Nascent Ribo-Seq measures ribosomal loading time and reveals kinetic impact on ribosome density

2021 ◽  
Author(s):  
Johanna Schott ◽  
Sonja Reitter ◽  
Doris Lindner ◽  
Jan Grosser ◽  
Marius Bruer ◽  
...  
Keyword(s):  
Ribosome Density

New computational model for miRNA-mediated repression reveals novel regulatory roles of miRNA bindings inside the coding region

2020 ◽  
Author(s):  
Shaked Bergman ◽  
Alon Diament ◽  
Tamir Tuller
Keyword(s):  
Binding Sites ◽  
Supplementary Information ◽  
Coding Region ◽  
Reading Frame ◽  
Coding Sequence ◽  
Elastic Net Regularization ◽  
Physiological Processes ◽  
Ribosome Density ◽  
Weak Binding ◽  
Non Coding Rnas

Abstract Motivation MicroRNAs (miRNAs) are short (∼24nt), non-coding RNAs, which downregulate gene expression in many species and physiological processes. Many details regarding the mechanism which governs miRNA-mediated repression continue to elude researchers. Results We elucidate the interplay between the coding sequence and the 3′UTR, by using elastic net regularization and incorporating translation-related features to predict miRNA-mediated repression. We find that miRNA binding sites at the end of the coding sequence contribute to repression, and that weak binding sites are linked to effective de-repression, possibly as a result of competing with stronger binding sites. Furthermore, we propose a recycling model for miRNAs dissociated from the open reading frame (ORF) by traversing ribosomes, explaining the observed link between increased ribosome density/traversal speed and increased repression. We uncover a novel layer of interaction between the coding sequence and the 3′UTR (untranslated region) and suggest the ORF has a larger role than previously thought in the mechanism of miRNA-mediated repression. Availability and implementation The code is freely available at https://github.com/aescrdni/miRNA_model. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Endurance training lowers ribosome density despite increasing ribosome biogenesis markers in rodent skeletal muscle

2017 ◽  
Vol 10 (1) ◽  
Author(s):  
Matthew A. Romero ◽  
C. Brooks Mobley ◽  
Melissa A. Linden ◽  
Grace Margaret-Eleanor Meers ◽  
Jeffrey S. Martin ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Endurance Training ◽  
Ribosome Biogenesis ◽  
Ribosome Density

scholarly journals Ribosome flow model with extended objects

2017 ◽  
Vol 14 (135) ◽  
pp. 20170128 ◽  
Author(s):  
Yoram Zarai ◽  
Michael Margaliot ◽  
Tamir Tuller
Keyword(s):  
Steady State ◽  
Production Rate ◽  
Protein Production ◽  
Flow Model ◽  
Mean Field ◽  
State Density ◽  
Transition Rates ◽  
Ribosome Density ◽  
Protein Production Rate ◽  
Unique Steady State

We study a deterministic mechanistic model for the flow of ribosomes along the mRNA molecule, called the ribosome flow model with extended objects  (RFMEO). This model encapsulates many realistic features of translation including non-homogeneous transition rates along mRNA, the fact that every ribosome covers several codons, and the fact that ribosomes cannot overtake one another. The RFMEO is a mean-field approximation of an important model from statistical mechanics called the totally asymmetric simple exclusion process with extended objects (TASEPEO). We demonstrate that the RFMEO describes biophysical aspects of translation better than previous mean-field approximations, and that its predictions correlate well with those of TASEPEO. However, unlike TASEPEO, the RFMEO is amenable to rigorous analysis using tools from systems and control theory. We show that the ribosome density profile along the mRNA in the RFMEO converges to a unique steady-state density that depends on the length of the mRNA, the transition rates along it, and the number of codons covered by every ribosome, but not on the initial density of ribosomes along the mRNA. In particular, the protein production rate also converges to a unique steady state. Furthermore, if the transition rates along the mRNA are periodic with a common period  T then the ribosome density along the mRNA and the protein production rate converge to a unique periodic pattern with period  T , that is, the model entrains to periodic excitations in the transition rates. Analysis and simulations of the RFMEO demonstrate several counterintuitive results. For example, increasing the ribosome footprint may sometimes lead to an increase in the production rate. Also, for large values of the footprint the steady-state density along the mRNA may be quite complex (e.g. with quasi-periodic patterns) even for relatively simple (and non-periodic) transition rates along the mRNA. This implies that inferring the transition rates from the ribosome density may be non-trivial. We believe that the RFMEO could be useful for modelling, understanding and re-engineering translation as well as other important biological processes.

scholarly journals RiboAbacus: a model trained on polyribosome images predicts ribosome density and translational efficiency from mammalian transcriptomes

2015 ◽  
Vol 43 (22) ◽  
pp. e153-e153 ◽  
Author(s):  
Fabio Lauria ◽  
Toma Tebaldi ◽  
Lorenzo Lunelli ◽  
Paolo Struffi ◽  
Pamela Gatto ◽  
...  
Keyword(s):  
Translational Efficiency ◽  
Ribosome Density

scholarly journals Inferring translational heterogeneity from ribosome profiling data

2019 ◽  
Author(s):  
Pedro do Couto Bordignon ◽  
Sebastian Pechmann
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Protein Biosynthesis ◽  
Ribosome Profiling ◽  
Translation Regulation ◽  
Messenger Rnas ◽  
Translation Elongation ◽  
Cellular Homeostasis ◽  
Ribosome Density ◽  
Experimental Variability ◽  
Underlying Mechanisms

