- Evolution from de novo mutations - influence of elevated mutation rates. Summary
- Evolution of sex-specific neuronal signaling. Summary
- Genome evolution in columbines. Summary
- Inference of selection signatures from time-series data. Summary
- Long-term dynamics of local Drosophila populations. Summary
- Molecular evolution of coding sequences. Summary
- Molecular genetics of epigenetics. Summary
- PoPoolation3. Summary
- Seed ecology. Summary
- Structural variation and genome evolution. Summary
- Temperature adaptation in Drosophila: phenotypic adaptation. Summary
- The sources of diversity shaping adaptive radiation. Summary
- Understanding polygenic adaptation. Summary
Evolution from de novo mutations - influence of elevated mutation rates
Advisor: C. Schlötterer
Most new mutations are deleterious and will be purged from evolving populations. This PhD project will evaluate how a genetically identical population of fruit flies can adapt to a new polygenic phenotype by novel mutations. By contrasting populations with different mutation rates and population sizes this project seeks to characterize the adaptive response of a polygenic trait. Since only a few mutations are expected to be beneficial, this project provides the opportunity to identify and characterize individual alleles contributing to a highly polygenic trait.
The project is particularly well-suited for students with a keen interest to combine experimental fly work with state of the art bioinformatic analyses characterizing the trajectories of selected alleles. Candidates are provided the opportunity to test beneficial alleles in transgenic assays. Experience with CRISPR/Cas9 is beneficial for the functional characterization, but not required for the project.
Evolution of sex-specific neuronal signaling
Advisor: C. Schlötterer
Previous work showed that neuronal signaling evolved in Drosophila simulans from Florida in response to a new temperature regime. Interestingly, this evolutionary response occurred in a sex-specific manner: males and females modified different signaling pathways.
This PhD project will use a combination of single cell RNA-Seq and behavioral analyses to identify the selective forces driving this sex specific signaling. A comparison to flies from other populations and species that evolved under the same selection regime will inform us to what extent this evolutionary response is population specific or provides a general temperature adaptation.
Future PhD students should have a vivid interest in exploring new data analyses and develop new innovative phenotyping methods.
- Hsu SK, Jaksic AM, Nolte V, Lirakis M, Kofler R, Barghi N, Versace E, Schlötterer C. 2020. Rapid sex-specific adaptation to high temperature in Drosophila. Elife 9.
- Jaksic AM, Karner J, Nolte V, Hsu SK, Barghi N, Mallard F, Otte KA, Svecnjak L, Senti KA, Schlötterer C. 2020. Neuronal function and dopamine signaling evolve at high temperature in Drosophila. Molecular biology and evolution doi:10.1093/molbev/msaa116.
Genome evolution in columbines
Advisor: M. Nordborg
Initial analysis of the columbine (Aquilegia sp.) genome yielded a remarkable discovery — one of the chromosomes harbored twice the level of polymorphism of the other chromosomes, and also showed strong evidence of having a different evolutionary history than the other chromosomes (Filiault et al. 2018). We believe the key to understanding this phenomenon lies in understanding the structure of the genome better, and a first step towards doing this is generating and analyzing better genomes sequences using long-read sequencing technology.
The project is suitable for someone interested in learning genomics, bioinformatics, and genome analysis using cutting-edge technology.
- Filiault, Danièle L., Evangeline S. Ballerini, Terezie Mandáková, Gökçe Aköz, Nathan J. Derieg, Jeremy Schmutz, Jerry Jenkins, et al. 2018. “The Aquilegia Genome Provides Insight into Adaptive Radiation and Reveals an Extraordinarily Polymorphic Chromosome with a Unique History.” eLife 7 (October). https://doi.org/10.7554/eLife.36426.
Inference of selection signatures from time-series data
Advisor: C. Schlötterer
Molecular population genetics has a long-standing tradition to infer selection signatures from genomic data. Most of the developed methods rely either on a single population or the contrast of multiple populations with different selection pressure in the past. With the increasing availability of time series data from ancient DNA and experimental evolution, it has become possible to study time-series data. Hence, the temporal pattern of allele frequency changes provides extremely rich information to distinguish selection from neutral patterns. This PhD project builds on an exceptionally powerful experimental evolution study, with 15 replicate Drosophila populations adapting to a novel environment for more than 100 generations. Genomic data are available in 10 generation intervals to study the allele frequency trajectories at high temporal resolution.
