Editing Evolvability (section)

{{Short description|Capacity of a system for adaptive evolution}}
{{Use mdy dates |date=September 2017}}
'''Evolvability''' is defined as the capacity of a system for [[Adaptation|adaptive evolution]]. Evolvability is the ability of a population of organisms to not merely generate [[genetic diversity]], but to generate ''[[adaptation |adaptive]]'' genetic diversity, and thereby evolve through [[natural selection]].<ref>{{cite journal | vauthors = Colegrave N, Collins S | title = Experimental evolution: experimental evolution and evolvability | journal = Heredity | volume = 100 | issue = 5 | pages = 464–70 | date = May 2008 | pmid = 18212804 | doi = 10.1038/sj.hdy.6801095 | doi-access = free }}</ref><ref>{{cite journal | vauthors = Kirschner M, Gerhart J | title = Evolvability | journal = Proceedings of the National Academy of Sciences of the United States of America | volume = 95 | issue = 15 | pages = 8420–7 | date = July 1998 | pmid = 9671692 | pmc = 33871 | doi = 10.1073/pnas.95.15.8420 | bibcode = 1998PNAS...95.8420K | doi-access = free }}</ref><ref name="Altenberg 1994">{{cite book |doi=10.1007/3-540-59046-3_11 | last = Altenberg | first = Lee | title = Evolution and Biocomputation | name-list-style = vanc |chapter=Genome growth and the evolution of the genotype–phenotype map |volume=899 |pages=205–259 |year=1995|series=Lecture Notes in Computer Science |isbn=978-3-540-59046-0 | citeseerx = 10.1.1.493.6534 }}</ref>

In order for a biological organism to evolve by natural selection, there must be a certain minimum probability that new, heritable variants are beneficial. Random [[mutation]]s, unless they occur in [[Non-coding DNA|DNA sequences with no function]], are expected to be mostly detrimental. Beneficial mutations are always rare, but if they are too rare, then [[adaptation]] cannot occur. Early failed efforts to evolve computer programs by random mutation and selection<ref>{{cite journal | vauthors = Friedberg RM |title=A Learning Machine: Part I &#124; |journal=IBM Journal of Research and Development |volume=2 |issue=1 |pages=2–13 |year=1958 |doi=10.1147/rd.21.0002}}</ref> showed that evolvability is not a given, but depends on the representation of the program as a data structure, because this determines how changes in the program map to changes in its behavior.<ref>{{cite journal |editor= Kinnear, Kenneth | last = Altenberg | first = Lee | name-list-style = vanc |title=The evolution of evolvability in genetic programming |url=http://dynamics.org/Altenberg/PAPERS/EEGP/ |journal=Advances in Genetic Programming |pages=47–74 |year=1994}}</ref> Analogously, the evolvability of organisms depends on their [[Genetic architecture|genotype–phenotype]] map.<ref>{{cite journal | vauthors = Wagner GP, Altenberg L | title = Perspective: Complex adaptations and the evolution of evolvability | journal = Evolution; International Journal of Organic Evolution | volume = 50 | issue = 3 | pages = 967–976 | date = June 1996 | pmid = 28565291 | doi = 10.1111/j.1558-5646.1996.tb02339.x | jstor = 2410639 | s2cid = 21040413 | doi-access = free }}</ref><ref name="Bianco-2022">{{cite journal | last=Bianco | first=Simone | title=Artificial Intelligence: Bioengineers' Ultimate Best Friend | journal=[[GEN Biotechnology]] | publisher=[[Mary Ann Liebert]] | volume=1 | issue=2 | date=2022-04-01 | issn=2768-1572 | doi=10.1089/genbio.2022.29027.sbi | pages=140–141 | s2cid=248313305}}</ref><ref>{{cite journal | vauthors = Vaishnav ED, de Boer CG, Molinet J, Yassour M, Fan L, Adiconis X, Thompson DA, Levine JZ, Cubillos FA, Regev A  | title = The evolution, evolvability and engineering of gene regulatory DNA | journal = Nature | volume = 603 | issue = 7901 | pages = 455–463 | date = March 2022 | pmid = 35264797 | doi = 10.1038/s41586-022-04506-6| pmc = 8934302 | bibcode = 2022Natur.603..455V }}</ref> This means that [[genome]]s are structured in ways that make beneficial changes more likely. This has been taken as evidence that evolution has created fitter populations of organisms that are better able to evolve.