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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Nat Rev Genet. Author manuscript; available in PMC Apr 12, 2011.
Published in final edited form as:
Published online Nov 23, 2010. doi:  10.1038/nrg2899
PMCID: PMC3074964
NIHMSID: NIHMS252477

Synonymous but not the same: the causes and consequences of codon bias

Abstract

Despite their name, synonymous mutations have significant consequences for cellular processes in all taxa. As a result, an understanding of codon bias is central to fields as diverse as molecular evolution and biotechnology. Although recent advances in sequencing and synthetic biology have helped resolve longstanding questions about codon bias, they have also uncovered striking patterns that suggest new hypotheses about protein synthesis. Ongoing work to quantify the dynamics of initiation and elongation is as important for understanding natural synonymous variation as it is for designing transgenes in applied contexts.

When the inherent redundancy of the genetic code was discovered, scientists were rightly puzzled by the role of synonymous mutations1. The central dogma of molecular biology suggests that synonymous mutations – those that do not alter the encoded amino acid – will have no effect on the resulting protein sequence and, therefore, no effect on cellular function, organismal fitness, or evolution. Nonetheless, in most sequenced genomes, synonymous codons are not used in equal frequencies. This phenomenon, termed codon usage bias (Figure 1), is now recognized as critical in shaping gene expression and cellular function, through its effects on diverse processes ranging from RNA processing to protein translation and protein folding. Naturally occurring codon biases are pervasive, and they can be extremely strong. Some species, such as Thermus thermophilus, avoid certain codons almost entirely. Synonymous mutations are important in applied settings as well – the use of particular codons can increase the expression of a transgene by over 1,000-fold2.

Figure 1
Codon bias within and between genomes

We already enjoy a broad array of often conflicting hypotheses for the mechanisms that induce codon usage biases in nature, and for their effects on protein synthesis and cellular fitness. Until recently we have been unable to systematically interrogate these hypotheses through large-scale experimentation. As a result, despite decades of interest and substantial progress in understanding codon usage biases, there is an over-abundance of plausible explanatory models whose relative, quantitative contributions are seldom compared.

Advances in synthetic biology, mass spectrometry, and sequencing now provide tools for systematically elucidating the molecular and cellular consequences of synonymous nucleotide variation. Such studies have refined our understanding of the relative roles of initiation, elongation, degradation, and mis-folding in determining expression levels of individual genes and the overall fitness of a cell. This information, in turn, is helping researchers to distinguish among the forces that shape naturally occurring patterns of codon usage. Researchers can also leverage high-throughput studies in applied settings that require controlled, heterologous gene expression -- to improve design principles for vaccine development and gene therapy, for example.

Here we review the causes, consequences, and practical utility of codon usage biases. Because we already benefit from several outstanding reviews on naturally occurring codon biases3-7, we focus here on those classical hypotheses that remain unresolved, as well as recent developments arising from high-throughput studies. We begin by summarizing the empirical patterns of codon usage observed across species, across genomes, and across individual genes. We describe the diverse array of mechanistic hypotheses for the causes of such variation, and the sequence signatures that support them. Against this backdrop of hypotheses and sequence analysis, we describe experimental work relating codon usage to endogenous gene expression and cellular fitness. From this, we turn to experimental studies on heterologous gene expression, and their implications both for understanding natural synonymous variation and for engineering novel constructs in applied settings.

Mechanistic hypotheses

Significant deviations from uniform codon choice have been observed in species from all taxa, including bacteria, archaea, yeast, flies, worms, and mammals. The overall codon usage in a genome can differ dramatically between species, although seldom between closely related species6.

Mutational versus selective hypotheses

Explanations for patterns of codon usage, within or between species, fall into two distinct categories associated with two independent forces in molecular evolution: mutation and natural selection3-5.

A mutational explanation posits that codon bias arises from the properties of underlying mutational processes – e.g. biases in nucleotides produced by point mutations8, contextual biases in the point mutation rates, or biases in repair. Mutational explanations are neutral, because they posit no fitness advantage or detriment associated with alternative synonymous codons. Mutational mechanisms are typically invoked to explain inter-specific variation in codon usage, especially among unicellular organisms.

Explanations involving natural selection posit that synonymous mutations somehow influence the fitness of an organism, and they can thus be promoted or repressed throughout evolution. Selective mechanisms are typically invoked to explain variation in codon usage across a genome or across a gene, although some inter-specific variation is also attributable to such mechanisms (see below).

