bioRxivMicrobiologyPreprint
Revealing Gene Expression Heterogeneity in a Clonal Population of Tetrahymena thermophila through Single-Cell RNA Sequencing
Abstract
We performed single-cell RNA sequencing (scRNA-seq) on a population of 5,000 Tetrahymena thermophila, using the 10x Genomics 3 gene expression analysis, to investigate gene expression variability within this clonal population. Initially, we estimated the 3-untranslated regions (3 UTRs), which were absent in existing annotation files but are crucial for the 10x Genomics 3 gene expression analysis, using the peaks2utr method. This allowed us to create a modified annotation file, which was then utilized in our scRNA-seq analysis. Our analysis revealed significant gene expression variability within the population, even after removing the effect of cell phase-related features. This variability predominantly appeared in six distinct clusters. Through gene ontology and KEGG pathway enrichment analyses, we identified that these were primarily associated with ribosomal proteins, proteins specific to mitochondria, proteins involved in peroxisome-specific carbon metabolism, cytoskeletal proteins, motor proteins, and immobilized antigens.
- assay: scRNA-seq
- research focus: cell type annotation
- approach: deep learning
- approach: statistical model
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Transcript assembly improves expression quantification of transposable elements in single cell RNA-seq data
Wanqing Shao, Ting Wang·Genome ResearchPeer-reviewed·Jan 1, 2021
- Transcriptome analysis of the binucleate ciliate Tetrahymena thermophila with asynchronous nuclear cell cycles
Lixin Zhang, M. D. Cervantes, … Geoffrey M. Kapler·Molecular Biology of the CellPeer-reviewed·Dec 7, 2022
- Quantitative Description of C. elegans mRNA Landscapes From High Coverage Single Cell Transcriptomes
Florian Bernard, Emma Kandel, … Denis Dupuy·bioRxiv·Jul 21, 2026
- SC1: A Tool for Interactive Web-Based Single Cell RNA-Seq Data Analysis
Marmar R. Moussa, Ion Măndoiu·Journal of Computational BiologyPeer-reviewed·Jun 11, 2021
- Dynamics of gene expression in single root cells of A. thaliana
Ken Jean-Baptiste, José L. McFaline‐Figueroa, … Josh T. Cuperus·The Plant CellPeer-reviewed·Mar 28, 2019
- Single-cell phenotyping and RNA sequencing reveal novel patterns of gene expression heterogeneity and regulation during growth and stress adaptation in a unicellular eukaryote
Malika Saint, François Bertaux, … Samuel Marguerat·Nature MicrobiologyPeer-reviewed·Feb 4, 2019