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Article ; Online: No Dataset Left Behind: Mechanistic Insights into Thyroid Receptor Signaling Through Transcriptomic Consensome Meta-Analysis.

Ochsner, Scott A / McKenna, Neil J

Thyroid : official journal of the American Thyroid Association

2020 Volume 30, Issue 4, Page(s) 621–639

Abstract: Background: ...

Abstract	Background:
MeSH term(s)	Computational Biology ; Gene Expression Profiling ; Humans ; Liver/metabolism ; Receptors, Thyroid Hormone/metabolism ; Signal Transduction/physiology ; Thyroid Gland/metabolism ; Thyroid Hormones/metabolism ; Transcriptome
Chemical Substances	Receptors, Thyroid Hormone ; Thyroid Hormones
Language	English
Publishing date	2020-01-29
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	1086044-7
ISSN	1557-9077 ; 1050-7256
ISSN (online)	1557-9077
ISSN	1050-7256
DOI	10.1089/thy.2019.0307
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Article ; Online: Transcriptional regulatory networks of circulating immune cells in type 1 diabetes: A community knowledgebase.

Ochsner, Scott A / Pillich, Rudolf T / Rawool, Deepali / Grethe, Jeffrey S / McKenna, Neil J

iScience

2022 Volume 25, Issue 7, Page(s) 104581

Abstract: 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 ... ...

Abstract	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.
Language	English
Publishing date	2022-06-11
Publishing country	United States
Document type	Journal Article
ISSN	2589-0042
ISSN (online)	2589-0042
DOI	10.1016/j.isci.2022.104581
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Article: Histone proteoform analysis reveals epigenetic changes in adult mouse brown adipose tissue in response to cold stress.

Taylor, Bethany C / Steinthal, Loic H / Dias, Michelle / Yalamanchili, Hari K / Ochsner, Scott A / Zapata, Gladys E / Mehta, Nitesh R / McKenna, Neil J / Young, Nicolas L / Nuotio-Antar, Alli M

bioRxiv : the preprint server for biology

2024

Abstract: Regulation of the thermogenic response by brown adipose tissue (BAT) is an important component of energy homeostasis with implications for the treatment of obesity and diabetes. Our preliminary analyses uncovered many nodes representing epigenetic ... ...

Abstract	Regulation of the thermogenic response by brown adipose tissue (BAT) is an important component of energy homeostasis with implications for the treatment of obesity and diabetes. Our preliminary analyses uncovered many nodes representing epigenetic modifiers that are altered in BAT in response to chronic thermogenic activation. Thus, we hypothesized that chronic thermogenic activation broadly alters epigenetic modifications of DNA and histones in BAT. Motivated to understand how BAT function is regulated epigenetically, we developed a novel method for the first-ever unbiased top-down proteomic quantitation of histone modifications in BAT and validated our results with a multi-omic approach. To test our hypothesis, wildtype male C57BL/6J mice were housed under chronic conditions of thermoneutral temperature (TN, 28.8°C), mild cold/room temperature (RT, 22°C), or severe cold (SC, 8°C) and BAT was analyzed for DNA methylation and histone modifications. Methylation of promoters and intragenic regions in genomic DNA decrease in response to chronic cold exposure. Integration of DNA methylation and RNA expression data suggest a role for epigenetic modification of DNA in gene regulation in response to cold. In response to cold housing, we observe increased bulk acetylation of histones H3.2 and H4, increased histone H3.2 proteoforms with di- and trimethylation of lysine 9 (K9me2 and K9me3), and increased histone H4 proteoforms with acetylation of lysine 16 (K16ac) in BAT. Taken together, our results reveal global epigenetically-regulated transcriptional "on" and "off" signals in murine BAT in response to varying degrees of chronic cold stimuli and establish a novel methodology to quantitatively study histones in BAT, allowing for direct comparisons to decipher mechanistic changes during the thermogenic response. Additionally, we make histone PTM and proteoform quantitation, RNA splicing, RRBS, and transcriptional footprint datasets available as a resource for future research.
Language	English
Publishing date	2024-01-22
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.07.30.551059
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Article ; Online: A transcriptional regulatory atlas of coronavirus infection of human cells

Scott A Ochsner / Neil J McKenna

Abstract: AbstractIdentifying transcriptional responses that are most consistently associated with experimental coronavirus (CoV) infection can help illuminate human cellular signaling pathways impacted by CoV infection. Here, we distilled over 3,000,000 data ... ...

