Copy number variation of multiple genes at Rhg1 mediates nematode resistance in soybean

High-quality genome of a modern soybean cultivar and resequencing of 547 accessions provide insights into the role of structural variation

Soybean provides protein, oil and multiple health-related compounds. Understanding the effects of structural variations (SVs) on economic traits in modern breeding is important for soybean improvement. Here we assembled the high-quality genome of modern cultivar Nongdadou2 (NDD2) and identified 25,814 SV-gene pairs compared to 29 reported genomes, with 13 NDD2-private SVs validated in 547 deep-resequencing (average = 18.05-fold) accessions, which advances our understanding of genomic variation biology. We found some insertions/deletions involved in seed protein and weight formation, an inversion related to adaptation to drought and a large intertranslocation implicated in a key divergence event in soybean. Of 749,714 SVs from 547 accessions, 6,013 were significantly associated with 22 yield-related and seed-quality-related traits determined in ten location × year environments. We uncovered 1,761 associated SVs that hit genes or regulatory regions, with 12 in GmMQT influencing oil and isoflavone contents. Our work provides resources and insights into SV roles in soybean improvement.

Genome scans for selection signatures identify candidate virulence genes for adaptation of the soybean cyst nematode to host resistance

Plant pathogens are constantly under selection pressure for host resistance adaptation. Soybean cyst nematode (SCN, Heterodera glycines) is a major pest of soybean primarily managed through resistant cultivars; however, SCN populations have evolved virulence in response to selection pressures driven by repeated monoculture of the same genetic resistance. Resistance to SCN is mediated by multiple epistatic interactions between Rhg (for resistance to H. glycines) genes. However, the identity of SCN virulence genes that confer the ability to overcome resistance remains unknown. To identify candidate genomic regions showing signatures of selection for increased virulence, we conducted whole genome resequencing of pooled individuals (Pool-Seq) from two pairs of SCN populations adapted on soybeans with Peking-type (rhg1-a, rhg2, and Rhg4) resistance. Population differentiation and principal component analysis-based approaches identified approximately 0.72-0.79 million SNPs, the frequency of which showed potential selection signatures across multiple genomic regions. Chromosomes 3 and 6 between population pairs showed the greatest density of outlier SNPs with high population differentiation. Conducting multiple outlier detection tests to identify overlapping SNPs resulted in a total of 966 significantly differentiated SNPs, of which 285 exon SNPs were mapped to 97 genes. Of these, six genes encoded members of known stylet-secreted effector protein families potentially involved in host defence modulation including venom-allergen-like, annexin, glutathione synthetase, SPRYSEC, chitinase, and CLE effector proteins. Further functional analysis of identified candidate genes will provide new insights into the genetic mechanisms by which SCN overcomes soybean resistance and inform the development of molecular markers for rapidly screening the virulence profile of an SCN-infested field.

Fortifying nematode resistance through susceptibility gene inactivation

The predominant genetic defense mechanism against soybean cyst nematode (SCN) in 95% of the North America market is under threat by virulent SCN populations. Usovsky et al. identified GmSNAP02 as an SCN susceptibility gene through fine-mapping of unique bi-parental populations. Loss-of-function of GmSNAP02 confers enhanced resistance to more virulent SCN.

Improvement of plant quality by amino acid transporters: A comprehensive review

Amino acids serve as the primary means of transport and organic nitrogen carrier in plants, playing an essential role in plant growth and development. Amino acid transporters (AATs) facilitate the movement of amino acids within plants and have been identified and characterised in a number of species. It has been demonstrated that these amino acid transporters exert an influence on the quality attributes of plants, in addition to their primary function of transporting amino acid transport. This paper presents a summary of the role of AATs in plant quality improvement. This encompasses the enhancement of nitrogen utilization efficiency, root development, tiller number and fruit yield. Concurrently, AATs can bolster the resilience of plants to pests, diseases and abiotic stresses, thereby further enhancing the yield and quality of fruit. AATs exhibit a wide range of substrate specificity, which greatly optimizes the use of pesticides and significantly reduces pesticide residues, and reduces the risk of environmental pollution while increasing the safety of fruit. The discovery of AATs function provides new ideas and ways to cultivate high-quality crop and promote changes in agricultural development, and has great potential in the application of plant quality improvement.

Evaluation of deep learning for predicting rice traits using structural and single-nucleotide genomic variants

BACKGROUND

Structural genomic variants (SVs) are prevalent in plant genomes and have played an important role in evolution and domestication, as they constitute a significant source of genomic and phenotypic variability. Nevertheless, most methods in quantitative genetics focusing on crop improvement, such as genomic prediction, consider only Single Nucleotide Polymorphisms (SNPs). Deep Learning (DL) is a promising strategy for genomic prediction, but its performance using SVs and SNPs as genetic markers remains unknown.

RESULTS

We used rice to investigate whether combining SVs and SNPs can result in better trait prediction over SNPs alone and examine the potential advantage of Deep Learning (DL) networks over Bayesian Linear models. Specifically, the performances of BayesC (considering additive effects) and a Bayesian Reproducible Kernel Hilbert space (RKHS) regression (considering both additive and non-additive effects) were compared to those of two different DL architectures, the Multilayer Perceptron, and the Convolution Neural Network, to explore their prediction ability by using various marker input strategies. We found that exploiting structural and nucleotide variation slightly improved prediction ability on complex traits in 87% of the cases. DL models outperformed Bayesian models in 75% of the studied cases, considering the four traits and the two validation strategies used. Finally, DL systematically improved prediction ability of binary traits against the Bayesian models.

CONCLUSIONS

Our study reveals that the use of structural genomic variants can improve trait prediction in rice, independently of the methodology used. Also, our results suggest that Deep Learning (DL) networks can perform better than Bayesian models in the prediction of binary traits, and in quantitative traits when the training and target sets are not closely related. This highlights the potential of DL to enhance crop improvement in specific scenarios and the importance to consider SVs in addition to SNPs in genomic selection.

De novo genome assembly of white clover (Trifolium repens L.) reveals the role of copy number variation in rapid environmental adaptation

BACKGROUND

White clover (Trifolium repens) is a globally important perennial forage legume. This species also serves as an eco-evolutionary model system for studying within-species chemical defense variation; it features a well-studied polymorphism for cyanogenesis (HCN release following tissue damage), with higher frequencies of cyanogenic plants favored in warmer locations worldwide. Using a newly generated haplotype-resolved genome and two other long-read assemblies, we tested the hypothesis that copy number variants (CNVs) at cyanogenesis genes play a role in the ability of white clover to rapidly adapt to local environments. We also examined questions on subgenome evolution in this recently evolved allotetraploid species and on chromosomal rearrangements in the broader IRLC legume clade.

RESULTS

Integration of PacBio HiFi, Omni-C, Illumina, and linkage map data yielded a completely de novo genome assembly for white clover (created without a priori sequence assignment to subgenomes). We find that white clover has undergone extensive transposon diversification since its origin but otherwise shows highly conserved genome organization and composition with its diploid progenitors. Unlike some other clover species, its chromosomal structure is conserved with other IRLC legumes. We further find extensive evidence of CNVs at the major cyanogenesis loci; these contribute to quantitative variation in the cyanogenic phenotype and to local adaptation across wild North American populations.

CONCLUSIONS

This work provides a case study documenting the role of CNVs in local adaptation in a plant species, and it highlights the value of pan-genome data for identifying contributions of structural variants to adaptation in nature.

