S Evan Staton1, John M Burke1. 1. Department of Genetics and Department of Plant Biology, University of Georgia, Athens, GA 30602, USA.
Abstract
MOTIVATION: Transposable elements (TEs) can be found in virtually all eukaryotic genomes and have the potential to produce evolutionary novelty. Despite the broad taxonomic distribution of TEs, the evolutionary history of these sequences is largely unknown for many taxa due to a lack of genomic resources and identification methods. Given that most TE annotation methods are designed to work on genome assemblies, we sought to develop a method to provide a fine-grained classification of TEs from DNA sequence reads. Here, we present a toolkit for the efficient annotation of TE families from low-coverage whole-genome shotgun (WGS) data, enabling the rapid identification of TEs in a large number of taxa. We compared our software, Transposome, with other approaches for annotating repeats from WGS data, and we show that it offers significant improvements in run time and produces more precise estimates of genomic repeat abundance. Transposome may also be used as a general toolkit for working with Next Generation Sequencing (NGS) data, and for constructing custom genome analysis pipelines. AVAILABILITY AND IMPLEMENTATION: The source code for Transposome is freely available (http://sestaton.github.io/Transposome), implemented in Perl and is supported on Linux.
MOTIVATION: Transposable elements (TEs) can be found in virtually all eukaryotic genomes and have the potential to produce evolutionary novelty. Despite the broad taxonomic distribution of TEs, the evolutionary history of these sequences is largely unknown for many taxa due to a lack of genomic resources and identification methods. Given that most TE annotation methods are designed to work on genome assemblies, we sought to develop a method to provide a fine-grained classification of TEs from DNA sequence reads. Here, we present a toolkit for the efficient annotation of TE families from low-coverage whole-genome shotgun (WGS) data, enabling the rapid identification of TEs in a large number of taxa. We compared our software, Transposome, with other approaches for annotating repeats from WGS data, and we show that it offers significant improvements in run time and produces more precise estimates of genomic repeat abundance. Transposome may also be used as a general toolkit for working with Next Generation Sequencing (NGS) data, and for constructing custom genome analysis pipelines. AVAILABILITY AND IMPLEMENTATION: The source code for Transposome is freely available (http://sestaton.github.io/Transposome), implemented in Perl and is supported on Linux.