Journal of Energy Bioscience 2025, Vol.16, No.1, 13-20 http://bioscipublisher.com/index.php/jeb 15 Ming et al. (2002) and Barreto et al. (2019) argued that stem weight and stem yield are controlled by multiple quantitative trait loci located in specific genomic regions, which is helpful for researchers to find favorable alleles to improve sugar yield. 3.2 Molecular basis of sugar accumulation Sun et al. (2022) and Ren et al. (2023) found that the molecular mechanism of sugar accumulation is related to multiple genes and their complex interactions with environmental factors. Yang et al. (2020) and Li et al. (2024) identified a large number of single nucleotide polymorphism loci significantly associated with sugar-related traits through GWAS, revealing the genetic architecture of sugar accumulation. A recent study by Chen et al. (2025) found that genes related to lignin synthesis were negatively correlated with sugar content, indicating that there is a complex regulatory balance between metabolic pathways. Earlier studies by Casu et al. (2005) showed that candidate genes identified by transcriptome analysis can help to resolve key molecular mechanisms controlling sugar accumulation. 3.3 Trait heritability and genetic architecture Ngaklunchon et al. (2023) and Rakesh et al. (2023) found in the same year that sucrose content had relatively high heritability and stem yield had moderate heritability, indicating that some sugarcane sugar yield traits were suitable for selection in the early stage of breeding, while others required more complex selection strategies. According to Ming et al. (2002) and Barreto et al. (2019), the genetic framework of these traits is related to multiple quantitative trait loci, and some loci are clustered in the genome, which indicates that the genetic framework of these traits may have pleiotrophy effects or genetic linkage. Hayes et al. (2021) believe that genomic prediction models have shown potential in improving the accuracy of breeding value estimation in recent years, which is expected to further improve the efficiency of sugarcane breeding. 4 Phylogenetic Relationships among Sugarcane Accessions 4.1 Interspecific relationships and lineage divergence Vilela et al. (2017) and Meng et al. (2019) found that sugarcane, as a complex polyploid hybrid crop, experienced many polyploidy events in its evolution, especially the hybridization between Saccharum officinarum and S. spontaneum. Vilela et al. ’s 2017 study found that the divergence time between Saccharum officinarum and S. spontaneum was estimated to be 2.5 million to 3.5 million years ago, indicating that their ancient evolutionary paths are very important for the genome composition of modern sugarcane. Meng et al. (2019) found a new tetraploid S. spontaneumin their study with a basic chromosome number of x=10, which more clearly revealed the existence of parallel evolutionary paths between Saccharumspecies. 4.2 Insights from phylogenetics into sugar yield evolution Li et al. (2024) used whole genome sequencing and genome-wide association analysis to find multiple single nucleotide polymorphisms associated with key agronomic traits, which are helpful for revealing the genetic basis of sugar yield traits in sugarcane and identifying selective imprinting occurring in the history of sugarcane breeding. The results of Medeiros et al. (2020) and Xiong et al. (2022) demonstrated that genetic diversity and population structure analysis supported the phylogenetic differentiation of sugarcane germplasm materials, which was closely related to the variation of sugar yield traits. 4.3 Phylogenomic support for breeding group classification Evans et al. (2019) and Zhou et al. (2022) used mitochondrial and nuclear genome data to distinguish closely related sugarcane varieties and trace their ancestral lineages. Evans et al. (2019) and Medeiros et al. (2020) found that the phylogenetic tree constructed based on genomic data was consistent with the clustering model of known breeding populations, providing a theoretical basis for the classification and management of sugarcane germplasm resources. Mahadevaiah et al. (2021) believe that this systematic genomic approach is helpful for accurately partitioning breeding populations and understanding the genetic relationships and evolutionary history of sugarcane.
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