MACGT: multi-dimensional automated clustering genotyping tool for analysis of microarray-based mini-sequencing data

SUMMARY: Multi-dimensional Automated Clustering Genotyping Tool (MACGT) is a Java application that clusters complex multi-dimensional vector data derived from single nucleotide polymorphism (SNP) genotyping experiments using mini-sequencing based microarray chemistries such as arrayed primer extension (APEX). Spot intensity output files from microarray experiments across multiple samples are imported into MACGT. The datasets can include four channels of intensity data for each spot, replica spots for each SNP probe and multiple probe types (APEX and allele-specific APEX probes) on both DNA strands for each SNP. MACGT automatically clusters these multi-dimensionality datasets for each SNP across multiple samples. Incorporation of additional array datasets from known samples that have previously validated SNP genotype calls allows unknown samples to be automatically assigned a genotype based on the clustering, along with numerical measures of confidence for each genotype call. Calling accuracy by MACGT exceeds 98% when applied to genotyping data from APEX microarrays, and can be increased to >99.5% by applying thresholds to the confidence measures.     

Dynamic variable selection in SNP genotype autocalling from APEX microarray data

Background  

Single nucleotide polymorphisms (SNPs) are DNA sequence variations, occurring when a single nucleotide – adenine (A), thymine (T), cytosine (C) or guanine (G) – is altered. Arguably, SNPs account for more than 90% of human genetic variation. Our laboratory has developed a highly redundant SNP genotyping assay consisting of multiple probes with signals from multiple channels for a single SNP, based on arrayed primer extension (APEX). This mini-sequencing method is a powerful combination of a highly parallel microarray with distinctive Sanger-based dideoxy terminator sequencing chemistry. Using this microarray platform, our current genotype calling system (known as SNP Chart) is capable of calling single SNP genotypes by manual inspection of the APEX data, which is time-consuming and exposed to user subjectivity bias.     

ArrayFusion: a web application for multi-dimensional analysis of CGH, SNP and microarray data

ArrayFusion annotates conventional CGH results and various types of microarray data from a range of platforms (cDNA, expression, exon, SNP, array-CGH and ChIP-on-chip) and converts them into standard formats which can be visualized in genome browsers (Affymetrix Integrated Genome Browser and GBrowse in the HapMap Project). Converted files can then be imported simultaneously into a single genome browser to benefit a collective interpretation between different array results. ArrayFusion therefore provides a new type of tool facilitating the integration of CGH and array results to provide new experimental directions. AVAILABILITY: http://microarray.ym.edu.tw/tools/arrayfusion     

The application of single nucleotide polymorphism microarrays in cancer research

The development of microarray technology has had a significant impact on the genetic analysis of human disease. The recently developed single nucleotide polymorphism (SNP) array can be used to measure both DNA polymorphism and dosage changes. Our laboratory has applied SNP microarray analysis to uncover frequent uniparental disomies and sub-microscopic genomic copy number gains and losses in different cancers. This review will focus on the wide range of applications of SNP microarray analysis to cancer research. SNP array genotyping can determine loss of heterozygosity, genomic copy number changes and DNA methylation alterations of cancer cells. The same technology can also be used to investigate allelic association in cancers. Therefore, it can be applied to the identification of cancer predisposition genes, oncogenes and tumor suppressor genes in specific types of tumors. As a consequence, they have potential in cancer risk assessment, diagnosis, prognosis and treatment selection.     

Effect of secondary structure on single nucleotide polymorphism detection with a porous microarray matrix; implications for probe selection

Oligonucleotide arrays capable of detecting single nucleotide polymorphisms (SNPs) from amplified nucleic acid have many applications. The expected SNP is usually placed approximately in the center of the probe to ensure the maximum shift in Tm between complementary and SNP sequences. Unfortunately, different short probes (< 30 bases) selected using widely accepted criteria do not perform consistently in this type of assay. Here we present a systematic study on the effect of secondary structure on the ability of oligonucleotide probes to detect an SNP, using real-time array monitoring of a porous microarray substrate that incorporates a novel intra-array mixing system. These results demonstrate that, although positioning of an SNP in the middle of the probe is highly destabilizing, the effect of stable secondary structure on the signal obtained is so dramatic that such probes may be very insensitive. Therefore, if the SNP flanking sequence contains significant secondary structure, then more sensitive probes with good specificity may be obtained by positioning the mutation towards one end of the probe.     

