Editing Non-coding DNA (section)

==Genome-wide association studies (GWAS) and non-coding DNA==

[[Genome-wide association studies]] (GWAS) identify linkages between alleles and observable traits such as phenotypes and diseases. Most of the associations are between [[single-nucleotide polymorphisms]] (SNPs) and the trait being examined and most of these SNPs are located in non-functional DNA. The association establishes a linkage that helps map the DNA region responsible for the trait but it does not necessarily identify the mutations causing the disease or phenotypic difference.<ref>{{ cite journal | vauthors = Korte A, Farlwo A | date = 2013 | title = The advantages and limitations of trait analysis with GWAS: a review | journal = Plant Methods | volume = 9 | pages = 29 | doi = 10.1186/1746-4811-9-29| pmid = 23876160 | pmc = 3750305 | s2cid = 206976469 | doi-access = free }}</ref><ref name = Manolio>{{cite journal | vauthors = Manolio TA | title = Genomewide association studies and assessment of the risk of disease | journal = The New England Journal of Medicine | volume = 363 | issue = 2 | pages = 166–76 | date = July 2010 | pmid = 20647212 | doi = 10.1056/NEJMra0905980 | doi-access = free }}</ref><ref>{{cite journal | vauthors = Visscher PV, Wray NR, Zhang Q, Sklar P, McCarthy MI, Brown MA, Yang J | date = 2017 | title = 10 Years of GWAS Discovery: Biology, Function, and Translation | journal =  American Journal of Human Genetics | volume = 101 | issue = 1 | pages = 5–22 | doi = 10.1016/j.ajhg.2017.06.005| pmid = 28686856 | pmc = 5501872 }}</ref><ref>{{ cite journal | vauthors = Gallagher MD, Chen-Plotkin, AS | date = 2018 | title = The Post-GWAS Era: From Association to Function | journal = American Journal of Human Genetics | volume = 102 | issue = 5 | pages = 717–730 | doi = 10.1016/j.ajhg.2018.04.002| pmid = 29727686 | pmc = 5986732 }}</ref><ref>{{ cite journal | vauthors = Marigorta UM, Rodríguez JA, Gibson G, Navarro A | date = 2018 | title = Replicability and Prediction: Lessons and Challenges from GWAS | journal = Trends in Genetics | volume = 34 | issue = 7 | pages = 504–517 | doi = 10.1016/j.tig.2018.03.005| pmid = 29716745 | pmc = 6003860 }}</ref>
 
SNPs that are tightly linked to traits are the ones most likely to identify a causal mutation. (The association is referred to as tight [[linkage disequilibrium]].) About 12% of these polymorphisms are found in coding regions; about 40% are located in introns; and most of the rest are found in intergenic regions, including regulatory sequences.<ref name=Manolio/>