A comprehensive tRNA deletion library unravels the genetic architecture of the tRNA pool

Identification of the mRNA targets of tRNA-specific regulation using genome-wide simulation of translation

tRNA gene copy number is a primary determinant of tRNA abundance and therefore the rate at which each tRNA delivers amino acids to the ribosome during translation. Low-abundance tRNAs decode rare codons slowly, but it is unclear which genes might be subject to tRNA-mediated regulation of expression. Here, those mRNA targets were identified via global simulation of translation. In-silico mRNA translation rates were compared for each mRNA in both wild-type and a \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\rm{tRNA}}_{{\rm{CUG}}}^{{\rm{Gln}}}$\end{document}sup70-65 mutant, which exhibits a pseudohyphal growth phenotype and a 75% slower CAG codon translation rate. Of 4900 CAG-containing mRNAs, 300 showed significantly reduced in silico translation rates in a simulated tRNA mutant. Quantitative immunoassay confirmed that the reduced translation rates of sensitive mRNAs were \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\rm{tRNA}}_{{\rm{CUG}}}^{{\rm{Gln}}}$\end{document} concentration-dependent. Translation simulations showed that reduced \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\rm{tRNA}}_{{\rm{CUG}}}^{{\rm{Gln}}}$\end{document} concentrations triggered ribosome queues, which dissipated at reduced translation initiation rates. To validate this prediction experimentally, constitutive gcn2 kinase mutants were used to reduce in vivo translation initiation rates. This repaired the relative translational rate defect of target mRNAs in the sup70-65 background, and ameliorated sup70-65 pseudohyphal growth phenotypes. We thus validate global simulation of translation as a new tool to identify mRNA targets of tRNA-specific gene regulation.

Codon-Driven Translational Efficiency Is Stable across Diverse Mammalian Cell States

Whether codon usage fine-tunes mRNA translation in mammals remains controversial, with recent papers suggesting that production of proteins in specific Gene Ontological (GO) pathways can be regulated by actively modifying the codon and anticodon pools in different cellular conditions. In this work, we compared the sequence content of genes in specific GO categories with the exonic genome background. Although a substantial fraction of variability in codon usage could be explained by random sampling, almost half of GO sets showed more variability in codon usage than expected by chance. Nevertheless, by quantifying translational efficiency in healthy and cancerous tissues in human and mouse, we demonstrated that a given tRNA pool can equally well translate many different sets of mRNAs, irrespective of their cell-type specificity. This disconnect between variations in codon usage and the stability of translational efficiency is best explained by differences in GC content between gene sets. GC variation across the mammalian genome is most likely a result of the interplay between genome repair and gene duplication mechanisms, rather than selective pressures caused by codon-driven translational rates. Consequently, codon usage differences in mammalian transcriptomes are most easily explained by well-understood mutational biases acting on the underlying genome.

The fitness landscape of a tRNA gene

Fitness landscapes describe the genotype-fitness relationship and represent major determinants of evolutionary trajectories. However, the vast genotype space, coupled with the difficulty of measuring fitness, has hindered the empirical determination of fitness landscapes. Combining precise gene replacement and next-generation sequencing, we quantified Darwinian fitness under a high-temperature challenge for more than 65,000 yeast strains, each carrying a unique variant of the single-copy tRNA(CCU)(Arg) gene at its native genomic location. Approximately 1% of single point mutations in the gene were beneficial and 42% were deleterious. Almost half of all mutation pairs exhibited statistically significant epistasis, which had a strong negative bias, except when the mutations occurred at Watson-Crick paired sites. Fitness was broadly correlated with the predicted fraction of correctly folded transfer RNA (tRNA) molecules, thereby revealing a biophysical basis of the fitness landscape.

