Data from: Pleiotropy can be effectively estimated without counting phenotypes through the rank of genotype-phenotype map
Gu, Xun (2015), Data from: Pleiotropy can be effectively estimated without counting phenotypes through the rank of genotype-phenotype map, Dryad, Dataset, https://doi.org/10.5061/dryad.s84fm
Though pleiotropy, the capability of a gene affecting multiple phenotypes, has been well-known as one of common gene properties, a quantitative estimation remains a great challenge, simply because of the phenotype complexity. Not surprisingly, it is hard for general readers to understand how, without counting phenotypes, gene pleiotropy can be effectively estimated from the genetics data. In this article we extensively discussed the Gu-2007-method (Genetics 175: 1813-1822) that estimated pleiotropy from the protein sequence analysis. We have shown that this method is actually to estimate the rank (K) of genotype-phenotype mapping that can be concisely written as K=min(r, Pmin), where Pmin is the minimum pleiotropy among all legitimate measures including the fitness components, and r is the rank of mutational effects of an amino acid site. Together, the 'effective gene pleiotropy' (Ke) estimated by Gu-2007-method has the following meanings: (i) Ke is an estimate of K=min(r, Pmin), the rank of genotype-phenotype map. (ii) Ke is an estimate for the minimum pleiotropy Pmin only if Pmin < r. (iii) Gu-2007 method attempted to estimate the pleiotropy of amino acid sites, a conserved proxy to the true gene pleiotropy. (iv) With a sufficiently large phylogeny such that the rank of mutational effect at an amino acid site is r→19, one can estimate Pmin between 1 and 19. And (v) Ke is a conserved estimate of K because those slightly affected components in fitness have been effectively removed by the estimation procedure. Besides, we conclude that mutational pleiotropy (number of traits affected by a single mutation) cannot be estimated without knowing the phenotypes.