The creation of single-nucleotide polymorphism (SNP) databases (such as NCBI dbSNP) has facilitated scientific research in many fields. SNP discovery and detection has improved to the extent that there are over 17 million human reference (rs) SNPs reported to date (Build 129 of dbSNP). SNP databases are unfortunately not always complete and/or accurate. In fact, half of the reported SNPs are still only candidate SNPs and are not validated in a population.
We describe the identification of SNDs (Single Nucleotide Differences) in humans, that may contaminate the dbSNP database. These SNDs, reported as real SNPs in the database, do not exist as such, but are merely artifacts due to the presence of a paralogue (highly similar duplicated) sequence in the genome. Using sequencing we showed how SNDs could originate in two paralogous genes and evaluated samples from a population of 100 individuals for the presence/absence of SNPs. Moreover using bioinformatics, we predicted as many as 8.32% of the biallelic, coding SNPs in the dbSNP database to be SNDs.
Our identification of SNDs in the database will allow researchers to not only select truly informative SNPs for association studies, but also aid in determining accurate SNP genotypes and haplotypes.