Evidence map›Paper›PMID 40494877›Full record

ArticleScientific data2025

Seasonal transcriptome profile across three different tissues of the Andean Killifish Orestias ascotanensis.

Rodrigo Maldonado-Agurto, Elvis Acevedo, Vinicius Maracaja-Coutinho, Martin Montecino

Abstract readDataset
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Rodrigo Maldonado-AgurtoCenter for Biomedical Research (CIBMED), Faculty of Medicine, Universidad Finis Terrae, Santiago, Chile.ORCID 0000-0002-8326-9800
Elvis AcevedoInstitute of Biomedical Sciences, Faculty of Medicine, Universidad Andres Bello, Santiago, Chile.
Vinicius Maracaja-CoutinhoUnidad de Genómica Avanzada - UGA, Facultad de Ciencias Químicas y Farmacéuticas, Universidad de Chile, Santiago, Chile.
Martin MontecinoInstitute of Biomedical Sciences, Faculty of Medicine, Universidad Andres Bello, Santiago, Chile. mmontecino@unab.cl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Andean killifish Orestias ascotanensis inhabits the high-altitude Ascotán Salt Pan, an environment with variable salinity, high UV exposure, low oxygen, and extreme daily temperature fluctuations. These conditions make it an excellent model for studying high-altitude fish biology. However, the transcriptomic responses of O. ascotanensis to seasonal acclimation remain unexplored. To investigate seasonal and tissue-specific transcriptomic profiles, RNA-seq was performed on 42 libraries from gills, skin, and muscle tissues of 14 individuals collected in summer (n = 7) and winter (n = 7). Each library had a median of 105 million reads. Principal component analysis revealed strong tissue-specific expression, and seasonal differential expression analyses identified significant transcriptomic changes within each tissue. Additionally, a bioinformatics pipeline identified 10,365 high-confidence long non-coding RNAs (lncRNAs), predicted by at least three computational tools. Compared to protein-coding genes, lncRNAs exhibited higher tissue specificity, with a predominance of monoexonic structures and shorter exon lengths. This dataset provides the first comprehensive view of seasonal mRNA and lncRNA expression in O. ascotanensis tissues.

Indexed as

KillifishesSeasonsTranscriptomeAnimalsGillsRNA, Long NoncodingRNA, MessengerRNA, Long NoncodingRNA, Messenger

Identifiers

PMID40494877
PMCPMC12152186

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.