Genome-wide association mapping of partial resistance to Phytophthora sojae in soybean plant introductions from the Republic of Korea

Genome-wide association study and haplotype analysis reveal novel candidate genes for resistance to powdery mildew in soybean

Powdery mildew disease (PMD) is caused by the obligate biotrophic fungus Microsphaera diffusa Cooke & Peck (M. diffusa) and results in significant yield losses in soybean (Glycine max (L.) Merr.) crops. By identifying disease-resistant genes and breeding soybean accessions with enhanced resistance, we can effectively mitigate the detrimental impact of PMD on soybeans. We analyzed PMD resistance in a diversity panel of 315 soybean accessions in two locations over 3 years, and candidate genes associated with PMD resistance were identified through genome-wide association studies (GWAS), haplotype analysis, qRT-PCR, and EMS mutant analysis. Based on the GWAS approach, we identified a region on chromosome 16 (Chr16) in which 21 genes form a gene cluster that is highly correlated with PMD resistance. In order to validate and refine these findings, we conducted haplotype analysis of 21 candidate genes and indicated there are single nucleotide polymorphisms (SNPs) and insertion-deletions (InDels) variations of Glyma.16G214000, Glyma.16G214200, Glyma.16G215100 and Glyma.16G215300 within the coding and promoter regions that exhibit a strong association with resistance against PMD. Subsequent structural analysis of candidate genes within this cluster revealed that in 315 accessions, the majority of accessions exhibited resistance to PMD when Glyma.16G214300, Glyma.16G214800 and Glyma.16G215000 were complete; however, they demonstrated susceptibility to PMD when these genes were incomplete. Quantitative real-time PCR assays (qRT-PCR) of possible candidate genes showed that 14 candidate genes (Glyma.16G213700, Glyma.16G213800, Glyma.16G213900, Glyma.16G214000, Glyma.16G214200, Glyma.16G214300, Glyma.16G214500, Glyma.16G214585, Glyma.16G214669, Glyma.16G214700, Glyma.16G214800, Glyma.16G215000, Glyma.16G215100 and Glyma.16G215300) were involved in PMD resistance. Finally, we evaluated the PMD resistance of mutant lines from the Williams 82 EMS mutations library, which revealed that mutants of Glyma.16G214000, Glyma.16G214200, Glyma.16G214300, Glyma.16G214800, Glyma.16G215000, Glyma.16G215100 and Glyma.16G215300, exhibited sensitivity to PMD. Combined with the analysis results of GWAS, haplotypes, qRT-PCR and mutants, the genes Glyma.16G214000, Glyma.16G214200, Glyma.16G214300, Glyma.16G214800, Glyma.16G215000, Glyma.16G215100 and Glyma.16G215300 were identified as highly correlated with PMD resistance. The candidate genes identified above are all NLR family genes, and these discoveries deepen our understanding of the molecular basis of PMD resistance in soybeans and will be useful for guiding breeding strategies.

Molecular mechanisms underpinning quantitative resistance to Phytophthora sojae in Glycine max using a systems genomics approach

Expression of quantitative disease resistance in many host-pathogen systems is controlled by genes at multiple loci, each contributing a small effect to the overall response. We used a systems genomics approach to study the molecular underpinnings of quantitative disease resistance in the soybean-Phytophthora sojae pathosystem, incorporating expression quantitative trait loci (eQTL) mapping and gene co-expression network analysis to identify the genes putatively regulating transcriptional changes in response to inoculation. These findings were compared to previously mapped phenotypic (phQTL) to identify the molecular mechanisms contributing to the expression of this resistance. A subset of 93 recombinant inbred lines (RILs) from a Conrad × Sloan population were inoculated with P. sojae isolate 1.S.1.1 using the tray-test method; RNA was extracted, sequenced, and the normalized read counts were genetically mapped from tissue collected at the inoculation site 24 h after inoculation from both mock and inoculated samples. In total, more than 100,000 eQTLs were mapped. There was a switch from predominantly cis-eQTLs in the mock treatment to an almost entirely nonoverlapping set of predominantly trans-eQTLs in the inoculated treatment, where greater than 100-fold more eQTLs were mapped relative to mock, indicating vast transcriptional reprogramming due to P. sojae infection occurred. The eQTLs were organized into 36 hotspots, with the four largest hotspots from the inoculated treatment corresponding to more than 70% of the eQTLs, each enriched for genes within plant-pathogen interaction pathways. Genetic regulation of trans-eQTLs in response to the pathogen was predicted to occur through transcription factors and signaling molecules involved in plant-pathogen interactions, plant hormone signal transduction, and MAPK pathways. Network analysis identified three co-expression modules that were correlated with susceptibility to P. sojae and associated with three eQTL hotspots. Among the eQTLs co-localized with phQTLs, two cis-eQTLs with putative functions in the regulation of root architecture or jasmonic acid, as well as the putative master regulators of an eQTL hotspot nearby a phQTL, represent candidates potentially underpinning the molecular control of these phQTLs for resistance.