Allelic variability in the Rpp1 locus conferring resistance to Asian soybean rust revealed by genome-wide association

Soybean is a crucial crop for the Brazilian economy, but it faces challenges from the biotrophic fungus Phakopsora pachyrhizi, which causes Asian Soybean Rust (ASR). In this study, we aimed to identify SNPs associated with resistance within the Rpp1 locus, which is effective against Brazilian ASR populations. We employed GWAS and re-sequencing analyzes to pinpoint SNP markers capable of differentiating between soybean accessions harboring the Rpp1, Rpp1-b and other alternative alleles in the Rpp1 locus and from susceptible soybean cultivars. Seven SNP markers were found to be associated with ASR resistance through GWAS, with three of them defining haplotypes that efficiently distinguished the accessions based on their ASR resistance and source of the Rpp gene. These haplotypes were subsequently validated using a bi-parental population and a diverse set of Rpp sources, demonstrating that the GWAS markers co-segregate with ASR resistance. We then examined the presence of these haplotypes in a diverse set of soybean genomes worldwide, finding a few new potential sources of Rpp1/Rpp1-b. Further genomic sequence analysis revealed nucleotide differences within the genes present in the Rpp1 locus, including the ULP1-NBS-LRR genes, which are potential R gene candidates. These results provide valuable insights into ASR resistance in soybean, thus helping the development of resistant soybean varieties through genetic breeding programs.

A soybean cyst nematode suppresses microbial plant symbionts using a lipochitooligosaccharide-hydrolysing enzyme

Cyst nematodes are the most damaging species of plant-parasitic nematodes. They antagonize the colonization of beneficial microbial symbionts that are important for nutrient acquisition of plants. The molecular mechanism of the antagonism, however, remains elusive. Here, through biochemical combined with structural analysis, we reveal that Heterodera glycines, the most notorious soybean cyst nematode, suppresses symbiosis by secreting an enzyme named HgCht2 to hydrolyse the key symbiotic signalling molecules, lipochitooligosaccharides (LCOs). We solved the three-dimensional structures of apo HgCht2, as well as its chitooligosaccharide-bound and LCO-bound forms. These structures elucidated the substrate binding and hydrolysing mechanism of the enzyme. We designed an HgCht2 inhibitor, 1516b, which successfully suppresses the antagonism of cyst nematodes towards nitrogen-fixing rhizobia and phosphorus-absorbing arbuscular mycorrhizal symbioses. As HgCht2 is phylogenetically conserved across all cyst nematodes, our study revealed a molecular mechanism by which parasitic cyst nematodes antagonize the establishment of microbial symbiosis and provided a small-molecule solution.

N6-Methyladenosine (m6A) Sequencing Reveals Heterodera glycines-Induced Dynamic Methylation Promoting Soybean Defense

Unraveling the intricacies of soybean cyst nematode (Heterodera glycines) race 4 resistance and susceptibility in soybean breeding lines-11-452 (highly resistant) and Dongsheng1 (DS1, highly susceptible)-was the focal point of this study. Employing cutting-edge N6-methyladenosine (m6A) and RNA sequencing techniques, we delved into the impact of m6A modification on gene expression and plant defense responses. Through the evaluation of nematode development in both resistant and susceptible roots, a pivotal time point (3 days postinoculation) for m6A methylation sequencing was identified. Our sequencing data exhibited robust statistics, successful soybean genome mapping, and prevalent m6A peak distributions, primarily in the 3' untranslated region and stop codon regions. Analysis of differential methylation peaks and differentially expressed genes revealed distinctive patterns between resistant and susceptible genotypes. In the highly resistant line (11-452), key resistance and defense-associated genes displayed increased expression coupled with inhibited methylation, encompassing crucial players such as R genes, receptor kinases, and transcription factors. Conversely, the highly susceptible DS1 line exhibited heightened expression correlated with decreased methylation in genes linked to susceptibility pathways, including Mildew Locus O-like proteins and regulatory elements affecting defense mechanisms. Genome-wide assessments, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses, and differential methylation peak/differentially expressed gene overlap emphasized the intricate interplay of m6A modifications, alternative splicing, microRNA, and gene regulation in plant defense. Protein-protein interaction networks illuminated defense-pivotal genes, delineating divergent mechanisms in resistant and susceptible responses. This study sheds light on the dynamic correlation between methylation, splicing, and gene expression, providing profound insights into plant responses to nematode infection.

TWAS facilitates gene-scale trait genetic dissection through gene expression, structural variations, and alternative splicing in soybean

A genome-wide association study (GWAS) identifies trait-associated loci, but identifying the causal genes can be a bottleneck, due in part to slow decay of linkage disequilibrium (LD). A transcriptome-wide association study (TWAS) addresses this issue by identifying gene expression-phenotype associations or integrating gene expression quantitative trait loci with GWAS results. Here, we used self-pollinated soybean (Glycine max [L.] Merr.) as a model to evaluate the application of TWAS to the genetic dissection of traits in plant species with slow LD decay. We generated RNA sequencing data for a soybean diversity panel and identified the genetic expression regulation of 29 286 soybean genes. Different TWAS solutions were less affected by LD and were robust to the source of expression, identifing known genes related to traits from different tissues and developmental stages. The novel pod-color gene L2 was identified via TWAS and functionally validated by genome editing. By introducing a new exon proportion feature, we significantly improved the detection of expression variations that resulted from structural variations and alternative splicing. As a result, the genes identified through our TWAS approach exhibited a diverse range of causal variations, including SNPs, insertions or deletions, gene fusion, copy number variations, and alternative splicing. Using this approach, we identified genes associated with flowering time, including both previously known genes and novel genes that had not previously been linked to this trait, providing insights complementary to those from GWAS. In summary, this study supports the application of TWAS for candidate gene identification in species with low rates of LD decay.

GmSABP2-1 encodes methyl salicylate esterase and functions in soybean defense against soybean cyst nematode

KEY MESSAGE

The soybean gene GmSABP2-1 encodes methyl salicylate esterase and its overexpression led to significant reduction in development of pathogenic soybean cyst nematode. Soybean cyst nematode (SCN, Heterodera glycines) is one of the most devastating pests of soybean (Glycine max L. Merr.). In searching for SCN-defense genes, a soybean gene of the methylesterase (MES) family was found to be upregulated in an SCN-resistant soybean line and downregulated in an SCN-susceptible line upon SCN infection. This gene was designated as GmSABP2-1. Here, we report on biochemical and overexpression studies of GmSABP2-1 to examine its possible function in SCN resistance. The protein encoded by GmSABP2-1 is closely related to known methyl salicylate esterases. To determine the biochemical function of GmSABP2-1, a full-length cDNA of GmSABP2-1 was cloned into a protein expression vector and expressed in Escherichia coli. The resulting recombinant GmSABP2-1 was demonstrated to catalyze the demethylation of methyl salicylate. The biochemical properties of GmSABP2-1 were determined. Its apparent Km value was 46.2 ± 2.2 μM for methyl salicylate, comparable to those of the known methyl salicylate esterases. To explore the biological significance of GmSABP2-1 in soybean defense against SCN, we first overexpressed GmSABP2-1 in transgenic hairy roots of an SCN-susceptible soybean line. When infected with SCN, GmSABP2-1-overexpressing hairy roots showed 84.5% reduction in the development of SCN beyond J2 stage. To provide further genetic evidence for the role of GmSABP2-1 in SCN resistance, stable transgenic soybean plants overexpressing GmSABP2-1 were produced. Analysis of the GmSABP2-1-overexpressing lines showed a significant reduction in SCN development compared to non-transgenic plants. In conclusion, we demonstrated that GmSABP2-1 encodes methyl salicylate esterase and functions as a resistance-related gene against SCN.

