Human genetic diversity named top breakthrough

3 minute read

This week's Science includes an article by Elizabeth Pennisi naming "Human Genetic Variation" as the science breakthrough of the year.

Less than a year ago, the big news was triangulating variation between us and our primate cousins to get a better handle on genetic changes along the evolutionary tree that led to humans. Now, we have moved from asking what in our DNA makes us human to striving to know what in my DNA makes me me.
Techniques that scan for hundreds of thousands of genetic differences at once are linking particular variations to particular traits and diseases in ways not possible before. Efforts to catalog and assess the effects of insertions and deletions in our DNA are showing that these changes are more common than expected and play important roles in how our genomes work--or don't work. By looking at variations in genes for hair and skin color and in the "speech" gene, we have also gained a better sense of how we are similar to and different from Neandertals.

This is a very wide story, encompassing distinct studies that really have little to do with each other. For example, the restless leg syndrome gene association study doesn't connect in any simple way to the study of selection on amylase copy number variants, both mentioned in the article.

But what has actually changed in the last two to three years is the availability of large-scale genotyping of marker arrays. These underlie the HapMap and have enabled genome-wide association studies. The article puts these methods together with large-scale sequencing projects, like ENCODE and the Personal Genome Project. These sequencing efforts haven't yet given rise to a clear picture of diversity, but mainly because they haven't been around as long.

Probably the most important aspect accelerating research is the public accessibility of these datasets. Once a whole lot of people are using the same kinds of data, tremendous new synergies become possible. Of course, that also raises a frightening specter to many people -- if anyone can use the data generated by these projects, that will include people with a diversity of objectives.

Hence, discovering and characterizing human genetic diversity comes as a two-edged sword to many people. Demonstrating significant health impacts of human diversity has the potential to bring a truly individualized treatment of disease and reduction of risk. But recognizing that people are really different demands that we develop a more sophisticated approach to teaching human genetics. The "99 percent chimpanzee" and other factoids about human similarity are no longer sufficient in the age when anybody can scan freely-accessible genomes.

In a related article, Jocelyn Kaiser covers the prospects for personal genomics:

A glimpse of one's genome is already within the reach of ordinary people, thanks to several companies. They include 23andMe, which has financing from Google and may let users link to others with shared traits; Navigenics, which will screen for about 20 medical conditions; and deCODE Genetics in Iceland, a pioneer in disease gene hunting. For $1000 to $2500, these companies will have consumers send in a saliva sample or cheek swab, then use "SNP chips" to scan their DNA for as many as 1 million markers. The companies will then match the results with the latest publications on traits, common diseases, and ancestry.

A million SNPs is enough to do a lot. Not everything you would want to do, possibly. But almost certainly everything that it would be economical for the pharmaceutical industry to develop treatments or other approaches to address.

The articles don't make much of the evolution of all this human genetic variation, but as things develop there will be a heavy hand of recent selection in the results. Long, common associations are mostly there because of selection. These personal genomic approaches assume much about the process of human genetic diversification -- the more that recent variants have been selected, the more useful a "personal genomics" is likely to be.