Literature DB >> 24686929

The genetical theory of social behaviour.

Laurent Lehmann1, François Rousset.   

Abstract

We survey the population genetic basis of social evolution, using a logically consistent set of arguments to cover a wide range of biological scenarios. We start by reconsidering Hamilton's (Hamilton 1964 J. Theoret. Biol. 7, 1-16 (doi:10.1016/0022-5193(64)90038-4)) results for selection on a social trait under the assumptions of additive gene action, weak selection and constant environment and demography. This yields a prediction for the direction of allele frequency change in terms of phenotypic costs and benefits and genealogical concepts of relatedness, which holds for any frequency of the trait in the population, and provides the foundation for further developments and extensions. We then allow for any type of gene interaction within and between individuals, strong selection and fluctuating environments and demography, which may depend on the evolving trait itself. We reach three conclusions pertaining to selection on social behaviours under broad conditions. (i) Selection can be understood by focusing on a one-generation change in mean allele frequency, a computation which underpins the utility of reproductive value weights; (ii) in large populations under the assumptions of additive gene action and weak selection, this change is of constant sign for any allele frequency and is predicted by a phenotypic selection gradient; (iii) under the assumptions of trait substitution sequences, such phenotypic selection gradients suffice to characterize long-term multi-dimensional stochastic evolution, with almost no knowledge about the genetic details underlying the coevolving traits. Having such simple results about the effect of selection regardless of population structure and type of social interactions can help to delineate the common features of distinct biological processes. Finally, we clarify some persistent divergences within social evolution theory, with respect to exactness, synergies, maximization, dynamic sufficiency and the role of genetic arguments.

Keywords:  demographic stochasticity; environmental stochasticity; game theory; inclusive fitness; maximization; multi-locus models

Mesh:

Year:  2014        PMID: 24686929      PMCID: PMC3982659          DOI: 10.1098/rstb.2013.0357

Source DB:  PubMed          Journal:  Philos Trans R Soc Lond B Biol Sci        ISSN: 0962-8436            Impact factor:   6.237


  67 in total

Review 1.  General models of multilocus evolution.

Authors:  Mark Kirkpatrick; Toby Johnson; Nick Barton
Journal:  Genetics       Date:  2002-08       Impact factor: 4.562

2.  The origin of gender dimorphism in animal-dispersed plants: disruptive selection in a model of social evolution.

Authors:  Jay M Biernaskie
Journal:  Am Nat       Date:  2010-06       Impact factor: 3.926

3.  Heterozygosity and relationship in regularly subdivided populations.

Authors:  G Malécot
Journal:  Theor Popul Biol       Date:  1975-10       Impact factor: 1.570

4.  Multilocus models in the infinite island model of population structure.

Authors:  Denis Roze; François Rousset
Journal:  Theor Popul Biol       Date:  2008-03-22       Impact factor: 1.570

5.  Darwinian adaptation, population genetics and the streetcar theory of evolution.

Authors:  P Hammerstein
Journal:  J Math Biol       Date:  1996       Impact factor: 2.259

6.  The components of kin competition.

Authors:  J David Van Dyken
Journal:  Evolution       Date:  2010-08-19       Impact factor: 3.694

7.  Hierarchical selection theory and sex ratios. I. General solutions for structured populations.

Authors:  S A Frank
Journal:  Theor Popul Biol       Date:  1986-06       Impact factor: 1.570

8.  Selection and covariance.

Authors:  G R Price
Journal:  Nature       Date:  1970-08-01       Impact factor: 49.962

9.  The genetical evolution of social behaviour. I.

Authors:  W D Hamilton
Journal:  J Theor Biol       Date:  1964-07       Impact factor: 2.691

10.  Kin competition, the cost of inbreeding and the evolution of dispersal

Authors: 
Journal:  J Theor Biol       Date:  1999-10-21       Impact factor: 2.691

View more
  14 in total

1.  Cooperation, clumping and the evolution of multicellularity.

Authors:  Jay M Biernaskie; Stuart A West
Journal:  Proc Biol Sci       Date:  2015-08-22       Impact factor: 5.349

Review 2.  There is no fitness but fitness, and the lineage is its bearer.

Authors:  Erol Akçay; Jeremy Van Cleve
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2016-02-05       Impact factor: 6.237

3.  The evolution of early-life effects on social behaviour-why should social adversity carry over to the future?

Authors:  Bram Kuijper; Rufus A Johnstone
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2019-04-15       Impact factor: 6.237

4.  The general form of Hamilton's rule makes no predictions and cannot be tested empirically.

Authors:  Martin A Nowak; Alex McAvoy; Benjamin Allen; Edward O Wilson
Journal:  Proc Natl Acad Sci U S A       Date:  2017-05-16       Impact factor: 11.205

5.  The gene's eye view, the Gouldian knot, Fisherian swords and the causes of selection.

Authors:  David C Queller
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2020-03-09       Impact factor: 6.237

6.  The genetical theory of multilevel selection.

Authors:  A Gardner
Journal:  J Evol Biol       Date:  2015-01-06       Impact factor: 2.411

Review 7.  Kin and multilevel selection in social evolution: a never-ending controversy?

Authors:  Jos Kramer; Joël Meunier
Journal:  F1000Res       Date:  2016-04-28

8.  Antisocial rewarding in structured populations.

Authors:  Miguel Dos Santos; Jorge Peña
Journal:  Sci Rep       Date:  2017-07-24       Impact factor: 4.379

9.  Altruism in a volatile world.

Authors:  Patrick Kennedy; Andrew D Higginson; Andrew N Radford; Seirian Sumner
Journal:  Nature       Date:  2018-03-07       Impact factor: 49.962

10.  The causal meaning of Hamilton's rule.

Authors:  Samir Okasha; Johannes Martens
Journal:  R Soc Open Sci       Date:  2016-03-16       Impact factor: 2.963

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.