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Enregistrement W6889132079 · doi:10.25394/pgs.22696648

GENETIC MARKERS IN DOGS INFLUENCING CRANIAL CRUCIATE LIGAMENT RUPTURE, ASSOCIATED WITH HYPOMYELINATING POLYNEUROPATHY, AND INDICATING WELFARE

2023· dissertation· en· W6889132079 sur OpenAlexaboutno aff

Notice bibliographique

RevuePurdue · 2023
Typedissertation
Langueen
DomaineVeterinary
ThématiqueVeterinary Orthopedics and Neurology
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésHeritabilityCruciate ligamentSNPGenotypeSingle-nucleotide polymorphismTraitAlleleQuantitative trait locus

Résumé

récupéré en direct d'OpenAlex

Comprehensive mastery of modern genetics involves a myriad of data processing and analytic techniques; these approaches vary because some genetic conditions are the result of single gene mutations that alter protein function, while other more complex diseases and traits are influenced by many genes. This dissertation will undertake investigation of the heritability and genetic risk of cranial cruciate ligament rupture in Labrador Retrievers, a congenital hypomyelinating polyneuropathy in four Golden Retrievers, and the potential usage of telomere length as a biomarker of welfare in dogs housed in commercial breeding facilities. In the first disease studied, 333 Labrador Retrievers with known torn or healthy cranial cruciate ligament(s) were genotyped via SNP array. Heritability of this polygenic trait was calculated using a variety of programs and including different fixed effects. Overall, heritability was high, ranging from 0.550 to 0.893, with sex and sterilization at a young age (≤12 months) strongly influencing risk of cranial cruciate ligament rupture. Neither genome-wide association analyses using this novel dataset of 333 Labrador Retrievers, nor additional analyses combining this data with publicly-available data, identified any significantly associated SNPs. However, the most associated SNPs were located near biologically relevant genes, such as <em>COL1A2</em> (a collagen gene) and <em>ITGA11</em> (a protein that binds to collagen), as well as genes encoding sex hormone receptors, such as <em>FSHR </em>and <em>LHCCGR</em>. Splitting the data in an attempt to predict phenotypes based on genotype was unsuccessful. Future work focused on parsing out genetic influencers of cranial cruciate ligament rupture risk should continue to collect sex, sterilization status, and age at sterilization data, and larger collaborations and use of publicly-available data will be required to increase the data robustness. For the second study, DNA from four unrelated Golden Retrievers diagnosed with congenital hypomyelinating polyneuropathy via neurological examination, electrodiagnostic evaluation, and peripheral nerve pathology were explored for genetic causes. Whole-genome sequencing was performed on all four dogs to identify potential causative variants. When compared to WGS from &gt;1,000 other dogs who were presumably unaffected by this rare disease, likely causative variants were identified in all four dogs. Two cases shared a homozygous <em>MTMR2 </em>splice donor site variant, with a stop codon introduced within six codons following the inclusion of the intron. One case had a heterozygous <em>MPZ</em> missense mutation leading to an isoleucine to threonine substitution. The last case had a homozygous <em>SH3TC2</em> nonsense variant predicted to truncate approximately one-half of the protein. Haplotype analyses using 524 Golden Retrievers indicated that these variants emerged recently. Each of these variants occurred in genes that are associated with the human Charcot-Marie-Tooth group of heterogeneous peripheral nervous system diseases. Testing a population of unrelated Golden Retrievers (n &gt; 200) did not identify any other dogs with these variants, though breeders should be cautious to avoid propagating these alleles. Finally, the last study within this dissertation investigates the relationship between telomere length and metrics such as age, breed, environment, average breed lifespan, parity, and response to a mild social stressor in a population of dogs housed at commercial breeding facilities. FIDO scores (behavioral phenotypes) were collected for all dogs as a measurement of response to a social stressor. This study is not yet complete; many more dogs remain to be recruited in the near future. Telomere lengths were measured using qPCR and compared to a single-copy gene, <em>36B4</em>, for 309 dogs representing 37 breeds or breed crosses. Age was not significantly associated with telomere length after making appropriate corrections (p-value = 0.077). Breed and facility were significantly associated with telomere length after corrections (p-value = 0.010 and &lt;2.2E-16, respectively). Neither parity nor average breed lifespan were associated with telomere length, however, response to a mild social stressor was, with dogs who responded positively having significantly longer telomeres than dogs who responded negatively across all analyses. This preliminary data indicates that, within this population, breed, environment, and response to stress have strong influences on telomere length, while parity and average breed lifespan did not. As this work continues, increased sample sizes will lead to increased power for detecting associations. Future work should examine these identified relationships in other populations of dogs. Taken together, these studies encompass phenotypes of various complexity, and each study encompassed different methodologies utilized in modern canine genetics. The overall goal for this work was to improve canine health, with the potential for translational implications to human health. The identification of genetic markers associated with or causative of disease, or indicative of health and welfare traits, is necessary for reducing the prevalence of disease and increasing the knowledge of welfare metrics in canines, respectively.

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)0,001
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 enseignants0,436
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
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 Opus0,021
Tête enseignante GPT0,279
Écart entre enseignants0,258 · 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

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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