Control of translation efficiency in yeast
by codon–anticodon interactions
DANIEL P. LETZRING, KIMBERLY M. DEAN, and ELIZABETH J. GRAYHACK
Department of Biochemistry and Biophysics, University of Rochester Medical School, Rochester, New York 14642, USA
The choice of synonymous codons used to encode a polypeptide contributes to substantial differences in translation efficiency
between genes. However, both the magnitude and the mechanisms of codon-mediated effects are unknown, as neither the
effects of individual codons nor the parameters that modulate codon-mediated regulation are understood, particularly in
eukaryotes. To explore this problem in Saccharomyces cerevisiae, we performed the first systematic analysis of codon effects on
expression. We find that the arginine codon CGA is strongly inhibitory, resulting in progressively and sharply reduced
expression with increased CGA codon dosage. CGA-mediated inhibition of expression is primarily due to wobble decoding of
CGA, since it is nearly completely suppressed by coexpression of an exact match anticodon-mutated tRNAArg(UCG), and is
associated with generation of a smaller RNA fragment, likely due to endonucleolytic cleavage at a stalled ribosome. Moreover,
CGA codon pairs are more effective inhibitors of expression than individual CGA codons. These results directly implicate decoding
by the ribosome and interactions at neighboring sites within the ribosome as mediators of codon-specific translation efficiency.
Keywords: yeast; translation; genetic code; ribosome; codons; tRNA
Differences in translation efficiency contribute substantially
to the large variation in protein expression, with translation
of individual mRNAs ranging over at least three orders of
magnitude in the yeast Saccharomyces cerevisiae (Arava et al.
2003; de Godoy et al. 2008; Ingolia et al. 2009). While
differential translation efficiency is the result of many fac-
tors, substantial evidence from both bacteria and eukary-
otes indicates that the amount of polypeptide produced per
mRNA is influenced by the particular choice of synonymous
codons, codons that specify insertion of the same amino acid
(Ghaemmaghami et al. 2003; Brockmann et al. 2007).
In organisms such as Escherichia coli, S. cerevisiae,
Caenorhabditis elegans, and Drosophila melanogaster, a sub-
set of synonymous codons, generally those decoded by the
most abundant tRNAs without wobble decoding (Ikemura
1982), are ‘‘preferred codons’’ for efficient translation and
are used more frequently than their synonyms (dos Reis
et al. 2004; Parmley and Hurst 2007). Preferred codons are
used nearly exclusively in many highly expressed genes,
sharply differentiating these genes from the majority of
other genes (Grantham et al. 1980; Bennetzen and Hall
1982; Duret and Mouchiroud 1999). Indeed, codon usage
and protein abundance correlate genome-wide in S. cer-
evisiae and E. coli (Ghaemmaghami et al. 2003; Tuller et al.
2007; Ishihama et al. 2008; Tuller et al. 2010b). Remarkably,
despite changes in the actual identity of the preferred
codons, the selection for preferred codons in many gene
families is maintained across species (Man and Pilpel 2007).
In addition, expression of genes in E. coli and in S. cerevisiae
is frequently improved by recoding genes with preferred
codons (Gustafsson et al. 2004; Burgess-Brown et al. 2008;
Keppler-Ross et al. 2008; Quartley et al. 2009; Welch et al.
2009), or by overproducing rare tRNAs in E. coli (Burgess-
Brown et al. 2008).
Nonetheless, the degree to which codons affect expres-
sion in E. coli has been the topic of some debate, with two
recent papers arriving at very different conclusions about
the quantitative importance of codon effects. Kudla et al.
(2009) concluded that codon bias had little significant
effect on protein levels of GFP variants, while Welch et al.
(2009) found that variation in expression of two genes was
strongly correlated with codon biases for 10 amino acids.
However, it is likely that the coupling between transcription
and translation complicates the analysis of codon effects in
bacteria, since some codon changes are known to cause
premature rho-mediated transcription termination (Deana
Reprint requests to: Elizabeth J. Grayhack, Department of Biochemistry
and Biophysics, University of Rochester School of Medicine and Den-
tistry, 601 Elmwood Ave., Rochester, NY 14642, USA; e-mail: elizabeth_
email@example.com; fax: (585) 272-2766.
