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Published on: June 3, 2018
A mouse tissue transcription factor atlas
Quan Zhou1, Mingwei Liu1, Xia Xia1
1State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine; National Center for Protein Sciences (The PHOENIX Center, Beijing), Beijing 102206, China.
Abstract:
Transcription factors (TFs) drive various biological processes ranging from embryonic development to carcinogenesis. Here, we employ a recently developed concatenated tandem array of consensus TF response elements (catTFRE) approach to profile the activated TFs in 24 adult and 8 fetal mouse tissues on proteome scale. A total of 941 TFs are quantitatively identified, representing over 60% of the TFs in the mouse genome. Using an integrated omics approach, we present a TF network in the major organs of the mouse, allowing data mining and generating knowledge to elucidate the roles of TFs in various biological processes, including tissue type maintenance and determining the general features of a physiological system. This study provides a landscape of TFs in mouse tissues that can be used to elucidate transcriptional regulatory specificity and programming and as a baseline that may facilitate understanding diseases that are regulated by TFs.
Insights
This study profiles activated transcription factors (TFs) across mouse tissues, identifying 941 TFs. The findings reveal TF networks crucial for tissue maintenance and understanding diseases.
Area of Science:
- Molecular Biology
- Genomics
- Proteomics
Background:
- Transcription factors (TFs) are critical regulators of diverse biological processes, including development and disease.
- Understanding the landscape of activated TFs in different tissues is essential for deciphering gene regulation.
Purpose of the Study:
- To quantitatively profile activated transcription factors (TFs) across multiple adult and fetal mouse tissues.
- To construct a comprehensive TF network in major mouse organs using an integrated omics approach.
- To provide a foundational dataset for understanding TF roles in tissue specificity, physiological systems, and TF-regulated diseases.
Main Methods:
- Utilized a concatenated tandem array of consensus TF response elements (catTFRE) approach.
- Performed proteome-scale profiling of activated TFs in 24 adult and 8 fetal mouse tissues.
- Integrated omics data to build a TF network.
Main Results:
- Quantitatively identified 941 transcription factors (TFs), representing over 60% of those in the mouse genome.
- Established a TF network map for major mouse organs.
- Characterized TF roles in tissue maintenance and physiological system features.
Conclusions:
- The study provides an unprecedented landscape of TFs in mouse tissues.
- The generated TF network facilitates data mining for elucidating TF functions in biological processes.
- This resource serves as a baseline for understanding TF-mediated diseases and transcriptional regulation.
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