Accelerated DNA replication fork speed due to loss of R-loops in myelodysplastic syndromes with SF3B1 mutation.

Myelodysplastic syndromes (MDS) with mutated SF3B1 gene present features including a favourable outcome distinct from MDS with mutations in other splicing factor genes SRSF2 or U2AF1. Molecular bases of these divergences are poorly understood. Here we find that SF3B1-mutated MDS show reduced R-loop formation predominating in gene bodies associated with intron retention reduction, not found in U2AF1- or SRSF2-mutated MDS. Compared to erythroblasts from SRSF2- or U2AF1-mutated patients, SF3B1-mutated erythroblasts exhibit augmented DNA synthesis, accelerated replication forks, and single-stranded DNA exposure upon differentiation. Importantly, histone deacetylase inhibition using vorinostat restores R-loop formation, slows down DNA replication forks and improves SF3B1-mutated erythroblast differentiation. In conclusion, loss of R-loops with associated DNA replication stress represents a hallmark of SF3B1-mutated MDS ineffective erythropoiesis, which could be used as a therapeutic target.

Exploration and analysis of R-loop mapping data with RLBase.

R-loops are three-stranded nucleic acid structures formed from the hybridization of RNA and DNA. In 2012, Ginno et al. introduced the first R-loop mapping method. Since that time, dozens of R-loop mapping studies have been conducted, yielding hundreds of publicly available datasets. Current R-loop databases provide only limited access to these data. Moreover, no web tools for analyzing user-supplied R-loop datasets have yet been described. In our recent work, we reprocessed 810 R-loop mapping samples, building the largest R-loop data resource to date. We also defined R-loop consensus regions and developed a framework for R-loop data analysis. Now, we introduce RLBase, a user-friendly database that provides the capability to (i) explore hundreds of public R-loop mapping datasets, (ii) explore R-loop consensus regions, (iii) analyze user-supplied data and (iv) download standardized and reprocessed datasets. RLBase is directly accessible via the following URL: https://gccri.bishop-lab.uthscsa.edu/shiny/rlbase/.

Senataxin and RNase H2 act redundantly to suppress genome instability during class switch recombination.

Class switch recombination generates distinct antibody isotypes critical to a robust adaptive immune system, and defects are associated with autoimmune disorders and lymphomagenesis. Transcription is required during class switch recombination to recruit the cytidine deaminase AID-an essential step for the formation of DNA double-strand breaks-and strongly induces the formation of R loops within the immunoglobulin heavy-chain locus. However, the impact of R loops on double-strand break formation and repair during class switch recombination remains unclear. Here, we report that cells lacking two enzymes involved in R loop removal-senataxin and RNase H2-exhibit increased R loop formation and genome instability at the immunoglobulin heavy-chain locus without impacting its transcriptional activity, AID recruitment, or class switch recombination efficiency. Senataxin and RNase H2-deficient cells also exhibit increased insertion mutations at switch junctions, a hallmark of alternative end joining. Importantly, these phenotypes were not observed in cells lacking senataxin or RNase H2B alone. We propose that senataxin acts redundantly with RNase H2 to mediate timely R loop removal, promoting efficient repair while suppressing AID-dependent genome instability and insertional mutagenesis.

