Artificial selection on phenotypically plastic traits

Kirkpatrick, Mark; Bataillon, Thomas

doi:10.1017/s0016672399004115

Cited by 14 publications

(10 citation statements)

References 19 publications

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“…Kolmodin et al 2002;Calus & Veerkamp 2003). Optimization of selection programmes considering environmental sensitivity described by a reaction norm has been considered by Kirkpatrick & Bataillon (1999), de Jong & Bijma (2002, Kolmodin et al (2003) and Kolmodin & Bijma (2004).…”

Section: (B) Multiple Control Variablesmentioning

confidence: 99%

Up hill, down dale: quantitative genetics of curvaceous traits

Meyer

Kirkpatrick

2005

Phil. Trans. R. Soc. B

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100

107

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'Repeated' measurements for a trait and individual, taken along some continuous scale such as time, can be thought of as representing points on a curve, where both means and covariances along the trajectory can change, gradually and continually. Such traits are commonly referred to as 'functionvalued' (FV) traits. This review shows that standard quantitative genetic concepts extend readily to FV traits, with individual statistics, such as estimated breeding values and selection response, replaced by corresponding curves, modelled by respective functions. Covariance functions are introduced as the FV equivalent to matrices of covariances.Considering the class of functions represented by a regression on the continuous covariable, FV traits can be analysed within the linear mixed model framework commonly employed in quantitative genetics, giving rise to the so-called random regression model. Estimation of covariance functions, either indirectly from estimated covariances or directly from the data using restricted maximum likelihood or Bayesian analysis, is considered. It is shown that direct estimation of the leading principal components of covariance functions is feasible and advantageous. Extensions to multidimensional analyses are discussed.

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Section: (B) Multiple Control Variablesmentioning

confidence: 99%

Up hill, down dale: quantitative genetics of curvaceous traits

Meyer

Kirkpatrick

2005

Phil. Trans. R. Soc. B

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100

107

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“…Kirkpatrick and Bataillon [10] have derived equations for the maximisation of selection response in the phenotypic value in a specified environment to mass selection on a trait affected by G × E. Their approach was to derive optimum index weights for observations recorded in different environments, modelling a covariance function without any assumptions of the shape of the reaction norm. Another approach is to model G × E as a linear reaction norm.…”

Section: Introductionmentioning

confidence: 99%

Response to mass selection when the genotype by environment interaction is modelled as a linear reaction norm

Kolmodin

Bijma

2004

Genet Sel Evol

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-A breeding goal accounting for the effects of genotype by environment interaction (G × E) has to define not only traits but also the environment in which those traits are to be improved. The aim of this study was to predict the selection response in the coefficients of a linear reaction norm, and response in average phenotypic value in any environment, when mass selection is applied to a trait where G × E is modelled as a linear reaction norm. The optimum environment in which to test the selection candidates for a given breeding objective was derived. Optimisation of the selection environment can be used as a means to either maximise genetic progress in a certain response environment, to keep the change in environmental sensitivity at a desired rate, or to reduce the proportion of animals performing below an acceptance level. The results showed that the optimum selection environment is not always equal to the environment in which the response is to be realised, but depends on the degree of G × E (determined by the ratio of variances in slope and level of a linear reaction norm), the correlation between level and slope, and the heritability of the trait. mass selection / selection response / reaction norm / genotype by environment interaction INTRODUCTIONGenotype by environment interaction (G × E) is becoming increasingly important due to the globalisation of animal breeding. With G × E, the phenotypic expression of a trait in different environments, such as countries, climatic zones or production systems, is genetically not the same trait. In such cases, the breeding goal should define not only the traits but also the environment in which those traits are to be improved. * Corresponding author: Rebecka.Kolmodin@hgen.slu.se

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“…Moreover, novel markets and industries may emerge through innovative utilization of existing organic "waste products" and in the process eliminate waste streams and create jobs and industries. Other examples include use of organic wastes as substrate for mushroom production, compost, energy production, or fillers in animal feed (e.g., insect biomass) (Surendra et al 2016;Lou and Nair 2009;Kusch et al 2015;Kabongo 2013;Lim et al 2016; California Biomass Collaborative 2012; Zweigle 2010).…”

Section: The Solutionmentioning

confidence: 99%

“…Additionally, some models for insect bioconversion have breeding and egg production facilities far from the location bioconversion actually occurs, necessitating insects to tolerate not only variable environmental conditions, such as temperature and humidity, but also differences in regional crop varieties, which may differ in nutrient quality (Palma et al 2018). Viewed in this way, the plasticity across environment itself may be treated a component within the estimated breeding values used in index selection (Kirkpatrick and Bataillon 1999). In this way, breeding program objectives may be set to maximize phenotypic responses across environments.…”

Section: How To Monitor and Quantify Adaptive Phenotypic Plasticitymentioning

confidence: 99%

Artificial selection of insects to bioconvert pre-consumer organic wastes. A review

Fowles

Nansen

2019

Agron. Sustain. Dev.

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As the human population continues to grow, so too do the concerns regarding the sustainability of waste management from our food production systems. Faced with limited environmental resources for food production, issues related to food loss and waste are critical in mitigating challenges stemming from projected population growth and long-term food security and sustainability. The potential for using insects to consume organic waste materials and convert them into feed for animal, biofuels, and other valuable secondary products is gaining momentum as both a research discipline and as a business opportunity. Here, this ecosystem service is referred to as "insects as bioconverters of organic waste." Scientific reviews of this topic have mainly focused on the challenges associated with development of commercial scale systems. To compliment existing reviews, we address this exciting topic from an artificial selection perspective, as we review and discuss aspects associated with targeted breeding and adaptation of both gut microbial communities and host insects themselves. We describe the "ideal insect bioconverter," insects uniquely equipped to convert wastes into biomass and other valuable secondary products, and we present the current knowledge and existing research gaps towards the development of such organisms. We conclude that (1) targeted breeding of insects and their gut microbes can produce tailored insect lineages for bioconversion of specific waste streams; (2) research is needed to take full advantage of the existing insect diversity to identify new candidate species for bioconversion; and (3) further research into insect-gut microbial complexes will likely provide important insight into ways insects can be used as sustainable bioconverters of highly specialized waste streams.

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Artificial selection on phenotypically plastic traits

Cited by 14 publications

References 19 publications

Up hill, down dale: quantitative genetics of curvaceous traits

Up hill, down dale: quantitative genetics of curvaceous traits

Response to mass selection when the genotype by environment interaction is modelled as a linear reaction norm

Artificial selection of insects to bioconvert pre-consumer organic wastes. A review

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