Author
Listed:
- Anamaria Necsulea
(Center for Integrative Genomics, University of Lausanne
Swiss Institute of Bioinformatics
Present addresses: Laboratory of Developmental Genomics, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland (A.N.); Harvard Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts 02138, USA, and Broad Institute, Cambridge, Massachusetts 02142, USA (M.S.).)
- Magali Soumillon
(Center for Integrative Genomics, University of Lausanne
Swiss Institute of Bioinformatics
Present addresses: Laboratory of Developmental Genomics, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland (A.N.); Harvard Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts 02138, USA, and Broad Institute, Cambridge, Massachusetts 02142, USA (M.S.).)
- Maria Warnefors
(Center for Integrative Genomics, University of Lausanne
Swiss Institute of Bioinformatics)
- Angélica Liechti
(Center for Integrative Genomics, University of Lausanne
Swiss Institute of Bioinformatics)
- Tasman Daish
(The Robinson Institute, School of Molecular and Biomedical Science, University of Adelaide, Adelaide, South Australia 5005, Australia)
- Ulrich Zeller
(Faculty of Agriculture and Horticulture, Humboldt University Berlin)
- Julie C. Baker
(Stanford University School of Medicine, Stanford University, Stanford, California 94305, USA)
- Frank Grützner
(The Robinson Institute, School of Molecular and Biomedical Science, University of Adelaide, Adelaide, South Australia 5005, Australia)
- Henrik Kaessmann
(Center for Integrative Genomics, University of Lausanne
Swiss Institute of Bioinformatics)
Abstract
Only a very small fraction of long noncoding RNAs (lncRNAs) are well characterized. The evolutionary history of lncRNAs can provide insights into their functionality, but the absence of lncRNA annotations in non-model organisms has precluded comparative analyses. Here we present a large-scale evolutionary study of lncRNA repertoires and expression patterns, in 11 tetrapod species. We identify approximately 11,000 primate-specific lncRNAs and 2,500 highly conserved lncRNAs, including approximately 400 genes that are likely to have originated more than 300 million years ago. We find that lncRNAs, in particular ancient ones, are in general actively regulated and may function predominantly in embryonic development. Most lncRNAs evolve rapidly in terms of sequence and expression levels, but tissue specificities are often conserved. We compared expression patterns of homologous lncRNA and protein-coding families across tetrapods to reconstruct an evolutionarily conserved co-expression network. This network suggests potential functions for lncRNAs in fundamental processes such as spermatogenesis and synaptic transmission, but also in more specific mechanisms such as placenta development through microRNA production.
Suggested Citation
Anamaria Necsulea & Magali Soumillon & Maria Warnefors & Angélica Liechti & Tasman Daish & Ulrich Zeller & Julie C. Baker & Frank Grützner & Henrik Kaessmann, 2014.
"The evolution of lncRNA repertoires and expression patterns in tetrapods,"
Nature, Nature, vol. 505(7485), pages 635-640, January.
Handle:
RePEc:nat:nature:v:505:y:2014:i:7485:d:10.1038_nature12943
DOI: 10.1038/nature12943
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Cited by:
- Luisa Santus & Maria Sopena-Rios & Raquel García-Pérez & Aaron E. Lin & Gordon C. Adams & Kayla G. Barnes & Katherine J. Siddle & Shirlee Wohl & Ferran Reverter & John L. Rinn & Richard S. Bennett & L, 2023.
"Single-cell profiling of lncRNA expression during Ebola virus infection in rhesus macaques,"
Nature Communications, Nature, vol. 14(1), pages 1-14, December.
- Dongqing Li & Zhuang Liu & Letian Zhang & Xiaowei Bian & Jianmin Wu & Li Li & Yongjian Chen & Lihua Luo & Ling Pan & Lingzhuo Kong & Yunting Xiao & Jiating Wang & Xiya Zhang & Wang Wang & Maria Toma &, 2024.
"The lncRNA SNHG26 drives the inflammatory-to-proliferative state transition of keratinocyte progenitor cells during wound healing,"
Nature Communications, Nature, vol. 15(1), pages 1-19, December.
- Wei Vivian Li & Yiling Chen & Jingyi Jessica Li, 2017.
"TROM: A Testing-Based Method for Finding Transcriptomic Similarity of Biological Samples,"
Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(1), pages 105-136, June.
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