title: Mining hidden polymorphic sequence motifs from divergent planthelitrons.
abstract: 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 discoveredHelitrontransposons 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.Helitronsare 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 conservedHelitrontermini or manual curation. The abundance ofHelitronsin genomes is still underestimated. We developed an automated and generalized tool, HelitronScanner, that identified a plethora of divergentHelitronsin 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 divergentHelitrons. This commentary provides an in-depth view of the local combinational variable approach and its association withHelitronsequence patterns. Analysis ofHelitronterminal sequences shows that the local combinational variable approach is an efficacious representation of nucleotide patterns imperceptible at a full-sequence level.
authors.affiliation: Department of Biology and Molecular Biology; Montclair State University ; Montclair, NJ USA.
authors.forename: Wenwei
authors.initials: W
authors.lastname: Xiong
authors.affiliation: Department of Biology and Molecular Biology; Montclair State University ; Montclair, NJ USA.
authors.forename: Chunguang
authors.initials: C
authors.lastname: Du
keywords: Helitron; algorithm; bioinformatic analysis; local combinational variable; sequence pattern