- Open Access
Gene Designer: a synthetic biology tool for constructing artificial DNA segments
© Villalobos et al; licensee BioMed Central Ltd. 2006
- Received: 24 January 2006
- Accepted: 06 June 2006
- Published: 06 June 2006
Direct synthesis of genes is rapidly becoming the most efficient way to make functional genetic constructs and enables applications such as codon optimization, RNAi resistant genes and protein engineering. Here we introduce a software tool that drastically facilitates the design of synthetic genes.
Gene Designer is a stand-alone software for fast and easy design of synthetic DNA segments. Users can easily add, edit and combine genetic elements such as promoters, open reading frames and tags through an intuitive drag-and-drop graphic interface and a hierarchical DNA/Protein object map. Using advanced optimization algorithms, open reading frames within the DNA construct can readily be codon optimized for protein expression in any host organism. Gene Designer also includes features such as a real-time sliding calculator of oligonucleotide annealing temperatures, sequencing primer generator, tools for avoidance or inclusion of restriction sites, and options to maximize or minimize sequence identity to a reference.
Gene Designer is an expandable Synthetic Biology workbench suitable for molecular biologists interested in the de novo creation of genetic constructs.
- Codon Usage
- Synthetic Biology
- Gene Designer
- Codon Optimization
DNA, like any other form of information, can be both written and read. For DNA, reading is done by DNA sequencing and writing by gene synthesis. Most of molecular biology over the last decade has focused on reading and analyzing naturally occurring DNA sequences as revealed by massive worldwide sequencing efforts. In contrast, the emerging field of Synthetic Biology aims to write new genetic information, thereby creating designed non-natural genes, proteins, biological processes and organisms. Gene synthesis was conceived as a means of gene acquisition in the 1970s and early 1980s[2, 3], but was soon overtaken by cloning from libraries and later by PCR. More recently, protein and DNA sequences have become easier to obtain electronically through databases than physically from library clones. At the same time gene synthesis technology has matured. Direct synthesis of genes is rapidly becoming the most efficient way to make functional genetic constructs and enables applications such as codon optimization, making RNAi resistant genes and protein engineering.
Synthetic Biology is the convergence of molecular biology and engineering principles that is underpinned by increasingly efficient technologies for creating full length genes, operons and even genomes denovo [7–9]. Codon optimization for heterologous protein expression has been shown to often drastically increase protein expression levels. Central to such efforts is the ability to design the genetic constructs as easily as possible while considering multiple design parameters in parallel. For example, considerations such as codon bias use in the desired expression system, avoidance of mRNA secondary structures, degree of sequence identity to homologs and the presence or absence of specific restriction sites or motifs must all be considered simultaneously.
Public codon optimization softwares.
CUT, RE, DO
CUT, RE, DO
CUT, RE, mSeq, Rep
Precursor to Gene Designer
CUT, RE, mSeq, DO
Synthetic Gene Designer
CUT, RE, DO
Input and manipulation of data
Gene Designer is easy and intuitive to learn. It has a graphically rich molecular viewer for displaying and manipulating genetic constructs using simple drag-and-drop manipulations, coupled with a hierarchical data structure for storing, managing and accessing sequence objects. Gene Designer is a stand-alone secure software that provides an efficient integrated solution for gene design projects.
New sequence objects in Gene Designer can be entered as AA (amino acid sequence), DNA (nucleotide sequence object) or ORF (amino acid sequence linked to a nucleotide sequence). Each object can be imported directly in FASTA format or manually imported by cut-and-paste into a data entry window. Once loaded, each object can be displayed in icon, sequence or notes (annotation) view.
A set of commonly used genetic objects are provided in a tree structured Design Toolbox. The list includes prokaryotic and eukaryotic transcriptional and translational regulatory elements, purification and solubility tags, protease cleavage sites, secretion signals, restriction sites and recombinase cloning elements. The toolbox is not a complete and final list of genetic elements, but rather a convenient starting point for each user to assemble their own custom set of genetic objects. The software is built to enable the user to add and edit new custom objects and make notes associated with each object. These objects can be saved in the toolbox and can be shared between users. For detailed and up to date information of each existing building block, or to create new building blocks, we recommend the user searching NCBI databases and the World Wide Web.
