Moussa, R. | Search bioRxiv

bioRxiv2024

Mechanistic basis of gene-specific transcription regulation by the Integrator complex

The Integrator complex (INT) regulates gene expression via premature transcription termination of RNA polymerase II (RNAP2) at promoter-proximal pausing sites. This attenuation of transcription is required for cellular response to external stimuli, cell differentiation and neurodevelopment. How gene-specific regulation is achieved by INT in an inducible manner remains unclear. Here, we identify two sites on INT subunits 13/14 that serve as direct binding hubs for diverse sets of sequence-specific transcription factors (TFs) and other transcription effector complexes. The TFs co-localize with INT genome-wide, increase INT abundance on target genes and co-regulate inducible transcriptional programs. Consistently, disruption of INT-TF contacts impairs sensory cilia formation in response to glucose starvation. Structural analysis places INTs TF binding hubs upstream of the transcription bubble when attached to paused RNAP2, consistent with simultaneous TF-promoter association. Our data establish TF-mediated recruitment of INT to promoters as a widespread mechanism for targeted and inducible transcription attenuation.

molecular biology↗

bioRxiv2021

GRaNIE and GRaNPA: Inference and evaluation of enhancer-mediated gene regulatory networks applied to study macrophages

Among the biggest challenges in the post-GWAS (genome-wide association studies) era is the interpretation of disease-associated genetic variants in non-coding genomic regions. Enhancers have emerged as key players in mediating the effect of genetic variants on complex traits and diseases. Their activity is regulated by a combination of transcription factors (TFs), epigenetic changes and genetic variants. Several approaches exist to link enhancers to their target genes, and others that infer TF-gene connections. However, we currently lack a framework that systematically integrates enhancers into TF-gene regulatory networks. Furthermore, we lack an unbiased way of assessing whether inferred regulatory interactions are biologically meaningful. Here we present two methods, implemented as user-friendly R packages: GRaNIE (Gene Regulatory Network Inference including Enhancers) for building enhancer-based gene regulatory networks (eGRNs) and GRaNPA (Gene Regulatory Network Performance Analysis) for evaluating GRNs. GRaNIE jointly infers TF-enhancer, enhancer-gene and TF-gene interactions by integrating open chromatin data such as ATAC-Seq or H3K27ac with RNA-seq across a set of samples (e.g. individuals), and optionally also Hi-C data. GRaNPA is a general framework for evaluating the biological relevance of TF-gene GRNs by assessing their performance for predicting cell-type specific differential expression. We demonstrate the power of our tool-suite by investigating gene regulatory mechanisms in macrophages that underlie their response to infection and cancer, their involvement in common genetic diseases including autoimmune diseases, and identify the TF PURA as putative regulator of pro-inflammatory macrophage polarisation. Availability- GRaNIE: https://bioconductor.org/packages/release/bioc/html/GRaNIE.html - GRaNPA: https://git.embl.de/grp-zaugg/GRaNPA Graphical abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

genomics↗