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

A chromosome 16 deletion conferring a high sucrose phenotype in soybean

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.

Breeding for disease resistance in soybean: a global perspective

KEY MESSAGE

This review provides a comprehensive atlas of QTLs, genes, and alleles conferring resistance to 28 important diseases in all major soybean production regions in the world. Breeding disease-resistant soybean [Glycine max (L.) Merr.] varieties is a common goal for soybean breeding programs to ensure the sustainability and growth of soybean production worldwide. However, due to global climate change, soybean breeders are facing strong challenges to defeat diseases. Marker-assisted selection and genomic selection have been demonstrated to be successful methods in quickly integrating vertical resistance or horizontal resistance into improved soybean varieties, where vertical resistance refers to R genes and major effect QTLs, and horizontal resistance is a combination of major and minor effect genes or QTLs. This review summarized more than 800 resistant loci/alleles and their tightly linked markers for 28 soybean diseases worldwide, caused by nematodes, oomycetes, fungi, bacteria, and viruses. The major breakthroughs in the discovery of disease resistance gene atlas of soybean were also emphasized which include: (1) identification and characterization of vertical resistance genes reside rhg1 and Rhg4 for soybean cyst nematode, and exploration of the underlying regulation mechanisms through copy number variation and (2) map-based cloning and characterization of Rps11 conferring resistance to 80% isolates of Phytophthora sojae across the USA. In this review, we also highlight the validated QTLs in overlapping genomic regions from at least two studies and applied a consistent naming nomenclature for these QTLs. Our review provides a comprehensive summary of important resistant genes/QTLs and can be used as a toolbox for soybean improvement. Finally, the summarized genetic knowledge sheds light on future directions of accelerated soybean breeding and translational genomics studies.

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.

Incorporation of Soil-Derived Covariates in Progeny Testing and Line Selection to Enhance Genomic Prediction Accuracy in Soybean Breeding

The availability of high-dimensional molecular markers has allowed plant breeding programs to maximize their efficiency through the genomic prediction of a phenotype of interest. Yield is a complex quantitative trait whose expression is sensitive to environmental stimuli. In this research, we investigated the potential of incorporating soil texture information and its interaction with molecular markers via covariance structures for enhancing predictive ability across breeding scenarios. A total of 797 soybean lines derived from 367 unique bi-parental populations were genotyped using the Illumina BARCSoySNP6K and tested for yield during 5 years in Tiptonville silt loam, Sharkey clay, and Malden fine sand environments. Four statistical models were considered, including the GBLUP model (M1), the reaction norm model (M2) including the interaction between molecular markers and the environment (G×E), an extended version of M2 that also includes soil type (S), and the interaction between soil type and molecular markers (G×S) (M3), and a parsimonious version of M3 which discards the G×E term (M4). Four cross-validation scenarios simulating progeny testing and line selection of tested–untested genotypes (TG, UG) in observed–unobserved environments [OE, UE] were implemented (CV2 [TG, OE], CV1 [UG, OE], CV0 [TG, UE], and CV00 [UG, UE]). Across environments, the addition of G×S interaction in M3 decreased the amount of variability captured by the environment (−30.4%) and residual (−39.2%) terms as compared to M1. Within environments, the G×S term in M3 reduced the variability captured by the residual term by 60 and 30% when compared to M1 and M2, respectively. M3 outperformed all the other models in CV2 (0.577), CV1 (0.480), and CV0 (0.488). In addition to the Pearson correlation, other measures were considered to assess predictive ability and these showed that the addition of soil texture seems to structure/dissect the environmental term revealing its components that could enhance or hinder the predictability of a model, especially in the most complex prediction scenario (CV00). Hence, the availability of soil texture information before the growing season could be used to optimize the efficiency of a breeding program by allowing the reconsideration of field experimental design, allocation of resources, reduction of preliminary trials, and shortening of the breeding cycle.

Exploring Machine Learning Algorithms to Unveil Genomic Regions Associated With Resistance to Southern Root-Knot Nematode in Soybeans

