Fine-grained annotation and classification of de novo predicted LTR retrotransposons.

ABSTRACT: Long terminal repeat (LTR) retrotransposons and endogenous retroviruses (ERVs) are transposable elements in eukaryotic genomes well suited for computational identification. De novo identification tools determine the position of potential LTR retrotransposon or ERV insertions in genomic sequences. For further analysis, it is desirable to obtain an annotation of the internal structure of such candidates. This article presents LTRdigest, a novel software tool for automated annotation of internal features of putative LTR retrotransposons. It uses local alignment and hidden Markov model-based algorithms to detect retrotransposon-associated protein domains as well as primer binding sites and polypurine tracts. As an example, we used LTRdigest results to identify 88 (near) full-length ERVs in the

SUBMITTER: Steinbiss S 

PROVIDER: S-EPMC2790888 | biostudies-literature | 2009 Nov

REPOSITORIES: biostudies-literature