Selective and neutral explanations for codon usage are not mutually exclusive, and both types of mechanisms surely play a role in patterning synonymous variation within and between genomes3, 5, 9. Below we discuss the patterns of codon usage that have been documented, at various levels of biological organization, in light of their mutational or selective causes.

Patterns of codon usage

Patterns across species

The strongest single determinant of codon usage variation across species is genomic GC content. In fact, differences in codon usage between bacterial species can be accurately predicted from the nucleotide content in their non-coding regions3, 10. Genomic GC content is itself typically determined by mutational processes acting genome-wide. As a result, most inter-specific variation in codon usage is attributed to mutational mechanisms3, 10, although the molecular causes of mutation biases are largely unknown10. Contrary to early expectations, the GC content of bacterial genomes or protein-coding genes is not correlated with optimal growth temperature (although, interestingly, structural RNAs show such a correlation)11.

In those species for which the point mutation rate depends strongly on the sequence context of a nucleotide – e.g. in mammals, which experience hypermutable CpG dinucleotides – the mutational model predicts a strong context-dependence of codon usage, which has indeed been observed12. Thus, at the genomic scale, neutral processes that do not discriminate among synonymous mutations remain plausible for explaining interspecific variation in codon usage among higher eukaryotes, and they are well accepted as the primary determinants of inter-specific variation in most other taxa (but see 13).

Aside from mutation biases, adaptation of codon usage to cellular tRNA abundances can also influence synonymous sequence variation across species (see below), since codon usage and tRNA regulation can co-evolve. Finally, some neutral processes responsible for codon bias across taxa are not mutational per se. Even in the absence of selection at synonymous sites, selection at non-synonymous sites can induce differences in nucleotide composition between coding and non-coding regions5, 14-16.

Patterns across a genome

There is often systematic variation in codon usage among the genes in a genome, usually attributed to selection. In organisms including Escherichia coli, Saccharomyes cerevisiae, Caenorhabditis elegans, Arabidopsis thaliana, Drosophila melanogaster and possibly mammals as well (see below), there is a significant positive correlation between a gene’s expression level and the degree of its codon bias, as well a negative correlation between expression level and the rate of synonymous substitutions between divergent species9, 17, 18 – features that are difficult to explain through mutation alone. Although mutational effects could possibly covary with expression levels, because transcription can be mutagenic19, 20, this effect is unlikely to account for the correlations between codon usage and expression levels observed in multiple species5, 19, 21.

The classic explanation for systematic variation across a genome is selectionist: codon bias is more extreme in highly expressed genes in order to match a skew in iso-accepting tRNAs and thereby provide a fitness advantage through increased translation efficiency or accuracy of protein synthesis9, 17, 22-27. There is strong evidence for this hypothesis in several species, mostly in the form of broad correspondences between the “preferred codons” used in highly expressed genes and measures of relative tRNA abundances28-32. As a result, translational selection remains the dominant explanation for systematic variation in codon usage among genes, despite the fact that supporting evidence is sometimes incomplete: direct measurements of tRNA abundances are rare in higher eukaryotes; the correspondence of tRNA abundance with tRNA copy number5 is weak in D. melanogaster and humans33; and 30% of bacterial species show no evidence of translational selection34

There are two possible directions of causality relating an endogenous gene’s expression level and the degree of its codon adaptation35 to tRNA abundances. Under one view2, 36, 37 high codon adaptation induces strong protein expression, because rapid and/or accurate elongation increases a given protein’s rate of synthesis; under the other view, strong expression selects for high codon adaptation, in order to avoid costs that scale with a gene’s expression level. In the biotechnology literature, the former interpretation is de rigueur whereas the latter interpretation prevails in the literature on molecular evolution3-5. The idea that high codon adaptation induces high protein levels per mRNA molecule does not square well with the notion that initiation is generally rate-limiting for endogenous protein production7, 9, 38, 39 (although it may apply to heterologous genes (see below)). When initiation is limiting, the elongation rate should not influence the amount of protein produced from a given message7, 9 (Figure 2). Moreover, from an evolutionary perspective, if high protein levels are desirable it would seem easier to tune a promoter for increased transcription than to select on hundreds of individual synonymous mutations each of which has only a marginal effect on the overall amount of protein synthesis. Conversely, the use of poorly adapted codons in order to slow the translation of genes expressed at low levels36 would seem wasteful compared to simply reducing transcription or slowing initiation.