Multi-omics assisted breeding for biotic stress resistance in soybean

Biotic stress is a critical factor limiting soybean growth and development. Soybean responses to biotic stresses such as insects, nematodes, fungal, bacterial, and viral pathogens are governed by complex regulatory and defense mechanisms. Next-generation sequencing has availed research techniques and strategies in genomics and post-genomics. This review summarizes the available information on marker resources, quantitative trait loci, and marker-trait associations involved in regulating biotic stress responses in soybean. We discuss the differential expression of related genes and proteins reported in different transcriptomics and proteomics studies and the role of signaling pathways and metabolites reported in metabolomic studies. Recent advances in omics technologies offer opportunities to reshape and improve biotic stress resistance in soybean by altering gene regulation and/or other regulatory networks. We suggest using 'integrated omics' to precisely understand how soybean responds to different biotic stresses. We also discuss the potential challenges of integrating multi-omics for the functional analysis of genes and their regulatory networks and the development of biotic stress-resistant cultivars. This review will help direct soybean breeding programs to develop resistance against different biotic stresses.

Evaluation of Short-Season Soybean Genotypes for Resistance and Partial Resistance to Phytophthora sojae

Phytophthora root and stem rot caused by Phytophthora sojae Kaufmann and Gerdemann is a soil-borne disease severely affecting soybean production worldwide. Losses caused by P. sojae can be controlled by both major genes and quantitative trait locus. Here, we tested 112 short-season soybean cultivars from Northeast China for resistance to P. sojae. A total of 58 germplasms were resistant to 7-11 P. sojae strains. Among these, Mengdou 28 and Kejiao 10-262 may harbor either Rps3a or multiple Rps genes conferring resistance to P. sojae. The remaining 110 germplasms produced 91 reaction types and may contain new resistance genes or gene combinations. Partial resistance evaluation using the inoculum layer method revealed that 34 soybean germplasms had high partial resistance, with a mean disease index lower than 30. Combining the results of resistance and partial resistance analyses, we identified 35 excellent germplasm resources as potential elite materials for resistance and tolerance in future breeding programs. In addition, we compared the radicle inoculation method with the inoculum layer method to screen for partial resistance to P. sojae. Our results demonstrate that the radicle inoculation method could potentially replace the inoculum layer method to identify partial resistance against P. sojae, and further verification with larger samples is required in the future.

Progress and prospectus in genetics and genomics of Phytophthora root and stem rot resistance in soybean (Glycine max L.)

Soybean is one of the largest sources of protein and oil in the world and is also considered a "super crop" due to several industrial advantages. However, enhanced acreage and adoption of monoculture practices rendered the crop vulnerable to several diseases. Phytophthora root and stem rot (PRSR) caused by Phytophthora sojae is one of the most prevalent diseases adversely affecting soybean production globally. Deployment of genetic resistance is the most sustainable approach for avoiding yield losses due to this disease. PRSR resistance is complex in nature and difficult to address by conventional breeding alone. Genetic mapping through a cost-effective sequencing platform facilitates identification of candidate genes and associated molecular markers for genetic improvement against PRSR. Furthermore, with the help of novel genomic approaches, identification and functional characterization of Rps (resistance to Phytophthora sojae) have also progressed in the recent past, and more than 30 Rps genes imparting complete resistance to different PRSR pathotypes have been reported. In addition, many genomic regions imparting partial resistance have also been identified. Furthermore, the adoption of emerging approaches like genome editing, genomic-assisted breeding, and genomic selection can assist in the functional characterization of novel genes and their rapid introgression for PRSR resistance. Hence, in the near future, soybean growers will likely witness an increase in production by adopting PRSR-resistant cultivars. This review highlights the progress made in deciphering the genetic architecture of PRSR resistance, genomic advances, and future perspectives for the deployment of PRSR resistance in soybean for the sustainable management of PRSR disease.

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.

Genome-Wide Association Study of Partial Resistance to P. sojae in Wild Soybeans from Heilongjiang Province, China

Phytophthora root rot (PRR) is a destructive disease of soybeans (Glycine max (L.) Merr) caused by Phytophthora sojae (P. sojae). The most effective way to prevent the disease is growing resistant or tolerant varieties. Partial resistance provides a more durable resistance against the pathogen compared to complete resistance. Wild soybean (Glycine soja Sieb. & Zucc.) seems to be an extraordinarily important gene pool for soybean improvement due to its high level of genetic variation. In this study, 242 wild soybean germplasms originating from different regions of Heilongjiang province were used to identify resistance genes to P. sojae race 1 using a genome-wide association study (GWAS). A total of nine significant SNPs were detected, repeatedly associated with P. sojae resistance and located on chromosomes 1, 10, 12, 15, 17, 19 and 20. Among them, seven favorable allelic variations associated with P. sojae resistance were evaluated by a t-test. Eight candidate genes were predicted to explore the mechanistic hypotheses of partial resistance, including Glysoja.19G051583, which encodes an LRR receptor-like serine/threonine protein kinase protein, Glysoja.19G051581, which encodes a receptor-like cytosolic serine/threonine protein kinase protein. These findings will provide additional insights into the genetic architecture of P. sojae resistance in a large sample of wild soybeans and P. sojae-resistant breeding through marker-assisted selection.

