PhD Topics 2017

Please note: Application for topics marked with •+ is preferred for the present call and interested applicants will be treated with priority in the ranking.

•+ Evolution of gene expression summary

•+ Understanding thermal adaptation summary

•+ The impact of new transposable element insertions on adaptation to a new environment summary

Wolbachia infection dynamics in evolving Drosophila populations summary

•+ The adaptive value of diversity produced by recurrent whole genome doubling summary

•+• Epigenetic variation in Arabidopsis summary

•+• Suggested project: Genetic footprints of adaptive introgression (student input in project choice and design welcome) summary

•+• Statistical inference concerning population genetic parameters from repeated genomic measurement data summary

•+• New methods for modelling and analysis of data from experimental evolution summary

•+• Maximum likelihood inference of population genetic parameters using genome-wide data summary

•+• Macroevolutionary dynamics of selfish DNA unravelled by third generation sequencing summary

•+• Dynamics of a selfish DNA invasion summary

•+• Evolution of bird sex chromosomes summary

Population trees and polymorphism-aware phylogenetic models summary

Topics

 

•+• Evolution of gene expression

Principal advisor: Christian Schlötterer

While variation in gene expression is a major source of phenotypic diversity, our understanding of the processes driving changes in gene expression are still poorly understood. With the new sequencing technologies it will be possible to address many important questions about the evolution of gene expression.

The successful candidate will be part of a team of scientists studying adaptation of experimental Drosophila populations to temperature stress. She/he can build on several highly replicated Drosophila populations that have evolved under various temperature regimes.  We are planning to address the importance of plasticity in gene expression for adaptation to novel temperature regimes and how expression differences translate into fitness.

Background:

1: Jaksic, A.M., and Schlötterer, C. (2016). The interplay of temperature and genotype on patterns of alternative splicing in Drosophila melanogaster. Genetics 204, 315-325.

2: Chen, J., Nolte, V., and Schlötterer, C. (2015a). Temperature stress mediates decanalization and dominance of gene expression in Drosophila melanogaster. PLoS Genetics 11, e1004883. 10.1371

3: Chen, J., Nolte, V., and Schlötterer, C. (2015b). Temperature related reaction norms of gene expression: regulatory architecture and functional implications. Molecular Biology and Evolution 32, 2393-2402.

 

•+• Understanding thermal adaptation

Principal advisor: Christian Schlötterer

We are using experimental evolution to study the evolutionary response of natural Drosophila populations when they encounter a novel thermal environment. The successful candidate will have access to highly replicated Drosophila experimental evolution data, which have been cultivated by more than 60 generations. Using Pool-Seq data from multiple time points and experimentally phased haplotype data, the successful candidate will characterize the adaptive genomic landscape. Combining the genomic selection signatures with fitness measurements and gene expression data, the project will determine the repeatability of evolution in the experimental populations.

Background:

1: Franssen, S.U., Barton, N.H., and Schlötterer, C. (2016). Reconstruction of haplotype-blocks selected during experimental evolution. Molecular biology and evolution, in press

2: Schlötterer, C., Kofler, R., Versace, E., Tobler, R., and Franssen, S.U. (2015). Combining experimental evolution with next-generation sequencing: a powerful tool to study adaptation from standing genetic variation. Heredity 114, 431-440.

3: Schlötterer, C., Tobler, R., Kofler, R., and Nolte, V. (2014). Sequencing pools of individuals - mining genome-wide polymorphism data without big funding. Nature reviews Genetics 15, 749-763.

4: Orozco-terWengel, P., Kapun, M., Nolte, V., Kofler, R., Flatt, T., and Schlötterer, C. (2012). Adaptation of Drosophila to a novel laboratory environment reveals temporally heterogeneous trajectories of selected alleles. Molecular ecology 21, 4931-4941.

