scholarly journals Genome-wide discovery and characterization of long noncoding RNAs in African oil palm (Elaeis guineensis Jacq.)

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9585
Author(s):  
Wei Xia ◽  
Yajing Dou ◽  
Rui Liu ◽  
Shufang Gong ◽  
Dongyi Huang ◽  
...  
Keyword(s):  
Fatty Acid ◽  
Oil Palm ◽  
Target Genes ◽  
De Novo ◽  
Elaeis Guineensis ◽  
Expression Patterns ◽  
Noncoding Rnas ◽  
Snp Markers ◽  
Long Noncoding Rnas ◽  
Rna Seq

Long noncoding RNAs (lncRNAs) are an important class of genes and play important roles in a range of biological processes. However, few reports have described the identification of lncRNAs in oil palm. In this study, we applied strand specific RNA-seq with rRNA removal to identify 1,363 lncRNAs from the equally mixed tissues of oil palm spear leaf and six different developmental stages of mesocarp (8–24 weeks). Based on strand specific RNA-seq data and 18 released oil palm transcriptomes, we systematically characterized the expression patterns of lncRNA loci and their target genes. A total of 875 uniq target genes for natural antisense lncRNAs (NAT-lncRNA, 712), long intergenic noncoding RNAs (lincRNAs, 92), intronic-lncRNAs (33), and sense-lncRNAs (52) were predicted. A majority of lncRNA loci (77.8%–89.6%) had low expression in 18 transcriptomes, while only 89 lncRNA loci had medium to high expression in at least one transcriptome. Coexpression analysis between lncRNAs and their target genes indicated that 6% of lncRNAs had expression patterns positively correlated with those of target genes. Based on single nucleotide polymorphism (SNP) markers derived from our previous research, 6,882 SNPs were detected for lncRNAs and 28 SNPs belonging to 21 lncRNAs were associated with the variation of fatty acid contents. Moreover, seven lncRNAs showed expression patterns positively correlated expression pattern with those of genes in de novo fatty acid synthesis pathways. Our study identified a collection of lncRNAs for oil palm and provided clues for further research into lncRNAs that may regulate mesocarp development and lipid metabolism.

scholarly journals Chromatin and RNA Maps Reveal Regulatory Long Noncoding RNAs in Mouse

2015 ◽  
Vol 36 (5) ◽  
pp. 809-819 ◽  
Author(s):  
Gireesh K. Bogu ◽  
Pedro Vizán ◽  
Lawrence W. Stanton ◽  
Miguel Beato ◽  
Luciano Di Croce ◽  
...  
Keyword(s):  
Cell Line ◽  
Cell Lines ◽  
De Novo ◽  
Noncoding Rnas ◽  
Mouse Cell ◽  
Long Noncoding Rnas ◽  
Chromatin State ◽  
Rna Seq ◽  
Gene Encoding ◽  
Protein Coding

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 andde novoassembling 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-codingKdm8gene, encoding a histone demethylase. Our findings provide 2,803 novel lncRNAs and a comprehensive catalog of chromatin-associated lncRNAs across different tissues in mouse.

Long Noncoding RNAs in Erythropoiesis and Megakaryopoiesis.

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 2331-2331
Author(s):  
Vikram R Paralkar ◽  
Tejaswini Mishra ◽  
Jing Luan ◽  
Yu Yao ◽  
Neeraja Konuthula ◽  
...  
Keyword(s):  
Gene Expression ◽  
De Novo ◽  
Conflicts Of Interest ◽  
Noncoding Rnas ◽  
Cell Types ◽  
Long Noncoding Rnas ◽  
Read Length ◽  
Rna Seq ◽  
Erythroid Progenitors ◽  
Specific Expression

