Similar Datasets
Project description:Enhancer elements in the human genome control how genes are expressed in specific cell types and harbor thousands of genetic variants that influence risk for common diseases1-4. Yet, we still do not know how enhancers regulate specific genes, and we lack general rules to predict enhancer-gene connections across cell types5,6. We developed an experimental approach, CRISPRi-FlowFISH, to perturb enhancers in the genome, and we applied it to test >3,500 potential enhancer-gene connections for 30 genes. We found that a simple activity-by-contact model substantially outperformed previous methods at predicting the complex connections in our CRISPR dataset. This activity-by-contact model allows us to construct genome-wide maps of enhancer-gene connections in a given cell type, on the basis of chromatin state measurements. Together, CRISPRi-FlowFISH and the activity-by-contact model provide a systematic approach to map and predict which enhancers regulate which genes, and will help to interpret the functions of the thousands of disease risk variants in the noncoding genome.
| S-EPMC6886585 | biostudies-literature
Project description:Mammalian genomes harbor millions of noncoding elements called enhancers that quantitatively regulate gene expression, but the mechanisms that determine which enhancers regulate which genes are not well understood. Here we describe a high-throughput approach, based on CRISPR interference, RNA FISH, and flow cytometry (CRISPRi-FlowFISH), to perturb enhancers in the genome and apply it to test >3,000 potential regulatory enhancer-gene connections across multiple genomic loci. Seemingly complex patterns of enhancer-gene connections in this dataset can largely be explained by a simple quantitative Activity-by-Contact (ABC) model, in which the effect of a candidate enhancer on a target gene is predicted by the intrinsic activity of the enhancer multiplied by the contact frequency between the enhancer and promoter. This ABC score can identify regulatory enhancer-gene connections and predict their quantitative effects from DNase-Seq, H3K27ac ChIP-seq, and Hi-C measurements. The ABC model can explain even complex regulatory phenomena including the ability of an enhancer to “skip” over one gene to regulate a more distant one. Our approach provides a foundation for dissecting mechanisms of enhancer-gene regulation and predicting enhancer-gene connections across cell types.
2019-10-21 | GSE124191 | GEO
Project description:Mammalian genomes harbor millions of noncoding elements called enhancers that quantitatively regulate gene expression, but the mechanisms that determine which enhancers regulate which genes are not well understood. Here we describe a high-throughput approach, based on CRISPR interference, RNA FISH, and flow cytometry (CRISPRi-FlowFISH), to perturb enhancers in the genome and apply it to test >3,000 potential regulatory enhancer-gene connections across multiple genomic loci. Seemingly complex patterns of enhancer-gene connections in this dataset can largely be explained by a simple quantitative Activity-by-Contact (ABC) model, in which the effect of a candidate enhancer on a target gene is predicted by the intrinsic activity of the enhancer multiplied by the contact frequency between the enhancer and promoter. This ABC score can identify regulatory enhancer-gene connections and predict their quantitative effects from DNase-Seq, H3K27ac ChIP-seq, and Hi-C measurements. The ABC model can explain even complex regulatory phenomena including the ability of an enhancer to “skip” over one gene to regulate a more distant one. Our approach provides a foundation for dissecting mechanisms of enhancer-gene regulation and predicting enhancer-gene connections across cell types.
2019-11-01 | GSE124193 | GEO
Project description:Mammalian genomes harbor millions of noncoding elements called enhancers that quantitatively regulate gene expression, but the mechanisms that determine which enhancers regulate which genes are not well understood. Here we describe a high-throughput approach, based on CRISPR interference, RNA FISH, and flow cytometry (CRISPRi-FlowFISH), to perturb enhancers in the genome and apply it to test >3,000 potential regulatory enhancer-gene connections across multiple genomic loci. Seemingly complex patterns of enhancer-gene connections in this dataset can largely be explained by a simple quantitative Activity-by-Contact (ABC) model, in which the effect of a candidate enhancer on a target gene is predicted by the intrinsic activity of the enhancer multiplied by the contact frequency between the enhancer and promoter. This ABC score can identify regulatory enhancer-gene connections and predict their quantitative effects from DNase-Seq, H3K27ac ChIP-seq, and Hi-C measurements. The ABC model can explain even complex regulatory phenomena including the ability of an enhancer to “skip” over one gene to regulate a more distant one. Our approach provides a foundation for dissecting mechanisms of enhancer-gene regulation and predicting enhancer-gene connections across cell types.
2019-10-21 | GSE118843 | GEO
Project description:Mammalian genomes harbor millions of noncoding elements called enhancers that quantitatively regulate gene expression, but the mechanisms that determine which enhancers regulate which genes are not well understood. Here we describe a high-throughput approach, based on CRISPR interference, RNA FISH, and flow cytometry (CRISPRi-FlowFISH), to perturb enhancers in the genome and apply it to test >3,000 potential regulatory enhancer-gene connections across multiple genomic loci. Seemingly complex patterns of enhancer-gene connections in this dataset can largely be explained by a simple quantitative Activity-by-Contact (ABC) model, in which the effect of a candidate enhancer on a target gene is predicted by the intrinsic activity of the enhancer multiplied by the contact frequency between the enhancer and promoter. This ABC score can identify regulatory enhancer-gene connections and predict their quantitative effects from DNase-Seq, H3K27ac ChIP-seq, and Hi-C measurements. The ABC model can explain even complex regulatory phenomena including the ability of an enhancer to “skip” over one gene to regulate a more distant one. Our approach provides a foundation for dissecting mechanisms of enhancer-gene regulation and predicting enhancer-gene connections across cell types.
2020-01-01 | GSE118878 | GEO
Project description:Mammalian genomes harbor millions of noncoding elements called enhancers that quantitatively regulate gene expression, but the mechanisms that determine which enhancers regulate which genes are not well understood. Here we describe a high-throughput approach, based on CRISPR interference, RNA FISH, and flow cytometry (CRISPRi-FlowFISH), to perturb enhancers in the genome and apply it to test >3,000 potential regulatory enhancer-gene connections across multiple genomic loci. Seemingly complex patterns of enhancer-gene connections in this dataset can largely be explained by a simple quantitative Activity-by-Contact (ABC) model, in which the effect of a candidate enhancer on a target gene is predicted by the intrinsic activity of the enhancer multiplied by the contact frequency between the enhancer and promoter. This ABC score can identify regulatory enhancer-gene connections and predict their quantitative effects from DNase-Seq, H3K27ac ChIP-seq, and Hi-C measurements. The ABC model can explain even complex regulatory phenomena including the ability of an enhancer to “skip” over one gene to regulate a more distant one. Our approach provides a foundation for dissecting mechanisms of enhancer-gene regulation and predicting enhancer-gene connections across cell types.
2019-10-21 | GSE118911 | GEO
Project description:Activity-by-Contact model of enhancer specificity from thousands of CRISPR perturbations
| PRJNA487267 | ENA
Project description:Activity-by-Contact model of enhancer specificity from thousands of CRISPR perturbations [ChIP-Seq]
| PRJNA510972 | ENA
Project description:Activity-by-Contact model of enhancer specificity from thousands of CRISPR perturbations [ATAC-Seq]
| PRJNA510974 | ENA
Project description:Activity-by-Contact model of enhancer specificity from thousands of CRISPR perturbations [RNA-Seq mouse]
| PRJNA487087 | ENA