Genetic mapping reveals the complex genetic architecture controlling slow canopy wilting in soybean.

In soybean [Glycine max (L.) Merr.], drought stress is the leading cause of yield loss from abiotic stress in rain-fed US growing areas. Only 10% of the US soybean production is irrigated; therefore, plants must possess physiological mechanisms to tolerate drought stress. Slow canopy wilting is a physiological trait that is observed in a few exotic plant introductions (PIs) and may lead to yield improvement under drought stress. Canopy wilting of 130 recombinant inbred lines (RILs) derived from Hutcheson × PI 471938 grown under drought stress was visually evaluated and genotyped with the SoySNP6K BeadChip. Over four years, field evaluations of canopy wilting were conducted under rainfed conditions at three locations across the US (Georgia, Kansas, and North Carolina). Due to the variation in weather among locations and years, the phenotypic data were collected from seven environments. Substantial variation in canopy wilting was observed among the genotypes in the RIL population across environments. Three QTLs were identified for canopy wilting from the RIL population using composite interval mapping on chromosomes (Chrs) 2, 8, and 9 based on combined environmental analyses. These QTLs inherited the favorable alleles from PI 471938 and accounted for 11, 10, and 14% of phenotypic variation, respectively. A list of 106 candidate genes were narrowed down for these three QTLs based on the published information. The QTLs identified through this research can be used as targets for further investigation to understand the mechanisms of slow canopy wilting. These QTLs could be deployed to improve drought tolerance through a targeted selection of the genomic regions from PI 471938.

Genome-wide association study reveals novel loci and a candidate gene for resistance to frogeye leaf spot (Cercospora sojina) in soybean.

Frogeye leaf spot, caused by the fungus Cercospora sojina, is a threat to soybeans in the southeastern and midwestern United States that can be controlled by crop genetic resistance. Limited genetic resistance to the disease has been reported, and only three sources of resistance have been used in modern soybean breeding. To discover novel sources and identify the genomic locations of resistance that could be used in soybean breeding, a GWAS was conducted using a panel of 329 soybean accessions selected to maximize genetic diversity. Accessions were phenotyped using a 1-5 visual rating and by using image analysis to count lesion number and measure the percent of leaf area diseased. Eight novel loci on eight chromosomes were identified for three traits utilizing the FarmCPU or BLINK models, of which a locus on chromosome 11 was highly significant across all model-trait combinations. KASP markers were designed using the SoySNP50K Beadchip and variant information from 65 of the accessions that have been sequenced to target SNPs in the gene model Glyma.11g230400, a LEUCINE-RICH REPEAT RECEPTOR-LIKE PROTEIN KINASE. The association of a KASP marker, GSM990, designed to detect a missense mutation in the gene was the most significant with all three traits in a genome-wide association, and the marker may be useful to select for resistance to frogeye leaf spot in soybean breeding.

A chromosome 16 deletion conferring a high sucrose phenotype in soybean.

KEY MESSAGE: Sucrose in soybean seeds is desirable for many end-uses. Increased sucrose contents were discovered to associate with a chromosome 16 deletion resulting from fast neutron irradiation. Soybean is one of the most economically important crops in the United States. A primary end-use of soybean is for livestock feed. Therefore, genetic improvement of seed composition is one of the most important goals in soybean breeding programs. Sucrose is desired in animal feed due to its role as an easily digestible energy source. An elite soybean line was irradiated with fast neutrons and the seed from plants were screened for altered seed composition with near-infrared spectroscopy (NIR). One mutant line, G15FN-54, was found to have higher sucrose content (8-9%) than the parental line (5-6%). Comparative genomic hybridization (CGH) revealed three large deletions on chromosomes (Chrs) 10, 13, and 16 in the mutant, which were confirmed through whole genome sequencing (WGS). A bi-parental population derived from the mutant G15FN-54 and the cultivar Benning was developed to conduct a bulked segregant analysis (BSA) with SoySNP50K BeadChips, revealing that the deletion on Chr 16 might be responsible for the altered phenotype. The mapping result using the bi-parental population confirmed that the deletion on Chr 16 conferred elevated sucrose content and a total of 21 genes are located within this Chr 16 deletion. NIR and high-pressure liquid chromatography (HPLC) were used to confirm the stability of the phenotype across generations in the bi-parental population. The mutation will be useful to understand the genetic control of soybean seed sucrose content.

