General information

How to cite LEADER_RNA?

LEADER_RNA publications

LEADER_RNA Workgroup

User's guide

Principles of prediction process

Database scheme

Additional information

Description of the principles of the prediction process

The analysis of general and translational properties of the mRNAs of eukaryotic genes revealed several parameters allowing to discriminate between the high-and low-expression mRNAs (the set of the high-expression genes was consisted of the tissue-specific (Rbcs, Ca/b .. ), constitutive (actins, tubulins, histones, ribosomal proteins, etc.), and inducible (hsp, alcoholdehydrogenases, aldolases, etc.) genes; the set of low-expression genes was consisted of transcriptional factors, protein kinases, homeobox-containing genes, etc.). The main idea was that the leader sequences of low-expression mRNAs were often hard for the scanning by the 40S ribosomal subunits (according to scanning model, Kozak, 1989).

The results of the analysis demonstrated that some 5'UTR parameters differed significantly between the two samples (formalized description is available in file LEADER_WHY):

  1. The length of 5'UTR.
  2. The nucleotide content in the leader (including the G/C and A/U ratios and GC level, potentiating the formation of the secondary structure).
  3. The presence of AUG codons (in different contexts) within the 5'UTR.
  4. Mono-, di-, and trinucleotide concentrations near the translational start.
  5. The position-dependent nucleotide frequencies near the translational starts.

The computer system determines the set of the above mentioned parameters of the nucleotide sequence of the 5'UTR tested and make the prognosis of its transltional properties and the level of expression of the corresponding gene. The prognosis is made as a sum of all parameters used (computer system allows the user to correct the list of parameters and their relative significance). The use of the system to discriminate the mRNAs of high- and low-expression genes (the control set) showed that 84% of high- and 76% of low-expressed genes were predicted correctly. The prediction was significant at alpha<0.001.

The system may be also useful to design the gene-engineering experiments to predict the changes in translation properties of modified mRNA sequences.

Here you can find examples of translatability prediction for HIGH and LOW expression genes.


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