Codon optimality, bias and usage in translation and mRNA decay

Weak selection on synonymous codons substantially inflates dN/dS estimates in bacteria

Synonymous codon substitutions are not always selectively neutral as revealed by several types of analyses, including studies of codon usage patterns among genes. We analyzed codon usage in 13 bacterial genomes sampled from across a large order of bacteria, Enterobacterales, and identified presumptively neutral and selected classes of synonymous substitutions. To estimate substitution rates, given a neutral/selected classification of synonymous substitutions, we developed a flexible [Formula: see text] substitution model that allows multiple classes of synonymous substitutions. Under this multiclass synonymous substitution (MSS) model, the denominator of [Formula: see text] includes only the strictly neutral class of synonymous substitutions. On average, the value of [Formula: see text] under the MSS model was 80% of that under the standard codon model in which all synonymous substitutions are assumed to be neutral. The indication is that conventional [Formula: see text] analyses overestimate these values and thus overestimate the frequency of positive diversifying selection and underestimate the strength of purifying selection. To quantify the strength of selection necessary to explain this reduction, we developed a model of selected compensatory codon substitutions. The reduction in synonymous substitution rate, and thus the contribution that selection makes to codon bias variation among genes, can be adequately explained by very weak selection, with a mean product of population size and selection coefficient, [Formula: see text].

Transcription, mRNA export and immune evasion shape the codon usage of viruses

The nucleotide composition, dinucleotide composition, and codon usage of many viruses differs from their hosts. These differences arise because viruses are subject to unique mutation and selection pressures that do not apply to host genomes; however, the molecular mechanisms that underlie these evolutionary forces are unclear. Here, we analysed the patterns of codon usage in 1,520 vertebrate-infecting viruses, focusing on parameters known to be under selection and associated with gene regulation. We find that GC content, dinucleotide content, and splicing and m6A modification-related sequence motifs are associated with the type of genetic material (DNA or RNA), strandedness, and replication compartment of viruses. In an experimental follow-up, we find that the effects of GC content on gene expression depend on whether the genetic material is delivered to the cell as DNA or mRNA, whether it is transcribed by endogenous or exogenous RNA polymerase, and whether transcription takes place in the nucleus or cytoplasm. Our results suggest that viral codon usage cannot be explained by a simple adaptation to the codon usage of the host - instead, it reflects the combination of multiple selective and mutational pressures, including the need for efficient transcription, export, and immune evasion.

Porcine Reproductive and Respiratory Syndrome Virus: Immune Escape and Application of Reverse Genetics in Attenuated Live Vaccine Development

Porcine reproductive and respiratory syndrome virus (PRRSV), an RNA virus widely prevalent in pigs, results in significant economic losses worldwide. PRRSV can escape from the host immune response in several processes. Vaccines, including modified live vaccines and inactivated vaccines, are the best available countermeasures against PRRSV infection. However, challenges still exist as the vaccines are not able to induce broad protection. The reason lies in several facts, mainly the variability of PRRSV and the complexity of the interaction between PRRSV and host immune responses, and overcoming these obstacles will require more exploration. Many novel strategies have been proposed to construct more effective vaccines against this evolving and smart virus. In this review, we will describe the mechanisms of how PRRSV induces weak and delayed immune responses, the current vaccines of PRRSV, and the strategies to develop modified live vaccines using reverse genetics systems.

Codon Bias Can Determine Sorting of a Potassium Channel Protein

Due to the redundancy of the genetic code most amino acids are encoded by multiple synonymous codons. It has been proposed that a biased frequency of synonymous codons can affect the function of proteins by modulating distinct steps in transcription, translation and folding. Here, we use two similar prototype K⁺ channels as model systems to examine whether codon choice has an impact on protein sorting. By monitoring transient expression of GFP-tagged channels in mammalian cells, we find that one of the two channels is sorted in a codon and cell cycle-dependent manner either to mitochondria or the secretory pathway. The data establish that a gene with either rare or frequent codons serves, together with a cell-state-dependent decoding mechanism, as a secondary code for sorting intracellular membrane proteins.

Chloroplast genomes in Populus (Salicaceae): comparisons from an intensively sampled genus reveal dynamic patterns of evolution

The chloroplast is one of two organelles containing a separate genome that codes for essential and distinct cellular functions such as photosynthesis. Given the importance of chloroplasts in plant metabolism, the genomic architecture and gene content have been strongly conserved through long periods of time and as such are useful molecular tools for evolutionary inferences. At present, complete chloroplast genomes from over 4000 species have been deposited into publicly accessible databases. Despite the large number of complete chloroplast genomes, comprehensive analyses regarding genome architecture and gene content have not been conducted for many lineages with complete species sampling. In this study, we employed the genus Populus to assess how more comprehensively sampled chloroplast genome analyses can be used in understanding chloroplast evolution in a broadly studied lineage of angiosperms. We conducted comparative analyses across Populus in order to elucidate variation in key genome features such as genome size, gene number, gene content, repeat type and number, SSR (Simple Sequence Repeat) abundance, and boundary positioning between the four main units of the genome. We found that some genome annotations were variable across the genus owing in part from errors in assembly or data checking and from this provided corrected annotations. We also employed complete chloroplast genomes for phylogenetic analyses including the dating of divergence times throughout the genus. Lastly, we utilized re-sequencing data to describe the variations of pan-chloroplast genomes at the population level for P. euphratica. The analyses used in this paper provide a blueprint for the types of analyses that can be conducted with publicly available chloroplast genomes as well as methods for building upon existing datasets to improve evolutionary inference.

RNA therapeutics for cardiovascular disease

PURPOSE OF REVIEW

The development of mRNA vaccines against coronavirus disease 2019 has brought worldwide attention to the transformative potential of RNA-based therapeutics. The latter is essentially biological software that can be rapidly designed and generated, with an extensive catalog of applications. This review aims to highlight the mechanisms of action by which RNA-based drugs can affect specific gene targets and how RNA drugs can be employed to treat cardiovascular disease, with the focus on the therapeutics being evaluated in clinical trials. The recent advances in nanotechnology aiding the translation of such therapies into the clinic are also discussed.

RECENT FINDINGS

There is a growing body of studies demonstrating utility of RNA for targeting previously 'undruggable' pathways involved in development and progression of cardiovascular disease. Some challenges in RNA delivery have been overcome thanks to nanotechnology. There are several RNA-based drugs to treat hypercholesterolemia and myocardial infarction which are currently in clinical trials.

SUMMARY

RNA therapeutics is a rapidly emerging field of biotherapeutics based upon a powerful and versatile platform with a nearly unlimited capacity to address unmet clinical needs. These therapeutics are destined to change the standard of care for many diseases, including cardiovascular disease.

A role for circular code properties in translation

Circular codes represent a form of coding allowing detection/correction of frame-shift errors. Building on recent theoretical advances on circular codes, we provide evidence that protein coding sequences exhibit in-frame circular code marks, that are absent in introns and are intimately linked to the keto-amino transformation of codon bases. These properties strongly correlate with translation speed, codon influence and protein synthesis levels. Strikingly, circular code marks are absent at the beginning of coding sequences, but stably occur 40 codons after the initiator codon, hinting at the translation elongation process. Finally, we use the lens of circular codes to show that codon influence on translation correlates with the strong-weak dichotomy of the first two bases of the codon. The results can lead to defining new universal tools for sequence indicators and sequence optimization for bioinformatics and biotechnological applications, and can shed light on the molecular mechanisms behind the decoding process.

