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  • Review Article
  • Published:

In pursuit of design principles of regulatory sequences

Nature Reviews Genetics volume 15, pages 453–468 (2014)Cite this article

Subjects

Key Points

  • Regulatory DNA sequences contain information on the timing and level at which different genes are expressed. An ongoing challenge is to uncover the means by which this information is encoded and executed, and thereby also advance our understanding of fundamental biological processes such as development, differentiation and disease.

  • High-throughput methods for in vitro characterization of transcription factor (TF) sequence preferences and for in vivo genome-wide measurements of TF binding improved our understanding of fundamental 'building blocks' of regulatory sequences — namely, TF binding sites (TFBSs). However, these also revealed a pronounced gap between predictions based on the in vitro-derived motifs and the binding patterns observed in cells.

  • Different states of regulatory proteins (such as TFs) in different in vivo conditions or cell types, including the formation of complexes and interaction with cofactors, can result in differential sequence preferences. Accounting for these preferences can help to bridge the gap between in vitro characterization of binding specificity and binding profiles obtained in vivo.

  • TFBSs appear in a range of combinations and organizations within regulatory sequences. The extent to and the manner by which the expression outcome depends on properties of the composition and arrangement of these regulatory architectures differ. For some regulatory sequences, functional dependencies (for example, on the number of TFBSs or the relative distance between these sites) can be characterized, which provides hints into the mechanisms involved (for example, TF cooperativity).

  • The sequence context in which TFBSs are embedded can have important effects on TF binding and the expression outcome. These include effects of TFBS-flanking base pairs, which may be mediated by DNA shape, and effects related to GC content, as may be mediated by nucleosome occupancy.

  • A surge of new methods that couple the classic reporter assay with high-throughput sequencing provide efficient means for quantitatively examining the ability of many thousands of different sequences — both derived from native genomic sequences and systematically designed — to drive gene expression. A challenge for future research is to improve our mechanistic and predictive understanding of these data sets, as well as their relationship to the endogenous activity of promoters and enhancers.

  • An improved understanding of various properties of regulatory sequences and their functional implications can facilitate a better interpretation of personal genomes. There are already efforts to incorporate regulatory annotations into genome-wide association studies and expression quantitative trait locus analyses.

Abstract

Instructions for when, where and to what level each gene should be expressed are encoded within regulatory sequences. The importance of motifs recognized by DNA-binding regulators has long been known, but their extensive characterization afforded by recent technologies only partly accounts for how regulatory instructions are encoded in the genome. Here, we review recent advances in our understanding of regulatory sequences that influence transcription and go beyond the description of motifs. We discuss how understanding different aspects of the sequence-encoded regulation can help to unravel the genotype–phenotype relationship, which would lead to a more accurate and mechanistic interpretation of personal genome sequences.

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Figure 1: Mechanisms affecting transcription factor binding: beyond simple binding site specificities.
Figure 2: Properties of regulatory sequence architectures.
Figure 3: A possible scheme for the incorporation of regulatory annotations to the analysis of expression quantitative trait loci.

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Acknowledgements

This work was supported by grants from the European Research Council and the US National Institutes of Health to E.S. M.L. thanks the Azrieli Foundation for the award of an Azrieli Fellowship.

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Authors and Affiliations

  1. Department of Molecular Cell Biology, and Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, 76100, Israel

    Michal Levo & Eran Segal

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  1. Michal Levo
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Correspondence to Eran Segal.

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PowerPoint slides

Glossary

Genome-wide association studies

(GWASs). Genome-wide studies that are designed to identify genetic associations with an observable trait, disease or condition.

Expression quantitative trait locus

(eQTL). A locus at which genetic variation is associated with variation in gene expression levels.

In vivo

In the context of this Review, in vivo refers to experiments carried out in living cells, regardless of whether the cells are within or outside a whole organism (sometimes referred to as ex vivo).

Position weight matrices

(PWMs). Representations for the specificity of DNA-binding proteins, in which a score is assigned to every possible base pair at each position in the binding site. A PWM score for a specific sequence is the sum of position-specific scores for each of its base pair.

Dissociation constant

(Kd). The dissociation constant between two molecules (in this context, for a transcription factor and a DNA sequence). It is the ratio of the off:on rate for the formation and dissolution of the complex.

Orthologous

Pertaining to loci in two species that are derived from a common ancestral locus.

Homotypic TFBS cluster

A cluster of multiple transcription factor binding sites for the same transcription factor.

Heterotypic clustering

Clustering of multiple transcription factor binding sites for different transcription factors.

Regression model

A model that describes the relationship between a dependent variable and one or more independent variables.

Linkage disequilibrium

(LD). A nonrandom association of alleles at different loci (as might be observed for particular alleles at neighbouring loci that tend to be co-inherited).

DNase I sensitivity QTLs

(dsQTLs). Locations at which DNaseI hypersensitive site sequencing read depth significantly correlates with the genotypes at nearby single-nucleotide polymorphisms, or insertions or deletions.

Bayesian approach

A modelling approach that uses Bayes' rule and that computes a posterior probability that a hypothesis is true using a combination of prior beliefs and observed data.

k-nearest neighbours

(KNN). A non-parametric regression method that predicts the value of a new point on the basis of the values of the k closest training points in the feature space.

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Levo, M., Segal, E. In pursuit of design principles of regulatory sequences. Nat Rev Genet 15, 453–468 (2014). https://doi.org/10.1038/nrg3684

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