Biology subjects

Pushkarev, O.

Publications and source records attributed to Pushkarev, O..

3 recordsLinked to original sources

bioRxiv2023

Non-coding variants impact cis-regulatory coordination in a cell type-specific manner

BACKGROUNDInteractions among cis-regulatory elements (CREs) play a crucial role in gene regulation. Various approaches have been developed to map these interactions genome-wide, including those relying on interindividual epigenomic variation to identify groups of covariable regulatory elements, referred to as chromatin modules (CMs). While CM mapping allows to investigate the relationship between chromatin modularity and gene expression, the computational principles used for CM identification vary in their application and outcomes. RESULTSWe comprehensively evaluate and streamline existing CM mapping tools and present guidelines for optimal utilization of epigenome data from a diverse population of individuals to assess regulatory coordination across the human genome. We showcase the effectiveness of our recommended practices by analysing distinct cell types and demonstrate cell type-specificity of CRE interactions in CMs and their relevance for gene expression. Integration of genotype information revealed that many non-coding disease-associated variants affect the activity of CMs in a cell type-specific manner by affecting the binding of cell type-specific transcription factors. We provide example cases that illustrate in detail how CMs can be used to deconstruct GWAS loci, understand variable expression of cell surface receptors in immune cells and reveal how genetic variation can impact the expression of prognostic markers in chronic lymphocytic leukaemia. CONCLUSIONSOur study presents an optimal strategy for CM mapping, and reveals how CMs capture the coordination of CREs and its impact on gene expression. Non-coding genetic variants can disrupt this coordination, and we highlight how this may lead to disease predisposition in a cell type-specific manner.

genomics↗

bioRxiv2023

ChromatinHD connects single-cell DNA accessibility and conformation to gene expression through scale-adaptive machine learning

1Machine learning methods that fully exploit the dual modality of single-cell RNA+ATAC-seq techniques are still lacking. Here, we developed ChromatinHD, a pair of models that uses the raw accessibility data, with-out peak-calling or windows, to predict gene expression and determine differentially accessible chromatin. We show how both models consistently outperform existing peak and window-based approaches, and find that this is due to a considerable amount of functional accessibility changes within and outside of putative cis-regulatory regions, both of which are uniquely captured by our models. Furthermore, ChromatinHD can delineate collaborating regions including their preferential genomic conformations that drive gene expression. Finally, our models also use changes in ATAC-seq fragment lengths to identify dense binding of transcription factors, a feature not captured by footprinting methods. Altogether, ChromatinHD, available at https://deplanckelab.github.io/ChromatinHD, is a suite of computational tools that enables a data-driven understanding of chromatin accessibility at various scales and how it relates to gene expression.

bioinformatics↗

bioRxiv2023

Context transcription factors establish cooperative environments and mediate enhancer communication

Many enhancers play a crucial role in regulating gene expression by assembling regulatory factor (RF) clusters, also referred to as condensates. This process is essential for facilitating enhancer communication and establishing cellular identity. However, how DNA sequence and transcription factor (TF) binding instruct the formation of such high RF environments is still poorly understood. To address this, we developed a novel approach leveraging enhancer-centric chromatin accessibility quantitative trait loci (caQTLs) to nominate RF clusters genome-wide. By analyzing TF binding signatures within the context of caQTLs, we discovered a new class of TFs that specifically contributes to establishing cooperative environments. These "context-only" TFs bind promiscuously with cell type-specific pioneers, recruit coactivators, and, like super enhancers, render downstream gene expression sensitive to condensate-disrupting molecules. We further demonstrate that joint context-only and pioneer TF binding explains enhancer compatibility and provides a mechanistic rationale for how a loose TF syntax can still confer regulatory specificity.

molecular biology↗