Linkage disequilibrium based association mapping is a powerful tool for dissecting the genetic basis underlying complex traits. In this study, an association mapping panel consisting of 356 representative Upland cotton cultivars was constructed, evaluated in three environments and genotyped using 381 SSRs to detect molecular markers associated with lint yield and its components. The results showed that abundant phenotypic and moderate genetic diversities existed within this germplasm panel. The population could be divided into two subpopulations, and weak relatedness was detected between pair-wise accessions. LD decayed to the background (r 2 = 0.1182, P≤0.01), r 2 = 0.1 and r 2 = 0.2 level within 12–13 cM, 17–18 cM and 3–4 cM, respectively, providing the potential for association mapping of agronomically important traits in Chinese Upland cotton. A total of 55 marker-trait associations were detected between 26 SSRs and seven lint yield traits, based on a mixed linear model (MLM) and Bonferroni correction (P≤0.05/145, −log10 P≥3.46). Of which 41 could be detected in more than one environment and 17 markers were simultaneously associated with two or more traits. Many associations were consistent with QTLs identified by linkage mapping in previous reports. Phenotypic values of alleles of each loci in 41 stably detected associations were compared, and 23 favorable alleles were identified. Population frequency of each favorable allele in historically released cultivar groups was also evaluated. The QTLs detected in this study will be helpful in further understanding the genetic basis of lint yield and its components, and the favorable alleles may facilitate future high-yield breeding by genomic selection in Upland cotton.

Cotton is the world’s leading cash crop, and genetic improvement of fiber yield and quality is the primary objective of cotton breeding program. In this study, we used various approaches to identify QTLs related to fiber yield and quality. Firstly, we constructed a four-way cross (4WC) mapping population with four base core cultivars, Stoneville 2B, Foster 6, Deltapine 15 and Zhongmiansuo No.7 (CRI 7), as parents in Chinese cotton breeding history and identified 83 QTLs for 11 agronomic and fiber quality traits. Secondly, association mapping of agronomical and fiber quality traits was based on 121 simple sequence repeat (SSR) markers using a general linear model (GLM). For this, 81 Gossypium hirsutum L. accessions including the four core parents and their derived cultivars were grown in seven diverse environments. Using these approaches, we successfully identified 180 QTLs significantly associated with agronomic and fiber quality traits. Among them were 66 QTLs that were identified via linkage disequilibrium (LD) and 4WC family-based linkage (FBL) mapping and by previously published family-based linkage (FBL) mapping in modern Chinese cotton cultivars. Twenty eight and 44 consistent QTLs were identified by 4WC and LD mapping, and by FBL and LD mapping methods, respectively. Furthermore, transmission and variation of QTL-alleles mapped by LD association in the three breeding periods revealed that some could be detected in almost all Chinese cotton cultivars, suggesting their stable transmission and some identified only in the four base cultivars and not in the modern cultivars, suggesting they were missed in conventional breeding. These results will be useful to conduct genomics-assisted breeding effectively using these existing and novel QTL alleles to improve yield and fiber qualities in cotton.

The characterization of genetic diversity and population structure can be used in tandem to detect reliable phenotype–genotype associations. In the present study, we genotyped a set of 366 sesame germplasm accessions by using 89,924 single-nucleotide polymorphisms (SNPs). The number of SNPs on each chromosome was consistent with the physical length of the respective chromosome, and the average marker density was approximately 2.67 kb/SNP. The genetic diversity analysis showed that the average nucleotide diversity of the panel was 1.1 × 10-3, with averages of 1.0 × 10-4, 2.7 × 10-4, and 3.6 × 10-4 obtained, respectively for three identified subgroups of the panel: Pop 1, Pop 2, and the Mixed. The genetic structure analysis revealed that these sesame germplasm accessions were structured primarily along the basis of their geographic collection, and that an extensive admixture occurred in the panel. The genome-wide linkage disequilibrium (LD) analysis showed that an average LD extended up to ∼99 kb. The genetic diversity and population structure revealed in this study should provide guidance to the future design of association studies and the systematic utilization of the genetic variation characterizing the sesame panel.