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genome browsers (e.g. Ensembl or UCSC). Specific genomic mutations, for example in

human tumors or heart failure, are also deposited in various databases (e.g. OMIM) and

can be used by users. DNA sequencing thus makes it possible to sequence unknown

genomes, such as new resistant bacterial strains, or to determine the underlying mutations

in diseases in medical diagnostics.

Transcriptome sequencing (gene expression sequencing) provides insights into gene

expression, i.e. into the activation of gene transcripts. Common methods are microarray

experiments or newer high-throughput methods such as RNA sequencing. These measure

gene expression (mRNA level) and thus provide information on the corresponding changes

in mRNA (up- or down-regulated), for example after infection or treatment. Meanwhile,

there are increasingly efficient methods that can, for example, measure the expression of

the host and the pathogen in parallel in one cell and thus provide insights into the changes

in both organisms after an infection (dual RNAseq). Subsequent bioinformatic gene

expression analysis can then examine the RNA secondary structure (e.g., RNAfold), the

RNA sequence for regulatory RNA elements such as IRE (e.g., RNAAnalyzer) or in more

detail with regard to possible interaction partners, for example RNA-protein (e.g., catR­

APID, NPInter) or miRNA-mRNA interactions (e.g., miRanda, TargetScan). Numerous

databases already contain gene expression datasets (e.g. GEO, cBioPortal, TCGA or

GENEVESTIGATOR), information on RNA sequence, structure and binding motifs (e.g.

Rfam) or information on specific RNA classes (e.g. miRNA [miRBase], lncRNA

[LNCipedia]) and can be used for own analyses.

Protein sequencing can be done with mass spectroscopy or protein microarrays and

provides information on the amino acid sequence in the protein. It is often of great interest

how the proteome changes under certain conditions, for example after an infection or

therapy. However, one is usually also interested in the changes or modifications in the

amino acid sequence, for example in the functional side, and their effect on protein

9  Complex Systems Behave Fundamentally in a Similar Way