Large-scale detection of in vivo transcription errors

Promoter dependent RNA polymerase II bypass of the epimerizable DNA lesion, Fapy•dG and 8-Oxo-2'-deoxyguanosine

Formamidopyrimidine (Fapy•dG) is a major lesion arising from oxidation of dG that is produced from a common chemical precursor of 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-OxodGuo). In human cells, replication of single-stranded shuttle vectors containing Fapy•dG is more mutagenic than 8-OxodGuo. Here, we present the first data regarding promoter dependent RNA polymerase II bypass of Fapy•dG. 8-OxodGuo bypass was examined side-by-side. Experiments were carried out using double-stranded shuttle vectors in HeLa cell nuclear lysates and in HEK 293T cells. The lesions do not significantly block transcriptional bypass efficiency. Less than 2% adenosine incorporation occurred in cells when the lesions were base paired with dC. Inhibiting base excision repair in HEK 293T cells significantly increased adenosine incorporation, particularly from Fapy•dG:dC bypass which yielded ∼25% adenosine incorporation. No effect was detected upon transcriptional bypass of either lesion in nucleotide excision repair deficient cells. Transcriptional mutagenesis was significantly higher when shuttle vectors containing dA opposite one of the lesions were employed. For Fapy•dG:dA bypass, adenosine incorporation was greater than 85%; whereas 8-OxodGuo:dA yielded >20% point mutations. The combination of more frequent replication mistakes and greater error-prone Pol II bypass suggest that Fapy•dG is more mutagenic than 8-OxodGuo.

GTDrift: a resource for exploring the interplay between genetic drift, genomic and transcriptomic characteristics in eukaryotes

We present GTDrift, a comprehensive data resource that enables explorations of genomic and transcriptomic characteristics alongside proxies of the intensity of genetic drift in individual species. This resource encompasses data for 1506 eukaryotic species, including 1413 animals and 93 green plants, and is organized in three components. The first two components contain approximations of the effective population size, which serve as indicators of the extent of random genetic drift within each species. In the first component, we meticulously investigated public databases to assemble data on life history traits such as longevity, adult body length and body mass for a set of 979 species. The second component includes estimations of the ratio between the rate of non-synonymous substitutions and the rate of synonymous substitutions (dN/dS) in protein-coding sequences for 1324 species. This ratio provides an estimate of the efficiency of natural selection in purging deleterious substitutions. Additionally, we present polymorphism-derived N e estimates for 66 species. The third component encompasses various genomic and transcriptomic characteristics. With this component, we aim to facilitate comparative transcriptomics analyses across species, by providing easy-to-use processed data for more than 16 000 RNA-seq samples across 491 species. These data include intron-centered alternative splicing frequencies, gene expression levels and sequencing depth statistics for each species, obtained with a homogeneous analysis protocol. To enable cross-species comparisons, we provide orthology predictions for conserved single-copy genes based on BUSCO gene sets. To illustrate the possible uses of this database, we identify the most frequently used introns for each gene and we assess how the sequencing depth available for each species affects our power to identify major and minor splice variants.

Effects of the glyphosate-based herbicide Roundup on C. elegans and S. cerevisiae mortality, reproduction, and transcription fidelity

Glyphosate-based weed killers such as Roundup have been implicated in detrimental effects on single- and multicellular eukaryotic model organism health and longevity. However, the mode(s) of action for these effects are currently unknown. In this study, we investigate the impact of exposure to Roundup on two model organisms: Saccharomyces cerevisiae and Caenorhabditis elegans and test the hypothesis that exposure to Roundup decreases transcription fidelity. Population growth assays and motility assays were performed in order to determine the phenotypic effects of Roundup exposure. We also used Rolling-Circle Amplification RNA sequencing to quantify the impact of exposure to Roundup on transcription fidelity in these two model organisms. Our results show that exposure to the glyphosate-based herbicide Roundup increases mortality, reduces reproduction, and increases transcription error rates in C. elegans and S. cerevisiae. We suggest that these effects may be due in part to the involvement of inflammation and oxidative stress, conditions which may also contribute to increases in transcription error rates.

Random genetic drift sets an upper limit on mRNA splicing accuracy in metazoans

Most eukaryotic genes undergo alternative splicing (AS), but the overall functional significance of this process remains a controversial issue. It has been noticed that the complexity of organisms (assayed by the number of distinct cell types) correlates positively with their genome-wide AS rate. This has been interpreted as evidence that AS plays an important role in adaptive evolution by increasing the functional repertoires of genomes. However, this observation also fits with a totally opposite interpretation: given that 'complex' organisms tend to have small effective population sizes (Ne), they are expected to be more affected by genetic drift, and hence more prone to accumulate deleterious mutations that decrease splicing accuracy. Thus, according to this 'drift barrier' theory, the elevated AS rate in complex organisms might simply result from a higher splicing error rate. To test this hypothesis, we analyzed 3496 transcriptome sequencing samples to quantify AS in 53 metazoan species spanning a wide range of Ne values. Our results show a negative correlation between Ne proxies and the genome-wide AS rates among species, consistent with the drift barrier hypothesis. This pattern is dominated by low abundance isoforms, which represent the vast majority of the splice variant repertoire. We show that these low abundance isoforms are depleted in functional AS events, and most likely correspond to errors. Conversely, the AS rate of abundant isoforms, which are relatively enriched in functional AS events, tends to be lower in more complex species. All these observations are consistent with the hypothesis that variation in AS rates across metazoans reflects the limits set by drift on the capacity of selection to prevent gene expression errors.

Molecular Mechanism of RNA Polymerase II Transcriptional Mutagenesis by the Epimerizable DNA Lesion, Fapy·dG

Oxidative DNA lesions cause significant detrimental effects on a living species. Two major DNA lesions resulting from dG oxidation, 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-OxodGuo) and formamidopyrimidine (Fapy·dG), are produced from a common chemical intermediate. Fapy·dG is formed in comparable yields under oxygen-deficient conditions. Replicative bypass of Fapy·dG in human cells is more mutagenic than that of 8-OxodGuo. Despite the biological importance of transcriptional mutagenesis, there are no reports of the effects of Fapy·dG on RNA polymerase II (Pol II) activity. Here we perform comprehensive kinetic studies to investigate the impact of Fapy·dG on three key transcriptional fidelity checkpoint steps by Pol II: insertion, extension, and proofreading steps. The ratios of error-free versus error-prone incorporation opposite Fapy·dG are significantly reduced in comparison with undamaged dG. Similarly, Fapy·dG:A mispair is extended with comparable efficiency as that of the error-free, Fapy·dG:C base pair. The α- and β-configurational isomers of Fapy·dG have distinct effects on Pol II insertion and extension. Pol II can preferentially cleave error-prone products by proofreading. To further understand the structural basis of transcription processing of Fapy·dG, five different structures were solved, including Fapy·dG template-loading state (apo), error-free cytidine triphosphate (CTP) binding state (prechemistry), error-prone ATP binding state (prechemistry), error-free Fapy·dG:C product state (postchemistry), and error-prone Fapy·dG:A product state (postchemistry), revealing distinctive nucleotide binding and product states. Taken together, our study provides a comprehensive mechanistic framework for better understanding how Fapy·dG lesions impact transcription and subsequent pathological consequences.

