Rsite: a computational method to identify the functional sites of noncoding RNAs

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Abstract

There is an increasing demand for identifying the functional sites of noncoding RNAs (ncRNAs). Here we introduce a tertiary-structure based computational approach, Rsite, which first calculates the Euclidean distances between each nucleotide and all the other nucleotides in a RNA molecule and then determines the nucleotides that are the extreme points in the distance curve as the functional sites. By analyzing two ncRNAs, tRNA (Lys) and Diels-Alder ribozyme, we demonstrated the efficiency of Rsite. As a result, Rsite recognized all of the known functional sites of the two ncRNAs, suggesting that Rsite could be a potentially useful tool for discovering the functional sites of ncRNAs. The source codes and data sets of Rsite are available at http://www.cuilab.cn/rsite.

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Global identification of human transcribed sequences with genome tiling arrays.

Paul Bertone, Viktor Stolc, Thomas E Royce … (2004)

Elucidating the transcribed regions of the genome constitutes a fundamental aspect of human biology, yet this remains an outstanding problem. To comprehensively identify coding sequences, we constructed a series of high-density oligonucleotide tiling arrays representing sense and antisense strands of the entire nonrepetitive sequence of the human genome. Transcribed sequences were located across the genome via hybridization to complementary DNA samples, reverse-transcribed from polyadenylated RNA obtained from human liver tissue. In addition to identifying many known and predicted genes, we found 10,595 transcribed sequences not detected by other methods. A large fraction of these are located in intergenic regions distal from previously annotated genes and exhibit significant homology to other mammalian proteins.

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Network analysis of protein structures identifies functional residues.

Gil Amitai, Arye Shemesh, Einat Sitbon … (2004)

Identifying active site residues strictly from protein three-dimensional structure is a difficult task, especially for proteins that have few or no homologues. We transformed protein structures into residue interaction graphs (RIGs), where amino acid residues are graph nodes and their interactions with each other are the graph edges. We found that active site, ligand-binding and evolutionary conserved residues, typically have high closeness values. Residues with high closeness values interact directly or by a few intermediates with all other residues of the protein. Combining closeness and surface accessibility identified active site residues in 70% of 178 representative structures. Detailed structural analysis of specific enzymes also located other types of functional residues. These include the substrate binding sites of acetylcholinesterases and subtilisin, and the regions whose structural changes activate MAP kinase and glycogen phosphorylase. Our approach uses single protein structures, and does not rely on sequence conservation, comparison to other similar structures or any prior knowledge. Residue closeness is distinct from various sequence and structure measures and can thus complement them in identifying key protein residues. Closeness integrates the effect of the entire protein on single residues. Such natural structural design may be evolutionary maintained to preserve interaction redundancy and contribute to optimal setting of functional sites.

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Long noncoding RNAs in cardiac development and pathophysiology.

John S. Mattick, Richard Harvey, Nicole Schonrock (2012)

Heart function requires sophisticated regulatory networks to orchestrate organ development, physiological responses, and environmental adaptation. Until recently, it was thought that these regulatory networks are composed solely of protein-mediated transcriptional control and signaling systems; consequently, it was thought that cardiac disease involves perturbation of these systems. However, it is becoming evident that RNA, long considered to function primarily as the platform for protein production, may in fact play a major role in most, if not all, aspects of gene regulation, especially the epigenetic processes that underpin organogenesis. These include not only well-validated classes of regulatory RNAs, such as microRNAs, but also tens of thousands of long noncoding RNAs that are differentially expressed across the entire genome of humans and other animals. Here, we review this emerging landscape, summarizing what is known about their functions and their role in cardiac biology, and provide a toolkit to assist in exploring this previously hidden layer of gene regulation that may underpin heart adaptation and complex heart diseases.

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Author and article information

Journal

Journal ID (nlm-ta): Sci Rep

Journal ID (iso-abbrev): Sci Rep

Title: Scientific Reports

Publisher: Nature Publishing Group

ISSN (Electronic): 2045-2322

Publication date (Electronic): 17 March 2015

Publication date Collection: 2015

Volume: 5

Electronic Location Identifier: 9179

Affiliations

[1 ]Department of Biomedical Informatics, MOE Key Lab of Cardiovascular Sciences, School of Basic Medical Sciences, Peking University , 38 xueyuan Rd, Beijing. 100191, China

[2 ]Lab of Translational Biomedicine Informatics, School of Computer Science and Engineering, Hebei University of Technology , 5340 Xiping Rd, Tianjin. 300401, China

Author notes

[a ] cuiqinghua@ 123456bjmu.edu.cn

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Publisher Item ID: srep09179

DOI: 10.1038/srep09179

PMC ID: 4361870

PubMed ID: 25776805

SO-VID: a8caedbe-53b9-4fbc-aeb8-f29c37aae552

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Rsite: a computational method to identify the functional sites of noncoding RNAs

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Computational Communication Research

Most cited references 11

Global identification of human transcribed sequences with genome tiling arrays.

Network analysis of protein structures identifies functional residues.

Long noncoding RNAs in cardiac development and pathophysiology.

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