06:18pm Tuesday 26 September 2017

Genetic 'Rosetta Stone' unveiled in Nature

A new paper in Nature describes the Drosophila Genetic Reference Panel, or DGRP, which provides the highest-resolution view to date of the genome structure and variation in a population of 192 fruit flies with diverse traits. 

The study was led by Trudy Mackay of North Carolina State University, in collaboration with the Human Genome Sequencing Center at Baylor College of Medicine and David Mittelman of Virginia Tech’s Virginia Bioinformatics Institute, as well as a large group of researchers around the world.

“One of the grand challenges of biology is to understand how genetic variants and environmental factors interact to produce variation in complex phenotypes such as height, behaviors, and disease susceptibility within populations. This effort has been stymied by the lack of knowledge of all genetic variants in a population of a genetically tractable model organism. The DGRP sequences provide such a resource,” Mackay noted.

It’s been known for a long time that genes often work in concert to produce different effects, or phenotypes. But determining the exact contribution of these genes and genetic changes within them to animal traits remains a key challenge in genetics.

That’s where model organisms like Drosophila melanogaster (the common fruit fly) shine. Using inbred strains of fruit flies in controlled environments, researchers can use whole genome data, which captures genetic changes at the nucleotide level, to better explain why strains exhibit variable traits. The DGRP acts as a “living library” of this information, helping researchers understand both common traits and rare variants. 

Mittelman, with support from the NVIDIA Foundation’s Compute the Cure Award, aided the study by analyzing genetic variation in the Drosophila population.  “To truly exploit whole genome sequencing as a means of determining the basis for traits and disease, it is critical to develop methods for detecting all forms of genetic variation. In this study, we developed a method for measuring tandem repeat variation, which has been shown to modulate gene function, traits, and disease,” said Mittelman. 

A companion paper describing this method has been recently accepted for publication which will enable others to exploit these tools in their research.

The study has far reaching effects that span animal breeding, pesticide development, and personalized medicine.

The Virginia Bioinformatics Institute at Virginia Tech is a premier bioinformatics, computational biology, and systems biology research facility that uses transdisciplinary approaches to science combining information technology, biology, and medicine. These approaches are used to interpret and apply vast amounts of biological data generated from basic research to some of today’s key challenges in the biomedical, environmental, and agricultural sciences. With more than 240 highly trained multidisciplinary, international personnel, research at the institute involves collaboration in diverse disciplines such as mathematics, computer science, biology, plant pathology, biochemistry, systems biology, statistics, economics, synthetic biology, and medicine. The large amounts of data generated by this approach are analyzed and interpreted to create new knowledge that is disseminated to the world’s scientific, governmental, and wider communities.

Tiffany L Trent 540-231-6822


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