title: Tuber proteome comparison of five potato varieties by principal component analysis.
abstract: 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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Food Science and Technology Department, Federal University of Santa Catarina, Rod. Admar Gonzaga 1346, 88034-001, Florianópolis, SC, Brazil.
authors.forename: Carla Souza
authors.initials: CS
authors.lastname: de Mello
authors.affiliation: RIKILT, Wageningen University and Research Centre, PO Box 230, NL-6700, AE, Wageningen, The Netherlands.
authors.forename: Jeroen P
authors.initials: JP
authors.lastname: Van Dijk
authors.affiliation: RIKILT, Wageningen University and Research Centre, PO Box 230, NL-6700, AE, Wageningen, The Netherlands.
authors.forename: Marleen
authors.initials: M
authors.lastname: Voorhuijzen
authors.affiliation: RIKILT, Wageningen University and Research Centre, PO Box 230, NL-6700, AE, Wageningen, The Netherlands.
authors.forename: Esther J
authors.initials: EJ
authors.lastname: Kok
authors.affiliation: Food Science and Technology Department, Federal University of Santa Catarina, Rod. Admar Gonzaga 1346, 88034-001, Florianópolis, SC, Brazil.
authors.forename: Ana Carolina Maisonnave
authors.identifier: http://orcid.org/0000-0001-6077-7960
authors.initials: AC
authors.lastname: Arisi
mesh_terms: D016000:Cluster Analysis; D018556:Crops, Agricultural / Q000737:chemistry* / Q000378:metabolism; D020869:Gene Expression Profiling; D018506:Gene Expression Regulation, Plant; D008954:Models, Biological; D009426:Netherlands; D010940:Plant Proteins / Q000235:genetics / Q000378:metabolism*; D014674:Plant Proteins, Dietary / Q000032:analysis* / Q000096:biosynthesis; D035281:Plant Tubers / Q000737:chemistry* / Q000378:metabolism; D025341:Principal Component Analysis; D020543:Proteome / Q000096:biosynthesis; D040901:Proteomics / Q000379:methods; D011198:Solanum tuberosum / Q000737:chemistry* / Q000378:metabolism; D013045:Species Specificity; D057825:Two-Dimensional Difference Gel Electrophoresis
chemical_list: D010940:Plant Proteins; D014674:Plant Proteins, Dietary; D020543:Proteome
keywords: 2-DE, proteomics; PCA; two-dimensional electrophoresis