Supercomputers have been brought in to identify how plants survive a changing climate.

Scientists using supercomputers hope their findings will increase basic understanding of plant adaptation, which can be applied to improve crops.

The computational biology study looked at the flowering mustard weed (Arabidopsis thaliana) on a genetic level.

“We found pretty good evidence, certainly the best evidence to date, that the evolution of gene expression is an important way that plant populations adapt to local environments,” said study co-author Jesse Lasky, a fellow of the Columbia University.

Arabidopsis was picked because it has one of the smallest genomes of any plant, and in 2000 it was the first plant genome to be completely sequenced.

Some plant biologists consider Arabidopsis to be the fruit fly of genetic research in their field.

Instead of knocking out or ramping up genes with genetic engineering, study leader Thomas Juenger is looking at natural variation in genes.

“We want to understand how they've evolved in response to the processes of natural selection and gene flow and mutation in the field,” he said.

Arabidopsis is perfect for the current study, because years of data have shown it can thrive in environments as diverse as Scandinavia, North Africa, and Central Asia.

The researchers say genes must play a big part in allowing it to live in so many areas.

Gene expression “... is the part of the organism that we show here is strongly involved in local adaptation to environment,” Lasky said.

Juenger says that the plants can cope with environmental change (including temperature, soil moisture, and insect attacks) by changing their gene expression.

“As a plant starts to sense dropping temperatures, a cascade of gene expression can allow the plant to acclimatise to cold temperatures, and in effect prepare itself for the coming freezing conditions,” Juenger said.

The scientists took genes they suspected triggered the cascade, and compared them with genomic data from previous studies that sampled Arabidopsis from populations throughout Europe and Asia.

They narrowed the reference data to 1,003 strains of the flowering mustard weed that showed changes in their response to their environment, but the scientists needed to know if they also showed changes in DNA along environmental gradients.

Such a pattern “suggests that there are changes in the DNA sequence that are adapted to those local conditions and that are associated with changes in gene expression,” Lasky said.

So they took the thousands of individual strains of Arabidopsis with hundreds of thousands of markers across the genome to the supercomputer clusters at the Texas Advanced Computing Center (TACC).

“It's impossible to do this on a standard desktop computer,” Juenger said.

“It requires some of the throughput that we can have on a cluster.”

The project was funded by the US National Science Foundation (NSF) iPlant Collaborative, which helps life scientists use high performance computers.

“iPlant, associated with TACC, has certainly been developing lots of new tools, simplifying computational tools for biologists, and giving us access to data storage as well as service units through high performance computing clusters like those at TACC,” Juenger remarked.

“It's a helpful, timely program that's impacting plant biologists in individual labs around the country.”