Genome-Wide Analysis of DNA-RNA Hybrids in Yeast by DRIPc-Seq and DRIP-Seq

DNA-RNA hybrids are required for several natural processes in the cell, such as replication and transcription. However, the misregulation of its metabolism is an important source of genetic instability, a hallmark of diseases including cancer. For this reason, genome-wide detection of DNA-RNA hybrids is becoming essential to identify new factors that play a role in its formation or resolution and to understand the global changes in its dynamics because of genetic alterations or chemical treatments. Here, we describe two different immunoprecipitation-based procedures for the genome-wide profiling of DNA-RNA hybrids in the yeast Saccharomyces cerevisiae: DRIP-seq and DRIPc-seq.

Harmful R-loops are prevented via different cell cycle-specific mechanisms

Identifying how R-loops are generated is crucial to know how transcription compromises genome integrity. We show by genome-wide analysis of conditional yeast mutants that the THO transcription complex, prevents R-loop formation in G1 and S-phase, whereas the Sen1 DNA-RNA helicase prevents them only in S-phase. Interestingly, damage accumulates asymmetrically downstream of the replication fork in sen1 cells but symmetrically in the hpr1 THO mutant. Our results indicate that: R-loops form co-transcriptionally independently of DNA replication; that THO is a general and cell-cycle independent safeguard against R-loops, and that Sen1, in contrast to previously believed, is an S-phase-specific R-loop resolvase. These conclusions have important implications for the mechanism of R-loop formation and the role of other factors reported to affect on R-loop homeostasis.

Analysis of the relationship between coexpression domains and chromatin 3D organization

Gene order is not random in eukaryotic chromosomes, and co-regulated genes tend to be clustered. The mechanisms that determine co-regulation of large regions of the genome and its connection with chromatin three-dimensional (3D) organization are still unclear however. Here we have adapted a recently described method for identifying chromatin topologically associating domains (TADs) to identify coexpression domains (which we term “CODs”). Using human normal breast and breast cancer RNA-seq data, we have identified approximately 500 CODs. CODs in the normal and breast cancer genomes share similar characteristics but differ in their gene composition. COD genes have a greater tendency to be coexpressed with genes that reside in other CODs than with non-COD genes. Such inter-COD coexpression is maintained over large chromosomal distances in the normal genome but is partially lost in the cancer genome. Analyzing the relationship between CODs and chromatin 3D organization using Hi-C contact data, we find that CODs do not correspond to TADs. In fact, intra-TAD gene coexpression is the same as random for most chromosomes. However, the contact profile is similar between gene pairs that reside either in the same COD or in coexpressed CODs. These data indicate that co-regulated genes in the genome present similar patterns of contacts irrespective of the frequency of physical chromatin contacts between them.

Prokaryotic operons normally comprise functionally related genes whose expression is coordinated. Even though operons do not exist in most eukaryotes, results from the last fifteen years indicate that gene order is nonetheless not random in eukaryotes, and that coexpressed genes tend to be grouped in the genome. We identify here about 500 coexpression domain (CODs) in normal breast tissue. Interestingly, we find that genes within CODs often are coexpressed with other genes that reside in other CODs placed very far away in the same chromosome, which is indicative of long-range inter-COD co-regulation. Furthermore, we find that coexpressed genes within CODs or within co-regulated CODs display similar three-dimensional chromatin contacts, suggesting a spatial coordination of CODs.