Single Nucleotide Polymorphisms (SNPs) represent a natural genetic variability at high density in the human genome. A synonymous expression is ¨biallelic marker¨ corresponding to the two alleles that may differ in a given nucleotide position in a diploid cell. A SNP represents an alternate nucleotide in a given and defined genetic location at a frequency exceeding 1 % in a given population. This definition does not include other types of genetic variability like insertions and deletions, and variability in copy number of repeated sequences. SNPs are considered to be the major genetic source to phenotypic variability that differentiate individuals within a given species.

SNPs may occur in non-coding regions (SNPs) as well as in coding regions (cSNPs). cSNPs often generate polymorphic variants of expressed proteins that sometimes affect their functional properties. Since SNPs are bi-allelic they are not as informative as, for example, microsalites which can have many alleles and may be associated with rare diseases.

單核苷酸多態(tài)性[SNP，Single Nucleotide Polymorphisms]The allelic frequencies of a given SNP may vary in different populations. On average, an SNP is believed to be present in every 300 to 1000 bases in man. Thus there may be several million nucleotide positions in the human genome at which there is some degree of natural variation.

How can SNP"s be used for identifying disease related GENEs?

SNPs have properties and a density in the human genome that makes them attractive as markers or tools for identification of genes in as yet uncharacterised parts of the genome that may have some relation to a specific disease. There are great expectations that SNPs will be useful in identifying candidate genes that contribute to population-wide, polygenic diseases.
At present several initiatives are ongoing to exploit the information contents of genetic variability. Their purpose is to

· identify genes that contribute to disease
· identify gene targets for development of new therapeutic principles
· identify genes that may predict outcome from therapy

The exploitation of SNPs is likely to proceed in several phases.

In the first phase a sufficiently dense map of SNPs will be created which will eventually cover the entire genome. The physical location of SNPs will be determined in a similar way to micro-salite markers. SNPs will, at least initially, be selected based on how informative they might be as genetic markers. SNPs in low proportions (<10 %) will be less informative than SNPs at higher frequency (30-50 %) in a given population.

In a second phase, the relative frequencies of SNPs covering a large portion of the human genome will be correlated to specific diseases by comparing allelic frequencies in healthy and diseased populations. This information will focus further analysis to a smaller part of the genome thus continuously increasing the resolution of useful SNPs.

In a third phase genetic variability will be studied in more detail utilising SNPs. Typically, a limited number of genes (10-100) which link with specific diseases will be investigated for genetic variability. In this phase genetic variability present at a lower frequency is likely to be more informative. Genes contributing to disease are expected to be identified in an iterative process. The majority of SNPs are likely to be located in non-coding regions (SNP) but SNPs located in the coding regions (cSNP) will also be detected. The identification of SNPs located in coding regions of genes (cSNPs) will be particularly important since they may represent a genotype/phenotype relationship in specific diseases.