The immune system is a complex network of cells and molecules, which helps to protect the body from invaders. The adaptive immune system can recognise millions of assailants, kill them, and 'learn' from this experience to mount an even quicker defence the next time the body is infected. To achieve this level of protection, specific immune cells, called B cells, divide when they come into contact with a molecule from a foreign particle, the antigen. The cloned B cells then produce millions of protective proteins, the antibodies, which patrol the blood stream and tag harmful particles for destruction. An antibody resembles a Y-shaped structure that contains a 'variable' region, which gives it the specificity to interact with an antigen, and a 'constant' region, which interacts with components of the immune system and determines the mechanisms used to destroy a pathogen. Based on the constant region, antibodies can be divided into five main classes. B cells are able to switch their production from one antibody class to another in an event known as class switch recombination, by making changes to the constant region. They do this by cutting out a portion of the genes for the constant region from their DNA and fusing the remaining DNA. The resulting antibodies still recognise the same target, but interact with different components of the immune system, ensuring that all the body's forces are mobilised. R-loops are temporary structures that form when a cell 'reads' the instructions in its DNA to make proteins. R-loops provide physical support by anchoring the transcription template to the DNA. They help control the activity of genes, but if they stay on the DNA for too long they could interfere with any form of. DNA repair ­ including the cutting and fusing mechanisms during class switch recombination. To find out more about this process, Zhao et al. used B-cells from mice lacking two specific proteins that usually help to remove R-loops. Without these proteins, the B cells generated more R-loops than normal. Nevertheless, the B-cells were able to undergo class switch recombination, even though their chromosomes showed large areas of DNA damage, and DNA sections that had been repaired contained several mistakes. Errors that occur during class switch recombination have been linked to immune disorders and B cell cancers. The study of Zhao et al. shows that even if R-loops do not affect some processes in B cells, they could still impact the overall health of their DNA. A next step would be to test if an inability to remove R-loops could indeed play a role in immune disorders and B-cell cancers.

Profiling Genome-Wide DNA Methylation in Children with Autism Spectrum Disorder and in Children with Fragile X Syndrome.

Autism spectrum disorder (ASD) is an early onset, developmental disorder whose genetic cause is heterogeneous and complex. In total, 70% of ASD cases are due to an unknown etiology. Among the monogenic causes of ASD, fragile X syndrome (FXS) accounts for 2-4% of ASD cases, and 60% of individuals with FXS present with ASD. Epigenetic changes, specifically DNA methylation, which modulates gene expression levels, play a significant role in the pathogenesis of both disorders. Thus, in this study, using the Human Methylation EPIC Bead Chip, we examined the global DNA methylation profiles of biological samples derived from 57 age-matched male participants (2-6 years old), including 23 subjects with ASD, 23 subjects with FXS with ASD (FXSA) and 11 typical developing (TD) children. After controlling for technical variation and white blood cell composition, using the conservatory threshold of the false discovery rate (FDR ≤ 0.05), in the three comparison groups, TD vs. AD, TD vs. FXSA and ASD vs. FXSA, we identified 156, 79 and 3100 differentially methylated sites (DMS), and 14, 13 and 263 differential methylation regions (DMRs). Interestingly, several genes differentially methylated among the three groups were among those listed in the SFARI Gene database, including the PAK2, GTF2I and FOXP1 genes important for brain development. Further, enrichment analyses identified pathways involved in several functions, including synaptic plasticity. Our preliminary study identified a significant role of altered DNA methylation in the pathology of ASD and FXS, suggesting that the characterization of a DNA methylation signature may help to unravel the pathogenicity of FXS and ASD and may help the development of an improved diagnostic classification of children with ASD and FXSA. In addition, it may pave the way for developing therapeutic interventions that could reverse the altered methylome profile in children with neurodevelopmental disorders.

Quality-controlled R-loop meta-analysis reveals the characteristics of R-loop consensus regions.

R-loops are three-stranded nucleic acid structures formed from the hybridization of RNA and DNA. While the pathological consequences of R-loops have been well-studied to date, the locations, classes, and dynamics of physiological R-loops remain poorly understood. R-loop mapping studies provide insight into R-loop dynamics, but their findings are challenging to generalize. This is due to the narrow biological scope of individual studies, the limitations of each mapping modality, and, in some cases, poor data quality. In this study, we reprocessed 810 R-loop mapping datasets from a wide array of biological conditions and mapping modalities. From this data resource, we developed an accurate R-loop data quality control method, and we reveal the extent of poor-quality data within previously published studies. We then identified a set of high-confidence R-loop mapping samples and used them to define consensus R-loop sites called 'R-loop regions' (RL regions). In the process, we identified a stark divergence between RL regions detected by S9.6 and dRNH-based mapping methods, particularly with respect to R-loop size, location, and colocalization with RNA binding factors. Taken together, this work provides a much-needed method to assess R-loop data quality and offers novel context regarding the differences between dRNH- and S9.6-based R-loop mapping approaches.

