SNP array: Difference between revisions

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{{Short description|Technique for detecting polymorphisms in a genome}}

{{See also|DNA microarray|SNP genotyping}}

{{expert needed|Computational Biology|date=April 2016}}

In [[molecular biology]] and [[bioinformatics]], '''SNP array''' is a type of [[DNA microarray]] which is used to detect [[Polymorphism (biology)|polymorphisms]] within a population. A [[single nucleotide polymorphism]] (SNP), a variation at a single site in [[DNA]], is the most frequent type of variation in the genome. Currently,Around there are around 85335 million SNPs that have been identified in the [[human genome]].,<ref>{{cite journalweb|title=dbSNP Summary|doiurl=10https://www.ncbi.nlm.nih.1093gov/narprojects/29SNP/snp_summary.1cgi|archive-url=https://archive.308 today/20121214045801/http://www.ncbi.nlm.nih.gov/projects/SNP/snp_summary.cgi|pmidurl-status=11125122 dead|pmcarchive-date=29783December 14, 2012|titlewebsite=DbSNP:www.ncbi.nlm.nih.gov|accessdate=4 TheOctober NCBI2017}}</ref> database15 million of geneticwhich variationare |journal=Nucleicpresent Acidsat Researchfrequencies |volume=29of |issue=1% |pages=308–11or |year=2001higher |last1=Sherryacross |first1=S.different populations Tworldwide.<ref |last2name=Ward"DurbinAltshuler2010">{{cite journal|first2author=M.The H.1000 Genomes Project Consortium|last3title=KholodovA map of human genome variation from population-scale sequencing|first3journal=M Nature|last4volume=Baker 467|first4issue=J 7319|last5year=Phan 2010|first5pages=L 1061–1073|last6issn=Smigielski 0028-0836|first6doi=E10. M. 1038/nature09534|last7pmid=Sirotkin 20981092|first7pmc=K 3042601|bibcode=2010Natur.467.1061T}}</ref>

==Principles==

The basic principles of SNP array are the same as the DNA microarray. These are the convergence of [[DNA hybridization]], [[fluorescence microscope|fluorescence microscopy]], and solid surface DNA capture. The three mandatory components of the SNP arrays are:<ref>{{cite journal|last1=LaFramboise|first1=T.|title=Single nucleotide polymorphism arrays: a decade of biological, computational and technological advances|journal=Nucleic Acids Research|date=1 July 2009|volume=37|issue=13|pages=4181–4193|doi=10.1093/nar/gkp552|pmid=19570852|pmc=2715261}}</ref>

{{Unreferenced section|date=April 2015}}

The basic principles of SNP array are the same as the DNA microarray. These are the convergence of [[DNA hybridization]], [[fluorescence microscope|fluorescence microscopy]], and solid surface DNA capture. The three mandatory components of the SNP arrays are:

# An array containing immobilized [[allele-specific oligonucleotide]] (ASO) probes.

# Fragmented [[nucleic acid]] sequences of target, labeledlabelled with fluorescent dyes.

# A detection system that records and interprets the [[DNA-DNADNA–DNA hybridization|hybridization]] signal.

The ASO probes are often chosen based on sequencing of a representative panel of individuals: positions found to vary in the panel at a specified frequency are used as the basis for probes. SNP chips are generally described by the number of SNP positions they assay. Two probes must be used for each SNP position to detect both alleles; if only one probe were used, experimental failure would be indistinguishable from [[homozygosity]] of the non-probed allele.<ref>{{cite book|first1=Ralph| last1=Rapley|first2=Stuart|last2=Harbron|title=Molecular analysis and genome discovery|date=2004|publisher=Wiley|___location=Chichester [u.a.]|isbn=978-0-471-49919-0}}</ref>

==Applications==

{{Unreferenced section|date=April 2015}}

[[File:LRR and BAF profiles for the T47D breast cancer cell line top.svg|right|thumb|DNA copy number profile for the T47D breast cancer cell line (Affymetrix SNP Array)]]

[[File:LRR and BAF profiles for the T47D breast cancer cell line bottom.svg|thumb|LOH profile for the T47D breast cancer cell line (Affymetrix SNP Array)]]

