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Nature communications
Nov 09, 2024;15 (1): 9709.

Uncovering functional lncRNAs by scRNA-seq with ELATUS.

Enrique Goñi, Aina Maria Mas, Jovanna Gonzalez, Amaya Abad, Marta Santisteban, Puri Fortes, Maite Huarte, Mikel Hernaez
Author Information
  1. Enrique Goñi: Center for Applied Medical Research, University of Navarra, PIO XII 55 Ave, Pamplona, Spain. ORCID
  2. Aina Maria Mas: Center for Applied Medical Research, University of Navarra, PIO XII 55 Ave, Pamplona, Spain. ORCID
  3. Jovanna Gonzalez: Center for Applied Medical Research, University of Navarra, PIO XII 55 Ave, Pamplona, Spain.
  4. Amaya Abad: Center for Applied Medical Research, University of Navarra, PIO XII 55 Ave, Pamplona, Spain.
  5. Marta Santisteban: Institute of Health Research of Navarra (IdiSNA), Pamplona, Spain. ORCID
  6. Puri Fortes: Center for Applied Medical Research, University of Navarra, PIO XII 55 Ave, Pamplona, Spain. ORCID
  7. Maite Huarte: Center for Applied Medical Research, University of Navarra, PIO XII 55 Ave, Pamplona, Spain. maitehuarte@unav.es. ORCID
  8. Mikel Hernaez: Center for Applied Medical Research, University of Navarra, PIO XII 55 Ave, Pamplona, Spain. mhernaez@unav.es. ORCID
PMID: 39521797 DOI: 10.1038/s41467-024-54005-7

Abstract

Long non-coding RNAs (lncRNAs) play fundamental roles in cellular processes and pathologies, regulating gene expression at multiple levels. Despite being highly cell type-specific, their study at single-cell (sc) level is challenging due to their less accurate annotation and low expression compared to protein-coding genes. Here, we systematically benchmark different preprocessing methods and develop a computational framework, named ELATUS, based on the combination of the pseudoaligner Kallisto with selective functional filtering. ELATUS enhances the detection of functional lncRNAs from scRNA-seq data, detecting their expression with higher concordance than standard methods with the ATAC-seq profiles in single-cell multiome data. Interestingly, the better results of ELATUS are due to its advanced performance with an inaccurate reference annotation such as that of lncRNAs. We independently confirm the expression patterns of cell type-specific lncRNAs exclusively detected with ELATUS and unveil biologically important lncRNAs, such as AL121895.1, a previously undocumented cis-repressor lncRNA, whose role in breast cancer progression is unnoticed by traditional methodologies. Our results emphasize the necessity for an alternative scRNA-seq workflow tailored to lncRNAs that sheds light on the multifaceted roles of lncRNAs.

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Grants

  1. LCF/PR/HR21/00176/"la Caixa" Foundation (Caixa Foundation)
  2. 0011-0537-2020-000038/Departamento de Educación, Gobierno de Navarra (Department of Education, Government of Navarra)
  3. 898356/EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 Marie Skłodowska-Curie Actions (H2020 Excellent Science - Marie Skłodowska-Curie Actions)

MeSH Term

RNA, Long Noncoding
Humans
Single-Cell Analysis
RNA-Seq
Computational Biology
Gene Expression Profiling
Sequence Analysis, RNA
Single-Cell Gene Expression Analysis

Chemicals

RNA, Long Noncoding
Journal Article
Article has an altmetric score of 21

Word Cloud

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