Phantom epistasis in genomic selection: on the predictive ability of epistatic models

Autores
Schrauf, Matías Florián; Martini, Johannes W.R.; Simianer, Henner; de los Campos, Gustavo; Cantet, Rodolfo Juan Carlos; Freudenthal, Jan; Korte, Arthur; Munilla Leguizamon, Sebastian
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Genomic selection uses whole-genome marker models to predict phenotypes or genetic values for complex traits. Some of these models fit interaction terms between markers, and are therefore called epistatic. The biological interpretation of the corresponding fitted effects is not straightforward and there is the threat of overinterpreting their functional meaning. Here we show that the predictive ability of epistatic models relative to additive models can change with the density of the marker panel. In more detail, we show that for publicly available Arabidopsis and rice datasets, an initial superiority of epistatic models over additive models, which can be observed at a lower marker density, vanishes when the number of markers increases. We relate these observations to earlier results reported in the context of association studies which showed that detecting statistical epistatic effects may not only be related to interactions in the underlying genetic architecture, but also to incomplete linkage disequilibrium at low marker density (“Phantom Epistasis”). Finally, we illustrate in a simulation study that due to phantom epistasis, epistatic models may also predict the genetic value of an underlying purely additive genetic architecture better than additive models, when the marker density is low. Our observations can encourage the use of genomic epistatic models with low density panels, and discourage their biological over-interpretation.
Fil: Schrauf, Matías Florián. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal. Cátedra de Mejoramiento Genético Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Martini, Johannes W.R.. Centro Internacional de Mejoramiento de Maíz y Trigo; México
Fil: Simianer, Henner. Universität Göttingen; Alemania
Fil: de los Campos, Gustavo. Michigan State University; Estados Unidos
Fil: Cantet, Rodolfo Juan Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Unidad Ejecutora de Investigaciones en Producción Animal. Universidad de Buenos Aires. Facultad de Ciencias Veterinarias. Unidad Ejecutora de Investigaciones en Producción Animal; Argentina
Fil: Freudenthal, Jan. Universität Würzburg; Alemania
Fil: Korte, Arthur. Universität Würzburg; Alemania
Fil: Munilla Leguizamon, Sebastian. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal. Cátedra de Mejoramiento Genético Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
ADDITIVE EFFECTS
BREEDING
EPISTASIS
GENOMIC
GENOMICS
GENPRED
PREDICTION
RESOURCES
SHARED DATA
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/142691
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/142691
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Phantom epistasis in genomic selection: on the predictive ability of epistatic modelsSchrauf, Matías FloriánMartini, Johannes W.R.Simianer, Hennerde los Campos, GustavoCantet, Rodolfo Juan CarlosFreudenthal, JanKorte, ArthurMunilla Leguizamon, SebastianADDITIVE EFFECTSBREEDINGEPISTASISGENOMICGENOMICSGENPREDPREDICTIONRESOURCESSHARED DATAhttps://purl.org/becyt/ford/4.1https://purl.org/becyt/ford/4Genomic selection uses whole-genome marker models to predict phenotypes or genetic values for complex traits. Some of these models fit interaction terms between markers, and are therefore called epistatic. The biological interpretation of the corresponding fitted effects is not straightforward and there is the threat of overinterpreting their functional meaning. Here we show that the predictive ability of epistatic models relative to additive models can change with the density of the marker panel. In more detail, we show that for publicly available Arabidopsis and