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.

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.