Enhancing Genomic Research Collaboration: A New Database

Sharing datasets that reveal the function of genomic variants in health and disease has become easier with the launch of a new, open-source database called MaveDB presented today in Genome Biology. MaveDB is a repository for data from experiments called MAVEs (multiplex assays of variant effect) that systematically measure the impact of thousands of individual sequence variants on a gene’s function. These experiments can provide valuable information about how proteins are produced by that gene function, how variants in that gene may contribute to disease, and how to engineer synthetic versions of naturally occurring proteins that are more effective than the original protein.

“In the past, researchers had to focus on a handful of changes in a gene to understand its function. It was too complex to generate the data from an exhaustive scan of variants of a gene that might be hundreds or thousands of bases in length,” says senior author Alan Rubin of the Walter and Eliza Hall Institute in Australia. “The development of MAVEs provided a way for researchers to experimentally measure every single genetic change in a gene with its functional consequence. These assays can handle tens of thousands of genetic variants, allowing researchers to home in on the relevant changes and place them in context.”

However, until now, MAVE data have existed in isolation. Data from individual studies were uploaded to journal websites when research papers were published or else provided upon request to other researchers.

“This made it hard for researchers to access the data of other groups, or even know that a particular MAVE experiment had been done. So it potentially hindered collaborations and the progress of genomics research,” Rubin says. “MaveDB makes it easier for scientists to share their datasets in a single location, using a flexible format that is applicable to multiple research fields, and enables other scientists to easily access this data to enhance their research. We’ve also ensured MaveDB can ‘talk’ to other databases to add an extra level of collaborative capacity.”

In addition to establishing MaveDB, the team also developed data visualization software called MaveVis that makes it easier for researchers to understand and interpret the results of MAVE experiments. “MaveVis provides an immediate and consistent display for MAVE data, including valuable annotations such as protein structure information, that will accelerate collaborative research,” Rubin says.

Image: Sharing datasets that reveal the function of genomic variants in health and disease has become easier with the launch of a new, open-source database called MaveDB. Image courtesy of Walter and Eliza Hall Institute, Australia.