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The fatty acid composition of seed oil is a major determinant of the flavor, shelf-life, and nutritional quality of peanuts. Major QTLs controlling high oil content, high oleic content, and low linoleic content have been characterized in several seed oil crop species. Here we employ genome-wide association approaches on a recently genotyped collection of 787 plant introduction accessions in the USDA peanut core collection, plus selected improved cultivars, to discover markers associated with the natural variation in fatty acid composition, and to explain the genetic control of fatty acid composition in seed oils.Overall, 251 single nucleotide polymorphisms (SNPs) had significant trait associations with the measured fatty acid components. Twelve SNPs were associated with two or three different traits. Of these loci with apparent pleiotropic effects, 10 were associated with both oleic (C18:1) and linoleic acid (C18:2) content at different positions in the genome. In all 10 cases, the favorable allele had an opposite effect - increasing and lowering the concentration, respectively, of oleic and linoleic acid. The other traits with pleiotropic variant control were palmitic (C16:0), behenic (C22:0), lignoceric (C24:0), gadoleic (C20:1), total saturated, and total unsaturated fatty acid content. One hundred (100) of the significantly associated SNPs were located within 1000 kbp of 55 genes with fatty acid biosynthesis functional annotations. These genes encoded, among others: ACCase carboxyl transferase subunits, and several fatty acid synthase II enzymes.With the exception of gadoleic (C20:1) and lignoceric (C24:0) acid content, which occur at relatively low abundance in cultivated peanut, all traits had significant SNP interactions exceeding a stringent Bonferroni threshold (α = 1%). We detected 7,682 pairwise SNP interactions affecting the relative abundance of fatty acid components in the seed oil. Of these, 627 SNP pairs had at least one SNP within 1000 kbp of a gene with fatty acid biosynthesis functional annotation. We evaluated 168 candidate genes underlying these SNP interactions. Functional enrichment and protein-to-protein interactions supported significant interactions (p- value < 1.0E-16) among the genes evaluated. These results show the complex nature of the biology and genes underlying the variation in seed oil fatty acid composition and contribute to an improved genotype-to-phenotype map for fatty acid variation in peanut seed oil.Key phrasesSNP Genotyping, Genome-wide Association Study (GWAS), GWAS of interacting SNPs (GWASi), Pleiotropy, Seed fatty acid composition, Oleic-Linoleic acid ratio.

Cultivated peanut (Arachis hypogaea) is an important oil, food, and feed crop worldwide. The USDA peanut germplasm collection currently contains 8,982 accessions. In the 1990s, 812 accessions were selected as a core collection on the basis of phenotype and country of origin. The present study reports genotyping results for the entire available core collection. Each accession was genotyped with the Arachis_Axiom2 SNP array, yielding 14,430 high-quality, informative SNPs across the collection. Additionally, a subset of 253 accessions was replicated, using between two and five seeds per accession, to assess heterogeneity within these accessions. the genotypic diversity of the core is mostly captured in five genotypic clusters, which have some correspondence with botanical variety and market type. There is little genetic clustering by country of origin, reflecting peanut’s rapid global dispersion in the 18th and 19th centuries. A genetic cluster associated with the hypogaea/aequatoriana/peruviana varieties, with accessions coming primarily from Bolivia, Peru, and Ecuador, is consistent with these having been the earliest landraces. The genetics, phenotypic characteristics, and biogeography are all consistent with previous reports of tetraploid peanut originating in Southeast Bolivia. Analysis of the genotype data indicates an early genetic radiation, followed by regional distribution of major genetic classes through South America, and then a global dissemination that retains much of the early genetic diversity in peanut. Comparison of the genotypic data relative to alleles from the diploid progenitors also indicates that subgenome exchanges, both large and small, have been major contributors to the genetic diversity in peanut.All data is available at the National Ag Library: https://doi.org/10.15482/USDA.ADC/1518508 and at PeanutBase: https://peanutbase.org/data/public/Arachis_hypogaea/mixed.esm.KNWV

