Axiom Microbiome Array, the next generation microarray for high-throughput pathogen and microbiome analysis.

Microarrays have proven to be useful in rapid detection of many viruses and bacteria. Pathogen detection microarrays have been used to diagnose viral and bacterial infections in clinical samples and to evaluate the safety of biological drug materials. In this study, the Axiom Microbiome Array was evaluated to determine its sensitivity, specificity and utility in microbiome analysis of veterinary clinical samples. The array contains probes designed to detect more than 12,000 species of viruses, bacteria, fungi, protozoa and archaea, yielding the most comprehensive microbial detection platform built to date. The array was able to detect Shigella and Aspergillus at 100 genome copies, and vaccinia virus DNA at 1,000 genome copies. The Axiom Microbiome Array made correct species-level calls in mock microbial community samples. When tested against serum, tissue, and fecal samples from pigs experimentally co-infected with porcine reproductive and respiratory syndrome virus and porcine circovirus type 2, the microarray correctly detected these two viruses and other common viral and bacterial microbiome species. This cost-effective and high-throughput microarray is an efficient tool to rapidly analyze large numbers of clinical and environmental samples for the presence of multiple viral and bacterial pathogens.

MicroRNA polymorphisms and risk of colorectal cancer.

BACKGROUND: miRNAs act as post-transcriptional regulators of gene expression. Genetic variation in miRNA-encoding sequences or their corresponding binding sites may affect the fidelity of the miRNA-mRNA interaction and subsequently alter the risk of cancer development. METHODS: This study expanded the search for miRNA-related polymorphisms contributing to the etiology of colorectal cancer across the genome using a novel platform, the Axiom miRNA Target Site Genotyping Array (237,858 markers). After quality control, the study included 596 cases and 429 controls from the Molecular Epidemiology of Colorectal Cancer study, a population-based case-control study of colorectal cancer in northern Israel. The association between each marker and colorectal cancer status was examined assuming a log-additive genetic model using logistic regression adjusted for sex, age, and two principal components. RESULTS: Twenty-three markers had P values less than 5.0E-04, and the most statistically significant association involved rs2985 (chr6:34845648; intronic of UHRF1BP1; OR = 0.66; P = 3.7E-05). Furthermore, this study replicated a previously published risk locus, rs1051690, in the 3'-untranslated region of the insulin receptor gene INSR (OR = 1.38; P = 0.03), with strong evidence of differences in INSR gene expression by genotype. CONCLUSIONS: This study is the first to examine associations between genetic variation in miRNA target sites and colorectal cancer using a genome-wide approach. Functional studies to identify allele-specific effects on miRNA binding are needed to confirm the regulatory capacity of genetic variation to influence risk of colorectal cancer. IMPACT: This study demonstrates the potential for an miRNA-targeted genome-wide association study to identify candidate susceptibility loci and prioritize them for functional characterization.

Design and coverage of high throughput genotyping arrays optimized for individuals of East Asian, African American, and Latino race/ethnicity using imputation and a novel hybrid SNP selection algorithm.

Four custom Axiom genotyping arrays were designed for a genome-wide association (GWA) study of 100,000 participants from the Kaiser Permanente Research Program on Genes, Environment and Health. The array optimized for individuals of European race/ethnicity was previously described. Here we detail the development of three additional microarrays optimized for individuals of East Asian, African American, and Latino race/ethnicity. For these arrays, we decreased redundancy of high-performing SNPs to increase SNP capacity. The East Asian array was designed using greedy pairwise SNP selection. However, removing SNPs from the target set based on imputation coverage is more efficient than pairwise tagging. Therefore, we developed a novel hybrid SNP selection method for the African American and Latino arrays utilizing rounds of greedy pairwise SNP selection, followed by removal from the target set of SNPs covered by imputation. The arrays provide excellent genome-wide coverage and are valuable additions for large-scale GWA studies.

Next generation genome-wide association tool: design and coverage of a high-throughput European-optimized SNP array.

The success of genome-wide association studies has paralleled the development of efficient genotyping technologies. We describe the development of a next-generation microarray based on the new highly-efficient Affymetrix Axiom genotyping technology that we are using to genotype individuals of European ancestry from the Kaiser Permanente Research Program on Genes, Environment and Health (RPGEH). The array contains 674,517 SNPs, and provides excellent genome-wide as well as gene-based and candidate-SNP coverage. Coverage was calculated using an approach based on imputation and cross validation. Preliminary results for the first 80,301 saliva-derived DNA samples from the RPGEH demonstrate very high quality genotypes, with sample success rates above 94% and over 98% of successful samples having SNP call rates exceeding 98%. At steady state, we have produced 462 million genotypes per week for each Axiom system. The new array provides a valuable addition to the repertoire of tools for large scale genome-wide association studies.

