Abstract
The ability to extract, identify and annotate large amounts of biological data is a key feature of the “omics” era, and has led to an explosion in the amount of data available. One pivotal advance is the use of Next-Generation Sequencing (NGS) techniques such as RNA-sequencing (RNA-seq). RNA-seq uses data from millions of small mRNA transcripts or “reads” which are aligned to a reference genome. Comparative transcriptomics analyses using RNA-seq can provide the researcher with a comprehensive view of the cells’ response to a given environment or stimulus.
Here, we describe the NGS techniques (based on Illumina technology) that are routinely used for comparative transcriptome analysis of fungal species. We describe the entire process from isolation of RNA to computational identification of differentially expressed genes. We provide instructions to allow the beginner to implement packages in R such as Bioconductor. The methods described are not limited to yeast, and can also be applied to other eukaryotic organisms.
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Acknowledgements
We are grateful to Dr Amanada Lohan, UCD, for helpful advice and for designing the original sequencing strategy. Work in the Butler lab is supported by Science Foundation Ireland and the Wellcome Trust.
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Wang, C., Schröder, M.S., Hammel, S., Butler, G. (2016). Using RNA-seq for Analysis of Differential Gene Expression in Fungal Species. In: Devaux, F. (eds) Yeast Functional Genomics. Methods in Molecular Biology, vol 1361. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3079-1_1
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DOI: https://doi.org/10.1007/978-1-4939-3079-1_1
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