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DNA molecule 1 differs from DNA molecule 2 at a single base-pair location (a C/A polymorphism).
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.[1] Other factors, like genetic recombination and mutation rate, can also determine SNP density.[2]
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.[3]
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.[4]
Contents
- 1 Types
- 2 Use and importance
- 3 Examples
- 4 Databases
- 5 Nomenclature
- 6 SNP analysis
- 7 SNPs simulation
- 8 Programs for prediction of SNP effects
- 9 See also
- 10 Notes
- 11 References
- 12 External links
Types
| Types of SNPs |
- Non-coding region
- Coding region
|
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.[5] 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.
The study of SNPs is also important in crop and livestock breeding programs. See SNP genotyping for details on the various methods used to identify SNPs.
SNPs are usually biallelic and thus easily assayed.[6] 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.[7]
As of 16 October 2014[update], dbSNP listed 112,736,879 SNPs in humans.[8][9]
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.[10][11][12] Diseases with different SNPs may become relevant pharmacogenomic targets for drug therapy.[13] Some SNPs are associated with the metabolism of different drugs.[14][15][16]
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.[17]
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[18]
- 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[19]
- 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,[20] 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).[21]
Examples
- rs6311 and rs6313 are SNPs in the HTR2A gene on human chromosome 13.[22]
- A SNP in the F5 gene causes a hypercoagulability disorder with the variant Factor V Leiden.[23]
- rs3091244 is an example of a triallelic SNP in the CRP gene on human chromosome 1.[24]
- TAS2R38 codes for PTC tasting ability, and contains 6 annotated SNPs.[25]
- rs148649884 and rs138055828 in the FCN1 gene encoding M-ficolin crippled the ligand-binding capability of the recombinant M-ficolin.[26]
Databases
As there are for genes, bioinformatics databases exist for SNPs. dbSNP is a SNP database from the National Center for Biotechnology Information (NCBI). Kaviar[27] 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.[28] 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 |
| 1 |
214,066,000 |
129,931 |
1.65 |
75,166 |
2.85 |
| 2 |
222,889,000 |
103,664 |
2.15 |
76,985 |
2.90 |
| 3 |
186,938,000 |
93,140 |
2.01 |
63,669 |
2.94 |
| 4 |
169,035,000 |
84,426 |
2.00 |
65,719 |
2.57 |
| 5 |
170,954,000 |
117,882 |
1.45 |
63,545 |
2.69 |
| 6 |
165,022,000 |
96,317 |
1.71 |
53,797 |
3.07 |
| 7 |
149,414,000 |
71,752 |
2.08 |
42,327 |
3.53 |
| 8 |
125,148,000 |
57,834 |
2.16 |
42,653 |
2.93 |
| 9 |
107,440,000 |
62,013 |
1.73 |
43,020 |
2.50 |
| 10 |
127,894,000 |
61,298 |
2.09 |
42,466 |
3.01 |
| 11 |
129,193,000 |
84,663 |
1.53 |
47,621 |
2.71 |
| 12 |
125,198,000 |
59,245 |
2.11 |
38,136 |
3.28 |
| 13 |
93,711,000 |
53,093 |
1.77 |
35,745 |
2.62 |
| 14 |
89,344,000 |
44,112 |
2.03 |
29,746 |
3.00 |
| 15 |
73,467,000 |
37,814 |
1.94 |
26,524 |
2.77 |
| 16 |
74,037,000 |
38,735 |
1.91 |
23,328 |
3.17 |
| 17 |
73,367,000 |
34,621 |
2.12 |
19,396 |
3.78 |
| 18 |
73,078,000 |
45,135 |
1.62 |
27,028 |
2.70 |
| 19 |
56,044,000 |
25,676 |
2.18 |
11,185 |
5.01 |
| 20 |
63,317,000 |
29,478 |
2.15 |
17,051 |
3.71 |
| 21 |
33,824,000 |
20,916 |
1.62 |
9,103 |
3.72 |
| 22 |
33,786,000 |
28,410 |
1.19 |
11,056 |
3.06 |
| X |
131,245,000 |
34,842 |
3.77 |
20,400 |
6.43 |
| Y |
21,753,000 |
4,193 |
5.19 |
1,784 |
12.19 |
| RefSeq |
15,696,674 |
14,534 |
1.08 |
| Totals |
2,710,164,000 |
1,419,190 |
1.91 |
887,450 |
3.05 |
Nomenclature
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.[29][30][31] SNPs are frequently referred to by their dbSNP rs number, as in the examples above.
