Genomic predictions can accelerate selection for resistance against Piscirickettsia salmonis in Atlantic salmon (Salmo salar)

© 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...

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Bibliographic Details
Published in:BMC Genomics
Main Authors: Bangera, Rama, Correa, Katharina, Lhorente, Jean Paul, Figueroa, René, Yáñez López, José
Format: Article in Journal/Newspaper
Language:English
Published: BioMed Central Ltd. 2017
Subjects:
Disease resistance
Genomic selection
Reliability
Salmon Rickettsial Syndrome
Atlantic salmon
Salmo salar
Online Access:https://doi.org/10.1186/s12864-017-3487-y
https://repositorio.uchile.cl/handle/2250/167010
Description
Summary:© 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

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