Identification of functional long non-coding RNAs in C. elegans View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Alper Akay, David Jordan, Isabela Cunha Navarro, Tomasz Wrzesinski, Chris P. Ponting, Eric A. Miska, Wilfried Haerty

ABSTRACT

BACKGROUND: Functional characterisation of the compact genome of the model organism Caenorhabditis elegans remains incomplete despite its sequencing 20 years ago. The last decade of research has seen a tremendous increase in the number of non-coding RNAs identified in various organisms. While we have mechanistic understandings of small non-coding RNA pathways, long non-coding RNAs represent a diverse class of active transcripts whose function remains less well characterised. RESULTS: By analysing hundreds of published transcriptome datasets, we annotated 3392 potential lncRNAs including 143 multi-exonic loci that showed increased nucleotide conservation and GC content relative to other non-coding regions. Using CRISPR/Cas9 genome editing, we generated deletion mutants for ten long non-coding RNA loci. Using automated microscopy for in-depth phenotyping, we show that six of the long non-coding RNA loci are required for normal development and fertility. Using RNA interference-mediated gene knock-down, we provide evidence that for two of the long non-coding RNA loci, the observed phenotypes are dependent on the corresponding RNA transcripts. CONCLUSIONS: Our results highlight that a large section of the non-coding regions of the C. elegans genome remains unexplored. Based on our in vivo analysis of a selection of high-confidence lncRNA loci, we expect that a significant proportion of these high-confidence regions is likely to have a biological function at either the genomic or the transcript level. More... »

PAGES

14

References to SciGraph publications

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s12915-019-0635-7

    DOI

    http://dx.doi.org/10.1186/s12915-019-0635-7

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1112214792

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/30777050


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