Biology subjects

Wissink, E. M.

Publications and source records attributed to Wissink, E. M..

3 recordsLinked to original sources

bioRxiv2023

Cis-regulatory control of transcriptional timing and noise in response to estrogen

Cis-regulatory elements control transcription levels, temporal dynamics, and cell-cell variation or transcriptional noise. However, the combination of regulatory features that control these different attributes is not fully understood. Here, we used single cell RNA-seq during an estrogen treatment time course and machine learning to identify predictors of expression timing and noise. We find that genes with multiple active enhancers exhibit faster temporal responses. We verified this finding by showing that manipulation of enhancer activity changes the temporal response of estrogen target genes. Analysis of transcriptional noise uncovered a relationship between promoter and enhancer activity, with active promoters associated with low noise and active enhancers linked to high noise. Finally, we observed that co-expression across single cells is an emergent property associated with chromatin looping, timing, and noise. Overall, our results indicate a fundamental tradeoff between a genes ability to quickly respond to incoming signals and maintain low variation across cells.

genomics↗

bioRxiv2021

Glucocorticoid receptor collaborates with pioneer factors and AP-1 to execute genome-wide regulation

AO_SCPLOWBSTRACTC_SCPLOWThe glucocorticoid receptor (GR) regulates transcription through binding to specific DNA motifs, particularly at enhancers. While the motif to which it binds is constant across cell types, GR has cell type-specific binding at genomic loci, resulting in regulation of different genes. The presence of other bound transcription factors (TFs) is hypothesized to strongly influence where GR binds. Here, we addressed the roles of other TFs in the glucocorticoid response by comparing changes in GR binding and nascent transcription at promoters and distal candidate cis-regulatory elements (CCREs) in two distinct human cancer cell types. We found that after glucocorticoid treatment, GR binds to thousands of genomic loci that are primarily outside of promoter regions and are potentially enhancers. The majority of these GR binding sites are cell-type specific, and they are associated with pioneer factor binding. A small fraction of GR occupied regions (GORs) displayed increased bidirectional nascent transcription, which is a characteristic of many active enhancers, after glucocorticoid treatment. Non-promoter GORs with increased transcription were specifically enriched for AP-1 binding prior to glucocorticoid treatment. These results support a model of transcriptional regulation in which multiple classes of TFs are required. The pioneer factors increase chromatin accessibility, facilitating the binding of GR and additional factors. AP-1 binding poises a fraction of accessible sites to be rapidly transcribed upon glucocorticoid-induced GR binding. The coordinated activity of multiple TFs then results in cell type-specific changes in gene expression. We anticipate that many models of inducible gene expression also require multiple distinct TFs that act at multiple steps of transcriptional regulation.

genomics↗

bioRxiv2020

A rapid, sensitive, scalable method for Precision Run-On sequencing (PRO-seq)

Tracking active transcription with the nuclear run-on (NRO) assays has been instrumental in uncovering mechanisms of gene regulation. The coupling of NROs with high-throughput sequencing has facilitated the discovery of previously unannotated or undetectable RNA classes genome-wide. Precision run-on sequencing (PRO-seq) is a run-on variant that maps polymerase active sites with nucleotide or near-nucleotide resolution. One main drawback to this and many other nascent RNA detection methods is the somewhat intimidating multi-day workflow associated with creating the libraries suitable for high-throughput sequencing. Here, we present an improved PRO-seq protocol where many of the enzymatic steps are carried out while the biotinylated NRO RNA remains bound to streptavidin-coated magnetic beads. These adaptations reduce time, sample loss and RNA degradation, and we demonstrate that the resulting libraries are of the same quality as libraries generated using the original published protocol. The assay is also more sensitive which permits reproducible, high-quality libraries from 104-105 cells instead of 106-107. Altogether, the improved protocol is more tractable allows for nascent RNA profiling from small samples, such as rare samples or FACS sorted cell populations.

genomics↗