Non-B DNA structures as a booster of genome instability

Non-canonical secondary structures (NCSs) are alternative nucleic acid structures that differ from the canonical B-DNA conformation. NCSs often occur in repetitive DNA sequences and can adopt different conformations depending on the sequence. The majority of these structures form in the context of physiological processes, such as transcription-associated R-loops, G4s, as well as hairpins and slipped-strand DNA, whose formation can be dependent on DNA replication. It is therefore not surprising that NCSs play important roles in the regulation of key biological processes. In the last years, increasing published data have supported their biological role thanks to genome-wide studies and the development of bioinformatic prediction tools. Data have also highlighted the pathological role of these secondary structures. Indeed, the alteration or stabilization of NCSs can cause the impairment of transcription and DNA replication, modification in chromatin structure and DNA damage. These events lead to a wide range of recombination events, deletions, mutations and chromosomal aberrations, well-known hallmarks of genome instability which are strongly associated with human diseases. In this review, we summarize molecular processes through which NCSs trigger genome instability, with a focus on G-quadruplex, i-motif, R-loop, Z-DNA, hairpin, cruciform and multi-stranded structures known as triplexes.

Quantitative detection of CpG methylation level on G-quadruplex and i-motif-forming DNA by recombinase polymerase amplification

Detection of CpG methylation levels holds immense potential for application in medical diagnosis of various diseases. In this study, we report the development of a recombinase polymerase amplification (RPA)-based CpG methylation level sensing system on G-quadruplex (G4) and intercalated motif (i-motif)-forming regions, which are stabilized by CpG methylation. This detection system is based on the principle that DNA polymerase is stalled at the methylated G4 and i-motif-forming region, which results in a decrease in the initial elongation efficiency of RPA. This reduction in turn affects the onset of amplification depending on the extent of CpG methylation; therefore, the methylation level is quantified by RPA. We demonstrate that the onset of amplification was delayed by CpG methylation when PCR products containing the vascular endothelial growth factor (VEGF) G4 and i-motif-forming region were used as the template. Furthermore, onset of amplification was delayed with the increase in CpG methylation of the VEGF region on genomic DNA. These results demonstrate that the sensing system is capable of directly detecting the methylation level at a constant temperature (39 °C) within 30 min without performing bisulfite conversion or affinity capture of methylated DNA.

DROPA: DRIP-seq optimized peak annotator

Background

R-loops are three-stranded nucleic acid structures that usually form during transcription and that may lead to gene regulation or genome instability. DRIP (DNA:RNA Immunoprecipitation)-seq techniques are widely used to map R-loops genome-wide providing insights into R-loop biology. However, annotation of DRIP-seq peaks to genes can be a tricky step, due to the lack of strand information when using the common basic DRIP technique.

Results

Here, we introduce DRIP-seq Optimized Peak Annotator (DROPA), a new tool for gene annotation of R-loop peaks based on gene expression information. DROPA allows a full customization of annotation options, ranging from the choice of reference datasets to gene feature definitions. DROPA allows to assign R-loop peaks to the DNA template strand in gene body with a false positive rate of less than 7%. A comparison of DROPA performance with three widely used annotation tools show that it identifies less false positive annotations than the others.

Conclusions

DROPA is a fully customizable peak-annotation tool optimized for co-transcriptional DRIP-seq peaks, which allows a finest gene annotation based on gene expression information. Its output can easily be integrated into pipelines to perform downstream analyses, while useful and informative summary plots and statistical enrichment tests can be produced.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-3009-9) contains supplementary material, which is available to authorized users.

R-loop generation during transcription: Formation, processing and cellular outcomes

R-loops are structures consisting of an RNA-DNA duplex and an unpaired DNA strand. They can form during transcription upon nascent RNA "threadback" invasion into the DNA duplex to displace the non-template strand. Although R-loops occur naturally in all kingdoms of life and serve regulatory roles, they are often deleterious and can cause genomic instability. Of particular importance are the disastrous consequences when replication forks or transcription complexes collide with R-loops. The appropriate processing of R-loops is essential to avoid a number of human neurodegenerative and other clinical disorders. We provide a perspective on mechanistic aspects of R-loop formation and their resolution learned from studies in model systems. This should contribute to improved understanding of R-loop biological functions and enable their practical applications. We propose the novel employment of artificially-generated stable R-loops to selectively inactivate tumor cells.