Localization and abundance analysis of human lncRNAs at single-cell and single-molecule resolution

By M. Cabili, Margaret C. Dunagin, P. McClanahan, Andrew G Biaesch, Olivia M. Padovan-Merhar, Aviv Regev, Johannes Rinn, Arjun Raj. Genome Biology, 2015

634 citations recorded by the source corpus.

BackgroundLong non-coding RNAs (lncRNAs) have been implicated in diverse biological processes. In contrast to extensive genomic annotation of lncRNA transcripts, far fewer have been characterized for subcellular localization and cell-to-cell variability. Addressing this requires systematic, direct visualization of lncRNAs in single cells at single-molecule resolution.ResultsWe use single-molecule RNA-FISH to systematically quantify and categorize the subcellular localization patterns of a representative set of 61 lncRNAs in three different cell types. Our survey yields high-resolution quantification and stringent validation of the number and spatial positions of these lncRNA, with an mRNA set for comparison. Using this highly quantitative image-based dataset, we observe a variety of subcellular localization patterns, ranging from bright sub-nuclear foci to almost exclusively cytoplasmic localization. We also find that the low abundance of lncRNAs observed from cell population measurements cannot be explained by high expression in a small subset of ‘jackpot’ cells. Additionally, nuclear lncRNA foci dissolve during mitosis and become widely dispersed, suggesting these lncRNAs are not mitotic bookmarking factors. Moreover, we see that divergently transcribed lncRNAs do not always correlate with their cognate mRNA, nor do they have a characteristic localization pattern.ConclusionsOur systematic, high-resolution survey of lncRNA localization reveals aspects of lncRNAs that are similar to mRNAs, such as cell-to-cell variability, but also several distinct properties. These characteristics may correspond to particular functional roles. Our study also provides a quantitative description of lncRNAs at the single-cell level and a universally applicable framework for future study and validation of lncRNAs.

Subfields: Cancer Research, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/e564f78be2e44c835ac017353ebb94ffb453188c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cancer Research

In Molecular Biology

Citations in the corpus

Long Non-Coding RNA in the Pathogenesis of Cancers (2019, background): “It has been shown that the majority of lncRNAs are localized in the nucleus [9], but some of the lncRNAs also play roles in cytoplasm [10].”
Xist nucleates local protein gradients to propagate silencing across the X chromosome (2021, background): “There has been considerable debate about how lncRNAs can robustly regulate gene expression, given that they are often expressed at low levels (Cabili et al., 2015; Derrien et al., 2012).”
Single-Cell and Single-Molecule Analysis of Gene Expression Regulation (2016, background): “In addition, specific protocols have been optimized for rapid diagnostics (128) and for detecting transcribed gene fusions (125), singlenucleotide variants (SNVs) (84), noncoding RNAs (21), and nascent mRNAs (85).”
Linking Long Noncoding RNA Localization and Function. (2016, background): “It is worth noting that a recent large-scale evaluation of the subcellular fates of lncRNAs in human cell lines using singlemolecule RNA fluorescence in situ hybridization revealed that lncRNAs exhibited a wide range of subcellular localization patterns, including not only distinct patterns of nucle”
The multidimensional mechanisms of long noncoding RNA function (2017, background): “For instance, lncRNAs are known to be highly cell and tissue specific [68, 69], which means that, without changing the transcriptional machinery, cell- and tissuespecific regulation of gene expression could be achieved.”
Spatial transcriptome profiling by MERFISH reveals subcellular RNA compartmentalization and cell cycle-dependent gene expression (2019, background): “Notably, some other genes, as exemplified by the lncRNA MALAT1, remained evenly distributed across the nucleus and cytoplasm even within postmitotic daughter cells, and the nuclear enrichment gradually recovered through the G1 phase (Fig.”
Museum of spatial transcriptomics (2020, positive): “Advantages of smFISH based techniques include high gene detection eﬃ-ciency ( 95% for Hamming distance 4 MERFISH [79] compared to smFISH), single cell resolution, and subcellular transcript localization, which can be biologically relevant [80, 81].”