While microarrays are the predominant method for gene expression profiling, understanding the variation of measurement signals is still an area of active research. Signals are probe sequence dependent, and both the interpretation of measurements and the design of microarrays need to take this into account.
In view of the extremely large number of potential probe sequences to consider, many approaches to microarray design employ heuristic shortcuts in lieu of more elaborate thermodynamic models of the probe binding process. We here demonstrate the benefits of an improved model for microarray hybridization and assess the relative contributions of the probe-target binding strength and various competing structures. Remarkably, specific and unspecific hybridization were apparently driven by different energetic contributions: For unspecific hybridization, the probe–target melting temperature Tm was the best predictor of signal variation. For specific hybridization, however, the effective interaction energy that also considered alternative competing conformations was twice as powerful a predictor of probe signal variation, highlighting the importance of secondary structures in the probe and target molecules.
Mueckstein U, Leparc GG, Posekany A, Hofacker I, Kreil DP (2010) Hybridization thermodynamics of NimbleGen microarrays. BMC Bioinformatics 11, 35. (read more)