Molecular Biology of the CellBioinformaticsPeer-reviewed journal article
Transcriptome analysis of the binucleate ciliate Tetrahymena thermophila with asynchronous nuclear cell cycles
Lixin ZhangiD, M. D. CervantesiD, Simin PaniD, J. Lindsley, Alan R. DabneyiD, Geoffrey M. KapleriD
Abstract
As a prototypic ciliated protozoan, Tetrahymena thermophila harbors two functionally and physically distinct nuclei within a shared cytoplasm. During vegetative growth, the cell cycles of the diploid germline micronucleus and polyploid somatic macronucleus are offset. Micronuclear S phase initiates just before cell division and is completed in daughter cells prior to the onset of macronuclear S phase. Whereas mitotic micronuclear division occurs mid-cell cycle, amitotic macronuclear division immediately precedes cytokinesis. Here we report the first RNA-seq analysis across the cell cycle of a binucleated organism. RNA was isolated at 30 min intervals across 1.5 vegetative cell cycles, starting with a macronuclear G1 population synchronized by centrifugal elutriation. Using MetaCycle, 3244 of the predicted 26,000+ T. thermophila genes were shown to be cell cycle regulated. Proteins that are required in micro- and macronuclei exhibit a single mRNA peak that correlates with their macronuclear function, while the expression of nucleus-limited protein-coding genes, including nucleoporins and importins, peak prior to their respective nucleus-specific role. Cyclin D and cyclin A/B genes showed distinct expression patterns that predict nucleus-specific functions. Clustering of periodically expressed genes revealed seven gene expression patterns. Four clusters have known PANTHER GO biological processes that are overrepresented for G1/S and G2/M phase functions. We propose that these clusters encode known and novel factors that coordinate micro- and macronuclear-specific events such as mitosis, amitosis, DNA replication and cell division.
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: clustering
- approach: statistical model
- Citations
- 16
- FWCI
- 2.13
- Field percentile
- top 13%
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