Figure 2
Relationships between initiation rate, elongation rate, ribosome density, and rate of protein synthesis for endogenous genes

Although evolutionary studies generally agree that high expression selects for high codon adaptation in endogenous genes (as opposed to the converse), the precise nature of fitness gains associated with translationally adapted codons remains a topic of active debate (see Box 1, Selection for Accuracy or Efficiency). Furthermore, even though translational efficiency is energetically beneficial to the cell, efficient translation generally increases the amount of cell-to-cell variation in expression levels40, and this noise is typically deleterious41. Even though translational selection has received the most attention, systematic variation in codon usage across a genome can also be caused by neutral processes in certain species; these processes include horizontal gene transfer42, different nucleotide bias in leading and lagging strands of replication in bacteria43, and isochore structure in mammals (see Mammals Are Different, Box 2).

Box 1 Selection for accuracy or efficiency?

The nature of translational selection remains a topic of active debate. Codons adapted to tRNA pools might be preferentially used in highly expressed genes because such genes experience greater pressure for translational efficiency28, 29, 110, accuracy22-27, or both. Efficient elongation of a transcript might increase its protein yield2, 36, 37, 92, or it may provide a global benefit to the cell by increasing the number of ribosomes available to translate other messages even if it does not increase the yield of the transcript itself3, 7, 9, 55. Accurate elongation, by contrast, benefits the cell by reducing the costs of useless mistranslation products or the toxicity of harmful mistranslation products111. These two models can make different predictions for the fitness costs of maladaptive codons, as a function of transcript level.

There are several lines of sequence-based evidence that discriminate between the efficiency and accuracy hypotheses. Some of the most compelling evidence in favor of accuracy was introduced by Akashi23, 112, who found a greater tendency towards tRNA-adapted codons at residues that are strongly conserved across divergent Drosophila species – suggesting that sites under strong negative selection at the amino acid level also exhibit stronger codon adaptation, presumably to reduce mis-translation. The same finding was later extended to C. elegans113 and unicellular organisms25, 27. A separate line of evidence arises from the correlation between codon adaptation and gene length in E. coli24, reflecting a greater energetic cost of mis-sense and nonsense translation errors in a long protein, especially if they occur near the 3′ end. However, the relationship with gene length does not hold in C. elegans, D.melanogaster or A. thaliana21. Other evidence for the accuracy hypothesis comes from simulations of sequence evolution, protein translation, and protein folding26.

There is also convincing evidence in favor of translational efficiency, especially in prokaryotes. The most compelling observation is a broad correlation between the minimum generation time of a bacterial species and the strength of selection it experiences for codon adaptation in highly expressed genes34, 114. We would expect to see this correlation if preferred codons increase the elongation rate, which is beneficial for rapid growth, but it unclear why we would observe this correlation if preferred codons increase only the accuracy of elongation. Furthermore, Zhang and others have recently shown that codon usage in highly expressed yeast genes is consistent with selection to avoid unnecessary ribosomal sequestration of messages (Zhang et al., in preparation).

The accuracy and efficiency hypotheses are not mutually exclusive, in general. However, in a recent computational study, Shah and Gilchrist115 demonstrated that codons corresponding to more abundant tRNAs are not always expected to produce lower mis-sense error rates, as has been commonly assumed. Moreover, they found that for some amino acids, pressure for elongation speed would result in a different codon choice than pressure for elongation accuracy. Whether patterns of codon bias in evolutionary conserved residues22 occurs only for those amino acids for which efficiency and accuracy selection have the same predicted effect on codon choice remains unresolved and might help to distinguish between these two modes of selection.

Box 2 Mammals are different

Intra-genomic patterns of codon usage are markedly different in mammals than in other taxa. Selective mechanisms were initially ruled out for humans, on the basis of their small effective population size, which limits the efficacy of selection4. Moreover, the most obvious pattern of gene-to-gene codon usage variation in mammals arises not from selection but from large-scale variation in the GC content -- i.e. the isochores116. Isochores themselves are likely caused by processes primarily related to recombination and repair, such as biased gene conversion117.

Over the past decade, however, researchers have identified several sources of potentially strong selection on synonymous mutations in mammals – a trend that was highlighted by Hurst and others4. Some of these observations fit within the classical model of translational selection – e.g. the presence of a weak but positive relationship between gene expression and codon bias118, 119, especially after accounting for the local GC content120. But studies comparing expression levels to codon adaptation (that is, to tRNA abundances) have been contradictory33, 36, 119. Researchers have also observed significant differences in codon usage between genes specifically expressed in several different tissues121, as well as variation in relative tRNA abundances by tissue type122. But there is little evidence for systematic variation associated with tissue type123; and the quantification of mammalian tRNAs, which contain numerous nucleotide modifications, is still relatively noisy122.

