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Updated: Jun 18, 2025
In Utero Electroporation of Multiaddressable Genome-Integrating Color MAGIC Markers to Individualize Cortical Mouse Astrocytes
Published on: May 21, 2020
Single-mitochondrion sequencing uncovers distinct mutational patterns and heteroplasmy landscape in mouse astrocytes
Parnika S Kadam1, Zijian Yang2, Youtao Lu3
1Department of Pharmacology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Background:
Mitochondrial (mt) heteroplasmy can cause adverse biological consequences when deleterious mtDNA mutations accumulate disrupting "normal" mt-driven processes and cellular functions. To investigate the heteroplasmy of such mtDNA changes, we developed a moderate throughput mt isolation procedure to quantify the mt single-nucleotide variant (SNV) landscape in individual mouse neurons and astrocytes. In this study, we amplified mt-genomes from 1645 single mitochondria isolated from mouse single astrocytes and neurons to (1) determine the distribution and proportion of mt-SNVs as well as mutation pattern in specific target regions across the mt-genome, (2) assess differences in mtDNA SNVs between neurons and astrocytes, and (3) study co-segregation of variants in the mouse mtDNA.
Results:
(1) The data show that specific sites of the mt-genome are permissive to SNV presentation while others appear to be under stringent purifying selection. Nested hierarchical analysis at the levels of mitochondrion, cell, and mouse reveals distinct patterns of inter- and intra-cellular variation for mt-SNVs at different sites. (2) Further, differences in the SNV incidence were observed between mouse neurons and astrocytes for two mt-SNV 9027:G > A and 9419:C > T showing variation in the mutational propensity between these cell types. Purifying selection was observed in neurons as shown by the Ka/Ks statistic, suggesting that neurons are under stronger evolutionary constraint as compared to astrocytes. (3) Intriguingly, these data show strong linkage between the SNV sites at nucleotide positions 9027 and 9461.
Conclusions:
This study suggests that segregation as well as clonal expansion of mt-SNVs is specific to individual genomic loci, which is important foundational data in understanding of heteroplasmy and disease thresholds for mutation of pathogenic variants.
Insights
Mitochondrial DNA (mtDNA) single-nucleotide variants (SNVs) show cell-type-specific patterns in mouse neurons and astrocytes. This study reveals distinct variation patterns and linkage between SNV sites, crucial for understanding heteroplasmy and disease.
Area of Science:
- Cellular Biology
- Genetics
- Mitochondrial Biology
Background:
- Mitochondrial heteroplasmy, arising from accumulating mtDNA mutations, disrupts cellular functions.
- Investigating mtDNA single-nucleotide variants (SNVs) is key to understanding these disruptions.
- A novel method was developed to isolate and analyze mitochondria from individual mouse cells.
Purpose of the Study:
- To quantify the mt-SNV landscape in individual mouse neurons and astrocytes.
- To determine the distribution, proportion, and mutation patterns of mt-SNVs across the mitochondrial genome.
- To compare mtDNA SNVs between neurons and astrocytes and study variant co-segregation.
Main Methods:
- Isolation of 1645 single mitochondria from mouse astrocytes and neurons.
- Amplification of mitochondrial genomes from isolated mitochondria.
- Analysis of mt-SNV distribution, mutation patterns, and co-segregation.
Main Results:
- Specific mt-genome sites are permissive to SNVs, while others are under purifying selection.
- Distinct inter- and intra-cellular variation patterns for mt-SNVs were observed.
- Neurons exhibit stronger evolutionary constraint (purifying selection) than astrocytes, with specific SNVs (9027:G>A, 9419:C>T) differing between cell types.
- Strong linkage was found between SNV sites at nucleotide positions 9027 and 9461.
Conclusions:
- mt-SNV segregation and clonal expansion are locus-specific.
- This foundational data is vital for understanding heteroplasmy and disease thresholds related to pathogenic variants.
