Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 425839
Title Genetic analysis of tolerance to infections using random regressions: a simulation study
Author(s) Kause, A.
Source Genetics Research 93 (2011)4. - ISSN 0016-6723 - p. 291 - 302.
DOI http://dx.doi.org/10.1017/S0016672311000176
Department(s) Animal Breeding and Genetics
WIAS
Publication type Refereed Article in a scientific journal
Publication year 2011
Keyword(s) environment interaction - rainbow-trout - oncorhynchus-mykiss - natural enemies - reaction norms - growth-rates - resistance - selection - genotype - parameters
Abstract Tolerance to infections is the ability of a host to limit the impact of a given pathogen burden on host performance. This simulation study demonstrated the merit of using random regressions to estimate unbiased genetic variances for tolerance slope and its genetic correlations with other traits, which could not be obtained using the previously implemented statistical methods. Genetic variance in tolerance was estimated as genetic variance in regression slopes of host performance along an increasing pathogen burden level. Random regressions combined with covariance functions allowed genetic variance for host performance to be estimated at any point along the pathogen burden trajectory, providing a novel means to analyse infection-induced changes in genetic variation of host performance. Yet, the results implied that decreasing family size as well as a non-zero environmental or genetic correlation between initial host performance before infection and pathogen burden led to biased estimates for tolerance genetic variance. In both cases, genetic correlation between tolerance slope and host performance in a pathogen-free environment became artificially negative, implying a genetic trade-off when it did not exist. Moreover, recording a normally distributed pathogen burden as a threshold trait is not a realistic way of obtaining unbiased estimates for tolerance genetic variance. The results show that random regressions are suitable for the genetic analysis of tolerance, given suitable data structure collected either under field or experimental conditions.
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