Characterisation and mapping of a Globodera pallida resistance derived from the wild potato species Solanum spegazzinii

KEY MESSAGE

A new resistance locus acting against the potato cyst nematode Globodera pallida was mapped to chromosome VI in the diploid wild potato species Solanum spegazzinii CPC 7195. The potato cyst nematodes (PCN) Globodera pallida and Globodera rostochiensis are economically important potato pests in almost all regions where potato is grown. One important management strategy involves deployment through introgression breeding into modern cultivars of new sources of naturally occurring resistance from wild potato species. We describe a new source of resistance to G. pallida from wild potato germplasm. The diploid species Solanum spegazzinii Bitter accession CPC 7195 shows resistance to G. pallida pathotypes Pa1 and Pa2/3. A cross and first backcross of S. spegazzinii with Solanum tuberosum Group Phureja cultivar Mayan Gold were performed, and the level of resistance to G. pallida Pa2/3 was determined in progeny clones. Bulk-segregant analysis (BSA) using generic mapping enrichment sequencing (GenSeq) and genotyping-by-sequencing were performed to identify single-nucleotide polymorphisms (SNPs) that are genetically linked to the resistance, using S. tuberosum Group Phureja clone DM1-3 516 R44 as a reference genome. These SNPs were converted into allele-specific PCR assays, and the resistance was mapped to an interval of roughly 118 kb on chromosome VI. This newly identified resistance, which we call Gpa VIlspg, can be used in future efforts to produce modern cultivars with enhanced and broad-spectrum resistances to the major pests and pathogens of potato.

Mitogen-activated protein kinases MPK3 and MPK6 phosphorylate receptor-like cytoplasmic kinase CDL1 to regulate soybean basal immunity

Soybean cyst nematode (SCN; Heterodera glycines Ichinohe), one of the most devastating soybean (Glycine max) pathogens, causes significant yield loss in soybean production. Nematode infection triggers plant defense responses; however, the components involved in the upstream signaling cascade remain largely unknown. In this study, we established that a mitogen-activated protein kinase (MAPK) signaling module, activated by nematode infection or wounding, is crucial for soybeans to establish SCN resistance. GmMPK3 and GmMPK6 directly interact with CDG1-LIKE1 (GmCDL1), a member of the receptor-like cytoplasmic kinase (RLCK) subfamily VII. These kinases phosphorylate GmCDL1 at Thr-372 to prevent its proteasome-mediated degradation. Functional analysis demonstrated that GmCDL1 positively regulates immune responses and promotes SCN resistance in soybeans. GmMPK3-mediated and GmMPK6-mediated phosphorylation of GmCDL1 enhances GmMPK3 and GmMPK6 activation and soybean disease resistance, representing a positive feedback mechanism. Additionally, 2 L-type lectin receptor kinases, GmLecRK02g and GmLecRK08g, associate with GmCDL1 to initiate downstream immune signaling. Notably, our study also unveils the potential involvement of GmLecRKs and GmCDL1 in countering other soybean pathogens beyond nematodes. Taken together, our findings reveal the pivotal role of the GmLecRKs-GmCDL1-MAPK regulatory module in triggering soybean basal immune responses.

Duplicated Copy Number Variant of the Maize 9-Lipoxygenase ZmLOX5 Improves 9,10-KODA-Mediated Resistance to Fall Armyworms

Extensive genome structure variations, such as copy number variations (CNVs) and presence/absence variations, are the basis for the remarkable genetic diversity of maize; however, the effect of CNVs on maize herbivory defense remains largely underexplored. Here, we report that the naturally occurring duplication of the maize 9-lipoxygenase gene ZmLOX5 leads to increased resistance of maize to herbivory by fall armyworms (FAWs). Previously, we showed that ZmLOX5-derived oxylipins are required for defense against chewing insect herbivores and identified several inbred lines, including Yu796, that contained duplicated CNVs of ZmLOX5, referred to as Yu796-2×LOX5. To test whether introgression of the Yu796-2×LOX5 locus into a herbivore-susceptible B73 background that contains a single ZmLOX5 gene is a feasible approach to increase resistance, we generated a series of near-isogenic lines that contained either two, one, or zero copies of the Yu796-2×LOX5 locus in the B73 background via six backcrosses (BC6). Droplet digital PCR (ddPCR) confirmed the successful introgression of the Yu796-2×LOX5 locus in B73. The resulting B73-2×LOX5 inbred line displayed increased resistance against FAW, associated with increased expression of ZmLOX5, increased wound-induced production of its primary oxylipin product, the α-ketol, 9-hydroxy-10-oxo-12(Z),15(Z)-octadecadienoic acid (9,10-KODA), and the downstream defense hormones regulated by this molecule, 12-oxo-phytodienoic acid (12-OPDA) and abscisic acid (ABA). Surprisingly, wound-induced JA-Ile production was not increased in B73-2×LOX5, resulting from the increased JA catabolism. Furthermore, B73-2×LOX5 displayed reduced water loss in response to drought stress, likely due to increased ABA and 12-OPDA content. Taken together, this study revealed that the duplicated CNV of ZmLOX5 quantitively contributes to maize antiherbivore defense and presents proof-of-concept evidence that the introgression of naturally occurring duplicated CNVs of a defensive gene into productive but susceptible crop varieties is a feasible breeding approach for enhancing plant resistance to herbivory and tolerance to abiotic stress.

Common signatures of selection reveal target loci for breeding across soybean populations

Understanding the underlying genetic bases of yield-related selection and distinguishing these changes from genetic drift are critical for both improved understanding and future success of plant breeding. Soybean [Glycine max (L.) Merr.] is a key species for world food security, yet knowledge of the mechanism of selective breeding in soybean, such as the century-long program of artificial selection in U.S. soybean germplasm, is currently limited to certain genes and loci. Here, we identify genome-wide signatures of selection in separate populations of soybean subjected to artificial selection for increased yield by multiple breeding programs in the United States. We compared the alternative soybean breeding population (AGP) created by USDA-ARS to the conventional public soybean lines (CGP) developed at three different stages of breeding (ancestral, intermediate, and elite) to identify shared signatures of selection and differentiate these from drift. The results showed a strong selection for specific haplotypes identified by single site frequency and haplotype homozygosity methods. A set of common selection signatures was identified in both AGP and CGP that supports the hypothesis that separate breeding programs within similar environments coalesce on the fixation of the same key haplotypes. Signatures unique to each breeding program were observed. These results raise the possibility that selection analysis can allow the identification of favorable alleles to enhance directed breeding approaches.

Rapid mini-chromosome divergence among fungal isolates causing wheat blast outbreaks in Bangladesh and Zambia

The fungal pathogen, Magnaporthe oryzae Triticum pathotype, causing wheat blast disease was first identified in South America and recently spread across continents to South Asia and Africa. Here, we studied the genetic relationship among isolates found on the three continents. Magnaporthe oryzae strains closely related to a South American field isolate B71 were found to have caused the wheat blast outbreaks in South Asia and Africa. Genomic variation among isolates from the three continents was examined using an improved B71 reference genome and whole-genome sequences. We found strong evidence to support that the outbreaks in Bangladesh and Zambia were caused by the introductions of genetically separated isolates, although they were all close to B71 and, therefore, collectively referred to as the B71 branch. In addition, B71 branch strains carried at least one supernumerary mini-chromosome. Genome assembly of a Zambian strain revealed that its mini-chromosome was similar to the B71 mini-chromosome but with a high level of structural variation. Our findings show that while core genomes of the multiple introductions are highly similar, the mini-chromosomes have undergone marked diversification. The maintenance of the mini-chromosome and rapid genomic changes suggest the mini-chromosomes may serve important virulence or niche adaptation roles under diverse environmental conditions.

R we there yet? Advances in cloning resistance genes for engineering immunity in crop plants

Over the past three decades, significant progress has been made in the field of resistance (R) gene cloning. Advances in recombinant DNA technology, genome sequencing, bioinformatics, plant transformation and plant husbandry have facilitated the transition from cloning R genes in model species to crop plants and their wild relatives. To date, researchers have isolated more than 450 R genes that play important roles in plant immunity. The molecular and biochemical mechanisms by which intracellular immune receptors are activated and initiate defense responses are now well understood. These advances present exciting opportunities for engineering disease-resistant crop plants that are protected by genetics rather than pesticides.

