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Evaluating oligonucleotide properties for DNA microarray probe design.

ABSTRACT: Most current microarray oligonucleotide probe design strategies are based on probe design factors (PDFs), which include probe hybridization free energy (PHFE), probe minimum folding energy (PMFE), dimer score, hairpin score, homology score and complexity score. The impact of these PDFs on probe performance was evaluated using four sets of microarray comparative genome hybridization (aCGH) data, which included two array manufacturing methods and the genomes of two species. Since most of the hybridizing DNA is equimolar in CGH data, such data are ideal for testing the general hybridization properties of almost all candidate oligonucleotides. In all our data sets, PDFs related to probe secondary structure (PMFE, hairpin score and dimer score) are the most significant factors linearly correlated with probe hybridization intensities. PHFE, homology and complexity score are correlating significantly with probe specificities, but in a non-linear fashion. We developed a new PDF, pseudo probe binding energy (PPBE), by iteratively fitting dinucleotide positional weights and dinucleotide stacking energies until the average residue sum of squares for the model was minimized. PPBE showed a better correlation with probe sensitivity and a better specificity than all other PDFs, although training data are required to construct a PPBE model prior to designing new oligonucleotide probes. The physical properties that are measured by PPBE are as yet unknown but include a platform-dependent component. A practical way to use these PDFs for probe design is to set cutoff thresholds to filter out bad quality probes. Programs and correlation parameters from this study are freely available to facilitate the design of DNA microarray oligonucleotide probes.

SUBMITTER: Xia XQ

PROVIDER: S-EPMC2887943 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:MicroRNAs (miRNAs) have been shown to play an important role in many different cellular, developmental, and physiological processes. Accordingly, numerous methods have been established to identify and quantify miRNAs. The shortness of miRNA sequence results in a high dynamic range of melting temperatures and, moreover, impedes a proper selection of detection probes or optimized PCR primers. While miRNA microarrays allow for massive parallel and accurate relative measurement of all known miRNAs, they have so far been less useful as an assay for absolute quantification. Here, we present a microarray based approach for global and absolute quantification of miRNAs. The method relies on an equimolar pool of about 1000 synthetic miRNAs of known concentration which is used as an universal reference and labeled and hybridized in a dual colour approach on the same array as the sample of interest. Each single miRNA is quantified with respect to the universal reference outbalancing bias related to sequence, labeling, hybridization or signal detection method. We demonstrate the accuracy of the method by various spike in experiments. Further, we quantified miRNA copy numbers in liver samples and CD34(+)CD133(-) hematopoietic stem cells. Different probe designs were investigated with respect to sensitivity and selectivity of microarray hybridization. An array with 11 different variants of oligonucleotides for miR-122a and miR-16 was produced. 5 µg of respective total RNA was fluorescently labelled by 3’ ligation. Total RNA was hybridized in a dual colour approach to microarrays versus a second labelled synthetic miRNA pool. The synthetic miRNA pool consisted of 5 fmol of each of 816 non redundant miRNAs sequences and miRControl 3 sequences. Local background was subtracted from the signal to obtain the net signal intensity and the mean of the net signal intensities of 4 corresponding spots representing the same miRNA was computed for those spots only which were unflagged (empty spots, poor spots, negative spots) and for which the fluorescent intensity of the miRNAs derived from the samples of interest was two-fold the mean background value (2bkg dataset).

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Evaluating oligonucleotide properties for DNA microarray probe design.

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