Estimating selection on synonymous codon usage from noisy experimental data

Wallace, Edward W.J.; Airoldi, Edoardo M.; Drummond, D. Allan

doi:10.1093/molbev/mst051

Cited by 49RNA and protein synthesis mechanismsEvolution and Genetic DynamicsGenomics and Phylogenetic Studies

Estimating selection on synonymous codon usage from noisy experimental data

Open access

Wallace, Edward W.J., Airoldi, Edoardo M., Drummond, D. Allan·2013·Molecular Biology and Evolution

DOI 10.1093/molbev/mst051PMC PMC3649678

Open this paper in CoChat — free account Open PDF

Abstract

A key goal in molecular evolution is to extract mechanistic insights from signatures of selection. A case study is codon usage, where despite many recent advances and hypotheses, two longstanding problems remain: the relative contribution of selection and mutation in determining codon frequencies and the relative contribution of translational speed and accuracy to selection. The relevant targets of selection--the rate of translation and of mistranslation of a codon per unit time in the cell--can only be related to mechanistic properties of the translational apparatus if the number of transcripts per cell is known, requiring use of gene expression measurements. Perhaps surprisingly, different gene-expression data sets yield markedly different estimates of selection. We show that this is largely due to measurement noise, notably due to differences between studies rather than instrument error or biological variability. We develop an analytical framework that explicitly models noise in expression in the context of the population-genetic model. Estimates of mutation and selection strength in budding yeast produced by this method are robust to the expression data set used and are substantially higher than estimates using a noise-blind approach. We introduce per-gene selection estimates that correlate well with previous scoring systems, such as the codon adaptation index, while now carrying an evolutionary interpretation. On average, selection for codon usage in budding yeast is weak, yet our estimates show that genes range from virtually unselected to average per-codon selection coefficients above the inverse population size. Our analytical framework may be generally useful for distinguishing biological signals from measurement noise in other applications that depend upon measurements of gene expression.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Integrity signals

