Genetic Analysis of Tomato Fruit Ripening at Polypeptide Profiles Level through Quantitative and Multivariate Approaches

Multivariate analysis became essential in functional and structural Genomics because of the large quantity of biological data provided by these new research areas. Diallel mating design was widely applied to analyze the heritability of quantitative traits but it was recently used for approaching to...

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Detalles Bibliográficos
Autores: Marchionni Basté, Ezequiel, Pereira Da Costa, Javier Hernán, Rodríguez, Gustavo Rubén, Zorzoli, Roxana, Pratta, Guillermo Raúl
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2014
País:Argentina
Institución:Consejo Nacional de Investigaciones Científicas y Técnicas
Repositorio:CONICET Digital (CONICET)
Idioma:inglés
OAI Identifier:oai:ri.conicet.gov.ar:11336/30238
Acceso en línea:http://hdl.handle.net/11336/30238
Access Level:acceso abierto
Palabra clave:Solanum lycopersicum
Plant Genetic Resources
Proteomics
Cluster Analysis
https://purl.org/becyt/ford/4.1
https://purl.org/becyt/ford/4
Descripción
Sumario:Multivariate analysis became essential in functional and structural Genomics because of the large quantity of biological data provided by these new research areas. Diallel mating design was widely applied to analyze the heritability of quantitative traits but it was recently used for approaching to the inheritance patterns of other levels of gene expression such as transcript profiles. Investigating the inheritance pattern of total polypeptide profiles with a diallel design remains as a vacancy subject. The objective of the present research was to infer the inheritance of total polypeptides profiles from tomato pericarp tissue at four different ripening stages in a diallel mating design including five recombinant inbred lines (RILs) and their ten second cycle hybrids (SCH). To achieve this objective, a multivariate analysis was applied to identify eventual inheritance patterns through a data mining approach and then univariate analyses were used to verify these patterns. Mainly dominance and also overdominance, though in a minor percentage, contributed to the gene actions involved in their genetic basis. Multivariate analysis was efficient in identifying inheritance patterns of total polypeptide profiles through a data mining approach, and univariate analyses largely verified the identified gene actions