Genomic patterns of transcription-replication interactions in mouse primary B cells.

Conflicts between transcription and replication machinery are a potent source of replication stress and genome instability; however, no technique currently exists to identify endogenous genomic locations prone to transcription-replication interactions. Here, we report a novel method to identify genomic loci prone to transcription-replication interactions termed transcription-replication immunoprecipitation on nascent DNA sequencing, TRIPn-Seq. TRIPn-Seq employs the sequential immunoprecipitation of RNA polymerase 2 phosphorylated at serine 5 (RNAP2s5) followed by enrichment of nascent DNA previously labeled with bromodeoxyuridine. Using TRIPn-Seq, we mapped 1009 unique transcription-replication interactions (TRIs) in mouse primary B cells characterized by a bimodal pattern of RNAP2s5, bidirectional transcription, an enrichment of RNA:DNA hybrids, and a high probability of forming G-quadruplexes. TRIs are highly enriched at transcription start sites and map to early replicating regions. TRIs exhibit enhanced Replication Protein A association and TRI-associated genes exhibit higher replication fork termination than control transcription start sites, two marks of replication stress. TRIs colocalize with double-strand DNA breaks, are enriched for deletions, and accumulate mutations in tumors. We propose that replication stress at TRIs induces mutations potentially contributing to age-related disease, as well as tumor formation and development.

Mapping R-Loops and RNA:DNA Hybrids with S9.6-Based Immunoprecipitation Methods.

R-loops constitute a prevalent class of transcription-driven non-B DNA structures that occur in all genomes depending on both DNA sequence and topological favorability. In recent years, R-loops have been implicated in a variety of adaptive and maladaptive roles and have been linked to genomic instability in the context of human disorders. As a consequence, the accurate mapping of these structures in genomes is of high interest to many investigators. DRIP-seq (DNA:RNA Immunoprecipitation followed by high throughput sequencing) is described here. It is a robust and reproducible technique that permits accurate and semi-quantitative mapping of R-loops. A recent iteration of the method is also described in which fragmentation is accomplished using sonication (sDRIP-seq), which allows strand-specific and high-resolution mapping of R-loops. sDRIP-seq thus addresses some of the common limitations of the DRIP-seq method in terms of resolution and strandedness, making it a method of choice for R-loop mapping.

Defining R-loop classes and their contributions to genome instability.

R-loops are non-B DNA structures that form during transcription when the nascent RNA anneals to the template DNA strand forming a RNA:DNA hybrid. Understanding the genomic distribution and function of R-loops is an important goal, since R-loops have been implicated in a number of adaptive and maladaptive processes under physiological and pathological conditions. Based on R-loop mapping datasets, we propose the existence of two main classes of R-loops, each associated with unique characteristics. Promoter-paused R-loops (Class I) are short R-loops that form at high frequency during promoter-proximal pausing by RNA polymerase II. Elongation-associated R-loops (Class II) are long structures that occur throughout gene bodies at modest frequencies. We further discuss the relationships between each R-loop class with instances of genome instability and suggest that increased class I R-loops, resulting from enhanced promoter-proximal pausing, represent the main culprits for R-loop mediated genome instability under pathological conditions.