Abstract Abstract 2331 Lnc (long noncoding) RNAs are RNA transcripts greater than 200nt that regulate gene expression independent of protein coding potential. It is estimated that thousands of lncRNAs play vital roles in diverse cellular processes and are involved in numerous diseases, including cancer. We hypothesize that multiple lncRNAs regulate erythrocyte and megakaryocyte formation by modulating gene expression. To identify lncRNAs in erythro-megakaryopoiesis, we purified two biological replicates each of murine Ter119+ erythroblasts, CD41+ megakaryocytes and bipotential megakaryocyte-erythroid progenitors (MEPs) [Lin− Kit+, Sca1−, CD16/32−, CD34−]. We performed strand-specific, paired-end, 200nt-read-length deep sequencing (RNA-Seq) to a depth of ∼200 million reads per sample using the Illumina GAII platform. We used the Tophat and Cufflinks suite of bioinformatic tools to assemble and compare de-novo transcriptomes from these three cell types, producing a high-confidence set of 69,488 transcripts. We confirmed that the RNA-seq assemblies accurately reflect gene expression predicted from prior studies. For example, Ter119+ cells were highly enriched for key erythroid transcripts encoding globins, heme synthetic enzymes and specialized membrane proteins. Megakaryocytes expressed high levels of gene encoding lineage-specific integrins and platelet markers. MEPs expressed numerous progenitor genes including Gata2, Kit and Myc. Thus, the RNA-seq data are of high-quality and sufficient complexity to accurately represent erythroid, megakaryocytic and MEP transcriptomes. We used a series of Unix-based bioinformatic filtering tools to identify lncRNAs that are expressed in these transcriptomes. We identified 605 “stringent” lncRNAs, and 813 “potential noncoding” transcripts. 47% of the lncRNAs are novel unannotated transcripts, validating the use of de-novo RNA-Seq in unique cell populations for lncRNA discovery. Among the 605 “stringent” lncRNAs, 103 are erythroid-restricted, 133 are meg-restricted and 280 are MEP-restricted, consistent with reports that lncRNAs exhibit exquisitely cell-type specific expression. Current efforts are aimed at generating a more comprehensive map of lncRNA expression at specific stages of erythroid and megakaryocyte/platelet development, and performing high throughput functional screens to analyze currently identified lncRNAs. Our studies are beginning to define new layers of gene regulation in normal erythro-megakaryopoiesis and are relevant to the pathophysiology of related disorders including various anemias, myeloproliferative and myelodysplastic syndromes and leukemias. Disclosures: No relevant conflicts of interest to declare.

scholarly journals PLncDB V2.0: a comprehensive encyclopedia of plant long noncoding RNAs

2020 ◽  
Vol 49 (D1) ◽  
pp. D1489-D1495 ◽  
Author(s):  
Jingjing Jin ◽  
Peng Lu ◽  
Yalong Xu ◽  
Zefeng Li ◽  
Shizhou Yu ◽  
...  
Keyword(s):  
Noncoding Rna ◽  
Regulatory Networks ◽  
Expression Patterns ◽  
Noncoding Rnas ◽  
Long Noncoding Rnas ◽  
Data Driven ◽  
Rna Seq ◽  
Protein Coding ◽  
User Friendly ◽  
Coding Potential

Abstract Long noncoding RNAs (lncRNAs) are transcripts longer than 200 nucleotides with little or no protein coding potential. The expanding list of lncRNAs and accumulating evidence of their functions in plants have necessitated the creation of a comprehensive database for lncRNA research. However, currently available plant lncRNA databases have some deficiencies, including the lack of lncRNA data from some model plants, uneven annotation standards, a lack of visualization for expression patterns, and the absence of epigenetic information. To overcome these problems, we upgraded our Plant Long noncoding RNA Database (PLncDB, http://plncdb.tobaccodb.org/), which was based on a uniform annotation pipeline. PLncDB V2.0 currently contains 1 246 372 lncRNAs for 80 plant species based on 13 834 RNA-Seq datasets, integrating lncRNA information from four other resources including EVLncRNAs, RNAcentral and etc. Expression patterns and epigenetic signals can be visualized using multiple tools (JBrowse, eFP Browser and EPexplorer). Targets and regulatory networks for lncRNAs are also provided for function exploration. In addition, PLncDB V2.0 is hierarchical and user-friendly and has five built-in search engines. We believe PLncDB V2.0 is useful for the plant lncRNA community and data mining studies and provides a comprehensive resource for data-driven lncRNA research in plants.

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