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Controlling for Variable Transposition Rate with an Age-Adjusted Site Frequency Spectrum.

Robert Horvath1, Mitra Menon1,2, Michelle Stitzer3

  • 1Department of Evolution and Ecology, University of California, Davis, USA.

Genome Biology and Evolution
|February 1, 2022
PubMed
Summary

Transposable elements (TEs) can evolve differently than expected, as bursts of transposition can skew frequency spectrum analysis. An age-adjusted site frequency spectrum (SFS) method helps accurately detect selection on TEs, even after bursts.

Keywords:
TE burstallele ageselectionsite frequency spectrumtransposable elementstransposition rate change

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Area of Science:

  • Genomics
  • Evolutionary Biology
  • Population Genetics

Background:

  • Transposable elements (TEs) play a significant role in eukaryotic genome evolution.
  • Analyzing the site frequency spectrum (SFS) is a common method to study selection on TEs.
  • Standard SFS models may be inaccurate for TEs due to non-clock-like transposition patterns, such as bursts.

Purpose of the Study:

  • To investigate the impact of transposition bursts on TE frequency distributions and age-allele frequency correlations.
  • To develop a novel method for more accurately assessing selection on TEs.
  • To improve the reliability of identifying selective constraints on TEs.

Main Methods:

  • Investigated the effects of transposition bursts on TE frequency distributions.
  • Developed an age-adjusted SFS method.
  • Compared age-adjusted SFS with standard SFS for TEs and neutral polymorphisms.

Main Results:

  • Transposition bursts can inflate low-frequency TE categories, mimicking purifying selection.
  • The proposed age-adjusted SFS minimizes false inferences of selective constraint.
  • The method is robust to demographic changes and identifies weak selection on TEs after bursts.

Conclusions:

  • Transposition bursts significantly affect TE frequency spectra, challenging standard analyses.
  • The age-adjusted SFS provides a more reliable tool for detecting selection on TEs.
  • This approach enhances the understanding of TE evolution and selection without assuming constant transposition rates.