Use of High-density SNP analyses to develop a long-term strategy for conventional populations to prevent loss of diversity - review
Notice bibliographique
Résumé
Article Details: Received: 2020-09-10 | Accepted: 2020-10-30 | Available online: 2020-12-31 https://doi.org/10.15414/afz.2020.23.04.236-240 The aim was to review obtained results related to molecular-genetic analyses by high-density SNP chips and mtDNA in farm and wild populations within the project APVV-17-0060 Genomic Indicators of extranuclear DNA as a source of Diversity for Animal Breeding. Continuous human activity and subsequent socioeconomic and climatic changes of the environment significantly affect the genetic diversity of livestock on both intra- and inter-population levels. Concerning the conservation of local livestock populations and thus animal genetic resources (AnGR) for future generations is, therefore, necessary to monitor and look for new âmore preciseâ tools to measure the amount of genetic diversity. The expected result will be the identification of SNP markers and spot mutations with a significant effect on the process of development resp. variability of traits. In the case of the dog, identification of regions related to fitness, health, and trainability will be the primary objective. Keywords: Genetic diversity, economically important breeds, Animal genetic resources, Slovakia References CURIK, I., FERENÄAKOVIÄ, M. and SÃLKNER, J. (2014). Inbreeding and runs of homozygosity: a possible solution to an old problem. Livestock Science, 166, 26â34. ENGELSMA, K.A., VEERKAMP, R.F., CALUS, M.P., BIJMA, P. and WINDIG, J.J. (2012). Pedigree and marker-based methods in the estimation of genetic diversity in small groups of Holstein cattle. Journal of Animal Breeding and Genetics, 129, 195â205. FERENÄAKOVIÄ, M., BANADINOVIÄ, M., MERCVAJLER, M., KHAYATZADEH, N., MÃSZÃROS, G., CUBRIC-CURIK, V., CURIK, I. and SÃLKNER, J. 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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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,003 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».