Fungal stress responses from the view of transcriptome vectors
Authors:Károly Antal1, István Pócsi2,3 and Tamás Emri2,3,*
doi: 10.15698/mic2026.11.889
Volume 13, pp. 378 to 391, published 02/11/2026.
1 Department of Zoology, Eszterházy Károly Catholic University, Eger, Hungary. 2 Department of Molecular Biotechnology and Microbiology, Faculty of Sciences and Technology, University of Debrecen, Debrecen, Hungary. 3 HUN-REN–UD Fungal Stress Biology Research Group, University of Debrecen, Debrecen, Hungary.
Keywords:
adaptation vector, Aspergillus, response vector, RNA sequencing, stress adaptation, stress response, transcriptomics
Corresponding Author(s):
Conflict of interest statement:
The authors declare no conflicts of interest.
Please cite this article as:
Károly Antal, István Pócsi, Tamás Emri (2026). Fungal stress responses from the view of transcriptome vectors. Microbial Cell 13: 378-391. doi: 10.15698/mic2026.11.889
© 2026 Antal et al. This is an open-access article released under the terms of the Creative Commons Attribution (CC BY) license, which allows the unrestricted use, distribution, and reproduction in any medium, provided the original author and source are acknowledged.
Abstract:
Transcriptomic approaches are widely used to study the stress biology of fungi or other (micro)organisms. When three or more transcriptomes are compared, considering their relative positions can clarify their relations. Here we represent transcriptomes as points in an N-dimensional space (transcriptome space), where dimensions measure the transcriptional intensities of genes. In this space stress responses correspond to vectors from the pretreatment transcriptome to the transcriptome altered by the treatment. This approach enables us to create simple definitions that let us focus on the data measured in the experiment. In addition, we show (1) the importance of kinetic studies in comparing stress responses, especially when examining responses to changes of different magnitudes; (2) how a reference transcriptome with genes expressed near the upper and lower ends of their transcriptional range constrains stress responses; (3) why the pre-treatment difference between transcriptomes makes the evaluation process difficult. We also show that comprehending the results of combinatorial stress response experiments is disproportionately challenging because of the cumulative nature of the problems mentioned above in these experiments. We propose that considering the relations of transcriptomes as points in the transcriptome space provides a view that complements the standard gene-centered analyses. Developing a model that describes the processes resulting in the observed relative position of transcriptomes can help reduce the risk of misinterpreting transcriptional changes at the level of individual genes or gene groups.