Rothenberg, E. | Search bioRxiv

bioRxiv2018

A role for RNA and DNA:RNA hybrids in the modulation of DNA repair by homologous recombination

DNA double-strand breaks (DSBs) are toxic DNA lesions which, if not properly repaired, may lead to genomic instability, cell death and senescence. Damage-induced long non-coding RNAs (dilncRNAs) are transcribed from broken DNA ends and contribute to DNA damage response (DDR) signaling. Here we show that dilncRNAs play a role in DSB repair by homologous recombination (HR) by contributing to the recruitment of the HR proteins BRCA1, BRCA2, and RAD51, without affecting DNA-end resection. In S/G2-phase cells, dilncRNAs pair to the resected DNA ends and form DNA:RNA hybrids, which are recognized by BRCA1 and promote its recruitment to DSBs. We also show that RNase H2 is in a complex with the HR proteins BRCA1, PALB2, BRCA2, and RAD51, and that it localizes to DSBs in the S/G2 cell-cycle phase. BRCA2 controls DNA:RNA hybrid levels at DSBs by mediating RNase H2 recruitment and, therefore, hybrids degradation. These results demonstrate that regulated DNA:RNA hybrid levels at DSBs contribute to HR-mediated repair.

cell biology↗

bioRxiv2017

A Method for Quantifying Molecular Interactions Using Stochastic Modelling and Super-Resolution Microscopy

We introduce the Interaction Factor (IF), a measure for quantifying the interaction of molecular clusters in super-resolution microscopy images. The IF is robust in the sense that it is independent of cluster density, and it only depends on the extent of the pair-wise interaction between different types of molecular clusters in the image. The IF for a single or a collection of images is estimated by first using stochastic modelling where the locations of clusters in the images are repeatedly randomized to estimate the distribution of the overlaps between the clusters in the absence of interaction (IF=0). Second, an analytical form of the relationship between IF and the overlap (which has the random overlap as its only parameter) is used to estimate the IF for the experimentally observed overlap. The advantage of IF compared to conventional methods to quantify interaction in microscopy images is that it is insensitive to changing cluster density and is an absolute measure of interaction, making the interpretation of experiments easier. We validate the IF method by using both simulated and experimental data and provide an ImageJ plugin for determining the IF of an image.

bioinformatics↗