DMET microarray technology for pharmacogenomics-based personalized medicine.

Human genome sequence variation in the form of single nucleotide polymorphisms (SNPs) as well as more complex structural variation such as insertions, duplications, and deletions underlies each individual's response to drugs and thus the likelihood of experiencing an adverse drug reaction. The ongoing challenge of the field of pharmacogenetics is to further understand the relationship between genetic variation and differential drug responses, with the overarching goal being that this will lead to improvements in both the safety and efficacy of drugs. The Affymetrix DMET Plus Premier Pack (DMET stands for Drug Metabolizing Enzymes and Transporters) enables highly multiplexed genotyping of known polymorphisms in Absorption, Distribution, Metabolism, and Elimination (ADME)-related genes on a single array. The DMET Plus Panel interrogates markers in 225 genes that have documented functional significance in phase I and phase II drug metabolism enzymes as well as drug transporters. The power of the DMET Assay has previously been demonstrated with regard to several different drugs including warfarin and clopidogrel. In a research study using an earlier four-color version of the assay, it was demonstrated that warfarin dosing can be influenced by a cytochrome P450 (CYP) 4F2 variant. Additionally, the assay has been used to demonstrate that CYP2C19 variants with decreased enzyme activity led to lower levels of the active clopidogrel metabolite, resulting in a decreased inhibition of platelets and a higher rate of cardiovascular events when compared to noncarriers of the DNA variant. Thus, highly multiplexed SNP genotyping focused on ADME-related polymorphisms should enable research into development of safer drugs with greater efficacy.

Population-genetic nature of copy number variations in the human genome.

Copy number variations (CNVs) are universal genetic variations, and their association with disease has been increasingly recognized. We designed high-density microarrays for CNVs, and detected 3000-4000 CNVs (4-6% of the genomic sequence) per population that included CNVs previously missed because of smaller sizes and residing in segmental duplications. The patterns of CNVs across individuals were surprisingly simple at the kilo-base scale, suggesting the applicability of a simple genetic analysis for these genetic loci. We utilized the probabilistic theory to determine integer copy numbers of CNVs and employed a recently developed phasing tool to estimate the population frequencies of integer copy number alleles and CNV-SNP haplotypes. The results showed a tendency toward a lower frequency of CNV alleles and that most of our CNVs were explained only by zero-, one- and two-copy alleles. Using the estimated population frequencies, we found several CNV regions with exceptionally high population differentiation. Investigation of CNV-SNP linkage disequilibrium (LD) for 500-900 bi- and multi-allelic CNVs per population revealed that previous conflicting reports on bi-allelic LD were unexpectedly consistent and explained by an LD increase correlated with deletion-allele frequencies. Typically, the bi-allelic LD was lower than SNP-SNP LD, whereas the multi-allelic LD was somewhat stronger than the bi-allelic LD. After further investigation of tag SNPs for CNVs, we conclude that the customary tagging strategy for disease association studies can be applicable for common deletion CNVs, but direct interrogation is needed for other types of CNVs.

Integrated detection and population-genetic analysis of SNPs and copy number variation.

Dissecting the genetic basis of disease risk requires measuring all forms of genetic variation, including SNPs and copy number variants (CNVs), and is enabled by accurate maps of their locations, frequencies and population-genetic properties. We designed a hybrid genotyping array (Affymetrix SNP 6.0) to simultaneously measure 906,600 SNPs and copy number at 1.8 million genomic locations. By characterizing 270 HapMap samples, we developed a map of human CNV (at 2-kb breakpoint resolution) informed by integer genotypes for 1,320 copy number polymorphisms (CNPs) that segregate at an allele frequency >1%. More than 80% of the sequence in previously reported CNV regions fell outside our estimated CNV boundaries, indicating that large (>100 kb) CNVs affect much less of the genome than initially reported. Approximately 80% of observed copy number differences between pairs of individuals were due to common CNPs with an allele frequency >5%, and more than 99% derived from inheritance rather than new mutation. Most common, diallelic CNPs were in strong linkage disequilibrium with SNPs, and most low-frequency CNVs segregated on specific SNP haplotypes.

