Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
21
pubmed:dateCreated
2009-12-16
pubmed:abstractText
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 chromosome 4 sequence of Mus musculus, separating them from truncated insertions and other repeats. Furthermore, we propose a work flow for the use of LTRdigest in de novo LTR retrotransposon classification and perform an exemplary de novo analysis on the Drosophila melanogaster genome as a proof of concept. Using a new method solely based on the annotations generated by LTRdigest, 518 potential LTR retrotransposons were automatically assigned to 62 candidate groups. Representative sequences from 41 of these 62 groups were matched to reference sequences with >80% global sequence similarity.
pubmed:commentsCorrections
http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-10556309, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-10827456, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-11577982, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-12584121, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-15003117, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-15186483, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-15892872, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-16093699, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-16819780, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-17024082, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-17064419, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-17134480, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-17363976, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-17407597, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-17485477, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-17636050, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-17895280, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-17932080, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-17984973, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-18039703, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-18194517, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-18694346, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-18818875, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-18948289, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-18984615, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-19033362, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-19106120, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-19226459, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-19349283, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-2231712, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-2543105, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-7265238, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-7541250, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-9023104, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-9343157, http://linkedlifedata.com/resource/pubmed/commentcorrection/19786494-9918945
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
1362-4962
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
37
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
7002-13
pubmed:dateRevised
2010-9-27
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Fine-grained annotation and classification of de novo predicted LTR retrotransposons.
pubmed:affiliation
Center for Bioinformatics, University of Hamburg, Bundesstrasse 43, 20146 Hamburg, Germany. steinbiss@zbh.uni-hamburg.de
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't