Unknown

Dataset Information

0

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


ABSTRACT: 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.

SUBMITTER: Malig M 

PROVIDER: S-EPMC7669280 | biostudies-literature |

REPOSITORIES: biostudies-literature

Similar Datasets

2019-09-20 | GSE130726 | GEO
| PRJNA541182 | ENA
| S-EPMC7735760 | biostudies-literature
| S-EPMC5548954 | biostudies-literature
| S-EPMC7498336 | biostudies-literature
2020-12-02 | GSE162410 | GEO
| S-EPMC5563512 | biostudies-literature
| PRJNA681807 | ENA
| S-EPMC4714976 | biostudies-literature
2020-12-26 | E-MTAB-9033 | biostudies-arrayexpress