The Fungus Candida albicans Tolerates Ambiguity at Multiple Codons

The ascomycete Candida albicans is a normal resident of the gastrointestinal tract of humans and other warm-blooded animals. It occurs in a broad range of body sites and has high capacity to survive and proliferate in adverse environments with drastic changes in oxygen, carbon dioxide, pH, osmolarity, nutrients, and temperature. Its biology is unique due to flexible reassignment of the leucine CUG codon to serine and synthesis of statistical proteins. Under standard growth conditions, CUG sites incorporate leucine (3% of the times) and serine (97% of the times) on a proteome wide scale, but leucine incorporation fluctuates in response to environmental stressors and can be artificially increased up to 98%. In order to determine whether such flexibility also exists at other codons, we have constructed several serine tRNAs that decode various non-cognate codons. Expression of these tRNAs had minor effects on fitness, but growth of the mistranslating strains at different temperatures, in medium with different pH and nutrients composition was often enhanced relatively to the wild type (WT) strain, supporting our previous data on adaptive roles of CUG ambiguity in variable growth conditions. Parallel evolution of the recombinant strains (100 generations) followed by full genome resequencing identified various strain specific single nucleotide polymorphisms (SNP) and one SNP in the deneddylase (JAB1) gene in all strains. Since JAB1 is a subunit of the COP9 signalosome complex, which interacts with cullin (Cdc53p) to mediate degradation of a variety of cellular proteins, our data suggest that neddylation plays a key role in tolerance and adaptation to codon ambiguity in C. albicans.

Large-Effect Beneficial Synonymous Mutations Mediate Rapid and Parallel Adaptation in a Bacterium

Contrary to previous understanding, recent evidence indicates that synonymous codon changes may sometimes face strong selection. However, it remains difficult to generalize the nature, strength, and mechanism(s) of such selection. Previously, we showed that synonymous variants of a key enzyme-coding gene (fae) of Methylobacterium extorquens AM1 decreased enzyme production and reduced fitness dramatically. We now show that during laboratory evolution, these variants rapidly regained fitness via parallel yet variant-specific, highly beneficial point mutations in the N-terminal region of fae. These mutations (including four synonymous mutations) had weak but consistently positive impacts on transcript levels, enzyme production, or enzyme activity. However, none of the proposed mechanisms (including internal ribosome pause sites or mRNA structure) predicted the fitness impact of evolved or additional, engineered point mutations. This study shows that synonymous mutations can be fixed through strong positive selection, but the mechanism for their benefit varies depending on the local sequence context.

A relay race on the evolutionary adaptation spectrum

Adaptation is the process in which organisms improve their fitness by changing their phenotype using genetic or non-genetic mechanisms. The adaptation toolbox consists of varied molecular and genetic means that we posit span an almost continuous "adaptation spectrum." Different adaptations are characterized by the time needed for organisms to attain them and by their duration. We suggest that organisms often adapt by progressing the adaptation spectrum, starting with rapidly attained physiological and epigenetic adaptations and culminating with slower long-lasting genetic ones. A tantalizing possibility is that earlier adaptations facilitate realization of later ones.

Unbiased Quantitative Models of Protein Translation Derived from Ribosome Profiling Data

Translation of RNA to protein is a core process for any living organism. While for some steps of this process the effect on protein production is understood, a holistic understanding of translation still remains elusive. In silico modelling is a promising approach for elucidating the process of protein synthesis. Although a number of computational models of the process have been proposed, their application is limited by the assumptions they make. Ribosome profiling (RP), a relatively new sequencing-based technique capable of recording snapshots of the locations of actively translating ribosomes, is a promising source of information for deriving unbiased data-driven translation models. However, quantitative analysis of RP data is challenging due to high measurement variance and the inability to discriminate between the number of ribosomes measured on a gene and their speed of translation. We propose a solution in the form of a novel multi-scale interpretation of RP data that allows for deriving models with translation dynamics extracted from the snapshots. We demonstrate the usefulness of this approach by simultaneously determining for the first time per-codon translation elongation and per-gene translation initiation rates of Saccharomyces cerevisiae from RP data for two versions of the Totally Asymmetric Exclusion Process (TASEP) model of translation. We do this in an unbiased fashion, by fitting the models using only RP data with a novel optimization scheme based on Monte Carlo simulation to keep the problem tractable. The fitted models match the data significantly better than existing models and their predictions show better agreement with several independent protein abundance datasets than existing models. Results additionally indicate that the tRNA pool adaptation hypothesis is incomplete, with evidence suggesting that tRNA post-transcriptional modifications and codon context may play a role in determining codon elongation rates.

