PhD candidates (m/f/d) | Evolution of Polygenic Traits

The Max Planck Institute for Evolutionary Biology in Plön is an internationally oriented institution whose research focuses on the principles, mechanisms and effects of evolutionary change. Around 200 employees from more than 30 nations currently work at our institute in the departments of Theoretical Biology and Microbial Population Biology, as well as in a number of independent research groups.

We are looking for two PhD candidates (m/f/d) for the Research Group Evolution of Polygenic Traits.

The position is available from the earliest possible starting date. Contracts are awarded after an initial start-up phase (6 months; non-taxable stipend) for a period of three years (fully funded). Remuneration and social benefits are based on the German Civil Service Collective Agreement (TVöD Bund). The salary includes all mandatory social insurance contributions for health care, long-term care, unemployment, and retirement. The candidate will be part of the International Max Planck Research School for Evolutionary PhD, a well-established program with a vibrant research community and outstanding infrastructure.

Project 1 - Genetic and adaptive architecture of polygenic traits

Project description: The genetic architecture of quantitative traits identified by QTL and GWA studies includes all contributing alleles and their effect sizes. However‚ only a subset of the underlying alleles respond to selection; these alleles constitute the adaptive architecture (1). Factors such as distance to the new trait optimum‚ initial allele frequencies‚ and pleiotropy determine which alleles are potentially adaptive. The aim of this doctoral project is to compare the genetic and adaptive architectures of a polygenic trait‚ female body size in Drosophila simulans. We will determine the genetic architecture of female body size using GWAS. In a parallel evolve and re-sequence (E&R) project, D. simulans populations will be experimentally evolved for larger body size. The availability of this dataset will allow comparison of the adaptive and genetic architecture of female body size‚ and distinguish alleles with adaptive potential from alleles with constraints. The doctoral student will have access to a large dataset of 1000 individuals for GWAS and time-series genomic‚ transcriptomic‚ and high-order phenotypic data from E&R experiments.

References:

1. Barghi N, Hermisson J, Schlötterer C. Polygenic adaptation: a unifying framework to understand positive selection. Nat Rev Genet. 2020;21(12)‚769-781.

Project 2 - The genomic and phenotypic patterns of adaptation in large and small populations

Project description: In quantitative genetics‚ adaptation of quantitative and complex traits is assumed to occur through subtle frequency changes at many loci following a shift in the trait optimum. While polygenic adaptation is likely the prevalent mode of adaptation for many quantitative and complex traits (1), we still lack a solid understanding of the selection signatures under this model. In a computer simulation study (2)‚ we identified several distinct patterns of polygenic adaptation in populations of different sizes. Building on the results of the computer simulations‚ we conducted an experimental evolution in which 20 replicates of small (800 individuals) and 6 replicates of large (100‚000 individuals) populations of D. simulans were adapted to a high-protein diet. The proposed project aims to test the predictions of computer simulations with empirical data. The doctoral student will have access to a large dataset consisting of time series genomic‚ gene expression‚ and fitness data for these experimentally evolved populations.

References:

1. Barton NH‚ Etheridge AM, Véber A. The infinitesimal model: Definition‚ derivation‚ and implications. Theor Popul Biol. 2017;118:50-73.
2. Barghi N‚ Schlötterer C. Distinct patterns of selective sweep and polygenic adaptation in evolve and re-sequence studies. Genome Biol Evol. 2020;12(6):890–904

Project 3 - Evolution of gene regulatory networks

Project description: Many genetic variants underlying complex traits are located in regulatory regions‚ and adaptation can be manifested by changes in the expression of adaptive genes (1‚ 2). Adaptation of complex traits may also take different evolutionary paths in replicate populations despite phenotypic convergence‚ i.e.‚genetic redundancy (3). Genetic redundancy could manifest itself as a change in the expression of genes in the same or different regulatory modules (with either similar or different functions) in different populations. The aim of this project is to understand how gene regulatory networks are modified during polygenic adaptation. Tissue-specific gene expression and genomic data from hundreds of individuals from multiple replicate populations adapting to a new trait optimum will be used to reconstruct gene regulatory networks. In addition‚ eQTL mapping will be performed to identify the genetic variation underlying the changes in adaptive gene expression.

References:

1. Fagny‚ M. & Austerlitz‚ F. Polygenic Adaptation: Integrating Population Genetics and Gene Regulatory Networks. Trends Genet 37‚ 631-638 (2021). 
2. Boyle‚ E. A.‚ Li, Y. I. & Pritchard‚ J. K. An Expanded View of Complex Traits: From Polygenic to Omnigenic. Cell 169‚ 1177-1186 (2017).
3. Barghi, N.‚ Hermisson‚ J. & Schlötterer‚ C. Polygenic adaptation: a unifying framework to understand positive selection. Nature Reviews Genetics 11‚ 665-13 (2020).

Qualifications

• Master's degree in evolutionary biology with a strong background in population genetics and quantitative genetics. Projects 1 and 2 are great opportunities for those interested in analyzing time series data and combining bioinformatics methods with population genetic theory. Applicants for project 3 should have a strong interest in combining systems biology approaches with population genetics
• All projects will be challenging but rewarding‚ so the applicant should be a curious‚ highly motivated and dedicated researcher with grit‚ i.e. the passion and perseverance for very long-term goals
• Excellent written and oral communication skills in English
• Candidates should have strong programming skills (Python‚ R‚ etc.) and experience working with large datasets

How to apply

• We have three projects available in our group, please indicate which one you would like to apply for (you can choose more than 1). If you like the research in our group and have your own ideas for a doctoral research‚ please contact the principal investigator (Dr. Neda Barghi‚ barghi@evolbio.mpg.de ) directly.
• Your application should include 1) a cover letter outlining your research interests‚ motivation‚ and relevant work experience‚ 2) your CV including a list of publications and methodological skills‚ 3) your bachelor’s and/or master‘s degree and transcripts‚ and 4) contact information for two references. The cover letter should clearly and convincingly explain why you want to work on the selected project. Applications without a clear connection between the motivation in the cover letter and the project described will not be considered.

The Max Planck Society has set itself the goal of employing more severely disabled people. Applications from severely disabled people are expressly welcome. In addition‚ the Max Planck Society strives for gender equality and diversity. We welcome applications from any background.

Send the required application material as a single PDF to: bewerbung@evolbio.mpg.de by April 30th 2025.

For further inquiries‚ please contact the principle investigator (Dr. Neda Barghi‚ barghi@evolbio.mpg.de) directly.