Codon-based indices for modeling gene expression and transcript evolution

Codon usage bias (CUB) refers to the phenomena that synonymous codons are used in different frequencies in most genes and organisms. The general assumption is that codon biases reflect a balance between mutational biases and natural selection. Today we understand that the codon content is related and can affect all gene expression steps. Starting from the 1980s, codon-based indices have been used for answering different questions in all biomedical fields, including systems biology, agriculture, medicine, and biotechnology. In general, codon usage bias indices weigh each codon or a small set of codons to estimate the fitting of a certain coding sequence to a certain phenomenon (e.g., bias in codons, adaptation to the tRNA pool, frequencies of certain codons, transcription elongation speed, etc.) and are usually easy to implement. Today there are dozens of such indices; thus, this paper aims to review and compare the different codon usage bias indices, their applications, and advantages. In addition, we perform analysis that demonstrates that most indices tend to correlate even though they aim to capture different aspects. Due to the centrality of codon usage bias on different gene expression steps, it is important to keep developing new indices that can capture additional aspects that are not modeled with the current indices.

Preclinical evaluation for engraftment of CD34+ cells gene-edited at the sickle cell disease locus in xenograft mouse and non-human primate models

Sickle cell disease (SCD) is caused by a 20A > T mutation in the β-globin gene. Genome-editing technologies have the potential to correct the SCD mutation in hematopoietic stem cells (HSCs), producing adult hemoglobin while simultaneously eliminating sickle hemoglobin. Here, we developed high-efficiency viral vector-free non-footprint gene correction in SCD CD34+ cells with electroporation to deliver SCD mutation-targeting guide RNA, Cas9 endonuclease, and 100-mer single-strand donor DNA encoding intact β-globin sequence, achieving therapeutic-level gene correction at DNA (∼30%) and protein (∼80%) levels. Gene-edited SCD CD34+ cells contributed corrected cells 6 months post-xenograft mouse transplant without off-target δ-globin editing. We then developed a rhesus β-to-βs-globin gene conversion strategy to model HSC-targeted genome editing for SCD and demonstrate the engraftment of gene-edited CD34+ cells 10-12 months post-transplant in rhesus macaques. In summary, gene-corrected CD34+ HSCs are engraftable in xenograft mice and non-human primates. These findings are helpful in designing HSC-targeted gene correction trials.

Insights into the evolutionary forces that shape the codon usage in the viral genome segments encoding intrinsically disordered protein regions

Intrinsically disordered regions/proteins (IDRs) are abundant across all the domains of life, where they perform important regulatory roles and supplement the biological functions of structured proteins/regions (SRs). Despite the multifunctionality features of IDRs, several interrogations on the evolution of viral genomic regions encoding IDRs in diverse viral proteins remain unreciprocated. To fill this gap, we benchmarked the findings of two most widely used and reliable intrinsic disorder prediction algorithms (IUPred2A and ESpritz) to a dataset of 6108 reference viral proteomes to unravel the multifaceted evolutionary forces that shape the codon usage in the viral genomic regions encoding for IDRs and SRs. We found persuasive evidence that the natural selection predominantly governs the evolution of codon usage in regions encoding IDRs by most of the viruses. In addition, we confirm not only that codon usage in regions encoding IDRs is less optimized for the protein synthesis machinery (transfer RNAs pool) of their host than for those encoding SRs, but also that the selective constraints imposed by codon bias sustain this reduced optimization in IDRs. Our analysis also establishes that IDRs in viruses are likely to tolerate more translational errors than SRs. All these findings hold true, irrespective of the disorder prediction algorithms used to classify IDRs. In conclusion, our study offers a novel perspective on the evolution of viral IDRs and the evolutionary adaptability to multiple taxonomically divergent hosts.

MiniCAFE, a CRISPR/Cas9-based compact and potent transcriptional activator, elicits gene expression in vivo

CRISPR-mediated gene activation (CRISPRa) is a promising therapeutic gene editing strategy without inducing DNA double-strand breaks (DSBs). However, in vivo implementation of these CRISPRa systems remains a challenge. Here, we report a compact and robust miniCas9 activator (termed miniCAFE) for in vivo activation of endogenous target genes. The system relies on recruitment of an engineered minimal nuclease-null Cas9 from Campylobacter jejuni and potent transcriptional activators to a target locus by a single guide RNA. It enables robust gene activation in human cells even with a single DNA copy and is able to promote lifespan of Caenorhabditis elegans through activation of longevity-regulating genes. As proof-of-concept, delivered within an all-in-one adeno-associated virus (AAV), miniCAFE can activate Fgf21 expression in the liver and regulate energy metabolism in adult mice. Thus, miniCAFE holds great therapeutic potential against human diseases.

Genome-wide analysis of lncRNA stability in human

Transcript stability is associated with many biological processes, and the factors affecting mRNA stability have been extensively studied. However, little is known about the features related to human long noncoding RNA (lncRNA) stability. By inhibiting transcription and collecting samples in 10 time points, genome-wide RNA-seq studies was performed in human lung adenocarcinoma cells (A549) and RNA half-life datasets were constructed. The following observations were obtained. First, the half-life distributions of both lncRNAs and messanger RNAs (mRNAs) with one exon (lnc-human1 and m-human1) were significantly different from those of both lncRNAs and mRNAs with more than one exon (lnc-human2 and m-human2). Furthermore, some factors such as full-length transcript secondary structures played a contrary role in lnc-human1 and m-human2. Second, through the half-life comparisons of nucleus- and cytoplasm-specific and common lncRNAs and mRNAs, lncRNAs (mRNAs) in the nucleus were found to be less stable than those in the cytoplasm, which was derived from transcripts themselves rather than cellular location. Third, kmers-based protein−RNA or RNA−RNA interactions promoted lncRNA stability from lnc-human1 and decreased mRNA stability from m-human2 with high probability. Finally, through applying deep learning−based regression, a non-linear relationship was found to exist between the half-lives of lncRNAs (mRNAs) and related factors. The present study established lncRNA and mRNA half-life regulation networks in the A549 cell line and shed new light on the degradation behaviors of both lncRNAs and mRNAs.

Transcript stability is important for many biological processes. However, little is known about the features related to human lncRNA stability. Through quantitative analysis between the half-lives of lncRNAs (mRNAs) and various factors, we found a nonlinear relationship between the half-lives of lncRNAs (mRNAs) and the related factors and their combinations. Our research provided a comprehensive understanding of lncRNA stability. Further efforts are needed to develop an accurate quantitative prediction model for the half-lives of lncRNA (mRNA).

mRNA vaccines for COVID-19: what, why and how

The Coronavirus disease-19 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus -2 (SARS-CoV-2), has impacted human lives in the most profound ways with millions of infections and deaths. Scientists and pharmaceutical companies have been in race to produce vaccines against SARS-CoV-2. Vaccine generation usually demands years of developing and testing for efficacy and safety. However, it only took less than one year to generate two mRNA vaccines from their development to deployment. The rapid production time, cost-effectiveness, versatility in vaccine design, and clinically proven ability to induce cellular and humoral immune response have crowned mRNA vaccines with spotlights as most promising vaccine candidates in the fight against the pandemic. In this review, we discuss the general principles of mRNA vaccine design and working mechanisms of the vaccines, and provide an up-to-date summary of pre-clinical and clinical trials on seven anti-COVID-19 mRNA candidate vaccines, with the focus on the two mRNA vaccines already licensed for vaccination. In addition, we highlight the key strategies in designing mRNA vaccines to maximize the expression of immunogens and avoid intrinsic innate immune response. We also provide some perspective for future vaccine development against COVID-19 and other pathogens.

