Tools to refine unknown parent group definitions.

ABSTRACT.- Unknown parent groups (UPG) model missing parentships according to breed, year, and pathway of selection. Genetic evaluations need a sensible definition of rules to form UPG to ensure their accurate estimation. With more complex evaluations, systematic rules are needed to form UPG. We propose several methods to ascertain informativity and join consecutive UPG within breed and pathway. First, a pseudocount of records based on descendants with record can be easily computed from a pedigree and a list of animals in records by propagating fractions of one from the flagged animals to ancestors through the pedigree, from youngest to oldest. Then, 2 rules are proposed: the first joins UPG forward in time until records appear, and the second joins consecutive UPG backward in time to achieve a minimum pseudocount. Finally, a simplified model estimates the precision of contrasts of UPG. Computations are feasible even for very large datasets. We illustrate with 2 examples from all-breed US traditional BLUP evaluation for yield and health traits. For yield traits, the number of pseudorecords is very high, and joining UPG occurs mainly in small breeds. Joining or not results in very similar estimated breeding values and genetic trends. For health traits, joining UPG occurs for all breeds, and more intensely for small breeds. Joining or not joining UPG resulted, for some trait-breed combinations, in quite different genetic trends and estimated breeding values. The approximated contrasts across all pairwise UPG show that the joining strategies achieve more precision, in the form of lower SE. © 2025 American Dairy Science Association

Publication Details

Journal
LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)
Published
2025-01-01
Primary Topic
Theoretical and Computational Physics
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article
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article

Tools to refine unknown parent group definitions.

LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)
Theoretical and Computational Physics
article

Tools to refine unknown parent group definitions.

article en

Abstract

ABSTRACT.- Unknown parent groups (UPG) model missing parentships according to breed, year, and pathway of selection. Genetic evaluations need a sensible definition of rules to form UPG to ensure their accurate estimation. With more complex evaluations, systematic rules are needed to form UPG. We propose several methods to ascertain informativity and join consecutive UPG within breed and pathway. First, a pseudocount of records based on descendants with record can be easily computed from a pedigree and a list of animals in records by propagating fractions of one from the flagged animals to ancestors through the pedigree, from youngest to oldest. Then, 2 rules are proposed: the first joins UPG forward in time until records appear, and the second joins consecutive UPG backward in time to achieve a minimum pseudocount. Finally, a simplified model estimates the precision of contrasts of UPG. Computations are feasible even for very large datasets. We illustrate with 2 examples from all-breed US traditional BLUP evaluation for yield and health traits. For yield traits, the number of pseudorecords is very high, and joining UPG occurs mainly in small breeds. Joining or not results in very similar estimated breeding values and genetic trends. For health traits, joining UPG occurs for all breeds, and more intensely for small breeds. Joining or not joining UPG resulted, for some trait-breed combinations, in quite different genetic trends and estimated breeding values. The approximated contrasts across all pairwise UPG show that the joining strategies achieve more precision, in the form of lower SE. © 2025 American Dairy Science Association

LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)
Openalex Percentile: Top 60%
Theoretical and Computational Physics
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Tools to refine unknown parent group definitions. · LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (2025) | TGRS Research Map | TGRS