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Since the discovery of computers, bioinformatics and computational biology have been instrumental in a wide range of discoveries in virology. These include early mathematical models of virus-host interaction, and more recently the analysis of viral nucleotide and protein sequences to track their function, epidemiology, and evolution. The genomics revolution has provided an unprecedented amount of sequence information from both viruses and their hosts. In this article, we discuss how bioinformatics allows viral sequence data to be analyzed and interpreted, including an overview of commonly used tools and examples of applications.

Additional file 8: Figure S8. Here, we exemplarily show the results of our re-assembly and re-arrangement efforts for the plasmid of C. psittaci strain MN. A) CDS annotation achieved with pLannotate for plasmid sequence directly obtained from NCBI. Note that genes GP5D_CHLPS and GP2D_CHLPS were only found with 68 and 52 % sequence similarity, respectively, which is marked by white arrows. B) Re-assembled plasmid sequence using corresponding raw-read data of strain MN and after re-arrangement using GP3D_CHLT2 as marker gene (orange frame). In the re-assembled plasmid, GP5D_CHLPS and GP2D_CHLPS achieved a sequence similarity of 99 and 100 %, respectively. Further details and results for all other plasmids can be found in the OSF (https://osf.io/rbca9).

We present CoVpipe2, a bioinformatics workflow developed at the Public Health Institute of Germany to reconstruct SARS-CoV-2 genomes based on short-read sequencing data accurately. The decisive factor here is the reliable, accurate, and rapid reconstruction of genomes, considering the specifics of the used sequencing protocol. We introduce CoVpipe2 to address common pittalls and have compared and successfully validated the pipeline against selected publicly available benchmark datasets.

Additional file 6: Figure S6. Phylogenetic tree reconstructed from the alignment of re-assembled and re-arranged plasmid sequences from 47 C. psittaci strains. The tree was built using RAxML version 8.2.12 with the GTRGAMMA model and 1000 bootstrap replicates.

Additional file 2: Figure S2. Phylogenetic tree based on the 904 common genes of 61 C. psittaci strains. The tree was reconstructed based on the concatenated core gene alignments at protein level produced by RIBAP and calculated using FastTree.

Additional file 4: Figure S4. Phylogenetic tree based on nucleotide sequences of the extracted PZ of 53 C. psittaci strains used in this study. Sequences of 8 strains, where this region was located on several scaffolds, were not included here. The tree was constructed using RAxML v8.2.11 with GTRGAMMA nucleotide model and Rapid hill-climbing algorithm.

Additional file 3: Figure S3. SNP-based tree determined from 61 C. psittaci genomes. The eight distinct lineages defined by Vorimore et al. [37],i.e. group I_psittacine, group II_duck, group III_pigeon, group IV_turkey,group V_Mat116, group VI_M56, group VII_VS225, and group VIII_WC, are represented by colored circles. The tree was built using RAxML version 8.2.9 with the GTRGAMMA model and 1000 bootstrap replicates based on thefiltered SNP matrix (4011 SNPs) from BioNumerics.

Additional file 1: Table S1. Differentially expressed genes between growth on different media at 10 h. Table S2. Differentially expressed genes between growth on different media when glycerol consumption became visible. Table S3. Differentially expressed genes between growth on different media when glycerol concentration is lower. Table S4. Gene expression in TPM within central metabolic pathways. Figure S1. Principal Component Analysis based on expression level from the 500 highest expressed genes in each of the cultivation media and RNA sampling points. Figure S2. Overview of differential expression analysis between Rhodotorula toruloides CBS 14 cultivated on crude glycerol and a mixture of crude glycerol and hemicellulose hydrolysate, at 10 h cultivation. Figure S3. Overview of differential expression analysis between Rhodotorula toruloides CBS 14 grown on different media when glycerol consumption became visible. Figure S4. Overview of differential expression analysis between Rhodotorula toruloides CBS 14 grown on different media when about 20 g/l of glycerol were left. Figure S5. Differentially expressed genes in Rhodotorula toruloides CBS 14 within sampling time points in each of the growth media. Figure S6. Examples of upregulated genes in Rhodotorula toruloides CBS 14 grown on a mixture of crude glycerol (CG) and hemicellulose hydrolysate (CGHH) for 10 h of cultivation, whose expression is higher than CG 10 h. Figure S7. Examples of upregulated genes in Rhodotorula toruloides CBS 14 grown on a mixture of crude glycerol (CG) and hemicellulose hydrolysate (CGHH) for 10 h of cultivation, whose expression is higher than CG 30 h. Figure S8. Examples of upregulated genes in Rhodotorula toruloides CBS 14 grown on a mixture of crude glycerol (CG) and hemicellulose hydrolysate (CGHH) for 36 h of cultivation, whose expression is higher than CG 60 h. Figure S9. Distribution of shared ortholog clusters within differentially expressed genes in each of the three differential expression analyzes. The diagram was generated using OrthoVenn2.

Additional file 1: Figure S1. Assembly contiguity and size of 38 re-assembled genomes. For n = 38 NCBI genomes we were able to find Illumina short-read sequencing data to reassemble these strains. The Icarus plot (output of Quast v5.2.0 run with default parameters) shows the assembly contiguity and size for all 38 re-assemblies together with the corresponding genomes downloaded from NCBI. In addition, re-assemblies and NCBI genomes were decontaminated using CLEAN. The top eleven re-assemblies were finally selected to be integrated in our study and replaced the original NCBI genomes due to higher assembly contiguity and better N50 values. All contigs are sorted by length, starting with the longest contigs on the left and decreasing in length to the right. Thus, it is possible to mark the contigs where 50% (90%) of all the nucleotides in an assembly are covered by this contig and all longer contigs as a measure of assembly contiguity and quality. The purple bars mark contigs where a certain Nx (N50 or N90) is reached in an assembly.

Additional file 7: Figure S7. Location of genes encoding polymorphic membrane proteins in the genome of C. psittaci strain 6BC.

Additional file 5: Figure S5. RAxML tree of the alignment of OmpA amino acid sequences from 61 C. psittaci strains as processed by RIBAP (Group 879). Bootstrap values are indicated at inner nodes. For identical taxa, bootstrap values were discarded, due to the interchangeability of corresponding gene sequences. The colored bar on the right indicates the respective ompA genotypes.

Supplementary data for "Impact of reference design on estimating SARS-CoV-2 lineage abundances from wastewater sequencing data"