Results of four generations of a canalising selection for rabbit birth weight

Garreau, Hervé; Bolet, Gérard; Larzul, Catherine; Robert-Granié, Christèle; Saleil, Georges; SanCristobal, Magali; Bodin, Loýs

doi:10.1016/j.livsci.2008.02.009

Cited by 66 publications

(87 citation statements)

References 22 publications

(27 reference statements)

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“…No response to divergent selection in pigs on EBV for V E in pH was observed by Larzul et al (2006), but EBVs were based on only four progeny and had low accuracy. In experiments with rabbits, divergent selection was practised for eight generations on within-litter variability in birth weight (Garreau et al, 2008 ;Bodin et al, 2010) and for high or low variability in litter size for three generations in another population (Argente et al, 2010). Although a substantial response was obtained in the first generation in both experiments, only after generation 5 was further response achieved in the experiment of Bodin et al (2010) and little further response was obtained by Argente et al (2010).…”

Section: (Iii) Results From Selection Experimentsmentioning

confidence: 99%

Genetic analysis of environmental variation

2010

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SummaryEnvironmental variation (V E ) in a quantitative trait -variation in phenotype that cannot be explained by genetic variation or identifiable genetic differences -can be regarded as being under some degree of genetic control. Such variation may be either between repeated expressions of the same trait within individuals (e.g. for bilateral traits), in the phenotype of different individuals, where variation within families may differ, or in both components. We consider alternative models for defining the distribution of phenotypes to include a component due to heterogeneity of V E . We review evidence for the presence of genetic variation in V E and estimates of its magnitude. Typically the heritability of V E is under 10 %, but its genetic coefficient of variation is typically 20 % or more. We consider experimental designs appropriate for estimating genetic variance in V E and review alternative methods of estimation. We consider the effects of stabilizing and directional selection on V E and review both the forces that might be maintaining levels of V E and heritability found in populations. We also evaluate the opportunities for reducing V E in breeding programmes. Although empirical and theoretical studies have increased our understanding of genetic control of environmental variance, many issues remain unresolved.

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Section: (Iii) Results From Selection Experimentsmentioning

confidence: 99%

Genetic analysis of environmental variation

2010

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“…Sensitivity to the environment may also contribute to the environmental variance of a trait, which has been shown to be under genetic control (SanCristobal-Gaudy et al, 2001;Sorensen and Waagepetersen, 2003;Ros et al, 2004;Mulder et al, 2007 and2008;Mulder et al, 2009). The reduction of trait variance by genetic selection is also known as canalizing selection or canalization (SanCristobal-Gaudy et al, 1998;Bolet et al, 2007;Garreau et al, 2008;Bodin et al, 2010).…”

Section: Genetic Strategies Towards Robust Animalsmentioning

confidence: 99%

Breeding for robustness: the role of cortisol

Mormède

Foury

Terenina

et al. 2011

Animal

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Robustness in farm animals was defined by Knap as 'the ability to combine a high production potential with resilience to stressors, allowing for unproblematic expression of a high production potential in a wide variety of environmental conditions'. The importance of robustness-related traits in breeding objectives is progressively increasing towards the production of animals with a high production level in a wide range of climatic conditions and production systems, together with a high level of animal welfare. Current strategies to increase robustness include selection for 'functional traits', such as skeletal and cardiovascular integrity, disease resistance and mortality in various stages. It is also possible to use global evaluation of sensitivity to the environment (e.g. reaction norm analysis or canalization), but these techniques are difficult to implement in practice. The hypothalamic-pituitaryadrenocortical (HPA) axis is the most important stress-responsive neuroendocrine system. Cortisol (or corticosterone) released by the adrenal cortices exerts a large range of effects on metabolism, the immune system, inflammatory processes and brain function, for example. Large individual variations have been described in the HPA axis activity with important physiopathological consequences. In terms of animal production, higher cortisol levels have negative effects on growth rate and feed efficiency and increase the fat/lean ratio of carcasses. On the contrary, cortisol has positive effects on traits related to robustness and adaptation. For instance, newborn survival was shown to be directly related to plasma cortisol levels at birth, resistance to bacteria and parasites are increased in animals selected for a higher HPA axis response to stress, and tolerance to heat stress is better in those animals that are able to mount a strong stress response. Intense selection for lean tissue growth during the last decades has concomitantly reduced cortisol production, which may be responsible for the negative effects of selection on piglet survival. One strategy to improve robustness is to select animals with higher HPA axis activity. Several sources of genetic polymorphism have been described in the HPA axis. Hormone production by the adrenal cortices under stimulation by adrenocorticotropin hormone is a major source of individual differences. Several candidate genes have been identified by genomic studies and are currently under investigation. Bioavailability of hormones as well as receptor and post-receptor mechanisms are also subject to individual variation. Integration of these different sources of genetic variability will allow the development of a model for marker-assisted selection to improve animal robustness without negative side effects on production traits.