SNP analysis
Analytical methods to discover novel SNPs and detect known SNPs include:
- capillary electrophoresis;[33]
- single-strand conformation polymorphism (SSCP);[35]
- electrochemical analysis;
- denaturating HPLC and gel electrophoresis;
- restriction fragment length polymorphism;
SNPs simulation
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:
- SIFT
- SuSPect
- PolyPhen-2
- PredictSNP
- MutationTaster
See also
- Illumina
- Affymetrix
- International HapMap Project
- SNP array
- SNV calling from NGS data
- Short tandem repeat (STR)
- Single-base extension
- Snpstr
- Tag SNP
- TaqMan
- Variome
- SNP Annotation
Notes
- ^ Barreiro LB, Laval G, Quach H, Patin E, Quintana-Murci L.; Laval; Quach; Patin; Quintana-Murci (2008). "Natural selection has driven population differentiation in modern humans". Nature Genetics 40 (3): 340–345. doi:10.1038/ng.78. PMID 18246066.
- ^ Nachman, Michael W. (2001). "Single nucleotide polymorphisms and recombination rate in humans". Trends in genetics 17 (9): 481–485. doi:10.1016/S0168-9525(01)02409-X. PMID 11525814.
- ^ M.A. Varela and W. Amos (2010). "Heterogeneous distribution of SNPs in the human genome: Microsatellites as predictors of nucleotide diversity and divergence". Genomics 95 (3): 151–159. doi:10.1016/j.ygeno.2009.12.003. PMID 20026267.
- ^ Wolf, A. B.; Caselli, R. J.; Reiman, E. M.; Valla, J. (2012). "APOE and neuroenergetics: An emerging paradigm in Alzheimer's disease". Neurobiology of Aging 34 (4): 1007–17. doi:10.1016/j.neurobiolaging.2012.10.011. PMID 23159550. edit
- ^ Carlson, Bruce (2008-06-15). "SNPs — A Shortcut to Personalized Medicine". Genetic Engineering & Biotechnology News (Mary Ann Liebert, Inc.) 28 (12). Retrieved 2008-07-06.
(subtitle) Medical applications are where the market's growth is expected
- ^ Sachidanandam, Ravi; Weissman, David; Schmidt, Steven C.; Kakol, Jerzy M.; Stein, Lincoln D.; Marth, Gabor; Sherry, Steve; Mullikin, James C. et al. (2001). "A map of human genome sequence variation containing 1.42 million single nucleotide polymorphisms". Nature 409 (6822): 928–33. doi:10.1038/35057149. PMID 11237013.
- ^ Singh, Monica; Singh, Puneetpal; Juneja, Pawan Kumar; Singh, Surinder; Kaur, Taranpal (2010). "SNP–SNP interactions within APOE gene influence plasma lipids in postmenopausal osteoporosis". Rheumatology International 31 (3): 421–3. doi:10.1007/s00296-010-1449-7. PMID 20340021.
