241 research outputs found
The evolution of genetic architectures underlying quantitative traits
In the classic view introduced by R. A. Fisher, a quantitative trait is
encoded by many loci with small, additive effects. Recent advances in QTL
mapping have begun to elucidate the genetic architectures underlying vast
numbers of phenotypes across diverse taxa, producing observations that
sometimes contrast with Fisher's blueprint. Despite these considerable
empirical efforts to map the genetic determinants of traits, it remains poorly
understood how the genetic architecture of a trait should evolve, or how it
depends on the selection pressures on the trait. Here we develop a simple,
population-genetic model for the evolution of genetic architectures. Our model
predicts that traits under moderate selection should be encoded by many loci
with highly variable effects, whereas traits under either weak or strong
selection should be encoded by relatively few loci. We compare these
theoretical predictions to qualitative trends in the genetics of human traits,
and to systematic data on the genetics of gene expression levels in yeast. Our
analysis provides an evolutionary explanation for broad empirical patterns in
the genetic basis of traits, and it introduces a single framework that unifies
the diversity of observed genetic architectures, ranging from Mendelian to
Fisherian.Comment: Minor changes in the text; Added supplementary materia
Small games and long memories promote cooperation
Complex social behaviors lie at the heart of many of the challenges facing
evolutionary biology, sociology, economics, and beyond. For evolutionary
biologists in particular the question is often how such behaviors can arise
\textit{de novo} in a simple evolving system. How can group behaviors such as
collective action, or decision making that accounts for memories of past
experience, emerge and persist? Evolutionary game theory provides a framework
for formalizing these questions and admitting them to rigorous study. Here we
develop such a framework to study the evolution of sustained collective action
in multi-player public-goods games, in which players have arbitrarily long
memories of prior rounds of play and can react to their experience in an
arbitrary way. To study this problem we construct a coordinate system for
memory- strategies in iterated -player games that permits us to
characterize all the cooperative strategies that resist invasion by any mutant
strategy, and thus stabilize cooperative behavior. We show that while larger
games inevitably make cooperation harder to evolve, there nevertheless always
exists a positive volume of strategies that stabilize cooperation provided the
population size is large enough. We also show that, when games are small,
longer-memory strategies make cooperation easier to evolve, by increasing the
number of ways to stabilize cooperation. Finally we explore the co-evolution of
behavior and memory capacity, and we find that longer-memory strategies tend to
evolve in small games, which in turn drives the evolution of cooperation even
when the benefits for cooperation are low
The collapse of cooperation in evolving games
Game theory provides a quantitative framework for analyzing the behavior of
rational agents. The Iterated Prisoner's Dilemma in particular has become a
standard model for studying cooperation and cheating, with cooperation often
emerging as a robust outcome in evolving populations. Here we extend
evolutionary game theory by allowing players' strategies as well as their
payoffs to evolve in response to selection on heritable mutations. In nature,
many organisms engage in mutually beneficial interactions, and individuals may
seek to change the ratio of risk to reward for cooperation by altering the
resources they commit to cooperative interactions. To study this, we construct
a general framework for the co-evolution of strategies and payoffs in arbitrary
iterated games. We show that, as payoffs evolve, a trade-off between the
benefits and costs of cooperation precipitates a dramatic loss of cooperation
under the Iterated Prisoner's Dilemma; and eventually to evolution away from
the Prisoner's Dilemma altogether. The collapse of cooperation is so extreme
that the average payoff in a population may decline, even as the potential
payoff for mutual cooperation increases. Our work offers a new perspective on
the Prisoner's Dilemma and its predictions for cooperation in natural
populations; and it provides a general framework to understand the co-evolution
of strategies and payoffs in iterated interactions.Comment: 33 pages, 13 figure
The evolution of complex gene regulation by low specificity binding sites
Transcription factor binding sites vary in their specificity, both within and
between species. Binding specificity has a strong impact on the evolution of
gene expression, because it determines how easily regulatory interactions are
gained and lost. Nevertheless, we have a relatively poor understanding of what
evolutionary forces determine the specificity of binding sites. Here we address
this question by studying regulatory modules composed of multiple binding
sites. Using a population-genetic model, we show that more complex regulatory
modules, composed of a greater number of binding sites, must employ binding
sites that are individually less specific, compared to less complex regulatory
modules. This effect is extremely general, and it hold regardless of the
regulatory logic of a module. We attribute this phenomenon to the inability of
stabilising selection to maintain highly specific sites in large regulatory
modules. Our analysis helps to explain broad empirical trends in the yeast
regulatory network: those genes with a greater number of transcriptional
regulators feature by less specific binding sites, and there is less variance
in their specificity, compared to genes with fewer regulators. Likewise, our
results also help to explain the well-known trend towards lower specificity in
the transcription factor binding sites of higher eukaryotes, which perform
complex regulatory tasks, compared to prokaryotes
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