DiffBrainNet: Differential analyses add new insights into the response to glucocorticoids at the level of genes, networks and brain regions
Genome-wide gene expression analyses are invaluable tools for studying biological and disease processes, allowing a hypothesis-free comparison of expression profiles. Traditionally, transcriptomic analysis has focused on gene-level effects found by differential expression. In recent years, network a...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-11-01
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| Series: | Neurobiology of Stress |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352289522000716 |
| _version_ | 1811201779496386560 |
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| author | Nathalie Gerstner Anthi C. Krontira Cristiana Cruceanu Simone Roeh Benno Pütz Susann Sauer Monika Rex-Haffner Mathias V. Schmidt Elisabeth B. Binder Janine Knauer-Arloth |
| author_facet | Nathalie Gerstner Anthi C. Krontira Cristiana Cruceanu Simone Roeh Benno Pütz Susann Sauer Monika Rex-Haffner Mathias V. Schmidt Elisabeth B. Binder Janine Knauer-Arloth |
| author_sort | Nathalie Gerstner |
| collection | DOAJ |
| description | Genome-wide gene expression analyses are invaluable tools for studying biological and disease processes, allowing a hypothesis-free comparison of expression profiles. Traditionally, transcriptomic analysis has focused on gene-level effects found by differential expression. In recent years, network analysis has emerged as an important additional level of investigation, providing information on molecular connectivity, especially for diseases associated with a large number of linked effects of smaller magnitude, like neuropsychiatric disorders. Here, we describe how combined differential expression and prior-knowledge-based differential network analysis can be used to explore complex datasets. As an example, we analyze the transcriptional responses following administration of the glucocorticoid/stress receptor agonist dexamethasone in 8 mouse brain regions important for stress processing. By applying a combination of differential network- and expression-analyses, we find that these explain distinct but complementary biological mechanisms of the glucocorticoid responses. Additionally, network analysis identifies new differentially connected partners of risk genes and can be used to generate hypotheses on molecular pathways affected. With DiffBrainNet (http://diffbrainnet.psych.mpg.de), we provide an analysis framework and a publicly available resource for the study of the transcriptional landscape of the mouse brain which can identify molecular pathways important for basic functioning and response to glucocorticoids in a brain-region specific manner. |
| first_indexed | 2024-04-12T02:27:42Z |
| format | Article |
| id | doaj.art-54f05cebe8c844a4b4319b65530cf834 |
| institution | Directory Open Access Journal |
| issn | 2352-2895 |
| language | English |
| last_indexed | 2024-04-12T02:27:42Z |
| publishDate | 2022-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Neurobiology of Stress |
| spelling | doaj.art-54f05cebe8c844a4b4319b65530cf8342022-12-22T03:51:55ZengElsevierNeurobiology of Stress2352-28952022-11-0121100496DiffBrainNet: Differential analyses add new insights into the response to glucocorticoids at the level of genes, networks and brain regionsNathalie Gerstner0Anthi C. Krontira1Cristiana Cruceanu2Simone Roeh3Benno Pütz4Susann Sauer5Monika Rex-Haffner6Mathias V. Schmidt7Elisabeth B. Binder8Janine Knauer-Arloth9Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804, Munich, Germany; International Max Planck Research School for Translational Psychiatry, Kraepelinstr. 2-10, 80804, Munich, Germany; Institute of Computational Biology, Helmholtz Zentrum München, Ingolstaedter Landstr. 1, 85764, Neuherberg, GermanyDepartment of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804, Munich, Germany; International Max Planck Research School for Translational Psychiatry, Kraepelinstr. 2-10, 80804, Munich, GermanyDepartment of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804, Munich, GermanyDepartment of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804, Munich, GermanyDepartment of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804, Munich, GermanyDepartment of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804, Munich, GermanyDepartment of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804, Munich, GermanyResearch Group Neurobiology of Stress Resilience, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804, Munich, GermanyDepartment of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804, Munich, Germany; Corresponding author.Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804, Munich, Germany; Institute of Computational Biology, Helmholtz Zentrum München, Ingolstaedter Landstr. 1, 85764, Neuherberg, Germany; Corresponding author. Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804, Munich, Germany.Genome-wide gene expression analyses are invaluable tools for studying biological and disease processes, allowing a hypothesis-free comparison of expression profiles. Traditionally, transcriptomic analysis has focused on gene-level effects found by differential expression. In recent years, network analysis has emerged as an important additional level of investigation, providing information on molecular connectivity, especially for diseases associated with a large number of linked effects of smaller magnitude, like neuropsychiatric disorders. Here, we describe how combined differential expression and prior-knowledge-based differential network analysis can be used to explore complex datasets. As an example, we analyze the transcriptional responses following administration of the glucocorticoid/stress receptor agonist dexamethasone in 8 mouse brain regions important for stress processing. By applying a combination of differential network- and expression-analyses, we find that these explain distinct but complementary biological mechanisms of the glucocorticoid responses. Additionally, network analysis identifies new differentially connected partners of risk genes and can be used to generate hypotheses on molecular pathways affected. With DiffBrainNet (http://diffbrainnet.psych.mpg.de), we provide an analysis framework and a publicly available resource for the study of the transcriptional landscape of the mouse brain which can identify molecular pathways important for basic functioning and response to glucocorticoids in a brain-region specific manner.http://www.sciencedirect.com/science/article/pii/S2352289522000716GlucocorticoidsStress responseTranscriptomicsNetwork analysisMouse brain |
| spellingShingle | Nathalie Gerstner Anthi C. Krontira Cristiana Cruceanu Simone Roeh Benno Pütz Susann Sauer Monika Rex-Haffner Mathias V. Schmidt Elisabeth B. Binder Janine Knauer-Arloth DiffBrainNet: Differential analyses add new insights into the response to glucocorticoids at the level of genes, networks and brain regions Neurobiology of Stress Glucocorticoids Stress response Transcriptomics Network analysis Mouse brain |
| title | DiffBrainNet: Differential analyses add new insights into the response to glucocorticoids at the level of genes, networks and brain regions |
| title_full | DiffBrainNet: Differential analyses add new insights into the response to glucocorticoids at the level of genes, networks and brain regions |
| title_fullStr | DiffBrainNet: Differential analyses add new insights into the response to glucocorticoids at the level of genes, networks and brain regions |
| title_full_unstemmed | DiffBrainNet: Differential analyses add new insights into the response to glucocorticoids at the level of genes, networks and brain regions |
| title_short | DiffBrainNet: Differential analyses add new insights into the response to glucocorticoids at the level of genes, networks and brain regions |
| title_sort | diffbrainnet differential analyses add new insights into the response to glucocorticoids at the level of genes networks and brain regions |
| topic | Glucocorticoids Stress response Transcriptomics Network analysis Mouse brain |
| url | http://www.sciencedirect.com/science/article/pii/S2352289522000716 |
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