 

•+• The impact of new transposable element insertions on adaptation to a new environment

Principal advisor: Christian Schlötterer

This project builds on a Drosophila simulans population in which the P-element has recently invaded. Using experimental evolution 10 replicate populations are adapting to novel temperature environments. Since the P-element is highly active in these populations, many new TE insertions are occurring during the experiment. Taking advantage of time-series Pool-Seq data the successful candidate will study the dynamics of novel TE insertions and test to what extent they are beneficial (i.e. contribute to adaptation) or deleterious. The results of this experiment will be compared to another D. simulans population, which evolves to the same environment, but the P-element is absent.

Background:

1: Kofler, R., Gomez-Sanchez, D., and Schlötterer, C. (2016). PoPoolationTE2: Comparative Population Genomics of Transposable Elements Using Pool-Seq. Molecular biology and evolution 33, 2759-2764.

2: Kofler, R., Hill, T., Nolte, V., Betancourt, A.J., and Schlötterer, C. (2015a). The recent invasion of natural Drosophila simulans populations by the P-element. Proceedings of the National Academy of Sciences of the United States of America 112, 6659-6663.

3: Kofler, R., Nolte, V., and Schlötterer, C. (2015b). Tempo and Mode of Transposable Element Activity in Drosophila. PLoS Genetics 11, e1005406.

 

Wolbachia infection dynamics in evolving Drosophila populations

Principal advisor: Christian Schlötterer

Wolbachia are intracellular α-Proteobacteria found in insect, filarial nematode, mite and crustacean species. Previously, we have shown that Wolbachia strains differ in their relative fitness and that these fitness differences depend on the environment [1]. This project will use experimental evolution [2, 3] and next generation sequencing technology  in combination with population genetic modeling and functional Drosophila genetics to understand the evolutionary dynamics of an endosymbiont in an evolving host.

1 Versace E., et al. (2014) Experimental evolution reveals habitat-specific fitness dynamics among Wolbachia clades in Drosophila melanogaster. Molecular ecology 23, 802-814

2 Schlötterer C., et al. (2015) Combining experimental evolution with next-generation sequencing: a powerful tool to study adaptation from standing genetic variation. Heredity in press

3 Schlötterer C., et al. (2014) Sequencing pools of individuals - mining genome-wide polymorphism data without big funding. Nature reviews. Genetics 15, 749-763

 

•+• The adaptive value of diversity produced by recurrent whole genome doubling

Principal advisor: Ovidiu Paun

Whole genome doubling (WGD) and hybridization profoundly shaped plant genome evolution. However, most neopolyploids show poor fitness and fail to establish. To be successful, first generation allopolyploids must quickly adjust their genome and function, thereby altering their ecological properties and adaptive success, as a function of their environment. The duplicated nature of polyploids buffers more effectively deleterious alleles and provides genome-wide opportunities for adaptive evolution. Recurrent origins of polyploids are widespread and provide natural replicates to study mechanisms of rapid adaptation to divergent environments.

This project will combine molecular and ecological investigations in a fairly young polyploid complex in Dactylorhiza, comprising sibling terrestrial orchids with divergent ecological preferences. Specifically, to complement ongoing analyses of the nature of the extant molecular diversity in the D. majalis complex, we will interrogate the adaptive value of this diversity within reciprocal transplant experiments in the Alps and Scandinavia. We will shed light on the links between genotype, epigenotype and environmental conditions, by focusing on the environmental sensitivity of gene expression (with RNAseq) and of post-transcriptional regulation by small RNAs (with smRNAseq), exploring also in detail the link between DNA methylation patterns and expression of duplicated genes.

 

•+• Epigenetic variation in Arabidopsis

Principal advisor: Magnus Nordborg

It has long been argued that epigenetic transgenerational inheritance could play an important role in adaptation (as well as in breeding and human complex trait variation). However, while the existence of such inheritance is no longer in doubt (at least not in plants, where DNA methylation can clearly be inherited; see Grossniklaus et al. 2013; Heard and Martienssen 2014), evidence that it plays an adaptive role is mostly limited to geographic correlations between methylation and the environment that are suggestive of selection, but prove little (Verhoeven, vonHoldt, and Sork 2016).