Improved detection of global copy number variation using high density, non-polymorphic oligonucleotide probes.

BACKGROUND: DNA sequence diversity within the human genome may be more greatly affected by copy number variations (CNVs) than single nucleotide polymorphisms (SNPs). Although the importance of CNVs in genome wide association studies (GWAS) is becoming widely accepted, the optimal methods for identifying these variants are still under evaluation. We have previously reported a comprehensive view of CNVs in the HapMap DNA collection using high density 500 K EA (Early Access) SNP genotyping arrays which revealed greater than 1,000 CNVs ranging in size from 1 kb to over 3 Mb. Although the arrays used most commonly for GWAS predominantly interrogate SNPs, CNV identification and detection does not necessarily require the use of DNA probes centered on polymorphic nucleotides and may even be hindered by the dependence on a successful SNP genotyping assay. RESULTS: In this study, we have designed and evaluated a high density array predicated on the use of non-polymorphic oligonucleotide probes for CNV detection. This approach effectively uncouples copy number detection from SNP genotyping and thus has the potential to significantly improve probe coverage for genome-wide CNV identification. This array, in conjunction with PCR-based, complexity-reduced DNA target, queries over 1.3 M independent NspI restriction enzyme fragments in the 200 bp to 1100 bp size range, which is a several fold increase in marker density as compared to the 500 K EA array. In addition, a novel algorithm was developed and validated to extract CNV regions and boundaries. CONCLUSION: Using a well-characterized pair of DNA samples, close to 200 CNVs were identified, of which nearly 50% appear novel yet were independently validated using quantitative PCR. The results indicate that non-polymorphic probes provide a robust approach for CNV identification, and the increasing precision of CNV boundary delineation should allow a more complete analysis of their genomic organization.

High-density oligonucleotide array with sub-kilobase resolution reveals breakpoint information of submicroscopic deletions in nevoid basal cell carcinoma syndrome.

Small submicroscopic genomic deletions and duplications constitute up to 15% of all mutations underlying human monogenic diseases. In this study, we used newly designed high-resolution oligonucleotide microarrays with a median distance between the probes of 776 bp (average probe interval 2,271 bp) to detect gene deletions in nevoid basal cell carcinoma syndrome (NBCCS) patients. NBCCS, also called Gorlin syndrome, is characterized by developmental defects and tumorigenesis such as medulloblastomas and basal cell carcinomas, caused by mutations of the human patched-1 (PTCH1) gene. Two out of three deletions could not be detected by a conventional chromosomal analysis. A submicroscopic deletion as small as 165 kb was detected affecting only PTCH1, whereas the other two deletions were much larger (5 and 11 Mb). We demonstrated not only the exact number of genes involved in the deletion but also rapidly determined the junction sequences after pinpointing the breakpoint regions in all individuals analyzed. This report of an array-based determination of junction sequences of long deletions circumvented a labor-intensive analysis such as Southern blotting or FISH. Alu-mediated recombination in one case and non-homologous end joining in the other two were probably implicated in the generation of deletions. This method will contribute to the understanding of molecular pathogenesis of gene deletions as well as rapid genetic testing.

Global variation in copy number in the human genome.

Copy number variation (CNV) of DNA sequences is functionally significant but has yet to be fully ascertained. We have constructed a first-generation CNV map of the human genome through the study of 270 individuals from four populations with ancestry in Europe, Africa or Asia (the HapMap collection). DNA from these individuals was screened for CNV using two complementary technologies: single-nucleotide polymorphism (SNP) genotyping arrays, and clone-based comparative genomic hybridization. A total of 1,447 copy number variable regions (CNVRs), which can encompass overlapping or adjacent gains or losses, covering 360 megabases (12% of the genome) were identified in these populations. These CNVRs contained hundreds of genes, disease loci, functional elements and segmental duplications. Notably, the CNVRs encompassed more nucleotide content per genome than SNPs, underscoring the importance of CNV in genetic diversity and evolution. The data obtained delineate linkage disequilibrium patterns for many CNVs, and reveal marked variation in copy number among populations. We also demonstrate the utility of this resource for genetic disease studies.

Genome-wide detection of human copy number variations using high-density DNA oligonucleotide arrays.

