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Normalization procedures and detection of linkage signal in genetical-genomics experiments

Nature Genetics volume 38, pages 855–856 (2006)Cite this article

To the Editor:

Recent microarray-based experiments, designed to measure the influence of genetic variation on gene expression at a near–genome-wide scale, have offered the first evidence of heritability of mRNA levels between individuals1,2,3,4,5,6. The collective approach has been to treat expression values for each transcript across individuals as a molecular phenotype, in a massively parallel linkage analysis. In genetical-genomics experiments, each array measures expression levels from an individual with a different genetic background (e.g., BxD mouse4). Unprocessed data from microarrays representing individuals may show quite different distributional characteristics due to experimental vagaries rather than true biological influence. If these are not removed by normalization7, then the expression levels of a given set of genes will systematically vary across the arrays; this variation can then correlate with genotype distributions at one or more loci, giving rise to spurious 'genetic signal'.

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Figure 1: Concordance analysis of linkage statistics based upon three normalization methods.

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Acknowledgements

We thank J. Schimenti (formerly of the Jackson Laboratory) and M. Bucan (University of Pennsylvania) for assistance in obtaining mouse strains. Supported by an Australian Research Council Discovery Grant award (P.F.R.L.), a National Health and Medical Research Council Peter Doherty Fellowship (R.B.H.W.), the University of New South Wales Genome Informatics Scholarship (C.J.C.) and Australian Postgraduate Awards (E.C. and M.J.C.) and a grant-in-aid from the Australian Centre for Advanced Computing and Communications (P.F.R.L.).

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Author notes

  1. Rohan B H Williams and Chris J Cotsapas: These authors contributed equally to this work.

Authors and Affiliations

  1. School of Biotechnology and Biomolecular Sciences, The University New South Wales, 2052, Sydney, Australia

    Rohan B H Williams, Chris J Cotsapas, Mark J Cowley, Eva Chan & Peter F R Little

  2. The Clive and Vera Ramaciotti Centre for Gene Function Analysis, The University New South Wales, 2052, Sydney, Australia

    Rohan B H Williams

  3. School of Mathematics, The University New South Wales, 2052, Sydney, Australia

    David J Nott

Authors
  1. Rohan B H Williams
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  2. Chris J Cotsapas
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  4. Eva Chan
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Corresponding author

Correspondence to Peter F R Little.

Supplementary information

Supplementary Fig. 1

Influence of normalization on genome-wide linkage statistics in ref. 4. (PDF 552 kb)

Supplementary Fig. 2

Influence of transcript variance on concordance analysis of linkage statistics. (PDF 647 kb)

Supplementary Fig. 3

Concordance analysis of linkage 'peaks'. (PDF 782 kb)

Supplementary Table 1

Simulation. (PDF 462 kb)

Supplementary Methods (PDF 83 kb)

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Williams, R., Cotsapas, C., Cowley, M. et al. Normalization procedures and detection of linkage signal in genetical-genomics experiments. Nat Genet 38, 855–856 (2006). https://doi.org/10.1038/ng0806-855

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