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     

Penetration and Development of Meloidogyne incognita on Roots of Resistant Soybean Genotypes

Meloidogyne incognita penetration and development were studied in roots of highly resistant (PI 96354, PI 417444), resistant (Forrest), and susceptible (Bossier) soybean genotypes. Although more second-stage juveniles (J2) had penetrated roots of PI 96354 and PI 417444 than roots of Forrest and Bossier by 2 days after inoculation, fewer J2 were present in roots of PI 96354 at 4 days after inoculation. Juvenile development in all genotypes was evident by 6 days after inoculation, with the highest number of swollen J2 present in roots of Bossier. At 16 days after inoculation, roots of PI 96354 had 87%, 74%, and 53% fewer J2 than were present in roots of Bossier, Forrest, and PI 417444, respectively. Differential emigration of J2, not fewer invasion sites, was responsible for the low number of nematodes in roots of the highly resistant PI 96354. Some 72% of the J2 penetrating the roots of this genotype emerged within 5 days after inoculation, whereas 4%, 54%, and 83% emerged from roots of Bossier, Forrest, and PI 417444, respectively. Penetration of roots of PI 96354 decreased the ability of J2 emerging from these roots to infect other soybean roots.     

Response of Resistant Soybean Plant Introductions to Meloidogyne incognita in Field Microplots

The response of two soybean plant introductions, PI 96354 and PI 417444, highly resistant to Meloidogyne incognita, to increasing initial soil population densities (Pi) (0, 31, 125, and 500 eggs/100 cm³ soil) of M. incognita was studied in field microplots for 2 years. The plant introductions were compared to the cultivars Forrest, moderately resistant, and Bossier, susceptible to M. incognita. Averaged across years, the yield suppressions of Bossier, Forrest, PI 417444, and PI 96354 were 97, 12, 18, and < 1%, respectively, at the highest Pi when compared with uninfested control plots. Penetration of roots by second-stage juveniles (J2) increased linearly with increasing Pi at 14 days after planting. At the highest Pi, 62% fewer J2 were present in roots of PI 96354 than in roots of the other resistant genotypes. Soil population densities of M. incognita were lower on both plant introductions than on Forrest. At 75 and 140 days after planting, PI 96354 had the lowest number of J2 in the soil, with 49% and 56% fewer than Forrest at the highest Pi. The resistance genes in PI 96354 should be useful in a breeding program to improve the level of resistance to M. incognita in soybean cultivars.     

Fine Mapping and Characterization of Candidate Genes that Control Resistance to Cercospora sojina K. Hara in Two Soybean Germplasm Accessions

Frogeye leaf spot (FLS), caused by the fungus Cercospora sojina K. Hara, may cause a significant yield loss to soybean growers in regions with a warm and humid climate. Two soybean accessions, PI 594891 and PI 594774, were identified to carry a high level of resistance similar to that conditioned by the Rcs3 gene in ''Davis''. Previously, we reported that the resistance to FLS in these two plant introductions (PIs) was controlled by a novel gene (s) on chromosome 13 that is different from Rcs3. To fine-map the novel FLS resistance gene(s) in these two PIs, F_{2: 3} seeds from the crosses between PI 594891 and PI 594774, and the FLS susceptible genotype ''Blackhawk'' were genotyped with SNP markers that were designed based on the SoySNP50k iSelect BeadChip data to identify recombinant events and locate candidate genes. Analysis of lines possessing key recombination events helped narrow down the FLS-resistance genomic region in PI 594891 from 3.3 Mb to a 72.6 kb region with five annotated genes. The resistance gene in PI 594774 was fine-mapped into a 540 kb region that encompasses the 72.6 kb region found in PI 594891. Sequencing five candidate genes in PI 594891 identified three genes that have several mutations in the promoter, intron, 5'', and 3'' UTR regions. qPCR analysis showed a difference in expression levels of these genes in both lines compared to Blackhawk in the presence of C. sojina. Based on phenotype, genotype and haplotype analysis results, these two soybean accessions might carry different resistance alleles of the same gene or two different gene(s). The identified SNPs were used to develop Kompetitive Allele Specific PCR (KASP) assays to detect the resistance alleles on chromosome 13 from the two PIs for marker-assisted selection.     