The future PhD student will have the opportunity to analyze the best time series data set available for a sexual organism. Hence, experience with handling large data sets is clearly a benefit and candidates with a keen interest to advance currently available statistical methods to analyze time-series data are particularly welcome to apply.
- Vlachos, C. Burny, C., Pelizzola, M., Borges, R., Futschik, A., Kofler, R. & Schlötterer, C. Benchmarking software tools for detecting and quantifying selection in evolve and resequencing studies. Genome Biology 20, 169, doi:10.1186/s13059-019-1770-8 (2019).
- Taus, T., Futschik, A. & Schlötterer, C. Quantifying Selection with Pool-Seq Time Series Data. Molecular Biology and Evolution 34, 3023-3034, doi:10.1093/molbev/msx225 (2017).
- Barghi, N., Tobler, R., Nolte, V., Jakšić, A. M., Mallard, F., Otte, K. A., Dolezal, M., Taus, T., Kofler, R. & Schlötterer, C. Genetic redundancy fuels polygenic adaptation in Drosophila. PLoS Biology 17, e3000128, doi:10.1371/journal.pbio.3000128 (2019).
Long-term dynamics of local Drosophila populations
Advisor: C. Schlötterer
Most inference of adaptation in natural populations is either based on genomic polymorphisms patterns of a single population or the contrast between populations adapted to different environments. Since time series data provide a very powerful approach to distinguish selection from other evolutionary forces changing allele frequencies, longitudinal sampling of a single population provides a hitherto underexplored approach to study the evolutionary dynamics of natural populations. The future PhD student will be granted access to an unique collection of samples covering more than 10 years with multiple samples throughout the entire season. This outstanding data set will provide new insights in the dynamics of local populations and their evolutionary response to a changing climate.
This project is particularly well suited for PhD students with a background in population genetics, who are interested to develop new cutting edge data analyses that incorporate time series data to distinguish selection from other forces. Whole genome polymorphism Pool-Seq data will be available as well as sequence data from individual flies to facilitate haplotype-based analyses.
Advisor: R. Borges
A major goal in evolutionary biology is to understand the forces that operate in the genomic sequences and are responsible for the adaptation of species to different environments. Codon models are one of the main tools used to infer selection on protein-coding genes. These have been popularized in comparative genomic studies by their extensive use in genome-wide scans of natural selection. However, current models of codon evolution have significant limitations that are increasingly being recognized. The main one being that current codon models make simplistic assumptions about the evolutionary process. This Ph.D. project seeks to develop a new codon evolution model to detect signatures of natural selection on protein-coding sequences. By properly reconciling the neutral and adaptive processes by which coding sequences evolve, the models and methods developed in this project will allow us to tell apart the sole action of natural selection from known confounding forces (e.g., fluctuating demography and GC-biased gene conversion). This project will ultimately contribute to better understanding the dynamics of adaptation during species divergence.
The project is particularly well-suited for students with a keen interest in computational biology, phylogenetics, or population genetics. Prior experience in programming or statistics would be a plus.
- Sackton. Studying natural selection in the era of ubiquitous genomes. Trends Genet. 36, 792–803. 2020. DOI: 10.1016/j.tig.2020.07.008
- Borges, Szöllősi, Kosiol. Quantifying GC-biased gene conversion in great ape genomes using polymorphism-aware models. Genetics 212 (4), 1321-1336. 2019. DOI: 10.1534/genetics.119.302074
- Borges, Boussau, Szöllősi and Kosiol. Pervasive selection biases inferences of the species tree. bioRxiv. 2020. DOI: 10.1101/2020.07.30.228965
Molecular genetics of epigenetics
Advisor: M. Nordborg
In a series of papers, we have discovered remarkable genetic variation influencing patterns of DNA methylation, in particular of transposable elements (Kawakatsu et al. 2016; Sasaki et al. 2019). This work continues, and we are in particular interested in investigating the function of the identified polymorphisms using modern molecular genetics.