Translation of messenger RNAs into proteins by the ribosome is the most important step of protein biosynthesis. Accordingly, translation is tightly controlled and heavily regulated to maintain cellular homeostasis. Ribosome profiling (Ribo-seq) has revolutionized the study of translation by revealing many of its underlying mechanisms. However, equally many aspects of translation remain mysterious, in part also due to persisting challenges in the interpretation of data obtained from Ribo-seq experiments. Here, we show that some of the variability observed in Ribo-seq data has biological origins and reflects programmed heterogeneity of translation. To systematically identify sequences that are differentially translated (DT) across mRNAs beyond what can be attributed to experimental variability, we performed a comparative analysis of Ribo-seq data from Saccharomyces cerevisiae and derived a consensus ribosome density profile that reflects consistent signals in individual experiments. Remarkably, the thus identified DT sequences link to mechanisms known to regulate translation elongation and are enriched in genes important for protein and organelle biosynthesis. Our results thus highlight examples of translational heterogeneity that are encoded in the genomic sequences and tuned to optimizing cellular homeostasis. More generally, our work highlights the power of Ribo-seq to understand the complexities of translation regulation.

scholarly journals Deciphering the rules of mRNA structure differentiation in vivo and in vitro with deep neural networks in Saccharomyces cerevisiae

2018 ◽  
Author(s):  
Haopeng Yu ◽  
Wenjing Meng ◽  
Yuanhui Mao ◽  
Yi Zhang ◽  
Qing Sun ◽  
...  
Keyword(s):  
Structural Stability ◽  
Initial Density ◽  
Gc Content ◽  
New Paradigm ◽  
Translation Process ◽  
Accurate Analysis ◽  
Mrna Structure ◽  
Ribosome Density

The structure of mRNA in vivo is influenced by various factors involved in the translation process, resulting in significant differentiation of mRNA structure from that in vitro. Because multiple factors cause the differentiation of in vivo and in vitro mRNA structures, it was difficult to perform a more accurate analysis of mRNA structures in previous studies. In this study, we have proposed a novel application of a deep neural network (DNN) model to predict the structural stability of mRNA in vivo by fitting six quantifiable features that may affect mRNA folding: ribosome density, minimum folding free energy, GC content, mRNA abundance, ribosomal initial density and position of mRNA structure. Simulated mutations of the mRNA structure were designed and then fed into the trained DNN model to compute their structural stability. We found unique effects of these six features on mRNA structural stability in vivo. Strikingly, the ribosome density of the structural region is the most important factor affecting the structural stability of mRNA in vivo, and the strength of the mRNA structure in vitro should have a relatively small effect on its structural stability in vivo. The recruitment of DNNs provides a new paradigm to decipher the differentiation of mRNA structure in vivo and in vitro. This improved knowledge on the mechanisms of factors influencing mRNA structural stability will facilitate the design and functional analysis of mRNA structure in vivo.

scholarly journals Understanding biases in ribosome profiling experiments reveals signatures of translation dynamics in yeast

2015 ◽  
Author(s):  
Jeffrey A Hussmann ◽  
Stephanie Patchett ◽  
Arlen Johnson ◽  
Sara Sawyer ◽  
William H Press
Keyword(s):  
Negative Correlation ◽  
Ribosome Profiling ◽  
Messenger Rnas ◽  
Translation Rate ◽  
Ribosome Density ◽  
Weak Negative Correlation ◽  
Specific Elongation ◽  
Positive Correlations ◽  
Cognate Trna

Ribosome profiling produces snapshots of the locations of actively translating ribosomes on messenger RNAs. These snapshots can be used to make inferences about translation dynamics. Recent ribosome profiling studies in yeast, however, have reached contradictory conclusions regarding the average translation rate of each codon. Some experiments have used cycloheximide (CHX) to stabilize ribosomes before measuring their positions, and these studies all counterintuitively report a weak negative correlation between the translation rate of a codon and the abundance of its cognate tRNA. In contrast, some experiments performed without CHX report strong positive correlations. To explain this contradiction, we identify unexpected patterns in ribosome density downstream of each type of codon in experiments that use CHX. These patterns are evidence that elongation continues to occur in the presence of CHX but with dramatically altered codon-specific elongation rates. The measured positions of ribosomes in these experiments therefore do not reflect the amounts of time ribosomes spend at each position in vivo. These results suggest that conclusions from experiments in yeast using CHX may need reexamination. In particular, we show that in all such experiments, codons decoded by less abundant tRNAs were in fact being translated more slowly before the addition of CHX disrupted these dynamics.

scholarly journals Gene length as a regulator for ribosome recruitment and protein synthesis: theoretical insights

2017 ◽  
Author(s):  
Lucas Dias Fernandes ◽  
Alessandro de Moura ◽  
Luca Ciandrini
Keyword(s):  
Protein Synthesis ◽  
Binding Sites ◽  
Translation Efficiency ◽  
Gene Length ◽  
Translation Rate ◽  
Ribosome Binding Sites ◽  
Transcript Length ◽  
Ribosome Density ◽  
Protein Elongation ◽  
Kinetics Of

AbstractProtein synthesis rates are determined, at the translational level, by properties of the transcript’s sequence. The efficiency of an mRNA can be tuned by varying the ribosome binding sites controlling the recruitment of the ribosomes, or the codon usage establishing the speed of protein elongation. In this work we propose transcript length as a further key determinant of translation efficiency. Based on a physical model that considers the kinetics of ribosomes advancing on the mRNA and diffusing in its surrounding, as well as mRNA circularisation and ribosome drop-off, we explain how the transcript length may play a central role in establishing ribosome recruitment and the overall translation rate of an mRNA. We also demonstrate how this process may be involved in shaping the experimental ribosome density-gene length dependence. Finally, we argue that cells could exploit this mechanism to adjust and balance the usage of its ribosomal resources.

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