Tree Genetics and Molecular Breeding 2024, Vol.14, No.3, 132-143 http://genbreedpublisher.com/index.php/tgmb 137 enabling the identification and characterization of resistance genes in various environments, thus contributing to global pathogen surveillance and AMR tracking (Hendriksen et al., 2019; Gupta et al., 2020; Florensa et al., 2022). The integration of NGS with other advanced research fields, such as genome editing technologies, has further enhanced the potential for plant health improvement by diagnosing and mitigating novel or unidentified pathogens (Mushtaq et al., 2021). 6.2 Emerging tools in CRISPR and other genome editing technologies Genome editing technologies, particularly CRISPR-Cas9, have revolutionized plant biology by enabling precise and targeted modifications of genomes. CRISPR-Cas9 has democratized genome editing in plants due to its ease of use, robustness, and cost-effectiveness. This technology has been successfully applied to enhance disease resistance in crops by targeting and modifying susceptibility genes, thereby providing broad-spectrum and durable resistance (Borrelli et al., 2018; Langner et al., 2018; Zaidi et al., 2018). For example, CRISPR-Cas9 has been used to produce plants resistant to single-stranded RNA viruses by targeting critical genes such as eIF4E (Mushtaq et al., 2021). The development of transgene-free and durable disease-resistant crop varieties through genome editing holds great promise for future plant breeding programs (Zaidi et al., 2018). Moreover, the integration of CRISPR with NGS technologies has the potential to revolutionize plant virology by enabling rapid engineering of viral resistance and precise modulation of viral genomes (Mushtaq et al., 2021). 6.3 Bioinformatics tools for data analysis and gene prediction The rapid advancements in sequencing technologies have generated vast amounts of biological data, necessitating the development of sophisticated bioinformatics tools for data analysis and gene prediction. Bioinformatics approaches are crucial for retrieving, annotating, analyzing, and identifying functional aspects of genes and genomes. For instance, tools such as ARG-ANNOT, CARD, and ResFinder have been developed to detect antimicrobial resistance determinants in DNA or amino acid sequence data, providing essential insights into the evolution and emergence of AMR (Hendriksen et al., 2019; Gupta et al., 2020; Florensa et al., 2022). These tools differ in their input data requirements, search approaches, and sensitivity and specificity of detection, highlighting the importance of selecting appropriate tools for specific analyses (Hendriksen et al., 2019; Florensa et al., 2022). Additionally, bioinformatics platforms have been employed to characterize resistance genes in plants, facilitating the identification and isolation of candidate resistance genes and the development of disease-resistant crops (Joshi et al., 2023). The integration of molecular and bioinformatics approaches has thus become a cornerstone of modern plant pathology, enabling the development of novel diagnostic tools and strategies for plant disease management (Joshi et al., 2023). 7 Applications in Breeding and Forestry Management 7.1 Translating genomic insights into breeding strategies for disease resistance The integration of genomic insights into breeding strategies for disease resistance in conifers has shown significant promise. High-density genetic maps, such as those developed for limber pine (Pinus flexilis), provide essential knowledge for understanding genetic disease resistance and local adaptation to changing climates. These maps include numerous genes with potential roles in defense responses and induced systemic resistance to pathogens, making them practical tools for breeding and genetic conservation programs (Liu et al., 2019). Similarly, the development of high-density exome capture genotype-by-sequencing panels for radiata pine (Pinus radiata) has enabled the capture of a vast number of single nucleotide polymorphism (SNP) markers, facilitating marker-based breeding value predictions and accelerating selection processes (Telfer et al., 2019). The application of genomic selection and genetic engineering to enhance oleoresin production in loblolly pine (Pinus taeda) demonstrates the potential to increase resistance to bark beetles and improve bioenergy potential, further underscoring the utility of genomic tools in breeding for disease resistance (Westbrook et al., 2013). 7.2 Integrating genomic information into sustainable forestry practices The integration of genomic information into sustainable forestry practices is crucial for the effective management of genetic resources and the adaptation of forests to environmental changes. Advances in next-generation sequencing (NGS) technologies have significantly accelerated conifer genomics research, providing insights into
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