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| Status |
Public on May 11, 2022 |
| Title |
Glucocorticoid receptor-regulated enhancers play a central role in the gene regulatory networks underlying drug addiction |
| Organism |
Rattus norvegicus |
| Experiment type |
Expression profiling by high throughput sequencing
Genome binding/occupancy profiling by high throughput sequencing
Other
Non-coding RNA profiling by high throughput sequencing
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| Summary |
Substance abuse and addiction represent a major public health problem that impacts multiple dimensions of society, including healthcare, economy, and workforce. In 2021, over 100,000 drug overdose deaths have been reported in the US with an alarming increase in fatalities related to opioids and psychostimulants. Understanding of the fundamental gene regulatory mechanisms underlying addiction and related behaviors could facilitate more effective treatments. To explore how repeated drug exposure alters gene regulatory networks in the brain, we combined capped small (cs)RNA-seq, which accurately captures nascent-like initiating transcripts from total RNA, with Hi-C and single nuclei (sn)ATAC-seq. We profiled initiating transcripts in two addiction-related brain regions, the prefrontal cortex (PFC) and the nucleus accumbens (NAc), from rats that were never exposed to drugs or were subjected to prolonged abstinence after oxycodone or cocaine intravenous self-administration (IVSA). Interrogating in total over 100,000 active transcription start regions (TSRs) revealed that most TSRs had hallmarks of bona-fide enhancers and highlighted the KLF/SP1, RFX and AP1 transcription factors families as central to establishing brain-specific gene regulatory programs. Analysis of rats with addiction-like behaviors versus controls, identified addiction-associated repression of transcription at regulatory enhancers recognized by nuclear receptor subfamily 3 group C (NR3C) factors, which include glucocorticoid receptors. Cell-type deconvolution analysis using snATAC-seq uncovered a potential role of glial cells in driving the gene regulatory programs associated with addiction-related phenotypes. These findings highlight the power of advanced transcriptomics methods to provide insight into how addiction perturbs gene regulatory programs in the brain.
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| Overall design |
Transcription initiation profiling (csRNA-seq), 3D genome structure (Hi-C), and single cell open chromatin profiling (snATAC-seq) all using high-throughput sequencing
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| Contributor(s) |
Duttke SH, Montilla-Perez P, Chang MW, Li H, Chen H, Carrette LL, de Guglielmo G, George O, Palmer AA, Benner C, Telese F |
| Citation(s) |
35651629 |
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| Submission date |
Jan 15, 2022 |
| Last update date |
Jun 21, 2022 |
| Contact name |
Christopher Benner |
| E-mail(s) |
cbenner@ucsd.edu
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| Organization name |
University of California, San Diego (UCSD)
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| Department |
Medicine
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| Street address |
9500 Gilman Dr. MC 0640
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| City |
La Jolla |
| State/province |
California |
| ZIP/Postal code |
92093-0640 |
| Country |
USA |
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| Platforms (2) |
| GPL20084 |
Illumina NextSeq 500 (Rattus norvegicus) |
| GPL25947 |
Illumina NovaSeq 6000 (Rattus norvegicus) |
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| Samples (36)
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| Relations |
| BioProject |
PRJNA797649 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE193757_RAW.tar |
3.6 Gb |
(http)(custom) |
TAR (of CSV, H5, HIC, TSV) |
| GSE193757_gene_counts.txt.gz |
544.2 Kb |
(ftp)(http) |
TXT |
| GSE193757_tsr.nac.bed.gz |
1.2 Mb |
(ftp)(http) |
BED |
| GSE193757_tsr.pfc.bed.gz |
1.6 Mb |
(ftp)(http) |
BED |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
| Processed data are available on Series record |
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