Population growth makes waves in the distribution of pairwise genetic differences. (original) (raw)
Journal Article
,
Search for other works by this author on:
Search for other works by this author on:
Navbar Search Filter Mobile Enter search term Search
Abstract
Episodes of population growth and decline leave characteristic signatures in the distribution of nucleotide (or restriction) site differences between pairs of individuals. These signatures appear in histograms showing the relative frequencies of pairs of individuals who differ by i sites, where i = 0, 1, .... In this distribution an episode of growth generates a wave that travels to the right, traversing 1 unit of the horizontal axis in each 1/2u generations, where u is the mutation rate. The smaller the initial population, the steeper will be the leading face of the wave. The larger the increase in population size, the smaller will be the distribution's vertical intercept. The implications of continued exponential growth are indistinguishable from those of a sudden burst of population growth Bottlenecks in population size also generate waves similar to those produced by a sudden expansion, but with elevated uppertail probabilities. Reductions in population size initially generate L-shaped distributions with high probability of identity, but these converge rapidly to a new equilibrium. In equilibrium populations the theoretical curves are free of waves. However, computer simulations of such populations generate empirical distributions with many peaks and little resemblance to the theory. On the other hand, agreement is better in the transient (nonequilibrium) case, where simulated empirical distributions typically exhibit waves very similar to those predicted by theory. Thus, waves in empirical distributions may be rich in information about the history of population dynamics.
This content is only available as a PDF.
Citations
Views
Altmetric
Metrics
Total Views 3,476
810 Pageviews
2,666 PDF Downloads
Since 12/1/2016
Month: | Total Views: |
---|---|
December 2016 | 5 |
January 2017 | 8 |
February 2017 | 71 |
March 2017 | 128 |
April 2017 | 75 |
May 2017 | 75 |
June 2017 | 42 |
July 2017 | 40 |
August 2017 | 48 |
September 2017 | 67 |
October 2017 | 59 |
November 2017 | 51 |
December 2017 | 49 |
January 2018 | 78 |
February 2018 | 76 |
March 2018 | 76 |
April 2018 | 84 |
May 2018 | 19 |
June 2018 | 16 |
July 2018 | 16 |
August 2018 | 13 |
September 2018 | 18 |
October 2018 | 19 |
November 2018 | 24 |
December 2018 | 19 |
January 2019 | 19 |
February 2019 | 16 |
March 2019 | 41 |
April 2019 | 33 |
May 2019 | 15 |
June 2019 | 24 |
July 2019 | 18 |
August 2019 | 19 |
September 2019 | 21 |
October 2019 | 11 |
November 2019 | 12 |
December 2019 | 13 |
January 2020 | 14 |
February 2020 | 13 |
March 2020 | 19 |
April 2020 | 16 |
May 2020 | 6 |
June 2020 | 15 |
July 2020 | 23 |
August 2020 | 26 |
September 2020 | 46 |
October 2020 | 28 |
November 2020 | 55 |
December 2020 | 27 |
January 2021 | 30 |
February 2021 | 20 |
March 2021 | 24 |
April 2021 | 43 |
May 2021 | 41 |
June 2021 | 29 |
July 2021 | 27 |
August 2021 | 34 |
September 2021 | 60 |
October 2021 | 55 |
November 2021 | 52 |
December 2021 | 44 |
January 2022 | 65 |
February 2022 | 36 |
March 2022 | 45 |
April 2022 | 64 |
May 2022 | 36 |
June 2022 | 37 |
July 2022 | 33 |
August 2022 | 30 |
September 2022 | 49 |
October 2022 | 63 |
November 2022 | 32 |
December 2022 | 25 |
January 2023 | 37 |
February 2023 | 34 |
March 2023 | 43 |
April 2023 | 38 |
May 2023 | 26 |
June 2023 | 40 |
July 2023 | 25 |
August 2023 | 27 |
September 2023 | 33 |
October 2023 | 31 |
November 2023 | 39 |
December 2023 | 20 |
January 2024 | 54 |
February 2024 | 53 |
March 2024 | 61 |
April 2024 | 48 |
May 2024 | 45 |
June 2024 | 34 |
July 2024 | 35 |
August 2024 | 27 |
September 2024 | 30 |
October 2024 | 16 |
×
Email alerts
Email alerts
Citing articles via
More from Oxford Academic