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      HelitronScanner uncovers a large overlooked cache of Helitron transposons in many plant genomes.

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          Abstract

          Transposons make up the bulk of eukaryotic genomes, but are difficult to annotate because they evolve rapidly. Most of the unannotated portion of sequenced genomes is probably made up of various divergent transposons that have yet to be categorized. Helitrons are unusual rolling circle eukaryotic transposons that often capture gene sequences, making them of considerable evolutionary importance. Unlike other DNA transposons, Helitrons do not end in inverted repeats or create target site duplications, so they are particularly challenging to identify. Here we present HelitronScanner, a two-layered local combinational variable (LCV) tool for generalized Helitron identification that represents a major improvement over previous identification programs based on DNA sequence or structure. HelitronScanner identified 64,654 Helitrons from a wide range of plant genomes in a highly automated way. We tested HelitronScanner's predictive ability in maize, a species with highly heterogeneous Helitron elements. LCV scores for the 5' and 3' termini of the predicted Helitrons provide a primary confidence level and element copy number provides a secondary one. Newly identified Helitrons were validated by PCR assays or by in silico comparative analysis of insertion site polymorphism among multiple accessions. Many new Helitrons were identified in model species, such as maize, rice, and Arabidopsis, and in a variety of organisms where Helitrons had not been reported previously to our knowledge, leading to a major upward reassessment of their abundance in plant genomes. HelitronScanner promises to be a valuable tool in future comparative and evolutionary studies of this major transposon superfamily.

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          Author and article information

          Journal
          Proc Natl Acad Sci U S A
          Proceedings of the National Academy of Sciences of the United States of America
          Proceedings of the National Academy of Sciences
          1091-6490
          0027-8424
          Jul 15 2014
          : 111
          : 28
          Affiliations
          [1 ] Department of Biology and Molecular Biology, Montclair State University, Montclair, NJ 07043;
          [2 ] Waksman Institute, Rutgers, the State University of New Jersey, Piscataway, NJ 08854;
          [3 ] National Maize Improvement Center, China Agricultural University, Beijing 100083, China; and.
          [4 ] Waksman Institute, Rutgers, the State University of New Jersey, Piscataway, NJ 08854;Department of Plant Biology, Rutgers, the State University of New Jersey, New Brunswick, NJ 08801 dooner@waksman.rutgers.edu duc@mail.montclair.edu.
          [5 ] Department of Biology and Molecular Biology, Montclair State University, Montclair, NJ 07043; dooner@waksman.rutgers.edu duc@mail.montclair.edu.
          Article
          1410068111
          10.1073/pnas.1410068111
          4104883
          24982153
          31ff5de6-21a4-4e67-a1bc-c1fe617d4afd
          History

          algorithm,bioinformatic analysis,computational tool,transposition

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