Temporal regulation of kin recognition maintains recognition-cue diversity and suppresses cheating.
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ABSTRACT:
SUBMITTER: Ho HI
PROVIDER: S-EPMC4448137 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The evolution of sociality and altruism is enigmatic because cooperators are constantly threatened by cheaters who benefit from cooperation without incurring its full cost [1, 2]. Kin recognition is the ability to recognize and cooperate with genetically close relatives. It has also been proposed as a potential mechanism that limits cheating [3, 4], but there has been no direct experimental support for that possibility. Here we show that kin recognition protects cooperators against cheaters. The social amoebae Dictyostelium discoideum cooperate by forming multicellular aggregates that develop into fruiting bodies of viable spores and dead stalk cells. Cheaters preferentially differentiate into spores while their victims die as stalk cells in chimeric aggregates. We engineered syngeneic cheaters and victims that differed only in their kin-recognition genes, tgrB1 and tgrC1, and in a single cheater allele and found that the victims escaped exploitation by different types of nonkin cheaters. This protection depends on kin-recognition-mediated segregation because it is compromised when we disrupt strain segregation. These findings provide direct evidence for the role of kin recognition in cheater control and suggest a mechanism for the maintenance of stable cooperative systems.
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Project description:Kin recognition is important in animal social systems. However, though plants often compete with kin, there has been as yet no direct evidence that plants recognize kin in competitive interactions. Here we show in the annual plant Cakile edentula, allocation to roots increased when groups of strangers shared a common pot, but not when groups of siblings shared a pot. Our results demonstrate that plants can discriminate kin in competitive interactions and indicate that the root interactions may provide the cue for kin recognition. Because greater root allocation is argued to increase below-ground competitive ability, the results are consistent with kin selection.
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Project description:Social interactions among individuals are widespread, both in natural and domestic populations. As a result, trait values of individuals may be affected by genes in other individuals, a phenomenon known as indirect genetic effects (IGEs). IGEs can be estimated using linear mixed models. The traditional IGE model assumes that an individual interacts equally with all its partners, whether kin or strangers. There is abundant evidence, however, that individuals behave differently towards kin as compared with strangers, which agrees with predictions from kin-selection theory. With a mix of kin and strangers, therefore, IGEs estimated from a traditional model may be incorrect, and selection based on those estimates will be suboptimal. Here we investigate whether genetic parameters for IGEs are statistically identifiable in group-structured populations when IGEs differ between kin and strangers, and develop models to estimate such parameters. First, we extend the definition of total breeding value and total heritable variance to cases where IGEs depend on relatedness. Next, we show that the full set of genetic parameters is not identifiable when IGEs differ between kin and strangers. Subsequently, we present a reduced model that yields estimates of the total heritable effects on kin, on non-kin and on all social partners of an individual, as well as the total heritable variance for response to selection. Finally we discuss the consequences of analysing data in which IGEs depend on relatedness using a traditional IGE model, and investigate group structures that may allow estimation of the full set of genetic parameters when IGEs depend on kin.
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