Survival, growth and sexual maturation in Atlantic salmon exposed to infectious pancreatic necrosis: A multi-variate mixture model approach

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Survival, growth and sexual maturation in Atlantic salmon exposed to infectious pancreatic necrosis : A multi-variate mixture model approach. / Lillehammer, Marie; Ødegård, Jørgen; Madsen, Per; Gjerde, Bjarne; Refstie, Terje; Rye, Morten .

I: Genetics Selection Evolution, Bind 45, Nr. 8, 25.03.2013.

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Lillehammer, Marie ; Ødegård, Jørgen ; Madsen, Per ; Gjerde, Bjarne ; Refstie, Terje ; Rye, Morten . / Survival, growth and sexual maturation in Atlantic salmon exposed to infectious pancreatic necrosis : A multi-variate mixture model approach. I: Genetics Selection Evolution. 2013 ; Bind 45, Nr. 8.

Bibtex

@article{cc1bd5d8380e432f8f6c6c5c4b9eed74,
title = "Survival, growth and sexual maturation in Atlantic salmon exposed to infectious pancreatic necrosis: A multi-variate mixture model approach",
abstract = "BackgroundOutbreaks of infectious pancreatic necrosis (IPN) in Atlantic salmon can result in reduced growth rates in a fraction of the surviving fish (runts). Genetic and environmental variation also affects growth rates within different categories of healthy animals and runts, which complicates identification of runts. Mixture models are commonly used to identify the underlying structures in such data, and the aim of this study was to develop Bayesian mixture models for the genetic analysis of health status (runt/healthy) of surviving fish from an IPN outbreak. MethodsFive statistical models were tested on data consisting of 10 972 fish that died and 3959 survivors with recorded growth data. The most complex models (4 and 5) were multivariate normal-binary mixture models including growth, sexual maturity and field survival traits. Growth rate and liability of sexual maturation were treated as two-component normal mixtures, assuming phenotypes originated from two potentially overlapping distributions, (runt/normal). Runt status was an unobserved binary trait. These models were compared to mixture models with fewer traits (Models 2 and 3) and a classical linear animal model for growth (Model 1). ResultsAssuming growth as a mixture trait improved the predictive ability of the statistical model considerably (Model 2 vs. 1). The final models (4 and 5) yielded the following results: estimated (underlying) heritabilities were moderate for growth in healthy fish (0.32 +/- 0.04 and 0.35 +/- 0.05), runt status (0.39 +/- 0.07 and 0.36 +/- 0.08) and sexual maturation (0.33 +/- 0.05), and high for field survival (0.47 +/- 0.03 and 0.48 +/- 0.03). Growth in healthy animals, runt status and survival showed consistent favourable genetic associations. Sexual maturation showed an unfavourable non-significant genetic correlation with runt status, but favourable genetic correlations with other traits. The estimated fraction of healthy fish was 81-85{\%}. The estimated breeding values for runt status and (normal) growth were consistent for the most complex models (4 and 5), but showed imperfect correlations with estimated breeding values from the simpler models. ConclusionsModelling growth in IPN survivors as a mixture trait improved the predictive ability of the model compared with a classical linear model. The results indicated considerable genetic variation in health status among survivors. Mixture modelling may be useful for the genetic analysis of diseases detected mainly through indicator traits.",
author = "Marie Lillehammer and J{\o}rgen {\O}deg{\aa}rd and Per Madsen and Bjarne Gjerde and Terje Refstie and Morten Rye",
year = "2013",
month = "3",
day = "25",
doi = "10.1186/1297-9686-45-8",
language = "English",
volume = "45",
journal = "Genetics Selection Evolution",
issn = "0999-193X",
publisher = "BioMed Central Ltd.",
number = "8",

}

RIS

TY - JOUR

T1 - Survival, growth and sexual maturation in Atlantic salmon exposed to infectious pancreatic necrosis