Fitness Effects of Phenotypic Mutations at Proteome-Scale Reveal Optimality of Translation Machinery

Errors in protein translation can lead to non-genetic, phenotypic mutations, including amino acid misincorporations. While phenotypic mutations can increase protein diversity, the systematic characterization of their proteome-wide frequencies and their evolutionary impact has been lacking. Here, we developed a mechanistic model of translation errors to investigate how selection acts on protein populations produced by amino acid misincorporations. We fitted the model to empirical observations of misincorporations obtained from over a hundred mass spectrometry datasets of E. coli and S. cerevisiae. We found that on average 20% to 23% of proteins synthesized in the cell are expected to harbor at least one amino acid misincorporation, and that deleterious misincorporations are less likely to occur. Combining misincorporation probabilities and the estimated fitness effects of amino acid substitutions in a population genetics framework, we found 74% of mistranslation events in E. coli and 94% in S. cerevisiae to be neutral. We further show that the set of available synonymous tRNAs is subject to evolutionary pressure, as the presence of missing tRNAs would increase codon-anticodon cross-reactivity and misincorporation error rates. Overall, we find that the translation machinery is likely optimal in E. coli and S. cerevisiae and that both local solutions at the level of codons and a global solution such as the tRNA pool can mitigate the impact of translation errors. We provide a framework to study the evolutionary impact of codon-specific translation errors and a method for their proteome-wide detection across organisms and conditions.

Single-cell mutation rate of turnip crinkle virus (-)-strand replication intermediates

Viruses with single-stranded, positive-sense (+) RNA genomes incur high numbers of errors during replication, thereby creating diversified genome populations from which new, better adapted viral variants can emerge. However, a definitive error rate is known for a relatively few (+) RNA plant viruses, due to challenges to account for perturbations caused by natural selection and/or experimental set-ups. To address these challenges, we developed a new approach that exclusively profiled errors in the (-)-strand replication intermediates of turnip crinkle virus (TCV), in singly infected cells. A series of controls and safeguards were devised to ensure errors inherent to the experimental process were accounted for. This approach permitted the estimation of a TCV error rate of 8.47 X 10-5 substitution per nucleotide site per cell infection. Importantly, the characteristic error distribution pattern among the 50 copies of 2,363-base-pair cDNA fragments predicted that nearly all TCV (-) strands were products of one replication cycle per cell. Furthermore, some of the errors probably elevated error frequencies by lowering the fidelity of TCV RNA-dependent RNA polymerase, and/or permitting occasional re-replication of progeny genomes. In summary, by profiling errors in TCV (-)-strand intermediates incurred during replication in single cells, this study provided strong support for a stamping machine mode of replication employed by a (+) RNA virus.

When Size Really Matters: The Eccentricities of Dystrophin Transcription and the Hazards of Quantifying mRNA from Very Long Genes

At 2.3 megabases in length, the dystrophin gene is enormous: transcription of a single mRNA requires approximately 16 h. Principally expressed in skeletal muscle, the dystrophin protein product protects the muscle sarcolemma against contraction-induced injury, and dystrophin deficiency results in the fatal muscle-wasting disease, Duchenne muscular dystrophy. This gene is thus of key clinical interest, and therapeutic strategies aimed at eliciting dystrophin restoration require quantitative analysis of its expression. Approaches for quantifying dystrophin at the protein level are well-established, however study at the mRNA level warrants closer scrutiny: measured expression values differ in a sequence-dependent fashion, with significant consequences for data interpretation. In this manuscript, we discuss these nuances of expression and present evidence to support a transcriptional model whereby the long transcription time is coupled to a short mature mRNA half-life, with dystrophin transcripts being predominantly nascent as a consequence. We explore the effects of such a model on cellular transcriptional dynamics and then discuss key implications for the study of dystrophin gene expression, focusing on both conventional (qPCR) and next-gen (RNAseq) approaches.

Synergy among Pausing, Intrinsic Proofreading, and Accessory Proteins Results in Optimal Transcription Speed and Tolerable Accuracy

Cleavage of dinucleotides after the misincorporational pauses serves as a proofreading mechanism that increases transcriptional elongation accuracy. The accuracy is further improved by accessory proteins such as GreA and TFIIS. However, it is not clear why RNAP pauses and why cleavage-factor-assisted proofreading is necessary despite transcriptional errors in vitro being of the same order as those in downstream translation. Here, we developed a chemical-kinetic model that incorporates most relevant features of transcriptional proofreading and uncovers how the balance between speed and accuracy is achieved. We found that long pauses are essential for high accuracy, whereas cleavage-factor-stimulated proofreading optimizes speed. Moreover, in comparison to the cleavage of a single nucleotide or three nucleotides, RNAP backtracking and dinucleotide cleavage improve both speed and accuracy. Our results thereby show how the molecular mechanism and the kinetic parameters of the transcriptional process were evolutionarily optimized to achieve maximal speed and tolerable accuracy.

Phenotypic mutations contribute to protein diversity and shape protein evolution

Errors in DNA replication generate genetic mutations, while errors in transcription and translation lead to phenotypic mutations. Phenotypic mutations are orders of magnitude more frequent than genetic ones, yet they are less understood. Here, we review the types of phenotypic mutations, their quantifications, and their role in protein evolution and disease. The diversity generated by phenotypic mutation can facilitate adaptive evolution. Indeed, phenotypic mutations, such as ribosomal frameshift and stop codon readthrough, sometimes serve to regulate protein expression and function. Phenotypic mutations have often been linked to fitness decrease and diseases. Thus, understanding the protein heterogeneity and phenotypic diversity caused by phenotypic mutations will advance our understanding of protein evolution and have implications on human health and diseases.

Stop codon usage as a window into genome evolution: mutation, selection, biased gene conversion and the TAG paradox

Protein coding genes terminate with one of three stop codons (TAA, TGA, or TAG) that, like synonymous codons, are not employed equally. With TGA and TAG having identical nucleotide content, analysis of their differential usage provides an unusual window into the forces operating on what are ostensibly functionally identical residues. Across genomes and between isochores within the human genome, TGA usage increases with G + C content but, with a common G + C → A + T mutation bias, this cannot be explained by mutation bias-drift equilibrium. Increased usage of TGA in G + C-rich genomes or genomic regions is also unlikely to reflect selection for the optimal stop codon, as TAA appears to be universally optimal, probably because it has the lowest read-through rate. Despite TAA being favored by selection and mutation bias, as with codon usage bias G + C pressure is the prime determinant of between-species TGA usage trends. In species with strong G + C-biased gene conversion (gBGC), such as mammals and birds, the high usage and conservation of TGA is best explained by an A + T → G + C repair bias. How to explain TGA enrichment in other G + C-rich genomes is less clear. Enigmatically, across bacterial and archaeal species and between human isochores TAG usage is mostly unresponsive to G + C pressure. This unresponsiveness we dub the TAG paradox as currently no mutational, selective, or gBGC model provides a well-supported explanation. That TAG does increase with G + C usage across eukaryotes makes the usage elsewhere yet more enigmatic. We suggest resolution of the TAG paradox may provide insights into either an unknown but common selective preference (probably at the DNA/RNA level) or an unrecognized complexity to the action of gBGC.

