Evidence map›Paper›PMID 37308782›Full record

ArticleScientific reports2023

Accurate, non-destructive, and high-throughput age estimation for Golden perch (Macquaria ambigua spp.) using DNA methylation.

Benjamin Mayne, Tom Espinoza, David A Crook, Chloe Anderson, Darren Korbie, Jonathan C Marshall, Mark J Kennard, Doug J Harding, Gavin L Butler, Brien Roberts and 2 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.4field-weighted citation impact, top 20% of its field
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

5 citing papers in PubMed, 9 citations in OpenAlex.

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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

12 authors at 4 institutions in 1 country.

Benjamin MayneEnvironomics Future Science Platform, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Indian Ocean Marine Research Centre, Crawley, WA, Australia. benjamin.mayne@csiro.au.
Tom EspinozaDepartment of Regional Development, Manufacturing and Water, Brisbane, QLD, Australia.
David A CrookDepartment of Primary Industries, Narrandera Fisheries Centre, Narrandera, NSW, Australia.
Chloe AndersonEnvironomics Future Science Platform, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Indian Ocean Marine Research Centre, Crawley, WA, Australia.
Darren KorbieAustralian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, QLD, Australia.
Jonathan C MarshallQueensland Department of Environment and Science, Brisbane, QLD, Australia.
Mark J KennardAustralian Rivers Institute and Griffith School of Environment and Science, Griffith University, Nathan, QLD, 4111, Australia.
Doug J HardingDepartment of Regional Development, Manufacturing and Water, Brisbane, QLD, Australia.
Gavin L ButlerNSW Department of Primary Industries (Fisheries), Grafton, NSW, Australia.
Brien RobertsFisheries Division, Department of Industry, Tourism and Trade, Darwin, NT, Australia.
Josh WhileyAustralian Rivers Institute and Griffith School of Environment and Science, Griffith University, Nathan, QLD, 4111, Australia.
Sharon MarshallDepartment of Regional Development, Manufacturing and Water, Brisbane, QLD, Australia.
Griffith University · AUCommonwealth Scientific and Industrial Research Organisation · AUNew South Wales Department of Primary Industries · AUUniversity of Queensland · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Age structure information of animal populations is fundamental to their conservation and management. In fisheries, age is routinely obtained by counting daily or annual increments in calcified structures (e.g., otoliths) which requires lethal sampling. Recently, DNA methylation has been shown to estimate age using DNA extracted from fin tissue without the need to kill the fish. In this study we used conserved known age-associated sites from the zebrafish (Danio rerio) genome to predict the age of golden perch (Macquaria ambigua), a large-bodied native fish from eastern Australia. Individuals aged using validated otolith techniques from across the species' distribution were used to calibrate three epigenetic clocks. One clock was calibrated using daily (daily clock) and another with annual (annual clock) otolith increment counts, respectively. A third used both daily and annual increments (universal clock). We found a high correlation between the otolith and epigenetic age (Pearson correlation > 0.94) across all clocks. The median absolute error was 2.4 days in the daily clock, 184.6 days in the annual clock, and 74.5 days in the universal clock. Our study demonstrates the emerging utility of epigenetic clocks as non-lethal and high-throughput tools for obtaining age estimates to support the management of fish populations and fisheries.

Indexed as

PerchesPerciformesAnimalsAustraliaDNA MethylationZebrafish

Identifiers

PMID37308782
PMCPMC10260977
OpenAlexW4380359515

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.