Editing Functional genomics (section)

====Deep mutational scanning====
In deep mutational scanning, every possible amino acid change in a given protein is first synthesized.<ref>{{cite journal |last1=Araya |first1=Carlos |last2=Fowler |first2=Douglas |title=Deep mutational scanning: assessing protein function on a massive scale |journal=Trends in Biotechnology |date=September 29, 2011 |volume=29 |issue=9 |pages=435–442 |doi=10.1016/j.tibtech.2011.04.003 |pmid=21561674|pmc=3159719 }}</ref> The activity of each of these protein variants is assayed in parallel using barcodes for each variant.<ref>{{cite journal | vauthors = Penn WD, McKee AG, Kuntz CP, Woods H, Nash V, Gruenhagen TC, Roushar FJ, Chandak M, Hemmerich C, Rusch DB, Meiler J, Schlebach JP| title = Probing biophysical sequence constraints within the transmembrane domains of rhodopsin by deep mutational scanning| journal = Sci Adv | volume =  6 | issue = 10 | pages = eaay7505| date = March 2020 | pmid = 32181350 | doi = 10.1126/sciadv.aay7505| pmc = 7056298 | bibcode = 2020SciA....6.7505P}}</ref> By comparing the activity to the wild-type protein, the effect of each mutation is identified. While it is possible to assay every possible single amino-acid change due to combinatorics two or more concurrent mutations are hard to test. Deep mutational scanning experiments have also been used to infer protein structure and protein-protein interactions.<ref>{{cite journal |last1=Rollins |first1=N.J. |last2=Brock |first2=K.P. |last3=Poelwijk |first3=F.J |last4=Marks |first4=Debora |title=Inferring protein 3D structure from deep mutation scans |journal=Nature Genetics |date=2019 |volume=51 |issue=7 |pages=1170–1176 |doi=10.1038/s41588-019-0432-9 |pmid=31209393 |pmc=7295002 }}</ref> Deep Mutational Scanning is an example of a multiplexed assays of variant effect (MAVEs), a family of methods that involve mutagenesis of a DNA-encoded protein or regulatory element followed by a multiplexed assay for some aspect of function. MAVEs enable the generation of ‘variant effect maps’ characterizing aspects of the function of every possible single nucleotide change in a gene or functional element of interest. <ref>{{cite journal |last1=Fowler |first1=DM |last2=Adams |first2=DJ |last3=Gloyn |first3=AL |last4=Starita |first4=Lea |title=An Atlas of Variant Effects to understand the genome at nucleotide resolution |journal=Genome Biology |date=2023 |volume=24 |issue=1 |page=147 |doi=10.1186/s13059-023-02986-x |doi-access=free |pmid=37394429|pmc=10316620 }}</ref>