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CoCoPUTs, TissueCoCoPUTs and CancerCoCoPUTs

Welcome to CoCoPUTs, TissueCoCoPUTs and CancerCoCoPUTs (collectively referred to as HIVE-CUTs), a collaborative set of projects between Dr. Kimchi-Sarfaty's research group at the FDA and HIVE-FDA. Building on our previous version of HIVE-CUTs, here we present two new databases for codon, codon pair and dinucleotide usage information.

The HIVE-CUTs databases are available to the public and regularly updated. Notice: HIVE-CUTs works in Firefox, Chrome, and Safari.
There is no need to create an account in HIVE in order to use HIVE-CUTs.

CoCoPUTS TissueCoCoPUTs CancerCoCoPUTs SARS-CoV-2 CoCoPUTs EmbryoCoCoPUTs

Video Tutorial

Codon and codon pair usage bias refer to the relative frequency that different codons and codon pairs are used in genes within a given species. Codon and Codon Pair Usage Tables (CoCoPUTs) are presenting a measure of codon and codon pair usage bias, along with dinucleotide usage information, for all species with available sequence information in GenBank and RefSeq. CoCoPUTs are based on the genomic or organelle information for a given organism.

TissueCoCoPUTs contains human tissue-specific codon, codon pair and dinucleotide usage information based on tissue-level differential gene expression derived from the Genotype-Tissue Expression (GTEx) Project. The user may access tissue level codon, codon pair and dinucleotide usage data for 52 human tissues.

CUTs - Codon usage table platform
HIVE-CUTs platform | Previewing tabs: genomic codon pair observed/expected ratio heatmap, liver codon usage table, junction dinucleotide frequencies

CancerCoCoPUTs are human primary tumor-specific codon and codon pair usage tables derived from genomic codon usage information and primary tumor-specific transcriptomic data. The tables presented here represent 32 human primary tumor types / subtypes and their respective normal tissues. Transcriptomic data are derived from The Cancer Genome Atlas (TCGA).

Amino acids can be encoded by various synonymous codons; likewise, two consecutive amino acids can be encoded by different combinations of synonymous codons, termed bicodons or codon pairs. The frequency with which certain synonymous codons and codon pairs are used varies by organism, and can impact protein expression. Furthermore, codon pair usage bias is related to, but distinct from codon usage bias, and cannot be predicted by codon frequencies alone. Recombinant protein engineering exploits this fact through codon and codon pair optimization, wherein native codons and codon pairs are replaced with synonymous alternatives leading to increased expression. To this end, accurate and updated codon and codon pair usage information is key. Given the recent massive increase in GenBank and RefSeq databases, we have created new codon and codon pair usage tables with the most up-to-date sequence information. The tool prioritizes RefSeq, such that if a queried species has a RefSeq assembly, it will pull codon and codon pair information calculated from that assembly.



Searches with this tool will produce the following types of output:

  1. Clickable heatmap displaying codon pair information

  2. Text-based codon usage table

  3. Graphs plotting the codon frequencies per 1000 codons for each query

  4. Graphs showing total dinucleotide and junction dinucleotide frequencies

  5. Graphs showing the GC% content of each query

  6. Effective Number of Codons (ENC) and Codon Pairs (ENCP), metrics measuring codon and codon pair usage bias (Wright 1990)

  7. Taxonomy tree that displays each query and traces the route back to their last shared classification (only available for species related queries)

Furthermore, searches in CoCoPUTs may be performed on individual species or taxonomic group, such as genus or family. Codon pair heat maps can represent, depending on the preference of the user, either (a) frequency per 1M codon pairs, (b) log Frequency, (c) observed / expected ratio or (d) percentile rank.

The codon usage table data files can also be downloaded through the "Available Files to Download" tab, where the user will also find a readme.txt explaining what is contained in each file. Data for queried species or human tissues can be found under "Codon Pair Data" and "Dinucleotide Data" tabs, which can be copied into a spreadsheet or text editor. Other online tools for a variety of functions that are relevant to codon usage statistics can be found in the "External Tools" tab on the left.

The user may switch between "CancerCoCoPUTs", "TissueCoCoPUTs" and "CoCoPUTs" databases by clicking on the blue button to the right of the search box.



The HIVE-CUTs databases are available to the public and regularly updated.
Notice: HIVE-CUTs works in Firefox, Chrome, and Safari.

Citation for CancerCoCoPUTs:

Douglas Meyer, Jacob Kames, Haim Bar, Anton A. Komar, Aikaterini Alexaki, Juan Ibla, Ryan C. Hunt, Luis V. Santana-Quintero, Anton Golikov, Michael DiCuccio & Chava Kimchi-Sarfaty Distinct signatures of codon and codon pair usage in 32 primary tumor types in the novel database CancerCoCoPUTs for cancer-specific codon usage

Citation for TissueCoCoPUTs:

Kames, J., Alexaki, A., Holcomb, D.D., Santana-Quintero, L.V., Athey, J.C., Hamasaki-Katagiri, N., Katneni, U.K., Golikov, A., Ibla, J.C., Bar, H., Kimchi-Sarfaty, C. TissueCoCoPUTs: novel human tissue-specific codon and codon-pair usage tables based on differential tissue gene expression. Journal of Molecular Biology. 2019

Citation for CoCoPUTs:

Alexaki, A., Kames, J., Holcomb, D.D., Athey, J., Santana-Quintero, L. V., Lam, P.V.N., Hamasaki-Katagiri, N., Osipova, E., Simonyan, V., Bar, H., Komar A.A., Kimchi-Sarfaty, C. Codon and Codon-Pair Usage Tables (CoCoPUTs): facilitating genetic variation analyses and recombinant gene design. Journal of Molecular Biology. 2019

Athey J., Alexaki A., Osipova E., Rostovtsev A., Santana-Quintero L.V., Simonyan V., Kimchi-Sarfaty C. A new and updated resource for codon usage tables. BMC Bionformatics, 2017; 18(1):391

Wikipedia: Codon Usage Bias

For questions about HIVE-CUTs, please contact Dr. Chava Kimchi-Sarfaty: Chava.Kimchi-Sarfaty@fda.hhs.gov.