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.

BackgroundPlant bZIP proteins characteristically harbor a highly conserved bZIP domain with two structural features: a DNA-binding basic region and a leucine (Leu) zipper dimerization region. They have been shown to be diverse transcriptional regulators, playing crucial roles in plant development, physiological processes, and biotic/abiotic stress responses. Despite the availability of six completely sequenced legume genomes, a comprehensive investigation of bZIP family members in legumes has yet to be presented.ResultsIn this study, we identified 428 bZIP genes encoding 585 distinct proteins in six legumes, Glycine max, Medicago truncatula, Phaseolus vulgaris, Cicer arietinum, Cajanus cajan, and Lotus japonicus. The legume bZIP genes were categorized into 11 groups according to their phylogenetic relationships with genes from Arabidopsis. Four kinds of intron patterns (a–d) within the basic and hinge regions were defined and additional conserved motifs were identified, both presenting high group specificity and supporting the group classification. We predicted the DNA-binding patterns and the dimerization properties, based on the characteristic features in the basic and hinge regions and the Leu zipper, respectively, which indicated that some highly conserved amino acid residues existed across each major group. The chromosome distribution and analysis for WGD-derived duplicated blocks revealed that the legume bZIP genes have expanded mainly by segmental duplication rather than tandem duplication. Expression data further revealed that the legume bZIP genes were expressed constitutively or in an organ-specific, development-dependent manner playing roles in multiple seed developmental stages and tissues. We also detected several key legume bZIP genes involved in drought- and salt-responses by comparing fold changes of expression values in drought-stressed or salt-stressed roots and leaves.ConclusionsIn summary, this genome-wide identification, characterization and expression analysis of legume bZIP genes provides valuable information for understanding the molecular functions and evolution of the legume bZIP transcription factor family, and highlights potential legume bZIP genes involved in regulating tissue development and abiotic stress responses.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2258-x) contains supplementary material, which is available to authorized users.

The rational design of nanoscale metal oxides with hollow structures and tunable porosity has stimulated tremendous attention due to their vital importance for practical applications. Here, we report the designed synthesis of ZnO/ZnCoO hollow core-shell nanocages (HCSNCs) through a metal-organic framework (MOF) route. The strategy includes the synthesis of a zeolite imidazolate framework-8 (ZIF-8)/Co-Zn hydroxide core-shell nanostructure precursor and subsequent transformation to ZnO/ZnCoO HCSNCs by thermal annealing of the as-prepared precursor in air. Various techniques were employed for characterization of the structure and morphology of the as-prepared ZnO/ZnCoO HCSNCs. When applied as a gas sensing material, the ZnO/ZnCoO HCSNCs show enhanced sensitivity to xylene when compared with ZnCoO shells as well as ZnO nanocages (NCs). In addition, excellent reversibility and superior selectivity of the sensor were observed. The remarkable enhancement in the gas-sensing properties of the ZnO/ZnCoO HCSNCs is attributed to their unique structure and a synergistic effect of ZnO and ZnCoO.

Co-localized intervals and candidate genes were identified for major and stable QTLs controlling pod weight and size on chromosomes A07 and A05 in an RIL population across four environments. Cultivated peanut (Arachis hypogaea L.) is an important legume crops grown in > 100 countries. Hundred-pod weight (HPW) is an important yield trait in peanut, but its underlying genetic mechanism was not well studied. In this study, a mapping population (Xuhua 13 × Zhonghua 6) with 187 recombinant inbred lines (RILs) was developed to map quantitative trait loci (QTLs) for HPW together with pod length (PL) and pod width (PW) by both unconditional and conditional QTL analyses. A genetic map covering 1756.48 cM was constructed with 817 markers. Additive effects, epistatic interactions, and genotype-by-environment interactions were analyzed using the phenotyping data generated across four environments. Twelve additive QTLs were identified on chromosomes A05, A07, and A08 by unconditional analysis, and five of them (qPLA07, qPLA05.1, qPWA07, qHPWA07.1, and qHPWA05.2) showed major and stable expressions in all environments. Conditional QTL mapping found that PL had stronger influences on HPW than PW. Notably, qHPWA07.1, qPLA07, and qPWA07 that explained 17.93-43.63% of the phenotypic variations of the three traits were co-localized in a 5 cM interval (1.48 Mb in physical map) on chromosome A07 with 147 candidate genes related to catalytic activity and metabolic process. In addition, qHPWA05.2 and qPLA05.1 were co-localized with minor QTL qPWA05.2 to a 1.3 cM genetic interval (280 kb in physical map) on chromosome A05 with 12 candidate genes. This study provides a comprehensive characterization of the genetic components controlling pod weight and size as well as candidate QTLs and genes for improving pod yield in future peanut breeding.