rice datasets, an initial superiority of epistatic models over additive models, which can be observed at a lower marker density, vanishes when the number of markers increases. We relate these observations to earlier results reported in the context of association studies which showed that detecting statistical epistatic effects may not only be related to interactions in the underlying genetic architecture, but also to incomplete linkage disequilibrium at low marker density (“Phantom Epistasis”). Finally, we illustrate in a simulation study that due to phantom epistasis, epistatic models may also predict the genetic value of an underlying purely additive genetic architecture better than additive models, when the marker density is low. Our observations can encourage the use of genomic epistatic models with low density panels, and discourage their biological over-interpretation.Fil: Schrauf, Matías Florián. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal. Cátedra de Mejoramiento Genético Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Martini, Johannes W.R.. Centro Internacional de Mejoramiento de Maíz y Trigo; MéxicoFil: Simianer, Henner. Universität Göttingen; AlemaniaFil: de los Campos, Gustavo. Michigan State University; Estados UnidosFil: Cantet, Rodolfo Juan Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Unidad Ejecutora de Investigaciones en Producción Animal. Universidad de Buenos Aires. Facultad de Ciencias Veterinarias. Unidad Ejecutora de Investigaciones en Producción Animal; ArgentinaFil: Freudenthal, Jan. Universität Würzburg; AlemaniaFil: Korte, Arthur. Universität Würzburg; AlemaniaFil: Munilla Leguizamon, Sebastian. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal. Cátedra de Mejoramiento Genético Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaGenetics Society of America2020-09-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/142691Schrauf, Matías Florián; Martini, Johannes W.R.; Simianer, Henner; de los Campos, Gustavo; Cantet, Rodolfo Juan Carlos; et al.; Phantom epistasis in genomic selection: on the predictive ability of epistatic models; Genetics Society of America; G3: Genes, Genomes, Genetics; 10; 9; 1-9-2020; 3137-31452160-1836CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.g3journal.org/content/10/9/3137info:eu-repo/semantics/altIdentifier/doi/10.1534/g3.120.401300info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T12:03:34Zoai:ri.conicet.gov.ar:11336/142691instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-22 12:03:35.169CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Phantom epistasis in genomic selection: on the predictive ability of epistatic models
title Phantom epistasis in genomic selection: on the predictive ability of epistatic models
spellingShingle Phantom epistasis in genomic selection: on the predictive ability of epistatic models
Schrauf, Matías Florián
ADDITIVE EFFECTS
BREEDING
EPISTASIS
GENOMIC
GENOMICS
GENPRED
PREDICTION
RESOURCES
SHARED DATA
title_short Phantom epistasis in genomic selection: on the predictive ability of epistatic models
title_full Phantom epistasis in genomic selection: on the predictive ability of epistatic models
title_fullStr Phantom epistasis in genomic selection: on the predictive ability of epistatic models
title_full_unstemmed Phantom epistasis in genomic selection: on the predictive ability of epistatic models
title_sort Phantom epistasis in genomic selection: on the predictive ability of epistatic models
dc.creator.none.fl_str_mv Schrauf, Matías Florián
Martini, Johannes W.R.
Simianer, Henner
de los Campos, Gustavo
Cantet, Rodolfo Juan Carlos
Freudenthal, Jan
Korte, Arthur
Munilla Leguizamon, Sebastian
author Schrauf, Matías Florián
author_facet Schrauf, Matías Florián
Martini, Johannes W.R.
Simianer, Henner
de los Campos, Gustavo
Cantet, Rodolfo Juan Carlos
Freudenthal, Jan
Korte, Arthur
Munilla Leguizamon, Sebastian
author_role author
author2 Martini, Johannes W.R.
