PhD Topics 2016

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

•+ Convergent and adaptive evolution during ecotype formation summary

•+ Wolbachia infection dynamics in evolving Drosophila populations summary

•+ Evolution of gene expression in Drosophila summary

•+ Optimizing novel, Next Generation Sequencing based, approaches for dissecting the genetic basis of complex traits summary 

•+ Evolution of the transposable element landscape in Drosophila summary

•+ Statistical inference for experimental evolution using pooled NGS data summary

 

Other topics:

Selfish mutations summary

Inferring  evolutionary trajectories from time series data summary

Functional characterization of beneficial alleles in Drosophila summary

Modified evolve and re-sequence design summary

 

Topics

 

•+• Convergent and adaptive evolution during ecotype formation

Principal advisor: Ovidiu Paun

Recent genomic evidence indicates repeated ecological divergence is a common process of species diversification. Parallel ecological divergence on the other hand offers invaluable natural replicates to study ecological speciation. This comparative genomics project will investigate Heliosperma veselskyi and H. pusillum, two young plant species characterized by clear morphological (hairy versus glabrous) and ecological (montane versus alpine, dry versus wet) differentiation. Despite this striking phenotypic divergence, a dataset of over 2,000 SNPs suggests at least five independent origins of H. veselskyi from H. pusillum. Crossing experiments and genomic data support the circumscription of both taxa within a single species. However, very low levels of recent gene flow are detectable between the two ecotypes. Metagenomic data suggests a significant difference in the pathogen load between the two habitats, which is hypothesized to be a strong barrier to gene flow.

Through the integration of genomic, transcriptomic, epigenetic and environmental data this project will interrogate the molecular basis of phenotypic differentiation and adaptation to divergent environments between the two ecotypes. We will also aim to understand what mechanisms are aiding the onset of reproductive isolation. Our working hypothesis is that due to short time since their divergence, quantitative rather than qualitative differences in gene expression translate to the phenotypic differentiation observed. The project will focus on six pairs of geographically close natural populations of the two ecotypes in the Alps. In addition, it will make use of transplantations, crossings, physiological and ecological experiments already started at the University of Innsbruck. Finally, we will specifically target the molecular components of the developmental pathway of trichomes, since they are an obvious phenotypic difference between the two ecotypes.

 

 

•+• 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

 

•+• Evolution of gene expression in Drosophila

Principal advisor: Christian Schlötterer

Evolution of gene expression in Drosophila

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. In this project the following aspects can be studied:

1) Evolution of sex-biased gene expression: are the differences in gene expression between males and females conserved among species?
2) Evolution of cis- and trans-effects: how does natural variation within and between species affect the regulation of gene expression?
3) Evolution of alternative splicing: to what extent do new splicing variants contribute to adaptation to different habitats?

 

•+• Optimizing novel, Next Generation Sequencing based, approaches for dissecting the genetic basis of complex traits

Principal advisor: Robert Kofler

Evolution acts on variation within species where qualitative variation, like eye color, and quantitative variation, like body size, can be distinguished. It is a major aim in biology to identify the molecular basis of this variation, that is to identify the genetic mutations that are responsible for differences between individuals. Such an enhanced understanding of variation will, for example, help to improve the yield of crop plants and allow to custom tailor medical treatment to the unique genetic make-up of a patient. While the genetic basis of most qualitative traits could be readily identified, revealing the genetic basis of quantitative traits remains a challenge, some even argue the major challenge for biology in the 21th century.

Novel approaches for mapping quantitative traits may help to meet this challenge. Recently, due to the advent of Next Generation Sequencing technologies, two new approaches for identifying the molecular basis of quantitative traits became feasible. In Evolve and Resequencing (E&R) studies molecular changes in experimentally evolving populations are monitored and with Pool-GWAS the genetic make-up of two groups of individuals, showing the most pronounced differences for a trait of interest (e.g. short versus tall specimens), is compared. Using computer simulations we will optimize the design and evaluate the strength and weaknesses of these novel approaches for unraveling the genetic basis of quantitative traits. This work will help researchers from many diverse fields to meet one of the major open questions in biology.

This is pure computational work and therefore a working knowledge of Unix and proficiency in at least one programming language would be highly advantageous.

 

•+• Evolution of the transposable element landscape in Drosophila summary

Principal advisor: Robert Kofler

We all know parasites. They live in our pets, in our beds and sometimes even in our hair. What most people however don't know: they also live in our genomes. These so called transposable elements (TEs) selfishly propagate within our genomes even if they cause negative effects to our health (e.g. cancer). Continued selfish activity has led to a gradual accumulation of TEs in our genome where they now constitute up to 60%. However, TEs are also a source of large-scale genomic rearrangements and are thus recognized as major drivers of genome evolution. 

