An automated image analysis pipeline to quantify the coordination and overlap of transcription and replication...

Transcription-replication conflicts (TRCs) represent a potent endogenous source of replication stress. Besides the spatial and temporal coordination of replication and transcription programs, cells employ many additional mechanisms to resolve TRCs in a timely manner, thereby avoiding replication fork stalling and genomic instability. Proximity ligation assays (PLA) using antibodies against actively elongating RNA Polymerase II (RNAPIIpS2) and PCNA to detect proximity (<40nm) between transcribing RNA polymerases and replication forks can be used to assess and quantify TRC levels in cells. A complementary fluorescence microscopy approach to assess the spatial coordination of transcription and replication activities in the nucleus is to quantify the colocalization (200-400nm) between active transcription and ongoing replication using immunofluorescence staining with an antibody against elongating RNA Polymerase II (RNAPIIpS2) and EdU-Click-it pulse-labelling, respectively. Despite significant efforts to automate image analysis, the need for manual verification, correction, and complementation of automated processes creates a bottleneck for efficient, high-throughput and large-scale imaging. Here, we describe an automated Fiji image analysis macro that allows the user to automate the measurement of RNAPIIpS2 and EdU levels and extract the key parameters such as transcription-replication (TR) colocalization and TRC-PLA foci count from single cells in a high throughput manner. While we showcase the usability of this analysis pipeline for quantifying TR colocalization and TRC-PLA in mouse embryonic stem cells (mESCs), the analysis pipeline is designed as a generally applicable tool allowing the quantification of nuclear signals, colocalization and foci count in various model systems and cell types.