Translation, the process of synthesizing proteins from mRNA templates, is an essential biological process in all living organisms. A better understanding of this process will have ramifications in various fields—from gene regulation, disease understanding and medicine to biotechnology and synthetic biology. Nonetheless, a holistic understanding of the processes remains elusive, making computational modelling a promising approach for studying it. However, accurate modelling of translation is challenging due to many assumptions made by such models and due to the sheer number of parameters that need to be specified. Here, we propose to fit models of translation onto ribosome profiling measurements, which record snapshots of the locations of actively translating ribosomes on mRNAs from millions of cells. We develop statistical and computational methods for fitting the Totally Asymmetric Exclusion Process (TASEP) models of translation on these measurements and verify them by deriving highly accurate translation models for the baker’s yeast Saccharomyces cerevisiae, which outperform existing models on independent datasets. We find that fitted elongation rate parameters from the derived models deviate significantly from the widely accepted tRNA pool adaptation hypothesis.

Maximizing protein translation rate in the non-homogeneous ribosome flow model: a convex optimization approach

Translation is an important stage in gene expression. During this stage, macro-molecules called ribosomes travel along the mRNA strand linking amino acids together in a specific order to create a functioning protein. An important question, related to many biomedical disciplines, is how to maximize protein production. Indeed, translation is known to be one of the most energy-consuming processes in the cell, and it is natural to assume that evolution shaped this process so that it maximizes the protein production rate. If this is indeed so then one can estimate various parameters of the translation machinery by solving an appropriate mathematical optimization problem. The same problem also arises in the context of synthetic biology, namely, re-engineer heterologous genes in order to maximize their translation rate in a host organism. We consider the problem of maximizing the protein production rate using a computational model for translation-elongation called the ribosome flow model (RFM). This model describes the flow of the ribosomes along an mRNA chain of length n using a set of n first-order nonlinear ordinary differential equations. It also includes n + 1 positive parameters: the ribosomal initiation rate into the mRNA chain, and n elongation rates along the chain sites. We show that the steady-state translation rate in the RFM is a strictly concave function of its parameters. This means that the problem of maximizing the translation rate under a suitable constraint always admits a unique solution, and that this solution can be determined using highly efficient algorithms for solving convex optimization problems even for large values of n. Furthermore, our analysis shows that the optimal translation rate can be computed based only on the optimal initiation rate and the elongation rate of the codons near the beginning of the ORF. We discuss some applications of the theoretical results to synthetic biology, molecular evolution, and functional genomics.

Chromatin-dependent regulation of RNA polymerases II and III activity throughout the transcription cycle

The particular behaviour of eukaryotic RNA polymerases along different gene regions and amongst distinct gene functional groups is not totally understood. To cast light onto the alternative active or backtracking states of RNA polymerase II, we have quantitatively mapped active RNA polymerases at a high resolution following a new biotin-based genomic run-on (BioGRO) technique. Compared with conventional profiling with chromatin immunoprecipitation, the analysis of the BioGRO profiles in Saccharomyces cerevisiae shows that RNA polymerase II has unique activity profiles at both gene ends, which are highly dependent on positioned nucleosomes. This is the first demonstration of the in vivo influence of positioned nucleosomes on transcription elongation. The particular features at the 5' end and around the polyadenylation site indicate that this polymerase undergoes extensive specific-activity regulation in the initial and final transcription elongation phases. The genes encoding for ribosomal proteins show distinctive features at both ends. BioGRO also provides the first nascentome analysis for RNA polymerase III, which indicates that transcription of tRNA genes is poorly regulated at the individual copy level. The present study provides a novel perspective of the transcription cycle that incorporates inactivation/reactivation as an important aspect of RNA polymerase dynamics.

