30 million pair-end reads per sample were assessed with 101 bp read length. Reference P1 phage genome sequence (NC_005856.1) and annotations were downloaded from GenBank. Quality and adapter trimming of the short reads was performed using Trimmomatic [65]. Short reads matching known rRNA sequences were removed using the HISAT2 aligner [66]. Read quality reports before and after quality filtering were prepared using the FastQC software v0.11.7 [67]. Filtered reads were aligned to the reference genome using Burrows-Wheeler Aligner with the selected BWA-MEM algorithm [68]. The Sambamba software was used for BAM file processing [69]. Read mapping reports were created using the Qualimap software [70]. RSEM (RNA-Seq by Expectation Maximization) [71] was used to quantify the expression values of genes. Additionally, Salmon [72] was used to quantify the expression values of genes (not used in further analysis). Hierarchical clustering of RNA-seq samples (Pearson correlation metric, centroid linkage) based on the expression values of all genes was performed using standard R functions (R Core) and variance stabilizing transformation was provided by the DESeq2 package [73]. Differential expression analysis between designated groups of samples was performed using the voom+limma pipeline [74]. The false discovery rate (FDR) threshold of 0.01 and a fold change threshold of 1.5 were used in the analysis. Gene Set Annotation (GSA) was done using GSAn 1.0.5, a public web server for characterizing gene lists of high-throughput genomics [75]. Glimma package [76] was used to provide interactive graphics—Interactive HTML Volcano plots, Interactive HTML MA plots (Suplementary_plots_Volcano_MA.rar). GSA is a tool that uses semantic similarity and it is based on the IC (Information Content) proposed by Mazandu and Mulder [77]. Detailed analysis of gene expression and GSA analysis can be found in Supplementary Materials (Table S1). The RNA-seq data have been deposited at the NCBI’s Gene Expression Omnibus [78] and are accessible through GEO Series accession number GSE173614.

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