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Series GSE183939 Query DataSets for GSE183939
Status Public on Feb 24, 2022
Title DeepSTARR predicts enhancer activity from DNA sequence and enables the de novo design of synthetic enhancers
Organisms Drosophila melanogaster; Homo sapiens; synthetic construct
Experiment type Other
Summary 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.
 
Overall design Refer to individual Series
 
Citation(s) 35551305
Submission date Sep 10, 2021
Last update date May 26, 2022
Contact name Bernardo P de Almeida
E-mail(s) bernardo.almeida@imp.ac.at
Organization name Research Institute of Molecular Pathology (IMP)
Lab Stark Lab
Street address Campus-Vienna-Biocenter 1
City Wien
ZIP/Postal code 1030
Country Austria
 
Platforms (6)
GPL19604 Illumina HiSeq 2500 (synthetic construct)
GPL21697 NextSeq 550 (Homo sapiens)
GPL22106 NextSeq 550 (Drosophila melanogaster)
Samples (22)
GSM5574549 S2_dev_STARRseq_input
GSM5574550 S2_dev_STARRseq_rep1
GSM5574551 S2_dev_STARRseq_rep2
This SuperSeries is composed of the following SubSeries:
GSE183936 DeepSTARR predicts enhancer activity from DNA sequence and enables the de novo design of synthetic enhancers [Drosophila genome-wide UMI-STARR-seq]
GSE183937 DeepSTARR predicts enhancer activity from DNA sequence and enables the de novo design of synthetic enhancers [Drosophila oligo UMI-STARR-seq]
GSE183938 DeepSTARR predicts enhancer activity from DNA sequence and enables the de novo design of synthetic enhancers [Human oligo UMI-STARR-seq]
Relations
BioProject PRJNA762359

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Supplementary file Size Download File type/resource
GSE183939_RAW.tar 555.4 Mb (http)(custom) TAR (of BW)
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