Registry

Crossref · 10.1093/molbev/mst051

Cites

66 of 66 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Because codon bias strongly associates with mRNA level, the null expectation is that it will correlate with PPM even if codon bias had no effect on translational activity.
“For features such as codon bias, which arises in response to selection for translational efficiency [66], association with increased PPM might seem an obvious causal link, but because codon bias strongly associates with mRNA level, the null expectation is that it will correlate with PPM even if codon bias had no effect on translational activity at all.”
From Accounting for Experimental Noise Reveals That mRNA Levels, Amplified by Post-Transcriptional Processes, Largely Determine Steady-State Protein Levels in Yeast (2015) · cites this paper as [66]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Bayesian Data Analysis
Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013) · doi:10.1201/b16018 · Cited by 27,276 · see citing works
Data Analysis Using Regression and Multilevel/Hierarchical Models
Gelman, A., & Hill, J. (2006) · doi:10.1017/cbo9780511790942 · Cited by 13,597 · see citing works
Gentleman R: R: A language for data analysis and graphics
Ihaka, R., & Gentleman, R. (1996) · Journal of Computational and Graphical Statistics · doi:10.1080/10618600.1996.10474713 · Cited by 11,747 · see citing works
General methods for monitoring convergence of iterative simulations
Brooks, S. P., & Gelman, A. (1998) · Journal of Computational and Graphical Statistics · doi:10.1080/10618600.1998.10474787 · Cited by 6,045 · see citing works
The codon adaptation index-a measure of directional synonymous codon usage bias, and its potential applications
Sharp, P. M., & Li, W.-H. (1987) · Nucleic Acids Research · doi:10.1093/nar/15.3.1281 · Cited by 3,992 · see citing works
Genome-Wide Analysis in Vivo of Translation with Nucleotide Resolution Using Ribosome Profiling
Ingolia, N. T., Ghaemmaghami, S., Newman, J. R. S., & Weissman, J. S. (2009) · Science · doi:10.1126/science.1168978 · Cited by 3,853 · see citing works
A "Silent" Polymorphism in the MDR 1 Gene Changes Substrate Specificity
Kimchi-Sarfaty, C., Oh, J. M., Kim, I.-W., Sauna, Z. E., Calcagno, A. M., Ambudkar, S. V., & Gottesman, M. M. (2007) · Science · doi:10.1126/science.1135308 · Cited by 2,416 · see citing works
Tackling the widespread and critical impact of batch effects in high-throughput data
Leek, J. T., Scharpf, R. B., Bravo, H. C., Simcha, D., Langmead, B., Johnson, W. E., Geman, D., Baggerly, K., & Irizarry, R. A. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2825 · Cited by 2,196 · see citing works
Measurement Error in Nonlinear Models
Carroll, R. J., Ruppert, D., Stefanski, L. A., & Crainiceanu, C. M. (2006) · Chapman & Hall/CRC eBooks · doi:10.1201/9781420010138 · Cited by 2,125 · see citing works
Noise in Gene Expression: Origins, Consequences, and Control
Raser, J. M., & O’Shea, E. K. (2005) · Science · doi:10.1126/science.1105891 · Cited by 1,719 · see citing works
Synonymous but not the same: the causes and consequences of codon bias
Plotkin, J. B., & Kudla, G. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2899 · Cited by 1,677 · see citing works
Coding-Sequence Determinants of Gene Expression in Escherichia coli
Kudla, G., Murray, A. W., Tollervey, D., & Plotkin, J. B. (2009) · Science · doi:10.1126/science.1170160 · Cited by 1,458 · see citing works
Correlation between the abundance of Escherichia coli transfer RNAs and the occurrence of the respective codons in its protein genes: A proposal for a synonymous codon choice that is optimal for the E. coli translational system
Ikemura, T. (1981) · Journal of Molecular Biology · doi:10.1016/0022-2836(81)90003-6 · Cited by 1,423 · see citing works
Measurement error in nonlinear models: a modern perspective
Carroll, R. J. (2006) · Cited by 1,374 · see citing works
Selection on Codon Bias
Hershberg, R., & Petrov, D. A. (2008) · Annual Review of Genetics · doi:10.1146/annurev.genet.42.110807.091442 · Cited by 1,056 · see citing works
Mistranslation-Induced Protein Misfolding as a Dominant Constraint on Coding-Sequence Evolution
Drummond, D. A., & Wilke, C. O. (2008) · Cell · doi:10.1016/j.cell.2008.05.042 · Cited by 1,041 · see citing works
Self-citation
The selection-mutation-drift theory of synonymous codon usage.
Bulmer, M. G. (1991) · Genetics · doi:10.1093/genetics/129.3.897 · Cited by 1,024 · see citing works
An evolutionarily conserved mechanism for controlling the efficiency of protein translation
Tuller, T., Carmi, A., Vestsigian, K., Navon, S., Dorfan, Y., Zaborske, J., Pan, T., Dahan, O., Furman, I., & Pilpel, Y. (2010) · Cell · doi:10.1016/j.cell.2010.03.031 · Cited by 874 · see citing works
The Laplace Distribution and Generalizations
Kotz, S., Kozubowski, T. J., & Podgórski, K. (2001) · Birkhäuser Boston eBooks · doi:10.1007/978-1-4612-0173-1 · Cited by 830 · see citing works
Noise in protein expression scales with natural protein abundance
