A Single Nucleotide Polymorphism (SNP, pronounced snip; plural snips) is a DNA sequence variation occurring commonly within a population (e.g. 1%) in which a single nucleotide — A, T, C or G — in the genome (or other shared sequence) differs between members of a biological species or paired chromosomes. For example, two sequenced DNA fragments from different individuals, AAGCCTA to AAGCTTA, contain a difference in a single nucleotide. In this case we say that there are two alleles. Almost all common SNPs have only two alleles. The genomic distribution of SNPs is not homogenous; SNPs occur in non-coding regions more frequently than in coding regions or, in general, where natural selection is acting and 'fixing' the allele (eliminating other variants) of the SNP that constitutes the most favorable genetic adaptation. Other factors, like genetic recombination and mutation rate, can also determine SNP density.
SNP density can be predicted by the presence of microsatellites: AT microsatellites in particular are potent predictors of SNP density, with long (AT)(n) repeat tracts tending to be found in regions of significantly reduced SNP density and low GC content.
Within a population, SNPs can be assigned a minor allele frequency — the lowest allele frequency at a locus that is observed in a particular population. This is simply the lesser of the two allele frequencies for single-nucleotide polymorphisms. There are variations between human populations, so a SNP allele that is common in one geographical or ethnic group may be much rarer in another.
These genetic variations between individuals (particularly in non-coding parts of the genome) are sometimes exploited in DNA fingerprinting, which is used in forensic science. Also, these genetic variations underlie differences in our susceptibility to disease. The severity of illness and the way our body responds to treatments are also manifestations of genetic variations. For example, a single base mutation in the APOE (apolipoprotein E) gene is associated with a higher risk for Alzheimer disease.
|Types of SNPs|
Single-nucleotide polymorphisms may fall within coding sequences of genes, non-coding regions of genes, or in the intergenic regions (regions between genes). SNPs within a coding sequence do not necessarily change the amino acid sequence of the protein that is produced, due to degeneracy of the genetic code.
SNPs in the coding region are of two types, synonymous and nonsynonymous SNPs. Synonymous SNPs do not affect the protein sequence while nonsynonymous SNPs change the amino acid sequence of protein. The nonsynonymous SNPs are of two types: missense and nonsense.
SNPs that are not in protein-coding regions may still affect gene splicing, transcription factor binding, messenger RNA degradation, or the sequence of non-coding RNA. Gene expression affected by this type of SNP is referred to as an eSNP (expression SNP) and may be upstream or downstream from the gene.
Use and importance
Variations in the DNA sequences of humans can affect how humans develop diseases and respond to pathogens, chemicals, drugs, vaccines, and other agents. SNPs are also critical for personalized medicine. However, their greatest importance in biomedical research is for comparing regions of the genome between cohorts (such as with matched cohorts with and without a disease) in genome-wide association studies.
SNPs are usually biallelic and thus easily assayed. A single SNP may cause a Mendelian disease. For complex diseases, SNPs do not usually function individually, rather, they work in coordination with other SNPs to manifest a disease condition as has been seen in Osteoporosis.
SNPs have been used in genome-wide association studies (GWAS), e.g. as high-resolution markers in gene mapping related to diseases or normal traits. The knowledge of SNPs will help in understanding pharmacokinetics (PK) or pharmacodynamics, i.e. how drugs act in individuals with different genetic variants. A wide range of human diseases, e.g. Sickle–cell anemia, β Thalassemia and Cystic fibrosis result from SNPs. Diseases with different SNPs may become relevant pharmacogenomic targets for drug therapy. Some SNPs are associated with the metabolism of different drugs.
SNPs without an observable impact on the phenotype (so called silent mutations) are still useful as genetic markers in genome-wide association studies, because of their quantity and the stable inheritance over generations.
On the other site, all types of SNPs can have observable phenotype or can result in disease:
- SNPs in non-coding regions can manifest in higher risk of cancer
- SNPs in coding regions:
- synonymous substitutions by the definition do not trigger amino acid change in the protein, but still can affect its function e.g. seemingly silent mutation in the multidrug resistance gene 1 (MDR1), which codes for a cellular membrane pump that expels drugs from the cell, can slow down translation to allow the peptide chain to fold into an unusual conformation causing the mutant pump be less functional
- nonsynonymous substitutions:
- missense - single change in the base results in change in amino acid of protein and its malfunction which leads to disease (e.g. c.1580G>T SNP in LMNA gene - position 1580 (nt) in the DNA sequence (CGT codon) causing the guanine to be replaced with the thymine, yielding CTT codon in the DNA sequence, results at the protein level in the replacement of the arginine by the leucine in the position 527, at phenotype level this manifest with overlapping mandibuloacral dysplasia and progeria syndrome)
- nonsense - point mutation in a sequence of DNA that results in a premature stop codon, or a nonsense codon in the transcribed mRNA, and in a truncated, incomplete, and usually nonfunctional protein product (e.g. Cystic fibrosis caused by the G542X mutation in the cystic fibrosis transmembrane conductance regulator gene).