Pinpointing Rcs3 for frogeye leaf spot resistance and tracing its origin in soybean breeding.

Frogeye leaf spot is a yield-reducing disease of soybean caused by the pathogen Cercospora sojina. Rcs3 has provided durable resistance to all known races of C. sojina since its discovery in the cultivar Davis during the 1980s. Using a recombinant inbred line population derived from a cross between Davis and the susceptible cultivar Forrest, Rcs3 was fine-mapped to a 1.15 Mb interval on chromosome 16. This single locus was confirmed by tracing Rcs3 in resistant and susceptible progeny derived from Davis, as well as three near-isogenic lines. Haplotype analysis in the ancestors of Davis indicated that Davis has the same haplotype at the Rcs3 locus as susceptible cultivars in its paternal lineage. On the basis of these results, it is hypothesized that the resistance allele in Davis resulted from a mutation of a susceptibility allele. Tightly linked SNP markers at the Rcs3 locus identified in this research can be used for effective marker-assisted selection. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-023-01397-x.

Genomic regions associated with resistance to soybean rust (Phakopsora pachyrhizi) under field conditions in soybean germplasm accessions from Japan, Indonesia and Vietnam.

KEY MESSAGE: Eight soybean genomic regions, including six never before reported, were found to be associated with resistance to soybean rust (Phakopsora pachyrhizi) in the southeastern USA. Soybean rust caused by Phakopsora pachyrhizi is one of the most important foliar diseases of soybean [Glycine max (L.) Merr.]. Although seven Rpp resistance gene loci have been reported, extensive pathotype variation in and among fungal populations increases the importance of identifying additional genes and loci associated with rust resistance. One hundred and ninety-one soybean plant introductions from Japan, Indonesia and Vietnam, and 65 plant introductions from other countries were screened for resistance to P. pachyrhizi under field conditions in the southeastern USA between 2008 and 2015. The results indicated that 84, 69, and 49% of the accessions from southern Japan, Vietnam or central Indonesia, respectively, had negative BLUP values, indicating less disease than the panel mean. A genome-wide association analysis using SoySNP50K Infinium BeadChip data identified eight genomic regions on seven chromosomes associated with SBR resistance, including previously unreported regions of Chromosomes 1, 4, 6, 9, 13, and 15, in addition to the locations of the Rpp3 and Rpp6 loci. The six unreported genomic regions might contain novel Rpp loci. The identification of additional sources of rust resistance and associated genomic regions will further efforts to develop soybean cultivars with broad and durable resistance to soybean rust in the southern USA.

Identification of Functional Genetic Variations Underlying Flooding Tolerance in Brazilian Soybean Genotypes.

Flooding is a frequent environmental stress that reduces soybean (Glycine max) growth and grain yield in many producing areas in the world, such as, e.g., in the United States, Southeast Asia and Southern Brazil. In these regions, soybean is frequently cultivated in lowland areas by rotating with rice (Oryza sativa), which provides numerous technical, economic and environmental benefits. Given these realities, this work aimed to characterize physiological responses, identify genes differentially expressed under flooding stress in Brazilian soybean genotypes with contrasting flooding tolerance, and select SNPs with potential use for marker-assisted selection. Soybean cultivars TECIRGA 6070 (flooding tolerant) and FUNDACEP 62 (flooding sensitive) were grown up to the V6 growth stage and then flooding stress was imposed. Total RNA was extracted from leaves 24 h after the stress was imposed and sequenced. In total, 421 induced and 291 repressed genes were identified in both genotypes. TECIRGA 6070 presented 284 and 460 genes up- and down-regulated, respectively, under flooding conditions. Of those, 100 and 148 genes were exclusively up- and down-regulated, respectively, in the tolerant genotype. Based on the RNA sequencing data, SNPs in differentially expressed genes in response to flooding stress were identified. Finally, 38 SNPs, located in genes with functional annotation for response to abiotic stresses, were found in TECIRGA 6070 and absent in FUNDACEP 62. To validate them, 22 SNPs were selected for designing KASP assays that were used to genotype a panel of 11 contrasting genotypes with known phenotypes. In addition, the phenotypic and grain yield impacts were analyzed in four field experiments using a panel of 166 Brazilian soybean genotypes. Five SNPs possibly related to flooding tolerance in Brazilian soybean genotypes were identified. The information generated from this research will be useful to develop soybean genotypes adapted to poorly drained soils or areas subject to flooding.

