29 May 2015
Finding loopholes in the genome: first-of-its-kind predictive tool to identify sequences susceptible to causing mutations, genome instability and diseases.
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R-loops, thought to initiate cellular mutations, genome breaks and diseases, may be identified with an accuracy of between 80-90% at lower costs and effort.

Singapore - 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 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, revolutionising the field[1],[2].

Scientists from BII’s Genome and Gene Expression Data Analysis Division developed the Quantitative Model of R-loop Forming Sequence finder (QmRLFS-finder), 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 RLFS. The tool has also proven to have an accuracy of between 80 to 90% in predicting the location of RLFS in any genome sequence. The high accuracy would significantly accelerate R-loop detecting 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.

Its benefit to the global research community and the industry is apparent considering that there is currently only one experimental method developed for genome-wide location of R-loops[3], which has been applied at the genome level only to a single cell line. This and current non-genome level experimental methods to detect R-loops in a  double-helix DNA sequence  take a long time, high costs and a high level of expertise found in only a few laboratories worldwide.

The use of the QmRLFS-finder would empower users to conduct research in this field and contribute to growing knowledge of the importance of R-loops to human biology and diseases. The increased understanding of R-loops would also support the development of novel therapies targeting these hybrid structures.

Dr Vladimir Kuznetsov, head of the division and Senior Principal Investigator who led the development of the tool, said “We developed this predictive tool as we foresee that it has a great number of applications that can contribute to the advancement of this field. It is our hope that an increased understanding of R-loop formation and functions will in turn allow us to better predict and treat various diseases.”

The QmRLFS-finder has been accessed more than 1200 times by users from more than 20 countries since a paper on its development and use had been recently published in Nucleic Acids Research[4].

Notes to Editor:

The research findings described in this media release can be found in the Nucleic Acids Research, under the title, “QmRLFS-finder: a model, web server and stand-alone tool for prediction and analysis of R-loop forming sequences” by Piroon Jenjaroenpun, Thidathip Wongsurawat, Surya Pavan Yenamandra, and Vladimir A. Kuznetsov.

Genome and Gene Expression Data Analysis Division, Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR)

Correspondence should be addressed to Vladimir A Kuznetsov, Genome and Gene Expression Data Analysis Division, A*STAR Bioinformatics Institute, 30 Biopolis Street, #07-01, Singapore 138671. E-mail:

Full text of the paper can be accessed online from:

For media queries and clarifications, please contact:

Vanessa Loh

Senior Officer, Corporate Communications
Agency for Science, Technology and Research

Tel: +65 6826 6395

About the Bioinformatics Institute (BII)

The Bioinformatics Institute (BII) is an institute of the Agency for Science, Technology and Research (A*STAR). BII was set up in July 2001 as part of the national initiative to foster and advance biomedical research and human capital for a vibrant knowledge-based Singapore. With a multi-disciplinary focus and collaborative outlook, BII recognises the need for depth and breadth in all its activities for building a thriving world-class biomedical research, graduate training and development hub in Singapore. In addition, BII is proactively involved in building a national resource centre in bioinformatics to meet the evolving needs of the scientific community in Singapore.

For more information on BII, please visit:

About the Agency for Science, Technology and Research (A*STAR)

The Agency for Science, Technology and Research (A*STAR) is Singapore's lead public sector agency that spearheads economic oriented research to advance scientific discovery and develop innovative technology. Through open innovation, we collaborate with our partners in both the public and private sectors to benefit society.

As a Science and Technology Organisation, A*STAR bridges the gap between academia and industry. Our research creates economic growth and jobs for Singapore, and enhances lives by contributing to societal benefits such as improving outcomes in healthcare, urban living, and sustainability. 

We play a key role in nurturing and developing a diversity of talent and leaders in our Agency and Research Institutes, the wider research community and industry. A*STAR oversees 18 biomedical sciences and physical sciences and engineering research entities primarily located in Biopolis and Fusionopolis. 

For more information on A*STAR, please visit

[1] Quantitative model of R-loop forming structures reveals a novel level of RNA-DNA interactome complexity”, Nucleic Acids Res. 2012 Jan; 40(2):e16. (

[2] Out of Balance: R-loops in human disease”, PLOS Genetics, September 2014, Volume 10, Issue 9 (

[3] Different methods exist to detect the presence of R-loops in a specific gene.

[4] Nucleic Acids Research is a leading journal in the field that has been named in the Top 100 of the most influential journals in Biology and Medicine over the past 100 years. The paper was published online on 16 April 2015

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