Plant Science – ACENET

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.

Unlocking the Secrets of a Vital Plant Hormone

A major high performance computing event may seem like an unusual place to showcase landmark research about plants. But that’s exactly what happened at this year’s High Performance Computing Symposium in Halifax. The research, carried out by a team at Saint Mary’s University in Halifax and the University of Jyväskylä in Finland, has unlocked the secrets of ethylene formation using a rather unconventional tool. The team used the ACENET Data Cave located at SMU to create a virtual 3-D model of the molecules involved in the process; a model that allowed them to visualize the process more accurately. Ethylene is a key hormone in plants – a chemical compound that plays a critical role in causing fruit to ripen. But until recently, the chemical process that created ethylene in plants remained a mystery. For one thing, the biosynthesis process that creates ethylene gives off carbon dioxide along with cyanide, a deadly poison that should kill the enzyme that serves as a catalyst in the ethylene creation process. Dr. Jason Clyburne, a chemistry professor and Canada Research Chair in Environmental Science and Materials at Saint Mary’s University, headed up the research study. It was the first time he has used the ACENET Data Cave as part of his research. “Understanding the reaction mechanisms catalyzed by enzymes is a very difficult process, usually requiring a host of chemical, spectroscopic and other techniques,” says Clyburne. “By creating a visual model in the Data Cave, we were able to examine the active site and its environment. It was an extremely useful tool for us.” A number of developments have come from Clyburne’s landmark research. For one thing, the study confirmed the existence of a molecule called cyanoformate, a fragile and elusive ion long speculated to exist, that neutralizes the deadly properties of cyanide. Cyanoformate is formed when molecules of carbon dioxide and cyanide combine. It breaks down quickly, but before it does it carries the cyanide away from the enzyme before it can cause damage to the plant cell. “We learned how nature handles cyanide, a process that we didn’t really understand before,” says Clyburne. The research has some potential practical applications as well, including a better understanding of how fruit ripens – knowledge that could have major benefits to the global agricultural industry. The cyanoformate process also opens up possibilities for a new carbon capture process that could be used to help combat greenhouse gas emissions. Because cyanoformate forms an extremely weak bond between the carbon dioxide and cyanide, the process is attractive to carbon capture technologies that need to be able to easily transport and then release the carbon dioxide so that it can be recycled cheaply and easily. Because crystal structures are freely available on the Internet in a variety of file formats and can be projected in 3-D using the tools available in the ACEnet Data Cave, Clyburne predicts that this form of research will probably become more commonplace in years to come. “The Data Cave really opened my eyes up to the possibilities of seeing inside a material to explore its properties.