Tree Genetics and Molecular Breeding 2024, Vol.14, No.2, 69-80 http://genbreedpublisher.com/index.php/tgmb 72 indicating they are under less selective pressure or are pseudogenes. These structural variations have significant impacts on the phenotypic diversity and genomic evolution of poplars. Transgenic technologies showcase tremendous potential in synthetic biology, improving industrial applications of wood such as biofuel production by optimizing lignin biosynthesis and cell wall structure. Additionally, the PoplarGene network offers extensive functional annotations and interactions for approximately 70% of poplar genes, facilitating the understanding of biological processes such as wood development (Liu et al., 2016). Furthermore, the annotation of 19 841 full-length cDNA clones from Populus nigra has enriched the functional genomics resources, aiding in the accurate molecular annotation of poplar genes (Nanjo et al., 2007). 4.2 Success stories of gene verification through experimental approaches Experimental approaches have played a crucial role in verifying gene functions in poplar. For example, the sequencing and annotation of a 95-kb genomic sequence from Populus deltoides revealed a cluster of disease resistance genes and novel transposable elements, which were experimentally validated to understand their roles in disease resistance (Lescot et al., 2004). Another success story involves the generation of a high-quality full-length cDNA collection for poplar, which was used to identify genes responding to insect feeding. This collection has been instrumental in reassessing gene predictions and identifying differentially expressed transcripts associated with defense mechanisms (Ralph et al., 2008). Additionally, the use of comparative genomics and functional genomic data from model microorganisms has enabled the prediction and experimental validation of functions for previously uncharacterized protein families, demonstrating the power of integrative approaches in gene function discovery (Gerdes et al., 2011). 4.3 Comparative analysis with gene function studies in model plants Comparative analysis with model plants such as Arabidopsis thaliana has provided valuable insights into gene functions in poplar. The PLAZA 3.0 platform, which integrates comparative genomics data for 37 plant species, including poplar and Arabidopsis, allows for the transfer of functional annotations between species. This platform has facilitated the study of genome organization and gene functions across different plant species (Proost et al., 2014). Moreover, the re-annotation of carbohydrate-active enzyme (CAZyme) genes in Populus trichocarpa, based on RNA-Seq data, revealed similarities and differences in gene families between poplar and Arabidopsis, highlighting the evolutionary conservation and divergence of these enzymes (Kumar et al., 2019). The standardized genome-wide function prediction using the GOMAP pipeline has further enabled comparative functional genomics analyses, demonstrating that functional annotations across multiple species can retain sufficient biological signal to recover known phylogenetic relationships (Fattel et al., 2021). 5 Functional Genomics in Poplar Research 5.1 Role of functional genomics in unraveling gene functions Functional genomics plays a crucial role in understanding the complex biological functions of genes within the poplar genome. By integrating various high-throughput techniques, researchers can systematically investigate gene functions and their interactions. For instance, the integration of transcriptomic and proteomic data has been shown to significantly enhance the accuracy of genome assembly and gene annotation, as demonstrated in studies involving Anopheles stephensi (Prasad et al., 2017). This approach can be similarly applied to poplar to identify and correct incomplete genome assemblies and to discover novel genes and gene functions. 5.2 Techniques for gene function verification Gene function verification in poplar research often involves techniques such as gene knockout and overexpression studies. These methods allow researchers to observe the phenotypic consequences of gene disruption or overexpression, thereby elucidating gene functions. For example, the use of high-throughput sequencing and functional annotation tools like ANNOVAR can help identify functionally important genetic variants and their effects on gene expression (Wang et al., 2010). Additionally, the application of Bayesian frameworks to integrate heterogeneous data sources can improve the accuracy of gene function predictions, as seen in studies on Saccharomyces cerevisiae.
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