Southern root-knot nematode [SRKN, Meloidogyne incognita (Kofold & White) Chitwood] is a plant-parasitic nematode challenging to control due to its short life cycle, a wide range of hosts, and limited management options, of which genetic resistance is the main option to efficiently control the damage caused by SRKN. To date, a major quantitative trait locus (QTL) mapped on chromosome (Chr.) 10 plays an essential role in resistance to SRKN in soybean varieties. The confidence of discovered trait-loci associations by traditional methods is often limited by the assumptions of individual single nucleotide polymorphisms (SNPs) always acting independently as well as the phenotype following a Gaussian distribution. Therefore, the objective of this study was to conduct machine learning (ML)-based genome-wide association studies (GWAS) utilizing Random Forest (RF) and Support Vector Machine (SVM) algorithms to unveil novel regions of the soybean genome associated with resistance to SRKN. A total of 717 breeding lines derived from 330 unique bi-parental populations were genotyped with the Illumina Infinium BARCSoySNP6K BeadChip and phenotyped for SRKN resistance in a greenhouse. A GWAS pipeline involving a supervised feature dimension reduction based on Variable Importance in Projection (VIP) and SNP detection based on classification accuracy was proposed. Minor effect SNPs were detected by the proposed ML-GWAS methodology but not identified using Bayesian-information and linkage-disequilibrium Iteratively Nested Keyway (BLINK), Fixed and Random Model Circulating Probability Unification (FarmCPU), and Enriched Compressed Mixed Linear Model (ECMLM) models. Besides the genomic region on Chr. 10 that can explain most of SRKN resistance variance, additional minor effects SNPs were also identified on Chrs. 10 and 11. The findings in this study demonstrated that overfitting in GWAS may lead to lower prediction accuracy, and the detection of significant SNPs based on classification accuracy limited false-positive associations. The expansion of the basis of the genetic resistance to SRKN can potentially reduce the selection pressure over the major QTL on Chr. 10 and achieve higher levels of resistance.

Classification Methods and Identification of Reniform Nematode Resistance in Known Soybean Cyst Nematode-Resistant Soybean Genotypes

Plant parasitic nematodes are a major yield-limiting factor of soybean in the United States and Canada. It has been indicated that soybean cyst nematode (SCN; Heterodera glycines Ichinohe) and reniform nematode (RN; Rotylenchulus reniformis Linford and Oliveira) resistance could be genetically related. For many years, fragmentary data have shown this relationship. This report evaluates RN reproduction on 418 plant introductions (PIs) selected from the U.S. Department of Agriculture Soybean Germplasm Collection with reported SCN resistance. The germplasm was divided into two tests of 214 PIs reported as resistant and 204 PIs reported as moderately resistant to SCN. The defining and reporting of RN resistance changed several times in the last 30 years, causing inconsistencies in RN resistance classification among multiple experiments. Comparison of four RN resistance classification methods was performed: (i) ≤10% as compared with the susceptible check, (ii) using normalized reproduction index (RI) values, and using (iii) transformed data log10(x), and (iv) transformed data log10(x + 1) in an optimal univariate k-means clustering analysis. The method of transformed data log10(x) was selected as the most accurate for classification of RN resistance. Among 418 PIs with reported SCN resistance, the log10(x) method grouped 59 PIs (15%) as resistant and 130 PIs (31%) as moderately resistant to RN. Genotyping of a subset of the most resistant PIs to both nematode species revealed their strong correlation with rhg1-a allele. This research identified genotypes with resistance to two nematode species and potential new sources of RN resistance that could be valuable to breeders in developing resistant cultivars.

Identification of genomic loci conferring broad-spectrum resistance to multiple nematode species in exotic soybean accession PI 567305

KEY MESSAGE

Genetic analysis identified a unique combination of major QTL for resistance to important soybean nematodes concurrently present in a single soybean accession, which has not been reported earlier. An exotic soybean [Glycine max (L.) Merr.] accession, PI 567305, was reported to be highly resistant to three important nematode species, soybean cyst (SCN), root-knot (RKN), and reniform (RN) nematodes. However, genetic basis controlling broad-spectrum resistance in this germplasm has not been investigated. We report results of genetic analysis to identify genomic loci conferring resistance to these nematode species. A bi-parental population consisting of 242 F8-derived recombinant inbred lines (RILs) was developed from a cross of a nematode susceptible cultivar, Magellan, and resistant accession, PI 567305. The RILs were phenotyped for nematode resistance to three SCN HG types. They were genotyped using the Infinium SoySNP6K BeadChips and genotype-by-sequencing (GBS) methods in an attempt to evaluate the cost-effectiveness and efficiency of these two genotyping platforms. Genetic analysis confirmed the major QTL on chromosomes (Chrs) 10 and 18 with broad-spectrum resistance to the three nematodes present in this germplasm. Haplotype and copy number variation analyses of SCN resistance QTL indicated that PI 567305 has a different haplotype, which is associated with likely a unique SCN resistance mechanism different from Peking- or PI 88788-type resistance. The evaluations of both Infinium Beadchip- and GBS-based genotyping technologies provided comprehensive insights for researchers to choose a cost-effective and efficient platform for QTL mapping and for other genomic studies in soybeans.

