Hierarchical genetic clusters for phenotypic analysis

Methods to obtain phenotypic information were evaluated to help breeders choosing the best methodology for analysis of genetic diversity in backcross populations. Phenotypes were simulated for 13 characteristics generated in 10 populations with 100 individuals each. Genotypic information was generat...

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Detalles Bibliográficos
Autores: Matta, Luiza Barbosa da, Tomé, Lívia Gracielle Oliveira, Salgado, Caio Césio, Cruz, Cosme Damião, Silva, Letícia de Faria
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2013
País:Brasil
Institución:Universidade Federal de Viçosa (UFV)
Repositorio:LOCUS Repositório Institucional da UFV
Idioma:inglés
OAI Identifier:oai:locus.ufv.br:123456789/18448
Acceso en línea:http://dx.doi.org/10.4025/actasciagron.v37i4.19746
http://www.locus.ufv.br/handle/123456789/18448
Access Level:acceso abierto
Palabra clave:Hierarchical clustering
Genetic diversity
Backcrossing
Descripción
Sumario:Methods to obtain phenotypic information were evaluated to help breeders choosing the best methodology for analysis of genetic diversity in backcross populations. Phenotypes were simulated for 13 characteristics generated in 10 populations with 100 individuals each. Genotypic information was generated from 100 loci of which 20 were taken at random to determine the characteristics expressing two alleles. Dissimilarity measures were calculated, and genetic diversity was analyzed through hierarchical clustering and graphic projection of the distances. A backcross was performed from the two most divergent populations. A set of characteristics with variable heritability was taken into account. The environmental effect was simulated assuming x~N(0, σ2). For hierarchical clusters, the following methods were used: Gower Method, average linkage within the cluster, average linkage among clusters, the furthest neighbor method, the nearest neighbor method, Ward's method, and the median method. The environmental effect and heritability of the analyzed variables had an influence on the pattern of hierarchical clustering populations according to the backcrossed generations. The nearest neighbor method was the most efficient in reconstructing the system of backcrossing, and it presented the highest cophenetic correlation. The efficiency of the nearest neighbor method was the highest when the analysis involved characteristics of high heritability.