Bioinformatics and genomic analysis of transposable elements in eukaryotic genomes
Identifieur interne : 002585 ( Main/Exploration ); précédent : 002584; suivant : 002586Bioinformatics and genomic analysis of transposable elements in eukaryotic genomes
Auteurs : Mateusz Janicki [Canada] ; Rebecca Rooke [Canada] ; Guojun Yang [Canada]Source :
- Chromosome Research [ 0967-3849 ] ; 2011-08-01.
English descriptors
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Abstract
Abstract: A major portion of most eukaryotic genomes are transposable elements (TEs). During evolution, TEs have introduced profound changes to genome size, structure, and function. As integral parts of genomes, the dynamic presence of TEs will continue to be a major force in reshaping genomes. Early computational analyses of TEs in genome sequences focused on filtering out “junk” sequences to facilitate gene annotation. When the high abundance and diversity of TEs in eukaryotic genomes were recognized, these early efforts transformed into the systematic genome-wide categorization and classification of TEs. The availability of genomic sequence data reversed the classical genetic approaches to discovering new TE families and superfamilies. Curated TE databases and their accurate annotation of genome sequences in turn facilitated the studies on TEs in a number of frontiers including: (1) TE-mediated changes of genome size and structure, (2) the influence of TEs on genome and gene functions, (3) TE regulation by host, (4) the evolution of TEs and their population dynamics, and (5) genomic scale studies of TE activity. Bioinformatics and genomic approaches have become an integral part of large-scale studies on TEs to extract information with pure in silico analyses or to assist wet lab experimental studies. The current revolution in genome sequencing technology facilitates further progress in the existing frontiers of research and emergence of new initiatives. The rapid generation of large-sequence datasets at record low costs on a routine basis is challenging the computing industry on storage capacity and manipulation speed and the bioinformatics community for improvement in algorithms and their implementations.
Url:
DOI: 10.1007/s10577-011-9230-7
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