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Quantitative genome-wide enhancer activity maps for five Drosophila species show functional enhancer conservation and turnover during cis-regulatory evolution

ABSTRACT: Phenotypic differences between closely related species are thought to arise primarily from changes in gene expression due to mutations in cis-regulatory sequences (enhancers). However, it has remained unclear how frequently mutations alter enhancer activity or create functional enhancers de novo. Here we use STARR-seq, a recently developed quantitative enhancer assay, to determine genome-wide enhancer activity profiles for five Drosophila species in the constant trans-regulatory environment of Drosophila melanogaster S2 cells. We find that the functions of a large fraction of D. melanogaster enhancers are conserved for their orthologous sequences owing to selection and stabilizing turnover of transcription factor motifs. Moreover, hundreds of enhancers have been gained since the D. melanogaster-Drosophila yakuba split about 11 million years ago without apparent adaptive selection and can contribute to changes in gene expression in vivo. Our finding that enhancer activity is often deeply conserved and frequently gained provides functional insights into regulatory evolution.

ORGANISM(S): Drosophila ananassae Drosophila willistoni Drosophila yakuba Drosophila melanogaster Drosophila pseudoobscura

PROVIDER: GSE48251 | GEO | 2014/04/28

SECONDARY ACCESSION(S): PRJNA209379

REPOSITORIES: GEO

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Quantitative genome-wide enhancer activity maps for five Drosophila species show functional enhancer conservation and turnover during cis-regulatory evolution

Project description:Phenotypic differences between closely related species are thought to arise primarily from changes in gene expression due to mutations in cis-regulatory sequences (enhancers). However, it has remained unclear, how frequently mutations alter enhancer activity or create functional enhancers de novo. Here, we use STARR-seq, a recently developed quantitative enhancer assay, to determine genome-wide enhancer activity profiles for five Drosophila species in the constant trans-regulatory environment of D. melanogaster S2 cells. We find that the function of a large fraction of D. melanogaster enhancers is conserved in their orthologous sequences due to selection and stabilizing turnover of transcription factor motifs. Moreover, hundreds of enhancers have been gained since the D. melanogaster M-bM-^@M-^S D. yakuba split about 11 million years ago without apparent adaptive selection and can contribute to gene expression changes in vivo. Our finding that enhancer activity is often deeply conserved and frequently gained provides important functional insights into regulatory evolution. STARR-seq was performed in S2 cells with paired-end sequencing in two replicates and respective inputs using genomic DNA from different Drosophila species. RNA-seq was performed in a non-stranded manner without replicates for two Drosophila species.

2014-04-28 | E-GEOD-48251 | biostudies-arrayexpress

Mutant p63 affects epidermal cell identity through rewiring the enhancer landscape

Project description:<p>Transcription factor p63 is a key regulator of epidermal keratinocyte proliferation and differentiation. Mutations in the p63 DNA-binding domain are associated with Ectrodactyly Ectodermal Dysplasia Cleft Lip/Palate (EEC) syndrome. Underlying molecular mechanism of these mutations however remain unclear. Here we characterized the transcriptome and epigenome of p63 mutant keratinocytes derived from EEC patients. The transcriptome of p63 mutant keratinocytes deviated from the normal epidermal cell identity. Epigenomic analyses showed an altered enhancer landscape in p63 mutant keratinocytes contributed by loss of p63-bound active enhancers and by unexpected gain of enhancers. The gained enhancers were frequently bound by deregulated transcription factors such as RUNX1. Reversing RUNX1 overexpression partially rescued deregulated gene expression and the altered enhancer landscape. Our findings identify an unreported disease mechanism whereby mutant p63 rewires the enhancer landscape and affects epidermal cell identity, consolidating the pivotal role of p63 in controlling the enhancer landscape of epidermal keratinocytes.</p>

| phs001737 | dbGaP

Dynamic-network-guided CRISPRi screen identifies CTCF loop-constrained 1 nonlinear enhancer-gene regulatory activity in cell state transitions

Project description:Enhancers play key roles in gene regulation. However, comprehensive enhancer discovery is challenging because most enhancers, especially those affected in complex diseases, have weak effects on gene expression. Through gene regulatory network modeling, we identified that dynamic cell state transitions, a critical missing component in prevalent enhancer discovery strategies, can be utilized to improve the cells’ sensitivity to enhancer perturbation. Guided by the modeling results, we performed a mid-transition CRISPRi-based enhancer screen utilizing human embryonic stem cell definitive endoderm differentiation as a dynamic transition system. The screen discovered a comprehensive set of enhancers (4 to 9 per locus) for each of the core lineage-specifying transcription factors (TFs), including many enhancers with weak to moderate effects. Integrating the screening results with enhancer activity measurements (ATAC-seq, H3K27ac ChIP-seq) and three-dimensional enhancer-promoter interaction information (CTCF looping, Hi-C), we were able to develop a CTCF loop-constrained Interaction Activity (CIA) model that can better predict functional enhancers compared to models that rely on Hi-C-based enhancer-promoter contact frequency. Together, our dynamic network-guided enhancer screen and the CIA enhancer prediction model provide generalizable strategies for sensitive and more comprehensive enhancer discovery in both normal and pathological cell state transitions.

