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R-loops (RLs) are cellular three-stranded nucleic acid structures comprised of a DNA:RNA hybrid and a displaced DNA strand (Figure 1). The first R-loops, which can be formed co-transcriptionally in cis and post-transcriptionally in trans by Rad51 and Rad52, were visualized by electron microscopy in 1976 (Costantino and Koshland 2015, Thomas et al. 1976).
Since then, R-loops have been shown to be important in many biological processes; for example, they play a role in regulating gene expression (Ginno et al. 2013, Skourti-Stathaki et al. 2011, Skourti-Stathaki et al. 2014b), DNA methylation (Ginno et al. 2012), histone modifications (Castellano-Pozo et al. 2013), immunoglobulin class switch recombination (Yu et al. 2003) and driving embryonic stem cell differentiation (Chen et al. 2015). Interestingly, R-loops can also be formed at telomeres, which impacts telomere-length dynamics and senescence (Balk et al. 2013).
Based on their importance, it is no surprise that dysregulation of R-loop structures is associated with several human diseases, including neurodegenerative syndromes and cancer (Groh and Gromak 2014). R-loop formation has to be strictly regulated by the cell to ensure genome integrity, for example, the exposed ssDNA on R-loops is more vulnerable to breakage, deamination and nuclease cleavage, resulting in DNA damage, mutations and chromosome rearrangements (Constantino and Koshland 2015). In addition, R-loops can block replication fork progression, leading to double strand breaks (Gan et al. 2011). A number of DNA damage and repair proteins such as BRCA1 and members of the Fanconi Anemia protein family are known as important regulators of R-loop levels (Bhatia et al. 2014, Schwab et al. 2015).
As R-loop formation has to be tightly controlled, cells have mechanisms to prevent their generation. RNA processing factors and members of the topoisomerase family assist in the regulation of R-loop levels (Skourti-Stathaki et al. 2014a). Another mechanism for R-loop dissolution is activity of RNase H1 and RNase H2 enzymes, which specifically degrade the RNA in hybrids (Hiller et al. 2012). In addition, RNA-DNA helicases, such as probable helicase senataxin (SETX) and ATP-dependent RNA helicase A (DHX9), are reported to unwind the RNA/DNA hybrids thereby preventing R-loop accumulation (Skourti-Stathaki et al. 2011; Costantino and Koshland 2014; Cristini et al. 2018) (Figure 1). In addition, the 5′-3′ exonuclease XRN2 binds to and is associated with R-loop-mediated transcription termination (Skourti-Stathaki et al. 2011; Cristini et al. 2018).
The antibody based method used for R-loop mapping is called DIP or DRIP (DNA/RNA immunoprecipitation) and it relies on the Anti-DNA-RNA Hybrid Antibody, clone S9.6, used for the immunoprecipitation step (Boguslawski et al. 1986).
Fig. 1. A recent R-loop interactome study identified ATP-dependent RNA helicase, also known as DHX9, as a top promoter of R-loop formation suppression (adapted from Cristini et al. 2018 and Skourti-Stathaki et al. 2011). The 5′-3′ exonuclease XRN2 is associated with R-loop-mediated transcription termination (Skourti-Stathaki et al. 2011); SETX – probable helicase senetaxin Pol II - polymerase II.
The potential of R-loops as therapeutic cancer targets is currently under investigation. This type of research has been fuelled by studies showing the impact of the cancer drugs topotecan and camptothecin, inhibitors of topoisomerase, on R-loop formation in vivo (Powell et al. 2013, Marinello et al. 2013). In addition to its therapeutic potential, identification of small–molecule inhibitors of RNase H2 may serve as tools to investigate the function of R-loops (White et al. 2013). In fact, RNase H2 was identified in a genomic screen as a putative anti-cancer drug target (Flanagan et al. 2009). In addition to cancer, R-loops could also provide potential targets for treatment of neurological disorders, such as trinucleotide expansion diseases (Colak et al. 2014). There is also potential for the wider use of anti-DNA-RNA Hybrid antibodies, which is supported by the use of the S9.6 clone for sensitive miRNA analysis (Qavi et al. 2011). Surprisingly, a small number of miRNAs (∼200 in total) can be sufficient for cancer classification, emphasizing the potential of miRNA profiling in cancer diagnosis (Lu et al. 2005).
Additional data support the conflicting nature of R loops - they can be detrimental structures, which when uncontrolled result in disease, but they can also have a positive effect by regulating essential cellular processes. The future challenge is to fully understand the complex mechanisms balancing these two opposing effects.