Our recent studies in Arabidopsis thaliana have uncovered remarkable geographic patterns that will enable us to address this issue (Dubin et al. 2015; Kawakatsu et al. 2016). Analysis of the genomes, transcriptomes, and methylomes of over 1,000 natural inbred lines grown in the same environment revealed genome-wide variation in DNA methylation that was strongly correlated with the environment of origin of the lines — implying either that they carry an epigenetic memory of their ancestral environment, or that the divergence in methylation is simply due to genetics. These two explanations are not mutually exclusive. In support of the former, DNA methylation is known to be heritable; in support of the latter, genome-wide association studies (GWAS) and crosses revealed that much of the variation clearly has a genetic basis.

My lab is currently trying to determine the extent to which these two explanations are responsible for the observed patterns, i.e., their proximal cause. We also seek to elucidate their ultimate cause, i.e., the evolutionary mechanisms that lead to such strong environment correlations. Research will involve analysis of large genomic data sets, and the requisite skills are required.

Background:

Dubin, Manu J., Pei Zhang, Dazhe Meng, Marie-Stanislas Remigereau, Edward J. Osborne, Francesco Paolo Casale, Philipp Drewe, et al. 2015. “DNA Methylation in Arabidopsis Has a Genetic Basis and Shows Evidence of Local Adaptation.” Genomics. eLife 4 (May). doi:10.7554/eLife.05255.

Grossniklaus, Ueli, William G. Kelly, Bill Kelly, Anne C. Ferguson-Smith, Marcus Pembrey, and Susan Lindquist. 2013. “Transgenerational Epigenetic Inheritance: How Important Is It?” Nature Reviews. Genetics 14 (3): 228–35.

Heard, Edith, and Robert A. Martienssen. 2014. “Transgenerational Epigenetic Inheritance: Myths and Mechanisms.” Cell 157 (1). Elsevier Inc.: 95–109.

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.

Verhoeven, Koen J. F., Bridgett M. vonHoldt, and Victoria L. Sork. 2016. “Epigenetics in Ecology and Evolution: What We Know and What We Need to Know.” Molecular Ecology 25 (8): 1631–38.

 

•+• Suggested project: Genetic footprints of adaptive introgression (student input in project choice and design welcome)

Principal advisor: Joachim Hermisson

Background: In nature, diverged populations or incipient species can often still exchange genetic material. This is particularly interesting if species exchange adaptive genes. Recent research has shown that adaptive introgression is indeed an important source for new adaptations in many animal and plant species. In particular, it has been shown that there has been adaptive gene flow from archaic humans (such as Neanderthals or Denisovans) to ancient modern humans.

Project: Haplotype patterns after adaptive gene introgression. The aim of the planned project is to characterize the expected footprint of adaptive introgression and to develop statistical methods to detect such footprints in genome-wide polymorphism data. It has previously been shown that tests based on haplotype patterns are the most powerful ones to detect events of recent adaptation in human populations. We therefore will focus on the haplotype patterns generated by adaptive introgression. We will address question such as: What is the distribution of introgression tract lengths around the beneficial allele for a single successful introgression event? How many distinct pieces of introgressed material do we expect to find – and at which distance to the beneficial allele? How do linked deleterious alleles (which may either hitch-hike or not) affect these results? We will use analytical theory based on branching processes and coalescent simulations. Knowledge about the haplotype pattern is very relevant, in particular, to link any theoretical results to data. In the context of the graduate school, we will cooperate with Christian Schlötterer, who will study the introgression of single hot-temperature-adapted genotypes into a cold-adapted population under the hot selection regime. We will also apply the methods to Human data sets.

 

•+• Statistical inference concerning population genetic parameters from repeated genomic measurement data

Principal Advisor: Andreas Futschik

High dimensional data, such as those produced from DNA and RNA sequencing experiments lead to exciting new challenges for the field of statistics. The proposed project is connected to the modelling of such data. Existing statistical methods will need to be adapted and new methods developed.

This Ph.D. project will provide a motivated student with the opportunity to participate in such research, and to apply new methods to analyze real population genetic data.