2023-06-17 | PXD043070 | Pride

Dissection of thousands of cell type-specific enhancers identifies dinucleotide repeat motifs as general enhancer features

Project description:Gene expression is determined by genomic elements called enhancers, which contain short motifs bound by different transcription factors (TFs). However, how enhancer sequences and TF motifs relate to enhancer activity is unknown and general sequence requirements for enhancers or comprehensive sets of important enhancer sequence elements have remained elusive. Here, we computationally dissect thousands of functional enhancer sequences from three different Drosophila cell lines. We find that the enhancers display distinct cis-regulatory sequence signatures, which are predictive of the enhancersM-bM-^@M-^Y cell type-specific or broad activities. These signatures contain transcription factor motifs and a novel class of enhancer sequence elements, dinucleotide repeat motifs (DRMs). DRMs are highly enriched in enhancers, particularly in enhancers that are broadly active across different cell types. We experimentally validate the importance of the identified TF motifs and DRMs for enhancer function and show that they can be sufficient to create an active enhancer de novo from non-functional sequence. The function of DRMs as a novel class of general enhancer features that are also enriched in human regulatory regions might explain their implication in several diseases and provides important insights into gene regulation. STARR-seq was performed in BG3 cells with paired-end sequencing in two replicates and respective inputs.

2014-04-02 | E-GEOD-49809 | biostudies-arrayexpress

DeepSTARR predicts enhancer activity from DNA sequence and enables the de novo design of synthetic enhancers

Project description:Enhancer sequences control gene expression and comprise binding sites (motifs) for different transcription factors (TFs). Despite extensive genetic and computational studies, the relationship between DNA sequence and regulatory activity is poorly understood and enhancer de novo design is considered impossible. Here we built a deep learning model, DeepSTARR, to quantitatively predict the activities of thousands of developmental and housekeeping enhancers directly from DNA sequence in Drosophila melanogaster S2 cells. The model learned relevant TF motifs and higher-order syntax rules, including functionally non-equivalent instances of the same TF motif that are determined by motif-flanking sequence and inter-motif distances. We validated these rules experimentally and demonstrated their conservation in human by testing more than 40,000 wildtype and mutant Drosophila and human enhancers. Finally, we designed and functionally validated synthetic enhancers with desired activities de novo. This SuperSeries is composed of the SubSeries listed below.

2022-02-24 | GSE183939 | GEO

DeepSTARR predicts enhancer activity from DNA sequence and enables the de novo design of synthetic enhancers [Drosophila oligo UMI-STARR-seq]

2022-02-24 | GSE183937 | GEO

DeepSTARR predicts enhancer activity from DNA sequence and enables the de novo design of synthetic enhancers [Human oligo UMI-STARR-seq]

2022-02-24 | GSE183938 | GEO

DeepSTARR predicts enhancer activity from DNA sequence and enables the de novo design of synthetic enhancers [Drosophila genome-wide UMI-STARR-seq]

2022-02-24 | GSE183936 | GEO

Genome-wide quantitative enhancer activity maps identified by STARR-seq

Project description:Genomic enhancers are important regulators of gene expression, but their identification is a challenge and methods depend on indirect measures of activity. We developed a method termed STARR-seq to directly and quantitatively assess enhancer activity for millions of candidates from arbitrary sources of DNA, enabling screens across entire genomes. When applied to the Drosophila genome, STARR-seq identifies thousands of cell type-specific enhancers across a broad continuum of strengths, linking differential gene expression to differences in enhancer activity and creating a genome-wide quantitative enhancer map. This map reveals the highly complex regulation of transcription, with several independent enhancers for both developmental regulators and ubiquitously expressed genes. STARR-seq can be used to identify and quantitate enhancer activity in other eukaryotes, including human. STARR-seq was performed in S2 and OSC cells with paired-end sequencing in two replicates and respective inputs. DHS-seq was done with single-end sequencing in two replicates for S2 and OSC cells. RNA-seq was performed with a strand-specific protocol using single-end sequencing in two replicates within S2 and OSC cells. STARR-seq was also performed in HeLa cells with single-end sequencing with a respective input.

2013-01-17 | E-GEOD-40739 | biostudies-arrayexpress

Hormone-responsive enhancer-activity maps reveal predictive motifs, indirect repression, and targeting of closed chromatin

Project description:Steroid hormones act as important developmental switches and their nuclear receptors regulate many genes. However, few hormone-dependent enhancers have been characterized and important aspects of their sequence architecture, cell type-specific activating and repressing functions, or the regulatory roles of their chromatin structure have remained unclear. We used STARR-seq, a recently developed enhancer-screening assay, and ecdysone signaling in two different Drosophila cell types to derive the first genome-wide hormone-dependent enhancer activity maps. We demonstrate that enhancer activation depends on cis-regulatory motif combinations that differ between cell types and can predict cell type-specific ecdysone targeting. Activated enhancers are often not accessible prior to induction. Enhancer repression following hormone treatment is independent of receptor motifs and receptor binding to the enhancer as we show using ChIP-seq, but appears to rely on motifs for other factors, including Eip74. Our strategy is applicable to study signal-dependent enhancers for different pathways and across organisms. STARR-seq was performed in S2 and OSC cells treated with ecdysone in two replicates. DHS-seq before and after treatment was done with single-end sequencing in two replicates. RNA-seq (with and without ecdysone) was performed with a strand-specific protocol using single-end sequencing in two replicates in S2. ChIP-seq (with and without ecdysone) was performed single-end sequencing in two replicates in S2 cells.

2014-03-27 | E-GEOD-47691 | biostudies-arrayexpress

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