Computational Tools to Detect Single Nucleotide Polymorphism (SNP) in Nucleotide Sequences: A Review

European Journal of Bioinformatics Vol. 2, 2015, 1-8

Satpathy Raghunath, Behera Rashmiranjan




Single nucleotide polymorphisms (SNPs) are basically single base pair alterations present in the genomic DNA. SNPs is usually treated as one of the most common genetic markers in case of plants, animals as well as the human genome to study the complex genetic traits and evolutionary status of the genome. SNPs are widely used as popular markers due to their continuous presence in the genome, highly reproducible, relatively easy to score. In addition to this, SNPs in coding sequences are used to directly examine the genetics of expressing genes and to study various polymorphic functional traits. Specifically the non-synonymous SNPs are more attractive because they alter the amino acid that ultimately affecting the protein functions. The direct application of SNP exists with pharmacogenomics study and crop improvement.  Various strategies have been used for SNP discovery that comes from both observational and computational techniques. SNPs can be detected by laboratory based experimental methods, which are time consuming and expensive also the development costs are high. The implementations of Bioinformatics approach reduce the development cost of SNPs as it uses publicly available sequences from databases like expressed sequence tags (ESTS) that cause the development of SNP markers rapid and less expensive.

Keywords   Single nucleotide polymorphism, computational methods, genome evolution, genetic traits, sequence analysis