Abstract
Single nucleotide polymorphism (SNP) detection technologies are used to scan for new polymorphisms and to determine the allele(s) of a known polymorphism in target sequences. SNP detection technologies have evolved from labor intensive, time consuming, and expensive processes to some of the most highly automated, efficient, and relatively inexpensive methods. Driven by the Human Genome Project, these technologies are now maturing and robust strategies are found in both SNP discovery and genotyping areas. The nearly completed human genome sequence provides the reference against which all other sequencing data can be compared. Global SNP discovery is therefore only limited by the amount of funding available for the activity. Local, target, SNP discovery relies mostly on direct DNA sequencing or on denaturing high performance liquid chromatography (dHPLC). The number of SNP genotyping methods has exploded in recent years and many robust methods are currently available. The demand for SNP genotyping is great, however, and no one method is able to meet the needs of all studies using SNPs. Despite the considerable gains over the last decade, new approaches must be developed to lower the cost and increase the speed of SNP detection.
Highlights
When any two human genomes are compared side by side, they are 99.9% identical (Cooper et al, 1985)
While the majority of the Single nucleotide polymorphism (SNP) are of no biological consequence, a fraction of the substitutions have functional significance and are the basis for the diversity found among humans (Collins et al, 1997)
SNP detection technologies have evolved from a laborintensive, painstaking endeavor involving numerous steps to a highly paralleled, automated process
Summary
When any two human genomes are compared side by side, they are 99.9% identical (Cooper et al, 1985). The advantages of this method are that it detects 100% of the mismatches in relatively large DNA fragments (up to several kb) and yields positional information of the polymorphic site.
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