Developmental Evolution in Social Insects: Regulatory Networks from Genes to Societies

Linksvayer, Timothy A.; Fewell, Jennifer H.; Gadau, Jürgen; Laubichler, Manfred D.

doi:10.1002/jez.b.22001

Cited by 39 publications

(42 citation statements)

References 103 publications

(112 reference statements)

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“…This approach can be extended to more complex cases, including so-called emergent traits that cannot be observed on a single individual, as illustrated by examples in Wilson et al (2011) and Bijma (2011); see also Linksvayer et al (2012) and Bailey (2012).…”

Section: Basic Quantitative Genetic Results For Igesmentioning

confidence: 99%

“…At present, models including IGEs are finding widespread application in natural populations, which may considerably broaden our quantitative genetic understanding of evolution by natural selection (Bailey, 2012). Examples are the impact of IGEs on the evolution of social interactions due to sexual selection (Chenoweth et al, 2010;Bailey and Moore, 2012) and the extension of gene networks to societies (Linksvayer et al, 2012).…”

Section: Genetic Architecture and Sustainability Of Response To Selecmentioning

confidence: 99%

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The quantitative genetics of indirect genetic effects: a selective review of modelling issues

2013

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Indirect genetic effects (IGE) occur when the genotype of an individual affects the phenotypic trait value of another conspecific individual. IGEs can have profound effects on both the magnitude and the direction of response to selection. Models of inheritance and response to selection in traits subject to IGEs have been developed within two frameworks; a trait-based framework in which IGEs are specified as a direct consequence of individual trait values, and a variance-component framework in which phenotypic variance is decomposed into a direct and an indirect additive genetic component. This work is a selective review of the quantitative genetics of traits affected by IGEs, with a focus on modelling, estimation and interpretation issues. It includes a discussion on variance-component vs trait-based models of IGEs, a review of issues related to the estimation of IGEs from field data, including the estimation of the interaction coefficient W (psi), and a discussion on the relevance of IGEs for response to selection in cases where the strength of interaction varies among pairs of individuals. An investigation of the trait-based model shows that the interaction coefficient W may deviate considerably from the corresponding regression coefficient when feedback occurs. The increasing research effort devoted to IGEs suggests that they are a widespread phenomenon, probably particularly in natural populations and plants. Further work in this field should considerably broaden our understanding of the quantitative genetics of inheritance and response to selection in relation to the social organisation of populations.

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Section: Basic Quantitative Genetic Results For Igesmentioning

confidence: 99%

Section: Genetic Architecture and Sustainability Of Response To Selecmentioning

confidence: 99%

The quantitative genetics of indirect genetic effects: a selective review of modelling issues

2013

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“…While most of the phenomena studied by systems biologists are processes taking place within single organisms or even single cells (Helms, 2008), there is also research pertaining to the interaction of microorganisms or the distribution and transfer of genes across whole microbial communities (e.g., using data of metagenomics projects), so that systems biology can have connections to ecology (Crawford et al, 2005;Jansson et al, 2012). Studies on (changes in) gene regulatory networks are germane to evolutionary biology (Davidson, 2006;Davidson & Erwin, 2006;Linksvayer et al, 2012;O'Malley & Soyer, 2012). Of course, research on the workings of biological systems also has medical applications in view, most notably in the context of cancer biology (Faratian et al, 2009;Kitano, 2004b;Patel & Nagl, 2010;Wang, 2010), and such broader technological applications as synthetic biology (Fu & Panke, 2009).…”

Section: Systems Biologymentioning

confidence: 99%

Systems biology and the integration of mechanistic explanation and mathematical explanation

Brigandt

2013

Studies in History and Philosophy of Science Part C: Studies in

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The paper discusses how systems biology is working toward complex accounts that integrate explanation in terms of mechanisms and explanation by mathematical models-which some philosophers have viewed as rival models of explanation. Systems biology is an integrative approach, and it strongly relies on mathematical modeling. Philosophical accounts of mechanisms capture integrative in the sense of multilevel and multifield explanations, yet accounts of mechanistic explanation (as the analysis of a whole in terms of its structural parts and their qualitative interactions) have failed to address how a mathematical model could contribute to such explanations. I discuss how mathematical equations can be explanatorily relevant. Several cases from systems biology are discussed to illustrate the interplay between mechanistic research and mathematical modeling, and I point to questions about qualitative phenomena (rather than the explanation of quantitative details), where quantitative models are still indispensable to the explanation. Systems biology shows that a broader philosophical conception of mechanisms is needed, which takes into account functional-dynamical aspects, interaction in complex networks with feedback loops, system-wide functional properties such as distributed functionality and robustness, and a mechanism's ability to respond to perturbations (beyond its actual operation). I offer general conclusions for philosophical accounts of explanation.

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“…Evodevo's diversity holds even for its development component. Many studies of development focus on the regulation of individual genes (Prud'homme et al 2011;Shigetani et al 2002), or complete gene regulatory networks (Davidson 2006(Davidson , 2010Linksvayer et al 2012), so that morphological evolution is conceived as change in gene regulation (Carroll 2008;Davidson and Erwin 2006;Erwin and Davidson 2009;Laubichler 2009). However, not all explanations are restricted to developmental genetics.…”

Section: Evolutionary Developmental Biology: Integrative and Diversementioning

confidence: 99%

Evolutionary Developmental Biology and the Limits of Philosophical Accounts of Mechanistic Explanation

Brigandt

2015

History, Philosophy and Theory of the Life Sciences

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Evolutionary developmental biology (evo-devo) is considered a 'mechanistic science,' in that it causally explains morphological evolution in terms of changes in developmental mechanisms. Evo-devo is also an interdisciplinary and integrative approach, as its explanations use contributions from many fields and pertain to different levels of organismal organization. Philosophical accounts of mechanistic explanation are currently highly prominent, and have been particularly able to capture the integrative nature of multifield and multilevel explanations. However, I argue that evo-devo demonstrates the need for a broadened philosophical conception of mechanisms and mechanistic explanation.Mechanistic explanation (in terms of the qualitative interactions of the structural parts of a whole) has been developed as an alternative to the traditional idea of explanation as derivation from laws or quantitative principles. Against the picture promoted by Carl Craver, that mathematical models describe but usually do not explain, my discussion of cases from the strand of evo-devo which is concerned with developmental processes points to qualitative phenomena where quantitative mathematical models are an indispensable part of the explanation. While philosophical accounts have focused on the actual organization and operation of mechanisms, properties of developmental mechanisms that are about how a mechanism reacts to modifications are of major evolutionary significance, including robustness, phenotypic plasticity, and modularity. A philosophical conception of mechanisms is needed that takes into account quantitative changes, transient entities and the generation of novel types of entities, feedback loops and complex interaction networks, emergent properties, and, in particular, functional-dynamical aspects of mechanisms, including functional (as opposed to structural) organization and distributed, system-wide phenomena. I conclude with general remarks on philosophical accounts of explanation.

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Developmental Evolution in Social Insects: Regulatory Networks from Genes to Societies

Cited by 39 publications

References 103 publications

The quantitative genetics of indirect genetic effects: a selective review of modelling issues

The quantitative genetics of indirect genetic effects: a selective review of modelling issues

Systems biology and the integration of mechanistic explanation and mathematical explanation

Evolutionary Developmental Biology and the Limits of Philosophical Accounts of Mechanistic Explanation

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