Premise: Wild species are strategic sources of valuable traits to be introduced into crops through hybridization. For peanut, the 33 currently described wild species in the section Arachis are particularly important because of their sexual compatibility with the domesticated species, Arachis hypogaea. Although numerous wild accessions are carefully preserved in seed banks, their morphological similarities pose challenges to routine classification.Methods: Using a high‐density array, we genotyped 272 accessions encompassing all diploid species in section Arachis. Detailed relationships between accessions and species were revealed through phylogenetic analyses and interpreted using the expertise of germplasm collectors and curators.Results: Two main groups were identified: one with A genome species and the other with B, D, F, G, and K genomes. Species groupings generally showed clear boundaries. Structure within groups was informative, for instance, revealing the history of the proto‐domesticate A. stenosperma. However, some groupings suggested multiple sibling species. Others were polyphyletic, indicating the need for taxonomic revision. Annual species were better defined than perennial ones, revealing limitations in applying classical and phylogenetic species concepts to the genus. We suggest new species assignments for several accessions.Conclusions: Curated by germplasm collectors and curators, this analysis of species relationships lays the foundation for future species descriptions, classification of unknown accessions, and germplasm use for peanut improvement. It supports the conservation and curation of current germplasm, both critical tasks considering the threats to the genus posed by habitat loss and the current restrictions on new collections and germplasm transfer.

Cowpea (Vigna unguiculata L. Walp., 2n = 2x = 22) is a protein-rich crop that complements staple cereals for humans and serves as fodder for livestock. It is widely grown in Africa and other developing countries as the primary source of protein in the diet; therefore, it is necessary to identify the protein-related loci to improve cowpea breeding. In the current study, we conducted a genome-wide association study (GWAS) on 161 cowpea accessions (151 USDA germplasm plus 10 Arkansas breeding lines) with a wide range of seed protein contents (21.8~28.9%) with 110,155 high-quality whole-genome single-nucleotide polymorphisms (SNPs) to identify markers associated with protein content, then performed genomic prediction (GP) for future breeding. A total of seven significant SNP markers were identified using five GWAS models (single-marker regression (SMR), the general linear model (GLM), Mixed Linear Model (MLM), Fixed and Random Model Circulating Probability Unification (FarmCPU), and Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK), which are located at the same locus on chromosome 8 for seed protein content. This locus was associated with the gene Vigun08g039200, which was annotated as the protein of the thioredoxin superfamily, playing a critical function for protein content increase and nutritional quality improvement. In this study, a genomic prediction (GP) approach was employed to assess the accuracy of predicting seed protein content in cowpea. The GP was conducted using cross-prediction with five models, namely ridge regression best linear unbiased prediction (rrBLUP), Bayesian ridge regression (BRR), Bayesian A (BA), Bayesian B (BB), and Bayesian least absolute shrinkage and selection operator (BL), applied to seven random whole genome marker sets with different densities (10 k, 5 k, 2 k, 1 k, 500, 200, and 7), as well as significant markers identified through GWAS. The accuracies of the GP varied between 42.9% and 52.1% across the seven SNPs considered, depending on the model used. These findings not only have the potential to expedite the breeding cycle through early prediction of individual performance prior to phenotyping, but also offer practical implications for cowpea breeding programs striving to enhance seed protein content and nutritional quality.

Cowpea is one of the most popular dry-land legumes cultivated for food and forage in arid and semi-arid areas. Genetic diversity for global germplasm can be organized into core collections providing optimum resources to serve breeding requirements. Here, we present diversity analysis and genome-wide association study (GWAS) results for part of the cowpea core collection of the United States Department of Agriculture (USDA) along with breeding line controls. Included in the analysis were a total of 373 accessions analyzed with 6880 Single Nucleotide Polymorphism (SNP) markers from Genotyping by Sequencing (GBS). Population structure differentiated accessions into two groups irrespective of geographical origin and formed three clusters based on taxa upon phylogenetic analysis. A total of 56 SNPs were significantly associated to nine traits including pod length (25 Quantitative Trait Nucleotides, QTNs), seed anti-oxidant content (7 QTNs), dry pod color (7 QTNs), plant maturity (5 QTNs), flower color (5 QTNs), seed weight (4 QTNs), tolerance to low phosphate (1 QTN), growth habit (1 QTN), and response to rock phosphate (1 QTN) using Bayesian-information, Linkage-disequilibrium Iteratively Nested Keyway (BLINK), and Fixed and random model Circulating Probability Unification (FarmCPU) association models. Key genes related to all significant SNPs were identified based on annotations of the cowpea reference genome, including a flavonoid gene controlling flower color (Vigun08g040200.1), a root nodulation regulator for tolerance to low phosphate (Vigun11g168000.1), and numerous genes involved in signaling, biosynthesis, metabolite transport, and abiotic stress. Our results highlight the importance of maintaining public phenotyping databases at USDA and strengthening collaborations for data collection in cowpea to maximize research impacts.

The genetic diversity that exists in natural populations of Arachis duranensis, the wild diploid donor of the A subgenome of cultivated tetraploid peanut, has the potential to improve crop adaptability, resilience to major pests and diseases, and drought tolerance. Despite its potential value for peanut improvement, limited research has been focused on the association between allelic variation, environmental factors, and response to early (ELS) and late leaf spot (LLS) diseases. The present study implemented a landscape genomics approach to gain a better understanding of the genetic variability of A. duranensis represented in the ex-situ peanut germplasm collection maintained at the U.S. Department of Agriculture, which spans the entire geographic range of the species in its center of origin in South America. A set of 2810 single nucleotide polymorphism (SNP) markers allowed a high-resolution genome-wide characterization of natural populations. The analysis of population structure showed a complex pattern of genetic diversity with five putative groups. The incorporation of bioclimatic variables for genotype-environment associations, using the latent factor mixed model (LFMM2) method, provided insights into the genomic signatures of environmental adaptation, and led to the identification of SNP loci whose allele frequencies were correlated with elevation, temperature, and precipitation-related variables (q < 0.05). The LFMM2 analysis for ELS and LLS detected candidate SNPs and genomic regions on chromosomes A02, A03, A04, A06, and A08. These findings highlight the importance of the application of landscape genomics in ex situ collections of peanut and other crop wild relatives to effectively identify favorable alleles and germplasm for incorporation into breeding programs. We report new sources of A. duranensis germplasm harboring adaptive allelic variation, which have the potential to be utilized in introgression breeding for a single or multiple environmental factors, as well as for resistance to leaf spot diseases.

Groundnut bud necrosis orthotospovirus (GBNV), a tripartite single-stranded RNA virus, poses a significant threat to United States agriculture. GBNV is a quarantine pathogen, and its introduction could lead to severe damage to economically important crops, such as groundnuts, tomatoes, potatoes, peas, and soybeans. For the rapid and accurate detection of GBNV at points of entry, TaqMan reverse transcriptase–quantitative polymerase chain reaction (RT-qPCR) assays were developed and the results validated using conventional reverse transcriptase–polymerase chain reaction (RT-PCR) followed by Sanger sequencing. These assays target highly conserved regions of the nucleocapsid (NP) and movement (MP) proteins within the viral genome. Multiplex GBNV detection assays targeting the NP and MP genes, as well as an internal control plant gene, ACT11, showed efficiency rates between 90% and 100% and R² values of 0.98 to 0.99, indicating high accuracy and precision. Moreover, there was no significant difference in sensitivity between multiplex and singleplex assays, ensuring reliable detection across various plant tissues. This rapid, sensitive, and specific diagnostic assay will provide a valuable tool at ports of entry to prevent the entry of GBNV into the United States.