Gabriel Keeble-Gagnère

Gabriel Keeble-Gagnère

Gabriel Keeble-Gagnère has been involved with the IWGSC since 2010. His first contributions were on the BAC-based assembly of chromosome 7A, as part of Rudi Appels’ group. This work involved collaborating with many groups in Australia as well as overseas since there was not much experience working with large BAC assemblies in Australia. Gabriel worked very closely with the team he is now part of at Agriculture Victoria, including Matthew Hayden and Josquin Tibbits, as well as Philippe Rigault at Gydle in Canada. As a result, they were able to produce high quality assemblies of regions of 7A (published in Genome Biology in 2018), including “finished” regions of particular interest.

Bringing in the experience gained from the assembly of chromosome 7A, Gabriel joined the Pseudomolecule Group in 2016, with Frédéric Choulet and Martin Mascher. The group was tasked with integrating the large amount of assembly resources (physical, genetic and optical maps, WGP tags, etc.) already generated by the IWGSC as part of the BAC-based approach with the NRGene/Hi-C assembly (IWGSC WGA) to produce the final pseudomolecules for IWGSC RefSeq v1.0 ( published in 2018 in the journal Science ).

Most recently, Gabriel has contributed to the updated v2.0 assembly being led by Jan Dvorak and Mingcheng Luo’s group at University of California, Davis.

Gabriel received an IWGSC Early Career Award in 2014 for his work on the chromosome 7A assembly and joined the IWGSC Coordinating Committee in 2018.

What motivated you to become a bioinformatician? How did you become involved in genomics? And why wheat?

I got into bioinformatics completely by chance – I didn’t know anything about the field before 2009. I was looking for a job in Perth at the end of 2009, and ended up at Murdoch University, in a bioinformatics lab Rudi Appels was part of at the time. As anyone who knows Rudi can attest, it’s hard not to get swept up in his enthusiasm for wheat. As a bread lover, I didn’t need much convincing of the importance of wheat, but he got me interested in the wheat genome and its challenges. Rudi has been a huge support through my whole career – I can’t thank him enough.

In your daily work as a bioinformatician, what excites you the most?

Having focused mostly on theoretical, “pure” topics during my higher education it was quite a change moving into “messy” applied science. But of course, the other side to that is the work is much closer to real-world outcomes. I find bioinformatics particularly interesting because it’s a great example of a hybrid field: somewhere between biology, computer science and mathematics. A lot of the successes in bioinformatics stem from effective cross-domain collaboration and we are seeing this more and more; for example, it is hard to deny the importance of high-performance computing in crop research today.

What would you say are the benefits of being part of an international consortium?

Collaboration is a critical part of scientific research. Approaching a complex task as an international consortium means the problem can be broken down and tackled by many groups simultaneously, but also allows knowledge and expertise to filter back down to the members and countries involved. For example, being part of the IWGSC has been greatly beneficial to Australian wheat research as a whole, since it provided early access to datasets as well as led to the development of local expertise. On a more personal level, being part of an international consortium provides opportunities to travel and interact with researchers around the world. I was lucky enough to visit Etienne Paux’s lab in Clermont-Ferrand, France, Abraham Korol’s in Haifa, Israel, and Jaroslav Dolezel’s lab in Olomouc, Czech Republic, as well as visit conferences in Germany and the US as part of the IWGSC. The places and people I met on those trips will stay with me. Ultimately research is about people working together.

What did you find most challenging about your work on the IWGSC RefSeq assembly?

There were many challenges, but I will just highlight two in particular. Firstly, not having a “ground truth” to refer back to can be very challenging when trying to assess the correctness of a new assembly. For example, a genetic map “agreeing” with the order of some scaffolds can be due to both being incorrect in the same way. So, having many sources of information becomes critical to make informed choices. Secondly, drawing a line in the sand and finalizing an assembly can be very difficult as there are always small improvements that can be made. But, as with many real-world problems, continuing indefinitely is not an option either. You have to strike a balance between doing the best you can and delivering outputs to a deadline so the next part of the project can move forward – in this case, for the pseudomolecules to be annotated and analyzed.