Deep Learning Model for Classifying and Evaluating Soybean Leaf Disease Damage

Soybean (Glycine max (L.) Merr.) is a major source of oil and protein for human food and animal feed; however, soybean crops face diverse factors causing damage, including pathogen infections, environmental shifts, poor fertilization, and incorrect pesticide use, leading to reduced yields. Identifying the level of leaf damage aids yield projections, pesticide, and fertilizer decisions. Deep learning models (DLMs) and neural networks mastering tasks from abundant data have been used for binary healthy/unhealthy leaf classification. However, no DLM predicts and categorizes soybean leaf damage severity (five levels) for tailored pesticide use and yield forecasts. This paper introduces a novel DLM for accurate damage prediction and classification, trained on 2930 near-field soybean leaf images. The model quantifies damage severity, distinguishing healthy/unhealthy leaves and offering a comprehensive solution. Performance metrics include accuracy, precision, recall, and F1-score. This research presents a robust DLM for soybean damage assessment, supporting informed agricultural decisions based on specific damage levels and enhancing crop management and productivity.

No Pairwise Interactions of GmSNAP18, GmSHMT08 and AtPR1 with Suppressed AtPR1 Expression Enhance the Susceptibility of Arabidopsis to Beet Cyst Nematode

GmSNAP18 and GmSHMT08 are two major genes conferring soybean cyst nematode (SCN) resistance in soybean. Overexpression of either of these two soybean genes would enhance the susceptibility of Arabidopsis to beet cyst nematode (BCN), while overexpression of either of their corresponding orthologs in Arabidopsis, AtSNAP2 and AtSHMT4, would suppress it. However, the mechanism by which these two pairs of orthologous genes boost or inhibit BCN susceptibility of Arabidopsis still remains elusive. In this study, Arabidopsis with simultaneously overexpressed GmSNAP18 and GmSHMT0 suppressed the growth of underground as well as above-ground parts of plants. Furthermore, Arabidopsis that simultaneously overexpressed GmSNAP18 and GmSHMT08 substantially stimulated BCN susceptibility and remarkably suppressed expression of AtPR1 in the salicylic acid signaling pathway. However, simultaneous overexpression of GmSNAP18 and GmSHMT08 did not impact the expression of AtJAR1 and AtHEL1 in the jasmonic acid and ethylene signaling pathways. GmSNAP18, GmSHMT08, and a pathogenesis-related (PR) protein, GmPR08-Bet VI, in soybean, and AtSNAP2, AtSHMT4, and AtPR1 in Arabidopsis could interact pair-wisely for mediating SCN and BCN resistance in soybean and Arabidopsis, respectively. Both AtSNAP2 and AtPR1 were localized on the plasma membrane, and AtSHMT4 was localized both on the plasma membrane and in the nucleus of cells. Nevertheless, after interactions, AtSNAP2 and AtPR1 could partially translocate into the cell nucleus. GmSNAP18 interacted with AtSHMT4, and GmSHMT4 interacted with AtSNAP2. However, neither GmSNAP18 nor GmSHMT08 interacted with AtPR1. Thus, no pairwise interactions among α-SNAPs, SHMTs, and AtPR1 occurred in Arabidopsis overexpressing either GmSNAP18 or GmSHMT08, or both of them. Transgenic Arabidopsis overexpressing either GmSNAP18 or GmSHMT08 substantially suppressed AtPR1 expression, while transgenic Arabidopsis overexpressing either AtSNAP2 or AtSHMT4 remarkably enhanced it. Taken together, no pairwise interactions of GmSNAP18, GmSHMT08, and AtPR1 with suppressed expression of AtPR1 enhanced BCN susceptibility in Arabidopsis. This study may provide a clue that nematode-resistant or -susceptible functions of plant genes likely depend on both hosts and nematode species.

k-mer-based GWAS enhances the discovery of causal variants and candidate genes in soybean

Genome-wide association studies (GWAS) are powerful statistical methods that detect associations between genotype and phenotype at genome scale. Despite their power, GWAS frequently fail to pinpoint the causal variant or the gene controlling a given trait in crop species. Assessing genetic variants other than single-nucleotide polymorphisms (SNPs) could alleviate this problem. In this study, we tested the potential of structural variant (SV)- and k-mer-based GWAS in soybean by applying these methods as well as conventional SNP/indel-based GWAS to 13 traits. We assessed the performance of each GWAS approach based on loci for which the causal genes or variants were known from previous genetic studies. We found that k-mer-based GWAS was the most versatile approach and the best at pinpointing causal variants or candidate genes. Moreover, k-mer-based analyses identified promising candidate genes for loci related to pod color, pubescence form, and resistance to Phytophthora sojae. In our dataset, SV-based GWAS did not add value compared to k-mer-based GWAS and may not be worth the time and computational resources invested. Despite promising results, significant challenges remain regarding the downstream analysis of k-mer-based GWAS. Notably, better methods are needed to associate significant k-mers with sequence variation. Our results suggest that coupling k-mer- and SNP/indel-based GWAS is a powerful approach for discovering candidate genes in crop species.

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.

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.

Involvement of cyclic nucleotide-gated channels in soybean cyst nematode chemotaxis and thermotaxis

The soybean cyst nematode (SCN) is one of the most damaging pests affecting soybean production. SCN displays important host recognition behaviors, such as hatching and infection, by recognizing several compounds produced by the host. Therefore, controlling SCN behaviors such as chemotaxis and thermotaxis is an attractive pest control strategy. In this study, we found that cyclic nucleotide-gated channels (CNG channels) regulate SCN chemotaxis and thermotaxis and Hg-tax-2, a gene encoding a CNG channel, is an important regulator of SCN behavior. Gene silencing of Hg-tax-2 and treatment with a CNG channel inhibitor reduced the attraction of second-stage juveniles to nitrate, an attractant with a different recognition mechanism from the host-derived chemoattractant(s), and to host soybean roots, as well as their avoidance behavior toward high temperatures. Co-treatment of ds Hg-tax-2 with the CNG channel inhibitor indicated that Hg-tax-2 is a major regulator of SCN chemotaxis and thermotaxis. These results suggest new avenues for research on control of SCN.

Soybean-SCN Battle: Novel Insight into Soybean's Defense Strategies against Heterodera glycines

Soybean cyst nematode (SCN, Heterodera glycines, Ichinohe) poses a significant threat to global soybean production, necessitating a comprehensive understanding of soybean plants' response to SCN to ensure effective management practices. In this study, we conducted dual RNA-seq analysis on SCN-resistant Plant Introduction (PI) 437654, 548402, and 88788 as well as a susceptible line (Lee 74) under exposure to SCN HG type 1.2.5.7. We aimed to elucidate resistant mechanisms in soybean and identify SCN virulence genes contributing to resistance breakdown. Transcriptomic and pathway analyses identified the phenylpropanoid, MAPK signaling, plant hormone signal transduction, and secondary metabolite pathways as key players in resistance mechanisms. Notably, PI 437654 exhibited complete resistance and displayed distinctive gene expression related to cell wall strengthening, oxidative enzymes, ROS scavengers, and Ca2+ sensors governing salicylic acid biosynthesis. Additionally, host studies with varying immunity levels and a susceptible line shed light on SCN pathogenesis and its modulation of virulence genes to evade host immunity. These novel findings provide insights into the molecular mechanisms underlying soybean-SCN interactions and offer potential targets for nematode disease management.