An SNP array is a useful tool for studying slight variations between whole [[genomes]]. The most important clinical applications of SNP arrays are for determining disease susceptibility<ref>{{cite journal|last1=Schaaf|first1=Christian P.|last2=Wiszniewska|first2=Joanna|last3=Beaudet|first3=Arthur L.|title=Copy Number and SNP Arrays in Clinical Diagnostics|journal=Annual Review of Genomics and Human Genetics|date=22 September 2011|volume=12|issue=1|pages=25–51|doi=10.1146/annurev-genom-092010-110715|pmid=21801020}}</ref> and for measuring the efficacy of drug therapies designed specifically for individuals.<ref>{{cite journal|last1=Alwi|first1=Zilfalil Bin|title=The Use of SNPs in Pharmacogenomics Studies|journal=The Malaysian Journal of Medical Sciences |date=2005|volume=12|issue=2|pages=4–12|issn=1394-195X|pmc=3349395|pmid=22605952}}</ref> In research, SNP arrays are most frequently used for [[genome-wide association studies]].<ref name="GibbsBelmont2003">{{cite journal|author=The International HapMap Consortium|title=The International HapMap Project|journal=Nature|volume=426|issue=6968|year=2003|pages=789–796|issn=0028-0836|doi=10.1038/nature02168|pmid=14685227|bibcode=2003Natur.426..789G|hdl=2027.42/62838|s2cid=4387110|url=https://deepblue.lib.umich.edu/bitstream/2027.42/62838/1/nature02168.pdf|hdl-access=free}}</ref> Each individual has many SNPs. SNP-based [[genetic linkage]] analysis can be used to map disease loci, and determine disease susceptibility genes in individuals. The combination of SNP maps and high density SNP arrays allows SNPs to be used as markers for genetic diseases that have [[complex traits]]. For example, whole-genome [[geneticgenome-wide linkageassociation studies]] analysishave showsidentified linkageSNPs forassociated with diseases such as [[rheumatoid arthritis]],<ref>{{cite [[prostatejournal|last1=Walsh|first1=Alice cancer]],M.|last2=Whitaker|first2=John andW.|last3=Huang|first3=C. neonatalChris|last4=Cherkas|first4=Yauheniya|last5=Lamberth|first5=Sarah [[diabetes]]L.|last6=Brodmerkel|first6=Carrie|last7=Curran|first7=Mark ThisE.|last8=Dobrin|first8=Radu|title=Integrative informationgenomic candeconvolution helpof designrheumatoid [[drug]]sarthritis thatGWAS actloci oninto agene groupand ofcell individualstype whoassociations|journal=Genome shareBiology|date=30 aApril common2016|volume=17|issue=1|pages=79|doi=10.1186/s13059-016-0948-6|pmid=27140173|pmc=4853861 |doi-access=free }}</ref> and [[alleleprostate cancer]].<ref>{{cite journal|last1=Amin Al Olama|first1=A.|display-authors=etal|title=The orgenetics evenof atype single2 individual.{{Citationdiabetes: neededwhat have we learned from GWAS?|journal=Annals of the New York Academy of Sciences|date=AprilNovember 20112010|volume=1212|issue=1|pages=59–77|doi=10.1111/j.1749-6632.2010.05838.x|pmid=21091714|pmc=3057517|bibcode=2010NYASA1212...59B}}</ref> A SNP array can also be used to generate a virtual [[karyotype]] using software to determine the copy number of each SNP on the array and then align the SNPs in chromosomal order.<ref>{{cite journal|last1=Sato-Otsubo|first1=Aiko|last2=Sanada|first2=Masashi|last3=Ogawa|first3=Seishi|title=Single-Nucleotide Polymorphism Array Karyotyping in Clinical Practice: Where, When, and How?|journal=Seminars in Oncology|date=February 2012|volume=39|issue=1|pages=13–25|doi=10.1053/j.seminoncol.2011.11.010|pmid=22289488}}</ref>

