Postdoctoral Associate, Duke University
Recommended by David Goldstein, Duke University
NEW YORK (GenomeWeb) – Some genes can handle changes better than others, and figuring which gene is which will help researchers better interpret the coming piles of genomic data, said Slavé Petrovski.
"Certain genes have different intolerance and tolerance to genetic variation," Petrovski told GenomeWeb, "and that actually plays an important role when you are interpreting these genomes, especially the N-of-one cases."
As a postdoc at Duke, Petrovski is working on tools to make interpreting personal genomes easier. This, he said, involves tweaking some existing tools like Polyphen as well as determining which mutations researchers should actually give a second look versus ones that are likely benign changes.
Additionally, Petrovski is involved in investigating and interpreting sequence data from children with undiagnosed genetic disorders, and is involved in some larger-scale projects. For instance, he's a part of the Epi4K project that aims to sequence the exomes and genomes of some 4,000 epilepsy patients to try to get a handle on the complex causes of epilepsy.
Paper of note
The Epi4K project published a Nature paper in 2013 that Petrovski took part in that linked a handful of de novo mutations to epileptic encephalopathies. The consortium sequenced the exomes of some 264 trios — probands and their parents — to find 329 de novo mutations. Nine genes harbored mutations that were present in more than one proband, A likelihood analysis the researchers performed found that the probands had an excess of de novo mutations in genes that were intolerant to such functional genetic variation, including GABRB3 and ALG13.
In a separate paper, appearing in PLOS Genetics, Petrovski and his colleagues at Duke describe their effort to create an intolerance scoring system.
"We can use information about where mutations occur, not just variant effect predictions, to help us better interpret individual genomes, again the N-of-one cases," Petrovski said.
He and his colleagues reported that by drawing on data from the more than 6,500 exome sequences from the NHLBI Exome Sequencing Project, they could show that genes that are behind Mendelian diseases are much more intolerant to functional genetic variation than genes that aren't known to cause disease.
With the advent of machines like Illumina's X Tens, Petrovski noted that millions of new genome sequences would be churned out, providing both a challenge and an opportunity for genome interpretation.
The field, Petrovski noted, has gotten pretty good at interpreting what protein-coding mutations mean, but non-coding regions still pose a bit of a challenge, and having a greater amount of data will help researchers get that better understanding.
"The question I often get now is: 'How are we going to interpret? Why should we do whole-genome sequencing data if we can't interpret it well?'" Petrovski said. "That's not a reason not to generate it. Generating the data is what will help us learn how to interpret it better."
And the Nobel goes to…
One possible invention that Petrovski said could be Nobel-worthy would be if there were a streamlined way to take a patients' cells, turn them into induced pluripotent stem cells, and then differentiate them into the cell type their disease is affecting — if, for instance, the patient has a neurological disease, those cells would transform into neurons. Then, this approach would use high-throughput screening to uncover a compound that returns those diseased cells to the wild-type, non-diseased state.
"When that's around — and it's not too hard to imagine that will be a possibility in the near future — that would revolutionize things, I think, quite a bit," Petrovski said.
This is the eighth in a series of Young Investigator Profiles for 2015 that will appear on GenomeWeb over the next few months.