Molecular Plant Breeding 2024, Vol.15, No.5, 247-258 http://genbreedpublisher.com/index.php/mpb 247 Research Insight Open Access Integrating QTL Mapping and Genomic Selection in Eucommia ulmoides Breeding Ruoruo Wang1, LuoWang1, Degang Zhao1,2 1 Plant Conservation & Breeding Technology Center, Guizhou Key Laboratory of Agricultural Biotechnology/Biotechnology Institute of Guizhou Province, Guizhou Academy of Agricultural Sciences, Guiyang, 550006, Guizhou, China 2 The Key Laboratory of Plant Resources Conservation and Germplasm Innovation in Mountainous Region (Ministry of Education), College of Life Sciences / Institute of Agro- Bioengineering, Guizhou University, Guiyang, 550025, Guizhou, China Corresponding email: dgzhao@gzu.edu.cn Molecular Plant Breeding, 2024, Vol.15, No.5 doi: 10.5376/mpb.2024.15.0024 Received: 18 Aug., 2024 Accepted: 20 Sep., 2024 Published: 28 Sep., 2024 Copyright © 2024 Wang 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: Wang R.R., Wang L., and Zhao D.G., 2024, Integrating QTL mapping and genomic selection in Eucommia ulmoides breeding, Molecular Plant Breeding, 15(5): 247-258 (doi: 10.5376/mpb.2024.15.0024) Abstract Eucommia ulmoides is a tree species with significant medicinal and industrial value. In recent years, some progress has been made in the genetic improvement of E. ulmoides through the construction of high-density genetic maps and the identification of massive quantitative trait loci (QTLs). This study focuses on the integrated application of QTL mapping and genomic selection (GS) in the breeding of E. ulmoides. By integrating current researches, the study analyzes the role of QTL mapping in identifying loci associated with growth traits, secondary metabolites, and yield, and discusses the potential of applying this information in GS models to enhance breeding efficiency. The results indicate that combining QTL mapping with GS methods can significantly improve the accuracy of selecting complex traits and help accelerate the breeding of superior Eucommia varieties. This study provides theoretical support for future genetic research and breeding strategies in E. ulmoides, promoting the development of varieties with higher economic and ecological value. Keywords Eucommia ulmoides; QTL mapping; Genomic selection; Genetic linkage map; Breeding efficiency 1 Introduction Eucommia ulmoides, commonly known as the hardy rubber tree, is a significant tree species with both economic and ecological value. It is prized for its applications in pharmacology, landscaping, wind protection, and sand stabilization (Jin et al., 2020). The tree is notable for producing Eucommia rubber (Eu-rubber), a trans-polyisoprene that serves as a unique strategic resource in China and can be used as a substitute for natural rubber (Wuyun et al., 2017; Zhang et al., 2023). Additionally, E. ulmoides is rich in chlorogenic acid and flavonoids, both of which possess high medicinal value (Xie et al., 2023). Endemic to China, this species has been classified as a national level II key protected tree species due to its economic and ecological significance (Wang et al., 2023). Despite its significance, the breeding and genetic improvement of E. ulmoides face several challenges. One major issue is the inadequate comprehension of the genetic basis of key traits, which limits efforts to breed varieties with enhanced yield and quality (Li et al., 2014). The dioecious nature of the species complicates early-stage sex identification, hindering efficient breeding practices (Wang et al., 2020). Additionally, the lack of a high-quality genome sequence has restricted both fundamental biological research and applied studies (Wuyun et al., 2017; Li et al., 2020; Du et al., 2023). Furthermore, the phenotypic variation within and among natural populations poses a challenge for genetic improvement and resource management (Wang et al., 2023). Quantitative trait loci (QTLs) mapping is a method used to identify regions of the genome associated with specific phenotypic traits. This technique is crucial for understanding the genetic architecture of complex traits and for identifying candidate genes that influence these traits. In E. ulmoides, QTL mapping has been employed to identify loci linked to growth traits, which is essential for improving breeding efficiency and genetic improvement at the molecular level (Li et al., 2014; Jin et al., 2020; Liu et al., 2022). GS is a modern breeding approach that utilizes genome-wide markers to predict the genetic value of individuals in a breeding population. Unlike
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