This project is for someone interested in the molecular genetics of epigenetics.
- Kawakatsu, Taiji, Shao-Shan Carol Huang, Florian Jupe, Eriko Sasaki, Robert J. Schmitz, Mark A. Urich, Rosa Castanon, et al. 2016. “Epigenomic Diversity in a Global Collection of Arabidopsis Thaliana Accessions.” Cell 166 (2): 492–505.
- Sasaki, Eriko, Taiji Kawakatsu, Joseph R. Ecker, and Magnus Nordborg. 2019. “Common Alleles of CMT2 and NRPE1 Are Major Determinants of CHH Methylation Variation in Arabidopsis Thaliana.” PLoS Genetics 15 (12): e1008492.
Advisors: R. Kofler and C. Schlötterer
Sequencing pools of individuals (Pool-Seq) is a widely used approach to estimate the levels of polymorphism in populations, identify selected loci and unravel patterns of molecular adaptation in experimentally evolving populations. It has even been used to identify driving mutations in cancer tissues. Due to this popularity, many software tools for the analysis of Pool-Seq data have been developed. Especially our tools PoPoolation1 and PoPoolation2 are widely used, with each receiving about 100 citations per year. We have several novel ideas to streamline and enhance the functionality of these two tools. In this Ph.D. project, you will thus have the opportunity to develop PoPoolation3, which will merge the functionality of PoPoolation1/2, allow for external SNP callers, support Unix style command piping, rely on improved file formats, and implement novel functions important for population genetics. PoPoolation3 will support multi-threading and be implemented in Julia, an emerging high-performance language for large-scale data analysis. We also plan to draw on the experience of the wide user base of PoPoolation1/2 and involve the community in important design decisions and in prioritizing novel functions for PoPoolation3. With the improved usability and functionality, we are confident that PoPoolation3 will be even more popular than its two predecessors. You will thus have the opportunity to develop a software that may be a cornerstone of future population genetics data analysis.
Advisor: M. Nordborg
The seed stage plays a crucial role in plant life history, in particular via dispersal and the ability to survive harsh environmental conditions. Studies in the model plant Arabidopsis thaliana have revealed tremendous variation in both dormancy and seed size — as well as some of the genetic polymorphisms that underlie these traits (Kerdaffrec et al. 2016). This project seeks to establish fitness consequences through field experiments, as well as investigate the genetic basis further using GWAS and molecular genetics.
The project is suitable for someone who wants to do cutting-edge genetics of ecologically important traits.
- Kerdaffrec, Envel, Danièle L. Filiault, Arthur Korte, Eriko Sasaki, Viktoria Nizhynska, Ümit Seren, and Magnus Nordborg. 2016. “Multiple Alleles at a Single Locus Control Seed Dormancy in Swedish Arabidopsis.” eLife 5 (December): e22502.
Structural variation and genome evolution
Advisor: M. Nordborg
In a continuation of the 1001 Arabidopsis Genomes project (1001 Genomes Consortium 2016), we are sequencing a couple of hundred genomes of Arabidopsis thaliana using long-read sequencing technology. This project is providing an unprecedented resource for studying structural variation into structural variation, and there is room for people working on methods for describing such variation, as well as investigating their origin and function.
This project requires serious interest in computational biology and molecular evolution.
- 1001 Genomes Consortium. 2016. “1,135 Genomes Reveal the Global Pattern of Polymorphism in Arabidopsis Thaliana.” Cell 166 (2): 481–91.
Temperature adaptation in Drosophila: phenotypic adaptation
Advisor: C. Schlötterer
In the wake of global warming, adaptive strategies to cope with such environmental changes become essential for a broad range of organisms. We are using the genetic model organism Drosophila to study the adaptive strategies. This PhD project will characterize the phenotypic changes required for fruit flies to be successful at high temperatures and integrate the phenotypic data with available genomic and transcriptomic data. The future PhD student take advantage of highly replicated experimental populations, from three Drosophila species, which evolved for more than 60 generations in a novel hot temperature regime. We will determine population and species-specific phenotypic responses to laboratory induced climatic change.
The future PhD student is expected to have a vivid interest to develop and establish new phenotyping methods.
