Population Genomics and Quantitative Genetics of Polar Bears (Ursus maritimus)
Notice bibliographique
Résumé
Polar bears (Ursus maritimus) were among the first large mammals to be assessed for genetic variation in the wild, and they remain a common subject of genetics studies. Although recent advances in genotyping technology have allowed for more accurate determination of population structure and the detection of adaptive variation, most modern research has focused on historical divergence between polar bears and brown bears—a topic with little relevance to current management. The goal of this dissertation is to develop and use large datasets to better describe contemporary genetic variation in polar bears. To this end, I first describe a reanalysis of global polar bear population structure using nuclear microsatellites and mitochondrial DNA. This reanalysis was necessitated by the publication of a study suffering from flaws in design and analysis, most notably non-convergence of BAYESASS, a program used to estimate migration rates. In this reanalysis, I have rectified these errors, and—in contrast to the original study—I show that there is no evidence of strong directional movement in response to recent climate-change-induced loss of sea ice. Second, I describe the development of a custom 9K Illumina Infinium BeadChip for polar bears from restriction-site associated DNA (RAD) and transcriptome sequencing. I show the utility of this chip for sex determination of samples from harvested individuals, and that it gives realistic estimates of population structure and linkage disequilibrium (LD) decay. Third, I perform a more comprehensive Canada-wide population genetic analysis using genotypes from this BeadChip, which provides higher resolution than microsatellites. I confirm the presence of four moderately differentiated genetic clusters of polar bears across the Canadian Arctic, including the Beaufort Sea, the Canadian Arctic Archipelago, Norwegian Bay, and the Hudson Bay Complex. I also confirm the presence of east–west substructure within the Canadian Arctic Archipelago and north–south substructure within the Hudson Bay Complex. Evidence for adaptive differentiation between these clusters is limited. For the two remaining data chapters, I narrow my focus to the Western Hudson Bay management unit, where Environment and Climate Change Canada researchers have conducted mark–recapture studies and collected phenotypic data since 1966. First, I describe the construction of a 4449-individual multigenerational pedigree for Western Hudson Bay bears—among the most extensive pedigrees for any large mammal in the world. I show that inbreeding is rare in this subpopulation, and I document the first known pair of identical twin bears and six new cases of cub adoption. These results are discussed in the context of inclusive fitness theory. Finally, I use this pedigree to estimate the heritability of four routinely measured adult traits: head length, zygomatic breadth, body length, and axillary girth (a measure that is partially dependent on fatness). I then use the BeadChip to perform association studies of these traits. I find moderate heritability (h2 = 0.34–0.48) for strictly skeletal traits and lower heritability (h2 = 0.17) for axillary girth, and I show that variability in these traits is not convincingly affected by any genes of large effect in LD with markers on the BeadChip. Implications for future adaptation are discussed. Collectively, this dissertation represents the most comprehensive assessment of contemporary polar bear genetic variation that has ever been conducted, not only within Western Hudson Bay, but also at the Canadian and circumpolar levels.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| 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 | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 tête enseignante, 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 ».