Pervasive sequence-level variation in the transcriptome of Plasmodium falciparum

Single-nucleotide variations (SNVs) in RNA, arising from co- and post-transcriptional phenomena including transcription errors and RNA-editing, are well studied in a range of organisms. In the malaria parasite Plasmodium falciparum, stage-specific and non-specific gene-expression variations accompany the parasite's array of developmental and morphological phenotypes over the course of its complex life cycle. However, the extent, rate and effect of sequence-level variation in the parasite's transcriptome are unknown. Here, we report the presence of pervasive, non-specific SNVs in the P. falciparum transcriptome. SNV rates for a gene were correlated to gene length (r[Formula: see text]0.65-0.7) but not to the AT-content of that gene. Global SNV rates for the P. falciparum lines we used, and for publicly available P. vivax and P. falciparum clinical isolate datasets, were of the order of 10-3 per base, ∼10× higher than rates we calculated for bacterial datasets. These variations may reflect an intrinsic transcriptional error rate in the parasite, and RNA editing may be responsible for a subset of them. This seemingly characteristic property of the parasite may have implications for clinical outcomes and the basic biology and evolution of P. falciparum and parasite biology more broadly. We anticipate that our study will prompt further investigations into the exact sources, consequences and possible adaptive roles of these SNVs.

Density- and elongation speed-dependent error correction in RNA polymerization

Backtracking of RNA polymerase (RNAP) is an important pausing mechanism during DNA transcription that is part of the error correction process that enhances transcription fidelity. We model the backtracking mechanism of RNA polymerase, which usually happens when the polymerase tries to incorporate a noncognate or "mismatched" nucleotide triphosphate. Previous models have made simplifying assumptions such as neglecting the trailing polymerase behind the backtracking polymerase or assuming that the trailing polymerase is stationary. We derive exact analytic solutions of a stochastic model that includes locally interacting RNAPs by explicitly showing how a trailing RNAP influences the probability that an error is corrected or incorporated by the leading backtracking RNAP. We also provide two related methods for computing the mean times for error correction and incorporation given an initial local RNAP configuration. Using these results, we propose an effective interacting-RNAP lattice that can be readily simulated.

Global quantification exposes abundant low-level off-target activity by base editors

Base editors are dedicated engineered deaminases that enable directed conversion of specific bases in the genome or transcriptome in a precise and efficient manner, and hold promise for correcting pathogenic mutations. A major concern limiting application of this powerful approach is the issue of off-target edits. Several recent studies have shown substantial off-target RNA activity induced by base editors and demonstrated that off-target mutations may be suppressed by improved deaminases versions or optimized guide RNAs. Here, we describe a new class of off-target events that are invisible to the established methods for detection of genomic variations and were thus far overlooked. We show that nonspecific, seemingly stochastic, off-target events affect a large number of sites throughout the genome or the transcriptome, and account for the majority of off-target activity. We develop and employ a different, complementary approach that is sensitive to the stochastic off-target activity and use it to quantify the abundant off-target RNA mutations due to current, optimized deaminase editors. We provide a computational tool to quantify global off-target activity, which can be used to optimize future base editors. Engineered base editors enable directed manipulation of the genome or transcriptome at single-base resolution. We believe that implementation of this computational approach would facilitate design of more specific base editors.

Host-specific asymmetric accumulation of mutation types reveals that the origin of SARS-CoV-2 is consistent with a natural process

The capacity of RNA viruses to adapt to new hosts and rapidly escape the host immune system is largely attributable to de novo genetic diversity that emerges through mutations in RNA. Although the molecular spectrum of de novo mutations—the relative rates at which various base substitutions occur—are widely recognized as informative toward understanding the evolution of a viral genome, little attention has been paid to the possibility of using molecular spectra to infer the host origins of a virus. Here, we characterize the molecular spectrum of de novo mutations for SARS-CoV-2 from transcriptomic data obtained from virus-infected cell lines, enabled by the use of sporadic junctions formed during discontinuous transcription as molecular barcodes. We find that de novo mutations are generated in a replication-independent manner, typically on the genomic strand, and highly dependent on mutagenic mechanisms specific to the host cellular environment. De novo mutations will then strongly influence the types of base substitutions accumulated during SARS-CoV-2 evolution, in an asymmetric manner favoring specific mutation types. Consequently, similarities between the mutation spectra of SARS-CoV-2 and the bat coronavirus RaTG13, which have accumulated since their divergence strongly suggest that SARS-CoV-2 evolved in a host cellular environment highly similar to that of bats before its zoonotic transfer into humans. Collectively, our findings provide data-driven support for the natural origin of SARS-CoV-2.

•

The asymmetric de novo mutations in SARS-CoV-2 are induced by mutagenic mechanisms in the host cellular environment

•

De novo mutations determine the molecular spectrum of accumulated mutations during SARS-CoV-2 evolution

•

Molecular spectra of accumulated mutations in betacoronaviruses cluster according to the host species instead of the phylogenetic relationship

•

The mutations accumulated in SARS-CoV-2 prior to its transmission to humans are consistent with an evolutionary process in a bat host

A general evidence-based sequence variant control limit for recombinant therapeutic protein development

Sequence variants (SVs) resulting from unintended amino acid substitutions in recombinant therapeutic proteins have increasingly gained attention from both regulatory agencies and the biopharmaceutical industry given their potential impact on efficacy and safety. With well-optimized production systems, such sequence variants usually exist at very low levels in the final protein products due to the high fidelity of DNA replication and protein biosynthesis process in mammalian expression systems such as Chinese hamster ovary cell lines. However, their levels can be significantly elevated in cases where the selected production cell line has unexpected DNA mutations or the manufacturing process is not fully optimized, for example, if depletion of certain amino acids occurs in the cell culture media in bioreactors. Therefore, it is important to design and implement an effective monitoring and control strategy to prevent or minimize the possible risks of SVs during the early stage of product and process development. However, there is no well-established guidance from the regulatory agencies or consensus across the industry to assess and manage SV risks. A question frequently asked is: What levels of SVs can be considered acceptable during product and process development, but also have no negative effects on drug safety and efficacy in patients? To address this critical question, we have taken a holistic approach and conducted a comprehensive sequence variant analysis. To guide biologic development, a general SV control limit of 0.1% at individual amino acid sites was proposed and properly justified based on extensive literature review, SV benchmark survey of approved therapeutic proteins, and accumulated experience on SV control practice at Regeneron.

