Filling gaps in PPAR-alpha signaling through comparative nutrigenomics analysis

Duccio Cavalieri, Enrica Calura, Chiara Romualdi, Emmanuela Marchi, Marijana Radonjic, Ben van Ommen, Michael Müller

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

The application of high-throughput genomic tools in nutrition research is a widespread practice. However, it is becoming increasingly clear that the outcome of individual expression studies is insufficient for the comprehensive understanding of such a complex field. Currently, the availability of the large amounts of expression data in public repositories has opened up new challenges on microarray data analyses. We have focused on PPARalpha, a ligand-activated transcription factor functioning as fatty acid sensor controlling the gene expression regulation of a large set of genes in various metabolic organs such as liver, small intestine or heart. The function of PPARalpha is strictly connected to the function of its target genes and, although many of these have already been identified, major elements of its physiological function remain to be uncovered. To further investigate the function of PPARalpha, we have applied a cross-species meta-analysis approach to integrate sixteen microarray datasets studying high fat diet and PPARalpha signal perturbations in different organisms.
Original languageEnglish
Article number596
JournalBMC Genomics
Volume10
DOIs
Publication statusPublished - 11 Dec 2009

Keywords

  • Animals
  • Binding Sites
  • Cluster Analysis
  • Comparative Genomic Hybridization
  • Computational Biology
  • Gene Expression Profiling
  • Gene Expression Regulation
  • Humans
  • Mice
  • Nutrigenomics
  • Oligonucleotide Array Sequence Analysis
  • PPAR alpha
  • Saccharomyces cerevisiae
  • Signal Transduction
  • Transcription Factors

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