MOTIVATION: Long terminal repeat (LTR) retrotransposons constitute a substantial fraction of most eukaryotic genomes and are believed to have a significant impact on genome structure and function. Conventional methods used to search for LTR retrotransposons in genome databases are labor intensive. We present an efficient, reliable and automated method to identify and analyze members of this important class of transposable elements. RESULTS: We have developed a new data-mining program, LTR_STRUC (LTR retrotransposon structure program) which identifies and automatically analyzes LTR retrotransposons in genome databases by searching for structural features characteristic of such elements. LTR_STRUC has significant advantages over conventional search methods in the case of LTR retrotransposon families having low sequence homology to known queries or families with atypical structure (e.g. non-autonomous elements lacking canonical retroviral ORFs) and is thus a discovery tool that complements established methods. LTR_STRUC finds LTR retrotransposons using an algorithm that encompasses a number of tasks that would otherwise have to be initiated individually by the user. For each LTR retrotransposon found, LTR_STRUC automatically generates an analysis of a variety of structural features of biological interest. AVAILABILITY: The LTR_STRUC program is currently available as a console application free of charge to academic users from the authors.
MOTIVATION: Long terminal repeat (LTR) retrotransposons constitute a substantial fraction of most eukaryotic genomes and are believed to have a significant impact on genome structure and function. Conventional methods used to search for LTR retrotransposons in genome databases are labor intensive. We present an efficient, reliable and automated method to identify and analyze members of this important class of transposable elements. RESULTS: We have developed a new data-mining program, LTR_STRUC (LTR retrotransposon structure program) which identifies and automatically analyzes LTR retrotransposons in genome databases by searching for structural features characteristic of such elements. LTR_STRUC has significant advantages over conventional search methods in the case of LTR retrotransposon families having low sequence homology to known queries or families with atypical structure (e.g. non-autonomous elements lacking canonical retroviral ORFs) and is thus a discovery tool that complements established methods. LTR_STRUC finds LTR retrotransposons using an algorithm that encompasses a number of tasks that would otherwise have to be initiated individually by the user. For each LTR retrotransposon found, LTR_STRUC automatically generates an analysis of a variety of structural features of biological interest. AVAILABILITY: The LTR_STRUC program is currently available as a console application free of charge to academic users from the authors.
Authors: François Sabot; Romain Guyot; Thomas Wicker; Nathalie Chantret; Bastien Laubin; Boulos Chalhoub; Philippe Leroy; Pierre Sourdille; Michel Bernard Journal: Mol Genet Genomics Date: 2005-10-11 Impact factor: 3.291
Authors: Adam Wawrzynski; Tom Ashfield; Nicolas W G Chen; Jafar Mammadov; Ashley Nguyen; Ram Podicheti; Steven B Cannon; Vincent Thareau; Carine Ameline-Torregrosa; Ethalinda Cannon; Ben Chacko; Arnaud Couloux; Anita Dalwani; Roxanne Denny; Shweta Deshpande; Ashley N Egan; Natasha Glover; Stacy Howell; Dan Ilut; Hongshing Lai; Sara Martin Del Campo; Michelle Metcalf; Majesta O'Bleness; Bernard E Pfeil; Milind B Ratnaparkhe; Sylvie Samain; Iryna Sanders; Béatrice Ségurens; Mireille Sévignac; Sue Sherman-Broyles; Dominic M Tucker; Jing Yi; Jeff J Doyle; Valérie Geffroy; Bruce A Roe; M A Saghai Maroof; Nevin D Young; Roger W Innes Journal: Plant Physiol Date: 2008-10-24 Impact factor: 8.340