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second- and third-best structure), I can see what remains conserved. These are usually also

the structural regions actually present in the cell. In parallel with experiments, this gives a

precise idea of what the RNA structure looks like in the living cell.

Conclusion   

• RNA is an important level of information processing. About half of the human genome

is actively transcribed and new RNAs such as miRNA and lncRNAs highlight the

importance of deciphering the information encoded in RNA. In this chapter, we have

therefore focused on the analysis of RNA sequence, structure and folding energy.

• RNA and regulatory RNA elements can initially be analysed with the RNAAnalyzer

software, the Rfam database and the RNAfold server. For those who want to learn

more, the tutorials show further steps (practice is important here, the tutorials offer a

first introduction) to systematically analyze the transcriptome of a cell (e.g. GEO and

GeneVestigator databases). For more in-depth statistical analysis of gene expression

differences, R and Bioconductor are available. Both are important tools and have to be

learned like a language in order to be able to write instructions for biostatistical analysis

(so-called “scripts”, both are scripting languages).

• In the field of computational analysis of RNA, new surprises and insights can be

expected in the coming years, e.g. strong genetic engineering and matching software

through the CRISPR/Cas9 system and the pathophysiology of newly discovered small

RNAs in many bacteria and infectious agents (sRNAs). Non-coding RNA is also impor­

tant in disease and bioinformatics is helping to uncover this, e.g. chast-lncRNA in heart

failure (Viereck et al. 2016). ◄

2.3

Exercises for Chap. 2

In the exercises, important parts of the book will be dealt with in more detail in order to

consolidate and practise what you have learned. Tasks that are marked as examples serve

as application tasks in which you are to work independently with the computer in order to

become more familiar with bioinformatics. In addition, we have provided numerous tuto­

rials in the appendix, which also support the material of the textbook and the exercises and

should contribute to a better understanding.

We recommend that you briefly review the material from Chap. 2 in Chap. 3 using the

exercises.

Task 2.1

Example: As a result of transcription, a complete RNA sequence (mRNA, but also non-­

coding miRNA, lncRNAetc.) is formed, i.e. a copy of the DNA, whereby the nucleotides

of the DNA (A, T, G and C) are translated into the nucleotides of the RNA (A, U, G and

C) and the deoxyribose is exchanged for ribose. An RNA can form a secondary structure

(alpha-helix and beta-sheet), which can be predicted bioinformatically.

2  Magic RNA