Movatterモバイル変換


[0]ホーム

URL:


Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
Thehttps:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

NIH NLM Logo
Log inShow account info
Access keysNCBI HomepageMyNCBI HomepageMain ContentMain Navigation
pubmed logo
Advanced Clipboard
User Guide

Full text links

Silverchair Information Systems full text link Silverchair Information Systems Free PMC article
Full text links

Actions

.2010 Feb;184(2):467-81.
doi: 10.1534/genetics.109.109009. Epub 2009 Nov 30.

Rate of adaptation in large sexual populations

Affiliations

Rate of adaptation in large sexual populations

R A Neher et al. Genetics.2010 Feb.

Abstract

Adaptation often involves the acquisition of a large number of genomic changes that arise as mutations in single individuals. In asexual populations, combinations of mutations can fix only when they arise in the same lineage, but for populations in which genetic information is exchanged, beneficial mutations can arise in different individuals and be combined later. In large populations, when the product of the population size N and the total beneficial mutation rate U(b) is large, many new beneficial alleles can be segregating in the population simultaneously. We calculate the rate of adaptation, v, in several models of such sexual populations and show that v is linear in NU(b) only in sufficiently small populations. In large populations, v increases much more slowly as log NU(b). The prefactor of this logarithm, however, increases as the square of the recombination rate. This acceleration of adaptation by recombination implies a strong evolutionary advantage of sex.

PubMed Disclaimer

Figures

F<sc>igure</sc> 1.—
Figure 1.—
A novel mutation needs to recombine onto fitter genetic backgrounds to become established and eventually fix. (A) The distribution in fitness of the population moves toward higher fitness with velocityv = σ2. The new mutation, illustrated by the black bars, has to switch backgrounds by recombination to keep up with the moving wave of the population fitness distribution. (B) Initially, the novel mutation is present on a single genetic background with fitnessX0, struggling not to go extinct. Recombination can transfer the mutated allele onto a new background,e.g., fromX0 toX1, and spawn a daughter clone that starts an independent struggle against extinction. The mutation establishes if at least one branch survives indefinitely. The complementary case of an unsuccessful mutation is shown: all branches die out. The probability of establishment,w(X,t), depends on the fitnessX of the genome in which the mutation arose and is a solution to Equation 2.
F<sc>igure</sc> 2.—
Figure 2.—
Fixation probabilities in recombining populations. (A) The mean fixation probability normalized to the value in the high recombination limit as a function ofr for three different genome sizesL (withs = 0.002,N = 20,000). The effective rate of beneficial mutationsNUb is shown in the inset (see main text). The scaled fixation probability in the simulation (solid lines) is calculated asv/2NUbs2 and compared to the analytic results for the scaled establishment probabilityPe(r, σ)/s (dashed lines). The latter are obtained through numerical solution of Equation 3, using σ2 observed in simulations. The agreement between simulations and the analytic approximation improves with increasingL,i.e., increasingNUb, as expected. (B) The scaled fixation probability as a function of the rescaled background fitnessx/σ (relative to the mean). The solid lines are simulation results forw(x)/2s usingL = 6400 andr = 0.512, 0.128, 0.064, and 0.032: the corresponding values of the key ratior/σ, which determines the shape ofw(x), are indicated. The dashed lines are predictions forw(x)/s obtained via numerical solutions of Equation 3. Note that the simulation data become noisy when the frequency ofx in the population is ∼1/N.
F<sc>igure</sc> 3.—
Figure 3.—
Asymptotics of the establishment probability. The fitness distributionP(x) of the population is shown in black, and a sketch of the establishment probability,w(x), is shown in red forformula image. At lowx,w(x) is small and depends sensitively on the recombination model; at intermediate σ <x < σΘ,w(x) increases sharply asformula image, modulated by a slowly varying function φ(x) that depends on the recombination model. At still largerx, beyond σΘ, the quadratic term in Equation 3 becomes important, forcingw(x) to saturate atxr. The width of the crossover region is of the order of σ/Θ.
See this image and copyright information in PMC

References

    1. Abramowitz, M., and I. A. Stegun, 1964. Handbook of Mathematical Functions With Formulas, Graphs, and Mathematical Tables. Dover, New York.
    1. Barton, N. H., 1995. a A general model for the evolution of recombination. Genet. Res. 65 123–145. - PubMed
    1. Barton, N. H., 1995. b Linkage and the limits to natural selection. Genetics 140 821–841. - PMC - PubMed
    1. Barton, N. H., and B. Charlesworth, 1998. Why sex and recombination? Science 281 1986–1990. - PubMed
    1. Barton, N. H., and S. P. Otto, 2005. Evolution of recombination due to random drift. Genetics 169 2353–2370. - PMC - PubMed

Publication types

MeSH terms

LinkOut - more resources

Full text links
Silverchair Information Systems full text link Silverchair Information Systems Free PMC article
Cite
Send To

NCBI Literature Resources

MeSHPMCBookshelfDisclaimer

The PubMed wordmark and PubMed logo are registered trademarks of the U.S. Department of Health and Human Services (HHS). Unauthorized use of these marks is strictly prohibited.


[8]ページ先頭

©2009-2025 Movatter.jp