Identification and Characterization of Long Non-Coding RNAs Related to Mouse Embryonic Brain Development from Available Transcriptomic Data

Lv, Jie; Cui, Wei; Liu, Hongbo; He, Hongbin; Xiu, Youcheng; Guo, Jing; Liu, Hui; Liu, Qi; Zeng, Tiebo; Chen, Yan; Zhang, Yan; Wu, Qiong

doi:10.1371/journal.pone.0071152

Cited by 54 publications

(47 citation statements)

References 110 publications

(163 reference statements)

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“…Importantly, these lncRNAs did not contain transcripts with coding potential, as measured by the two independent methods, including conservation-independent CPAT (22) and conservation-dependent PhyloCSF (23) (see Materials and Methods). About 85% of this data set overlapped previously identified lncRNAs (17,20,(34)(35)(36)(37)(38)) (see Fig. S1 in the supplemental material), supporting the accuracy of our prediction pipeline, with a total of 34% of all known lncRNAs recovered (Fig.…”

Section: Resultssupporting

confidence: 78%

“…In total, 10,728 unique lncRNAs were overlapped with chromatin state maps discovered by using ChromHMM by pooling various ChIP-seq data sets and classified chromatin-associated lncRNAs in mouse. (B) Overlap between lncRNAs identified in this study (small circle) and previously published lncRNAs (large circle; UCSC/Ensembl/RefSeq [5,17,20,[34][35][36][37][38]). A total of 2,803 nonannotated lncRNAs were identified, and 34% (13,382) of the known lncRNAs were recovered in this study.…”

Section: Resultsmentioning

confidence: 95%

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Chromatin and RNA Maps Reveal Regulatory Long Noncoding RNAs in Mouse

Bogu

Vizán

Stanton

et al. 2016

Molecular and Cellular Biology

101

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g Discovering and classifying long noncoding RNAs (lncRNAs) across all mammalian tissues and cell lines remains a major challenge. Previously, mouse lncRNAs were identified using transcriptome sequencing (RNA-seq) data from a limited number of tissues or cell lines. Additionally, associating a few hundred lncRNA promoters with chromatin states in a single mouse cell line has identified two classes of chromatin-associated lncRNA. However, the discovery and classification of lncRNAs is still pending in many other tissues in mouse. To address this, we built a comprehensive catalog of lncRNAs by combining known lncRNAs with high-confidence novel lncRNAs identified by mapping and de novo assembling billions of RNA-seq reads from eight tissues and a primary cell line in mouse. Next, we integrated this catalog of lncRNAs with multiple genome-wide chromatin state maps and found two different classes of chromatin state-associated lncRNAs, including promoter-associated (plncRNAs) and enhancer-associated (elncRNAs) lncRNAs, across various tissues. Experimental knockdown of an elncRNA resulted in the downregulation of the neighboring protein-coding Kdm8 gene, encoding a histone demethylase. Our findings provide 2,803 novel lncRNAs and a comprehensive catalog of chromatin-associated lncRNAs across different tissues in mouse.

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Section: Resultssupporting

confidence: 78%

Section: Resultsmentioning

confidence: 95%

Chromatin and RNA Maps Reveal Regulatory Long Noncoding RNAs in Mouse

Bogu

Vizán

Stanton

et al. 2016

Molecular and Cellular Biology

101

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“…The results together with others (Lv et al, 2013a;Lv et al, 2013b;Ng et al, 2012b;Qureshi and Mehler, 2012) have highlighted the importance of lncRNAs in regulation of cellular fate in neural cells and brain. Increasing evidences suggested that lncRNAs can control epigenetic targeting via their ability to bind RNA, DNA and protein (Guttman and Rinn, 2012;Mercer and Mattick, 2013;Tsai et al, 2010).…”

Section: High-throughput Approaches To Study the Lncrnas In Cns Develsupporting

confidence: 68%

“…Actually, many transcriptomic studies have revealed the dynamic lncRNA expression profiles and their functions among developing, fetal and adult tissues, in additional to embryonic stem (ES) cells Sheik Mohamed et al, 2010), neural cell subtypes Aprea et al, 2013;Lin et al, 2011), and brain Ponjavic et al, 2009;Lv et al, 2013a;Lv et al, 2013b).…”