- ^ National Center for Biotechnology Information, United States National Library of Medicine. 2014. NCBI dbSNP build 142 for human. http://www.ncbi.nlm.nih.gov/mailman/pipermail/dbsnp-announce/2014q4/000147.html
- ^ National Center for Biotechnology Information, United States National Library of Medicine. 2014. NCBI dbSNP build 142 for human. Summary Page. http://www.ncbi.nlm.nih.gov/projects/SNP/snp_summary.cgi?build_id=142
- ^ Ingram, V. M. (1956). "A specific chemical difference between the globins of normal human and sickle-cell anaemia haemoglobin". Nature 178 (4537): 792–794. doi:10.1038/178792a0. PMID 13369537. edit
- ^ Chang, J. C.; Kan, Y. W. (1979). "Beta 0 thalassemia, a nonsense mutation in man". Proceedings of the National Academy of Sciences of the United States of America 76 (6): 2886–2889. doi:10.1073/pnas.76.6.2886. PMC 383714. PMID 88735. edit
- ^ Hamosh, A.; King, T. M.; Rosenstein, B. J.; Corey, M.; Levison, H.; Durie, P.; Tsui, L. C.; McIntosh, I.; Keston, M.; Brock, D. J.; Macek, M.; Zemková, D.; Krásničanová, H.; Vávrová, V.; Macek, M.; Golder, N.; Schwarz, M. J.; Super, M.; Watson, E. K.; Williams, C.; Bush, A.; O'Mahoney, S. M.; Humphries, P.; Dearce, M. A.; Reis, A.; Bürger, J.; Stuhrmann, M.; Schmidtke, J.; Wulbrand, U.; Dörk, T. (1992). "Cystic fibrosis patients bearing both the common missense mutation Gly----Asp at codon 551 and the delta F508 mutation are clinically indistinguishable from delta F508 homozygotes, except for decreased risk of meconium ileus". American journal of human genetics 51 (2): 245–250. PMC 1682672. PMID 1379413. edit
- ^ Fareed, M., Afzal, M (2013) "Single nucleotide polymorphism in genome-wide association of human population: A tool for broad spectrum service". Egyptian Journal of Medical Human Genetics 14: 123–134. http://dx.doi.org/10.1016/j.ejmhg.2012.08.001.
- ^ Goldstein, J. A. (2001). "Clinical relevance of genetic polymorphisms in the human CYP2C subfamily". British journal of clinical pharmacology 52 (4): 349–355. doi:10.1046/j.0306-5251.2001.01499.x. PMC 2014584. PMID 11678778. edit
- ^ Lee, C. R. (2004). "CYP2C9 genotype as a predictor of drug disposition in humans". Methods and findings in experimental and clinical pharmacology 26 (6): 463–472. PMID 15349140. edit
- ^ Yanase, K.; Tsukahara, S.; Mitsuhashi, J.; Sugimoto, Y. (2006). "Functional SNPs of the breast cancer resistance protein ‐ therapeutic effects and inhibitor development". Cancer Letters 234 (1): 73–80. doi:10.1016/j.canlet.2005.04.039. PMID 16303243. edit
- ^ Thomas, P. E.; Klinger, R.; Furlong, L. I.; Hofmann-Apitius, M.; Friedrich, C. M. (2011). "Challenges in the association of human single nucleotide polymorphism mentions with unique database identifiers". BMC Bioinformatics 12: S4. doi:10.1186/1471-2105-12-S4-S4. PMC 3194196. PMID 21992066. edit
- ^ Li, G.; Pan, T.; Guo, D.; Li, LC. (2014). "Regulatory Variants and Disease: The E-Cadherin -160C/A SNP as an Example". Mol Biol Int 2014: 967565. doi:10.1155/2014/967565. PMC 4167656. PMID 25276428.
- ^ Kimchi-Sarfaty, C.; Oh, JM.; Kim, IW.; Sauna, ZE.; Calcagno, AM.; Ambudkar, SV.; Gottesman, MM. (Jan 2007). "A "silent" polymorphism in the MDR1 gene changes substrate specificity". Science 315 (5811): 525–8. doi:10.1126/science.1135308. PMID 17185560.
- ^ Al-Haggar M, Madej-Pilarczyk A, Kozlowski L, Bujnicki JM, Yahia S, Abdel-Hadi D, Shams A, Ahmad N, Hamed S, Puzianowska-Kuznicka M; Madej-Pilarczyk; Kozlowski; Bujnicki; Yahia; Abdel-Hadi; Shams; Ahmad; Hamed; Puzianowska-Kuznicka (2012). "A novel homozygous p.Arg527Leu LMNA mutation in two unrelated Egyptian families causes overlapping mandibuloacral dysplasia and progeria syndrome". Eur J Hum Genet. 20 (11): 1134–40. doi:10.1038/ejhg.2012.77. PMC 3476705. PMID 22549407.
