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The Mitochondrial D‐Loop Is An Error‐Prone Reference For Mitochondrial DNA Copy Number Of Common Deletion Frequency

2017· article· en· W4389023633 on OpenAlexaffabout
Damon Poburko, Brian Li, Pola Kalinowski, Bob Mulamba, Cynthia Gershome

Bibliographic record

VenueThe FASEB Journal · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMitochondrial DNADigital polymerase chain reactionBiologyMolecular biologyDNAGeneticsCopy-number variationPolymerase chain reactionGenomeGene

Abstract

fetched live from OpenAlex

BACKGROUND Changes in mitochondrial DNA (mtDNA) copy number and the common deletion that affect electron transport chain function are associated with diverse age‐ and disease‐related pathologies of the heart, vasculature and other major organs. Changes in mtDNA and common deletion copy number to date have been studied as relative changes using qPCR, often using the mitochondrial D‐Loop (DL) as an internal mtDNA reference. However, the fraction of mtDNA containing triple‐stranded DNA (tsDNA) in the DL ranges from ~0 to >95% between tissue types and varying with cells cycle, such that DL copy number could be 1.0–1.5× that of mtDNA copy number. While difficult to assess by qPCR, droplet digital PCR (ddPCR) provides the absolute measurement of copy number required to assess whether changes in the fraction triple‐stranded DL significantly affects assays using the DL as a reference. OBJECTIVE To develop cost effective, duplex assays for mtDNA copy number and common deletion using DNA‐binding dyes and droplet digital PCR (ddPCR), and to test if variations in tsDNA DL affect measured changes in mtDNA copy number or common deletion frequency. METHODS Total genomic DNA (gDNA) was isolated from rat A7r5 aorta smooth muscle cells and freshly isolated rat aorta, heart, brain, gastrocnemius, and liver using commercial kits. Primers were selected for mtDNA references (DL, ND1), mitochondrial common deletion (ND3, ND4 and ND5) and nuclear references (Eif2c1, beta‐actin). DNA copy number was analyzed using the EvaGreen dye on a Bio‐Rad QX200. RESULTS Based on bioinformatics, Eif2C1 is a single copy number gene, while beta‐actin primers detected ~3 beta‐actin genes (i.e. two pseudogenes). Counting mtDNA copy number as DL/(2*beta‐actin*beta‐actin copy #), A7r5 and aorta had 756 ±2 and 249 ± 86 (n = 9) mtDNA/cell, consistent with published values. The ND3/DL ratio was 0.7 – 0.8 in A7r5 cells and varied between rat tissues (0.4 – 0.9), giving unusually high common deletion frequencies of 20–30% and 10–60%. Using ND1 as a reference, the DL/ND1 ratio was ~1.2–1.3 in A7r5 cells, while the ratio of ND3, ND4 and ND5 to ND1 were all ~1.0. The results were consistent with DL primers were detecting tsDNA D‐Loop. Treating A7r5 cells with the replication terminator 2′,3′‐dideoxycytidine caused DL/ND1 ratios to fall (1.31 ± 0.08 to 1.21 ± 0.05), while ND3/ND1 ratios were unaffected (1.02 ± 0.01 vs 1.05 ± 0.04), consistent with inhibition of rapid DL turn‐over. In gDNA from rat tissues, DL/ND1 showed much greater variation than ND3/ND1, suggesting that variation in the fraction of DL containing tsDNA is a significant confounding factor when comparing mtDNA copy number and common deletion between tissues or experimentally imposed conditions. CONCLUSION The D‐Loop is an error prone reference for analyses of mtDNA, imposing up to ~60% error in estimates of mtDNA copy number and common deletion frequency. Future studies should avoid the use of the DL as a reference. Further, ddPCR provides a novel and simple method for detecting changes the frequency of tsDNA in the mitochondrial D‐Loop. Support or Funding Information Natural Sciences and Engineering Research Council of Canada, Canadian Foundation for Innovation

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.005

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.039
GPT teacher head0.319
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2017
Admission routes2
Has abstractyes

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