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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.

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. Cancer Epidemiol Biomarkers Prev; 24(1); 65–72. ©2014 AACR.

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.

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.

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.

The Kaiser Permanente (KP) Research Program on Genes, Environment and Health (RPGEH), in collaboration with the University of California—San Francisco, undertook genome-wide genotyping of >100,000 subjects that constitute the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. The project, which generated >70 billion genotypes, represents the first large-scale use of the Affymetrix Axiom Genotyping Solution. Because genotyping took place over a short 14-month period, creating a near-real-time analysis pipeline for experimental assay quality control and final optimized analyses was critical. Because of the multi-ethnic nature of the cohort, four different ethnic-specific arrays were employed to enhance genome-wide coverage. All assays were performed on DNA extracted from saliva samples. To improve sample call rates and significantly increase genotype concordance, we partitioned the cohort into disjoint packages of plates with similar assay contexts. Using strict QC criteria, the overall genotyping success rate was 103,067 of 109,837 samples assayed (93.8%), with a range of 92.1–95.4% for the four different arrays. Similarly, the SNP genotyping success rate ranged from 98.1 to 99.4% across the four arrays, the variation depending mostly on how many SNPs were included as single copy vs. double copy on a particular array. The high quality and large scale of genotype data created on this cohort, in conjunction with comprehensive longitudinal data from the KP electronic health records of participants, will enable a broad range of highly powered genome-wide association studies on a diversity of traits and conditions.

Changes in DNA copy number are one of the hallmarks of the genetic instability common to most human cancers. Previous micro-array-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.

The emerging role of single-nucleotide polymorphisms (SNPs) in clinical association and pharmacogenetic studies has created a need for high-throughput genotyping technologies. We describe a novel method for multiplexed genotyping of SNPs that employs PCR amplification on microspheres. Oligonucleotide PCR primers were designed for each polymorphic locus such that one of the primers contained a recognition site for BbvI (a type IIS restriction enzyme), followed by 11 nucleotides of locus-specific sequence, which reside immediately upstream of the polymorphic site. Following amplification, this configuration allows for any SNP to be exposed by BbvI digestion and interrogated via primer extension, four-color minisequencing. Primers containing 5′ acrylamide groups were attached covalently to the solid support through copolymerization into acrylamide beads. Highly multiplexed solid-phase amplification using human genomic DNA was demonstrated with 57 beads in a single reaction. Multiplexed amplification and minisequencing reactions using bead sets representing eight polymorphic loci were carried out with genomic DNA from eight individuals. Sixty-three of 64 genotypes were accurately determined by this method when compared to genotypes determined by restriction-enzyme digestion of PCR products. This method provides an accurate, robust approach toward multiplexed genotyping that may facilitate the use of SNPs in such diverse applications as pharmacogenetics and genome-wide association studies for complex genetic diseases.

Both single and two SNP strategies for predicting NAT2 phenotype have been recently proposed [1]. The potential for practical utility caused an assessment of predictive potential across multiple world populations, with the goal of determining predictive ability for global health studies. A NAT2 genotype profile of 16 SNPs (including rs1041983 and rs1801280) were determined in 595 HapMap samples (59 Utah residents with Northern and Western European ancestry (CEU), 60 Mexican ancestry in Los Angeles, California (MEX), 90 Han Chinese in Beijing, China (CHB), 87 Chinese in Metropolitan Denver, Colorado (CHD), 91 Japanese in Tokyo, Japan (JPT), 89 Luhya in Webuye, Kenya (LWK) and 119 Yoruba in Ibadan, Nigeria (YRI)) using the Affymetrix® DMET™ Plus genotyping platform [2]. The NAT2 haplotype pairs were then determined by these SNPs via DMET Console 1.0 [2]. According to the Consensus Human Arylamine N-Acetyltransferase Gene Nomenclature [3], the phenotype of NAT2 in HapMap samples was determined based on the haplotype. The genotype calls for tagSNP, rs1495741, was retrieved from the HAPMAP database release#28. Percent of agreement (concordance) and kappa statistics (percent of agreement above and beyond chance alone) were calculated for the genotype of rs1495741, 2-SNP (rs1041983 and rs1801280) and NAT2 haplotype predicted phenotype. Kappa=0.81 was considered as cutoff to evaluate rs1495741 and 2-SNP panel in this study. The value of area under the curve (AUC) for the receiver operating characteristic (ROC) curve was measured using SPSS Statistics software, version 12.0 (SPSS Inc., Chicago, Illinois, USA). P

