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Translational regulation plays a central role in the global gene expression of a cell, and detection of such regulation has allowed deciphering of critical biological mechanisms. Genome-wide studies of the regulation of translation (translatome) performed on microarrays represent a substantial proportion of studies, alongside with recent advances in deep-sequencing methods. However, there has been a lack of development in specific processing methodologies that deal with the distinct nature of translatome array data. In this study, we confirm that polysome profiling yields skewed data and thus violates the conventional transcriptome analysis assumptions. Using a comprehensive simulation of translatome array data varying the percentage and symmetry of deregulation, we show that conventional analysis methods (Quantile and LOESS normalizations) and statistical tests failed, respectively, to correctly normalize the data and to identify correctly deregulated genes (DEGs). We thus propose a novel analysis methodology available as a CRAN package; Internal Control Analysis of Translatome (INCATome) based on a normalization tied to a group of invariant controls. We confirm that INCATome outperforms the other normalization methods and allows a stringent identification of DEGs. More importantly, INCATome implementation on a biological translatome data set (cells silenced for splicing factor PSF) resulted in the best normalization performance and an improved validation concordance for identification of true positive DEGs. Finally, we provide evidence that INCATome is able to infer novel biological pathways with superior discovery potential, thus confirming the benefits for researchers of implementing INCATome for future translatome studies as well as for existing data sets to generate novel avenues for research., (© 2017 Sbarrato et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.)

We aimed to find candidate molecules possibly involved in the anti-inflammatory activity of shikonin (active compound of "Shikon") by analyzing its effects on gene expression of lipopolysaccharide (LPS)-treated THP-1 macrophages. Polysome-associated mRNAs (those expected to be under translation: translatome) from cells treated with LPS alone (LPS: 5 µg/mL), shikonin alone (S: 100 nM), or LPS plus shikonin (LPS&S) for 3 h were analyzed by DNA microarray followed by detection of enriched pathways/gene ontologies using the tools of the STRING database. Candidate genes in enriched pathways in the comparison of LPS&S cells vs. LPS cells were analyzed by reverse-transcription quantitative real-time PCR (RT-qPCR; 1, 2, and 3 h). DNA microarray showed shikonin significantly influences gene expression. Gene expression changes between LPS&S cells and LPS cells were compared to detect relevant proteins and/or mRNAs underlying its anti-inflammatory effects: shikonin downregulated pathways which were upregulated in LPS cells, for example, 'innate immune response'. Within changed pathways, three genes were selected for RT-qPCR analyses as key candidates influencing inflammatory responses: CYBA (component of the superoxide-generating Nox2 enzyme), GSK3B (controller of cell responses after toll-like receptor stimulation), and EIF4E (a key factor of the eukaryotic translation initiation factor 4F complex that regulates abundance of other proteins involved in immune functions). All three mRNAs were decreased at 2 h, and CYBA continued low at 3 h relative to LPS cells. Given that shikonin decreased the expression of CYBA gene of Nox2, in addition to the direct inhibition of the Nox2 activity that we have previously shown, it is suggested that one of its anti-inflammatory mechanisms could be attenuation of oxidative stress.

Genome-wide studies of transcripts expression help in systematic monitoring of genes and allow targeting of candidate genes for future research. In contrast to relatively stable genomic data, the expression of genes is dynamic and regulated both at time and space level at different level in. The variation in the rate of translation is specific for each protein. Both the inherent nature of an mRNA molecule to be translated and the external environmental stimuli can affect the efficiency of the translation process. In biocontrol agents (BCAs), the molecular response at translational level may represents noise-like response of absolute transcript level and an adaptive response to physiological and pathological situations representing subset of mRNAs population actively translated in a cell. The molecular responses of biocontrol are complex and involve multistage regulation of number of genes. The use of high-throughput techniques has led to rapid increase in volume of transcriptomics data of Trichoderma . In general, almost half of the variations of transcriptome and protein level are due to translational control. Thus, studies are required to integrate raw information from different "omics" approaches for accurate depiction of translational response of BCAs in interaction with plants and plant pathogens. The studies on translational status of only active mRNAs bridging with proteome data will help in accurate characterization of only a subset of mRNAs actively engaged in translation. This review highlights the associated bottlenecks and use of state-of-the-art procedures in addressing the gap to accelerate future accomplishment of biocontrol mechanisms.

