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Methods for quantitative genetic analyses in autotetraploids

Principal Supervisor: Professor Zewei Luo – School of Biosciences

Co-supervisor: Dr Lindsey Leach – School of Biosciences

PhD project title: Methods for quantitative genetic analyses in autotetraploids

University of Registration: University of Birmingham

Project outline:

This PhD project will focus on development of statistical methods for quantitative genetic analyses in autotetraploid species.

Methods for quantitative genetic analysis have been well established in almost all important diploid plants and animal including humans, and have served as essential tools for dissecting the genetic architectures underlying agronomically, evolutionarily and medically interesting quantitative and complex traits. In sharp contrast, the corresponding studies in polyploid, particularly autopolyploid, species lags far behind this level of advancement, largely because of complexity in segregation and recombination of genes under polysomic inheritance, leaving quantitative genetic analysis in polyploid species a historical challenge since the era of pioneering quantitative geneticists such as RA Fisher, K Mather, JBS Haldane, etc.

This project will characterize key features of segregation and recombination of genes in outbred segregating populations of autotetraploid species, the most prominent type of autopolyploid. Autotetraploids have great agronomic and economic value, and include cultivated potato (the world’s third most important food crop), alfalfa, domestic trout and salmonidae.

There is a wide spectrum of possible quantitative genetic analysis, and we will open the following diverse areas for the PhD project candidate:

  1. Development of genomic DNA sequencing experiments to identify genome-wide genetic variants in an outbred segregating population from two potato cultivars.
  2. Involvement in the development of genetic models and methods for modelling and estimating quantitative genetic effects in both natural and crossing populations of autotetraploid species.
  3. Development of methods for mapping quantitative trait loci (QTLs) in outbred segregating populations of autotetraploid species.
  4. Involvement in modelling and analyzing various quantitative phenotypes, genomics/epigenetic datasets collected from the tetraploid potato quantitative genetics project.

The project will involve conducting a wide range of computer simulation studies to explore the properties of the methods to be developed. There may also be an opportunity to develop user-friendly computational tools to enable the developed methods to become widely accessible to the scientific community.

Applications are encouraged from graduates with backgrounds in any of the following disciplines: biology (particularly genetics), statistics, mathematics and computer science. The ideal candidate will have a passion for genetics and an aptitude for genomics and molecular biology experimental analyses, including modelling and analysing large-scale genomics data.

BBSRC Strategic Research Priority: Food Security

Techniques that will be undertaken during the project:

The project will involve largely analytical and computer-based work, but the candidate will be encouraged to participate in data generation and collection.

Experimental skills: crossing experiments in Arabidopsis/potato, phenotyping quantitative traits, lab-based skills for running PCR, RT-PCR, qPCR, sequencing/array based analyses.

Analytical/computational skills: (i) development of mathematical/statistical models for gene segregation and recombination under tetrasomic inheritance (e.g. using Mathematica), (ii) developing statistical approaches and algorithms for analyzing the quantitative phenotypic and genomic datasets involved in quantitative genetic analysis specified above, (iii) developing computational ability to compile computer programmes and scripts for computer simulation study and analysis of real experimental datasets (e.g. using Fortran 90/95 with IMSL libraries, C++, Perl), and (iv) developing skills to use main stream computer software for mathematical and statistical analyses (e.g. Mathematica, R), for data manipulation (e.g. Perl) on windows or linux platforms.

Contact: Professor Zewei Luo, University of Birmingham