This study aimed to develop a set of perfect simple sequence repeat (SSR) markers with a single copy in the cotton genome, to construct a DNA fingerprint database suitable for authentication of cotton cultivars. We optimized the polymerase chain reaction (PCR) system for multi-platform compatibility and improving detection efficiency. Based on the reference genome of upland cotton and 10× resequencing data of 48 basic cotton germplasm lines, single-copy polymorphic SSR sites were identified and developed as diploidization SSR markers. The SSR markers were detected by denaturing polyacrylamide gel electrophoresis (PAGE) for initial screening, then fluorescence capillary electrophoresis for secondary screening. The final perfect SSR markers were evaluated and verified using 210 lines from different sources among Chinese cotton regional trials. Using bioinformatics techniques, 1 246 SSR markers were designed from 26 626 single-copy SSR loci. Adopting a stepwise (primary and secondary) screening strategy, a set of 60 perfect SSR markers was selected with high amplification efficiency and stability, easy interpretation of peak type, multiple allelic variations, high polymorphism information content (PIC) value, uniform chromosome distribution, and single-copy characteristics. A multiplex PCR system was established with ten SSR markers using capillary electrophoresis detection. A set of perfect SSR markers of cotton was developed and a high-throughput SSR marker detection system was established. This study lays a foundation for large-scale and standardized construction of a cotton DNA fingerprint database for authentication of cotton varieties.

Cottonseeds, rich in high-quality protein and fatty acids, represent a vital plant-derived feedstuff and edible oil resource. To systematically investigate genetic variation patterns in nutritional quality and screen superior germplasm, this study analyzed 26 nutritional quality traits and 8 fiber traits across 259 upland cotton (Gossypium hirsutum L.) accessions using multivariate statistical approaches. Results revealed significant genetic diversity in cottonseed nutritional profiles, with coefficients of variation ranging from 3.42% to 26.37%. Moreover, with advancements in breeding periods, the contents of protein, amino acids, and the proportion of unsaturated fatty acids (UFAs) increased, while oil content and C16:0 levels decreased. Correlation analyses identified significant positive associations (p < 0.05) between proteins, amino acids, UFAs, and most fiber traits, except for seed index (SI), fiber micronaire (FM), and fiber elongation (FE). Through a principal component analysis–fuzzy membership function (PCA-FMF) model, 13 elite accessions (F > 0.75) with high protein content, high UFA proportion, and excellent fiber quality were identified. These findings provide both data-driven foundations and practical germplasm resources for value-added utilization of cottonseed and coordinated breeding for dual-quality traits of nutrition and fiber.