Skip to main content Skip to navigation

Genetics of quantitative traits through a multi-omic approach

Primary Supervisor: Professor Zewei Luo,School of Biosciences

Secondary 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

Project outline:

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. We established this yeast model for several major reasons. Firstly, we have many years of successful working experience in quantitative genetic analysis under a yeast model. It is a simple but effective working model to test some sophisticated fundamental questions in polygenic genetics. Ethanol tolerance has a significant value to industries and is one of central questions of yeast evolution. 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: Sustainable Agriculture and Food: Plant and Crop Science

Techniques that will be undertaken during the project:

Experimental: Next generation sequencing (NGS), crossing and propagation of budding yeast, PCR, RT-PCR, microscopy

Computational: 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