Photo credit: Phys.Org
This network shows the cross-species co-expression relationships between genes in Arabidopsis and Agave. Dark green nodes represent Agave genes, light green nodes represent Arabidopsis genes, blue edges represent positive co-expression relationships, and red edges represent negative co-expression relationships. The co-expression network was used in the paper to investigate the co-expression relationships of genes within the same gene family. Credit: ORNL
Research team uses supercomputing to understand processes leading to increased drought resistance in food and fuel crops
April 18, 2017 by Eric Gedenk
Read more at: https://phys.org/news/2017-04-team-supercomputing-drought-resistance-food.html#jCp
Photosynthesis, the method plants use to convert energy from the sun into food, is a ubiquitous process many people learn about in elementary school. Almost all plants use photosynthesis to gather energy and stay alive.
Not all photosynthetic processes are the same, though. In recent years, researchers have grown increasingly interested in desert plants‘ preferred method of photosynthesis—crassulacean acid metabolism (CAM), a process named after the Crassulaceae family of plants, which include succulents like friendship plants, pig’s ears, and hens and chicks.
These plants caught researchers’ attention because of their seemingly opposite photosynthetic schedule, and understanding this process may be the genetic key to helping plants of all kinds conserve water. With a more fundamental understanding of CAM, scientists aim to help the plants upon which society relies for food and fuel become more drought resistant, thereby expanding the area where crops can grow and thrive.
“One of the benefits of CAM photosynthesis is water efficiency,” said Oak Ridge National Laboratory (ORNL) computational biologist Dan Jacobson, who is part of a multi-institutional team that recently published a CAM study in Nature Plants. “When you think of bioenergy and food crops, you want them to be able to tolerate drought stress or grow in areas that aren’t currently arable land. That means they have to be able to withstand some kind of environmental stress, most commonly drought stress. CAM species are very good at this.”
To that end, Jacobson works with a large group of experimentalists and computational scientists to more fully understand the CAM process. This cross-omics team (combining expertise in metabolomics, proteomics, and genomics) uses computing resources at the Oak Ridge Leadership Computing Facility (OLCF)—a US Department of Energy Office of Science User Facility located at ORNL—to catalog how plants’ CAM processes vary and ultimately uncover how CAM processes may be genetically engineered into feed stock, food crops, and crops for bioenergy applications.
Shining a light on photosynthesis
When most people think of photosynthesis, they are actually thinking of a specific form, called C3 photosynthesis. This process follows the Calvin Cycle, in which plants capture light energy during the day and convert it into energy-bearing adenosine triphosphate (ATP).
ATP helps plants split water atoms into their hydrogen and oxygen constituent particles. Meanwhile, a C3 photosynthetic plant opens up small pores—called stomata—to absorb carbon dioxide from the atmosphere. Then at night, the newly freed hydrogen particles combine with carbon dioxide absorbed during the day to create the carbohydrates plants use to live and grow.
CAM photosynthesis works the same way, but stomata open for respiration at night and stay tightly closed during the day, allowing plants to conserve more water. This helps plants like cactus and Agave survive in climates where water is scarce.
The team then studied what gene expressions control stomata opening and closing in both CAM and C3 plants and how proteins regulated this process. Collecting this data in both a common CAM and a C3 species allowed the team to distinguish traits ubiquitous to CAM plants from species-specific traits. However, finding these connections required a machine capable of comparing large data sets against themselves.
More information: Paul E. Abraham et al. Transcript, protein and metabolite temporal dynamics in the CAM plant Agave, Nature Plants (2016). DOI: 10.1038/nplants.2016.178