Claudia Chica

Cockayne syndrome (CS) and UV‐sensitive syndrome (UVSS) are rare genetic disorders caused by mutation of the DNA repair and multifunctional CSA or CSB protein, but only CS patients display a progeroid and neurodegenerative phenotype, providing a unique conceptual and experimental paradigm. As DNA methylation (DNAm) remodelling is a major ageing marker, we performed genome‐wide analysis of DNAm of fibroblasts from healthy, UVSS and CS individuals. Differential analysis highlighted a CS‐specific epigenomic signature (progeroid‐related; not present in UVSS) enriched in three categories: developmental transcription factors, ion/neurotransmitter membrane transporters and synaptic neuro‐developmental genes. A large fraction of CS‐specific DNAm changes were associated with expression changes in CS samples, including in previously reported post‐mortem cerebella. The progeroid phenotype of CS was further supported by epigenomic hallmarks of ageing: the prediction of DNAm of repetitive elements suggested an hypomethylation of Alu sequences in CS, and the epigenetic clock returned a marked increase in CS biological age respect to healthy and UVSS cells. The epigenomic remodelling of accelerated ageing in CS displayed both commonalities and differences with other progeroid diseases and regular ageing. CS shared DNAm changes with normal ageing more than other progeroid diseases do, and included genes functionally validated for regular ageing. Collectively, our results support the existence of an epigenomic basis of accelerated ageing in CS and unveil new genes and pathways that are potentially associated with the progeroid/degenerative phenotype.

We present ePeak, a Snakemake-based pipeline for the identification and quantification of reproducible peaks from raw ChIP-seq, CUT&RUN and CUT&Tag epigenomic profiling techniques. It also includes a statistical module to perform tailored differential marking and binding analysis with state of the art methods. ePeak streamlines critical steps like the quality assessment of the immunoprecipitation, spike-in calibration and the selection of reproducible peaks between replicates for both narrow and broad peaks. It generates complete reports for data quality control assessment and optimal interpretation of the results. We advocate for a differential analysis that accounts for the biological dynamics of each chromatin factor. Thus, ePeak provides linear and nonlinear methods for normalisation as well as conservative and stringent models for variance estimation and significance testing of the observed marking/binding differences. Using a published ChIP-seq dataset, we show that distinct populations of differentially marked/bound peaks can be identified. We study their dynamics in terms of read coverage and summit position, as well as the expression of the neighbouring genes. We propose that ePeak can be used to measure the richness of the epigenomic landscape underlying a biological process by identifying diverse regulatory regimes.