Systematic determination of the mitochondrial proportion in human and mice tissues for single-cell RNA-sequencing data quality control
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Abstract
Motivation: Quality control (QC) is a critical step in single-cell RNA-seq (scRNA-seq) data analysis. Low-quality cells are removed from the analysis during the QC process to avoid misinterpretation of the data. An important QC metric is the mitochondrial proportion (mtDNA%), which is used as a threshold to filter out low-quality cells. Early publications in the field established a threshold of 5% and since then, it has been used as a default in several software packages for scRNA-seq data analysis, and adopted as a standard in many scRNA-seq studies. However, the validity of using a uniform threshold across different species, single-cell technologies, tissues and cell types has not been adequately assessed. Results: We systematically analyzed 5 530 106 cells reported in 1349 annotated datasets available in the PanglaoDB database and found that the average mtDNA% in scRNA-seq data across human tissues is significantly higher than in mouse tissues. This difference is not confounded by the platform used to generate the data. Based on this finding, we propose new reference values of the mtDNA% for 121 tissues of mouse and 44 tissues of humans. In general, for mouse tissues, the 5% threshold performs well to distinguish between healthy and low-quality cells. However, for human tissues, the 5% threshold should be reconsidered as it fails to accurately discriminate between healthy and low-quality cells in 29.5% (13 of 44) tissues analyzed. We conclude that omitting the mtDNA% QC filter or adopting a suboptimal mtDNA% threshold may lead to erroneous biological interpretations of scRNA-seq data. Availabilityand implementation: The code used to download datasets, perform the analyzes and produce the figures is available at https://github.com/dosorio/mtProportion. Supplementary information: Supplementary data are available at Bioinformatics online.
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Features present in less than five cells were removed and only high-quality cells were retained, i.e. singlets with more than 200 features and a maximal percentage of mitochondrial RNA content of 15% for scRNA-seq data and 5% for snRNA-seq data.
“Features (genes) present in less than five cells were removed and only high-quality cells were retained, i.e. singlets with more than 200 features and a maximal percentage of mitochondrial RNA content of 15% for scRNA-seq data70 and 5% for snRNA-seq data25,64 (Supplementary Data 2).”
From CHIT1 at diagnosis predicts faster disability progression and reflects early microglial activation in multiple sclerosis (2024) · cites this paper as [70]
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Experimental — accuracy not yet measuredMicro3 nuclei expressed fewer total genes and an increased percentage of mitochondrial genes relative to other sub-populations.
“This microglial nuclei sub-population expressed fewer total genes and an increased percentage of mitochondrial genes relative to other sub-populations (Supplementary Fig. 9a, d, e) [54].”
From Characterisation of premature cell senescence in Alzheimer's disease using single nuclear transcriptomics (2024) · cites this paper as [54]
The Results (section 3; page unavailable) report that cardiomyocyte cells with higher mitochondrial proportions had fewer genes with detectable expression. The paper does not report the Micro3 microglial-nuclei sub-population or compare it with other microglial sub-populations, so it supports the general association but not the specific observation. (LLM, conf=0.84)
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- Authors
- Osorio, D., & Cai, J. J.
- Affiliations
- Texas A&M University (US)
- Corresponding author
- Osorio, Daniel
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2020-08-25
- Volume
- 37
- Issue
- 7
- Pages
- 963-967
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- PMC
- PMC8599307
- OpenAlex
- W3080945506
- Cited by
- 212
- References
- 24
- Citations by year
- 2026: 26 · 2025: 45 · 2024: 59 · 2023: 36 · 2022: 27 · 2021: 15 · 2020: 3
- FWCI
- 6.54
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
- Locations
- Bioinformatics (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Texas A&M University
- Texas A&M Institute of Data Science
- NIH
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Keywords
- single-cell RNA sequencing, data quality control, human tissue, mouse tissues, species differences
- MeSH terms
- Animals, Humans, Quality Control, Software, Sequence Analysis, RNA, Gene Expression Profiling, Mice, Single-Cell Analysis
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