Individual-based simulations of genome evolution with ancestry:The GenomeAdmixR R package

Hybridization between populations or species results in a mosaic of the two parental genomes. This and other types of genome admixture have received increasing attention for their implications in speciation, human evolution, Evolve and Resequence (E&R) and genetic mapping. However, a thorough understanding of how local ancestry changes after admixture and how selection affects patterns of local ancestry remains elusive. The complexity of these questions limits analytical treatment, but these scenarios are specifically suitable for simulation. Here, we present the R package GenomeAdmixR, which uses an individual-based model to simulate genomic patterns following admixture forward in time. GenomeAdmixR provides user-friendly functions to set up and analyse simulations under evolutionary scenarios with selection, linkage and migration. We show the flexible functionality of the GenomeAdmixR workflow by demonstrating (a) how to design an E&R simulation using GenomeAdmixR and (b) how to use GenomeAdmixR to verify analytical expectations following from the theory of junctions. GenomeAdmixR provides a mechanistic approach to explore expected genome responses to realistic admixture scenarios. With this package, we aim to aid researchers in testing specific hypotheses based on empirical findings involving admixing populations

Inferring the role of habitat dynamics in driving diversification: evidence for a species pump in Lake Tanganyika cichlids

Geographic isolation that drives speciation is often assumed to slowly increase over time, for instance through the formation of rivers, the formation of mountains or the movement of tectonic plates. Cyclic changes in connectivity between areas may occur with the advancement and retraction of glaciers, with water level fluctuations in seas between islands or in lakes that have an uneven bathymetry. These habitat dynamics may act as a driver of allopatric speciation and propel local diversity. Here we present a parsimonious model of the interaction between cyclical (but not necessarily periodic) changes in the environment and speciation, and provide an ABC-SMC method to infer the rates of allopatric and sympatric speciation from a phylogenetic tree. We apply our approach to the posterior sample of an updated phylogeny of the Lamprologini, a tribe of cichlid fish from Lake Tanganyika where such cyclic changes in water level have occurred. We find that water level changes play a crucial role in driving diversity in Lake Tanganyika. We note that if we apply our analysis to the Most Credible Consensus (MCC) tree, we do not find evidence for water level changes influencing diversity in the Lamprologini, suggesting that the MCC tree is a misleading representation of the true species tree. Furthermore, we note that the signature of habitat dynamics is found in the posterior sample despite the fact that this sample was constructed using a species tree prior that ignores habitat dynamics. However, in other cases this species tree prior might erase this signature. Hence we argue that in order to improve inference of the effect of habitat dynamics on biodiversity, phylogenetic reconstruction methods should include tree priors that explicitly take into account such dynamics

What lies beneath?:How patterns in ecology and evolution inform us about underlying processes

In mijn thesis heb ik mij gefocused op het begrijpen van processen in ecologie en evolutie door te kijken naar patronen die worden veroorzaakt door deze processen, en door gebruik te maken van computer modellen om deze ptaronen te reproduceren. Gebruik makend van de verdeling van soorteneigenschappen heb ik achterhaald dat de soortensamenstelling van bomen op de savanne en van cichliden voor het grootste deel afhankelijk zijn van willekeurige verspreiding. Daarnaast blijkt dat de specifieke manier van verspreiding ook van grote invloed is op de soortensamenstelling van het tropisch regenwoud. Om fylogenien te mogen gebruiken om diversificatie analyse te kunnen doen, heb ik eerst geconstroleerd of het diversificatie model dat word gebruikt bij de reconstructive van een fylogenie van invloed is op latere diversificatie schattingen. Daarnaast heb ik verschillende statistieken die beschikbaar zijn voor Approximate Bayesian Computation (ABC) getest. Het blijkt dat het diversificatie model dat word gebruikt bij de reconstructie van een fylogenie niet van invloed is op latere schattingen, en het blijkt dat de huidige statistieken die worden gebruikt in ABC zeer slecht functioneren, en we hebben daarom een nieuwe statistiek geintroduceerd: de nLTT. Gebruikmakend van de nLTT hebben we vervolgens geprobeerd uit de fylogenie van cichliden uit het Tanganyika meer te achterhalen wat de impact is geweest van schommelingen in het waterniveau van het meer. Opvallend genoeg waren we niet in staat om hiervoor duidelijke aanwijzingen te vinden. Concluderend vind ik dat computationele kracht meer en meer belangrijk word, en denk ik dat we nog maar aan het begin staan van een hele nieuwe tak van theoretische biologie

Haplotype block dynamics in hybrid populations

When species originate through hybridization, the genomes of the ancestral species are blended together. Over time genomic blocks that originate from either one of the ancestral species accumulate in the hybrid genome through genetic recombination. Modeling the accumulation of ancestry blocks can elucidate processes and patterns of genomic admixture. However, previous models have ignored ancestry block dynamics for chromosomes that consist of a discrete, finite number of chromosomal elements. Here we present an analytical treatment of the dynamics of the mean number of blocks over time, for continuous and discrete chromosomes, in finite and infinite populations. We describe the mean number of haplotype blocks as a universal function dependent on population size, the number of genomic elements per chromosome, the number of recombination events, and the initial relative frequency of the ancestral species

Nucleotide Substitutions during Speciation may Explain Substitution Rate Variation

