RESUMEN
BACKGROUND: Data analysis of omics data should be performed by multivariate analysis such as principal component analysis (PCA). The way data are clustered in PCA is of major importance to develop some classification systems based on multivariate analysis, such as soft independent modeling of class analogy (SIMCA). In a previous study a one-class classifier based on SIMCA was built using microarray data from a set of potatoes. The PCA grouped the transcriptomic data according to varieties. The present work aimed to use PCA to verify the clustering of the proteomic profiles for the same potato varieties. RESULTS: Proteomic profiles of five potato varieties (Biogold, Fontane, Innovator, Lady Rosetta and Maris Piper) were evaluated by two-dimensional gel electrophoresis (2-DE) performed on two immobilized pH gradient (IPG) strip lengths, 13 and 24 cm, both under pH range 4-7. For each strip length, two gels were prepared from each variety; in total there were ten gels per analysis. For 13 cm strips, 199-320 spots were detected per gel, and for 24 cm strips, 365-684 spots. CONCLUSION: All four PCAs performed with these datasets presented clear grouping of samples according to the varieties. The data presented here showed that PCA was applicable for proteomic analysis of potato and was able to separate the samples by varieties. © 2016 Society of Chemical Industry.
Asunto(s)
Productos Agrícolas/química , Regulación de la Expresión Génica de las Plantas , Modelos Biológicos , Proteínas de Vegetales Comestibles/análisis , Proteínas de Plantas/metabolismo , Tubérculos de la Planta/química , Solanum tuberosum/química , Análisis por Conglomerados , Productos Agrícolas/metabolismo , Perfilación de la Expresión Génica , Países Bajos , Proteínas de Plantas/genética , Proteínas de Vegetales Comestibles/biosíntesis , Tubérculos de la Planta/metabolismo , Análisis de Componente Principal , Proteoma/biosíntesis , Proteómica/métodos , Solanum tuberosum/metabolismo , Especificidad de la Especie , Electroforesis Bidimensional Diferencial en GelRESUMEN
An important part of the current hazard identification of novel plant varieties is comparative targeted analysis of the novel and reference varieties. Comparative analysis will become much more informative with unbiased analytical approaches, e.g. omics profiling. Data analysis estimating the similarity of new varieties to a reference baseline class of known safe varieties would subsequently greatly facilitate hazard identification. Further biological and eventually toxicological analysis would then only be necessary for varieties that fall outside this reference class. For this purpose, a one-class classifier tool was explored to assess and classify transcriptome profiles of potato (Solanum tuberosum) varieties in a model study. Profiles of six different varieties, two locations of growth, two year of harvest and including biological and technical replication were used to build the model. Two scenarios were applied representing evaluation of a 'different' variety and a 'similar' variety. Within the model higher class distances resulted for the 'different' test set compared with the 'similar' test set. The present study may contribute to a more global hazard identification of novel plant varieties.