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Mining hidden polymorphic sequence motifs from divergent plant helitrons
As a major driving force of genome evolution, transposons have been deviating from their original connotation as “junk” DNA ever since their important roles were revealed. The recently discovered Helitron transposons have been investigated in diverse eukaryotic genomes because of their remarkable ge...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4588551/ https://www.ncbi.nlm.nih.gov/pubmed/26442169 http://dx.doi.org/10.4161/21592543.2014.971635 |
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author | Xiong, Wenwei Du, Chunguang |
author_facet | Xiong, Wenwei Du, Chunguang |
author_sort | Xiong, Wenwei |
collection | PubMed |
description | As a major driving force of genome evolution, transposons have been deviating from their original connotation as “junk” DNA ever since their important roles were revealed. The recently discovered Helitron transposons have been investigated in diverse eukaryotic genomes because of their remarkable gene-capture ability and other features that are crucial to our current understanding of genome dynamics. Helitrons are not canonical transposons in that they do not end in inverted repeats or create target site duplications, which makes them difficult to identify. Previous methods mainly rely on sequence alignment of conserved Helitron termini or manual curation. The abundance of Helitrons in genomes is still underestimated. We developed an automated and generalized tool, HelitronScanner, that identified a plethora of divergent Helitrons in many plant genomes. A local combinational variable approach as the key component of HelitronScanner offers a more granular representation of conserved nucleotide combinations and therefore is more sensitive in finding divergent Helitrons. This commentary provides an in-depth view of the local combinational variable approach and its association with Helitron sequence patterns. Analysis of Helitron terminal sequences shows that the local combinational variable approach is an efficacious representation of nucleotide patterns imperceptible at a full-sequence level. |
format | Online Article Text |
id | pubmed-4588551 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
spelling | pubmed-45885512015-10-30 Mining hidden polymorphic sequence motifs from divergent plant helitrons Xiong, Wenwei Du, Chunguang Mob Genet Elements Commentary As a major driving force of genome evolution, transposons have been deviating from their original connotation as “junk” DNA ever since their important roles were revealed. The recently discovered Helitron transposons have been investigated in diverse eukaryotic genomes because of their remarkable gene-capture ability and other features that are crucial to our current understanding of genome dynamics. Helitrons are not canonical transposons in that they do not end in inverted repeats or create target site duplications, which makes them difficult to identify. Previous methods mainly rely on sequence alignment of conserved Helitron termini or manual curation. The abundance of Helitrons in genomes is still underestimated. We developed an automated and generalized tool, HelitronScanner, that identified a plethora of divergent Helitrons in many plant genomes. A local combinational variable approach as the key component of HelitronScanner offers a more granular representation of conserved nucleotide combinations and therefore is more sensitive in finding divergent Helitrons. This commentary provides an in-depth view of the local combinational variable approach and its association with Helitron sequence patterns. Analysis of Helitron terminal sequences shows that the local combinational variable approach is an efficacious representation of nucleotide patterns imperceptible at a full-sequence level. Taylor & Francis 2014-10-30 /pmc/articles/PMC4588551/ /pubmed/26442169 http://dx.doi.org/10.4161/21592543.2014.971635 Text en © 2014 The Author(s). Published with license by Taylor & Francis Group, LLC http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The moral rights of the named author(s) have been asserted. |
spellingShingle | Commentary Xiong, Wenwei Du, Chunguang Mining hidden polymorphic sequence motifs from divergent plant helitrons |
title | Mining hidden polymorphic sequence motifs from divergent plant helitrons |
title_full | Mining hidden polymorphic sequence motifs from divergent plant helitrons |
title_fullStr | Mining hidden polymorphic sequence motifs from divergent plant helitrons |
title_full_unstemmed | Mining hidden polymorphic sequence motifs from divergent plant helitrons |
title_short | Mining hidden polymorphic sequence motifs from divergent plant helitrons |
title_sort | mining hidden polymorphic sequence motifs from divergent plant helitrons |
topic | Commentary |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4588551/ https://www.ncbi.nlm.nih.gov/pubmed/26442169 http://dx.doi.org/10.4161/21592543.2014.971635 |
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