SNP array

In molecular biology, SNP array is a type of DNA microarray which is used to detect polymorphisms within a population. A single nucleotide polymorphism (SNP), a variation at a single site in DNA, is the most frequent type of variation in the genome. Currently, there are around 85 million SNPs that have been identified in the human genome.

The basic principles of SNP array are the same as the DNA microarray. These are the convergence of DNA hybridization, fluorescence microscopy, and solid surface DNA capture. The three mandatory components of the SNP arrays are:

The ASO probes are often chosen based on sequencing of a representative panel of individuals: positions found to vary in the panel at a specified frequency are used as the basis for probes. SNP chips are generally described by the number of SNP positions they assay. Two probes must be used for each SNP position to detect both alleles; if only one probe were used, experimental failure would be indistinguishable from homozygosity of the non-probed allele.

An SNP array is a useful tool for studying slight variations between whole genomes. The most important applications of SNP arrays are for determining disease susceptibility and for measuring the efficacy of drug therapies designed specifically for individuals. Each individual has many SNPs. SNP-based genetic linkage analysis can be used to map disease loci, and determine disease susceptibility genes in individuals. The combination of SNP maps and high density SNP arrays allows SNPs to be used as markers for genetic diseases that have complex traits. For example, whole-genome genetic linkage analysis shows linkage for diseases such as rheumatoid arthritis, prostate cancer, and neonatal diabetes. This information can help design drugs that act on a group of individuals who share a common allele - or even a single individual. A SNP array can also be used to generate a virtual karyotype using software to determine the copy number of each SNP on the array and then align the SNPs in chromosomal order.

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