G-stack modulated probe intensities on expression arrays - sequence corrections and signal calibration
1 Interdisciplinary Centre for Bioinformatics, University Leipzig, Germany
2 Leipzig Interdisciplinary Research Cluster of Genetic Factors, Clinical Phenotypes and Environment (LIFE), University Leipzig, Germany
3 Max-Planck-Insitute for Mathematics in Sciences, Leipzig, Germany
4 Fraunhofer Institut for Cell Therapy and Immunology, Leipzig, Germany
5 Institute for Theoretical Chemistry, University of Vienna, Vienna, Austria
6 The Santa Fe Institute, Santa Fe, New Mexico, USA
BMC Bioinformatics 2010, 11:207 doi:10.1186/1471-2105-11-207Published: 27 April 2010
The brightness of the probe spots on expression microarrays intends to measure the abundance of specific mRNA targets. Probes with runs of at least three guanines (G) in their sequence show abnormal high intensities which reflect rather probe effects than target concentrations. This G-bias requires correction prior to downstream expression analysis.
Longer runs of three or more consecutive G along the probe sequence and in particular triple degenerated G at its solution end ((GGG)1-effect) are associated with exceptionally large probe intensities on GeneChip expression arrays. This intensity bias is related to non-specific hybridization and affects both perfect match and mismatch probes. The (GGG)1-effect tends to increase gradually for microarrays of later GeneChip generations. It was found for DNA/RNA as well as for DNA/DNA probe/target-hybridization chemistries. Amplification of sample RNA using T7-primers is associated with strong positive amplitudes of the G-bias whereas alternative amplification protocols using random primers give rise to much smaller and partly even negative amplitudes.
We applied positional dependent sensitivity models to analyze the specifics of probe intensities in the context of all possible short sequence motifs of one to four adjacent nucleotides along the 25meric probe sequence. Most of the longer motifs are adequately described using a nearest-neighbor (NN) model. In contrast, runs of degenerated guanines require explicit consideration of next nearest neighbors (GGG terms). Preprocessing methods such as vsn, RMA, dChip, MAS5 and gcRMA only insufficiently remove the G-bias from data.
Positional and motif dependent sensitivity models accounts for sequence effects of oligonucleotide probe intensities. We propose a positional dependent NN+GGG hybrid model to correct the intensity bias associated with probes containing poly-G motifs. It is implemented as a single-chip based calibration algorithm for GeneChips which can be applied in a pre-correction step prior to standard preprocessing.