Translational control on a global scale
Translational control of gene expression occurs after transcription and helps to determine how many proteins per messenger RNA (mRNA) are produced. Malfunction in this process is crucial to development and memory and contributes to many human diseases. The TRANSLATOMICS (Painting the landscape of translational control of gene expression through meta-analysis of genome wide data sets) project has taken several novel steps to achieve a multidisciplinary approach to study translational control. Data mining over a wide range of studies provided information to derive rules and mechanisms of translational control throughout the whole genome. Researchers combed data repositories for independent comparisons and eliminated them from the study on several counts. Criteria included lack of sound biological underpinning, failure to show differential translation after adjustments for multiple testing and those considered to be non-informative. After identification of differentially translated genes, the scientists singled out a set of co-regulation modules that define higher-order organisation of mRNA translation. Sifting the modules for validity, the researchers found more than 100 operons that coordinate gene expression. Applying network approaches, TRANSLATOMICS researchers then discovered a second level of regulation where the modules were not regulated as units but as pairs. As increased activity in one module is accompanied by lowered in the other, homeostasis can be achieved, for example. The next step is to link these mechanisms with biological phenotypes and disease giving information on the nature of mRNA perturbation. The pipeline for identification of RNA regulatory elements is complete and future research will continue with high-throughput functional validation of the regulatory modules. This revolutionary approach to how translational control is organised on multiple levels promises to deliver new therapies that target normalisation of gene expression. Deregulation of translation is associated with a wide range of cancers, for example. As further research unfolds, it is likely to be found that variants in regulatory regions contribute to complex diseases more than faults in protein production.
Keywords
Translational control, gene expression, cancer, genome-wide, mRNA, disease
