R环的形成及对基因组稳定性的影响

R-环是由一个RNA:DNA杂交体和一条单链状态的DNA分子共同组成的三链核酸结构。其中, RNA:DNA杂交体的形成起因于基因转录所合成的RNA分子不能与模板分开, 或RNA分子重新与一段双链DNA分子中的一条链杂交。在基因转录过程中, 当转录泡遇到富含G碱基的非模板链区或位于某些与人类疾病有关的三核苷酸卫星DNA时, 转录泡后方累积的负超螺旋可促进R环形成。同时, 新生RNA分子未被及时加工、成熟或未被快速转运到细胞质等因素也会催生R环。研究表明, 细胞拥有多种管理R环的方法, 可以有效地管理R环的形成和处理已经形成的R环, 以尽量避免R环对DNA复制、基因突变和同源重组产生不利影响。文章重点分析了R-环的形成机制及R环对DNA复制、基因突变和同源重组的影响, 并针对R-环诱导的DNA复制在某些三核苷酸重复扩增有关的神经肌肉退行性疾病发生过程中的作用进行了分析和讨论。     

TDRD3 promotes DHX9 chromatin recruitment and R-loop resolution

R-loops, which consist of a DNA/RNA hybrid and a displaced single-stranded DNA (ssDNA), are increasingly recognized as critical regulators of chromatin biology. R-loops are particularly enriched at gene promoters, where they play important roles in regulating gene expression. However, the molecular mechanisms that control promoter-associated R-loops remain unclear. The epigenetic ‘reader’ Tudor domain-containing protein 3 (TDRD3), which recognizes methylarginine marks on histones and on the C-terminal domain of RNA polymerase II, was previously shown to recruit DNA topoisomerase 3B (TOP3B) to relax negatively supercoiled DNA and prevent R-loop formation. Here, we further characterize the function of TDRD3 in R-loop metabolism and introduce the DExH-box helicase 9 (DHX9) as a novel interaction partner of the TDRD3/TOP3B complex. TDRD3 directly interacts with DHX9 via its Tudor domain. This interaction is important for recruiting DHX9 to target gene promoters, where it resolves R-loops in a helicase activity-dependent manner to facilitate gene expression. Additionally, TDRD3 also stimulates the helicase activity of DHX9. This stimulation relies on the OB-fold of TDRD3, which likely binds the ssDNA in the R-loop structure. Thus, DHX9 functions together with TOP3B to suppress promoter-associated R-loops. Collectively, these findings reveal new functions of TDRD3 and provide important mechanistic insights into the regulation of R-loop metabolism.     

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.     

R-loop stability as a function of RNA structure and size.

The sequence-specific formation of R-loops can be assayed using RNAs which overlap a HindIII cleavage site in a 3.5 kb plasmid. Chemical modification of the displaced DNA strand has permitted stabilization of these R-loops and allowed a systematic investigation of the dependence of these triple-stranded structures on the chain length and structure of the input RNA. RNAs as short as 50 nt form stable R-loops if 5-allylamine uridines (Uaa-RNA) are used in place of normal uridines; normal RNAs must be 100 nt long to form R-loops quantitatively. Since acetic anhydride decreases the hybridization efficiency of Uaa-RNAs, the positive charge of the RNAs must diminish the electrostatic repulsion of the three negatively charged phosphodiester backbones. The dependence of R-loop stability on the length of RNA can be stimulated with a random walk model, which also applies to strand migration within Holiday junctions. R-loop hybridization provides a versatile method to generate single-stranded DNA in a sequence-selective manner.     

Untangling the crosstalk between BRCA1 and R-loops during DNA repair

R-loops are RNA:DNA hybrids assembled during biological processes but are also linked to genetic instability when formed out of their natural context. Emerging evidence suggests that the repair of DNA double-strand breaks requires the formation of a transient R-loop, which eventually must be removed to guarantee a correct repair process. The multifaceted BRCA1 protein has been shown to be recruited at this specific break-induced R-loop, and it facilitates mechanisms in order to regulate R-loop removal. In this review, we discuss the different potential roles of BRCA1 in R-loop homeostasis during DNA repair and how these processes ensure faithful DSB repair.     

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.