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dc.contributor.author
Schrauf, Matías Florián  
dc.contributor.author
Martini, Johannes W.R.  
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Simianer, Henner  
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de los Campos, Gustavo  
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Cantet, Rodolfo Juan Carlos  
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Freudenthal, Jan  
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Korte, Arthur  
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Munilla Leguizamon, Sebastian  
dc.date.available
2021-10-05T15:21:51Z  
dc.date.issued
2020-09-01  
dc.identifier.citation
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  
dc.identifier.issn
2160-1836  
dc.identifier.uri
http://hdl.handle.net/11336/142691  
dc.description.abstract
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.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Genetics Society of America  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by/2.5/ar/  
dc.subject
ADDITIVE EFFECTS  
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BREEDING  
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EPISTASIS  
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GENOMIC  
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GENOMICS  
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GENPRED  
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PREDICTION  
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RESOURCES  
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SHARED DATA  
dc.subject.classification
Agronomía, reproducción y protección de plantas  
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Agricultura, Silvicultura y Pesca  
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CIENCIAS AGRÍCOLAS  
dc.title
Phantom epistasis in genomic selection: on the predictive ability of epistatic models  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2021-08-25T19:39:48Z  
dc.journal.volume
10  
dc.journal.number
9  
dc.journal.pagination
3137-3145  
dc.journal.pais
Estados Unidos  
dc.description.fil
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  
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Fil: Martini, Johannes W.R.. Centro Internacional de Mejoramiento de Maíz y Trigo; México  
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Fil: Simianer, Henner. Universität Göttingen; Alemania  
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Fil: de los Campos, Gustavo. Michigan State University; Estados Unidos  
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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  
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Fil: Freudenthal, Jan. Universität Würzburg; Alemania  
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Fil: Korte, Arthur. Universität Würzburg; Alemania  
dc.description.fil
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  
dc.journal.title
G3: Genes, Genomes, Genetics  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.g3journal.org/content/10/9/3137  
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info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1534/g3.120.401300