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dc.contributor.authorVillanueva, Beatriz
dc.contributor.authorFernández, Almudena
dc.contributor.authorSaura, María
dc.contributor.authorCaballero Rua, Armando 
dc.contributor.authorFernández, Jesús
dc.contributor.authorMorales González, Elisabeth
dc.contributor.authorToro, Miguel A.
dc.contributor.authorPong Wong, Ricardo
dc.date.accessioned2021-11-25T12:54:47Z
dc.date.available2021-11-25T12:54:47Z
dc.date.issued2021-05-01
dc.identifier.citationGenetics Selection Evolution, 53(1): 42 (2021)spa
dc.identifier.issn12979686
dc.identifier.urihttp://hdl.handle.net/11093/2752
dc.description.abstractBackground 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 (FNEJ), the Li and Horvitz matrix based on excess of homozygosity (FL&H), and the VanRaden (methods 1, FVR1, and 2, FVR2) and Yang (FYAN) genomic relationship matrices. We derived expectations for each inbreeding coefficient, assuming a single locus model, and used these expectations to explain the patterns of the coefficients that were computed from thousands of single nucleotide polymorphism genotypes in a population of Iberian pigs. Results Except for FNEJ, the evaluated measures of inbreeding do not match with the original definitions of inbreeding coefficient of Wright (correlation) or Malécot (probability). When inbreeding coefficients are interpreted as indicators of variability (heterozygosity) that was gained or lost relative to a base population, both FNEJ and FL&H led to sensible results but this was not the case for FVR1, FVR2 and FYAN. When variability has increased relative to the base, FVR1, FVR2 and FYAN can indicate that it decreased. In fact, based on FYAN, variability is not expected to increase. When variability has decreased, FVR1 and FVR2 can indicate that it has increased. Finally, these three coefficients can indicate that more variability than that present in the base population can be lost, which is also unreasonable. The patterns for these coefficients observed in the pig population were very different, following the derived expectations. As a consequence, the rate of inbreeding depression estimated based on these inbreeding coefficients differed not only in magnitude but also in sign. 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.eng
dc.description.sponsorshipMinisterio de Ciencia e Innovación | Ref. CGL2016-75904-C2spa
dc.description.sponsorshipMinisterio de Ciencia e Innovación | Ref. PID2020-114426GB-C22spa
dc.description.sponsorshipEuropean Commission | Ref. H2020, n. 727315spa
dc.description.sponsorshipXunta de Galicia | Ref. ED431C 2020-05spa
dc.description.sponsorshipEuropean Commission | Ref. H2020, SMARTER, n. 772787spa
dc.description.sponsorshipBiotechnology and Biological Sciences Research Council | Ref. BBS / E / D / 30002275spa
dc.language.isoengspa
dc.publisherGenetics Selection Evolutionspa
dc.relationinfo:eu-repo/grantAgreement/ES/MINECO/CGL2016-75904-C2
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-114426GB-C22/es
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleThe value of genomic relationship matrices to estimate levels of inbreedingeng
dc.typearticlespa
dc.rights.accessRightsopenAccessspa
dc.relation.projectIDinfo:eu-repo/grantAgreement/EU/H2020/727315spa
dc.relation.projectIDinfo:eu-repo/grantAgreement/EU/H2020/SMARTER/772787spa
dc.identifier.doi10.1186/s12711-021-00635-0
dc.identifier.editorhttps://gsejournal.biomedcentral.com/articles/10.1186/s12711-021-00635-0spa
dc.publisher.departamentoBioquímica, xenética e inmunoloxíaspa
dc.publisher.grupoinvestigacionXenética de Poboacións e Citoxenéticaspa
dc.subject.unesco2302.04 Genética Bioquímicaspa
dc.subject.unesco2409.90 Citogenética Animalspa
dc.subject.unesco2401.08 Genética Animalspa
dc.date.updated2021-11-25T08:52:33Z
dc.referencesWe are grateful to Jaime Rodrigáñez, Luis Silió and the staff of the CIA ‘Dehesón del Encinar’ (Oropesa, Toledo) for their excellent job in maintaining the Guadyerbas herd for decades. We thank the ‘Centro de Supercomputación de Galicia’ (Cesga) for their computing support and two anonymous referees for helpful comments on the manuscripteng


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