve traits were examined in acid soils. A linkage map was constructed using 296 simple sequence repeat (SSR) markers with the Kosambi function, and the QTLs associated with these traits were detected by composite interval mapping and multiple-QTL mapping.

Key Results

The first soybean genetic map based on field data from parental genotypes contrasting both in P efficiency and root architecture was constructed. Thirty-one putative QTLs were detected on five linkage groups, with corresponding contribution ratios of 9·1–31·1 %. Thirteen putative QTLs were found for root traits, five for P content, five for biomass and five for yield traits. Three clusters of QTLs associated with the traits for root and P efficiency at low P were located on the B1 linkage group close to SSR markers Satt519 and Satt519-Sat_128, and on the D2 group close to Satt458; and one cluster was on the B1 linkage group close to Satt519 at high P.

Conclusions

Most root traits in soybean were conditioned by more than two minor QTLs. The region closer to Satt519 on the B1 linkage group might have great potential for future genetic improvement for soybean P efficiency through root selection.     

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 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.     

Mapping Isoflavone QTL with Main,Epistatic and QTL × Environment Effects in Recombinant Inbred Lines of Soybean

Soybean (Glycine max (L.) Merr.) isoflavone is important for human health and plant defense system. To identify novel quantitative trait loci (QTL) and epistatic QTL underlying isoflavone content in soybean, F_5:6, F_5:7 and F_5:8 populations of 130 recombinant inbred (RI) lines, derived from the cross of soybean cultivar ‘Zhong Dou 27′ (high isoflavone) and ‘Jiu Nong 20′ (low isoflavone), were analyzed with 95 new SSR markers. A new linkage map including 194 SSR markers and covering 2,312 cM with mean distance of about 12 cM between markers was constructed. Thirty four QTL for both individual and total seed isoflavone contents of soybean were identified. Six, seven, ten and eleven QTL were associated with daidzein (DZ), glycitein (GC), genistein (GT) and total isoflavone (TI), respectively. Of them 23 QTL were newly identified. The qTIF_1 between Satt423 and Satt569 shared the same marker Satt569 with qDZF_2, qGTF_1 and qTIF_2. The qGTD2_1 between Satt186 and Satt226 was detected in four environments and explained 3.41%-10.98% of the phenotypic variation. The qGTA2_1, overlapped with qGCA2_1 and detected in four environments, was close to the previously identified major QTL for GT, which were responsible for large a effects. QTL (qDZF_2, qGTF_1 and qTIF_2) between Satt144-Satt569 were either clustered or pleiotropic. The qGCM_1, qGTM_1 and qTIM_1 between Satt540-Sat_244 explained 2.02%–9.12% of the phenotypic variation over six environments. Moreover, the qGCE_1 overlapped with qGTE_1 and qTIE_1, the qTIH_2 overlapped with qGTH_1, qGCI_1 overlapped with qDZI_1, qTIL_1 overlapped with qGTL_1, and qTIO_1 overlapped with qGTO_1. In this study, some of unstable QTL were detected in different environments, which were due to weak expression of QTL, QTL by environment interaction in the opposite direction to a effects, and/or epistasis. The markers identified in multi-environments in this study could be applied in the selection of soybean cultivars for higher isoflavone content and in the map-based gene cloning.     

Validation of SSR markers linked to null kunitz tryspin inhibitor allele in Indian soybean [Glycine max (L.) Merr.] population

Kunitz trypsin inhibitor, a proteinaceous antinutritional factor present in soybean seeds, is responsible for inferior nutritional quality of raw soybean and incompletely processed soy products. The objective of the present investigation was to validate the SSR markers (Satt228 and Satt409) reported to be linked to Ti locus in an Indian soybean population generated from the cross between soybean cultivar LSb1 (TiTi) and PI542044 (titi). Parental polymorphism was surveyed using Satt409, Satt228 and 5 SSR markers in the neighbouring genomic region of Ti locus. A portion of the cotyledon of F₂ seeds was used for analyzing the presence or absence of kunitz trypsin inhibitor polypeptide electrophoretically while the remaining portion containing the embryo was used for raising the F₂ plants (104) for the development of mapping population. The SSR marker Satt228 reported to be tightly linked with Ti locus was not found to be polymorphic for the parents used in our study. Satt409 was found to be linked with Ti locus at 4.7 cM. Besides, a new marker Satt538 was found to be linked with Ti locus at a distance of 17.8 cM. Thus, the SSR marker Satt409 can be useful for Marker Assisted Selection for transferring titi allele in the background of Indian soybean genotypes.     

Soybean aphid resistance genes in the soybean cultivars Dowling and Jackson map to linkage group M

The soybean aphid [Aphis glycines Matsumura] is an important pest of soybean [Glycine max (L.) Merr.] in North America. Single dominant genes in the cultivars ‘Dowling’ and ‘Jackson’ control resistance to the soybean aphid. The gene in Dowling was named Rag1, and the genetic relationship between Rag1 and the gene in Jackson is not known. The objectives of this study were to map the locations of Rag1 and the Jackson gene onto the soybean genetic map. Segregation of aphid resistance and simple sequence repeat (SSR) markers in F _2:3 populations developed from crosses between Dowling and the two susceptible soybean cultivars ‘Loda’ and ‘Williams 82’, and between Jackson and Loda, were analyzed. Both Rag1 and the Jackson gene segregated 1:2:1 in the F _2:3 populations and mapped to soybean linkage group M between the markers Satt435 and Satt463. Rag1 mapped 4.2 cM from Satt435 and 7.9 cM from Satt463. The Jackson gene mapped 2.1 cM from Satt435 and 8.2 cM from Satt463. Further tests to determine genetic allelism between Rag1 and the Jackson gene are in progress. The SSR markers flanking these resistance genes are being used in marker-assisted selection for aphid resistance in soybean breeding programs. Trade and manufacturers’ names are necessary to report factually on available data; however, the USDA neither guarantees nor warrants the standard of the product, and the use of the name by USDA implies no approval of the product to the exclusion of others that may also be suitable.     

Quantitative trait loci for aluminum resistance in wheat

Quantitative trait loci (QTL) for wheat resistance to aluminum (Al) toxicity were analyzed using simple sequence repeats (SSRs) in a population of 192 F₆ recombinant inbred lines (RILs) derived from a cross between an Al-resistant cultivar, Atlas 66 and an Al-sensitive cultivar, Chisholm. Wheat reaction to Al was measured by relative root growth and root response to hematoxylin stain in nutrient-solution culture. After screening 1,028 SSR markers for polymorphisms between the parents and bulks, we identified two QTLs for Al resistance in Atlas 66. One major QTL was mapped on chromosome 4D that co-segregated with the Al-activated malate transporter gene (ALMT1). Another minor QTL was located on chromosome 3BL. Together, these two QTLs accounted for about 57% of the phenotypic variation in hematoxylin staining score and 50% of the variation in net root growth (NRG). Expression of the minor QTL on 3BL was suppressed by the major QTL on 4DL. The two QTLs for Al resistance in Atlas 66 were also verified in an additional RIL population derived from Atlas 66/Century. Several SSR markers closely linked to the QTLs were identified and have potential to be used for marker-assisted selection (MAS) to improve Al-resistance of wheat cultivars in breeding programs.