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SNPs on chips: the hidden genetic code in expression arrays.

Elzbieta Sliwerska1, Fan Meng, Terence P Speed

  • 1Molecular & Behavioral Neuroscience Institute, University of Michigan, Ann Arbor, Michigan 48109-2220, USA.

Biological Psychiatry
|May 13, 2006
PubMed
Summary
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Common genetic variations called single nucleotide polymorphisms (SNPs) can falsely appear as gene expression changes in brain tissue studies. This artifact, observed in the COMT gene, can confound psychiatric research findings.

Area of Science:

  • Neuroscience
  • Genetics
  • Bioinformatics

Background:

  • Gene expression microarray analysis is a rapidly advancing field in psychiatric research.
  • Postmortem brain tissue is frequently used for these studies.

Purpose of the Study:

  • To investigate whether common genetic variations (SNPs) on microarray probe sets can be mistaken for significant gene expression differences.
  • To identify potential confounding factors in gene expression analysis of postmortem brain samples.

Main Methods:

  • Analysis of gene expression microarrays in postmortem brain samples.
  • Identification and validation of artifacts caused by single nucleotide polymorphisms (SNPs) within probe sets.
  • Replication of findings in multiple genes, including Catechol-O-methyl transferase (COMT).

Related Experiment Videos

Main Results:

  • Common single nucleotide polymorphisms (SNPs) present on microarray probe sets can mimic significant gene expression differences.
  • This artifact was initially observed in the Catechol-O-methyl transferase (COMT) gene and subsequently replicated in two additional genes.
  • Thousands of SNPs on common Affymetrix chips are positioned in critical probe regions, potentially affecting hybridization and confounding results.

Conclusions:

  • Single nucleotide polymorphisms (SNPs) represent a significant source of artifact in gene expression microarray analysis of postmortem brain tissue.
  • Researchers must account for potential SNP-related artifacts to ensure the accuracy of findings in psychiatric research.
  • This highlights the need for careful data analysis and validation in gene expression studies.