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Zwarts, L., Magwire, M.M., Carbone, M.A., Verstevena, M., Herteleer, L., Anholt, R.R.H., Callaertsa, P. and Mackay, T.F.C. (2011) Complex Genetic Architecture of Drosophila Aggressive Behavior. Proceedings of the National Academy of Sciences of the United States of America, 108, 17070-17075.
http://dx.doi.org/10.1073/pnas.1113877108

has been cited by the following article:

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

  AUTHORS: Ezequiel Marchionni Basté, Javier H. Pereira da Costa, Gustavo R. Rodríguez, Roxana Zorzoli, Guillermo R. Pratta

  KEYWORDS: Solanum lycopersicum, Plant Genetic Resources, Proteomics, Cluster Analysis

  JOURNAL NAME: American Journal of Plant Sciences, Vol.5 No.13, June 18, 2014

  ABSTRACT: 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.