Genome-wide association study for resistance to the Meloidogyne javanica causing root-knot nematode in soybean

KEY MESSAGE

A locus on chromosome 13, containing multiple TIR-NB-LRR genes and SNPs associated with M. javanica resistance, was identified using a combination of GWAS, resequencing, genetic mapping and expression profiling. Meloidogyne javanica, a root-knot nematode, is an important problem in soybean-growing areas, leading to severe yield losses. Some accessions have been identified carrying resistance loci to this nematode. In this study, a set of 317 soybean accessions was characterized for resistance to M. javanica. A genome-wide association study was performed using SNPs from genotyping-by-sequencing, and a region of 29.2 kb on chromosome 13 was identified. An analysis of haplotypes showed that SNPs were able to discriminate between susceptible and resistant accessions, with 25 accessions sharing the haplotype associated with resistance. Furthermore, five accessions that exhibited resistance without carrying this haplotype may carry different loci conferring resistance to M. javanica. We also conducted the screening of the SNPs in the USDA soybean germplasm, revealing that several soybean accessions previously reported as resistant to other nematodes also shared the resistance haplotype on chromosome 13. Two SNP-based TaqMan® assays were developed and validated in two panels of soybean cultivars and in biparental populations. In silico analysis of the region associated with resistance identified the occurrence of genes with structural similarity with classical major resistance genes (NBS-LRR genes). Specifically, several nonsynonymous SNPs were observed in Glyma.13g194800 and Glyma.13g194900. The expression profile of these candidate genes demonstrated that the two gene models were up-regulated in the resistance source PI 505,099 after nematode infection. Overall, the SNPs associated with resistance and the genes identified constitute an important tool for introgression of resistance to the root-knot nematode by marker-assisted selection in soybean breeding programs.

Dissecting the Genetic Architecture of Aphanomyces Root Rot Resistance in Lentil by QTL Mapping and Genome-Wide Association Study

Lentil (Lens culinaris Medikus) is an important source of protein for people in developing countries. Aphanomyces root rot (ARR) has emerged as one of the most devastating diseases affecting lentil production. In this study, we applied two complementary quantitative trait loci (QTL) analysis approaches to unravel the genetic architecture underlying this complex trait. A recombinant inbred line (RIL) population and an association mapping population were genotyped using genotyping by sequencing (GBS) to discover novel single nucleotide polymorphisms (SNPs). QTL mapping identified 19 QTL associated with ARR resistance, while association mapping detected 38 QTL and highlighted accumulation of favorable haplotypes in most of the resistant accessions. Seven QTL clusters were discovered on six chromosomes, and 15 putative genes were identified within the QTL clusters. To validate QTL mapping and genome-wide association study (GWAS) results, expression analysis of five selected genes was conducted on partially resistant and susceptible accessions. Three of the genes were differentially expressed at early stages of infection, two of which may be associated with ARR resistance. Our findings provide valuable insight into the genetic control of ARR, and genetic and genomic resources developed here can be used to accelerate development of lentil cultivars with high levels of partial resistance to ARR.

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.

Candidate genes underlying the quantitative trait loci for root-knot nematode resistance in a Cucumis hystrix introgression line of cucumber based on population sequencing

The southern root-knot nematode (RKN), Meloidogyne incognita (Kofoid & White) Chitwood, is one of most destructive species of plant parasitic nematodes, causing significant economic losses to numerous crops including cucumber (Cucumis sativus L. 2n = 14). No commercial cultivar is currently available with resistance to RKN, severely hindering the genetic improvement of RKN resistance in cucumber. An introgression line, IL10-1, derived from the interspecific hybridization between the wild species Cucumis hystrix Chakr. (2n = 24, HH) and cucumber, was identified with resistance to RKN. In this study, an ultrahigh-density genetic linkage bin-map, composed of high-quality single-nucleotide polymorphisms (SNPs), was constructed based on low-coverage sequences of the F2:6 recombinant inbred lines derived from the cross between inbred line IL10-1 and cultivar 'Beijingjietou' CC3 (hereinafter referred to as CC3). Three QTLs were identified accounting for 13.36% (qRKN1-1), 9.07% and 9.58% (qRKN5-1 and qRKN5-2) of the resistance variation, respectively. Finally, four genes with nonsynonymous SNPs from chromosome 5 were speculated to be the candidate RKN-resistant related genes, with annotation involved in disease resistance. Though several gaps still exist on the bin-map, our results could potentially be used in breeding programs and establish an understanding of the associated mechanisms underlying RKN resistance in cucumber.

Effective approaches to study the plant-root knot nematode interaction

Plant-parasitic nematodes cause major agricultural losses worldwide. Examining the molecular mechanisms underlying plant-nematode interactions and how plants respond to different invading pathogens is attracting major attention to reduce the expanding gap between agricultural production and the needs of the growing world population. This review summarizes the most recent developments in plant-nematode interactions and the diverse approaches used to improve plant resistance against root knot nematode (RKN). We will emphasize the recent rapid advances in genome sequencing technologies, small interfering RNA techniques (RNAi) and targeted genome editing which are contributing to the significant progress in understanding the plant-nematode interaction mechanisms. Also, molecular approaches to improve plant resistance against nematodes are considered.