Instead, researchers have identified other mechanistic explanations for codon usage variation in mammals, aside from translational selection. One possibility is selection for the overall stability of mRNA transcripts124, 125, via a skew towards C at fourfold degenerate sites. In mice, computational analyses suggest that such skews have been selected to promote mRNA stability124. Moreover, several diseases arise from mutations that disrupt mRNA structure4, 126, providing a clear target of selection. Another possibility, related to splicing control, is described in the main text.

Patterns across a gene

Codon usage can vary dramatically even within a single gene. Synonymous mutations at specific sites may experience selection because they disrupt motifs recognized by transcription factors or by post-transcriptional regulatory mechanisms – eg, micro-RNAs. Sites that require ribosomal pausing for proper co-translational protein folding or ubiquitin modification44 may experience selection for poorly adapted codons45 or strong mRNA folding 46. Codon choice that promotes proper nucleosome positioning is selectively advantageous in eukaryotes, especially in 5′ regions47. And finally, in mammals, synonymous mutations near an intron–exon boundary can create spurious splice sites or disrupt splicing-control elements4, 48, causing disease4. This phenomenon helps to explain the reduced rate of synonymous substitutions and SNP density near splicing control elements49, 50. Selection for proper splicing also extends to D. melanogaster, and sequence variation suggests it is probably an even stronger force than translational selection in shaping codon usage near intron–exon boundaries51

Although important, the mechanisms of intragenic codon usage variation described above are typically restricted to specific taxa or special classes of sites. Recent studies have argued for three mechanisms that produce systematic variation in codon usage across the sites in a gene, in a diverse range of species.

One of these mechanisms is selection against strong 5′ mRNA structure, in order to facilitate translation initiation. mRNA structure near the 5′ end of a coding region is generally disadvantageous9 as it can inhibit ribosomal initiation52, 53 (Figure 3A). Eyre-Walker and Bulmer proposed selection against mRNA structure to explain a trend towards reduced codon adaptation in the 5′ region of E. coli genes, and a corresponding reduced rate of synonymous substitutions across divergent species54. More recently, following similar observations in E. coli55, Gu et al. demonstrated a broad trend in all sequenced prokaryotes and eukaryotes towards reduced mRNA stability near the translationin-itiation sites of genes, especially for GC-rich genes56. This study relied on computational predictions of mRNA structure in short windows; combined with large-scale experimental studies (see below), this work suggests a systematic role for selection on mRNA structure in shaping codon usage in the first 30-60 nucleotides of genes.

Figure 3
Effects of mRNA secondary structure on translation initiation in Bacteria

Tuller et al.57 recently described a second, systematic trend in the pattern of intragenic codon usage: a ‘ramp’ of poorly adapted codons in the first 90-150 nucleotides of genes, which had earlier been observed in bacteria, yeast, and fly58, 59. This pattern has been preserved across divergent species even when tRNA pools (estimated from gene copy numbers) have changed57. A ramp of poorly adapted codons presumably slows elongation at the start of a gene, which may provide several physiological benefits. Slow 5′ elongation is predicted to reduce the frequency of ribosomal traffic jams towards the 3′ end57, 60, thus reducing the cost of wasted ribosomes and of spontaneous or collision-induced abortions. Alternatively, a ramp of slow elongation may facilitate recruitment of chaperone proteins to the emergent peptide61. Other explanations, unrelated to elongation rate, are also plausible -- such as weaker selection for accurate translation near the start of a gene, where mis-sense and non-sense errors would be less costly24, 59. The earliest interpretation of unusual 5′ codon usage posited selection to increase the initiation rate9 – and, interestingly, the 5′ region of poorly-adapted codons identified by Tuller et al. overlaps significantly with the region in which synonymous codon choice systematically reduces mRNA stability54-56, 58. It remains unclear which selective mechanisms are primarily responsible for the unusual and nearly universal pattern of 5′ codon usage. Multiple mechanisms may certainly operate in different genes; however, it is unclear why a single gene should experience selection both to increase its rate of ribosomal initiation9 and to reduce the subsequent rate of its early elongation57.