Rescue of Infectious Sindbis Virus by Yeast Spheroplast-Mammalian Cell Fusion

Sindbis virus (SINV), a positive-sense single stranded RNA virus that causes mild symptoms in humans, is transmitted by mosquito bites. SINV reverse genetics have many implications, not only in understanding alphavirus transmission, replication cycle, and virus-host interactions, but also in biotechnology and biomedical applications. The rescue of SINV infectious particles is usually achieved by transfecting susceptible cells (BHK-21) with SINV-infectious mRNA genomes generated from cDNA constructed via in vitro translation (IVT). That procedure is time consuming, costly, and relies heavily on reagent quality. Here, we constructed a novel infectious SINV cDNA construct that expresses its genomic RNA in yeast cells controlled by galactose induction. Using spheroplasts made from this yeast, we established a robust polyethylene glycol-mediated yeast: BHK-21 fusion protocol to rescue infectious SINV particles. Our approach is timesaving and utilizes common lab reagents for SINV rescue. It could be a useful tool for the rescue of large single strand RNA viruses, such as SARS-CoV-2.

The impact of mistranslation on phenotypic variability and fitness

Phenotypic variation is widespread in natural populations, and can significantly alter population ecology and evolution. Phenotypic variation often reflects underlying genetic variation, but also manifests via non-heritable mechanisms. For instance, translation errors result in about 10% of cellular proteins carrying altered sequences. Thus, proteome diversification arising from translation errors can potentially generate phenotypic variability, in turn increasing variability in the fate of cells or of populations. However, the link between protein diversity and phenotypic variability remains unverified. We manipulated mistranslation levels in Escherichia coli, and measured phenotypic variability between single cells (individual-level variation), as well as replicate populations (population-level variation). Monitoring growth and survival, we find that mistranslation indeed increases variation across E. coli cells, but does not consistently increase variability in growth parameters across replicate populations. Interestingly, although any deviation from the wild-type (WT) level of mistranslation reduces fitness in an optimal environment, the increased variation is associated with a survival benefit under stress. Hence, we suggest that mistranslation-induced phenotypic variation can impact growth and survival and has the potential to alter evolutionary trajectories.

Biased Pol II fidelity contributes to conservation of functional domains in the Potato spindle tuber viroid genome

Accurate calculation of mutation rates for viruses and viroids is necessary for evolutionary studies and to evaluate adaptation potential. However, estimation of in vivo mutation rates is complicated by selection, which leads to loss or proliferation of certain mutations. To minimize this concern, lethal mutations, including nonsense and non-synonymous mutations, have been used to determine mutation rates for several viruses and viroids, including Potato spindle tuber viroid (PSTVd). However, this approach has limitations, including focus on a relatively small number of genome sites and the possibility that mutations may not actually be lethal or may be maintained by wild type individuals. To avoid selection bias altogether, we sequenced minus-strand PSTVd dimers from concatemeric replication intermediates. The underlying rationale is that mutations found in only one of the monomers were likely generated de novo during RNA polymerase II (Pol II) transcription of the circular plus-strand RNA genome. This approach yielded an apparent Pol II error rate of ~1/1837 nucleotides per transcription cycle, and an estimated mutation rate of ~1/919 nucleotides for a single replication cycle. Remarkably, de novo mutations were nearly absent from the most conserved, replication-critical regions of the PSTVd genome, suggesting that sequence conservation is a consequence of both essential function and template optimization for greater Pol II fidelity. Such biased fidelity may constitute a novel strategy to ensure population success while allowing abundant sampling of sequence space in other genome regions. Comparison with variants in progeny populations derived from a cloned, wild type PSTVd master sequence revealed that most de novo mutations were lost through selection.

Polymerase errors are the major source of variation in virus and viroid genomes, and as a consequence polymerase error rates are major determinants of adaptation potential. Accurate calculation of in vivo mutation rates is complicated by selection. To circumvent this issue, dimeric PSTVd minus-strand replication intermediates generated in vivo by host RNA polymerase II (Pol II) were sequenced to identify de novo mutations. This analysis revealed a very high error rate for Pol II transcribing genomic PSTVd RNA, leading to an extremely high mutation rate. Remarkably, however, de novo mutations were rare in the most highly conserved, replication-critical genome regions, suggesting these sequences are selected for both function and enhanced transcription fidelity. This biased fidelity may reveal a novel strategy to ensure population survival while maximizing adaptation potential. Further, comparison of mutations identified by minus-strand dimer sequencing with mutations observed in progeny variants derived from wild type PSTVd showed that most de novo mutations were lost through selection.

The Boggarts of biology: how non-genetic changes influence the genotype

The notion that there is a one-one mapping from genotype to phenotype was overturned a long time ago. Along with genotype and environment, 'non-genetic changes' orchestrated by altered RNA and protein molecules also guide the development of phenotype. The idea that there is a route through which changes in phenotype can lead to changes in genotype impinges on several phenomena of molecular, developmental, evolutionary and applied interest. Phenotypic changes that do not alter the underlying DNA sequence have been studied across model systems (eg: DNA and histone modifications, RNA editing, prion formation) and are known to play an important role in short-term adaptation. However, because of their transient nature and unstable inheritance, the role of such changes in long-term evolution has remained controversial. I classify and review three ways in which non-genetic changes can influence genotype and impact cellular fitness across generations, with an emphasis on the enticing idea that they may act as stepping stones for genetic adaptation. I focus on work from microbial systems and attempt to highlight recent experiments and models that bear on this idea. Overall, I review evidence which suggests that non-genetic changes can impact phenotype via their influence on the genotype, and thus play a role in evolutionary change.

The evolution and clinical impact of hepatitis B virus genome diversity

The global burden of hepatitis B virus (HBV) is enormous, with 257 million persons chronically infected, resulting in more than 880,000 deaths per year worldwide. HBV exists as nine different genotypes, which differ in disease progression, natural history and response to therapy. HBV is an ancient virus, with the latest reports greatly expanding the host range of the Hepadnaviridae (to include fish and reptiles) and casting new light on the origins and evolution of this viral family. Although there is an effective preventive vaccine, there is no cure for chronic hepatitis B, largely owing to the persistence of a viral minichromosome that is not targeted by current therapies. HBV persistence is also facilitated through aberrant host immune responses, possibly due to the diverse intra-host viral populations that can respond to host-mounted and therapeutic selection pressures. This Review summarizes current knowledge on the influence of HBV diversity on disease progression and treatment response and the potential effect on new HBV therapies in the pipeline. The mechanisms by which HBV diversity can occur both within the individual host and at a population level are also discussed.

Translational quality control and reprogramming during stress adaptation

Organisms encounter stress throughout their lives, and therefore require the ability to respond rapidly to environmental changes. Although transcriptional responses are crucial for controlling changes in gene expression, regulation at the translational level often allows for a faster response at the protein levels which permits immediate adaptation. The fidelity and robustness of protein synthesis are actively regulated under stress. For example, mistranslation can be beneficial to cells upon environmental changes and also alters cellular stress responses. Additionally, stress modulates both global and selective translational regulation through mechanisms including the change of aminoacyl-tRNA activity, tRNA pool reprogramming and ribosome heterogeneity. In this review, we draw on studies from both the prokaryotic and eukaryotic systems to discuss current findings of cellular adaptation at the level of translation, specifically translational fidelity and activity changes in response to a wide array of environmental stressors including oxidative stress, nutrient depletion, temperature variation, antibiotics and host colonization.

