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Principal components analysis classifies the phenotypic variation of a population into independent systems of correlated traits. It has been postulated that principal components can be used to identify genetic networks involved in regulating complex biological systems as each individual in the popul...

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Published inJournal of Basic & Applied Genetics Vol. 21; no. 1; pp. 15 - 25
Main Authors Di Masso, RJ, Pippa, C, Silva, P S, Font, M T
Format Journal Article
LanguageSpanish
Published 01.01.2010
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Summary:Principal components analysis classifies the phenotypic variation of a population into independent systems of correlated traits. It has been postulated that principal components can be used to identify genetic networks involved in regulating complex biological systems as each individual in the population has values which may be associated with phenotypes susceptible to be analyzed genetically. The technique was applied to five traits involved in muscle-bone relationship (PESMUS: gastrocnemius muscle weight; PESTIB and PESFEM: weight of tibia and femur, and LONFEM and LONTIB: length of femur and tibia) measured at 150 days of age in males (n = 336) and females (n = 319) of a segregating population (F2) of mice derived from crossing two lines selected for body conformation. The three first principal components explained almost the same proportion of the total variance (87%) in males and females. The first component (PC1) explained 60% of the generalized variance and was negatively associated with the five muscle-bone indicators, so it may be considered as an indicator of body size. The second component (PC2) explained 15% of the total variance and was associated with bone length with little effect on bone weight and muscle weight so it can be interpreted as an indicator of skeleton length. The third component explained 12% of the variance and was associated with muscle weight, with little effect on bone weight and no effect on bone length, so it can be interpreted as an indicator of the biomass sustained. The results indicate the coexistence of independent sources of phenotypic variance in the characterization of this complex biological system that allow to identify particular combinations of the triad -body size, skeleton as a scaffold for soft tissues and biomass sustained.Original Abstract: El analisis de componentes principales clasifica la variation fenotipica en sistemas independientes de caracteres correlacionados. Se ha postulado que las componentes pueden utilizarse para identificar redes geneticas involucradas en la regulacion de sistemas complejos dado que cada individuo de la poblacion presenta valores que pueden asociarse con fenotipos sus-ceptibles de analizarse geneticamente. La tecnica se aplico a cinco indicadores de la relacion musculo-hueso (PESMUS: peso del musculo gastrocnemio, PESFEM y PESTIB: peso del femur y de la tibia, y LONFEM y LONTIB: longitud del femur y de la tibia) medidos a los 150 dias de edad en machos (n=336) y hembras (n=319) de una poblacion segregante (F2) de ratones proveniente del cruzamiento entre dos lineas seleccionadas por conformation corporal. Las tres primeras componentes explicaron similar proportion de la variancia total (87%) en ambos sexos. La primera (PCI) explicd el 60% de la variancia y se asocio negativamente con los cinco indicadores por lo que puede ser considerada un indicador de tamano corporal. La segunda (PC2) explico el 15% de la variancia y se asocio con la longitud del hueso con poco efecto sobre el peso del hueso y el peso del musculo que en el se inserta por lo que puede ser interpretada como un indicador de longitud del esqueleto, base de sustentacion de los tejidos blandos. La tercera explico el 12% de la variancia y se asocio con el peso del musculo, con escaso efecto sobre el peso del hueso y nulo sobre su longitud por lo que puede ser interpretada como un indicador de la biomasa sustentada Los resultados indican la coexistencia de fuentes independientes de variancia fenotipica en la caracterizacion de este sistema biologico complejo que permiten identificar combinaciones particulares de la triada tamano corporal-base osea de sustentacion- biomasa sustentada.
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ISSN:1666-0390