Abstracts (first author)

Talk Plenary (Wed 21)

Population genetics of host-parasite coevolution

Author(s): Ebert D


Hosts evolve to minimize the fitness reduction caused by parasites, while parasites optimise the exploitation of their hosts. In models of this process high genetic specificity in host – parasite interactions is assumed. These interactions are in the centre of theory of host – parasite coevolution and determine important aspects of the coevolutionary process, such as its tempo and mode, the occurrence of cyclic allele frequencies, and the potential for evolutionary novelty. They are also crucial for the consequences of coevolution, such as the maintenance of sex and of genetic variation. In my presentation I will analyse the genetic architecture of host-parasite interactions and will test predictions and assumptions of models of host – parasite coevolution. Finally I will match predictions with patterns from long-term coevolution records.

Abstracts (coauthor)


The roles of communities of host-associated microorganisms (microbiota) in the function, ecology and evolution of their hosts are increasingly being demonstrated across different model systems. We have recently shown that in the water flea Daphnia, a well-studied model for many questions in evolutionary ecology, absence of microbiota significantly decreases survival, growth and fecundity compared to animals with normal microbiota. In this project, we examine the influence of the microbiota on the severity of an infection caused by a microsporidian that is vertically transmitted into diapausing eggs of Daphnia by raising infected and uninfected Daphnia with and without microbiota. Since previous observations suggested that daphnids emerging from diapausing eggs obtain their microbiota horizontally from the environment, we also specifically investigated the ability of several environmental bacteria to restore the normal functioning of infected and uninfected animals. This project addresses both the interaction of parasites and mutualists during the course of the organism's lifetime, and the particular challenges of recruiting and maintaining a functional microbiome faced by diapausing organisms.


In nature, hosts are exposed to a multitude of diseases and a wide range of food qualities and quantities. Hereby, hosts and diseases are in a constant co-evolutionary struggle, which might be influenced by the hosts‘ food intake. This could lead to non-linear responses in host-pathogen interactions. These host food intake dependent host-pathogen interactions on individual level could be translated to the dynamics in populations. Nevertheless, food and disease effects are usually studied independently. So far, prediction models from host individual to population level exist, which either predict food or disease effects, but not effects of both factors at the same time. To fill this gap, a new mathematical model was developed. Due to its characteristics, the model can additionally be used to inversely predict individual level host parameters from population parameters. The given predictions were then compared to the results of life history and population experiments. Therefore, we tested the crustacean model organism Daphnia magna, which offers a wide range of pathogens and foods. We concluded, that population parameters can be successfully predicted from single host parameters and vice versa, depending on specific host, disease and food properties.


Crustaceans of the genus Daphnia have long been used as models in studies of ecology and evolution and of host-pathogen coevolution in particular. However, little is known about the genetic and molecular basis of Daphnia resistance to pathogens. A well-known ecology combined with recent advances in genomic, genetic and molecular tools make Daphnia crustaceans, and in particular Daphnia magna and Daphnia pulex, remarkable models for modern evolution and ecology. D. magna is colonized by a wide range of parasites and pathogens, among them the bacterium Pasteuria ramosa. The study of inheritance patterns of resistance and susceptibility of D. magna clones to different P. ramosa genetic isolates reveals strong genotype-to-genotype interactions, suggesting coevolution between host and pathogen populations. Resistance and susceptibility of D. magna to different P. ramosa isolates follow mendelian patterns of inheritance and segregation, suggesting that a small number of loci underlie natural variation in D. magna resistance to P. ramosa infection. A F2 panel of D. magna was generated, with more than 200 genotypes that are kept by clonal reproduction. A QTL analysis revealed one genomic region of 150kb in linkage group 4 that explaining approximately 60% of the observed variation. However, further inheritance analysis showed that at least 3 loci underlie natural variation in D. magna resistance to P. ramosa infection. One of those loci corresponds to an indel of approximately 50kb. We are currently fine-mapping the QTL interval to identify genes and polymorphisms underlying Daphnia resistance to Pasteuria. We aim to identify which genes and networks and which polymorphisms underlie the natural variation and evolution of pathogen resistance in D. magna. We plan to use molecular tools recently developed for D. magna to achieve our objectives.


