Literature DB >> 22133681

Small RNA transcriptome investigation based on next-generation sequencing technology.

Linglin Zhou1, Xueying Li, Qi Liu, Fangqing Zhao, Jinyu Wu.   

Abstract

Over the past decade, there has been a growing realization that studying the small RNA transcriptome is essential for understanding the complexity of transcriptional regulation. With an increased throughput and a reduced cost, next-generation sequencing technology has provided an unprecedented opportunity to measure the extent and complexity of small RNA transcriptome. Meanwhile, the large amount of obtained data and varied technology platforms have also posed multiple challenges for effective data analysis and mining. To provide some insight into the small RNA transcriptome investigation, this review describes the major small RNA classes, experimental methods to identify small RNAs, and available bioinformatics tools and databases.
Copyright © 2011. Published by Elsevier Ltd.

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Year:  2011        PMID: 22133681     DOI: 10.1016/j.jgg.2011.08.006

Source DB:  PubMed          Journal:  J Genet Genomics        ISSN: 1673-8527            Impact factor:   4.275


  13 in total

1.  mirTools 2.0 for non-coding RNA discovery, profiling, and functional annotation based on high-throughput sequencing.

Authors:  Jinyu Wu; Qi Liu; Xin Wang; Jiayong Zheng; Tao Wang; Mingcong You; Zhong Sheng Sun; Qinghua Shi
Journal:  RNA Biol       Date:  2013-05-29       Impact factor: 4.652

2.  Rat mir-155 generated from the lncRNA Bic is 'hidden' in the alternate genomic assembly and reveals the existence of novel mammalian miRNAs and clusters.

Authors:  Paolo Uva; Letizia Da Sacco; Manuela Del Cornò; Antonella Baldassarre; Paola Sestili; Massimiliano Orsini; Alessia Palma; Sandra Gessani; Andrea Masotti
Journal:  RNA       Date:  2013-01-17       Impact factor: 4.942

3.  Characterization of the stress associated microRNAs in Glycine max by deep sequencing.

Authors:  Haiyan Li; Yuanyuan Dong; Hailong Yin; Nan Wang; Jing Yang; Xiuming Liu; Yanfang Wang; Jinyu Wu; Xiaokun Li
Journal:  BMC Plant Biol       Date:  2011-11-23       Impact factor: 4.215

Review 4.  Recent developments in epigenetics of acute and chronic kidney diseases.

Authors:  Marpadga A Reddy; Rama Natarajan
Journal:  Kidney Int       Date:  2015-05-20       Impact factor: 10.612

Review 5.  Computational Approaches for the Analysis of ncRNA through Deep Sequencing Techniques.

Authors:  Dario Veneziano; Giovanni Nigita; Alfredo Ferro
Journal:  Front Bioeng Biotechnol       Date:  2015-06-03

Review 6.  The success of pharmacogenomics in moving genetic association studies from bench to bedside: study design and implementation of precision medicine in the post-GWAS era.

Authors:  Marylyn D Ritchie
Journal:  Hum Genet       Date:  2012-08-25       Impact factor: 4.132

7.  YM500: a small RNA sequencing (smRNA-seq) database for microRNA research.

Authors:  Wei-Chung Cheng; I-Fang Chung; Tse-Shun Huang; Shih-Ting Chang; Hsing-Jen Sun; Cheng-Fong Tsai; Muh-Lii Liang; Tai-Tong Wong; Hsei-Wei Wang
Journal:  Nucleic Acids Res       Date:  2012-11-29       Impact factor: 16.971

8.  Bioinformatics of Cancer ncRNA in High Throughput Sequencing: Present State and Challenges.

Authors:  Natasha Andressa Nogueira Jorge; Carlos Gil Ferreira; Fabio Passetti
Journal:  Front Genet       Date:  2012-12-17       Impact factor: 4.599

Review 9.  Next-generation sequencing and epigenomics research: a hammer in search of nails.

Authors:  Shrutii Sarda; Sridhar Hannenhalli
Journal:  Genomics Inform       Date:  2014-03-31

Review 10.  MicroRNAs as biomarkers for CNS disease.

Authors:  Pooja Rao; Eva Benito; André Fischer
Journal:  Front Mol Neurosci       Date:  2013-11-26       Impact factor: 5.639

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