Abstract	AbstractIdentifying transcriptional responses that are most consistently associated with experimental coronavirus (CoV) infection can help illuminate human cellular signaling pathways impacted by CoV infection. Here, we distilled over 3,000,000 data points from publically archived CoV infection transcriptomic datasets into consensus regulatory signatures, or consensomes, that rank genes based on their transcriptional responsiveness to infection of human cells by MERS, SARS-CoV-1 and SARS-CoV-2 subtypes. We computed overlap between genes with elevated rankings in the CoV consensomes against those from transcriptomic and ChIP-Seq consensomes for nearly 880 cellular signaling pathway nodes. Validating the CoV infection consensomes, we identified robust overlap between their highly ranked genes and high confidence targets of signaling pathway nodes with known roles in CoV infection. We then developed a series of use cases that illustrate the utility of the CoV consensomes for hypothesis generation around mechanistic aspects of the cellular response to CoV infection. We make the CoV infection consensomes and their universe of underlying data points freely accessible through the Signaling Pathways Project web knowledgebase.
Keywords	covid19
Publisher	biorxiv
Document type	Article ; Online
DOI	10.1101/2020.04.24.059527
Database	COVID19

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Article: Consensus transcriptional regulatory networks of coronavirus-infected human cells.

Ochsner, Scott A / Pillich, Rudolf T / McKenna, Neil J

bioRxiv : the preprint server for biology

2020

Abstract: Establishing consensus around the transcriptional interface between coronavirus (CoV) infection and human cellular signaling pathways can catalyze the development of novel anti-CoV therapeutics. Here, we used publicly archived transcriptomic datasets to ... ...

Abstract	Establishing consensus around the transcriptional interface between coronavirus (CoV) infection and human cellular signaling pathways can catalyze the development of novel anti-CoV therapeutics. Here, we used publicly archived transcriptomic datasets to compute consensus regulatory signatures, or consensomes, that rank human genes based on their rates of differential expression in MERS-CoV (MERS), SARS-CoV-1 (SARS1) and SARS-CoV-2 (SARS2)-infected cells. Validating the CoV consensomes, we show that high confidence transcriptional targets (HCTs) of CoV infection intersect with HCTs of signaling pathway nodes with known roles in CoV infection. Among a series of novel use cases, we gather evidence for hypotheses that SARS2 infection efficiently represses E2F family target genes encoding key drivers of DNA replication and the cell cycle; that progesterone receptor signaling antagonizes SARS2-induced inflammatory signaling in the airway epithelium; and that SARS2 HCTs are enriched for genes involved in epithelial to mesenchymal transition. The CoV infection consensomes and HCT intersection analyses are freely accessible through the Signaling Pathways Project knowledgebase, and as Cytoscape-style networks in the Network Data Exchange repository.
Keywords	covid19
Language	English
Publishing date	2020-07-15
Publishing country	United States
Document type	Preprint
DOI	10.1101/2020.04.24.059527
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Article ; Online: Consensus transcriptional regulatory networks of coronavirus-infected human cells.

