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TypeTE: a tool to genotype mobile element insertions from whole genome resequencing data
Author(s) -
Clément Goubert,
Jainy Thomas,
Lindsay M. Payer,
Jeffrey M. Kidd,
Julie Feusier,
W. Scott Watkins,
Kathleen H. Burns,
Lynn B. Jorde,
Cédric Feschotte
Publication year - 2020
Publication title -
nucleic acids research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/gkaa074
Subject(s) - biology , retrotransposon , genome , genetics , genotyping , alu element , genomics , population , genotype , haplotype , human genome , reference genome , computational biology , gene , transposable element , demography , sociology
Alu retrotransposons account for more than 10% of the human genome, and insertions of these elements create structural variants segregating in human populations. Such polymorphic Alus are powerful markers to understand population structure, and they represent variants that can greatly impact genome function, including gene expression. Accurate genotyping of Alus and other mobile elements has been challenging. Indeed, we found that Alu genotypes previously called for the 1000 Genomes Project are sometimes erroneous, which poses significant problems for phasing these insertions with other variants that comprise the haplotype. To ameliorate this issue, we introduce a new pipeline – TypeTE – which genotypes Alu insertions from whole-genome sequencing data. Starting from a list of polymorphic Alus, TypeTE identifies the hallmarks (poly-A tail and target site duplication) and orientation of Alu insertions using local re-assembly to reconstruct presence and absence alleles. Genotype likelihoods are then computed after re-mapping sequencing reads to the reconstructed alleles. Using a high-quality set of PCR-based genotyping of >200 loci, we show that TypeTE improves genotype accuracy from 83% to 92% in the 1000 Genomes dataset. TypeTE can be readily adapted to other retrotransposon families and brings a valuable toolbox addition for population genomics.

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