Your browser doesn't support javascript.
loading
RepeatModeler2 for automated genomic discovery of transposable element families.
Flynn, Jullien M; Hubley, Robert; Goubert, Clément; Rosen, Jeb; Clark, Andrew G; Feschotte, Cédric; Smit, Arian F.
Afiliação
  • Flynn JM; Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14853.
  • Hubley R; Institute for Systems Biology, Seattle, WA 98109.
  • Goubert C; Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14853.
  • Rosen J; Institute for Systems Biology, Seattle, WA 98109.
  • Clark AG; Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14853; ac347@cornell.edu cf458@cornell.edu asmit@systemsbiology.org.
  • Feschotte C; Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14853; ac347@cornell.edu cf458@cornell.edu asmit@systemsbiology.org.
  • Smit AF; Institute for Systems Biology, Seattle, WA 98109 ac347@cornell.edu cf458@cornell.edu asmit@systemsbiology.org.
Proc Natl Acad Sci U S A ; 117(17): 9451-9457, 2020 04 28.
Article em En | MEDLINE | ID: mdl-32300014
ABSTRACT
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 time-consuming 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/).
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Elementos de DNA Transponíveis / Genômica Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Elementos de DNA Transponíveis / Genômica Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Ano de publicação: 2020 Tipo de documento: Article