Development of a Standardized Soybean Cyst Nematode Screening Assay in Pennycress and Identification of Resistant Germplasm.

The prospect of incorporating pennycress as an oilseed cover crop in the Midwest's corn-soybean rotation system has drawn researcher and farmer attention. The inclusion of pennycress will be beneficial as it provides an excellent soil cover to reduce soil erosion and nutrient leaching while serving as an additional source for oilseed production and income. However, pennycress is an alternative host for soybean cyst nematode (SCN), which is a major biological threat to soybean that needs to be addressed for sustainable pennycress adoption into our current production systems. To develop a standardized SCN resistance screening strategy in pennycress, we tested and optimized five parameters: (i) germination stimulants, (ii) inoculation timing, (iii) inoculation rate, (iv) experimental incubation time, and (v) susceptible checks. The standardized SCN resistance screening protocol includes the following: (i) treating pennycress seeds with gibberellic acid for 24 h, (ii) transplanting seedlings 12 to 15 days after initiating germination and inoculating 10 to 12 days after transplantation, (iii) inoculating at a rate of 1,500 eggs/100 cc soil (1,500 eggs per plant), (iv) processing roots at 30 days after inoculation, and (v) using susceptible pennycress accession Ames 32869 to calculate the female index. The standardized protocol was used to quantify the response of a diverse set of pennycress accessions for response against SCN HG type 1.2.5.7 and HG type 7. While there were no highly resistant pennycress lines identified, 15 were rated as moderately resistant to HG type 1.2.5.7, and eight were rated moderately resistant to HG type 7. The resistant lines identified in this study could be utilized to develop SCN-resistant pennycress cultivars. The study also opens a new avenue for research to understand SCN-pennycress interactions through molecular and genomic studies. This knowledge could aid in the successful inclusion of pennycress as a beneficial cover/oilseed crop in the United States Midwest.[Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Cataloging SCN resistance loci in North American public soybean breeding programs.

Soybean cyst nematode (SCN) is a destructive pathogen of soybeans responsible for annual yield loss exceeding $1.5 billion in the United States. Here, we conducted a series of genome-wide association studies (GWASs) to understand the genetic landscape of SCN resistance in the University of Missouri soybean breeding programs (Missouri panel), as well as germplasm and cultivars within the United States Department of Agriculture (USDA) Uniform Soybean Tests-Northern Region (NUST). For the Missouri panel, we evaluated the resistance of breeding lines to SCN populations HG 2.5.7 (Race 1), HG 1.2.5.7 (Race 2), HG 0 (Race 3), HG 2.5.7 (Race 5), and HG 1.3.6.7 (Race 14) and identified seven quantitative trait nucleotides (QTNs) associated with SCN resistance on chromosomes 2, 8, 11, 14, 17, and 18. Additionally, we evaluated breeding lines in the NUST panel for resistance to SCN populations HG 2.5.7 (Race 1) and HG 0 (Race 3), and we found three SCN resistance-associated QTNs on chromosomes 7 and 18. Through these analyses, we were able to decipher the impact of seven major genetic loci, including three novel loci, on resistance to several SCN populations and identified candidate genes within each locus. Further, we identified favorable allelic combinations for resistance to individual SCN HG types and provided a list of available germplasm for integration of these unique alleles into soybean breeding programs. Overall, this study offers valuable insight into the landscape of SCN resistance loci in U.S. public soybean breeding programs and provides a framework to develop new and improved soybean cultivars with diverse plant genetic modes of SCN resistance.

Loss-of-function of an α-SNAP gene confers resistance to soybean cyst nematode.

Plant-parasitic nematodes are one of the most economically impactful pests in agriculture resulting in billions of dollars in realized annual losses worldwide. Soybean cyst nematode (SCN) is the number one biotic constraint on soybean production making it a priority for the discovery, validation and functional characterization of native plant resistance genes and genetic modes of action that can be deployed to improve soybean yield across the globe. Here, we present the discovery and functional characterization of a soybean resistance gene, GmSNAP02. We use unique bi-parental populations to fine-map the precise genomic location, and a combination of whole genome resequencing and gene fragment PCR amplifications to identify and confirm causal haplotypes. Lastly, we validate our candidate gene using CRISPR-Cas9 genome editing and observe a gain of resistance in edited plants. This demonstrates that the GmSNAP02 gene confers a unique mode of resistance to SCN through loss-of-function mutations that implicate GmSNAP02 as a nematode virulence target. We highlight the immediate impact of utilizing GmSNAP02 as a genome-editing-amenable target to diversify nematode resistance in commercially available cultivars.

Epistatic interaction between Rhg1-a and Rhg2 in PI 90763 confers resistance to virulent soybean cyst nematode populations.

KEY MESSAGE: An epistatic interaction between SCN resistance loci rhg1-a and rhg2 in PI 90763 imparts resistance against virulent SCN populations which can be employed to diversify SCN resistance in soybean cultivars. With more than 95% of the $46.1B soybean market dominated by a single type of genetic resistance, breeding for soybean cyst nematode (SCN)-resistant soybean that can effectively combat the widespread increase in virulent SCN populations presents a significant challenge. Rhg genes (for Resistance to Heterodera glycines) play a key role in resistance to SCN; however, their deployment beyond the use of the rhg1-b allele has been limited. In this study, quantitative trait loci (QTL) were mapped using PI 90763 through two biparental F3:4 recombinant inbred line (RIL) populations segregating for rhg1-a and rhg1-b alleles against a SCN HG type 1.2.5.7 (Race 2) population. QTL located on chromosome 18 (rhg1-a) and chromosome 11 (rhg2) were determined to confer SCN resistance in PI 90763. The rhg2 gene was fine-mapped to a 169-Kbp region pinpointing GmSNAP11 as the strongest candidate gene. We demonstrated a unique epistatic interaction between rhg1-a and rhg2 loci that not only confers resistance to multiple virulent SCN populations. Further, we showed that pyramiding rhg2 with the conventional mode of resistance, rhg1-b, is ineffective against these virulent SCN populations. This highlights the importance of pyramiding rhg1-a and rhg2 to maximize the impact of gene pyramiding strategies toward management of SCN populations virulent on rhg1-b sources of resistance. Our results lay the foundation for the next generation of soybean resistance breeding to combat the number one pathogen of soybean.

