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  Comparative Profiling of Regulatory Modules as a Tool for Identifying the Transcription Factor Network Linked to Leukemogenesis

Subramanian, S., Phongbunchoo, Y., Cauchy, P., & Ramamoorthy, S. (2025). Comparative Profiling of Regulatory Modules as a Tool for Identifying the Transcription Factor Network Linked to Leukemogenesis. Springer Protocols, 2909, 179-209. doi:10.1007/978-1-0716-4442-3_13.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0010-EBCC-0 Version Permalink: https://hdl.handle.net/21.11116/0000-0010-EBCD-F
Genre: Journal Article

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10.1007_978-1-0716-4442-3_13_vs2.pdf (Publisher version), 3MB
 
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2025
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The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature
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 Creators:
Subramanian, Swetha1, Author
Phongbunchoo, Yutthaphong1, Author
Cauchy, Pierre2, Author
Ramamoorthy, Senthilkumar2, Author
Affiliations:
1External Organizations, ou_persistent22              
2Department of Cellular and Molecular Immunology, Max Planck Institute of Immunobiology and Epigenetics, Max Planck Society, ou_2243641              

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 Abstract: The dynamic gene expression program of hematopoiesis is controlled by a complex network of regulatory modules consisting of transcription factors, chromatin modifiers, and genomic organizers. Genetic abnormalities or changes in the levels of these factors can disrupt normal development and often lead to malignant transformation into leukemic cells. Open chromatin regions are hallmarks of regulatory elements that can be profiled by their susceptibility to DNase I and Tn5 transposase. Genome-wide comparative profiling of open chromatin regions of normal and malignant cells can identify differentially induced regulatory elements and their associated regulatory modules in disease development. We provide an optimized bioinformatics pipeline for the processing of assay for transposase-accessible chromatin sequencing (ATAC-seq) and comparative profiling of open chromatin regions. The identified differentially induced open chromatin regions are used to investigate the changes in molecular networks that drive disease development through integrative analysis with other multi-OMICS data. Here, we demonstrate the robust application of this methodology to compare murine B-cell acute lymphoblastic leukemia cells with wild-type control, which can be applied to any two biological conditions. This integrative computational methodology can also be used for comparative profiling of genome-wide functional element screening methods such as DNaseI hypersensitive sites seq (DNase-seq) and chromatin immunoprecipitation seq (ChIP-seq).

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Language(s): eng - English
 Dates: 2025-03-04
 Publication Status: Published online
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 Rev. Type: Peer
 Identifiers: DOI: 10.1007/978-1-0716-4442-3_13
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Title: Springer Protocols
Source Genre: Journal
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Publ. Info: Berlin, Germany : Springer
Pages: - Volume / Issue: 2909 Sequence Number: - Start / End Page: 179 - 209 Identifier: CoNE: https://pure.mpg.de/cone/journals/resource/2478541-6