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RepeatModeler2 for automated genomic discovery of transposable element families
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RepeatModeler2 for automated genomic discovery of transposable element families
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Journal Article
RepeatModeler2 for automated genomic discovery of transposable element families
2020
Overview
The accelerating pace of genome sequencing throughout the tree of life is driving the need for improved unsupervised annotation of genome components such as transposable elements (TEs). Because the types and sequences of TEs are highly variable across species, automated TE discovery and annotation are challenging and timeconsuming tasks. A critical first step is the de novo identification and accurate compilation of sequence models representing all of the unique TE families dispersed in the genome. Here we introduce RepeatModeler2, a pipeline that greatly facilitates this process. This program brings substantial improvements over the original version of RepeatModeler, one of the most widely used tools for TE discovery. In particular, this version incorporates a module for structural discovery of complete long terminal repeat (LTR) retroelements, which are widespread in eukaryotic genomes but recalcitrant to automated identification because of their size and sequence complexity. We benchmarked RepeatModeler2 on three model species with diverse TE landscapes and high-quality, manually curated TE libraries: Drosophila melanogaster (fruit fly), Danio rerio (zebrafish), and Oryza sativa (rice). In these three species, RepeatModeler2 identified approximately 3 times more consensus sequences matching with >95% sequence identity and sequence coverage to the manually curated sequences than the original RepeatModeler. As expected, the greatest improvement is for LTR retroelements. Thus, RepeatModeler2 represents a valuable addition to the genome annotation toolkit that will enhance the identification and study of TEs in eukaryotic genome sequences. RepeatModeler2 is available as source code or a containerized package under an open license (https://github.com/Dfam-consortium/ RepeatModeler, http://www.repeatmasker.org/RepeatModeler/).
Publisher
National Academy of Sciences
Subject
