The aims of this PhD research are to identify and characterise genome diversity in Triticum aestivum (bread wheat).
This research will establish a process for the identification of large numbers of single nucleotide polymorphisms (SNPs) and other genetic variations in Triticum aestivum.
Single nucleotide polymorphisms (SNPs) are the most abundant type of molecular genetic marker and can be used for producing high-resolution genetic maps, marker-trait association studies and marker assisted breeding. Large polyploid genomes, such as wheat, present a challenge for SNP discovery due to the potential presence of multiple homoeologues for each gene.
AutoSNPdb has been successfully applied to identify SNPs from Sanger sequence data for several species, including barley, rice and Brassica, but the volume of data required to accurately call SNPs in the complex genome of wheat has prevented its application to this important crop. DNA sequencing technology has been revolutionised by the introduction of next generation sequencing, and it is now possible to generate several million sequence reads in a timely and cost effective manner.
Wheat transcriptome sequence data has been generated using Roche 454 Life Sciences technology. This data has been applied for SNP discovery using a modified autoSNPdb method, which integrates SNP and gene annotation information with a graphical viewer. A total of 4,694,141 sequence reads from three bread wheat varieties were assembled to identify a total of 38,928 candidate SNPs. Each SNP is within an assembly complete with annotation, enabling the selection of polymorphism within genes of interest.
The discovery of large numbers of genomic SNPs across 16 Australian diverse bread wheat varieties has been completed using a novel algorithm SGSautoSNP. More than 10x whole genome shotgun Illumina paired read sequence data was generated through a bioplatforms collaboration and the data mapped to the draft assemblies of chromosomes 7A, 7B and 7D. Over 4 million inter-varietal SNPs were identified. SNP density varied along the lengths chromosome syntenic builds as well as between genomes.
SNP density analysis and SNP transition/transversion ratio analysis provide insights into the evolution and breeding history of this important crop. Both the SNP density and SNP transition/transversion ratios across the D genome are significantly lower than across the A and B genomes. This difference reflects the evolutionary history of this crop. In addition, genes within low SNP density regions may have been selected during domestication and breeding. Furthermore, this SNP resource permits the application of high resolution skim based genotyping by sequencing (GBS), trait association and analysis of structural variation in populations.
An integrated database and portal for wheat genome resource, WheatGenome.info, has been established and published online. This portal provides a variety of web-based systems hosting wheat genome and genomic data, including genomic SNPs, to support wheat research and crop improvement.
This research provides approaches to understand the effect of sequence variation on the form and function of wheat growth and development and response to environment.