Transcript Tutorial_11 (2014)

Tutorial 11
RNA Structure Prediction
RNA Structure Prediction
• Introduction – RNA secondary structure
• RNAfold – RNA secondary structure
prediction
• TargetScan – microRNA prediction
Cool story of the day:
How viruses use miRNAs to attack humans
About RNA…
RNA secondary structure
3D perspective
RNA secondary structure types
stem
Structure representations
::::::
free extremes
((())) Stem
<<<>>> Internal Stem
______ Loop
,,,,,,
Internal loop
Directionality
RNA secondary structure prediction
GGGCUAUUAGCUCAGUUGGUUA
GAGCGCACCCCUGAUAAGGGUGA
GGUCGCUGAUUCGAAUUCAGCAU
AGCCCA
Base pair
probability
RNA structure prediction by Vienna RNA
package
RNAfold server
minimum free energy structures and base pair probabilities from
single RNA or DNA sequences.
RNAalifold server
consensus secondary structures from an alignment of several
related RNA or DNA sequences. You need to upload an alignment.
RNAinverse server
design RNA sequences for any desired target secondary structure.
http://rna.tbi.univie.ac.at/
RNAfold
• Gives best stabilized structure (structure with
minimal free energy (MFE))
• Uses a dynamic programming algorithm that
exploits base pairing and thermodynamic
probabilities in order to predict the most likely
structures of an RNA molecule.
RNAfold - input
RNA sequence
RNAfold - output
Minimal free energy
structure
Structure prediction
Frequency of the
structure
Best “average”
structure
Graphic representation
MFE
structure
An average,
may not
exist in the
ensemble
RNAalifold
Structure prediction based on alignments
Alignment
RNAalifold - output
Understanding the color scheme
Lighter color
C-G
U-A
C-G
G-C
U-A
A-U
http://www.almob.org/content/pdf/1748-7188-6-26.pdf
RNAinverse
• Find sequences that match a structure.
• Binding in RNA is based a lot on the structure,
and not only the sequence.
• Helps identify a function.
RNAinverse - input
RNAinverse - output
MicroRNA
• May reside in host
genes or in intragenic
region.
• The RNA structure of
the hairpins in a primiRNA is recognized
by the proteins.
http://www.targetscan.org/
• Search for predicted microRNA targets in
mammals (/worm/fly) 3’ UTRs.
• Find conserved 8mer and 7mer sites that
match the seed region of each miRNA.
• Predictions are ranked based on the
predicted efficacy of targeting as calculated
using the context+ scores of the sites.
Sum of phylogenetic
branch lengths
between species
that contain a site
More negative
scores represent
a more favorable
site
The stability of
of a miRNAtarget duplex
A score reflecting the
probability that a site
is conserved due to
selective
maintenance of
miRNA targeting
rather than by chance
or any other reason.
Mir 31 - broadly conserved* microRNA
* conserved across most vertebrates, usually to zebrafish
Mir 136 - conserved* microRNA
* conserved across most mammals, but usually not beyond placental mammals
Cool Story of the day
How viruses use miRNAs to attack
humans?
“…We developed an algorithm for the prediction of
miRNA targets and applied it to human
cytomegalovirus miRNAs…”
Viruses
• Human cytomegalovirus (HCMV) is known to have
evolved effective immune evasion strategies.
• RepTar has its basis in the observation that miRNA
binding sites can repeat several times in the target’s
3′UTR (1). It therefore searches for repetitive
elements in each 3′UTR sequence and evaluates
these elements as potential miRNA binding sites.
• This algorithm is independent of evolutionary
conservation of the binding sites.
MICB, an immunorelated gene, was among the
highest ranking predicted targets and the top
prediction for hcmv-miR-UL112.
Natural Killer (NK) cells
• NK cells are cytotoxic lymphocyte that kill virus-infected cells
and tumor cells.
• In order to function they should be activated through
receptors. One of these is NKG2D.
• MICB is a stress-induced ligand of NK cells through the NKG2D
receptor).
Cerwenka et al. Nature Reviews Immunology 2001
“…We show that hcmv-miR-UL112 specifically
down-regulates MICB expression during viral
infection, leading to decreased binding of
NKG2D and reduced killing by NK cells…”
“Our results demonstrate a novel miRNA-based
evasion strategy used by HCMV, in which a viral
miRNA directly down-regulates a host immune
defense gene.