Genetic mapping revealed two loci for soybean aphid resistance in PI 567301B

The soybean aphid (Aphis glycines Matsumura) is the most damaging insect pest of soybean [Glycine max (L.) Merr.] in North America. New soybean aphid biotypes have been evolving quickly and at least three confirmed biotypes have been reported in USA. These biotypes are capable of defeating most known aphid resistant soybean genes indicating the need for identification of new genes. Plant Introduction (PI) 567301B was earlier identified to have antixenosis resistance against biotype 1 and 2 of the soybean aphid. Two hundred and three F_7:9 recombinant inbred lines (RILs) developed from a cross of soybean aphid susceptible cultivar Wyandot and resistant PI 567301B were used for mapping aphid resistance genes using the quantitative trait loci (QTL) mapping approach. A subset of 94 RILs and 516 polymorphic SNP makers were used to construct a genome-wide molecular linkage map. Two candidate QTL regions for aphid resistance were identified on this linkage map. Fine mapping of the QTL regions was conducted with SSR markers using all 203 RILs. A major gene on chromosome 13 was mapped near the previously identified Rag2 gene. However, an earlier study revealed that the detached leaves of PI 567301B had no resistance against the soybean aphids while the detached leaves of PI 243540 (source of Rag2) maintained aphid resistance. These results and the earlier finding that PI 243540 showed antibiosis resistance and PI 567301B showed antixenosis type resistance, indicating that the aphid resistances in the two PIs are not controlled by the same gene. Thus, we have mapped a new gene near the Rag2 locus for soybean aphid resistance that should be useful in breeding for new aphid-resistant soybean cultivars. Molecular markers closely linked to this gene are available for marker-assisted breeding. Also, the minor locus found on chromosome 8 represents the first reported soybean aphid-resistant locus on this chromosome.     

Genetic mapping of three quantitative trait loci for soybean aphid resistance in PI 567324

Host-plant resistance is an effective method for controlling soybean aphid (Aphis glycines Matsumura), the most damaging insect pest of soybean (Glycine max (L.) Merr.) in North America. Recently, resistant soybean lines have been discovered and at least four aphid resistance genes (Rag1, Rag2, Rag3 and rag4) have been mapped on different soybean chromosomes. However, the evolution of new soybean aphid biotypes capable of defeating host-plant resistance conferred by most single genes demonstrates the need for finding germplasm with multigenic resistance to the aphid. This study was conducted to map quantitative trait loci (QTL) for aphid resistance in PI 567324. We identified two major QTL (QTL_13_1 and QTL_13_2) for aphid resistance on soybean chromosome 13 using 184 recombinant inbred lines from a ‘Wyandot'' × PI 567324 cross. QTL_13_1 was located close to the previously reported Rag2 gene locus, and QTL_13_2 was close to the rag4 locus. A minor QTL (QTL_6_1) was also detected on chromosome 6, where no gene for soybean aphid resistance has been reported so far. These results indicate that PI 567324 possesses oligogenic resistance to the soybean aphid. The molecular markers closely linked to the QTL reported here will be useful for development of cultivars with oligogenic resistance that are expected to provide broader and more durable resistance against soybean aphids compared with cultivars with monogenic resistance.     

QTL‐seq approach identified genomic regions and diagnostic markers for rust and late leaf spot resistance in groundnut (Arachis hypogaea L.)

Rust and late leaf spot (LLS) are the two major foliar fungal diseases in groundnut, and their co‐occurrence leads to significant yield loss in addition to the deterioration of fodder quality. To identify candidate genomic regions controlling resistance to rust and LLS, whole‐genome resequencing (WGRS)‐based approach referred as ‘QTL‐seq’ was deployed. A total of 231.67 Gb raw and 192.10 Gb of clean sequence data were generated through WGRS of resistant parent and the resistant and susceptible bulks for rust and LLS. Sequence analysis of bulks for rust and LLS with reference‐guided resistant parent assembly identified 3136 single‐nucleotide polymorphisms (SNPs) for rust and 66 SNPs for LLS with the read depth of ≥7 in the identified genomic region on pseudomolecule A03. Detailed analysis identified 30 nonsynonymous SNPs affecting 25 candidate genes for rust resistance, while 14 intronic and three synonymous SNPs affecting nine candidate genes for LLS resistance. Subsequently, allele‐specific diagnostic markers were identified for three SNPs for rust resistance and one SNP for LLS resistance. Genotyping of one RIL population (TAG 24 × GPBD 4) with these four diagnostic markers revealed higher phenotypic variation for these two diseases. These results suggest usefulness of QTL‐seq approach in precise and rapid identification of candidate genomic regions and development of diagnostic markers for breeding applications.     

