Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “SNP Array”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6Linked to original sources
PubMed2026

The curious case of sporadic nematode susceptibility in "Tifguard" peanut (Arachis hypogaea): seed mixture or genetic instability?

The Runner-type peanut (Arachis hypogaea L.) cultivar "Tifguard" carries an introgressed chromosomal segment on chromosome A09 from A. cardenasii that confers resistance to root-knot nematode (RKN). Despite this, a proportion of "Tifguard" plants show RKN symptoms, which could plausibly be attributed to seed mixture or outcrossing. However, recent work has shown that cultivated peanut exhibits surprisingly frequent large-scale chromosomal instability (1% to 5%); suggesting that resistance loss could arise from spontaneous structural genomic change. To test these possibilities, we grew foundation seed in an RKN-infested field and collected symptomatic and asymptomatic plants. Lineages derived by single-seed descent were genotyped using the Axiom Arachis 48K SNP array v2 and whole-genome sequencing. Symptomatic lineages lacked the A. cardenasii introgression on chromosome A09 and instead carried the complete endogenous A. hypogaea A09 region at the expected dosage. There was no evidence of large-scale homoeologous exchange, deletion, or other genomic instability affecting this chromosome. Most susceptible plants were closely related to resistant "Tifguard" but lacked the A09 introgression, with a smaller proportion assignable to known nematode-susceptible cultivars, implicating seed mixture with a possible contribution from cross-pollination rather than genomic instability. Because resistance depends on a single major-effect segment, rare events have disproportionate phenotypic impact, placing high demands on genetic purity. For important traits conferred by major loci, marker-based testing across seed-increase stages could verify trait retention directly, and is increasingly practical as marker costs decline.

Arachis↗
PubMed2006

Evidence for a colorectal cancer susceptibility locus on chromosome 3q21-q24 from a high-density SNP genome-wide linkage scan.

To identify a novel susceptibility gene for colorectal cancer (CRC), we conducted a genome-wide linkage analysis of 69 pedigrees segregating colorectal neoplasia in which involvement of known loci had been excluded, using a high-density single nucleotide polymorphism (SNP) array containing 10,204 markers. Multipoint linkage analyses were undertaken using both non-parametric (model-free) and parametric (model-based) methods. After the removal of SNPs in strong linkage disequilibrium, we obtained a maximum non-parametric linkage statistic of 3.40 (P=0.0003) at chromosomal region 3q21-q24. The same genomic position also yielded the highest multipoint heterogeneity LOD (HLOD) score under a dominant model (HLOD=3.10, genome-wide P=0.038) with 62% of families linked to the locus. We provide evidence for a novel CRC susceptibility gene. Further studies are needed to confirm this localization and to evaluate the contribution of this locus to disease incidence.

Chromosome Mapping↗
PubMed2025

Accurate identification of abnormal ploidy using an artificial intelligence model in preimplantation genetic testing.