Cannarozzi et al.62 recently exposed a third, novel pattern of intra-genic codon usage in eukaryotes: the re-use or autocorrelation of codons across a gene sequence, driven, they argue, to improve elongation efficiency through tRNA recycling. If a recently used tRNA molecule is bound to the ribosome, or if it diffuses slowly compared to ribosomal progression and re-acytilation63, then it would be efficient to re-use the same tRNA molecule for subsequent incorporations of the same amino acid. This physical model predicts selection for using the same codon, or, more generally, a codon that is read by the same tRNA species, at nearby sites in a gene that encode the same amino acid. Indeed, Cannarozzi et al. observed significant autocorrelation of codons across gene sequences in most eukaryotes, especially in genes that are rapidly up-regulated in response to stress. Of course, autocorrelation would also be predicted if all sites in a gene independently experience pressure for biased codon usage – e.g. in order to match the global pool of tRNAs. To control for overall codon usage, Cannarozzi et al compared the degree of autocorrelation in actual gene sequences to gene sequences that had been re-shuffled at random, finding more autocorrelation on average in the un-shuffled genes, although only marginally so. More convincing, they observed that autocorrelation is strongest for isoaccepting codons of rare tRNAs in highly expressed genes – which is predicted by the tRNA recycling hypothesis but not by a selective pressure that applies at all sites independently.

Measurements of endogenous expression

Recent developments in mass spectrometry and fluorescence microscopy allow for large-scale measurements of endogenous protein levels64-66. Together with techniques for quantifying ribosomal occupancy67 and measuring elongation dynamics 68, these advances provide a spectacularly detailed accounting of basic cellular processes, with implications for our understanding of codon biases.

Variation in protein/mRNA ratios

Shotgun proteomics have revealed an extensive role for post-transcriptional processes in determining eventual protein levels in bacteria, yeast69, worm70, fly70, and especially mammals65, 66. Whereas the imperfect correlations between protein and mRNA levels (R2 ≈ 47%-77% in E. coli65, 71, 73% in yeast65, and 29% in humans66) may once have been seen as measurement noise, researchers have since attributed much of the variation in protein/mRNA ratios to sequence-derived characteristics of genes. In a recent study in human cells66, the strongest correlates of steady-state protein levels, controlling for mRNA levels, were coding-sequence length (reflecting that longer transcripts are less stable72 or slower to initiate73), amino acid content (reflecting variable costs associated with synthesizing different amino acids, or variable rates of protein degradation), and predicted 5′ mRNA structure (reflecting lower initiation rates when 5′ structure is strong). Importantly, the codon adaptation index35, which correlates strongly with mRNA levels in yeast65 and weakly in human66, shows little or no significant correlation with protein levels per mRNA molecule in either organism65, 66 – suggesting that codon adaptation does not significantly increase the protein yield from a given message, at least among endogenous genes74, 75. It is important to note that steady-state protein levels are influenced by both protein production and protein degradation; and so any variation in degradation rates unrelated to codon usage will further reduce the correlation between codon usage and protein/mRNA ratios.

Ribosomal footprints

Ingolia et al. recently devised a clever application of RNAseq to quantify ribosome-protected RNA fragments in a cell, thereby estimating ‘ribosomal footprints’ across the transcriptome67. This method has provided rich information about translational regulation, and it has uncovered some startling phenomena – such as an abundance of upstream open reading frames with non-AUG start codons. The footprint data in yeast show a greater mean density of ribosomes in the first 100-150 codons of genes, suggesting locally slow elongation; this is consistent with the observation of poorly adapted codons in the 5′ region58, 59. There is also significant negative correlation, genome-wide, between a transcript’s ribosome density and the experimentally measured strength of mRNA structure near its start site 76 – suggesting that strong 5′ mRNA structure retards initiation and reduces the density of translating ribosomes. Remarkably, upon averaging data from all yeast genes, Tuller et al.37 also observed a negative correlation between predicted mRNA folding energy and ribosome density among the first 65 codons – suggesting that strong mRNA structure downstream of start retards elongation. This observation is somewhat surprising, given the helicase activity of translating ribosomes77; however, the correlation between the genome-wide average profiles of mRNA folding and ribosome density does not imply a correlation at the level of individual sites. Ingolia et al. also measured ribosomal footprints under amino-acid starvation, finding one-third of yeast genes with either substantially increased or decreased translational efficiency67. A detailed parsing of the relationship between a gene’s amino-acid content and translational response to starvation may improve design principles for over-expressed heterologous genes, which often induce starvation78, 79 (see below).

