Modeling the evolutionary architectures of human enhancer sequences reveals distinct origins, functions, and associations with human-trait variation

ABSTRACTMotivationDespite the importance of gene regulatory enhancers in human biology and evolution, we lack a comprehensive evolutionary model of enhancer sequence architecture and function. This substantially limits our understanding of the genetic basis for divergence between species and our ability to interpret the effects of non-coding variants on human traits.ResultsTo explore enhancer sequence evolution and its relationship to regulatory function, we traced the evolutionary origins of human sequences with enhancer activity defined by eRNA from diverse tissues and cellular contexts. The majority of enhancers are sequences of a single evolutionary age (“simple” enhancer architectures), likely indicating constraint against genomic rearrangements. A minority of enhancers are composites of sequences of multiple evolutionary ages (“complex” enhancer architectures). Compared to simple enhancers, complex enhancers are older, more pleiotropic, and more active across species. Genetic variants within complex enhancers are also less likely to have effects on human traits and biochemical activity. Transposable-element-derived sequences have made diverse contributions to enhancer architectures; some have nucleated enhancers with simple architectures, while others have remodeled older sequences to create complex regulatory architectures.ConclusionsBased on these results, we propose a framework for modeling enhancer sequence architecture and evolution. Applying this framework to human enhancer sequences reveals multiple, distinct trajectories of human regulatory sequence evolution. Considering these evolutionary histories can aid interpretation of the effects of variants on enhancer function.

Motif signatures of transcribed enhancers

ABSTRACTIn mammalian cells, transcribed enhancers (TrEn) play important roles in the initiation of gene expression and maintenance of gene expression levels in spatiotemporal manner. One of the most challenging questions in biology today is how the genomic characteristics of enhancers relate to enhancer activities. This is particularly critical, as several recent studies have linked enhancer sequence motifs to specific functional roles. To date, only a limited number of enhancer sequence characteristics have been investigated, leaving space for exploring the enhancers genomic code in a more systematic way. To address this problem, we developed a novel computational method, TELS, aimed at identifying predictive cell type/tissue specific motif signatures. We used TELS to compile a comprehensive catalog of motif signatures for all known TrEn identified by the FANTOM5 consortium across 112 human primary cells and tissues. Our results confirm that distinct cell type/tissue specific motif signatures characterize TrEn. These signatures allow discriminating successfully a) TrEn from random controls, proxy of non-enhancer activity, and b) cell type/tissue specific TrEn from enhancers expressed and transcribed in different cell types/tissues. TELS codes and datasets are publicly available at http://www.cbrc.kaust.edu.sa/TELS.