2.6 | Differential gene expression analysis
Differential gene expression (DGE) analysis was conducted using the program DESeq2 version 1.22.2 (Love et al., 2014). The DESeq2 package has a normalization function implemented based on the median of ratios method, in which the geometric mean of the gene counts across all samples is used to calculate the ratios of each gene and each sample, allowing between-sample comparisons (hbctraining, DGE_workshop (2022), GitHub repository, [accessed 05.04.2022]; https://github.com/hbctraining/DGE_workshop). Additionally, a variance stabilizing transformation (VST) was performed on the data to remove variance-mean dependence (Anders & Huber, 2010). All genes were taxonomically assigned with MEGAN6 version 6.13.1 (Huson et al., 2007); only ascomycete, chlorophyte and cyanobacterial genes were retained for DGE analysis (after DGE analysis the term ’genes’ will be used instead of ’transcripts’ to be congruent with the terminology of ’differentially expressed genes’). The vst-normalized data of each of the three taxonomic units was used to perform Principal Component Analysis (PCA) (R version 3.5.2). In the DGE analyses, we quantified differences in fungal gene expression owing to morph type (tripartite vs. cyanobacterial) and those in fungal, algal and cyanobacterial gene expression owing to temperature. Transcripts with an adjusted Benjamini-Hochberg p -value < 0.05 and a log2-fold change > |2| were regarded as significantly differentially expressed. Our analyses focus on the 200 most significantly differentially expressed genes as determined with two-way ANOVAs for all organisms. Functional annotation of these differentially expressed genes was conducted using UniProt BLAST (The UniProt Consortium, 2021). The BLAST search was run using default settings with the target databases being “Fungi”, “Plants” and “Bacteria”. The best alignment based on e-value (<10-5) was used to infer gene functions. 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our own database consisting of filtered metagenomic sequences of Peltigera britannica , P. leucophlebia and P. collina (unpublished data of the authors) using standalone BLAST for Linux Ubuntu (ncbi-blast+ package). This latter step was carried out to evaluate if the differentially expressed ascomycete genes were likely to originate from the lichen mycobiont or from other lichen-associated fungi. In the former case, there should be a hit both in the P. britannica metagenome, and in at least some of its congeners. The P. britannica metagenome was sequenced from a lichen individual not included in transcriptome sequencing (unpublished data by Werth, Andrésson, Resl and Warshan) and was built after de novo transcriptome assembly and DGE analysis. Gene Ontology (GO) annotations of all DEGs were conducted with the Bioconductor package topGO version 2.34.0 (Alexa & Rahnenführer, 2018).