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

ABSTRACT: 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.

ORGANISM(S): synthetic construct Drosophila melanogaster

PROVIDER: GSE183937 | GEO | 2022/02/24

REPOSITORIES: GEO

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

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

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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.

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