SNPs can also be used to study genetic abnormalities in cancer. For example, SNP arrays can be used to study [[loss of heterozygosity]] (LOH). LOH occurs when one allele of a gene is mutated in a deleterious way and the normally-functioning allele is lost. LOH occurs commonly in oncogenesis. For example, tumor suppressor genes help keep cancer from developing. If a person has one mutated and dysfunctional copy of a tumor suppressor gene and his second, functional copy of the gene gets damaged, they may become more likely to develop cancer.<ref>{{cite journal|last1=Zheng|first1=Hai-Tao|title=Loss of heterozygosity analyzed by single nucleotide polymorphism array in cancer|journal=World Journal of Gastroenterology|date=2005|volume=11|issue=43|pages=6740–4|doi=10.3748/wjg.v11.i43.6740|pmid=16425377|pmc=4725022 |doi-access=free }}</ref>

Other chip-based methods such as [[comparative genomic hybridization]] can detect genomic gains or deletions leading to LOH. SNP arrays, however, have an additional advantage of being able to detect copy-neutral LOH (also called [[uniparental disomy]] or gene conversion). Copy-neutral LOH is a form of allelic imbalance. In copy-neutral LOH, one allele or whole chromosome from a parent is missing. This problem leads to duplication of the other parental allele. Copy-neutral LOH may be pathological. For example, say that the mother's allele is wild-type and fully functional, and the fathersfather's allele is mutated. If the mother's allele is missing and the child has two copies of the father's mutant allele, disease can occur.

High density SNP arrays help scientists identify patterns of allelic imbalance. These studies have potential prognostic and diagnostic uses. Because LOH is so common in many human cancers, SNP arrays have great potential in cancer diagnostics. For example, recent SNP array studies have shown that solid [[tumor]]s such as [[gastric cancer]] and [[hepatocellular carcinoma|liver cancer]] show LOH, as do non-solid malignancies such as [[leukemia|hematologic malignancies]], [[leukemia#acute lymphocytic leukemia (ALL)|ALL]], [[myelodysplastic syndrome|MDS]], [[Leukemia#Chronic myelogenous|CML]] and others. These studies may provide insights into how these diseases develop, as well as information about how to create therapies for them.<ref>{{cite journal|last1=Mao|first1=Xueying|last2=Young|first2=Bryan D|last3=Lu|first3=Yong-Jie|title=The Application of Single Nucleotide Polymorphism Microarrays in Cancer Research|journal=Current Genomics|date=2007|volume=8|issue=4|pages=219–228|issn=1389-2029|doi=10.2174/138920207781386924|pmc=2430687|pmid=18645599}}</ref>