Reverse Transcriptase: From Transcriptomics to Genome Editing

Reverse transcriptases (RTs) are enzymes that can generate a complementary strand of DNA (cDNA) from RNA. Coupled with PCR, RTs have been widely used to detect RNAs and to clone expressed genes. Classical retroviral RTs have been improved by protein engineering. These enzymes and newly characterized RTs are key elements in the development of next-generation sequencing techniques that are now being applied to the study of transcriptomics. In addition, engineered RTs fused to a CRISPR/Cas9 nickase have recently shown great potential as tools to manipulate eukaryotic genomes. In this review, we discuss the properties and uses of wild type and engineered RTs in biotechnological applications, from conventional RT-PCR to recently introduced prime editing.

mRNA Editing, Processing and Quality Control in Caenorhabditis elegans

While DNA serves as the blueprint of life, the distinct functions of each cell are determined by the dynamic expression of genes from the static genome. The amount and specific sequences of RNAs expressed in a given cell involves a number of regulated processes including RNA synthesis (transcription), processing, splicing, modification, polyadenylation, stability, translation, and degradation. As errors during mRNA production can create gene products that are deleterious to the organism, quality control mechanisms exist to survey and remove errors in mRNA expression and processing. Here, we will provide an overview of mRNA processing and quality control mechanisms that occur in Caenorhabditis elegans, with a focus on those that occur on protein-coding genes after transcription initiation. In addition, we will describe the genetic and technical approaches that have allowed studies in C. elegans to reveal important mechanistic insight into these processes.

High Transcriptional Error Rates Vary as a Function of Gene Expression Level

Errors in gene transcription can be costly, and organisms have evolved to prevent their occurrence or mitigate their costs. The simplest interpretation of the drift barrier hypothesis suggests that species with larger population sizes would have lower transcriptional error rates. However, Escherichia coli seems to have a higher transcriptional error rate than species with lower effective population sizes, for example Saccharomyces cerevisiae. This could be explained if selection in E. coli were strong enough to maintain adaptations that mitigate the consequences of transcriptional errors through robustness, on a gene by gene basis, obviating the need for low transcriptional error rates and associated costs of global proofreading. Here, we note that if selection is powerful enough to evolve local robustness, selection should also be powerful enough to locally reduce error rates. We therefore predict that transcriptional error rates will be lower in highly abundant proteins on which selection is strongest. However, we only expect this result when error rates are high enough to significantly impact fitness. As expected, we find such a relationship between expression and transcriptional error rate for non-C→U errors in E. coli (especially G→A), but not in S. cerevisiae. We do not find this pattern for C→U changes in E. coli, presumably because most deamination events occurred during sample preparation, but do for C→U changes in S. cerevisiae, supporting the interpretation that C→U error rates estimated with an improved protocol, and which occur at rates comparable with E. coli non-C→U errors, are biological.

Identifying Transcription Error-Enriched Genomic Loci Using Nuclear Run-on Circular-Sequencing Coupled with Background Error Modeling

RNA polymerase transcribes certain genomic loci with higher errors rates. These transcription error-enriched genomic loci (TEELs) have implications in disease. Current deep-sequencing methods cannot distinguish TEELs from post-transcriptional modifications, stochastic transcription errors, and technical noise, impeding efforts to elucidate the mechanisms linking TEELs to disease. Here, we describe background error model-coupled precision nuclear run-on circular-sequencing (EmPC-seq) to discern genomic regions enriched for transcription misincorporations. EmPC-seq innovatively combines a nuclear run-on assay for capturing nascent RNA before post-transcriptional modifications, a circular-sequencing step that sequences the same nascent RNA molecules multiple times to improve accuracy, and a statistical model for distinguishing error-enriched regions among stochastic polymerase errors. Applying EmPC-seq to the ribosomal RNA transcriptome, we show that TEELs of RNA polymerase I are not randomly distributed but clustered together, with higher error frequencies at nascent transcript 3' ends. Our study establishes a reliable method of identifying TEELs with nucleotide precision, which can help elucidate their molecular origins.

DNA is not an ontologically distinctive developmental cause

In this article I critically evaluate the thesis that DNA is an ontologically distinctive developmental cause. I shall critically analyse different versions of the latter thesis by taking into consideration concrete developmental cases. I shall argue that DNA is neither a developmental determinant nor an ontologically distinctive developmental cause. Instead, I shall argue that mechanistic analysis shows that DNA's causal role in development depends on the higher robustness of the developmental processes in which it exerts its causal capacities. The focus on process and developmental system implies a metaphysical shift: rather than attributing to DNA molecules biochemically unique properties, I suggest that it might be better to think about DNA's causal role in development in terms of the causal capacities that DNA molecules manifest in a rich developmental milieu. I shall also suggest that my position is distinct both from the view advocating the instrumental primacy of DNA-centric biology and developmental constructionism. It is different from the former because it provides a substantial answer to the question of what makes DNA causally central in developmental processes. Finally, I argue that evolutionary considerations pose an important challenge to developmental constructionism.

Universally high transcript error rates in bacteria

Errors can occur at any level during the replication and transcription of genetic information. Genetic mutations derived mainly from replication errors have been extensively studied. However, fundamental details of transcript errors, such as their rate, molecular spectrum, and functional effects, remain largely unknown. To globally identify transcript errors, we applied an adapted rolling-circle sequencing approach to Escherichia coli, Bacillus subtilis, Agrobacterium tumefaciens, and Mesoplasma florum, revealing transcript-error rates 3 to 4 orders of magnitude higher than the corresponding genetic mutation rates. The majority of detected errors would result in amino-acid changes, if translated. With errors identified from 9929 loci, the molecular spectrum and distribution of errors were uncovered in great detail. A G→A substitution bias was observed in M. florum, which apparently has an error-prone RNA polymerase. Surprisingly, an increased frequency of nonsense errors towards the 3' end of mRNAs was observed, suggesting a Nonsense-Mediated Decay-like quality-control mechanism in prokaryotes.

Comparison of personal and shared frameshift neoantigen vaccines in a mouse mammary cancer model

Background

It is widely hoped that personal cancer vaccines will extend the number of patients benefiting from checkpoint and other immunotherapies. However, it is clear creating such vaccines will be challenging. It requires obtaining and sequencing tumor DNA/RNA, predicting potentially immunogenic neoepitopes and manufacturing a one-use vaccine. This process takes time and considerable cost. Importantly, most mutations will not produce an immunogenic peptide and many patient’s tumors do not contain enough DNA mutations to make a vaccine. We have discovered that frameshift peptides (FSP) created from errors in the production of RNA rather than from DNA mutations are potentially a rich source of neoantigens for cancer vaccines. These errors are predictable, enabling the production of a FSP microarray. Previously we found that these microarrays can identify both personal and shared neoantigens. Here, we compared the performance of personal cancer vaccines (PCVs) with that of a shared antigen vaccine, termed Frameshift Antigen Shared Therapeutic (FAST) vaccine, using the 4 T1 breast cancer model. Sera from 4 T1-tumor bearing mice were assayed on the peptide microarray containing 200 Fs neoantigens, for the PCV, the top 10 candidates were select and personal vaccines constructed and administrated to the respective mice. For the FAST, we selected the top 10 candidates with higher prevalence among all the mice challenged. Seven to 12 days challenged mice were immunized, combined or not with immune checkpoint inhibitor (ICI) (αPD-L1 and αCTLA-4). Primary and secondary tumor clearance and growth were evaluated as well as cellular and humoral immune response against the vaccine targets by IFN-γ ELISPOT and ELISA. Lastly, we analyzed the immune response of the FAST-vaccinated mice by flow cytometry in comparison to the control group.

