Universal tight correlation of codon bias and pool of RNA codons (codonome): The genome is optimized to allow any distribution of gene expression values in the transcriptome from bacteria to humans

Genomics

Volumn 101, Issue 5, 2013, Pages 282-289

  Piovesan, Allison ^a   Vitale, Lorenza ^a   Pelleri, Maria Chiara ^a   Strippoli, Pierluigi ^a  

^a UNIVERSITY OF BOLOGNA   (Italy)

Author keywords

Codon bias; Codonome; Genome; Pool of RNA codons; Transcriptome

Indexed keywords

TRANSCRIPTOME;

ACUTE MEGAKARYOCYTIC LEUKEMIA; ANEUPLOIDY; ARTICLE; CAENORHABDITIS ELEGANS; CODON; COMPUTER PROGRAM; DOWN SYNDROME; ESCHERICHIA COLI; GENE EXPRESSION REGULATION; GENE LOCATION; GENE NUMBER; GENE POOL; GENETIC ASSOCIATION; GENETIC DATABASE; GENOME ANALYSIS; HUMAN; HUMAN CELL; HUMAN TISSUE; MALIGNANT NEOPLASTIC DISEASE; NONHUMAN; PRIORITY JOURNAL; SACCHAROMYCES CEREVISIAE;

AMINO ACYL-TRNA SYNTHETASES; ANIMALS; BASE SEQUENCE; BRAIN; CAENORHABDITIS ELEGANS; CODON; DATABASES, NUCLEIC ACID; ERYTHROCYTES; ESCHERICHIA COLI; GENE EXPRESSION REGULATION; GENOME, BACTERIAL; GENOME, HUMAN; HUMANS; MODELS, GENETIC; SACCHAROMYCES CEREVISIAE; SOFTWARE; TRANSCRIPTOME; ZEBRAFISH;

EID: 84876406714     PISSN: 08887543     EISSN: 10898646     Source Type: Journal    
DOI: 10.1016/j.ygeno.2013.02.009     Document Type: Article

References (38)

