On the classification of long non-coding RNAs

Handle URI:
http://hdl.handle.net/10754/566007
Title:
On the classification of long non-coding RNAs
Authors:
Ma, Lina; Bajic, Vladimir B. ( 0000-0001-5435-4750 ) ; Zhang, Zhang
Abstract:
Long non-coding RNAs (lncRNAs) have been found to perform various functions in a wide variety of important biological processes. To make easier interpretation of lncRNA functionality and conduct deep mining on these transcribed sequences, it is convenient to classify lncRNAs into different groups. Here, we summarize classification methods of lncRNAs according to their four major features, namely, genomic location and context, effect exerted on DNA sequences, mechanism of functioning and their targeting mechanism. In combination with the presently available function annotations, we explore potential relationships between different classification categories, and generalize and compare biological features of different lncRNAs within each category. Finally, we present our view on potential further studies. We believe that the classifications of lncRNAs as indicated above are of fundamental importance for lncRNA studies, helpful for further investigation of specific lncRNAs, for formulation of new hypothesis based on different features of lncRNA and for exploration of the underlying lncRNA functional mechanisms. © 2013 Landes Bioscience.
KAUST Department:
Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Publisher:
Informa UK Limited
Journal:
RNA Biology
Issue Date:
Jun-2013
DOI:
10.4161/rna.24604
PubMed ID:
23696037
PubMed Central ID:
PMC4111732
Type:
Article
ISSN:
15476286
Sponsors:
We thank Hao Wu and Gang Wu for their valuable comments on this manuscript. This work was supported by grants from National Natural Science Foundation of China (Grant No. 31200978 to L.M.), King Abdullah University of Science and Technology research funds (to V.B.B.), the "100-Talent Program" of Chinese Academy of Sciences (Y1SLXb1365 to Z.Z.) and National Programs for High Technology Research and Development (863 Program; Grant No. 2012AA020409 to Z.Z.), the Ministry of Science and Technology of the People's Republic of China.
Appears in Collections:
Articles; Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorMa, Linaen
dc.contributor.authorBajic, Vladimir B.en
dc.contributor.authorZhang, Zhangen
dc.date.accessioned2015-08-12T08:59:08Zen
dc.date.available2015-08-12T08:59:08Zen
dc.date.issued2013-06en
dc.identifier.issn15476286en
dc.identifier.pmid23696037en
dc.identifier.doi10.4161/rna.24604en
dc.identifier.urihttp://hdl.handle.net/10754/566007en
dc.description.abstractLong non-coding RNAs (lncRNAs) have been found to perform various functions in a wide variety of important biological processes. To make easier interpretation of lncRNA functionality and conduct deep mining on these transcribed sequences, it is convenient to classify lncRNAs into different groups. Here, we summarize classification methods of lncRNAs according to their four major features, namely, genomic location and context, effect exerted on DNA sequences, mechanism of functioning and their targeting mechanism. In combination with the presently available function annotations, we explore potential relationships between different classification categories, and generalize and compare biological features of different lncRNAs within each category. Finally, we present our view on potential further studies. We believe that the classifications of lncRNAs as indicated above are of fundamental importance for lncRNA studies, helpful for further investigation of specific lncRNAs, for formulation of new hypothesis based on different features of lncRNA and for exploration of the underlying lncRNA functional mechanisms. © 2013 Landes Bioscience.en
dc.description.sponsorshipWe thank Hao Wu and Gang Wu for their valuable comments on this manuscript. This work was supported by grants from National Natural Science Foundation of China (Grant No. 31200978 to L.M.), King Abdullah University of Science and Technology research funds (to V.B.B.), the "100-Talent Program" of Chinese Academy of Sciences (Y1SLXb1365 to Z.Z.) and National Programs for High Technology Research and Development (863 Program; Grant No. 2012AA020409 to Z.Z.), the Ministry of Science and Technology of the People's Republic of China.en
dc.publisherInforma UK Limiteden
dc.subjectlncRNAen
dc.subjectlncRNA classificationen
dc.subjectLong non-coding RNAen
dc.subjectRNA transcriptsen
dc.titleOn the classification of long non-coding RNAsen
dc.typeArticleen
dc.contributor.departmentComputational Bioscience Research Center (CBRC)en
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalRNA Biologyen
dc.identifier.pmcidPMC4111732en
dc.contributor.institutionCAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, Chinaen
kaust.authorBajic, Vladimir B.en

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