Beyond genomic selection: the animal model strikes back (one generation)!

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Genome inheritance is by segments of DNA rather than by independent loci. We introduce the ancestral regression (AR) as a recursive system of simultaneous equations, with grandparental path coefficients as novel parameters. The information given by the pedigree in the AR is complementary with that p...

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Detalles Bibliográficos
Autores principales: Cantet, R.J.C., García Baccino, C. A., Rogberg Muñoz, Andrés, Forneris, N. S., Munilla, S.
Formato: Articulo
Lenguaje:Inglés
Publicado: 2017
Materias:
Ciencias Veterinarias
breeding value
causal inference
Gaussian Markov density
genomic data
segmental inheritance
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/87597
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-87597
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Veterinarias
breeding value
causal inference
Gaussian Markov density
genomic data
segmental inheritance
spellingShingle Ciencias Veterinarias
breeding value
causal inference
Gaussian Markov density
genomic data
segmental inheritance
Cantet, R.J.C.
García Baccino, C. A.
Rogberg Muñoz, Andrés
Forneris, N. S.
Munilla, S.
Beyond genomic selection: the animal model strikes back (one generation)!
topic_facet Ciencias Veterinarias
breeding value
causal inference
Gaussian Markov density
genomic data
segmental inheritance
description Genome inheritance is by segments of DNA rather than by independent loci. We introduce the ancestral regression (AR) as a recursive system of simultaneous equations, with grandparental path coefficients as novel parameters. The information given by the pedigree in the AR is complementary with that provided by a dense set of genomic markers, such that the resulting linear function of grandparental BV is uncorrelated to the average of parental BV in the absence of inbreeding. AR is then connected to segmental inheritance by a causal multivariate Gaussian density for BV. The resulting covariance structure (Σ) is Markovian, meaning that conditional on the BV of parents and grandparents, the BV of the animal is independent of everything else. Thus, an algorithm is presented to invert the resulting covariance structure, with a computing effort that is linear in the number of animals as in the case of the inverse additive relationship matrix.
format Articulo
Articulo
author Cantet, R.J.C.
García Baccino, C. A.
Rogberg Muñoz, Andrés
Forneris, N. S.
Munilla, S.
author_facet Cantet, R.J.C.
García Baccino, C. A.
Rogberg Muñoz, Andrés
Forneris, N. S.
Munilla, S.
author_sort Cantet, R.J.C.
title Beyond genomic selection: the animal model strikes back (one generation)!
title_short Beyond genomic selection: the animal model strikes back (one generation)!
title_full Beyond genomic selection: the animal model strikes back (one generation)!
title_fullStr Beyond genomic selection: the animal model strikes back (one generation)!
title_full_unstemmed Beyond genomic selection: the animal model strikes back (one generation)!
title_sort beyond genomic selection: the animal model strikes back (one generation)!
publishDate 2017
url http://sedici.unlp.edu.ar/handle/10915/87597
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AT rogbergmunozandres beyondgenomicselectiontheanimalmodelstrikesbackonegeneration
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bdutipo_str Repositorios
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