Article citationsMore>>
Akihiro, T., Koike, S., Tani, R., Tominaga, T., Watanabe, S., Iijima, Y., Aoki, K., Shibata, D., Ashihara, H., Matsukura, C., Akama, K., Fujimura, T. and Ezura, H. (2008) Biochemical Mechanism on GABA Accumulation during Fruit Development in Tomato. Plant and Cell Physiology, 49, 1378-1389.
http://dx.doi.org/10.1093/pcp/pcn113
has been cited by the following article:
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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.
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