We consider evolution of a large population, where fitness of each organism is defined by many phenotypical traits. These traits result from expression of many genes. Under some assumptions on  fitness we prove that such model organisms  are capable, to some extent, to recognize the fitness landscape. That fitness landscape learning sharply reduces the number of mutations needed for adaptation. Moreover, this learning increases phenotype robustness with respect to mutations, i.e., canalizes the phenotype.  We show that learning and canalization work only when evolution is gradual. Organisms can be adapted to  many constraints associated with a hard environment, if that environment becomes harder step by step. Our results explain why evolution can involve genetic changes of a relatively large effect and why the total number of changes are surprisingly small.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6798318PMC
http://dx.doi.org/10.12688/f1000research.18575.2DOI Listing

Publication Analysis

Top Keywords

fitness landscape
8
landscape learning
8
adaptation fitness
4
learning
4
learning fast
4
evolution
4
fast evolution
4
evolution consider
4
consider evolution
4
evolution large
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!