IngentaConnect Bioinformatic analysis of primary endothelial cell gene array dat...

Authors: Jonathan Schoenfeld¹; Khashayar Lessan¹; Nicola Johnson¹; D. Charnock-jones¹; Amanda Evans¹; Ekaterini Vourvouhaki¹; Laurie Scott²; Richard Stephens²; Tom Freeman²; Samir Saidi¹; Brian Tom³; Gareth Weston⁴; Peter Rogers⁴; Stephen Smith¹; Cristin Print¹

Source: Angiogenesis, Volume 7, Number 2, 2004 , pp. 143-156(14)

Publisher: Springer

Abstract:

We recently published a review in this journal describing the design, hybridisation and basic data processing required to use gene arrays to investigate vascular biology (Evans etal. Angiogenesis 2003; 6: 93--104). Here, we build on this review by describing a set of powerful and robust methods for the analysis and interpretation of gene array data derived from primary vascular cell cultures. First, we describe the evaluation of transcriptome heterogeneity between primary cultures derived from different individuals, and estimation of the false discovery rate introduced by this heterogeneity and by experimental noise. Then, we discuss the appropriate use of Bayesian t-tests, clustering and independent component analysis to mine the data. We illustrate these principles by analysis of a previously unpublished set of gene array data in which human umbilical vein endothelial cells (HUVEC) cultured in either rich or low-serum media were exposed to vascular endothelial growth factor (VEGF)-A₁₆₅ or placental growth factor (PlGF)-1₁₃₁. We have used Affymetrix U95A gene arrays to map the effects of these factors on the HUVEC transcriptome. These experiments followed a paired design and were biologically replicated three times. In addition, one experiment was repeated using serial analysis of gene expression (SAGE). In contrast to some previous studies, we found that VEGF-A and PlGF consistently regulated only small, non-overlapping and culture media-dependant sets of HUVEC transcripts, despite causing significant cell biological changes.

Keywords: bioinformatics; endothelial; gene array; PlGF; VEGF-A

Document Type: Research article

DOI: 10.1007/s10456-004-1677-0

Affiliations: 1: Department of Pathology, Cambridge University, Tennis Court Rd, UK 2: UK MRC Hinxton Genome Mapping Project Resource Centre, UK 3: Medical Research Council Biostatistics Unit, UK 4: Centre for Women's Health Research, Monash University, Department of Obstetrics and Gynaecology, Monash Medical Centre, Victoria, Australia

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Bioinformatic analysis of primary endothelial cell gene array data illustrated by the analysis of transcriptome changes in endothelial cells exposed to VEGF-A and PlGF