Conversion of array‐based single nucleotide polymorphic markers for use in targeted genotyping by sequencing in hexaploid wheat (Triticum aestivum)

Wheat breeders and academics alike use single nucleotide polymorphisms (SNP s) as molecular markers to characterize regions of interest within the hexaploid wheat genome. A number of SNP ‐based genotyping platforms are available, and their utility depends upon factors such as the available technologies, number of data points required, budgets and the technical expertise required. Unfortunately, markers can rarely be exchanged between existing and newly developed platforms, meaning that previously generated data cannot be compared, or combined, with more recently generated data sets. We predict that genotyping by sequencing will become the predominant genotyping technology within the next 5–10 years. With this in mind, to ensure that data generated from current genotyping platforms continues to be of use, we have designed and utilized SNP ‐based capture probes from several thousand existing and publicly available probes from Axiom® and KASP ? genotyping platforms. We have validated our capture probes in a targeted genotyping by sequencing protocol using 31 previously genotyped UK elite hexaploid wheat accessions. Data comparisons between targeted genotyping by sequencing, Axiom® array genotyping and KASP ? genotyping assays, identified a set of 3256 probes which reliably bring together targeted genotyping by sequencing data with the previously available marker data set. As such, these probes are likely to be of considerable value to the wheat community. The probe details, full probe sequences and a custom built analysis pipeline may be freely downloaded from the CerealsDB website (http://www.cerealsdb.uk.net/cerealgenomics/CerealsDB /sequence_capture.php).     

A multi-array multi-SNP genotyping algorithm for Affymetrix SNP microarrays

MOTIVATION: Modern strategies for mapping disease loci require efficient genotyping of a large number of known polymorphic sites in the genome. The sensitive and high-throughput nature of hybridization-based DNA microarray technology provides an ideal platform for such an application by interrogating up to hundreds of thousands of single nucleotide polymorphisms (SNPs) in a single assay. Similar to the development of expression arrays, these genotyping arrays pose many data analytic challenges that are often platform specific. Affymetrix SNP arrays, e.g. use multiple sets of short oligonucleotide probes for each known SNP, and require effective statistical methods to combine these probe intensities in order to generate reliable and accurate genotype calls. RESULTS: We developed an integrated multi-SNP, multi-array genotype calling algorithm for Affymetrix SNP arrays, MAMS, that combines single-array multi-SNP (SAMS) and multi-array, single-SNP (MASS) calls to improve the accuracy of genotype calls, without the need for training data or computation-intensive normalization procedures as in other multi-array methods. The algorithm uses resampling techniques and model-based clustering to derive single array based genotype calls, which are subsequently refined by competitive genotype calls based on (MASS) clustering. The resampling scheme caps computation for single-array analysis and hence is readily scalable, important in view of expanding numbers of SNPs per array. The MASS update is designed to improve calls for atypical SNPs, harboring allele-imbalanced binding affinities, that are difficult to genotype without information from other arrays. Using a publicly available data set of HapMap samples from Affymetrix, and independent calls by alternative genotyping methods from the HapMap project, we show that our approach performs competitively to existing methods. AVAILABILITY: R functions are available upon request from the authors.     

Three-dimensional microarray platform applied to single nucleotide polymorphism analysis

Bio-Strand, Inc., has developed a novel DNA microarray platform utilizing a three-dimensional (3D) DNA format. DNA probes or polymerase chain reaction (PCR) products are spotted onto a thread-like scaffold, which is then wound onto a cylindrical core. By wrapping the thread around the core, high efficiencies are achieved in sample analysis. Using allele-specific oligo (ASO) competitive hybridization (with Cy5 fluorescently labeled sequences), hybridized arrays are visualized using a helium-neon (HeNe) laser and quantitated/scored. The method can readily detect single nucleotide differences. We demonstrate the use of this Bio-Strand 3D array in the analysis of a single nucleotide polymorphism (SNP).     

