Phylogenetic Symposium 2022

Claudia Bank (University of Bern, Switzerland)

Epistasis and adaptation on fitness landscapes

Epistasis occurs when the effect of a mutation depends on its carrier's genetic background. Although increasing evidence indicates ubiquitous epistasis for fitness, its role during evolution is debated. Fitness landscapes are mappings of genotype or phenotype to fitness, which capture the full extent and complexity of epistasis. Theoretical studies of fitness landscapes have shown how epistasis affects the path and the outcome of evolution. In addition, empirical fitness landscapes, in which the competitive fitness of sets of tens to thousands of connected genotypes was measured, have shown that epistasis is common and depends on the measure of fitness, the choice of mutations for the fitness landscape, and the environment in which fitness was assessed. Here, I present an overview of the field of evolutionary fitness landscape research and highlight ongoing work in my research group that aims at bridging the gap between fitness landscape theory and the role of epistasis in nature. 

 Tiffany Knight  (Helmholtz-Z. für Umweltforsch., Germany)

Title and abstract tba

  Mihaela Pavličev  (University of Vienna, Austria)

How genotype-phenotype maps influence evolvability: beyond modularity

The potential for evolutionary change is deeply anchored in the kind and amount of heritable phenotypic variation that organisms can produce, which is substantially guided by the ways that genetic predispositions translate into the phenotype in physiology and during development. To discuss the role of this genotype-phenotype (GP) mapping and its evolution, I will first outline the two common conceptualizations of the GP map: the global correspondence map and the local mechanistic map, and the relation between them. I will then focus on the structural organismal aspects of the GP map and suggest that the summary concepts that we currently use in evolutionary quantitative genetics are not the appropriate abstractions for understanding long-term evolvability, because they miss important aspects of variation. The summarizing refers to (at least) two dimensions: the levels of organismal organization (from cells to end-phenotypes), as well as across the importantly differing developmental phases (morphogenesis vs. growth vs. maintenance). One way to approach this problem is to address the mechanistic, causal mapping explicitly and explore the variational properties of various well-known biochemical or regulatory processes, and their effects on function systematically. This may reveal more suitable levels of abstraction and allow us to not only better account for the complexity of adaptive process, but also better capture the underlying mechanisms- thus adding the mechanistic aspect to the global GP map.

        P. David Polly  (Indiana University, USA)

Functional trade-offs carry phenotypes across the valley of the shadow of death: Why multi-peak OU models may not be a good model for performance trade-offs

Phylogenetic evolutionary model fitting has become a state-of-the-art tool for studying the tempo and mode of evolution.  One such option is the multi-peak OU model, which estimates the number and location of adaptive peaks in a morphospace based on the phylogenetic distribution of traits in that space. The multi-peak model is derived from Simpson’s and Wright’s ideas of adaptive landscapes where peaks of high fitness are separated by valleys of low fitness defining adaptive zones and it is frequently used to study the evolutionary consequences of functional trade-offs performance for one function is minimized when a character complex is optimized for performance for another.  However, such a trade-off will be represented by two adaptive peaks only when taxa never need both functions; when a taxon periodically needs to perform both functions, the appropriate model is a single adaptive peak whose location and breadth is defined by the frequency of selection for the competing functions.  In this talk I present this alternative model of adaptive peak and I show that its location in morphospace shifts as functional demands change, much like Simpon’s original conception of the historical origin and loss of adaptive zones.  I also show how parameters for the dynamic adaptive peak model can be estimated in a phylogenetic context, thus tracing the temporal history of the shifting adaptive landscape.  Functional trade-offs may help explain how lineages shift from one performance peak to another without inhibition of fitness valleys.  

David Labonte  (Imperial College London, UK)

Functional, historical and structural constraints in allometry

Selective pressure can result in adaptation, but this process is not entirely free. Instead, it must occur within boundaries defined by historical and structural constraints. The interaction between  pressures and constraints underpins the evolution of the diversity of form, but is difficult to disentangle for at least two reasons. First, it typically requires large comparative data sets. Second, functional demands can be inferred from ecology and life history, and physical constraints from first principles, but historical constraints are hard to define quantitatively, and may vary substantially with phylogenetic level. I submit that the study of trait allometry - how shape or `performance’ vary with size - provides an opportunity to tackle this complex problem, provided that the functional demand can be linked to physical constraints via first principles. Such a link establishes all possible architectural pathways for satisfying a functional demand; observation of architectural variation within and across species reveals which of these pathways may be favoured; and variations in preferred pathway with degree of relatedness indicate the presence of phylogenetic or developmental constraints. I illustrate this approach with examples from animal biomechanics, and argue that a variation of constraints with phylogenetic level can result in weak instances of Simpson’s paradox: an association between variables in a population disappears or reverses when the population is divided into subpopulations.