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“…This indicates that V E could be increased or decreased by 30% if changed by one genetic standard deviation. These analyses were mainly based on genetic analysis of pedigreed livestock populations; but with 300 isofemale lines of Drosophila melanogaster, thereby avoiding possible confounding by within-line genetic heterogeneity, Mackay and Lyman (2005) showed a significant genetic variance in CV and V E : In a selection experiment in rabbits, selection on estimated breeding value for V E of birth weight successfully changed the within-litter variability of birth weight (Garreau et al 2008). There are more recent data on genetic control of V E at the level of individual loci from genome-wide association studies (see review by GeilerSamerotte et al 2013).…”

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confidence: 99%

“…For instance, penalties are imposed by slaughterhouses for meat animals delivered with excessive variability because uniform products are demanded by retailers and packing efficiency of products is higher (Hennessy 2005). It has been shown both in theory (SanCristobal-Gaudy et al 1998;Sorensen and Waagepetersen 2003;Mulder et al 2007Mulder et al , 2008 and from experiment (Garreau et al 2008) that uniformity can be increased by selection.…”

mentioning

confidence: 99%

“…Whether plastic genotypes with high V E or stable genotypes with small V E are better capable of handling unpredictable environments is under debate. In livestock little is known about trade-offs between V E and means of other traits, except that uniformity of birth weight in litter-bearing animals does increase the survival of the offspring, e.g., in pigs (Kapell et al 2011) and rabbits (Garreau et al 2008).…”

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confidence: 99%

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Heritable Environmental Variance Causes Nonlinear Relationships Between Traits: Application to Birth Weight and Stillbirth of Pigs

2015

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There is recent evidence from laboratory experiments and analysis of livestock populations that not only the phenotype itself, but also its environmental variance, is under genetic control. Little is known about the relationships between the environmental variance of one trait and mean levels of other traits, however. A genetic covariance between these is expected to lead to nonlinearity between them, for example between birth weight and survival of piglets, where animals of extreme weights have lower survival. The objectives were to derive this nonlinear relationship analytically using multiple regression and apply it to data on piglet birth weight and survival. This study provides a framework to study such nonlinear relationships caused by genetic covariance of environmental variance of one trait and the mean of the other. It is shown that positions of phenotypic and genetic optima may differ and that genetic relationships are likely to be more curvilinear than phenotypic relationships, dependent mainly on the environmental correlation between these traits. Genetic correlations may change if the population means change relative to the optimal phenotypes. Data of piglet birth weight and survival show that the presence of nonlinearity can be partly explained by the genetic covariance between environmental variance of birth weight and survival. The framework developed can be used to assess effects of artificial and natural selection on means and variances of traits and the statistical method presented can be used to estimate trade-offs between environmental variance of one trait and mean levels of others.KEYWORDS genetics of environmental variance; optimum trait; fitness; complex traits; mass selection I N the classic model of quantitative genetics, the phenotype is assumed to be the sum of an effectively infinite number of genes and environmental effects; i.e., P ¼ G þ E (Falconer and Mackay 1996; Lynch and Walsh 1998). The phenotypic variance is the sum of the genetic (V G ) and environmental (V E ) variance. It is assumed that the environmental variance is homogeneous across genotypes, but recently there is evidence from laboratory experiments and analysis of livestock populations that not only the phenotype itself, but also its V E ; is under genetic control (Hill and Mulder 2010). This might be expressed as genetic heterogeneity in the withinindividual variance of a trait with repeat measurements, such as weight of individual piglets in a litter or total litter weight across parities, or as a difference in within-family variance for traits such as juvenile body weight expressed once.The median genetic coefficient of variation for V E (GCV VE ¼ s Av =V E ; where s Av is additive genetic variance in V E ) is 0.3 based on a review of 14 studies with estimates of genetic variance in V E primarily on livestock populations (Hill and Mulder 2010). This indicates that V E could be increased or decreased by 30% if changed by one genetic standard deviation. These analyses were mainly based on genetic analysis...

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Results of four generations of a canalising selection for rabbit birth weight

Cited by 66 publications

References 22 publications

Genetic analysis of environmental variation

Genetic analysis of environmental variation

Breeding for robustness: the role of cortisol

Heritable Environmental Variance Causes Nonlinear Relationships Between Traits: Application to Birth Weight and Stillbirth of Pigs

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