Ontology highlight
ABSTRACT:
PROVIDER: PRJNA715325 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR13994122_1.fastq.gz | Fastqsanger.gz | |||
| SRR13994122_2.fastq.gz | Fastqsanger.gz | |||
| SRR13994123_1.fastq.gz | Fastqsanger.gz | |||
| SRR13994123_2.fastq.gz | Fastqsanger.gz | |||
| SRR13994124_1.fastq.gz | Fastqsanger.gz |
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Project description:The genetic regulation of gene expression varies greatly across tissue-type and individuals and can be strongly influenced by the environment. Many variants, under healthy control conditions, may be silent or even have the opposite effect under diseased stress conditions. This study uses an in vivo mouse model to investigate how the effect of genetic variation changes with cellular stress across different tissues. Endoplasmic reticulum (ER) stress occurs when misfolded proteins accumulate in the ER. This triggers the unfolded protein response (UPR), a large transcriptional response which attempts to restore homeostasis. This transcriptional response, despite being a conserved, basic cellular process, is highly variable across different genetic backgrounds, making it an ideal system to study the dynamic effects of genetic variation. In this study, we sought to better understand how genetic variation alters expression across tissues, in the presence and absence of ER stress. The use of different mouse strains and their F1s allow us to also identify context specific cis- and trans- regulatory variation underlying variable transcriptional responses. We found hundreds of genes that respond to ER stress in a tissue- and/or genotype-dependent manner. The majority of the regulatory effects we identified were acting in cis-, which in turn, contribute to the variable ER stress- and tissue-specific transcriptional response. This study demonstrates the need for incorporating environmental stressors across multiple different tissues in future studies to better elucidate the effect of any particular genetic factor in basic biological pathways, like the ER stress response.
2022-11-01 | GSE189419 | GEO
Project description:The dynamic effec of genetic variation on the in vivo ER stress transcriptional response in different tissues
| PRJNA782981 | ENA
Project description:Endoplasmic reticulum (ER) stress occurs when misfolded proteins accumulate in the ER. The cellular response to ER stress involves complex transcriptional and translational changes, important to the survival of the cell. ER stress is a primary cause and a modifier of many human diseases. A first step to understanding how the ER stress response impacts human disease is to determine how the transcriptional response to ER stress varies among individuals. The genetic diversity of the eight mouse Collaborative Cross (CC) founder strains allowed us to determine how genetic variation impacts the ER stress transcriptional response. We used tunicamycin, a drug commonly used to induce ER stress, to elicit an ER stress response in mouse embryonic fibroblasts (MEFs) derived from the CC founder strains and measured their transcriptional responses. We identified hundreds of genes that differed in response to ER stress across these genetically diverse strains. Strikingly, inflammatory response genes differed most between strains; major canonical ER stress response genes showed relatively invariant responses across strains. To uncover the genetic architecture underlying these strain differences in ER stress response, we measured the transcriptional response to ER stress in MEFs derived from a subset of F1 crosses between the CC founder strains. We found a unique layer of regulatory variation that is only detectable under ER stress conditions. Over 80% of the regulatory variation under ER stress derives from cis-regulatory differences. This is the first study to characterize the genetic variation in ER stress transcriptional response in the laboratory mouse. Our findings indicate that the ER stress transcriptional response is highly variable among strains and arises from genetic variation in individual downstream response genes, rather than major signaling transcription factors. These results have important implications for understanding how genetic variation impacts the ER stress response, an important component of many human diseases.
2014-12-02 | GSE63756 | GEO
Project description:Endoplasmic reticulum (ER) stress occurs when misfolded proteins accumulate in the ER. The cellular response to ER stress involves complex transcriptional and translational changes, important to the survival of the cell. ER stress is a primary cause and a modifier of many human diseases. A first step to understanding how the ER stress response impacts human disease is to determine how the transcriptional response to ER stress varies among individuals. The genetic diversity of the eight mouse Collaborative Cross (CC) founder strains allowed us to determine how genetic variation impacts the ER stress transcriptional response. We used tunicamycin, a drug commonly used to induce ER stress, to elicit an ER stress response in mouse embryonic fibroblasts (MEFs) derived from the CC founder strains and measured their transcriptional responses. We identified hundreds of genes that differed in response to ER stress across these genetically diverse strains. Strikingly, inflammatory response genes differed most between strains; major canonical ER stress response genes showed relatively invariant responses across strains. To uncover the genetic architecture underlying these strain differences in ER stress response, we measured the transcriptional response to ER stress in MEFs derived from a subset of F1 crosses between the CC founder strains. We found a unique layer of regulatory variation that is only detectable under ER stress conditions. Over 80% of the regulatory variation under ER stress derives from cis-regulatory differences. This is the first study to characterize the genetic variation in ER stress transcriptional response in the laboratory mouse. Our findings indicate that the ER stress transcriptional response is highly variable among strains and arises from genetic variation in individual downstream response genes, rather than major signaling transcription factors. These results have important implications for understanding how genetic variation impacts the ER stress response, an important component of many human diseases. We investigated the genetic variation in ER stress transcriptional response in mouse embryonic fibroblasts (MEFs) across eight mouse strains: A/J, C57BL/6J, 129S1Sv/ImJ, NOD/ShiLtJ, NZO/H1LtJ, CAST/EiJ, PWK/PhJ, and WSB/EiJ. MEFs from each strain were treated with a control DMSO or ER stress-inducing drug, Tunicamycin (TM). To identify the genetic architecture underlying this genetic variation, MEFs from F1 strains were also studied. MEFs from the following F1s were evaluated: C57BL/6J X CAST/EiJ, C57BL/6J X 129S1Sv/ImJ, C57BL/6J X NOD/ShiLtJ, C57BL/6J X NZO/H1LtJ, and C57BL/6J X WSB/EiJ. Again F1 MEFS were treated with either DMSO or TM. There are two or three replicates for each sample.