Why should cancer biologists care about tRNAs? tRNA synthesis, mRNA translation and the control of growth

Transfer RNAs (tRNAs) are essential for mRNA translation. They are transcribed in the nucleus by RNA polymerase III and undergo many modifications before contributing to cytoplasmic protein synthesis. In this review I highlight our understanding of how tRNA biology may be linked to the regulation of mRNA translation, growth and tumorigenesis. First, I review how oncogenes and tumour suppressor signalling pathways, such as the PI3 kinase/TORC1, Ras/ERK, Myc, p53 and Rb pathways, regulate Pol III and tRNA synthesis. In several cases, this regulation contributes to cell, tissue and body growth, and has implications for our understanding of tumorigenesis. Second, I highlight some recent work, particularly in model organisms such as yeast and Drosophila, that shows how alterations in tRNA synthesis may be not only necessary, but also sufficient to drive changes in mRNA translation and growth. These effects may arise due to both absolute increases in total tRNA levels, but also changes in the relative levels of tRNAs in the overall pool. Finally, I review some recent studies that have revealed how tRNA modifications (amino acid acylation, base modifications, subcellular shuttling, and cleavage) can be regulated by growth and stress cues to selectively influence mRNA translation. Together these studies emphasize the importance of the regulation of tRNA synthesis and modification as critical control points in protein synthesis and growth. This article is part of a Special Issue entitled: Translation and Cancer.

Synonymous codons, ribosome speed, and eukaryotic gene expression regulation

Quantitative control of gene expression occurs at multiple levels, including the level of translation. Within the overall process of translation, most identified regulatory processes impinge on the initiation phase. However, recent studies have revealed that the elongation phase can also regulate translation if elongation and initiation occur with specific, not mutually compatible rate parameters. Translation elongation then limits the overall amount of protein that can be made from an mRNA. Several recently discovered control mechanisms of biological pathways are based on such elongation control. Here, we review the molecular mechanisms that determine ribosome speed in eukaryotic organisms, and discuss under which conditions ribosome speed can become the controlling parameter of gene expression levels.

High-resolution mapping of transcriptional dynamics across tissue development reveals a stable mRNA-tRNA interface

The genetic code is an abstraction of how mRNA codons and tRNA anticodons molecularly interact during protein synthesis; the stability and regulation of this interaction remains largely unexplored. Here, we characterized the expression of mRNA and tRNA genes quantitatively at multiple time points in two developing mouse tissues. We discovered that mRNA codon pools are highly stable over development and simply reflect the genomic background; in contrast, precise regulation of tRNA gene families is required to create the corresponding tRNA transcriptomes. The dynamic regulation of tRNA genes during development is controlled in order to generate an anticodon pool that closely corresponds to messenger RNAs. Thus, across development, the pools of mRNA codons and tRNA anticodons are invariant and highly correlated, revealing a stable molecular interaction interlocking transcription and translation.

Different types of secondary information in the genetic code

Whole-genome and functional analyses suggest a wealth of secondary or auxiliary genetic information (AGI) within the redundancy component of the genetic code. Although there are multiple aspects of biased codon use, we focus on two types of auxiliary information: codon-specific translational pauses that can be used by particular proteins toward their unique folding and biased codon patterns shared by groups of functionally related mRNAs with coordinate regulation. AGI is important to genetics in general and to human disease; here, we consider influences of its three major components, biased codon use itself, variations in the tRNAome, and anticodon modifications that distinguish synonymous decoding. AGI is plastic and can be used by different species to different extents, with tissue-specificity and in stress responses. Because AGI is species-specific, it is important to consider codon-sensitive experiments when using heterologous systems; for this we focus on the tRNA anticodon loop modification enzyme, CDKAL1, and its link to type 2 diabetes. Newly uncovered tRNAome variability among humans suggests roles in penetrance and as a genetic modifier and disease modifier. Development of experimental and bioinformatics methods are needed to uncover additional means of auxiliary genetic information.

