A single nucleotide polymorphism based approach for the identification and characterization of gene expression modulation using MassARRAY

Mutat Res. 2005 Jun 3;573(1-2):83-95. doi: 10.1016/j.mrfmmm.2005.01.007.


Single nucleotide polymorphisms (SNPs) are the most common form of genetic variation. Their abundance and the ease with which they can be assayed have lead to their use in applications beyond simple genotyping. One such application is the quantitative determination of transcript levels associated with distinct alleles or haplotypes found in promoters and coding regions of genes. These changes in expression due to allelic variation are often associated with additional genomic or transcript modifications such as DNA methylation or RNA editing. Here, we describe the use of an integrated genetic analysis platform, based on matrix-assisted laser desorption/ionisation-time-of-flight (MALDI-TOF) to first, discover coding SNPs (cSNPs); second, use these cSNPs to identify and analyze allele-specific expression; and third, from this knowledge to further analyze methylation patterns as a putative cause for the allele-specific expression. An established model involving allele-specific expression profiles of the human tumor protein 73 (TP73) gene is presented as an example to outline and validate data obtained from the MassARRAY platform. The availability of a single integrated platform to assay stable and dynamic variation at the genomic and transcript level greatly simplifies complex functional genomic studies.

Publication types

  • Review

MeSH terms

  • 5' Untranslated Regions
  • Alleles
  • DNA Methylation
  • DNA-Binding Proteins / genetics
  • Gene Expression
  • Genes, Tumor Suppressor
  • Genotype*
  • Humans
  • Nuclear Proteins / genetics
  • Polymorphism, Single Nucleotide*
  • Promoter Regions, Genetic
  • Tumor Protein p73
  • Tumor Suppressor Proteins


  • 5' Untranslated Regions
  • DNA-Binding Proteins
  • Nuclear Proteins
  • TP73 protein, human
  • Tumor Protein p73
  • Tumor Suppressor Proteins