Editorial: Exploring the developmental plasticity and transgenerational effects on the thermal biology of aquatic ectotherms
Notice bibliographique
Résumé
As the projected 1.5 °C warmer world is likely to be realized, scientific studies exploring response strategies of animals to warmer climates are shifting from mechanisms of phenotypic plasticity, to those of adaptation at the genomic level. Physiological adjustments that shift with environmental temperature increases may also persist given the impacts on developmental trajectories plasticity and transgenerational effects such as through nutritional deficits placed on gametes and genomic imprinting. This short special issue includes four model organisms: purple sea urchins (Strongylocentrotus purpuratus), Olympia oysters (Ostrea lurida), green-lipped mussels (Perna canaliculus) and sharks to gauge an understanding of developmental plasticity and transgenerational potential of thermal biology from aquatic invertebrates to elasmobranch fishes.Purple sea urchins in the kelp forests of the California Current System have experienced marine heat waves that overlap with their developmental stages. This scenario provides a model system to study the transgenerational plasticity of thermal tolerance in invertebrates. The study showed that embryos from females experiencing prolonged marine heatwave events increase thermal tolerance relative to those from females not experiencing prolonged marine heatwaves. More thermally tolerant embryos resulted from eggs with higher protein concentrations (Chamorro et al., 2023). This study revealed a potential for transgenerational adaptation to heat waves in sea urchins through maternal effects on the protein content of the eggs.Green-lipped mussels in New Zealand are also experiencing increased frequencies of marine heat waves and extreme weather events. Here, Ericson et al. (2024) show that such events correlate with increased stress-related mortality. They also reveal that the microbiome is an important factor that is associated with green-lipped mussel survival. The family of mussels with the highest survival in the face of thermal stress differed from others in terms of microbiome species-richness, despite gene expression profiles for heat shock proteins and immune responses being similarly up-regulated in all families (Ericson et al. 2024). This study highlights the importance of considering the roles of the microbiome when monitoring the impacts of thermal stress on ectotherms. As highlighted by this special issue, aquatic invertebrate models are at the frontline of the research on developmental plasticity and transgenerational effects on the thermal biology of aquatic ectotherms. While comparatively short generational times present promising and model organisms that facilitate the study of transgenerational effects, elasmobranchs showcase challenges in studying the transgenerational plasticity species with contrasting long life spans, late sexual maturation and low fecundity. These organisms demonstrated that aquatic ectotherms can manifest developmental plasticity, which shapes the phenotype within a generation. Then they illustrate transgenerational carryover effects that impact phenotype. At least in the purple urchin, a predominated component influencing transgenerational effects correlates with egg protein compositions. In addition, microbial diversity adds another layer of complexity to greenlipped mussels. This indicates that symbiotic relationships warrant consideration as drivers of developmental plasticity and transgenerational effects. A perspective paper summarizes the case studies and some future directions for tackling the challenging research area of transgenic aspects of thermal biology on elasmobranchs. While we are distant from predicting whether the new steady state of a phenotypic trait is heritable or is simply a transient plastic response, this special issue hopefully inspires future studies to disentangle the transgenerational genomic changes and the epigenetic effects. Author contributions: YZ, KA, TH all revised the final versions
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,005 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,003 |
| Bibliométrie | 0,003 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,005 | 0,005 |
| Science ouverte | 0,004 | 0,001 |
| Intégrité de la recherche | 0,012 | 0,015 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,021 | 0,012 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».