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Imaging Gene Regulation

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  • Title: Assistant Professor, Biostatistics & Bioinformatics, Duke University
  • Education: PhD, University of Erlangen-Nuremberg, 2002
  • Recommended by: Hunt Willard

As a computer scientist with a biology background, Uwe Ohler knows a thing or two about collaboration. On his website at Duke University's Institute for Genome Sciences and Policy, where he's an assistant professor in bio-statistics and bioinformatics, he's listed several current collaborators. They range from colleagues at the IGSP to researchers at the University of Chicago and the Max Planck Institute. For the kind of work he does — computationally predicting and mapping gene regulatory elements — it's essential to involve a multi-disciplinary cast.

Ohler's lab focuses on transcription start site and microRNA target site prediction. While his lab aims to map regulatory sequences, the team is also putting these predictions to functional test using high-throughput microscopy. To study gene expression in plant roots, incorporating imaging allows Ohler to "look at individual expression profiles from a single gene or a few genes, and look at that in a living organism under the microscope — and actually be able to tell exactly where and when was the gene expressed and how that could change under different conditions," he says. "Microarrays only tell us the average story."

Recently, Ohler won a Human Frontier Science Program. In this work, Ohler looks at individual expression patterns of a handful of genes in Drosophila embryos under the microscope, and then compares those to patterns in different species and back to the regulatory DNA sequences. "Ultimately what we hope to do is see where the sequences change and how that correlates with a change in the expression of the genes," he says.

Ohler started his career majoring in computer science and minoring in biology at University of Erlangen-Nuremberg in Germany. It was while working on his honors thesis that he began looking at promoter sequences. That "got me hooked on this whole area of computational biology," he says. During his PhD at the University of Erlangen, he spent three years as a visiting researcher for the Berkeley Drosophila Genome Project on a grant from the Boehringer Ingelheim Foundation.

Publications of note

In a 2006 Bioinformatics paper entitled "Quantification of transcription factor expression from Arabidopsis images," Ohler and colleagues imaged the expression pattern of one gene, tagged with a green fluorescent marker, in many different tissues, and then mapped that data back to an atlas image in order to get relative expression values. "We have been working on a robotic platform to scale up the generation of images," he says, "and a good property is that we can do that in living plants and thus get expression over time from a single specimen."

Looking ahead

Ohler sees more and more people taking advantage of high-throughput microscopic image data to decipher gene networks, particularly in the areas of gene regulation, gene expression, and regulatory genomics.  He expects that, in time, image data will be "more high throughput and available."

Ohler also sees next-generation sequencing tools as having a big impact on his work. In contrast to microscopy, "the technology's not going to be the limiting part," he says. "It will be more a matter of keeping up with the pace of the technology development as a computational person and adjusting our models to actually deal with that data in terms of just basic infrastructure."

And the Nobel goes to …

If he were to win the Nobel, Ohler suggests petitioning the Nobel committee to add another category to include computational research. "I think it would be pretty astonishing in general if somebody wins for work that is mostly theoretical."

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