Recent advances in transcriptome sequencing have made it possible to distinguish ubiquitously expressed long non-coding RNAs (UE lncRNAs) from tissue-specific lncRNAs (TS lncRNAs), thereby providing clues to their cellular functions. Here, we assembled and functionally characterized a consensus lncRNA transcriptome by curating hundreds of RNA-seq datasets across normal human tissues from 16 independent studies. In total, 1,184 UE and 2,583 TS lncRNAs were identified. These different lncRNA populations had several distinct features. Specifically, UE lncRNAs were associated with genomic compaction and highly conserved exons and promoter regions. We found that UE lncRNAs are regulated at the transcriptional level (with especially strong regulation of enhancers) and are associated with epigenetic modifications and post-transcriptional regulation. Based on these observations we propose a novel way to predict the functions of UE and TS lncRNAs through analysis of their genomic location and similarities in epigenetic modifications. Our characterization of UE and TS lncRNAs may provide a foundation for lncRNA genomics and the delineation of complex disease mechanisms.
Pubmed ID: 26760768 RIS Download
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A database for decoding transcription factor binding maps, expression profiles and transcriptional regulation of long non-coding RNAs (lncRNAs, lincRNAs), microRNAs, other ncRNAs (snoRNAs, tRNAs, snRNAs, etc.) and protein-coding genes from ChIP-Seq data. ChIPBase currently includes millions of transcription factor binding sites (TFBSs) among 6 species. ChIPBase provides several web-based tools and browsers to explore TF-lncRNA, TF-miRNA, TF-mRNA, TF-ncRNA and TF-miRNA-mRNA regulatory networks.
View all literature mentionsBioconductor software package for Empirical analysis of Digital Gene Expression data in R. Used for differential expression analysis of RNA-seq and digital gene expression data with biological replication.
View all literature mentionsSoftware tool for transcriptome assembly and differential expression analysis for RNA-Seq. Includes script called cuffmerge that can be used to merge together several Cufflinks assemblies. It also handles running Cuffcompare as well as automatically filtering a number of transfrags that are likely to be artifacts. If the researcher has a reference GTF file, the researcher can provide it to the script to more effectively merge novel isoforms and maximize overall assembly quality.
View all literature mentionsHuman and mouse genome annotation project which aims to identify all gene features in the human genome using computational analysis, manual annotation, and experimental validation.
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