Editing Single-nucleotide polymorphism (section)

== Applications ==
{{Prose|date=May 2023|section}}
* [[Genetic association|Association studies]] (such as [[Genome-wide association study|GWAS]], see below) can determine whether a genetic variant is associated with a disease or trait.<ref>{{cite journal|vauthors=Zhang K, Qin ZS, Liu JS, Chen T, Waterman MS, Sun F|date=May 2004|title=Haplotype block partitioning and tag SNP selection using genotype data and their applications to association studies|journal=Genome Research|volume=14|issue=5|pages=908–16|doi=10.1101/gr.1837404|pmc=479119|pmid=15078859}}</ref>
* A tag SNP is a representative single-nucleotide polymorphism in a region of the genome with high [[linkage disequilibrium]] (the non-random association of alleles at two or more loci). Tag SNPs are useful in whole-genome SNP association studies, in which hundreds of thousands of SNPs across the entire genome are genotyped.
* [[Haplotype]] mapping: sets of alleles or DNA sequences can be clustered so that a single SNP can identify many linked SNPs.
* [[Linkage disequilibrium]] (LD), a term used in population genetics, indicates non-random association of alleles at two or more loci, not necessarily on the same chromosome. It refers to the phenomenon that SNP allele or DNA sequence that are close together in the genome tend to be inherited together. LD can be affected by two parameters (among other factors, such as population stratification):
** The distance between the SNPs (the larger the distance, the lower the LD)
** Recombination rate (the lower the recombination rate, the higher the LD)<ref name="Gupta">{{Cite journal|vauthors=Gupta PK, Roy JK, Prasad M|date=25 February 2001|title=Single nucleotide polymorphisms: a new paradigm for molecular marker technology and DNA polymorphism detection with emphasis on their use in plants|url=https://www.researchgate.net/publication/229085137|url-status=live|journal=Current Science|volume=80|issue=4|pages=524–535|archive-url=https://web.archive.org/web/20170213091838/https://www.researchgate.net/publication/229085137_Single_nucleotide_polymorphisms_a_new_paradigm_for_molecular_marker_technology_and_DNA_polymorphism_detection_with_emphasis_on_their_use_in_plantsPK_Gupta_JK_Roy_M_PrasadCurr_Sci_80_4_524-35|archive-date=13 February 2017}}</ref>
* In [[genetic epidemiology]] SNPs are used to estimate transmission clusters.<ref>{{cite journal|vauthors=Stimson J, Gardy J, Mathema B, Crudu V, Cohen T, Colijn C|title=Beyond the SNP Threshold: Identifying Outbreak Clusters Using Inferred Transmissions|url=|journal=Molecular Biology and Evolution|volume=36|issue=3|pages=587–603|doi=10.1093/molbev/msy242|date=25 January 2019|pmid=30690464|pmc=6389316 }}</ref>

=== Importance ===
Variations in the DNA sequences of humans can affect how humans develop [[disease]]s and respond to [[pathogen]]s, [[chemical]]s, [[medication|drugs]], [[vaccine]]s, and other agents. SNPs are also critical for [[personalized medicine]].<ref>{{cite journal|first1 = Bruce|last1 = Carlson|title = SNPs — A Shortcut to Personalized Medicine|url = http://www.genengnews.com/gen-articles/snps-a-shortcut-to-personalized-medicine/2507/|journal = [[Gen. Eng. Biotechnol. News|Genetic Engineering & Biotechnology News]]|publisher = [[Mary Ann Liebert, Inc.]]|date = 15 June 2008|access-date = 2008-07-06|volume = 28|issue = 12|quote = (subtitle) Medical applications are where the market's growth is expected|url-status = live|archive-url = https://web.archive.org/web/20101226164858/http://www.genengnews.com/gen-articles/snps-a-shortcut-to-personalized-medicine/2507|archive-date = 26 December 2010}}</ref> Examples include biomedical research, forensics, pharmacogenetics, and disease causation, as outlined below.

=== Clinical research ===

==== Genome-wide association study (GWAS) ====
One of the main contributions of SNPs in clinical research is genome-wide association study (GWAS).<ref name="auto">{{Cite journal|last1=Visscher|first1=Peter M.|last2=Wray|first2=Naomi R.|last3=Zhang|first3=Qian|last4=Sklar|first4=Pamela|last5=McCarthy|first5=Mark I.|last6=Brown|first6=Matthew A.|last7=Yang|first7=Jian|date=July 2017|title=10 Years of GWAS Discovery: Biology, Function, and Translation|url=|journal=The American Journal of Human Genetics|volume=101|issue=1|pages=5–22|doi=10.1016/j.ajhg.2017.06.005|pmid=28686856|pmc=5501872|issn=0002-9297}}</ref> Genome-wide genetic data can be generated by multiple technologies, including SNP array and whole genome sequencing. GWAS has been commonly used in identifying SNPs associated with diseases or clinical phenotypes or traits. Since GWAS is a genome-wide assessment, a large sample site is required to obtain sufficient statistical power to detect all possible associations. Some SNPs have relatively small effect on diseases or clinical phenotypes or traits. To estimate study power, the genetic model for disease needs to be considered, such as dominant, recessive, or additive effects. Due to genetic heterogeneity, GWAS analysis must be adjusted for race.

