Evidence map›Paper›PMID 21535899›Full record

ArticleBMC bioinformatics2011

An automated homology-based approach for identifying transposable elements.

Ryan C Kennedy, Maria F Unger, Scott Christley, Frank H Collins, Gregory R Madey

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.2field-weighted citation impact, top 22% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 40 citations in OpenAlex.

  1. Review
  2. Article
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  4. Review
  5. Finding and Characterizing Repeats in Plant Genomes.Methods in molecular biology (Clifton, N.J.) · 2022
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  11. FishTEDB: a collective database of transposable elements identified in the complete genomes of fish.Database : the journal of biological databases and curation · 2018
    Article
  12. Article
  13. Article
  14. Draft genome of the scabies mite.Parasites & vectors · 2015
    Article
  15. Article
  16. XS: a FASTQ read simulator.BMC research notes · 2014
    Article
  17. Article
  18. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Ryan C KennedyDepartment of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA. Ryan.C.Kennedy@alumni.nd.edu
Maria F Unger
Scott Christley
Frank H Collins
Gregory R Madey
University of Notre Dame · USUniversity of Chicago · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTransposable elements (TEs) are mobile sequences found in nearly all eukaryotic genomes. They have the ability to move and replicate within a genome, often influencing genome evolution and gene expression. The identification of TEs is an important part of every genome project. The number of sequenced genomes is rapidly rising, and the need to identify TEs within them is also growing. The ability to do this automatically and effectively in a manner similar to the methods used for genes is of increasing importance. There exist many difficulties in identifying TEs, including their tendency to degrade over time and that many do not adhere to a conserved structure. In this work, we describe a homology-based approach for the automatic identification of high-quality consensus TEs, aimed for use in the analysis of newly sequenced genomes.

resultsWe describe a homology-based approach for the automatic identification of TEs in genomes. Our modular approach is dependent on a thorough and high-quality library of representative TEs. The implementation of the approach, named TESeeker, is BLAST-based, but also makes use of the CAP3 assembly program and the ClustalW2 multiple sequence alignment tool, as well as numerous BioPerl scripts. We apply our approach to newly sequenced genomes and successfully identify consensus TEs that are up to 99% identical to manually annotated TEs.

conclusionsWhile TEs are known to be a major force in the evolution of genomes, the automatic identification of TEs in genomes is far from mature. In particular, there is a lack of automated homology-based approaches that produce high-quality TEs. Our approach is able to generate high-quality consensus TE sequences automatically, requiring the user to only provide a few basic parameters. This approach is intentionally modular, allowing researchers to use components separately or iteratively. Our approach is most effective for TEs with intact reading frames. The implementation, TESeeker, is available for download as a virtual appliance, while the library of representative TEs is available as a separate download.

Indexed as

DNA Transposable ElementsGenomeSequence Homology, Nucleic AcidAnimalsBase SequenceConserved SequenceEukaryotaGene LibraryHumansDNA Transposable Elements

Identifiers

PMID21535899
PMCPMC3107183
OpenAlexW2155308032

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.