Evolutionary dynamics of oncogenes and tumor suppressor genes: higher intensities of purifying selection than other genes.

Oncogenes and tumor suppressor genes (hereafter referred to as "cancer genes") result in cancer when they experience substitutions that prevent or distort their normal function. We examined evolutionary pressures acting on cancer genes and other classes of disease-related genes and compared our results to analyses of genes without known association to disease. We compared synonymous and nonsynonymous substitution rates in 3,035 human genes-approximately 10% of the genome-measuring the intensity of purifying selection on 311 human disease genes, including 122 cancer-related genes. Although the genes examined are similar to nondisease genes in product, expression, function, and pathway affiliation, we found intriguing differences in the selective pressures experienced by cancer genes relative to other (noncancer) disease-related and non-disease-related genes. We found a statistically significant increase in the intensity of purifying selection exerted on cancer genes (the average ratio of nonsynonymous to synonymous substitutions, omega, was 0.079) relative to all other disease-related genes groups (omega = 0.101) and non-disease-related genes (omega = 0.100). This difference indicates a striking increase in selection against nonsynonymous substitutions in oncogenes and tumor suppressor genes. This finding provides insight into the etiology of cancer and the differences between genes involved in cancer and those implicated in other human diseases. Specifically, we found a significant overlap between human oncogenes and tumor suppressor genes and "essential genes," human homologs of mouse lethal genes identified by knockout experiments. This insight may improve our ability to identify cancer-related genes and enhances our understanding of the nature of these genes.

[1]  Wen-Hsiung Li,et al.  The K(A)/K(S) ratio test for assessing the protein-coding potential of genomic regions: an empirical and simulation study. , 2002, Genome research.

[2]  T. Gojobori,et al.  Molecular evolutionary rates of oncogenes , 2005, Journal of Molecular Evolution.

[3]  G. Glazko,et al.  Estimation of divergence times from multiprotein sequences for a few mammalian species and several distantly related organisms , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[4]  Ross Ihaka,et al.  Gentleman R: R: A language for data analysis and graphics , 1996 .

[5]  S. Stearns,et al.  Evolution in Health and Disease: Work in Progress , 2001, The Quarterly Review of Biology.

[6]  A. E. Hirsh,et al.  Protein dispensability and rate of evolution , 2001, Nature.

[7]  Y. Ina,et al.  New methods for estimating the numbers of synonymous and nonsynonymous substitutions , 1995, Journal of Molecular Evolution.

[8]  Z. Yang,et al.  Estimating synonymous and nonsynonymous substitution rates under realistic evolutionary models. , 2000, Molecular biology and evolution.

[9]  R. Nesse,et al.  How is Darwinian medicine useful? , 2001, The Western journal of medicine.

[10]  D. Liberles,et al.  Evaluation of methods for determination of a reconstructed history of gene sequence evolution. , 2001, Molecular biology and evolution.

[11]  David Valle,et al.  Human disease genes , 2001, Nature.

[12]  Z. Yang,et al.  Rates of nucleotide substitution and mammalian nuclear gene evolution. Approximate and maximum-likelihood methods lead to different conclusions. , 2000, Genetics.

[13]  E. Fearon.  Human cancer syndromes: clues to the origin and nature of cancer. , 1997, Science.

[14]  Laurence D. Hurst,et al.  Do essential genes evolve slowly? , 1999, Current Biology.

[15]  M. Boguski,et al.  A Survey of Human Disease Gene Counterparts in the Drosophila Genome , 2000, The Journal of cell biology.

[16]  P Bork,et al.  Positionally cloned human disease genes: patterns of evolutionary conservation and functional motifs. , 1997, Proceedings of the National Academy of Sciences of the United States of America.

[17]  M. Boguski,et al.  Evolutionary parameters of the transcribed mammalian genome: an analysis of 2,820 orthologous rodent and human sequences. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[18]  Sudhir Kumar,et al.  Mutation rates in mammalian genomes , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[19]  Ziheng Yang,et al.  Statistical methods for detecting molecular adaptation , 2000, Trends in Ecology & Evolution.

[20]  H. B. Mann,et al.  On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other , 1947 .

[21]  M. Nei,et al.  Simple methods for estimating the numbers of synonymous and nonsynonymous nucleotide substitutions. , 1986, Molecular biology and evolution.

[22]  C. Pál,et al.  Evidence for purifying selection acting on silent sites in BRCA1. , 2001, Trends in genetics : TIG.

[23]  N. M. Brooke,et al.  A molecular timescale for vertebrate evolution , 1998, Nature.

[24]  M Gribskov,et al.  A systematic analysis of human disease-associated gene sequences in Drosophila melanogaster. , 2001, Genome research.