Synonymous mutations that regulate translation speed might play a non-negligible role in liver cancer development

Background

Synonymous mutations do not change the protein sequences. Automatically, they have been regarded as neutral events and are ignored in the mutation-based cancer studies. However, synonymous mutations will change the codon optimality, resulting in altered translational velocity.

Methods

We fully utilized the transcriptome and translatome of liver cancer and normal tissue from ten patients. We profiled the mutation spectrum and examined the effect of synonymous mutations on translational velocity.

Results

Synonymous mutations that increase the codon optimality significantly enhanced the translational velocity, and were enriched in oncogenes. Meanwhile, synonymous mutations decreasing codon optimality slowed down translation, and were enriched in tumor suppressor genes. These synonymous mutations significantly contributed to the translational changes in tumor samples compared to normal samples.

Conclusions

Synonymous mutations might play a role in liver cancer development by altering codon optimality and translational velocity. Synonymous mutations should no longer be ignored in the genome-wide studies.

Synonymous variants that disrupt messenger RNA structure are significantly constrained in the human population

BACKGROUND

The role of synonymous single-nucleotide variants in human health and disease is poorly understood, yet evidence suggests that this class of "silent" genetic variation plays multiple regulatory roles in both transcription and translation. One mechanism by which synonymous codons direct and modulate the translational process is through alteration of the elaborate structure formed by single-stranded mRNA molecules. While tools to computationally predict the effect of non-synonymous variants on protein structure are plentiful, analogous tools to systematically assess how synonymous variants might disrupt mRNA structure are lacking.

RESULTS

We developed novel software using a parallel processing framework for large-scale generation of secondary RNA structures and folding statistics for the transcriptome of any species. Focusing our analysis on the human transcriptome, we calculated 5 billion RNA-folding statistics for 469 million single-nucleotide variants in 45,800 transcripts. By considering the impact of all possible synonymous variants globally, we discover that synonymous variants predicted to disrupt mRNA structure have significantly lower rates of incidence in the human population.

CONCLUSIONS

These findings support the hypothesis that synonymous variants may play a role in genetic disorders due to their effects on mRNA structure. To evaluate the potential pathogenic impact of synonymous variants, we provide RNA stability, edge distance, and diversity metrics for every nucleotide in the human transcriptome and introduce a "Structural Predictivity Index" (SPI) to quantify structural constraint operating on any synonymous variant. Because no single RNA-folding metric can capture the diversity of mechanisms by which a variant could alter secondary mRNA structure, we generated a SUmmarized RNA Folding (SURF) metric to provide a single measurement to predict the impact of secondary structure altering variants in human genetic studies.

A rare germline CDKN2A variant (47T>G; p16-L16R) predisposes carriers to pancreatic cancer by reducing cell cycle inhibition

Germline mutations in CDKN2A, encoding the tumor suppressor p16, are responsible for a large proportion of familial melanoma cases and also increase risk of pancreatic cancer. We identified four families through pancreatic cancer probands that were affected by both cancers. These families bore a germline missense variant of CDKN2A (47T>G), encoding a p16-L16R mutant protein associated with high cancer occurrence. Here, we investigated the biological significance of this variant. When transfected into p16-null pancreatic cancer cells, p16-L16R was expressed at lower levels than wild-type (WT) p16. In addition, p16-L16R was unable to bind CDK4 or CDK6 compared with WT p16, as shown by coimmunoprecipitation assays and also was impaired in its ability to inhibit the cell cycle, as demonstrated by flow cytometry analyses. In silico molecular modeling predicted that the L16R mutation prevents normal protein folding, consistent with the observed reduction in expression/stability and diminished function of this mutant protein. We isolated normal dermal fibroblasts from members of the families expressing WT or L16R proteins to investigate the impact of endogenous p16-L16R mutant protein on cell growth. In culture, p16-L16R fibroblasts grew at a faster rate, and most survived until later passages than p16-WT fibroblasts. Further, western blotting demonstrated that p16 protein was detected at lower levels in p16-L16R than in p16-WT fibroblasts. Together, these results suggest that the presence of a CDKN2A (47T>G) mutant allele contributes to an increased risk of pancreatic cancer as a result of reduced p16 protein levels and diminished p16 tumor suppressor function.

Ribosome states signal RNA quality control

Eukaryotic cells integrate multiple quality control (QC) responses during protein synthesis in the cytoplasm. These QC responses are signaled by slow or stalled elongating ribosomes. Depending on the nature of the delay, the signal may lead to translational repression, messenger RNA decay, ribosome rescue, and/or nascent protein degradation. Here, we discuss how the structure and composition of an elongating ribosome in a troubled state determine the downstream quality control pathway(s) that ensue. We highlight the intersecting pathways involved in RNA decay and the crosstalk that occurs between RNA decay and ribosome rescue.

The molecular biology of FMRP: new insights into fragile X syndrome

Fragile X mental retardation protein (FMRP) is the product of the fragile X mental retardation 1 gene (FMR1), a gene that - when epigenetically inactivated by a triplet nucleotide repeat expansion - causes the neurodevelopmental disorder fragile X syndrome (FXS). FMRP is a widely expressed RNA-binding protein with activity that is essential for proper synaptic plasticity and architecture, aspects of neural function that are known to go awry in FXS. Although the neurophysiology of FXS has been described in remarkable detail, research focusing on the molecular biology of FMRP has only scratched the surface. For more than two decades, FMRP has been well established as a translational repressor; however, recent whole transcriptome and translatome analyses in mouse and human models of FXS have shown that FMRP is involved in the regulation of nearly all aspects of gene expression. The emerging mechanistic details of the mechanisms by which FMRP regulates gene expression may offer ways to design new therapies for FXS.

