Using DNA microarrays to study gene expression in closely related species

DOI PDF 1 Citations
  • Alicia Oshlack
    1 Walter and Eliza Hall Institute of Medical Research, Parkville, Vic 3050, Australia and 2Department of Human Genetics, University of Chicago, Chicago, IL 60605, USA
  • Adrien E. Chabot
    1 Walter and Eliza Hall Institute of Medical Research, Parkville, Vic 3050, Australia and 2Department of Human Genetics, University of Chicago, Chicago, IL 60605, USA
  • Gordon K. Smyth
    1 Walter and Eliza Hall Institute of Medical Research, Parkville, Vic 3050, Australia and 2Department of Human Genetics, University of Chicago, Chicago, IL 60605, USA
  • Yoav Gilad
    1 Walter and Eliza Hall Institute of Medical Research, Parkville, Vic 3050, Australia and 2Department of Human Genetics, University of Chicago, Chicago, IL 60605, USA

Description

<jats:title>Abstract</jats:title><jats:p>Motivation: Comparisons of gene expression levels within and between species have become a central tool in the study of the genetic basis for phenotypic variation, as well as in the study of the evolution of gene regulation. DNA microarrays are a key technology that enables these studies. Currently, however, microarrays are only available for a small number of species. Thus, in order to study gene expression levels in species for which microarrays are not available, researchers face three sets of choices: (i) use a microarray designed for another species, but only compare gene expression levels within species, (ii) construct a new microarray for every species whose gene expression profiles will be compared or (iii) build a multi-species microarray with probes from each species of interest. Here, we use data collected using a multi-primate cDNA array to evaluate the reliability of each approach.</jats:p><jats:p>Results: We find that, for inter-species comparisons, estimates of expression differences based on multi-species microarrays are more accurate than those based on multiple species-specific arrays. We also demonstrate that within-species expression differences can be estimated using a microarray for a closely related species, without discernible loss of information.</jats:p><jats:p>Contact: A.O. (oshlack@wehi.edu.au) or Y.G. (gilad@uchicago.edu)</jats:p><jats:p>Supplementary information: Supplementary data are available at Bioinformatics online.</jats:p>

Journal

  • Bioinformatics

    Bioinformatics 23 (10), 1235-1242, 2007-03-23

    Oxford University Press (OUP)

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