119 Pedigree and Population-Based Genomic Inbreeding Trends Over Time in Five Commercial Swine Breeding Populations
Notice bibliographique
Résumé
Abstract Controlling inbreeding within a population is critical to maintain additive genetic variance and reduce negative consequences such as inbreeding depression in small, closed herds. Some breeding programs may utilize subjective standard operating procedures (SOPs) such as setting the minimum number of boars, limiting the number of matings per boar, and limiting the relationships among active boars. Software programs such as Matesel can control inbreeding within a population more precisely using evolutionary algorithms by optimizing the mating and selection process to constrain inbreeding at a given target degree or other metric specified (e.g., coancestry). The main problem has been the choice of what relationship matrix to use in constraining inbreeding in these programs. Furthermore, there are many different genomic inbreeding metrics that can be used to quantify inbreeding rates over time. The objective of the current research was to investigate the trends in the pedigree [PED, (A diagonal – 1) * 100] and two population-based genomic inbreeding metrics. One based on expected homozygosity (2pq, Ghom) and one based on drift (squared allele frequency changes, Gdrift). Data included nucleus animals born from 2017 through 2022 from five different genetic lines (lines A-E). Most parents and male selection candidates were genotyped using the commercial 50k SNP panel from GeneSeek. Pedigree was traced back at least 3 generations. A total of 80k animals were sampled from the total number of genotyped animals for computational reasons across line and birth year. Results show that in general, the maternal lines (A and B) showed the least rate of inbreeding over time (0.30 and 0.43% / year for A and B, respectively), while terminal lines were greater, especially line D (0.36 to 0.76% / year). Pedigree inbreeding in 2022 was between 1.48% (line A) to 3.80% (line D) after subtracting the average pedigree inbreeding in 2017. Population-based genomic measures of inbreeding showed a very small difference in line A (0.09%), larger Gdrift than Ghom in line B (1.37%), and larger Ghom than Gdrift in lines C, D, and E (2.87% to 4.38%). In general, the trend for PED and Gdrift was very similar for all lines, while Ghom tended to increase rapidly out of control in the three terminal lines (C-E) in later years. Future research will focus on integrating results from the diagonals of a variety of G matrices on an individual basis (e.g., VanRaden 1 and 2, runs-of-homozygosity, and a linkage-analysis matrix). Results showed the pedigree and genomic drift trends over time were similar, however, the genomic homozygosity trend was much greater in terminal lines.
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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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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) | 0,000 | 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 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 ».