Have you had an opportunity to assess how well the wheat reference genome sequence has met the needs of plant scientists / plant breeders in Australia? What resources do you think should be added?

It has had a huge impact. Not just in terms of traditional mapping projects where it’s now feasible to more or less identify all genes in a given genetic interval. But it has massively enabled the development of new resources such as genotyping arrays and better markers. In addition, it has meant that previously generated resources, like the 16 wheat varieties relevant to Australia sequenced by Bioplatforms Australia almost ten years ago (arguably ahead of its time!) can now be effectively used. One challenge now is making all this data accessible to the researchers and users who need it most – pre-breeders and breeders. This is something we are trying to address with our Pretzel project.

According to you, what will be the biggest advances in wheat research in the next 5-10 years?

We already have the technology to do mass-scale genotyping, the main issue now being cost, but this is decreasing every year. The challenge now is phenotyping at a similar scale, which also requires very accurate definition and classification of traits. These advances coupled with approaches such as Genomic Selection should see gains in breeding as they are adopted more widely. As the number of complete reference-level assemblies increases, of both elite varieties, landraces and wild relatives, we will start to piece together the puzzle of wheat’s history. This will help us not only to understand exactly where the various haplotypes being tagged by markers used by breeders have come from, but also assist in efforts to bring more diversity into the gene pool. This knowledge, combined with genome editing technologies, will be a powerful combination. One other thing: I think we will see an increased spirit of collaboration, between researchers but also between research and industry, as the scale of projects are now too large for single groups to tackle alone.

There are currently a lot of talk about the use of AI and deep learning to better understand genomes and biology, what’s your take on this?

There’s no question machine learning is an incredibly powerful tool for understanding complex datasets. I am sure it will be used more and more in every scientific field. But worth noting is these kinds of approaches rely on the right kind of data combined with the right problem. For example, the impressive results reported in fields like image analysis are possible because big tech companies such as Google already have vast stores of images from operations such as Google Photos (i.e. users are providing billions of datapoints every day). In order to most effectively apply machine learning in crop research, say, will require rigorous definition of phenotype and ability to screen tens of thousands of plants. Naturally, all this takes time to set up and get running smoothly. We can’t just press a button and solve all our problems.

As a bioinformatician, is there a particular genome you would love to work on? Why?

I’m already working on wheat and barley, which covers bread, beer and whisky – what else do you need? I’m very interested in wild species – the wild relatives of wheat and barley are a rich resource for bringing in new variation. Beyond that I think we can learn a lot from wild species more generally. It would be interesting to study genomes of wild native plants in Australia to see what insights they can bring on local adaptation, for example.

What are your future plans?

I feel like I got into wheat research at the right time, just as the IWGSC BAC-based assembly approach was taking off. The experience of working on that project, capped off with the publication of the IWGSC RefSeq v1.0 in 2018, was a huge learning process for me and a truly exciting journey. I feel lucky to have been a part of it all. I’m now part of a great group of researchers and hope we can all continue to build on the work achieved so far. AgriBio, the centre where I work, is an inspiring place to work with a lot of expertise and research capacity. I am sure that the most exciting years for wheat research are still ahead of us.

About Gabriel

Gabriel studied Mathematics and Computer Science at Imperial College London, then went to Japan for two years to teach English as part of the JET Program. Upon his return, he studied Pure Mathematics in Paris for one year (what is called a “Maitrise” in France, equivalent to MSc. in the UK). From 2013 to 2016, he led the bioinformatics activities for the Australia-China Centre for Wheat Improvement. He joined Agriculture Victoria in 2016 as a Senior Research Scientist.

Publication date: 07/01/2020

Modification date: 16 August 2023 | Publication date: 16 October 2020 | By: ic