Codon and Codon-Pair Usage Tables (CoCoPUTs): Facilitating Genetic Variation Analyses and Recombinant Gene Design

Alexaki, Aikaterini; Kames, Jacob; Holcomb, David D.; Athey, John C.; Santana‐Quintero, Luis V.; Lam, Phuc Vihn Nguyen; Hamasaki-Katagiri, Nobuko; Osipova, Ekaterina; Simonyan, Vahan; Bar, Haim; Komar, Anton A.; Kimchi-Sarfaty, Chava

doi:10.1016/j.jmb.2019.04.021

Cited by 121 publications

(114 citation statements)

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“…Codon, codon pair and dinucleotide usage data for Homo sapiens, Canis lupus familiaris, Chiroptera (bats) and Pholidota (pangolins) were downloaded from the CoCoPUTs database [5] on March 13, 2020.…”

Section: Comparison Of Codon and Codon Pair Usage In Host Speciesmentioning

confidence: 99%

“…RSCU was calculated as defined in Sharp et al [31] based on Homo sapiens genomic codon usage data accessed from the CoCoPUTs database [5] on March 13, 2020. Codon pair scores (CPS) for all 4096 codon pairs were calculated as described in Coleman et al [2] using Homo sapiens genomic codon pair usage data accessed from the CoCoPUTs database [5] on March 13, 2020. Codon pair bias (CPB) of a gene is the arithmetic mean of all CPSs throughout the gene, as defined in Coleman et al [2].…”

Section: Rscu Cps and Cpbmentioning

confidence: 99%

“…It is thought that preferred codons correspond to more abundant tRNAs, and therefore, are translated more efficiently [6]. Similarly, there is bias in codon pair usage, with certain codon pairs occurring at a much different frequency than would be expected based on the codon usage [5]. Codon pair usage also appears to affect translation efficiency [6], although the mechanism is not entirely clear, and it has been argued that dinucleotide usage may be the driving force in determining viral sequence fitness, while codon pair bias may be a secondary effect of altered dinucleotide frequency [7].…”

Section: Introductionmentioning

confidence: 99%

“…We have conducted a thorough analysis of the codon, codon pair and dinucleotide usage of the SARS-CoV-2 and have assessed how it relates to other coronaviruses, its hosts, and to the tissues that SARS-CoV-2 has been reported to infect [21][22][23]. We have taken advantage of our recently published databases, which include genomic codon usage statistics for all species with available sequence data, and transcriptomic codon usage statistics from several human tissues [4,5,24]. We further analyzed each viral gene in terms of its codon characteristics and used an array of codon usage metrics that informed us of the potential of each gene sequence to contribute to the deoptimization of the virus.…”

Section: Introductionmentioning

confidence: 99%

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Sequence analysis of SARS-CoV-2 genome reveals features important for vaccine design

Kames

Holcomb

Kimchi

et al. 2020

Preprint

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As the SARS-CoV-2 pandemic is rapidly progressing, the need for the development of an effective vaccine is critical. A promising approach for vaccine development is to generate, through codon pair deoptimization, an attenuated virus. This approach carries the advantage that it only requires limited knowledge specific to the virus in question, other than its genome sequence. Therefore, it is well suited for emerging viruses for which we may not have extensive data. We performed comprehensive in silico analyses of several features of SARS-CoV-2 genomic sequence (e.g., codon usage, codon pair usage, dinucleotide/junction dinucleotide usage, RNA structure around the frameshift region) in comparison with other members of the coronaviridae family of viruses, the overall human genome, and the transcriptome of specific human tissues such as lung, which are primarily targeted by the virus. Our analysis identified the spike (S) and nucleocapsid (N) proteins as promising targets for deoptimization and suggests a roadmap for SARS-CoV-2 vaccine development, which can be generalizable to other viruses.

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Section: Comparison Of Codon and Codon Pair Usage In Host Speciesmentioning

confidence: 99%

Section: Rscu Cps and Cpbmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Sequence analysis of SARS-CoV-2 genome reveals features important for vaccine design

Kames

Holcomb

Kimchi

et al. 2020

Preprint

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“…In most cases, the preferred specifier is the least preferred codon for the amino acid family. For example in the taxonomical order Bacillales, the Phe UUU codon is used in approximately 70% of cases for translation, but is present in only 1% of Phe T-box specifiers [42]. One possible hypothesis for the specifier-use bias could be attributed to T-boxes favoring interaction with a single tRNA species and disfavoring wobble basepairing.…”

Section: T-box Specifier Usagementioning

confidence: 99%

TBDB – A database of structurally annotated T-box riboswitch:tRNA pairs

Marchand

Smela

Narasimhan

et al. 2020

Preprint

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AbstractT-box riboswitches constitute a large family of tRNA-binding leader sequences that play a central role in gene regulation in many gram-positive bacteria. Accurate inference of the tRNA binding to T-boxes is critical to predict their cis-regulatory activity. However, there is no central repository of information on the tRNA binding specificities of T-box riboswitches and de novo prediction of binding specificities requires advance knowledge of computational tools to annotate riboswitch secondary structure features. Here we present T-box annotation Database (TBDB,https://tbdb.io), an open-access database with a collection of 23,497 T-box sequences, spanning the major phyla of 3,621 bacterial species. Among structural predictions, the TBDB also identifies specifier sequences, cognate tRNA binding partners, and downstream regulatory target. To our knowledge, the TBDB presents the largest collection of feature, sequence, and structural annotations carried out on this important family of regulatory RNA.

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Mistranslation Drives Alterations in Protein Levels and the Effects of a Synonymous Variant at the Fibroblast Growth Factor 21 Locus

et al. 2021

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Fibroblast growth factor 21 (FGF21) is a liver‐derived hormone with pleiotropic beneficial effects on metabolism. Paradoxically, FGF21 levels are elevated in metabolic diseases. Interventions that restore metabolic homeostasis reduce FGF21. Whether abnormalities in FGF21 secretion or resistance in peripheral tissues is the initiating factor in altering FGF21 levels and function in humans is unknown. A genetic approach is used to help resolve this paradox. The authors demonstrate that the primary event in dysmetabolic phenotypes is the elevation of FGF21 secretion. The latter is regulated by translational reprogramming in a genotype‐ and context‐dependent manner. To relate the findings to tissues outcomes, the minor (A) allele of rs838133 is shown to be associated with increased hepatic inflammation in patients with metabolic associated fatty liver disease. The results here highlight a dominant role for translation of the FGF21 protein to explain variations in blood levels that is at least partially inherited. These results provide a framework for translational reprogramming of FGF21 to treat metabolic diseases.

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Codon and Codon-Pair Usage Tables (CoCoPUTs): Facilitating Genetic Variation Analyses and Recombinant Gene Design

Cited by 121 publications

References 48 publications

Sequence analysis of SARS-CoV-2 genome reveals features important for vaccine design

Sequence analysis of SARS-CoV-2 genome reveals features important for vaccine design

TBDB – A database of structurally annotated T-box riboswitch:tRNA pairs

Mistranslation Drives Alterations in Protein Levels and the Effects of a Synonymous Variant at the Fibroblast Growth Factor 21 Locus

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