A Comprehensive FXR Signaling Atlas Derived from Pooled ChIP-seq Data

Emilian Jungwirth, Katrin Panzitt, Hanns-Ulrich Marschall, Martin Wagner, Gerhard G Thallinger

Publikation: Beitrag in einer FachzeitschriftArtikelForschungBegutachtung

Abstract

BACKGROUND: ChIP-seq is a method to identify genome-wide transcription factor (TF) binding sites. The TF FXR is a nuclear receptor that controls gene regulation of different metabolic pathways in the liver.

OBJECTIVES: To re-analyze, standardize and combine all publicly available FXR ChIP-seq data sets to create a global FXR signaling atlas.

METHODS: All data sets were (re-)analyzed in a standardized manner and compared on every relevant level from raw reads to affected functional pathways.

RESULTS: Public FXR data sets were available for mouse, rat and primary human hepatocytes in different treatment conditions. Standardized re-analysis shows that the data sets are surprisingly heterogeneous concerning baseline quality criteria. Combining different data sets increased the depth of analysis and allowed to recover more peaks and functional pathways.

CONCLUSION: Published single FXR ChIP-seq data sets do not cover the full spectrum of FXR signaling. Combining different data sets and creating a "FXR super-signaling atlas" enhances understanding of FXR signaling capacities.

Originalspracheenglisch
Seiten (von - bis)105-112
Seitenumfang8
FachzeitschriftStudies in health technology and informatics
Jahrgang260
DOIs
PublikationsstatusVeröffentlicht - 2019
Veranstaltung13th Health Informatics Meets Digital Health Conference - Wien, Österreich
Dauer: 28 Mai 2019 → …

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Atlases
Transcription factors
Binding sites
Gene expression
Liver
Transcription Factors
Rats
Genes
Cytoplasmic and Nuclear Receptors
Metabolic Networks and Pathways
Datasets
Hepatocytes
Binding Sites
Genome

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    A Comprehensive FXR Signaling Atlas Derived from Pooled ChIP-seq Data. / Jungwirth, Emilian; Panzitt, Katrin; Marschall, Hanns-Ulrich; Wagner, Martin; Thallinger, Gerhard G.

    in: Studies in health technology and informatics, Jahrgang 260, 2019, S. 105-112.

    Publikation: Beitrag in einer FachzeitschriftArtikelForschungBegutachtung

    Jungwirth, Emilian ; Panzitt, Katrin ; Marschall, Hanns-Ulrich ; Wagner, Martin ; Thallinger, Gerhard G. / A Comprehensive FXR Signaling Atlas Derived from Pooled ChIP-seq Data. in: Studies in health technology and informatics. 2019 ; Jahrgang 260. S. 105-112.
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    abstract = "BACKGROUND: ChIP-seq is a method to identify genome-wide transcription factor (TF) binding sites. The TF FXR is a nuclear receptor that controls gene regulation of different metabolic pathways in the liver.OBJECTIVES: To re-analyze, standardize and combine all publicly available FXR ChIP-seq data sets to create a global FXR signaling atlas.METHODS: All data sets were (re-)analyzed in a standardized manner and compared on every relevant level from raw reads to affected functional pathways.RESULTS: Public FXR data sets were available for mouse, rat and primary human hepatocytes in different treatment conditions. Standardized re-analysis shows that the data sets are surprisingly heterogeneous concerning baseline quality criteria. Combining different data sets increased the depth of analysis and allowed to recover more peaks and functional pathways.CONCLUSION: Published single FXR ChIP-seq data sets do not cover the full spectrum of FXR signaling. Combining different data sets and creating a {"}FXR super-signaling atlas{"} enhances understanding of FXR signaling capacities.",
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    year = "2019",
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    T1 - A Comprehensive FXR Signaling Atlas Derived from Pooled ChIP-seq Data

    AU - Jungwirth, Emilian

    AU - Panzitt, Katrin

    AU - Marschall, Hanns-Ulrich

    AU - Wagner, Martin

    AU - Thallinger, Gerhard G

    PY - 2019

    Y1 - 2019

    N2 - BACKGROUND: ChIP-seq is a method to identify genome-wide transcription factor (TF) binding sites. The TF FXR is a nuclear receptor that controls gene regulation of different metabolic pathways in the liver.OBJECTIVES: To re-analyze, standardize and combine all publicly available FXR ChIP-seq data sets to create a global FXR signaling atlas.METHODS: All data sets were (re-)analyzed in a standardized manner and compared on every relevant level from raw reads to affected functional pathways.RESULTS: Public FXR data sets were available for mouse, rat and primary human hepatocytes in different treatment conditions. Standardized re-analysis shows that the data sets are surprisingly heterogeneous concerning baseline quality criteria. Combining different data sets increased the depth of analysis and allowed to recover more peaks and functional pathways.CONCLUSION: Published single FXR ChIP-seq data sets do not cover the full spectrum of FXR signaling. Combining different data sets and creating a "FXR super-signaling atlas" enhances understanding of FXR signaling capacities.

    AB - BACKGROUND: ChIP-seq is a method to identify genome-wide transcription factor (TF) binding sites. The TF FXR is a nuclear receptor that controls gene regulation of different metabolic pathways in the liver.OBJECTIVES: To re-analyze, standardize and combine all publicly available FXR ChIP-seq data sets to create a global FXR signaling atlas.METHODS: All data sets were (re-)analyzed in a standardized manner and compared on every relevant level from raw reads to affected functional pathways.RESULTS: Public FXR data sets were available for mouse, rat and primary human hepatocytes in different treatment conditions. Standardized re-analysis shows that the data sets are surprisingly heterogeneous concerning baseline quality criteria. Combining different data sets increased the depth of analysis and allowed to recover more peaks and functional pathways.CONCLUSION: Published single FXR ChIP-seq data sets do not cover the full spectrum of FXR signaling. Combining different data sets and creating a "FXR super-signaling atlas" enhances understanding of FXR signaling capacities.

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    KW - Binding Sites

    KW - Chromatin Immunoprecipitation

    KW - Data Analysis

    KW - Databases, Factual

    KW - Gene Expression Regulation

    KW - Genome

    KW - Humans

    KW - Mice

    KW - Rats

    KW - Receptors, Cytoplasmic and Nuclear

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