Despite this importance for human diseases and genome evolution, little is known about the long term evolutionary dynamics of TEs. Why are TEs highly abundant in some species and almost absent in others? Why are some TEs going extinct in some species while others rapidly invade novel species? How frequent are TE-induced genomic rearrangement and what is the impact of TEs on the evolution of genomes? In this work we will address these open questions by investigating TE abundance in multiple related Drosophila species using state of the art sequencing technologies (Illumina, PacBio) and bioinformatics approaches.

This project will require about 10% lab-work and 90% computational-work. A strong interest in genome evolution and some computational skills (e.g. R, Python, Unix) would be highly advantageous.

 

•+• Statistical inference for experimental evolution using pooled NGS data

Principal Advisor: Andreas Futschik

Background: At the Institute of Population Genetics, Vetmeduni Vienna and other institutions, pool sequencing experiments are carried out. The statistical modeling of the resulting data usually requires special or at least adapted methodology. We plan to focus on experimental evolution, as this will permit for interactions within the DK (in particular with Christian Schlötterer and Carolin Kosiol). In experimental evolution, samples from an initial population are kept for several generations under different environmental conditions. The goal is to identify genomic targets of selection from sequencing data obtained from replicate experimental  populations at various time points (Kawecki et al., 2012). This can be done by studying allele frequency changes and investigating whether these changes are large enough to rule out drift, and the random errors induced by pool sequencing as possible explanations.

Project: As a first step, new strategies to model experimental evolution using pool-seq data will be investigated. An appropriate model needs to take all possible sources of variation into account: drift, sampling, and the pool sequencing process. While (Kofler and Schlötterer, 2014) used the CMH-test to scan for selection, we plan to consider repeated measurement and mixed effect models that also model the dependence structure across time. Based on theoretical considerations as well as simulations, we want to check whether our considered (Bayesian and frequentist) models incorporate the sources of variation adequately. We will then choose the best suited model, and analyze different design strategies for this model. The goal is to figure out, how resources can best be allocated in order to optimize the power when scanning for selection from standing variation. We will investigate the influence of issues such as the number of time points sequenced, the size of the sequenced sample, and the number of replicate populations. All these factors involve a trade-off between the cost of the experiment and the gain in accuracy. Besides theoretical derivations, simulations using the software package mimicree should also be useful. This package has been used by (Kofler and Schlötterer, 2014) in their CMH-test ased power-analysis. In cooperation with Carolin Kosiol’s group, we want to check whether the derived design guidelines also apply approximately to an alternative more complicated approach, Bayesian Gaussian process models, as proposed in Topa et al. (2014). We furthermore plan to investigate partial barcoding strategies: while less expensive than complete individual barcoding, adding genetic barcodes to a part of the pool permits to obtain additional information concerning common haplotypes such as those favored by selection. Furthermore, additional information concerning the amount of over-dispersion due to pool sequencing can be obtained which could be helpful in a subsequent data analysis.

 

Selfish mutations

Principal advisor: Irene Tiemann-Boege

New germline mutations arise randomly throughout the genome and are much rarer than somatic mutations. Yet, there are certain de novo mutations that are highly recurrent with a mutation rate orders of magnitude higher than genome average. These mutations have been discovered because they are associated with a phenotype such as a congenital disorder. Moreover, these mutations have a series of other associated characteristics. All are point mutations that result in a gain-of function change, they occur exclusively in the male germline and older men have a higher probability of having an affected child than younger males, known as the paternal age-effect (PAE). The mechanisms propagating these mutations are not well understood but in the last decade it was shown that for certain spontaneous congenital disorders that mutations can confer a selective advantage to spermatogonial stem cells caused by the mutant protein. Yet, there are still many open questions on how and to what extent mutations change germline stem-cell behavior, if all PAE mutations are driven by similar mechanisms, and whether other mechanisms such as apoptosis or cell-death counterbalance oncogenic expansions of mutant germline cells.

My group is interested in understanding the mutation mechanisms behind the paternal age effect. Of particular interest are mutations in FGFR3, a growth factor receptor with a role in many developmental processes. As such, several different mutations in this gene have been associated with a congenital disorder reported to have different degrees of phenotypic severity associated with a bigger dysfunctional tyrosine signaling activity in FGFR3. But also certain genes involved in neurodevelopmental disorders (e.g autism) for which a strong paternal age effect has been described, are of interest. So far, studying mutations has been extremely difficult given the lack of sensitivity of available assays. The Tiemann-Boege lab has developed a technique based on bead-emulsion amplification that can for the first time measure rare mutations at a very high sensitivity. We are also developing an ultrasensitive assay based on next-generation sequencing, known as duplex sequencing to screen rare mutations in nucleotides without a reported phenotype.