Nowadays, population genetics relies to a large extent on the analysis of next generation sequencing data. Such data are challenging to handle as they are high dimensional. The sample size can be fairly large, when whole pools of organisms are simulated simultaneously. When individual organisms are sequenced separately, they tend to be considerably smaller. A further characteristic of such data is the complex error structure, with error components including the sampling from the population, genetic drift, as well as sequencing and alignment errors.  If whole pools of individuals are sequenced, this would add a further component of variance.  Statistical models have to take these error components properly into account, in order to provide valid conclusions. Previous publications by Futschik et al. deal with the proper estimation of population genetic parameters (such as the mutation rate, the effective population size, and the population recombination rate) under such a setting.

Project: An important issue is to disentangle local features such as selection from global features such as demography using genomic data at repeated time points. One question will be to estimate the proportion of the genome affected by selection. Empirical Bayes in the context of mixture models could be a promising approach to tackle such questions.  A further question will be to investigate how estimates of global parameters are affected by local model deviations e.g. due to selection. Subsequently we want to optimize the separation between local and global features in terms of the performance of estimates for global parameters.

 

•+• New methods for modelling and analysis of data from experimental evolution

Principal Advisor: Andreas Futschik

As sequencing data are becoming less and less expensive, experiments to investigate the genomic response to selection are carried out at larger and larger scales. At the Vienna Graduate School of Population Genetics such experiments are carried out using Drosophila as a model organism. These experiments typically involve replicate populations and look for instance at unusual allele frequency changes. A further typical feature of such experiments is that whole pools of individuals are sequenced together at several time points. With more and more data coming in, it became apparent that adaptive signals are often more complicated than initially anticipated. This leads to new interesting methodological challenges with the analysis of such data.

The goal of the project will be the evaluation of existing methods, as well as the development of new statistical methods that help to investigate the genetic response to selection pressure, as occurring for instance when populations adapt to new environments.

The successful applicant should have good programming skills. As this project will take place at the interface between statistics and population genetics, interest in both areas will be important. Some existing knowledge in one of these fields will be a plus, but can also be acquired during the course of the PhD studies.

 

•+• Maximum likelihood inference of population genetic parameters using genome-wide data

Principal advisor: Claus Vogl

Our aim is to infer population histories and population genetic parameters given population genetic data. With model species, such as Drosophila, or humans genome-wide sequencing  data of individuals or pools of individuals are available. We focus on genomic regions with relatively high recombination rates, such that individual nucleotide sites can be assumed to be independently and often also identically distributed. Such site data are typically represented as site frequency spectra (SFS). For a single population and in equilibrium, methods are available that allow for maximum likelihood inference of population genetic parameters given SFS. For multiple populations and outside of equilibrium, such methods are generally lacking. We develop maximum likelihood methods for exact inference of population genetic parameters, e.g., mutation, selection, and drift, given SFS. This involves probabilistic modeling similar to hidden Markov models, bioinformatic processing of genome-wide sequence data, and implementation of algorithms with the statistical programming language "R".

 

•+• Macroevolutionary dynamics of selfish DNA unravelled by third generation sequencing

Principal advisor: Robert Kofler

Few people are aware that our genomes are filled with parasites. These so called transposable elements (TEs) selfishly spread in our genomes and may even cause diverse diseases. TEs have been remarkably successful: they occur in all eukaryotic species and constitute about 50% of our genomes.

Despite the fundamental importance of TEs little is known about their long term evolution.

In this work we will sequence populations of closely related Drosophila species using the most recent long read technologies (PacBio and Oxford Nanopore). This will allow to unravel the evolutionary dynamics of TEs with unprecedented resolution and shed light on the following questions:

  • How fast are these parasites spreading in genomes?
  • Are invasions of these parasites influencing the large-scale evolution of genomes (e.g. inversions, translocations)?
  • How frequent is the invasion of a novel genomic parasite in the course of evolution?
  • Can we also find evidence for the death of a TE?

This work will allow the student to get in contact with cutting edge sequencing technologies, shed light on the evolution of genomes within a young and international team and receive a first-rate training in bioinformatics. The project will involve 20% lab-work and 80% computer work. Some programming skills (e.g. R or Python) and some wet-lab experience (e.g. PCR) would be beneficial.