Genome-Wide Association Analysis and Gene Mining of Resistance to China Race 1 of Frogeye Leaf Spot in Soybean

Soybean frogeye leaf spot (FLS) is a worldwide fungal disease. Its higher occurrence frequency and wider distribution range always led to severe yield losses of soybean, therefore, breeding new cultivars with FLS resistance has been an important breeding goal for soybean breeders. In this study, an association panel of 183 representative soybean accessions was used to evaluate their resistance to FLS race 1, and to identify quantitative trait nucleotides (QTNs) and candidate genes based on genome-wide association study (GWAS) and high-throughput single-nucleotide polymorphisms (SNPs). A total of 23,156 high-quality SNPs were developed using the specific locus-amplified fragment sequencing (SLAF-seq) approach. Finally, 13 novel association signals associated with FLS race 1 resistance were identified by the compressed mixed linear model (CMLM). In addition, 119 candidate genes were found within the 200-kb flanking genomic region of these 13 peak SNPs. Based on the gene-based association analysis, haplotype analysis, expression pattern analysis, and virus-induced gene silencing (VIGS) systems, four genes (Glyma.05G121100, Glyma.17G228300, Glyma.19G006900, and Glyma.19G008700) were preliminarily proved to play an important role in the soybean resistance to FLS race 1.

Identification of Candidate Genes for a Major Quantitative Disease Resistance Locus From Soybean PI 427105B for Resistance to Phytophthora sojae

Phytophthora root and stem rot is a yield-limiting soybean disease caused by the soil-borne oomycete Phytophthora sojae. Although multiple quantitative disease resistance loci (QDRL) have been identified, most explain <10% of the phenotypic variation (PV). The major QDRL explaining up to 45% of the PV were previously identified on chromosome 18 and represent a valuable source of resistance for soybean breeding programs. Resistance alleles from plant introductions 427105B and 427106 significantly increase yield in disease-prone fields and result in no significant yield difference in fields with less to no disease pressure. In this study, high-resolution mapping reduced the QDRL interval to 3.1 cm, and RNA-seq analysis of near-isogenic lines (NILs) varying at QDRL-18 pinpointed a single gene of interest which was downregulated in inoculated NILs carrying the resistant allele compared to inoculated NILs with the susceptible allele. This gene of interest putatively encodes a serine-threonine kinase (STK) related to the AtCR4 family and may be acting as a susceptibility factor, based on the specific increase of jasmonic acid concentration in inoculated NILs. This work facilitates further functional analyses and marker-assisted breeding efforts by prioritizing candidate genes and narrowing the targeted region for introgression.

Mapping of partial resistance to Phytophthora sojae in soybean PIs using whole-genome sequencing reveals a major QTL

In the last decade, more than 70 quantitative trait loci (QTL) related to soybean [Glycine max (L.) Merr.] partial resistance (PR) against Phytophthora sojae have been identified by genome-wide association studies (GWAS). However, most of them have either a minor effect on the resistance level or are specific to a single phenotypic variable or one isolate, thereby limiting their use in breeding programs. In this study, we have used an analytical approach combining (a) the phenotypic characterization of a diverse panel of 357 soybean accessions for resistance to P. sojae captured through a single variable, corrected dry weight; (b) a new hydroponic assay allowing the inoculation of a combination of P. sojae isolates covering the spectrum of commercially relevant Rps genes; and (c) exhaustive genotyping through whole-genome resequencing (WGS). This led to the identification of a novel P. sojae resistance QTL with a relatively major effect compared with the previously reported QTL. The QTL interval, spanning ∼500 kb on chromosome (Chr) 15, does not colocalize with previously reported QTL for P. sojae resistance. Plants carrying the favorable allele at this QTL were 60% more resistant. Eight genes were found to reside in the linkage disequilibrium (LD) block containing the peak single-nucleotide polymorphism (SNP) including Glyma.15G217100, which encodes a major latex protein (MLP)-like protein, with a functional annotation related to pathogen resistance. Expression analysis of Glyma.15G217100 indicated that it was nearly eight times more highly expressed in a group of plant introductions (PIs) carrying the resistant (R) allele compared with those carrying the susceptible (S) allele within a short period after inoculation. These results offer new and valuable options to develop improved soybean cultivars with broad resistance to P. sojae through marker-assisted selection.

Mapping Major Disease Resistance Genes in Soybean by Genome-Wide Association Studies

Soybean is one of the most valuable agricultural crops in the world. Besides, this legume is constantly attacked by a wide range of pathogens (fungi, bacteria, viruses, and nematodes) compromising yield and increasing production costs. One of the major disease management strategies is the genetic resistance provided by single genes and quantitative trait loci (QTL). Identifying the genomic regions underlying the resistance against these pathogens on soybean is one of the first steps performed by molecular breeders. In the past, genetic mapping studies have been widely used to discover these genomic regions. However, over the last decade, advances in next-generation sequencing technologies and their subsequent cost decreasing led to the development of cost-effective approaches to high-throughput genotyping. Thus, genome-wide association studies applying thousands of SNPs in large sets composed of diverse soybean accessions have been successfully done. In this chapter, a comprehensive review of the majority of GWAS for soybean diseases published since this approach was developed is provided. Important diseases caused by Heterodera glycines, Phytophthora sojae, and Sclerotinia sclerotiorum have been the focus of the several GWAS. However, other bacterial and fungi diseases also have been targets of GWAS. As such, this GWAS summary can serve as a guide for future studies of these diseases. The protocol begins by describing several considerations about the pathogens and bringing different procedures of molecular characterization of them. Advice to choose the best isolate/race to maximize the discovery of multiple R genes or to directly map an effective R gene is provided. A summary of protocols, methods, and tools to phenotyping the soybean panel is given to several diseases. We also give details of options of DNA extraction protocols and genotyping methods, and we describe parameters of SNP quality to soybean data. Websites and their online tools to obtain genotypic and phenotypic data for thousands of soybean accessions are highlighted. Finally, we report several tricks and tips in Subheading 4, especially related to composing the soybean panel as well as generating and analyzing the phenotype data. We hope this protocol will be helpful to achieve GWAS success in identifying resistance genes on soybean.