Full-length ribosome density prediction by a multi-input and multi-output model

Translation elongation is regulated by a series of complicated mechanisms in both prokaryotes and eukaryotes. Although recent advance in ribosome profiling techniques has enabled one to capture the genome-wide ribosome footprints along transcripts at codon resolution, the regulatory codes of elongation dynamics are still not fully understood. Most of the existing computational approaches for modeling translation elongation from ribosome profiling data mainly focus on local contextual patterns, while ignoring the continuity of the elongation process and relations between ribosome densities of remote codons. Modeling the translation elongation process in full-length coding sequence (CDS) level has not been studied to the best of our knowledge. In this paper, we developed a deep learning based approach with a multi-input and multi-output framework, named RiboMIMO, for modeling the ribosome density distributions of full-length mRNA CDS regions. Through considering the underlying correlations in translation efficiency among neighboring and remote codons and extracting hidden features from the input full-length coding sequence, RiboMIMO can greatly outperform the state-of-the-art baseline approaches and accurately predict the ribosome density distributions along the whole mRNA CDS regions. In addition, RiboMIMO explores the contributions of individual input codons to the predictions of output ribosome densities, which thus can help reveal important biological factors influencing the translation elongation process. The analyses, based on our interpretable metric named codon impact score, not only identified several patterns consistent with the previously-published literatures, but also for the first time (to the best of our knowledge) revealed that the codons located at a long distance from the ribosomal A site may also have an association on the translation elongation rate. This finding of long-range impact on translation elongation velocity may shed new light on the regulatory mechanisms of protein synthesis. Overall, these results indicated that RiboMIMO can provide a useful tool for studying the regulation of translation elongation in the range of full-length CDS.

Translation elongation is a process in which amino acids are linked into proteins by ribosomes in cells. Translation elongation rates along the mRNAs are not constant, and are regulated by a series of mechanisms, such as codon rarity and mRNA stability. In this study, we modeled the translation elongation process at a full-length coding sequence level and developed a deep learning based approach to predict the translation elongation rates from mRNA sequences, through extracting the regulatory codes of elongation rates from the contextual sequences. The analyses, based on our interpretable metric named codon impact score, for the first time (to the best of our knowledge), revealed that in addition to the neighboring codons of the ribosomal A sites, the remote codons may also have an important impact on the translation elongation rates. This new finding may stimulate additional experiments and shed light on the regulatory mechanisms of protein synthesis.

Another layer of complexity in Staphylococcus aureus methionine biosynthesis control: unusual RNase III-driven T-box riboswitch cleavage determines met operon mRNA stability and decay

In Staphylococcus aureus, de novo methionine biosynthesis is regulated by a unique hierarchical pathway involving stringent-response controlled CodY repression in combination with a T-box riboswitch and RNA decay. The T-box riboswitch residing in the 5′ untranslated region (met leader RNA) of the S. aureus metICFE-mdh operon controls downstream gene transcription upon interaction with uncharged methionyl-tRNA. met leader and metICFE-mdh (m)RNAs undergo RNase-mediated degradation in a process whose molecular details are poorly understood. Here we determined the secondary structure of the met leader RNA and found the element to harbor, beyond other conserved T-box riboswitch structural features, a terminator helix which is target for RNase III endoribonucleolytic cleavage. As the terminator is a thermodynamically highly stable structure, it also forms posttranscriptionally in met leader/ metICFE-mdh read-through transcripts. Cleavage by RNase III releases the met leader from metICFE-mdh mRNA and initiates RNase J-mediated degradation of the mRNA from the 5′-end. Of note, metICFE-mdh mRNA stability varies over the length of the transcript with a longer lifespan towards the 3′-end. The obtained data suggest that coordinated RNA decay represents another checkpoint in a complex regulatory network that adjusts costly methionine biosynthesis to current metabolic requirements.

Disrupting upstream translation in mRNAs is associated with human disease

Ribosome-profiling has uncovered pervasive translation in non-canonical open reading frames, however the biological significance of this phenomenon remains unclear. Using genetic variation from 71,702 human genomes, we assess patterns of selection in translated upstream open reading frames (uORFs) in 5’UTRs. We show that uORF variants introducing new stop codons, or strengthening existing stop codons, are under strong negative selection comparable to protein-coding missense variants. Using these variants, we map and validate gene-disease associations in two independent biobanks containing exome sequencing from 10,900 and 32,268 individuals, respectively, and elucidate their impact on protein expression in human cells. Our results suggest translation disrupting mechanisms relating uORF variation to reduced protein expression, and demonstrate that translation at uORFs is genetically constrained in 50% of human genes.

The significance of translated upstream open reading frames is not well known. Here, the authors investigate genetic variants in these regions, finding that they are under high evolutionary constraint and may contribute to disease.

OTTER, a new method quantifying absolute amounts of tRNAs

To maintain optimal proteome, both codon choice of each mRNA and supply of aminoacyl-tRNAs are two principal factors in translation. Recent reports have revealed that the amounts of tRNAs in cells are more dynamic than we had expected. High-throughput methods such as RNA-Seq and microarrays are versatile for comprehensive detection of changes in individual tRNA amounts, but they suffer from inability to assess signal production efficiencies of individual tRNA species. Thus, they are not the perfect choice to measure absolute amounts of tRNAs. Here, we introduce a novel method for this purpose, termed Oligonucleotide-directed Three-prime Terminal Extension of RNA (OTTER), which employs fluorescence-labeling at the 3'-terminus of a tRNA by optimized reverse primer extension and an assessment step of each labeling efficiency by northern blotting. Using this method, we quantified the absolute amounts of the 34 individual and 4 pairs of isoacceptor tRNAs out of the total 42 nuclear-encoded isoacceptors in the yeast Saccharomyces cerevisiae. We found that the amounts of tRNAs in log phase yeast cells grown in a rich glucose medium range from 0.030 to 0.73 pmol/µg RNA. The tRNA amounts seem to be altered at the isoacceptor level by a few folds in response to physiological growing conditions. The data obtained by OTTER are poorly correlated with those by simple RNA-Seq, marginally with those by microarrays and by microscale thermophoresis. However, the OTTER data showed good agreement with the data obtained by 2D-gel analysis of in vivo radiolabeled RNAs. Thus, OTTER is a suitable method for quantifying absolute amounts of tRNAs at the level of isoacceptor resolution.

The expanding world of tRNA modifications and their disease relevance

Transfer RNA (tRNA) is an adapter molecule that links a specific codon in mRNA with its corresponding amino acid during protein synthesis. tRNAs are enzymatically modified post-transcriptionally. A wide variety of tRNA modifications are found in the tRNA anticodon, which are crucial for precise codon recognition and reading frame maintenance, thereby ensuring accurate and efficient protein synthesis. In addition, tRNA-body regions are also frequently modified and thus stabilized in the cell. Over the past two decades, 16 novel tRNA modifications were discovered in various organisms, and the chemical space of tRNA modification continues to expand. Recent studies have revealed that tRNA modifications can be dynamically altered in response to levels of cellular metabolites and environmental stresses. Importantly, we now understand that deficiencies in tRNA modification can have pathological consequences, which are termed 'RNA modopathies'. Dysregulation of tRNA modification is involved in mitochondrial diseases, neurological disorders and cancer.

Massively parallel gene expression variation measurement of a synonymous codon library

BACKGROUND

Cell-to-cell variation in gene expression strongly affects population behavior and is key to multiple biological processes. While codon usage is known to affect ensemble gene expression, how codon usage influences variation in gene expression between single cells is not well understood.

RESULTS

Here, we used a Sort-seq based massively parallel strategy to quantify gene expression variation from a green fluorescent protein (GFP) library containing synonymous codons in Escherichia coli. We found that sequences containing codons with higher tRNA Adaptation Index (TAI) scores, and higher codon adaptation index (CAI) scores, have higher GFP variance. This trend is not observed for codons with high Normalized Translation Efficiency Index (nTE) scores nor from the free energy of folding of the mRNA secondary structure. GFP noise, or squared coefficient of variance (CV2), scales with mean protein abundance for low-abundant proteins but does not change at high mean protein abundance.