High-throughput SNP genotyping based on solid-phase PCR on magnetic nanoparticles with dual-color hybridization

Single-nucleotide polymorphisms (SNPs) are one-base variations in DNA sequence that can often be helpful when trying to find genes responsible for inherited diseases. In this paper, a microarray-based method for typing single nucleotide polymorphisms (SNPs) using solid-phase polymerase chain reaction (PCR) on magnetic nanoparticles (MNPs) was developed. One primer with biotin-label was captured by streptavidin coated magnetic nanoparticles (SA-MNPs), and PCR products were directly amplified on the surface of SA-MNPs in a 96-well plate. The samples were interrogated by hybridization with a pair of dual-color probes to determine SNP, and then genotype of each sample can be simultaneously identified by scanning the microarray printed with the denatured fluorescent probes. The C677T polymorphisms of methylenetetrahydrofolate reductase (MTHFR) gene from 126 samples were interrogated using this method. The results showed that three different genotypes were discriminated by three fluorescence patterns on the microarray. Without any purification and reduction procedure, and all reactions can be performed in the same vessel, this approach will be a simple and labor-saving method for SNP genotyping and can be applicable towards the automation system to achieve high-throughput SNP detection.     

Guidelines for incorporating non-perfectly matched oligonucleotides into target-specific hybridization probes for a DNA microarray

Sequence-specific oligonucleotide probes play a crucial role in hybridization techniques including PCR, DNA microarray and RNA interference. Once the entire genome becomes the search space for target genes/genomic sequences, however, cross-hybridization to non-target sequences becomes a problem. Large gene families with significant similarity among family members, such as the P450s, are particularly problematic. Additionally, accurate single nucleotide polymorphism (SNP) detection depends on probes that can distinguish between nearly identical sequences. Conventional oligonucleotide probes that are perfectly matched to target genes/genomic sequences are often unsuitable in such cases. Carefully designed mismatches can be used to decrease cross-hybridization potential, but implementing all possible mismatch probes is impractical. Our study provides guidelines for designing non-perfectly matched DNA probes to target DNA sequences as desired throughout the genome. These guidelines are based on the analysis of hybridization data between perfectly matched and non-perfectly matched DNA sequences (single-point or double-point mutated) calculated in silico. Large changes in hybridization temperature predicted by these guidelines for non-matched oligonucleotides fit independent experimental data very well. Applying the guidelines to find oligonucleotide microarray probes for P450 genes, we confirmed the ability of our point mutation method to differentiate the individual genes in terms of thermodynamic calculations of hybridization and sequence similarity.     

Free energy of DNA duplex formation on short oligonucleotide microarrays

DNA/DNA duplex formation is the basic mechanism that is used in genome tiling arrays and SNP arrays manufactured by Affymetrix. However, detailed knowledge of the physical process is still lacking. In this study, we show a free energy analysis of DNA/DNA duplex formation these arrays based on the positional-dependent nearest-neighbor (PDNN) model, which was developed previously for describing DNA/RNA duplex formation on expression microarrays. Our results showed that the two ends of a probe contribute less to the stability of the duplexes and that there is a microarray surface effect on binding affinities. We also showed that free energy cost of a single mismatch depends on the bases adjacent to the mismatch site and obtained a comprehensive table of the cost of a single mismatch under all possible combination of adjacent bases. The mismatch costs were found to be correlated with those determined in aqueous solution. We further demonstrate that the DNA copy number estimated from the SNP array correlates negatively with the target length; this is presumably caused by inefficient PCR amplification for long fragments. These results provide important insights into the molecular mechanisms of microarray technology and have implications for microarray design and the interpretation of observed data.     

