COMPUTER ANALYSIS OF mRNAs TRANSLATION EFFICIENCY

1
COMPUTER ANALYSIS OF mRNAs TRANSLATION EFFICIENCY
http//wwwmgs.bionet.nsc.ru/systems/LeaderRNA/
Bioinformatics, 1999, vol. 15(7), pp.
704-712. Prediction of eukaryotic mRNA
translational properties. Kochetov A.V.,
Ponomarenko M.P., Frolov A.S., Kisselev L.L.,
Kolchanov N.A.
FEBS Lett. 1998, vol. 440(3), pp.
351-355. Eukaryotic mRNAs encoding abundant and
scarce proteins are statistically dissimilar in
many structural features. Kochetov A.V., Ischenko
I.V., Vorobiev D.G., Kel A.E., Babenko V.N.,
Kisselev L.L., Kolchanov N.A.
Figure 1
2
Figure 1?. WWW interface of the LEADER
systemhttp//wwwmgs.bionet.nsc.ru/mgs/systems/le
aderrna/.
3
Figure 2. The relative abundancies of various
eukaryotic proteins
Figure 3. Sequence data used for analysis
samples of high and low expression mRNAs.
4
The low level of polypeptide production may be
caused by limiting any stage of gene expression.
The high level of polypeptide production should
meet the demand of high efficiency at every
stage of expression
Figure 3a.
5
Figure 4. Scanning model of the translation
initiation of eukaryotic mRNA
6
a)
b)
Figure 5. Comparison of the length of 5' UTR of
high and low expressed eukaryotic mRNAs
7
60S
40S
AUG
AUG
UAA
Figure 6. Efficiency of eukaryotic mRNA
translation initiation can be decreased by false
start codons (upstream AUGs) and stable hairpins
8
a)
b)
c)



Figure 7. Charactersization of AUG-containing
5'-UTRs in high and low expression eukaryotic
mRNAs.
9
Figure 8. Distributions of the best hairpin
energy in the 5'untranslated regions of high and
low expression mRNAs of eukaryotic genes
10
a)
b)
Figure 9. Characterization of the local context
of start codons in high and low expression mRNAs.
11
Figure 10. Portions of high and low expression
mRNAs containing different types of stop
codons. The most effective termination codon is
UAA.
12
Figure 13. Input interface of the program for
prediction of eukaryotic mRNAs translational
efficiency. The list of characteristics used for
calculations.
13
a)
b)
Figure 12. Classification of control sample of
high and low expression mRNAs by analysis of
features (Fi) of their 5'UTRs
14
The user interface of program for translation
efficiency prediction.
15
Figure 14. Output interface of the program for
prediction of eukaryotic mRNAs translational
efficiency. For prediction was taken the
random sequence with equal nucleotide frequency
composition.
16
Figure 15. Output interface of the program for
prediction of eukaryotic mRNAs translational
efficiency. For prediction was taken the
sequence with the high level of expression (AC
AT30SRS13).
17
Figure 16. Output interface of the program for
prediction of eukaryotic mRNAs translational
efficiency. For prediction was taken the
sequence with low level of expression (AC
AT31834).
18
1.

Translational features of high expression mRNAs
are similar to random sequences whereas
translational features of low expression mRNAs
have been decreased by selection
.
It was found for 5UTR
secondary structure
High
Random
Low

Translational
mRNA
activity
2.
Translational features of low expression mRNAs
are similar to random sequences whereas
translational features of high expression mRNAs
have been decreased by selection during evolution.
High
Low
Random


Translational
mRNA
activity
19
3.
Translational features of high e
xpression mRNAs have been increased and
translational features of
low expression mRNAs have been decreased by
selection during evolution.
Low
High
Random


Translational
mRNA
activity
4. Translational features of both high and low
expression mRNAs have been increased but at
different
extents.
It was found for
false
positive
AUG
codons
Low
High
Random
in 5UTR

Translational
mRNA
activity
Figure 17. Possible scenario of evolutionary
emergence of structural and contextual
characteristics of high and low expression mRNAs.