Mining QTLs for elevated protein and other major seed composition traits from diverse soybean germplasm.

Soybean is the world's largest source of protein for animal feed and the second largest source of vegetable oil. Improving the seed protein of soybean without negatively affecting yield and oil content is an important goal for soybean breeders. A population consisting of 132 recombinant inbred lines (RILs) was developed by crossing an elite breeding line, G00-3213 with a plant introduction, PI 594458A, with elevated protein content. In 2016 and 2017, each of the RILs was grown as a single row in Watkinsville, GA, while in 2018, the population was grown at two locations. The seed composition of RILs was analyzed with near-infrared (NIR) spectroscopy. The RIL population was genotyped using the SoySNP6k BeadChip for quantitative trait locus (QTL) mapping. Significant genotype × environment interaction was observed. QTL analyses in and across four environments identified 16, 10, 10, 16, and 5 QTLs for protein, oil, sucrose, and normalized cysteine and methionine contents, respectively. QTLs for protein content identified on chromosomes (Chrs) 3, 6, 13, and 20 were detected in multiple environments. Eight genomic regions on Chrs 3, 6, 8, 10, 13, 17, and 20 were detected that influenced two to four traits, indicating that pleiotropic or linkage effects of these loci may influence multiple seed composition traits. The results of this research provide additional genomic resources for genetic improvement of seed composition and help breeders to better understand the environmental impacts on these QTLs. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-021-01242-z.

Assessment of Quinone Outside Inhibitor Sensitivity and Frogeye Leaf Spot Race of Cercospora sojina in Georgia Soybean.

Frogeye leaf spot (FLS), caused by the fungal pathogen Cercospora sojina K. Hara, is a foliar disease of soybean (Glycine max L. [Merr.]) responsible for yield reductions throughout the major soybean-producing regions of the world. In the United States, management of FLS relies heavily on the use of resistant cultivars and in-season fungicide applications, specifically within the class of quinone outside inhibitors (QoIs), which has resulted in the development of fungicide resistance in many states. In 2018 and 2019, 80 isolates of C. sojina were collected from six counties in Georgia and screened for QoI fungicide resistance using molecular and in vitro assays, with resistant isolates being confirmed from three counties. Additionally, 50 isolates, including a "baseline isolate" with no prior fungicide exposure, were used to determine the percent reduction of mycelial growth to two fungicides, azoxystrobin and pyraclostrobin, at six concentrations: 0.0001, 0.001, 0.01, 0.1, 1, and 10 µg ml-1. Mycelial growth observed for resistant isolates varied significantly from both sensitive isolates and baseline isolate for azoxystrobin concentrations of 10, 1, 0.1, and 0.01 µg ml-1 and for pyraclostrobin concentrations of 10, 1, 0.1, 0.01, and 0.001 µg ml-1. Moreover, 40 isolates were used to evaluate pathogen race on six soybean differential cultivars by assessing susceptible or resistant reactions. Isolate reactions suggested 12 races of C. sojina present in Georgia, 4 of which have not been previously described. Species richness indicators (rarefaction and abundance-based coverage estimators) indicated that within-county C. sojina race numbers were undersampled in this study, suggesting the potential for the presence of either additional undescribed races or known but unaccounted for races in Georgia. However, no isolates were pathogenic on 'Davis', a differential cultivar carrying the Rcs3 resistance allele, suggesting that the gene is still an effective source of resistance in Georgia.

Unraveling the genetic architecture for carbon and nitrogen related traits and leaf hydraulic conductance in soybean using genome-wide association analyses.