PRMT1-dependent regulation of RNA metabolism and DNA damage response sustains pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer that has remained clinically challenging to manage. Here we employ an RNAi-based in vivo functional genomics platform to determine epigenetic vulnerabilities across a panel of patient-derived PDAC models. Through this, we identify protein arginine methyltransferase 1 (PRMT1) as a critical dependency required for PDAC maintenance. Genetic and pharmacological studies validate the role of PRMT1 in maintaining PDAC growth. Mechanistically, using proteomic and transcriptomic analyses, we demonstrate that global inhibition of asymmetric arginine methylation impairs RNA metabolism, which includes RNA splicing, alternative polyadenylation, and transcription termination. This triggers a robust downregulation of multiple pathways involved in the DNA damage response, thereby promoting genomic instability and inhibiting tumor growth. Taken together, our data support PRMT1 as a compelling target in PDAC and informs a mechanism-based translational strategy for future therapeutic development.Statement of significancePDAC is a highly lethal cancer with limited therapeutic options. This study identified and characterized PRMT1-dependent regulation of RNA metabolism and coordination of key cellular processes required for PDAC tumor growth, defining a mechanism-based translational hypothesis for PRMT1 inhibitors.

Catalytically inactive, purified RNase H1: A specific and sensitive probe for RNA-DNA hybrid imaging.

R-loops are three-stranded nucleic acid structures with both physiological and pathological roles in cells. R-loop imaging generally relies on detection of the RNA-DNA hybrid component of these structures using the S9.6 antibody. We show that the use of this antibody for imaging can be problematic because it readily binds to double-stranded RNA (dsRNA) in vitro and in vivo, giving rise to nonspecific signal. In contrast, purified, catalytically inactive human RNase H1 tagged with GFP (GFP-dRNH1) is a more specific reagent for imaging RNA-DNA hybrids. GFP-dRNH1 binds strongly to RNA-DNA hybrids but not to dsRNA oligonucleotides in fixed human cells and is not susceptible to binding endogenous RNA. Furthermore, we demonstrate that purified GFP-dRNH1 can be applied to fixed cells to detect hybrids after their induction, thereby bypassing the need for cell line engineering. GFP-dRNH1 therefore promises to be a versatile tool for imaging and quantifying RNA-DNA hybrids under a wide range of conditions.

Recognition of RNA by the S9.6 antibody creates pervasive artifacts when imaging RNA:DNA hybrids.

The S9.6 antibody is broadly used to detect RNA:DNA hybrids but has significant affinity for double-stranded RNA. The impact of this off-target RNA binding activity has not been thoroughly investigated, especially in the context of immunofluorescence microscopy. We report that S9.6 immunofluorescence signal observed in fixed human cells arises predominantly from ribosomal RNA, not RNA:DNA hybrids. S9.6 staining was unchanged by pretreatment with the RNA:DNA hybrid-specific nuclease RNase H1, despite verification in situ that S9.6 recognized RNA:DNA hybrids and that RNase H1 was active. S9.6 staining was, however, significantly sensitive to RNase T1, which specifically degrades RNA. Additional imaging and biochemical data indicate that the prominent cytoplasmic and nucleolar S9.6 signal primarily derives from ribosomal RNA. Importantly, genome-wide maps obtained by DNA sequencing after S9.6-mediated DNA:RNA immunoprecipitation (DRIP) are RNase H1 sensitive and RNase T1 insensitive. Altogether, these data demonstrate that imaging using S9.6 is subject to pervasive artifacts without pretreatments and controls that mitigate its promiscuous recognition of cellular RNAs.

CARM1 Inhibition Enables Immunotherapy of Resistant Tumors by Dual Action on Tumor Cells and T Cells.

