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HPC helps solve question of how a cell knows what to be when it grows up

Ohio State University systems biologist Dan Siegal-Gaskins is using HPC to help answer the question of how a cell knows what to turn into as it develops. To help him, he is studying the plant world’s answer to fruit flies, Arabidopsis thaliana (or mouse-ear cress)

At a specific phase of Arabidopsis leaf development, cells on the surface of the leaf receive genetic instructions to become either one of the majority ‘pavement’ cells or a large hair-like cell known as a trichome. The specific function of trichomes is unclear, although they may be involved in preventing infection, protecting delicate tissues on the underside of the leaf, or reducing the amount of water lost to evaporation.

…The mathematical model Siegal-Gaskins constructed consists of seven differential equations and twelve unknown factors. For his preliminary studies, he turned to OSC to choose random values for the unknowns and solve the equations for millions of different random value sets.

“Due to the large range of possible parameters and the complexity of the problem, we took advantage of OSC’s parallel processing capabilities and the MATLAB computing environment,” Siegal-Gaskins said. “This process was repeated for five million randomly-chosen parameter sets, and the set that gave us the closest agreement with experimentation was kept.”

It’s interesting that the team is using MATLAB for this problem — I’ve seen MATLAB function as a gateway into HPC for many teams of scientists that hadn’t previously used HPC before. I have a sense that its value in that role is seriously underestimated by mainstream HPC centers.

“Our bcMPI software, initially released in 2006, interfaces with HPC cluster technologies like PBS and Infiniband when executing MATLAB scripts on a cluster,” explained David Hudak, director of HPC engineering at OSC. “Over the last year, we have been working to improve the accessibility of parallel MATLAB. We designed Remote MATLAB Services (RMS) to enable our users to transition MATLAB scripts developed on their laptops to HPC resources. Dan was an early adopter of OSC RMS, and we learned a lot from his feedback. It was a very good fit for his needs.”

With the combination of computational modeling, literature-based analyses and laboratory experimentation, Siegal-Gaskins and Morohashi determined that the three cell fate proteins seem to constitute an “incoherent feed forward loop,” a relationship in which a master regulator (MR) triggers expression of two genes involved in the initiation of trichome cell development, one of which (G1) later suppresses expression of the other (G2).

More in the full story from OSC.

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