In 1990, after several years of planning, the Human Genome Project (HGP) was launched. An ambitious international scientific project, the HGP sought to map and sequence all the genes in a representative human.
The project took 13 years and cost a billion dollars.
Today, thanks to massive technological advances, the same task can be done in an individual scientist’s lab for about a thousand dollars.
And it is being done in labs across the world, generating reams of genetic data. It turns out that even though we all have the same 30,000 genes, there’s a huge amount of variability in our DNA.
Brenda Andrews, director of the Donnelly Centre for Cellular and Biomolecular Research and a professor in the Department of Molecular Genetics, is at the helm of an ambitious new project to try to make sense of that variability. She and collaborators are poised to make the next great leap forward in our understanding of genetics — fulfilling the promise of the HGP.
In the post-HGP era, she says, genetic researchers look at single-nucleotide polymorphisms (SNPs), which are part of the genetic variation among people. “Sometimes individual SNPs or other changes in genes, have an obvious effect. For example, SNPs could change the function of an important protein, which may result in a disease. The effects of most SNPs, though, are not understood. But the spectrum of SNPs and other changes in each person’s genome is thought to influence susceptibility to disease, as well as our responses to drugs and the environment. For example, my genome might have the same version of a gene that is linked to a disease as yours, but you don’t get the disease and I do.”
Each person’s genome has 10 million SNPs, so trying to understand why one person gets a disease or has an adverse reaction to a drug when another doesn’t is a bit like finding the proverbial needle in the haystack.
“It’s become very apparent that there’s a lot more going on in our genomes than we ever understood,” says Andrews. “We haven’t really gotten that much better at predicting variable responses among people. We can read the genome, but now the challenge is to interpret. This is the next big frontier in genetics.”
With $1 million in funding from the Connaught Global Challenge Program, Andrews will lead a team intent on developing rules for understanding genomes. The funding, she says, will go primarily to bridging the gap between biomedical researchers and computer scientists.
“We are trying to bring together people who do human genetics and generate all these wonderful data with people who are trying to understand the rules using simpler experimental systems like yeast, worms and flies.”
Specifically, most of the Connaught funding will be used to recruit postdoctoral fellows with expertise in computer science.
“They will try to think of ways we can take what we are doing in model organisms and apply it to all these reams of disease gene information we’ve got in human genetics. There’s been very little cross fertilization between these fields and we think if we can fix this problem, it will really accelerate our progress.”
This juncture between biomedicine and computer science, Andrews says, is critical. It’s also largely unexploited because traditional grant-making panels tend to focus more narrowly on a single field.
“We biomedical people can apply and get money to do our projects, and the computational people can apply and get money to do what they do. But the interface is difficult to fund.”
Andrews’s goal for the two-year project is new protocol for understanding genomes that will be made freely available to the scientific community.
Understanding an individual’s genome, of course, has potentially huge implications for the field of personalized medicine. Imagine a future in which your doctor can tell which diseases you’re likely to get and help you head them off. Or, just as important, know in advance how medications will interact with your genome before you take them.
Says Andrews: “We think it could be transformative.”