Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 439723
Title Systems biology and statistical data integration of ~omics data sets
Author(s) Acharjee, A.
Source Wageningen University. Promotor(en): Richard Visser, co-promotor(en): Chris Maliepaard. - S.l. : s.n. - ISBN 9789461735843 - 177
Department(s) Plant Breeding
Publication type Dissertation, internally prepared
Publication year 2013
Keyword(s) systeembiologie - statistische gegevens - gegevensanalyse - gegevens verzamelen - metabolomica - loci voor kwantitatief kenmerk - genomica - eiwitexpressieanalyse - solanum tuberosum - aardappelen - databanken - systems biology - statistical data - data analysis - data collection - metabolomics - quantitative trait loci - genomics - proteomics - solanum tuberosum - potatoes - databases
Categories Molecular Databases / Data Processing, Database Management

In this thesis quality traits of potato were related to different highly multivariate ~omics datasets containing information on proteins, primary and secondary metabolites and gene expression. The objectives were to explore and compare different statistical techniques that are able to quantify these relationships, and to identify components responsible for prediction of quality. We propose a strategy to integrate two or more of such datasets and to select subsets of predictive components. We used potato flesh colour as an example trait and identified metabolites and expressed genes that are associated with flesh colour. We identified two putative novel non-volatile glycosides of carotenoid-derived metabolites and a novel putative connection with the flavonoid pathway. From a gas chromatography data set we identified genetic factors underlying variation in primary metabolism and found the amino acid beta-alanine associated with starch content. Finally we performed an integrated analysis with gene expression, metabolites and proteomics data and present an approach to select a limited set of predictive genes, metabolites and proteins.

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