The Icon View provides an immediate overview of the entire design project. Each genetic object is shown as a differently colored arrow indicating the orientation of the object. Objects can be moved in this view by drag-and-drop. This is particularly convenient when moving affinity tags from the N to the C-terminal of a protein, creating chimeric proteins and editing restriction sites at ends of a construct.
The Sequence View provides a detailed display of the nucleotide and/or amino acid sequences of each object below a single nucleic acid sequence corresponding to the entire construct. For AA objects, each amino acid (single letter code) is shown immediately above its corresponding codons. Codons are shown in descending order of their frequency in the corresponding codon usage table.
The Notes View provides a convenient way for the user to annotate the sequence elements for future reference. There is also a feature in the Notes View for reports on the entire project.
The genetic code uses 64 nucleotide triplets (codons) to encode 20 amino acids and stop. Each amino acid is encoded by on average 3 codons that are read during translation by tRNAs charged with the cognate amino acid. The degeneracy of the genetic code enables many alternative nucleotide sequences to encode the same protein. The frequencies with which different codons are used by different organisms and different types of genes vary significantly and are correlated to the concentration of the corresponding tRNA population in the cell. Rare codons are not only strongly associated with low levels of protein expression due to ribosome stalling and abortive translation, but also implicated in frameshift and amino acid misincorporation[14, 15]. Codon usage has been identified as the single most important factor in prokaryotic gene expression.
The simplest way to design a DNA sequence from an amino acid sequence is to assign the most abundant codon to all instances of that amino acid in the sequence. Codon usage preference in a gene is often measured by Codon Adaptation Index (CAI score). The CAI score for such a construct is 1.0, i.e. in each case only the most abundant codon is used. This 'one amino acid – one codon' or 'CAI = 1.0' approach has several drawbacks. First, a strongly transcribed mRNA from such a gene will generate high codon concentrations for a subset of the tRNA populations, resulting in imbalanced tRNA pool, skewed codon usage pattern and increased translational error. Heterologously expressed proteins may be produced at levels as high as 60% of total cell mass, making an imbalance tRNA pool a significant problem resulting in reduced growth due to tRNA depletion and increased frameshift due to translational pausing at the ribosomal A-site. Second, with no flexibility in codon selection, it is impossible to avoid repetitive elements and mRNA secondary structures in the gene. Severe repetitive elements can affect the genetic stability of a gene and may lead to excision through recombination. Third, it is often desirable to incorporate or exclude sequence elements such as restriction sites from the sequence to facilitate subsequent manipulations. These modifications are impossible to accommodate if the codon usage is rigidly fixed. Fourth, in the literature there are many and sometimes conflicting data suggesting sequence elements that decrease protein expression levels. Such elements can not be avoided if the codon usage is fixed. Gene Designer users who wish to use the CAI = 1 optimization approach can either increase the threshold for codons used or use a modified codon usage table.
In contrast to the 'CAI = 1.0' method, Gene Designer optimizes genes for expression by using a codon usage table in which each codon is given a probability score based on the frequency distribution of the codons in the genome normalized for every amino acid. The codon usage tables for 25 common protein expression hosts are included with the download, and new codon usage tables can be imported from the Codon Usage Database http://www.kazusa.or.jp/codon or manually edited as required. The codon usage table created by one user is automatically imported when another user shares the project. For E. coli expression we recommend the user to use the EColi_CII table that is derived from a collection of highly expressed E. coli genes. Candidate sequences are generated in silico using a Monte Carlo algorithm by selecting codons based on the probabilities obtained from the codon usage table, with codons below the threshold value (default is 10%) excluded from consideration. Each designed sequence is then passed through subsequent iterations to ensure a match with additional design criteria such as filtering out mRNA secondary structures and DNA repeats, eliminating or incorporating restriction sites and avoiding methylation sites that overlap methylation sensitive restriction sites. A pseudo code for the algorithm in Gene Designer can be found in appendix A.