Expression of many liver-specific genes is extinguished when cultured hepatoma cells are fused with fibroblasts, but liver genes can be reexpressed in hybrid segregants that have lost fibroblast chromosomes. To map extinguisher loci involved in this process, hepatoma microcell hybrids retaining single fibroblast chromosomes have been employed. Two different, transdominant loci that affect liver gene expression have been defined in this way. To determine whether other monochromosomal extinction phenotypes could be observed, we inserted a selectable marker into many human chromosomal sites and transferred the marked human chromosomes into rat hepatoma recipient cells by microcell fusion. Nearly 200 microcell hybrid clones were isolated and screened for expression of liver-specific mRNAs. Most liver transcripts continued to be expressed. However, PEPCK mRNA was extinguished in 12 hybrid clones. Some of these hybrids contained human TSE1, the previously characterized extinguisher locus on chromosome 17, but others contained a novel extinguishing function that mapped to human chromosome 14. The implications of these findings are discussed.

Human genes expressed in interspecific somatic cell hybrids can be cloned specifically by subtractive cDNA hybridization. This approach is based on the observation that cDNA fragments from noncoding segments of mature human transcripts do not form stable heteroduplexes with their rodent homologues under high-stringency hybridization conditions. Thus, small, oligo-dT primed cDNAs from a rat/human hybrid retaining a fragment of human chromosome 17 were enriched for human sequences by hybridization with RNA from a sister clone containing a smaller human chromosome fragment. The enriched probe was used to screen a human cDNA library, and nine expressed genes from within the non-overlap region were obtained. This method should be useful for cloning active human genes from defined chromosome segments.

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.

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.

International audience; 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.

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 1–3 .W e 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 4,5 . 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’. The use of LD-based mapping strategies makes it practical to perform whole-genome association studies without typing every common variant in the human genome 6,7 . It has been suggested that the power of such studies is increased in isolated populations, and this has been demonstrated for rare alleles 8 . However, it remains unclear whether LD among common alleles in isolated populations extends significantly farther than in other populations—far enough to have impact for studies that seek to identify alleles contributing to common complex traits 9‐11 . Thus, although LD has been observed around rare alleles (such as disease genes) in isolated populations, facilitating disease gene mapping and cloning, this finding has not been extended to the common alleles and haplotypes that are the focus of the HapMap project. Even among isolated populations, variation in demographic history has powerful consequences for LD structure around rare alleles 3,12,13 , necessitating an evaluation of each population to assess the power of an LD-based mapping strategy. Thus, with the intense worldwide effort to generate a haplotype map for the general population, it is important to establish the utility of marker sets developed using samples from the HapMap project for use in other populations. We addressed these issues using samples from the island of Kosrae, Federated States of Micronesia 14 , which was settled by a small number of Micronesian founders B2,000 years ago 15 . In the current study, we generated a genome-wide high-density dataset of B110,000 SNPs to assess the effects of Kosraen population history on genomic variation in 30 Kosraen (KOS) trios. These same SNPs have been typed in the samples used in the HapMap project (see Methods). The 30 Kosraen trios were chosen such that all trios would be five or more generations separated from each other, which represents the most distant branches of the Kosrae pedigree. Thus, the individuals in these trios allow a fuller sampling of the range of diversity on Kosrae than if we had analyzed a random set of individuals. Comparing data on the same set of markers typed in samples included in the HapMap project permits examination of the relative extent of LD and haplotype diversity in Kosrae compared with these other populations.

BackgroundDNA 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.ResultsWe describe a novel algorithm called CARAT (Copy NumberAnalysis withRegressionAndTree) 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.ConclusionOverall, 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.

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.

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.