STUDY QUESTION: Can ultra-low-coverage whole-genome sequencing (ulc-WGS) accurately identify abnormal ploidy during preimplantation genetic testing (PGT)? SUMMARY ANSWER: The artificial intelligence (AI)-based PGT-Plus model demonstrates high accuracy in ploidy detection, offering a cost-effective solution that enhances clinical utility of PGT. WHAT IS KNOWN ALREADY: The predominant PGT for aneuploidy can identify chromosomal aneuploidies but cannot determine ploidy status. Transferring embryos with ploidy abnormalities can result in miscarriage and molar pregnancy. On the other hand, in ART, fertilization is assessed by morphological pronuclear assessment at the zygote stage. However, it has a low specificity in the prediction of abnormal ploidy status and embryos deemed abnormally fertilized can yield healthy pregnancies. Accurately identified abnormal ploidy in PGT-A can resolve current limitations and expand the utility range of PGT-A. Several studies have identified ploidy abnormalities; however, they were mainly based on single-nucleotide polymorphism (SNP) arrays or needed to combine additional targeted-next-generation sequencing (NGS) information. Studies based on ulc-WGS remain scarce. STUDY DESIGN SIZE DURATION: The study consisted of two stages: methodology establishment and validation. An AI model, named PGT-Plus, was developed using 653 samples with known ploidy status, which was further validated using 792 different ploidy status samples. In the clinical application stage, the approach was used to analyse the ploidy status of 19&#x2009;103 normally fertilized PGT blastocysts and 140 single pronucleus (1PN)-derived blastocysts collected between May 2022 and December 2023. All blastocysts were tested using trophectoderm biopsy and NGS. PARTICIPANTS/MATERIALS SETTING METHODS: The methodology is based on the ulc-WGS data. First, based on samples with known ploidy status: the heterozygosity rate of high-frequency biallelic SNPs, the likelihood ratio (LLR) of alleles was calculated under different assumptions ('both parental homologs' [BPH] from a single parent, 'single parental homolog' [SPH] from each parent, disomy, and monosomy) by leveraging allele frequencies and linkage disequilibrium (LD) measured in the 1000 genomes project database. Twenty-three continuous candidate features derived from heterozygosity rates and LLRs of chromosomes or selected windows were included to establish the ploidy prediction AI model. Gini importance analysis and multicollinearity mitigation was performed for feature selection, then the performance of Random Forest (RF), Support Vector Machine (SVM), and Logistic Regression for modelling was compared. Subsequently, the parameter optimization was performed based on the RF model. Ploidy constitution concordance was evaluated in known ploidy status samples. The frequency of abnormal ploidy in normal fertilized PGT blastocysts and 1PN-derived blastocysts (including conventional IVF and ICSI) was evaluated. MAIN RESULTS AND THE ROLE OF CHANCE: Eleven features were collected for model architecture compared to SVM and Logistic Regression; RF achieved superior performance for ploidy detection. The AI model achieved an AUC of 1 for genome-wide-uniparental diploidy (GW-UPD), 1 for triploidy, and 0.99 for diploidy. For the 792 validation samples, 99.5% of samples were successfully detected using the AI model, and the model showed 100% accuracy for ploidy classification. In the clinical application stage, out of 19&#x2009;103 PGT samples, 19&#x2009;069 were successfully analysed using the model, with 110 (0.57%) identified as having abnormal ploidy embryos. Among these, 12.7% (14/110) were identified as GW-UPD, and 87.3% (96/110) were triploid. Among 5563 diploid blastocysts transferred, 3478 clinical pregnancies were achieved. Subsequent ploidy analysis was performed for 217 spontaneous abortion and 935 prenatal diagnostic samples, and no abnormal ploidy was identified. Furthermore, of the 140 1PN embryos tested, 40 (28.6%) exhibited GW-UPD, 3 (2.1%) exhibited triploidy, and 97 (69.3%) were determined to be biparental and normally fertilized. Among the 97 biparental embryos, 46 were diploid, 11 were mosaic, and 40 were aneuploid. In terms of the insemination pattern, the percentage of abnormal ploidy in ICSI was significantly higher than in conventional IVF (P&#x2009;<&#x2009;0.01, 37.1% vs. 2.9%, respectively). With full informed consent, 20 patients without euploidy from normal fertilization chose 1PN-derived biparental and diploid blastocysts to transfer, resulting in 10 clinical pregnancies and 9 ongoing pregnancies. LARGE-SCALE DATA: N/A. LIMITATIONS REASONS FOR CAUTION: Some rare ploidy abnormalities, such as polyploidy with an equal number of identical sets of chromosomes and ploidy mosaicism cannot be accurately identified. Moreover, the origin of abnormal ploidy was not identified due to the unavailability of DNA from both parents. WIDER IMPLICATIONS OF THE FINDINGS: The PGT-Plus AI model provides a ploidy evaluation method based on the conventional PGT-A data and integrates directly into standard PGT-A workflows. Clinical utility results suggest that the model is a valuable tool for identifying embryos with abnormal ploidy in PGT-A and rescuing normal diploid embryos from abnormally fertilized embryos. These findings demonstrate that PGT-Plus significantly enhances the diagnostic accuracy of PGT. STUDY FUNDING/COMPETING INTERESTS: This study was supported by grants from Major Scientific Program of CITIC Group (No. 2023ZXKYB34100, to Ge.L.), Hunan Provincial Grant for Innovative Province Construction (2019SK4012), Hunan Xiangjiang New District (Changsha High-tech Zone) key core technology research project in 2023, and Science Foundation of Hunan Province (Grant 2023JJ30422). All authors declared no conflicts of interest..

