Molecular Plant Breeding 2024, Vol.15, No.5, 317-327 http://genbreedpublisher.com/index.php/mpb 321 regulator of lignin biosynthesis (Sun et al., 2021). Dai et al. (2020) targeted genes related to wood formation, such as Cinnamoyl-CoA Reductase1 (CCR1), in Eucalyptus using CRISPR/Cas9 technology. They found that the edited Eucalyptus exhibited changes in lignin content and wood density, further validating the potential of gene editing in regulating wood properties. Figure 2 Microscopic analyses of stems from the control and EgNAC141-overexpressing Arabidopsis plants (Adopted from Sun et al., 2021) Image caption: General view of the stem vascular tissues stained by TBO in the 4th and 5th internode of 2-month-old inflorescence stem transverse sections: WT and EgNAC141-overexpressing plants (L1, L4, and L5). Each independent line has four replicates, and the micrographs are from biological replicate 1 (R1). Bars: 500 μm (Adopted from Sun et al., 2021) Furthermore, the study conducted a genome-wide marker relationship matrix analysis on Eucalyptus hybrids (E. grandis × E. urophylla), revealing that the chemical properties and density of wood are strongly genetically controlled and can be effectively improved through gene editing technologies (Lima et al., 2019). The integration of transcriptome and proteome data enabled the identification of key genes and regulatory mechanisms affecting wood density and pulp yield, further supporting the use of gene editing in these applications (Paludeto et al., 2021). Genome editing offers promising avenues for improving lignin content and composition, enhancing cellulose content and fiber quality, and optimizing wood density and pulp yield in Eucalyptus. These advancements not only contribute to better wood quality but also support the sustainable and efficient use of Eucalyptus in various industrial applications. 5 Case Studies 5.1 Improving growth traits and wood quality simultaneously Integrative approaches to enhance both growth and wood quality traits in Eucalyptus have shown promising results. For instance, a study on Eucalyptus urograndis hybrid demonstrated that genetic parameters for growth and wood properties can be effectively estimated using genome-wide SNP-based relationships. This approach allows for the simultaneous selection of growth and wood traits with minimal negative impact on genetic gain for growth, thanks to low correlations between these traits (Lima et al., 2019). Additionally, the use of genomic prediction models, such as single-step GBLUP, has been shown to improve the accuracy and bias of breeding value predictions by incorporating phenotypic data from non-genotyped trees, further enhancing the selection process for both growth and wood quality traits (Cappa et al., 2019). 5.2 Regional heritability mapping inEucalyptus Regional Heritability Mapping (RHM) has been applied to identify stable quantitative trait loci (QTL) across different environments. A study involving 3 373 individuals from four breeding populations used RHM in combination with single-marker GWAS and joint GWAS to detect loci significantly associated with growth traits. The study found that single SNP GWAS analyses detected only a few significant associations, but using gene-based and regional joint GWAS models, researchers identified multiple significantly associated genes and regions (Figure 3) (Müller et al., 2018). For instance, the gene-based joint GWAS revealed nine genes significantly associated with tree height across the four Eucalyptus breeding populations. These genes are
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