Tissue-specific expression of GhnsLTPs identified via GWAS sophisticatedly coordinates disease and insect resistance by regulating metabolic flux redirection in cotton

Cotton (Gossypium hirsutum) is constantly attacked by pathogens and insects. The most efficient control strategy is to develop resistant varieties using broad-spectrum gene resources. Several resistance loci harboured by superior varieties have been identified through genome-wide association studies. However, the key genes and/or loci have not been functionally identified. In this study, we identified a locus significantly associated with Verticillium wilt (VW) resistance, and within a 145.5-kb linkage disequilibrium, two non-specific lipid transfer protein genes (named GhnsLTPsA10) were highly expressed under Verticillium pathogen stress. The expression of GhnsLTPsA10 significantly increased in roots upon Verticillium dahliae stress but significantly decreased in leaves under insect attack. Furthermore, GhnsLTPsA10 played antagonistic roles in positively regulating VW and Fusarium wilt resistance and negatively mediating aphid and bollworm resistance in transgenic Arabidopsis and silenced cotton. By combining transcriptomic, histological and physiological analyses, we determined that GhnsLTPsA10-mediated phenylpropanoid metabolism further affected the balance of the downstream metabolic flux of flavonoid and lignin biosynthesis. The divergent expression of GhnsLTPsA10 in roots and leaves coordinated resistance of cotton against fungal pathogens and insects via the redirection of metabolic flux. In addition, GhnsLTPsA10 contributed to reactive oxygen species accumulation. Therefore, in this study, we elucidated the novel function of GhnsLTP and the molecular association between disease resistance and insect resistance, balanced by GhnsLTPsA10. This broadens our knowledge of the biological function of GhnsLTPsA10 in crops and provides a useful locus for genetic improvement of cotton.

Molecular mapping of quantitative disease resistance loci for soybean partial resistance to Phytophthora sansomeana

KEY MESSAGE

Two soybean QDRL were identified with additive interaction to P. sansomeana isolate MPS17-22. Further analyses uncovered four interaction patterns between the two QDRL and seven additional P. sansomeana isolates. Phytophthora sansomeana is a recently recognized species that contributes to root rot in soybean. Previous studies indicated that P. sansomeana is widely distributed among soybean growing regions and has a much wider host range than P. sojae, a well-known pathogen of soybean. Unlike P. sojae, no known disease resistance genes have been documented that can effectively control P. sansomeana. Therefore, it is important to identify resistance that can be quickly integrated into future soybean varieties. E13901 is an improved soybean line that confers partial resistance to P. sansomeana. A mapping population of 228 F4:5 families was developed from a cross between E13901 and a susceptible improved soybean variety E13390. Using a composite interval mapping method, two quantitative disease resistance loci (QDRL) were identified on Chromosomes 5 (designated qPsan5.1) and 16 (designated qPsan16.1), respectively. qPsan5.1 was mapped at 54.71 cM between Gm05_32565157_T_C and Gm05_32327497_T_C. qPsan5.1 was contributed by E13390 and explained about 6% of the disease resistance variation. qPsan16.1 was located at 39.01 cM between Gm16_35700223_G_T and Gm16_35933600/ Gm16_35816475. qPsan16.1 was from E13901 and could explain 5.5% of partial disease resistance. Further analysis indicated an additive interaction of qPsan5.1 and qPsan16.1 against P. sansomeana isolate MPS17-22. Marker assisted resistance spectrum analysis and progeny tests verified the two QDRL and their interaction patterns with other P. sansomeana isolates. Both QDRL can be quickly integrated into soybean varieties using marker assisted selection.

Identification of SNP markers associated with soybean fatty acids contents by genome-wide association analyses

Composition of fatty acids (FAs) in soybean seed is important for the quality and uses of soybean oil. Using gas chromatography, we have measured soybean FAs profiles of 621 soybean accessions (maturity groups I through IV) grown in five different environments; Columbus, OH (2015), Wooster, OH (2014 and 2015), Plymouth, NC (2015), and Urbana, IL (2015). Using publicly available SoySNP50K genotypic data and the FA profiles from this study, a genome-wide association analysis was completed with a compressed mixed linear model to identify 43 genomic regions significantly associated with a fatty acid at a genome wide significance threshold of 5%. Among these regions, one and three novel genomic regions associated with palmitic acid and stearic acid, respectively, were identified across all five environments. Additionally, nine novel environment-specific FA-related genomic regions were discovered providing new insights into the genetics of soybean FAs. Previously reported FA-related loci, such as FATB1a, SACPD-C, and KASIII, were also confirmed in this study. Our results will be useful for future functional studies and marker-assisted breeding for soybean FAs.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01216-1.