Motifs such as internal Shine-Dalgarno sequences have been shown to decrease gene expression. Gene Designer allows the user to filter out Shine-Dalgarno sequences, splice donor and acceptor sequences as well as any other sequence motif defined by the user. The user can also maximize or minimize the similarity of the designed sequence to a reference sequence, for example to make RNAi-resistant genes or to maximize the probability of recombination between two variants. Since the algorithm is a Monte Carlo based algorithm where each codon choice is an independent probabilistic event, the software can iterate the optimization each time finding a new and equally good solution.
Gene Designer does not utilize advanced RNA folding calculation software such as the popular mFold as these types of software are designed to calculate RNA secondary structures for naked RNA. The translated mRNA within an ORF is in fact densely covered by ribosomes. Chemical footprinting of mRNA-ribosome complexes show that up to 20 codons (60 bases) are covered by a single translating ribosome, and the ribosomes are translating at ~18 codons (54 bp)/sec with one ribosome initiating translation every ~2 second leaving only ~50 mRNA bases available between translating ribosomes for folding an mRNA secondary structure. During translation, a stem-loop structure in the coding part of the mRNA does not hinder the progress of the translational machinery, and actively translating ribosomes can break up such structures, either by the energy driven translation process itself or by the support of RNA helicases [26–28].
Gene Designer filters out (or flags, if it can not be avoided) any mRNA structure with double-stranded RNA stem of 12 bp or more. This feature is included because it is very often requested by users and also because it ensures that oligonucleotides used in the gene synthesis process will not predominantly self-anneal during gene assembly.
The codons immediately 3' of the initiation ATG codon have a strong influence on gene expression[22, 29–31]. Accordingly, the codon optimization module in Gene Designer gives the user the option to treat the 5' end of the ORF separately. The default is conservatively set to include the first 15 codons of the ORF as 5' end, but can be changed as needed. Gene Designer will filter out NGG codons in the 5' region and predominantly use A/T in the wobble position[33, 34]. The 5' end is also set to filter out repeats of 8 bases or more and filter out mRNA secondary structures of 8 bp or more.
The local context of a codon can influence the protein expression levels. Back in the early 1980s it was shown that the efficiency of the UAG stop codon in E. coli is typically decreased in the presence of a 3' adenine and increased in the presence of a 3' cytidine[35, 36]. Since then, a multitude of experimentally validated codon contexts have been shown to affect ribosomal frameshift, missense and nonsense incorporations and translational efficiency [37–40]. Gene Designer avoids known codon context issues by omitting the use of rare codons and filtering out runs of C's and G's. We also recommend the addition of two stop codons at the end of an ORF to ensure proper translational termination.
Aside from the experimentally validated cases of codon context effect on protein expression levels, there are several publications where in which codon context effects have been proposed based on in silico analysis of genomes [41–43]. The absence or low level of certain codon contexts in the analysis of entire genomes does not necessarily reflect that the identified sequences affect protein expression of a recombinant gene when grown in rich media, but more likely is a consequence of other evolutionary pressures such as facilitating DNA replication, mutational bias, expression during starvation, intrinsic metabolic regulation etc..  In at least one case, the predicted codon pair bias effect on protein expression could not be experimentally validated. The current version of Gene Designer only includes pre-set sequence constraints that have been experimentally validated. The individual user may add to these any sequence elements they wish to eliminate.
Other design features
Any object can be split into two or more daughters by selecting a part of the sequence and using the Split function. Users can thus easily divide proteins into domains for easy drag-and-drop construction of chimeras or gene variants. Objects can also be linked within and between projects; changes in linked objects then propagate throughout all open projects. All changes, such as editing an object's sequence, changing codon table or codon threshold are incorporated into the final sequence in real time.
