By analyzing DNA from different cells in nearly 200 lines of maize plants, research led by the University of Michigan has revealed insights that could help growers better adapt their crops to a fast-changing environment.
The new study led by Alexandre Marand reveals previously hidden information about the activity of genes inside different cell types. This provides essential context that helps better understand how the molecular biology of a lineage connects to its readily visible traits, or its phenotype. This includes characteristics like how many ears of corn a plant has and how large those ears grow.
“One of the things that’s really remarkable to me is that, maybe a decade ago, when these sort of studies first started coming out, we were just trying to associate a genetic change to how the phenotypes would change,” said Marand, an assistant professor of molecular, cellular and developmental biology. “What this study shows is that, actually, most phenotypic variation comes from changes to regulation of a gene: when the gene is expressed, where it’s expressed and how much of it is expressed.”
Another way of looking at this is that there was a disconnect, at an intermediate stage, between our understanding of plant genetics and a plant’s characteristics.
Scientists first sequenced corn’s full genome more than 15 years ago and, since then, they’ve developed the ability to spot even subtle differences in the genetic code between specimens. But these differences at the molecular level often didn’t account for the large-scale differences that matter most to farmers.
So researchers began to suspect that how different cells were using those genes could play an important role. Although every cell in an organism shares the same genes, different cells use those genes differently.
Over the last five years or so, scientists’ ability to investigate plant genes in a cellular context really took off, Marand said. And his team’s new study, published in the journal Science, is the latest significant step in this promising trend.
“It’s really about connecting the dots,” said Marand, who began the work a few years ago as a postdoctoral scholar at the University of Georgia. It’s now been pushed past the finish line thanks, in large part, to two postdocs in his own lab at U-M: Luguang Jiang and Fabio Gomez-Cano.
“Now that we can make those connections, we can tease apart the different cell contexts and we can start to put things together to optimize plants or to optimize some trait that we’re interested in,” Marand said.
It’s a bit like having a car, he said, where we knew what the different parts were and what they did, but not how they worked. Getting that information gives a new appreciation for the working of the entire car — the corn plant in this analogy — and opens up new opportunities to improve its performance.
It also helps better understand how tweaking one the operation of one component influences others in the system.
“This really helps with prediction,” Marand said. “It lets us ask beforehand, ‘if we make changes, are they going to be additive or even synergistic?’ Will it be one plus one equals two? Or maybe it’s 10 — or negative 20.”
The work also helps provide a head start in understanding where the best opportunities for synergy are waiting. Corn originated in the planet’s tropical regions and has evolved into varieties that can now tolerate even Michigan’s more temperate climes.
By studying so many different varieties of corn, the new study shed a lot of light on evolutionary changes, helping understand how maize changed as growers selected the best performing plants in their environment.
“What we found is that a lot of those changes involved changes to the regulatory sequences that we were studying, and they have unique consequences in very specific types of cells,” Marand said. “We can use that information to continue to improve plants and to make corn more adaptable to different climates.”
Researchers at the University of Georgia and the University of Munich also contributed to the study, which was supported by the National Institutes of Health, the National Science Foundation and the University of Georgia Office of Research.