Loci and candidate gene identification for resistance to Sclerotinia sclerotiorum in soybean (Glycine max L. Merr.) via association and linkage maps

Soybean white mold (SWM), caused by Sclerotinia sclerotiorum ((Lib.) W. Phillips), is currently considered to be the second most important cause of soybean yield loss due to disease. Research is needed to identify SWM‐resistant germplasm and gain a better understanding of the genetic and molecular basis of SWM resistance in soybean. Stem pigmentation after treatment with oxaloacetic acid is an effective indicator of resistance to SWM. A total of 128 recombinant inbred lines (RILs) derived from a cross of ‘Maple Arrow’ (partial resistant to SWM) and ‘Hefeng 25’ (susceptible) and 330 diverse soybean cultivars were screened for the soluble pigment concentration of their stems, which were treated with oxalic acid. Four quantitative trait loci (QTLs) underlying soluble pigment concentration were detected by linkage mapping of the RILs. Three hundred and thirty soybean cultivars were sequenced using the whole‐genome encompassing approach and 25 179 single‐nucleotide polymorphisms (SNPs) were detected for the fine mapping of SWM resistance genes by genome‐wide association studies. Three out of five SNP markers representing a linkage disequilibrium (LD) block and a single locus on chromosome 13 (Gm13) were significantly associated with the soluble pigment content of stems. Three more SNPs that represented three minor QTLs for the soluble pigment content of stems were identified on another three chromosomes by association mapping. A major locus with the largest effect on Gm13 was found both by linkage and association mapping. Four potential candidate genes involved in disease response or the anthocyanin biosynthesis pathway were identified at the locus near the significant SNPs (<60 kbp). The beneficial allele and candidate genes should be useful in soybean breeding for improving resistance to SWM.     

Quantitative trait loci controlling aluminum tolerance in soybean: candidate gene and single nucleotide polymorphism marker discovery

Aluminum (Al) toxicity is an important abiotic stress that affects soybean production in acidic soils throughout the world. Development of Al-tolerant cultivars is an efficient and environmentally friendly solution to the problem. A previous report identified quantitative trait loci (QTL) for Al tolerance inherited from PI 416937, using restriction fragment length polymorphism markers, in a population of Young × PI 416937. The population was genotyped with 162 simple sequence repeats to enhance the power of QTL detection and enable the selection of candidate genes for functional marker development. Two QTL that explained 54 % of the phenotypic variation in root extension under Al stress conditions (HIAL) were refined on chromosomes (chr) Gm08 and Gm16. Three QTL located on chr Gm08, Gm16 and Gm19 explained 59 % of the phenotypic variation in root extension as a percent of control (PC). Two major QTL, designated qAL_HIAL_08 and qAL_PC_08, controlling HIAL and PC, respectively, were mapped to the same genomic region on chr Gm08 and inherited their favorable allele from PI 416937. These QTL explained 45 and 41 % of phenotypic variation in HIAL and PC, respectively. Six homologues for citrate synthase (CS) genes were found in the soybean genome sequence at chr Gm02, Gm08, Gm14, Gm15, and Gm18. Sixteen single nucleotide polymorphisms (SNPs) were identified in the CS homologue on chr Gm08. A SimpleProbe assay of Glyma08g42400-SNP was developed for the major QTL on chr Gm08. The SNPs identified from this region could be used for marker-assisted selection of Al tolerance.     

Mapping soybean aphid resistance genes in PI 567598B

The soybean aphid (Aphis glycines Matsumura) has been a major pest of soybean [Glycine max (L.) Merr.] in North America since it was first reported in 2000. Our previous study revealed that the strong aphid resistance of plant introduction (PI) 567598B was controlled by two recessive genes. The objective of this study was to locate these two genes on the soybean genetic linkage map using molecular markers. A mapping population of 282 F_4:5 lines derived from IA2070 × E06902 was evaluated for aphid resistance in a field trial in 2009 and a greenhouse trial in 2010. Two quantitative trait loci (QTLs) were identified using the composite and multiple interval mapping methods, and were mapped on chromosomes 7 (linkage group M) and 16 (linkage group J), respectively. E06902, a parent derived from PI 567598B, conferred resistance at both loci. In the 2010 greenhouse trial, each of the two QTLs explained over 30 % of the phenotypic variation. Significant epistatic interaction was also found between these two QTLs. However, in the 2009 field trial, only the QTL on chromosome 16 was found and it explained 56.1 % of the phenotypic variation. These two QTLs and their interaction were confirmed with another population consisting of 94 F_2:5 lines in the 2008 and 2009 greenhouse trials. For both trials in the alternative population, these two loci explained about 50 and 80.4 % of the total phenotypic variation, respectively. Our study shows that soybean aphid isolate used in the 2009 field trial defeated the QTL found on chromosome 7. Presence of the QTL on chromosome 16 conferred soybean aphid resistance in all trials. The markers linked to the aphid-resistant QTLs in PI 567598B or its derived lines can be used in marker-assisted breeding for aphid resistance.     