Translational efficiency

Notions of translational efficiency differ in the literature on gene expression. Ingolia et al.67 defined the translational efficiency of a gene as the number of bound ribosomes per mRNA molecule; whereas Tuller et al.37, 57 and others defined efficiency as protein yield per mRNA molecule (i.e. the ratio of protein abundance to mRNA abundance). The latter definition is more relevant to issues of total protein synthesis, whereas the former definition may be more relevant to ribosomal availability and overall cellular fitness. These two notions of translational efficiency are only weakly correlated for endogenous genes (R2 < 2.5 % comparing the data by Ingolia et al.67 to ref. 80 – indicating that the density of ribosomes on a given mRNA molecule does not determine the amount of protein produced from it. Similarly, in yeast, a gene’s codon adaptation index35 explains less than 3% of the variance in protein abundances per mRNA67. Both of these observations are consistent with the idea that, for most endogenous genes, initiation is rate-limiting for protein production38, 39 and thus determines the amount of protein produced from each message, regardless of ribosome density or codon adaptation7, 9 (Figure 2); however, this logic may not apply to over-expressed heterologous genes, described below.

Measurements of heterologous expression

Codon bias plays a critical role in heterologous gene expression. However, there is often a disconnect between technological and evolutionary studies of codon bias – a gap that partly reflects genuine differences between endogenous and heterologous situations. In many biotechnological applications, a transgene is massively over-expressed, accounting for up to 30% of the protein mass in cell. As a result, the principles relating heterologous codon usage to protein levels may differ substantially from the endogenous case.

The notion that initiation generally limits translation may not apply to an overexpressed transgene whose mRNA accounts for a very large proportion of total cellular mRNA. In such a case, inefficient use of ribosomes along the over-expressed mRNA may be sufficient to feed back and significantly deplete available ribosomes, thereby reducing initiation rates and retarding further heterologous protein production9 (Figure 4). Thus, we might expect that elongation effects of codon usage will influence protein yields per mRNA molecule for over-expressed genes. Nonetheless, we should not necessarily expect that the codons adapted to efficient elongation for endogenous genes will correspond to the efficient codons for heterologous genes, because over-expression causes amino-acid starvation and concomitant alternations in the abundances of charged tRNAs78, 79, 81. Indeed, there was no significant correlation between codon adaptation35 and expression levels in two large-scale systematic experiments55, 79. In fact, even endogenous genes that are essential during amino-acid starvation, such as amino acid biosynthetic enzymes, preferentially use codons that are poorly adapted to the typical pool of charged tRNAs, but well adapted to starvation-induced tRNA pools78, 79.

Figure 4
The elongation rate may influence the rate of protein synthesis for an over-expressed gene

Despite the complications described above, the field of codon optimization has traditionally focused on adjusting codon usage to match cellular tRNA abundances in standard conditions, disregarding other dimensions of bias. However, strategies are now changing. Several recent studies advocate for the role of global nucleotide content82, 83, local mRNA folding55, 84, codon pair bias85, a codon ramp57, or codon correlations62 in optimizing heterologous expression (see Table 1).

Table 1
Coding-sequence covariates of gene expression, and other sources of codon bias unrelated to gene expression

Effects of codon adaptation on expression levels

Many studies show strong effects of rare codons on heterologous expression. In E. coli, stretches of rare AGA or AGG codons cause ribosome pausing and co-translational cleavage of mRNA86, ribosomal frameshifting87, or amino-acid mis-incorporation88. Consistent with theoretical expectations, codons read by rare tRNAs can slow elongation several-fold89. And stretches of AGG codons near the ribosome binding site can reduce protein yields by obstructing translation initiation90. Even though such studies are convincing, they usually address the effect of a subset of very rare codons, often in long stretches, in E. coli cells; it is not known how generally these principles apply.

Observations such as the ones above were quickly followed by efforts to adjust the global codon adaptation of transgenes to cellular tRNA abundances. Several approaches have been proposed: ‘CAI maximization’ replaces all codons by the most preferred codons in the target genome, but this could result in unbalanced charged tRNA pools2; ‘codon harmonization’91 puts some nonpreferred codons in positions corresponding to predicted protein domain boundaries; ‘codon sampling’ adjusts the codon usage to reflect the overall usage in the target genome. In the absence of tRNA abundance estimates, codon frequencies in the target genome are sometimes used. It has also been suggested that codon usage should match the profile of charged tRNAs rather than total tRNAs79, 81. The utility of codon adaptation approaches is still unclear, as they have not been systematically compared against each other, and a number of anecdotal studies argue both for (eg. Ref 92) and against (eg Ref 93) their efficiency.