The Gene Designer can also be used to design oligonucleotides. To assist with this, a real-time Tm calculator can be positioned in the Sequence View and dragged until a preferred location, length and melting temperature is found. The DNA melting temperature calculation is performed using the nearest neighbor method[47, 48]. The software can also design sequencing primers for a specified region or spanning the entire construct through an integrated 'Actions' module.
Once a sequence has been designed, sequences can be saved with all the graphical elements and captured relationships as Gene Design files (.gd suffix), saved as a graphic image (.jpeg) or as plain text (.txt). Reports can be generated that contain the complete nucleotide sequence, the nucleotide sequence of each object, notes, translation map of each object, a restriction site summary, codon usage frequencies and GC content. Finally, by clicking the 'Get quotation' or 'Order gene' icon, the designed synthetic DNA fragment can be priced or placed in the gene synthesis pipeline of DNA 2.0.
Gene Designer provides an easily accessible means of designing synthetic genes, operons and other genetic constructs denovo. The user can combine and modify pre-defined and custom genetic building blocks directly through a user friendly drag-and-drop interface. All manipulations needed for gene design are integrated and immediately accessible under one interface.
The authors are using and have been using Gene Designer daily over the last year. Several thousand genes have now been designed using only this software. The savings in time, increased convenience and reliability of Gene Designer compared to other commercial and freeware tools has dramatically improved our efficiency and ensure a robust pipeline for sequence information handling. Furthermore, applications such as creating RNAi resistant genes could only be enabled using the Gene Designer software.
Please contact the authors to suggest features to include in upcoming Gene Designer releases.
Gene Designer is freely available for download from the 'Tools' menu at http://www.DNA20.com. Both Mac and PC versions are available. The software is provided "as is" with no guarantee or warranty of any kind for non-commercial use. Please see the download licensing agreement for further licensing details and restrictions on commercial use.
FOR EACH A.A. sequence
FOR EACH codon in sequence
Select a codon randomly from the probability distribution. †
FOR EACH A.A. sequence that needs homologue (aiming/avoidance)
Prepare homologue alignment matrix.
Pre select codons that are (closest to/furthest from) homologue sequence.
IF homologue dna contains unwanted restriction sites or other unwanted sequences THEN
Ask/warn user and eliminate if necessary.
Create a Ukkonen Suffix Tree of the entire construct concatenated with its reverse compliment.
H = homologue score for all A.A. sequences that require it.
R = number of repeats over given threshold.
M = size of largest repeat.
WHILE R > 0 DO ‡
Change a codon in the largest repeat region based on the probability distribution. †
H new = homologue score after change.
R new = number of repeats after change.
M new = size of largest repeat after change.
IF H new ≥ H AND ( R <R new OR M <M new ) THEN
H = H new
R = R new
M = M new
FOR EACH A.A. sequence that requires 5' translation optimization
Create a Ukkonen Suffix Tree of the 5' end concatenated with its reverse compliment.
Find hairpins in 5' end.
GC goal = CG ratio wanted × 3 × number of codons being considered in 5' end.
H = homologue score for the 5' end.
R = number of hairpins.
GC = total number of G's and C's in 5' end.
WHILE R > 0 OR GC > GC goal DO ‡
Change a random codon in 5'end based on the probability distribution. †
H new = homologue score after change.
R new = number of hairpins after change.
GC new = number of G's and C's after change.
IF H new ≥ H AND ( R new <R OR ( R new = R AND GC new <GC )) THEN
H = H new
R = R new
GC = GC new
FOR EACH restriction enzyme that needs to be checked for methylation
Find methylated sites.
WHILE still methylated DO ‡
Change a codon in the site based on the probability distribution. †
FOR EACH restriction enzyme that needs to be avoided.
Find restriction sites.
WHILE restriction site still exists DO ‡
Change a codon in the site based on the probability distribution. †
† Based on a given precompiled codon bias table.