Bar-Even, A., Paulsson, J., Maheshri, N., Carmi, M., O'Shea, E., Pilpel, Y., & Barkai, N. (2006) · Nature Genetics · doi:10.1038/ng1807 · Cited by 807 · see citing works
Synonymous codon usage in Drosophila melanogaster: Natural selection and translational accuracy
Akashi, H. (1994) · Genetics · doi:10.1093/genetics/136.3.927 · Cited by 742 · see citing works
A genome-wide view of the spectrum of spontaneous mutations in yeast.
Lynch, M., Sung, W., Morris, K., Coffey, N., Landry, C. R., Dopman, E. B., Dickinson, W. J., Okamoto, K., Kulkarni, S., Hartl, D. L., et al. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0803466105 · Cited by 708 · see citing works
Single-RNA counting reveals alternative modes of gene expression in yeast
Zenklusen, D., Larson, D. R., & Singer, R. H. (2008) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.1514 · Cited by 684 · see citing works
Genome-wide analysis of mRNA translation profiles in Saccharomyces cerevisiae
Arava, Y., Wang, Y., Storey, J. D., Liu, C. L., Brown, P. O., & Herschlag, D. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0635171100 · Cited by 663 · see citing works
Translational control in biology and medicine
Mathews, M. B., Sonenberg, N., & Hershey, J. W. B. (2007) · Cited by 661 · see citing works
The VGAM Package for Categorical Data Analysis
Yee, T. W. (2010) · Journal of Statistical Software · doi:10.18637/jss.v032.i10 · Cited by 640 · see citing works
The anti-Shine–Dalgarno sequence drives translational pausing and codon choice in bacteria
Li, G., Oh, E., & Weissman, J. S. (2012) · Nature · doi:10.1038/nature10965 · Cited by 640 · see citing works
Correlation between the abundance of yeast transfer RNAs and the occurrence of the respective codons in protein genes
Ikemura, T. (1982) · Journal of Molecular Biology · doi:10.1016/0022-2836(82)90250-9 · Cited by 605 · see citing works
The Laplace Distribution and Generalizations: A Revisit with Applications to Communications, Economics, Engineering, and Finance
Kotz, S., Kozubowski, T. J., & Podgórski, K. (2001) · Cited by 592 · see citing works
STRUCTURAL INSIGHTS INTO TRANSLATIONAL FIDELITY
Ogle, J. M., & Ramakrishnan, V. (2005) · Annual Review of Biochemistry · doi:10.1146/annurev.biochem.74.061903.155440 · Cited by 586 · see citing works
Codon usage determines translation rate in Escherichia coli
Sørensen, M. A., Kurland, C. G., & Pedersen, S. B. (1989) · Journal of Molecular Biology · doi:10.1016/0022-2836(89)90260-x · Cited by 579 · see citing works
The evolutionary consequences of erroneous protein synthesis
Allan Drummond, D., & Wilke, C. O. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2662 · Cited by 515 · see citing works
Self-citation
Codon preferences in free-living microorganisms
Andersson, S. G. E., & Kurland, C. G. (1990) · Microbiological Reviews · doi:10.1128/mr.54.2.198-210.1990 · Cited by 495 · see citing works
Mutation rate variation in multicellular eukaryotes: causes and consequences
Baer, C. F., Miyamoto, M. M., & Denver, D. R. (2007) · Nature Reviews Genetics · doi:10.1038/nrg2158 · Cited by 458 · see citing works
The application of statistical physics to evolutionary biology
Sella, G., & Hirsh, A. E. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0501865102 · Cited by 457 · see citing works
The frequency of translational misreading errors in E. coli is largely determined by tRNA competition
Kramer, E. B., & Farabaugh, P. J. (2006) · RNA · doi:10.1261/rna.294907 · Cited by 442 · see citing works
Variation in the strength of selected codon usage bias among bacteria
Sharp, P. M. (2005) · Nucleic Acids Research · doi:10.1093/nar/gki242 · Cited by 430 · see citing works
The Systemic Imprint of Growth and Its Uses in Ecological (Meta)Genomics
Vieira‐Silva, S., & Rocha, E. P. C. (2010) · PLoS Genetics · doi:10.1371/journal.pgen.1000808 · Cited by 408 · see citing works
A Layered Grammar of Graphics
Wickham, H. (2009) · Journal of Computational and Graphical Statistics · doi:10.1198/jcgs.2009.07098 · Cited by 400 · see citing works
Fidelity at the Molecular Level: Lessons from Protein Synthesis
Zaher, H. S., & Green, R. (2009) · Cell · doi:10.1016/j.cell.2009.01.036 · Cited by 381 · see citing works
Estimating the Per-Base-Pair Mutation Rate in the Yeast Saccharomyces cerevisiae
Lang, G. I., & Murray, A. W. (2008) · Genetics · doi:10.1534/genetics.107.071506 · Cited by 344 · see citing works
Synonymous Codon Usage in Escherichia coli: Selection for Translational Accuracy
Stoletzki, N., & Eyre‐Walker, A. (2006) · Molecular Biology and Evolution · doi:10.1093/molbev/msl166 · Cited by 340 · see citing works
Mutation-Selection Models of Codon Substitution and Their Use to Estimate Selective Strengths on Codon Usage
Yang, Z., & Nielsen, R. (2008) · Molecular Biology and Evolution · doi:10.1093/molbev/msm284 · Cited by 331 · see citing works
A universal trend of reduced mrna stability near the translation-initiation site in prokaryotes and eukaryotes
Gu, W., Zhou, T., & Wilke, C. O. (2010) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000664 · Cited by 313 · see citing works
