How does the mode of evolutionary divergence affect reproductive isolation?

When divergent populations interbreed, the outcome will be affected by the genomic and phenotypic differences that they have accumulated. In this way, the mode of evolutionary divergence between populations may have predictable consequences for the fitness of their hybrids, and so for the progress of speciation. To investigate these connections, we present a new analysis of hybridization under Fisher's geometric model, making few assumptions about the allelic effects that differentiate the hybridizing populations. Results show that the strength and form of postzygotic reproductive isolation (RI) depend on just two properties of the evolutionary changes, which we call the "total amount" and "net effect" of change, and whose difference quantifies the similarity of the changes at different loci, or their tendency to act in the same phenotypic direction. It follows from our results that identical patterns of RI can arise in different ways, since different evolutionary histories can lead to the same total amount and net effect of change. Nevertheless, we show how these estimable quantities do contain some information about the history of divergence, and that — thanks to Haldane's Sieve — the dominance and additive effects contain complementary information

Fitness Landscapes, Genetic Interactions, and the Fitness of Hybrids

When two genetically differentiated populations or species come into contact and interbreed, their hybrid offspring will contain a mosaic of the genetic variants characterising the parental lineages, re-arranged into novel combinations. The fitness of these hybrids is central to the evolution of reproductive isolation, but also plays an important role in conservation policy, and in crop and animal breeding. Fitness landscapes are simple mathematical models that generate a rich variety of context-dependent genetic interactions, making them a useful tool for studying the ways in which these interactions affect hybrid fitness. In this thesis, I will explore a particular fitness landscape model based on Fisher’s geometric model (Fisher, 1930), which provides a flexible yet tractable framework for modelling hybridisation. Throughout, I complement the analytical and simulation results with applications to published empirical data. First, I explore the fitness of F1 hybrids, and show how phenotypic dominance can generate a diverse range of outcomes. As the dominance effects at different loci are rarely expressed together during divergence, they are unlikely to be co-adapted. I show that, as a consequence, dominance generally reduces F1 fitness, closely resembling the effects of uniparental inheritance, Still, I predict the effects of dominance can also be beneficial, and this may help to explain transgressive hybrids that prosper in extreme environments. Next, I present results for hybrids of any type, based on a new and more general derivation of the model. I show that predictions can be expressed in terms of two distance measures capturing the net effect and total amount of evolutionary change in terms of additive and dominance effects, as well as their interaction. Each of these terms carries information about the history of divergence, telling us about the type, direction, and subject of selection respectively. Thinking about the long-term outcomes of hybridisation, I then investigate what we can learn from introgression line studies about coadaptation between alleles and the fixability of heterosis. Consolidating the classical theories of heterosis, I illustrate how this model generates complex genetic architectures characterised by transient overdominance. Finally, I present an extension of the model to arbitrary ploidy which lets us investigate the effects of dosage on hybrid fitness. Applying these predictions to published data, I show how they can help to explain repeatedly observed differences in patterns of heterosis and inbreeding depression between diploids and tetraploids.Wellcome Trust MRes+PhD programme in Mathematical Genomics and Medicine Cambridge School of Clinical Medicin

How does the mode of evolutionary divergence affect reproductive isolation?

When divergent populations interbreed, the outcome will be affected by the genomic and phenotypic differences that they have accumulated. In this way, the mode of evolutionary divergence between populations may have predictable consequences for the tness of their hybrids, and so for the progress of speciation. To investigate these connections, we present a new analysis of hybridization under Fisher's geometric model, making few assumptions about the allelic effects that differentiate the hybridizing populations. Results show that the strength and form of postzygotic reproductive isolation (RI) depend on just two properties of the evolutionary changes, which we call the "total amount" and "net effect" of change, and whose difference quantifies the similarity of the changes at different loci, or their tendency to act in the same phenotypic direction. It follows from our results that identical patterns of RI can arise in different ways, since different evolutionary histories can lead to the same total amount and net effect of change. Nevertheless, we show how these estimable quantities do contain some information about the history of divergence, and that - thanks to Haldane's Sieve - the dominance and additive effects contain complementary information.Wellcome Trust WT220023 and RG9277

Fisher’s geometric model as a tool to study speciation

Interactions between alleles and across environments play an important role in the fitness of hybrids, and are at the heart of the speciation process. Fitness landscapes capture these interactions and can be used to model hybrid fitness, helping us to interpret empirical observations and clarify verbal models. Here, we review recent progress in understanding hybridization outcomes through Fisher’s geometric model, an intuitive and analytically tractable fitness landscape that captures many fitness patterns observed across taxa. We use case studies to illustrate how the model parameters can be estimated from different types of data, and discuss how these estimates can be used to make inferences about the divergence history and genetic architecture. We also highlight some areas where the model's predictions differ from alternative incompatibility-based models, such as the snowball effect and outlier patterns in genome scans

Population Size and the Rate of Language Evolution: A Test Across Indo-European, Austronesian, and Bantu Languages

