Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

Plant breeding uses DNA sequence variation to make new allelic combinations for crop improvement. Our creation of the first wheat gene sequence assemblies (Brenchley et al Nature 491, 705) has enabled new levels of high throughput precise genotyping for breeding this globally important crop. Nevertheless, there are other levels of heritable variation, such as epigenetic modifications, that are widely thought to play a key role in shaping genomes and creating new variation. We have recently developed highly efficient re-sequencing technologies for wheat that can measure DNA methylation in genes of multiple lines. This provides an outstanding opportunity to assess epigenetic variation in a major polyploid crop and understand how it may influence traits. The overall objective of this proposal is to use newly available wheat genome resources, together with our innovative application of exome capture and bisulphite sequencing, to measure epigenetic modifications in wheat genes, and relate these to gene expression and the acquisition of new phenotypes, and how they may contribute to genetic changes such as gene loss during polyploid formation.

Metagenomics is the study of the DNA of mixed environmental samples that include the genomes of many different organisms. We can sequence metagenomic samples using the same next generation sequencing technology that we use to sequence the genome of a single organism, but analysing the data is much more complicated because it is difficult to know in advance which organisms are present in a sample and therefore difficult to know which organism a particular fragment of DNA (a 'read') has come from. Assembly is the process of putting together short reads into contigs that represent a much longer fragment of DNA, enabling more useful analysis. Assembly is a difficult but relatively mature field when it involves DNA from a single organism. However, many of the simplifying assumptions made by assembly tools are invalid when dealing with metagenomic data, making the process of metagenomic assembly much harder and the field much less mature. The aim of this project is to develop computational algorithms for metagenomic assembly and to produce a tool that is sensitive and able to accurately differentiate between very similar species. We have targeted a particular type of metagenomic data involving viral detection because this is an important area and one that is particularly under-addressed with the small number of metagenomic assembly tools that already exist. Using such a tool enables scientists to gain vital information from metagenomic samples, including understanding the mechanisms of disease in animals and humans, detecting novel viruses and monitoring the spread of viruses in order to prevent and contain outbreaks.