The Triticeae CBF Gene Cluster-To Frost Resistance and Beyond

The pivotal role of CBF/DREB1 transcriptional factors in Triticeae crops involved in the abiotic stress response has been highlighted. The CBFs represent an important hub in the ICE-CBF-COR pathway, which is one of the most relevant mechanisms capable of activating the adaptive response to cold and drought in wheat, barley, and rye. Understanding the intricate mechanisms and regulation of the cluster of CBF genes harbored by the homoeologous chromosome group 5 entails significant potential for the genetic improvement of small grain cereals. Triticeae crops seem to share common mechanisms characterized, however, by some peculiar aspects of the response to stress, highlighting a combined landscape of single-nucleotide variants and copy number variation involving CBF members of subgroup IV. Moreover, while chromosome 5 ploidy appears to confer species-specific levels of resistance, an important involvement of the ICE factor might explain the greater tolerance of rye. By unraveling the genetic basis of abiotic stress tolerance, researchers can develop resilient varieties better equipped to withstand extreme environmental conditions. Hence, advancing our knowledge of CBFs and their interactions represents a promising avenue for improving crop resilience and food security.

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.

A haplotype resolved chromosome-scale assembly of North American wild apple Malus fusca and comparative genomics of the fire blight Mfu10 locus

The Pacific crabapple (Malus fusca) is a wild relative of the commercial apple (Malus × domestica). With a range extending from Alaska to Northern California, M. fusca is extremely hardy and disease resistant. The species represents an untapped genetic resource for the development of new apple cultivars with enhanced stress resistance. However, gene discovery and utilization of M. fusca have been hampered by the lack of genomic resources. Here, we present a high‐quality, haplotype‐resolved, chromosome‐scale genome assembly and annotation for M. fusca. The genome was assembled using high‐fidelity long‐reads and scaffolded using genetic maps and high‐throughput chromatin conformation capture sequencing, resulting in one of the most contiguous apple genomes to date. We annotated the genome using public transcriptomic data from the same species taken from diverse plant structures and developmental stages. Using this assembly, we explored haplotypic structural variation within the genome of M. fusca, identifying thousands of large variants. We further showed high sequence co‐linearity with other domesticated and wild Malus species. Finally, we resolve a known quantitative trait locus associated with resistance to fire blight (Erwinia amylovora). Insights gained from the assembly of a reference‐quality genome of this hardy wild apple relative will be invaluable as a tool to facilitate DNA‐informed introgression breeding.

Importance of genetic architecture in marker selection decisions for genomic prediction

KEY MESSAGE

We demonstrate potential for improved multi-environment genomic prediction accuracy using structural variant markers. However, the degree of observed improvement is highly dependent on the genetic architecture of the trait. Breeders commonly use genetic markers to predict the performance of untested individuals as a way to improve the efficiency of breeding programs. These genomic prediction models have almost exclusively used single nucleotide polymorphisms (SNPs) as their source of genetic information, even though other types of markers exist, such as structural variants (SVs). Given that SVs are associated with environmental adaptation and not all of them are in linkage disequilibrium to SNPs, SVs have the potential to bring additional information to multi-environment prediction models that are not captured by SNPs alone. Here, we evaluated different marker types (SNPs and/or SVs) on prediction accuracy across a range of genetic architectures for simulated traits across multiple environments. Our results show that SVs can improve prediction accuracy, but it is highly dependent on the genetic architecture of the trait and the relative gain in accuracy is minimal. When SVs are the only causative variant type, 70% of the time SV predictors outperform SNP predictors. However, the improvement in accuracy in these instances is only 1.5% on average. Further simulations with predictors in varying degrees of LD with causative variants of different types (e.g., SNPs, SVs, SNPs and SVs) showed that prediction accuracy increased as linkage disequilibrium between causative variants and predictors increased regardless of the marker type. This study demonstrates that knowing the genetic architecture of a trait in deciding what markers to use in large-scale genomic prediction modeling in a breeding program is more important than what types of markers to use.

Exploring Pan-Genomes: An Overview of Resources and Tools for Unraveling Structure, Function, and Evolution of Crop Genes and Genomes

The availability of multiple sequenced genomes from a single species made it possible to explore intra- and inter-specific genomic comparisons at higher resolution and build clade-specific pan-genomes of several crops. The pan-genomes of crops constructed from various cultivars, accessions, landraces, and wild ancestral species represent a compendium of genes and structural variations and allow researchers to search for the novel genes and alleles that were inadvertently lost in domesticated crops during the historical process of crop domestication or in the process of extensive plant breeding. Fortunately, many valuable genes and alleles associated with desirable traits like disease resistance, abiotic stress tolerance, plant architecture, and nutrition qualities exist in landraces, ancestral species, and crop wild relatives. The novel genes from the wild ancestors and landraces can be introduced back to high-yielding varieties of modern crops by implementing classical plant breeding, genomic selection, and transgenic/gene editing approaches. Thus, pan-genomic represents a great leap in plant research and offers new avenues for targeted breeding to mitigate the impact of global climate change. Here, we summarize the tools used for pan-genome assembly and annotations, web-portals hosting plant pan-genomes, etc. Furthermore, we highlight a few discoveries made in crops using the pan-genomic approach and future potential of this emerging field of study.

The soybean immune receptor GmBIR1 regulates host transcriptome, spliceome, and immunity during cyst nematode infection

BAK1-INTERACTING RECEPTOR LIKE KINASE1 (BIR1) is a negative regulator of various aspects of disease resistance and immune responses. Here, we investigated the functional role of soybean (Glycine max) BIR1 (GmBIR1) during soybean interaction with soybean cyst nematode (SCN, Heterodera glycines) and the molecular mechanism through which GmBIR1 regulates plant immunity. Overexpression of wild-type variant of GmBIR1 (WT-GmBIR1) using transgenic soybean hairy roots significantly increased soybean susceptibility to SCN, whereas overexpression of kinase-dead variant (KD-GmBIR1) significantly increased plant resistance. Transcriptome analysis revealed that genes oppositely regulated in WT-GmBIR1 and KD-GmBIR1 upon SCN infection were enriched primarily in defense and immunity-related functions. Quantitative phosphoproteomic analysis identified 208 proteins as putative substrates of the GmBIR1 signaling pathway, 114 of which were differentially phosphorylated upon SCN infection. In addition, the phosphoproteomic data pointed to a role of the GmBIR1 signaling pathway in regulating alternative pre-mRNA splicing. Genome-wide analysis of splicing events provided compelling evidence supporting a role of the GmBIR1 signaling pathway in establishing alternative splicing during SCN infection. Our results provide novel mechanistic insights into the function of the GmBIR1 signaling pathway in regulating soybean transcriptome and spliceome via differential phosphorylation of splicing factors and regulation of splicing events of pre-mRNA decay- and spliceosome-related genes.

Subtelomeric 5-enolpyruvylshikimate-3-phosphate synthase copy number variation confers glyphosate resistance in Eleusine indica

Genomic structural variation (SV) has profound effects on organismal evolution; often serving as a source of novel genetic variation. Gene copy number variation (CNV), one type of SV, has repeatedly been associated with adaptive evolution in eukaryotes, especially with environmental stress. Resistance to the widely used herbicide, glyphosate, has evolved through target-site CNV in many weedy plant species, including the economically important grass, Eleusine indica (goosegrass); however, the origin and mechanism of these CNVs remain elusive in many weed species due to limited genetic and genomic resources. To study this CNV in goosegrass, we present high-quality reference genomes for glyphosate-susceptible and -resistant goosegrass lines and fine-assembles of the duplication of glyphosate's target site gene 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS). We reveal a unique rearrangement of EPSPS involving chromosome subtelomeres. This discovery adds to the limited knowledge of the importance of subtelomeres as genetic variation generators and provides another unique example for herbicide resistance evolution.