Abstract Although molecular mechanisms associated with the generation of mutations are highly conserved across taxa, there is widespread variation in mutation rates between evolutionary lineages. When phylogenies are reconstructed based on nucleotide sequences, such variation is typically accounted for by the assumption of a relaxed molecular clock, which is a statistical distribution of mutation rates without much underlying biological mechanism. Here, we propose that variation in accumulated mutations may be partly explained by an elevated mutation rate during speciation. Using simulations, we show how shifting mutations from branches to speciation events impacts inference of branching times in phylogenetic reconstruction. Furthermore, the resulting nucleotide alignments are better described by a relaxed than by a strict molecular clock. Thus, elevated mutation rates during speciation potentially explain part of the variation in substitution rates that is observed across the tree of life. [Molecular clock; phylogenetic reconstruction; speciation; substitution rate variation.

Modelling the spatial dynamics of oncolytic virotherapy in the presence of virus-resistant tumor cells

Oncolytic virotherapy is a promising form of cancer treatment that uses native or genetically engineered viruses to target, infect and kill cancer cells. Unfortunately, this form of therapy is not effective in a substantial proportion of cancer patients, partly due to the occurrence of infectionresistant tumor cells. To shed new light on the mechanisms underlying therapeutic failure and to discover strategies that improve therapeutic efficacy we designed a cell-based model of viral infection. The model allows to investigate the dynamics of infection-sensitive and infection-resistant cells in tumor tissue in presence of the virus. To reflect the importance of the spatial configuration of the tumor on the efficacy of virotherapy, we compare three variants of the model: two 2D models of a monolayer of tumor cells and a 3D model. In all model variants, we systematically investigate how the therapeutic outcome is affected by properties of the virus (e.g. the rate of viral spread), the tumor (e.g. production rate of resistant cells, cost of resistance), the healthy stromal cells (e.g. degree of resistance to virus) and the timing of treatment. We find that various therapeutic outcomes are possible when resistant cancer cells arise at low frequency in the tumor. These outcomes depend in an intricate but predictable way on the death rate of infected cells, where faster death leads to rapid virus clearance and cancer persistence. Our simulations reveal three different causes of therapy failure: rapid clearance of the virus, rapid selection of resistant cancer cells, and a low rate of viral spread due to the presence of infection-resistant healthy cells. Our models suggest that improved therapeutic efficacy can be achieved by sensitizing healthy stromal cells to infection, although this remedy has to be weighed against the toxicity induced in the healthy tissue

From Fossils to Living Canids:Two Contrasting Perspectives on Biogeographic Diversification

he Canidae are an ecologically important group of dog-like carnivores that arose in North America and spread across the planet around 10 million years ago. The current distribution patterns of species, coupled with their phylogenetic structure, suggest that Canidae diversification may have occurred at varying rates across different biogeographic areas. However, such extant-only analyses undervalued the group’s rich fossil history because of a limitation in method’s development. Current State-dependent Speciation and Extinction (SSE) models are (i) often parameter-rich which hinders reliable application to relatively small clades such as the Caninae (the only extant subclade of the Canidae consisting of 36 extant species); and (ii) often assume as possible states only the states that extant species present. Here we extend the SSE method SecSSE to apply to phylogenies with extinct species as well (111 Caninae species) and compare the results to those of analyses with the extant-species-only phylogeny. The results on the extant-species tree suggest that distinct diversification patterns are related to geographic areas, but the results on the complete tree do not support this conclusion. Furthermore, our extant-species analysis yielded an unrealistically low estimate of the extinction rate. These contrasting findings suggest that information from extinct species is different from information from extant species. A possible explanation for our results is that extinct species may have characteristics (causing their extinction), which may be different from the characteristics of extant species that caused them to be extant. Hence, we conclude that differences in biogeographic areas probably did not contribute much to the variation in diversification rates in Caninae

Detecting phylodiversity-dependent diversification with a general phylogenetic inference framework

Diversity-dependent diversification models have been extensively used to study the effect of ecological limits and feedback of community structure on species diversification processes, such as speciation and extinction. Current diversity-dependent diversification models characterise ecological limits by carrying capacities for species richness. Such ecological limits have been justified by niche filling arguments: as species diversity increases, the number of available niches for diversification decreases.However, as species diversify they may diverge from one another phenotypically, which may open new niches for new species. Alternatively, this phenotypic divergence may not affect the species diversification process or even inhibit further diversification. Hence, it seems natural to explore the consequences of phylogenetic diversity-dependent (or phylodiversity-dependent) diversification. Current likelihood methods for estimating diversity-dependent diversification parameters cannot be used for this, as phylodiversity is continuously changing as time progresses and species form and become extinct.Here, we present a new method based on Monte Carlo Expectation-Maximization (MCEM), designed to perform statistical inference on a general class of species diversification models and implemented in the R package emphasis. We use the method to fit phylodiversity-dependent diversification models to 14 phylogenies, and compare the results to the fit of a richness-dependent diversification model. We find that in a number of phylogenies, phylogenetic divergence indeed spurs speciation even though species richness reduces it. Not only do we thus shine a new light on diversity-dependent diversification, we also argue that our inference framework can handle a large class of diversification models for which currently no inference method exists