Genome-Wide Association Analysis Pinpoints Additional Major Genomic Regions Conferring Resistance to Soybean Cyst Nematode (Heterodera glycines Ichinohe)

Soybean cyst nematode (Heterodera glycines Ichinohe) (SCN) is the most destructive pest affecting soybeans [Glycine max (L.) Merr.] in the U.S. To date, only two major SCN resistance alleles, rhg1 and Rhg4, identified in PI 88788 (rhg1) and Peking (rhg1/Rhg4), residing on chromosomes (Chr) 18 and 8, respectively, have been widely used to develop SCN resistant cultivars in the U.S. Thus, some SCN populations have evolved to overcome the PI 88788 and Peking derived resistance, making it a priority for breeders to identify new alleles and sources of SCN resistance. Toward that end, 461 soybean accessions from various origins were screened using a greenhouse SCN bioassay and genotyped with Illumina SoySNP50K iSelect BeadChips and three KASP SNP markers developed at the Rhg1 and Rhg4 loci to perform a genome-wide association study (GWAS) and a haplotype analysis at the Rhg1 and Rhg4 loci. In total, 35,820 SNPs were used for GWAS, which identified 12 SNPs at four genomic regions on Chrs 7, 8, 10, and 18 that were significantly associated with SCN resistance (P < 0.001). Of those, three SNPs were located at Rhg1 and Rhg4, and 24 predicted genes were found near the significant SNPs on Chrs 7 and 10. KASP SNP genotyping results of the 462 accessions at the Rhg1 and Rhg4 loci identified 30 that carried PI 88788-type resistance, 50 that carried Peking-type resistance, and 58 that carried neither the Peking-type nor the PI 88788-type resistance alleles, indicating they may possess novel SCN resistance alleles. By using two subsets of SNPs near the Rhg1 and Rhg4 loci obtained from SoySNP iSelect BeadChips, a haplotype analysis of 461 accessions grouped those 58 accessions differently from the accessions carrying Peking or PI 88788 derived resistance, thereby validating the genotyping results at Rhg1 and Rhg4. The significant SNPs, candidate genes, and newly characterized SCN resistant accessions will be beneficial for the development of DNA markers to be used for marker-assisted breeding and developing soybean cultivars carrying novel sources of SCN resistance.

Quantitative trait loci mapping of Meloidogyne incognita and M. hapla resistance in a recombinant inbred line population of soybean

A recombinant inbred line population of soybean (Glycine max) was utilised to identify the quantitative trait loci (QTLs) determining the response to infection by two root-knot nematode species, Meloidogyne incognita and M. hapla, in glasshouse assays. QTL analysis detected seven major and four minor QTLs on seven soybean chromosomes ((Chrs) 1, 7, 8, 10, 14, 18, 20) explaining 6-41% phenotypic variance (PVE) for M. incognita root response and nematode reproduction. Three of the major QTLs, on Chrs 7, 10 and 18, were confirmed in previous reports and two major QTLs on Chrs 14 and 20 were detected for the first time. The QTL analysis with M. hapla provides the first report of a major QTL region mapped on Chr 7, explaining 70-82% PVE in M. hapla root response and nematode reproduction. These novel identified QTLs with flanking markers will be helpful in marker-assisted breeding for nematode resistance in soybean.

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.

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.

Identification of quantitative trait loci underlying resistance to southern root-knot and reniform nematodes in soybean accession PI 567516C

Soybean cyst nematode (SCN, Heterodera glycine Ichinohe), southern root-knot nematode [SRKN, Meloidogyne incognita (Kofoid and White) Chitwood] and reniform nematode (RN, Rotylenchulus reniformis Linford and Oliveira) are three important plant-parasitic pests in soybean. Previous study showed that plant introduction (PI) 567516C harbored novel quantitative trait loci (QTL) conferring SCN resistance to soybean. However, QTL underlying resistance to SRKN and RN in PI 567516C remain unknown. The objectives of this study were to identify QTL for resistance to SRKN and RN in PI 567516C. Two hundred and forty-seven F_6:9 recombinant inbred lines, derived from a cross between cultivar Magellan and PI 567516C, were evaluated for resistance to SRKN and RN. Two hundred and thirty-eight simple sequence repeats and 687 single nucleotide polymorphism markers were used to construct a genetic linkage map. Three significant QTL associated with resistance to SRKN were mapped on chromosomes (Chrs.) 10, 13 and 17. Two significant QTL associated with resistance to RN were detected on Chrs. 11 and 18. Whole-genome resequencing revealed that there might be Peking-type Rhg1 in PI 567516C. Our study provides useful information to employ PI 567516C in soybean breeding in order to develop new cultivars with resistance to multiple nematodes.

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.