An integrative approach revealing the landscape of long noncoding RNAs in human brain

被引:0
|
作者
Li, Dan [1 ,2 ,3 ]
Yang, William [1 ,2 ,3 ]
Arthur, Carolyn [1 ,2 ,3 ]
Yoshigoe, Kenji [1 ,2 ,3 ]
Tong, Weida [4 ]
Liu, Jun S. [5 ,6 ]
Yang, Mary [2 ,3 ,7 ]
机构
[1] Univ Arkansas Little Rock, MidSouth Bioinformat Ctr, 2801 S Univ Ave, Little Rock, AR 72204 USA
[2] Univ Arkansas Little Rock, Joint Bioinformat PhD Program, 2801 S Univ Ave, Little Rock, AR 72204 USA
[3] Univ Arkansas Med Sci, 2801 S Univ Ave, Little Rock, AR 72204 USA
[4] US FDA, Natl Ctr Toxicol Res, 3900 NCTR Rd, Jefferson, AR 72079 USA
[5] Harvard Univ, Fac Arts & Sci, Dept Stat, Cambridge, MA 02138 USA
[6] Harvard Univ, Harvard TH Chan Sch Publ Hlth, Cambridge, MA 02138 USA
[7] Univ Arkansas Little Rock, Dept Informat Sci, MidSouth Bioinformat Ctr, Little Rock, AR 72204 USA
基金
美国国家卫生研究院;
关键词
RNA-seq; Integrative approach; Long non-coding RNA; Landscape; Human Brain; GENE; SEQ; EXPRESSION; TRANSCRIPTION; GENERATION; PREDICTION; NETWORK; DISEASE; GENOME;
D O I
10.1109/CSCI.2016.26
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Long noncoding RNAs (lncRNAs) function as regulators and play critical roles in diverse biological processes; however, the majority of lncRNAs are not characterized, and their roles in regulation remain to be elucidated. Present RNAseq assembly approaches are insufficient to identify complete full-length transcripts and often reveal excessive amount of single-exon lncRNAs, many of them tend to be the fragments of transcripts. Here we developed an integrative approach that combined the results from reference-guided and de novo assembly to systematically identify lncRNAs. Experiments on simulated data and real RNA-seq data showed that our method effectively yielded a more comprehensive set of lncRNAs. We applied the method on 299 human brain RNA-seq samples with a total of 4.5 billion raw reads. The results yielded a comprehensive lncRNAs mapping in human brain, allowing discovery of novel lncRNAs and further function annotation.
引用
收藏
页码:104 / 109
页数:6
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