A large collaborative（合作的，协作的） study has added to the growing list of genetic¹ variants³ that determine how tall a person will be. The research, published by Cell Press on December 30 in the American Journal of Human Genetics, identifies uncommon⁴ and previously⁵ unknown variants associated with height and might provide insight into the genetic architecture（建筑学） of other complex traits. Although environmental variables can impact attained⁶ adult height, it is clear that height is primarily determined⁷ by specific alleles（等位基因） that an individual inherits（继承） . Height is thought to be influenced by variants in a large number of genes⁸, and each variant² is thought to have only a small impact on height. However, the genetics of height are still not completely understood. "All of the variants needed to explain height have not yet been identified, and it is likely that the additional genetic variants are uncommon in the population or of very small effect, requiring extremely large samples to be confidently identified," explains Dr. Hakon Hakonarson from The Children's Hospital of Philadelphia.

To search for genetic variants associated with adult height, researchers performed a complex genetic analysis of more than 100,000 individuals. "We set out to replicate⁹（复制，折叠） previous genetic associations with height and to find relevant genomic locations not previously thought to underpin¹⁰ this complex trait" explains Dr. Brendan Keating, also from The Children's Hospital of Philadelphia. The authors report that they identified 64 height-associated variants, two of which would not have been observed without such a large sample size and the inclusion（包含） of direct genotyping of uncommon single-nucleotide polymorphisms (SNPs单核苷酸多态位点). A SNP is a variation in just one nucleotide of a genetic sequence; think of it as a spelling change affecting just one letter in an uncommonly¹¹ long word.

These results suggest that genotyping arrays with SNPs that are relatively¹² rare and occur in less than 5% of the population have the ability to capture new signals and disease variants that the common SNP arrays missed (i.e., 30 new signals in this study), as long as sample sizes are large enough. These low-frequency variants also confer greater effect sizes and, when associated with a disease, could be a lot closer to causative than more common variants. "The increased power to identify variants of small effect afforded by large sample size and dense¹³ genetic coverage¹⁴ including low-frequency SNPs within loci（轨迹，地点） of interest has resulted in the identification of association between previously unreported genetic variants and height," concludes Dr. Keating.