Translational signatures and mRNA levels are highly correlated in human stably expressed genes

Abstract

BackgroundGene expression is one of the most relevant biological processes of living cells. Due to the relative small population sizes, it is predicted that human gene sequences are not strongly influenced by selection towards expression efficiency. One of the major problems in estimating to what extent gene characteristics can be selected to maximize expression efficiency is the wide variation that exists in RNA and protein levels among physiological states and different tissues. Analyses of datasets of stably expressed genes (i.e. with consistent expression between physiological states and tissues) would provide more accurate and reliable measurements of associations between variations of a specific gene characteristic and expression, and how distinct gene features work to optimize gene expression.ResultsUsing a dataset of human genes with consistent expression between physiological states we selected gene sequence signatures related to translation that can predict about 42% of mRNA variation. The prediction can be increased to 51% when selecting genes that are stably expressed in more than 1 tissue. These genes are enriched for translation and ribosome biosynthesis processes and have higher translation efficiency scores, smaller coding sequences and 3′ UTR sizes and lower folding energies when compared to other datasets. Additionally, the amino acid frequencies weighted by expression showed higher correlations with isoacceptor tRNA gene copy number, and smaller absolute correlation values with biosynthetic costs.ConclusionOur results indicate that human gene sequence characteristics related to transcription and translation processes can co-evolve in an integrated manner in order to optimize gene expression.

Multiple correlations of mRNA expression and protein abundance in human cytokine profile

“…Traditionally, people thought that there was good correlation between the level of a single mRNA and that of its protein [1][2][3][4]. And from tons of publications scientists successfully provided protein level evidence to confirm their science finding based on the nucleic acid level and vice versa.…”

“…(3) The different post-translational mechanisms is not yet sufficiently well defined to be able to compute protein concentrations from mRNA. (4) Half-life of proteins. Different proteins may differ substantially in their in vivo half-life and stability [20].…”

Predictive biophysical modeling and understanding of the dynamics of mRNA translation and its evolution

“…It is important to mention that many predictors and models integrated the tAI (or similar measures) into more complicated multivariate models (1–2,47,118–119). Such models try to predict gene expression aspects based on many transcript features, where the tAI (or similar measures) is only one of the features, but often has been one of the most predictive variables (2,47,118–119).…”

“…Such models try to predict gene expression aspects based on many transcript features, where the tAI (or similar measures) is only one of the features, but often has been one of the most predictive variables (2,47,118–119). …”

Identification of suitable adjuvant for vaccine formulation with the Neospora caninum antigen NcSRS2

“…First, the cytokine results are based splenic transcription and not by protein quantification. However, there is a large body of evidence suggesting there is a good correlation between the level of mRNA and its corresponding protein [30][31][32]. A second limitation is that we did not perform N. caninum challenge in the vaccinated experimental groups, such data would have added important information to our results.…”