Development of CRISPR-Cas9 Algorithm for Designing gRNAs for Polyploid Sugarcane

• Published in: Sugar tech : an international journal of sugar crops & related industries Vol. 27; no. 3; pp. 979 - 983
• Main Authors: Ajmal, C. P. Mohammed, Keerthana, S., Hemalatha, N., Suhail, K. Ameer
• Format: Journal Article
• Language: English
• Published: New Delhi Springer India 01.06.2025; Springer Nature B.V
• Subjects: Agriculture; Algorithms; Annotations; Biomedical and Life Sciences; Cloning; computer software; CRISPR; CRISPR-Cas systems; Crops; data collection; Datasets; Design; Editing; Gene families; Genes; Genetic engineering; Genetic modification; Genome editing; Genomes; Genomics; gRNA; Life Sciences; Machine learning; Neural networks; Pattern recognition; Polyploidy; Python; RNA; Short Communication; Sugarcane; sugars; User interface; gRNA design; Genetic editing; Genome analysis; Sequence alignment; CRISPR-Cas algorithm; Polyploid genomes; Pattern recognition; Sugarcane genome
• ISSN: 0972-1525; 0974-0740
• DOI: 10.1007/s12355-024-01523-9

This research paper addresses the challenge of editing complex genes in crops, specifically sugarcane and other polyploid plants, by leveraging CRISPR-Cas9 technology. A specialized computer program was developed to facilitate precise and efficient gene editing in these crops. Genomic sequences, annotations, and related datasets were sourced from the Sugarcane Genomes database ( http://sugarcane-genome.org ). Data in FASTA, GFF, and CSV formats enabled efficient preprocessing. ClustalW was used to identify target regions in the sugarcane genome for gRNA design, focusing on subsequences of 20 bases that ended with the "NGG" protospacer adjacent motif (PAM). Specific criteria were followed for gRNA design, considering patterns and matching confidence. High-performance computing, including GPUs and cloud platforms, handled the extensive genomic data. ChopChop and CRISPOR algorithms, along with Python libraries, supported systematic analysis, ensuring precise gRNA design. Potential target regions were identified in the PP2C genes within the sugarcane genome for CRISPR-Cas9 genome editing. The source genome database, classified based on gene families, yielded 6904 subsequences, with 1251 showing over 90% similarity, indicating conserved regions. The tool identified off-targets and unique targets. The sugarcane guide RNA (gRNA) design tool was initially developed and tested using a single set of genes and passed the initial validation, demonstrating its capability to accurately design gRNAs for the selected gene set. Given this success, the tool's application is planned to be expanded to encompass the entire sugarcane genome, enabling comprehensive gRNA design for all gene sets in sugarcane and facilitating more extensive genetic editing and research opportunities.