
Looking to the genes
While traditional breeding techniques provide incremental gains in yield quantity and quality, greater leaps in improvement are still much needed. Fortunately, recent advances in molecular-genetic techniques may make such fast-track changes possible, if they can be harnessed effectively. This is what Professor Mario Caccamo and his colleagues at NIAB aim to facilitate.
Over the past few years, scientists have developed methods for sequencing all the DNA of an organism (its genome) with increasing speed and decreasing cost – a ‘revolution in plant genomics’. As such, it is now possible to pinpoint the parts of a genome (‘markers’) associated with particular traits, such as resistance to a disease, or early fruiting. However, there may be many thousands, if not millions, of markers in the genome of a single crop species, and these need to be characterised in detail and located precisely for the successful breeding of desirable traits.
Plant genomes – and particularly highly bred crop genomes – present additional problems due to their notorious size and complexity. For instance, the genome of bread wheat, Triticum aestivum, is five times larger than the human genome and, in fact, incorporates genetic material from three distinct species, making it a hybrid of the most complex kind.
However, as a result of the process of domestication the genomes of many modern crops are also remarkably uniform among individuals, exhibiting little variation that could be used to breed improvements. It may therefore be better to turn to closely-related wild species with more diverse genomes. But breeding from wild species, with less well characterised genomes, runs the risk of bringing in undesirable traits alongside the desirable ones. For this reason, there is a need to build a very detailed understanding of the wild genomes in order to identify which markers are in close proximity to each other.
Calling on computers
Fortunately, informatics is advancing alongside genetics, enabling us to manage, model and mine the vast amount of genomic data to identify the markers that might contain the key to better varieties, or even entirely new crops.
Even using the best of existing breeding methods, crop yields are growing at only a fraction of the rate needed to keep up
With a background in theoretical computer science, Prof Caccamo is ideally placed to develop the computational tools needed to support the breeding of better and novel crop varieties. His lab specialises in designing and executing entire computational pipelines based on tools developed by other colleagues across the world to help identify genetic markers within the genomes of staple food crops, which can be used for targeted breeding programmes.
Better bred
Bread wheat is the most widely cultivated crop in the world, but is currently experiencing a ‘yield plateau’ of little or no improvement, representing a massive challenge to world food security. The crop is also highly susceptible to debilitating and fast-evolving pathogens causing immense economic losses.
This will help breeders to select varieties from the seed bank that might be most distinct or useful for breeding, to incorporate traits such as resistance to specific diseases.
Rice is life
It is often said that for Vietnam, rice is more than food, rice is life. In Prof Caccamo’s most recent project, Vietnamese scientists are being even more proactive: with funding from the UK’s Biotechnology and Biological Sciences Research Council (BBSRC) and the British Council’s Newton Fund, Prof Caccamo and collaborators are attempting to characterise the genomes of the Vietnamese rice varieties stored in the country’s National Gene Bank. The aim of this is to develop a modern platform – including computational tools such as databases and bioinformatics pipelines – for rice breeding in Vietnam, focused on traits of crucial agronomic interest.
Rice is the main staple food for huge numbers of people across Asia, and Vietnam is the world’s second-largest rice exporter. But, rising sea levels due to climate change are threatening the country’s two main rice cultivation areas – the deltas of the Mekong and Red Rivers. Prof Caccamo’s team hope to isolate genetic markers for traits, such as salt tolerance, that might help withstand this pressure, in order to accelerate breeding new varieties that are better suited to overcoming the challenges of climate change.
Computer technology is advancing alongside the genetic technology, enabling us to manage, model and mine genetic data
The technologies and protocols that Prof Caccamo’s team are developing through the Mexico and Vietnam projects will be equally applicable to other staple crops across the world. Rice and wheat lie at two ends of a continuum in terms of crop genomes: rice being relatively simple and wheat extremely complex. Thus, rice offers an excellent model for the evaluation and assessment of new strategies for breeding that could later be applied to more complex crops. Wheat on the other hand, provides more of a challenge.