Codon adaptation algorithms typically optimize many sequence properties at once. This makes it difficult to determine which parameter causes observed differences in expression. In two recent multi-gene studies, between 60% and 70% of genes experienced increased expression upon codon optimization94, 95 but whether this was a direct consequence of increased codon adaptation or other sequence properties is unclear. In our study of 154 synonymous variants of GFP, we observed no significant correlation between the codon adaption index35 and expression levels in E. coli55, but a weak positive correlation was later found using non-linear regressions37, 96. In any case, adaptation of codon usage is limited to species with pronounced and well-understood variation in tRNA concentrations, such as bacteria and yeast.

Effects of nucleotide bias on expression levels

Nucleotide biases are pervasive in natural genes and have the potential to alter the interactions of mRNA with DNA, with proteins, and with itself -- thereby influencing RNA production, degradation, and translation rates. Many of these effects are characterized, but this knowledge has yet to find its way into standard codon optimization procedures.

GC-rich mRNAs can form strong secondary structures, and, in bacteria, strong structure near the ribosome binding site prohibits initiation53, 55, 97 (Figure 3B). As a result, more than 40% of human genes would be expected to express poorly when placed in E. coli without modification (Figure 3C). Strong structure near the start codon reduces heterologous expression in yeast as well (G. Kudla, personal communication), consistent with evolutionary analyses56. No such effect has been described in mammals; on the contrary, high GC content generally increases expression levels in mammalian cells (see below). However, a strong mRNA hairpin away from the ribosome binding site (RBS) has been reported to interfere with translation in mammalian cells84 and strong hybrids between RNA and DNA (the R-loops) may interfere with transcription98.

GC-poor mRNAs are unlikely to fold strongly, but they often harbor other sequence elements that limit expression. For example, low GC content is commonly believed to limit the expression of Plasmodium falciparum genes in E. coli, even though the mechanisms are unknown. Such mRNAs may be targets for RNAse E, which cleaves AU-rich sequences with low sequence specificity99. The situation is slightly clearer in mammals, where low GC content (or high A content) has been shown to reduce expression82, 83. This effect is common knowledge in virology, since HIV and HPV genes are very poorly expressed in human cells unless optimized100, 101. The rate-limiting step in these cases may be transcription or nuclear RNA export82, 83, consistent with the efficient expression of GCpoor genes in cytoplasmic transcription systems based on the vaccinia virus101.

Little is known about the functional consequences of replication-strand-related bias or CTAG avoidance that are common in prokaryotes. High CpG content was reported to correlate with high expression in mammalian cells102, possibly by altering the distribution of nucleosomes on DNA.

Other effects of synonymous mutations on expression levels

Other examples of synonymous mutations influencing expression have been described as primarily anecdotal observations. In E. coli, over-represented codon pairs103 were proposed to decrease translation elongation rates104, although this conclusion was later disputed105. In an attempt to produce attenuated strains, Coleman et al.85 partially de-optimized codon pairs in the poliovirus genome and observed several-fold reduction in protein yield in mammalian cells, as well as a thousand-fold reduction in viral infectivity. A version of GFP with auto-correlated codon usage exhibited 30% lower ribosome density in yeast, suggesting faster elongation, than a version with anti-correlated codon usage62. And a synonymous mutation in the human MDR1 gene was proposed to influence mRNA stability106 or protein folding and substrate specificity107. These observations are all intriguing, and they form important avenues for future systematic studies to determine their molecular basis.

Conclusions

Recent years have begun to see a convergence of experimental work on endogenous and heterologous gene expression, as both types of studies take advantage of high-throughput, quantitative techniques. Heterologous studies based on large libraries of random or unbiased synonymous sequence variation55, 81, 97 are especially important for uncovering and comparing general rules to optimize expression. By contrast, relatively small-scale studies based on pre-conceived notions of “optimized” codon usage do not provide sufficient power to distinguish among alternative mechanisms, nor do they allow us to discover any new mechanisms that increase expression. Heterologous studies will be complemented by endogenous measurements of initiation and elongation dynamics, and their effects on protein synthesis as a function of a gene’s amino acid content and transcript level.

In the short-term, there will be a tradeoff between gaining predictive power for transgene optimization and deducing the underlying mechanisms that link codon usage and gene expression. High-dimensional, statistical regressions applied to large libraries of synonymous genes81, 96 provide a principled, effective means of increasing heterologous expression. Such techniques are increasingly valuable in applied contexts where high expression is required – such as viral-delivered gene therapies108, 109 – but they do not generally identify molecular mechanisms. Our hope, over the long-term, is that cross-fertilization between biotechnological and molecular biological studies will elucidate effective strategies for designing transgenes, as well as the mechanistic principles that underlie their expression.