artificial intelligence↗
PubMed2026

Scaling linear-model breeding values to the liability scale: an application to pig binary traits.

In commercial pig production, many important traits are recorded as binary phenotypes. For such traits, threshold models offer an appropriate framework but are computationally intensive. Thus, linear models are widely used to obtain genomic estimated breeding values (GEBV); however, these are on the observed scale (phenotypic). This creates the need for a robust method to approximate GEBV from linear models to the liability scale. A recently proposed approximation showed good concordance for low-prevalence traits (<5%) but has not yet been tested for a wider range of prevalence values and for models with more than one random effect. We aimed to evaluate the performance of this approximation for pig binary traits with prevalences ranging from <5% to >86%, in both animal and maternal animal models. Data were available for five fitness traits (FT1-FT5), with up to 233k animals with phenotypes, of which 204k animals were genotyped with a 25k SNP array. Variance component estimates were obtained using threshold models. Classical animal models were used for FT1-FT3, and maternal animal models for FT4 and FT5. Variance components on the observed scale were then obtained by multiplying estimates from a threshold model by the square of the height of the standard normal density evaluated at the threshold. GEBV were predicted using single-step genomic best linear unbiased prediction under both linear and threshold models. The approximation tested involved scaling the GEBV using the height of the ordinate of the standard normal distribution evaluated at the threshold as a scaling factor. The agreement between GEBV from the scaled linear model and the threshold model on the probability scale was evaluated using Pearson and Spearman correlations, mean squared error (MSE), regression parameters, overlapping coefficient (OVL), distribution overlap, and classification accuracy (CACC). Correlations between linear and threshold GEBV ranged from 0.94 (low-prevalence traits) to 0.99 (high-prevalence traits) for the direct GEBV and were 0.99 for the maternal GEBV. MSE were close to zero. The OVL exceeded 0.83 for all traits. CACC ranged from 95.10% to 98.33% for the direct GEBV and from 92.54% to 97.42% for the maternal GEBV. Regardless of model and trait prevalence, this approximation yielded GEBV that are highly consistent with threshold model GEBV, providing a reliable, practical approach for large-scale pig genetic evaluations for binary traits using linear models.

Animals↗
PubMed2026

Spectral Transforms as a Tool to Optimize Digital Phenotyping in Biological Images.

Modern livestock breeding has mastered genotyping. Genome-wide association studies, genomic selection, and SNP arrays enable genetic merit prediction at lower cost. However, phenotyping remains the bottleneck, as manual measurement is slow, expensive, subjective, and unable to capture spatial or temporal trait organization. Digital phenotyping via artificial intelligence could resolve this, but deep learning requires thousands of labelled examples, impractical when phenotyping cost itself limits datasets to hundreds of individuals. This creates a paradox: AI could accelerate phenotyping but requires large numbers of samples to train the models. Here, we demonstrate that integrating computer vision with machine learning offers sample-efficient digital phenotyping using eggshell colour as a model system. Rather than learning features from scratch (deep learning), we engineer physically motivated features via Wavelet transforms that decompose images into multi-scale spatial components. Wavelet features captured 14.2 percentage points more variance (R2&#x2009;=&#x2009;0.976 vs. 0.834, p&#x2009;<&#x2009;0.001) than standard colorimetry, with 50% better sample efficiency (achieving at n&#x2009;=&#x2009;60 what colorimetry required n&#x2009;=&#x2009;120). Variance decomposition revealed 77% of discriminative capacity derives from spatial patterns (bands, spots, gradients) invisible to scalar averages. Additionally, we identified "cryptic phenotypes" (3.3%) where spatial patterns contradicted average colour, cases where colorimeters failed but Wavelets succeeded. The underlying principle-that spatial decomposition can recover organizational information lost by scalar averaging-may be applicable to other traits with spatial or temporal structure, such as marbling, dermatitis, or pigmentation rhythms, although whether comparable performance gains would be observed remains to be tested empirically. Hence, for breeding programs implementing genomic selection, computer vision-based digital phenotyping captures complex trait variation without massive training datasets, addressing the bottleneck that increasingly limits genetic progress as genotyping becomes trivial.

