Population genetics, evolution, pathogens
In many pathogenic organisms, evolution can occur very rapidly, for example allowing a virus to escape from host immune mechanisms, or bacteria to become drug resistant. My research aims to understand the detail of these processes, using genome sequence data collected across multiple points in time.
Computational modelling plays a key role in my research, allowing statistical inferences to be made of where, and how, selection has acted to change the genetic make-up of a population. The common role of evolution across biological systems allows for the study of many different organisms; my recent work has addressed questions related to the evolution of yeast, of bacteria, and of the influenza virus.
5 recent publications
- C J R Illingworth (2015) Fitness inference from short-read data: within-host evolution of a reassortant H5N1 influenza virus, Mol Biol Evol, accepted
- C J R Illingworth, A Fischer, and V Mustonen (2014) Identifying selection in the within-host evolution of influenza using viral sequence data, PLoS Comput Biol, 10 (8), e1003755
- C J R Illingworth and V Mustonen (2012) Components of selection in the evolution of the influenza virus: Linkage effects beat inherent selection. PLoS Pathogens, 8 (12), e1003091
- C J R Illingworth, L Parts, S Schiffels, G Liti, and V Mustonen (2012) Quantifying selection acting on a complex trait using allele frequency time-series data. Mol. Biol. Evol., 29 (4), 1187-97
- C J R Illingworth and V Mustonen (2011) Distinguishing driver and passenger mutations in an evolutionary history categorized by interference. Genetics, 189, 989-1000