Professor Peter Donnelly

The Wellcome Trust Centre for Human Genetics, Oxford



The major focus in the Donnelly group is on the development and application of statistical methods for understanding genetic variation, and its association with phenotypic variation and disease susceptibility. These methods typically combine modern computationally-intensive statistical approaches with insights from population genetics models, and aim to get as much information as possible from the large datasets currently being generated by high-throughput experimental techniques.
Much current work involves genome-wide association studies, with Donnelly leading the Wellcome Trust Case Control Consortium (WTCCC), and a subsequent consortium, WTCCC2. These involve collaborations of several hundred scientists studying a range of common diseases. WTCCC was the largest study of its kind. It was responsible for the discovery of many novel genetic associations, and won several major awards and prizes. WTCCC2 will examine DNA samples from about 60,000 individuals with the goal of understanding the genetic basis of susceptibility to 15 human diseases and conditions.
Another research focus concerns human recombination. It had long been known from pedigree studies that recombination rates vary over large scales across chromosomes. More recently, experimental studies and patterns of human genetic variation suggested that most recombination occurs in small (~2kb) sequence regions called recombination hotspots. In collaboration with the McVean and Myers groups, we developed computational statistical methods and applied these to large surveys of human genetic variation to characterise over 30,000 human recombination hotspots, and to identify DNA sequence motifs associated with hotspot activity.
Experimental work in the group is currently principally focussed on natural variation in several bacterial species, and mechanisms for horizontal gene exchange and vaccine escape.

Updated:  25 September 2017/Responsible Officer:  Director, NCIG/Page Contact:  Web Admin, NCIG