Plant Gene and Trait 2025, Vol.16, No.3, 92-103 http://genbreedpublisher.com/index.php/pgt 99 8.3 Genetic markers associated with enhanced carbon assimilation and sugar yield Not all varieties with excellent performance can explain “why they are good”. However, we can now identify some key genetic markers that are directly related to highly expressed C4 pathway genes and carbon assimilation enzymes. Sites related to enhanced activity of PEPC, PPDK, and NADP-ME, as well as regulatory elements involved in sucrose and starch metabolism, have been repeatedly verified in some excellent hybrid sugarcanes (Figure 3) (Ding et al., 2015). What’s more interesting is that behind these high expressions, there are often clustered gene regulatory regions supporting them, which provides a very practical “entry point” for marker-assisted selection and precision breeding. If we can make further progress in this regard, there may be a lot of room for improvement in sugarcane yield and carbon utilization efficiency. Figure 3 Expression pattern of classical C4 genes in four species (Adopted from Ding et al., 2015) Image caption: Gene IDs were plotted with different colors, e.g., red, blue, green and yellow for maize, green foxtail, sorghum and rice, respectively. CA: carbonic anhydrase, PEPC: phosphoenolpyruvate carboxylase, NADP-MDH: NADP-malate dehydrogenase, NADP-ME: NADP-malic enzyme, PPDK: pyruvate orthophosphate dikinase, and PPDK-RP: PPDK regulatory protein (Adopted from Ding et al., 2015) 9 Future Perspectives and Research Directions 9.1 Need for integrative genetic models linking gene regulation to whole-plant productivity Sometimes it is difficult to explain why sugarcane grows fast or produces high sugar by simply looking at whether a gene is expressed well. What is really valuable for reference is the integrated model that can put gene regulation into the performance of the whole plant. Systems biology has actually been doing this for a long time - it is not a single breakthrough, but relies on multi-omics data and computational simulation to pull factors that affect photosynthesis, stress resistance, nutrient efficiency, etc. into a “network diagram” (Kumar et al., 2015). These models have an advantage, that is, they can “artificially” intervene in the plant system, and then observe the feedback of genes or proteins, so as to predict whether a certain gene mutation will make the plant grow faster and produce more. Compared with those traditional methods, integrated models can explain more carefully, and factors such as population competition, species diversity, and environmental gradients that are difficult to quantify in the field can also be included in the analysis range (Grace et al., 2016). If you want to breed high-yield and “smart” sugarcane, this prediction framework from genes to the whole plant is basically unavoidable. 9.2 Potential of synthetic biology in designing high-efficiency C4 pathways Synthetic biology has been a bit “hot” in recent years, but not everyone really understands its potential. It is not simply to move the C4 genes of other plants, but to redesign a whole set of operating logic from regulatory networks, metabolic pathways to gene expression levels. Operations such as constructing synthetic gene circuits,
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