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Updated: Jun 11, 2025

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ELLA: Modeling Subcellular Spatial Variation of Gene Expression within Cells in High-Resolution Spatial

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    Summary

    We developed subcellular expression localization analysis (ELLA), a computational tool to model mRNA localization within cells using high-resolution spatial transcriptomics. ELLA identifies genes with distinct subcellular patterns and links them to mRNA characteristics.

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    Area of Science:

    • Molecular Biology
    • Computational Biology
    • Genomics

    Background:

    • High-resolution spatial transcriptomics enables subcellular gene expression measurement.
    • Understanding mRNA localization is crucial for cellular function.

    Purpose of the Study:

    • Introduce subcellular expression localization analysis (ELLA) for modeling subcellular mRNA localization.
    • Detect genes with spatial expression variation within cells in high-resolution spatial transcriptomics.

    Main Methods:

    • Developed ELLA, a computational method using a unified cellular coordinate system.
    • Employed a nonhomogeneous Poisson process for spatial count data modeling.
    • Utilized an expression gradient function to characterize subcellular expression patterns.

    Main Results:

    • ELLA identified distinct subcellular localization patterns for various gene types.
    • Genes enriched in the nucleus are often long noncoding RNAs or protein-coding mRNAs with longer gene lengths.
    • Genes involved in cytoplasmic or membrane activities showed enrichment in those cellular compartments.
    • Revealed dynamic cell cycle-dependent subcellular localization patterns.

    Conclusions:

    • ELLA is a powerful, robust, and versatile tool for analyzing subcellular spatial expression variation.
    • The method enhances the understanding of mRNA localization and its relation to gene characteristics.
    • ELLA facilitates insights into dynamic gene expression during the cell cycle.