It is now generally accepted that microbiota play a major role in the proper functioning of their hosts. The use of model organisms and their bacteria has expedited the learning of these important roles by comparing conventionalized host-bacteria association with the bacteria-free host. In the model crustacean Daphnia, barely any knowledge exists as to the influence of microbiota on their physiology. We assessed if microbiota play a role in the fitness of D. magna by experimentally depriving them of their microbiota and compared their growth, survival and fecundity to that of their bacteria-bearing counterparts. We showed that bacteria-free hosts are smaller, less fecund, and have higher mortality than those with microbiota. We carried out these experiments on Daphnia coming from both a lab-reared parthenogenic clone and field-collected resting eggs (sexual eggs), demonstrating effects within and across host genotypes.


The most extreme inter-individual differences within species are often those between sexes. In populations of sexual species, these intersexual differences often include strong dimorphism in parasite prevalence, disease symptoms and virulence. These effects of host sex have traditionally been attributed to sex-specific differences in host properties such as behavior, immune responses, hormone balances and resource allocation. However, these profound differences between males and females may act as alternative “environments” for infectious parasites and may result in parasite lineages that are differently adapted to each host sex. Here, I will present different conceptual scenarios in which host sex can affect parasite evolution, illustrated with my empirical studies of bacteria evolving naturally in Daphnia or experimentally in Drosophila. A better understanding of specific adaptation of parasites to the host sexes will help us to understand sexual dimorphism in disease responses. Moreover, it will allow us to investigate how parasitism could favor the evolution of sexual dimorphism by reducing the probability that parasites could evolve optimal fitness across both host sexes.


Pond sediments represent a primary source of infective stages of parasites of planktonic organisms. The time and the type of interaction with the sediment are therefore important determinants of infection risk. The fresh water planktonic crustacean Daphnia magna exhibits a highly variable and heritable phototactic behaviour which influences the time spent in proximity of the sediment. It has been shown that clones that spend more time nearer the sediment have a grater risk of infection. Even if suspension feeding is the primary feeding mechanism in D. magna, an alternative behaviour has been described in which small amounts of sediment are stirred up and filtered. This behaviour is expected to increase the encounter rate with parasite infective stages harboured in the sediment and, therefore, infection risk. In the present study we are testing this hypothesis by assessing the heritability of the behaviour and by measuring the infection rates of D.magna clones with different feeding behaviours, exposed to sediment banks of resting spores of the bacterial parasite Pasteuria ramosa. The study is being performed on a large number of clones derived from a quantitative trait loci (QTL) panel. This design allows us to explore the genetic mechanisms underlying the feeding behaviour of D. magna, an ecologically relevant trait expected to influence infection risk in natural environments.


Explaining the ubiquity of sexual reproduction despite its high costs remains one of the major challenges in evolutionary biology. This problem is known as “paradox of sex” and many theoretical models concerning it have been proposed. Following the recent breakthroughs of sequencing technologies we are now able to experimentally evaluate some of the basic assumptions of these models. We used Restriction site Associated DNA (RAD) sequencing to examine the common assumption that asexual reproduction results in perfect clonal offspring with mutations being the only source of new variation. For this we chose the emerging model system Daphnia magna, a cyclic parthenogenetic planktonic crustacean. Comparing pathenogenetic offspring with their mothers at several thousand genetic markers, we detected loss of heterozygosity (LOH) within single asexual generations of D. magna. Our results indicate surprisingly high rates of genome homogenization events (homologous recombination, gene conversions or ploidy losses) during asexual reproduction. These findings should be incorporated in future theoretical models which might lead to the resolution of the “paradox of sex”.


Chairman: Octávio S. Paulo
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XIV Congress of the European Society for Evolutionary Biology

Organization Team
Department of Animal Biology (DBA)
Faculty of Sciences of the University of Lisbon
P-1749-016 Lisbon


Computational Biology & Population Genomics Group