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Enregistrement W2626461261 · doi:10.1101/148577

Parallel epigenetic modifications induced by hatchery rearing in a Pacific Salmon

2017· preprint· en· W2626461261 sur OpenAlexafffundabout
Jérémy Le Luyer, Martin Laporte, Terry D. Beacham, Karia H. Kaukinen, Ruth E. Withler, Jong S. Leong, Éric Rondeau, Ben F. Koop, Louis Bernatchez

Notice bibliographique

RevuebioRxiv (Cold Spring Harbor Laboratory) · 2017
Typepreprint
Langueen
DomaineEnvironmental Science
ThématiqueFish Ecology and Management Studies
Établissements canadiensUniversity of VictoriaUniversité Laval
Organismes subventionnairesGovernment of CanadaCompute CanadaGenome CanadaGenome British ColumbiaUniversité Laval
Mots-clésHatcheryBiologyFish migrationDomesticationCaptivityOncorhynchusThreatened speciesMaladaptationEcologySalmoCaptive breedingSmoltificationFish hatcherySelective breedingNatural selectionZoologyFisheryEvolutionary biologySelection (genetic algorithm)SalmonidaeAquacultureEndangered speciesHabitatFish farmingGeneticsFish <Actinopterygii>

Résumé

récupéré en direct d'OpenAlex

Highlights - First study to highlight parallel epigenetic modifications induced by hatchery rearing as a potential explanatory mechanism for rapid change in fitness Summary A puzzling question in conservation biology is how to maintain overall fitness of individuals bred in captive environment upon release into the wild, especially for rehabilitating declining or threatened species [1,2]. For salmonid species, a heritable change in fitness related traits and gene expression has been reported to occur in a single generation of captivity in hatchery environment [3–5]. Such rapid changes are congruent with models of inadvertent domestication selection which may lead to maladaptation in the natural environment [4]. Arguably, the underlying mechanism by which captivity may induce fitness difference between wild and captive congeners is still poorly understood. Short-term selection on complex phenotypic traits is expected to induce subtle changes in allele frequency over multiple loci [7–9]. Yet, most studies investigating the molecular basis for rapid change in fitness related traits occurring in hatchery have concentrated their effort on finding evidence for selection at the genome level by identifying loci with large effect. Numerous wild stocks of Pacific anadromous salmon and trout (genus Oncorhynchus and Salmo ) have experienced fluctuating abundance over the past century, with a series of sharp declines [6–8]. With the objectives of preserving ecosystem integrity, enhancing declining populations and sustaining fisheries, conservation hatcheries have been flourishing. This is particularly true along the North American Pacific coast where billions of salmonids, all species included, are released each year. Despite substantial improvement of production management, the beneficial ecological role of hatcheries in enhancing and restoring wild stocks is still debated, mainly because of the reduced fitness and maladaptation of hatchery-fish when released in the wild [3,5,9]. Although previous studies showed that domestication selection was involved in such fitness impairment, they also observed that different environmental conditions (e.g. reduced fish density) significantly modulated the physiological acclimation to hatchery environment [4]. Environmental stimuli are especially relevant during early embryonic development, which also correspond to a sensitive methylation reprogramming window in vertebrates [10,11]. It is therefore plausible that differences in rearing environment during early development may result in epigenetic modifications that could in turn impact on fitness. However, the only epigenetic study to date pertaining to captive rearing in salmonids and performed using methylation-sensitive amplified fragments (MSAP) failed to identify significant changes in methylation profile associated with hatchery rearing [12] Here, we used a higher resolution approach to compare the genome-wide pattern of methylation in hatchery-reared juvenile (smolt) Coho Salmon with that of their wild counterparts in two geographically distant rivers in British Columbia, Canada. Using a reduced representation bisulfite sequencing (RRBS) approach covering an average per individual of about 70 million cytosines in CpG context, we identified 100 methylated regions (DMRs) that differed in parallel between hatchery and natural origin salmon in both rivers. The total variance of epigenetic variation among individuals explained by river or origin and rearing environment in a RDA model was 16% (adj.R 2 =0.16), and both variables equally explained about 8% of the variance after controlling for each other. The gene ontology analysis revealed that regions with different methylation levels between hatchery and natural origin salmon showed enrichment for ion homeostasis, synaptic and neuromuscular regulation, immune and stress response, and control of locomotion functions. We further identified 15,044 SNPs that allowed detection of significant differences between either rivers or sexes. However, no effect of rearing environment was observed, confirming that hatchery and natural origin fish of a given river belong to the same panmictic population, as expected based on the hatchery programs applied in these rivers (see Supplementary experimental procedures). Moreover, neither a standard genome-scan approach nor a polygenic statistical framework allowed detection of selective effects within a single generation between hatchery and natural origin salmon. Therefore, this is the first study to demonstrate that parallel epigenetic modifications induced by hatchery rearing during early development may represent a potential explanatory mechanism for rapid change in fitness-related traits previously reported in salmonids.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,281
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,001
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,002
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,022
Tête enseignante GPT0,226
Écart entre enseignants0,204 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations20
Publié2017
Routes d'admission3
Résumé présentoui

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