LincRNAs: Systemic Computational Identification and Functional Exploration

Author(s): Hanyang Hu, Kitchener D. Wilson, Shan Zhong, Chunjiang He.

Journal Name: Current Bioinformatics

Volume 12 , Issue 1 , 2017

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Graphical Abstract:


Background: The mammalian genome is pervasively transcribed and produces a large number of non-coding products compared to protein-coding genes. One novel sub-class of non-coding RNAs, long intergenic non-coding RNAs (lincRNAs), has been identified in mammalian genomes and is thought to play multiple roles in gene regulation and other cellular processes, and even human disease.

Objective: Here, we describe the most up-to-date computational and experimental methods for identifying genome-wide mammalian lincRNAs from multiple high-throughput sequencing data sets, as well as the subsequent large scale functional prediction and verification methods for lincRNA. Furthermore, we discuss several novel approaches that could be useful for lincRNA research in the future.

Conclusion: We provide a global view of methods in identifying lincRNAs and procedure for further function research of those lincRNAs.

Keywords: LincRNA, non-coding RNA, high-throughput, mammalian genome, gene regulation.

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Article Details

Year: 2017
Page: [34 - 42]
Pages: 9
DOI: 10.2174/1574893611666160923125933
Price: $65

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PDF: 12