Modify or die?--RNA modification defects in metazoans

Chemical RNA modifications are present in all kingdoms of life and many of these post-transcriptional modifications are conserved throughout evolution. However, most of the research has been performed on single cell organisms, whereas little is known about how RNA modifications contribute to the development of metazoans. In recent years, the identification of RNA modification genes in genome wide association studies (GWAS) has sparked new interest in previously neglected genes. In this review, we summarize recent findings that connect RNA modification defects and phenotypes in higher eukaryotes. Furthermore, we discuss the implications of aberrant tRNA modification in various human diseases including metabolic defects, mitochondrial dysfunctions, neurological disorders, and cancer. As the molecular mechanisms of these diseases are being elucidated, we will gain first insights into the functions of RNA modifications in higher eukaryotes and finally understand their roles during development.

tRNA genes rapidly change in evolution to meet novel translational demands

Changes in expression patterns may occur when organisms are presented with new environmental challenges, for example following migration or genetic changes. To elucidate the mechanisms by which the translational machinery adapts to such changes, we perturbed the tRNA pool of Saccharomyces cerevisiae by tRNA gene deletion. We then evolved the deletion strain and observed that the genetic adaptation was recurrently based on a strategic mutation that changed the anticodon of other tRNA genes to match that of the deleted one. Strikingly, a systematic search in hundreds of genomes revealed that anticodon mutations occur throughout the tree of life. We further show that the evolution of the tRNA pool also depends on the need to properly couple translation to protein folding. Together, our observations shed light on the evolution of the tRNA pool, demonstrating that mutation in the anticodons of tRNA genes is a common adaptive mechanism when meeting new translational demands.

DOI:http://dx.doi.org/10.7554/eLife.01339.001

Genes contain the blueprints for the proteins that are essential for countless biological functions and processes, and the path that leads from a particular gene to the corresponding protein is long and complex. The genetic information stored in the DNA must first be transcribed to produce a messenger RNA molecule, which then has to be translated to produce a string of amino acids that fold to form a protein. The translation step is performed by a molecular machine called the ribosome, with transfer RNA molecules bringing the amino acids that are needed to make the protein.

The information in messenger RNA is stored as a series of letters, with groups of three letters called codons representing the different amino acids. Since there are four letters—A, C, G and U—it is possible to form 64 different codons. And since there are only 20 amino acids, two or more different codons can specify the same amino acid (for example, AGU and AGC both specify serine), and two or more different transfer RNA molecules can take this amino acid to the ribosome. Moreover, some codons are found more often than others in the messenger RNA molecules, so the genes that encode the related transfer RNA molecules are more common than the genes for other transfer RNA molecules.

Environmental pressures mean that organisms must adapt to survive, with some genes and proteins increasing in importance, and others becoming less important. Clearly the relative numbers of the different transfer RNA molecules will also need to change to reflect these evolutionary changes, but the details of how this happens were not understood.

Now Yona et al. have explored this issue by studying yeast cells that lack a gene for one of the less common transfer RNA molecules (corresponding to the codon AGG, which specifies the amino acid arginine). At first this mutation resulted in slower growth of the yeast cells, but after being allowed to evolve over 200 generations, the rate of growth matched that of a normal strain with all transfer RNA genes. Yona et al. found that the gene for a more common transfer RNA molecule, corresponding to the codon AGA, which also specifies arginine, had mutated to AGG. As a result, the mutated yeast was eventually able to produce proteins as quickly as wild type yeast. Moreover, further experiments showed that the levels of some transfer RNAs are kept deliberately low in order to slow down the production of proteins so as to ensure that the proteins assume their correct structure.

But does the way these cells evolved in the lab resemble what happened in nature? To address this question Yona et al. examined a database of transfer RNA sequences from more than 500 species, and found evidence for the same codon-based switching mechanism in many species across the tree of life.

DOI:http://dx.doi.org/10.7554/eLife.01339.002