Polysomes are macromolecular complexes made up of multiple ribosomes simultaneously translating a single mRNA into polypeptide chains. Together, the cellular mRNAs translated in this way are referred to 'translatome.' Translation determines a cell's overall gene expression profile. Studying translatome leads to a better understanding of the translational machinery and of its complex regulatory pathways. Given its fundamental role in cell homeostasis and division, bacterial translation is an important target for antibiotics. However, there are no detailed protocols for polysome purification from Staphylococcus aureus, the human pathogen responsible for the majority of multi-drug resistance issues. We therefore developed methods for the isolation of active polysomes, ribosomes, and ribosomal subunits, examining the purity and quality of each fraction and monitoring polysomal activity during protein synthesis. These steps are mandatory for the use of purified S. aureus polysomes and ribosomes for structural studies or for genome-scale analysis of most translated mRNAs., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Hormonal signaling pathways control almost every aspect of plant physiology and development. Extensive analysis of hormonal signaling output, i.e., gene expression, has therefore been the focus of many studies. These analyses have been primarily conducted on total extracts derived from a mixture of tissues and cell types, consequentially limiting delineation of precise models. In this chapter, methods for tissue-specific functional genomics are overviewed, in which hormonal responses are analyzed at the transcriptional and the translational levels. Deep sequencing of polysome-associated polyadenylated RNA is employed for cell type-specific quantitation of translatome responses to brassinosteroids. Polysomes are purified by the previously established Translating Ribosome Affinity Purification (TRAP) method, in which the expression of a tagged ribosomal protein is targeted to the tissue of interest, allowing tissue-specific immunopurification of the polysome complexes. The methods presented assess establishment and selection of suitable transgenic lines. A protocol for hormonal treatment of the Arabidopsis thaliana root as a case study, TRAP and linear amplification of the purified polysome-associated polyadenylated RNA are described. Finally, a step-by-step presentation is included of the analysis of the RNA deep-sequencing data and Rscript for plotting hierarchically clustered heatmap of the expressed genes.

Alteration of gene expression is an essential mechanism, which allows plants to respond and adapt to adverse environmental conditions. Transcriptome and proteome analyses in plants exposed to abiotic stresses revealed that protein levels are not correlated with the changes in corresponding mRNAs, indicating regulation at translational level is another major regulator for gene expression. Analysis of translatome, which refers to all mRNAs associated with ribosomes, thus has the potential to bridge the gap between transcriptome and proteome. Polysomal RNA profiling and recently developed ribosome profiling (Ribo-seq) are two main methods for translatome analysis at global level. Here, we describe the classical procedure for polysomal RNA isolation by sucrose gradient ultracentrifugation followed by highthroughput RNA-seq to identify genes regulated at translational level. Polysomal RNA can be further used for a variety of downstream applications including Northern blot analysis, qRT-PCR, RNase protection assay, and microarray-based gene expression profiling.

