BackgroundCultivated peanut, or groundnut (Arachis hypogaea L.), is an important oilseed crop with an allotetraploid genome (AABB, 2n = 4x = 40). In recent years, many efforts have been made to construct linkage maps in cultivated peanut, but almost all of these maps were constructed using low-throughput molecular markers, and most show a low density, directly influencing the value of their applications. With advances in next-generation sequencing (NGS) technology, the construction of high-density genetic maps has become more achievable in a cost-effective and rapid manner. The objective of this study was to establish a high-density single nucleotide polymorphism (SNP)-based genetic map for cultivated peanut by analyzing next-generation double-digest restriction-site-associated DNA sequencing (ddRADseq) reads.ResultsWe constructed reduced representation libraries (RRLs) for two A. hypogaea lines and 166 of their recombinant inbred line (RIL) progenies using the ddRADseq technique. Approximately 175 gigabases of data containing 952,679,665 paired-end reads were obtained following Solexa sequencing. Mining this dataset, 53,257 SNPs were detected between the parents, of which 14,663 SNPs were also detected in the population, and 1,765 of the obtained polymorphic markers met the requirements for use in the construction of a genetic map. Among 50 randomly selected in silico SNPs, 47 were able to be successfully validated. One linkage map was constructed, which was comprised of 1,685 marker loci, including 1,621 SNPs and 64 simple sequence repeat (SSR) markers. The map displayed a distribution of the markers into 20 linkage groups (LGs A01–A10 and B01–B10), spanning a distance of 1,446.7 cM. The alignment of the LGs from this map was shown in comparison with a previously integrated consensus map from peanut.ConclusionsThis study showed that the ddRAD library combined with NGS allowed the rapid discovery of a large number of SNPs in the cultivated peanut. The first high density SNP-based linkage map for A. hypogaea was generated that can serve as a reference map for cultivated Arachis species and will be useful in genetic mapping. Our results contribute to the available molecular marker resources and to the assembly of a reference genome sequence for the peanut.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-351) contains supplementary material, which is available to authorized users.

Key messageSSR-based QTL mapping provides useful information for map-based cloning of major QTLs and can be used to improve the agronomic and quality traits in cultivated peanut by marker-assisted selection.AbstractCultivated peanut (Arachis hypogaea L.) is an allotetraploid species (AABB, 2n = 4× = 40), valued for its edible oil and digestible protein. Linkage mapping has been successfully conducted for most crops, and it has been applied to detect the quantitative trait loci (QTLs) of biotic and abiotic traits in peanut. However, the genetic basis of agronomic and quality-related traits remains unclear. In this study, high levels of phenotypic variation, broad-sense heritability and significant correlations were observed for agronomic and quality-related traits in an F2:3 population. A genetic linkage map was constructed for cultivated peanut containing 470 simple sequence repeat (SSR) loci, with a total length of 1877.3 cM and average distance of 4.0 cM between flanking markers. For 10 agronomic traits, 24 QTLs were identified and each QTL explained 1.69–18.70 % of the phenotypic variance. For 8 quality-related traits, 12 QTLs were identified that explained 1.72–20.20 % of the phenotypic variance. Several QTLs for multiple traits were overlapped, reflecting the phenotypic correlation between these traits. The majority of QTLs exhibited obvious dominance or over-dominance effects on agronomic and quality traits, highlighting the importance of heterosis for breeding. A comparative analysis revealed genomic duplication and arrangement of peanut genome, which aids the assembly of scaffolds in genomic sequencing of Arachishypogaea. Our QTL analysis results enabled us to clearly understand the genetic base of agronomic and quality traits in cultivated peanut, further accelerating the progress of map-based cloning of major QTLs and marker-assisted selection in future breeding.Electronic supplementary materialThe online version of this article (doi:10.1007/s00122-015-2493-1) contains supplementary material, which is available to authorized users.

Association mapping is a powerful approach for exploring the molecular basis of phenotypic variations in plants. A peanut (Arachis hypogaea L.) mini-core collection in China comprising 298 accessions was genotyped using 109 simple sequence repeat (SSR) markers, which identified 554 SSR alleles and phenotyped for 15 agronomic traits in three different environments, exhibiting abundant genetic and phenotypic diversity within the panel. A model-based structure analysis assigned all accessions to three groups. Most of the accessions had the relative kinship of less than 0.05, indicating that there were no or weak relationships between accessions of the mini-core collection. For 15 agronomic traits in the peanut panel, generally the Q + K model exhibited the best performance to eliminate the false associated positives compared to the Q model and the general linear model-simple model. In total, 89 SSR alleles were identified to be associated with 15 agronomic traits of three environments by the Q + K model-based association analysis. Of these, eight alleles were repeatedly detected in two or three environments, and 15 alleles were commonly detected to be associated with multiple agronomic traits. Simple sequence repeat allelic effects confirmed significant differences between different genotypes of these repeatedly detected markers. Our results demonstrate the great potential of integrating the association analysis and marker-assisted breeding by utilizing the peanut mini-core collection.

