Principal Supervisor: Professor Zewei Luo – School of Biosciences
Co-supervisor: Dr Lindsey Leach – School of Biosciences
PhD project title: Genetics of quantitative traits through a multi-omic approach
University of Registration: University of Birmingham
Most characters of any living organism are polygenically controlled and environmentally modified, including those threatening human health and those important in breeding for high yield, better quality and improved adaption of animals, plants and microbes. Understanding the molecular mechanisms underlying polygenic variation has been one of the most challenging areas both in the history of genetics and the era of modern functional genomics. The genome-wide marker assisted mapping of quantitative trait loci (QTL) has greatly opened the window of quantitative genetic analysis at the genome level. However, dissecting QTL to a genic level is still a task with exceptionally few successes due to the bottleneck in both mapping precision and resolution for the current linkage and linkage disequilibrium based QTL mapping strategies.
To address this fundamental challenge, this project is designed to develop novel theoretical and experimental strategies to unveil the molecular basis underpinning quantitative genetic variation at genic, transcriptional and their interactional levels. To achieve this, novel theoretical frameworks and analytical tools will be developed that enable integration of genome and transcriptome sequence data from segregating populations created from recurrent bi-directional selection and backcrossing (RSB) schemes. Feasibility, reliability and utility of the theoretical analyses and experimental strategies will be tested by experimentally exploring ethanol tolerance of budding yeast as an experimental model of quantitative traits. For many years we have established the yeast model as a simple yet effective working model to test some sophisticated fundamental questions in polygenic genetics. The ethanol tolerance trait is chosen as a typical example of any quantitative trait, and for its significant industrial value and importance in yeast evolution.
This project aims to identify not only the major effect QTL and eQTL genes underlying the quantitative trait but also those interactions affecting the trait, differing in principle from the current forward and backward genetic approaches for dissecting quantitative genetic variation. In this way, the project will open a new route for understanding the complex molecular basis of quantitative traits in crops and other plant/animal species. This project will provide training in the key areas of genomics, molecular biology, statistical analysis and computer programing.
BBSRC Strategic Research Priority: Molecules, cells and systems & Food Security
Techniques that will be undertaken during the project:
Next generation sequencing (NGS), crossing and propagation of budding yeast, PCR, RT-PCR, microscopy
Creating mathematical/statistical models for modelling population dynamics of breeding programs involving backcrossing, selection, finite random sampling and drift (e.g. using Mathematica), writing programmes and scripts to analyse large-scale omics datasets (e.g. using Fortran 90/95 with IMSL libraries, C++, Perl), statistical techniques for data analysis (e.g. using statistical software R), linux and use of the command line.
Contact: Professor Zewei Luo, University of Birmingham