Recent reports indicate that copy number variations (CNVs) within the human genome contribute to nucleotide diversity to a larger extent than single nucleotide polymorphisms (SNPs). In addition, the contribution of CNVs to human disease susceptibility may be greater than previously expected, although a complete understanding of the phenotypic consequences of CNVs is incomplete. We have recently reported a comprehensive view of CNVs among 270 HapMap samples using high-density SNP genotyping arrays and BAC array CGH. In this report, we describe a novel algorithm using Affymetrix GeneChip Human Mapping 500K Early Access (500K EA) arrays that identified 1203 CNVs ranging in size from 960 bp to 3.4 Mb. The algorithm consists of three steps: (1) Intensity pre-processing to improve the resolution between pairwise comparisons by directly estimating the allele-specific affinity as well as to reduce signal noise by incorporating probe and target sequence characteristics via an improved version of the Genomic Imbalance Map (GIM) algorithm; (2) CNV extraction using an adapted SW-ARRAY procedure to automatically and robustly detect candidate CNV regions; and (3) copy number inference in which all pairwise comparisons are summarized to more precisely define CNV boundaries and accurately estimate CNV copy number. Independent testing of a subset of CNVs by quantitative PCR and mass spectrometry demonstrated a >90% verification rate. The use of high-resolution oligonucleotide arrays relative to other methods may allow more precise boundary information to be extracted, thereby enabling a more accurate analysis of the relationship between CNVs and other genomic features.

CARAT: a novel method for allelic detection of DNA copy number changes using high density oligonucleotide arrays.

BACKGROUND: DNA copy number alterations are one of the main characteristics of the cancer cell karyotype and can contribute to the complex phenotype of these cells. These alterations can lead to gains in cellular oncogenes as well as losses in tumor suppressor genes and can span small intervals as well as involve entire chromosomes. The ability to accurately detect these changes is central to understanding how they impact the biology of the cell. RESULTS: We describe a novel algorithm called CARAT (Copy Number Analysis with Regression And Tree) that uses probe intensity information to infer copy number in an allele-specific manner from high density DNA oligonuceotide arrays designed to genotype over 100,000 SNPs. Total and allele-specific copy number estimations using CARAT are independently evaluated for a subset of SNPs using quantitative PCR and allelic TaqMan reactions with several human breast cancer cell lines. The sensitivity and specificity of the algorithm are characterized using DNA samples containing differing numbers of X chromosomes as well as a test set of normal individuals. Results from the algorithm show a high degree of agreement with results from independent verification methods. CONCLUSION: Overall, CARAT automatically detects regions with copy number variations and assigns a significance score to each alteration as well as generating allele-specific output. When coupled with SNP genotype calls from the same array, CARAT provides additional detail into the structure of genome wide alterations that can contribute to allelic imbalance.

Evaluating potential for whole-genome studies in Kosrae, an isolated population in Micronesia.

Whole-genome association studies are predicted to be especially powerful in isolated populations owing to increased linkage disequilibrium (LD) and decreased allelic diversity, but this possibility has not been empirically tested. We compared genome-wide data on 113,240 SNPs typed on 30 trios from the Pacific island of Kosrae to the same markers typed in the 270 samples from the International HapMap Project. The extent of LD is longer and haplotype diversity is lower in Kosrae than in the HapMap populations. More than 98% of Kosraen haplotypes are present in HapMap populations, indicating that HapMap will be useful for genetic studies on Kosrae. The long-range LD around common alleles and limited diversity result in improved efficiency in genetic studies in this population and augments the power to detect association of 'hidden SNPs'.

Whole genome DNA copy number changes identified by high density oligonucleotide arrays.

Changes in DNA copy number are one of the hallmarks of the genetic instability common to most human cancers. Previous microarray-based methods have been used to identify chromosomal gains and losses; however, they are unable to genotype alleles at the level of single nucleotide polymorphisms (SNPs). Here we describe a novel algorithm that uses a recently developed high-density oligonucleotide array-based SNP genotyping method, whole genome sampling analysis (WGSA), to identify genome-wide chromosomal gains and losses at high resolution. WGSA simultaneously genotypes over 10,000 SNPs by allele-specific hybridisation to perfect match (PM) and mismatch (MM) probes synthesised on a single array. The copy number algorithm jointly uses PM intensity and discrimination ratios between paired PM and MM intensity values to identify and estimate genetic copy number changes. Values from an experimental sample are compared with SNP-specific distributions derived from a reference set containing over 100 normal individuals to gain statistical power. Genomic regions with statistically significant copy number changes can be identified using both single point analysis and contiguous point analysis of SNP intensities. We identified multiple regions of amplification and deletion using a panel of human breast cancer cell lines. We verified these results using an independent method based on quantitative polymerase chain reaction and found that our approach is both sensitive and specific and can tolerate samples which contain a mixture of both tumour and normal DNA. In addition, by using known allele frequencies from the reference set, statistically significant genomic intervals can be identified containing contiguous stretches of homozygous markers, potentially allowing the detection of regions undergoing loss of heterozygosity (LOH) without the need for a matched normal control sample. The coupling of LOH analysis, via SNP genotyping, with copy number estimations using a single array provides additional insight into the structure of genomic alterations. With mean and median inter-SNP euchromatin distances of 244 kilobases (kb) and 119 kb, respectively, this method affords a resolution that is not easily achievable with non-oligonucleotide-based experimental approaches.