Wavelet transform↗
PubMed2006

Toward universal varicella-zoster virus (VZV) genotyping: diversity of VZV strains from France and Spain.

Thirty-one isolates from France and Spain were genotyped using a published method analyzing DNA sequence variation in open reading frame (ORF) 22, together with an evaluation of three well-characterized single nucleotide polymorphisms (SNP) in ORF 38, 54, and 62. Nineteen were allocated to the European (E) genotype, six were mosaic-1 (M1), and two were mosaic-2 (M2). Four strains were assigned to a new genotype, mosaic-4 (M4). All isolates were wild type, with no Oka vaccine-associated markers. No isolates of the mosaic-3 (M3) or Japanese (J) genotype were observed. We also evaluated 13 selected isolates of E, J, M1, and M2 strains (9 of the 31 described above) using an alternative genotyping method based on the assessment of multiple SNP located in ORF 1, 9, 10, 21, 31, 50, 54, 62, and 68. This method assigns wild-type varicella-zoster virus (VZV) strains to seven genotypes: A1, A2, J1, B1, B2, C, and C1. VZV isolates identified as E (ORF22 method) had the genetic signature of genotype C VZV strains, M1 strains were A1, and M2 were A2. No J strains were detected, but parental Oka and vaccine Oka (genotype J) corresponded to genotype J1. M4 isolates (B) share the SNP array observed for M1 and E viruses, and probably represent recombinants between African-Asian (M1) and European (E) viruses. The two genotyping methods, using entirely different genomic targets, produced identical clusters for the strains examined, suggesting robust phylogenetic linkages among VZV strains circulating in Europe.

Adult↗
PubMed2005

Loss of heterozygosity in childhood acute lymphoblastic leukemia detected by genome-wide microarray single nucleotide polymorphism analysis.

Loss of heterozygosity (LOH) is detectable in many forms of malignancy, including leukemia, using techniques such as microsatellite analysis and comparative genomic hybridization. However, these techniques are laborious and require the use of relatively large amounts of DNA if the whole genome is to be examined. Here we describe the use of oligonucleotide microarrays to characterize single nucleotide polymorphisms (SNPs) in lymphoblasts isolated from children with acute lymphoblastic leukemia for the pan-genomic mapping of LOH with a resolution of 100 to 200 kb. Results were compared with DNA obtained during remission and on relapse. Abnormalities were seen in 8 of 10 cases. The two cases with no abnormalities and one case that showed identical changes at relapse and presentation remain in remission 1 to 9 years following retreatment. The remaining seven patients died following relapse. In four cases, LOH was only detectable at relapse suggesting that progressive LOH may be a cause of disease progression and/or drug resistance. This was supported by detailed analysis of one case in which LOH involving the glucocorticoid receptor was associated with mutation of the remaining allele. The most frequent abnormality detected involved chromosome 9p. In each of the four cases where this was observed LOH included the INK4 locus. In three of the four cases, INK4 loss was only observed at relapse, suggesting that this abnormality may be commonly associated with treatment failure. These observations show that SNP array analysis is a powerful new tool for the analysis of allelic imbalance in leukemic blasts.

Child↗
PubMed2026

Identification and fine mapping of a locus controlling multi-main-stem trait in Brassica napus.