We thank Ramasubbu Venkatesh for an early implementation of the codon optimization algorithm and Glenn Björk (University of Umeå) for comments on the manuscript. Funding for the development and distribution of the software was provided by DNA 2.0, Inc.
- Benner SA, Sismour AM: Synthetic biology. Nat Rev Genet 2005, 6: 533–543. 10.1038/nrg1637View ArticlePubMedGoogle Scholar
- Agarwal KL, Buchi H, Caruthers MH, Gupta N, Khorana HG, Kleppe K, Kumar A, Ohtsuka E, Rajbhandary UL, Van de Sande JH, Sgaramella V, Weber H, Yamada T: Total synthesis of the gene for an alanine transfer ribonucleic acid from yeast. Nature 1970, 227: 27–34. 10.1038/227027a0View ArticlePubMedGoogle Scholar
- Nambiar KP, Stackhouse J, Stauffer DM, Kennedy WP, Eldredge JK, Benner SA: Total synthesis and cloning of a gene coding for the ribonuclease S protein. Science 1984, 223: 1299–1301.View ArticlePubMedGoogle Scholar
- Gustafsson C, Govindarajan S, Minshull J: Codon bias and heterologous protein expression. Trends Biotechnol 2004, 22: 346–353. 10.1016/j.tibtech.2004.04.006View ArticlePubMedGoogle Scholar
- Kumar D, Gustafsson C, Klessig DF: Validation of RNAi Silencing Specificity Using Synthetic Genes: Salicylic Acid-binding Protein 2 Is Required For Plant Innate Immunity. Plant J 2006, 45: 863–868. 10.1111/j.1365-313X.2005.02645.xView ArticlePubMedGoogle Scholar
- Gustafsson C, Govindarajan S, Minshull J: Putting engineering back into protein engineering: bioinformatic approaches to catalyst design. Curr Opin Biotechnol 2003, 14: 366–370. 10.1016/S0958-1669(03)00101-0View ArticlePubMedGoogle Scholar
- Cello J, Paul AV, Wimmer E: Chemical synthesis of poliovirus cDNA: generation of infectious virus in the absence of natural template. Science 2002, 297: 1016–1018. 10.1126/science.1072266View ArticlePubMedGoogle Scholar
- Kodumal SJ, Patel KG, Reid R, Menzella HG, Welch M, Santi DV: Total synthesis of long DNA sequences: synthesis of a contiguous 32-kb polyketide synthase gene cluster. Proc Natl Acad Sci USA 2004, 101: 15573–15578. 10.1073/pnas.0406911101PubMed CentralView ArticlePubMedGoogle Scholar
- Tian J, Gong H, Sheng N, Zhou X, Gulari E, Gao X, Church GM: Accurate multiplex gene synthesis from programmable DNA microchips. Nature 2004, 432: 1050–1054. 10.1038/nature03151View ArticlePubMedGoogle Scholar
- Stewart L, Burgin AB: Whole gene synthesis: A Gene-O-Matic future. Frontiers in Drug Design & Discovery 2005, 1: 297–341.View ArticleGoogle Scholar
- Gouy M, Gautier C: Codon usage in bacteria: correlation with gene expressivity. Nucleic Acids Res 1982, 10: 7055–7074.PubMed CentralView ArticlePubMedGoogle Scholar
- Ikemura T: 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. J Mol Biol 1981, 151: 389–409. 10.1016/0022-2836(81)90003-6View ArticlePubMedGoogle Scholar
- Hayes C, Bose B, Sauer R: Stop codons preceded by rare arginine codons are efficient determinants of SsrA tagging in Escherichia coli. Proc Natl Acad Sci USA 2002, 99: 3440–3445. 10.1073/pnas.052707199PubMed CentralView ArticlePubMedGoogle Scholar
- McNulty D, Claffee B, Huddleston M, Porter M, Cavnar K, Kane J: Mistranslational errors associated with the rare arginine codon CGG in Escherichia coli. Protein Expr Purif 2003, 27: 365–374. 10.1016/S1046-5928(02)00610-1View ArticlePubMedGoogle Scholar
