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GEO help: Mouse over screen elements for information. |
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| Status |
Public on Jan 31, 2025 |
| Title |
Interpretable deep learning reveals the sequence rules of Hippo signaling (RNA-Seq) |
| Organism |
Mus musculus |
| Experiment type |
Expression profiling by high throughput sequencing
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| Summary |
How specific cells respond to signaling pathways is largely encoded in the DNA sequence. However, the sequence rules result from complex interactions between signaling and cell-type-specific transcription factors and are considered intractable by traditional methods. Here, we leverage interpretable deep learning on high-resolution data and extensive validation experiments to identify the sequence rules for the Hippo pathway in mouse trophoblast stem cells. We show that Tead4 and Yap1 engage in two types of cooperativity. First, their binding is enhanced by cell-type-specific transcription factors, including Tfap2c, in a distance-dependent manner. Second, a strictly-spaced Tead double motif is a canonical Hippo pathway element that mediates strong Tead4 cooperativity through transient protein-protein interactions on DNA. These mechanisms occur genome-wide and allow us to predict how small sequence changes alter the activity of enhancers in vivo. This illustrates the power of interpretable deep learning to decode canonical and cell type-specific sequence rules of signaling pathways.
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| Overall design |
RNA-seq and Nascent RNA captured through TT-seq method (Schwalb et al. 2016) in wild-type mouse trophoblast stem cells (Singh and Gerton 2021). RNA-seq in CRISPR mutatated cell lines at genomic region of chr17:6,827,739-6,828,394 (putative enhancer for Ezrin gene consisting for Tead double motif)
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| Web link |
https://doi.org/10.1101/2024.02.22.580842
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| Contributor(s) |
Dalal K, McAnany C, Weilert M, McKinney C, Krueger S, Zeitlinger J |
| Citation missing |
Has this study been published? Please login to update or notify GEO. |
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| Submission date |
Jan 03, 2024 |
| Last update date |
Feb 01, 2025 |
| Contact name |
Khyati Sudhir Dalal |
| E-mail(s) |
khyatidalal0805@gmail.com
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| Organization name |
Stowers Institute for Medical Research
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| Street address |
75th street, APT 106, 6329 W
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| City |
Overland Park |
| State/province |
KS |
| ZIP/Postal code |
66204 |
| Country |
USA |
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| Platforms (2) |
| GPL19057 |
Illumina NextSeq 500 (Mus musculus) |
| GPL30172 |
NextSeq 2000 (Mus musculus) |
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| Samples (9)
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| GSM8001681 |
mTSC,ezrmut,rna,1 |
| GSM8001682 |
mTSC,ezrmut,rna,2 |
| GSM8001683 |
mTSC,ezrmut,rna,3 |
| GSM8001684 |
mTSC,wildtype,nascent_rna,1 |
| GSM8001685 |
mTSC,wildtype,nascent_rna,2 |
| GSM8001686 |
mTSC,wildtype,nascent_rna,3 |
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| This SubSeries is part of SuperSeries: |
| GSE252463 |
Interpreting regulatory mechanisms of Hippo signaling through a deep learning sequence model |
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| Relations |
| BioProject |
PRJNA1060693 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE252462_mtsc_nascent_rna_combined_negative.bw |
185.7 Mb |
(ftp)(http) |
BW |
| GSE252462_mtsc_nascent_rna_combined_positive.bw |
172.7 Mb |
(ftp)(http) |
BW |
| GSE252462_mtsc_starcount_table_rep1.csv.gz |
242.3 Kb |
(ftp)(http) |
CSV |
| GSE252462_mtsc_starcount_table_rep2.csv.gz |
248.5 Kb |
(ftp)(http) |
CSV |
| GSE252462_mtsc_starcount_table_rep3.csv.gz |
245.3 Kb |
(ftp)(http) |
CSV |
| GSE252462_mtsc_tpm_rep1.csv.gz |
477.4 Kb |
(ftp)(http) |
CSV |
| GSE252462_mtsc_tpm_rep2.csv.gz |
481.6 Kb |
(ftp)(http) |
CSV |
| GSE252462_mtsc_tpm_rep3.csv.gz |
478.3 Kb |
(ftp)(http) |
CSV |
| GSE252462_wildtype_ezrmut_differential_analysis_edgeR.tsv.gz |
489.9 Kb |
(ftp)(http) |
TSV |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data are available on Series record |
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