Efficacy of population structure analysis with breeding populations and inbred lines

Abstract

The objective was to assess by simulation the efficacy of population structure analysis in plant breeding. Twelve populations and 300 inbred lines were simulated and genotyped using 100 microsatellite loci. The experimental material included populations with and without admixture, ancestry relationship and linkage disequilibrium, and with distinct levels of genetic differentiation and effective sizes. The analyses were performed using Structure software and employed all available models. For all the group number (K) tested, for both populations and inbred lines, the admixture model with correlated allelic frequencies provided the highest value for the logarithm of the marginal likelihood. Fitting appropriate model and using adequate sample size for individuals and markers, Structure was effective in identifying the correct population structure, migrants and individuals with genome from distinct populations. The linkage model did not result in an improvement in clustering relative to the admixture model with correlated allelic frequencies. The inclusion of prior information did not change the results; for some K values the analyses showed slight higher values of the marginal likelihood. The reduction in the number of individuals and markers negatively affected the results. There was a high variation in the most probable K value between the evaluated methods.

Variability and Genetic Structure in Populations of Arrabidaea bilabiata (Sprague) Sandwith in the Amazonas State

“…To perform the analyses, the mixture model with correlated frequency and clustering (K) values were considered, ranging from 1 to 8, with five repetitions for each tested K value. The determination of the most likely K value was taken according to the ΔK criterion described by Evanno et al (2005) from the Structure Harvester software (Earl & Vonholdt, 2011) and the IPlateau method described by Viana et al (2013). The graphical visualization of the association coefficients for genotypes was generated by the Distruct software (Rosenberg, 2003), using the repetition that provided the greatest value of the likelihood function logarithm.…”

“…This result corroborates the UPGMA cluster analysis and separates the populations sampled in Autazes from the others. However, the Iplateau method (Viana et al, 2013) suggests that the most likely number of clusters is K = 6, which separated effectively all sampled populations, according to the geographical origin.…”

“…These observations are possible due to an increased alignment of the graphical analysis results, according to the tested K. The Structure software separates the most disparate individuals in more distant populations and then, when increasing the number of tested groups, it identifies the most similar populations. Thus, it was possible to have a better sense of the relationship among the populations (Viana et al, 2013).…”

DIVERSIDADE E ESTRUTURA GENÉTICA DE Senna reticulata

“…Porém, ao observar os acessos de Matrinchã, houve mistura de materiais genéticos dos dois grupos, o que indicaria que esse é um ponto de transição (ecótono) entre essas localidades e/ou que essa é uma região de intenso intercâmbio de material genético entre as demais localidades. O genoma de Matrinchã também pode ser entendido como um composto obtido do cruzamento entre populações parentais com genoma contrastante para grande parte dos locos considerados (VIANA et al, 2013).…”

Seleção genômica para melhoramento vegetal com diferentes estruturas populacionais

“…Utilizou-se o programa Realbreeding, também utilizado em outros trabalhos de simulação (Viana et al, 2013(Viana et al, , 2016, desenvolvido a partir do programa Realbasic. Consideraram-se dois caracteres de milho-pipoca, determinados por: 100 QTLs; três densidades de marcadores SNP (single nucleotide polymorphism); duas herdabilidades; e seis populações, representadas em duas gerações, o que totalizou 144 cenários.…”