Genetic Mutation

Supercomputers at the Frontline of Climate-Resilient Forests

When he was introduced to forest genetics as a 23-year-old researcher in India, Dr. Om Rajora became obsessed and devoted to forest genetics research. “Sometimes, even at the cost of my health,” he says, laughing.

Decades later and half a world away, he is still going at it, and busier than ever. He heads the forest genetics and genomics lab and is a professor of Forest Genetics and Genomics at the University of New Brunswick, where he joined as the Tier 1 Canada Research Chair in Forest and Conservation Genomics and Biotechnology. He also coordinates the Population, Ecological and Conservation Genetics research unit at the International Union of Forest Research Organizations, and he developed and published a pioneering book series called Population Genomics.

Through his work, Rajora seeks to reveal the secrets hidden within the genes of our woodlands, offering unprecedented insights into resilience, adaptability, and the preservation of biodiversity (genetic diversity) in the face of a rapidly changing world. His research has encompassed a wide range of forest genetic and genomics topics and fields, which besides contributing to basic science, can be used for conservation of genetic resources and sustainable forest management.

One of those areas involves analyzing the genes, gene expression, and metabolic pathways of trees under ambient and changing climate conditions. This in turn gives hints to how forests respond to environmental changes. By sequencing and analyzing the genes expressed under different scenarios, Rajora aims to identify the genes, biological processes and molecular functions affected by climate change, including those related to photosynthesis and stress response. “For example,” he explains, “this could provide us information about what traits could be affected with elevated levels of CO₂.”

Rajora’s research obsession and a strong work ethic have their limits, however, and today’s rapid gene sequencing techniques have created the need for advanced methods of data analysis and storage.

In a recent project, Rajora and his post-doctoral fellow, Dr. Rajni Parmar, needed to undertake extensive genetic analysis of the red spruce transcriptome and chloroplast genome, and identification and characterization of genes and pathways expressed differentially in response to climate change conditions. This required significant computational resources. In the past, they relied on personal computers for certain analyses, but the advent of next-generation sequencing—rapid DNA/RNA sequencing techniques—and the accumulation of massive amounts of data necessitated the use of supercomputers or computer clusters. ACENET and the Digital Research Alliance of Canada have been instrumental in providing these capabilities.

Dr. Serguei Vassiliev, a research consultant with ACENET, played a pivotal role in the study. He delved into the project, learning the fundamentals of computational bioinformatics, installing software, and creating parallelization schemes to process large problems simultaneously. He also trained the group in essential computational techniques, including genome assembly and annotation, transcriptome construction, statistical analysis of gene expression, and protein interaction network identification.

The outcomes were remarkable: computation time was slashed from weeks to hours, the group acquired advanced computational skills, and they published an article in the International Journal of Molecular Science, with another in progress. Vassiliev’s significant contribution earned him co-authorship on the publication.

“The knowledge provided by this research is beneficial to the global plant genomics community,” explains Rajora. The variations found in gene expression clue scientists into what genes may allow forests to survive adverse conditions. Through international collaboration, scientists can pool their resources, data, and insights to develop innovative solutions that can be applied globally in the face of climate change.

From Megabytes to Megafauna: Driving Whale Conservation to New Depths with High Performance Computing

“I think whales are kind of like dinosaurs,” says Tim Frasier. “Almost everyone is interested in them at some point in their childhood, but some of us don’t grow out of it.”

Frasier, now a biology professor at Saint Mary’s University in Halifax, Nova Scotia, is following his dream. His lab studies genetic variations in whale populations to fuel conservation efforts using high performance computing (HPC). Their present focus is on the North Atlantic right whale and Saint-Lawrence beluga.

By observing the variability of an individual’s genome over its lifetime, Frasier and his students determine how inbreeding and traumatic events, such as ship strikes or entanglement in fishing gear, make individuals and populations less able to recover and reproduce.

The Frasier Lab sequences whale genomes from minuscule pieces of skin collected humanely by field teams. They then compare the variation in gene expression in healthy and injured whales, the life histories of which they know thanks to data collected by researchers through photo-identification over the last several decades. All these data provide the basis to understand how the cumulative effects of inbreeding and multiple stress factors can cause individuals to not reproduce or live as long.

Frasier specifies, however, that these analyses involve millions of DNA fragments, which take up huge amounts of both storage space and computing power. “You just can’t do it on a normal computer.” Access to ACENET and the Alliance’s supercomputing facilities are instrumental in enabling his lab to tackle complex genetic analyses that would otherwise be impossible.

