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Embryonic Development via Enhancers and their Regulatory Landscapes


Nature  502, 499–506 (24 October 2013)

Topology of mammalian developmental enhancers and their regulatory landscapes

Wouter de Laat & Denis Duboule

Hubrecht Institute-KNAW and University Medical Center Utrecht, Uppsalalaan 8, 3584 CT, Utrecht, the Netherlands.

School of Life Sciences, Ecole Polytechnique Fédérale, CH-1015, Lausanne, Switzerland.

Department of Genetics and Evolution, University of Geneva, CH-1211, Geneva, Switzerland.


How a complex animal can arise from a fertilized egg is one of the oldest and most fascinating questions of biology, the answer to which is encoded in the genome. Body shape and organ development, and their integration into a functional organism all depend on the precise expression of genes in space and time. The orchestration of transcription relies mostly on surrounding control sequences such as enhancers, millions of which form complex regulatory landscapes in the non-coding genome. Recent research shows that high-order chromosome structures make an important contribution to enhancer functionality by triggering their physical interactions with target genes.

Access to animal genome sequences has revealed that the level of complexity of an organism does not relate to its number of genes. Mammals are more complex in morphology and behaviour than roundworms, but their genomes both contain around 20,000 genes. Various parameters can contribute to increased complexity, such as the extent of protein modifications or the diversity of splicing patterns.   Pleiotropy is another possible contributor, whereby genes acquire multiple functional tasks at different times and places either during development or in adult life. In this case, gene regulation, rather than function, had to evolve to associate regulatory alternatives to particular genes. Although gene transcription is initiated at promoters, which recruit the basal transcription machinery, these sequences have little impact on transcription control during development and hence this latter task mostly relies on enhancers.

Enhancers are sequence modules that contain binding motifs for transcription factors. They are preferentially located in the non-coding part of the genome, at various distances from their target genes. In mammals, more than 95% of the genome is non-coding and large gene deserts can sometimes span several megabases. The recent development of high-throughput methods has made it possible to systematically search for enhancers; millions of such regulatory modules have been predicted, with 40% of our genome now estimated to carry some regulatory potential. The importance of enhancers for normal development and disease is further underscored by the fact that disease-associated single nucleotide polymorphisms (SNPs) often co-localize with these modules. In addition, congenital diseases and cancers can be induced by chromosomal rearrangements that affect the regulatory neighbourhoods of target genes.

With so many more potential enhancers than genes, an outstanding task is to functionally connect mammalian regulatory sequences to target genes. In this context, the three-dimensional (3D) configuration of the genome is important because it must accommodate the physical contacts between promoters and distant enhancers. Chromosome conformation studies and genetic analyses of representative loci have recently started to uncover the complex and versatile mechanisms behind target gene selection and enhancer landscape recruitment. In this Review, we discuss a few specific cases involving long-range gene regulation in mammals to illustrate emerging principles whereby remote enhancers can achieve their functions in complex genomic environments.

Regulatory landscapes in mammalian genomes

Ÿ Around 20,000 genes

Ÿ More than 106 enhancers (potential regulatory sequences)

Ÿ About four enhancers contact an active gene on average per cell type

Ÿ Average enhancer–promoter loop size is 120 kb

Ÿ Largest enhancer–promoter distance so far (SOX9, Pierre Robin disease) is 1,300 kb

Ÿ 545 gene deserts (>640 kb, that is, top 3% largest deserts)

Ÿ Largest gene desert is 5.1 Mb

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