Identification of SNPs tightly linked to the QTL for pod shattering in soybean

The pod shattering or dehiscence is essential for the propagation of pod-bearing plant species in the wild, but it causes significant yield losses during harvest of domesticated crop plants. Identifying novel molecular makers, which are linked to seed-shattering genes, is needed to employ the molecular marker-assisted selection for efficiently developing shattering-resistant soybean varieties. In this study, a genetic linkage map was constructed using 115 recombinant inbred lines (RILs) developed from crosses between the pod shattering susceptible variety, Keunol, and resistant variety, Sinpaldal. A 180 K Axiom® SoyaSNPs data and pod shattering data from two environments in 2001 and 2015 were used to identify quantitative trait loci (QTL) for pod shattering. A major QTL was identified between two flanking single nucleotide polymorphism (SNP) markers, AX-90320801 and AX-90306327 on chromosome 16 with 1.3 cM interval, 857 kb of physical range. In sequence, genotype distribution analysis was conducted using extreme phenotype RILs. This could narrow down the QTL down to 153 kb on the physical map and was designated as qPDH1-KS with 6 annotated gene models. All exons within qPDH1-KS were sequenced and the 6 polymorphic SNPs affecting the amino acid sequence were identified. To develop universally available molecular markers, 38 Korean soybean cultivars were investigated by the association study using the 6 identified SNPs. Only two SNPs were strongly associated with the pod shattering. These two identified SNPs will help to identify the pod shattering responsible gene and to develop pod shattering-resistant soybean plants using marker-assisted selection.     

Novel quantitative trait loci for broad-based resistance to soybean cyst nematode (Heterodera glycines Ichinohe) in soybean PI 567516C

Soybean cyst nematode (SCN, Heterodera glycines Ichinohe) is the most destructive pest of soybean worldwide. Host plant resistance is an effective approach to control this pest. Plant introduction PI 567516C has been reported to be highly resistant to multiple-HG types of SCN. The objectives of this study were to identify and map novel quantitative trait loci (QTL) for SCN resistance to six HG types (also known as races 1, 2, 3, 5, 14, and LY1). Mapping was conducted using 250 F_2:3 progeny derived from a Magellan (susceptible) × PI 567516C (resistant) cross. F_6:7 recombinant inbred lines (RILs) developed from the F_2:3 progeny were employed to confirm the putative QTL identified. A total of 927 polymorphic simple sequence repeats (SSR) and single nucleotide polymorphism (SNP) markers were genotyped. Following the genetic linkage analysis, permutation tests and composite interval mapping were performed to identify and map QTL. Four QTL were associated with resistance to either multiple- or single-SCN HG types. Two QTL for resistance to multiple-SCN HG types were mapped to Chromosomes 10 and 18 and have not been reported in other SCN resistance sources. New QTL were confirmed by analysis of 250 F_6:7 RILs from the same population. SSR and SNP markers closely associated with these QTL can be useful for the development of near-isogenic lines for fine-mapping and positional cloning of candidate genes for SCN resistance.     

Field evaluation of three sources of genetic resistance to sudden death syndrome of soybean

Key message

Despite numerous challenges, field testing of three sources of genetic resistance to sudden death syndrome of soybean provides information to more effectively improve resistance to this disease in cultivars.

