Embryonic Stem Cells: A Perfect Tool for Studying Mammalian Transcriptional Enhancers

Enhancer RNA: What we know and what we can achieve

Enhancers are important cis-acting elements that can regulate gene transcription and cell fate alongside promoters. In fact, many human cancers and diseases are associated with the malfunction of enhancers. Recent studies have shown that enhancers can produce enhancer RNAs (eRNAs) by RNA polymerase II. In this review, we discuss eRNA production, characteristics, functions and mechanics. eRNAs can determine chromatin accessibility, histone modification and gene expression by constructing a 'chromatin loop', thereby bringing enhancers to their target gene. eRNA can also be involved in the phase separation with enhancers and other proteins. eRNAs are abundant, and importantly, tissue-specific in tumours, various diseases and stem cells; thus, eRNAs can be a potential target for disease diagnosis and treatment. As eRNA is produced from the active transcription of enhancers and is involved in the regulation of cell fate, its manipulation will influence cell function, and therefore, it can be a new target for biological therapy.

Nanog Expression in Embryonic Stem Cells - An Ideal Model System to Dissect Enhancer Function

Embryonic stem cells (ESCs) are derived from the preimplantation embryo and can differentiate into virtually any other cell type (termed pluripotency), which is governed by lineage specific transcriptions factors (TFs) binding to cis regulatory elements (CREs) to mediate changes in gene expression. The reliance on transcriptional regulation to maintain pluripotency makes ESCs a valuable model to study the role of distal CREs such as enhancers in modulating gene expression to affect cell fate decisions. This review will highlight recent advance on transcriptional enhancers, focusing on studies performed in ESCs. In addition, we argue that the Nanog locus, which encodes for an ESC-critical TF, is particularly informative because it contains multiple co-regulated genes and enhancers in close proximity to one another. The unique landscape at Nanog permits the study of ongoing questions including whether multiple enhancers function additively versus synergistically, determinants of gene specificity, and cell-to-cell variability in gene expression.

EP-DNN: A Deep Neural Network-Based Global Enhancer Prediction Algorithm

We present EP-DNN, a protocol for predicting enhancers based on chromatin features, in different cell types. Specifically, we use a deep neural network (DNN)-based architecture to extract enhancer signatures in a representative human embryonic stem cell type (H1) and a differentiated lung cell type (IMR90). We train EP-DNN using p300 binding sites, as enhancers, and TSS and random non-DHS sites, as non-enhancers. We perform same-cell and cross-cell predictions to quantify the validation rate and compare against two state-of-the-art methods, DEEP-ENCODE and RFECS. We find that EP-DNN has superior accuracy with a validation rate of 91.6%, relative to 85.3% for DEEP-ENCODE and 85.5% for RFECS, for a given number of enhancer predictions and also scales better for a larger number of enhancer predictions. Moreover, our H1 → IMR90 predictions turn out to be more accurate than IMR90 → IMR90, potentially because H1 exhibits a richer signature set and our EP-DNN model is expressive enough to extract these subtleties. Our work shows how to leverage the full expressivity of deep learning models, using multiple hidden layers, while avoiding overfitting on the training data. We also lay the foundation for exploration of cross-cell enhancer predictions, potentially reducing the need for expensive experimentation.

Enhancer transcribed RNAs arise from hypomethylated, Tet-occupied genomic regions

Enhancers are cis-acting elements capable of regulating transcription in a distance and orientation-independent manner. A subset of enhancers are occupied by RNA polymerase II (RNAP II) and transcribed to produce long non-coding RNAs termed eRNAs. We thoroughly investigated the association between eRNA productivity and various chromatin marks and transcriptional regulators in mouse embryonic stem cells (ESCs) through an integrative approach. We found that eRNA-producing enhancers exhibited elevated levels of the active mark H3K27Ac, decreased DNA methylation, and enrichment for the DNA hydroxylase Tet1. Many eRNA-producing enhancers have recently been characterized as "super-enhancers," suggesting an important role in the maintenance of pluripotency. Using experimental methods, we focally investigated a well-characterized enhancer linked to the Nanog locus and confirmed its exclusive eRNA productivity in ESCs. We further demonstrate that the binding of Sall4 and Tet family proteins were required for eRNA productivity at this locus. Collectively, we demonstrate that Tet1 binding and DNA hypomethylation are hallmarks of eRNA production.