Single-nucleotide polymorphism (SNP) is a kind of single nucleotide variations, which could be caused by base conversion, transversion, insertion or deletion at a specific location in the genome. It’s directly associated with many diseases, thus, fast and accurate detection of SNP is of vital importance for drug research, individual medication, clinical testing and molecular diagnostics. A great deal of efforts have been devoted to developing accurate, rapid, and low-cost technologies for SNP analysis. However most of those methods need complicated probe-labeling and depend on high-cost equipment.

Prof. TANG Zhuo’s group of Chengdu Institute of Biology, Chinese Academy of Sciences, who works on organic chemistry, nucleic acid chemistry and chemical biology, has been committed to develop biosensors for nucleic acid detection (especially for clinical diagnosis) based on DNAzyme for a long time. Recently, they reported a novel DNAzyme based Gap-LCR detection method for SNP analysis.

This proposed detection method averts any chemical modification on probesby incorporating a short functional DNA sequence (DNAzyme) into one of the Gap-LCR probes. Then two kinds of exonuclease were utilized in their strategy to digest all the unreacted probes and release the DNAzyme embedded in the Gap-LCR product. The DNAzyme applied in their method was a versatile tool to report the result of SNP detection in colorimetric or fluorometric ways for different detection purposes.

Finally, they got a detection limit as low as 1000 copies of target genes with a 3 folds of signal-to-noise ratio and a discrimination of mutant DNA present at frequencies as low as one in 105 normal DNA copies. Except for the high sensitivity and specificity, the authors also checked the generality of the method. They had successfully applied their technology in the detection of GJB2 235delC from blood DNA sample, one of the most frequently found single base mutation in human hearing impairment.

The paper entitled "DNAzyme based Gap-LCR detection of Single-Nucleotide Polymorphism " was published online in Biosensors and Bioelectronics (2013,45, 141-147).