BACKGROUND: Drought stress is a major limiting factor of soybean [Glycine max (L.) Merr.] production around the world. Soybean plants can ameliorate this stress with improved water-saving, sustained N2 fixation during water deficits, and/or limited leaf hydraulic conductance. In this study, carbon isotope composition (δ13C), which can relate to variation in water-saving capability, was measured. Additionally, nitrogen isotope composition (δ15N) and nitrogen concentration that relate to nitrogen fixation were evaluated. Decrease in transpiration rate (DTR) of de-rooted soybean shoots in a silver nitrate (AgNO3) solution compared to deionized water under high vapor pressure deficit (VPD) conditions was used as a surrogate measurement for limited leaf hydraulic conductance. A panel of over 200 genetically diverse soybean accessions genotyped with the SoySNP50K iSelect BeadChips was evaluated for the carbon and nitrogen related traits in two field environments (Athens, GA in 2015 and 2016) and for transpiration response to AgNO3 in a growth chamber. A multiple loci linear mixed model was implemented in FarmCPU to perform genome-wide association analyses for these traits. RESULTS: Thirty two, 23, 26, and nine loci for δ13C, δ15N, nitrogen concentration, and transpiration response to AgNO3, respectively, were significantly associated with these traits. Candidate genes that relate to drought stress tolerance enhancement or response were identified near certain loci that could be targets for improving and understanding these traits. Soybean accessions with favorable breeding values were also identified. Low correlations were observed between many of the traits and the genetic loci associated with each trait were largely unique, indicating that these drought tolerance related traits are governed by different genetic loci. CONCLUSIONS: The genomic regions and germplasm identified in this study can be used by breeders to understand the genetic architecture for these traits and to improve soybean drought tolerance. Phenotyping resources needed, trait heritability, and relationship to the target environment should be considered before deciding which of these traits to ultimately employ in a specific breeding program. Potential marker-assisted selection efforts could focus on loci which explain the greatest amount of phenotypic variation for each trait, but may be challenging due to the quantitative nature of these traits.

Identification and characterization of a fast-neutron-induced mutant with elevated seed protein content in soybean.

KEY MESSAGE: Protein content of soybean is critical for utility of soybean meal. A fast-neutron-induced deletion on chromosome 12 was found to be associated with increased protein content. Soybean seed composition affects the utility of soybean, and improving seed composition is an essential breeding goal. Fast neutron radiation introduces genomic mutations resulting in novel variation for traits of interest. Two elite soybean lines were irradiated with fast neutrons and screened for altered seed composition. Twenty-three lines with altered protein, oil, or sucrose content were selected based on near-infrared spectroscopy data from five environments and yield tested at five locations. Mutants with significantly increased protein averaged 19.1-36.8 g kg-1 more protein than the parents across 10 environments. Comparative genomic hybridization (CGH) identified putative mutations in a mutant, G15FN-12, that has 36.8 g kg-1 higher protein than the parent genotype, and whole genome sequencing (WGS) of the mutant has confirmed these mutations. An F2:3 population was developed from G15FN-12 to determine association between genomic changes and increased protein content. Bulked segregant analysis of the population using the SoySNP50K BeadChip identified a CGH- and WGS-confirmed deletion on chromosome 12 to be responsible for elevated protein content. The population was genotyped using a KASP marker designed at the mutation region, and significant association (P < 0.0001) between the deletion on chromosome 12 and elevated protein content was observed and confirmed in the F3:4 generation. The F2 segregants homozygous for the deletion averaged 27 g kg-1 higher seed protein and 8 g kg-1 lower oil than homozygous wild-type segregants. Mutants with altered seed composition are a new resource for gene function studies and provide elite materials for genetic improvement of seed composition.

Genetic mapping and validation of the loci controlling 7S α' and 11S A-type storage protein subunits in soybean [Glycine max (L.) Merr.].

KEY MESSAGE: Four soybean storage protein subunit QTLs were mapped using bulked segregant analysis and an F2 population, which were validated with an F5 RIL population. The storage protein globulins ß-conglycinin (7S subunit) and glycinin (11S subunits) can affect the quantity and quality of proteins found in soybean seeds and account for more than 70% of the total soybean protein. Manipulating the storage protein subunits to enhance soymeal nutrition and for desirable tofu manufacturing characteristics are two end-use quality goals in soybean breeding programs. To aid in developing soybean cultivars with desired seed composition, an F2 mapping population (n = 448) and an F5 RIL population (n = 180) were developed by crossing high protein cultivar 'Harovinton' with the breeding line SQ97-0263_3-1a, which lacks the 7S α', 11S A1, 11S A2, 11S A3 and 11S A4 subunits. The storage protein composition of each individual in the F2 and F5 populations were profiled using SDS-PAGE. Based on the presence/absence of the subunits, genomic DNA bulks were formed among the F2 plants to identify genomic regions controlling the 7S α' and 11S protein subunits. By utilizing polymorphic SNPs between the bulks characterized with Illumina SoySNP50K iSelect BeadChips at targeted genomic regions, KASP assays were designed and used to map QTLs causing the loss of the subunits. Soybean storage protein QTLs were identified on Chromosome 3 (11S A1), Chromosome 10 (7S α' and 11S A4), and Chromosome 13 (11S A3), which were also validated in the F5 RIL population. The results of this research could allow for the deployment of marker-assisted selection for desired storage protein subunits by screening breeding populations using the SNPs linked with the subunits of interest.

