Peanut (Arachis hypogaea L.) is one of the most important oilseed and nutritional crops in the world. To efficiently utilize the germplasm collection, a peanut mini-core containing 112 accessions was established in the United States. To determine the population structure and its impact on marker-trait association, this mini-core collection was assessed by genotyping 94 accessions with 81 SSR markers and two functional SNP markers from fatty acid desaturase 2 (FAD2). Seed quality traits (including oil content, fatty acid composition, flavonoids, and resveratrol) were obtained through nuclear magnetic resonance (NMR), gas chromatography (GC), and high-performance liquid chromatography (HPLC) analysis. Genetic diversity and population structure analysis identified four major subpopulations that are related to four botanical varieties. Model comparison with different levels of population structure and kinship control was conducted for each trait and association analyses with the selected models verified that the functional SNP from the FAD2A gene is significantly associated with oleic acid (C18:1), linoleic acid (C18:2), and oleic-to-linoleic (O/L) ratio across this diverse collection. Even though the allele distribution of FAD2A was structured among the four subpopulations, the effect of FAD2A gene remained significant after controlling population structure and had a likelihood-ratio-based R ( 2 ) (R ( LR ) ( 2 ) ) value of 0.05 (oleic acid), 0.09 (linoleic acid), and 0.07 (O/L ratio) because the FAD2A alleles were not completely fixed within subpopulations. Our genetic analysis demonstrated that this peanut mini-core panel is suitable for association mapping. Phenotypic characterization for seed quality traits and association testing of the functional SNP from FAD2A gene provided information for further breeding and genetic research.

BackgroundCultivated soybean (Glycine max) is a major agricultural crop that provides a crucial source of edible protein and oil. Decreased amounts of saturated palmitic acid and increased amounts of unsaturated oleic acid in soybean oil are considered optimal for human cardiovascular health and therefore there has considerable interest by breeders in discovering genes affecting the relative concentrations of these fatty acids. Using a genome-wide association (GWA) approach with nearly 30,000 single nucleotide polymorphisms (SNPs), we investigated the genetic basis of protein, oil and all five fatty acid levels in seeds from a sample of 570 wild soybeans (Glycine soja), the progenitor of domesticated soybean, to identify quantitative trait loci (QTLs) affecting these seed composition traits.ResultsWe discovered 29 SNPs located on ten different chromosomes that are significantly associated with the seven seed composition traits in our wild soybean sample. Eight SNPs co-localized with QTLs previously uncovered in linkage or association mapping studies conducted with cultivated soybean samples, while the remaining SNPs appeared to be in novel locations. Twenty-four of the SNPs significantly associated with fatty acid variation, with the majority located on chromosomes 14 (6 SNPs) and seven (8 SNPs). Two SNPs were common for two or more fatty acids, suggesting loci with pleiotropic effects. We also identified some candidate genes that are involved in fatty acid metabolism and regulation. For each of the seven traits, most of the SNPs produced differences between the average phenotypic values of the two homozygotes of about one-half standard deviation and contributed over 3% of their total variability.ConclusionsThis is the first GWA study conducted on seed composition traits solely in wild soybean populations, and a number of QTLs were found that have not been previously discovered. Some of these may be useful to breeders who select for increased protein/oil content or altered fatty acid ratios in the seeds. The results also provide additional insight into the genetic architecture of these traits in a large sample of wild soybean, and suggest some new candidate genes whose molecular effects on these traits need to be further studied.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3397-4) contains supplementary material, which is available to authorized users.

Peanut seeds contain high amounts of oil and protein as well as some useful bioactive phytochemicals which can contribute to human health. The U.S. peanut mini-core collection is an important genetic resource for improving seed quality and developing new cultivars. Variability of seed chemical composition within the mini-core was evaluated from freshly harvested seeds for two years. Oil, fatty acid composition, and flavonoid/resveratrol content were quantified by NMR, GC, and HPLC, respectively. Significant variability was detected in seed chemical composition among accessions and botanical varieties. Accessions were further genotyped with a functional SNP marker from the FAD2A gene using real-time PCR and classified into three genotypes with significantly different O/L ratios: wild type (G/G with a low O/L ratio <1.7), heterozygote (G/A with O/L ratio >1.4 but <1.7), and mutant (A/A with a high O/L ratio >1.7). The results from real-time PCR genotyping and GC fatty acid analysis were consistent. Accessions with high amounts of oil, quercetin, high seed weight, and O/L ratio were identified. The results from this study may be useful not only for peanut breeders, food processors, and product consumers to select suitable accessions or cultivars but also for curators to potentially expand the mini-core collection.

Roots are a vital organ for absorbing soil moisture and nutrients and influence drought resistance. The identification of quantitative trait loci (QTLs) with molecular markers may allow the estimation of parameters of genetic architecture and improve root traits by molecular marker-assisted selection (MAS). A mapping population of 120 recombinant inbred lines (RILs) derived from a cross between japonica upland rice 'IRAT109' and paddy rice 'Yuefu' was used for mapping QTLs of developmental root traits. All plant material was grown in PVC-pipe. Basal root thickness (BRT), root number (RN), maximum root length (MRL), root fresh weight (RFW), root dry weight (RDW) and root volume (RV) were phenotyped at the seedling (I), tillering (II), heading (III), grain filling (IV) and mature (V) stages, respectively. Phenotypic correlations showed that BRT was positively correlated to MRL at the majority of stages, but not correlated with RN. MRL was not correlated to RN except at the seedling stage. BRT, MRL and RN were positively correlated to RFW, RDW and RV at all growth stages. QTL analysis was performed using QTLMapper 1.6 to partition the genetic components into additive-effect QTLs, epistatic QTLs and QTL-by-year interactions (Q x E) effect. The results indicated that the additive effects played a major role for BRT, RN and MRL, while for RFW, RDW and RV the epistatic effects showed an important action and Q x E effect also played important roles in controlling root traits. A total of 84 additive-effect QTLs and 86 pairs of epistatic QTLs were detected for the six root traits at five stages. Only 12 additive QTLs were expressed in at least two stages. This indicated that the majority of QTLs were developmental stage specific. Two main effect QTLs, brt9a and brt9b, were detected at the heading stage and explained 19% and 10% of the total phenotypic variation in BRT without any influence from the environment. These QTLs can be used in breeding programs for improving root traits.