Summary Bacterial wilt, caused by Ralstonia solanacearum, is a devastating disease affecting over 350 plant species. A few peanut cultivars were found to possess stable and durable bacterial wilt resistance (BWR). Genomics‐assisted breeding can accelerate the process of developing resistant cultivars by using diagnostic markers. Here, we deployed sequencing‐based trait mapping approach, QTL‐seq, to discover genomic regions, candidate genes and diagnostic markers for BWR in a recombination inbred line population (195 progenies) of peanut. The QTL‐seq analysis identified one candidate genomic region on chromosome B02 significantly associated with BWR. Mapping of newly developed single nucleotide polymorphism (SNP) markers narrowed down the region to 2.07 Mb and confirmed its major effects and stable expressions across three environments. This candidate genomic region had 49 nonsynonymous SNPs affecting 19 putative candidate genes including seven putative resistance genes (R‐genes). Two diagnostic markers were successfully validated in diverse breeding lines and cultivars and could be deployed in genomics‐assisted breeding of varieties with enhanced BWR.

BackgroundThe cultivated peanut (Arachis hypogaea L.) is an important oil and food crop in the world. Pod- and kernel-related traits are direct factors involved in determining the yield of the peanut. However, the genetic basis underlying pod- and kernel-related traits in the peanut remained largely unknown, which hampered the improvement of peanut through marker-assisted selection. To understand the genetic basis underlying pod- and kernel-related traits in the peanut and provide more useful information for marker-assisted breeding, we conducted quantitative trait locus (QTL) analysis for pod length and width and seed length and width by use of two F2:3 populations derived from cultivar Fuchuan Dahuasheng × ICG 6375 (FI population) and cultivar Xuhua 13 × cultivar Zhonghua 6 (XZ population) in this study.ResultsTwo genetic maps containing 347 and 228 polymorphic markers were constructed for FI and XZ populations respectively. In total, 39 QTLs explaining 1.25–26.11 % of the phenotypic variations were detected in two populations. For the FI population, 26 QTLs were detected between the two environments, among which twelve were not mapped before. For the XZ population, thirteen QTLs were detected, among which eight were not reported before. One QTL for pod width was repeatedly mapped between the two populations.ConclusionThe QTL analyses for pod length and width and seed length and width were conducted in this study using two mapping populations. Novel QTLs were identified, which included two for pod length, four for pod width, five for seed length and one for seed width in the FI population, and three for pod length, three for pod width and two for seed width in the XZ population. Our results will be helpful for improving pod- and seed-related traits in peanuts through marker-assisted selection.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-016-0337-x) contains supplementary material, which is available to authorized users.

One hundred and forty-six highly polymorphic simple sequence repeat (SSR) markers were used to assess the genetic diversity and population structure of 196 peanut (Arachis Hypogaea L.) cultivars which had been extensively planted in different regions in China. These SSR markers amplified 440 polymorphic bands with an average of 2.99, and the average gene diversity index was 0.11. Eighty-six rare alleles with a frequency of less than 1% were identified in these cultivars. The largest Fst or genetic distance was found between the cultivars that adapted to the south regions and those to the north regions in China. A neighbor-joining tree of cultivars adapted to different ecological regions was constructed based on pairwise Nei’s genetic distances, which showed a significant difference between cultivars from the south and the north regions. A model-based population structure analysis divided these peanut cultivars into five subpopulations (P1a, P1b, P2, P3a and P3b). P1a and P1b included most the cultivars from the southern provinces including Guangdong, Guangxi and Fujian. P2 population consisted of the cultivars from Hubei province and parts from Shandong and Henan. P3a and P3b had cultivars from the northern provinces including Shandong, Anhui, Henan, Hebei, Jiangsu and the Yangtze River region including Sichuan province. The cluster analysis, PCoA and PCA based on the marker genotypes, revealed five distinct clusters for the entire population that were related to their germplasm regions. The results indicated that there were obvious genetic variations between cultivars from the south and the north, and there were distinct genetic differentiation among individual cultivars from the south and the north. Taken together, these results provided a molecular basis for understanding genetic diversity of Chinese peanut cultivars.