Article

Multi-disciplinary methods to define RNA-protein interactions and regulatory networks.

Howard Hughes Medical Institute and Laboratory for RNA Molecular Biology, The Rockefeller University, 1230 York Avenue, New York, NY, 10065, United States.
Current opinion in genetics & development (Impact Factor: 8.99). 02/2013; DOI: 10.1016/j.gde.2013.01.003
Source: PubMed

ABSTRACT The advent of high-throughput technologies including deep-sequencing and protein mass spectrometry is facilitating the acquisition of large and precise data sets toward the definition of post-transcriptional regulatory networks. While early studies that investigated specific RNA-protein interactions in isolation laid the foundation for our understanding of the existence of molecular machines to assemble and process RNAs, there is a more recent appreciation of the importance of individual RNA-protein interactions that contribute to post-transcriptional gene regulation. The multitude of RNA-binding proteins (RBPs) and their many RNA targets has only been captured experimentally in recent times. In this review, we will examine current multidisciplinary approaches toward elucidating RNA-protein networks and their regulation.

0 Bookmarks
 · 
100 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: RNA-binding proteins (RBPs) are effectors and regulators of posttranscriptional gene regulation (PTGR). RBPs regulate stability, maturation, and turnover of all RNAs, often binding thousands of targets at many sites. The importance of RBPs is underscored by their dysregulation or mutations causing a variety of developmental and neurological diseases. This chapter globally discusses human RBPs and provides a brief introduction to their identification and RNA targets. We review RBPs based on common structural RNA-binding domains, study their evolutionary conservation and expression, and summarize disease associations of different RBP classes.
    Advances in Experimental Medicine and Biology 01/2014; 825:1-55. · 2.01 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The recent explosion of high-throughput sequencing methods applied to RNA molecules is allowing us to go beyond the description of sequence variants and their relative abundances, as measured by RNA-seq. We can now probe for RNA engagement in polysomes, for ribosomes, RNA binding proteins and microRNAs binding sites, for RNA secondary structure and for RNA methylation. These descriptors produce a steadily growing multidimensional array of positional information on RNA sequences, whose effective integration only would bring to decipher the regulatory interplay occurring between proteins, RNAs and their modifications on the transcriptome. This interplay ultimately dictates the degree of mRNA availability to translation, and thus the occurrence of cell phenotypes. However, several issues in data presentation are slowing down effective integration. A standardization effort for new dataset types produced should be urgently undertaken to solve these issues. Providing uniformed experimental details along with datasets processed to be directly usable and employing shared formats would greatly simplify integration efforts, strengthening hypotheses stemming from correlative observations and eventually bringing to mechanistic understanding.
    Frontiers in Cell and Developmental Biology 07/2014; 2(39).
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: RNA-binding proteins (RBPs) are at the core of post-transcriptional regulation and thus of gene expression control at the RNA level. One of the principal challenges in the field of gene expression regulation is to understand RBPs mechanism of action. As a result of recent evolution of experimental techniques, it is now possible to obtain the RNA regions recognized by RBPs on a transcriptome-wide scale. In fact, CLIP-seq protocols use the joint action of CLIP, crosslinking immunoprecipitation, and high-throughput sequencing to recover the transcriptome-wide set of interaction regions for a particular protein. Nevertheless, computational methods are necessary to process CLIP-seq experimental data and are a key to advancement in the understanding of gene regulatory mechanisms. Considering the importance of computational methods in this area, we present a review of the current status of computational approaches used and proposed for CLIP-seq data.
    Bioinformatics and biology insights 01/2014; 8:199-207.

Full-text

Download
120 Downloads
Available from
May 22, 2014