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Related Concept Videos

RNA-seq03:21

RNA-seq

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
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Among all the organelles in an animal cell, only mitochondria have their own independent genomes. Animal mitochondrial DNA is a double-stranded, closed-circular molecule with around 20,000 base pairs. Mitochondrial DNA is unique in that one of its two strands, the heavy, or H, -strand is guanine rich, whereas the complementary strand is cytosine rich and called the light, or L, -strand. Compared to nuclear DNA, mitochondrial DNA has a very low percentage of non-coding regions and is marked by...
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Related Experiment Video

Updated: Jan 16, 2026

Measuring Single-Cell Mitochondrial DNA Copy Number and Heteroplasmy Using Digital Droplet Polymerase Chain Reaction
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MitoDelta: identifying mitochondrial DNA deletions at cell-type resolution from single-cell RNA sequencing data.

Haruko Nakagawa1,2, Yasuyuki Shima3,4, Yohei Sasagawa1,2

  • 1Department of Functional Genome Informatics, Division of Biological Data Science, Medical Research Laboratory, Institute of Integrated Research, Institute of Science Tokyo, 1-5-45 Yushima, Bunkyo-Ku, Tokyo, 113-8510, Japan.

BMC Genomics
|September 26, 2025
PubMed
Summary

MitoDelta is a new computational tool that detects mitochondrial DNA (mtDNA) deletions in specific cell types using single-cell RNA sequencing data. This method reveals how mtDNA mutations impact different cell populations, aiding disease research.

Keywords:
Deletion variantMitochondrial DNASingle-cell transcriptomicsVariant caller

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Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Mitochondrial DNA (mtDNA) deletions are linked to diseases like neurodegeneration.
  • Bulk sequencing masks cell-type-specific mtDNA mutation patterns.
  • Single-cell resolution is crucial for understanding mtDNA deletion impact.

Purpose of the Study:

  • Develop a method to detect cell-type-specific mtDNA deletions from single-cell RNA sequencing (scRNA-seq) data.
  • Leverage the high abundance of mtDNA reads in scRNA-seq data.
  • Provide a tool for analyzing mitochondrial genome alterations at single-cell resolution.

Main Methods:

  • MitoDelta pipeline uses sensitive alignment and beta-binomial statistical filtering.
  • Analyzes reads pooled by annotated cell types for deletion burden quantification.
  • Benchmarked against existing tools, showing superior performance.

Main Results:

  • MitoDelta accurately identifies mtDNA deletions from noisy scRNA-seq data.
  • Quantifies deletion burden across distinct cellular populations.
  • Applied to Parkinson's disease data, revealing cell-type-specific deletion patterns in neuronal subtypes.

Conclusions:

  • MitoDelta enables transcriptome-integrated, cell-type-specific detection of mtDNA deletions from scRNA-seq data.
  • Offers a framework for reanalyzing public datasets and studying mitochondrial alterations.
  • Facilitates investigation into mtDNA deletions in cell-type-specific disease mechanisms.