 

•+• Dynamics of a selfish DNA invasion

Principal advisor: Robert Kofler

Few people are aware that our genomes are filled with parasites. These so called transposable elements (TEs) selfishly spread in our genomes and may even cause diverse diseases. TEs have been remarkably successful: they occur in all eukaryotic species and constitute about 50% of our genomes.

TEs are also known to frequently invade novel species by horizontal transfer. They rapidly spread within afflicted populations, while the hosts struggle to contain their spread in order to avert major damage. However, after some time most hosts succeed in controlling the invasion of a TE, but it is largely unknown how this is exactly achieved. To shed light on this  we will investigate TE invasions at high resolution using cutting edge technologies such as small RNA sequencing, RNA-Seq, phenotypic assays and Pool-Seq.

This work will allow the student to shed light on the invasion of parasitic DNA within a young and international team, get in contact with cutting-edge technologies and receive a first-rate training in bioinformatics. The project will involve 60% lab-work and 40% computer work. Some wet-lab experience (e.g. PCR) and programming skills (e.g. R or Python) would be beneficial.

 

•+• Evolution of bird sex chromosomes

Principal advisor: Qi Zhou

While mammals and fruitflies have XY sex chromosomes, birds and butterflies have ZW sex chromosomes. These are the two major genetic sex determination systems of all plants and animals. It has been proposed that both follow a similar evolution trajectory: on a pair of ancient autosomes, the emergence of master sex-determining gene has led to the suppression of recombination, so that the male-determining gene on the Y cannot recombine onto the X and then become inherited in female, and the same for the female-determining gene on the W. As a result, the non-recomning Y/W chromosome suffers genetic degeneration and has lost most functional genes except for those with sex-determining roles. However, recent characterization of 50 birds’ genomes showed a different story: about half of the studied species’ W chromosomes are not highly degenerated as previously assumed.

This project aims to address the degree and the cause of genetic differentiation between the avian sex chromosomes. The successful candidate has the chance to work on the unpublished 200 avian genomes, as an independent project under the framework of avian genomics consortium. The consortium plans to sequence all the 10,000 bird species’ genomes in the next five years, and this is one of the planned second-phase work (https://b10k.genomics.cn/index.html). Thus the preferred candidate should have basic bioinformatic skills and some experience of comparative genomics.

 

Population trees and polymorphism-aware phylogenetic models

Principal advisor: Carolin Kosiol

By modelling genome evolution as a process by which a single genome sequence mutates along the branches of a species phylogeny, standard phylogenetic methods reduce the entire populations to single points in genotypic space. In reality, each population consists of many individuals that are related by trees of genetic ancestry known as genealogies.

Some progress has been made towards the estimation of the population/species tree under a coalescent theoretic set up. For the neutral case, it is already possible to estimate population trees (Lui and Perl, 2007; Hey, 2009, Yang & Rannala, 2010). However, these recent papers use Bayesian methods and MCMC techniques, which make an accurate estimation of parameters only possible for a few individuals from a few populations. These methods will not scale to estimate parameter-rich models such as codon models.

In my group, we have developed an allele-frequency based approach called Polymorphism-Aware Phylogenetic Models (PoMo, De Maio, et al., 2013). While standard phylogenetic models treat substitutions as instantaneous events, PoMo describes them as gradual: substitutions require first a mutation introducing a new rare allele, followed by a series of changes in allele frequency. This innovation accounted for many problems in classical phylogenetics, such as incomplete lineage sorting and shared ancestral polymorphisms that cause the tree topology to vary along the genome. In this project, we plan to expand this approach to infer population trees that can be used for molecular dating as well as model of character evolution that allow for polymorphism in traits along the tree.

 

 

FWF - Der Wissenschaftsfond Partner: FWF - Der Wissenschaftsfond
Vetmed Uni Vienna Partner: Vetmed Uni Vienna
Max F. Perutz Laboratories Partner: Max D. Perutz Laboratories
Gregor Mendel Institut Partner: Gregor Mendel Institute
Uniwien Partner: Uniwien