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United States Department of Agriculture

Agricultural Research Service

Research Project: FUNCTIONAL GENOMICS OF CEREAL DISEASE DEFENSE Title: TEnest 2.0: Computational annotation and visualization of nested transposable elements

Authors
item Kronmiller, Brent -
item Wise, Roger

Submitted to: Methods in Molecular Biology
Publication Type: Book / Chapter
Publication Acceptance Date: August 9, 2012
Publication Date: August 14, 2013
Citation: Kronmiller, B.A., Wise, R.P. 2013. TEnest 2.0: Computational annotation and visualization of nested transposable elements. In: Peterson, T., editor. Methods in Molecular Biology. New York, NY: Springer. p. 305-320.

Technical Abstract: Grass genomes are highly repetitive, for example, Oryza sativa (rice) contains 35% repeat sequences, Zea mays (maize) comprise 75%, and Triticum aestivum (wheat) includes approximately 80%. Most of these repeats occur as abundant transposable elements (TE), which present unique challenges to sequence, assemble, and annotate genomes. Multiple copies of long terminal repeat (LTR) retrotransposons cause regions of the genome to collapse during sequence assembly. In addition to hindering assembly, TEs can directly cause problems with gene annotation. Clusters of TEs also contain protein-encoding genes, and if not correctly masked, they will be identified by gene finding software, further complicating annotation. Hence, accurate assembly is crucial for gene annotation. We present TEnest v2.0. TEnest computationally annotates and chronologically displays nested transposable elements. Utilizing organism specific TE databases as a reference for reconstructing degraded TEs to their ancestral state, annotation of repeats is accomplished by iterative sequence alignment. Subsequently, a graphical display of the chronological nesting structure and a tab delimited text file of the quantitative data is the output, facilitating interpretation of genome structure in higher eukaryotes. Both a downloadable linux command line version and web versions of TEnest are available at www.wiselab.org and www.PlantGDB.org, respectively.

Last Modified: 12/25/2014
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