Finanzierte Masterarbeit in Molekularer Evolution / Bioinformatik / Genomik
- Structural and functional properties of de novo proteins in recently diverged fly populations
A major shift has occurred in understanding how new proteins, the key components of all forms of life, come about. Earlier research assumed that smaller adaptive changes in duplicates of established and evolutionary ”successful” proteins shape the majority of new proteins. However, recent research showed that completely new proteins can arise by emergence of ”de novo” genes from previously non-coding DNA in eukaryotes. Some mechanisms underlying de novo protein emergence are now understood. However, no coherent picture of how and how often novel protein coding genes become fixed and their encoded proteins become functional is available. This new research area has gained much attention at conferences and in high-profile journals.
This project uses genomes and transcriptomes from inbred fly populations generated in our group. Chosen populations follow a close geographic and genetic gradient across Europe to study the dynamics of gain and loss of novel genes at unprecedented accuracy. Transcripts have been precisely mapped on the originating genomes in order to understand the prevalence of underlying genetic mechanisms and by comparing population data to outgroup genomes (other fly species) it is possible to pin down selective constraints and adaptive pressures which possibly act on de novo proteins. To date it is completely unclear if and how random proteins, such as proteins with sequences derived from previosuly non-coding regions, acquire folded structures and functional properties such as binding or catalytic activity.
The project will aim at a detailed structural and functional analysis of all proteins encoded by putative de novo genes. This will include classical methods such as secondary structure predictions and hydrophobic clustering but also cutting-edge machine learning algorithms such as the deep learning Alphafold and other recently developed methods predicting binding properties based on the calculated surfaces of these structural models. Eventually, these predictions will be experimentally tested using phage-display and library screening in our collaborating groups (Florian Hollfelder, Cambridge; Klara Hlouchova, Prague; Ylva Ivarsson, Uppsala).
Our group has rich and diverse experience on reconstructing the evolutionary history of proteins and delineating the specific functional forces shaping them from multiple data (see http://bornberglab.org/research). Candidates will thus work in a highly successful and stimulating environment on a demanding project at the forefront of molecular evolution and structural biology which puts candidates in an excellent position for a further career in many sought after research areas.
Candidates should have a strong background in either biotechnology, biochemistry, biophysics or bioinformatics and basic knowledge about principles of molecular evolution and protein structures. Good skills in programming and digesting large data sets using Python (or similar languages) are essential. For excellent candidates, a substantial amount of funding through a student helper contract (Studentische Hilfskraft mit Bachelorabschluss) will be provided.
Applications (max 2 pages) covering in reverse chronological order prior employments, education, specific relevant skills, publications (if any), career goals and statement of interest should be sent (2 pages maximum) as soon as possible (but no later than Mar 31st) to email@example.com.
MASTER and BSc THESES
Theses are available at Institute of Evolution and Biodiversity, University of Muenster at the end of every semester to start at the following semester, for subjects listed and with financial support being possible (see below for student helpers/researchers), depending on qualifications, tasks etc. International and national collaborations are often endorsed. Students are invited to inquire any time at the office e.g. by email to firstname.lastname@example.org or call ext. 21638.
Student helpers / researchers (" Studentische / Wissenschaftliche Hilfskraft") may be hired to help install and maintain computer infrastructure, web resources and establish and refine teaching materials and databases in the group and for research projects such as Genome Evolution and Protein Evolution. Commencing date is any time within the year, contracts can be issued to the needs of the applicants with flexible working times ranging from 7 hrs (complies with the 450 EUR threshold) to 19 hrs per week.