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Bioinformatics Approaches to Gain Insights into cis-Regulatory Motifs Involved in mRNA Localization.
Benoit Bouvrette, Louis Philip; Blanchette, Mathieu; Lécuyer, Eric.
Afiliação
  • Benoit Bouvrette LP; Institut de Recherches Cliniques de Montréal (IRCM), Montréal, QC, Canada.
  • Blanchette M; Département de Biochimie, Université de Montréal, Montréal, QC, Canada.
  • Lécuyer E; McGill School of Computer Science, McGill University, Montréal, QC, Canada.
Adv Exp Med Biol ; 1203: 165-194, 2019.
Article em En | MEDLINE | ID: mdl-31811635
ABSTRACT
Messenger RNA (mRNA) is a fundamental intermediate in the expression of proteins. As an integral part of this important process, protein production can be localized by the targeting of mRNA to a specific subcellular compartment. The subcellular destination of mRNA is suggested to be governed by a region of its primary sequence or secondary structure, which consequently dictates the recruitment of trans-acting factors, such as RNA-binding proteins or regulatory RNAs, to form a messenger ribonucleoprotein particle. This molecular ensemble is requisite for precise and spatiotemporal control of gene expression. In the context of RNA localization, the description of the binding preferences of an RNA-binding protein defines a motif, and one, or more, instance of a given motif is defined as a localization element (zip code). In this chapter, we first discuss the cis-regulatory motifs previously identified as mRNA localization elements. We then describe motif representation in terms of entropy and information content and offer an overview of motif databases and search algorithms. Finally, we provide an outline of the motif topology of asymmetrically localized mRNA molecules.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: RNA Mensageiro / Proteínas de Ligação a RNA / Biologia Computacional Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: RNA Mensageiro / Proteínas de Ligação a RNA / Biologia Computacional Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2019 Tipo de documento: Article