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Optimization of Single-Base-Pair Mismatch Discrimination in Oligonucleotide Microarrays
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ABSTRACT
The discrimination between perfect-match and single-base-pair-mismatched nucleic acid duplexes was investigated by using oligonucleotide DNA microarrays and nonequilibrium dissociation rates (melting profiles). DNA and RNA versions of two synthetic targets corresponding to the 16S rRNA sequences of
Staphylococcus epidermidis
(38 nucleotides) and
Nitrosomonas eutropha
(39 nucleotides) were hybridized to perfect-match probes (18-mer and 19-mer) and to a set of probes having all possible single-base-pair mismatches. The melting profiles of all probe-target duplexes were determined in parallel by using an imposed temperature step gradient. We derived an optimum wash temperature for each probe and target by using a simple formula to calculate a discrimination index for each temperature of the step gradient. This optimum corresponded to the output of an independent analysis using a customized neural network program. These results together provide an experimental and analytical framework for optimizing mismatch discrimination among all probes on a DNA microarray.
American Society for Microbiology
Title: Optimization of Single-Base-Pair Mismatch Discrimination in Oligonucleotide Microarrays
Description:
ABSTRACT
The discrimination between perfect-match and single-base-pair-mismatched nucleic acid duplexes was investigated by using oligonucleotide DNA microarrays and nonequilibrium dissociation rates (melting profiles).
DNA and RNA versions of two synthetic targets corresponding to the 16S rRNA sequences of
Staphylococcus epidermidis
(38 nucleotides) and
Nitrosomonas eutropha
(39 nucleotides) were hybridized to perfect-match probes (18-mer and 19-mer) and to a set of probes having all possible single-base-pair mismatches.
The melting profiles of all probe-target duplexes were determined in parallel by using an imposed temperature step gradient.
We derived an optimum wash temperature for each probe and target by using a simple formula to calculate a discrimination index for each temperature of the step gradient.
This optimum corresponded to the output of an independent analysis using a customized neural network program.
These results together provide an experimental and analytical framework for optimizing mismatch discrimination among all probes on a DNA microarray.
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