A portal to visualize transcriptome profiles in mouse models of neurological disorders
Open accessAbstract
Target nomination for drug development has been a major challenge in the path to finding a cure for several neurological disorders. Comprehensive transcriptome profiles have revealed brain gene expression changes associated with many neurological disorders, and the functional validation of these changes is a critical next step. Model organisms are a proven approach for the elucidation of disease mechanisms, including screening of gene candidates as therapeutic targets. Frequently, multiple models exist for a given disease, creating a challenge to select the optimal model for validation and functional follow-up. To help in nominating the best mouse models for studying neurological diseases, we developed a web portal to visualize mouse transcriptomic data related to neurological disorders. Users can examine gene expression changes across mouse model studies to help select the optimal mouse model for further investigation. The portal provides access to mouse studies related to Alzheimer’s diseases (AD), Parkinson’s disease (PD), Huntington’s disease (HD), Amyotrophic Lateral Sclerosis (ALS), Spinocerebellar ataxia (SCA), and models related to aging.
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The output of the mouse neurological disorders RNA-seq portal showed a downregulation of Signature C genes within studies designated "other cell types".
“Notably, the output of this portal showed a downregulation of Signature C genes within studies designated “other cell types” (Fig. S5 C).”
From Network analysis identifies strain-dependent response to tau and tau seeding-associated genes (2023) · cites this paper as Al-Ouran et al., 2019
The Results and Discussion section describes this portal and shows downregulated genes in mouse models studying different cell types. Those results concern the paper’s yellow-module gene set, however; our copy does not report an analysis of Signature C genes or a category designated “other cell types.” (LLM, conf=0.82)
Experimental — accuracy not yet measuredThe gene lists can be used with external databases like the mouse neurological disorders RNA-seq portal to probe similar signatures across mouse models.
“We demonstrated the ability to use our gene lists with external databases like the mouse neurological disorders RNA-seq portal (Al-Ouran et al., 2019) to probe similar signatures across mouse models.”
From Network analysis identifies strain-dependent response to tau and tau seeding-associated genes (2023) · cites this paper as Al-Ouran et al., 2019
Among 26 mouse transcriptomic cohorts where Abi3 and Gngt2 were both differentially regulated, their expression changes were concordant in 24 studies.
“In addition, we investigated 96 additional mouse transcriptomic datasets [33, 34] and in 26 of these cohorts, we found that Abi3 and Gngt2 were both differentially regulated. Among these 26 cohorts, Abi3 and Gngt2 expression changes were concordant in 24 studies (Additional File 6: Table S4), showing that these genes are consistently co-regulated across different mouse models and experimental”
From Deletion of Abi3/Gngt2 influences age-progressive amyloid β and tau pathologies in distinctive ways (2022) · cites this paper as [34]
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Cites
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Cited by
Sorted by citations
Deletion of Abi3/Gngt2 influences age-progressive amyloid β and tau pathologies in distinctive ways
Ibanez, K. R., McFarland, K. N., Phillips, J., Allen, M., Lessard, C. B., Zobel, L., De La Cruz, E. G., Shah, S., Vo, Q., Wang, X., et al. (2022) · Alzheimer's Research & Therapy · doi:10.1186/s13195-022-01044-1 · Cited by 18 · see citing works
Network analysis identifies strain-dependent response to tau and tau seeding-associated genes
Acri, D. J., You, Y., Tate, M. D., Karahan, H., Martinez, P., McCord, B., Sharify, A. D., John, S., Kim, B., Dabin, L. C., et al. (2023) · Journal of Experimental Medicine · doi:10.1084/jem.20230180 · Cited by 3 · see citing works
- Authors
- Al-Ouran, R., Wan, Y.-W., Mangleburg, C. G., Lee, T. V., Allison, K., Shulman, J. M., & Liu, Z.
- Affiliations
- Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA
- Baylor College of Medicine (US)
- Corresponding author
- Wan, Ying-Wooi
- Liu, Zhandong
- Venue
- Genes
- Publisher
- MDPI AG
- Published
- 2019-09-26
- Volume
- 10
- Issue
- 10
- Pages
- 759
- ISSN
- 2073-4425 (ISSN-L)
- PMC
- PMC6826490
- OpenAlex
- W2977066221
- Cited by
- 19
- References
- 2
- Citations by year
- 2023: 2 · 2022: 13 · 2021: 2 · 2020: 1 · 2019: 1
- FWCI
- 1.41
- Type
- journal article
- Language
- en
- Open access
- gold
- dx.doi.org
- Licence
- Locations
- Genes (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Huffington Foundation
- National Institutes of Health (5r01gm120033-05)
- National Institute on Aging (F31AG067677, R01AG057339)
- National Institute of General Medical Sciences (R01-GM120033)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Keywords
- gene expression profiling, web portal, gene expression changes, drug target validation, Alzheimer's disease, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis, spinocerebellar ataxia, aging, brain gene expression, model selection
- MeSH terms
- Animals, Disease Models, Animal, Nervous System Diseases, Software, Databases, Genetic, Mice, Transcriptome
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