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TITLE
Genome-wide profiling of RNA-DNA hybrids in bacteria reveals the central role of R-loops in shaping bacterial genome evolution
SPEAKER
Dr. Lydia Freddolino
INSTITUTE
University of Michigan, Ann Arbor
SUMMARY
RNA-DNA hybrids arise over the course of several essential biological processes, notably including transcription and DNA replication. However, in addition to playing necessary functional roles, they can also be harmful, potentially causing blocks to DNA replication and genomic instability. Research on RNA-DNA hybrids has also been hampered by a lack of highly effective methods for isolating them and profiling their locations genome-wide; in particular, while an antibody against RNA-DNA hybrids, S9.6, exists, it has fairly low specificity for RNA-DNA hybrids over duplex RNA, and has known sequence biases.
We have developed a new workflow, making use of an epitope-tagged hybrid binding domain as a pulldown reagent, to isolate and profile the locations of RNA-DNA hybrids genome-wide.We show that our procedure provides far higher specificity for RNA-DNA hybrids than competing methods, and permits detection of both transcription-associated R-loops and other locations of RNA-DNA hybrid formation. Applications in the model bacteria Bacillus subtilis and Escherichia coli demonstrate that RNA-DNA hybrids have indeed shaped the genomic evolution of bacteria throughout essentially all of natural history, but that cells can make use of a wide range of strategies to mitigate their harmful effects. By including strand-specific DNA sequencing on our pulldown samples, we further find that in addition to their necessary formation during active transcriptional elongation, RNA-DNA hybrids form at silenced heterochromatin-like regions in bacterial chromosomes, and may be important for the regulation of processes such as adhesion to host cells and virulence. We also demonstrate the use of a newly developed, fully Bayesian postprocessing pipeline, Enricherator, specifically designed for optimally using strand-specific genome-wide occupancy data (e.g., ChIP-seq and similar experiments with single-stranded sequencing preparation methods).