Different loci associated with root and foliar resistance to sudden death syndrome (Fusarium virguliforme) in soybean.

KEY MESSAGE: Different loci associated with root resistance to F. virguliforme colonization and foliar resistance to phytotoxin damage in soybean. Use of resistant cultivars is the most efficacious approach to manage soybean sudden death syndrome (SDS), caused by Fusarium virguliforme. The objectives of this study were to (1) map the loci associated with root and foliar resistance to F. virguliforme infection and (2) decipher the relationships between root infection, foliar damage, and plot yield. A mapping population consisting of 153 F4-derived recombinant inbred lines from the cross U01-390489 × E07080 was genotyped by SoySNP6 K BeadChip assay. Both foliar damage and F. virguliforme colonization in roots were investigated in the field, and a weak positive correlation was identified between them. Foliar damage had a stronger negative correlation with plot yield than F. virguliforme colonization. Twelve loci associated with foliar damage were identified, and four of them were associated with multiple traits across environments. In contrast, only one locus associated with root resistance to F. virguliforme colonization was identified and mapped on Chromosome 18. It colocalized with the locus associated with foliar damage in the same environment. The locus on Chromosome 6, qSDS6-2, and the locus on Chromosome 18, qSDS18-1, were associated with resistance to SDS phytotoxins and resistance to F. virguliforme colonization of roots, respectively. Both loci affected plot yield. Foliar damage-related traits, especially disease index, are valuable indicators for SDS resistance breeding because of consistency of the identified loci and their stronger correlation with plot yield. The information provided by this study will facilitate marker-assisted selection to improve SDS resistance in soybean.

QTL mapping and epistatic interaction analysis of field resistance to sudden death syndrome (Fusarium virguliforme) in soybean.

KEY MESSAGE: Two interactive quantitative trait loci (QTLs) controlled the field resistance to sudden death syndrome (SDS) in soybean. The interaction between them was confirmed. Sudden death syndrome (SDS), caused by Fusarium virguliforme, is a major disease of soybean [Glycine max (L.) Merr.] in the United States. Breeding for soybean resistance to SDS is the most cost-effective method to manage the disease. The objective of this study was to identify and characterize quantitative trait loci (QTLs) underlying field resistance to SDS in a recombinant inbred line population from the cross GD2422 × LD01-5907. This population was genotyped with 1786 polymorphic single nucleotide polymorphisms (SNPs) using SoySNP6 K iSelect BeadChip and evaluated for SDS resistance in a naturally infested field. Four SDS resistance QTLs were mapped on Chromosomes 4, 8, 12 and 18. The resistant parent, LD01-5907, contributed the resistance alleles for the QTLs on Chromosomes 8 and 18 (qSDS-8 and qSDS-18), while the other parent, GD2422, provided the resistance alleles for the QTLs on Chromosomes 4 and 12 (qSDS-4 and qSDS-12). The minor QTL on Chromosome 12 (qSDS-12) is novel. The QTL on Chromosomes 8 and 18 (qSDS-8 and qSDS-18) overlapped with two soybean cyst nematode resistance-related loci, Rhg4 and Rhg1, respectively. A significant interaction between qSDS-8 and qSDS-18 was detected by disease incidence. Individual effects together with the interaction effect explained around 70% of the phenotypic variance. The epistatic interaction of qSDS-8 and qSDS-18 was confirmed by the field performance across multiple years. Furthermore, the resistance alleles at qSDS-8 and qSDS-18 were demonstrated to be recessive. The SNP markers linked to these QTLs will be useful for marker-assisted breeding to enhance the SDS resistance.

Integrating GWAS and gene expression data for functional characterization of resistance to white mould in soya bean.

