Thesis: Uncovering structural variations using optimized plant reference genomes
Next generation sequencing (NGS) technologies have contributed significantly to the study of crops. However, due to the large number of repetitive regions and short length of sequence reads, assembling a perfect reference genome using NGS data remains a challenge. To overcome this problem, long read sequencing technologies and optical mapping technologies have been developed. This project uses long read sequence data and optical mapping data by applying bioinformatics tools and pipelines to develop a robust algorithm to optimize the draft reference genomes of different plants, such as canola and bread wheat. As structural variations relate to important agronomic traits, we set up an exhaustive assessment of genome structural variations in different plant accessions. This project refined the draft of plant reference genomes using newly improved long range genomic data and explored associations between structural variations and agronomic traits to help accelerate crop breeding.
Why my research is important
Brassicas are grown as vegetable crops or ornamentals, and the oil derived from the seed is useful for food and industrial purposes. To improve the productivity and reduce production loss by disease and global climate change, an accurate canola reference genome is needed. In this project, we optimized the B.napus draft genome using long read and optical mapping technologies to assemble a gold standard reference genome. Based on the genome, structural variations were detected to associate with agronomic traits.
Wheat is Australia’s top commercial crop and its genome is complex and hard to assemble. In this project, we also included the study of bread wheat.