CONCLUSIONS

Our results suggest that the main source of noise for high-abundance proteins is likely not originating at translation elongation. Additionally, the drastic change in mean protein abundance with small changes in protein noise seen from our library implies that codon optimization can be performed without concerning gene expression noise for biotechnology applications.

Integrated analyses of translatome and proteome identify the rules of translation selectivity in RPS14-deficient cells

In ribosomopathies, the Diamond-Blackfan anemia (DBA) or 5q- syndrome, ribosomal protein (RP) genes are affected by mutation or deletion, resulting in bone marrow erythroid hypoplasia. Unbalanced production of ribosomal subunits leading to a limited ribosome cellular content regulates translation at the expense of the master erythroid transcription factor GATA1. In RPS14-deficient cells mimicking 5q- syndrome erythroid defects, we show that the transcript length, codon bias of the coding sequence (CDS) and 3’UTR (untranslated region) structure are the key determinants of translation. In these cells, short transcripts with a structured 3’UTR and high codon adaptation index (CAI) showed a decreased translation efficiency. Quantitative analysis of the whole proteome confirmed that the post-transcriptional changes depended on the transcript characteristics that governed the translation efficiency in conditions of low ribosome availability. In addition, proteins involved in normal erythroid differentiation share most determinants of translation selectivity. Our findings thus indicate that impaired erythroid maturation due to 5q- syndrome may proceed from a translational selectivity at the expense of the erythroid differentiation program, and suggest that an interplay between the CDS and UTR may regulate mRNA translation.

The effects of codon bias and optimality on mRNA and protein regulation

The central dogma of molecular biology entails that genetic information is transferred from nucleic acid to proteins. Notwithstanding retro-transcribing genetic elements, DNA is transcribed to RNA which in turn is translated into proteins. Recent advancements have shown that each stage is regulated to control protein abundances for a variety of essential physiological processes. In this regard, mRNA regulation is essential in fine-tuning or calibrating protein abundances. In this review, we would like to discuss one of several mRNA-intrinsic features of mRNA regulation that has been gaining traction of recent-codon bias and optimality. Specifically, we address the effects of codon bias with regard to codon optimality in several biological processes centred on translation, such as mRNA stability and protein folding among others. Finally, we examine how different organisms or cell types, through this system, are able to coordinate physiological pathways to respond to a variety of stress or growth conditions.

Systematic Quantification of Sequence and Structural Determinants Controlling mRNA stability in Bacterial Operons

mRNA degradation is a central process that affects all gene expression levels, and yet, the determinants that control mRNA decay rates remain poorly characterized. Here, we applied a synthetic biology, learn-by-design approach to elucidate the sequence and structural determinants that control mRNA stability in bacterial operons. We designed, constructed, and characterized 82 operons in Escherichia coli, systematically varying RNase binding site characteristics, translation initiation rates, and transcriptional terminator efficiencies in the 5' untranslated region (UTR), intergenic, and 3' UTR regions, followed by measuring their mRNA levels using reverse transcription quantitative polymerase chain reaction (RT-qPCR) assays during exponential growth. We show that introducing long single-stranded RNA into 5' UTRs reduced mRNA levels by up to 9.4-fold and that lowering translation rates reduced mRNA levels by up to 11.8-fold. We also found that RNase binding sites in intergenic regions had much lower effects on mRNA levels. Surprisingly, changing the transcriptional termination efficiency or introducing long single-stranded RNA into 3' UTRs had no effect on upstream mRNA levels. From these measurements, we developed and validated biophysical models of ribosome protection and RNase activity with excellent quantitative agreement. We also formulated design rules to rationally control a mRNA's stability, facilitating the automated design of engineered genetic systems with desired functionalities.

The regulation of protein translation and its implications for cancer

In addition to the deregulation of gene transcriptions and post-translational protein modifications, the aberrant translation from mRNAs to proteins plays an important role in the pathogenesis of various cancers. Targeting mRNA translation are expected to become potential approaches for anticancer treatments. Protein translation is affected by many factors including translation initiation factors and RNA-binding proteins. Recently, modifications of mRNAs mainly N6-methyladenine (m⁶A) modification and noncoding RNAs, such as microRNAs and long noncoding RNAs are involved. In this review, we generally summarized the recent advances on the regulation of protein translation by the interplay between mRNA modifications and ncRNAs. By doing so, we hope this review could offer some hints for the development of novel approaches in precision therapy of human cancers.

Eliciting the silent lucensomycin biosynthetic pathway in Streptomyces cyanogenus S136 via manipulation of the global regulatory gene adpA

Actinobacteria are among the most prolific sources of medically and agriculturally important compounds, derived from their biosynthetic gene clusters (BGCs) for specialized (secondary) pathways of metabolism. Genomics witnesses that the majority of actinobacterial BGCs are silent, most likely due to their low or zero transcription. Much effort is put into the search for approaches towards activation of silent BGCs, as this is believed to revitalize the discovery of novel natural products. We hypothesized that the global transcriptional factor AdpA, due to its highly degenerate operator sequence, could be used to upregulate the expression of silent BGCs. Using Streptomyces cyanogenus S136 as a test case, we showed that plasmids expressing either full-length adpA or its DNA-binding domain led to significant changes in the metabolome. These were evident as changes in the accumulation of colored compounds, bioactivity, as well as the emergence of a new pattern of secondary metabolites as revealed by HPLC-ESI-mass spectrometry. We further focused on the most abundant secondary metabolite and identified it as the polyene antibiotic lucensomycin. Finally, we uncovered the entire gene cluster for lucensomycin biosynthesis (lcm), that remained elusive for five decades until now, and outlined an evidence-based scenario for its adpA-mediated activation.

Potential role of the X circular code in the regulation of gene expression

The X circular code is a set of 20 trinucleotides (codons) that has been identified in the protein-coding genes of most organisms (bacteria, archaea, eukaryotes, plasmids, viruses). It has been shown previously that the X circular code has the important mathematical property of being an error-correcting code. Thus, motifs of the X circular code, i.e. a series of codons belonging to X and called X motifs, allow identification and maintenance of the reading frame in genes. X motifs are significantly enriched in protein-coding genes, but have also been identified in many transfer RNA (tRNA) genes and in important functional regions of the ribosomal RNA (rRNA), notably in the peptidyl transferase center and the decoding center. Here, we investigate the potential role of X motifs as functional elements of protein-coding genes. First, we identify the codons of the X circular code which are frequent or rare in each domain of life (archaea, bacteria, eukaryota) and show that, for the amino acids with the highest codon bias, the preferred codon is often an X codon. We also observe a correlation between the 20 X codons and the optimal codons/dicodons that have been shown to influence translation efficiency. Then, we examined recently published experimental results concerning gene expression levels in diverse organisms. The approach used is the analysis of X motifs according to their density d_s(X), i.e. the number of X motifs per kilobase in a gene sequence s. Surprisingly, this simple parameter identifies several unexpected relations between the X circular code and gene expression. For example, the X motifs are significantly enriched in the minimal gene set belonging to the three domains of life, and in codon-optimized genes. Furthermore, the density of X motifs generally correlates with experimental measures of translation efficiency and mRNA stability. Taken together, these results lead us to propose that the X motifs may represent a genetic signal contributing to the maintenance of the correct reading frame and the optimization and regulation of gene expression.

