Cotton Genomics and Genetics 2025, Vol.16, No.3, 117-125 http://cropscipublisher.com/index.php/cgg 117 Feature Review Open Access Improving Cotton Yield and Fiber Quality Based on QTL Mapping and Genomic Selection Xian Zhang, Jiamin Wang, Jiong Fu Hainan Provincial Key Laboratory of Crop Molecular Breeding, Sanya, 572025, Hainan, China Corresponding email: jiong.fu@hitar.org 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 Copyright © 2025 Zhang et al., 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. Preferred citation for this article: 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) Abstract 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. Keywords Cotton breeding; QTL mapping; Genomic selection; Fiber quality; Genetic improvement 1 Introduction Cotton is the most common natural fiber crop in the world and an important raw material for the textile industry. Its production feeds millions of people in the world. Because of its wide planting range and many uses in industry and agriculture, its economic value is very large. Therefore, how to improve cotton yield and fiber quality has always been a key issue for breeders and producers (Zhang et al., 2019b; Li et al., 2022). However, it is not easy to improve both yield and fiber quality at the same time. This is because the genetic structure of cotton is relatively complex, and the two traits of yield and quality often affect each other. Sometimes, if one is improved, the other will decrease. In addition, the genetic diversity of cultivated cotton is not large, and the traits are affected by many genes and environmental factors, so it is difficult to make breakthroughs using traditional breeding methods. Now, people need new varieties that can produce high yields, provide good fiber, and adapt to changes more than ever before (Diouf et al., 2018; Yang et al., 2022). In recent years, advances in molecular genetics have brought new tools to breeding, such as quantitative trait loci (QTL) mapping and genomic selection. These methods can help us better understand the genetic basis of cotton traits. By constructing high-density genetic maps and conducting genome-wide association studies (GWAS), researchers have found some stable QTLs and candidate genes related to yield and fiber quality. These results have promoted marker-assisted selection (MAS), making breeding more efficient. These methods allow breeders to focus on specific gene regions for improvement and integrate good genes from different germplasm resources (including interspecific hybrids) to improve cotton yield and quality (Li et al., 2016; Liu et al., 2018; Zhang et al., 2019a; Lu et al., 2022). The purpose of this study is to summarize the recent progress in improving cotton yield and fiber quality through QTL mapping and genomic selection. We synthesize recent research results and focus on several key gene regions,
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