Evidence map›Paper›PMID 26018764›Full record

ArticleBMC genomics2015

Key genes as stress indicators in the ubiquitous diatom Skeletonema marinoi.

Chiara Lauritano, Ida Orefice, Gabriele Procaccini, Giovanna Romano, Adrianna Ianora

Abstract read
In one paragraph

Article in BMC genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Article
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  4. Differential Expression of Stress Adaptation Genes in a DiatomInternational journal of molecular sciences · 2024
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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.

Chiara LauritanoStazione Zoologica Anton Dohrn, Villa Comunale, 80121, Napoli, Italy. chiara.lauritano@szn.it.
Ida OreficeStazione Zoologica Anton Dohrn, Villa Comunale, 80121, Napoli, Italy. ida.orefice@szn.it.
Gabriele ProcacciniStazione Zoologica Anton Dohrn, Villa Comunale, 80121, Napoli, Italy. gabriele.procaccini@szn.it.
Giovanna RomanoStazione Zoologica Anton Dohrn, Villa Comunale, 80121, Napoli, Italy. giovanna.romano@szn.it.
Adrianna IanoraStazione Zoologica Anton Dohrn, Villa Comunale, 80121, Napoli, Italy. adrianna.ianora@szn.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe dense phytoplankton blooms that characterize productive regions and seasons in the oceans are dominated, from high to low latitudes and from coast line to open ocean, by comparatively few, often cosmopolitan species of diatoms. These key dominant species may undergo dramatic changes due to global climate change.

resultsIn order to identify molecular stress-indicators for the ubiquitous diatom species Skeletonema marinoi, we tested stress-related genes in different environmental conditions (i.e. nutrient starvation/depletion, CO2-enrichment and combined effects of these stressors) using RT-qPCR. The data show that these stressors impact algal growth rate, inducing early aging and profound changes in expression levels of the genes of interest.

conclusionsMost analyzed genes (e.g. antioxidant-related and aldehyde dehydrogenases) were strongly down-regulated which may indicate a strategy to avoid unnecessary over-investment in their respective proteins. By contrast, key genes were activated (e.g. HSPs, GOX) which may allow the diatom species to better cope with adverse conditions. We propose the use of this panel of genes as early bio-indicators of environmental stress factors in a changing ocean.

Indexed as

Algal ProteinsCarbon DioxideDiatomsGene Expression Regulation, ArchaealPhytoplanktonSilicic AcidStress, PhysiologicalAlgal ProteinsCarbon DioxideSilicic Acid

Identifiers

PMID26018764
PMCPMC4445783

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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.