Results

We found that PCVs and FAST vaccines both reduced primary tumor incidence and growth as well as lung metastases when delivered as monotherapies or in combination with ICI. Additionally, the FAST vaccine induces a robust and effective T-cell response.

Conclusions

These results suggest that FSPs produced from RNA-based errors are potent neoantigens that could enable production of off-the-shelf shared antigen vaccines for solid tumors with efficacy comparable to that of PCVs.

The FKH domain in FOXP3 mRNA frequently contains mutations in hepatocellular carcinoma that influence the subcellular localization and functions of FOXP3

The transcription factor forkhead box P3 (FOXP3) is a biomarker for regulatory T cells and can also be expressed in cancer cells, but its function in cancer appears to be divergent. The role of hepatocyte-expressed FOXP3 in hepatocellular carcinoma (HCC) is unknown. Here, we collected tumor samples and clinical information from 115 HCC patients and used five human cancer cell lines. We examined FOXP3 mRNA sequences for mutations, used a luciferase assay to assess promoter activities of FOXP3's target genes, and employed mouse tumor models to confirm in vitro results. We detected mutations in the FKH domain of FOXP3 mRNAs in 33% of the HCC tumor tissues, but in none of the adjacent nontumor tissues. None of the mutations occurred at high frequency, indicating that they occurred randomly. Notably, the mutations were not detected in the corresponding regions of FOXP3 genomic DNA, and many of them resulted in amino acid substitutions in the FKH region, altering FOXP3's subcellular localization. FOXP3 delocalization from the nucleus to the cytoplasm caused loss of transcriptional regulation of its target genes, inactivated its tumor-inhibitory capability, and changed cellular responses to histone deacetylase (HDAC) inhibitors. More complex FKH mutations appeared to be associated with worse prognosis in HCC patients. We conclude that mutations in the FKH domain of FOXP3 mRNA frequently occur in HCC and that these mutations are caused by errors in transcription and are not derived from genomic DNA mutations. Our results suggest that transcriptional mutagenesis of FOXP3 plays a role in HCC.

A Theoretical Framework for Evolutionary Cell Biology

One of the last uncharted territories in evolutionary biology concerns the link with cell biology. Because all phenotypes ultimately derive from events at the cellular level, this connection is essential to building a mechanism-based theory of evolution. Given the impressive developments in cell biological methodologies at the structural and functional levels, the potential for rapid progress is great. The primary challenge for theory development is the establishment of a quantitative framework that transcends species boundaries. Two approaches to the problem are presented here: establishing the long-term steady-state distribution of mean phenotypes under specific regimes of mutation, selection, and drift and evaluating the energetic costs of cellular structures and functions. Although not meant to be the final word, these theoretical platforms harbor potential for generating insight into a diversity of unsolved problems, ranging from genome structure to cellular architecture to aspects of motility in organisms across the Tree of Life.

RNA Transcription and Splicing Errors as a Source of Cancer Frameshift Neoantigens for Vaccines

The success of checkpoint inhibitors in cancer therapy is largely attributed to activating the patient's immune response to their tumor's neoantigens arising from DNA mutations. This realization has motivated the interest in personal cancer vaccines based on sequencing the patient's tumor DNA to discover neoantigens. Here we propose an additional, unrecognized source of tumor neoantigens. We show that errors in transcription of microsatellites (MS) and mis-splicing of exons create highly immunogenic frameshift (FS) neoantigens in tumors. The sequence of these FS neoantigens are predictable, allowing creation of a peptide array representing all possible neoantigen FS peptides. This array can be used to detect the antibody response in a patient to the FS peptides. A survey of 5 types of cancers reveals peptides that are personally reactive for each patient. This source of neoantigens and the method to discover them may be useful in developing cancer vaccines.

Base modifications affecting RNA polymerase and reverse transcriptase fidelity

Ribonucleic acid (RNA) is capable of hosting a variety of chemically diverse modifications, in both naturally-occurring post-transcriptional modifications and artificial chemical modifications used to expand the functionality of RNA. However, few studies have addressed how base modifications affect RNA polymerase and reverse transcriptase activity and fidelity. Here, we describe the fidelity of RNA synthesis and reverse transcription of modified ribonucleotides using an assay based on Pacific Biosciences Single Molecule Real-Time sequencing. Several modified bases, including methylated (m⁶A, m⁵C and m⁵U), hydroxymethylated (hm⁵U) and isomeric bases (pseudouridine), were examined. By comparing each modified base to the equivalent unmodified RNA base, we can determine how the modification affected cumulative RNA polymerase and reverse transcriptase fidelity. 5-hydroxymethyluridine and N⁶-methyladenosine both increased the combined error rate of T7 RNA polymerase and reverse transcriptases, while pseudouridine specifically increased the error rate of RNA synthesis by T7 RNA polymerase. In addition, we examined the frequency, mutational spectrum and sequence context of reverse transcription errors on DNA templates from an analysis of second strand DNA synthesis.

Transcription fidelity: New paradigms in epigenetic inheritance, genome instability and disease

RNA transcription errors are transient, yet frequent, events that do have consequences for the cell. However, until recently we lacked the tools to empirically measure and study these errors. Advances in RNA library preparation and next generation sequencing (NGS) have allowed the spectrum of transcription errors to be empirically measured over the entire transcriptome and in nascent transcripts. Combining these powerful methods with forward and reverse genetic strategies has refined our understanding of transcription factors known to enhance RNA accuracy and will enable the discovery of new candidates. Furthermore, these approaches will shed additional light on the complex interplay between transcription fidelity and other DNA transactions, such as replication and repair, and explore a role for transcription errors in cellular evolution and disease.

Using Frameshift Peptide Arrays for Cancer Neo-Antigens Screening

It has been demonstrated that DNA mutations generating neo-antigens are important for an effective immune response to tumors as evident from recent clinical studies of immune checkpoint inhibitors (ICIs). Further, it was shown that frameshift peptides (FSP) generated in tumors from insertions and deletions (INDELs) of microsatellites (MS) in coding region are a very good correlate of positive response to PD1 treatment. However, these types of DNA-sourced FSPs are infrequent in cancer. We hypothesize that tumors may also generate FSPs in transcription errors through INDELs in MS or by exon mis-splicing. Since there are a finite number of predictable sequences of such possible FSPs in the genome, we propose that peptide arrays with all possible FSPs could be used to analyze antibody reactivity to FSPs in patient sera as a FS neo-antigen screen. If this were the case it would facilitate finding common tumor neoantigens for cancer vaccines. Here we test this proposal using an array of 377 predicted FS antigens. The results of screening 9 types of dog cancer sera indicate that cancer samples had significantly higher antibody responses against FSPs than non-cancer samples. Both common reactive FSPs and cancer-type specific immune responses were detected. In addition, the protection of a common reactive FSP was tested in mouse tumor models, comparing to the non-reactive FSPs. The mouse homologs non-reactive FSPs did not offer protection in either the mouse melanoma or breast cancer models while the reactive FSP did in both models. The tumor protection was positively correlated to antibody response to the FSP. These data suggest that FSP arrays could be used for cancer neo-antigen screening.