By collaborating with institutes in the countries where he works, Prof Caccamo’s approach will leave a long-term legacy – not just in terms of research findings and methodologies, but also trained scientists able to continue the work.
Crop breeders will face ever more challenges as environmental conditions continue to evolve. But solutions do exist inside the genomes of crops and their wild relatives.
Prof Caccamo’s work provides the tools for scientists and breeders to mine their genetic diversity and rise to the challenges of feeding the world for the future.
The lack of genetic diversity compounded by the pressure to deliver novel crops on ever shorter timelines are undoubtedly big challenges for breeders. The advent of new data-driven technologies will help but interestingly brings other challenges such as the access to the skills to manage and model the data. The need to train the new generation of crop researchers and breeders in these technologies is increasingly becoming more important and remains an area that has not seen as much progress as it requires if we are looking to benefit from them.
As a computer scientist, how did you get into crop breeding?
As a scientist, I was drawn to the challenge of making sense of the genetic data for a very complex genome such as the one for bread wheat. Until only a few years ago the aim of sequencing and managing large crop genomes was considered unreachable. I can think of many similar problems in other fields of science but the unique opportunity to work on an area of research that has a large impact on our daily lives, such as food, was the other great incentive for me.
How can computational tools help with crop breeding?
We live in a digital age in which much of what we do is governed by our access to data and information. Science and indeed crop breeding is no different. We now have access to relatively inexpensive technologies that allow us to gather vast volumes of data at an unprecedented pace. Computational tools are essential to first manage these data, and second help us to model them to make sense of the information. Specifically, in breeding we are focused on developing genetic markers that could help us to accelerate the process of selection for better yielding, better quality crops.
How can germplasm banks and seed banks help with your research?
One way of tackling the lack of diversity is to look for individuals with potential novel alleles that perhaps have been cultivated in other territories or, why not, other times. A seed and gene banks’ mission is to preserve and make accessible genetic diversity that then could be used to breed novel crops in the future. They also provide a snapshot of the past that could help us to understand how crops have moved around the globe and crossed with other cultivars as a signature of our recent human history.
Why is international collaboration and an international perspective so important in your research?
The threats that we are facing to ensure food security are global; thus, the solutions will also need to be global. Drawing from the successes and failures of our colleagues in other countries, working with similar challenges but in different backgrounds is the best insurance policy to support the development of lasting and effective solutions.
Professor Mario Caccamo’s research focuses on genetic diversity in crops. He and his team develop computational tools to support the breeding of novel crops with advantageous survival traits. This work has typically focused on the wheat genome and, more recently, the rice genome – looking at overcoming the threats from climate change.
Funding
- Biotechnology and Biological Sciences Research Council (BBSRC)
- Newton Fund
Collaborators
- Professor Le Huy Ham – Director of AGI (Hanoi, Vietnam)
- Dr Kevin Pixley, Dr Carolina Sansaloni (Seeds of Discovery, CIMMYT)
- Dr Jose De-Vega, Dr Tim Stitt, Paul Fretter (Earlham Institute)
- Dr Sarah Dyer, Dr Bruno Santos (NIAB)
Bio
Mario Caccamo is head of Crop Bioinformatics at NIAB in Cambridge, UK and holds an honorary professorship at the University of East Anglia. Previously, Professor Caccamo directed the Earlham Institute. He also completed a PhD in theoretical computer science at BRICS, University of Aarhus (Denmark). Since April 2017 Professor Caccamo has also been the Managing Director of NIAB EMR.
Contact
Professor Mario Caccamo (Managing Director)
NIAB EMR
New Road
East Malling
Kent
ME19 6BJ
UK
E: mario.caccamo@niab.com
T: +44 (0)1732 523711
W: www.emr.ac.uk/staff/professor-mario-caccamo/
W: www.niab.com/pages/id/421/professor_mario_caccamo
W: www.niab.com