Scientists from A*STAR's Bioinformatics Institute (BII) have developed an analytical model and computational tool to rapidly and accurately predict the occurrence and locations of R-loop Forming Sequences (RLFSs) in any genome or artificial nucleic acid sequences. R-loops, which are three-stranded RNA and DNA hybrid structures, can be crucial to many normal biological processes and have also been associated with triggering mutations, DNA breaks, and diseases. These hybrid structures provide intriguing possibilities for use as novel targets for diagnostics and treatment of diseases including cancer, autoimmune diseases, and neurodegenerative conditions. While R-loops were first described in 1976 and were for many years associated with only a few specific genes, it is only in recent years that understanding of their critical function and prevalence in the genomes has advanced, revolutionizing the field. Scientists from BII's Genome and Gene Expression Data Analysis Division developed the Quantitative Model of R-loop Forming Sequence finder (QmRLFS-finder), and are making it freely available to accelerate research in this area. Using the QmRLFS-finder, the scientists made a surprising discovery that 75% of well-annotated human genes and/or their vicinities contain RLFSs. The tool has also proven to have an accuracy of between 80% and 90% in predicting the location of RLFS in any genome sequence. The high accuracy would significantly accelerate R-loop detection and dramatically reduce the cost and time taken compared to currently available experimental methods, paving the way for further improvement and development in the relatively nascent field of R-loop biology.
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