Projektbeschreibung
Bewertung der Fitnesslandschaft-Theorie
Die menschliche Anpassung an neue Umgebungen ist in der Evolutionsbiologie ein viel diskutiertes Thema. Seit Jahrzehnten umstritten ist etwa die Rolle der Epistase, d. h. des genetischen Hintergrundeffekts auf Mutationen als Schlüsselfaktor der Anpassung. Mit dem Konzept der sogenannten Fitnesslandschaft, die Zusammenhänge zwischen Genotyp und Fortpflanzungserfolg beschreibt, näherte man sich bislang dieser Problematik. Nun ist es möglich, diese Theorie zu bewerten. Das EU-finanzierte Projekt FIT2GO wird die Theorie der Fitnesslandschaften gezielt auf die Quantifizierung der Epistase über biologische Strukturen und Umgebungen anwenden und deren Beitrag zur Populationsgenetik von Anpassung und Hybridisierung untersuchen. Ergebnisse und Methoden werden dazu dienen, das Potenzial für die Vorhersage von Wegen zur Arzneimittelresistenz bei Krankheitserregern zu bewerten.
Ziel
A major challenge in evolutionary biology is to quantify the processes and mechanisms by which populations adapt to new environments. In particular, the role of epistasis, which is the genetic-background dependent effect of mutations, and the constraints it imposes on adaptation, has been contentious for decades. This question can be approached using the concept of a fitness landscape: a map of genotypes or phenotypes to fitness, which dictates the dynamics and the possible paths towards increased reproductive success. This analogy has inspired a large body of theoretical work, in which various models of fitness landscapes have been proposed and analysed. Only recently, novel experimental approaches and advances in sequencing technologies have provided us with large empirical fitness landscapes at impressive resolution, which call for the evaluation of the related theory.
The aim of this proposal is to build on the theory of fitness landscapes to quantify epistasis across levels of biological organization and across environments, and to study its impact on the population genetics of adaptation and hybridization. Each work package involves classical theoretical modelling, statistical inference and method development, and data analysis and interpretation; a combination of approaches for which my research group has strong expertise. In addition, we will perform experimental evolution in Escherichia coli and influenza to test hypotheses related to the change of fitness effects across environments, and to adaptation by means of highly epistatic mutations. We will specifically apply our methods to evaluate the potential for predicting routes to drug resistance in pathogens. The long-term goal lies in the development of a modeling and inference framework that utilizes fitness landscape theory to infer the ecological history of a genome, which may ultimately allow for a prediction of its future adaptive potential.
Wissenschaftliches Gebiet
Programm/Programme
Thema/Themen
Finanzierungsplan
ERC-STG - Starting GrantGastgebende Einrichtung
3012 Bern
Schweiz