Ribosome biogenesis disruption mediated chromatin structure changes revealed by SRAtac, a customizable end to end analysis pipeline for ATAC-seq

Abstract

The nucleolus is a large nuclear body that serves as the primary site for ribosome biogenesis. Recent studies have suggested that it also plays an important role in organizing chromatin architecture. However, to establish a causal relationship between nucleolar ribosome assembly and chromatin architecture, genetic tools are required to disrupt nucleolar ribosome biogenesis. In this study, we used ATAC-seq to investigate changes in chromatin accessibility upon specific depletion of two ribosome biogenesis components, RPOA-2 and GRWD-1, in the model organism Caenorhabditis elegans. To facilitate the analysis of ATAC-seq data, we introduced two tools: SRAlign, an extensible NGS data processing workflow, and SRAtac, a customizable end-to-end ATAC-seq analysis pipeline. Our results revealed highly comparable changes in chromatin accessibility following both RPOA-2 and GRWD-1 perturbations. However, we observed a weak correlation between changes in chromatin accessibility and gene expression. While our findings corroborate the idea of a feedback mechanism between ribosomal RNA synthesis, nucleolar ribosome large subunit biogenesis, and chromatin structure during the L1 stage of C. elegans development, they also prompt questions regarding the functional impact of these alterations on gene expression.

Cactus: a user-friendly and reproducible ATAC-Seq and mRNA-Seq analysis pipeline for data preprocessing, differential analysis, and enrichment analysis

“…mRNA-Seq measures gene expression, while ATAC-Seq measures chromatin accessibility, both without the need to optimize the assay for a specific set of molecules or genomic regions. Many pipelines exist to analyze mRNA-Seq and ATAC-Seq data, but most of them only go as far as peak calling for ATAC-Seq [10][11][12] or differential gene expression analysis for mRNA-Seq [13,14], leaving many researchers in need of deeper biological insights. Particularly, combining omics results from different methods and performing enrichment analyses is often done in a lowthroughput, time-consuming, and hard-to-reproduce manner, creating a strong need for pipelines that offer easy automation of these steps.…”