- rs6311 and rs6313 are SNPs in the HTR2A gene on human chromosome 13.
- A SNP in the F5 gene causes a hypercoagulability disorder with the variant Factor V Leiden.
- rs3091244 is an example of a triallelic SNP in the CRP gene on human chromosome 1.
- TAS2R38 codes for PTC tasting ability, and contains 6 annotated SNPs.
- rs148649884 and rs138055828 in the FCN1 gene encoding M-ficolin crippled the ligand-binding capability of the recombinant M-ficolin.
As there are for genes, bioinformatics databases exist for SNPs. dbSNP is a SNP database from the National Center for Biotechnology Information (NCBI). Kaviar is a compendium of SNPs from multiple data sources including dbSNP. SNPedia is a wiki-style database supporting personal genome annotation, interpretation and analysis. The OMIM database describes the association between polymorphisms and diseases (e.g., gives diseases in text form), the Human Gene Mutation Database provides gene mutations causing or associated with human inherited diseases and functional SNPs, and GWAS Central allows users to visually interrogate the actual summary-level association data in one or more genome-wide association studies. The International SNP Map working group mapped the sequence flanking each SNP by alignment to the genomic sequence of large-insert clones in Genebank. These alignments were converted to chromosomal coordinates that is shown in Table 1. Another database is the International HapMap Project, where researchers are identifying Tag SNP to be able to determine the collection of haplotypes present in each subject.
|Chromosome||Length(bp)||All SNPs||TSC SNPs|
|SNPs||kb per SNP||SNPs||kb per SNP|
The nomenclature for SNPs can be confusing: several variations can exist for an individual SNP and consensus has not yet been achieved. One approach is to write SNPs with a prefix, period and "greater than" sign showing the wild-type and altered nucleotide or amino acid; for example, c.76A>T. SNPs are frequently referred to by their dbSNP rs number, as in the examples above.
Analytical methods to discover novel SNPs and detect known SNPs include:
- PLINK (module)
Programs for prediction of SNP effects
An important group of SNPs are those that corresponds to missense mutations causing amino acid change on protein level. Point mutation of particular residue can have different effect on protein function (from no effect to complete disruption its function). Usually, change in amino acids with similar size and physico-chemical properties (e.g. substitution from leucine to valine) has mild effect, and opposite. Similarly, if SNP disrupts secondary structure elements (e.g. substitution to proline in alpha helix region) such mutation usually may affect whole protein structure and function. Using those simple and many other machine learning derived rules a group of programs for the prediction of SNP effect was developed:
- International HapMap Project
- SNP array
- SNV calling from NGS data
- Short tandem repeat (STR)
- Single-base extension
- Tag SNP
- SNP Annotation
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- Nature Reviews Glossary
- Human Genome Project Information — SNP Fact Sheet
- Relation of SNP's with Cancer
- NCBI resources — Introduction to SNPs from NCBI
- The SNP Consortium LTD — SNP search
- NCBI dbSNP database — "a central repository for both single base nucleotide substitutions and short deletion and insertion polymorphisms"
- HGMD — the Human Gene Mutation Database, includes rare mutations and functional SNPs
- SNPedia - a wiki devoted to the medical consequences of DNA variations, including software to analyze personal genomes
- International HapMap Project — "a public resource that will help researchers find genes associated with human disease and response to pharmaceuticals"
- GWAS Central — a central database of summary-level genetic association findings
- 1000 Genomes Project — A Deep Catalog of Human Genetic Variation
- WatCut — an online tool for the design of SNP-RFLP assays
- SNPStats — SNPStats, a web tool for analysis of genetic association studies
- Restriction HomePage — a set of tools for DNA restriction and SNP detection, including design of mutagenic primers
- American Association for Cancer Research Cancer Concepts Factsheet on SNPs
- PharmGKB — The Pharmacogenetics and Pharmacogenomics Knowledge Base, a resource for SNPs associated with drug response and disease outcomes.
- GEN-SNiP — Online tool that identifies polymorphisms in test DNA sequences.
- Rules for Nomenclature of Genes, Genetic Markers, Alleles, and Mutations in Mouse and Rat
- HGNC Guidelines for Human Gene Nomenclature
- SNP effect predictor with galaxy integration
- Human Gene Mutation Database
- GWAS Central
- Open SNP — a portal for sharing own SNP test results
- The HapMap Project