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Related Concept Videos

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The present-day mitochondrial and chloroplast genomes have retained some of the characteristics of their ancestral prokaryotes and also have acquired new attributes during their evolution within eukaryotic cells. Like prokaryotic genomes, mitochondrial and chloroplast genomes neither bind with histone-like proteins nor show complex packaging into chromosome-like structures, as observed in eukaryotes. Unlike mitotic cell divisions observed in eukaryotic cells, mitochondria and chloroplasts...
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A eukaryotic cell can have up to three different types of genetic systems: nuclear, mitochondrial, and chloroplast. During evolution, organelles have exported many genes to the nucleus; this transfer is still ongoing in some plant species. Approximately 18% of the Arabidopsis thaliana nuclear genome is thought to be derived from the chloroplast’s cyanobacterial ancestor, and around 75% of the yeast genome derived from the mitochondria’s bacterial ancestor. This export has occurred...
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Related Experiment Video

Updated: May 20, 2025

Author Spotlight: An Optimized Automated Method for Investigating Retinoic Acid Receptors in Neuronal Mitochondria
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mitoXplorer 3.0, A Web Tool for Exploring Mitochondrial Dynamics in Single-cell RNA-seq Data.

Margaux Haering1, Andrea Del Bondio2, Helene Puccio2

  • 1Aix-Marseille University, CNRS, IBDM UMR7288, Turing Center for Living Systems (CENTURI), 13009 Marseille, France.

Journal of Molecular Biology
|March 26, 2025
PubMed
Summary
This summary is machine-generated.

MitoXplorer 3.0 analyzes mitochondrial gene expression at the single-cell level, revealing cell-to-cell variability and identifying disease-specific mitochondrial dysfunction in Spinocerebellar Ataxia Type 1. This tool enhances understanding of mitochondrial roles in cellular health and disease.

Keywords:
data integrationmitoXplorermitochondriasingle-nuclei sequencingvisual data mining

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Area of Science:

  • Mitochondrial biology
  • Single-cell genomics
  • Bioinformatics tools

Background:

  • Mitochondria are vital organelles with diverse functions, yet their variability within a single cell type remains underexplored.
  • Understanding mitochondrial dynamics at single-cell resolution is crucial for comprehensive functional analysis.

Purpose of the Study:

  • Introduce mitoXplorer 3.0, an enhanced web tool for analyzing single-cell sequencing data focused on mitochondrial genes (mito-genes).
  • Provide a new formatting script, scXplorer, to prepare single-cell RNA sequencing data for mitoXplorer 3.0 analysis.
  • Enable identification of cell subpopulations and in-depth analysis of mitochondrial function and variability.

Main Methods:

  • Development of mitoXplorer 3.0 with new features for single-cell mitochondrial analysis.
  • Creation of scXplorer script for data formatting and generation of pseudo-bulk and single-cell mito-gene expression matrices.
  • Application of mitoXplorer 3.0 to analyze single-cell transcriptome data from a Spinocerebellar Ataxia Type 1 (SCA1) study.

Main Results:

  • MitoXplorer 3.0 successfully generates compatible files and enables novel single-cell based mitochondrial analyses.
  • Identification of cell subpopulations based solely on mito-gene expression.
  • Significant mitochondrial processes and genes affected in SCA1 Purkinje cells were identified, linking them to disease pathology.

Conclusions:

  • MitoXplorer 3.0 provides powerful, interactive interfaces for in-depth, single-cell mitochondrial research.
  • The tool aids in understanding mitochondrial dysfunction in neurodegenerative diseases like SCA1.
  • MitoXplorer 3.0 is freely accessible, promoting further research in mitochondrial biology and disease.