T2 - A multi-variate mixture model approach

AU - Lillehammer, Marie

AU - Ødegård, Jørgen

AU - Madsen, Per

AU - Gjerde, Bjarne

AU - Refstie, Terje

AU - Rye, Morten

PY - 2013/3/25

Y1 - 2013/3/25

N2 - BackgroundOutbreaks of infectious pancreatic necrosis (IPN) in Atlantic salmon can result in reduced growth rates in a fraction of the surviving fish (runts). Genetic and environmental variation also affects growth rates within different categories of healthy animals and runts, which complicates identification of runts. Mixture models are commonly used to identify the underlying structures in such data, and the aim of this study was to develop Bayesian mixture models for the genetic analysis of health status (runt/healthy) of surviving fish from an IPN outbreak. MethodsFive statistical models were tested on data consisting of 10 972 fish that died and 3959 survivors with recorded growth data. The most complex models (4 and 5) were multivariate normal-binary mixture models including growth, sexual maturity and field survival traits. Growth rate and liability of sexual maturation were treated as two-component normal mixtures, assuming phenotypes originated from two potentially overlapping distributions, (runt/normal). Runt status was an unobserved binary trait. These models were compared to mixture models with fewer traits (Models 2 and 3) and a classical linear animal model for growth (Model 1). ResultsAssuming growth as a mixture trait improved the predictive ability of the statistical model considerably (Model 2 vs. 1). The final models (4 and 5) yielded the following results: estimated (underlying) heritabilities were moderate for growth in healthy fish (0.32 +/- 0.04 and 0.35 +/- 0.05), runt status (0.39 +/- 0.07 and 0.36 +/- 0.08) and sexual maturation (0.33 +/- 0.05), and high for field survival (0.47 +/- 0.03 and 0.48 +/- 0.03). Growth in healthy animals, runt status and survival showed consistent favourable genetic associations. Sexual maturation showed an unfavourable non-significant genetic correlation with runt status, but favourable genetic correlations with other traits. The estimated fraction of healthy fish was 81-85%. The estimated breeding values for runt status and (normal) growth were consistent for the most complex models (4 and 5), but showed imperfect correlations with estimated breeding values from the simpler models. ConclusionsModelling growth in IPN survivors as a mixture trait improved the predictive ability of the model compared with a classical linear model. The results indicated considerable genetic variation in health status among survivors. Mixture modelling may be useful for the genetic analysis of diseases detected mainly through indicator traits.

AB - BackgroundOutbreaks of infectious pancreatic necrosis (IPN) in Atlantic salmon can result in reduced growth rates in a fraction of the surviving fish (runts). Genetic and environmental variation also affects growth rates within different categories of healthy animals and runts, which complicates identification of runts. Mixture models are commonly used to identify the underlying structures in such data, and the aim of this study was to develop Bayesian mixture models for the genetic analysis of health status (runt/healthy) of surviving fish from an IPN outbreak. MethodsFive statistical models were tested on data consisting of 10 972 fish that died and 3959 survivors with recorded growth data. The most complex models (4 and 5) were multivariate normal-binary mixture models including growth, sexual maturity and field survival traits. Growth rate and liability of sexual maturation were treated as two-component normal mixtures, assuming phenotypes originated from two potentially overlapping distributions, (runt/normal). Runt status was an unobserved binary trait. These models were compared to mixture models with fewer traits (Models 2 and 3) and a classical linear animal model for growth (Model 1). ResultsAssuming growth as a mixture trait improved the predictive ability of the statistical model considerably (Model 2 vs. 1). The final models (4 and 5) yielded the following results: estimated (underlying) heritabilities were moderate for growth in healthy fish (0.32 +/- 0.04 and 0.35 +/- 0.05), runt status (0.39 +/- 0.07 and 0.36 +/- 0.08) and sexual maturation (0.33 +/- 0.05), and high for field survival (0.47 +/- 0.03 and 0.48 +/- 0.03). Growth in healthy animals, runt status and survival showed consistent favourable genetic associations. Sexual maturation showed an unfavourable non-significant genetic correlation with runt status, but favourable genetic correlations with other traits. The estimated fraction of healthy fish was 81-85%. The estimated breeding values for runt status and (normal) growth were consistent for the most complex models (4 and 5), but showed imperfect correlations with estimated breeding values from the simpler models. ConclusionsModelling growth in IPN survivors as a mixture trait improved the predictive ability of the model compared with a classical linear model. The results indicated considerable genetic variation in health status among survivors. Mixture modelling may be useful for the genetic analysis of diseases detected mainly through indicator traits.

U2 - 10.1186/1297-9686-45-8

DO - 10.1186/1297-9686-45-8

M3 - Journal article

C2 - 23531148

VL - 45

JO - Genetics Selection Evolution

JF - Genetics Selection Evolution

SN - 0999-193X

IS - 8

ER -