Cotton Genomics and Genetics 2024, Vol.15, No.2, 112-126 http://cropscipublisher.com/index.php/cgg 122 The integration of NGS and CRISPR/Cas9 technologies has significantly advanced the field of cotton genomics, enabling comprehensive gene discovery, functional characterization, and precise genome editing. These tools have not only enhanced our understanding of the cotton genome but also provided new opportunities for the development of improved cotton varieties with desirable traits. 6 Challenges and Limitations of NGS in Cotton Genomics 6.1 Technical challenges Next-generation sequencing (NGS) technologies have revolutionized genomic research, but they are not without technical challenges. One significant issue is the accurate detection and quantification of rare variants, which is crucial for understanding genetic diversity in cotton. Conventional NGS protocols often struggle with characterizing subclonal variants due to inherent error rates and biases in sequencing (Salk et al., 2018). Additionally, the complexity of cotton's polyploid genome poses a challenge for sequencing and assembly, as it requires distinguishing between homologous sequences and accurately mapping reads to the correct genomic locations (Kumar et al., 2019; Pervez et al., 2022). Advances in long-read sequencing technologies, such as nanopore sequencing, promise to overcome some of these limitations by providing longer reads that can span repetitive regions and complex genomic rearrangements (Kumar et al., 2019). 6.2 Data management and analysis The vast amount of data generated by NGS technologies presents significant challenges in data management and analysis. Efficient storage, processing, and interpretation of sequencing data require robust bioinformatics pipelines and computational resources (Church, 2020; Pereira et al., 2020). The development of specialized algorithms and software tools is essential to handle the high-throughput data and to accurately call variants, annotate genes, and integrate multi-omics data (Pereira et al., 2020). Moreover, the complexity of cotton's genome, with its high level of genetic redundancy and polyploidy, necessitates advanced bioinformatics approaches to ensure accurate data analysis and meaningful biological insights (Hwang et al., 2018; Henriksen et al., 2023). The need for continuous improvement in bioinformatics tools and the integration of machine learning techniques is critical to address these challenges (Pereira et al., 2020). 6.3 Cost and accessibility Despite the decreasing costs of NGS technologies, the financial burden remains a significant barrier for many research institutions, particularly those in developing countries. The initial investment in sequencing platforms, along with the ongoing costs of reagents, maintenance, and data storage, can be prohibitive (Morganti et al., 2019; Satam et al., 2023). Additionally, the accessibility of NGS technologies is often limited by the availability of technical expertise and infrastructure required to perform and interpret sequencing experiments (Satam et al., 2023). Efforts to democratize access to NGS, such as the development of more affordable and user-friendly sequencing platforms, are essential to enable broader participation in cotton genomics research (Pervez et al., 2022; Satam et al., 2023). Collaborative initiatives and funding support can also play a crucial role in overcoming these barriers and promoting the widespread adoption of NGS technologies in cotton genomics. While NGS technologies have significantly advanced cotton genomics, several challenges remain. Addressing technical issues, improving data management and analysis, and reducing costs and increasing accessibility are critical steps to fully realize the potential of NGS in cotton research. Continued innovation and collaboration will be key to overcoming these limitations and driving further progress in the field. 7 Future Prospects and Directions 7.1 Emerging NGS technologies Next-generation sequencing (NGS) technologies continue to evolve, offering significant advancements in sequencing capabilities. Emerging methodologies such as nanopore technology, in situ nucleic acid sequencing, and microscopy-based sequencing are poised to further revolutionize the field. These technologies promise to enhance sequencing accuracy, reduce costs, and increase throughput, thereby providing deeper insights into complex genomic structures and functions (Kumar et al., 2019; Muhammed et al., 2023). Third-generation long-read sequencing technologies, such as those offered by nanopore sequencing, are particularly noteworthy for
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