The value of genomic relationship matrices to estimate levels of inbreeding.


Journal

Genetics, selection, evolution : GSE
ISSN: 1297-9686
Titre abrégé: Genet Sel Evol
Pays: France
ID NLM: 9114088

Informations de publication

Date de publication:
01 May 2021
Historique:
received: 17 07 2020
accepted: 19 04 2021
entrez: 2 5 2021
pubmed: 3 5 2021
medline: 4 8 2021
Statut: epublish

Résumé

Genomic relationship matrices are used to obtain genomic inbreeding coefficients. However, there are several methodologies to compute these matrices and there is still an unresolved debate on which one provides the best estimate of inbreeding. In this study, we investigated measures of inbreeding obtained from five genomic matrices, including the Nejati-Javaremi allelic relationship matrix (F Except for F Genomic inbreeding coefficients obtained from the diagonal elements of genomic matrices can lead to inconsistent results in terms of gain and loss of genetic variability and inbreeding depression estimates, and thus to misleading interpretations. Although these matrices have proven to be very efficient in increasing the accuracy of genomic predictions, they do not always provide a useful measure of inbreeding.

Sections du résumé

BACKGROUND BACKGROUND
Genomic relationship matrices are used to obtain genomic inbreeding coefficients. However, there are several methodologies to compute these matrices and there is still an unresolved debate on which one provides the best estimate of inbreeding. In this study, we investigated measures of inbreeding obtained from five genomic matrices, including the Nejati-Javaremi allelic relationship matrix (F
RESULTS RESULTS
Except for F
CONCLUSIONS CONCLUSIONS
Genomic inbreeding coefficients obtained from the diagonal elements of genomic matrices can lead to inconsistent results in terms of gain and loss of genetic variability and inbreeding depression estimates, and thus to misleading interpretations. Although these matrices have proven to be very efficient in increasing the accuracy of genomic predictions, they do not always provide a useful measure of inbreeding.

Identifiants

pubmed: 33933002
doi: 10.1186/s12711-021-00635-0
pii: 10.1186/s12711-021-00635-0
pmc: PMC8088726
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

42

Subventions

Organisme : Ministerio de Ciencia, Innovación y Universidades
ID : CGL2016-75904-C2
Organisme : European Commission Horizon 2020 (H2020) Framework Programme
ID : 727315
Organisme : Xunta de Galicia
ID : ED431C 2020-05
Organisme : Horizon 2020 Framework Programme
ID : 772787
Organisme : Biotechnology and Biological Sciences Research Council
ID : BBS/E/D/30002275
Pays : United Kingdom
Organisme : Ministerio de Ciencia e Innovación
ID : PID2020-114426GB-C22

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Auteurs

Beatriz Villanueva (B)

Departamento de Mejora Genética Animal, INIA, Ctra. de La Coruña, km 7.5, 28040, Madrid, Spain. villanueva.beatriz@inia.es.

Almudena Fernández (A)

Departamento de Mejora Genética Animal, INIA, Ctra. de La Coruña, km 7.5, 28040, Madrid, Spain.

María Saura (M)

Departamento de Mejora Genética Animal, INIA, Ctra. de La Coruña, km 7.5, 28040, Madrid, Spain.

Armando Caballero (A)

Centro de Investigación Mariña, Universidade de Vigo, Departamento de Bioquímica, Genética E Inmunología, Campus de Vigo, 36310, Vigo, Spain.

Jesús Fernández (J)

Departamento de Mejora Genética Animal, INIA, Ctra. de La Coruña, km 7.5, 28040, Madrid, Spain.

Elisabeth Morales-González (E)

Departamento de Mejora Genética Animal, INIA, Ctra. de La Coruña, km 7.5, 28040, Madrid, Spain.

Miguel A Toro (MA)

Departamento de Producción Agraria, ETSI Agrónomos, Universidad Politécnica de Madrid, 28040, Madrid, Spain.

Ricardo Pong-Wong (R)

Genetics and Genomics, The Roslin Institute and the R(D)SVS, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, UK.

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Classifications MeSH