A number of cancer drugs activate innate immune pathways in tumor cells but unfortunately also compromise antitumor immune function. We discovered that inhibition of CARM1, an epigenetic enzyme and cotranscriptional activator, elicited beneficial antitumor activity in both cytotoxic T cells and tumor cells. In T cells, Carm1 inactivation substantially enhanced their antitumor function and preserved memory-like populations required for sustained antitumor immunity. In tumor cells, Carm1 inactivation induced a potent type 1 interferon response that sensitized resistant tumors to cytotoxic T cells. Substantially increased numbers of dendritic cells, CD8 T cells, and natural killer cells were present in Carm1-deficient tumors, and infiltrating CD8 T cells expressed low levels of exhaustion markers. Targeting of CARM1 with a small molecule elicited potent antitumor immunity and sensitized resistant tumors to checkpoint blockade. Targeting of this cotranscriptional regulator thus offers an opportunity to enhance immune function while simultaneously sensitizing resistant tumor cells to immune attack. SIGNIFICANCE: Resistance to cancer immunotherapy remains a major challenge. Targeting of CARM1 enables immunotherapy of resistant tumors by enhancing T-cell functionality and preserving memory-like T-cell populations within tumors. CARM1 inhibition also sensitizes resistant tumor cells to immune attack by inducing a tumor cell-intrinsic type 1 interferon response.This article is highlighted in the In This Issue feature, p. 1861.

Best practices for the visualization, mapping, and manipulation of R-loops.

R-loops represent an abundant class of large non-B DNA structures in genomes. Even though they form transiently and at modest frequencies, interfering with R-loop formation or dissolution has significant impacts on genome stability. Addressing the mechanism(s) of R-loop-mediated genome destabilization requires a precise characterization of their distribution in genomes. A number of independent methods have been developed to visualize and map R-loops, but their results are at times discordant, leading to confusion. Here, we review the main existing methodologies for R-loop mapping and assess their limitations as well as the robustness of existing datasets. We offer a set of best practices to improve the reproducibility of maps, hoping that such guidelines could be useful for authors and referees alike. Finally, we propose a possible resolution for the apparent contradictions in R-loop mapping outcomes between antibody-based and RNase H1-based mapping approaches.

SETX (senataxin), the helicase mutated in AOA2 and ALS4, functions in autophagy regulation.

SETX (senataxin) is an RNA/DNA helicase that has been implicated in transcriptional regulation and the DNA damage response through resolution of R-loop structures. Mutations in SETX result in either of two distinct neurodegenerative disorders. SETX dominant mutations result in a juvenile form of amyotrophic lateral sclerosis (ALS) called ALS4, whereas recessive mutations are responsible for ataxia called ataxia with oculomotor apraxia type 2 (AOA2). How mutations in the same protein can lead to different phenotypes is still unclear. To elucidate AOA2 disease mechanisms, we first examined gene expression changes following SETX depletion. We observed the effects on both transcription and RNA processing, but surprisingly observed decreased R-loop accumulation in SETX-depleted cells. Importantly, we discovered a strong connection between SETX and the macroautophagy/autophagy pathway, reflecting a direct effect on transcription of autophagy genes. We show that SETX depletion inhibits the progression of autophagy, leading to an accumulation of ubiquitinated proteins, decreased ability to clear protein aggregates, as well as mitochondrial defects. Analysis of AOA2 patient fibroblasts also revealed a perturbation of the autophagy pathway. Our work has thus identified a novel function for SETX in the regulation of autophagy, whose modulation may have a therapeutic impact for AOA2.Abbreviations: 3'READS: 3' region extraction and deep sequencing; ACTB: actin beta; ALS4: amyotrophic lateral sclerosis type 4; AOA2: ataxia with oculomotor apraxia type 2; APA: alternative polyadenylation; AS: alternative splicing; ATG7: autophagy-related 7; ATP6V0D2: ATPase H+ transporting V0 subunit D2; BAF: bafilomycin A1; BECN1: beclin 1; ChIP: chromatin IP; Chloro: chloroquine; CPT: camptothecin; DDR: DNA damage response; DNMT1: DNA methyltransferase 1; DRIP: DNA/RNA IP; DSBs: double strand breaks; EBs: embryoid bodies; FTD: frontotemporal dementia; GABARAP: GABA type A receptor-associated protein; GO: gene ontology; HR: homologous recombination; HTT: huntingtin; IF: immunofluorescence; IP: immunoprecipitation; iPSCs: induced pluripotent stem cells; KD: knockdown; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; MN: motor neuron; MTORC1: mechanistic target of rapamycin kinase complex 1; PASS: PolyA Site Supporting; PFA: paraformaldehyde; RNAPII: RNA polymerase II; SCA: spinocerebellar ataxia; SETX: senataxin; SMA: spinal muscular atrophy; SMN1: survival of motor neuron 1, telomeric; SQSTM1/p62: sequestosome 1; TFEB: transcription factor EB; TSS: transcription start site; TTS: transcription termination site; ULK1: unc-51 like autophagy activating kinase 1; WB: western blot; WIPI2: WD repeat domain, phosphoinositide interacting 2; XRN2: 5'-3' exoribonuclease 2.