==== Candidate gene association study ====
Candidate gene association study is commonly used in genetic study before the invention of high throughput genotyping or sequencing technologies.<ref>{{Cite journal|last1=Dong|first1=Linda M.|last2=Potter|first2=John D.|last3=White|first3=Emily|last4=Ulrich|first4=Cornelia M.|last5=Cardon|first5=Lon R.|last6=Peters|first6=Ulrike|date=2008-05-28|title=Genetic Susceptibility to Cancer|url=|journal=JAMA|volume=299|issue=20|pages=2423–2436|doi=10.1001/jama.299.20.2423|pmid=18505952|pmc=2772197|issn=0098-7484}}</ref> Candidate gene association study is to investigate limited number of pre-specified SNPs for association with diseases or clinical phenotypes or traits. So this is a hypothesis driven approach. Since only a limited number of SNPs are tested, a relatively small sample size is sufficient to detect the association. Candidate gene association approach is also commonly used to confirm findings from GWAS in independent samples.

==== Homozygosity mapping in disease ====
Genome-wide SNP data can be used for homozygosity mapping.<ref>{{Cite journal|last=Alkuraya|first=Fowzan S.|date=April 2010|title=Homozygosity mapping: One more tool in the clinical geneticist's toolbox|journal=Genetics in Medicine|volume=12|issue=4|pages=236–239|doi=10.1097/gim.0b013e3181ceb95d|pmid=20134328|s2cid=10789932|issn=1098-3600|doi-access=free}}</ref> Homozygosity mapping is a method used to identify homozygous autosomal recessive loci, which can be a powerful tool to map genomic regions or genes that are involved in disease pathogenesis.

==== Methylation patterns ====
[[File:Associations between SNPs, methylation patterns and gene expression.png|thumb|Associations between SNPs, methylation patterns and gene expression of biological traits]]
Recently, preliminary results reported SNPs as important components of the epigenetic program in organisms.<ref>{{Cite journal |last1=Vohra |first1=Manik |last2=Sharma |first2=Anu Radha |last3=Prabhu B |first3=Navya |last4=Rai |first4=Padmalatha S. |date=2020 |title=SNPs in Sites for DNA Methylation, Transcription Factor Binding, and miRNA Targets Leading to Allele-Specific Gene Expression and Contributing to Complex Disease Risk: A Systematic Review |journal=Public Health Genomics |volume=23 |issue=5–6 |pages=155–170 |doi=10.1159/000510253 |pmid=32966991 |s2cid=221886624 |issn=1662-4246|doi-access=free }}</ref><ref>{{Cite journal |last1=Wang |first1=Jing |last2=Ma |first2=Xiaoqin |last3=Zhang |first3=Qi |last4=Chen |first4=Yinghui |last5=Wu |first5=Dan |last6=Zhao |first6=Pengjun |last7=Yu |first7=Yu |date=2021 |title=The Interaction Analysis of SNP Variants and DNA Methylation Identifies Novel Methylated Pathogenesis Genes in Congenital Heart Diseases |journal=Frontiers in Cell and Developmental Biology |volume=9 |page=665514 |doi=10.3389/fcell.2021.665514 |issn=2296-634X |pmc=8143053 |pmid=34041244|doi-access=free }}</ref> Moreover, cosmopolitan studies in European and South Asiatic populations have revealed the influence of SNPs in the methylation of specific CpG sites.<ref name=":0">{{Cite journal |last1=Hawe |first1=Johann S. |last2=Wilson |first2=Rory |last3=Schmid |first3=Katharina T. |last4=Zhou |first4=Li |last5=Lakshmanan |first5=Lakshmi Narayanan |last6=Lehne |first6=Benjamin C. |last7=Kühnel |first7=Brigitte |last8=Scott |first8=William R. |last9=Wielscher |first9=Matthias |last10=Yew |first10=Yik Weng |last11=Baumbach |first11=Clemens |last12=Lee |first12=Dominic P. |last13=Marouli |first13=Eirini |last14=Bernard |first14=Manon |last15=Pfeiffer |first15=Liliane |date=January 2022 |title=Genetic variation influencing DNA methylation provides insights into molecular mechanisms regulating genomic function |journal=Nature Genetics |language=en |volume=54 |issue=1 |pages=18–29 |doi=10.1038/s41588-021-00969-x |pmid=34980917 |s2cid=256821844 |issn=1546-1718|pmc=7617265 }}</ref> In addition, meQTL enrichment analysis using GWAS database, demonstrated that those associations are important toward the prediction of biological traits.<ref name=":0" /><ref>{{Cite journal |last1=Perzel Mandell |first1=Kira A. |last2=Eagles |first2=Nicholas J. |last3=Wilton |first3=Richard |last4=Price |first4=Amanda J. |last5=Semick |first5=Stephen A. |last6=Collado-Torres |first6=Leonardo |last7=Ulrich |first7=William S. |last8=Tao |first8=Ran |last9=Han |first9=Shizhong |last10=Szalay |first10=Alexander S. |last11=Hyde |first11=Thomas M. |last12=Kleinman |first12=Joel E. |last13=Weinberger |first13=Daniel R. |last14=Jaffe |first14=Andrew E. |date=2021-09-02 |title=Genome-wide sequencing-based identification of methylation quantitative trait loci and their role in schizophrenia risk |journal=Nature Communications |language=en |volume=12 |issue=1 |pages=5251 |doi=10.1038/s41467-021-25517-3 |issn=2041-1723 |pmc=8413445 |pmid=34475392|bibcode=2021NatCo..12.5251P }}</ref><ref>{{Cite journal |last1=Hoffmann |first1=Anke |last2=Ziller |first2=Michael |last3=Spengler |first3=Dietmar |date=December 2016 |title=The Future is The Past: Methylation QTLs in Schizophrenia |journal=Genes |language=en |volume=7 |issue=12 |pages=104 |doi=10.3390/genes7120104 |issn=2073-4425 |pmc=5192480 |pmid=27886132|doi-access=free }}</ref>  

