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Author | dc.contributor.author | Bangera, Rama | |
Author | dc.contributor.author | Correa, Katharina | |
Author | dc.contributor.author | Lhorente, Jean Paul | |
Author | dc.contributor.author | Figueroa, René | |
Author | dc.contributor.author | Yáñez López, José | |
Admission date | dc.date.accessioned | 2019-03-18T11:55:37Z | |
Available date | dc.date.available | 2019-03-18T11:55:37Z | |
Publication date | dc.date.issued | 2017 | |
Cita de ítem | dc.identifier.citation | BMC Genomics, Volumen 18, Issue 1, 2018, | |
Identifier | dc.identifier.issn | 14712164 | |
Identifier | dc.identifier.other | 10.1186/s12864-017-3487-y | |
Identifier | dc.identifier.uri | https://repositorio.uchile.cl/handle/2250/167010 | |
Abstract | dc.description.abstract | © 2017 The Author(s). Background: Salmon Rickettsial Syndrome (SRS) caused by Piscirickettsia salmonis is a major disease affecting the Chilean salmon industry. Genomic selection (GS) is a method wherein genome-wide markers and phenotype information of full-sibs are used to predict genomic EBV (GEBV) of selection candidates and is expected to have increased accuracy and response to selection over traditional pedigree based Best Linear Unbiased Prediction (PBLUP). Widely used GS methods such as genomic BLUP (GBLUP), SNPBLUP, Bayes C and Bayesian Lasso may perform differently with respect to accuracy of GEBV prediction. Our aim was to compare the accuracy, in terms of reliability of genome-enabled prediction, from different GS methods with PBLUP for resistance to SRS in an Atlantic salmon breeding program. Number of days to death (DAYS), binary survival status (STATUS) phenotypes, and 50 K SNP array genotypes were obtained from 2601 smolts challenged with P. salmonis. The reliability of | |
Lenguage | dc.language.iso | en | |
Publisher | dc.publisher | BioMed Central Ltd. | |
Type of license | dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Chile | |
Link to License | dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/cl/ | |
Source | dc.source | BMC Genomics | |
Keywords | dc.subject | Disease resistance | |
Keywords | dc.subject | Genomic selection | |
Keywords | dc.subject | Reliability | |
Keywords | dc.subject | Salmon Rickettsial Syndrome | |
Título | dc.title | Genomic predictions can accelerate selection for resistance against Piscirickettsia salmonis in Atlantic salmon (Salmo salar) | |
Document type | dc.type | Artículo de revista | |
dcterms.accessRights | dcterms.accessRights | Acceso Abierto | |
Cataloguer | uchile.catalogador | SCOPUS | |
Indexation | uchile.index | Artículo de publicación SCOPUS | |
uchile.cosecha | uchile.cosecha | SI | |
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