Вавиловский журнал генетики и селекции (Feb 2017)

Estimation of translational importance of mammalian mRNA nucleotide sequence characteristics based on ribosome profiling data

  • O. A. Volkova,
  • Yu. V. Kondrakhin,
  • R. N. Sharipov

DOI
https://doi.org/10.18699/VJ16.195
Journal volume & issue
Vol. 20, no. 6
pp. 779 – 786

Abstract

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It is known that the 5’ untranslated region (5’ UTR) mRNA characteristics can influence translation initiation efficiency and specificity. Previous knowledge about 5’ UTR characteristics was obtained theoretically and in vitro for mRNA of individual genes. It did not allow systematic analysis of mRNA translationally important parameters. To identify the above mentioned 5’ UTR characteristics, it is necessary to analyze their relationships with the translational activity of the corresponding mRNAs. Until recently, there were no experimental data on translation efficiency. Thanks to ribosome profiling technology, genome-wide experimental data of translation efficiency have been obtained for many eukaryotic mRNAs. Now it seems to be possible to reveal translationally important mRNA parameters and predict translation efficiency based on their nucleotide sequences. The aim of this study was to determine the translational significance of individual 5’ UTR characteristics in accordance with experimental ribosome profiling data. A statistical analysis was carried out for revealing relationships between the human and mouse mRNA nucleotide sequence characteristics and ribosome profiling data. Some of the mRNA parameters influencing translation efficiency were most significant, and the same trends for all three samples analyzed were revealed: a purine at start codon context position –3, upstream AUG presence and G+C complementary nucleotide concentration reduce translation efficiency; whereas gexonucleotides CCGCCA (5’ UTR) and AAGAAA, AAGAAG, AAGCAG, AAAAAG (CDS) increase translation efficiency. A toolkit that allows analyzing the importance of 5’ UTR characteristics and a program for prediction of translation efficiency were developed on the base of the BioUML platform.

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