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  1. Article ; Online: Clover: An unbiased method for prioritizing differentially expressed genes using a data-driven approach.

    Oba, Gina Miku / Nakato, Ryuichiro

    Genes to cells : devoted to molecular & cellular mechanisms

    2024  

    Abstract: Identifying key genes from a list of differentially expressed genes (DEGs) is a critical step in transcriptome analysis. However, current methods, including Gene Ontology analysis and manual annotation, essentially rely on existing knowledge, which is ... ...

    Abstract Identifying key genes from a list of differentially expressed genes (DEGs) is a critical step in transcriptome analysis. However, current methods, including Gene Ontology analysis and manual annotation, essentially rely on existing knowledge, which is highly biased depending on the extent of the literature. As a result, understudied genes, some of which may be associated with important molecular mechanisms, are often ignored or remain obscure. To address this problem, we propose Clover, a data-driven scoring method to specifically highlight understudied genes. Clover aims to prioritize genes associated with important molecular mechanisms by integrating three metrics: the likelihood of appearing in the DEG list, tissue specificity, and number of publications. We applied Clover to Alzheimer's disease data and confirmed that it successfully detected known associated genes. Moreover, Clover effectively prioritized understudied but potentially druggable genes. Overall, our method offers a novel approach to gene characterization and has the potential to expand our understanding of gene functions. Clover is an open-source software written in Python3 and available on GitHub at https://github.com/G708/Clover.
    Language English
    Publishing date 2024-04-11
    Publishing country England
    Document type Journal Article
    ZDB-ID 1330000-3
    ISSN 1365-2443 ; 1356-9597
    ISSN (online) 1365-2443
    ISSN 1356-9597
    DOI 10.1111/gtc.13119
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Context-dependent perturbations in chromatin folding and the transcriptome by cohesin and related factors.

    Nakato, Ryuichiro / Sakata, Toyonori / Wang, Jiankang / Nagai, Luis Augusto Eijy / Nagaoka, Yuya / Oba, Gina Miku / Bando, Masashige / Shirahige, Katsuhiko

    Nature communications

    2023  Volume 14, Issue 1, Page(s) 5647

    Abstract: Cohesin regulates gene expression through context-specific chromatin folding mechanisms such as enhancer-promoter looping and topologically associating domain (TAD) formation by cooperating with factors such as cohesin loaders and the insulation factor ... ...

    Abstract Cohesin regulates gene expression through context-specific chromatin folding mechanisms such as enhancer-promoter looping and topologically associating domain (TAD) formation by cooperating with factors such as cohesin loaders and the insulation factor CTCF. We developed a computational workflow to explore how three-dimensional (3D) structure and gene expression are regulated collectively or individually by cohesin and related factors. The main component is CustardPy, by which multi-omics datasets are compared systematically. To validate our methodology, we generated 3D genome, transcriptome, and epigenome data before and after depletion of cohesin and related factors and compared the effects of depletion. We observed diverse effects on the 3D genome and transcriptome, and gene expression changes were correlated with the splitting of TADs caused by cohesin loss. We also observed variations in long-range interactions across TADs, which correlated with their epigenomic states. These computational tools and datasets will be valuable for 3D genome and epigenome studies.
    MeSH term(s) Transcriptome ; Cell Cycle Proteins/genetics ; Chromosomal Proteins, Non-Histone/genetics ; Chromatin/genetics ; Cohesins
    Chemical Substances Cell Cycle Proteins ; Chromosomal Proteins, Non-Histone ; Chromatin
    Language English
    Publishing date 2023-09-19
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2553671-0
    ISSN 2041-1723 ; 2041-1723
    ISSN (online) 2041-1723
    ISSN 2041-1723
    DOI 10.1038/s41467-023-41316-4
    Database MEDical Literature Analysis and Retrieval System OnLINE

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