Balanced Codon Usage Optimizes Eukaryotic Translational Efficiency
Qian, W., Yang, J.-R., Pearson, N. M., Maclean, C. J., & Zhang, J. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002603 · Cited by 303 · see citing works
Misfolded proteins impose a dosage-dependent fitness cost and trigger a cytosolic unfolded protein response in yeast
Geiler‐Samerotte, K., Dion, M. F., Budnik, B., Wang, S. M., Hartl, D. L., & Drummond, D. A. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1017570108 · Cited by 285 · see citing works
Self-citation
Codon Usage and tRNA Genes in Eukaryotes: Correlation of Codon Usage Diversity with Translation Efficiency and with CG-Dinucleotide Usage as Assessed by Multivariate Analysis
Kanaya, S., Yamada, Y., Kinouchi, M., Kudo, Y., & Ikemura, T. (2001) · Journal of Molecular Evolution · doi:10.1007/s002390010219 · Cited by 279 · see citing works
What Drives Codon Choices in Human Genes?
Karlin, S., & Mrázek, J. (1996) · Journal of Molecular Biology · doi:10.1006/jmbi.1996.0528 · Cited by 278 · see citing works
Number and distribution of polyadenylated RNA sequences in yeast
Hereford, L. M., & Rosbash, M. (1977) · Cell · doi:10.1016/0092-8674(77)90032-0 · Cited by 261 · see citing works
Ab initio construction of a eukaryotic transcriptome by massively parallel mRNA sequencing
Yassour, M., Kaplan, T., Fraser, H. B., Levin, J. Z., Pfiffner, J., Adiconis, X., Schroth, G. P., Luo, S. J., Khrebtukova, I., Gnirke, A., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0812841106 · Cited by 213 · see citing works
Translationally Optimal Codons Associate with Structurally Sensitive Sites in Proteins
Zhou, T., Weems, M., & Wilke, C. O. (2009) · Molecular Biology and Evolution · doi:10.1093/molbev/msp070 · Cited by 205 · see citing works
Principles of Translational ControlPreprint
Hershey, J. W. B., Sonenberg, N., & Mathews, M. B. (2018) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a032607 · Cited by 205 · see citing works
Explaining complex codon usage patterns with selection for translational efficiency, mutation bias, and genetic drift
Shah, P., & Gilchrist, M. A. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1016719108 · Cited by 196 · see citing works
Quantification of the yeast transcriptome by single-molecule sequencing
Lipson, D., Raz, T., Kieu, A., Jones, D. R., Giladi, E., Thayer, E. C., Thompson, J. F., Letovsky, S., Milos, P. M., & Causey, M. (2009) · Nature Biotechnology · doi:10.1038/nbt.1551 · Cited by 187 · see citing works
Control of translation efficiency in yeast by codon–anticodon interactions
Letzring, D. P., Dean, K., & Grayhack, E. J. (2010) · RNA · doi:10.1261/rna.2411710 · Cited by 167 · see citing works
A quantitative estimation of the global translational activity in logarithmically growing yeast cells
von der Haar, T. (2008) · BMC Systems Biology · doi:10.1186/1752-0509-2-87 · Cited by 163 · see citing works
Mutation Rates across Budding Yeast Chromosome VI Are Correlated with Replication Timing
Lang, G. I., & Murray, A. W. (2011) · Genome Biology and Evolution · doi:10.1093/gbe/evr054 · Cited by 159 · see citing works
A comprehensive analysis of translational missense errors in the yeast Saccharomyces cerevisiae
Kramer, E. B., Vallabhaneni, H., Mayer, L. M., & Farabaugh, P. J. (2010) · RNA · doi:10.1261/rna.2201210 · Cited by 134 · see citing works
Error Distribution for Gene Expression Data
Purdom, E., & Holmes, S. (2005) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1070 · Cited by 117 · see citing works
Neighboring base effects on substitution rates in pseudogenes.
Bulmer, M. G. (1986) · Molecular Biology and Evolution · doi:10.1093/oxfordjournals.molbev.a040401 · Cited by 108 · see citing works
A comprehensive, quantitative, and genome-wide model of translation
Siwiak, M., & Zielenkiewicz, P. (2010) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000865 · Cited by 93 · see citing works
DNA Sequence Analysis of Spontaneous Mutagenesis in Saccharomyces cerevisiae
Kunz, B. A., Ramachandran, K., & Vonarx, E. J. (1998) · Genetics · doi:10.1093/genetics/148.4.1491 · Cited by 76 · see citing works
Getting Started in Probabilistic Graphical Models
Airoldi, E. M. (2007) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0030252 · Cited by 71 · see citing works
Self-citation
Codon choice and gene expression: synonymous codons differ in translational accuracy.
Dix, D. B., & Thompson, R. C. (1989) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.86.18.6888 · Cited by 47 · see citing works
Spontaneous mutagenesis in haploid and diploid Saccharomyces cerevisiae
Ohnishi, G., Endo, K., Doi, A., Fujita, A., Daigaku, Y., Nunoshiba, T., & Yamamoto, K. (2004) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2004.10.120 · Cited by 46 · see citing works
Translationally optimal codons associate with aggregation‐prone sites in proteins
Lee, Y., Zhou, T., Tartaglia, G. G., Vendruscolo, M., & Wilke, C. O. (2010) · PROTEOMICS · doi:10.1002/pmic.201000229 · Cited by 42 · see citing works

Flagged first, then by citations

Sorted by citations

Codon influence on protein expression in E. coli correlates with mRNA levels
Boël, G., Letso, R. R., Neely, H., Price, W. N., Wong, K., Su, M., Luff, J. D., Valecha, M., Everett, J. K., Acton, T., et al. (2016) · Nature · doi:10.1038/nature16509 · Cited by 429 · see citing works
Genes from scratch – the evolutionary fate of de novo genes
Schlötterer, C. (2015) · Trends in Genetics · doi:10.1016/j.tig.2015.02.007 · Cited by 222 · see citing works
Accounting for Experimental Noise Reveals That mRNA Levels, Amplified by Post-Transcriptional Processes, Largely Determine Steady-State Protein Levels in Yeast
Csárdi, G., Franks, A., Choi, D. S., Airoldi, E. M., & Drummond, D. A. (2015) · PLOS Genetics · doi:10.1371/journal.pgen.1005206 · Cited by 181 · see citing works
Self-citation
An Integrated Approach Reveals Regulatory Controls on Bacterial Translation Elongation
Subramaniam, A. R., Zid, B. M., & O’Shea, E. K. (2014) · Cell · doi:10.1016/j.cell.2014.10.043 · Cited by 141 · see citing works
Accounting for biases in riboprofiling data indicates a major role for proline in stalling translationPreprint
Artieri, C. G., & Fraser, H. B. (2014) · Genome Research · doi:10.1101/gr.175893.114 · Cited by 133 · see citing works
A Nutrient-Driven tRNA Modification Alters Translational Fidelity and Genome-wide Protein Coding across an Animal Genus
Zaborske, J. M., DuMont, V. L. B., Wallace, E. W. J., Pan, T., Aquadro, C. F., & Drummond, D. A. (2014) · PLoS Biology · doi:10.1371/journal.pbio.1002015 · Cited by 120 · see citing works
Self-citation
Global translational impacts of the loss of the tRNA modification t6A in yeast
Thiaville, P. C., Legendre, R., Rojas‐Benítez, D., Baudin‐Baillieu, A., Hatin, I., Chalancon, G., Glavic, Á., Namy, O., & de Crécy‐Lagard, V. (2015) · Microbial Cell · doi:10.15698/mic2016.01.473 · Cited by 119 · see citing works
Translate to divide: сontrol of the cell cycle by protein synthesis
Department of Biochemistry and Biophysics, T. A. U., Polymenis, M., Aramayo, R., & Department of Biology, T. A. U. (2015) · Microbial Cell · doi:10.15698/mic2015.04.198 · Cited by 91 · see citing works
Genetic Influences on Translation in Yeast
Albert, F. W., Muzzey, D., Weissman, J. S., & Kruglyak, L. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004692 · Cited by 72 · see citing works
Estimating Gene Expression and Codon-Specific Translational Efficiencies, Mutation Biases, and Selection Coefficients from Genomic Data Alone ‡
Gilchrist, M. A., Chen, W.-C., Shah, P., Landerer, C., & Zaretzki, R. (2015) · Genome Biology and Evolution · doi:10.1093/gbe/evv087 · Cited by 49 · see citing works
Bridging the gap between transcriptome and proteome measurements identifies post-translationally regulated genes
Gunawardana, Y., & Niranjan, M. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt537 · Cited by 46 · see citing works
Different types of secondary information in the genetic code
Maraia, R. J., & Iben, J. (2014) · RNA · doi:10.1261/rna.044115.113 · Cited by 30 · see citing works
The Impact of Selection at the Amino Acid Level on the Usage of Synonymous Codons
Błażej, P., Mackiewicz, D., Wnętrzak, M., & Mackiewicz, P. (2017) · G3 Genes Genomes Genetics · doi:10.1534/g3.116.038125 · Cited by 28 · see citing works
Quantifying codon usage in signal peptides: Gene expression and amino acid usage explain apparent selection for inefficient codons
Cope, A. L., Hettich, R. L., & Gilchrist, M. A. (2018) · Biochimica et Biophysica Acta (BBA) - Biomembranes · doi:10.1016/j.bbamem.2018.09.010 · Cited by 24 · see citing works
Selfing in Haploid Plants and Efficacy of Selection: Codon Usage Bias in the Model Moss Physcomitrella patens
Szövényi, P., Ullrich, K. K., Rensing, S. A., Lang, D., van Gessel, N., Stenoien, H. K., Conti, E., & Ralf Reski, A. (2017) · Genome Biology and Evolution · doi:10.1093/gbe/evx098 · Cited by 22 · see citing works
Quantifying shifts in natural selection on codon usage between protein regions: a population genetics approach
Cope, A. L., & Gilchrist, M. A. (2022) · BMC Genomics · doi:10.1186/s12864-022-08635-0 · Cited by 17 · see citing works
Gene expression of functionally-related genes coevolves across fungal species: detecting coevolution of gene expression using phylogenetic comparative methods
Cope, A. L., O’Meara, B. C., & Gilchrist, M. A. (2020) · BMC Genomics · doi:10.1186/s12864-020-6761-3 · Cited by 17 · see citing works
AnaCoDa: analyzing codon data with Bayesian mixture models
Landerer, C., Cope, A. L., Zaretzki, R., & Gilchrist, M. A. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty138 · Cited by 16 · see citing works
A codon model of nucleotide substitution with selection on synonymous codon usage
Kubatko, L. S., Shah, P., Herbei, R., & Gilchrist, M. A. (2014) · Molecular Phylogenetics and Evolution · doi:10.1016/j.ympev.2015.08.026 · Cited by 16 · see citing works
SENCA: A Multilayered Codon Model to Study the Origins and Dynamics of Codon Usage
Pouyet, F., Bailly‐Bechet, M., Mouchiroud, D., & Guéguen, L. (2016) · Genome Biology and Evolution · doi:10.1093/gbe/evw165 · Cited by 14 · see citing works
Intragenomic variation in non-adaptive nucleotide biases causes underestimation of selection on synonymous codon usage
Cope, A. L., & Shah, P. (2022) · PLoS Genetics · doi:10.1371/journal.pgen.1010256 · Cited by 12 · see citing works
Estimating a Structured Covariance Matrix From Multilab Measurements in High-Throughput Biology
Franks, A. M., Csárdi, G., Drummond, D. A., & Airoldi, E. M. (2014) · Journal of the American Statistical Association · doi:10.1080/01621459.2014.964404 · Cited by 11 · see citing works
Self-citation
Conservation of location of several specific inhibitory codon pairs in the Saccharomyces sensu stricto yeasts reveals translational selection
Ghoneim, D. H., Zhang, X., Brule, C. E., Mathews, D. H., & Grayhack, E. J. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky1262 · Cited by 12 · see citing works
Nucleotide composition affects codon usage toward the 3'-end
Zahdeh, F., & Carmel, L. (2019) · PLoS ONE · doi:10.1371/journal.pone.0225633 · Cited by 11 · see citing works
Variation in the fitness impact of translationally optimal codons among animalsPreprint
Bénitière, F., Tristan, L., & Duret, L. (2025) · Genome Research · doi:10.1101/gr.279837.124 · Cited by 11 · see citing works
Cubar: a versatile package for codon usage bias analysis in R
Liu, M., Zi, B., Zhang, H., & Zhang, H. (2025) · Genetics · doi:10.1093/genetics/iyaf191 · Cited by 10 · see citing works
Finding Genes in Genome Sequence
McHardy, A. C., & Kloetgen, A. (2016) · Methods in molecular biology · doi:10.1007/978-1-4939-6622-6_11 · Cited by 9 · see citing works
Unlocking a signal of introgression from codons in Lachancea kluyveri using a mutation-selection model
Landerer, C., O’Meara, B. C., Zaretzki, R., & Gilchrist, M. A. (2020) · BMC Evolutionary Biology · doi:10.1186/s12862-020-01649-w · Cited by 9 · see citing works
Massively parallel identification of sequence motifs triggering ribosome-associated mRNA quality control
Chen, K. Y., Park, H., & Subramaniam, A. R. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae285 · Cited by 6 · see citing works
Drift sometimes dominates selection, and vice versa: a reply to Clatterbuck, Sober and Lewontin
Brandon, R. N., & Fleming, L. (2014) · Biology & Philosophy · doi:10.1007/s10539-014-9437-z · Cited by 6 · see citing works
The role of APOBEC3-induced mutations in the differential evolution of monkeypox virus
Li, X., Habibipour, S., Chou, T., & Yang, O. O. (2023) · Virus Evolution · doi:10.1093/ve/vead058 · Cited by 6 · see citing works
The Evolution of Molecular Compatibility between Bacteriophage ΦX174 and its Host
Kula, A., Saelens, J. W., Cox, J., Schubert, A. M., Travisano, M., & Putonti, C. (2018) · Scientific Reports · doi:10.1038/s41598-018-25914-7 · Cited by 5 · see citing works
Accounting for biases in riboprofiling data indicates a major role for proline and not positive amino acids in stalling translationPreprint
Artieri, C. G., & Fraser, H. B. (2014) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/006221 · Cited by 5 · see citing works
De Novo Gene Emergence: Summary, Classification, and Challenges of Current Methods
Grandchamp, A., Aubel, M., Eicholt, L. A., Roginski, P., Luria, V. A., Karger, A., & Dohmen, E. (2025) · Genome Biology and Evolution · doi:10.1093/gbe/evaf197 · Cited by 7 · see citing works
Re-examining Correlations Between Synonymous Codon Usage and Protein Bond Angles in Escherichia coli
Akeju, O. J., & Cope, A. L. (2024) · Genome Biology and Evolution · doi:10.1093/gbe/evae080 · Cited by 3 · see citing works
Macroevolutionary changes in natural selection on codon usage reflect evolution of the tRNA pool across a budding yeast subphylum
Cope, A. L., & Shah, P. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2419889122 · Cited by 3 · see citing works
Growth-dependent Gene Expression Variation Influences the Strength of Codon Usage Biases
Johnson, M. M., Hockenberry, A. J., McGuffie, M. J., Vieira, L. C., & Wilke, C. O. (2023) · Molecular Biology and Evolution · doi:10.1093/molbev/msad189 · Cited by 3 · see citing works
Accounting for experimental noise reveals that mRNA levels, amplified by post-transcriptional processes, largely determine steady-state protein levels in yeast
Csárdi, G., Franks, A., Choi, D. S., Airoldi, E. M., & Drummond, D. A. (2014) · doi:10.1101/009472 · Cited by 8 · see citing works
Self-citation
Natural variation in codon bias and mRNA folding strength interact synergistically to modify protein expression in Saccharomyces cerevisiae
Wienecke, A., Barry, M. L., & Pollard, D. A. (2023) · Genetics · doi:10.1093/genetics/iyad113 · Cited by 1 · see citing works
Analysis of Mutation Bias in Shaping Codon Usage Bias and Its Association with Gene Expression Across Species
Lu, Z., Gilchrist, M. A., & Emrich, S. (2020) · EPiC series in computing · doi:10.29007/87r9 · Cited by 1 · see citing works
Genetic influences on translation in yeastPreprint
Albert, F. W., Muzzey, D., Weissman, J. S., & Kruglyak, L. (2014) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/003319 · Cited by 1 · see citing works
AnaCoDa: Analysis of Codon Data under Stationarity using a Bayesian Framework
Authors@R (2018) · doi:10.32614/cran.package.anacoda · Cited by 1 · see citing works
Measuring Selection Across HIV Gag: Combining Physico-Chemistry and Population GeneticsPreprint
Johnson, E., & Gilchrist, M. A. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/204297
Intragenomic variation in mutation biases causes underestimation of selection on synonymous codon usagePreprint
Cope, A. L., & Shah, P. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.10.29.466462
Re-examining supposed correlations between synonymous codon usage and protein bond angles in E. coliPreprint
Akeju, O. J., & Cope, A. L. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.10.26.513858
The Importance of Nonsense Errors: Estimating the Rate and Implications of Drop-Off Errors during Protein SynthesisPreprint
Cope, A. L., Pak, D., & Gilchrist, M. A. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.09.05.611510
Additional file 1 of Unlocking a signal of introgression from codons in Lachancea kluyveri using a mutation-selection model
Landerer, C., O’Meara, B. C., Zaretzki, R., & Gilchrist, M. A. (2020) · Figshare · doi:10.6084/m9.figshare.12864466
Additional file 1 of Quantifying shifts in natural selection on codon usage between protein regions: a population genetics approach
Cope, A. L., & Gilchrist, M. A. (2022) · Figshare · doi:10.6084/m9.figshare.19932972
The importance of nonsense errors: Estimating the rates and implications of ribosome drop-off during protein synthesis
Cope, A. L., Pak, D., & Gilchrist, M. A. (2026) · PLoS Genetics · doi:10.1371/journal.pgen.1012162

Estimating Gene Expression and Codon-Specific Translational Efficiencies, Mutation Biases, and Selection Coefficients from Genomic Data Alone ‡
Gilchrist, M. A., Chen, W.-C., Shah, P., Landerer, C., & Zaretzki, R. (2015) · Genome Biology and Evolution · doi:10.1093/gbe/evv087 · Cited by 49 · see citing works
Evolutionary principles underpinning codon usage bias: patterns, functions, and mechanismsPreprint
Cope, A., Shah, P., Shah, P., & Wallace, E. W. J. (2024) · doi:10.32942/x2802v · Cited by 1 · see citing works
Self-citation
Estimating Translational Selection in Eukaryotic Genomes
dos Reis, M., & Wernisch, L. (2008) · Molecular Biology and Evolution · doi:10.1093/molbev/msn272 · Cited by 112 · see citing works
Mutation-Selection Models of Codon Substitution and Their Use to Estimate Selective Strengths on Codon Usage
Yang, Z., & Nielsen, R. (2008) · Molecular Biology and Evolution · doi:10.1093/molbev/msm284 · Cited by 331 · see citing works
Estimating the evolutionary fitness of specific synonymous codon changes
Pavinato, V. A. C., & Hey, J. (2026) · Molecular Biology and Evolution · doi:10.1093/molbev/msag199

