Cotton is a leading natural fiber crop. Beyond its fiber, cottonseed is a valuable source of plant protein and oil. Due to the much higher value of cotton fiber, there is less consideration of cottonseed quality despite its potential value. Though some QTL controlling cottonseed quality have been identified, few of them that warrant further study are known. Identifying stable QTL controlling seed size, oil and protein content is necessary for improvement of cottonseed quality. In this study, a recombinant inbred line (RIL) population was developed from a cross between upland cotton cultivars/lines Yumian 1 and M11. Specific locus amplified fragment sequencing (SLAF-seq) technology was used to construct a genetic map that covered 3353.15 cM with an average distance between consecutive markers of 0.48 cM. The seed index, together with kernel size, oil and protein content were further used to identify QTL. In total, 58 QTL associated with six traits were detected, including 13 stable QTL detected in all three environments and 11 in two environments. A high resolution genetic map including 7033 SNP loci was constructed through specific locus amplified fragment sequencing technology. A total of 13 stable QTL associated with six cottonseed quality traits were detected. These stable QTL have the potential for fine mapping, identifying candidate genes, elaborating molecular mechanisms of cottonseed development, and application in cotton breeding programs.

Flue-cured tobacco (Nicotiana tabacum L.) is one of the most important economic crops in the world, and is the most important raw material in the cigarette industry. Construction of a high-density linkage map and identification of agronomic and leaf traits quantitative trail loci (QTLs) are prerequisites for molecular marker-assisted selective breeding projects. In the present study, an integrated high-density linkage map for flue-cured tobacco was constructed using a doubled haploid (DH) population based on SSR and SNP markers. The integrated genetic map spans 2618.89 cM and contains 607 SSR marker loci, and 917 SNP marker loci. Using the newly constructed map, QTL mapping was performed using the method of composite interval mapping (CIM) for six plant and six leaf chemistry traits. A total of 102 QTLs associated with 1.77–27.65% of the phenotypic variation were identified on 22 linkage groups in two years (2021 and 2022). Eighty-four and 89 QTLs were detected using 2021 and 2022 field experiments, respectively. Seventy-one QTLs were detected in both years. Most QTLs presented small effects, but six QTLs presented relatively large effects in both two years, with each explaining 15–28% of the phenotypic variation in the DH population. The twelve measured traits were strongly correlated with each other. Consistent with this finding, many QTLs identified for one trait overlapped with those identified for alternative traits.