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Despite the recent rapid growth in genome-wide data, much of human variation remains entirely unexplained. A significant challenge in the pursuit of the genetic basis for variation in common human traits is the efficient, coordinated collection of genotype and phenotype data. We have developed a novel research framework that facilitates the parallel study of a wide assortment of traits within a single cohort. The approach takes advantage of the interactivity of the Web both to gather data and to present genetic information to research participants, while taking care to correct for the population structure inherent to this study design. Here we report initial results from a participant-driven study of 22 traits. Replications of associations (in the genes  OCA2 ,  HERC2 ,  SLC45A2 ,  SLC24A4 ,  IRF4 ,  TYR ,  TYRP1 ,  ASIP , and  MC1R ) for hair color, eye color, and freckling validate the Web-based, self-reporting paradigm. The identification of novel associations for hair morphology (rs17646946, near  TCHH ; rs7349332, near  WNT10A ; and rs1556547, near  OFCC1 ), freckling (rs2153271, in  BNC2 ), the ability to smell the methanethiol produced after eating asparagus (rs4481887, near  OR2M7 ), and photic sneeze reflex (rs10427255, near  ZEB2 , and rs11856995, near  NR2F2 ) illustrates the power of the approach.

Web-Based, Participant-Driven Studies Yield Novel Genetic Associations for Common Traits