Hi-C analyses with GENOVA: a case study with cohesin variants

Abstract Conformation capture-approaches like Hi-C can elucidate chromosome structure at a genome-wide scale. datasets are large and require specialised software. Here, we present GENOVA: user-friendly software package to analyse visualise conformation capture (3C) data. GENOVA is an R-package that includes the most common analyses, such as compartment insulation score analysis. It create annotated heatmaps contact frequency specific locus aggregate signal over user-specified genomic regions ChIP-seq Finally, our supports output from major mapping-pipelines. We demonstrate capabilities of by analysing data HAP1 cell lines in which cohesin-subunits SA1 SA2 were knocked out. find ?SA1 cells gain intra-TAD interactions increase compartmentalisation. ?SA2 have longer loops less compartmentalised genome. These results suggest cohesinSA1 forms loops, while cohesinSA2 plays role forming maintaining interactions. Our model genome provided 3D counter-balancing loop formation on one hand, compartmentalization other hand. By differentially controlling therefore also affect nuclear compartmentalization. show easy use R-package, allows researchers explore great detail.