Genomic structural variation: A complex but important driver of human evolution

Structural variants (SVs)-including duplications, deletions, and inversions of DNA-can have significant genomic and functional impacts but are technically difficult to identify and assay compared with single-nucleotide variants. With the aid of new genomic technologies, it has become clear that SVs account for significant differences across and within species. This phenomenon is particularly well-documented for humans and other primates due to the wealth of sequence data available. In great apes, SVs affect a larger number of nucleotides than single-nucleotide variants, with many identified SVs exhibiting population and species specificity. In this review, we highlight the importance of SVs in human evolution by (1) how they have shaped great ape genomes resulting in sensitized regions associated with traits and diseases, (2) their impact on gene functions and regulation, which subsequently has played a role in natural selection, and (3) the role of gene duplications in human brain evolution. We further discuss how to incorporate SVs in research, including the strengths and limitations of various genomic approaches. Finally, we propose future considerations in integrating existing data and biospecimens with the ever-expanding SV compendium propelled by biotechnology advancements.

k-mer-Based Genome-Wide Association Studies in Plants: Advances, Challenges, and Perspectives

Genome-wide association studies (GWAS) have allowed the discovery of marker-trait associations in crops over recent decades. However, their power is hampered by a number of limitations, with the key one among them being an overreliance on single-nucleotide polymorphisms (SNPs) as molecular markers. Indeed, SNPs represent only one type of genetic variation and are usually derived from alignment to a single genome assembly that may be poorly representative of the population under study. To overcome this, k-mer-based GWAS approaches have recently been developed. k-mer-based GWAS provide a universal way to assess variation due to SNPs, insertions/deletions, and structural variations without having to specifically detect and genotype these variants. In addition, k-mer-based analyses can be used in species that lack a reference genome. However, the use of k-mers for GWAS presents challenges such as data size and complexity, lack of standard tools, and potential detection of false associations. Nevertheless, efforts are being made to overcome these challenges and a general analysis workflow has started to emerge. We identify the priorities for k-mer-based GWAS in years to come, notably in the development of user-friendly programs for their analysis and approaches for linking significant k-mers to sequence variation.

Large-scale data mining pipeline for identifying novel soybean genes involved in resistance against the soybean cyst nematode

The soybean cyst nematode (SCN) [Heterodera glycines Ichinohe] is a devastating pathogen of soybean [Glycine max (L.) Merr.] that is rapidly becoming a global economic issue. Two loci conferring SCN resistance have been identified in soybean, Rhg1 and Rhg4; however, they offer declining protection. Therefore, it is imperative that we identify additional mechanisms for SCN resistance. In this paper, we develop a bioinformatics pipeline to identify protein-protein interactions related to SCN resistance by data mining massive-scale datasets. The pipeline combines two leading sequence-based protein-protein interaction predictors, the Protein-protein Interaction Prediction Engine (PIPE), PIPE4, and Scoring PRotein INTeractions (SPRINT) to predict high-confidence interactomes. First, we predicted the top soy interacting protein partners of the Rhg1 and Rhg4 proteins. Both PIPE4 and SPRINT overlap in their predictions with 58 soybean interacting partners, 19 of which had GO terms related to defense. Beginning with the top predicted interactors of Rhg1 and Rhg4, we implement a "guilt by association" in silico proteome-wide approach to identify novel soybean genes that may be involved in SCN resistance. This pipeline identified 1,082 candidate genes whose local interactomes overlap significantly with the Rhg1 and Rhg4 interactomes. Using GO enrichment tools, we highlighted many important genes including five genes with GO terms related to response to the nematode (GO:0009624), namely, Glyma.18G029000, Glyma.11G228300, Glyma.08G120500, Glyma.17G152300, and Glyma.08G265700. This study is the first of its kind to predict interacting partners of known resistance proteins Rhg1 and Rhg4, forming an analysis pipeline that enables researchers to focus their search on high-confidence targets to identify novel SCN resistance genes in soybean.

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

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

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01397-x.

Single Nematode Transcriptomic Analysis, Using Long-Read Technology, Reveals Two Novel Virulence Gene Candidates in the Soybean Cyst Nematode, Heterodera glycines

The soybean cyst nematode (Heterodera glycines, SCN), is the most damaging disease of soybean in North America. While management of this pest using resistant soybean is generally still effective, prolonged exposure to cultivars derived from the same source of resistance (PI 88788) has led to the emergence of virulence. Currently, the underlying mechanisms responsible for resistance breakdown remain unknown. In this study, we combined a single nematode transcriptomic profiling approach with long-read sequencing to reannotate the SCN genome. This resulted in the annotation of 1932 novel transcripts and 281 novel gene features. Using a transcript-level quantification approach, we identified eight novel effector candidates overexpressed in PI 88788 virulent nematodes in the late infection stage. Among these were the novel gene Hg-CPZ-1 and a pioneer effector transcript generated through the alternative splicing of the non-effector gene Hetgly21698. While our results demonstrate that alternative splicing in effectors does occur, we found limited evidence of direct involvement in the breakdown of resistance. However, our analysis highlighted a distinct pattern of effector upregulation in response to PI 88788 resistance indicative of a possible adaptation process by SCN to host resistance.

A comprehensive analysis of copy number variations in diverse apple populations

BACKGROUND

As an important source of genetic variation, copy number variation (CNV) can alter the dosage of DNA segments, which in turn may affect gene expression level and phenotype. However, our knowledge of CNV in apple is still limited. Here, we obtained high-confidence CNVs and investigated their functional impact based on genome resequencing data of two apple populations, cultivars and wild relatives.

RESULTS

In this study, we identified 914,610 CNVs comprising 14,839 CNV regions (CNVRs) from 346 apple accessions, including 289 cultivars and 57 wild relatives. CNVRs summed to 71.19 Mb, accounting for 10.03% of the apple genome. Under the low linkage disequilibrium (LD) with nearby SNPs, they could also accurately reflect the population structure of apple independent of SNPs. Furthermore, A total of 3,621 genes were covered by CNVRs and functionally involved in biological processes such as defense response, reproduction and metabolic processes. In addition, the population differentiation index ([Formula: see text]) analysis between cultivars and wild relatives revealed 127 CN-differentiated genes, which may contribute to trait differences in these two populations.

CONCLUSIONS

This study was based on identification of CNVs from 346 diverse apple accessions, which to our knowledge was the largest dataset for CNV analysis in apple. Our work presented the first comprehensive CNV map and provided valuable resources for understanding genomic variations in apple.

Soybean transporter AAT Rhg1 abundance increases along the nematode migration path and impacts vesiculation and ROS

Rhg1 (Resistance to Heterodera glycines 1) mediates soybean (Glycine max) resistance to soybean cyst nematode (SCN; H. glycines). Rhg1 is a 4-gene, ∼30-kb block that exhibits copy number variation, and the common PI 88788-type rhg1-b haplotype carries 9 to 10 tandem Rhg1 repeats. Glyma.18G022400 (Rhg1-GmAAT), 1 of 3 resistance-conferring genes at the complex Rhg1 locus, encodes the putative amino acid transporter AATRhg1 whose mode of action is largely unknown. We discovered that AATRhg1 protein abundance increases 7- to 15-fold throughout root cells along the migration path of SCN. These root cells develop an increased abundance of vesicles and large vesicle-like bodies (VLB) as well as multivesicular and paramural bodies. AATRhg1 protein is often present in these structures. AATRhg1 abundance remained low in syncytia (plant cells reprogrammed by SCN for feeding), unlike the Rhg1 α-SNAP protein, whose abundance has previously been shown to increase in syncytia. In Nicotiana benthamiana, if soybean AATRhg1 was present, oxidative stress promoted the formation of large VLB, many of which contained AATRhg1. AATRhg1 interacted with the soybean NADPH oxidase GmRBOHG, the ortholog of Arabidopsis thaliana RBOHD previously found to exhibit upregulated expression upon SCN infection. AATRhg1 stimulated reactive oxygen species (ROS) generation when AATRhg1 and GmRBOHG were co-expressed. These findings suggest that AATRhg1 contributes to SCN resistance along the migration path as SCN invades the plant and does so, at least in part, by increasing ROS production. In light of previous findings about α-SNAPRhg1, this study also shows that different Rhg1 resistance proteins function via at least 2 spatially and temporally separate modes of action.

