About the Project
This doctoral programme represents a unique opportunity for a student to develop of a range of skills in Bioinformatics and Computational Biology and analytical skills, including those required for the analysis of large next generation sequencing data. It is expected that this multidisciplinary PhD would be suitable for graduates with a keen interest in computational modelling and a background in either biology or one of the physical sciences. Within the remit of this research area, after the development of the initial skills set and an understanding of the biological context of Lolium/Festuca, the candidate would be able to make choices in terms of the focus of the research, i.e., broad-scale structural variation vs. narrower functional variation; whole genome annotation vs. specific gene family comparisons; the relationship of lifecycle to genome composition.
Our institute, IBERS, is part of an international consortium developing a draft reference genome sequence for Lolium perenne (perennial ryegrass). The current assembly is based around c. 100x coverage and likely to contain the majority of the Lolium perenne genespace, hence a suitable reference sequence for the resequencing and assembly of multiple Lolium/Festuca genomes. Within the Lolium/Festuca complex of grasses there is a broad range of phenotypic adaptation and phenological variation. For instance, Lolium spp. lifecycle-types range from short lived annuals to long-lived perennials; Lolium and Festuca spp. occupy a wide range of both agricultural and natural habitats with markedly differing adaptations in terms of tolerance to abiotic stresses (e.g. freezing tolerance, drought tolerance, water-stress survival). Various genotypic analyses have also indicated that this phenotypic variation is associated with a broad spectrum of variation at the DNA level. This is enhanced by the obligate outbreeding nature of most Lolium/Festuca genotypes (though can be contrasted with inbreeding in other genotypes).
Within this research area, there is scope for a range of Bioinformatic investigations relating to the underlying genome structure of contrasting Lolium/Festuca genotypes. Using genome resequencing data to sample this variation, it will be possible to develop and contrast genome assemblies derived from inbreeding, homozygous annuals and shorter and longer lived perennials derived from contrasting environments. Using these assemblies, it will be possible to develop detailed comparative characterisations of genome structural variation and predicted genic composition using gene prediction methods and subsequent annotation of genes and predicted gene products. Critically, transcriptomic data is also available to guide and validate the annotation process. By focusing on specific gene families, it will be possible to develop in silico models of the relation between SNP variation at the DNA level and functional variation at the protein level. For instance, the prediction of DNA binding domains in transcription factors associated with the flowering response or the complexity of disease resistance gene families in relation to annuality/perenniality may be of interest. Deep comparisons and integration with the growing bodies of knowledge on genome annotation and protein prediction for model species such as rice, Brachypodium and Arabidopsis may also form a part of the research.
Supervisors: Martin Swain, Narcis Fernandez-Fuentes and Ian Armstead
"Candidates should have (or expect to achieve) a First Class or Upper second class honours degree and/or a masters degree
(or equivalent) in a relevant subject."
We encourage prospective candidates to contact the lead supervisor Dr Narcis Fernandez-Fuentes, [Email Address Removed] ;01970 621680; http://www.bioinsilico.org
This project is one available as part of the IBERS PhD Studentships initiative. This is an open competition.
Subsistenace rates will be in accordance with current Research Council rates.
Applications through PG Admissions - http://www.aber.ac.uk/en/postgrad/howtoapply/ - please ensure that you enter the lead supervisors name under 'name of proposed research supervisor'.