Skip to Main Content

Identifying the Genomic Basis of Biological Variation: Discovering the Genomic Basis of Human Variation

By Diane P. Genereux

Discovering the Genomic Basis of Human Variation

The finding of the Human Genome Project that much of biological variation cannot be explained by the presence or absence of specific genes, or even by the specific sequences of the DNA that encodes them, raised essential questions that researchers around the world are still working to address: Which parts of the genome are relevant to specific biological traits? How can we turn our emerging understanding of genome biology into specific therapeutics to improve human health? And how can we ensure that these advances benefit people all over the world, rather than only those living in the most-resourced regions? Many of the most powerful methods now in use for discovering the genomic basis of intraspecific biological variation can be traced to interest in human disease, which has inspired further questions, for example: What genetic features can explain, or help to explain, human traits like height, blindness, and autism spectrum disorder?

Genome-wide association studies (GWAS), introduced in 2005, remains the most broadly applicable approach for identifying trait-relevant variation.Though the details of GWAS implementation can be complex, the motivating logic is surprisingly simple. If one knows that some individuals have a trait of interest and others do not, then relevant genetic differences must reside in parts of the genome that differ between the two groups, regardless of whether or not those differences are within protein-coding regions. In one of the earliest GWAS projects, Robert Klein and colleagues searched for genetic variants associated with macular degeneration onset, a decline in vision that can result in blindness in elderly individuals. Their population-based comparison of individuals with and without this condition, “Complement Factor H Polymorphism in Age-Related Macular Degeneration,” identified a disease-associated change within a gene that had previously been implicated in this same disease using family-based studies.

While the review article by Shiro Ikegawa, “A Short History of the Genome-Wide Association Study,” provides a critical review of the history of GWAS, an account by T. M. Frayling, “Genome-Wide Association Studies: The Good, the Bad and the Ugly,” emphasizes aspects of GWAS that are yet to be realized, and Ruth Loos, in “15 Years of Genome-Wide Association Studies and No Signs of Slowing Down,” points to the potential power of more detailed phenotyping to enable discovery of more specific associations. Meanwhile Ben Hayes, in his contributed chapter “Overview of Statistical Methods for Genome-Wide Association Studies (GWAS),” reviews the approaches currently applied for assessing statistical significance in the common scenario where a given genetic variant is more common but not universal among individuals with a disease of interest.