There is growing recognition that small open reading frames (sORFs) encoding peptides shorter than 100 amino acids are an important class of functional elements in the eukaryotic genome, with several already identified to play critical roles in growth, development, and disease. However, our understanding of their biological importance has been hindered owing to the significant technical challenges limiting their annotation. Here we combined ultra-deep sequencing of ribosome-associated poly-adenylated RNAs with rigorous conservation analysis to identify a comprehensive population of translated sORFs during early Drosophila embryogenesis. In total, we identify 399 sORFs, including those previously annotated but without evidence of translational capacity, those found within transcripts previously classified as non-coding, and those not previously known to be transcribed. Further, we find, for the first time, evidence for translation of many sORFs with different isoforms, suggesting their regulation is as complex as longer ORFs. Furthermore, many sORFs are found not associated with ribosomes in late-stage Drosophila S2 cells, suggesting that many of the translated sORFs may have stage-specific functions during embryogenesis. These results thus provide the first comprehensive annotation of the sORFs present during early Drosophila embryogenesis, a necessary basis for a detailed delineation of their function in embryogenesis and other biological processes., (© The Author 2016. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.)

Gene expression involves multiple steps from the transcription of a mRNA in the nucleus to the production of the encoded protein in the cytoplasm. This final step occurs through a highly regulated process of mRNA translation on ribosomes that is required to maintain cell homeostasis. Alterations in the control of mRNA translation may lead to cell's transformation, a hallmark of cancer development. Indeed, recent advances indicated that increased translation of mRNAs encoding tumor-promoting proteins may be a key mechanism of tumor resistance in several cancers. Moreover, it was found that proteins whose encoding mRNAs are translated at higher efficiencies may be effective biomarkers. Evaluation of global changes in translation efficiency in human tumors has thus the potential of better understanding what can be used as biomarkers and therapeutic targets. Investigating changes in translation efficiency in human cancer cells has been made possible through the development and use of the polyribosome profiling combined with DNA microarray or deep RNA sequencing (RNA-Seq). While helpful, the use of cancer cell lines has many limitations and it is essential to define translational changes in human tumor samples in order to properly prioritize genes implicated in cancer phenotype. We present an optimized polyribosome RNA-Seq protocol suitable for quantitative analysis of mRNA translation that occurs in human tumor samples and murine xenografts. Applying this innovative approach to human tumors, which requires a complementary bioinformatics analysis, unlocks the potential to identify key mRNA which are preferentially translated in tumor tissue compared to benign tissue as well as translational changes which occur following treatment. These technical advances will be of interest to those researching all solid tumors, opening possibilities for understanding what may be therapeutic Achilles heels' or relevant biomarkers., Competing Interests: The authors have declared that no competing interests exist.

Mycoplasma gallisepticum is a bacterium of class Mollicutes which encompasses wall-less bacteria with significantly reduced genomes. Due to their overall reduction and simplicity mycoplasmas serve as a model of minimal cell and are used for systems biology studies. Here we present raw data on translatome (ribosome-bound mRNA) analysis of Mycoplasma gallisepticum under logarithm growth and heat stress. The data supports the publication of "Ribosomal profiling of Mycoplasma gallisepticum " (G. Y. Fisunov, D. V Evsyutina, A. A. Arzamasov, I. O. Butenko, V. M. Govorun, 2015) [1].

Cell identity and function are largely determined by specific gene expression patterns and ultimately by the proteome. Current high-throughput sequencing technologies offer the possibility of quantifying gene expression at high resolution, with minimum input and without the constraints of array-based systems, such as the need for specific probes. In addition, techniques are now available to capture genes that are actively being translated. These techniques use either density gradients or epitope-based immunoprecipitation to purify translating ribosomes and associated mRNAs (i.e., translatomes). More recently, the combination of tissue-specific promoters driving epitope-tagged ribosomes with high-throughput sequencing has allowed the identification of genes and networks unique to specific cell types. Translatome analyses have the potential to unravel genetic programs and cellular responses to environmental stresses at cell-specific resolution. This unit describes steps for the use of epitope-based immunoprecipitation to purify translating ribosomes from soybean and the recovery of mRNA for downstream applications such as gene expression analysis. © 2016 by John Wiley & Sons, Inc., (Copyright © 2016 John Wiley & Sons, Inc.)