1. Hershberg R., Petrov D.A. Selection on codon bias. Annu. Rev. Genet. 2008, 42:287-299.
2. 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.
3. Grantham R., Gautier C., Gouy M., Mercier R., Pavé A. Codon catalog usage and the genome hypothesis. Nucleic Acids Res. 1980, 8:r49-r62.
4. Plotkin J.B., Kudla G. Synonymous but not the same: the causes and consequences of codon bias. Nat. Rev. Genet. 2011, 12:32-42.
5. Ikemura T. Codon usage and tRNA content in unicellular and multicellular organisms. Mol. Biol. Evol. 1985, 2:13-34.
6. Sueoka N., Kawanishi Y. DNA G+C content of the third codon position and codon usage biases of human genes. Gene 2000, 261:53-62.
7. Gilchrist M.A., Shah P., Zaretzki R. Measuring and detecting molecular adaptation in codon usage against nonsense errors during protein translation. Genetics 2009, 183:1493-1505.
8. Kanaya S., Yamada Y., Kudo Y., Ikemura T. Studies of codon usage and tRNA genes of 18 unicellular organisms and quantification of Bacillus subtilis tRNAs: gene expression level and species-specific diversity of codon usage based on multivariate analysis. Gene 1999, 238:143-155.
9. Kanaya S., Yamada Y., Kinouchi M., Kudo Y., Ikemura T. Codon usage and tRNA genes in eukaryotes: correlation of codon usage diversity with translation efficiency and with CG-dinucleotide usage as assessed by multivariate analysis. J. Mol. Evol. 2001, 53:290-298.
10. Plotkin J.B., Robins H., Levine A.J. Tissue-specific codon usage and the expression of human genes. Proc. Natl. Acad. Sci. U. S. A. 2004, 101:12588-12591.
11. Sémon M., Lobry J.R., Duret L. No evidence for tissue-specific adaptation of synonymous codon usage in humans. Mol. Biol. Evol. 2006, 23:523-529.
12. Sharp P.M., Li W.H. The codon Adaptation Index - a measure of directional synonymous codon usage bias, and its potential applications. Nucleic Acids Res. 1987, 15:1281-1295.
13. Puigbò P., Bravo I.G., Garcia-Vallvé S. E-CAI: a novel server to estimate an expected value of Codon Adaptation Index (eCAI). BMC Bioinformatics 2008, 9:65-71.
14. Bennetzen J.L., Hall B.D. Codon selection in yeast. J. Biol. Chem. 1982, 257:3026-3031.
15. Wright F. The effective number of codons used in a gene. Gene 1990, 87:23-29.
16. Peden J. Correspondence Analysis of Codon Usage http://codonw.sourceforge.net/.
17. Grote A. Java Codon Adaptation Tool http://www.jcat.de/Introduction.jsp.
18. INCA http://bioinfo.hr/research/inca/.
19. Barrett T., Edgar R. Gene expression omnibus: microarray data storage, submission, retrieval, and analysis. Methods Enzymol. 2006, 411:352-369.
20. Barrett T., Troup D.B., Wilhite S.E., Ledoux P., Rudnev D., Evangelista C., Kim I.F., Soboleva A., Tomashevsky M., Marshall K.A., Phillippy K.H., Sherman P.M., Muertter R.N., Edgar R. NCBI GEO: archive for high-throughput functional genomic data. Nucleic Acids Res. 2009, 37:D885-D890.
21. Lenzi L., Facchin F., Piva F., Giulietti M., Pelleri M.C., Frabetti F., Vitale L., Casadei R., Canaider S., Bortoluzzi S., Coppe A., Danieli G.A., Principato G., Ferrari S., Strippoli P. TRAM (Transcriptome Mapper): database-driven creation and analysis of transcriptome maps from multiple sources. BMC Genomics 2011, 12:121-138.
22. Nakamura Y. Codon Usage Database http://www.kazusa.or.jp/codon/.
23. Gustafsson C., Govindarajan S., Minshull J. Codon bias and heterologous protein expression. Trends Biotechnol. 2004, 22:346-353.
24. Lockstone H.E., Harris L.W., Swatton J.E., Wayland M.T., Holland A.J., Bahn S. Gene expression profiling in the adult Down syndrome brain. Genomics 2007, 90:647-660.
25. Ge X., Yamamoto S., Tsutsumi S., Midorikawa Y., Ihara S., Wang S.M., Aburatani H. Interpreting expression profiles of cancers by genome-wide survey of breadth of expression in normal tissues. Genomics 2005, 86:127-141.
26. Yanai I., Benjamin H., Shmoish M., Chalifa-Caspi V., Shklar M., Ophir R., Bar-Even A., Horn-Saban S., Safran M., Domany E., Lancet D., Shmueli O. Genome-wide midrange transcription profiles reveal expression level relationships in human tissue specification. Bioinformatics 2005, 21:650-659.
27. Detwiller K.Y., Fernando N.T., Segal N.H., Ryeom S.W., D'Amore P.A., Yoon S.S. Analysis of hypoxia-related gene expression in sarcomas and effect of hypoxia on RNA interference of vascular endothelial cell growth factor A. Cancer Res. 2005, 65:5881-5889.
28. Yoon S.S., Segal N.H., Park P.J., Detwiller K.Y., Fernando N.T., Ryeom S.W., Brennan M.F., Singer S. Angiogenic profile of soft tissue sarcomas based on analysis of circulating factors and microarray gene expression. J. Surg. Res. 2006, 135:282-290.
29. Nguyen D.K., Disteche C.M. Dosage compensation of the active X chromosome in mammals. Nat. Genet. 2006, 38:47-53.
30. Padden M., Leech S., Craig B., Kirk J., Brankin B., McQuaid S. Differences in expression of junctional adhesion molecule-A and beta-catenin in multiple sclerosis brain tissue: increasing evidence for the role of tight junction pathology. Acta Neuropathol. 2007, 113:177-186.
31. Auer H., Newsom D.L., Kornacker K. Expression profiling using Affymetrix GeneChip microarrays. Methods Mol. Biol. 2009, 509:35-46.
32. Goh S.H., Josleyn M., Lee Y.T., Danner R.L., Gherman R.B., Cam M.C., Miller J.L. The human reticulocyte transcriptome. Physiol. Genomics 2007, 30:172-178.
33. Kabanova S., Kleinbongard P., Volkmer J., Andrée B., Kelm M., Jax T.W. Gene expression analysis of human red blood cells. Int. J. Med. Sci. 2009, 6:156-159.
34. Noh S.J., Miller S.H., Lee Y.T., Goh S.H., Marincola F.M., Stroncek D.F., Reed C., Wang E., Miller J.L. Let-7 microRNAs are developmentally regulated in circulating human erythroid cells. J. Transl. Med. 2009, 7:98.
35. Klusmann J.H., Godinho F.J., Heitmann K., Maroz A., Koch M.L., Reinhardt D., Orkin S.H., Li Z. Developmental stage-specific interplay of GATA1 and IGF signaling in fetal megakaryopoiesis and leukemogenesis. Genes Dev. 2010, 24:1659-1672.
36. Bourquin J.P., Subramanian A., Langebrake C., Reinhardt D., Bernard O., Ballerini P., Baruchel A., Cavé H., Dastugue N., Hasle H., Kaspers G.L., Lessard M., Michaux L., Vyas P., van Wering E., Zwaan C.M., Golub T.R., Orkin S.H. Identification of distinct molecular phenotypes in acute megakaryoblastic leukemia by gene expression profiling. Proc. Natl. Acad. Sci. U. S. A. 2006, 103:3339-3344.
37. Klusmann J.H., Li Z., Böhmer K., Maroz A., Koch M.L., Emmrich S., Godinho F.J., Orkin S.H., Reinhardt D. miR-125b-2 is a potential oncomiR on human chromosome 21 in megakaryoblastic leukemia. Genes Dev. 2010, 24:478-490.
38. Lenzi L., Frabetti F., Facchin F., Casadei R., Vitale L., Canaider S., Carinci P., Zannotti M., Strippoli P. UniGene Tabulator: a full parser for the UniGene format. Bioinformatics 2006, 22:2570-2571.