Three minutes to unravel DNA data

SOME professors can barely choke out a coherent, plain-English explanation about their field of study after a lifetime of pursuing it, so Michael Imelfort has the drop on them.

SOME professors can barely choke out a coherent, plain-English explanation about their field of study after a lifetime of pursuing it, so Michael Imelfort has the drop on them.

The 30-year-old doctoral student at the University of Queensland has just won the Three Minute Thesis competition for spruiking his topic -- the assembly of short-read DNA sequence data -- in a way that's comprehensible to an intelligent, but not expert, audience.

He managed to explain his thesis, entitled The Development and Application of Bioinfomatics and Statistical Tools for the Assembly and Analysis of Plant Genome Sequence Data, without notes and with the aid of a single PowerPoint slide.

The slide was a fabricated cover of a puzzle, of the kind popular with 11-year-olds and sold in good toy shops. Even better, he had one of an orator's most powerful tools: an excellent image, the jigsaw puzzle.

"My project involves making programs that will solve complex puzzles to sequence DNA," says Imelfort, a student at UQ's land, crop and plant sciences school.

He works with very large text files of data produced by new generation sequencing machines, consisting almost entirely of the letters A, C and G.

Unfortunately, these strings are in no particular order and reassembling them into the correct sequence is fiendishly complicated. "People like me take data and put it into a readable form so scientists can use it," Imelfort says.

An advantage of the image he uses is that people are likelier to understand that sometimes jigsaw puzzles are not perfectly made: "People cut some pieces wrong and they will never fit. That's what it is like with DNA: they make multiple copies of the pieces so that those that don't fit can be filtered out."

Only a handful of scientists are in the race to write the algorithm to most quickly and accurately reassemble the sequence, he says.

"The idea is to reduce the cost of sequencing and increase volume of organisms that can be sequenced but, until we can process this data efficiently, the machines are not being used to their full potential."

The practical value of all this is that once genomes are mapped and compared, advantages from one plant can be bred into others and thus progress is achieved.

But that's not his field: his job is to get the program written that can crunch that data speedily.

Watch and learn, professors.