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.
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).
Project description:This study aimed to model formamide-based melting for the optimization of the sensitivity and specifcity of oligonucleotide probes in dignostic high-density microarrays. Formamide melting profiles of DNA oligonucleotides were obtained with a high-density microarray targeting 16S rRNA genes of Escherichia coli and Rhodobacter sphaeroides. One or two mismatched versions of perfect match probes were included on the array to systematically analyze the effect of formamide on mismatch stability and mismatch discrimination. A thermodynamics-based mathematical model of formamide denaturation was developed to predict the formamide melting profiles with sufficient accuracy to help with oligonucleotide design in microbial ecology applications. 16S rRNA sequences with GenBank accession codes U00006 ( E. coli ) and X53853 (R. sphaeroides) were used for probe design. The following oligonucleotide probe sets were used for the systematic analysis of the effect of formamide on probe-target hybrids (parenthetic information gives set name followed by the number of probes): 22-mer perfect match probes tiling the 16S rRNA gene of E. coli (TileE, n=1521), perfect match E.coli probes of variable length between 18 and 26 mers (Length, n=1045), E. coli probes with central single mismatches (OneM, n=1563), E. coli probes with single positional mismatches (PosM, n=4092), E. coli probes with single deletion mismatches (Gap, n=248), E. coli probes with single insertion mismatches (Insertion, n=248), E. coli probes with two separate mismatches (TwoM, n=1674), E. coli probes with central tandem mismatches (Tandem, n=558), and 22-mer perfect match probes tiling the 16S rRNA gene of R. sphaeroides. Also, a probe with no match to 16S rRNA genes was used as a background control. On the array, regular probes were replicated three times and the Nonsense probe ten times. See the manuscript of Yilmaz et al. for details.
Project description:This study aimed to model formamide-based melting for the optimization of the sensitivity and specifcity of oligonucleotide probes in dignostic high-density microarrays. Formamide melting profiles of DNA oligonucleotides were obtained with a high-density microarray targeting 16S rRNA genes of Escherichia coli and Rhodobacter sphaeroides. One or two mismatched versions of perfect match probes were included on the array to systematically analyze the effect of formamide on mismatch stability and mismatch discrimination. A thermodynamics-based mathematical model of formamide denaturation was developed to predict the formamide melting profiles with sufficient accuracy to help with oligonucleotide design in microbial ecology applications.
Project description:HiSpOD is a new efficient functional microarrays probe design algorithm especially dedicated for the microbial ecology and environmental studies. It was used to design 3392 probes targeting 21 genes involved in chlorinated solvent biodegradation pathways and synthesized on a nimblegen microarray. In order to test the probe specificity, the microarray was firstly hybridized to 6 µg of labelled aRNA from sheep rumen content (background aRNA). Secondly, hybridization of 1011 copies of labelled aRNA derived from in vitro transcription of three synthetic genes (mmoC, vcrA and tceA) and mixed with 6 µg of the same complex background material were performed to test their sensibility. Finally, the expression analysis of a contaminated groundwater sample was performed.
Project description:BACKGROUND: Microarray comparative genomic hybridization (CGH) is currently one of the most powerful techniques to measure DNA copy number in large genomes. In humans, microarray CGH is widely used to assess copy number variants in healthy individuals and copy number aberrations associated with various diseases, syndromes and disease susceptibility. In model organisms such as Caenorhabditis elegans (C. elegans) the technique has been applied to detect mutations, primarily deletions, in strains of interest. Although various constraints on oligonucleotide properties have been suggested to minimize non-specific hybridization and improve the data quality, there have been few experimental validations for CGH experiments. For genomic regions where strict design filters would limit the coverage it would also be useful to quantify the expected loss in data quality associated with relaxed design criteria. RESULTS: We have quantified the effects of filtering various oligonucleotide properties by measuring the resolving power for detecting deletions in the human and C. elegans genomes using NimbleGen microarrays. Approximately twice as many oligonucleotides are typically required to be affected by a deletion in human DNA samples in order to achieve the same statistical confidence as one would observe for a deletion in C. elegans. Surprisingly, the ability to detect deletions strongly depends on the oligonucleotide 15-mer count, which is defined as the sum of the genomic frequency of all the constituent 15-mers within the oligonucleotide. A similarity level above 80% to non-target sequences over the length of the probe produces significant cross-hybridization. We recommend the use of a fairly large melting temperature window of up to 10 C, the elimination of repeat sequences, the elimination of homopolymers longer than 5 nucleotides, and a threshold of -1 kcal/mol on the oligonucleotide self-folding energy. We observed very little difference in data quality when varying the oligonucleotide length between 50 and 70, and even when using an isothermal design strategy. CONCLUSIONS: We have determined experimentally the effects of varying several key oligonucleotide microarray design criteria for detection of deletions in C. elegans and humans with NimbleGen's CGH technology. Our oligonucleotide design recommendations should be applicable for CGH analysis in most species.
Project description:Microarrays have evolved from low-density cDNA or oligonucleotide arrays to high-density platforms, for several study species even covering the complete transcriptome. At the same time, transcriptomics experiments have become more complex and multifactorial in nature, requiring many microarrays to assess multiple biologically relevant hypotheses. Scientists using this technology are therefore painfully aware of the high financial cost of a typical microarray experiment. Unfortunately, this often leads to either a suboptimal experimental design in an effort to reduce the cost by using fewer microarrays, or to abandoning microarray technology altogether. In this study, we argue that for many studies high-density full genome microarrays are in fact technical overkill. By selectively reducing full genome probe sets to a lower number of probes, it is possible to significantly reduce the total cost of a microarray experiment. The study consists of four microarray analyses: a cadmium probe selection experiment, a temperature probe selection experiment, a cadmium validation experiment and a cadmium validation experiment.
Project description:Microarrays have evolved from low-density cDNA or oligonucleotide arrays to high-density platforms, for several study species even covering the complete transcriptome. At the same time, transcriptomics experiments have become more complex and multifactorial in nature, requiring many microarrays to assess multiple biologically relevant hypotheses. Scientists using this technology are therefore painfully aware of the high financial cost of a typical microarray experiment. Unfortunately, this often leads to either a suboptimal experimental design in an effort to reduce the cost by using fewer microarrays, or to abandoning microarray technology altogether. In this study, we argue that for many studies high-density full genome microarrays are in fact technical overkill. By selectively reducing full genome probe sets to a lower number of probes, it is possible to significantly reduce the total cost of a microarray experiment. The study consists of four microarray analyses: a cadmium probe selection experiment, a temperature probe selection experiment, a cadmium validation experiment and a cadmium validation experiment.