Understanding recombination through tractable statistical analysis of whole genome sequences

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This project concerns the analysis of whole genome sequence data: that is, the complete DNA sequence, the genetic code, of an organism. The technology for acquiring such a sequence is relatively new. It was used to sequence a single human genome in the "Human Genome Project", which finished in 2003. This project took 13 years and cost $2.7 billion. However, technological advances in the past 10 years have led to the cost of sequencing genomes to drop dramatically. It now costs only $1,000 to sequence a human genome and this price continues to fall.Why should one wish to sequence a genome? The human genome can be thought of as the blueprint for building a human. Each person has a slightly different genome: the parts that are common to everyone are what make us human; the parts that differ are responsible for the (genetic) differences between us. Understanding our genomes, through studying both the common parts of the genome and the differences, promises scientific breakthroughs in many areas, particularly medicine. For example, Genomics England are currently planning to sequence 100,000 genomes for the purposes of improving clinical practice in dealing with rare disease, cancer and infectious disease.The study of DNA sequences is not restricted to humans. It is also useful to obtain whole genome sequences from many other living things. This project is focussed on analysing genetic information obtained from bacteria. There are many reasons for studying bacteria, one of the most obvious being that some bacteria cause disease in plants and livestock (affecting our food supply) and in humans (affecting our health). Obtaining a better understanding of the genetic code of bacteria offers the promise of both tracking the spread of infections and also reducing the occurrence of disease.However, although sequence data is relatively easy to obtain, extracting useful information from it can be very difficult. Genome sequences can be stored on computers in text files as a long sequence of letters. A single gene might consist of a few hundred or thousand letters. A whole bacterial genome, containing thousands of genes, might be 3 million letters long. Most scientific projects involve studying a population (tens, hundreds or thousands) of these genomes, thus it is not unusual for a dataset to consist of over a billion letters! To make sense of such a large complicated data set, mathematical methods, implemented as computer programs, are required.This project is concerned with the development of such mathematical methods, and their implementation. The aim of the project is to learn about the evolution of bacteria by studying their genome sequences. As a rule, bacteria reproduce clonally: each individual only has a single parent. However, in some cases they can also exchange DNA, in a manner related to sexual reproduction in humans. It is of great scientific interest to understand such exchanges for several reasons, including that it is one of the main ways in which a bacteria can become resistant to antibiotics. MRSA is an example of an antibiotic resistant bacterial strain that has been of significant concern to the NHS. Understanding how antibiotic resistance is acquired is one way in which scientists can help to tackle such problems. Analysing whole genome sequences using mathematical methods, as is done in this project, is fundamental to these investigations.Currently there are several computer programs that can be used to investigate the exchange of DNA, and important discoveries have been made through using them. However, when they are used on whole genome sequences, some of the programs run too slowly to be useful in many cases (sometimes they take months) and others cannot detect (or provide an incomplete picture) of genetic exchange events. This project is developing new programs that are both accurate, and run quickly enough to be useful.