Discovery of a seventh Rpp soybean rust resistance locus in soybean accession PI 605823.

KEY MESSAGE: A novel Rpp gene from PI 605823 for resistance to Phakopsora pachyrhizi was mapped on chromosome 19. Soybean rust, caused by the obligate biotrophic fungal pathogen Phakopsora pachyrhizi Syd. & P. Syd, is a disease threat to soybean production in regions of the world with mild winters. Host plant resistance conditioned by resistance to P. pachyrhizi (Rpp) genes has been found in numerous soybean accessions, and at least 10 Rpp genes or alleles have been mapped to six genetic loci. Identifying additional disease-resistance genes will facilitate development of soybean cultivars with durable resistance. PI 605823, a plant introduction from Vietnam, was previously identified as resistant to US populations of P. pachyrhizi in greenhouse and field trials. In this study, bulked segregant analysis using an F2 population derived from 'Williams 82' × PI 605823 identified a genomic region associated with resistance to P. pachyrhizi isolate GA12, which had been collected in the US State of Georgia in 2012. To further map the resistance locus, linkage mapping was carried out using single-nucleotide polymorphism markers and phenotypic data from greenhouse assays with an F2:3 population derived from Williams 82 × PI 605823 and an F4:5 population derived from '5601T' × PI 605823. A novel resistance gene, Rpp7, was mapped to a 154-kb interval (Gm19: 39,462,291-39,616,643 Glyma.Wm82.a2) on chromosome 19 that is different from the genomic locations of any previously reported Rpp genes. This new gene could be incorporated into elite breeding lines to help provide more durable resistance to soybean rust.

Advancements in breeding, genetics, and genomics for resistance to three nematode species in soybean.

KEY MESSAGE: Integration of genetic analysis, molecular biology, and genomic approaches drastically enhanced our understanding of genetic control of nematode resistance and provided effective breeding strategies in soybeans. Three nematode species, including soybean cyst (SCN, Heterodera glycine), root-knot (RKN, Meloidogyne incognita), and reniform (RN, Rotylenchulus reniformis), are the most destructive pests and have spread to soybean growing areas worldwide. Host plant resistance has played an important role in their control. This review focuses on genetic, genomic studies, and breeding efforts over the past two decades to identify and improve host resistance to these three nematode species. Advancements in genetics, genomics, and bioinformatics have improved our understanding of the molecular and genetic mechanisms of nematode resistance and enabled researchers to generate large-scale genomic resources and marker-trait associations. Whole-genome resequencing, genotyping-by-sequencing, genome-wide association studies, and haplotype analyses have been employed to map and dissect genomic locations for nematode resistance. Recently, two major SCN-resistant loci, Rhg1 and Rhg4, were cloned and other novel resistance quantitative trait loci (QTL) have been discovered. Based on these discoveries, gene-specific DNA markers have been developed for both Rhg1 and Rhg4 loci, which were useful for marker-assisted selection. With RKN resistance QTL being mapped, candidate genes responsible for RKN resistance were identified, leading to the development of functional single nucleotide polymorphism markers. So far, three resistances QTL have been genetically mapped for RN resistance. With nematode species overcoming the host plant resistance, continuous efforts in the identification and deployment of new resistance genes are required to support the development of soybean cultivars with multiple and durable resistance to these pests.

A novel Phakopsora pachyrhizi resistance allele (Rpp) contributed by PI 567068A.