- Kane J, Violand B, Curran D, Staten N, Duffin K, Bogosian G: Novel in-frame two codon translational hop during synthesis of bovine placental lactogen in a recombinant strain of Escherichia coli. Nucleic Acids Res 1992, 20: 6707–6712.PubMed CentralView ArticlePubMedGoogle Scholar
- Lithwick G, Margalit H: Hierarchy of sequence-dependent features associated with prokaryotic translation. Genome Res 2003, 13: 2665–2673. 10.1101/gr.1485203PubMed CentralView ArticlePubMedGoogle Scholar
- Kurland C, Gallant J: Errors of heterologous protein expression. Curr Opin Biotechnol 1996, 7: 489–493. 10.1016/S0958-1669(96)80050-4View ArticlePubMedGoogle Scholar
- Gong M, Gong F, C Y: Overexpression of tnaC of Escherichia coli Inhibits Growth by Depleting tRNA2Pro Availability. J Bacteriol 2006, 188: 1892–1898. 10.1128/JB.188.5.1892-1898.2006PubMed CentralView ArticlePubMedGoogle Scholar
- Farabaugh PJ, Björk GR: How translational accuracy influences reading frame maintenance. Embo J 1999, 18: 1427–1434. 10.1093/emboj/18.6.1427PubMed CentralView ArticlePubMedGoogle Scholar
- Nakamura Y, Gojobori T, Ikemura T: Codon usage tabulated from international DNA sequence databases: status for the year 2000. Nucleic Acids Res 2000, 28: 292. 10.1093/nar/28.1.292PubMed CentralView ArticlePubMedGoogle Scholar
- Henaut A, Danchin A: Analysis and predictions from Escherichia coli sequences. In Escherichia coli and Salmonella typhimurium cellular and molecular biology. Edited by: Neidhardt FC, Curtiss RI, Ingraham J, Lin E, Brooks Low K, Magasanik B, Reznikoff W, Riley M, M S, Umbarger H. ASM press: Washington, D.C.; 1996:2047–2066.Google Scholar
- Jin H, Zhao Q, Gonzalez de Valdivia E, Ardell DH, Stenström M, Isaksson LA: Influences on gene expression in vivo by a Shine-Dalgarno sequence. Mol Microbiol 2006, 60: 480–92. 10.1111/j.1365-2958.2006.05110.xView ArticlePubMedGoogle Scholar
- Zuker M: Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Res 2003, 31: 3406–3415. 10.1093/nar/gkg595PubMed CentralView ArticlePubMedGoogle Scholar
- Green R, Noller H: Ribosomes and translation. Annu Rev Biochem 1997, 66: 679–716. 10.1146/annurev.biochem.66.1.679View ArticlePubMedGoogle Scholar
- Ingraham JL, Maaloe FCN: Growth rate as a variable. In Growth of the bacterial cell. Sinauer Associates Inc. : Sunderland, MA; 1983:267–315.Google Scholar
- Takyar S, Hickerson RP, Noller HF: mRNA helicase activity of the ribosome. Cell 2005, 120: 49–58. 10.1016/j.cell.2004.11.042View ArticlePubMedGoogle Scholar
- Sorensen MA, Kurland CG, Pedersen S: Codon usage determines translation rate in Escherichia coli. J Mol Biol 1989, 207: 365–377. 10.1016/0022-2836(89)90260-XView ArticlePubMedGoogle Scholar
- Iost I, Dreyfus M: mRNAs can be stabilized by DEAD-box proteins. Nature 1994, 372: 193–196. 10.1038/372193a0View ArticlePubMedGoogle Scholar
- Laursen BS, Sørensen HP, Mortensen KK, Sperling-Petersen HU: Initiation of Protein Synthesis in Bacteria. Microbiol Mol Biol Rev 2005, 69: 101–123. 10.1128/MMBR.69.1.101-123.2005PubMed CentralView ArticlePubMedGoogle Scholar