Using high-density exon arrays to profile gene expression in closely related species

Global comparisons of gene expression profiles between species provide significant insight into gene regulation, evolutionary processes and disease mechanisms. In this work, we describe a flexible and intuitive approach for global expression profiling of closely related species, using high-density exon arrays designed for a single reference genome. The high-density probe coverage of exon arrays allows us to select identical sets of perfect-match probes to measure expression levels of orthologous genes. This eliminates a serious confounding factor in probe affinity effects of species-specific microarray probes, and enables direct comparisons of estimated expression indexes across species. Using a newly designed Affymetrix exon array, with eight probes per exon for approximately 315 000 exons in the human genome, we conducted expression profiling in corresponding tissues from humans, chimpanzees and rhesus macaques. Quantitative real-time PCR analysis of differentially expressed candidate genes is highly concordant with microarray data, yielding a validation rate of 21/22 for human versus chimpanzee differences, and 11/11 for human versus rhesus differences. This method has the potential to greatly facilitate biomedical and evolutionary studies of gene expression in nonhuman primates and can be easily extended to expression array design and comparative analysis of other animals and plants.     

Suspension arrays for high throughput, multiplexed single nucleotide polymorphism genotyping

BACKGROUND: Genetic diversity can help explain disease susceptibility and differential drug response. The most common type of variant is the single nucleotide polymorphism (SNP). We present a low-cost, high throughput assay for SNP genotyping. METHODS: The assay uses oligonucleotide probes covalently attached to fluorescently encoded microspheres. These probes are hybridized directly to fluorescently labeled polymerase chain reaction (PCR) products and the results are analyzed in a standard flow cytometer. RESULTS: The genotypes determined with our assay are in good agreement with those determined by TaqMan. The range of G/C content for oligonucleotide probes was 23.5-65% in the 17 bases surrounding the SNP. Further optimization of probe length and target concentration is shown to dramatically enhance the assay performance for certain SNPs. Using microspheres which have unique fluorescent signatures, we performed a 32-plex assay where we simultaneously determined the genotypes of eight different polymorphic genes. CONCLUSIONS: We demonstrate, for the first time, the feasibility of multiplexed genotyping with suspension arrays using direct hybridization analyses. Our approach enables probes to be removed from or added to an array, enhancing flexibility over conventional chips. The ability to multiplex both the PCR preparation and the hybridization should enhance the throughput, cost, and speed of the assay.     

Estimation of relative allele frequencies of single-nucleotide polymorphisms in different populations by microarray hybridization of pooled DNA

Single-nucleotide polymorphisms (SNPs) are considered useful polymorphic markers for genetic studies of polygenic traits. A new practical approach to high-throughput genotyping of SNPs in a large number of individuals is needed in association study and other studies on relationships between genes and diseases. We have developed an accurate and high-throughput method for determining the allele frequencies by pooling the DNA samples and applying a DNA microarray hybridization analysis. In this method, the combination of the microarray, DNA pooling, probe pair hybridization, and fluorescent ratio analysis solves the dual problems of parallel multiple sample analysis, and parallel multiplex SNP genotyping for association study. Multiple DNA samples are immobilized on a slide and a single hybridization is performed with a pool of allele-specific oligonucleotide probes. The results of this study show that hybridization of microarray from pooled DNA samples can accurately obtain estimates of absolute allele frequencies in a sample pool. This method can also be used to identify differences in allele frequencies in distinct populations. It is amenable to automation and is suitable for immediate utilization for high-throughput genotyping of SNP.     

Demonstrating a Multi-drug Resistant Mycobacterium tuberculosis Amplification Microarray

Simplifying microarray workflow is a necessary first step for creating MDR-TB microarray-based diagnostics that can be routinely used in lower-resource environments. An amplification microarray combines asymmetric PCR amplification, target size selection, target labeling, and microarray hybridization within a single solution and into a single microfluidic chamber. A batch processing method is demonstrated with a 9-plex asymmetric master mix and low-density gel element microarray for genotyping multi-drug resistant Mycobacterium tuberculosis (MDR-TB). The protocol described here can be completed in 6 hr and provide correct genotyping with at least 1,000 cell equivalents of genomic DNA. Incorporating on-chip wash steps is feasible, which will result in an entirely closed amplicon method and system. The extent of multiplexing with an amplification microarray is ultimately constrained by the number of primer pairs that can be combined into a single master mix and still achieve desired sensitivity and specificity performance metrics, rather than the number of probes that are immobilized on the array. Likewise, the total analysis time can be shortened or lengthened depending on the specific intended use, research question, and desired limits of detection. Nevertheless, the general approach significantly streamlines microarray workflow for the end user by reducing the number of manually intensive and time-consuming processing steps, and provides a simplified biochemical and microfluidic path for translating microarray-based diagnostics into routine clinical practice.     

