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Nucleic Acids Res. 2015 Feb 18;43(3):1392-406. doi: 10.1093/nar/gku1357. Epub 2015 Jan 13.

Defining the transcriptomic landscape of Candida glabrata by RNA-Seq.

Author information

1
Research Group Systems Biology and Bioinformatics, Leibniz Institute for Natural Product Research and Infection Biology-Hans Knoell Institute, Jena, Germany joerg.linde@hki-jena.de.
2
Septomics Research Center, Fungal Septomics, Leibniz Institute for Natural Product Research and Infection Biology-Hans Knoell Institute, Jena, Germany.
3
Research Group Systems Biology and Bioinformatics, Leibniz Institute for Natural Product Research and Infection Biology-Hans Knoell Institute, Jena, Germany.
4
Research Group Systems Biology and Bioinformatics, Leibniz Institute for Natural Product Research and Infection Biology-Hans Knoell Institute, Jena, Germany Department of Bioinformatics, Faculty of Biology and Pharmacy, Friedrich Schiller University, Jena, Germany.
5
Research Group Bioinformatics and High Throughput Analysis, Faculty of Mathematics and Computer Sciences, Friedrich Schiller University, Jena, Germany.
6
Septomics Research Center, Fungal Septomics, Leibniz Institute for Natural Product Research and Infection Biology-Hans Knoell Institute, Jena, Germany National Reference Center for Invasive Mycoses, Leibniz Institute for Natural Product Research and Infection Biology-Hans Knoell Institute, Jena, Germany.

Abstract

Candida glabrata is the second most common pathogenic Candida species and has emerged as a leading cause of nosocomial fungal infections. Its reduced susceptibility to antifungal drugs and its close relationship to Saccharomyces cerevisiae make it an interesting research focus. Although its genome sequence was published in 2004, little is known about its transcriptional dynamics. Here, we provide a detailed RNA-Seq-based analysis of the transcriptomic landscape of C. glabrata in nutrient-rich media, as well as under nitrosative stress and during pH shift. Using RNA-Seq data together with state-of-the-art gene prediction tools, we refined the annotation of the C. glabrata genome and predicted 49 novel protein-coding genes. Of these novel genes, 14 have homologs in S. cerevisiae and six are shared with other Candida species. We experimentally validated four novel protein-coding genes of which two are differentially regulated during pH shift and interaction with human neutrophils, indicating a potential role in host-pathogen interaction. Furthermore, we identified 58 novel non-protein-coding genes, 38 new introns and condition-specific alternative splicing. Finally, our data suggest different patterns of adaptation to pH shift and nitrosative stress in C. glabrata, Candida albicans and S. cerevisiae and thus further underline a distinct evolution of virulence in yeast.

PMID:
25586221
PMCID:
PMC4330350
DOI:
10.1093/nar/gku1357
[Indexed for MEDLINE]
Free PMC Article

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