Symbiont-specific responses to environmental cues in a threesome lichen symbiosis
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Photosymbiodemes are a special case of lichen symbiosis where one lichenized fungus engages in symbiosis with two different photosynthetic partners, a cyanobacterium and a green alga, to develop two distinctly looking photomorphs. We investigated differential gene expression in photosymbiodemes of the lichen Peltigera britannica at different temperatures representing mild and putatively stressful conditions and compared gene expression of thallus sectors containing cyanobacterial photobionts with thallus sectors with both green algal and cyanobacterial photobionts. Firstly, because of known ecological differences between photomorphs, we investigated symbiont-specific responses in gene expression to temperature increases. Secondly, we quantified photobiont-mediated differences in fungal gene expression. High temperatures expectedly led to an upregulation of genes involved in heat shock responses in all organisms in whole transcriptome data. As expected, the expression of genes involved in photosynthesis was increased in both photobiont types at 15 and 25°C. The green algae exhibited thermal stress responses mainly at 25°C, and the fungus and the cyanobacteria already by 15°C, demonstrating symbiont-specific responses to environmental cues and symbiont-specific ecological optima. Furthermore, photobiont-mediated differences in fungal gene expression could be identified, with upregulation of distinct biological processes in the different morphs, showing that interaction with specific symbiosis partners profoundly impacts fungal gene expression.
Methods
RNA was isolated with the innuPREP Plant RNA Kit from Analytik Jena. RNA libraries were constructed with dual indexing using the TruSeq® Stranded mRNA Library Prep kit (Illumina) which included a poly-A selection step. Libraries were sequenced on a MiSeq as well as a HiSeq 3000/4000 SR platform (both Illumina). The processed paired-end MiSeq data was used for de novo transcriptome assembly with Trinity software version 2.4.0 (Haas et al., 2013). The HiSeq data was pseudoaligned to the de novo transcriptome with the RNA-seq quantification program kallisto version 0.45.0 (Bray et al., 2016). Differential gene expression analysis was conducted with the program DESeq2 version 1.22.2 (Love et al, 2014). All genes were taxonomically assigned with MEGAN6 version 6.13.1 (Huson et al., 2007); only ascomycete, chlorophytes and cyanobacterial genes were retained for differential gene expression analysis. Functional annotation of differentially expressed genes was conducted using UniProt BLAST (The UniProt Consortium, 2021). The top-200 fungal differentially expressed transcripts were also blasted (blastx version 2.7.1+, translated nucleotide to protein) (Sayers et al., 2020) against our own database consisting of filtered metagenomic sequences of Peltigera britannica, P. leucophlebia and P. collina (unpublished data of the authors) using standalone BLAST for Linux Ubuntu (ncbi-blast+ package).
References
Bray, N. L., Pimentel, H., Melsted, P., & Pachter, L. (2016). Near-optimal probabilistic RNA-seq quantification. Nature Biotechnology, 34(5), 525-527. doi:10.1038/nbt.3519
Haas, B. J., Papanicolaou, A., Yassour, M., Grabherr, M., Blood, P. D., Bowden, J., . . . Regev, A. (2013). De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis. Nature Protocols, 8(8), 1494-1512. doi:10.1038/nprot.2013.084
Huson, D. H., Auch, A. F., Qi, J., & Schuster, S. C. (2007). MEGAN analysis of metagenomic data. Genome Research, 17(3), 377-386. doi:10.1101/gr.5969107
Love, M., Huber, W., & Anders, S. (2014). Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology, 15(12), 550. doi:10.1186/s13059-014-0550-8
Sayers, E. W., Beck, J., Brister, J.R., Bolton, E. E., Canese, K., Comeau, D.C., ... Ostell, J. (2020). Database resources of the National Center for Biotechnology Information. Nucleic Acids Research, 48(D1), D9-D16. doi:10.1093/nar/gkz899
The UniProt Consortium. (2021). UniProt: the universal protein knowledgebase in 2021. Nucleic Acids Research, 49(D1), D480-D489. doi:10.1093/nar/gkaa1100
创建时间:
2022-12-09