Late leaf spot (LLS) is one of the most serious foliar diseases affecting peanut worldwide leading to huge yield loss. To understand the genetic basis of LLS and assist breeding in the future, we conducted quantitative trait locus (QTL) analysis for LLS and three plant-type-related traits including height of main stem (HMS), length of the longest branch (LLB) and total number of branches (TNB). Significant negative correlations were observed between LLS and the plant-type-related traits in multi-environments of a RIL population from the cross Zhonghua 5 and ICGV 86699. A total of 20 QTLs were identified for LLS, of which two QTLs were identified in multi-environments and six QTLs with phenotypic variation explained (PVE) more than 10%. Ten, seven, fifteen QTLs were identified for HMS, LLB and TNB, respectively. Of these, one, one, two consensus QTLs and three, two, three major QTLs were detected for HMS, LLB and TNB, respectively. Of all 52 unconditional QTLs for LLS and plant-type-related traits, 10 QTLs were clustered in five genetic regions, of which three clusters including five robust major QTLs overlapped between LLS and one of the plant-type-related traits, providing evidence that the correlation could be genetically constrained. On the other hand, conditional mapping revealed different numbers and different extent of additive effects of QTLs for LLS conditioned on three plant-type-related traits (HMS, LLB and TNB), which improved our understanding of interrelationship between LLS and plant-type-related traits at the QTL level. Furthermore, two QTLs, qLLSB6-7 and qLLSB1 for LLS resistance, were identified residing in two clusters of NB-LRR—encoding genes. This study not only provided new favorable QTLs for fine-mapping, but also suggested that the relationship between LLS and plant-type-related traits of HMS, LLB and TNB should be considered while breeding for improved LLS resistance in peanut.

Cultivated peanut (Arachis hypogaea L.) is an allotetraploid (AABB, 2n = 4x = 40), valued for its edible oil and digestible protein. Seed size and weight are important agronomical traits significantly influence the yield and nutritional composition of peanut. However, the genetic basis of seed-related traits remains ambiguous. Association mapping is a powerful approach for quickly and efficiently exploring the genetic basis of important traits in plants. In this study, a total of 104 peanut accessions were used to identify molecular markers associated with seed-related traits using 554 single-locus simple sequence repeat (SSR) markers. Most of the accessions had no or weak relationship in the peanut panel. The linkage disequilibrium (LD) decayed with the genetic distance of 1cM at the genome level and the LD of B subgenome decayed faster than that of the A subgenome. Large phenotypic variation was observed for four seed-related traits in the association panel. Using mixed linear model with population structure and kinship, a total of 30 significant SSR markers were detected to be associated with four seed-related traits (P < 1.81 × 10-3) in different environments, which explained 11.22–32.30% of the phenotypic variation for each trait. The marker AHGA44686 was simultaneously and repeatedly associated with seed length and hundred-seed weight in multiple environments with large phenotypic variance (26.23 ∼ 32.30%). The favorable alleles of associated markers for each seed-related trait and the optimal combination of favorable alleles of associated markers were identified to significantly enhance trait performance, revealing a potential of utilization of these associated markers in peanut breeding program.

No abstract

Cultivated peanut (Arachis hypogaea L.) is one of the most important oilseed crops worldwide. Pod-related traits, including pod length (PL), pod width (PW), ratio of PL to PW (PL/W) and 100-pod weight (100-PW), are crucial factors for pod yield and are key target traits for selection in peanut breeding. However, the studies on the natural variation and genetic mechanism of pod-related traits are not clear in peanut. In this study, we phenotyped 136 peanut accessions for four pod-related traits in two consecutive years and genotyped the population using a re-sequencing technique. Based on 884,737 high-quality single nucleotide polymorphisms (SNPs), genome-wide association studies (GWAS) were conducted for four pod-related traits using a fixed and random model uniform cyclic probability (FarmCPU) model. The results showed that a total of 36 SNPs were identified by GWAS, among which twenty-one, fourteen and one SNPs were significantly associated with PL, PL/W and 100-PW, respectively. The candidate regions where the four peak SNPs (10_76084075, 11_138356586, 16_64420451, and 18_126782541) were located were used for searching genes, and nineteen candidate genes for pod-related traits were preliminarily predicted based on functional annotations. In addition, we also compared the expression patterns of these nineteen candidate genes in different tissues of peanut, and we found that eight genes were specifically highly expressed in tender fruit, immature pericarp, or seed, so we considered these genes to be the potential candidate genes for pod-related traits. These results enriched the understanding of the genetic basis of pod-related traits and provided an important theoretical basis for subsequent gene cloning and marker-assisted selection (MAS) breeding in peanut.