Seeding Change III: From Past, to Present, to Future how Genomics is Transforming Agriculture

Scientist working on a farm using data insights to help improve crop breeds

Looking Forward; How Genomics Solutions can Tackle Challenges for Tomorrow’s Agriculture


By Tom Finn, Senior Program Officer

As highlighted in the articles Looking Back and Here and Now, Alberta’s agriculture sector is constantly adapting and innovating to meet new challenges. By leveraging emerging technologies like genomics, crop and livestock producers have improved yield and disease resilience and have begun to tackle solutions to reduce greenhouse gas emissions and address climate change. Alongside these technological advances are huge advances in information and big data. In today’s digital age, producers have access to more data than ever before, and agriculture is evolving to take advantage of new opportunities as a data-driven industry. Every aspect of farming, from crop selection to yield optimization, is now influenced and supported by data and technology. As available datasets continue to expand rapidly the future of agriculture will rely on our ability to access and apply insights for improved decision making of Alberta producers as they stay leading-edge in sustainable practices, competitive in global markets and ready to respond to emerging challenges.

Diving Deeper for More Data and Going Beyond Genomics

Genomics primarily deals with the study of an organism’s entire genome, or the totality of its DNA. But with continued scientific progress, even the term “genomics” no longer sufficiently captures the level of detail that we are capable of generating. The broader term “-omics” expands the spectrum of biological data that we can now observe, providing an even deeper look into an entire biological system. It includes areas like

  • proteomics – the study of all the proteins of an organism. Proteins are complex molecules that perform critical functions throughout the body. Identifying the proteins produced by an organism can help us understand how it carries out core functions at the cellular level. For instance, are certain proteins more prevalent in a drought-resistant crop variety
  • transcriptomics – the study of an organism’s entire transcripts or gene expression molecules known as RNA. The presence of these molecules indicate which genes are being “turned on” or “turned off” at a given time. Using transcriptomics, we can study how an organism’s gene activity changes in response to its environment. For instance, do genes associated with immune response become more or less active when cattle experience heat stress?
  • metabolomics – the study of all the metabolites or small molecules like antioxidants produced by within living organisms. These molecules are often intermediates or end products of various metabolic reactions that occur in cells as part of normal physiological functions. Through metabolomics, researchers can map out the biochemical pathways of an organism or even an entire ecosystem. For instance, how are nutrients transformed and stored within soils, and how do soil food webs differ between regions?

The information gained from these -omics technologies can be used to guide the selective breeding of crops and livestock with never-before-seen precision. For example, the area of metabolomics has enabled precise monitoring of the intricate metabolic pathways crucial for plant growth, stress responses, and overall health – and how they vary under diverse environmental conditions or stressors, such as drought, pests, or diseases. By correlating these metabolic changes with plant health, scientists can identify biomarkers for stress tolerance, optimal nutrient utilization, and enhanced crop productivity. Understanding plant metabolomics can then facilitate the development of resilient crop varieties through targeted breeding, where scientists can select for and improve plants with desirable metabolite profiles for better adaptation to changing climates.

Supporting a One Health Approach

The health of animals, people, and the environment are tightly linked. This is the foundation of the One Health approach, of which -omics technologies can play a critical role. By removing the need to grow living cultures of suspected pathogens, -omics enable far more rapid and cost-effective surveillance of diseases. This can support earlier detection and intervention of pathogen outbreaks on farms. By identifying biomarkers associated with immune response, -omics technologies can also support producers in the breeding of disease-resistant crop and livestock varieties. By allowing for more targeted and precise treatment approaches in livestock, -omics technologies could reduce reliance on antibiotics, decrease the spread of dangerous pathogens and improve animal welfare overall.

In partnership with RDAR (Results Driven Agriculture Research), and supported by funding through the Sustainable Canadian Agricultural Partnership, Genome Alberta has opened a new funding opportunity: Accelerating Agriculture Innovation One Health Solutions. $5M funding is available to support research projects that utilize genomic-enabled technologies, which offer collaborative, effective, and cost-efficient approaches, to provide solutions to One Health challenges and benefit Alberta producers. The funding will be targeted to address the priority issues of Chronic Wasting Disease, Feral Pigs, African Swine Fever, Antimicrobial Resistance (AMR), and Highly Pathogenic Avian Influenza (HPAI) through a One Health approach.

Agriculture’s Big Data Needs

-Omics technologies unlock new ways to understand biological processes, and generate massive datasets with this information. However, having more new data is simply not enough. To learn and better understand new insights from this data it is critically important we have the tools to do the analysis of the data. The fastest and most efficient way to do this is with artificial intelligence (AI) and machine learning (ML). Harnessing AI with -omics based datasets allows us to gather larger amounts of complex biological data and use ML to detect patterns and eventually, make predictions within these datasets. This is superior to using traditional mathematical and statistical models, as more complex repetitions can be identified, and the accuracy of predictions can be improved as datasets inevitably grow. Using new data and generating new insights in these ways can revolutionize crop management, disease control, and yield optimization. AI-supported systems in combination with high quality -omics based data, will allow farmers to make science-driven decisions that were previously unimaginable.

While big data in agriculture holds great promise, it also presents challenges that need to be addressed for its full potential to be realized. These challenges include the critical importance of data quality, diversity and representativeness. Other important considerations include concerns regarding privacy when collecting and sharing farm data, determining data ownership and usage rights among multiple stakeholders, building trust between invested parties, and the importance of user-friendly interfaces for effective data utilization. These challenges can be overcome through the development of clear guidelines, robust data governance frameworks and optimal design.

The Road Ahead

The expanded use and integration of different types of large data, including -omics data, is vital for the continued sustainable progress of agriculture. Throughout the years, innovative and future-thinking Alberta producers have worked closely with researchers & scientists to take solutions out of the laboratory and onto the landscape. Data-driven approaches will continue to be the cornerstone of progress into the future and by harnessing the potential of big data, the agricultural industry can become even more efficient, resilient, and sustainable.

For almost 20 years Genome Alberta has proudly enabled a portfolio of research projects (58) in the agricultural sector with a value of $186M (to March 2023). We are committed to supporting connections for broader application of genomic solutions in the agriculture sector. As we look to the future, Genome Alberta will continue to act as a catalyst to bridge knowledge and support partnerships between the academic community, government and industry in order to realize the potential of data-driven agriculture and grow even more benefit for our province.

See our Project Portfolio to learn more about projects Genome Alberta has funded in the Agriculture sector.

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