- ^ Cordovado, SK.; Hendrix, M.; Greene, CN.; Mochal, S.; Earley, MC.; Farrell, PM.; Kharrazi, M.; Hannon, WH.; Mueller, PW. (Feb 2012). "CFTR mutation analysis and haplotype associations in CF patients". Mol Genet Metab 105 (2): 249–54. doi:10.1016/j.ymgme.2011.10.013. PMC 3551260. PMID 22137130.
- ^ Giegling I, Hartmann AM, Möller HJ, Rujescu D (November 2006). "Anger- and aggression-related traits are associated with polymorphisms in the 5-HT-2A gene". Journal of Affective Disorders 96 (1–2): 75–81. doi:10.1016/j.jad.2006.05.016. PMID 16814396.
- ^ Kujovich, JL. (Jan 2011). "Factor V Leiden thrombophilia.". Genet Med 13 (1): 1–16. doi:10.1097/GIM.0b013e3181faa0f2. PMID 21116184.
- ^ Morita, Akihiko; Nakayama, Tomohiro; Doba, Nobutaka; Hinohara, Shigeaki; Mizutani, Tomohiko; Soma, Masayoshi (2007). "Genotyping of triallelic SNPs using TaqMan PCR". Molecular and Cellular Probes 21 (3): 171–6. doi:10.1016/j.mcp.2006.10.005. PMID 17161935.
- ^ Prodi, D.A.; Drayna, D; Forabosco, P; Palmas, MA; Maestrale, GB; Piras, D; Pirastu, M; Angius, A (2004). "Bitter Taste Study in a Sardinian Genetic Isolate Supports the Association of Phenylthiocarbamide Sensitivity to the TAS2R38 Bitter Receptor Gene". Chemical Senses 29 (8): 697–702. doi:10.1093/chemse/bjh074. PMID 15466815.
- ^ Ammitzbøll, Christian Gytz; Kjær, Troels Rønn; Steffensen, Rudi; Stengaard-Pedersen, Kristian; Nielsen, Hans Jørgen; Thiel, Steffen; Bøgsted, Martin; Jensenius, Jens Christian (28 November 2012). "Non-Synonymous Polymorphisms in the FCN1 Gene Determine Ligand-Binding Ability and Serum Levels of M-Ficolin". PLoS ONE 7 (11): e50585. doi:10.1371/journal.pone.0050585.
- ^ Glusman, G; Caballero, J; Mauldin, D. E.; Hood, L; Roach, J. C. (2011). "Kaviar: An accessible system for testing SNV novelty". Bioinformatics 27 (22): 3216–7. doi:10.1093/bioinformatics/btr540. PMC 3208392. PMID 21965822. edit
- ^ Sachidanandam, R.; Weissman, D.; Schmidt, S. C.; Kakol, J. M.; Stein, L. D.; Marth, G.; Sherry, S.; Mullikin, J. C.; Mortimore, B. J.; Willey, D. L.; Hunt, S. E.; Cole, C. G.; Coggill, P. C.; Rice, C. M.; Ning, Z.; Rogers, J.; Bentley, D. R.; Kwok, P. Y.; Mardis, E. R.; Yeh, R. T.; Schultz, B.; Cook, L.; Davenport, R.; Dante, M.; Fulton, L.; Hillier, L.; Waterston, R. H.; McPherson, J. D.; Gilman, B.; Schaffner, S. (2001). "A map of human genome sequence variation containing 1.42 million single nucleotide polymorphisms". Nature 409 (6822): 928–933. doi:10.1038/35057149. PMID 11237013. edit
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- ^ den Dunnen, Johan T.; Antonarakis, Stylianos E. (2000). "Mutation nomenclature extensions and suggestions to describe complex mutations: A discussion". Human Mutation 15 (1): 7–12. doi:10.1002/(SICI)1098-1004(200001)15:1<7::AID-HUMU4>3.0.CO;2-N. PMID 10612815.
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References
- Nature Reviews Glossary
- Human Genome Project Information — SNP Fact Sheet
- Relation of SNP's with Cancer
External links
- 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
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