- Kellermann, V., Hoffmann, A. A., Kristensen, T. N., Moghadam, N. N. & Loeschcke, V. Experimental evolution under fluctuating thermal conditions does not reproduce patterns of adaptive clinal differentiation in Drosophila melanogaster. Am Nat 186, 582-593, doi:10.1086/683252 (2015).
- Hsu, S. K., Jakšić, A. M., Nolte, V., Lirakis, M., Kofler, R., Barghi, N., Versace, E. & Schlötterer, C. Rapid sex-specific adaptation to high temperature in Drosophila. Elife 9, doi:10.7554/eLife.53237 (2020).
- Mallard, F., Nolte, V., Tobler, R., Kapun, M. & Schlötterer, C. A simple genetic basis of adaptation to a novel thermal environment results in complex metabolic rewiring in Drosophila. Genome Biology 19, 119, doi:10.1186/s13059-018-1503-4 (2018).
The sources of diversity shaping adaptive radiation
Advisor: O. Paun
Island biotas often feature diverse groups of closely related species, which take advantage of an array of niches, but are mostly the result of one to few colonization events followed by rapid diversification. In the case of remote oceanic archipelagos, the initial founder populations are likely to have an extreme size, with close to no variation that can be selected to result in novel and diverse adaptations. A recent hypothesis proposes that adaptive genome evolution after long-distance dispersal can be fuelled as a by-product of activation of transposable elements (TE) that can drive dynamics at the level of genome structure, boost phenotypic variation and trigger adaptation to new environments. This project aims to tackle the sources of variation that prime functional diversity after extreme bottlenecks, thereby triggering fast adaptation and explosive functional diversification. We will test the hypothesis that structural variation and in particular the activation of mobile elements act as a springboard for phenotypic variation, and drive the amazing ecological breadth of a young radiation of ca 30 closely-related persimmon species (Diospyros) on New Caledonia, a biodiversity hotspot. Importantly, this radiating group is characterized by increased genome sizes and TE dynamics compared to relatives.
The future PhD student will be interested to study the origin of biodiversity, by combining cutting-edge genomic inferences with ecological and physiological data. Prior experience with genomic analyses would be a plus.
- Merot et al. 2020. A roadmap for understanding the evolutionary significance of structural genomic variation. Trends in Ecology and Evolution 35: 561-572 https://doi.org/10.1016/j.tree.2020.03.002
- Paun et al. 2016. Processes driving the adaptive radiation of a tropical tree (Diospyros, Ebenaceae) in New Caledonia, a biodiversity hotspot. Systematic Biology 65: 212-217. https://doi.org/10.1093/sysbio/syv076
Understanding polygenic adaptation
Advisor: C. Schlötterer
It is becoming increasingly clear that most adaptive traits are polygenic, with many loci contributing to the new phenotypic optimum. The identification and characterization of the causative genes of these polygenic traits is difficult in natural populations because the selection signature is too weak at individual loci and can be only seen when the contributing loci are analyzed jointly. In experimental evolution studies, the combination of high replication with moderate population sizes provides an almost unique opportunity to study polygenic adaptation at an unprecedented level. This PhD project will further advance the characterization of polygenic adaptation by taking advantage of a new experimental design which builds on genetic redundancy, a key feature of polygenic adaptation.
The future PhD student will have experience with the analysis of large data sets and a keen interest to learn and apply new, state of the art statistical methods, such as Approximate Bayesian Computation and machine learning.
- Sella, G. & Barton, N. H. Thinking About the Evolution of Complex Traits in the Era of Genome-Wide Association Studies. Annu Rev Genomics Hum Genet 20, 461-493, doi:10.1146/annurev-genom-083115-022316 (2019).
- Pritchard, J. K., Pickrell, J. K. & Coop, G. The genetics of human adaptation: hard sweeps, soft sweeps, and polygenic adaptation. Current biology : CB 20, R208-215, doi:10.1016/j.cub.2009.11.055 (2010).
- Barghi, N. et al. Genetic redundancy fuels polygenic adaptation in Drosophila. PLoS Biology 17, e3000128, doi:10.1371/journal.pbio.3000128 (2019)