Breeding in a number of animal and plant species has been revolutionized by the emergence of SNP arrays. The method is based on the prediction of genetic merit by incorporating relationships among individuals based on SNP array data.<ref name="pmid11290733">{{cite journal |vauthors = Meuwissen TH, Hayes BJ, Goddard ME |title = Prediction of total genetic value using genome-wide dense marker maps |journal = Genetics |volume = 157 |issue = 4 |pages = 1819–29 |year = 2001 |doi = 10.1093/genetics/157.4.1819 |pmid = 11290733 |pmc = 1461589 }}</ref> This process is known as genomic selection. Crop-specific arrays find use in agriculture.<ref name="Hulse-Kemp-et-al-2015">{{cite journal | last1=Hulse-Kemp | first1=Amanda M |author-link1=Amanda M. Hulse-Kemp| last2=Lemm | first2=Jana | last3=Plieske | first3=Joerg | last4=Ashrafi | first4=Hamid | last5=Buyyarapu | first5=Ramesh | last6=Fang | first6=David D | last7=Frelichowski | first7=James | last8=Giband | first8=Marc | last9=Hague | first9=Steve | last10=Hinze | first10=Lori L | last11=Kochan | first11=Kelli J | last12=Riggs | first12=Penny K | last13=Scheffler | first13=Jodi A | last14=Udall | first14=Joshua A | last15=Ulloa | first15=Mauricio | last16=Wang | first16=Shirley S | last17=Zhu | first17=Qian-Hao | last18=Bag | first18=Sumit K | last19=Bhardwaj | first19=Archana | last20=Burke | first20=John J | last21=Byers | first21=Robert L | last22=Claverie | first22=Michel | last23=Gore | first23=Michael A | last24=Harker | first24=David B | last25=Islam | first25=Mohammad Sariful | last26=Jenkins | first26=Johnie N | last27=Jones | first27=Don C | last28=Lacape | first28=Jean-Marc | last29=Llewellyn | first29=Danny J | last30=Percy | first30=Richard G | last31=Pepper | first31=Alan E | last32=Poland | first32=Jesse A | last33=Mohan Rai | first33=Krishan | last34=Sawant | first34=Samir V | last35=Singh | first35=Sunil Kumar | last36=Spriggs | first36=Andrew | last37=Taylor | first37=Jen M | last38=Wang | first38=Fei | last39=Yourstone | first39=Scott M | last40=Zheng | first40=Xiuting | last41=Lawley | first41=Cindy T | last42=Ganal | first42=Martin W | last43=Van Deynze | first43=Allen | last44=Wilson | first44=Iain W | last45=Stelly | first45=David M | title=Development of a 63K SNP Array for Cotton and High-Density Mapping of Intraspecific and Interspecific Populations of ''Gossypium'' spp. | journal=[[G3: Genes, Genomes, Genetics]] | publisher=[[Genetics Society of America]] ([[Oxford University Press|OUP]]) | volume=5 | issue=6 | date=2015-06-01 | issn=2160-1836 | doi=10.1534/g3.115.018416 | pages=1187–1209 | pmid=25908569 | s2cid=11590488| pmc=4478548 }}</ref><ref name="Rasheed-et-al-2017">{{cite journal | last1=Rasheed | first1=Awais | last2=Hao | first2=Yuanfeng | last3=Xia | first3=Xianchun | last4=Khan | first4=Awais | last5=Xu | first5=Yunbi | last6=Varshney | first6=Rajeev K. | last7=He | first7=Zhonghu | title=Crop Breeding Chips and Genotyping Platforms: Progress, Challenges, and Perspectives | journal=[[Molecular Plant]] | publisher=[[Chinese Academy of Sciences|Chin Acad Sci]]+[[Chinese Society for Plant Biology|Chin Soc Plant Bio]]+[[Shanghai Institutes for Biological Sciences|Shanghai Inst Bio Sci]] ([[Elsevier]]) | volume=10 | issue=8 | year=2017 | issn=1674-2052 | doi=10.1016/j.molp.2017.06.008 | pages=1047–1064 | s2cid=33780984 | pmid=28669791| bibcode=2017MPlan..10.1047R | doi-access=free }}</ref>

Breeding in a number of animal and plant species has been revolutionized by the emergence of SNP arrays. The method is based on the prediction of genetic merit by incorporating relationships among individuals based on SNP array data.<ref>{{cite journal |title=Prediction of Total Genetic Value Using Genome-Wide Dense Marker Maps | journal=Genetics |volume=157 |pages=1819–1829 |year=2001 |last1=Meuwissen |first1=T.H.E. |last2=Hayes |first2=B.J. |last3=Goddard |first3=M.E. }}</ref> This process is known as genomic selection.

==References==

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==Further reading==

*{{cite book |last1=Barnes |first1=Michael R. |year=2003 |chapter=Human Genetic Variation: Databases and Concepts |pages=39–70[https://archive.org/details/bioinformaticsfo00barn_094/page/n61 39]–70 |doi=10.1002/0470867302.ch3 |editor1-first=Michael R. |editor1-last=Barnes |editor2-first=Ian C. |editor2-last=Gray |title=Bioinformatics for Geneticists |url=https://archive.org/details/bioinformaticsfo00barn_094 |url-access=limited |isbn=978-0-470-84393-2 }}

{{More footnotes|article|date=April 2015}}

*{{cite book |last1=Barnes |first1=Michael R. |year=2003 |chapter=Human Genetic Variation: Databases and Concepts |pages=39–70 |doi=10.1002/0470867302.ch3 |editor1-first=Michael R. |editor1-last=Barnes |editor2-first=Ian C. |editor2-last=Gray |title=Bioinformatics for Geneticists |isbn=978-0-470-84393-2 }}

