bioRxivMicrobiologyPreprint
Long-read direct RNA sequencing of the mitochondrial transcriptome of Saccharomyces cerevisiae reveals condition-dependent intron turnover
C. C. Koster, A. Kleefeldt, M. van den Broek, M. Luttik, J.-M. G. Daran, P. Daran-Lapujade
Abstract
Mitochondria fulfil many essential roles and have their own genome, which is expressed as polycistronic transcripts that undergo co- or post-transcriptional processing and splicing. Due to inherent complexity and limited technical accessibility of the mitochondrial transcriptome, fundamental questions regarding mitochondrial gene expression and splicing remain unresolved, even in the model eukaryote Saccharomyces cerevisiae. Long-read sequencing could address these fundamental questions. Therefore, a method for enrichment of mitochondrial RNA and sequencing using Nanopore technology was developed, enabling the resolution of splicing of polycistronic genes and the quantification the spliced RNA. This method successfully captured the full mitochondrial transcriptome and resolved RNA splicing patterns with single-base resolution, and was applied to explore the transcriptome of S. cerevisiae grown with glucose or ethanol as sole carbon source, revealing the impact of growth conditions on mitochondrial RNA-expression and splicing. This study uncovered a remarkable difference in turn-over of group II introns between yeast grown in mostly fermentative and fully respiratory conditions. Whether this accumulation of introns in glucose medium has an impact on mitochondrial functions remains to be explored. Combined with the high tractability of the model yeast S. cerevisiae, the developed method enables to explore mitochondrial transcriptome regulation and processing in a broad range of conditions relevant in human context, including aging, apoptosis and mitochondrial diseases.
- organism: yeast
- assay: long-read sequencing
- research focus: cell type annotation
- research focus: transcription & RNA processing
- research focus: chromatin & epigenetic regulation
- research focus: gene regulatory network inference
- approach: experimental assay
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