Dissecting the genetics of complex human traits: language and handedness

Background
The human brain is lateralized. For example, language is mainly processed in the left hemisphere by most people. Handedness is the most widely studied index of lateralization. Both atypical brain asymmetries and non-right handedness have been implicated in common neurodevelopmental disorders such as dyslexia and schizophrenia. Very little is known about the biological processes underlying lateralization and its role in disorders.
Our previous work opened new horizons in the understanding of handedness. We identified the first gene, PCSK6, to be statistically associated with handedness. PCSK6 controls the determination of the left/right body axis during embryonic development. Therefore, this genetic association supports the idea that structural laterality and handedness are controlled by shared biology which could also be implicated in the mechanisms leading to brain lateralization and neurodevelopmental disorders.

The project
The current proposal will take forward these findings through the analysis of large cohorts both genotyped at genome-wide level and richly characterised with cognitive and behavioural measures. This data include population-based and clinical cohorts assembled trough a wide and expanding network of collobarators in the UK, Europe, Asia and Americas. This setting will provide excellent opportunities to work as part of international consortia.
The project will mainly be computational and will involve approaches such as genome-wide association studies applied to quantitative traits, analyses of next generation sequencing data and the use of polygenic risk scores to dissect complex traits.

The person
Applications are encouraged from graduates with backgrounds in any of the following disciplines: bioinformatics, statistics, mathematics, biology, psychology, and computer science. The ideal candidate will have an interest in neuroscience and genetics and an aptitude for statistics and large-scale data analysis. A Masters degree in Statistics would be desirable. Some experience of working with genetic data would be desirable but not essential. While training will be provided, experience of coding and scripting in a statistical package (e.g. R, SAS, stata, Winbugs, Bioconductor) is desirable.

How to apply
For further details on the project and informal enquiries please contact to Dr. Silvia Paracchini ([Email Address Removed] ) with a CV and a covering letter. Start date: no later than 1st October 2018.