000145489 001__ 145489
000145489 005__ 20241030091919.0
000145489 0247_ $$2doi$$a10.1534/genetics.116.199406
000145489 0248_ $$2sideral$$a100949
000145489 037__ $$aART-2017-100949
000145489 041__ $$aeng
000145489 100__ $$aVitezica, Zulma G.
000145489 245__ $$aOrthogonal estimates of variances for additive, dominance, and epistatic effects in populations
000145489 260__ $$c2017
000145489 5203_ $$aGenomic prediction methods based on multiple markers have potential to include nonadditive effects in prediction and analysis of complex traits. However, most developments assume a Hardy-Weinberg equilibrium (HWE). Statistical approaches for genomic selection that account for dominance and epistasis in a general context, without assuming HWE (e.g., crosses or homozygous lines), are therefore needed. Our method expands the natural and orthogonal interactions (NOIA) approach, which builds incidence matrices based on genotypic (not allelic) frequencies, to include genome-wide epistasis for an arbitrary number of interacting loci in a genomic evaluation context. This results in an orthogonal partition of the variances, which is not warranted otherwise. We also present the partition of variance as a function of genotypic values and frequencies following Cockerham’s orthogonal contrast approach. Then we prove for the first time that, even not in HWE, the multiple-loci NOIA method is equivalent to construct epistatic genomic relationship matrices for higher-order interactions using Hadamard products of additive and dominant genomic orthogonal relationships. A standardization based on the trace of the relationship matrices is, however, needed. We illustrate these results with two simulated F1 (not in HWE) populations, either in linkage equilibrium (LE), or in linkage disequilibrium (LD) and divergent selection, and pure biological dominant pairwise epistasis. In the LE case, correct and orthogonal estimates of variances were obtained using NOIA genomic relationships but not if relationships were constructed assuming HWE. For the LD simulation, differences were smaller, due to the smaller deviation of the F1 from HWE. Wrongly assuming HWE to build genomic relationships and estimate variance components yields biased estimates, inflates the total genetic variance, and the estimates are not empirically orthogonal. The NOIA method to build genomic relationships, coupled with the use of Hadamard products for epistatic terms, allows the obtaining of correct estimates in populations either in HWE or not in HWE, and extends to any order of epistatic interactions.
000145489 536__ $$9info:eu-repo/grantAgreement/ES/MINECO/CGL2016-80155
000145489 540__ $$9info:eu-repo/semantics/closedAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000145489 590__ $$a4.075$$b2017
000145489 591__ $$aGENETICS & HEREDITY$$b38 / 171 = 0.222$$c2017$$dQ1$$eT1
000145489 592__ $$a3.484$$b2017
000145489 593__ $$aGenetics$$c2017$$dQ1
000145489 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000145489 700__ $$aLegarra, Andrés
000145489 700__ $$aToro, Miguel A.
000145489 700__ $$0(orcid)0000-0001-6256-5478$$aVarona, Luis$$uUniversidad de Zaragoza
000145489 7102_ $$11001$$2420$$aUniversidad de Zaragoza$$bDpto. Anatom.,Embri.Genét.Ani.$$cÁrea Genética
000145489 773__ $$g206, 3 (2017), 1297-1307$$pGenet.$$tGENETICS$$x0016-6731
000145489 8564_ $$s744453$$uhttps://zaguan.unizar.es/record/145489/files/texto_completo.pdf$$yVersión publicada
000145489 8564_ $$s2796677$$uhttps://zaguan.unizar.es/record/145489/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000145489 909CO $$ooai:zaguan.unizar.es:145489$$particulos$$pdriver
000145489 951__ $$a2024-10-30-08:49:28
000145489 980__ $$aARTICLE