Detecting chromosomal interactions in Capture Hi-C data with CHiCAGO and companion tools.

Capture Hi-C is widely used to obtain high-resolution profiles of chromosomal interactions involving, at least on one end, regions of interest such as gene promoters. Signal detection in Capture Hi-C data is challenging and cannot be adequately accomplished with tools developed for other chromosome conformation capture methods, including standard Hi-C. Capture Hi-C Analysis of Genomic Organization (CHiCAGO) is a computational pipeline developed specifically for Capture Hi-C analysis. It implements a statistical model accounting for biological and technical background components, as well as bespoke normalization and multiple testing procedures for this data type. Here we provide a step-by-step guide to the CHiCAGO workflow that is aimed at users with basic experience of the command line and R. We also describe more advanced strategies for tuning the key parameters for custom experiments and provide guidance on data preprocessing and downstream analysis using companion tools. In a typical experiment, CHiCAGO takes ~2-3 h to run, although pre- and postprocessing steps may take much longer.

Tri-methylation of histone H3 lysine 4 facilitates gene expression in ageing cells.

Transcription of protein coding genes is accompanied by recruitment of COMPASS to promoter-proximal chromatin, which methylates histone H3 lysine 4 (H3K4) to form H3K4me1, H3K4me2 and H3K4me3. Here, we determine the importance of COMPASS in maintaining gene expression across lifespan in budding yeast. We find that COMPASS mutations reduce replicative lifespan and cause expression defects in almost 500 genes. Although H3K4 methylation is reported to act primarily in gene repression, particularly in yeast, repressive functions are progressively lost with age while hundreds of genes become dependent on H3K4me3 for full expression. Basal and inducible expression of these genes is also impaired in young cells lacking COMPASS components Swd1 or Spp1. Gene induction during ageing is associated with increasing promoter H3K4me3, but H3K4me3 also accumulates in non-promoter regions and the ribosomal DNA. Our results provide clear evidence that H3K4me3 is required to maintain normal expression of many genes across organismal lifespan.