$200k awarded to genomics researchers for developing technologies

Toronto, ON – The Ontario Genomics Institute (OGI) has announced the recipients of its SPARK program, which was launched in April this year to seed high-impact, high-risk technology development projects in genomics.

Four researchers have received $50,000 each to put towards developing technologies such as instrumentation, software and reagents that have the potential to impact genomics research.

“We received over 40 applications for our SPARK grants, all demonstrating creative and imaginative research ideas,” said Dr Mark Poznansky, president and CEO, OGI. “We launched this program to support Ontario’s researchers and their work that might not be readily funded by other programs, or viewed as too risky or lacking preliminary results. All recipients demonstrated innovative ideas that have clear potential to impact the way genomics research is carried out, as well as produce significant results.”

The four grant recipients are:

1) Dr Michael Brudno and Marc Fiume, University of Toronto, who will be developing a software platform known as MedSavant, which allows for DNA to be analyzed quickly identifying mutations that may cause disease development.

MedSavant is being developed as a specialized, user-friendly search engine for patient information, medical observations and genome sequencing data, which will make the discovery of disease origin and analysis more accessible to geneticists and medical professionals who are best placed to interpret the results and translate findings back to patients.

By the end of the six month duration of the project, they want to have a software prototype that The Centre for Applied Genomics at The Hospital for Sick Children can use to identify disease-causing mutations.

2) Dr Yu Sun and Dr Zhe Lu, University of Toronto, are looking to develop a prototype for automated pronuclear injection, which is the most common method used to inject genetic material into mouse embryos, allowing for gene function and regulation studies to model human diseases.

The creation of an automated pronuclear injection using computer vision microscopy and precision robotic control will permit a researcher to operate it with a few clicks of a computer mouse. Many of the difficult and time consuming steps, previously only able to be done by highly trained professionals, will be removed by making the process automated, while ensuring accuracy and success rates. The prototype will be developed over a period of 12 months.

3) Dr Andrei Yudin, University of Toronto, will develop a novel technology to rapidly identify small cyclic protein fragments that can be used as cell-permeable probes of protein function and potentially aid the development of a new class of therapeutic agents.

This builds on an increase in interest around therapeutic agents that are peptides and proteins, as opposed to traditional drugs which are small chemical molecules. Peptides and proteins are made of up amino acids, which humans naturally have, and thus are less likely to cause unwanted side effects when used as therapeutic agents. The challenge with using peptides and proteins is that they are not stable for long periods of time in the bloodstream and do not readily enter cells, where they need to exert their action. The novel technology the Yudin group will develop is designed to overcome these challenges.

4) Dr Brendan Frey and Dr Benjamin J Blencowe, University of Toronto, are developing a new internet-accessible portal that medical researchers can use to study how DNA mutations affect RNA splicing and the genetic determinants of diseases.

Building on earlier work where they developed a tool for predicting tissue-dependent splicing and associated genomic regulatory features, this project will result in better understanding of the involvement of alternative splicing processes and regulation on human disease for the scientific community, and will benefit the biology and medical communities by making available a catalogue of novel functional sites and combinations of RNA features, which can be used to identify corresponding cellular features and regulatory mechanisms in a disease-specific manner.