MARA: a novel approach for highly multiplexed locus-specific SNP genotyping using high-density DNA oligonucleotide arrays.

We have developed a locus-specific DNA target preparation method for highly multiplexed single nucleotide polymorphism (SNP) genotyping called MARA (Multiplexed Anchored Runoff Amplification). The approach uses a single primer per SNP in conjunction with restriction enzyme digested, adapter-ligated human genomic DNA. Each primer is composed of common sequence at the 5' end followed by locus-specific sequence at the 3' end. Following a primary reaction in which locus-specific products are generated, a secondary universal amplification is carried out using a generic primer pair corresponding to the oligonucleotide and genomic DNA adapter sequences. Allele discrimination is achieved by hybridization to high-density DNA oligonucleotide arrays. Initial multiplex reactions containing either 250 primers or 750 primers across nine DNA samples demonstrated an average sample call rate of approximately 95% for 250- and 750-plex MARA. We have also evaluated >1000- and 4000-primer plex MARA to genotype SNPs from human chromosome 21. We have identified a subset of SNPs corresponding to a primer conversion rate of approximately 75%, which show an average call rate over 95% and concordance >99% across seven DNA samples. Thus, MARA may potentially improve the throughput of SNP genotyping when coupled with allele discrimination on high-density arrays by allowing levels of multiplexing during target generation that far exceed the capacity of traditional multiplex PCR.

High-resolution analysis of DNA copy number using oligonucleotide microarrays.

Genomic copy number alterations are a feature of many human diseases including cancer. We have evaluated the effectiveness of an oligonucleotide array, originally designed to detect single-nucleotide polymorphisms, to assess DNA copy number. We first showed that fluorescent signal from the oligonucleotide array varies in proportion to both decreases and increases in copy number. Subsequently we applied the system to a series of 20 cancer cell lines. All of the putative homozygous deletions (10) and high-level amplifications (12; putative copy number >4) tested were confirmed by PCR (either qPCR or normal PCR) analysis. Low-level copy number changes for two of the lines under analysis were compared with BAC array CGH; 77% (n = 44) of the autosomal chromosomes used in the comparison showed consistent patterns of LOH (loss of heterozygosity) and low-level amplification. Of the remaining 10 comparisons that were discordant, eight were caused by low SNP densities and failed in both lines. The studies demonstrate that combining the genotype and copy number analyses gives greater insight into the underlying genetic alterations in cancer cells with identification of complex events including loss and reduplication of loci.

In Vivo Persistence of Donor Cells following Adoptive Transfer of Allogeneic Dendritic Cells in HIV-Infected Patients.

Peripheral blood samples from HIV-seropositive individuals enrolled in a pilot clinical trial investigating the use of allogeneic dendritic cell therapy were evaluated for mixed chimerism. In this study, dendritic cells from HLA-identical, HIV-seronegative siblings were used. Patients received an infusion of dendritic cells pulsed with HIV MN gp160 protein or with peptides from HLA-A2 restricted epitopes of env, gag, and pol proteins every month for 6-9 months. Of the five allogeneic dendritic cell recipients, two showed increases in HIV antigen-specific immune responses. Allele-specific polymorphisms were identified in three sib-pairs that allowed infused donor cells to be detected using sensitive PCR-based molecular methods. Analysis of blood samples from patients showed similar patterns of donor cell persistence after the first infusion, in that cells were detectable for at least 1 week. Also, differences were observed in the kinetics of cell survival between the first and subsequent infusion cycles in all three patients. This suggests variation in HIV-specific immune responses detected among these three patients was not due to differences in persistence of infused donor cells.