Molecular Plant Breeding 2025, Vol.16, No.2, 133-145 http://genbreedpublisher.com/index.php/mpb 141 8.3 Boosting yield with marker-assisted selection Marker-assisted selection (MAS) is a powerful tool for improving crop yield by selecting for desirable traits at the genetic level. In sweet potatoes, MAS has been employed to enhance yield under various environmental conditions. For example, a study on potato, a close relative of sweet potato, demonstrated the use of SSR markers to identify allelic differences associated with drought sensitivity, which can be used to select for drought-tolerant cultivars (Schumacher et al., 2021). Similarly, integrating transcript and metabolite markers has shown promise in predicting drought tolerance and yield stability in potatoes, suggesting that a similar approach could be applied to sweet potatoes (Sprenger et al., 2017). These studies illustrate the potential of MAS in boosting sweet potato yield by selecting for traits that confer resilience and high productivity. 9 Challenges and Future Prospects 9.1 Limitations in sweet potato genomic research Sweet potato (Ipomoea batatas L.) is a crucial crop globally, yet its genomic research faces significant challenges. One primary limitation is the lack of comprehensive genomic resources, which hampers the understanding of its molecular biology. For instance, the absence of a complete reference genome for sweet potato complicates the identification and functional analysis of genes (Tao et al., 2012; Ding et al., 2019). Additionally, the genetic complexity of sweet potato, being a hexaploid organism, further complicates genomic studies and breeding efforts (Ding et al., 2019). The limited availability of molecular markers, such as SSR markers, also restricts the ability to track important loci for traits like starch content and β-carotene content (Zhang et al., 2016). 9.2 Potential of multi-omics approaches (transcriptomics, proteomics, metabolomics) The integration of multi-omics approaches holds great promise for advancing sweet potato research. Transcriptomics, proteomics, and metabolomics can provide a holistic view of the molecular mechanisms underlying nutrient composition and yield. For example, transcriptome analysis has revealed differentially expressed genes in response to various stresses and nutrient conditions, offering insights into stress tolerance and nutrient signaling pathways (Wang et al., 2021; Xiong et al., 2022). Proteomics studies have identified cultivar-specific protein expressions that influence nutrient acquisition and storage (Shekhar et al., 2015; Acharjee et al., 2018). Metabolomics, combined with other omics data, can help reconstruct metabolic networks and identify key metabolites associated with desirable traits (Acharjee et al., 2011). These integrated approaches can facilitate the identification of candidate genes and pathways for targeted breeding and genetic improvement. 9.3 Future directions for improving sweet potato nutrient composition and yield Future research should focus on several key areas to enhance sweet potato nutrient composition and yield. First, the development of a complete reference genome and the expansion of genomic resources are essential. This will enable more precise gene editing and marker-assisted selection (Tao et al., 2012; Ding et al., 2019). Second, leveraging multi-omics approaches can provide deeper insights into the regulatory networks and metabolic pathways involved in nutrient biosynthesis and stress responses (Ommen and Stierum, 2002; Acharjee et al., 2011). Third, the identification and functional validation of key genes through techniques like CRISPR/Cas9 can accelerate the development of improved sweet potato varieties with enhanced nutrient profiles and yield (Zhang et al., 2016; Peng et al., 2022). Finally, collaborative efforts and data sharing among researchers will be crucial to overcoming the current limitations and advancing sweet potato genomics research. 10 Concluding Remarks Recent advancements in sweet potato genomics have significantly deepened our understanding of this vital crop. High-throughput sequencing technologies, such as Illumina paired-end RNA-sequencing and single-molecule real-time sequencing, have played a crucial role in building comprehensive genomic resources. For example, de novo transcriptome assembly has identified over 128 000 transcripts, offering valuable insights into gene expression across various tissues and developmental stages. Additionally, full-length cDNA sequencing has uncovered extensive alternative splicing events and identified numerous transcription factors and long non-coding RNAs, laying a foundation for functional genomics and molecular breeding.
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