BACKGROUND: The main stem is a crucial component determining individual plant yield in rapeseed (Brassica napus). However, the genetic and developmental basis underlying the multi-main-stem trait remains largely unclear. RESULTS: In this study, we identified a multi-main-stem mutant, mms1, which exhibited a significantly increased silique number per plant and abnormal shoot apical meristem (SAM) development. Genetic analysis demonstrated that the multi-main-stem trait was controlled by a recessive gene. Using bulked segregant analysis combined with a Brassica napus 50&#xa0;K SNP array and map-based cloning, the locus was mapped to a 340-kb interval on chromosome A09 of the ZS11 reference genome and was designated BnaA09.MMS1. Candidate gene analysis revealed that BnaA09G0254500ZS, which harbors sequence variations in both the promoter and coding regions and shows significantly increased expression in the mutant, was the most likely candidate gene. In addition, phytohormone analysis revealed reduced auxin accumulation in mutant SAMs, together with transcriptomic changes in genes associated with the CLAVATA3 (CLV3)-WUSCHEL (WUS) feedback loop. CONCLUSIONS: These findings provide an important foundation for elucidating the genetic basis of the multi-main-stem trait and offer a valuable genetic resource for rapeseed improvement.

Brassica napus↗
PubMed2026

Beckwith-Wiedemann spectrum exhibiting a 46,XY karyotype caused by genome-wide paternal uniparental heterodisomy: a case report.

BACKGROUNDS: Patients with genome-wide paternal uniparental disomy (GWpUPD) usually exhibit clinical features of Beckwith-Wiedemann syndrome (BWS) and a 46,XX karyotype, with all chromosomes showing isodisomy. To date, male patients with GWpUPD and a complete 46,XY karyotype, specifically involving heterodisomy, have not been described. RESULTS: We report a male infant exhibiting classical BWS clinical features. DNA methylation analyses showed paternal-specific methylation across multiple imprinted loci, suggesting GWpUPD. Genetic analysis of autosomes and sex chromosomes indicated two distinct paternal genomes in peripheral blood leukocytes, whereas a normal biparental genome was detected in other tissues under chimeric conditions. These findings indicated that the patient had genome-wide paternal uniparental heterodisomy (GWpUPhD). The SNP array revealed the presence of one copy of the X chromosome and one copy of the Y chromosome, the patient is a chimera composed of 46,XY biparental cells (with maternal X) and 46,XY GWpUPhD cells (with paternal X). CONCLUSIONS: This is the first report of a male patient with a GWpUPhD chimera. We propose a potential mechanism of GWpUPhD formation. Our findings expand the molecular spectrum of GWpUPD and provide valuable insights into its pathogenesis in chimeric conditions. Furthermore, the potential for clinical manifestations unique to 46,XY heterodisomy warrants careful long-term follow-up.

Humans↗
PubMed2005

The Autism Genome Project: goals and strategies.

Autism is a complex neurodevelopmental disorder with a broad spectrum of symptoms and varying severity. Currently, no biological diagnosis exists. Although there has been a significant increase in autism genetics research recently, validated susceptibility genes for the most common, sporadic forms of autistic disorder, as well as familial autism, have yet to be identified. The identification of autism-susceptibility genes will not only assist in the identification and/or development of better medications that can help improve the health and neurodevelopment of children with autism, but will also allow for better perinatal diagnosis. The Autism Genome Project (AGP) is a large-scale, collaborative genetics research project initiated by the National Alliance for Autism Research and the National Institutes of Health, and is aimed at sifting through the human genome in search of autism-susceptibility genes. Phase I of the AGP will consist of genome-wide scans utilizing both SNP array and microsatellite technologies. Linkage analysis will subsequently be performed on approximately 1500 pedigrees as will downstream fine-mapping and sequencing of the critical linkage intervals. Ultimately, the vision will be to identify the exact nucleotide variants within genes which give rise to predisposition. The AGP intends to move the field of autism clinical management forward by answering questions about the causal mechanisms underlying the pathophysiology of autism. From this knowledge, therapeutic targets for drug treatments, and ultimately, a newborn screening diagnostic that would allow for early intervention, can begin to be developed.

