MétaCan
Menu
Retour à la cohorte
Enregistrement W2109729255 · doi:10.1186/s40575-015-0026-5

The effect of genetic bottlenecks and inbreeding on the incidence of two major autoimmune diseases in standard poodles, sebaceous adenitis and Addison’s disease

2015· article· en· W2109729255 sur OpenAlexaboutno aff
Niels C. Pedersen, Lynn Brucker, Natalie Green Tessier, Hongwei Liu, M. C. T. Penedo, Shayne S. Hughes, Anita M. Oberbauer, B. N. Sacks

Notice bibliographique

RevueCanine Genetics and Epidemiology · 2015
Typearticle
Langueen
DomaineMedicine
ThématiqueDermatology and Skin Diseases
Établissements canadiensnon disponible
Organismes subventionnairesUniversity of California, Davis
Mots-clésInbreedingBiologyGeneticsPopulationGenetic diversityGenome-wide association studyHaplotypeGenetic associationAlleleBreedSingle-nucleotide polymorphismGenotypeGeneDemography

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Sebaceous adenitis (SA) and Addison's disease (AD) increased rapidly in incidence among Standard Poodles after the mid-twentieth century. Previous attempts to identify specific genetic causes using genome wide association studies and interrogation of the dog leukocyte antigen (DLA) region have been non-productive. However, such studies led us to hypothesize that positive selection for desired phenotypic traits that arose in the mid-twentieth century led to intense inbreeding and the inadvertent amplification of AD and SA associated traits. RESULTS: This hypothesis was tested with genetic studies of 761 Standard, Miniature, and Miniature/Standard Poodle crosses from the USA, Canada and Europe, coupled with extensive pedigree analysis of thousands more dogs. Genome-wide diversity across the world-wide population was measured using a panel of 33 short tandem repeat (STR) loci. Allele frequency data were also used to determine the internal relatedness of individual dogs within the population as a whole. Assays based on linkage between STR genomic loci and DLA genes were used to identify class I and II haplotypes and disease associations. Genetic diversity statistics based on genomic STR markers indicated that Standard Poodles from North America and Europe were closely related and reasonably diverse across the breed. However, genetic diversity statistics, internal relatedness, principal coordinate analysis, and DLA haplotype frequencies showed a marked imbalance with 30 % of the diversity in 70 % of the dogs. Standard Poodles with SA and AD were strongly linked to this inbred population, with dogs suffering with SA being the most inbred. No single strong association was found between STR defined DLA class I or II haplotypes and SA or AD in the breed as a whole, although certain haplotypes present in a minority of the population appeared to confer moderate degrees of risk or protection against either or both diseases. Dogs possessing minor DLA class I haplotypes were half as likely to develop SA or AD as dogs with common haplotypes. Miniature/Standard Poodle crosses being used for outcrossing were more genetically diverse than Standard Poodles and genetically distinguishable across the genome and in the DLA class I and II region. CONCLUSIONS: Ancestral genetic polymorphisms responsible for SA and AD entered Standard Poodles through separate lineages, AD earlier and SA later, and were increasingly fixed by a period of close linebreeding that was related to popular bloodlines from the mid-twentieth century. This event has become known as the midcentury bottleneck or MCB. Sustained positive selection resulted in a marked imbalance in genetic diversity across the genome and in the DLA class I and II region. Both SA and AD were concentrated among the most inbred dogs, with genetic outliers being relatively disease free. No specific genetic markers other than those reflecting the degree of inbreeding were consistently associated with either disease. Standard Poodles as a whole remain genetically diverse, but steps should be taken to rebalance diversity using genetic outliers and if necessary, outcrosses to phenotypically similar but genetically distinct breeds.

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)0,005
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
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 enseignants0,098
Score d'incertitude au seuil0,551

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,005
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
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 Opus0,023
Tête enseignante GPT0,304
Écart entre enseignants0,281 · 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.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
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

Citations31
Publié2015
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueCanine Genetics and EpidemiologyMême sujetDermatology and Skin DiseasesTravaux en français237 207