What role does speaker population size play in shaping rates of language evolution? There has been little consensus on the expected relationship between rates and patterns of language change and speaker population size, with some predicting faster rates of change in smaller populations, and others expecting greater change in larger populations. The growth of comparative databases has allowed population size effects to be investigated across a wide range of language groups, with mixed results. One recent study of a group of Polynesian languages revealed greater rates of word gain in larger populations and greater rates of word loss in smaller populations. However, that test was restricted to 20 closely related languages from small Oceanic islands. Here, we test if this pattern is a general feature of language evolution across a larger and more diverse sample of languages from both continental and island populations. We analyzed comparative language data for 153 pairs of closely-related sister languages from three of the world's largest language families: Austronesian, Indo-European, and Niger-Congo. We find some evidence that rates of word loss are significantly greater in smaller languages for the Indo-European comparisons, but we find no significant patterns in the other two language families. These results suggest either that the influence of population size on rates and patterns of language evolution is not universal, or that it is sufficiently weak that it may be overwhelmed by other influences in some cases. Further investigation, for a greater number of language comparisons and a wider range of language features, may determine which of these explanations holds true

Parasites and politics: Why cross-cultural studies must control for relatedness, proximity and covariation

A growing number of studies seek to identify predictors of broad-scale patterns in human cultural diversity, but three sources of non-independence in human cultural variables can bias the results of cross-cultural studies. First, related cultures tend to have many traits in common, regardless of whether those traits are functionally linked. Second, societies in geographical proximity will share many aspects of culture, environment and demography. Third, many cultural traits covary, leading to spurious relationships between traits. Here, we demonstrate tractable methods for dealing with all three sources of bias. We use cross-cultural analyses of proposed associations between human cultural traits and parasite load to illustrate the potential problems of failing to correct for these three forms of statistical non-independence. Associations between parasite stress and sociosexuality, authoritarianism, democracy and language diversity are weak or absent once relatedness and proximity are taken into account, and parasite load has no more power to explain variation in traditionalism, religiosity and collectivism than other measures of biodiversity, climate or population size do. Without correction for statistical non-independence and covariation in cross-cultural analyses, we risk misinterpreting associations between culture and environment

There is little evidence that spicy food in hot countries is an adaptation to reducing infection risk

Spicier food in hot countries has been explained in terms of natural selection on human cultures, with spices with antimicrobial effects considered to be an adaptation to increased risk of foodborne infection. However, correlations between culture and environment are difficult to interpret, because many cultural traits are inherited together from shared ancestors, neighbouring cultures are exposed to similar conditions, and many cultural and environmental variables show strong covariation. Here, using a global dataset of 33,750 recipes from 70 cuisines containing 93 different spices, we demonstrate that variation in spice use is not explained by temperature and that spice use cannot be accounted for by diversity of cultures, plants, crops or naturally occurring spices. Patterns of spice use are not consistent with an infection-mitigation mechanism, but are part of a broader association between spice, health, and poverty. This study highlights the challenges inherent in interpreting patterns of human cultural variation in terms of evolutionary pressures

Population size and the rate of language evolution: A test across indo-European, Austronesian, and Bantu Languages

What role does speaker population size play in shaping rates of language evolution? There has been little consensus on the expected relationship between rates and patterns of language change and speaker population size, with some predicting faster rates of change in smaller populations, and others expecting greater change in larger populations. The growth of comparative databases has allowed population size effects to be investigated across a wide range of language groups, with mixed results. One recent study of a group of Polynesian languages revealed greater rates of word gain in larger populations and greater rates of word loss in smaller populations. However, that test was restricted to 20 closely related languages from small Oceanic islands. Here, we test if this pattern is a general feature of language evolution across a larger and more diverse sample of languages from both continental and island populations. We analyzed comparative language data for 153 pairs of closely-related sister languages from three of the world's largest language families: Austronesian, Indo-European, and Niger-Congo. We find some evidence that rates of word loss are significantly greater in smaller languages for the Indo-European comparisons, but we find no significant patterns in the other two language families. These results suggest either that the influence of population size on rates and patterns of language evolution is not universal, or that it is sufficiently weak that it may be overwhelmed by other influences in some cases. Further investigation, for a greater number of language comparisons and a wider range of language features, may determine which of these explanations holds true

The diverse effects of phenotypic dominance on hybrid fitness.

Funder: British Columbia Graduate ScholarshipFunder: UBC International Work Learn AwardFunder: NSERC Canada Graduate ScholarshipFunder: Karen McKellin International Leader of Tomorrow AwardFunder: Killam Doctoral ScholarshipFunder: UBC Four Year FellowshipWhen divergent populations interbreed, their alleles are brought together in hybrids. In the initial F1 cross, most divergent loci are heterozygous. Therefore, F1 fitness can be influenced by dominance effects that could not have been selected to function well together. We present a systematic study of these F1 dominance effects by introducing variable phenotypic dominance into Fisher's geometric model. We show that dominance often reduces hybrid fitness, which can generate optimal outbreeding followed by a steady decline in F1 fitness, as is often observed. We also show that "lucky" beneficial effects sometimes arise by chance, which might be important when hybrids can access novel environments. We then show that dominance can lead to violations of Haldane's Rule (reduced fitness of the heterogametic F1) but strengthens Darwin's Corollary (F1 fitness differences between cross directions). Taken together, results show that the effects of dominance on hybrid fitness can be surprisingly difficult to isolate, because they often resemble the effects of uniparental inheritance or expression. Nevertheless, we identify a pattern of environment-dependent heterosis that only dominance can explain, and for which there is some suggestive evidence. Our results also show how existing data set upper bounds on the size of dominance effects. These bounds could explain why additive models often provide good predictions for later-generation recombinant hybrids, even when dominance qualitatively changes outcomes for the F1