The elite variations in germplasms for soybean breeding

The genetic base of soybean cultivars (Glycine max (L.) Merr.) has been narrowed through selective domestication and specific breeding improvement, similar to other crops. This presents challenges in breeding new cultivars with improved yield and quality, reduced adaptability to climate change, and increased susceptibility to diseases. On the other hand, the vast collection of soybean germplasms offers a potential source of genetic variations to address those challenges, but it has yet to be fully leveraged. In recent decades, rapidly improved high-throughput genotyping technologies have accelerated the harness of elite variations in soybean germplasm and provided the important information for solving the problem of a narrowed genetic base in breeding. In this review, we will overview the situation of maintenance and utilization of soybean germplasms, various solutions provided for different needs in terms of the number of molecular markers, and the omics-based high-throughput strategies that have been used or can be used to identify elite alleles. We will also provide an overall genetic information generated from soybean germplasms in yield, quality traits, and pest resistance for molecular breeding.

Discovering and prioritizing candidate resistance genes against soybean pests by integrating GWAS and gene coexpression networks

Soybean is one of the most important legume crops worldwide. Soybean pests have a considerable impact on crop yield. Here, we integrated publicly available genome-wide association studies and transcriptomic data to prioritize candidate resistance genes against the insects Aphis glycines and Spodoptera litura, and the nematode Heterodera glycines. We identified 171, 7, and 228 high-confidence candidate resistance genes against A. glycines, S. litura, and H. glycines, respectively. We found some overlap of candidate genes between insect species, but not between insects and H. glycines. Although 15% of the prioritized candidate genes encode proteins of unknown function, the vast majority of the candidates are related to plant immunity processes, such as transcriptional regulation, signaling, oxidative stress, recognition, and physical defense. Based on the number of resistance alleles, we selected the ten most promising accessions against each pest species in the soybean USDA germplasm. The most resistant accessions do not reach the maximum theoretical resistance potential, indicating that they might be further improved to increase resistance in breeding programs or through genetic engineering. Finally, the coexpression networks we inferred in this work are available in a user-friendly web application (https://soypestgcn.venanciogroup.uenf.br/) and an R/Shiny package (https://github.com/almeidasilvaf/SoyPestGCN) that serve as a public resource to explore soybean-pest interactions at the transcriptional level.

Deciphering the genetic basis of resistance to soybean cyst nematode combining IBD and association mapping

IBD analysis clarified the dynamics of chromosomal recombination during the ZP pedigree breeding process and identified ten genomic regions resistant to SCN race3 combining association mapping. Soybean cyst nematode (SCN, Heterodera glycines Ichinohe) is one of the most devastating pathogens for soybean production worldwide. The cultivar Zhongpin03-5373 (ZP), derived from SCN-resistant progenitor parents, Peking, PI 437654 and Huipizhi Heidou, is an elite line with high resistance to SCN race3. In the current study, a pedigree variation map was generated for ZP and its ten progenitors using 3,025,264 high-quality SNPs identified from an average of 16.2 × re-sequencing for each genome. Through identity by decent (IBD) tracking, we showed the dynamic change of genome and detected important IBD fragments, which revealed the comprehensively artificial selection of important traits during ZP breeding process. A total of 2,353 IBD fragments related to SCN resistance including SCN-resistant genes rhg1, rhg4 and NSF_RAN07 were identified based on the resistant-related genetic paths. Moreover, 23 genomic regions underlying resistance to SCN race3 were identified by genome-wide association study (GWAS) in 481 re-sequenced cultivated soybeans. Ten common loci were found by both IBD tracking and GWAS analysis. Haplotype analysis of 16 potential candidate genes suggested a causative SNP (C/T, - 1065) located in the promoter of Glyma.08G096500 and encoding a predicted TIFY5b-related protein on chr8 was highly correlated with SCN race3 resistance. Our results more thoroughly elucidated the dynamics of genomic fragments during ZP pedigree breeding and the genetic basis of SCN resistance, which will provide useful information for gene cloning and the development of resistant soybean cultivars using a marker-assisted selection approach.

Identification of resistant sources from Glycine max against soybean cyst nematode

Soybean cyst nematode (SCN, Heterodera glycines, HG) is one of the severe pests in plant-parasitic nematodes, which impairs root development and causes severe losses in soybean production worldwide. Breeding SCN-resistant cultivars is an important measure for securing harvests without affecting the environment, as can be done with pesticides. The majority of genetic resources for plant pest resistances are found in wild or closely related species which are often difficult to use in breeding due to crossing barriers or close linkage with unfavorable agronomic traits. In this study, 12 soybean cultivars were evaluated for their marker haplotype at the rhg1 and Rhg4 SCN resistance loci and their SCN resistance tested against multiple races in environmentally controlled bioassays. The results showed that all 12 cultivars displayed Peking-type resistance marker haplotypes and all of them proved to be resistant to multiple SCN races. These cultivars provide potential for improving H. glycines resistance of soybean as donor parent in breeding and can contribute to reduce SCN field populations as part of a sustainable agriculture management.

The soybean ubiquitin-proteasome system: Current knowledge and future perspective

Increasing soybean [Glycine max (L.) Merr.] yield has become a worldwide scientific problem in the world. Many studies have shown that ubiquitination plays a key role in stress response and yield formation. In the UniProtKB database, 2,429 ubiquitin-related proteins were predicted in soybean, however, <20 were studied. One key way to address this lack of progress in increasing soybean yield will be a deeper understanding of the ubiquitin-proteasome system (UPS) in soybean. In this review, we summarized the current knowledge about soybean ubiquitin-related proteins and discussed the method of combining phenotype, mutant library, transgenic system, genomics, and proteomics approaches to facilitate the exploration of the soybean UPS. We also proposed the strategy of applying the UPS in soybean improvement based on related studies in model plants. Our review will be helpful for soybean scientists to learn current research progress of the soybean UPS and further lay a theoretical reference for the molecular improvement of soybean in future research by use of this knowledge.

Understandings and future challenges in soybean functional genomics and molecular breeding

Soybean (Glycine max) is a major source of plant protein and oil. Soybean breeding has benefited from advances in functional genomics. In particular, the release of soybean reference genomes has advanced our understanding of soybean adaptation to soil nutrient deficiencies, the molecular mechanism of symbiotic nitrogen (N) fixation, biotic and abiotic stress tolerance, and the roles of flowering time in regional adaptation, plant architecture, and seed yield and quality. Nevertheless, many challenges remain for soybean functional genomics and molecular breeding, mainly related to improving grain yield through high-density planting, maize-soybean intercropping, taking advantage of wild resources, utilization of heterosis, genomic prediction and selection breeding, and precise breeding through genome editing. This review summarizes the current progress in soybean functional genomics and directs future challenges for molecular breeding of soybean.