A Trans-Omics Comparison Reveals Common Gene Expression Strategies in Four Model Organisms and Exposes Similarities and Differences between Them

The ultimate goal of gene expression regulation is on the protein level. However, because the amounts of mRNAs and proteins are controlled by their synthesis and degradation rates, the cellular amount of a given protein can be attained by following different strategies. By studying omics data for six expression variables (mRNA and protein amounts, plus their synthesis and decay rates), we previously demonstrated the existence of common expression strategies (CESs) for functionally related genes in the yeast Saccharomyces cerevisiae. Here we extend that study to two other eukaryotes: the yeast Schizosaccharomyces pombe and cultured human HeLa cells. We also use genomic data from the model prokaryote Escherichia coli as an external reference. We show that six-variable profiles (6VPs) can be constructed for every gene and that these 6VPs are similar for genes with similar functions in all the studied organisms. The differences in 6VPs between organisms can be used to establish their phylogenetic relationships. The analysis of the correlations among the six variables supports the hypothesis that most gene expression control occurs in actively growing organisms at the transcription rate level, and that translation plays a minor role. We propose that living organisms use CESs for the genes acting on the same physiological pathways, especially for those belonging to stable macromolecular complexes, but CESs have been modeled by evolution to adapt to the specific life circumstances of each organism.

Inferring translational heterogeneity from Saccharomyces cerevisiae ribosome profiling

Translation of mRNAs 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. Through a comparative analysis of Ribo-seq data from Saccharomyces cerevisiae, we systematically identify short 3-codon sequences that are differentially translated (DT) across mRNAs, that is, identical sequences that are translated sometimes fast and sometimes slowly beyond what can be attributed to variability between 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.

Co-evolution between codon usage and protein-protein interaction in bacteria

We study the correlation between the codon usage bias of genetic sequences and the network features of protein-protein interaction (PPI) in bacterial species. We use PCA techniques in the space of codon bias indices to show that genes with similar patterns of codon usage have a significantly higher probability that their encoded proteins are functionally connected and interacting. Importantly, this signal emerges when multiple aspects of codon bias are taken into account at the same time. The present study extends our previous observations on E. coli over a wide set of 34 bacteria. These findings could allow for future investigations on the possible effects of codon bias on the topology of the PPI network, with the aim of improving existing bioinformatics methods for predicting protein interactions.

Effects of codon usage on gene expression are promoter context dependent

Codon usage bias is a universal feature of all genomes. Although codon usage has been shown to regulate mRNA and protein levels by influencing mRNA decay and transcription in eukaryotes, little or no genome-wide correlations between codon usage and mRNA levels are detected in mammalian cells, raising doubt on the significance of codon usage effect on gene expression. Here we show that gene-specific regulation reduces the genome-wide codon usage and mRNA correlations: Constitutively expressed genes exhibit much higher genome-wide correlations than differentially expressed genes from fungi to human cells. Using Drosophila S2 cells as a model system, we showed that the effect of codon usage on mRNA expression level is promoter-dependent. Regions downstream of the core promoters of differentially expressed genes can repress the codon usage effects on mRNA expression. An element in the Hsp70 promoter was identified to be necessary and sufficient for this inhibitory effect. The promoter-dependent codon usage effects on mRNA levels are regulated at the transcriptional level through modulation of histone modifications, nucleosome densities and premature termination. Together, our results demonstrate that promoters play a major role in determining whether codon usage influences gene expression and further establish the transcription-dependent codon usage effects on gene expression.

Modification of Transfer RNA Levels Affects Cyclin Aggregation and the Correct Duplication of Yeast Cells

Codon usage bias (the preferential use of certain synonymous codons (optimal) over others is found at the organism level (intergenomic) within specific genomes (intragenomic) and even in certain genes. Whether it is the result of genetic drift due to GC/AT content and/or natural selection is a topic of intense debate. Preferential codons are mostly found in genes encoding highly-expressed proteins, while lowly-expressed proteins usually contain a high proportion of rare (lowly-represented) codons. While optimal codons are decoded by highly expressed tRNAs, rare codons are usually decoded by lowly-represented tRNAs. Whether rare codons play a role in controlling the expression of lowly- or temporarily-expressed proteins is an open question. In this work we approached this question using two strategies, either by replacing rare glycine codons with optimal counterparts in the gene that encodes the cell cycle protein Cdc13, or by overexpression the tRNA ^Gly that decodes rare codons from the fission yeast, Schizosaccharomyces pombe. While the replacement of synonymous codons severely affected cell growth, increasing tRNA levels affected the aggregation status of Cdc13 and cell division. These lead us to think that rare codons in lowly-expressed cyclin proteins are crucial for cell division, and that the overexpression of tRNA that decodes rare codons affects the expression of proteins containing these rare codons. These codons may be the result of the natural selection of codons in genes that encode lowly-expressed proteins.

Statistical Design of Experiments for Synthetic Biology

The design and optimization of biological systems is an inherently complex undertaking that requires careful balancing of myriad synergistic and antagonistic variables. However, despite this complexity, much synthetic biology research is predicated on One Factor at A Time (OFAT) experimentation; the genetic and environmental variables affecting the activity of a system of interest are sequentially altered while all other variables are held constant. Beyond being time and resource intensive, OFAT experimentation crucially ignores the effect of interactions between factors. Given the ubiquity of interacting genetic and environmental factors in biology this failure to account for interaction effects in OFAT experimentation can result in the development of suboptimal systems. To address these limitations, an increasing number of studies have turned to Design of Experiments (DoE), a suite of methods that enable efficient, systematic exploration and exploitation of complex design spaces. This review provides an overview of DoE for synthetic biologists. Key concepts and commonly used experimental designs are introduced, and we discuss the advantages of DoE as compared to OFAT experimentation. We dissect the applicability of DoE in the context of synthetic biology and review studies which have successfully employed these methods, illustrating the potential of statistical experimental design to guide the design, characterization, and optimization of biological protocols, pathways, and processes.

Cost-efficiency tradeoff is optimized in various cancer types revealed by genome-wide analysis

The tradeoff between cost and efficiency is omnipresent in organisms. Specifically, how the evolutionary force shapes the tradeoff between biosynthetic cost and translation efficiency remains unclear. In the cancer community, whether the adjustment of cost-efficiency tradeoff acts as a strategy to facilitate tumor proliferation and contributes to oncogenesis is uninvestigated. To address this issue, we retrieved the gene expression profile in various cancer types and the matched normal samples from The Cancer Genome Atlas (TCGA). We found that the highly expressed genes in cancers generally have higher tAI/nitro ratios than those in normal samples. This is possibly caused by the higher tAI/nitro ratios observed in oncogenes than tumor suppressor genes (TSG). Furthermore, in the cancer samples, derived mutations in oncogenes usually lead to higher tAI/nitro ratios, while those mutations in TSG lead to lower tAI/nitro. For a special case of kidney cancer, we investigated several crucial genes in tumor samples versus normal samples, and discovered that the changes in tAI/nitro ratios are correlated with the changes in translation level. Our study for the first time revealed the optimization of cost-efficiency tradeoff in cancers. The cost-efficiency dilemma is optimized by the tumor cells, and is possibly beneficial for the translation and production of oncogenes, and eventually contributes to proliferation and oncogenesis. Our findings could provide novel perspectives in depicting the cancer genomes and might help unravel the cancer evolution.