KEY MESSAGE: The Rpp6 locus of PI 567102B was mapped from 5,953,237 to 5,998,461 bp (chromosome 18); and a novel allele at the Rpp6 locus or tightly linked gene Rpp[PI567068A] of PI 567068A was mapped from 5,998,461 to 6,160,481 bp. Soybean rust (SBR), caused by the obligate, fungal pathogen Phakopsora pachyrhizi is an economic threat to soybean production, especially in the Americas. Host plant resistance is an important management strategy for SBR. The most recently described resistance to P. pachyrhizi (Rpp) gene is Rpp6 contributed by PI 567102B. Rpp6 was previously mapped to an interval of over four million base pairs on chromosome 18. PI 567068A was recently demonstrated to possess a resistance gene near the Rpp6 locus, yet PI 567068A gave a differential isolate reaction to several international isolates of P. pachyrhizi. The goals of this research were to fine map the Rpp6 locus of PI 567102B and PI 567068A and determine whether or not PI 567068A harbors a novel Rpp6 allele or another allele at a tightly linked resistance locus. Linkage mapping in this study mapped Rpp6 from 5,953,237 to 5,998,461 bp (LOD score of 58.3) and the resistance from PI 567068A from 5,998,461 to 6,160,481 bp (LOD score of 4.4) (Wm82.a1 genome sequence). QTL peaks were 139,033 bp apart from one another as determined by the most significant SNPs in QTL mapping. The results of haplotype analysis demonstrated that PI 567102B and PI 567068A share the same haplotype in the resistance locus containing both Rpp alleles, which was designated as the Rpp6/Rpp[PI567068A] haplotype. The Rpp6/Rpp[PI567068A] haplotype identified in this study can be used as a tool to rapidly screen other genotypes that possess a Rpp gene(s) and detect resistance at the Rpp6 locus in diverse germplasm.

Pinpointing genes underlying the quantitative trait loci for root-knot nematode resistance in palaeopolyploid soybean by whole genome resequencing.

The objective of this study was to use next-generation sequencing technologies to dissect quantitative trait loci (QTL) for southern root-knot nematode (RKN) resistance into individual genes in soybean. Two hundred forty-six recombinant inbred lines (RIL) derived from a cross between Magellan (susceptible) and PI 438489B (resistant) were evaluated for RKN resistance in a greenhouse and sequenced at an average of 0.19× depth. A sequence analysis pipeline was developed to identify and validate single-nucleotide polymorphisms (SNPs), infer the parental source of each SNP allele, and genotype the RIL population. Based on 109,273 phased SNPs, recombination events in RILs were identified, and a total of 3,509 bins and 3,489 recombination intervals were defined. About 50.8% of bins contain 1 to 10 genes. A linkage map was subsequently constructed by using bins as molecular markers. Three QTL for RKN resistance were identified. Of these, one major QTL was mapped to bin 10 of chromosome 10, which is 29.7 kb in size and harbors three true genes and two pseudogenes. Based on sequence variations and gene-expression analysis, the candidate genes underlying the major QTL for RKN resistance were pinpointed. They are Glyma10g02150 and Glyma10g02160, encoding a pectin methylesterase inhibitor and a pectin methylesterase inhibitor -pectin methylesterase, respectively. This QTL mapping approach not only combines SNP discovery, SNP validation, and genotyping, but also solves the issues caused by genome duplication and repetitive sequences. Hence, it can be widely used in crops with a reference genome to enhance QTL mapping accuracy.

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 G00-3213xLG04-6000. 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.

Transcriptomic changes due to water deficit define a general soybean response and accession-specific pathways for drought avoidance.

BACKGROUND: Among abiotic stresses, drought is the most common reducer of crop yields. The slow-wilting soybean genotype PI 416937 is somewhat robust to water deficit and has been used previously to map the trait in a bi-parental population. Since drought stress response is a complex biological process, whole genome transcriptome analysis was performed to obtain a deeper understanding of the drought response in soybean. RESULTS: Contrasting data from PI 416937 and the cultivar 'Benning', we developed a classification system to identify genes that were either responding to water-deficit in both genotypes or that had a genotype x environment (GxE) response. In spite of very different wilting phenotypes, 90% of classifiable genes had either constant expression in both genotypes (33%) or very similar response profiles (E genes, 57%). By further classifying E genes based on expression profiles, we were able to discern the functional specificity of transcriptional responses at particular stages of water-deficit, noting both the well-known reduction in photosynthesis genes as well as the less understood up-regulation of the protein transport pathway. Two percent of classifiable genes had a well-defined GxE response, many of which are located within slow-wilting QTLs. We consider these strong candidates for possible causal genes underlying PI 416937's unique drought avoidance strategy. CONCLUSIONS: There is a general and functionally significant transcriptional response to water deficit that involves not only known pathways, such as down-regulation of photosynthesis, but also up-regulation of protein transport and chromatin remodeling. Genes that show a genotypic difference are more likely to show an environmental response than genes that are constant between genotypes. In this study, at least five genes that clearly exhibited a genotype x environment response fell within known QTL and are very good candidates for further research into slow-wilting.

