Transcriptional regulatory networks of circulating immune cells in type 1 diabetes: A community knowledgebase
Summary: Investigator-generated transcriptomic datasets interrogating circulating immune cell (CIC) gene expression in clinical type 1 diabetes (T1D) have underappreciated re-use value. Here, we repurposed these datasets to create an open science environment for the generation of hypotheses around C...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-07-01
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| Series: | iScience |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589004222008537 |
| _version_ | 1818114585748570112 |
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| author | Scott A. Ochsner Rudolf T. Pillich Deepali Rawool Jeffrey S. Grethe Neil J. McKenna |
| author_facet | Scott A. Ochsner Rudolf T. Pillich Deepali Rawool Jeffrey S. Grethe Neil J. McKenna |
| author_sort | Scott A. Ochsner |
| collection | DOAJ |
| description | Summary: Investigator-generated transcriptomic datasets interrogating circulating immune cell (CIC) gene expression in clinical type 1 diabetes (T1D) have underappreciated re-use value. Here, we repurposed these datasets to create an open science environment for the generation of hypotheses around CIC signaling pathways whose gain or loss of function contributes to T1D pathogenesis. We firstly computed sets of genes that were preferentially induced or repressed in T1D CICs and validated these against community benchmarks. We then inferred and validated signaling node networks regulating expression of these gene sets, as well as differentially expressed genes in the original underlying T1D case:control datasets. In a set of three use cases, we demonstrated how informed integration of these networks with complementary digital resources supports substantive, actionable hypotheses around signaling pathway dysfunction in T1D CICs. Finally, we developed a federated, cloud-based web resource that exposes the entire data matrix for unrestricted access and re-use by the research community. |
| first_indexed | 2024-12-11T03:53:04Z |
| format | Article |
| id | doaj.art-75c6d2e5b41948bfbca6353570aa3420 |
| institution | Directory Open Access Journal |
| issn | 2589-0042 |
| language | English |
| last_indexed | 2024-12-11T03:53:04Z |
| publishDate | 2022-07-01 |
| publisher | Elsevier |
| record_format | Article |
| series | iScience |
| spelling | doaj.art-75c6d2e5b41948bfbca6353570aa34202022-12-22T01:21:50ZengElsevieriScience2589-00422022-07-01257104581Transcriptional regulatory networks of circulating immune cells in type 1 diabetes: A community knowledgebaseScott A. Ochsner0Rudolf T. Pillich1Deepali Rawool2Jeffrey S. Grethe3Neil J. McKenna4Department of Molecular, Baylor College of Medicine, Houston, TX 77030, USA; Cellular Biology and Medicine, Baylor College of Medicine, Houston, TX 77030, USADepartment of Medicine, University of California San Diego, La Jolla, CA 92093, USACenter for Research in Biological Systems, University of California San Diego, La Jolla, CA 92093, USACenter for Research in Biological Systems, University of California San Diego, La Jolla, CA 92093, USADepartment of Molecular, Baylor College of Medicine, Houston, TX 77030, USA; Cellular Biology and Medicine, Baylor College of Medicine, Houston, TX 77030, USA; Corresponding authorSummary: Investigator-generated transcriptomic datasets interrogating circulating immune cell (CIC) gene expression in clinical type 1 diabetes (T1D) have underappreciated re-use value. Here, we repurposed these datasets to create an open science environment for the generation of hypotheses around CIC signaling pathways whose gain or loss of function contributes to T1D pathogenesis. We firstly computed sets of genes that were preferentially induced or repressed in T1D CICs and validated these against community benchmarks. We then inferred and validated signaling node networks regulating expression of these gene sets, as well as differentially expressed genes in the original underlying T1D case:control datasets. In a set of three use cases, we demonstrated how informed integration of these networks with complementary digital resources supports substantive, actionable hypotheses around signaling pathway dysfunction in T1D CICs. Finally, we developed a federated, cloud-based web resource that exposes the entire data matrix for unrestricted access and re-use by the research community.http://www.sciencedirect.com/science/article/pii/S2589004222008537BioinformaticsBiological databaseTranscriptomics |
| spellingShingle | Scott A. Ochsner Rudolf T. Pillich Deepali Rawool Jeffrey S. Grethe Neil J. McKenna Transcriptional regulatory networks of circulating immune cells in type 1 diabetes: A community knowledgebase iScience Bioinformatics Biological database Transcriptomics |
| title | Transcriptional regulatory networks of circulating immune cells in type 1 diabetes: A community knowledgebase |
| title_full | Transcriptional regulatory networks of circulating immune cells in type 1 diabetes: A community knowledgebase |
| title_fullStr | Transcriptional regulatory networks of circulating immune cells in type 1 diabetes: A community knowledgebase |
| title_full_unstemmed | Transcriptional regulatory networks of circulating immune cells in type 1 diabetes: A community knowledgebase |
| title_short | Transcriptional regulatory networks of circulating immune cells in type 1 diabetes: A community knowledgebase |
| title_sort | transcriptional regulatory networks of circulating immune cells in type 1 diabetes a community knowledgebase |
| topic | Bioinformatics Biological database Transcriptomics |
| url | http://www.sciencedirect.com/science/article/pii/S2589004222008537 |
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