Genomic prediction using training population design in interspecific soybean populations.

Agronomically important traits generally have complex genetic architecture, where many genes have a small and largely additive effect. Genomic prediction has been demonstrated to increase genetic gain and efficiency in plant breeding programs beyond marker-assisted selection and phenotypic selection. The objective of this study was to evaluate the impact of allelic origin, marker density, training population size, and cross-validation schemes on the accuracy of genomic prediction models in an interspecific soybean nested association mapping (NAM) panel. Three cross-validation schemes were used: (a) Within-Family (WF): training population and predictions are made exclusively within each family; (b) Across All families (AF): all the individuals from the three families were randomly assigned to either the training or validation set; (c) Leave one Family out (LFO): each family is predicted using a training set that contains the other two families. Predictive abilities increased with training population size up to 350 individuals, but no significant gains were noted beyond 250 individuals in the training population. The number of markers had a limited impact on the observed predictive ability across traits; increasing markers used in the model above 1000 revealed no significant increases in prediction accuracy. Predictive abilities for AF were not significantly different from the WF method, and predictive abilities across populations for the WF method had a range of 0.58 to 0.70 for maturity, protein, meal, and oil. Our results also showed encouraging prediction accuracies for grain yield (0.58-0.69) using the WF method. Partitioning genomic prediction between G. max and G. soja alleles revealed useful information to select material with a larger allele contribution from both parents and could accelerate allele introgression from exotic germplasm into the elite soybean gene pool. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-021-01203-6.

Nested association mapping of important agronomic traits in three interspecific soybean populations.

KEY MESSAGE: Glycine soja germplasm can be used to successfully introduce new alleles with the potential to add valuable new genetic diversity to the current elite soybean gene pool. Given the demonstrated narrow genetic base of the US soybean production, it is essential to identify beneficial alleles from exotic germplasm, such as wild soybean, to enhance genetic gain for favorable traits. Nested association mapping (NAM) is an approach to population development that permits the comparison of allelic effects of the same QTL in multiple parents. Seed yield, plant maturity, plant height and plant lodging were evaluated in a NAM panel consisting of 392 recombinant inbred lines derived from three biparental interspecific soybean populations in eight environments during 2016 and 2017. Nested association mapping, combined with linkage mapping, identified three major QTL for plant maturity in chromosomes 6, 11 and 12 associated with alleles from wild soybean resulting in significant increases in days to maturity. A significant QTL for plant height was identified on chromosome 13 with the allele increasing plant height derived from wild soybean. A significant grain yield QTL was detected on chromosome 17, and the allele from Glycine soja had a positive effect of 166 kg ha-1; RIL's with the wild soybean allele yielded on average 6% more than the lines carrying the Glycine max allele. These findings demonstrate the usefulness and potential of alleles from wild soybean germplasm to enhance important agronomic traits in a soybean breeding program.

Genomic-assisted phylogenetic analysis and marker development for next generation soybean cyst nematode resistance breeding.

Soybean cyst nematode (SCN, Heterodera glycines Ichinohe) is a serious soybean pest. The use of resistant cultivars is an effective approach for preventing yield loss. In this study, 19,652 publicly available soybean accessions that were previously genotyped with the SoySNP50K iSelect BeadChip were used to evaluate the phylogenetic diversity of SCN resistance genes Rhg1 and Rhg4 in an attempt to identify novel sources of resistance. The sequence information of soybean lines was utilized to develop KASPar (KBioscience Competitive Allele-Specific PCR) assays from single nucleotide polymorphisms (SNPs) of Rhg1, Rhg4, and other novel quantitative trait loci (QTL). These markers were used to genotype a diverse set of 95 soybean germplasm lines and three recombinant inbred line (RIL) populations. SNP markers from the Rhg1 gene were able to differentiate copy number variation (CNV), such as resistant-high copy (PI 88788-type), low copy (Peking-type), and susceptible-single copy (Williams 82) numbers. Similarly, markers for the Rhg4 gene were able to detect Peking-type (resistance) genotypes. The phylogenetic information of SCN resistance loci from a large set of soybean accessions and the gene/QTL specific markers that were developed in this study will accelerate SCN resistance breeding programs.

Measurement of inorganic phosphorus in soybeans with near-infrared spectroscopy.

This study explored the feasibility of near-infrared (NIR) quantitative and qualitative models for soybean inorganic phosphorus (Pi), which is complementary to phytic acid, a component of nutritional and environmental importance. Spectra, consisting of diffuse reflectance (1100-2500 nm) of ground meal and single-bean transmittance (600-1900 nm) of whole seed, were collected on 191 recombinant inbred soybean lines. Partial least-squares regression models were individually developed for soy meal diffuse reflectance, single-bean transmittance, and averaged (24 beans/line) whole seed transmittance data. The best performance was obtained with diffuse reflectance data, in which the standard errors (rmsd) were 263 and 248 mg/kg for cross-validation and validation sets, respectively. Model accuracy was lower for the 24-bean average transmittance spectra and still lower for single beans. Despite the overall poorer modeling ability of Pi with respect to the common macronutrient NIR regressions, such as those for protein and oil, this technique holds promise for use in breeding programs.