Frasier gets asked a lot how this kind of information translates into helping conservation. One way is by influencing policy. Existing legislation imposes limits on different industries according to their impact on whales. For example, a North American right whale hit by a ship or entangled in a fishery somewhere along the east coast of the US and Canada could trigger either a ship slowdown in the area or completely shut down that fishery for the season. He explains that these triggers might only be quantified based on whether the whale died or not, “like a yes-no question.” But if Frasier’s research can show that these incidents change their reproductive success for years afterward, then it would also demonstrate that current measures are vastly insufficient to help populations recover and thrive in the long term.

Frasier’s work both advances our understanding of whales and provides a framework for devising more appropriate measures to encourage population recovery. It also highlights the importance of computing resources in modern biology research and conservation. “Without ACENET, we wouldn’t be able to do this work,” he says. “It’s just such a great resource that we have, and many of the geneticists in Canada that I know feel that way.”

In Search of Apple Perfection

Zoë Migicovsky has the secret sauce to help farmers get more fruitful crops. The assistant professor of biology at Acadia University and Canada Research Chair (Tier II) in Agri-Food and Sustainable Agriculture works her magic by combining genetic data from fruit crops and agriculturally important trait information about the plants and then analyzing the data so plant breeders can make predictions about what their plants will produce in terms of fruit.

“Agriculturally important traits would be things such as when an apple might ripen or what its aroma might be,” Migicovsky says. “With an apple seedling, you’re going to be waiting four to seven years for there to be enough fruit for you to have a meaningful evaluation of what that fruit is like.”

There’s an enormous resource investment in that seedling in terms of breeding the plants, fertilizing, watering, managing for pests and disease and pruning, to name a few. “Then at the end, most of the plants won’t have desirable traits,” Migicovsky says. “That will be true regardless, but if we can make predictions about some of those traits early on, we can reduce the number of plants that need to be culled at a later date and narrow down which are more likely to be desirable plants later on.

She sums up the problem she’s addressing by quoting from an October 23, 2023 Financial Times article in which a breeder started with 90,000 trees. Of those, “Only 357 varieties made it to a second round of trials, 18 went to a third and 13 reached the final round.” The article states that apples are like diamonds in that way.

In order to do her work, Migicovsky needs computational resources that will handle large genomic trait datasets and link them together. “The plant breeder isn’t going to screen for 200,000 genetic markers. They would like to only screen for a couple, so we need to know which ones are the best for them to do that. If you have a quarter of a million columns to compute, you’re not going to do that on your laptop,” Migicovsky says. “We need computational resources like those available through ACENET and the Digital Research Alliance of Canada.”

The more genomic data she has, the more likely she is to find good predictors, but the more genetic data she has, the more computational resources she also needs.

Using ACENET resources saves her money in her research budget and enables continuity in her work. It’s a shared system, so her students are able to access her lab’s files and software. “It’s helpful because students are only there for a relatively short time so this allows for one student to pick up where another left off.”

Cracking Cannabis Codes

David Joly studies the interaction between plants and micro-organisms.

“We are looking at what genes make plants more resistant to disease and what genes make them more susceptible,” explains Joly, a biology professor at Université de Moncton. “On the pathogen side, we’re trying to determine what genes make a pathogen aggressive with a particular plant and what makes the pathogen detectable by that plant. Plants have an immune system and are able to recognize certain molecules from pathogens, triggering a defence response, a little like we humans do.”

Joly works mostly on cannabis and says some plants are more resistant than others — again, being comparable to humans. Some humans, for example, seem to get the flu every winter, and some simply never seem to get sick.

“If we focus on plants that are more resistant and compare them to plants that are susceptible, can we see differences in the genes?” he says, using tomatoes as an example. “We could take those more resistant plants and use them in a breeding program, crossing them with plants we know produce really juicy tomatoes.”

Joly says he’s starting from the beginning in many ways with cannabis because Canadian researchers have only recently been allowed to study it.

“I have to stick to what’s been authorized to work with,” he says. “So we have to gather as many different plants as possible and test them in our growth cabinets, and then we can sequence their DNA and ultimately use ACENET resources to look at their differences.”

He says he and his team need to screen millions of “letters” in the cannabis genome, and on a small computer, that would take weeks.

“So that’s where we use resources that are available from ACENET,” he says. “What I like about ACENET is the training they offer to take students from zero knowledge of bioinformatics to slowly making them more comfortable with bioinformatics coding. You need to be able to program and code and ACENET teaches them that. I can help them, but we often take advantage of the training from ACENET.”

He says ACENET has been especially instrumental with his undergraduate students, who are almost always new to bioinformatics.

