ADAM-multi: software to simulate complex breeding programs for animals and plants with different ploidy levels and generalized genotypic effect models to account for multiple alleles

Stochastic simulation software, ADAM, has been developed for the purpose of breeding optimization in animals and plants, and for validation of statistical models used in genetic evaluations. Just like other common simulation programs, ADAM assumed the bi-allelic state of quantitative trait locus (QT...

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Main Authors: Thinh Tuan Chu, Just Jensen
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-02-01
Series:Frontiers in Genetics
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Online Access:https://www.frontiersin.org/articles/10.3389/fgene.2025.1513615/full
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author Thinh Tuan Chu
Thinh Tuan Chu
Just Jensen
author_facet Thinh Tuan Chu
Thinh Tuan Chu
Just Jensen
author_sort Thinh Tuan Chu
collection DOAJ
description Stochastic simulation software, ADAM, has been developed for the purpose of breeding optimization in animals and plants, and for validation of statistical models used in genetic evaluations. Just like other common simulation programs, ADAM assumed the bi-allelic state of quantitative trait locus (QTL). While the bi-allelic state of marker loci is due to the common choice of genotyping technology of single nucleotide polymorphism (SNP) chip, the assumption may not hold for the linked QTL. In the version of ADAM-Multi, we employ a novel simulation model capable of simulating additive, dominance, and epistatic genotypic effects for species with different levels of ploidy, providing with a more realistic assumption of multiple allelism for QTL variants. When assuming bi-allelic QTL, our proposed model becomes identical to the model assumption in common simulation programs, and in genetic textbooks. Along with the description of the updated simulation model in ADAM-Multi, this paper shows two small-scale studies that investigate the effects of multi-allelic versus bi-allelic assumptions in simulation and the use of different prediction models in a single-population breeding program for potatoes. We found that genomic models using dense bi-allelic markers could effectively predicted breeding values of individuals in a well-structure population despite the presence of multi-allelic QTL. Additionally, the small-scale study indicated that including non-additive genetic effects in the prediction model for selection did not lead to an improvement in the rate of genetic gains of the breeding program.
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spelling doaj-art-cd83a781502841f39783a1b08019d64c2025-02-10T06:49:01ZengFrontiers Media S.A.Frontiers in Genetics1664-80212025-02-011610.3389/fgene.2025.15136151513615ADAM-multi: software to simulate complex breeding programs for animals and plants with different ploidy levels and generalized genotypic effect models to account for multiple allelesThinh Tuan Chu0Thinh Tuan Chu1Just Jensen2Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, DenmarkFaculty of Animal Science, Vietnam National University of Agriculture, Hanoi, VietnamCenter for Quantitative Genetics and Genomics, Aarhus University, Aarhus, DenmarkStochastic simulation software, ADAM, has been developed for the purpose of breeding optimization in animals and plants, and for validation of statistical models used in genetic evaluations. Just like other common simulation programs, ADAM assumed the bi-allelic state of quantitative trait locus (QTL). While the bi-allelic state of marker loci is due to the common choice of genotyping technology of single nucleotide polymorphism (SNP) chip, the assumption may not hold for the linked QTL. In the version of ADAM-Multi, we employ a novel simulation model capable of simulating additive, dominance, and epistatic genotypic effects for species with different levels of ploidy, providing with a more realistic assumption of multiple allelism for QTL variants. When assuming bi-allelic QTL, our proposed model becomes identical to the model assumption in common simulation programs, and in genetic textbooks. Along with the description of the updated simulation model in ADAM-Multi, this paper shows two small-scale studies that investigate the effects of multi-allelic versus bi-allelic assumptions in simulation and the use of different prediction models in a single-population breeding program for potatoes. We found that genomic models using dense bi-allelic markers could effectively predicted breeding values of individuals in a well-structure population despite the presence of multi-allelic QTL. Additionally, the small-scale study indicated that including non-additive genetic effects in the prediction model for selection did not lead to an improvement in the rate of genetic gains of the breeding program.https://www.frontiersin.org/articles/10.3389/fgene.2025.1513615/fullstochastic breeding programgenotypic modelpolyploidydominanceepistasis
spellingShingle Thinh Tuan Chu
Thinh Tuan Chu
Just Jensen
ADAM-multi: software to simulate complex breeding programs for animals and plants with different ploidy levels and generalized genotypic effect models to account for multiple alleles
Frontiers in Genetics
stochastic breeding program
genotypic model
polyploidy
dominance
epistasis
title ADAM-multi: software to simulate complex breeding programs for animals and plants with different ploidy levels and generalized genotypic effect models to account for multiple alleles
title_full ADAM-multi: software to simulate complex breeding programs for animals and plants with different ploidy levels and generalized genotypic effect models to account for multiple alleles
title_fullStr ADAM-multi: software to simulate complex breeding programs for animals and plants with different ploidy levels and generalized genotypic effect models to account for multiple alleles
title_full_unstemmed ADAM-multi: software to simulate complex breeding programs for animals and plants with different ploidy levels and generalized genotypic effect models to account for multiple alleles
title_short ADAM-multi: software to simulate complex breeding programs for animals and plants with different ploidy levels and generalized genotypic effect models to account for multiple alleles
title_sort adam multi software to simulate complex breeding programs for animals and plants with different ploidy levels and generalized genotypic effect models to account for multiple alleles
topic stochastic breeding program
genotypic model
polyploidy
dominance
epistasis
url https://www.frontiersin.org/articles/10.3389/fgene.2025.1513615/full
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AT thinhtuanchu adammultisoftwaretosimulatecomplexbreedingprogramsforanimalsandplantswithdifferentploidylevelsandgeneralizedgenotypiceffectmodelstoaccountformultiplealleles
AT justjensen adammultisoftwaretosimulatecomplexbreedingprogramsforanimalsandplantswithdifferentploidylevelsandgeneralizedgenotypiceffectmodelstoaccountformultiplealleles