RESUMO
The accuracy of quantitative trait loci (QTLs) identified using different sample sizes and marker densities was evaluated in different genetic models. Model I assumed one additive QTL; Model II assumed three additive QTLs plus one pair of epistatic QTLs; and Model III assumed two additive QTLs with opposite genetic effects plus two pairs of epistatic QTLs. Recombinant inbred lines (RILs) (50-1500 samples) were simulated according to the Models to study the influence of different sample sizes under different genetic models on QTL mapping accuracy. RILs with 10-100 target chromosome markers were simulated according to Models I and II to evaluate the influence of marker density on QTL mapping accuracy. Different marker densities did not significantly influence accurate estimation of genetic effects with simple additive models, but influenced QTL mapping accuracy in the additive and epistatic models. The optimum marker density was approximately 20 markers when the recombination fraction between two adjacent markers was 0.056 in the additive and epistatic models. A sample size of 150 was sufficient for detecting simple additive QTLs. Thus, a sample size of approximately 450 is needed to detect QTLs with additive and epistatic models. Sample size must be approximately 750 to detect QTLs with additive, epistatic, and combined effects between QTLs. The sample size should be increased to >750 if the genetic models of the data set become more complicated than Model III. Our results provide a theoretical basis for marker-assisted selection breeding and molecular design breeding.
Assuntos
Mapeamento Cromossômico/métodos , Cromossomos de Plantas/genética , Plantas/genética , Locos de Características Quantitativas , Simulação por Computador , Epistasia Genética , Endogamia , Modelos Genéticos , Melhoramento Vegetal , Tamanho da Amostra , Seleção GenéticaRESUMO
The study of quantitative trait effects is of great significance for molecular marker-assisted breeding. The accuracy of quantitative trait loci (QTL) mapping is the key factor affecting marker-assisted breeding, and is extremely significant. The effect of different heritability rates (10, 30, 50, 70, and 90%) on the accuracy of QTL mapping of five recombinant inbred lines (RILs) were analyzed via computer simulation. RILs display additive and epistatic genetic effects. The QTLs were analyzed using four different mapping procedures: multiple QTL model (MQM), composite interval mapping (CIM), multiple interval mapping (MIMR), and inclusive composite interval mapping (ICIM). The results revealed an increase in the QTL mapping accuracy and QTL detection power, and a decrease in the QTL interval range with the increase in heritability; conversely, an irregular number of false positive QTLs were generated. CIM and MQM only screen the additive and dominant effects; MIMR and ICIM screen the additive, dominant, and epistatic effects. The highest QTL detection power obtained using MQM and CIM was only 75%, while MIMR and ICIM showed a detection power of 100%. At heritability rates of more than 50 and less than 10%, the detection powers of the MIMR and ICIM procedures were >95 and <35%, respectively. QTL mapping has no significance at heritability rates <10%. The results of this study suggest that QTL mapping has significance at a heritability rate >30% (at least >10%) for practical marker-assisted breeding.