Efficiency of quantitative trait loci mapping under genotype x environment interaction

• Ano de defesa: 2022
• Autor(a) principal: David, Grace Sunshine
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade Federal de Viçosa; Genética e Melhoramento
• Palavras-chave em Português: Marcadores genéticos; Mapeamento cromossômico; Interação genótipo-ambiente; Genética Quantitativa
• Link de acesso: https://locus.ufv.br//handle/123456789/31517; https://doi.org/10.47328/ufvbbt.2022.797

Quantitative trait loci (QTL) mapping using simulation gives an opportunity to actually determine the number and positions of QTLs which cannot be done using field data. This study was carried out to assess the efficiency of quantitative trait loci mapping under genotype by environment interaction. In this investigation, we simulated 50 samples of 300 recombinant inbred lines (RILs) in six environments which were genotyped for 1000 single nucleotide polymorphism (SNPs) and phenotyped for grain yield. A total of six major and 190 minor QTLs (19 in each chromosome) were randomly distributed in the regions covered by the SNPs along ten chromosomes. The chromosome length was 200 cM and the average density was 2 cM. The average degree of dominance was 0.6. There were basically two scenarios for comparison in this investigation. The first (with genotype x environment effect) and the second (without genotype x environment effect). The QTL heritabilities ranged from 2.1 to 14% and the trait heritability across environments was within the range of 23 to 85%. The results across environments for the first scenario showed that QTL power of detection was 82% while bias and false positive rate (FPR) were 2.1 cM and 4.5% respectively. In the second scenario, power of detection was 86% while bias and FPR were 2.2 cM and 4.4% respectively. In the joint QTL mapping analysis, power of detection increased with higher QTL heritability and there was an effective control of false positive rate in the two scenarios. These results depict a real field data and shows the effectiveness of mapping QTLs across environment and its role in expression of quantitative traits. Keywords: Power of QTL detection, false positive rate, mapping precision, genotype by environment interaction.