Project description
A main feature in the origin of complex life is the translation system by means of the near-universal genetic code: stored information contained in large molecules (DNA) is copied onto smaller molecules (RNA) that are “read” by ribosomes, which make proteins based on the information. How this translation system originated and how it evolves, still poses many important questions. Evidence suggests that the translation system is highly adaptive and appears optimized by natural selection. What is missing, however, is an overall theoretical framework for the evolution of the translation system, which could predict the outcomes of experimental and bio-informatic efforts and thereby really test our insight into the evolution of translation. This project aims to build such a theoretical framework, based on existing models for protein synthesis and ideas on the evolution of the genetic code.
At the core of the translation system are codons, triplets of nucleotides of the RNA molecule that are recognized by tRNA molecules (because they have the mirror image of the codons: anticodons) in the ribosome. These codons cause the ribosome to add the amino acid that the tRNA molecule was charged with (through the enzyme AARS) to the emerging protein. The genetic code links each individual codon to one specific amino acid. There is quite some redundancy in the translation system, with multiple codons coding for the same amino acid. Open question are what level of redundancy is selected for, and what factors (e.g. growth rate, G-C content of the genome) drive the optimization of codon usage. Furthermore, experimental approaches in microbes, e.g. inserting or deleting specific tRNA genes to measure the effects on cellular function, showed that deletion of a non-mandatory tRNA gene does not strongly affect the functioning of the cell, but it does typically result in the evolution of a new tRNA gene with the same anticodon (by duplication of a tRNA gene followed by point mutation). Also, experiments have “resurrected” putative ancestral genes (“primordial genes”) for tRNA and AARS to test their function in translation. This project aims to develop theoretical predictions for these experimental approaches, but also offers possibilities for developing such experiments.
Additional specifications
We look for a candidate with a MSc in Biology, Life Sciences or a related discipline. Experience with modelling and programming (e.g. Python or C) is required, and experience with bio-informatic or statistical analysis is recommended.
