Dataset Information

High-throughput functional analysis of lncRNA core promoters elucidates rules governing tissue specificity

ABSTRACT: Bidirectional transcription initiates at both coding and non-coding genomic elements, including mRNA and long non-coding RNA (lncRNA) promoters and enhancer RNAs (eRNAs). However, each class has different tissue-specific expression profiles with lncRNAs and eRNAs being the most tissue-specific. How these complex differences in expression profiles and tissue-specificities are encoded in a single DNA sequence, however, remains an open question. Here, we address this question using multiple computational and experimental approaches, including massively parallel reporter assays (MPRA). As most transcription factors (TFs) are enriched near the transcription start sites (TSSs) of both promoters and enhancers, we focus our analyses on these core promoter regions. We find that divergent lncRNA and mRNA core promoters have higher capacities to drive transcription than non-divergent lncRNA and mRNA core promoters, respectively. Conversely, lincRNAs and eRNAs are more tissue-specific than divergent genes. This higher tissue-specificity is strongly associated with having less complex TF motif profiles at the core promoter. We confirm these findings using single-nucleotide deletions in MPRA and we identify specific TFs regulating a set of disease-related lncRNAs. Finally, we assess the effects of genetic variation at core promoters and find that 22% of common single nucleotide polymorphisms show significant regulatory effects. Collectively, our findings characterize the important role of core promoter sequences in determining expression levels across both coding and non-coding gene classes and highlight an unexpected role of TF motif architecture in explaining the more restricted expression patterns of lncRNAs and eRNAs.

ORGANISM(S): synthetic construct Homo sapiens

PROVIDER: GSE117594 | GEO | 2019/01/08

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Background: Long non-coding RNAs (lncRNAs) are increasingly implicated as gene regulators and may ultimately be more numerous than protein-coding genes in the human genome. Despite large numbers of reported lncRNAs, reference annotations are likely incomplete due to their lower and tighter tissue-specific expression compared to mRNAs. An unexplored factor potentially confounding lncRNA identification is inter-individual expression variability. Here, we characterize lncRNA natural expression variability in human primary granulocytes. Results: We annotate granulocyte lncRNAs and mRNAs in RNA-seq data from ten healthy individuals, identifying multiple lncRNAs absent from reference annotations, and use this to investigate three known features (higher tissue-specificity, lower expression, and reduced splicing efficiency) of lncRNAs relative to mRNAs. Expression variability was examined in seven individuals sampled three times at one or more than one month intervals. We show that lncRNAs display significantly more inter-individual expression variability compared to mRNAs. We confirm this finding in 2 independent human datasets by analyzing multiple tissues from the GTEx project and lymphoblastoid cell lines from the GEUVADIS project. Using the latter dataset we also show that including more human donors into the transcriptome annotation pipeline allows identification of an increasing number of lncRNAs, but minimally affects mRNA gene number. Conclusions: A comprehensive annotation of lncRNAs is known to require an approach that is sensitive to low and tight tissue-specific expression. Here we show that increased inter-individual expression variability is an additional general lncRNA feature to consider when creating a comprehensive annotation of human lncRNAs or proposing their use as prognostic or disease markers. We used PolyA+ RNA-seq data from human primary granulocytes of 10 healthy individuals to de novo annotate lncRNAs and mRNAs in this cell type and ribosomal depleted (total) RNA-seq data from seven of these individuals sampled three times to analyze lncRNA amd mRNA expression variability

Dataset Information

High-throughput functional analysis of lncRNA core promoters elucidates rules governing tissue specificity

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets