Conserved rates and patterns of transcription errors across bacterial growth states and lifestyles

Traverse, Charles C.; Ochman, Howard

doi:10.1073/pnas.1525329113

Cited by 68 publications

(77 citation statements)

References 66 publications

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“…In agreement with drift barrier theory, large-N e E. coli exhibits a local solution-a tendency for transcription errors to have synonymous effects-while small-N e B. aphidicola does not (Traverse and Ochman 2016a). While, as predicted, the global solution of low transcriptional error rates does not obey the naïve drift barrier expectation of being higher in B. aphidicola than in E. coli (Traverse and Ochman 2016a), nor are transcription error rates drastically lower in B. aphidicola as predicted by previous theory on the interplay between global and local solutions (Rajon and Masel 2011;McCandlish and Plotkin 2016).…”

Section: Discussionsupporting

confidence: 74%

“…While, as predicted, the global solution of low transcriptional error rates does not obey the naïve drift barrier expectation of being higher in B. aphidicola than in E. coli (Traverse and Ochman 2016a), nor are transcription error rates drastically lower in B. aphidicola as predicted by previous theory on the interplay between global and local solutions (Rajon and Masel 2011;McCandlish and Plotkin 2016). This significantly lower rate relative to E. coli is, however, found in intermediate-N e C. elegans.…”

Section: Discussionmentioning

confidence: 45%

“…The simplest interpretation of the drift barrier would seem to imply that large-N e species show stricter quality control over all biological processes, e.g., higher fidelity in DNA replication, transcription, and translation, than small-N e species, because molecular defects in quality control mechanisms are less effectively purged in the latter (Lynch 2010;Traverse and Ochman 2016a).…”

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confidence: 99%

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Drift barriers to quality control when genes are expressed at different levels

Xiong

McEntee

Porfirio

et al. 2016

Preprint

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Gene expression is imperfect, sometimes leading to toxic products. Solutions take two forms: globally reducing error rates, or ensuring that the consequences of erroneous expression are relatively harmless. The latter is optimal, but because it must evolve independently at so many loci, it is subject to a stringent "drift barrier"-a limit to how weak the effects of a deleterious mutation s can be, while still being effectively purged by selection, expressed in terms of the population size N of an idealized population such that purging requires s , 21/N. In previous work, only large populations evolved the optimal local solution, small populations instead evolved globally low error rates, and intermediate populations were bistable, with either solution possible. Here, we take into consideration the fact that the effectiveness of purging varies among loci, because of variation in gene expression level, and variation in the intrinsic vulnerabilities of different gene products to error. The previously found dichotomy between the two kinds of solution breaks down, replaced by a gradual transition as a function of population size. In the extreme case of a small enough population, selection fails to maintain even the global solution against deleterious mutations, explaining the nonmonotonic relationship between effective population size and transcriptional error rate that was recently observed in experiments on Escherichia coli, Caenorhabditis elegans, and Buchnera aphidicola.KEYWORDS cryptic genetic variation; stop codon readthrough; robustness; evolvability; transcriptional errors; proofreading I N classical population genetic models of idealized populations, the probability of fixation of a new mutant depends sharply on the product of the selection coefficient, s, and the population size, N. As s falls below 21/N, fixation probabilities drop exponentially, corresponding to efficient selective purging of deleterious mutations. For s . 21/N, random genetic drift makes the fate of new mutants less certain. This nonlinear dependence of fixation probability on sN has given rise to the "drift barrier" hypothesis (Lynch 2007), which holds that populations are characterized by a threshold or "barrier" value of the selection coefficient, s, corresponding to the tipping point at which the removal of deleterious mutations switches between effective and ineffective. In idealized populations, described by Wright-Fisher or Moran models, the drift barrier is positioned at s = 21/N. Drift barriers also exist, albeit sometimes with less abrupt threshold behavior, in more complex models of evolution in which some assumptions of an idealized population are relaxed (Good and Desai 2014).The drift barrier theory argues that variation among species in their characteristic threshold values for s, thresholds that are equal by definition to the inverse of the selection effective population size, N e , can explain why different species have different characteristics, e.g., streamlined vs. bloated genomes (Lynch 2007). The simplest i...