Simianer, Henner
de los Campos, Gustavo
Cantet, Rodolfo Juan Carlos
Freudenthal, Jan
Korte, Arthur
Munilla Leguizamon, Sebastian
author2_role author
author
author
author
author
author
author
dc.subject.none.fl_str_mv ADDITIVE EFFECTS
BREEDING
EPISTASIS
GENOMIC
GENOMICS
GENPRED
PREDICTION
RESOURCES
SHARED DATA
topic ADDITIVE EFFECTS
BREEDING
EPISTASIS
GENOMIC
GENOMICS
GENPRED
PREDICTION
RESOURCES
SHARED DATA
purl_subject.fl_str_mv https://purl.org/becyt/ford/4.1
https://purl.org/becyt/ford/4
dc.description.none.fl_txt_mv Genomic selection uses whole-genome marker models to predict phenotypes or genetic values for complex traits. Some of these models fit interaction terms between markers, and are therefore called epistatic. The biological interpretation of the corresponding fitted effects is not straightforward and there is the threat of overinterpreting their functional meaning. Here we show that the predictive ability of epistatic models relative to additive models can change with the density of the marker panel. In more detail, we show that for publicly available Arabidopsis and rice datasets, an initial superiority of epistatic models over additive models, which can be observed at a lower marker density, vanishes when the number of markers increases. We relate these observations to earlier results reported in the context of association studies which showed that detecting statistical epistatic effects may not only be related to interactions in the underlying genetic architecture, but also to incomplete linkage disequilibrium at low marker density (“Phantom Epistasis”). Finally, we illustrate in a simulation study that due to phantom epistasis, epistatic models may also predict the genetic value of an underlying purely additive genetic architecture better than additive models, when the marker density is low. Our observations can encourage the use of genomic epistatic models with low density panels, and discourage their biological over-interpretation.
Fil: Schrauf, Matías Florián. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal. Cátedra de Mejoramiento Genético Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Martini, Johannes W.R.. Centro Internacional de Mejoramiento de Maíz y Trigo; México
Fil: Simianer, Henner. Universität Göttingen; Alemania
Fil: de los Campos, Gustavo. Michigan State University; Estados Unidos
Fil: Cantet, Rodolfo Juan Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Unidad Ejecutora de Investigaciones en Producción Animal. Universidad de Buenos Aires. Facultad de Ciencias Veterinarias. Unidad Ejecutora de Investigaciones en Producción Animal; Argentina
Fil: Freudenthal, Jan. Universität Würzburg; Alemania
Fil: Korte, Arthur. Universität Würzburg; Alemania
Fil: Munilla Leguizamon, Sebastian. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal. Cátedra de Mejoramiento Genético Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description Genomic selection uses whole-genome marker models to predict phenotypes or genetic values for complex traits. Some of these models fit interaction terms between markers, and are therefore called epistatic. The biological interpretation of the corresponding fitted effects is not straightforward and there is the threat of overinterpreting their functional meaning. Here we show that the predictive ability of epistatic models relative to additive models can change with the density of the marker panel. In more detail, we show that for publicly available Arabidopsis and rice datasets, an initial superiority of epistatic models over additive models, which can be observed at a lower marker density, vanishes when the number of markers increases. We relate these observations to earlier results reported in the context of association studies which showed that detecting statistical epistatic effects may not only be related to interactions in the underlying genetic architecture, but also to incomplete linkage disequilibrium at low marker density (“Phantom Epistasis”). Finally, we illustrate in a simulation study that due to phantom epistasis, epistatic models may also predict the genetic value of an underlying purely additive genetic architecture better than additive models, when the marker density is low. Our observations can encourage the use of genomic epistatic models with low density panels, and discourage their biological over-interpretation.
publishDate 2020
dc.date.none.fl_str_mv 2020-09-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/142691
Schrauf, Matías Florián; Martini, Johannes W.R.; Simianer, Henner; de los Campos, Gustavo; Cantet, Rodolfo Juan Carlos; et al.; Phantom epistasis in genomic selection: on the predictive ability of epistatic models; Genetics Society of America; G3: Genes, Genomes, Genetics; 10; 9; 1-9-2020; 3137-3145
2160-1836
CONICET Digital
CONICET
url http://hdl.handle.net/11336/142691
identifier_str_mv Schrauf, Matías Florián; Martini, Johannes W.R.; Simianer, Henner; de los Campos, Gustavo; Cantet, Rodolfo Juan Carlos; et al.; Phantom epistasis in genomic selection: on the predictive ability of epistatic models; Genetics Society of America; G3: Genes, Genomes, Genetics; 10; 9; 1-9-2020; 3137-3145
2160-1836
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.g3journal.org/content/10/9/3137
info:eu-repo/semantics/altIdentifier/doi/10.1534/g3.120.401300
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Genetics Society of America
publisher.none.fl_str_mv Genetics Society of America
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 12.982451

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