Common bean (Phaseolus vulgaris L.) is the most important food legume crop in Africa and Latin America where rainfall pattern is unpredictable. The objectives were to identify better yielding common bean lines with good canning quality under drought, and to identify traits that could be used as selection criteria for evaluating drought-tolerant genotypes. In all, 35 advanced lines were developed through single seed descent and evaluated with a standard check under drought and irrigated conditions at two locations over 2 years in Ethiopia. Grain yield (GY), pod number per m2, seed number per m2 and seed weight decreased by 56%, 47%, 49% and 14%, respectively, under drought stress. Eight genotypes had better yield with good canning quality under drought compared to the check. Moderate to high proportion of genetic effects were observed under drought conditions for GY and yield components compared to genotype × environment effects. Significant positive correlations between GY and pod harvest index (PHI) in drought suggest that PHI could be used as an indirect selection criterion for common bean improvement.

Maize breeding efforts to generate high yielding and adaptive cultivars have recently been given emphasis by national maize breeding program. In Ethiopia, the maize production system is mainly dominated by subsistence farmers where their production is below average. The objectives of this study were to determine the combining ability between lines and testers, and to evaluate the performance of crosses (hybrids) and parents for grain yield and yield component traits. Twenty-seven inbred lines were generated by crossing nine female lines (L1-L9) and three male testers (T1-T3) using line × tester mating system at International Maize and Wheat Improvement Center (CIMMYT), East African high land maize improvement program. The inbred lines along with parents were evaluated in randomized complete block design with two replications at three locations (Ambo, Kulumsa and Haramaya). Significant differences were observed among genotypes for all ten traits considered. Eight crosses (L1 × T2, L1 × T3, L3 × T3, L8 × T1, L4 × T2, L9 × T1, L2 × T1, and L2 × T2) had higher yield performance compared to other crosses across environments. Significant mean square differences were found across locations for general combining ability (GCA) due to lines for all traits except for number of kernel rows per ear, whereas GCA due to testers were significant only for grain yield, ear length and 1000-seed weight. Significant mean square due to GCA × Loc (both for lines and testers) was found for days to maturity (38.71*), 1000-seed weight (4582.36**) and grain yield (2756777**), while significant SCA × Loc interaction was found for all traits except number of kernel rows per ear (1.07), ear length (0.79) and ear diameter (0.12), suggesting that the importance of additive and non-additive gene effects in controlling these characters.

Background Due to the recent domestication of peanut from a single tetraploidization event, relatively little genetic diversity underlies the extensive morphological and agronomic diversity in peanut cultivars today. To broaden the genetic variation in future breeding programs, it is necessary to characterize germplasm accessions for new sources of variation and to leverage the power of genome-wide association studies (GWAS) to discover markers associated with traits of interest. We report an analysis of linkage disequilibrium (LD), population structure, and genetic diversity, and examine the ability of GWA to infer marker-trait associations in the U.S. peanut mini core collection genotyped with a 58 K SNP array. Results LD persists over long distances in the collection, decaying to r2 = half decay distance at 3.78 Mb. Structure within the collection is best explained when separated into four or five groups (K = 4 and K = 5). At K = 4 and 5, accessions loosely clustered according to market type and subspecies, though with numerous exceptions. Out of 107 accessions, 43 clustered in correspondence to the main market type subgroup whereas 34 did not. The remaining 30 accessions had either missing taxonomic classification or were classified as mixed. Phylogenetic network analysis also clustered accessions into approximately five groups based on their genotypes, with loose correspondence to subspecies and market type. Genome wide association analysis was performed on these lines for 12 seed composition and quality traits. Significant marker associations were identified for arachidic and behenic fatty acid compositions, which despite having low bioavailability in peanut, have been reported to raise cholesterol levels in humans. Other traits such as blanchability showed consistent associations in multiple tests, with plausible candidate genes. Conclusions Based on GWA, population structure as well as additional simulation results, we find that the primary limitations of this collection for GWAS are a small collection size, significant remaining structure/genetic similarity and long LD blocks that limit the resolution of association mapping. These results can be used to improve GWAS in peanut in future studies – for example, by increasing the size and reducing structure in the collections used for GWAS. Electronic supplementary material The online version of this article (10.1186/s12864-019-5824-9) contains supplementary material, which is available to authorized users.