Cell Death and DiseaseBioinformaticsPeer-reviewed journal article
Single cell transcriptional landscape of long non-coding RNAs orchestrating mouse heart development
Thaís A. R. RamosiD, Sebastián Urquiza-ZurichiD, Soo Young KimiD, Thomas G. GilletteiD, Joseph A. HilliD, Sergio LavanderoiD, Thais Gaudencio do RegoiD, Vinicius Maracaja‐CoutinhoiD
Abstract
Long non-coding RNAs (lncRNAs) comprise the most representative transcriptional units of the mammalian genome, and theyre associated with organ development that can be associated with the emergence of diseases, such as cardiovascular diseases. Thus, we used bioinformatic approaches, machine learning algorithms and statistical techniques to define lncRNAs involved in mammalian cardiac development. We used a single-cell transcriptome dataset generated from 4 embryonic and 4 postnatal stages. Our study identified 8 distinct cell types, novel marker transcripts (coding/lncRNAs) and also, differential expression and functional enrichment analysis reveal cardiomyocyte subpopulations associated with cardiac function; meanwhile modular co-expression analysis reveals cell-specific functional insights for lncRNAs during myocardial development, including a potential association with key genes related to disease and the "fetal gene program". Our results evidence the role of particular lncRNAs in heart development, and highlights the usage of co-expression modular approaches in the cell-type functional definition.
- organism: mouse
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- approach: machine learning (classical)
- Citations
- 10
- FWCI
- 0.89
- Field percentile
- top 30%
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