2014-12-02 | E-GEOD-63756 | biostudies-arrayexpress
Project description:To measure natural variation in ER stress transcriptional response in a subset of lines from the Drosophila Genetic Reference Panel
2013-04-30 | GSE46425 | GEO
Project description:To measure natural variation in ER stress transcriptional response in a subset of lines from the Drosophila Genetic Reference Panel Transcriptional response to Tunicamycin and control conditions was measured at 8 hours of exposure (20 lines) and 20 hours of exposure (8 lines).
2013-04-30 | E-GEOD-46425 | biostudies-arrayexpress
Project description:Lysine methylation is abundant on histone proteins, representing a dynamic regulator of chromatin state and gene activity, but is also frequent on many nonhistone proteins, including eukaryotic elongation factor 1 alpha (eEF1A). However, the functional significance of eEF1Amethylation remains obscure and it has remained unclear whether eEF1A methylation is dynamic and subject to active regulation. We here demonstrate, using a wide range of in vitro and in vivo approaches, that the previously uncharacterized human methyltransferase METTL21B specifically targets Lys-165 in eEF1A in an aminoacyl-tRNA- and GTP-dependent manner. Interestingly, METTL21B mediated eEF1A methylation showed strong variation across different tissues and cell lines, and was induced by altering growth conditions or by treatment with certain ER-stress-inducing drugs, concomitant with an increase in METTL21B gene expression. Moreover, genetic ablation of METTL21B function in mammalian cells caused substantial alterations in mRNA translation, as measured by ribosome profiling. A non-canonical function for eEF1A in organization of the cellular cytoskeleton has been reported, and interestingly, METTL21B accumulated in centrosomes, in addition to the expected cytosolic localization. In summary, the present study identifies METTL21B as the enzyme responsible for methylation of eEF1A on Lys-165 and shows that this modification is dynamic, inducible and likely of regulatory importance.
2017-01-05 | GSE93133 | GEO
Project description:Apoptosis is a critical outcome of stress-induced processes, with the endoplasmic reticulum (ER) playing a central role in apoptotic protein processing and stress signal transduction. Profiling the ER proteome during stress to cell death offers valuable insights into these processes, but existing methods often suffer from a loss of in situ information or requirement of genetic manipulation. In this study, we introduce CAT-ER, a novel non-genetic ER proteomics system that provides in situ labeling, spatiotemporal resolution, and compatibility across diverse cell types. By combining an ER-targeted iridium photocatalyst with a thio-quinone methide (thioQM) probe, CAT-ER achieves high specificity in enriching ER proteins, comparable to traditional enzymatic methods. Importantly, CAT-ER is free of genetic manipulation, allowing its use in hard-to-transfect cell types like HeLa and immune cells (e.g., Raji, Jurkat, and RAW264.7). Given the high spatiotemporal resolution of CAT-ER, we revealed dynamic ER proteome changes during thapsigargin (Tg)-induced unfolded protein response (UPR) to apoptosis. Notably, NFIP2 mitigated ER stress by halting translation when UPR initiated, while compromised EMC2 delayed apoptosis during prolonged stress. These findings provide novel insights into the molecular dynamics linking the UPR and apoptosis. Collectively, CAT-ER serves as a versatile tool for spatiotemporal proteomic analysis without the need for genetic manipulation, offering a powerful approach to study ER dynamics in various biological contexts.
2025-07-23 | GSE298441 | GEO
Project description:Apoptosis is a critical outcome of stress-induced processes, with the endoplasmic reticulum (ER) playing a central role in apoptotic protein processing and stress signal transduction. Profiling the ER proteome during stress to cell death offers valuable insights into these processes, but existing methods often suffer from a loss of in situ information or requirement of genetic manipulation. In this study, we introduce CAT-ER, a novel non-genetic ER proteomics system that provides in situ labeling, spatiotemporal resolution, and compatibility across diverse cell types. By combining an ER-targeted iridium photocatalyst with a thio-quinone methide (thioQM) probe, CAT-ER achieves high specificity in enriching ER proteins, comparable to traditional enzymatic methods. Importantly, CAT-ER is free of genetic manipulation, allowing its use in hard-to-transfect cell types like HeLa and immune cells (e.g., Raji, Jurkat, and RAW264.7). Given the high spatiotemporal resolution of CAT-ER, we revealed dynamic ER proteome changes during thapsigargin (Tg)-induced unfolded protein response (UPR) to apoptosis. Notably, NFIP2 mitigated ER stress by halting translation when UPR initiated, while compromised EMC2 delayed apoptosis during prolonged stress. These findings provide novel insights into the molecular dynamics linking the UPR and apoptosis. Collectively, CAT-ER serves as a versatile tool for spatiotemporal proteomic analysis without the need for genetic manipulation, offering a powerful approach to study ER dynamics in various biological contexts.
2025-07-23 | GSE298442 | GEO