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Section: Discussionsupporting

confidence: 74%

Section: Discussionmentioning

confidence: 45%

mentioning

confidence: 99%

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Drift barriers to quality control when genes are expressed at different levels

Xiong

McEntee

Porfirio

et al. 2016

Preprint

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“…Such errors are not heritable and usually result in a very limited number of altered proteins. Traverse et al had measured the rates of transcription errors in Escherichia coli and in endosymbionts to range from 2 × 10 −5 to 5 × 10 −5 per base. Gout et al had analyzed the transcriptome of Caenorhabditis elegan and had detected a transcription error rate of 4 × 10 −6 .…”

Section: Discussionmentioning

confidence: 99%

Enhanced CHO Clone Screening: Application of Targeted Locus Amplification and Next‐Generation Sequencing Technologies for Cell Line Development

Aeschlimann

Graf

Mayilo

et al. 2019

Biotechnology Journal

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Early analytical clone screening is important during Chinese hamster ovary (CHO) cell line development of biotherapeutic proteins to select a clonally derived cell line with most favorable stability and product quality. Sensitive sequence confirmation methods using mass spectrometry have limitations in throughput and turnaround time. Next‐generation sequencing (NGS) technologies emerged as alternatives for CHO clone analytics. We report an efficient NGS workflow applying the targeted locus amplification (TLA) strategy for genomic screening of antibody expressing CHO clones. In contrast to previously reported RNA sequencing approaches, TLA allows for targeted sequencing of genomic integrated transgenic DNA without prior locus information, robust detection of single‐nucleotide variants (SNVs) and transgenic rearrangements. During clone selection, TLA/NGS revealed CHO clones with high‐level SNVs within the antibody gene and we report in another case the utility of TLA/NGS to identify rearrangements at transgenic DNA level. We also determined detection limits for SNVs calling and the potential to identify clone contaminations by TLA/NGS. TLA/NGS also allows to identify genetically identical clones. In summary, we demonstrate that TLA/NGS is a robust screening method useful for routine clone analytics during cell line development with the potential to process up to 24 CHO clones in less than 7 workdays.

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“…The CircSeq protocol (8) sequences the same nucleotide fragments several times in tandem, allowing errors in sequencing to be identified by differences among these tandem copies, rather than between the genome and the tandem copies. This procedure produces error rates of less than 10 −6 per base (8), much lower than the transcriptional error rates of 3.4 × 10 −5 to 5.1 × 10 −5 reported by Traverse and Ochman (4). Furthermore, as the quality score cutoff used in their analysis increases, the error rates inferred by Traverse and Ochman decrease and then asymptote.…”

Section: Possible Explanations For Conserved Error Ratesmentioning

confidence: 80%

Transcriptional errors and the drift barrier

McCandlish

Plotkin

2016

Proc. Natl. Acad. Sci. U.S.A.

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Population genetics predicts that the balance between natural selection and genetic drift is determined by the population size. Species with large population sizes are predicted to have properties governed mainly by selective forces; whereas species with small population sizes should exhibit features governed by mutational processes alone. This "drift-barrier hypothesis" has been successful in explaining extensive variation in genome size, mutation rate, transposable element abundance, and other molecular features across diverse taxa (1-3). However, in PNAS Traverse and Ochman (4) report a striking exception to this theory by showing that transcriptional error rates are nearly equal across several bacterial species with very different population sizes.Although the term "drift barrier" was coined in the context of mutation rates (5), the drift-barrier hypothesis applies to any heritable trait (e.g., ref. 6), and so it can provide a simple explanation for patterns of many molecular traits across the diversity of life. The explanation relies on the fact that mutations whose effects on fitness are smaller than the inverse of the population size behave like neutral mutations. As a result, natural selection will tend to optimize a trait until the selective benefits of further optimization are smaller than the inverse of the population size (7): that is, until the population hits the drift barrier. Because the location of the drift barrier depends on the population size, so too should the values of these phenotypic traits. Thus, differences in population size among species can explain a concerted syndrome of traits at the cellular and molecular levels (1-3, 5, 6).In the context of broad empirical support for the drift-barrier hypothesis, the results of Traverse and Ochman (4) are particularly surprising. Using a CircSeq (8) strategy (based on the sequencing of short, circularized fragments of mRNA that are copied multiple times by rolling-circle amplification before sequencing) to reduce errors in high-throughput sequencing, Traverse and Ochman measured transcriptional error rates in Escherichia coli along with two endosymbiotic prokaryotes, Buchnera aphidicola and Carsonella ruddii. These endosymbionts feature dramatically reduced genome sizes, increased mutation rates, and other features typical of their small population sizes, including the loss of several transcriptional fidelity factors (4). Nevertheless, Traverse and Ochman report less than twofold variation in the rates of transcriptional errors among these three species. This result is in sharp contrast to mutation rates, which differ by orders of magnitude between species (5). Possible Explanations for Conserved Error RatesWhat could explain the apparent constancy of transcriptional error rates across species with such different population sizes? One hypothesis we must consider is errors in the sequencing procedure itself. If the rate of sequencing error exceeds the true transcriptional error rates, then it would give the impression of constant error rates. Ho...

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Conserved rates and patterns of transcription errors across bacterial growth states and lifestyles

Cited by 68 publications

References 66 publications

Drift barriers to quality control when genes are expressed at different levels

Drift barriers to quality control when genes are expressed at different levels

Enhanced CHO Clone Screening: Application of Targeted Locus Amplification and Next‐Generation Sequencing Technologies for Cell Line Development

Transcriptional errors and the drift barrier

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