Genome-wide Surveillance of Transcription Errors in Eukaryotic Organisms

Accurate transcription is required for the faithful expression of genetic information. Surprisingly though, little is known about the mechanisms that control the fidelity of transcription. To fill this gap in scientific knowledge, we recently optimized the circle-sequencing assay to detect transcription errors throughout the transcriptome of Saccharomyces cerevisiae, Drosophila melanogaster, and Caenorhabditis elegans. This protocol will provide researchers with a powerful new tool to map the landscape of transcription errors in eukaryotic cells so that the mechanisms that control the fidelity of transcription can be elucidated in unprecedented detail.

Poor codon optimality as a signal to degrade transcripts with frameshifts

Frameshifting errors are common and mRNA quality control pathways, such as nonsense-mediated decay (NMD), exist to degrade these aberrant transcripts. Recent work has shown the existence of a genetic link between NMD and codon-usage mediated mRNA decay. Here we present computational evidence that these pathways are synergic for removing frameshifts.

Detecting Rare Mutations and DNA Damage with Sequencing-Based Methods

There is a great need in biomedical and genetic research to detect DNA damage and de novo mutations, but doing so is inherently challenging because of the rarity of these events. The enormous capacity of current DNA sequencing technologies has opened the door for quantifying sequence variants present at low frequencies in vivo, such as within cancerous tissues. However, these sequencing technologies are error prone, resulting in high noise thresholds. Most DNA sequencing methods are also generally incapable of identifying chemically modified bases arising from DNA damage. In recent years, numerous specialized modifications to sequencing methods have been developed to address these shortcomings. Here, we review this landscape of emerging techniques, highlighting their respective strengths, weaknesses, and target applications.

Molecular mechanisms of RNA polymerase II transcription elongation elucidated by kinetic network models

Transcription elongation cycle (TEC) of RNA polymerase II (Pol II) is a process of adding a nucleoside triphosphate to the growing messenger RNA chain. Due to the long timescale events in Pol II TEC, an advanced computational technique, such as Markov State Model (MSM), is needed to provide atomistic mechanism and reaction rates. The combination of MSM and experimental results can be used to build a kinetic network model (KNM) of the whole TEC. This review provides a brief protocol to build MSM and KNM of the whole TEC, along with the latest findings of MSM and other computational studies of Pol II TEC. Lastly, we offer a perspective on potentially using a sequence dependent KNM to predict genome-wide transcription error.

Transcriptional inaccuracy threshold attenuates differences in RNA-dependent DNA synthesis fidelity between retroviral reverse transcriptases

In M13mp2 lacZα forward mutation assays measuring intrinsic fidelity of DNA-dependent DNA synthesis, wild-type human immunodeficiency virus type 1 (HIV-1) RTs of group M/subtype B previously showed >10-fold higher error rates than murine leukaemia virus (MLV) and avian myeloblastosis virus (AMV) RTs. An adapted version of the assay was used to obtain error rates of RNA-dependent DNA synthesis for several RTs, including wild-type HIV-1_BH10, HIV-1_ESP49, AMV and MLV RTs, and the high-fidelity mutants of HIV-1_ESP49 RT K65R and K65R/V75I. Our results showed that there were less than two-fold differences in fidelity between the studied RTs with error rates ranging within 2.5 × 10^-5 and 3.5 × 10^-5. These results were consistent with the existence of a transcriptional inaccuracy threshold, generated by the RNA polymerase while synthesizing the RNA template used in the assay. A modest but consistent reduction of the inaccuracy threshold was achieved by lowering the pH and Mg²⁺ concentration of the transcription reaction. Despite assay limitations, we conclude that HIV-1_BH10 and HIV-1_ESP49 RTs are less accurate when copying DNA templates than RNA templates. Analysis of the RNA-dependent mutational spectra revealed a higher tendency to introduce large deletions at the initiation of reverse transcription by all HIV-1 RTs except the double-mutant K65R/V75I.

Transcriptional mutagenesis reduces splicing fidelity in mammalian cells

Splicing fidelity is essential to the maintenance of cellular functions and viability, and mutations or natural variations in pre-mRNA sequences and consequent alteration of splicing have been implicated in the etiology and progression of numerous diseases. The extent to which transcriptional errors or lesion-induced transcriptional mutagenesis (TM) influences splicing fidelity is not currently known. To investigate this, we employed site-specific DNA lesions on the transcribed strand of a minigene splicing reporter in normal mammalian cells. These were the common mutagenic lesions O⁶-methylguanine (O⁶-meG) and 8-oxoguanine (8-oxoG). The minigene splicing reporters were derived from lamin A (LMNA) and proteolipid protein 1 (PLP1), both with known links to human diseases that result from deregulated splicing. In cells with active DNA repair, 1–4% misincorporation occurred opposite the lesions, which increased to 20–40% when repair was compromised. Furthermore, our results reveal that TM at a splice site significantly reduces in vivo splicing fidelity, thereby changing the relative expression of alternative splicing forms in mammalian cells. These findings suggest that splicing defects caused by transcriptional errors can potentially lead to phenotypic cellular changes and increased susceptibility to the development of disease.

Transcriptional accuracy modeling suggests two-step proofreading by RNA polymerase

We suggest a novel two-step proofreading mechanism with two sequential rounds of proofreading selection in mRNA transcription. It is based on the previous experimental observations that the proofreading RNA polymerase cleaves off transcript fragments of at least 2 nt and that transcript elongation after a nucleotide misincorporation is anomalously slow. Taking these results into account, we extend the description of the accuracy of template guided nucleotide selection beyond previous models of RNA polymerase-dependent DNA transcription. The model derives the accuracy of initial and proofreading base selection from experimentally estimated nearest-neighbor parameters. It is also used to estimate the small accuracy enhancement of polymerase revisiting of previous positions following transcript cleavage.

Amino acid misincorporation in recombinant proteins

Proteins provide the molecular basis for cellular structure, catalytic activity, signal transduction, and molecular transport in biological systems. Recombinant protein expression is widely used to prepare and manufacture novel proteins that serve as the foundation of many biopharmaceutical products. However, protein translation bioprocesses are inherently prone to low-level errors. These sequence variants caused by amino acid misincorporation have been observed in both native and recombinant proteins. Protein sequence variants impact product quality, and their presence can be exacerbated through cellular stress, overexpression, and nutrient starvation. Therefore, the cell line selection process, which is used in the biopharmaceutical industry, is not only directed towards maximizing productivity, but also focuses on selecting clones which yield low sequence variant levels, thereby proactively avoiding potentially inauspicious patient safety and efficacy outcomes. Here, we summarize a number of hallmark studies aimed at understanding the mechanisms of amino acid misincorporation, as well as exacerbating factors, and mitigation strategies. We also describe key advances in analytical technologies in the identification and quantification of sequence variants, and some practical considerations when using LC-MS/MS for detecting sequence variants.