=== Forensic sciences ===

SNPs have historically been used to match a forensic DNA sample to a suspect but has been made obsolete due to advancing [[Microsatellite|STR]]-based [[DNA Fingerprinting|DNA fingerprinting]] techniques. However, the development of [[Next-Generation Sequencing|next-generation-sequencing]] (NGS) technology may allow for more opportunities for the use of SNPs in phenotypic clues such as [[ethnicity]], [[hair color]], and [[eye color]] with a good probability of a match. This can additionally be applied to increase the accuracy of facial reconstructions by providing information that may otherwise be unknown, and this information can be used to help identify suspects even without a STR [[DNA profiling|DNA profile]] match.

Some cons to using SNPs versus STRs is that SNPs yield less information than STRs, and therefore more SNPs are needed for analysis before a profile of a suspect is able to be created. Additionally, SNPs heavily rely on the presence of a database for comparative analysis of samples. However, in instances with degraded or small volume samples, SNP techniques are an excellent alternative to STR methods. SNPs (as opposed to STRs) have an abundance of potential markers, can be fully automated, and a possible reduction of required fragment length to less than 100&nbsp;bp.<ref name="Varela" />

=== Pharmacogenetics ===
Pharmacogenetics focuses on identifying genetic variations including SNPs associated with differential responses to treatment.<ref>{{Cite journal|last=Daly|first=Ann K|date=2017-10-11|title=Pharmacogenetics: a general review on progress to date|journal=British Medical Bulletin|volume=124|issue=1|pages=65–79|doi=10.1093/bmb/ldx035|pmid=29040422|issn=0007-1420|doi-access=free}}</ref> Many drug metabolizing enzymes, drug targets, or target pathways can be influenced by SNPs. The SNPs involved in drug metabolizing enzyme activities can change drug pharmacokinetics, while the SNPs involved in drug target or its pathway can change drug [[pharmacodynamics]]. Therefore, SNPs are potential genetic markers that can be used to predict drug exposure or effectiveness of the treatment. Genome-wide pharmacogenetic study is called [[pharmacogenomics]]. Pharmacogenetics and pharmacogenomics are important in the development of precision medicine, especially for life-threatening diseases such as cancers.

=== Disease ===
Only small amount of SNPs in the human genome may have impact on human diseases. Large scale GWAS has been done for the most important human diseases, including [[heart diseases]], [[metabolic diseases]], [[autoimmune diseases]], and [[Neurodegenerative disorder|neurodegenerative]] and [[Psychiatric disorder|psychiatric disorders]].<ref name="auto"/> Most of the SNPs with relatively large effects on these diseases have been identified. These findings have significantly improved understanding of disease pathogenesis and molecular pathways, and facilitated development of better treatment. Further GWAS with larger samples size will reveal the SNPs with relatively small effect on diseases. For common and complex diseases, such as [[type-2 diabetes]], [[rheumatoid arthritis]], and [[Alzheimer's disease]], multiple genetic factors are involved in disease etiology. In addition, gene-gene interaction and gene-environment interaction also play an important role in disease initiation and progression.<ref>{{Cite journal|last1=Musci|first1=Rashelle J.|last2=Augustinavicius|first2=Jura L.|last3=Volk|first3=Heather|date=2019-08-13|title=Gene-Environment Interactions in Psychiatry: Recent Evidence and Clinical Implications|url=|journal=Current Psychiatry Reports|volume=21|issue=9|page=81|doi=10.1007/s11920-019-1065-5|pmid=31410638|pmc=7340157|issn=1523-3812}}</ref>