Functional prediction and validation of lncRNAs using allele-sensitive single-cell RNA-sequencing
Per Johnsson1,2, Björn Reinius1,2, Rickard Sandberg1,2
1Ludwig Cancer Research Institute, Stockholm, Sweden; 2Cell and Molecular Biology, Karolinska Institutet, Stockholm, Sweden
Thousands of long non-coding RNAs (lncRNAs) have been identified but their functions remain largely unknown. Functional predictions have proved difficult and it is currently hard to determine whether a lncRNA acts in cis and/or trans mechanisms or as a negative or positive regulator. LncRNAs are in general detected at low copy numbers in bulk RNA-seq experiments, although it has been suggested that an averaging over thousands of cells masks high expression in specific cells.
We hypothesize that analyses of lncRNA expression at single-cell resolution could increase our understanding of their function, improve functional predictions and facilitate the design of downstream experiments. We apply allele-sensitive single-cell RNA-seq on individual primary mouse fibroblasts. We detect hundreds of different lncRNAs and identify rare cells where these transcripts are expressed at high levels. We show that the identification of such cells allows for accurate functional predictions and confirm these predictions using relevant model systems. Specifically, the cell cycle distribution of asynchronously growing MEF cells is identified and several lncRNAs with cell cycle specific pattern characterized. Intriguingly, several of these cell cycle specific lncRNAs was validated to be involved in cell cycle progression. Moreover, we use allele-specific information in order to identify lncRNAs involved in cis-regulatory mechanisms. Well-characterized examples, such as the Igf2r-Airn locus, are identified and more importantly, we predict multiple uncharacterized lncRNAs, including antisense RNAs, to be involved in cis-acting regulation.
In summary, we show that allele-sensitive single-cell RNA-seq enables functional predictions of previously uncharacterized lncRNAs, and we successfully validated their function. We suggest that single-cell RNA-seq could greatly increase our understanding of lncRNAs and their function.
Credits: None available.
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