The landscape of transcription errors in eukaryotic cells

Accurate transcription is required for the faithful expression of genetic information. To understand the molecular mechanisms that control the fidelity of transcription, we used novel sequencing technology to provide the first comprehensive analysis of the fidelity of transcription in eukaryotic cells. Our results demonstrate that transcription errors can occur in any gene, at any location, and affect every aspect of protein structure and function. In addition, we show that multiple proteins safeguard the fidelity of transcription and provide evidence suggesting that errors that evade these layers of RNA quality control profoundly affect the physiology of living cells. Together, these observations demonstrate that there is an inherent limit to the faithful expression of the genome and suggest that the impact of mutagenesis on cellular health and fitness is substantially greater than currently appreciated.

Transcription fidelity and its roles in the cell

•

The Trigger Loop is one of the major determinants of transcription fidelity.

•

Intrinsic proofreading occurs via transcript-assisted cleavage.

•

Factor-assisted proofreading takes place via exchange of RNAP active centres.

•

Misincorporation is a major source of transcription pausing.

•

Another role of fidelity is the prevention of conflicts with other cellular processes.

Accuracy of transcription is essential for productive gene expression, and the past decade has brought new understanding of the mechanisms ensuring transcription fidelity. The discovery of a new catalytic domain, the Trigger Loop, revealed that RNA polymerase can actively choose the correct substrates. Also, the intrinsic proofreading activity was found to proceed via a ribozyme-like mechanism, whereby the erroneous nucleoside triphosphate (NTP) helps its own excision. Factor-assisted proofreading was shown to proceed through an exchange of active centres, a unique phenomenon among proteinaceous enzymes. Furthermore, most recent in vivo studies have revised the roles of transcription accuracy and proofreading factors, as not only required for production of errorless RNAs, but also for prevention of frequent misincorporation-induced pausing that may cause conflicts with fellow RNA polymerases and the replication machinery.

Different rates of spontaneous mutation of chloroplastic and nuclear viroids as determined by high-fidelity ultra-deep sequencing

Mutation rates vary by orders of magnitude across biological systems, being higher for simpler genomes. The simplest known genomes correspond to viroids, subviral plant replicons constituted by circular non-coding RNAs of few hundred bases. Previous work has revealed an extremely high mutation rate for chrysanthemum chlorotic mottle viroid, a chloroplast-replicating viroid. However, whether this is a general feature of viroids remains unclear. Here, we have used high-fidelity ultra-deep sequencing to determine the mutation rate in a common host (eggplant) of two viroids, each representative of one family: the chloroplastic eggplant latent viroid (ELVd, Avsunviroidae) and the nuclear potato spindle tuber viroid (PSTVd, Pospiviroidae). This revealed higher mutation frequencies in ELVd than in PSTVd, as well as marked differences in the types of mutations produced. Rates of spontaneous mutation, quantified in vivo using the lethal mutation method, ranged from 1/1000 to 1/800 for ELVd and from 1/7000 to 1/3800 for PSTVd depending on sequencing run. These results suggest that extremely high mutability is a common feature of chloroplastic viroids, whereas the mutation rates of PSTVd and potentially other nuclear viroids appear significantly lower and closer to those of some RNA viruses.

Spontaneous mutations are the ultimate source of genetic variation and their characterization provides fundamental information about evolutionary processes. The highest mutation rate so far described corresponds to a hammerhead viroid infecting plant chloroplasts. Viroids are plant-exclusive parasites constituted by 250–400 nt-long, non-protein-coding RNAs, and are divided into two families with distinct mechanisms of replication and localization: chloroplastic (Avsunviroidae), and nuclear (Pospiviroidae). Here, we have used high-fidelity ultra-deep sequencing to compare side by side the mutation rates of one representative member of each viroid family in the same host. We found that the mutation rate of the nuclear viroid was several fold lower than that of the chloroplastic viroid.

Transcriptional fidelities of human mitochondrial POLRMT, yeast mitochondrial Rpo41, and phage T7 single-subunit RNA polymerases

Single-subunit RNA polymerases (RNAPs) are present in phage T7 and in mitochondria of all eukaryotes. This RNAP class plays important roles in biotechnology and cellular energy production, but we know little about its fidelity and error rates. Herein, we report the error rates of three single-subunit RNAPs measured from the catalytic efficiencies of correct and all possible incorrect nucleotides. The average error rates of T7 RNAP (2 × 10^-6), yeast mitochondrial Rpo41 (6 × 10^-6), and human mitochondrial POLRMT (RNA polymerase mitochondrial) (2 × 10^-5) indicate high accuracy/fidelity of RNA synthesis resembling those of replicative DNA polymerases. All three RNAPs exhibit a distinctly high propensity for GTP misincorporation opposite dT, predicting frequent A→G errors in RNA with rates of ∼10^-4 The A→C, G→A, A→U, C→U, G→U, U→C, and U→G errors mostly due to pyrimidine-purine mismatches were relatively frequent (10^-5-10^-6), whereas C→G, U→A, G→C, and C→A errors from purine-purine and pyrimidine-pyrimidine mismatches were rare (10^-7-10^-10). POLRMT also shows a high C→A error rate on 8-oxo-dG templates (∼10^-4). Strikingly, POLRMT shows a high mutagenic bypass rate, which is exacerbated by TEFM (transcription elongation factor mitochondrial). The lifetime of POLRMT on terminally mismatched elongation substrate is increased in the presence of TEFM, which allows POLRMT to efficiently bypass the error and continue with transcription. This investigation of nucleotide selectivity on normal and oxidatively damaged DNA by three single-subunit RNAPs provides the basic information to understand the error rates in mitochondria and, in the case of T7 RNAP, to assess the quality of in vitro transcribed RNAs.

Accurate RNA consensus sequencing for high-fidelity detection of transcriptional mutagenesis-induced epimutations

Transcriptional mutagenesis (TM) due to misincorporation during RNA transcription can result in mutant RNAs, or epimutations, that generate proteins with altered properties. TM has long been hypothesized to play a role in aging, cancer, and viral and bacterial evolution. However, inadequate methodologies have limited progress in elucidating a causal association. We present a high-throughput, highly accurate RNA sequencing method to measure epimutations with single-molecule sensitivity. Accurate RNA consensus sequencing (ARC-seq) uniquely combines RNA barcoding and generation of multiple cDNA copies per RNA molecule to eliminate errors introduced during cDNA synthesis, PCR, and sequencing. The stringency of ARC-seq can be scaled to accommodate the quality of input RNAs. We apply ARC-seq to directly assess transcriptome-wide epimutations resulting from RNA polymerase mutants and oxidative stress.