Evidence map›Paper›PMID 26768650›Full record

ArticleBMC genomics2016

Transcriptome profiling in fast versus slow-growing rainbow trout across seasonal gradients.

Roy G Danzmann, Andrea L Kocmarek, Joseph D Norman, Caird E Rexroad, Yniv Palti

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
7.1field-weighted citation impact, top 3% 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

30 citing papers in PubMed, 62 citations in OpenAlex.

  1. Multi-Organ Transcriptomic Analysis of Greater Amberjack (Animals : an open access journal from MDPI · 2026
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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

5 authors at 2 institutions in 2 countries.

Roy G DanzmannDepartment of Integrative Biology, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada. rdanzman@uoguelph.ca.
Andrea L KocmarekDepartment of Integrative Biology, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada. akocmare@uoguelph.ca.
Joseph D NormanDepartment of Integrative Biology, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada. jnorman@uoguelph.ca.
Caird E RexroadNational Center for Cool and Cold Water Aquaculture, ARS-USDA, 11861 Leetown Road, Kearneysville, WV, 25430, USA. Caird.RexroadIII@ars.usda.gov.
Yniv PaltiNational Center for Cool and Cold Water Aquaculture, ARS-USDA, 11861 Leetown Road, Kearneysville, WV, 25430, USA. Yniv.Palti@ars.usda.gov.
University of Guelph · CANational Center for Cool and Cold Water Aquaculture · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCircannual rhythms in vertebrates can influence a wide variety of physiological processes. Some notable examples include annual reproductive cycles and for poikilotherms, seasonal changes modulating growth. Increasing water temperature elevates growth rates in fishes, but increases in photoperiod regime can have similar influences even at constant temperature. Therefore, in order to understand the dynamics of growth in fish it is important to consider the background influence of photoperiod regime on gene expression differences. This study examined the influence of a declining photoperiod regime (winter solstice) compared to an increasing photoperiod regime (spring equinox) on white muscle transcriptome profiles in fast and slow-growing rainbow trout from a commercial aquaculture strain.

resultsSlow-growing fish could be characterized as possessing transcriptome profiles that conform in many respects to an endurance training regime in humans. They have elevated mitochondrial and cytosolic creatine kinase expression levels and appear to suppress mTOR-signaling as evidenced by elevated TSC2 expression, and they also have elevated p53 levels. Large fish display a physiological repertoire that may be consistent with strength/resistance physiology having elevated cytoskeletal gene component expression and glycogen metabolism cycling along with higher PI3K levels. In many respects small vs. large fish match eccentric vs. concentric muscle expression patterns, respectively. Lipid metabolic genes are also more elevated in larger fish, the most notable being the G0S2 switch gene. M and Z-line sarcomere remodelling appears to be more prevalent in large fish. Twenty-three out of 26 gene families with previously reported significant SNP-based growth differences were detected as having significant expression differences.

conclusionsLarger fish display a broader array of genes showing higher expression, and their profiles are more similar to those observed in December lot fish (i.e., an accelerated growth period). Conversely, small fish display gene profiles more similar to seasonal growth decline phases (i.e., September lot fish). Overall, seasonal timing was coupled to greater differences in gene expression compared to differences associated with fish size.

Indexed as

Gene Expression ProfilingAnimalsGene Expression Regulation, DevelopmentalOncorhynchus mykissPhosphatidylinositol 3-KinasesSeasonsTemperatureTOR Serine-Threonine KinasesTranscriptomeTuberous Sclerosis Complex 2 ProteinTumor Suppressor Protein p53Tumor Suppressor ProteinsPhosphatidylinositol 3-KinasesTOR Serine-Threonine KinasesTSC2 protein, humanTuberous Sclerosis Complex 2 ProteinTumor Suppressor Protein p53Tumor Suppressor Proteins

Identifiers

PMID26768650
PMCPMC4714434
OpenAlexW2236416058

What OpenQuestion holds

Textmetadata
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.