Causal Foundations of Evolutionary Genetics

The causal nature of evolution is one of the central topics in the philosophy of biology. It has been discussed whether equations used in evolutionary genetics point to some causal processes or are purely phenomenological patterns. To address this question the present paper builds well-defined causal models that underlie standard equations in evolutionary genetics. These models are based on minimal and biologically-plausible hypotheses about selection and reproduction, and generate statistics to predict evolutionary changes. The causal reconstruction of the evolutionary principles shows adaptive evolution as a genuine causal process, where fitness and selection are both causes of evolution

Evolutionary Genetics of Microbial Symbiosis

Symbiosis is the living together of dissimilar organisms [1,2]. As such, symbiotic relationships can range from antagonist (parasitic) to mutualistic and can vary along this continuum within and between species in space and time. Microbial symbioses encompass a wide array of players (e.g., bacteria, fungi, and small eukaryotes) and are an integral part of organismal life, contributing to phenotypes at all levels of biological organization, from molecules to ecosystems. There has been an explosion of microbiological research on symbiosis emerging from the omics revolution, which has made many previously intractable symbioses available for dissection. Current research ranges from unraveling the biochemical interactions among symbiont partners to uncovering the incredible ecological diversity and dynamics of microbial communities and host associations. Host-microbes engage in extensive and complex cross-kingdom molecular dialogue, where symbionts can modulate their reciprocal gene expression patterns, complement metabolic pathways, and combine genetic information through DNA exchange, in some cases becoming sufficiently integrated through coinheritance to be considered as an evolutionary unit of selection. This extensive genetic and biochemical interplay has enormous implications in the emergence of novel traits and the overall diversification of life

Replicator-mutator equations with quadratic fitness

This work completes our previous analysis on models arising in evolutionary genetics. We consider the so-called replicator-mutator equation, when the fitness is quadratic. This equation is a heat equation with a harmonic potential, plus a specific nonlocal term. We give an explicit formula for the solution, thanks to which we prove that when the fitness is non-positive (harmonic potential), solutions converge to a universal stationary Gaussian for large time, whereas when the fitness is non-negative (inverted harmonic potential), solutions always become extinct in finite time.Comment: 12 page

Proof of Concept Research

Researchers often pursue proof of concept research, but criteria for evaluating such research remain poorly specified. This paper proposes a general framework for proof of concept research that knits together and augments earlier discussions. The framework includes prototypes, proof of concept demonstrations, and post facto demonstrations. With a case from theoretical evolutionary genetics, the paper illustrates the general framework and articulates some of the reasoning strategies used within that field. This paper provides both specific tools with which to understand how researchers evaluate models in theoretical evolutionary genetics, and general tools that apply to proof of concept research more generally

Strategies of model building in population genetics

Journal ArticleIn 1966, Richard Levins argued that there are different strategies in model building in population biology. In this paper, I reply to Orzack and Sober's (1993) critiques of Levins and argue that his view on modeling strategies apply also in the context of evolutionary genetics. In particular, I argue that there are different ways in which models are used to ask and answer questions about the dynamics of evolutionary change, prospectively and retrospectively, in classical versus molecular evolutionary genetics. Further, I argue that robustness analysis is a tool for, if not confirmation, then something near enough, in this discipline

Strategies of Model Building in Population Genetics

In 1966, Richard Levins argued that there are different strategies in model building in population biology. In this paper, I reply to Orzack and Sober’s (1993) critiques of Levins and argue that his views on modeling strategies apply also in the context of evolutionary genetics. In particular, I argue that there are different ways in which models are used to ask and answer questions about the dynamics of evolutionary change, prospectively and retrospectively, in classical versus molecular evolutionary genetics. Further, I argue that robustness analysis is a tool for, if not confirmation, then something near enough, in this discipline