- Stenstrom CM, Holmgren E, Isaksson LA: Cooperative effects by the initiation codon and its flanking regions on translation initiation. Gene 2001, 273: 259–265. 10.1016/S0378-1119(01)00584-4View ArticlePubMedGoogle Scholar
- Sprengart ML, Fuchs E, Porter AG: The downstream box: an efficient and independent translation initiation signal in Escherichia coli. EMBO J 1996, 15: 665–674.PubMed CentralPubMedGoogle Scholar
- Gonzalez de Valdivia E, Isaksson LA: Abortive translation caused by peptidyl-tRNA drop-off at NGG codons in the early coding region of mRNA. FEBS J 2005, 272: 5306–5316. 10.1111/j.1742-4658.2005.04926.xView ArticlePubMedGoogle Scholar
- Stenstrom CM, Jin H, Major LL, Tate WP, Isaksson LA: Codon bias at the 3'-side of the initiation codon is correlated with translation initiation efficiency in Escherichia coli. Gene 2001, 263: 273–284. 10.1016/S0378-1119(00)00550-3View ArticlePubMedGoogle Scholar
- Looman AC, Bodlaender J, Comstock LJ, Eaton D, Jhurani P, de Boer HA, van Knippenberg PH: Influence of the codon following the AUG initiation codon on the expression of a modified lacZ gene in Escherichia coli. EMBO J 1987, 6: 2489–2492.PubMed CentralPubMedGoogle Scholar
- Bossi L, Roth JR: The influence of codon context on genetic code translation. Nature 1980, 286: 123–128. 10.1038/286123a0View ArticlePubMedGoogle Scholar
- Miller JH, Albertini AM: Effects of surrounding sequence on the suppression of nonsense codons. J Mol Biol 1983, 164: 59–71. 10.1016/0022-2836(83)90087-6View ArticlePubMedGoogle Scholar
- Hagervall T, Bjork G: Undermodification in the first position of the anticodon of supG-tRNA reduces translational efficiency. Mol Gen Genet 1984, 196: 194–200. 10.1007/BF00328050View ArticlePubMedGoogle Scholar
- Murgola E, Pagel FT, Hijazi KA: Codon context effects in missense suppression. J Mol Biol 1984, 175: 19–27. 10.1016/0022-2836(84)90442-XView ArticlePubMedGoogle Scholar
- Carrier MJ, Buckingham RH: An effect of codon context on the mistranslation of UGU codons in vitro. J Mol Biol 1984, 175: 29–38. 10.1016/0022-2836(84)90443-1View ArticlePubMedGoogle Scholar
- Bouadloun F, Srichaiyo T, Isaksson LA, Bjork GR: Influence of modification next to the anticodon in tRNA on codon context sensitivity of translational suppression and accuracy. J Bacteriol 1986, 166: 1022–1027.PubMed CentralPubMedGoogle Scholar
- Shpaer EG: Constraints on codon context in Escherichia coli genes. Their possible role in modulating the efficiency of translation. J Mol Biol 1986, 188: 555–564. 10.1016/S0022-2836(86)80005-5View ArticlePubMedGoogle Scholar
- Gouy M: Codon contexts in enterobacterial and coliphage genes. Mol Biol Evol 1987, 4: 426–444.PubMedGoogle Scholar
- Gutman GA, Hatfield GW: Nonrandom utilization of codon pairs in Escherichia coli. Proc Natl Acad Sci USA 1989, 86: 3699–3703. 10.1073/pnas.86.10.3699PubMed CentralView ArticlePubMedGoogle Scholar
- Moura G, Pinheiro M, Silva R, Miranda I, Afreixo V, Dias G, Freitas A, Oliveira JL, Santos MA: Comparative context analysis of codon pairs on an ORFeome scale. Genome Biol 2005, 6: R28. 10.1186/gb-2005-6-3-r28PubMed CentralView ArticlePubMedGoogle Scholar
- Irwin B, Heck JD, Hatfield GW: Codon pair utilization biases influence translational elongation step times. J Biol Chem 1995, 270: 22801–22806. 10.1074/jbc.270.39.22801View ArticlePubMedGoogle Scholar
