Tree Genetics and Molecular Breeding 2024, Vol.14, No.1, 12-21 http://genbreedpublisher.com/index.php/tgmb 17 al. (2020) utilized GWAS techniques to identify key genes in the pine genome associated with disease resistance, growth rate, and wood density. Through such analysis, breeders can more accurately identify genomic regions influencing important traits and perform effective genetic selection during the breeding process. Resende et al. (2017) discovered genetic markers associated with wood fiber length and density in Eucalyptus through GWAS. These findings not only deepened the understanding of tree genetic diversity but also provided crucial information for formulating tree breeding strategies. By selectively breeding individuals carrying favorable genetic variations, breeders can cultivate tree varieties with stronger adaptability, faster growth rates, and better stress resistance. Furthermore, GWAS has revealed some rare genetic variations in tree populations that significantly impact certain tree traits. The discovery of these rare variations provides important information for protecting tree genetic diversity and genetic resources, as well as valuable genetic resources for future breeding projects. The application of GWAS in tree breeding has provided new insights into understanding the genetic mechanisms of trees and laid the foundation for cultivating tree species that are better adapted to environmental changes and more economically valuable. As technology advances, the future application of GWAS in tree breeding will become more widespread, providing more precise and efficient methods for tree genetic improvement and resource management. 4.3 Protection of tree genetic diversity and genetic resources The application of GWAS in tree breeding is not only significant for breeding purposes but also plays an important role in the protection of tree genetic diversity and genetic resources. The genetic diversity within tree populations is key to their ability to adapt to environmental changes and resist pests and diseases. Through GWAS, a better understanding of the genetic variation within tree populations can be gained, guiding the formulation of conservation strategies. For example, GWAS can help identify rare or endangered tree species with unique genetic characteristics, providing scientific support for the conservation of these species (Funk et al., 2019). Additionally, an in-depth understanding of genetic resources can promote the sustainable utilization of tree germplasm, providing valuable genetic resources for future breeding projects. The application of GWAS in tree breeding not only improves the efficiency and accuracy of breeding but also provides important support for the protection and sustainable utilization of tree genetic resources. As technology advances and research deepens, GWAS is expected to play an increasingly important role in tree breeding and forest resource management. 5 Case Study 5.1 Case study of GWAS in forest trees: The case of Qinghai spruce (Picea crassifolia Kom.) Qinghai spruce (Picea crassifolia Kom.) is an important high-altitude tree species, mainly distributed in the eastern and central parts of the Qinghai-Tibet Plateau in China. As a tree species adapted to high altitudes, Picea crassifolia plays a crucial role in the ecosystem, serving as an important water conservation species and a vital component of biodiversity. Furthermore, Picea crassifolia also has high economic value, with its timber being used for construction and furniture manufacturing. Zhou et al. (2022) studied the earlywood tracheid properties of Picea crassifolia Kom., which have a significant impact on wood quality and processing performance. Earlywood is the initial portion of wood formed within an annual ring, typically lighter and lower in density, influencing the physical and mechanical properties of wood. The researchers conducted phenotypic and genotypic analyses on 106 Picea crassifolia Kom. clones and performed genome-wide association analysis using specific-locus amplified fragment sequencing (SLAF-seq) technology to identify single nucleotide polymorphisms (SNPs) and candidate genes associated with earlywood tracheid properties. The researchers characterized 14 earlywood tracheid traits phenotypically, then used SLAF-seq technology to sequence the Picea crassifolia Kom. genome, obtaining a large number of SNP markers. Through GWAS analysis, they identified SNPs significantly associated with earlywood tracheid properties and further screened for candidate genes in the surrounding regions.
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