Synonymous but Not Silent: The Codon Usage Code for Gene Expression and Protein Folding

Codon usage bias, the preference for certain synonymous codons, is found in all genomes. Although synonymous mutations were previously thought to be silent, a large body of evidence has demonstrated that codon usage can play major roles in determining gene expression levels and protein structures. Codon usage influences translation elongation speed and regulates translation efficiency and accuracy. Adaptation of codon usage to tRNA expression determines the proteome landscape. In addition, codon usage biases result in nonuniform ribosome decoding rates on mRNAs, which in turn influence the cotranslational protein folding process that is critical for protein function in diverse biological processes. Conserved genome-wide correlations have also been found between codon usage and protein structures. Furthermore, codon usage is a major determinant of mRNA levels through translation-dependent effects on mRNA decay and translation-independent effects on transcriptional and posttranscriptional processes. Here, we discuss the multifaceted roles and mechanisms of codon usage in different gene regulatory processes.

A Closer Look at Estrogen Receptor Mutations in Breast Cancer and Their Implications for Estrogen and Antiestrogen Responses

Breast cancer (BC) is the most common cancer among women worldwide. More than 70% of BC cases express estrogen receptor alpha (ERα), a central transcription factor that stimulates the proliferation of breast cancer cells, usually in the presence of estrogen. While most cases of ER-positive BC initially respond to antiestrogen therapies, a high percentage of cases develop resistance to treatment over time. The recent discovery of mutated forms of ERα that result in constitutively active forms of the receptor in the metastatic-resistance stage of BC has provided a strong rationale for the development of new antiestrogens. These molecules targeting clinically relevant ERα mutants and a combination with other pharmacological inhibitors of specific pathways may constitute alternative treatments to improve clinical practice in the fight against metastatic-resistant ER-positive BC. In this review, we summarize the latest advances regarding the particular involvement of point mutations of ERα in endocrine resistance. We also discuss the involvement of synonymous ERα mutations with respect to co-translational folding of the receptor and ribosome biogenesis in breast carcinogenesis.

A comprehensive analysis of the phylogenetic signal in ramp sequences in 211 vertebrates

Ramp sequences increase translational speed and accuracy when rare, slowly-translated codons are found at the beginnings of genes. Here, the results of the first analysis of ramp sequences in a phylogenetic construct are presented. Ramp sequences were compared from 247 vertebrates (114 Mammalian and 133 non-mammalian), where the presence and absence of ramp sequences was analyzed as a binary character in a parsimony and maximum likelihood framework. Additionally, ramp sequences were mapped to the Open Tree of Life synthetic tree to determine the number of parallelisms and reversals that occurred, and those results were compared to random permutations. Parsimony and maximum likelihood analyses of the presence and absence of ramp sequences recovered phylogenies that are highly congruent with established phylogenies. Additionally, 81% of vertebrate mammalian ramps and 81.2% of other vertebrate ramps had less parallelisms and reversals than the mean from 1000 randomly permuted trees. A chi-square analysis of completely orthologous ramp sequences resulted in a p-value < 0.001 as compared to random chance. Ramp sequences recover comparable phylogenies as other phylogenomic methods. Although not all ramp sequences appear to have a phylogenetic signal, more ramp sequences track speciation than expected by random chance. Therefore, ramp sequences may be used in conjunction with other phylogenomic approaches if many orthologs are taken into account. However, phylogenomic methods utilizing few orthologs should be cautious in incorporating ramp sequences because individual ramp sequences may provide conflicting signals.

Translational Control by Ribosome Pausing in Bacteria: How a Non-uniform Pace of Translation Affects Protein Production and Folding

Protein homeostasis of bacterial cells is maintained by coordinated processes of protein production, folding, and degradation. Translational efficiency of a given mRNA depends on how often the ribosomes initiate synthesis of a new polypeptide and how quickly they read the coding sequence to produce a full-length protein. The pace of ribosomes along the mRNA is not uniform: periods of rapid synthesis are separated by pauses. Here, we summarize recent evidence on how ribosome pausing affects translational efficiency and protein folding. We discuss the factors that slow down translation elongation and affect the quality of the newly synthesized protein. Ribosome pausing emerges as important factor contributing to the regulatory programs that ensure the quality of the proteome and integrate the cellular and environmental cues into regulatory circuits of the cell.

Crosstalk between codon optimality and cis-regulatory elements dictates mRNA stability

BACKGROUND

The regulation of messenger RNA (mRNA) stability has a profound impact on gene expression dynamics during embryogenesis. For example, in animals, maternally deposited mRNAs are degraded after fertilization to enable new developmental trajectories. Regulatory sequences in 3' untranslated regions (3'UTRs) have long been considered the central determinants of mRNA stability. However, recent work indicates that the coding sequence also possesses regulatory information. Specifically, translation in cis impacts mRNA stability in a codon-dependent manner. However, the strength of this mechanism during embryogenesis, as well as its relationship with other known regulatory elements, such as microRNA, remains unclear.

RESULTS

Here, we show that codon composition is a major predictor of mRNA stability in the early embryo. We show that this mechanism works in combination with other cis-regulatory elements to dictate mRNA stability in zebrafish and Xenopus embryos as well as in mouse and human cells. Furthermore, we show that microRNA targeting efficacy can be affected by substantial enrichment of optimal (stabilizing) or non-optimal (destabilizing) codons. Lastly, we find that one microRNA, miR-430, antagonizes the stabilizing effect of optimal codons during early embryogenesis in zebrafish.

CONCLUSIONS

By integrating the contributions of different regulatory mechanisms, our work provides a framework for understanding how combinatorial control of mRNA stability shapes the gene expression landscape.

The patterns of deleterious mutations during the domestication of soybean

Globally, soybean is a major protein and oil crop. Enhancing our understanding of the soybean domestication and improvement process helps boost genomics-assisted breeding efforts. Here we present a genome-wide variation map of 10.6 million single-nucleotide polymorphisms and 1.4 million indels for 781 soybean individuals which includes 418 domesticated (Glycine max), 345 wild (Glycine soja), and 18 natural hybrid (G. max/G. soja) accessions. We describe the enhanced detection of 183 domestication-selective sweeps and the patterns of putative deleterious mutations during domestication and improvement. This predominantly selfing species shows 7.1% reduction of overall deleterious mutations in domesticated soybean relative to wild soybean and a further 1.4% reduction from landrace to improved accessions. The detected domestication-selective sweeps also show reduced levels of deleterious alleles. Importantly, genotype imputation with this resource increases the mapping resolution of genome-wide association studies for seed protein and oil traits in a soybean diversity panel.

