Evidence map›Paper›PMID 30631147›Full record

ArticleHeredity2019

Mapping of quantitative trait loci for life history traits segregating within common frog populations.

Gemma Palomar, Anti Vasemägi, Freed Ahmad, Alfredo G Nicieza, José Manuel Cano

Open access · bronzeAbstract read
In one paragraph

Article in Heredity, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 22% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. The Ecology of Hybrid Incompatibilities.Cold Spring Harbor perspectives in biology · 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 at 3 institutions in 5 countries.

Gemma PalomarResearch Unit of Biodiversity (UO-CSIC-PA), 33600, Mieres, Asturias, Spain. gemma.palomar@yahoo.es.
Anti VasemägiDepartment of Biology, University of Turku, 20014, Turku, Finland.
Freed AhmadDepartment of Biology, University of Turku, 20014, Turku, Finland.
Alfredo G NiciezaResearch Unit of Biodiversity (UO-CSIC-PA), 33600, Mieres, Asturias, Spain.
José Manuel CanoResearch Unit of Biodiversity (UO-CSIC-PA), 33600, Mieres, Asturias, Spain.ORCID http://orcid.org/0000-0002-8788-7315
Universidad de Oviedo · ESUniversity of Turku · FIJagiellonian University · PL

Funding

Academy of Finland (Suomen Akatemia) 266321
6 · The paper itself

Abstract

The evolution of complex traits is often shaped by adaptive divergence. However, very little is known about the number, effect size, and location of the genomic regions influencing the variation of these traits in natural populations. Based on a dense linkage map of the common frog, Rana temporaria, we have localized, for the first time in amphibians, three significant and nine suggestive quantitative trait loci (QTLs) for metabolic rate, growth rate, development time, and weight at metamorphosis, explaining 5.6-18.9% of the overall phenotypic variation in each trait. We also found a potential pleiotropic QTL between development time and size at metamorphosis that, if confirmed, might underlie the previously reported genetic correlation between these traits. Furthermore, we demonstrate that the genetic variation linked to fitness-related larval traits segregates within Rana temporaria populations. This study provides the first insight into the genomic regions that affect larval life history traits in anurans, providing a valuable resource to delve further into the genomic basis of evolutionary change in amphibians.

Indexed as

Life History TraitsQuantitative Trait LociAnimalsBody SizeChromosome MappingFemaleMaleMetamorphosis, BiologicalRana temporaria

Identifiers

PMID30631147
PMCPMC6781108
OpenAlexW2910927735

What OpenQuestion holds

Textmetadata
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.