Impact of dominance and epistasis on the genetic make‐up of simulated populations under selection: a model development

Abstract

A two-locus genetic model was used to simulate different levels of additive, dominance, and additive-by-additive genetic effects. The character under phenotypic selection was controlled by 30 pairs of diallelic loci, located on different chromosomes. Initial gene frequencies were set to 0.5 for all loci and the recombination probability was 0.20 between adjacent loci. The broad-sense heritability was varied at levels of 0.03, 0.30, and 0.60. After building up a random mating population with 200 males and 400 females, the phenotypic best individuals per year were selected over 200 years (approx. 35 overlapping generations), keeping the population size constant. The results of the simulations showed extreme differences between eight models with the same initial heritability, but different amounts of additive, dominance, and additive-by-additive variance components. A model with additive, dominance, and additive-by-additive variance at the same initial magnitude, and negative dominance and positive additive-by-additive effect, led to the highest genetic response in the long term for all heritabilities simulated. The additive model showed the best selection advance in the short term. Some of the initial dominance and additive-by-additive variance was converted to additive genetic variance during the selection period, which in turn contributed to the selection response. ZUSAMMENFASSUNG: Auswirkungen von Dominanz and Epistasie auf den genetischen Aufbau von simulierten Populationen unter Selektion: Eine Modellentwicklung Ein 2-Locus-Genmodell wurde zur Simulation verschiedener Ausprägungen von additiven, Dominanz und additiv mal additiv genetischen Effekten verwendet. Das Merkmal under phänotypischer Selektion wurde von 30 diallelen Locuspaaren auf verschiedenen Chromosomen kontrolliert. Die Anfangsgenfrequenz wurde für alle Loci mit 0.5 angenommen und die Rekombinationsrate betrug 0.20 zwischen benachbarten Loci. Die Heritabilität im weiteren Sinn wurde zwischen 0.03, 0.30 und 0.60 variiert. Nach dem Aufbau einer Population durch Zufallspaarung von 200 männlichen und 400 weiblichen Individuen wurden die phänotypisch besten Individuen pro Jahr unter Konstanthaltung der Populationsgröße über einen Zeitraum von 200 Jahren (ca. 35 überlappende Generationen) selektiert. Die Ergebnisse der Simulationen zeigten extreme Unterschiede zwischen den acht Modellen mit der gleichen Anfangsheritabilität aber verschiedenen Anteilen von additiven, Dominanz und additiv mal additiven Varianzkomponenten. Ein Modell mit zu Beginn gleich hoher additiver, Dominanz und additiv mal additiver Varianz und negativem Dominanz- und positivem additiv mal additiven Effekt führte bei allen simulierten Heritabilitäten langfristig zum höchsten Selektionserfolg. Kurzfristig zeigte das additive Modell den höchsten Selektionsfortschritt. Ein Teil der Anfangs-Dominanz- und -Additiv mal additiv-Varianz wurde während der Selektionsperiode in additive Varianz umgewandelt, die wiederum zum Selektionserfolg beitrug.

The effect of non-additive genetic interactions on selection in multi-locus genetic models

“…Model 1 Model 1 was developed by Fuerst et al (1997), based on a model initially put forward by Mather and Jinks (1982). The trait is controlled by a variable number of locus pairs.…”

“…However, some theoretical studies of selection suggest that the level of additive variance can be sustained or even increased when non-additive variance is present (Gimelfarb 1989;Fuerst et al, 1997;Jannink, 2003;Carter et al, 2005), in a manner similar to the action of genetic drift. Experimental evidence for this phenomenon was found by Martinez et al (2000) when they selected for body fat in mice, and by Sorensen and Hill (1982) who performed a short-term selection experiment for abdominal bristle number in D. melanogaster.…”

“…Pairwise epistatic gene interactions affecting a trait have been simulated for the directional truncation selection process (Gill, 1965a-c;Young, 1966Young, , 1967Fuerst et al, 1997). However, few simulations have been performed on multiple interacting genes.…”

Optimization of a crossing system using mate selection

“…Wei proposed a selection index that combines information about crossbreds and purebreds (CCPS) to maximize the genetic response from a crossing system [27]. A number of studies have shown that selection response in crossbred performance can be increased by using CCPS [1][2][3]8,26,[28][29][30]. When using CCPS within index selection in the case of non-additive traits, two problems should be noted.…”

Efficient Markov Chain Monte Carlo Implementation of Bayesian Analysis of Additive and Dominance Genetic Variances in Noninbred Pedigrees

“…Hallander and Waldmann (2007) investigated the importance of nonadditive genetic interactions when truncation selection was applied to a breeding population. They found that nonadditive variance initially could be converted into additive genetic variance during truncation selection (see also Fuerst et al 1997). However, these issues need to be further investigated with pedigree-based statistical approaches.…”