Codon Resolution Analysis of Ribosome Profiling Data

Translation is a central biological process in living cells. Ribosome profiling approach enables assessing translation on a global, cell-wide level. Extracting versatile information from the ribosome profiling data usually requires specialized expertise for handling the sequencing data that is not available to the broad community of experimentalists. Here, we provide an easy-to-use and modifiable workflow that uses a small set of commands and enables full data analysis in a standardized way, including precise positioning of the ribosome-protected fragments, for determining codon-specific translation features. The workflow is complemented with simple step-by-step explanations and is accessible to scientists with no computational background.

De novo transcriptome assembly, functional annotation and characterization of the Atlantic bluefin tuna (Thunnus thynnus) larval stage

In the present work, we assembled and characterized a de novo larval transcriptome of the Atlantic bluefin tuna Thunnus thynnus by taking advantage of publicly available databases with the goal of better understanding its larval development. The assembled transcriptome comprised 37,117 protein-coding transcripts, of which 13,633 full-length (>80% coverage), with an Ex90N50 of 3061 bp and 76% of complete and single-copy core vertebrate genes orthologues. Of these transcripts, 34,980 had a hit against the EggNOG database and 14,983 with the KEGG database. Codon usage bias was identified in processes such as translation and muscle development. By comparing our data with a set of representative fish species, 87.1% of tuna transcripts were included in orthogroups with other species and 5.1% in assembly-specific orthogroups, which were enriched in terms related to muscle and bone development, visual system and ion transport. Following this comparative approach, protein families related to myosin, extracellular matrix and immune system resulted significantly expanded in the Atlantic bluefin tuna. Altogether, these results provide a glimpse of how the Atlantic bluefin tuna might have achieved early physical advantages over competing species in the pelagic environment. The information generated lays the foundation for future research on the more detailed exploration of physiological responses at the molecular level in different larval stages and paves the way to evolutionary studies on the Atlantic bluefin tuna.

Manipulation of the human tRNA pool reveals distinct tRNA sets that act in cellular proliferation or cell cycle arrest

Different subsets of the tRNA pool in human cells are expressed in different cellular conditions. The 'proliferation-tRNAs' are induced upon normal and cancerous cell division, while the 'differentiation-tRNAs' are active in non-dividing, differentiated cells. Here we examine the essentiality of the various tRNAs upon cellular growth and arrest. We established a CRISPR-based editing procedure with sgRNAs that each target a tRNA family. We measured tRNA essentiality for cellular growth and found that most proliferation-tRNAs are essential compared to differentiation- tRNAs in rapidly growing cell lines. Yet in more slowly dividing lines, the differentiation-tRNAs were more essential. In addition, we measured the essentiality of each tRNA family upon response to cell cycle arresting signals. Here we detected a more complex behavior with both proliferation-tRNAs and differentiation tRNAs showing various levels of essentiality. These results provide the so-far most comprehensive functional characterization of human tRNAs with intricate roles in various cellular states.

Expression of transgenes enriched in rare codons is enhanced by the MAPK pathway

The ability to translate three nucleotide sequences, or codons, into amino acids to form proteins is conserved across all organisms. All but two amino acids have multiple codons, and the frequency that such synonymous codons occur in genomes ranges from rare to common. Transcripts enriched in rare codons are typically associated with poor translation, but in certain settings can be robustly expressed, suggestive of codon-dependent regulation. Given this, we screened a gain-of-function library for human genes that increase the expression of a GFP^rare reporter encoded by rare codons. This screen identified multiple components of the mitogen activated protein kinase (MAPK) pathway enhancing GFP^rare expression. This effect was reversed with inhibitors of this pathway and confirmed to be both codon-dependent and occur with ectopic transcripts naturally coded with rare codons. Finally, this effect was associated, at least in part, with enhanced translation. We thus identify a potential regulatory module that takes advantage of the redundancy in the genetic code to modulate protein expression.

Enabling high-throughput single-animal gene-expression studies with molecular and micro-scale technologies

Gene expression and regulation play diverse and important roles across all living systems. By quantifying the expression, whether in a sample of single cells, a specific tissue, or in a whole animal, one can gain insights into the underlying biology. Many biological questions now require single-animal and tissue-specific resolution, such as why individuals, even within an isogenic population, have variations in development and aging across different tissues and organs. The popular techniques that quantify the transcriptome (e.g. RNA-sequencing) process populations of animals and cells together and thus, have limitations in both individual and spatial resolution. There are single-animal assays available (e.g. fluorescent reporters); however, they suffer other technical bottlenecks, such as a lack of robust sample-handling methods. Microfluidic technologies have demonstrated various improvements throughout the years, and it is likely they can enhance the impact of these single-animal gene-expression assays. In this perspective, we aim to highlight how the engineering/method-development field have unique opportunities to create new tools that can enable us to robustly answer the next set of important questions in biology that require high-density, high-quality gene expression data.

Exploiting codon usage identifies intensity-specific modifiers of Ras/MAPK signaling in vivo

Signal transduction pathways are intricately fine-tuned to accomplish diverse biological processes. An example is the conserved Ras/mitogen-activated-protein-kinase (MAPK) pathway, which exhibits context-dependent signaling output dynamics and regulation. Here, by altering codon usage as a novel platform to control signaling output, we screened the Drosophila genome for modifiers specific to either weak or strong Ras-driven eye phenotypes. Our screen enriched for regions of the genome not previously connected with Ras phenotypic modification. We mapped the underlying gene from one modifier to the ribosomal gene RpS21. In multiple contexts, we show that RpS21 preferentially influences weak Ras/MAPK signaling outputs. These data show that codon usage manipulation can identify new, output-specific signaling regulators, and identify RpS21 as an in vivo Ras/MAPK phenotypic regulator.

Cellular communication is critical in controlling the growth of organs and must be carefully regulated to prevent disease. The Ras signaling pathway is frequently used for cellular communication of tissue growth regulation but can operate at different signaling strengths. Here, we used a novel strategy to identify genes that specifically tune weak or strong Ras signaling states. We find that the gene RpS21 preferentially tunes weak Ras signaling states.

RiboDiPA: a novel tool for differential pattern analysis in Ribo-seq data

Ribosome profiling, also known as Ribo-seq, has become a popular approach to investigate regulatory mechanisms of translation in a wide variety of biological contexts. Ribo-seq not only provides a measurement of translation efficiency based on the relative abundance of ribosomes bound to transcripts, but also has the capacity to reveal dynamic and local regulation at different stages of translation based on positional information of footprints across individual transcripts. While many computational tools exist for the analysis of Ribo-seq data, no method is currently available for rigorous testing of the pattern differences in ribosome footprints. In this work, we develop a novel approach together with an R package, RiboDiPA, for Differential Pattern Analysis of Ribo-seq data. RiboDiPA allows for quick identification of genes with statistically significant differences in ribosome occupancy patterns for model organisms ranging from yeast to mammals. We show that differential pattern analysis reveals information that is distinct and complimentary to existing methods that focus on translational efficiency analysis. Using both simulated Ribo-seq footprint data and three benchmark data sets, we illustrate that RiboDiPA can uncover meaningful pattern differences across multiple biological conditions on a global scale, and pinpoint characteristic ribosome occupancy patterns at single codon resolution.