Article published online ahead of print. Article and publication date are
RNA (2010), 16:2516–2528. Published by Cold Spring Harbor Laboratory Press. Copyright ? 2010 RNA Society.
et al. 1998). This difference in the molecular basis for codon
effects between bacteria and eukaryotes is an argument to
examine the role of codon usage in a eukaryote.
Assessing the contribution of codons to gene expression
in eukaryotes still has at least two difficulties. First, syn-
onymous codon choice influences several aspects of trans-
lation, including the accuracy of amino acid insertion
(Kramer and Farabaugh 2007), reading frame maintenance
(Farabaugh et al. 2006), and folding of the nascent poly-
peptide (Kimchi-Sarfaty et al. 2007), each of which may
differentially affect the stability or activity of the resulting
protein. Second, synonymous codon choice affects the
mRNA sequence, thereby affecting mRNA structure, which
itself directly affects translation (Kudla et al. 2009). The
mRNA sequence also influences the binding of proteins
and RNAs that regulate splicing, decay, and translation effi-
ciency (Doma and Parker 2006; Isken and Maquat 2007).
Although the preferred codons are well characterized,
neither the identity nor the properties of codons or codon
combinations that cause reduced expression in eukaryotes
are known. Codons that impair expression in yeast are
difficult to decipher because the 37 unpreferred codons
have different properties, with some decoded by rare
tRNAs, others requiring wobble decoding, and still others
are simply underused. Moreover, it remains controversial
whether the mediator of reduced expression is individual
codons, adjacent codons (codon pairs), or clusters of rare
codons (Smith and Yarus 1989; Irwin et al. 1995; Kane
1995; Moura et al. 2005; Buchan et al. 2006; Coleman et al.
2008). Knowledge of the identity and properties of codon-
initiated inhibitory signals is required to understand the
underlying mechanisms for this regulation.
Here we describe the first systematic study of codon
effects on expression. We assessed the effect of each of 59
codons in the yeast S. cerevisiae by monitoring firefly lucif-
erase activity of constructs with repeats of individual codons.
We identify the Arg codon CGA as strongly inhibitory, an
effect due almost entirely to IdA wobble decoding of the
CGA codon. We find that CGA codons give rise to a stable
mRNA fragment containing sequences downstream from
the CGA codons, from which we infer that these codons
likely cause arrest of the ribosome. Moreover, we find that
adjacent CGA codons are much more potent inhibitors of
expression than separated CGA codons. Thus, we conclude
that translation efficiency is directly modulated by decod-
ing interactions within the ribosome.
In a systematic analysis, most codons exert only slight
effects on expression
To assay the effects of sequences containing codon repeats,
we inserted them into common flanking sequences, either
near the N-terminus at amino acid 4 of the firefly luciferase
gene (Grentzmann et al. 1998; Keeling et al. 2004) (referred
to as X4F), or at amino acid 314 between the fused Renilla
and firefly luciferase genes (RX314F) (Fig. 1A). We examined
FIGURE 1. Systematic screen of the effects of synonymous codon repeats on firefly luciferase expression. (A) Schematic of reporter constructs
used in these studies: Codon repeats (X) were inserted upstream of a firefly luciferase reporter gene either at position 4 of the coding region (X4F),
at position 314 in the Renilla-firefly fusion construct (RX314F) or at position 4 of the coding region of Renilla luciferase (X4R) or superfolder GFP
(X4G) (Pedelacq et al. 2006). X4F and RX314F were used for a systematic screen of the effects of 59 codons on expression. (B) Inhibitory effects
of several codon repeats, but not CGA repeats, in X4F are likely due to formation of strong RNA secondary structures. Luciferase activity for each
10-mer codon repeat at the N-terminus (%C) is plotted as a function of the free energy of the predicted RNA secondary structure from 1 to 50.
Free energy of folding (nucleotides 1–50 of X4F-reporter constructs containing 10 repeats of a particular codon for 59 of the 61 sense codons)
(kcal/mol) was calculated using RNAstructure (Mathews et al. 1999) version 4.6 (http://rna.urmc.rochester.edu/RNAstructure.html). Similar
results were obtained from calculations of free energy of folding from ?4 to +37.