Ochsner, Scott A / Pillich, Rudolf T / McKenna, Neil J

Scientific data

2020 Volume 7, Issue 1, Page(s) 314

Abstract	Establishing consensus around the transcriptional interface between coronavirus (CoV) infection and human cellular signaling pathways can catalyze the development of novel anti-CoV therapeutics. Here, we used publicly archived transcriptomic datasets to compute consensus regulatory signatures, or consensomes, that rank human genes based on their rates of differential expression in MERS-CoV (MERS), SARS-CoV-1 (SARS1) and SARS-CoV-2 (SARS2)-infected cells. Validating the CoV consensomes, we show that high confidence transcriptional targets (HCTs) of MERS, SARS1 and SARS2 infection intersect with HCTs of signaling pathway nodes with known roles in CoV infection. Among a series of novel use cases, we gather evidence for hypotheses that SARS2 infection efficiently represses E2F family HCTs encoding key drivers of DNA replication and the cell cycle; that progesterone receptor signaling antagonizes SARS2-induced inflammatory signaling in the airway epithelium; and that SARS2 HCTs are enriched for genes involved in epithelial to mesenchymal transition. The CoV infection consensomes and HCT intersection analyses are freely accessible through the Signaling Pathways Project knowledgebase, and as Cytoscape-style networks in the Network Data Exchange repository.
MeSH term(s)	Betacoronavirus ; COVID-19 ; Cell Cycle ; Consensus ; Coronavirus Infections/genetics ; DNA Replication ; Datasets as Topic ; Epithelial-Mesenchymal Transition/genetics ; Gene Expression ; Humans ; Interferon Regulatory Factors/genetics ; Middle East Respiratory Syndrome Coronavirus ; Pandemics ; Pneumonia, Viral/genetics ; Receptors, Progesterone ; Severe acute respiratory syndrome-related coronavirus ; SARS-CoV-2 ; Signal Transduction ; Transcriptome
Chemical Substances	Interferon Regulatory Factors ; Receptors, Progesterone
Keywords	covid19
Language	English
Publishing date	2020-09-22
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2775191-0
ISSN	2052-4463 ; 2052-4463
ISSN (online)	2052-4463
ISSN	2052-4463
DOI	10.1038/s41597-020-00628-6
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Article ; Online: A transcriptional regulatory atlas of coronavirus infection of human cells

Ochsner, Scott A / McKenna, Neil

bioRxiv

Abstract: Identifying transcriptional responses that are most consistently associated with experimental coronavirus (CoV) infection can help illuminate human cellular signaling pathways impacted by CoV infection. Here, we distilled over three million data points ... ...

Abstract	Identifying transcriptional responses that are most consistently associated with experimental coronavirus (CoV) infection can help illuminate human cellular signaling pathways impacted by CoV infection. Here, we distilled over three million data points from publically archived CoV infection transcriptomic datasets into consensus regulatory signatures, or consensomes, that rank genes based on their transcriptional responsiveness to infection of human cells by MERS, SARS-CoV-1 (SARS1), SARS-CoV-2 (SARS2) subtypes. We computed overlap between genes with elevated rankings in the CoV consensomes against those from transcriptomic and ChIP-Seq consensomes for nearly 880 cellular signaling pathway nodes. Validating the CoV infection consensomes, we identified robust overlap between their highly ranked genes and high confidence targets of signaling pathway nodes with known roles in CoV infection. We then developed a series of use cases that illustrate the utility of the CoV consensomes for hypothesis generation around mechanistic aspects of the cellular response to CoV infection. We make the CoV infection consensomes and their universe of underlying data points freely accessible through the Signaling Pathways Project web knowledgebase.
Keywords	covid19
Language	English
Publishing date	2020-04-25
Publisher	Cold Spring Harbor Laboratory
Document type	Article ; Online
DOI	10.1101/2020.04.24.059527
Database	COVID19

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Article ; Online: Consensus transcriptional regulatory networks of coronavirus-infected human cells

Scott A. Ochsner / Rudolf T. Pillich / Neil J. McKenna

Scientific Data, Vol 7, Iss 1, Pp 1-

2020 Volume 20

Abstract: Abstract Establishing consensus around the transcriptional interface between coronavirus (CoV) infection and human cellular signaling pathways can catalyze the development of novel anti-CoV therapeutics. Here, we used publicly archived transcriptomic ... ...