Authors: Wallace, E. W. J., Airoldi, E. M., & Drummond, D. A.
Affiliations: Harvard University (US)
Broad Institute (US)
University of Chicago (US)
Corresponding author: Wallace, Edward W.J.
ORCID: Wallace, Edward W.J.
Airoldi, Edoardo M.
Drummond, D. Allan
Venue: Molecular Biology and Evolution
Publisher: Oxford University Press (OUP)
Published: 2013-03-14
Volume: 30
Issue: 6
Pages: 1438-1453
ISSN: 0737-4038 (ISSN-L)
1537-1719
DOI: 10.1093/molbev/mst051
PMC: PMC3649678
OpenAlex: W2102206129
Cited by: 48
References: 66
Citations by year: 2026: 1 · 2025: 4 · 2024: 3 · 2023: 3 · 2022: 4 · 2021: 1 · 2020: 4 · 2019: 1 · 2018: 4 · 2017: 3 · 2016: 3 · 2015: 5 · 2014: 11 · 2013: 1
FWCI: 2.99
Type: journal article
Language: en
Open access: bronze
doi.org
Locations: Molecular Biology and Evolution (publishedVersion)
Europe PMC (PubMed Central) (publishedVersion)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
Funders: National Science Foundation (1017967)
Harvard University
National Institutes of Health (GM088344, GM068763)
FAS Center for Systems Biology, Harvard University
National Institute of General Medical Sciences (P50GM068763, R01GM096193, GM-068763, GM088344, R01GM088344)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Keywords: synonymous codon usage, selection coefficients, measurement noise, stochastic gene expression, mutation-selection balance, translational velocity, codon adaptation index, Saccharomyces cerevisiae, population genetic models, noisy experimental data
MeSH terms: Codon, Saccharomycetales, Models, Genetic, Mutation, Ribosomes, Selection, Genetic, Protein Biosynthesis, Gene Expression, Evolution, Molecular

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Estimating selection on synonymous codon usage from noisy experimental data

Abstract

Integrity signals

Claims the paper makes

Claims other papers make about this one

Self-check

Cites

Cited by

Related

Record

About these checks