Online Summary

  • Codon usage varies widely between species, between genes in a genome, and between sites in a gene.
  • Explanations for natural variation in codon usage fall into two categories: mutational and selective.
  • Mutational mechanisms are responsible for most codon usage variation between species; whereas selection for translation efficiency accounts for much of the systematic variation across a genome (except in mammals).
  • Translationally efficient codons may increase elongation rate, accuracy, or both.
  • Rapid elongation should not be expected to influence protein yield per mRNA molecule for an endogenous gene, but it may be relevant for an over-expressed transgene.
  • The codons that provide efficient translation of an over-expressed transgene may differ from the efficient codons for an endogenous gene.
  • High-throughput measurements of endogenous mRNA levels, protein levels, and ribosomal occupancies provide a detailed description of translation processes.
  • Libraries of randomized genes can elucidate design principles for efficient transgene expression, even without uncovering underlying mechanisms.

Acknowledgements

We thank Laurence Hurst for helpful discussions. We apologize to those whose work we were unable to cite because of space constraints. G.K. acknowledges funding from the Wellcome Trust. J.B.P. acknowledges support from the Burroughs Wellcome Fund, the David and Lucile Packard Foundation, the James S. McDonnell Foundation, the Alfred P. Sloan Foundation, the Defense Advanced Research Projects Agency (HR0011-05-1-0057), and the US National Institute of Allergy and Infectious Diseases (2U54AI057168).

Glossary

effective population sizeNumber of individuals in a population who
produce viable offspring.
biased gene conversionRecombination event in which one variant
of genomic sequence is preferentially
“copied/pasted” onto another one.
fourfold degenerate sitesPositions within the coding sequence of
a gene at which all four nucleotides
encode the same amino acid.
codon adaptation indexMeasure of similarity between the codon
usage of a gene and the average codon
usage of highly expressed genes in a
species.
iso-accepting tRNAsSubset of tRNAs that carry the same amino
acid.
horizontal gene transferTransfer of genetic material from one
species into another.
isochoreLarge fragment of a chromosome
characterized by homogeneous GC
content.
negative selectionA form of natural selection that
suppresses alternative genetic variants
in favor of the wildtype.
ribosomal pausingA temporary arrest of the ribosome
during translation elongation.
shotgun proteomicsMethods of quantifying protein levels in
a complex sample, typically using mass
spectrometry.
RNAseqQuantitative analysis of RNA in a
complex sample by high-throughput
sequencing.
upstream open reading framesOpen reading frames located 5′ from the
primary open reading frame; considered
to inhibit translation of the primary ORF.
ribosomal footprintsFragments of mRNA that were protected
by ribosomes from nuclease digestion in
a ribosomal profiling experiment.

Footnotes

Reference highlights (eleven)

Andersson and Kurland 1990

A classic paper that has framed the field of codon usage adaptation. A must-read.

de Smit and van Duin 1990

A very thorough study of how mRNA folding affects translation initiation, supported by a convincing theoretical model.

Akashi 1994

By quantifying rates of synonymous substitutions at conserved and non-conserved positions in proteins, Akashi shows that such mutations influence translational accuracy in Drosophila.

Bulmer 1991

A foundational study of both the population genetics underlying codon bias and the biophysics of translation. Emphasizes that elongation speed will not generally influence protein yield per mRNA, for endogenous genes.

Lu et al. Nature Biotechnology 2006

A quantitative proteomics approach that promises new insights into coding-sequence determinants of protein levels. See also Vogel et al. Mol. Sys. Biol. (2010)

Ingolia et al. Science 2009

A clever method to map the positions of ribosomes on messages with unprecedented accuracy; an essential tool for the study of translation kinetics.

Elf et al. Science 2003

A detailed theoretical model of what happens to tRNA when cells go hungry.

Chamary, J.V. et al Nat Rev Genet 2006

An excellent review of the many surprisingly strong effects of synonymous mutations on splicing.

Drummond & Wilke. Nat Rev Genet 2009

The various types of errors in protein synthesis, many of them directly related to codon usage, are summarized in this very readable review.

Tuller et al. Cell 2010

Rare codons at the beginning of genes could help prevent “ribosomal traffic jams”. See also Bulmer (1988), Qin et al. (2004).

Kudla et al. 2009

Libraries of synthetic genes isolate the effects of synonymous mutations on gene expression. See also Welch et al. (2009), Voges et al. (2004).

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