- Cheng L, Goldman E: Absence of effect of varying Thr-Leu codon pairs on protein synthesis in a T7 system. Biochemistry 2001, 40: 6102–6106. 10.1021/bi010236vView ArticlePubMedGoogle Scholar
- Le Novere N: MELTING, computing the melting temperature of nucleic acid duplex. Bioinformatics 2001, 17: 1226–1227. 10.1093/bioinformatics/17.12.1226View ArticlePubMedGoogle Scholar
- Sugimoto N, Nakano S, Katoh M, Matsumura A, Nakamuta H, Ohmichi T, Yoneyama M, Sasaki M: Thermodynamic parameters to predict stability of RNA/DNA hybrid duplexes. Biochemistry 1995, 34: 11211–11216. 10.1021/bi00035a029View ArticlePubMedGoogle Scholar
- Weiner M, Scheraga H: A set of Macintosh computer programs for the design and analysis of synthetic genes. Comput Appl Biosci 1989, 5: 191–198.PubMedGoogle Scholar
- Raghava G, Sahni G: GMAP: a multi-purpose computer program to aid synthetic gene design, cassette mutagenesis and the introduction of potential restriction sites into DNA sequences. Biotechniques 1994, 16: 1116–1123.PubMedGoogle Scholar
- Hale RS, Thompson G: Codon optimization of the gene encoding a domain from human type 1 neurofibromin protein results in a threefold improvement in expression level in Escherichia coli. Protein Expr Purif 1998, 12: 185–188. 10.1006/prep.1997.0825View ArticlePubMedGoogle Scholar
- Withers-Martinez C, Carpenter EP, Hackett F, Ely B, Sajid M, Grainger M, Blackman MJ: PCR-based gene synthesis as an efficient approach for expression of the A+T-rich malaria genome. Protein Eng 1999, 12: 1113–1120. 10.1093/protein/12.12.1113View ArticlePubMedGoogle Scholar
- Hoover DM, Lubkowski J: DNAWorks: an automated method for designing oligonucleotides for PCR- based gene synthesis. Nucleic Acids Res 2002, 30: e43. 10.1093/nar/30.10.e43PubMed CentralView ArticlePubMedGoogle Scholar
- Fuglsang A: Codon optimizer: a freeware tool for codon optimization. Protein Expr Purif 2003, 31: 247–249. 10.1016/S1046-5928(03)00213-4View ArticlePubMedGoogle Scholar
- Rouillard JM, Lee W, Truan G, Gao X, Zhou X, Gulari E: Gene2Oligo: oligonucleotide design for in vitro gene synthesis. Nucleic Acids Res 2004, 32: W176–180. 10.1093/nar/gnh174PubMed CentralView ArticlePubMedGoogle Scholar
- Gao W, Rzewski A, Sun H, Robbins P, Gambotto A: UpGene: Application of a web-based DNA codon optimization algorithm. Biotechnol Prog 2004, 20: 443–448. 10.1021/bp0300467View ArticlePubMedGoogle Scholar
- Jayaraj S, Reid R, Santi DV: GeMS: an advanced software package for designing synthetic genes. Nucleic Acids Res 2005, 33: 3011–3016. 10.1093/nar/gki614PubMed CentralView ArticlePubMedGoogle Scholar
- Grote A, Hiller K, Scheer M, Munch R, Nortemann B, Hempel DC, D J: JCat: a novel tool to adapt codon usage of a target gene to its potential expression host. Nucleic Acids Res 2005, 1: W526–531. 10.1093/nar/gki376View ArticleGoogle Scholar
- Wu G, Bashir-Bello N, Freeland SJ: The Synthetic Gene Designer: A flexible web platform to explore sequence manipulation for heterologous expression. Protein Expr Purif 2006, 47(2):441–5. 10.1016/j.pep.2005.10.020View ArticlePubMedGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.