ArticleGenetics2006
Cryptic genetic variation is enriched for potential adaptations.
Article in Genetics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers.
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Who cites it
65 citing papers in PubMed, 128 citations in OpenAlex.
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- Evolution in the weak-mutation limit: Stasis periods punctuated by fast transitions between saddle points on the fitness landscape.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
5 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cryptic genetic variation accumulates under weakened selection and has been proposed as a source of evolutionary innovations. Weakened selection may, however, also lead to the accumulation of strongly deleterious or lethal alleles, swamping the effect of any potentially adaptive alleles when they are revealed. Here I model variation that is partially shielded from selection, assuming that unconditionally deleterious variation is more strongly deleterious than variation that is potentially adaptive in a future environment. I find that cryptic genetic variation can be substantially enriched for potential adaptations under a broad range of realistic parameter values, including those applicable to alternative splices and readthrough products generated by the yeast prion [PSI+]. This enrichment is dramatically stronger when multiple simultaneous changes are required to generate a potentially adaptive phenotype. Cryptic genetic variation is likely to be an effective source of useful adaptations at a time of environmental change, relative to an equivalent source of variation that has not spent time in a hidden state.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.