Abstract

Sudden death syndrome (SDS) of soybean [Glycine max (L.) Merrill] is a disease that causes yield loss in soybean growing regions across the USA and worldwide. While several quantitative trait loci (QTL) for SDS resistance have been mapped, studies to further evaluate these QTL are limited. The objective of our research was to map SDS resistance QTL and to test the effect of mapped resistance QTL on foliar symptoms when incorporated into elite soybean backgrounds. We mapped a QTL from Ripley to chromosome 10 (CHR10) and a QTL from PI507531 to chromosomes 1 and 18 (CHR1 and 18). Six populations were then developed to test the following QTL: cqSDS-001, with resistance originating from PI567374, CHR10, CHR1, and CHR18. The populations which segregated for resistant and susceptible QTL alleles were field tested in multiple environments and evaluated for SDS foliar symptoms. While foliar disease development was variable across environments and populations, a significant effect of each QTL on disease was detected within at least one environment. This includes the detection of cqSDS-001 in three genetic backgrounds. The QTL allele from the resistant parents was associated with greater resistance than the susceptible alleles for all QTL and backgrounds with the exception of the allele for CHR18, where the opposite occurred. This study highlights the importance and difficulties of evaluating QTL and the need for multi-year SDS field testing. The information presented in this study can aid breeders in making decisions to improve resistance to SDS.

     

A Genome-Wide Association Study of the Maize Hypersensitive Defense Response Identifies Genes That Cluster in Related Pathways

Much remains unknown of molecular events controlling the plant hypersensitive defense response (HR), a rapid localized cell death that limits pathogen spread and is mediated by resistance (R-) genes. Genetic control of the HR is hard to quantify due to its microscopic and rapid nature. Natural modifiers of the ectopic HR phenotype induced by an aberrant auto-active R-gene (Rp1-D21), were mapped in a population of 3,381 recombinant inbred lines from the maize nested association mapping population. Joint linkage analysis was conducted to identify 32 additive but no epistatic quantitative trait loci (QTL) using a linkage map based on more than 7000 single nucleotide polymorphisms (SNPs). Genome-wide association (GWA) analysis of 26.5 million SNPs was conducted after adjusting for background QTL. GWA identified associated SNPs that colocalized with 44 candidate genes. Thirty-six of these genes colocalized within 23 of the 32 QTL identified by joint linkage analysis. The candidate genes included genes predicted to be in involved programmed cell death, defense response, ubiquitination, redox homeostasis, autophagy, calcium signalling, lignin biosynthesis and cell wall modification. Twelve of the candidate genes showed significant differential expression between isogenic lines differing for the presence of Rp1-D21. Low but significant correlations between HR-related traits and several previously-measured disease resistance traits suggested that the genetic control of these traits was substantially, though not entirely, independent. This study provides the first system-wide analysis of natural variation that modulates the HR response in plants.     

Quantitative trait locus for starvation resistance in an intercontinental set of mapping populations of Drosophila melanogaster

Starvation resistance (SR) is an important trait for survival of insects in the wild. We used recombinant inbred lines (RIL) to search for quantitative trait loci (QTL) in crosses between intercontinental inbred lines that were originally selected for heat-knockdown resistance. SR was measured as the time of survival under repeated events of starvation. SR was consistently higher in females than in males. Composite interval mapping identified one QTL region (cytological range 64D - 66E2) on the left arm of chromosome 3 in males, and no QTL was found in females. Many candidate genes that were identified in previous studies of QTL for stress resistance are included within this QTL region. The QTL-allele that decreased SR was found in the line originating from the colder population (Denmark). We discuss our results with regard to multiple candidate genes, non-colocalization with thermotolerance QTL, and possible geographical variation.     

Analysis of the genetic architecture of maize ear and grain morphological traits by combined linkage and association mapping

Key message

Using combined linkage and association mapping, 26 stable QTL and six stable SNPs were detected across multiple environments for eight ear and grain morphological traits in maize. One QTL, PKS2, might play an important role in maize yield improvement.

Abstract

In the present study, one bi-parental population and an association panel were used to identify quantitative trait loci (QTL) for eight ear and grain morphological traits. A total of 108 QTL related to these traits were detected across four environments using an ultra-high density bin map constructed using recombinant inbred lines (RILs) derived from a cross between Ye478 and Qi319, and 26 QTL were identified in more than two environments. Furthermore, 64 single nucleotide polymorphisms (SNPs) were found to be significantly associated with the eight ear and grain morphological traits (?log₁₀(P)?>?4) in an association panel of 240 maize inbred lines. Combining the two mapping populations, a total of 17 pleiotropic QTL/SNPs (pQTL/SNPs) were associated with various traits across multiple environments. PKS2, a stable locus influencing kernel shape identified on chromosome 2 in a genome-wide association study (GWAS), was within the QTL confidence interval defined by the RILs. The candidate region harbored a short 13-Kb LD block encompassing four SNPs (SYN11386, PHM14783.16, SYN11392, and SYN11378). In the association panel, 13 lines derived from the hybrid PI78599 possessed the same allele as Qi319 at the PHM14783.16 (GG) locus, with an average value of 0.21 for KS, significantly lower than that of the 34 lines derived from Ye478 that carried a different allele (0.25, P?<?0.05). Therefore, further fine mapping of PKS2 will provide valuable information for understanding the genetic components of grain yield and improving molecular marker-assisted selection (MAS) in maize.

