Tree Genetics and Molecular Breeding 2024, Vol.14, No.2, 43-56 http://genbreedpublisher.com/index.php/tgmb 47 Illumina/Solexa, ABI/SOLiD, and Roche/454 Pyrosequencing, provide high throughput and accuracy, allowing researchers to generate massive amounts of data quickly. These advancements have facilitated genome-wide association studies (GWAS), transcriptomics, and epigenomics in trees, leading to the discovery of genes associated with important traits like disease resistance, drought tolerance, and growth rate (Figure 1) (Satam et al., 2023). Figure 1 Overview of various NGS technologies with different platforms and principles (Adopted from Satam et al., 2023) Figure 1 provides an overview of various Next-Generation Sequencing (NGS) technologies, detailing the platforms and principles. Initially, the sample genome is extracted, fragmented, and adapters are ligated. Based on read length, technologies are categorized into long reads and short reads. Long reads include Single Molecule Real-Time (SMRT) sequencing with PCR and Nanopore sequencing without PCR. Short reads are further divided into Emulsion PCR, Bridge PCR, Nanoball PCR, and methods without PCR, each with synthesis and ligation subcategories. These categories lead to specific platforms such as Ion Torrent, Illumina, and Helicos single molecule sequencing. The ability to sequence large and complex tree genomes has opened new avenues for understanding the genetic basis of phenotypic traits, accelerating tree breeding programs, and enhancing conservation efforts. For example, the application of NGS in Populus trichocarpa has identified loci associated with resistance to fungal pathogens, providing valuable markers for breeding resistant tree varieties (Muchero et al., 2018). Overall, NGS technologies have transformed tree genomics by providing detailed insights into genetic diversity, evolution, and adaptation (Levy and Boone, 2018). 5.2 Bioinformatics tools and computational models in genome analysis The explosion of genomic data generated by NGS technologies necessitates advanced bioinformatics tools and computational models for effective data analysis. These tools are essential for tasks such as sequence alignment, variant calling, genome assembly, and functional annotation. Bioinformatics pipelines like BWA, GATK, and SAMtools are widely used for processing and analyzing NGS data, enabling researchers to identify genetic variants, construct high-quality genome assemblies, and annotate gene functions (Li et al., 2018). Additionally, specialized tools like Di3, a multi-resolution data structure for interval-based data queries, have been developed to handle the large and complex datasets typical of tree genomics (Jalili et al., 2017). Computational models and machine learning algorithms are also being increasingly applied to predict gene function, model gene regulatory networks, and identify candidate genes for traits of interest. For instance, decision-tree based algorithms have shown promise in fast and accurate variant calling from NGS data, improving the efficiency of genomic studies in trees (Li et al., 2018). These bioinformatics advancements are crucial for leveraging the full potential of NGS technologies in tree genomics, facilitating the integration of genomic data into practical applications like breeding and conservation.
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