Through the integration of genomic, transcriptomic, epigenetic and environmental data this project aims to interrogate the molecular basis of phenotypic differentiation and adaptation to divergent environments between the two ecotypes. We will also aim to understand what mechanisms are aiding the onset of reproductive isolation. Our working hypothesis is that due to short time since their divergence, quantitative rather than qualitative differences in gene expression translate to the phenotypic divergence observed. The project will focus on six pairs of geographically close natural populations of the two ecotypes in the Alps. In addition, it will make use of large scale transplantations, crossings, physiological and ecological experiments already started at the University of Innsbruck. Finally, we will specifically target the molecular components of the developmental pathway of trichomes, since they are an obvious phenotypic difference between the two ecotypes.

 

Inferring evolutionary trajectories from time series data

Principal advisor: Carolin Kosiol

Recent advances in sequencing technologies have made it possible to observe evolutionary trajectories in great detail. In addition to sequencing the final generation of a population after long-term artificial selection, we can experimentally monitor genome evolution at intermediate generations. Such an Evolve and Re-sequencing (E&R) approach results in genome-wide time-series data.  The project will be based on previous work in the lab for which we developed a novel Gaussian Processes (GPs) approach to identify signatures of selection using the time-series data.  We plan to improve the GP approach by incorporating spatial information in particular linkage. Furthermore, we will also consider time-series of phenotypic data.

 

Functional characterization of beneficial alleles in Drosophila

Principal advisors: Kirsten-André Senti, Christian Schlötterer

One of the most amazing feats in biology is how natural selection enabled the adaption of species to different natural environments. Yet even a single Drosophila species thrives in diverse climates as equatorial Africa or Europe. From the natural variation within such species, we can – in principle - learn how evolution has shaped environmental adaption. Yet until recently finding the link between phenotype and genotype was a rare and difficult undertaking (1). However, today’s next generation sequencing offers an unprecedented view on the genetic variability. Combining phenotypic analyses with sequencing, Genome Wide Association Studies (GWAS) for instance enabled the identification of beneficial human alleles that protect against diseases (2).

Using paradigms such as starvation resistance and adaption to different temperatures, we have performed both GWAS as well as experimental evolution in combination with whole-genome re-sequencing of natural Drosophila populations (3). These experiments have established a number naturally occurring alleles that are associated with either increased survival under starvation stress or improved adaption to warmer or colder climates.

To validate these associations, we aim to employ the powerful CRISPR/Cas9 mediated genome engineering to functionally test if these natural gene variants indeed provide fitness advantages in well-controlled experimental settings. First, this project will establish a stable genome modification platform for natural Drosophila strains. Secondly, it will provide genetic and functional proof for beneficial adaptive alleles. Finally and in conjunction with our previous work, this approach will uncover those biological mechanisms that evolution tinkered with during adaption of natural populations.

1 Sawyer L.A., et al., (1997) Natural Variation in a Drosophila Clock Gene and Temperature Compensation. Science 278, 5346, 2117-2120

2 Harper A.R., et al. (2015) Protective alleles and modifier variants in human health and disease. Nature Reviews Genetics, doi:10.1038/nrg4017

3 Schlötterer C., et al. (2015) Combining experimental evolution with next-generation sequencing: a powerful tool to study adaptation from standing genetic variation. Heredity 114, 431-440

 

Modified evolve and re-sequence design

Principal advisor: Christian Schlötterer

Experimental evolution in combination with whole genome resequencing (Evolve and Resequence, E&R [1]) provides a huge potential to uncover adaptive alleles in evolving populations. A series of studies applying E&R in Drosophila demonstrated that a clear response to selection can be already detected after a few generations only. In most studies, however, the number of candidate SNPs was too large to identify the causative variation. In this project a modified E&R strategy is used that reduces the complexity and results in a cleaner selection signature. This modified E&R approach will be applied to fine-map beneficial mutations in genomic regions that were previously shown to harbor alleles beneficial in a temperature environment fluctuating between 18°C and 28°C [2]. This project combines experimental evolution, bioinformatics and functional Drosophila genetics.

1 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

2 Franssen S.U., et al. (2015) Patterns of linkage disequilibrium and long range hitchhiking in evolving experimental Drosophila melanogaster populations. Molecular Biology and Evolution 32, 495-509

 

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