Washington, Jan 18 (ANI): Scientists have created a genetic model that can predict how plants respond to climate change and flower in different environments.

It has been known for some time that plants respond to environmental cues that guide their flowering.

Chief among these signals are light, temperature and vernalization, when flowering is promoted by prolonged exposure to cold temperatures.

In some plants, scientists have identified particular genes that deal with each of these environmental signals. But, they haven’t fully grasped how plants integrate these signals in nature.

Through a series of field experiments at five European sites, a Brown University-led research team has charted the internal and external signals that guide the life cycle of one plant species, Arabidopsis thaliana, across its native climate range.

The team has created a model that shows the importance of the genetic and environmental cues for key genotypes of Arabidopsis and how these signals vary depending on the plant’s location and seasonal environment.

“This is a powerful tool to predict how this plant species and other species will respond to climate change and which genetic pathways are important in different environments,” said Amity Wilczek, a postdoctoral research associate in ecology and evolutionary biology at Brown and the paper’s lead author.

The seesaw competition of genetic pathways inside the plant goes on until a threshold is reached, a molecular switch that triggers the plant to cross into the next stage of development.

By examining mutants impaired in different genes, the research team could quantify shifts in the balance of this seesaw across different seasons and climates.

The team discovered that certain mutations with major effects under laboratory conditions had variable and sometimes unexpectedly small effects in natural field environments.

Wilczek and Schmitt, along with Stephen Welch, a professor in the agronomy department at Kansas State University, then created models that charted precisely the rates of development for the genotypes at the field sites, using hourly temperature and light data collected at each site.

They showed when each genotype would reach its threshold and switch from a vegetative state to a flowering stage.

The models also accurately predicted the contribution of each genetic pathway to development and how the pathways are affected by environmental cues.

“With our model, we have shown that we can successfully predict how flowering is going to behave under a range of environmental conditions, not just those in which we originally grew our plants,” Wilczek said.

“Given the changing climate and the importance of flowering timing for wild plants and crop plants, this model can help us better understand how plants will respond to future conditions,” he added. (ANI)