Decoding interactions impair translation
reaction, 20 mL 1X Stop and Glo (Promega) was added, and
activity was measured as described above. In the systematic anal-
ysis of codon effects, activity was measured from three indepen-
dent transformants, and three readings were performed on each
lysate. Error bars reflect the standard deviation between three
Protein expression and RNA analysis
Yeast transformants, in which Renilla and firefly luciferase genes
were under control of the GAL1,10 promoter, were grown as
described (Quartley et al. 2009) except that strains were grown
overnight in raffinose to an OD600 between 1.8 and 2.4, and
expression was induced by addition of 3X YP media with 6%
galactose (1/3 final volume), followed by growth for 6 h. Crude
extract preparation and Western blot analysis were performed as
described (Quartley et al. 2009). Membranes were incubated
either with mouse anti-RGS-(His)6 (1:2500 dilution) or with
rabbit anti-enolase (1:25,000 dilution), followed by washing as
described previously, and incubation with either HRP-conjugated
Goat IgG anti-mouse (1:10,000 dilution, BioRad) for anti-RGS-
(His)6or HRP-conjugated Goat IgG anti-rabbit (1:10,000 dilu-
tion, Biorad) for anti-enolase, and development with ECL Plus
Western blotting detection system (GE Healthcare RPN2132).
RNA for RT-PCR was prepared from 50 OD-mL cells as
described (Schmitt et al. 1990). RNA (5 mg) was treated with
1.25 U RNase free RQ DNase I (Promega M6101), followed by
cDNA synthesis from DNase-treated RNA (0.3 mg) using Moloney
murine leukemia virus reverse transcriptase (Invitrogen); the
resulting cDNA was amplified by PCR using primers DLO527,
DLO528, DLO531, and DLO532 (Supplemental Table S3).
Expression of green fluorescent protein in yeast strains bearing
an integrated copy of pEKD1163, pEKD1170, or pEKD1167 was
assessed after growth in YP + adenine + 2% galactose + 2%
raffinose. Cells were washed in cold ddH2O, collected by centri-
fugation, resuspended in 1X PBS, and subjected to analysis on
the FACSCantoII with excitation at 488 nM and detection of
fluorescence emission using a 530/30 band pass filter.
For analysis by Northern blots, yeast transformants (150 OD-
mL), grown as described above, were resuspended in 3 mL RNA
isobuffer (0.5 M NaCl, 0.2 M Tris-Cl, pH 7.5, 0.01 M EDTA, 1%
SDS) followed by addition of 3 mL phenol-chloroform-isoamyl
alcohol (PCA) (25:24:1), equilibrated at pH 7.5, and glass beads,
and lysed by vortexing 10 times for 20 sec with 1 min on ice
between cycles. Additional RNA isobuffer (4.5 mL) and PCA
(4.5 mL) were added, and lysates were centrifugated; the aqueous
phase was re-extracted with 4.5mL PCA, nucleic acids were pre-
cipitated with ethanol, and the pellet was resuspended in TE,
pH 7.5, and stored at ?80°C. Total RNA (20 mg) was separated
by electrophoresis either in a 1.5% formaldehyde agarose gel
(Sambrook et al. 1989) or in a 6% polyacrylamide gel (19:1)
containing 7 M urea, transferred to Genescreen plus membrane,
and UV crosslinked to the membrane at 254 nm for 2 min. mRNA
was visualized by synthetic oligonucleotide probes DLO511,
DLO531, and SHO21 (Supplemental Table S3) labeled at the
59 end with
32P using T4 polynucleotide kinase (Roche).
Supplemental material can be found at http://www.rnajournal.org.
We thank Eric Phizicky, Stan Fields, Gloria Culver, Roy Parker,
and Mark Dumont for advice during the course of the work and
for comments on the manuscript, and Joe Whipple and E.P. for
the integrating vector. This work was supported by NSF grant no.
MCB-0919658 awarded to E.J.G.
Received August 12, 2010; accepted September 24, 2010.
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RNA, Vol. 16, No. 12