Xian Zhang , Jiamin Wang , Jiong Fu

Hainan Provincial Key Laboratory of Crop Molecular Breeding, Sanya, 572025, Hainan, China
Author    Correspondence author
Cotton Genomics and Genetics, 2025, Vol. 16, No. 3   doi: 10.5376/cgg.2025.16.0012
Received: 09 Mar., 2025    Accepted: 21 Apr., 2025    Published: 12 May, 2025

This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Zhang X., Wang J.M., and Fu J., 2025, Improving cotton yield and fiber quality based on QTL mapping and genomic selection, Cotton Genomics and Genetics, 16(3): 117-125 (doi: 10.5376/cgg.2025.16.0012)

 

Cotton is a globally significant cash crop, but breeding efforts are often challenged by the complexity of achieving both high yield and superior fiber quality. This study explores the integration of quantitative trait loci (QTL) mapping and genomic selection (GS) as advanced tools to improve cotton breeding efficiency. We reviewed the principles and applications of QTL mapping for dissecting complex yield- and fiber-related traits, and assessed its limitations such as environmental interactions and low resolution. Genomic selection was examined in terms of predictive models, implementation in breeding pipelines, and advantages over traditional methods. A synergistic approach combining QTL mapping with GS was proposed to enhance selection accuracy and genetic gain, with emphasis on key traits such as boll number, fiber strength, and drought tolerance. We also discussed technological advancements including high-throughput phenotyping, SNP arrays, and machine learning for data analysis. A case study in Upland cotton demonstrated successful integration of QTL and GS, resulting in 15-20% gains in yield and fiber quality. Despite challenges such as genotype-by-environment interactions and model limitations, this study underscores the potential of integrative, genomics-driven strategies to sustainably advance cotton improvement programs.

Cotton breeding; QTL mapping; Genomic selection; Fiber quality; Genetic improvement