Mining germplasm panels and phenotypic datasets to identify loci for resistance to Phytophthora sojae in soybean

Phytophthora sojae causes Phytophthora root and stem rot of soybean and has been primarily managed through deployment of qualitative Resistance to P. sojae genes (Rps genes). The effectiveness of each individual or combination of Rps gene(s) depends on the diversity and pathotypes of the P. sojae populations present. Due to the complex nature of P. sojae populations, identification of more novel Rps genes is needed. In this study, phenotypic data from previous studies of 16 panels of plant introductions (PIs) were analyzed. Panels 1 and 2 consisted of 448 Glycine max and 520 G. soja, which had been evaluated for Rps gene response with a combination of P. sojae isolates. Panels 3 and 4 consisted of 429 and 460 G. max PIs, respectively, which had been evaluated using individual P. sojae isolates with complex virulence pathotypes. Finally, Panels 5-16 (376 G. max PIs) consisted of data deposited in the USDA Soybean Germplasm Collection from evaluations with 12 races of P. sojae. Using these panels, genome-wide association (GWA) analyses were carried out by combining phenotypic and SoySNP50K genotypic data. GWA models identified two, two, six, and seven novel Rps loci with Panels 1, 2, 3, and 4, respectively. A total of 58 novel Rps loci were identified using Panels 5-16. Genetic and phenotypic dissection of these loci may lead to the characterization of novel Rps genes that can be effectively deployed in new soybean cultivars against diverse P. sojae populations.

Testing methods and statistical models of genomic prediction for quantitative disease resistance to Phytophthora sojae in soybean [Glycine max (L.) Merr] germplasm collections

KEY MESSAGE

Genomic prediction of quantitative resistance toward Phytophthora sojae indicated that genomic selection may increase breeding efficiency. Statistical model and marker set had minimal effect on genomic prediction with > 1000 markers. Quantitative disease resistance (QDR) toward Phytophthora sojae in soybean is a complex trait controlled by many small-effect loci throughout the genome. Along with the technical and rate-limiting challenges of phenotyping resistance to a root pathogen, the trait complexity can limit breeding efficiency. However, the application of genomic prediction to traits with complex genetic architecture, such as QDR toward P. sojae, is likely to improve breeding efficiency. We provide a novel example of genomic prediction by measuring QDR to P. sojae in two diverse panels of more than 450 plant introductions (PIs) that had previously been genotyped with the SoySNP50K chip. This research was completed in a collection of diverse germplasm and contributes to both an initial assessment of genomic prediction performance and characterization of the soybean germplasm collection. We tested six statistical models used for genomic prediction including Bayesian Ridge Regression; Bayesian LASSO; Bayes A, B, C; and reproducing kernel Hilbert spaces. We also tested how the number and distribution of SNPs included in genomic prediction altered predictive ability by varying the number of markers from less than 50 to more than 34,000 SNPs, including SNPs based on sequential sampling, random sampling, or selections from association analyses. Predictive ability was relatively independent of statistical model and marker distribution, with a diminishing return when more than 1000 SNPs were included in genomic prediction. This work estimated relative efficiency per breeding cycle between 0.57 and 0.83, which may improve the genetic gain for P. sojae QDR in soybean breeding programs.

Genome-wide association analyses of quantitative disease resistance in diverse sets of soybean [Glycine max (L.) Merr.] plant introductions

Phytophthora sojae is one of the costliest soybean pathogens in the US. Quantitative disease resistance (QDR) is a vital part of Phytophthora disease management. In this study, QDR was measured in 478 and 495 plant introductions (PIs) towards P. sojae isolates OH.121 and C2.S1, respectively, in genome-wide association (GWA) analyses to identify genetic markers linked to QDR loci (QDRL). Populations were generated by sampling PIs from the US, the Republic of Korea, and the full collection of PIs maintained by the USDA. Additionally, a meta-analysis of QDRL reported from bi-parental studies was done to compare past and present findings. Twenty-four significant marker-trait associations were identified from the 478 PIs phenotyped with OH.121, and an additional 24 marker-trait associations were identified from the 495 PIs phenotyped with C2.S1. In total, 48 significant markers were distributed across 16 chromosomes and based on linkage analysis, represent a total of 44 QDRL. The majority of QDRL were identified with only one of the two isolates, and only a region on chromosome 13 was consistently identified. Regions on chromosomes 3, 13, and 17 were identified in previous GWA-analyses and were re-identified in this study. Five QDRL co-localized with P. sojae meta-QDRL identified from QDRL reported in previous biparental mapping studies. The remaining regions represent novel QDRL, in the soybean-P. sojae pathosystem and were primarily identified in germplasm from the Republic of Korea. Overall, the number of loci identified in this study highlights the complexity of QDR to P. sojae.

An Improved Method for the Identification of Soybean Resistance to Phytophthora sojae Applied to Germplasm Resources from the Huanghuaihai and Dongbei Regions of China

Phytophthora root and stem rot (PRR) caused by Phytophthora sojae is a destructive disease afflicting soybean. The use of resistant cultivars is the most effective method to combat PRR. PRR resistance was assessed in 223 soybean cultivars from Huanghuaihai and Dongbei, major soybean-producing regions in east central and northeastern China. To evaluate levels of soybean resistance to P. sojae, we used eight representative P. sojae isolates and a modified etiolated hypocotyl-slit inoculation method. The cultivars Wandou21020, Xu9302-A, Kedou10, and Lidi055 showed resistance to all eight isolates; 14 cultivars showed intermediate resistance to all eight P. sojae isolates, and 53 cultivars were resistant to seven isolates. Thirty-three cultivars (15%) were susceptible only to the highly virulent PsJS2 isolate, which is consistent with the reactions of the Chapman differential line that carries Rps3a. The diverse reaction patterns seen in germplasm from different regions (provinces/cities) in this study reflect the variety of PRR-resistant soybean sources in China. Our research indicates that sources of P. sojae resistance are present in the major soybean production areas of China. This study provides useful information for soybean breeding programs.

