Direct empirical support for the infinitesimal model comes from genomic variance analyses70, 71. Animal breeders have been using ‘genomic selection’ methods with great success for the past decade72, basing their selection of sires and dams on the overall predicted breeding value determined from the full set of genomic markers that capture variation distributed throughout the genome. Similarly in humans, by taking all nominally significant SNPs rather than just the GWAS significant ones, it is possible to capture much more of the genetic variance than is explained by the highly significant loci73,74 (see Box 2). A multivariate version of this approach, implemented by regression of phenotypic similarity on genetic relatedness, also implies that common variants capture the majority of the genetic variants71. Furthermore, partitioning of the genetic variance on a chromosome-by-chromosome basis, for a diverse set of traits, shows that the proportion of variance explained is consistently proportional to chromosome length75,76. Variance is distributed along all of the chromosomes, and is therefore attributable to hundreds of loci. Since common variants are used for the partitioning it is most parsimonious to conclude that they are responsible, and simulations of rare variants so distributed capture much less of the variance.
