Flexible use of high-density oligonucleotide arrays for single-nucleotide polymorphism discovery and validation.

Affymetrix, Inc., Santa Clara, California 95051, USA.
Genome Research (Impact Factor: 14.4). 09/2001; 11(8):1418-24. DOI: 10.1101/gr.171101
Source: PubMed

ABSTRACT A method for identifying and validating single nucleotide polymorphisms (SNPs) with high-density oligonucleotide arrays without the need for locus-specific polymerase chain reactions (PCR) is described in this report. Genomic DNAs were divided into subsets with complexity of ~10 Mb by restriction enzyme digestion and gel-based fragment size resolution, ligated to a common adaptor, and amplified with one primer in a single PCR reaction. As a demonstration of this approach, a total of 124 SNPs were located in 190 kb of genomic sequences distributed across the entire human genome by hybridizing to high-density variant detection arrays (VDA). A set of independent validation experiments was conducted for these SNPs employing bead-based affinity selection followed by hybridization of the affinity-selected SNP-containing fragments to the same VDA that was used to identify the SNPs. A total of 98.7% (74/75) of these SNPs were confirmed using both DNA dideoxynucleotide sequencing and the VDA methodologies. With flexible sample preparation, high-density oligonucleotide arrays can be tailored for even larger scale genome-wide SNP discovery as well as validation.

  • Studies in Surface Science and Catalysis - STUD SURF SCI CATAL. 01/2000; 130:2777-2782.
  • [Show abstract] [Hide abstract]
    ABSTRACT: Introduction DNA microarray is a powerful technology which can rapidly provide a high throughput and detailed view of the entire genome and transcriptome. In this review we discuss the basic principles behind gene expression microarrays, CGH arrays and DNA microarray genotyping, and their potential applications to neurological diseases. State of the art Microarray gene expression profiling is a reliable technology that has already been used with great success in the molecular classification of cancer. It is a very promising technology in the field of Neurooncology. One of the interesting characteristics of DNA microarrays is also that they can be used in a non-hypothesis-driven manner to discover new genomic characteristics that will enable to establish new pathophysiological hypotheses. Such a strategy has already yielded interesting new insights in the study of multiple sclerosis, Alzheimer disease or neuromuscular diseases. With DNA microarray genotyping it is now possible to detect mutations in many genes simultaneously. Conclusions In Neurooncology DNA microarrays should help to establish a more accurate classification of brain tumors and recent studies have shown how gene expression profiling of brain tumors allows to uncover previously unrecognized patient subsets that differ in their survival. The applications of microarrays for the study of neurological diseases, like multiple sclerosis, Alzheimer disease or neuromuscular diseases are also promising both for generating new pathophysiological hypotheses and for enabling new molecular classifications. DNA microarray genotyping is a powerful technology that should help to discover genetic factors associated with multifactorial neurological disorders and help to diagnose complex neurogenetic diseases. This technology should also facilitate the realization of pharmacogenomic studies in neurological diseases.
    Revue Neurologique - REV NEUROL. 01/2007; 163(4):409-420.
  • [Show abstract] [Hide abstract]
    ABSTRACT: across large numbers of individuals 1 . Public efforts have so far identified over two million common human SNPs 2 ; however, the scoring of these SNPs is labor-intensive and requires a substantial amount of automation. Here we describe a simple but effective approach, termed whole- genome sampling analysis (WGSA), for genotyping thousands of SNPs simultaneously in a complex DNA sample without locus-specific primers or automation. Our method amplifies highly reproducible fractions of the genome across multiple DNA samples and calls genotypes at >99% accuracy. We rapidly genotyped 14,548 SNPs in three different human populations and identified a subset of them with significant allele frequency differences between groups. We also determined the ancestral allele for 8,386 SNPs by genotyping chimpanzee and gorilla DNA. WGSA is highly scaleable and enables the creation of ultrahigh density SNP maps for use in genetic studies.