Haldane's sieve
Haldane's sieve is a concept in population genetics named after the British geneticist J. B. S. Haldane. It refers to the fact that dominant advantageous alleles are more likely to fix in the population than recessive alleles.[1] Haldane's sieve is particularly relevant in situations where the effects of natural selection are strong and the beneficial mutations have a significant impact on an organism's fitness.
According to Haldane's sieve, when a new advantageous mutation arises in a population, it initially occurs as single copy (de novo mutations), borne by an heterozygous individual. This way, genetic dominance is important to estimate the fate of new mutations, that is, if new mutations are going to fix or go extinct. Dominant alleles are more readily exposed to directional selection since the moment they are rare, and thus they are more likely to fix as a result of a "hard sweep". The term "sieve" in Haldane's sieve metaphorically represents this filtering effect of natural selection.
When adaptation stem from the species pool of standing genetic variation, "soft sweep", the rationale does not apply, because the allele is no longer rare in the beginning of the sweep. In fact, recessive alleles are more likely to sweep than dominant sweeps when alleles are previously maintained in the population.[2]
Haldane's sieve has important implications for understanding the dynamics of adaptation and evolution in diploid populations. It highlights the role of natural selection in driving genetic changes in the presence of genetic dominance.
References
- Haldane, J. B. S. (1927). "A Mathematical Theory of Natural and Artificial Selection, Part V: Selection and Mutation". Mathematical Proceedings of the Cambridge Philosophical Society. 23 (7): 838–844. doi:10.1017/S0305004100015644. ISSN 0305-0041.
- Orr, H Allen; Betancourt, Andrea J (2001-02-01). "Haldane's Sieve and Adaptation From the Standing Genetic Variation". Genetics. 157 (2): 875–884. doi:10.1093/genetics/157.2.875. ISSN 1943-2631. PMC 1461537. PMID 11157004.