Genome-Wide Associations and Transcriptional Profiling Reveal ROS Regulation as One Underlying Mechanism of Sheath Blight Resistance in Rice

Rice sheath blight, caused by the necrotrophic fungus Rhizoctonia solani Kühn, continues to be an important and challenging rice disease worldwide. Here, we used genome-wide association studies over a high-density rice array to facilitate the identification of potential novel genes and quantitative trait loci related to sheath blight resistance. We identified multiple regions that significantly associated with independent disease components in chromosomes 1, 4, and 11 under controlled condition. In particular, we investigated qLN11²⁸, a quantitative trait locus enriched with defense-related genes that reduce disease lesions in a near-isogenic line. RNA profiling of the line carrying qLN11²⁸ showed a number of differentially expressed genes related to the reactive oxygen species (ROS)-redox pathway. Histochemical staining revealed less ROS accumulation on the resistant line, suggesting efficient ROS deregulation that delays pathogen colonization. The detection of genomic regions controlling multiple mechanisms of resistance to sheath blight will provide tools to design effective breeding interventions in rice.

GmWRKY40, a member of the WRKY transcription factor genes identified from Glycine max L., enhanced the resistance to Phytophthora sojae

BACKGROUND

The WRKY proteins are a superfamily of transcription factors and members play essential roles in the modulation of diverse physiological processes, such as growth, development, senescence and response to biotic and abiotic stresses. However, the biological roles of the majority of the WRKY family members remains poorly understood in soybean relative to the research progress in model plants.

RESULTS

In this study, we identified and characterized GmWRKY40, which is a group IIc WRKY gene. Transient expression analysis revealed that the GmWRKY40 protein is located in the nucleus of plant cells. Expression of GmWRKY40 was strongly induced in soybean following infection with Phytophthora sojae, or treatment with methyl jasmonate, ethylene, salicylic acid, and abscisic acid. Furthermore, soybean hairy roots silencing GmWRKY40 enhanced susceptibility to P. sojae infection compared with empty vector transgenic roots. Moreover, suppression of GmWRKY40 decreased the accumulation of reactive oxygen species (ROS) and modified the expression of several oxidation-related genes. Yeast two-hybrid experiment combined with RNA-seq analysis showed that GmWRKY40 interacted with 8 JAZ proteins with or without the WRKY domain or zinc-finger domain of GmWRKY40, suggesting there were different interaction patterns among these interacted proteins.

CONCLUSIONS

Collectively, these results suggests that GmWRKY40 functions as a positive regulator in soybean plants response to P. sojae through modulating hydrogen peroxide accumulation and JA signaling pathway.

Genome-wide association study of seed protein, oil and amino acid contents in soybean from maturity groups I to IV

KEY MESSAGE

Genomic regions associated with seed protein, oil and amino acid contents were identified by genome-wide association analyses. Geographic distributions of haplotypes indicate scope of improvement of these traits. Soybean [Glycine max (L.) Merr.] protein and oil are used worldwide in feed, food and industrial materials. Increasing seed protein and oil contents is important; however, protein content is generally negatively correlated with oil content. We conducted a genome-wide association study using phenotypic data collected from five environments for 621 accessions in maturity groups I-IV and 34,014 markers to identify quantitative trait loci (QTL) for seed content of protein, oil and several essential amino acids. Three and five genomic regions were associated with seed protein and oil contents, respectively. One, three, one and four genomic regions were associated with cysteine, methionine, lysine and threonine content (g kg-1 crude protein), respectively. As previously shown, QTL on chromosomes 15 and 20 were associated with seed protein and oil contents, with both exhibiting opposite effects on the two traits, and the chromosome 20 QTL having the most significant effect. A multi-trait mixed model identified trait-specific QTL. A QTL on chromosome 5 increased oil with no effect on protein content, and a QTL on chromosome 10 increased protein content with little effect on oil content. The chromosome 10 QTL co-localized with maturity gene E2/GmGIa. Identification of trait-specific QTL indicates feasibility to reduce the negative correlation between protein and oil contents. Haplotype blocks were defined at the QTL identified on chromosomes 5, 10, 15 and 20. Frequencies of positive effect haplotypes varied across maturity groups and geographic regions, providing guidance on which alleles have potential to contribute to soybean improvement for specific regions.