Bisulfite treatment and single-molecule real-time sequencing reveal D-loop length, position, and distribution.

Displacement loops (D-loops) are signature intermediates formed during homologous recombination. Numerous factors regulate D-loop formation and disruption, thereby influencing crucial aspects of DNA repair, including donor choice and the possibility of crossover outcome. While D-loop detection methods exist, it is currently unfeasible to assess the relationship between D-loop editors and D-loop characteristics such as length and position. Here, we developed a novel in vitro assay to characterize the length and position of individual D-loops with near base-pair resolution and deep coverage, while also revealing their distribution in a population. Non-denaturing bisulfite treatment modifies the cytosines on the displaced strand of the D-loop to uracil, leaving a permanent signature for the displaced strand. Subsequent single-molecule real-time sequencing uncovers the cytosine conversion patch as a D-loop footprint. The D-loop Mapping Assay is widely applicable with different substrates and donor types and can be used to study factors that influence D-loop properties.

Rdh54/Tid1 inhibits Rad51-Rad54-mediated D-loop formation and limits D-loop length.

Displacement loops (D-loops) are critical intermediates formed during homologous recombination. Rdh54 (a.k.a. Tid1), a Rad54 paralog in Saccharomyces cerevisiae, is well-known for its role with Dmc1 recombinase during meiotic recombination. Yet contrary to Dmc1, Rdh54/Tid1 is also present in somatic cells where its function is less understood. While Rdh54/Tid1 enhances the Rad51 DNA strand invasion activity in vitro, it is unclear how it interplays with Rad54. Here, we show that Rdh54/Tid1 inhibits D-loop formation by Rad51 and Rad54 in an ATPase-independent manner. Using a novel D-loop Mapping Assay, we further demonstrate that Rdh54/Tid1 uniquely restricts the length of Rad51-Rad54-mediated D-loops. The alterations in D-loop properties appear to be important for cell survival and mating-type switch in haploid yeast. We propose that Rdh54/Tid1 and Rad54 compete for potential binding sites within the Rad51 filament, where Rdh54/Tid1 acts as a physical roadblock to Rad54 translocation, limiting D-loop formation and D-loop length.

Topoisomerase 1 prevents replication stress at R-loop-enriched transcription termination sites.

R-loops have both positive and negative impacts on chromosome functions. To identify toxic R-loops in the human genome, here, we map RNA:DNA hybrids, replication stress markers and DNA double-strand breaks (DSBs) in cells depleted for Topoisomerase I (Top1), an enzyme that relaxes DNA supercoiling and prevents R-loop formation. RNA:DNA hybrids are found at both promoters (TSS) and terminators (TTS) of highly expressed genes. In contrast, the phosphorylation of RPA by ATR is only detected at TTS, which are preferentially replicated in a head-on orientation relative to the direction of transcription. In Top1-depleted cells, DSBs also accumulate at TTS, leading to persistent checkpoint activation, spreading of γ-H2AX on chromatin and global replication fork slowdown. These data indicate that fork pausing at the TTS of highly expressed genes containing R-loops prevents head-on conflicts between replication and transcription and maintains genome integrity in a Top1-dependent manner.

