Plant breeding is an important process in food production, which can be used to improve crops in various ways for societies. For farmers and producers, successful plant breeding provides more choices; higher yields, extended periods of cultivation, more resistant varieties to changing climatic conditions, and further profits. For the consumer, it provides healthier foods of higher nutritional quality at affordable prices. Making plant breeding more accurate and rapid greatly contributes to its effectiveness in managing crop disease and ensuring we have high-quality food. Recent breakthroughs in genetic sciences, along with the analysis power of computers has allowed for revolutionary innovations in plant breeding through a discipline called ‘bioinformatics’. It is in this relatively new and exciting discipline, which I work.
My research focuses on canola. Canola is the second major oilseed crop in the world after soybean. It is a trademark name, which is derived from low acid Canada oil. Pressed canola seed is used to make canola oil – a healthy alternative to other cooking oils. One of the species used to produce quality canola oilseeds is Brassica juncea, also known as Indian mustard or Brown mustard. This species is cultivated in many regions of the world, where the growing season encompasses hot-warm and dry climates, serving a variety of nutritional and industrial purposes. For example, these oilseeds are used as rotational crops, especially for cereals, such as wheat or barley, or to provide agronomic benefits, such as protection from crop diseases. Canola production is constantly increasing, and canola is now Australia’s third largest crop, after wheat and barley.
My project looks at the computational analysis of genomic data from the species B. juncea, using modern and advanced techniques. We focus on studying the characteristics of different varieties of B. juncea (in their genetic code), which make them better adjusted to grow. For example, we look for characteristics, which give the ability to grow with less water, under a very hot climate, or to be more resistant to external damage. Thanks to collaborators, an excellent lab team and the newest high throughput technologies, we are able to analyse, compare and integrate extensive genomic data. We at the Applied Bioinformatics group (www.appliedbioinformatics.com.au) focus mainly on detecting genes that might have important traits and genes that are conserved between varieties and genes that tend to be lost.
The results of my project can be used to distinguish differences between varieties, identify genomic regions that are conserved between species and assess how these genes might be carrying information to the next generation of plants. These outcomes are subsequently tested in the lab using selective breeding techniques and can be later linked to improved canola breeding for B. juncea and related species. In turn, improved canola breeding will help to provide consumers with a high standard of vegetable oil at affordable prices.
Paula A. Martinez has an MSc in Bioinformatics and Systems Biology. She is a current PhD candidate at the School of Agriculture and Food Sciences at the University of Queensland.