MicroRNAs (miRNAs) act as key post-transcriptional regulators of gene expression via binding to the 3’ untranslated regions (UTRs) of mRNAs. Single nucleotide polymorphisms (SNPs) found in the miRNA sequence and/or corresponding binding sites can affect the fidelity of this interaction, and evidence from candidate miRNA studies suggests that such SNPs may increase or decrease risk of tumor development. This study was designed to expand the search for miRNA-related polymorphisms important in cancer etiology across the genome and to investigate the association between thousands of genetic variants in miRNA target sites and colorectal cancer (CRC) risk using a novel genotyping platform, the Axiom® miRNA Target Site Genotyping Array (237,858 markers). The final study sample after quality control filtering included 605 cases and 615 controls from the Molecular Epidemiology of Colorectal Cancer (MECC) study, a population-based case-control study of incident CRC cases in a geographically-defined area of northern Israel. The marginal association between each marker with minor allele frequency >=1% and CRC risk was examined assuming a log-additive genetic model using logistic regression adjusted for sex, age, and the first two principal components (PC) to capture fine-scale population structure. There were 11 markers with p-values less than 3E-4, and the most statistically significant association involved rs12130051 (chr1:19545053; 3’-UTR of KIAA0090) with an OR of 2.24 (1.52,3.31) and p=4.48E-5. In addition, rs1051690 (chr5:142605172; 3’-UTR of ARHGAP26), was statistically significantly associated with decreased CRC risk (OR (95% CI): 0.71 (0.59, 0.85); p = 2.03E-4). Further, this study provided evidence for replication of a previously published locus, rs1051690 in the 3’UTR region of the insulin receptor gene, INSR (OR (95% CI): 1.27 (0.96,1.67); p = 0.09). A fixed-effects meta-analysis of sample-size weighted p-values from a recent publication in Carcinogenesis describing the INSR variant (Landi et al., 2012) and from the current MECC study yielded a combined p-value of 0.01. To our knowledge, this is the first study to examine the association between genetic variation in miRNA target sites and cancer risk using a genome-wide approach. Work is ongoing to replicate findings from this study and to characterize the functional impact of prioritized polymorphisms. Citation Format: Stephanie L. Stenzel, Jeremy Gollub, Michael Shapero, Andrea Finn, Gad Rennert, Stephen B. Gruber. MicroRNA target site polymorphisms and colorectal cancer risk in the Ashkenazi Jewish population. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2560. doi:10.1158/1538-7445.AM2013-2560

We have cloned human genes that are encoded in the region 17q12-q23 and expressed in breast tissue using interspecific somatic cell hybrids and subtractive hybridization. Two mouse microcell hybrids containing fragments of human chromosome 17 with a nonoverlap region at 17q12-q23 were generated by microcell transfer. Radiolabeled cDNA was synthesized from the hybrid cell containing the 17q12-q23 interval and was subtracted with an excess of RNA from the hybrid cell lacking the interval. Resulting cDNA probes enriched for sequences from 17q12-q23 were used to screen a human premenopausal breast cDNA library, and 60 cDNAs were identified. Three of these cDNAs mapped to the hybrid cell nonoverlap region. These cDNAs were expressed in mammary epithelial cell hybrids, although none appeared to be breast-specific. Sequence analysis of the cDNAs revealed that clone 93A represents a previously unidentified gene, clone 98C has homology to an expressed sequence tag from goat mammary tissue, and clone 200A is identical to the human homologue of the Drosophila melanogaster flightless-I gene. These genes map outside a 1-cM region linked to early onset familial breast cancer but may be useful genetic markers in the 17q12-q23 region. 47 refs., 6 figs.

A survey of exon sequence and structure requirements for splicing was undertaken using labeled pre-tRNA substrates prepared by in vitro transcription of bacterial promoter-yeast tRNA(Tyr) gene fusions. Transcription templates were assembled from oligonucleotide cassettes allowing analysis of 22 derivatives affecting each of the potential secondary and certain tertiary interactions in the pre-tRNA. Effects on both excision of the intervening sequence by yeast endonuclease and joining of exons by ligase were examined. Replacements within the D- and T-stems and anticodon stems revealed that while the primary sequences of these segments were not essential for splicing, formation of base-paired structures was required. Replacements which altered the primary sequence while retaining the secondary structure of the aminoacyl stem allowed efficient excision by endonuclease but reduced joining by ligase. Potentially, the effects of changes within these stems may be indirect through effects on adjacent or overall structure. The presence of either structured or unstructured 5' leader and/or 3' trailer sequences had no effect on either splicing step. Alterations in the conserved Levitt tertiary pair (G15/C48), previously implicated in splicing of pre-tRNA(Phe), did not alter splicing of pre-tRNA(Tyr). A precursor in which the small (type I) extra arm in pre-tRNA(Tyr) was replaced with the large (type II) extra arm sequence from tRNA(Ser) was efficiently spliced. These and previous results suggest that only limited features of exon sequence or structure are recognized by the splicing enzymes.

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.

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.