Tree Genetics and Molecular Breeding 2024, Vol.14, No.3, 132-143 http://genbreedpublisher.com/index.php/tgmb 134 has been utilized to identify quantitative trait loci (QTLs) linked to disease resistance. For example, in Norway spruce (Picea abies), eleven QTLs were identified that correlate with variation in resistance to Heterobasidion parviporum, a major pathogen causing stem and root-rot (Elfstrand et al., 2020). Transcript profiling and RNA sequencing are also common techniques used to analyze gene expression in response to pathogen infection. For instance, the differential expression of terpene synthase genes in Sitka spruce (Picea sitchensis) was analyzed to understand the biosynthesis of (+)-3-carene, a monoterpene associated with resistance to white pine weevil (Hall et al., 2011). 3.3 Key disease resistance genes discovered in conifers Several key disease resistance genes have been discovered in conifers through various studies. In limber pine, orthologous loci for resistance to rust pathogens were identified and co-positioned with multiple members of the R gene family, revealing the evolutionary pressure acting upon them (Liu et al., 2019). In Sitka spruce, the PsTPS-3car2 gene was found to be specifically expressed in resistant genotypes and was associated with higher levels of (+)-3-carene, contributing to resistance against white pine weevil (Hall et al., 2011). Another significant discovery is the Norway spruce laccase gene, PaLAC5, which is linked to resistance against Heterobasidion parviporum. This gene is specifically and strongly expressed in response to pathogen inoculation, suggesting its role in the formation of lignosuberized boundary zones in bark (Elfstrand et al., 2020). These case studies highlight the diverse genetic mechanisms that conifers employ to resist pathogen attacks. 4 Functional Genomics Approaches 4.1 Techniques for studying gene function in conifers Functional genomics in conifers employs a variety of techniques to elucidate gene function. High-density genetic mapping, such as exome-seq, has been used to construct genetic maps and identify genes involved in disease resistance, as demonstrated in limber pine (Pinus flexilis) (Liu et al., 2019). Additionally, cDNA microarrays have been utilized to monitor gene expression in response to biotic stress, providing insights into the complex defense mechanisms of conifers (Ralph et al., 2006). Genomic, proteomic, and biochemical approaches have also been combined to analyze specific phenotypes, such as the (+)-3-carene biosynthesis in Sitka spruce, revealing the role of specific terpene synthase genes in resistance to white pine weevil (Hall et al., 2011). 4.2 Transcriptomic and proteomic insights into gene function Transcriptomic and proteomic analyses offer deep insights into gene function by examining gene expression and protein profiles. For instance, microarray gene expression profiling has revealed large-scale changes in the host transcriptome of Sitka spruce in response to mechanical wounding and insect feeding, highlighting genes involved in defense signaling and secondary metabolism (Ralph et al., 2006). These approaches help in understanding the regulatory networks and protein diversity involved in conifer disease resistance (Michelmore, 2000). 4.3 Integrating functional data to validate gene roles in disease resistance Integrating data from various functional genomics approaches is crucial for validating the roles of genes in disease resistance. For example, the integration of genomic, transcriptomic, and proteomic data in Sitka spruce has provided a comprehensive understanding of the (+)-3-carene biosynthesis pathway and its role in resistance to white pine weevil (Hall et al., 2011). Such integrative approaches are essential for characterizing functional genes underlying complex traits and enhancing our understanding of conifer disease resistance mechanisms (Ralph et al., 2006; Hall et al., 2011; Liu et al., 2019). 5 Case Studies: Functional Verification of Resistance Genes 5.1 Experimental design and implementation for gene function studies The verification of resistance gene function in conifers involves a series of meticulous experimental steps to ensure the accuracy and reliability of the results. Key elements of the experimental design include: the first step involves identifying candidate resistance genes through genome sequencing and bioinformatics analyses. Once identified, these genes are cloned into suitable vectors for further study. The cloned genes are introduced into model systems or conifer tissue using methods such as Agrobacterium-mediated transformation or biolistic particle delivery. This step is crucial for analyzing the expression patterns and confirming that the genes are active
RkJQdWJsaXNoZXIy MjQ4ODYzMg==