Evidence map›Paper›PMID 39898529›Full record

ArticleBiology open2025

A high-resolution bovine mitochondrial co-expression network.

Pâmela A Alexandre, Kate Keogh, Antonio Reverter, Nicholas J Hudson

Abstract read
In one paragraph

Article in Biology open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Pâmela A AlexandreAgriculture and Food Department, Commonwealth Scientific and Industrial Research Organisation, Brisbane, Queensland 4067, Australia.ORCID 0000-0002-0649-7033
Kate KeoghAgriculture and Food Department, Commonwealth Scientific and Industrial Research Organisation, Brisbane, Queensland 4067, Australia.
Antonio ReverterAgriculture and Food Department, Commonwealth Scientific and Industrial Research Organisation, Brisbane, Queensland 4067, Australia.
Nicholas J HudsonSchool of Agriculture and Food Sustainability, The University of Queensland, Queensland, Gatton QLD4341, Australia.

Funding

Commonwealth Scientific and Industrial Research Organisation (CSIRO)CSIRO Agriculture and Food Business UnitTEAGASCThe University of Queensland
6 · The paper itself

Abstract

The mitochondrion is a sophisticated, versatile, and dynamic organelle whose function is incompletely understood. Intending to provide a framework for mitochondrial visualisation and interpretation of genome-wide molecular data, we reverse-engineered a co-expression network whose final structure represented mRNA encoding more than half of the entire mitochondrial proteome. We drew upon 723 RNA-seq data sets representing 91 tissues and cell types from 441 individual cattle. A mitochondrial landscape was formed comprising a main network and many smaller sub-networks. One of the discrete sub-networks contains all 13 mRNA (e.g. MT-ND1, MT -CYTB, MT -COX2, MT -ATP8) plus 15/22 tRNA (e.g. MT-TT) encoded by the mt-genome itself, indicating some independent regulation from the nuclear genome with whom it must cooperate. Intriguingly, this mtDNA sub-network also contains a single nuclear-encoded gene, that of PDHA1. PDHA1 encodes a subunit of the pyruvate dehydrogenase complex that governs the conversion of pyruvate to Acetyl CoA. This enzyme is extremely influential, representing the fundamental cellular connection between the ancient, conserved pathway of glycolysis that occurs exclusively in the cytoplasm, and the TCA cycle that occurs within the mitochondrial matrix. To demonstrate the downstream utility of our approach, we overlaid Longissimus dorsi muscle transcriptome data from differentially feed efficient Charolais and Holstein Friesian cattle. This approach highlighted expression patterns sensitive to both breed and diet in a complex manner. An analytic advantage of this approach is that relatively subtle (<2-fold) but coordinated changes that may be overlooked by conventional gene-by-gene significance testing become readily apparent. Finally, intending to understand the transcriptional regulation of mitochondrial function more thoroughly, we engineered a network built with transcription factors in addition to those mRNA encoding mitochondrial proteins. Here, a set of influential nuclear hormone receptors (e.g. PPARA) are enriched among the most highly and/or well-connected TF.

Indexed as

Gene Expression RegulationGene Regulatory NetworksMitochondriaAnimalsCattleComputational BiologyDNA, MitochondrialGene Expression ProfilingTranscriptomeDNA, MitochondrialBeef cattleFeed efficiencyOrganellePartial correlationRNAseq

Identifiers

PMID39898529
PMCPMC11832118

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.