*{{cite journal |doi=10.1093/dnares/dsm002 |pmid=17363414 |pmc=2779891 |title=Genome-wide Copy Number Profiling on High-density Bacterial Artificial Chromosomes, Single-nucleotide Polymorphisms, and Oligonucleotide Microarrays: A Platform Comparison based on Statistical Power Analysis |journal=DNA Research |volume=14 |issue=1 |pages=1–11 |year=2007 |last1=Hehir-Kwa |first1=J. Y. |last2=Egmont-Petersen |first2=M. |last3=Janssen |first3=I. M. |last4=Smeets |first4=D. |last5=Van Kessel |first5=A. G. |last6=Veltman |first6=J. A. }}

*{{cite journal |doi=10.1086/422195 |pmid=15154113 |pmc=1182008 |title=Whole-Genome Scan, in a Complex Disease, Using 11,245 Single-Nucleotide Polymorphisms: Comparison with Microsatellites |journal=The American Journal of Human Genetics |volume=75 |issue=1 |pages=54–64 |year=2004 |last1=John |first1=Sally |last2=Shephard |first2=Neil |last3=Liu |first3=Guoying |last4=Zeggini |first4=Eleftheria |last5=Cao |first5=Manqiu |last6=Chen |first6=Wenwei |last7=Vasavda |first7=Nisha |last8=Mills |first8=Tracy |last9=Barton |first9=Anne |last10=Hinks |first10=Anne |last11=Eyre |first11=Steve |last12=Jones |first12=Keith W. |last13=Ollier |first13=William |last14=Silman |first14=Alan |last15=Gibson |first15=Neil |last16=Worthington |first16=Jane |last17=Kennedy |first17=Giulia C. }}

*{{cite journal |pmid=10958631 |pmc=2235196 |year=2000 |author1last1=Mei |first1=R |title=Genome-wide detection of allelic imbalance using human SNPs and high-density DNA arrays |journal=Genome Research |volume=10 |issue=8 |pages=1126–37 |last2=Galipeau |first2=P. C. |last3=Prass |first3=C |last4=Berno |first4=A |last5=Ghandour |first5=G |last6=Patil |first6=N |last7=Wolff |first7=R. K. |last8=Chee |first8=M. S. |last9=Reid |first9=B. J. |last10=Lockhart |first10=D. J. |doi=10.1101/gr.10.8.1126}}

*{{cite journal |doi=10.1086/425870 |pmid=15514889 |pmc=1182157 |title=Comparison of Microsatellites Versus Single-Nucleotide Polymorphisms in a Genome Linkage Screen for Prostate Cancer–Susceptibility Loci |journal=The American Journal of Human Genetics |volume=75 |issue=6 |pages=948–65 |year=2004 |last1=Schaid |first1=Daniel J. |last2=Guenther |first2=Jennifer C. |last3=Christensen |first3=Gerald B. |last4=Hebbring |first4=Scott |last5=Rosenow |first5=Carsten |last6=Hilker |first6=Christopher A. |last7=McDonnell |first7=Shannon K. |last8=Cunningham |first8=Julie M. |last9=Slager |first9=Susan L. |last10=Blute |first10=Michael L. |last11=Thibodeau |first11=Stephen N. }}

*{{cite journal |doi=10.1093/nar/gnh163 |pmid=15561999 |pmc=534642 |title=Genomewide linkage searches for Mendelian disease loci can be efficiently conducted using high-density SNP genotyping arrays |journal=Nucleic Acids Research |volume=32 |issue=20 |pages=e164 |year=2004 |last1=Sellick |first1=G. S. |last2=Longman |first2=C |last3=Tolmie |first3=J |last4=Newbury-Ecob |first4=R |last5=Geenhalgh |first5=L |last6=Hughes |first6=S |last7=Whiteford |first7=M |last8=Garrett |first8=C |last9=Houlston |first9=R. S. }}