Polysome fractionation by sucrose density gradient centrifugation followed by analysis of RNA and protein is a technique that allows to understand the changes in translation of individual mRNAs as well as genome-wide effects on the translatome. Here, we describe the polysome profiling technique and RNA as well as protein isolation procedures from sucrose fractions.

Neuroblastoma is the most common pediatric cancer, arising from the neural crest cells of the sympathetic nervous system. Its most aggressive subtype, characterized by the amplification of the MYCN oncogene, has a dismal prognosis and no effective treatment is available. Understanding the alterations induced by the tumor on the various layers of gene expression is therefore important for a complete characterization of this neuroblastoma subtype and for the discovery of new therapeutic opportunities. Here we describe the profiling of 13 MYCN-amplified neuroblastoma cell lines at the genome (copy number), transcriptome, translatome and miRome levels (GEO series GSE56654, GSE56552 and GSE56655). We provide detailed experimental and data analysis procedures by means of which we derived the results described in [1].

Identifying gene function in specific cells is critical for understanding the processes that make cells unique. Several different methods are available to isolate actively transcribed RNA or actively translated RNA in specific cells at a chosen time point. Cell-specific mRNA isolation can be accomplished by the expression of transgenes in cells of interest, either directly from a specific promoter or using a modular system such as Gal4/UAS or Cre/lox. All of the methods described in this review, namely thiol-labeling of RNA (TU-tagging or RABT), TRAP (translating ribosome affinity purification) and INTACT (isolation of nuclei tagged in specific cell types), allow next generation sequencing, permitting the identification of enriched gene transcripts within the specific cell-type. We describe here the general concept of each method, include examples, evaluate possible problems related to each technique, and suggest the types of questions for which each method is best suited.

Post-transcriptional regulation (PTR) of gene expression is now recognized as a major determinant of cell phenotypes. The recent availability of methods to map protein-RNA interactions in entire transcriptomes such as RIP, CLIP and their variants, together with global polysomal and ribosome profiling techniques, are driving the exponential accumulation of vast amounts of data on mRNA contacts in cells, and of corresponding predictions of PTR events. However, this exceptional quantity of information cannot be exploited at its best to reconstruct potential PTR networks, as it still lies scattered throughout several databases and in isolated reports of single interactions. To address this issue, we developed the second and vastly enhanced version of the Atlas of UTR Regulatory Activity (AURA 2), a meta-database centered on mapping interaction of trans-factors with human and mouse UTRs. AURA 2 includes experimentally demonstrated binding sites for RBPs, ncRNAs, thousands of cis-elements, variations, RNA epigenetics data and more. Its user-friendly interface offers various data-mining features including co-regulation search, network generation and regulatory enrichment testing. Gene expression profiles for many tissues and cell lines can be also combined with these analyses to display only the interactions possible in the system under study. AURA 2 aims at becoming a valuable toolbox for PTR studies and at tracing the road for how PTR network-building tools should be designed. AURA 2 is available at http://aura.science.unitn.it.

Regulation of mRNA translation is a major modulator of gene expression, allowing cells to fine tune protein levels during growth and differentiation and in response to physiological signals and environmental changes. Mass-spectrometry and RNA-sequencing methods now enable global profiling of the translatome, but these still involve significant analytical and economical limitations. We developed a novel system-wide proteomic approach for direct monitoring of translation, termed PUromycin-associated Nascent CHain Proteomics (PUNCH-P), which is based on the recovery of ribosome-nascent chain complexes from cells or tissues followed by incorporation of biotinylated puromycin into newly-synthesized proteins. Biotinylated proteins are then purified by streptavidin and analyzed by mass-spectrometry. Here we present an overview of PUNCH-P, describe other methodologies for global translatome profiling (pSILAC, BONCAT, TRAP/Ribo-tag, Ribo-seq) and provide conceptual comparisons between these methods. We also show how PUNCH-P data can be combined with mRNA measurements to determine relative translation efficiency for specific mRNAs.