An optimized microarray platform for assaying genomic variation in <Emphasis Type="Italic">Plasmodium falciparum</Emphasis> field populations

We present an optimized probe design for copy number variation (CNV) and SNP genotyping in the Plasmodium falciparum genome. We demonstrate that variable length and isothermal probes are superior to static length probes. We show that sample preparation and hybridization conditions mitigate the effects of host DNA contamination in field samples. The microarray and workflow presented can be used to identify CNVs and SNPs with 95% accuracy in a single hybridization, in field samples containing up to 92% human DNA contamination.     

SNPTools: a software tool for visualization and analysis of microarray data

SUMMARY: We have created a software tool, SNPTools, for analysis and visualization of microarray data, mainly SNP array data. The software can analyse and find differences in intensity levels between groups of arrays and identify segments of SNPs (genes, clones), where the intensity levels differ significantly between the groups. In addition, SNPTools can show jointly loss-of-heterozygosity (LOH) data (derived from genotypes) and intensity data for paired samples of tumour and normal arrays. The output graphs can be manipulated in various ways to modify and adjust the layout. A wizard allows options and parameters to be changed easily and graphs replotted. All output can be saved in various formats, and also re-opened in SNPTools for further analysis. For explorative use, SNPTools allows various genome information to be loaded onto the graphs. AVAILABILITY: The software, example data sets and tutorials are freely available from http://www.birc.au.dk/snptools     

High reproducibility using sodium hydroxide-stripped long oligonucleotide DNA microarrays

Recently, long oligonucleotide (60- to 70-mer) microarrays for two-color experiments have been developed and are gaining widespread use. In addition, when there is limited availability of mRNA from tissue sources, RNA amplification can and is being used to produce sufficient quantities of cRNA for microarray hybridization. Taking advantage of the selective degradation of RNA under alkaline conditions, we have developed a method to "strip" glass-based oligonucleotide microarrays that use fluorescent RNA in the hybridization, while leaving the DNA oligonucleotide probes intact and usable for a second experiment. Replicate microarray experiments conducted using stripped arrays showed high reproducibility, however, we found that arrays could only be stripped and reused once without compromising data quality. The intraclass correlation (ICC) between a virgin array and a stripped array hybridized with the same sample showed a range of 0.90-0.98, which is comparable to the ICC of two virgin arrays hybridized with the same sample. Using this method, once-stripped oligonucleotide microarrays are usable, reliable, and help to reduce costs.     

Single-nucleotide polymorphism analysis by hybridization protection assay on solid support

The clinical need for high-throughput typing methods of single-nucleotide polymorphisms (SNPs) has been increasing. Conventional methods do not perform well enough in terms of speed and accuracy to process a large number of samples, as in clinical testing. We report a new DNA microarray method that uses hybridization protection assay (HPA) by acridinium-ester-labeled DNA probes. Probes were immobilized on the bottom of streptavidin-coated microtiter plates by streptavidin-biotin binding. We studied aldehyde dehydrogenase 2 (ALDH2) genotyping using two probes, discriminating A/G polymorphism. We also designed four probes to type the Alzheimer's disease-related gene ApoE, which has three genotypes (ApoE2, 3, and 4) determined by two SNP loci (C/T polymorphism). SNP analysis of the ALDH2 gene or the ApoE gene from human genome samples by solid-phase HPA was successful. Unlike other methods, the microarray by HPA does not require a washing step and can be completed within 30min. It also has advantages in discriminating one-base mismatch in targets. These characteristics make it a good candidate for practical SNP analysis of disease-related genes or drug-metabolizing enzymes in large numbers of samples.