     

Pooled analysis of data from multiple quantitative trait locus mapping populations

Quantitative trait locus (QTL) analysis on pooled data from multiple populations (pooled analysis) provides a means for evaluating, as a whole, evidence for existence of a QTL from different studies and examining differences in gene effect of a QTL among different populations. Objectives of this study were to: (1) develop a method for pooled analysis and (2) conduct pooled analysis on data from two soybean mapping populations. Least square interval mapping was extended for pooled analysis by inclusion of populations and cofactor markers as indicator variables and covariate variables separately in the multiple linear models. The general linear test approach was applied for detecting a QTL. Single population-based and pooled analyses were conducted on data from two F_2:3 mapping populations, Hamilton (susceptible) × PI 90763 (resistant) and Magellan (susceptible) × PI 404198A (resistant), for resistance to soybean cyst nematode (SCN) in soybean. It was demonstrated that where a QTL was shared among populations, pooled analysis showed increased LOD values on the QTL candidate region over single population analyses. Where a QTL was not shared among populations, however, the pooled analysis showed decreased LOD values on the QTL candidate region over single population analyses. Pooled analysis on data from genetically similar populations may have higher power of QTL detection than single population-based analyses. QTLs were identified by pooled analysis on linkage groups (LGs) G, B1 and J for resistance to SCN race 2 whereas QTLs on LGs G, B1 and E for resistance to SCN race 5 in soybean PI 90763 and PI 404198A. QTLs on LG G and B1 were identified in both PI 90763 and PI 404198A whereas QTLs on LG E and J were identified in PI 90763 only. QTLs on LGs G and B1 for resistance to race 2 may be the same or closely linked with QTLs on LG G and B1 for resistance to race 5, respectively. It was further demonstrated that QTLs on G and B1 carried by PI 90763 were not significantly different in gene effect from QTLs on LGs G and B1 in PI 404198A, respectively.     

SNP identification and marker assay development for high-throughput selection of soybean cyst nematode resistance

Background

Soybean cyst nematode (SCN) is the most economically devastating pathogen of soybean. Two resistance loci, Rhg1 and Rhg4 primarily contribute resistance to SCN race 3 in soybean. Peking and PI 88788 are the two major sources of SCN resistance with Peking requiring both Rhg1 and Rhg4 alleles and PI 88788 only the Rhg1 allele. Although simple sequence repeat (SSR) markers have been reported for both loci, they are linked markers and limited to be applied in breeding programs due to accuracy, throughput and cost of detection methods. The objectives of this study were to develop robust functional marker assays for high-throughput selection of SCN resistance and to differentiate the sources of resistance.

Results

Based on the genomic DNA sequences of 27 soybean lines with known SCN phenotypes, we have developed Kompetitive Allele Specific PCR (KASP) assays for two Single nucleotide polymorphisms (SNPs) from Glyma08g11490 for the selection of the Rhg4 resistance allele. Moreover, the genomic DNA of Glyma18g02590 at the Rhg1 locus from 11 soybean lines and cDNA of Forrest, Essex, Williams 82 and PI 88788 were fully sequenced. Pairwise sequence alignment revealed seven SNPs/insertion/deletions (InDels), five in the 6th exon and two in the last exon. Using the same 27 soybean lines, we identified one SNP that can be used to select the Rhg1 resistance allele and another SNP that can be employed to differentiate Peking and PI 88788-type resistance. These SNP markers have been validated and a strong correlation was observed between the SNP genotypes and reactions to SCN race 3 using a panel of 153 soybean lines, as well as a bi-parental population, F₅–derived recombinant inbred lines (RILs) from G00-3213 x LG04-6000.

Conclusions

Three functional SNP markers (two for Rhg1 locus and one for Rhg4 locus) were identified that could provide genotype information for the selection of SCN resistance and differentiate Peking from PI 88788 source for most germplasm lines. The robust KASP SNP marker assays were developed. In most contexts, use of one or two of these markers is sufficient for high-throughput marker-assisted selection of plants that will exhibit SCN resistance.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1531-3) contains supplementary material, which is available to authorized users.