Evidence map›Paper›PMID 31307373›Full record

ArticleBMC genomics2019

Development of a large SNPs resource and a low-density SNP array for brown trout (Salmo trutta) population genetics.

Keoni Saint-Pé, Maeva Leitwein, Laurence Tissot, Nicolas Poulet, Bruno Guinand, Patrick Berrebi, Geoffrey Marselli, Jean-Marc Lascaux, Pierre-Alexandre Gagnaire, Simon Blanchet

Abstract read
In one paragraph

Article in BMC genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

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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

10 authors.

Keoni Saint-PéCentre National de la Recherche Scientifique (CNRS), Université Paul Sabatier (UPS), Station d'Ecologie Théorique et Expérimentale, SETE, UMR 5321, 2 route du CNRS, 09200, Moulis, France. keoni.saintpe@sete.cnrs.fr.
Maeva LeitweinDépartement de Biologie, Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, QC, Canada.
Laurence TissotEDF R and D LNHE - Laboratoire National d'Hydraulique et Environnement, 6 quai Watier, 78401, Chatou Cedex, France.
Nicolas PouletPôle écohydraulique AFB-IMT, allée du Pr Camille Soula, 31400, Toulouse, France.
Bruno GuinandISEM, CNRS, Univ. Montpellier, IRD, EPHE, Montpellier, France.
Patrick BerrebiISEM, CNRS, Univ. Montpellier, IRD, EPHE, Montpellier, France.
Geoffrey MarselliCentre National de la Recherche Scientifique (CNRS), Université Paul Sabatier (UPS), Station d'Ecologie Théorique et Expérimentale, SETE, UMR 5321, 2 route du CNRS, 09200, Moulis, France.
Jean-Marc LascauxECOGEA, 352 Avenue Roger Tissandié, 31600, Muret, France.
Pierre-Alexandre GagnaireISEM, CNRS, Univ. Montpellier, IRD, EPHE, Montpellier, France.
Simon BlanchetCentre National de la Recherche Scientifique (CNRS), Université Paul Sabatier (UPS), Station d'Ecologie Théorique et Expérimentale, SETE, UMR 5321, 2 route du CNRS, 09200, Moulis, France.

Funding

Agence Française pour la Biodiversité 136406Électricité de France (FR) 8619-5920011137
6 · The paper itself

Abstract

backgroundThe brown trout (Salmo trutta) is an economically and ecologically important species for which population genetic monitoring is frequently performed. The most commonly used genetic markers for this species are microsatellites and mitochondrial markers that lack replicability among laboratories, and a large genome coverage. An alternative that may be particularly efficient and universal is the development of small to large panels of Single Nucleotide Polymorphism markers (SNPs). Here, we used Restriction site Associated DNA sequences (RADs) markers to identify a set of 12,204 informative SNPs positioned on the brown trout linkage map and suitable for population genetics studies. Then, we used this novel resource to develop a cost-effective array of 192 SNPs (96 × 2) evenly spread on this map. This array was tested for genotyping success in five independent rivers occupied by two main brown trout evolutionary lineages (Atlantic -AT- and Mediterranean -ME-) on a total of 1862 individuals. Moreover, inference of admixture rate with domestic strains and population differentiation were assessed for a small river system (the Taurion River, 190 individuals) and results were compared to a panel of 13 microsatellites.

resultsA high genotyping success was observed for all rivers (< 1% of non-genotyped loci per individual), although some initially used SNP failed to be amplified, probably because of mutations in primers, and were replaced. These SNPs permitted to identify patterns of isolation-by-distance for some rivers. Finally, we found that microsatellite and SNP markers yielded very similar patterns for population differentiation and admixture assessments, with SNPs having better ability to detect introgression and differentiation.

conclusionsThe novel resources provided here opens new perspectives for universality and genome-wide studies in brown trout populations.

Indexed as

Polymorphism, Single NucleotideAnimalsGenetics, PopulationMicrosatellite RepeatsTroutAdmixtureConservationManagementMicroarrayPopulation genomics

Identifiers

PMID31307373
PMCPMC6631668

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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.