First of all, this paper is part of a very recent shift in human genetics. This shift occurred away from common gene variant association studies that require gigantic cohorts and often only find small effects, to hunts for rare alleles in cohorts as small as one to four individuals. This approach can find causative alleles with strong enough effects to be not only of research significance but also diagnostic significance as well. Other examples are flowing out from the Shendure, Lupski, and Lifton groups. The reason is that sequencing costs have dropped about 40,000-fold over the past five years (down to $1,500 per 40X genome).

Secondly, this paper marks the triumphant return of small family studies that help technically to improve accuracy. They also help the interpretative weeding through dozens of potentially deleterious rare alleles for the ones which are actually causative.

View all comments by George Church

This study, while not all that revelatory or surprising, establishes a new benchmark in the field of genetics research that has been highly anticipated, especially during the past few years' next-generation sequencing horse race. Whichever platform(s) emerge as the winner, the heady reality is setting in that affordable, high-quality, whole-genome data is virtually in our grasp, taking genetics research to a whole new plane.

Technology is often the driver that ratchets up scientific discovery, but new tools can also expose the shortcomings of other aspects of research (the constant “whack-a-mole” problem...you solve one problem only to find another). What about the phenotypic data? It's one thing to correlate genetic variants—whether collected via SNP genotyping or full sequencing—to clear-cut disease phenotypes, such as those studied here, but quite another for complex diseases, like Alzheimer's, where the diagnosis/phenotype is not as straightforward and where the cause is a combination of genes and environment. These problems are just more opportunities for innovators to...  Read more

This study, while not all that revelatory or surprising, establishes a new benchmark in the field of genetics research that has been highly anticipated, especially during the past few years' next-generation sequencing horse race. Whichever platform(s) emerge as the winner, the heady reality is setting in that affordable, high-quality, whole-genome data is virtually in our grasp, taking genetics research to a whole new plane.

Technology is often the driver that ratchets up scientific discovery, but new tools can also expose the shortcomings of other aspects of research (the constant “whack-a-mole” problem...you solve one problem only to find another). What about the phenotypic data? It's one thing to correlate genetic variants—whether collected via SNP genotyping or full sequencing—to clear-cut disease phenotypes, such as those studied here, but quite another for complex diseases, like Alzheimer's, where the diagnosis/phenotype is not as straightforward and where the cause is a combination of genes and environment. These problems are just more opportunities for innovators to tackle. In the meantime, tremendous technological progress, as evidenced by this study, is cause for celebration.

View all comments by Linda Avey