| Date & time | Nov 22 '21 |
| Ends on | Nov 29 '21 |
| Location | The University of Edinburgh, United Kingdom |
| Creator | fbergstrom |
| Category | job-position-vacancy |
| Registration | Link |

Supervisors: James Prendergast, Albert Tenesa, Pau Navarro
Although researchers have used genetic approaches to map thousands of genomic loci linked to important traits, which of the genes in these regions are driving them is often unclear. To begin to address this issue the transcriptome-wide association study (TWAS) approach was developed (https://www.nature.com/articles/s41588-019-0385-z). In a TWAS, statistical models are created to predict the expression level of genes from an individual’s genome. These are then used to predict gene expression levels in people with and without the phenotype based on the genetic variants they carry. If the predicted expression levels of a gene are different between the groups, this suggests differences in the individual’s genomes are leading to differences in the particular gene’s expression, which in turn is potentially driving the disease or trait. The aim of this project will be to improve the TWAS approach. The student will do this by prioritising and weighting genetic variants to be used in the prediction models through incorporating further annotations, for example the distance of variants to genes, their chromatin context and any DNA motifs they affect. In this way the student can reduce the search-space of variants when training the models and upweight those variants most likely to be directly linked to gene expression levels. The student will then assess improvements in the models and the prediction accuracy of gene expression levels using the GTEx and farmGTEx datasets, and go on to apply these improved approaches to map novel genes linked to important phenotypes in mammalian cohorts.
The student will consequently develop or build upon important skills in bioinformatics/statistics/genetics that are highly sought after both within academia and beyond.
This opportunity is open to UK
and international students and provides funding covering stipend and UK
level tuition fees. The University of Edinburgh covers the difference
between home and international fees meaning that the EASTBIO DTP offers
fully-funded studentships to all appointees. There is a cap on the
number of international students the DTP recruits. It is therefore
important for us to know from the outset which fees status category
applicants will fall under when applying to our university.
Please refer to UKRI websiteand Annex B of the UKRI Training Grant Terms and Conditionsfor full eligibility criteria.
Closing Date: 16th December 2021
The Wall