“Even at the graduate level, I have students who arrive here and don’t know much about bioinformatics, so ACENET’s training is still useful there,” he says. “Then we access the different tools and software so we can analyze the data. Every time we encounter problems, the ACENET people are always very useful in helping us find the problem. Sometimes it’s just a semicolon in the coding and they’re patient enough to help us find it.”

Joly says his work would be “very difficult” to do without the services of ACENET.

“You can wash the dishes manually, or you can use the dishwasher, but if you use the dishwasher, you can wash way more dishes in a given amount of time and get other things done while that’s happening,” he says.

Predicting the Future of Fisheries

Ian Bradbury uses DNA technology to understand what aquatic species — whether Atlantic salmon, cod, crab or lobster to name just a few — Eastern Canada has and how they might respond to stressors such as climate change.

“We look at how things are adapted to the environment using genetic and genomic tools and then we use machine learning and climate models to look at how they might respond in the future,” explains Bradbury, a research scientist with the Department of Fisheries and Oceans and an adjunct professor at Dalhousie and Memorial Universities. (Genetics is the study of how genes work while genomics is the study and mapping of genomes, or the full set of genetic instructions for an organism.)

The goal is to be able to make projections in terms of the rate of change happening with a specific species, as well as how it will respond to climate change and how that might impact fisheries and other stakeholders using those resources in the future.

The classic example, he says, is Arctic char in Labrador, which is culturally important for Indigenous groups along the coast, ecologically important because it’s the dominant freshwater coastal fish species there and notable because it’s at the southern portion of its range in Labrador.

“So it would not be surprising that climate change might be pushing it northward,” Bradbury says. “And we’ve done a lot of work over the last couple of years, some of it using ACENET, to understand how Arctic char in Labrador and north of that, are adapted to their climate and then how climate change might affect that.”

Bradbury is building a baseline or map of genetic variation in Arctic char. His projections suggest that the Arctic char’s range will start moving north, meaning the southern portion of Labrador will no longer be suitable for char, which will have implications for the people living in the area and for the ecosystems that remain there.

Bradbury and his team need ACENET because genetic tools generate massive datasets — multiple terabytes in fact — and since data management and data analysis are most of what they do, they couldn’t do their work without ACENET.

“We don’t have access to the computational power that my students would need to do these sorts of analysis,” Bradbury says.

The students he supervises are sequencing the entire genomes of aquatic species and then analyzing them for differences among individuals and populations.

“We’re making associations with climate on a set, and we’re doing projections for future impacts,” Bradbury says.

While there are other options out there, he says, ACENET is particularly useful because it’s accessible to students. His research team includes students at all levels and postdocs at both Atlantic campuses.

Studying the Duplication of Genes

The duplication of DNA through the process of mitosis is essential to life. But that process doesn’t always go as planned. Sometimes the copies are flawed and the genes contained within them are mutated – the process that drives evolution. Sometimes extra copies of genes are produced. Those extra copies, or gene duplications, work like other gene mutations: sometimes the effect is good; other times it is bad or has no effect at all. Denise Clark is a geneticist and a professor of biology at the University of New Brunswick in Fredericton.She studies those gene duplications as part of her research and she’s using the ACENET computer network to do it. “When two copies of a gene are both functioning within a genome they can take on different roles,” says Clark. “We’re interested in how the the duplicated genes function and also in the mechanism that causes the duplications to arise.” Fruit flies are the primary organism Clark studies. The tiny insects are the gold standard for this kind of genetic research because they reproduce quickly and also because they have already been studied extensively by geneticists for many years. “There has been a determination of the entire DNA sequence, or “genome”, for hundreds individual fruit flies by several fruit fly research groups to look at genetic variation in populations,” she says. “That next-generation DNA sequencing data is available for anyone to look at.” “A couple of years ago I started using ACENET to look for duplicates. If those duplicates are localized – if they’re not present around the world – we can assume they are new.” ACENET provides a crucial piece of the puzzle. The file for one fruit fly genome is gigabytes in size, says Clark. The sheer size of the data that needs to be analyzed would quickly overtax a standard computer system. “I’ve looked at 500 genomes using ACENET. That’s something I couldn’t do on my laptop.” The job is made easier because ACENET has installed a number of genome tools that Clark can use off the shelf. It allows her to look at hundreds of genomes in parallel or string together the tools she wants to use in a pipeline.”I’m not building any new tools, except for the specific pipeline that lists what I need. I start with a genome file that’s gigabytes in size and at the end I’m left with a file that’s hundreds of kilobytes,” she says. Clark says that now that technology to sequence genes has gotten much cheaper and faster, there has been an explosion of new genetic knowledge and ideas recently. “A lot of geneticists’ ideas about genomes and genetic variation have changed since the development of next-generation sequencing technology.”