Improvement of Soybean; A Way Forward Transition from Genetic Engineering to New Plant Breeding Technologies

Soybean is considered one of the important crops among legumes. Due to high nutritional contents in seed (proteins, sugars, oil, fatty acids, and amino acids), soybean is used globally for food, feed, and fuel. The primary consumption of soybean is vegetable oil and feed for chickens and livestock. Apart from this, soybean benefits soil fertility by fixing atmospheric nitrogen through root nodular bacteria. While conventional breeding is practiced for soybean improvement, with the advent of new biotechnological methods scientists have also engineered soybean to improve different traits (herbicide, insect, and disease resistance) to fulfill consumer requirements and to meet the global food deficiency. Genetic engineering (GE) techniques such as transgenesis and gene silencing help to minimize the risks and increase the adaptability of soybean. Recently, new plant breeding technologies (NPBTs) emerged such as zinc-finger nucleases, transcription activator-like effector nucleases, and Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR/Cas9), which paved the way for enhanced genetic modification of soybean. These NPBTs have the potential to improve soybean via gene functional characterization precision genome engineering for trait improvement. Importantly, these NPBTs address the ethical and public acceptance issues related to genetic modifications and transgenesis in soybean. In the present review, we summarized the improvement of soybean through GE and NPBTs. The valuable traits that have been improved through GE for different constraints have been discussed. Moreover, the traits that have been improved through NPBTs and potential targets for soybean improvements via NPBTs and solutions for ethical and public acceptance are also presented.

Characterization of Virulence Phenotypes of Heterodera glycines during 2020 in Indiana

The soybean cyst nematode (SCN, Heterodera glycines) is the most yield-limiting pathogen of soybean in the US. This study was carried out in order to provide updated information on SCN virulence phenotypes in Indiana. A total of 124 soil samples were collected from soybean fields in 2020 and all of them tested positive for SCN. The virulence phenotypes of 42 representative SCN populations were determined with seven soybean indicator lines using the standard HG type test. The most predominant HG types were 2.5.7 and 1.2.5.7, which accounted for 64% and 14% of the SCN populations tested, respectively. None of the SCN populations tested were rated as HG type 0, compared with 28% of the populations in a previous survey in Indiana during 2006-2008. Nearly 88% of the SCN populations evaluated in this study overcame the resistance provided by PI 88788, which is the most common source of resistance in soybean, up from 56% in the 2006-2008 survey. Approximately 14% of SCN populations tested were virulent to PI 548402 (Peking), in contrast to 0% in the 2006-2008 survey. This study reveals a trend of increasing virulence of SCN populations to resistant sources of soybean in Indiana. The results highlighted the importance of rotating soybean varieties with different types of resistance and identifying new sources of resistance for sustainable management of SCN.

Interactions Among Heterodera glycines, Macrophomina phaseolina, and Soybean Genotype

Heterodera glycines, the soybean cyst nematode (SCN), and fungal pathogen Macrophomina phaseolina are economically important soybean pathogens that may coinfest fields. Resistance remains the most effective management tactic for SCN, and the rhg1-b resistance allele derived from plant introduction 88788 is most commonly deployed in the northern United States. The concomitant effects of SCN and M. phaseolina on soybean performance, as well as the effect of the rhg1-b allele in two different genetic backgrounds, were evaluated in three environments (during 2013 to 2015) and a greenhouse bioassay. Within two soybean populations, half of the lines had the rhg1-b allele, and the other half had the susceptible allele in the backgrounds of the cultivars IA3023 and LD00-3309. Significant interactions between soybean rhg1-b allele and M. phaseolina-infested plots were observed in 2014. In all experiments, initial SCN populations (Pi) and M. phaseolina in roots were associated with reduced soybean yield. SCN reproduction factor (RF = final population/Pi) was affected by SCN Pi, rhg1-b, and genetic background. A background-by-genotype interaction on yield was observed only in 2015, with a stronger rhg1-b effect in the LD00-3309 background, which suggested that the susceptible parent 'IA3023' is tolerant to SCN. SCN female index from greenhouse experiments was compared with field RF, and Lin's concordance and Pearson's correlation coefficients decreased with increasing field SCN Pi in soil. In this study, both SCN and M. phaseolina reduced soybean yield asymptomatically, and the impact of SCN rhg1-b resistance was dependent on SCN virulence but also population density.

Quantitative disease resistance: Multifaceted players in plant defense

In contrast to large-effect qualitative disease resistance, quantitative disease resistance (QDR) exhibits partial and generally durable resistance and has been extensively utilized in crop breeding. The molecular mechanisms underlying QDR remain largely unknown but considerable progress has been made in this area in recent years. In this review, we summarize the genes that have been associated with plant QDR and their biological functions. Many QDR genes belong to the canonical resistance gene categories with predicted functions in pathogen perception, signal transduction, phytohormone homeostasis, metabolite transport and biosynthesis, and epigenetic regulation. However, other "atypical" QDR genes are predicted to be involved in processes that are not commonly associated with disease resistance, such as vesicle trafficking, molecular chaperones, and others. This diversity of function for QDR genes contrasts with qualitative resistance, which is often based on the actions of nucleotide-binding leucine-rich repeat (NLR) resistance proteins. An understanding of the diversity of QDR mechanisms and of which mechanisms are effective against which classes of pathogens will enable the more effective deployment of QDR to produce more durably resistant, resilient crops.

Weighted gene co-expression network analysis identifies genes related to HG Type 0 resistance and verification of hub gene GmHg1

INTRODUCTION

The soybean cyst nematode (SCN) is a major disease in soybean production thatseriously affects soybean yield. At present, there are no studies on weighted geneco-expression network analysis (WGCNA) related to SCN resistance.

METHODS

Here, transcriptome data from 36 soybean roots under SCN HG Type 0 (race 3) stresswere used in WGCNA to identify significant modules.

RESULTS AND DISCUSSION

A total of 10,000 differentially expressed genes and 21 modules were identified, of which the module most related to SCN was turquoise. In addition, the hub gene GmHg1 with high connectivity was selected, and its function was verified. GmHg1 encodes serine/threonine protein kinase (PK), and the expression of GmHg1 in SCN-resistant cultivars ('Dongnong L-204') and SCN-susceptible cultivars ('Heinong 37') increased significantly after HG Type 0 stress. Soybean plants transformed with GmHg1-OX had significantly increased SCN resistance. In contrast, the GmHg1-RNAi transgenic soybean plants significantly reduced SCN resistance. In transgenic materials, the expression patterns of 11 genes with the same expression trend as the GmHg1 gene in the 'turquoise module' were analyzed. Analysis showed that 11genes were co-expressed with GmHg1, which may be involved in the process of soybean resistance to SCN. Our work provides a new direction for studying the Molecular mechanism of soybean resistance to SCN.

Transcriptome analysis of aphid-resistant and susceptible near isogenic lines reveals candidate resistance genes in cowpea (Vigna unguiculata)

BACKGROUND

Cowpea (Vigna unguiculata) is a crucial crop for regions of the world that are prone to both heat and drought; however, the phytotoxic cowpea aphid (Aphis craccivora) impairs plant physiology at low population levels. Both antibiotic and antixenotic forms of resistance to the aphid have been mapped to two quantitative trait loci (QTLs) and near isogenic lines (NILs). The molecular mechanism for this resistance response remains unknown.

RESULTS

To understand the genes underlying susceptibility and resistance, two cowpea lines with shared heritage were infested along a time course and characterized for transcriptome variation. Aphids remodeled cowpea development and signaling relative to host plant resistance and the duration of feeding, with resource acquisition and mobilization determining, in part, susceptibility to aphid attack. Major differences between the susceptible and resistant cowpea were identified including two regions of interest housing the most genetic differences between the lines. Candidate genes enabling aphid resistance include both conventional resistance genes (e.g., leucine rich repeat protein kinases) as well as multiple novel genes with no known orthologues.

CONCLUSIONS

Our results demonstrate that feeding by the cowpea aphid globally remodels the transcriptome of cowpea, but how this occurs depends on both the duration of feeding and host-plant resistance. Constitutive expression profiles of the resistant genotype link aphid resistance to a finely-tuned resource management strategy that ultimately reduces damage (e.g., chlorosis) and delays cell turnover, while impeding aphid performance. Thus, aphid resistance in cowpea is a complex, multigene response that involves crosstalk between primary and secondary metabolism.