Characterization of R-Loop Structures Using Single-Molecule R-Loop Footprinting and Sequencing.

R-loops are three-stranded structures that form during transcription when the nascent RNA hybridizes with the template DNA resulting in a DNA:RNA hybrid and a looped-out single-stranded DNA (ssDNA) strand. These structures are important for normal cellular processes and aberrant R-loop formation has been implicated in a number of pathological outcomes, including certain cancers and neurodegenerative diseases. Mapping R-loops has primarily been performed using DRIP (DNA:RNA immunoprecipitation) based methods that are dependent on the anti-DNA:RNA hybrid S9.6 antibody and short-read sequencing. While DRIP-based methods are robust and report R-loop formation genome-wide, they only do so at the population average level; interrogating R-loop formation at the single molecule level is not feasible with such approaches. Here we present single molecule R-loop footprinting (SMRF-seq), a method that relies on the chemical reactivity of the displaced ssDNA strand to non-denaturing sodium bisulfite and single molecule long-read sequencing as a readout, to characterize R-loops. SMRF-seq can be used independently of S9.6 to generate high resolution, strand-specific, maps of individual R-loops at ultra-deep coverage on kilobases-length DNA fragments.

RNA-DNA strand exchange by the Drosophila Polycomb complex PRC2.

Polycomb Group (PcG) proteins form memory of transient transcriptional repression that is necessary for development. In Drosophila, DNA elements termed Polycomb Response Elements (PREs) recruit PcG proteins. How PcG activities are targeted to PREs to maintain repressed states only in appropriate developmental contexts has been difficult to elucidate. PcG complexes modify chromatin, but also interact with both RNA and DNA, and RNA is implicated in PcG targeting and function. Here we show that R-loops form at many PREs in Drosophila embryos, and correlate with repressive states. In vitro, both PRC1 and PRC2 can recognize R-loops and open DNA bubbles. Unexpectedly, we find that PRC2 drives formation of RNA-DNA hybrids, the key component of R-loops, from RNA and dsDNA. Our results identify R-loop formation as a feature of Drosophila PREs that can be recognized by PcG complexes, and RNA-DNA strand exchange as a PRC2 activity that could contribute to R-loop formation.

Ultra-deep Coverage Single-molecule R-loop Footprinting Reveals Principles of R-loop Formation.

R-loops are a prevalent class of non-B DNA structures that have been associated with both positive and negative cellular outcomes. DNA:RNA immunoprecipitation (DRIP) approaches based on the anti-DNA:RNA hybrid S9.6 antibody revealed that R-loops form dynamically over conserved genic hotspots. We have developed an orthogonal approach that queries R-loops via the presence of long stretches of single-stranded DNA on their looped-out strand. Nondenaturing sodium bisulfite treatment catalyzes the conversion of unpaired cytosines to uracils, creating permanent genetic tags for the position of an R-loop. Long-read, single-molecule PacBio sequencing allows the identification of R-loop 'footprints' at near nucleotide resolution in a strand-specific manner on long single DNA molecules and at ultra-deep coverage. Single-molecule R-loop footprinting coupled with PacBio sequencing (SMRF-seq) revealed a strong agreement between S9.6-based and bisulfite-based R-loop mapping and confirmed that R-loops form over genic hotspots, including gene bodies and terminal gene regions. Based on the largest single-molecule R-loop dataset to date, we show that individual R-loops form nonrandomly, defining discrete sets of overlapping molecular clusters that pileup through larger R-loop zones. R-loops most often map to intronic regions and their individual start and stop positions do not match with intron-exon boundaries, reinforcing the model that they form cotranscriptionally from unspliced transcripts. SMRF-seq further established that R-loop distribution patterns are not simply driven by intrinsic DNA sequence features but most likely also reflect DNA topological constraints. Overall, DRIP-based and SMRF-based approaches independently provide a complementary and congruent view of R-loop distribution, consolidating our understanding of the principles underlying R-loop formation.