Álvarez Castro, José MaríaYang, Rong Cai2021-01-212021-01-212011Genetica, volume 139, pages 1119–1134 (2011)0016-6707http://hdl.handle.net/10347/24268Quantitative genetics stems from the theoretical models of genetic effects, which are re-parameterizations of the genotypic values into parameters of biological (genetic) relevance. Different formulations of genetic effects are adequate to address different subjects. We thus need to generalize and unify them under a common framework for enabling researchers to easily transform genetic effects between different biological meanings. The Natural and Orthogonal Interactions (NOIA) model of genetic effects has been developed to achieve this aim. Here, we further implement the statistical formulation of NOIA with multiple alleles under Hardy–Weinberg departures (HWD). We show that our developments are straightforwardly connected to the decomposition of the genetic variance and we point out several emergent properties of multiallelic quantitative genetic models, as compared to the biallelic ones. Further, NOIA entails a natural extension of one-locus developments to multiple epistatic loci under linkage equilibrium. Therefore, we present an extension of the orthogonal decomposition of the genetic variance to multiple epistatic, multiallelic loci under HWD. We illustrate this theory with a graphical interpretation and an analysis of published data on the human acid phosphatase (ACP1) polymorphismeng© The Author(s) 2011. Open Access. This is an open access article distributed under the terms of the Creative Commons Attribution Noncommercial License (https://creativecommons.org/licenses/by-nc/2.0), which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are creditedhttps://creativecommons.org/licenses/by-nc/2.0Models of genetic effectsHardy–Weinberg disequilibriumMultiple allelesVariance decompositionAcid phosphatase polymorphismMultiallelic models of genetic effects and variance decomposition in non-equilibrium populationsjournal article10.1007/s10709-011-9614-91573-6857open access