Fine mapping of the Asian soybean rust resistance gene Rpp2 from soybean PI 230970.

KEY MESSAGE: Asian soybean rust (ASR) resistance gene Rpp2 has been fine mapped into a 188.1 kb interval on Glyma.Wm82.a2, which contains a series of plant resistance ( R ) genes. Asian soybean rust (ASR), caused by the fungus Phakopsora pachyrihizi Syd. & P. Syd., is a serious disease in major soybean [Glycine max (L.) Merr.] production countries worldwide and causes yield losses up to 75 %. Defining the exact chromosomal position of ASR resistance genes is critical for improving the effectiveness of marker-assisted selection (MAS) for resistance and for cloning these genes. The objective of this study was to fine map the ASR resistance gene Rpp2 from the plant introduction (PI) 230970. Rpp2 was previously mapped within a 12.9-cM interval on soybean chromosome 16. The fine mapping was initiated by identifying recombination events in F2 and F3 plants using simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers that flank the gene. Seventeen recombinant plants were identified and then tested with additional genetic markers saturating the gene region to localize the positions of each recombination. The progeny of these selected plants were tested for resistance to ASR and with SSR markers resulting in the mapping of Rpp2 to a 188.1 kb interval on the Williams 82 reference genome (Glyma.Wm82.a2). Twelve genes including ten toll/interleukin-1 receptor (TIR)-nucleotide-binding site (NBS)-leucine-rich repeat (LRR) genes were predicted to exist in this interval on the Glyma.Wm82.a2.v1 gene model map. Eight of these ten genes were homologous to the Arabidopsis TIR-NBS-LRR gene AT5G17680.1. The identified SSR and SNP markers close to Rpp2 and the candidate gene information presented in this study will be significant resources for MAS and gene cloning research.

Confirmation of delayed canopy wilting QTLs from multiple soybean mapping populations.

KEY MESSAGE: QTLs for delayed canopy wilting from five soybean populations were projected onto the consensus map to identify eight QTL clusters that had QTLs from at least two independent populations. Quantitative trait loci (QTLs) for canopy wilting were identified in five recombinant inbred line (RIL) populations, 93705 KS4895 × Jackson, 08705 KS4895 × Jackson, KS4895 × PI 424140, A5959 × PI 416937, and Benning × PI 416937 in a total of 15 site-years. For most environments, heritability of canopy wilting ranged from 0.65 to 0.85 but was somewhat lower when averaged over environments. Putative QTLs were identified with composite interval mapping and/or multiple interval mapping methods in each population and positioned on the consensus map along with their 95% confidence intervals (CIs). We initially found nine QTL clusters with overlapping CIs on Gm02, Gm05, Gm11, Gm14, Gm17, and Gm19 identified from at least two different populations, but a simulation study indicated that the QTLs on Gm14 could be false positives. A QTL on Gm08 in the 93705 KS4895 × Jackson population co-segregated with a QTL for wilting published previously in a Kefeng1 × Nannong 1138-2 population, indicating that this may be an additional QTL cluster. Excluding the QTL cluster on Gm14, results of the simulation study indicated that the eight remaining QTL clusters and the QTL on Gm08 appeared to be authentic QTLs. QTL × year interactions indicated that QTLs were stable over years except for major QTLs on Gm11 and Gm19. The stability of QTLs located on seven clusters indicates that they are possible candidates for use in marker-assisted selection.

Non-toxic and efficient DNA extractions for soybean leaf and seed chips for high-throughput and large-scale genotyping.

In applied soybean (Glycine max L.) breeding programs, marker-assisted selection has become a necessity to select value-added quantitative trait loci. The goal of this work was to improve marker-assisted selection workflow by developing a reliable, inexpensive, high-throughput DNA extraction protocol for soybean seed and leaf samples that does not generate hazardous waste. The DNA extraction protocol developed allows for the leverage of robust SNP genotyping platforms such as the Simple Probe Assay and KASPar v4.0 SNP Genotyping System to genotype thousands of seeds or leaves non-destructively in a single day with a 95 % success rate. This methodology makes it possible to run up to 150 SNP markers on the DNA extracted from a single seed chip or leaf sample.