Section: Lncrnas In the Central Nervous Systemmentioning

confidence: 99%

Long Non-coding RNAs: key players in brain and central nervous system development

Lv¹,

Liu²,

Liu³

et al. 2014

cmb

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CanadaComputational Molecular Biology (Online, ISSN 1927-5587) ), indexed by international database ProQuest, is an open access, peer reviewed journal publishing original research papers of general interest involving in the computational biology at the molecular level.The Journal is publishing all the latest and outstanding research articles, letters, methods, and reviews in all areas of Computational Molecular Biology, covering new discoveries in molecular biology, from genes to genomes, using statistical, mathematical, and computational methods as well as new development of computational methods and databases in molecular and genome biology.The papers published in the journal are expected to be of interests to computational scientists, biologists, and teachers/students/researchers engaged in biology, as well as are appropriate for R & D personnel and general readers interested in computational technology and biology.Computational Molecular Biology is published independently by BioPublisher. It is committed to publishing and disseminating significant original achievements in the related research fields of molecular biology. Vol.4, No.5, 1-13 (doi: 10.5376/cmb.2014.04.0005) Abstract Regulatory long non-coding RNAs have been emerged as a major contribution of cognitive evolution in mammalian central nervous system and brain tissues. Though proteins have relatively conserved during evolution, the lncRNAs have evolved rapidly to cope with essential and widespread cellular regulation, partly by directing generic protein function. Long non-coding RNAs, highly yet specifically expressed in mammalian brain, provide tissue-and neuronal activity-specific epigenetic and transcriptional regulation. lncRNAs have been documented to be essential for brain development and be involved in brain related diseases. We suggest that lncRNAs are important to modulate diverse central nervous system processes and are the major factor that is important to the brain development, which may be employed to develop novel diagnostic and therapeutic strategies to treat brain related diseases. Moreover, animal models with altered lncRNA expressions and high-throughput approaches would help to understand the mechanisms of lncRNAs in brain development and the etiology of lncRNA-driven human neurological diseases.

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“…This property makes RNA-Seq a highly desirable method for the detection of novel transcripts including lncRNAs. As such, RNA-Seq has been successfully applied to identify thousands of lncRNAs in human, mouse and various other species (Li et al, 2012;Lv et al, 2013;Zhang et al, 2013;Ye et al, 2014).…”

Section: Identification Of Prostate Cancer Lncrnas By Rna-seqmentioning

confidence: 99%

Identification of Prostate Cancer LncRNAs by RNA-Seq

Gan²,

Zhang³

et al. 2014

Asian Pacific Journal of Cancer Prevention

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Purpose: To identify prostate cancer lncRNAs using a pipeline proposed in this study, which is applicable for the identification of lncRNAs that are differentially expressed in prostate cancer tissues but have a negligible potential to encode proteins. Materials and Methods: We used two publicly available RNA-Seq datasets from normal prostate tissue and prostate cancer. Putative lncRNAs were predicted using the biological technology, then specific lncRNAs of prostate cancer were found by differential expression analysis and co-expression network was constructed by the weighted gene co-expression network analysis. Results: A total of 1,080 lncRNA transcripts were obtained in the RNA-Seq datasets. Three genes (PCA3, C20orf166-AS1 and RP11-267A15.1) showed a significant differential expression in the prostate cancer tissues, and were thus identified as prostate cancer specific lncRNAs. Brown and black modules had significant negative and positive correlations with prostate cancer, respectively. Conclusions: The pipeline proposed in this study is useful for the prediction of prostate cancer specific lncRNAs. Three genes (PCA3, C20orf166-AS1, and RP11-267A15.1) were identified to have a significant differential expression in prostate cancer tissues. However, there have been no published studies to demonstrate the specificity of RP11-267A15.1 in prostate cancer tissues. Thus, the results of this study can provide a new theoretic insight into the identification of prostate cancer specific genes.

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Identification and Characterization of Long Non-Coding RNAs Related to Mouse Embryonic Brain Development from Available Transcriptomic Data

Cited by 54 publications

References 110 publications

Chromatin and RNA Maps Reveal Regulatory Long Noncoding RNAs in Mouse

Chromatin and RNA Maps Reveal Regulatory Long Noncoding RNAs in Mouse

Long Non-coding RNAs: key players in brain and central nervous system development

Identification of Prostate Cancer LncRNAs by RNA-Seq

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