Variation in the Resistance of Japanese Soybean Cultivars to Phytophthora Root and Stem Rot during the Early Plant Growth Stages and the Effects of a Fungicide Seed Treatment

Soybean cultivars susceptible to Phytophthora root and stem rot are vulnerable to seed rot and damping-off of seedlings and young plants following an infection by Phytophthora sojae. In this study, the disease responses of Japanese soybean cultivars including currently grown main cultivars during the early growth stages were investigated following infections by multiple P. sojae isolates from Japanese fields. The extent of the resistance to 17 P. sojae isolates after inoculations at 14, 21, and 28 days after seeding varied significantly among 18 Japanese and two US soybean cultivars. Moreover, the disease responses of each cultivar differed significantly depending on the P. sojae isolate and the plant age at inoculation. Additionally, the treatment of 'Nattosyo-ryu' seeds with three fungicidal agrochemicals provided significant protection from P. sojae when plants were inoculated at 14-28 days after seeding. These results indicate that none of the Japanese soybean cultivars are completely resistant to all tested P. sojae isolates during the first month after sowing. However, the severity of the disease was limited when plants were inoculated during the later growth stages. Furthermore, the protective effects of the tested agrochemicals were maintained for at least 28 days after the seed treatment. Japanese soybean cultivars susceptible to Phytophthora root and stem rot that are grown under environmental conditions favorable for P. sojae infections require the implementation of certain practices, such as seed treatments with appropriate agrochemicals, to ensure they are protected from P. sojae during the early part of the soybean growing season.

Identification of new loci for salt tolerance in soybean by high-resolution genome-wide association mapping

BACKGROUND

Salinity is an abiotic stress that negatively affects soybean [Glycine max (L.) Merr.] seed yield. Although a major gene for salt tolerance was identified and consistently mapped to chromosome (Chr.) 3 by linkage mapping studies, it does not fully explain genetic variability for tolerance in soybean germplasm. In this study, a genome-wide association study (GWAS) was performed to map genomic regions for salt tolerance in a diverse panel of 305 soybean accessions using a single nucleotide polymorphism (SNP) dataset derived from the SoySNP50K iSelect BeadChip. A second GWAS was also conducted in a subset of 234 accessions using another 3.7 M SNP dataset derived from a whole-genome resequencing (WGRS) study. In addition, three gene-based markers (GBM) of the known gene, Glyma03g32900, on Chr. 3 were also integrated into the two datasets. Salt tolerance among soybean lines was evaluated by leaf scorch score (LSS), chlorophyll content ratio (CCR), leaf sodium content (LSC), and leaf chloride content (LCC).

RESULTS

For both association studies, a major locus for salt tolerance on Chr. 3 was confirmed by a number of significant SNPs, of which three gene-based SNP markers, Salt-20, Salt14056 and Salt11655, had the highest association with all four traits studied. Also, additional genomic regions on Chrs. 1, 8, and 18 were found to be associated with various traits measured in the second GWAS using the WGRS-derived SNP dataset.

CONCLUSIONS

A region identified on Chr. 8 was identified to be associated with all four traits and predicted as a new minor locus for salt tolerance in soybean. The candidate genes harbored in this minor locus may help reveal the molecular mechanism involved in salt tolerance and to improve tolerance in soybean cultivars. The significant SNPs will be useful for marker-assisted selection for salt tolerance in soybean breeding programs.

Genome-Wide Association Studies for Dynamic Plant Height and Number of Nodes on the Main Stem in Summer Sowing Soybeans

Plant height (PH) and the number of nodes on the main stem (NN) serve as major plant architecture traits affecting soybean seed yield. Although many quantitative trait loci for the two traits have been reported, their genetic controls at different developmental stages in soybeans remain unclear. Here, 368 soybean breeding lines were genotyped using 62,423 single nucleotide polymorphism (SNP) markers and phenotyped for the two traits at three different developmental stages over two locations in order to identify their quantitative trait nucleotides (QTNs) using compressed mixed linear model (CMLM) and multi-locus random-SNP-effect mixed linear model (mrMLM) approaches. As a result, 11 and 13 QTNs were found by CMLM to be associated with PH and NN, respectively. Among these QTNs, 8, 3, and 4 for PH and 6, 6, and 8 for NN were found at the three stages, and 3 and 6 were repeatedly detected for PH and NN. In addition, 34 and 30 QTNs were found by mrMLM to be associated with PH and NN, respectively. Among these QTNs, 11, 13, and 16 for PH and 11, 15, and 8 for NN were found at the three stages. A majority of these QTNs overlapped with the previously reported loci. Moreover, one QTN within the known E2 locus for flowering time was detected for the two traits at all three stages, and another that overlapped with the Dt1 locus for stem growth habit was also identified for the two traits at the mature stage. This may explain the highly significant correlation between the two traits. Our findings provide evidence for mixed major plus polygenes inheritance for dynamic traits and an extended understanding of their genetic architecture for molecular dissection and breeding utilization in soybeans.

