The genetic basis of phenotypic differentiation in Python regius and Gasterosteus aculeatus
Notice bibliographique
Résumé
"Knowledge of the underlying genetic mechanisms responsible for phenotypic evolution is central for understanding the process of adaptation. In my dissertation I use two complementary study systems to generate insight into distinct parts of this process. I first use captive ball pythons (Python regius) from the pet trade to identify causal links between genetic variation and phenotypic diversity. Next, to understand real-world fitness consequences of genetic variation, I use natural populations of threespine stickleback (Gasterosteus aculeatus) experiencing rapid environmental change. The first section of my research takes advantage of artificial selection on colour and patterning imposed in captive breeding programs to understand genotype-phenotype connections. Most pigmentation studies lack the functional validation needed to make a causal link between genotype and phenotype. Those that do are usually based on a few model species, like the mouse and zebrafish. This raises the question of whether the knowledge gained from these classic model species is generalizable across vertebrates. Furthermore, by far the most intensely studied colour trait is melanin pigmentation, with relatively little known of the genetics of pteridine pigmentation and iridophore structural colouration in non-mammal vertebrates, particularly reptiles. Captive ball pythons display an extraordinary degree of colour variation, making them an excellent model species for the study of the genetics of phenotypic diversification. I use whole-genome sequencing, population genetics, gene-editing, and electron microscopy methods to uncover the genetic basis of a recessive colour phenotype characterized by blotches of white skin. This research led to the discovery of a transcription factor not previously linked to reptile colouration or white spotting in general. Functional validation confirmed the role of this transcription factor in reptile pigmentation and showed it is required for iridophore development in a lizard model. A genomic analysis of additional Mendelian colour morphs identified genes not only in the melanin pathway but also pteridine pigmentation. I next used threespine stickleback fish to study the effects of selection acting on genetic variation within natural populations. Stickleback are a classic system in evolutionary genetics for showing evidence of natural selection through parallel evolution of freshwater-adapted ecomorphs from marine ancestors. However, studies on parallel adaptation in stickleback tend to be restricted in time and space. Most have been focused on populations in which the ecological shift (e.g., colonization of freshwater habitats by marine populations), and thus natural selection, occurred thousands of years prior, and they have been confined to a few geographic regions where certain derived phenotypes are repeatedly observed. This leaves open questions of how quickly genomic responses to selection can be detected – months, years, thousands of years - and what alternative evolutionary pathways to freshwater adaptation have been taken in populations outside of the extensively studied locations. My research shows that parallel genomic changes in estuary stickleback can be detected within a single year near to genes linked to osmoregulation, largely mirroring the longer-term patterns observed in post-glacial populations. In addition, lake populations of stickleback from eastern Canada show different genotypic targets of selection to those that have been repeatedly identified in the more well-studied regions on the Pacific coast of North America, suggesting alternative pathways can be used for adaptation. This is likely due to differences in standing genetic variation among populations from different geographic regions as a result of range expansion. Collectively, this research is helping expand our knowledge of the functional connections between genotype, phenotype, and fitness, and the ways in which they interact to govern the trajectory of evolutionary change."@eng
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
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 ».