Tree Genetics and Molecular Breeding 2024, Vol.14, No.1, 12-21 http://genbreedpublisher.com/index.php/tgmb 14 2.3 Major challenges and demands facing tree breeding Despite the revolutionary progress brought about by modern technologies, tree breeding still faces numerous challenges. The long lifespan of trees means that any breeding improvements take a long time to manifest. The genetic diversity of trees and their complex environmental adaptation also require breeding strategies to consider the protection and sustainability of genetic resources. With the intensification of global climate change and environmental degradation, tree species resistant to adverse conditions (such as drought, pests, and diseases) are becoming increasingly important. Simultaneously, the societal demand for eco-friendly and sustainable forest products is growing, requiring tree breeding to not only improve yield and quality but also consider environmental impact and ecological balance. Tree breeding is in a period of transition. The combination of traditional breeding techniques and modern biotechnology provides new opportunities for improving tree quality, adaptability, and ecological sustainability. Future tree breeding will increasingly rely on scientific research and technological innovation to meet the growing human demand for forest resources while protecting and maintaining the health and diversity of natural ecosystems. 3 Overview of GWAS Technology Genome-wide Association Studies (GWAS) is a revolutionary genetic method that has demonstrated tremendous potential in numerous fields of biology. GWAS helps scientists unravel how genetic variations influence the phenotypic traits of organisms by analyzing the associations between polymorphic loci across the genome and specific traits. This method has achieved significant results in crop improvement and human disease research, providing new perspectives and tools for tree research. 3.1 Principles and methods of GWAS technology Genome-wide Association Studies (GWAS) is a method to study the relationship between genetic variations and phenotypic traits. Its core principle is to identify genetic markers (such as single nucleotide polymorphisms or SNPs) associated with a specific phenotype (such as a disease or biological trait) across a large number of individuals (Figure 1). GWAS typically involves scanning thousands to millions of genetic loci to find SNPs that are significantly associated with the phenotype of interest (Uffelmann et al., 2021). Figure 1 Standard analysis flow for GWAS (Genome-wide association studies) (Adopted from Uffelmann et al., 2021) To conduct a GWAS, a sufficiently large sample size is required, which helps improve the accuracy of detecting associations between genetic variations and phenotypes. The samples undergo high-throughput genome sequencing to generate a large amount of genetic data. This data contains thousands to millions of SNPs distributed across the entire genome. Statistical methods are then used to analyze the associations between these SNPs and the specific trait being studied. If the variation frequency of a particular SNP is significantly different between individuals with the specific phenotype and the general population, that SNP is likely associated with the phenotype.
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