Abstract	Abstract Establishing consensus around the transcriptional interface between coronavirus (CoV) infection and human cellular signaling pathways can catalyze the development of novel anti-CoV therapeutics. Here, we used publicly archived transcriptomic datasets to compute consensus regulatory signatures, or consensomes, that rank human genes based on their rates of differential expression in MERS-CoV (MERS), SARS-CoV-1 (SARS1) and SARS-CoV-2 (SARS2)-infected cells. Validating the CoV consensomes, we show that high confidence transcriptional targets (HCTs) of MERS, SARS1 and SARS2 infection intersect with HCTs of signaling pathway nodes with known roles in CoV infection. Among a series of novel use cases, we gather evidence for hypotheses that SARS2 infection efficiently represses E2F family HCTs encoding key drivers of DNA replication and the cell cycle; that progesterone receptor signaling antagonizes SARS2-induced inflammatory signaling in the airway epithelium; and that SARS2 HCTs are enriched for genes involved in epithelial to mesenchymal transition. The CoV infection consensomes and HCT intersection analyses are freely accessible through the Signaling Pathways Project knowledgebase, and as Cytoscape-style networks in the Network Data Exchange repository.
Keywords	Science ; Q ; covid19
Subject code	570
Language	English
Publishing date	2020-09-01T00:00:00Z
Publisher	Nature Publishing Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: IL17A Blockade with Ixekizumab Suppresses MuvB Signaling in Clinical Psoriasis.

Ochsner, Scott A / Pedroza, Mesias / Pillich, Rudolf T / Krishnan, Venkatesh / Konicek, Bruce W / Dow, Ernst R / Park, So Young / Agarwal, Sandeep K / McKenna, Neil J

The Journal of investigative dermatology

2023 Volume 143, Issue 9, Page(s) 1689–1699

Abstract: Unbiased informatics approaches have the potential to generate insights into uncharacterized signaling pathways in human disease. In this study, we generated longitudinal transcriptomic profiles of plaque psoriasis lesions from patients enrolled in a ... ...

Abstract	Unbiased informatics approaches have the potential to generate insights into uncharacterized signaling pathways in human disease. In this study, we generated longitudinal transcriptomic profiles of plaque psoriasis lesions from patients enrolled in a clinical trial of the anti-IL17A antibody ixekizumab (IXE). This dataset was then computed against a curated matrix of over 700 million data points derived from published psoriasis and signaling node perturbation transcriptomic and chromatin immunoprecipitation-sequencing datasets. We observed substantive enrichment within both psoriasis-induced and IXE-repressed gene sets of transcriptional targets of members of the MuvB complex, a master regulator of the mitotic cell cycle. These gene sets were similarly enriched for pathways involved in the regulation of the G2/M transition of the cell cycle. Moreover, transcriptional targets for MuvB nodes were strongly enriched within IXE-repressed genes whose expression levels correlated strongly with the extent and severity of the psoriatic disease. In models of human keratinocyte proliferation, genes encoding MuvB nodes were transcriptionally repressed by IXE, and depletion of MuvB nodes reduced cell proliferation. Finally, we made the expression and regulatory networks that supported this study available as a freely accessible, cloud-based hypothesis generation platform. Our study positions inhibition of MuvB signaling as an important determinant of the therapeutic impact of IXE in psoriasis.
MeSH term(s)	Humans ; Dermatologic Agents/pharmacology ; Dermatologic Agents/therapeutic use ; Double-Blind Method ; Psoriasis/drug therapy ; Psoriasis/genetics ; Psoriasis/pathology ; Antibodies, Monoclonal, Humanized/pharmacology ; Antibodies, Monoclonal, Humanized/therapeutic use ; Treatment Outcome
Chemical Substances	ixekizumab (BTY153760O) ; Dermatologic Agents ; Antibodies, Monoclonal, Humanized
Language	English
Publishing date	2023-03-24
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
ZDB-ID	80136-7
ISSN	1523-1747 ; 0022-202X
ISSN (online)	1523-1747
ISSN	0022-202X
DOI	10.1016/j.jid.2023.03.1658
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Article ; Online: Transcriptional regulatory networks of circulating immune cells in type 1 diabetes

Scott A. Ochsner / Rudolf T. Pillich / Deepali Rawool / Jeffrey S. Grethe / Neil J. McKenna

iScience, Vol 25, Iss 7, Pp 104581- (2022)

A community knowledgebase

2022

Abstract: 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 ... ...

Abstract	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.
Keywords	Bioinformatics ; Biological database ; Transcriptomics ; Science ; Q
Subject code	570
Language	English
Publishing date	2022-07-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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