naa a22 4500 510730159 CHVBK 20180411082949.0 cr unu---uuuuu 180411e20130201xx s 000 0 eng 10.1007/s11295-012-0521-8 doi (NATIONALLICENCE)springer-10.1007/s11295-012-0521-8 Accounting for competition in genetic analysis, with particular emphasis on forest genetic trials [Elektronische Daten] [João Costa e Silva, Richard Kerr] Available experimental evidence suggests that there are genetic differences in the abilities of trees to compete for resources, in addition to non-genetic differences due to micro-site variation. The use of indirect genetic effects within the framework of linear mixed model methodology has been proposed for estimating genetic parameters and responses to selection in the presence of genetic competition. In this context, an individual's total breeding value reflects the effects of its direct breeding value on its own phenotype and its competitive breeding value on the phenotype of its neighbours. The present study used simulated data to investigate the relevance of accounting for competitive effects at the genetic and non-genetic levels in terms of the estimation of (co)variance components and selection response. Different experimental designs that resulted in different genetic relatedness levels within a neighbourhood and survival were other key issues examined. Variances estimated for additive genetic and residual effects tended to be biased under models that ignored genetic competition. Models that fitted competition at the genetic level only also resulted in biased (co)variance estimates for direct additive, competitive additive and residual effects. The ability to detect the correct model was reduced when relatedness within a neighbourhood was very low and survival decreased. Selection responses changed considerably between selecting on breeding value estimates from a model ignoring genetic competition and total breeding estimates using the correct model. Our results suggest that considering a genetic basis to competitive ability will be important to optimise selection programmes for genetic improvement of tree species. Springer-Verlag, 2012 Competition nationallicence Direct and indirect genetic effects nationallicence Linear mixed model nationallicence Genetic (co)variance components nationallicence BLUP nationallicence Response to selection nationallicence Costa e Silva João Centro de Estudos Florestais, Departamento dos Recursos Naturais, Ambiente e Território, Instituto Superior de Agronomia, Universidade Técnica de Lisboa, Tapada da Ajuda, 1349-017, Lisboa, Portugal aut Kerr Richard PlantPlan Genetics Pty Ltd, School of Plant Science, University of Tasmania, Private Bag 55, 7001, Hobart, Tasmania, Australia aut Tree Genetics & Genomes Springer-Verlag 9/1(2013-02-01), 1-17 1614-2942 9:1<1 2013 9 11295 https://doi.org/10.1007/s11295-012-0521-8 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11295-012-0521-8 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Costa e Silva João Centro de Estudos Florestais, Departamento dos Recursos Naturais, Ambiente e Território, Instituto Superior de Agronomia, Universidade Técnica de Lisboa, Tapada da Ajuda, 1349-017, Lisboa, Portugal aut NATIONALLICENCE 700 1- Kerr Richard PlantPlan Genetics Pty Ltd, School of Plant Science, University of Tasmania, Private Bag 55, 7001, Hobart, Tasmania, Australia aut NATIONALLICENCE 773 0- Tree Genetics & Genomes Springer-Verlag 9/1(2013-02-01), 1-17 1614-2942 9:1<1 2013 9 11295 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer