This document discusses BioPython modules for handling RNA sequences containing modified nucleosides. There are 115 known post-transcriptionally modified nucleosides in RNA and several nomenclature schemes exist. The solution involves cloning a branch of the BioPython repository containing an RNA alphabet with modified nucleotides and using it to represent sequences containing modifications like 2-O-methyloadenosine. Example applications presented are ModeRNA for RNA structure modeling and CompaRNA for benchmarking RNA structure prediction methods, both of which use open source tools including BioPython.

1. BioPython modules for handling
RNA sequences containing modified
nucleosides.
Tomasz Puton, Kristian Rother,
Magdalena Rother, Janusz M. Bujnicki
Laboratory of Structural Bioinformatics
Adam Mickiewicz University, Poznań, Poland
http://bioinformatics.amu.edu.pl/Lab/
International Institute of Molecular and Cell Biology
Warsaw, Poland http://iimcb.genesilico.pl/

2. BioPython – a set of freely available tools for
biological computation written in Python.
http://biopython.org/

3. ACUGAUC

4. Guanosine (G)
ACUGAUC Cytidine (C)
Adenosine (A) Uridine (U)

5. ACUGAUC
>>> from Bio.Alphabet.IUPAC import
unambiguous_rna
>>> from Bio.Seq import Seq
>>> seq = Seq(‘ACUGAUC’, unambiguous_rna)

6. ACUGAUC
>>> from Bio.Alphabet.IUPAC import
unambiguous_rna
>>> from Bio.Seq import Seq
>>> seq = Seq(‘ACUGAUC’, unambiguous_rna)
>>> print seq.reverse_complement()
GAUCAGU

7. Problem:
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moved, renamed, or deleted. Verify that the link points to the
correct file and location.
There are 115 known post-
transcriptionally modified nucleosides
in RNA.
Known as: Moreover, several nomenclature
 wybutosine
schemes exist in parallel.
 yW
 Y
 16G

8. Solution:
http://github.com/krother/biopython
branch rna_alphabet
$ git clone git://github.com/krother/biopython.git
$ cd biopython
$ git checkout rna_alphabet

9. Solution:
$ python
>>> from Bio.Alphabet.ModifiedRNAAlphabet
import modified_rna
>>> from Bio.RNA.RNASeq import RNASeq

10. Solution:
$ python
>>> from Bio.Alphabet.ModifiedRNAAlphabet
import modified_rna
>>> from Bio.RNA.RNASeq import RNASeq
>>> seq = RNASeq('AG:7CU', modified_rna)

11. Solution:
$ python
>>> from Bio.Alphabet.ModifiedRNAAlphabet
import modified_rna
>>> from Bio.RNA.RNASeq import RNASeq
>>> seq = RNASeq('AG:7CU', modified_rna)
>>> print seq[2].full_name
2-O-methyloadenosine

12. Solution:
$ python
>>> from Bio.Alphabet.ModifiedRNAAlphabet
import modified_rna
>>> from Bio.RNA.RNASeq import RNASeq
>>> seq = RNASeq('AG:7CU', modified_rna)
>>> print seq[2].full_name
2-O-methyloadenosine
>>> print seq[3].long_abbrev
m7G

13. http://modomics.genesilico.pl/

14. Example applications (part 1):
ModeRNA: A tool for comparative modeling of
RNA 3D structure.
http://iimcb.genesilico.pl/moderna/
Our software models modified RNA 3D structures!
Open source project!

15. Example applications (part 2):
CompaRNA: A server for continuous benchmarking of
automated methods for RNA structure prediction
POSTER NUMBER: W17
SUNDAY, JULY 11: 12:40 p.m. – 2.30 p.m.
http://comparna.amu.edu.pl/
Uses open source software e.g.
BioPython, PyCogent & ModeRNA

16. Thank you for attention!
Tomasz Puton Kristian Rother
t.puton@amu.edu.pl krother@rubor.de
Magdalena Rother Janusz M. Bujnicki
lenam@amu.edu.pl iamb@genesilico.pl