Uncovering functional lncRNAs by scRNA-seq with ELATUS
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...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-11-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-024-54005-7 |
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| author | Enrique Goñi Aina Maria Mas Jovanna Gonzalez Amaya Abad Marta Santisteban Puri Fortes Maite Huarte Mikel Hernaez |
| author_facet | Enrique Goñi Aina Maria Mas Jovanna Gonzalez Amaya Abad Marta Santisteban Puri Fortes Maite Huarte Mikel Hernaez |
| author_sort | Enrique Goñi |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-d0075cb358734c02abc495fa200ba9bf |
| institution | Kabale University |
| issn | 2041-1723 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-d0075cb358734c02abc495fa200ba9bf2025-01-12T12:29:34ZengNature PortfolioNature Communications2041-17232024-11-0115111710.1038/s41467-024-54005-7Uncovering functional lncRNAs by scRNA-seq with ELATUSEnrique Goñi0Aina Maria Mas1Jovanna Gonzalez2Amaya Abad3Marta Santisteban4Puri Fortes5Maite Huarte6Mikel Hernaez7Center for Applied Medical Research, University of NavarraCenter for Applied Medical Research, University of NavarraCenter for Applied Medical Research, University of NavarraCenter for Applied Medical Research, University of NavarraInstitute of Health Research of Navarra (IdiSNA)Center for Applied Medical Research, University of NavarraCenter for Applied Medical Research, University of NavarraCenter for Applied Medical Research, University of NavarraAbstract 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.https://doi.org/10.1038/s41467-024-54005-7 |
| spellingShingle | Enrique Goñi Aina Maria Mas Jovanna Gonzalez Amaya Abad Marta Santisteban Puri Fortes Maite Huarte Mikel Hernaez Uncovering functional lncRNAs by scRNA-seq with ELATUS Nature Communications |
| title | Uncovering functional lncRNAs by scRNA-seq with ELATUS |
| title_full | Uncovering functional lncRNAs by scRNA-seq with ELATUS |
| title_fullStr | Uncovering functional lncRNAs by scRNA-seq with ELATUS |
| title_full_unstemmed | Uncovering functional lncRNAs by scRNA-seq with ELATUS |
| title_short | Uncovering functional lncRNAs by scRNA-seq with ELATUS |
| title_sort | uncovering functional lncrnas by scrna seq with elatus |
| url | https://doi.org/10.1038/s41467-024-54005-7 |
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