GWAS of a soybean breeding collection from South East and South Kazakhstan for resistance to fungal diseases

Soybean (Glycine max(L.) Merr) is an essential food, feed, and technical culture. In Kazakhstan the area under soybean is increasing every year, helping to solve the problem of protein deficiency in human nutrition and animal feeding. One of the main problems of soybean production is fungal diseases causing yields losses of up to 30 %. Modern genomic studies can be applied to facilitate efficient breeding research for improvement of soybean fungal disease tolerance. Therefore, the objective of this genome-wide association study (GWAS) was analysis of a soybean collection consisting of 182 accessions in relation to fungal diseases in the conditions of South East and South Kazakh­stan. Field evaluation of the soybean collection suggested thatFusariumspp. andCercospora sojinaaffected plants in the South region (RIBSP), andSeptoria glycines– in the South East region (KRIAPP). The major objective of the study was identification of QTL associated with resistance to fusarium root rot (FUS), frogeye leaf spot (FLS), and brown spot (BS). GWAS using 4 442 SNP (single nucleotide polymorphism) markers of Illumina iSelect array allowed for identification of fifteen marker trait associations (MTA) resistant to the three diseases at two different stages of growth. Two QTL both for FUS (chromosomes 13 and 17) and BS (chromosomes 14 and 17) were genetically mapped, including one presumably novel QTL for BS (chromo­some 17). Also, five presumably novel QTL for FLS were genetically mapped on chromosomes 2, 7, and 15. The results can be used for improvement of the local breeding projects based on marker-assisted selection approach.          

Development of a Simple Hydroponic Assay to Study Vertical and Horizontal Resistance of Soybean and Pathotypes of Phytophthora sojae

Phytophthora root rot, caused by Phytophthora sojae, is one of the most damaging diseases of soybean and the introgression of Rps (Resistance to P. sojae) genes into elite soybean lines is arguably the best way to manage this disease. Current bioassays to phenotype the gene-for-gene relationship are hampered with respect to reproducibility and long-term stability of isolates, and do not accurately predict horizontal resistance individually. The aim of our study was to investigate a new way of phenotyping P. sojae isolates and vertical and horizontal resistance in soybean that relies on zoospores inoculated directly into a hydroponic system. Inoculation of P. sojae isolates against a set of eight differentials accurately and reproducibly identified pathotypes over a period of two years. When applied to test vertical resistance of soybean lines with known and unknown Rps genes, the bioassay relied on plant dry weight to correctly identify all genes. In addition, simultaneous inoculations of three P. sojae isolates, collectively carrying eight major virulence factors against 64 soybean lines with known and unknown levels of horizontal resistance, separated the plants into five distinct groups of root rot, allowing the discrimination of lines with various degrees of partial resistance. Based on those results, this bioassay offers several advantages in facilitating efforts in breeding soybean for P. sojae resistance and in identifying virulence factors in P. sojae.

Genome-wide association mapping of resistance to Phytophthora sojae in a soybean [Glycine max (L.) Merr.] germplasm panel from maturity groups IV and V

Phytophthora sojae, an oomycete pathogen of soybean, causes stem and root rot, resulting in annual economic loss up to $2 billion worldwide. Varieties with P. sojae resistance are environmental friendly to effectively reduce disease damages. In order to improve the resistance of P. sojae and broaden the genetic diversity in Southern soybean cultivars and germplasm in the U.S., we established a P. sojae resistance gene pool that has high genetic diversity, and explored genomic regions underlying the host resistance to P. sojae races 1, 3, 7, 17 and 25. A soybean germplasm panel from maturity groups (MGs) IV and V including 189 accessions originated from 10 countries were used in this study. The panel had a high genetic diversity compared to the 6,749 accessions from MGs IV and V in USDA Soybean Germplasm Collection. Based on disease evaluation dataset of these accessions inoculated with P. sojae races 1, 3, 7, 17 and 25, which are publically available, five accessions in this panel were resistant to all races. Genome-wide association analysis identified a total of 32 significant SNPs, which were clustered in resistance-associated genomic regions, among those, ss715619920 was only 3kb away from the gene Glyma.14g087500, a subtilisin protease. Gene expression analysis showed that the gene was down-regulated more than 4 fold (log2 fold > 2.2) in response to P. sojae infection. The identified molecular markers and genomic regions that are associated with the disease resistance in this gene pool will greatly assist the U.S. Southern soybean breeders in developing elite varieties with broad genetic background and P. sojae resistance.

Fine mapping of a Phytophthora-resistance gene RpsWY in soybean (Glycine max L.) by high-throughput genome-wide sequencing

KEY MESSAGE

Using a combination of phenotypic screening, genetic and statistical analyses, and high-throughput genome-wide sequencing, we have finely mapped a dominant Phytophthora resistance gene in soybean cultivar Wayao. Phytophthora root rot (PRR) caused by Phytophthora sojae is one of the most important soil-borne diseases in many soybean-production regions in the world. Identification of resistant gene(s) and incorporating them into elite varieties are an effective way for breeding to prevent soybean from being harmed by this disease. Two soybean populations of 191 F2 individuals and 196 F7:8 recombinant inbred lines (RILs) were developed to map Rps gene by crossing a susceptible cultivar Huachun 2 with the resistant cultivar Wayao. Genetic analysis of the F2 population indicated that PRR resistance in Wayao was controlled by a single dominant gene, temporarily named RpsWY, which was mapped on chromosome 3. A high-density genetic linkage bin map was constructed using 3469 recombination bins of the RILs to explore the candidate genes by the high-throughput genome-wide sequencing. The results of genotypic analysis showed that the RpsWY gene was located in bin 401 between 4466230 and 4502773 bp on chromosome 3 through line 71 and 100 of the RILs. Four predicted genes (Glyma03g04350, Glyma03g04360, Glyma03g04370, and Glyma03g04380) were found at the narrowed region of 36.5 kb in bin 401. These results suggest that the high-throughput genome-wide resequencing is an effective method to fine map PRR candidate genes.