 John A. Nyakatura  (University of Berlin, Germany)

Tetrapod form and function in an evolutionary framework: the neck of artiodactyls and the iconic case of the giraffe’s loooong neck

The talk will use our team’s recent research into the iconic long necks of giraffes and the strikingly variable neck length of artiodactyls in general to demonstrate our approach for an integrative investigation at the interface of form, function, and evolution. We are leveraging museum collections and are making use of increasingly available non-destructive imaging techniques to conduct clade-wide comparative and quantitative analyses of 3D shape and structure within a phylogenetically informed framework. Computational modelling of the form-function relationship facilitates the identification of performance differences, e.g., in terms of a potential trade-off between joint mobility or vertebral robusticity across Artiodactyla. Phylogenetic reconstructions allow us to assess convergence while statistical models of trait evolution help to gain insight into the interplay between adaptation and phylogenetic constraints in shaping the current diversity.  This combined analysis, which is transferable to similar questions of evolutionary and functional morphology, not only revealed new insight into the unique morphology of the giraffe’s vertebrae especially at the transition from the neck to the trunk, but also shed light on the evolutionary dynamics of artiodactyl neck evolution.  

Moritz Lürig  (Lund University, Sweden)

Toward assembling the phenome: challenges and prospects

In the quest to understand biological phenomena that shape organismal phenotypes in nature, most ecologists and evolutionary biologists confine their efforts to a small set of observable characters. This century-old approach of breaking down the complexity of living beings to a tractable number of dimensions has been indispensable in both hypothesis and discovery driven research. However, it is becoming increasingly clear that by studying only a small number of traits, often discretized and with limited replication in space and time, we will not be able to deepen this knowledge and understand the causal links between genotypes, environment, and phenotypes. In other words, to construct the genotype-phenotype map of an organism we need to assemble its phenome; the phenotype as a whole mapped out along many concurrent trait axes. The challenges in this endeavor are obvious: in contrast to DNA, organisms are high-dimensional entities with often transient and seamlessly connected characteristics, making the assembly of phenomic datasets that are on par with genomic datasets extremely challenging. Computer vision, the automatic extraction of meaningful information from digital images, is a promising set of methods that may alleviate this methodological bottleneck and allow us to collect phenotypic information on a massive scale. The field has blossomed in recent years, and biologists now have a diverse array of computational tools at their disposal to assemble phenomic datasets with high throughput and reproducibility. In this lecture I will i) discuss the challenges and prospects of assembling phenomes, ii) attempt to provide an overview of the most common computer vision techniques for the extraction of phenotypic data from digital images, iii) and showcase a phenomics workflow using the sexual color polymorphism in the common bluetail damselfly Ischnura elegans.

  Emily Rayfield  (University of Bristol, UK) 

Are complex shapes better optimised for functional performance?

It has been argued that in the absence of selection and constraint, organisms accumulate variation and biological complexity will tend to increase (McShea’s Zero-Force Evolutionary Law). How widespread is this phenomenon and, at the organismal level, how do changes in complexity relate to function and organismal performance? The vertebrate jaw structure (mandible) is comprised of several component parts (individual bones). As noted by the proponents of the ZFEL, the jaw of synapsids on the lineage leading towards mammals demonstrates a clear reduction in bone count and a well-characterised decrease in constructional complexity. Individual postdentary bones are lost or incorporated into the mammalian middle ear, resulting in a single bone, the dentary, acting as tooth bearer, jaw hinge and muscle attachment site. In this study we ask the question, are complex or simpler shapes better optimsed for functional performance? We determine complexity in two ways, as complexity of outline jaw shape, and complexity of parts; the number of bones comprising the lower jaw. Using a novel theoretical morphology approach, we determine the function of jaw shapes representing non-mammalian tetrapods (multipart jaws) and mammals (single element jaws). We find that regardless of shape complexity, jaws comprised of a single bone (mammals) are more functionally optimal that jaws comprised from multiple bones. As complexity of shape increases in multipart or single element jaws, functional performance becomes less optimal. Overall, with respect to this dataset, we conclude that complex jaw shapes are less optimised for functional performance. 

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