A maximum-likelihood approach to estimating the insertion frequencies of transposable elements from population sequencing data

Abstract

Transposable elements (TEs) contribute to a large fraction of the expansion of many eukaryotic genomes due to the capability of TEs duplicating themselves through transposition. A first step to understanding the roles of TEs in a eukaryotic genome is to characterize the population-wide variation of TE insertions in the species. Here, we present a maximum-likelihood (ML) method for estimating allele frequencies and detecting selection on TE insertions in a diploid population, based on the genotypes at TE insertion sites detected in multiple individuals sampled from the population using paired-end (PE) sequencing reads. Tests of the method on simulated data show that it can accurately estimate the allele frequencies of TE insertions even when the PE sequencing is conducted at a relatively low coverage (= 5X). The method can also detect TE insertions under strong selection, and the detection ability increases with sample size in a population, although a substantial fraction of actual TE insertions under selection may be undetected. Application of the ML method to genomic sequencing data collected from a natural Daphnia pulex population shows that, on the one hand, most (> 90 ) TE insertions present in the reference D. pulex genome are either fixed or nearly fixed (with allele frequencies > 0.95); on the other hand, among the non-reference TE insertions (i.e., those detected in some individuals in the population but absent from the reference genome), the majority (> 70 ) are still at low frequencies (< 0.1). Finally, we detected a substantial fraction (~9 ) of non-reference TE insertions under selection.

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Document Details

Document Type
Technical Report
Publication Date
Aug 07, 2018
Accession Number
AD1069873

Entities

People

  • Haixu Tang
  • Michael Lynch
  • Rebekah Rogers
  • Wazim M. Ismail
  • Xiaoqian Jiang

Organizations

  • Indiana University

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Algorithms
  • Biology
  • Computational Biology
  • Computational Science
  • Computer Programs
  • Computer Simulations
  • Equations
  • Frequency
  • Genes
  • Genetics
  • Genomics
  • Genotypes
  • Molecular Biology
  • Personal Information Managers
  • Population Genetics
  • Probability
  • Simulations

Fields of Study

  • Biology

Readers

  • Aerospace Test and Evaluation
  • Molecular Genetics
  • Regression Analysis.