Molecular Plant Breeding 2024, Vol.15, No.4, 155-166 http://genbreedpublisher.com/index.php/mpb 162 7 Challenges and Future Directions 7.1 Overcoming genetic complexity Sugarcane exhibits polyploid and aneuploid genetic complexity, which poses significant challenges to genome assembly and genetic manipulation. However, recent advances in sequencing technologies have begun to alleviate some of these difficulties. For example, the use of high-throughput sequencing technologies, including long-read sequencing approaches, has enhanced the resolution of genetic information in sugarcane (Garsmeur et al., 2018; Souza et al., 2019). These methodologies enable researchers to navigate through large and repetitive genomic regions more effectively, which are prevalent in sugarcane due to its hybrid origin fromSaccharum officinarum and Saccharum spontaneum. Future strategies must focus on improving the efficiency of these technologies and integrating data from different genomic platforms to build a more comprehensive and detailed structure of the sugarcane genome. 7.2 Enhancing genomic resources Despite the advancements in sequencing and assembling the sugarcane genome, there is a crucial need for more comprehensive genomic databases and tools that can manage and analyze the vast amounts of data generated. The development of databases such as SUCEST, which facilitates access to expressed sequence tags (ESTs), represents a significant step forward (Casu et al., 2005). However, enhancing these resources to include more functional annotations and integration with phenotypic data could dramatically improve the utility of genomic information in breeding programs. Furthermore, there is a demand for tools that can effectively address polyploidy and heterozygosity in genetic analyses are needed to fully exploit the sugarcane genome for crop improvement. 7.3 Future of genomic selection The future of genomic selection in sugarcane looks promising with the potential to revolutionize breeding strategies for this vital crop. Genomic selection, which uses genome-wide genetic markers to predict phenotypic performance, is likely to become a pivotal component of sugarcane breeding programs. This approach can be particularly effective in sugarcane, where traditional breeding is hampered by the crop's complex genetics and long breeding cycles (Souza et al., 2011). Innovations such as SNP genotyping and gene editing technologies are expected to improve the accuracy and efficiency of genomic selection, enabling the manipulation of multiple traits simultaneously, such as yield, sucrose content, and stress resistance (Manimekalai et al., 2020). As these technologies mature, the integration of genomic selection with high-throughput phenotyping and environmental modeling could lead to a new era of precision breeding in sugarcane, specifically tailored to specific agro-environmental conditions. 8 Concluding Remarks Over the past decade, the field of sugarcane genomics has seen substantial advancements, driven by rapid technological innovations in sequencing and computational biology. The development and application of next-generation sequencing technologies have allowed researchers to delve into the highly complex and polyploid genome of sugarcane with unprecedented detail and accuracy. For example, the construction of a BAC-based monoploid reference sequence for sugarcane significantly enhances the resolution of genetic analysis in this crop. The integration of long-read sequencing platforms has facilitated the assembly of large genomic regions, which are particularly challenging in polyploid genomes like that of sugarcane. Additionally, functional genomics has progressed substantially, with extensive transcriptome analyses revealing the expression patterns and potential regulatory mechanisms of thousands of genes associated with traits such as sucrose accumulation, stress responses, and biomass production. The insights gained from these genomic studies have profoundly transformed sugarcane breeding programs. The ability to identify and manipulate genes related to yield, sucrose content, and stress resistance directly impacts the efficiency of breeding strategies, reducing the time and resources required to develop new cultivars. Marker-assisted selection has become more targeted, with genetic markers linked to desirable traits speeding up the selection process. Moreover, the advent of genomic selection in sugarcane offers the potential to revolutionize breeding by predicting the performance of genotypes based on genomic data alone, a shift that is expected to enhance the genetic gains per unit of time significantly.
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