BMC Genomics (Sep 2024)
Mitochondrial transcriptome of Candida albicans in flagranti — direct RNA sequencing reveals a new layer of information
Abstract
Abstract Background Organellar transcriptomes are relatively under-studied systems, with data related to full-length transcripts and posttranscriptional modifications remaining sparse. Direct RNA sequencing presents the possibility of accessing a previously unavailable layer of information pertaining to transcriptomic data, as well as circumventing the biases introduced by second-generation RNA-seq platforms. Direct long-read ONT sequencing allows for the isoform analysis of full-length transcripts and the detection of posttranscriptional modifications. However, there are still relatively few projects employing this method specifically for studying organellar transcriptomes. Results Candida albicans is a promising model for investigating nucleo-mitochondrial interactions. This work comprises ONT sequencing of the Candida albicans mitochondrial transcriptome along with the development of a dedicated data analysis pipeline. This approach allowed for the detection of complete transcript isoforms and posttranslational RNA modifications, as well as an analysis of C. albicans deletion mutants in genes coding for the 5' and 3' mitochondrial RNA exonucleases CaPET127 and CaDSS1. It also enabled for corrections to previous studies in terms of 3’ and 5’ transcript ends. A number of intermediate splicing isoforms was also discovered, along with mature and unspliced transcripts and changes in their abundances resulting from disruption of both 5’ and 3’ exonucleolytic processing. Multiple putative posttranscriptional modification sites have also been detected. Conclusions This preliminary work demonstrates the suitability of direct RNA sequencing for studying yeast mitochondrial transcriptomes in general and provides new insights into the workings of the C. albicans mitochondrial transcriptome in particular. It also provides a general roadmap for analyzing mitochondrial transcriptomic data from other organisms.
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