Characterization of regulatory architectures

Transcription is controlled in part by events proximal to gene promoters, where transcription factors (TF) bind and promote the recruitment of RNA polymerase II, and in part by events at enhancers – regulatory regions remote from gene transcription start sites. Enhancers and promoters cooperate in regulatory architectures with varying complexities. The regulatory activities of such architectures are context specific and determined by the DNA and chromatin contexts and their combinations of bound TFs.

There are many kinds of regulatory architectures with distinct levels of output, flexibility and cell type-specificity. A comprehensive characterization of the properties and activities of regulatory architectures is therefore crucial to understand the regulation and dysregulation of differentiation, homeostasis and cell type specificity. The importance of well-characterized regulatory architectures is perhaps best appreciated in the genetic community since most polymorphic and disease-associated genetic variants do not locate within genes and are likely regulatory. However, while some genetic variants disrupting regulatory TF binding may be disease-causative, the majority of regulatory genetic variants are likely to have little effect on gene regulation. Architectures with redundant regulatory elements are likely less affected than those with one essential regulatory element, because the redundancy will buffer the effects.

Hence, a comprehensive characterization of enhancers in terms of their TF binding, target genes, and spatio-temporal activities is necessary to understand what determines cell type-specificity and how and when regulatory disruptions may have detrimental effects.

Transcription as a measure of regulatory activity

Regulatory active enhancers are themselves transcribed, producing long non-coding enhancer RNAs (eRNAs). The characteristics of enhancer RNAs, detected using Cap Analysis of Gene Expression (CAGE, genome-scale 5’ RACE), are sufficiently distinct from those of gene promoters to permit accurate genome-wide inference of enhancers. While steady-state output of RNA is heavily biased to the sense strand at mRNA promoters, eRNAs are bidirectionally balanced. Importantly, by massive assays, we have shown that enhancer transcription is a much better predictor of enhancer activity than chromatin characteristics (3-fold increase in validation rate). Hence, by focusing on the initiation sites of eRNAs genome-wide we may more accurately identify enhancers and study their properties in the correct cellular contexts.

Transcription data permits unprecedented modeling of regulatory architectures because both enhancer and promoter usage are measured with the same assay. Careful computational/statistical analysis of such data from appropriate experimental systems has a great potential for distinguishing the different modes of regulation and their functional impact.


The Andersson lab aims to systematically characterize regulatory architectures and delineate what determines their: (1) spatio-temporal activity; (2) robustness to regulatory genetic variation; and (3) dynamic activities over time. We take a genomics approach and use computational and statistical learning techniques to model transcriptional regulation.

Defining work

  • Andersson R, et al. 2014. An atlas of active enhancers across human cell types and tissues. Nature DOI
  • Andersson R, et al. 2014. Nuclear stability and transcriptional directionality separate functionally distinct RNA species. Nat Comms. DOI | preprint
  • Arner E, et al. 2015. Transcribed enhancers lead waves of coordinated transcription in transitioning mammalian cells. Science. DOI
  • Andersson R. 2015. Promoter or enhancer, what’s the difference? Deconstruction of established distinctions and presentation of a unifying model. BioEssays. DOI
  • Andersson R, et al. 2015. A Unified Architecture of Transcriptional Regulatory Elements. Trends Genet. DOI | preprint


  • Alvaro Rada Iglesias, University of Cologne
  • Josée Dostie, McGill University
  • Torben Heick Jensen, Aarhus University
  • Ferenc Müller, University of Birmingham

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