Autistic Disorder↗
PubMed2006

High-resolution analysis of 9p loss in human cancer cells using single nucleotide polymorphism-based mapping arrays.

Single nucleotide polymorphism (SNP) mapping arrays were used to perform DNA copy number analysis of five human cancer cell lines (four malignant mesotheliomas; one non-small cell lung carcinoma) to identify and map the end-points of deletions of 9p. All five cell lines exhibited homozygous deletions encompassing the CDKN2A (alias INK4A/ARF) and CDKN2B loci. The DNA analysis profiles demarcated precisely two different, but overlapping, deletions in each mesothelioma cell line, but the lung cancer cells showed two copies of a single deletion. In the latter cell line, allele analysis revealed that virtually all SNPs for chromosome 9 were homozygous, suggestive of uniparental disomy. These findings demonstrate the utility of SNP-based mapping arrays for high-resolution analysis of genomic imbalances in cancer cells.

Cell Line, Tumor↗
PubMed2005

Universal tag arrays in forensic SNP analysis.

Microarray-based single nucleotide polymorphism (SNP) genotyping enables simultaneous and rapid detection of a large number of markers and is thus an attractive method for forensic individual acid identification. This assay relies on a one-color detection system and minisequencing in solution before hybridization to universal tag arrays. The minisequencing reaction is based on incorporation of a fluorescent dideoxynucleotide to a primer containing a tag-sequence flanking the position to be interrogated. This one-color system detects C and T polymorphisms in separate reactions on multiple polymerase chain reaction targets with the fluorophore TAMRA coupled to the respective dideoxynucleotide. After incorporation, tagged primer sequences are hybridized through their complementary sequence on the array, and positive signals are detected by a confocal laser-scanner.

Base Sequence↗
PubMed2003

Comparison of GenFlex Tag array and Pyrosequencing in SNP genotyping.

With the completion of the Human Genome Project, over 2 million sequence-verified single nucleotide polymorphisms (SNPs) have been deposited in public databases. The challenge has shifted from SNP identification to high-throughput SNP genotyping. Although this has had little impact on molecular diagnostics, it provides the potential for future molecular diagnostics of complex traits to include SNP profiling. Accordingly, efficient, accurate, and flexible SNP genotyping are needed. In addition, the drive for low cost has pushed genotyping reactions toward multiplexing capability. We compared two SNP genotyping techniques: Affymetrix GenFlex Tag array and Pyrosequencing. The reference method was a well-established, solid-phase, single nucleotide extension reaction technique based on tritium detection. Fourteen SNPs were selected from the fine mapping project of a multiple sclerosis locus on chromosome 17q. Using all three techniques and the reference method, the SNPs were analyzed in 96 related individuals. Without extensive optimization, we successfully genotyped 11 of 14 SNPs with both GenFlex and Pyrosequencing. Our study suggests that the Pyrosequencing technique provides higher accuracy between the two systems which is most likely due to the single-stranded template in the extension reaction. Thus, Pyrosequencing has potential for diagnostic applications. Pyrosequencing, however, is not optimal for large SNP profiling analyses wherein multiplexing potential is an advantage.

Alleles↗
PubMed2006

Genome-wide allelic imbalance analysis of pediatric gliomas by single nucleotide polymorphic allele array.

Using single nucleotide polymorphic (SNP) allele arrays, we analyzed 28 pediatric gliomas consisting of 14 high-grade gliomas and 14 low-grade gliomas. Most of the low-grade gliomas had no detectable loss of heterozygosity (LOH) in any of the 11,562 SNP loci; exceptions were two gangliogliomas (3q and 9p), one astrocytoma (6q), and two subependymal giant cell astrocytomas (16p and 21q). On the other hand, all high-grade gliomas had various degrees of LOH affecting 52 to 2,168 SNP loci on various chromosomes. LOH occurred most frequently in regions located at 4q (54%), 6q (46%), 9p (38%), 10q (38%), 11p (38%), 12 (38%), 13q (69%), 14q (54%), 17 (38%), 18p (46%), and 19q (38%). We also detected amplifications of epidermal growth factor receptor (EGFR) or platelet-derived growth factor receptor alpha (PDGFRalpha) in a few of the 13 cases of glioblastoma multiforme analyzed. Interestingly, the amplified EGFR and PDGFRalpha were located within regions of LOH. SNP loci with LOH and copy number changes were validated by sequencing and quantitative PCR, respectively. Our results indicate that, in some pediatric glioblastoma multiforme, one allele each of EGFR and PDGFRalpha was lost but the remaining allele was amplified. This may represent a new molecular mechanism underlying tumor progression.