White mould of soya bean, caused by Sclerotinia sclerotiorum (Lib.) de Bary, is a necrotrophic fungus capable of infecting a wide range of plants. To dissect the genetic architecture of resistance to white mould, a high-density customized single nucleotide polymorphism (SNP) array (52 041 SNPs) was used to genotype two soya bean diversity panels. Combined with resistance variation data observed in the field and greenhouse environments, genome-wide association studies (GWASs) were conducted to identify quantitative trait loci (QTL) controlling resistance against white mould. Results showed that 16 and 11 loci were found significantly associated with resistance in field and greenhouse, respectively. Of these, eight loci localized to previously mapped QTL intervals and one locus had significant associations with resistance across both environments. The expression level changes in genes located in GWAS-identified loci were assessed between partially resistant and susceptible genotypes through a RNA-seq analysis of the stem tissue collected at various time points after inoculation. A set of genes with diverse biological functionalities were identified as strong candidates underlying white mould resistance. Moreover, we found that genomic prediction models outperformed predictions based on significant SNPs. Prediction accuracies ranged from 0.48 to 0.64 for disease index measured in field experiments. The integrative methods, including GWAS, RNA-seq and genomic selection (GS), applied in this study facilitated the identification of causal variants, enhanced our understanding of mechanisms of white mould resistance and provided valuable information regarding breeding for disease resistance through genomic selection in soya bean.

Case Study of an Epidemiological Approach Dissecting Historical Soybean Sclerotinia Stem Rot Observations and Identifying Environmental Predictors of Epidemics and Yield Loss.

Sclerotinia sclerotiorum is a significant threat to soybean production worldwide. In this study, an epidemiological approach was used to examine 11 years of historical data from a soybean management performance trial in order to advance our understanding of Sclerotinia stem rot (SSR) development and to identify environmental predictors of SSR epidemics and associated yield losses. Recursive partitioning analysis suggested that average air temperature and total precipitation in July were the most significant variables associated with disease severity. High levels of SSR disease severity index were observed when the average temperature in July was below 19.5°C and total precipitation in July was moderate, between 20 and 108.5 mm. A biphasic sigmoidal curve accurately described the relationship between SSR disease severity index (DSI) and yield, with a DSI threshold of 22, below which minimal yield loss was observed. A 10% increase in the DSI, from 22.0 to 24.2, led to an 11% decrease in yield, from 3,308.14 to 2,951.29 kg/ha. Also, a yield threshold (3,353 kg/ha) that was higher than the annual U.S. average soybean yield (3,039.7 kg/ha) was suggested as an expected yield under low or no SSR pressure in the U.S. Midwest. These thresholds can allow soybean stakeholders to assess the value of disease control and establish an SSR baseline for cost-effective management to protect yields. Because S. sclerotiorum has more than 400 plant host species, and because having quantitative information concerning crop losses is crucial for decision making, this study shows the usefulness of historical data on SSR and, hence, can serve as a model in other SSR pathosystems (canola, dry bean, potato, pea, and so on).

Genomic consequences of selection and genome-wide association mapping in soybean.

BACKGROUND: Crop improvement always involves selection of specific alleles at genes controlling traits of agronomic importance, likely resulting in detectable signatures of selection within the genome of modern soybean (Glycine max L. Merr.). The identification of these signatures of selection is meaningful from the perspective of evolutionary biology and for uncovering the genetic architecture of agronomic traits. RESULTS: To this end, two populations of soybean, consisting of 342 landraces and 1062 improved lines, were genotyped with the SoySNP50K Illumina BeadChip containing 52,041 single nucleotide polymorphisms (SNPs), and systematically phenotyped for 9 agronomic traits. A cross-population composite likelihood ratio (XP-CLR) method was used to screen the signals of selective sweeps. A total of 125 candidate selection regions were identified, many of which harbored genes potentially involved in crop improvement. To further investigate whether these candidate regions were in fact enriched for genes affected by selection, genome-wide association studies (GWAS) were conducted on 7 selection traits targeted in soybean breeding (grain yield, plant height, lodging, maturity date, seed coat color, seed protein and oil content) and 2 non-selection traits (pubescence and flower color). Major genomic regions associated with selection traits overlapped with candidate selection regions, whereas no overlap of this kind occurred for the non-selection traits, suggesting that the selection sweeps identified are associated with traits of agronomic importance. Multiple novel loci and refined map locations of known loci related to these traits were also identified. CONCLUSIONS: These findings illustrate that comparative genomic analyses, especially when combined with GWAS, are a promising approach to dissect the genetic architecture of complex traits.