Alleles↗
PubMed2005

Allelic imbalance analysis of oral tongue squamous cell carcinoma by high-density single nucleotide polymorphism arrays using whole-genome amplified DNA.

Multiple displacement-based whole-genome DNA amplification is a promising tool to obtain sufficient DNA from small tissue specimens for various genetic analyses, such as SNP array-based analysis. Using Affymetrix 10 K and 100 K SNP mapping array, we evaluated the performance of the Phi29 DNA polymerase-based genome amplification. Greater than 99% concordance in genotyping calls were achieved between amplified and non-amplified DNAs for both arrays. By utilizing the Affymetrix GeneChip Chromosome Copy Number Tool, the allelic imbalance profiles for the advanced stage oral tongue squamous cell carcinoma (OTSCC) were generated based on 10 K and 100 K SNP mapping array results. The results from these two array platforms agree closely, but more precise allelic imbalance patterns can be revealed from the 100 K SNP mapping array data. Furthermore, our data suggested a frequent loss at 3p11-p12 for advanced stage OTSCC.

Allelic Imbalance↗
PubMed2005

High-throughput SNP genotyping on universal bead arrays.

We have developed a flexible, accurate and highly multiplexed SNP genotyping assay for high-throughput genetic analysis of large populations on a bead array platform. The novel genotyping system combines high assay conversion rate and data quality with >1500 multiplexing, and Array of Arrays formats. Genotyping assay oligos corresponding to specific SNP sequences are each linked to a unique sequence (address) that can hybridize to its complementary strand on universal arrays. The arrays are made of beads located in microwells of optical fiber bundles (Sentrix Array Matrix) or silicon slides (Sentrix BeadChip). The optical fiber bundles are further organized into a matrix that matches a 96-well microtiter plate. The arrays on the silicon slides are multi-channel pipette compatible for loading multiple samples onto a single silicon slide. These formats allow many samples to be processed in parallel. This genotyping system enables investigators to generate approximately 300,000 genotypes per day with minimal equipment requirements and greater than 1.6 million genotypes per day in a robotics-assisted process. With a streamlined and comprehensive assay, this system brings a new level of flexibility, throughput, and affordability to genetic research.

DNA Methylation↗
PubMed2006

Integration of global SNP-based mapping and expression arrays reveals key regions, mechanisms, and genes important in the pathogenesis of multiple myeloma.

Multiple myeloma is characterized by genomic alterations frequently involving gains and losses of chromosomes. Single nucleotide polymorphism (SNP)-based mapping arrays allow the identification of copy number changes at the sub-megabase level and the identification of loss of heterozygosity (LOH) due to monosomy and uniparental disomy (UPD). We have found that SNP-based mapping array data and fluorescence in situ hybridization (FISH) copy number data correlated well, making the technique robust as a tool to investigate myeloma genomics. The most frequently identified alterations are located at 1p, 1q, 6q, 8p, 13, and 16q. LOH is found in these large regions and also in smaller regions throughout the genome with a median size of 1 Mb. We have identified that UPD is prevalent in myeloma and occurs through a number of mechanisms including mitotic nondisjunction and mitotic recombination. For the first time in myeloma, integration of mapping and expression data has allowed us to reduce the complexity of standard gene expression data and identify candidate genes important in both the transition from normal to monoclonal gammopathy of unknown significance (MGUS) to myeloma and in different subgroups within myeloma. We have documented these genes, providing a focus for further studies to identify and characterize those that are key in the pathogenesis of myeloma.

Bone Marrow↗