Journal of Molecular Evolution

, Volume 65, Issue 5, pp 574–588 | Cite as

The Pattern of Evolution of Smaller-Scale Gene Duplicates in Mammalian Genomes is More Consistent with Neo- than Subfunctionalisation

  • Timothy Hughes
  • David A. Liberles


Gene duplication and the accompanying release of negative selective pressure on the duplicate pair is thought to be the key process that makes functional change in the coding and regulatory regions of genomes possible. However, the nature of these changes remains unresolved. There are a number of models for the fate of gene duplicates, the two most prominent of which are neofunctionalisation and subfunctionalisation, but it is still unclear which is the dominant fate. Using a dataset consisting of smaller-scale (tandem and segmental) duplications identified from the genomes of four fully sequenced mammalian genomes, we characterise two key features of smaller-scale duplicate evolution: the rate of pseudogenisation and the rate of accumulation of replacement substitutions in the coding sequence. We show that the best fitting model for gene duplicate survival is a Weibull function with a downward sloping convex hazard function which implies that the rate of pseudogenisation of a gene declines rapidly with time since duplication. Our analysis of the accumulation of replacement substitutions per replacement site shows that they accumulate on average at 64% of the neutral expectation immediately following duplication and as high as 73% in the human lineage. Although this rate declines with time since duplication, it takes several tens of millions of years before it has declined to half its initial value. We show that the properties of the gene death rate and of the accumulation of replacement substitutions are more consistent with neofunctionalisation (or subfunctionalisation followed by neofunctionalisation) than they are with subfunctionalisation alone or any of the other alternative modes of evolution of smaller-scale duplicates.


Gene duplication Chordata Pseudogenisation Neofunctionalisation Subfunctionalisation Positive selection Nonsynonymous substitution 



We are grateful to Alex Buerkle and Snehalata Huzurbazar for helpful discussion and to Annie Bouvier for help with the nls2 package. The work has been funded by FUGE, the functional genomics platform of the Norwegian research council.

Supplementary material

239_2007_9041_MOESM1_ESM.pdf (95 kb)
pdf (96 kb)


  1. Ahn S, Tanksley SD (1993) Comparative linkage maps of the rice and maize genomes. Proc Natl Acad Sci USA 90:7980–7984PubMedCrossRefGoogle Scholar
  2. Altschul SF, Madden TL, Schäffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ (1997) Gapped blast and psi-blast: a new generation of protein database search programs. Nucleic Acids Res 25:3389–3402PubMedCrossRefGoogle Scholar
  3. Aury JM, Jaillon O, Duret L, Noel B, Jubin C, Porcel BM, Ségurens B, Daubin V, Anthouard V, Aiach N, Arnaiz O, Billaut A, Beisson J, Blanc I, Bouhouche K, Câmara F, Duharcourt S, Guigo R, Gogendeau D, Katinka M, Keller AM, Kissmehl R, Klotz C, Koll F, Mouël AL, Lepère G, Malinsky S, Nowacki M, Nowak JK, Plattner H, Poulain J, Ruiz F, Serrano V, Zagulski M, Dessen P, Bétermier M, Weissenbach J, Scarpelli C, Schächter V, Sperling L, Meyer E, Cohen J, Wincker P (2006) Global trends of whole-genome duplications revealed by the ciliate Paramecium tetraurelia. Nature 444:171–178PubMedCrossRefGoogle Scholar
  4. Axelsson E, Webster MT, Smith NGC, Burt DW, Ellegren H (2005) Comparison of the chicken and turkey genomes reveals a higher rate of nucleotide divergence on microchromosomes than macrochromosomes. Genome Res 15:120–125PubMedCrossRefGoogle Scholar
  5. Berg J, Willmann S, Lässig M (2004) Adaptive evolution of transcription factor binding sites. BMC Evol Biol 4:42PubMedCrossRefGoogle Scholar
  6. Berglund AC, Wallner B, Elofsson A, Liberles DA (2005) Tertiary windowing to detect positive diversifying selection. J Mol Evol 60:499–504PubMedCrossRefGoogle Scholar
  7. Birney E, Andrews D, Caccamo M, et al. (51 co-authors) (2006) Ensembl 2006. Nucleic Acids Res 34:D556–D561Google Scholar
  8. Blomme T, Vandepoele K, Bodt SD, Simillion C, Maere S, van de Peer Y (2006) The gain and loss of genes during 600 million years of vertebrate evolution. Genome Biol 7:R43PubMedCrossRefGoogle Scholar
  9. Bouvier A, Huet S (1994) nls2: nonlinear regression by s-plus functions. Comput Stat Data Anal 18:187–190CrossRefGoogle Scholar
  10. Dimcheff DE, Drovetski SV, Mindell DP (2002) Phylogeny of Tetraoninae and other galliform birds using mitochondrial 12S and ND2 genes. Mol Phylogen Evol 24:203–215CrossRefGoogle Scholar
  11. Duarte JM, Cui L, Wall PK, Zhang Q, Zhang X, Leebens-Mack J, Ma H, Altman N, dePamphilis CW (2006) Expression pattern shifts following duplication indicative of subfunctionalization and neofunctionalization in regulatory genes of Arabidopsis. Mol Biol Evol 23:469–478PubMedCrossRefGoogle Scholar
  12. Edgar RC (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32:1792–1797PubMedCrossRefGoogle Scholar
  13. Eyre-Walker A (2006) The genomic rate of adaptive evolution. Trends Ecol Evol 21:569–575PubMedCrossRefGoogle Scholar
  14. Force A, Lynch M, Pickett FB, Amores A, Yan YL, Postlethwait J (1999) Preservation of duplicate genes by complementary, degenerative mutations. Genetics 151:1531–1545PubMedGoogle Scholar
  15. Galtier N (2001) Maximum-likelihood phylogenetic analysis under a covarion-like model. Mol Biol Evol 18:866–873PubMedGoogle Scholar
  16. Gu X, Wang Y, Gu J (2002) Age distribution of human gene families shows significant roles of both large- and small-scale duplications in vertebrate evolution. Nature Genet 31:205–209PubMedCrossRefGoogle Scholar
  17. Guan Y, Dunham MJ, Troyanskaya OG (2007) Functional analysis of gene duplications in saccharomyces cerevisiae. Genetics 175:933–943PubMedCrossRefGoogle Scholar
  18. Hughes MK, Hughes AL (1993) Evolution of duplicate genes in a tetraploid animal, Xenopus laevis. Mol Biol Evol 10:1360–1369PubMedGoogle Scholar
  19. Koshi JM, Goldstein RA (1996) Probabilistic reconstruction of ancestral protein sequences. J Mol Evol 42:313–320PubMedCrossRefGoogle Scholar
  20. Kuepfer L, Sauer U, Blank LM (2005) Metabolic functions of duplicate genes in Saccharomyces cerevisiae. Genome Res 15:1421–1430PubMedCrossRefGoogle Scholar
  21. Li WH (1980) Rate of gene silencing at duplicate loci: a theoretical study and interpretation of data from tetraploid fishes. Genetics 95:237–258PubMedGoogle Scholar
  22. Lopez P, Casane D, Philippe H (2002) Heterotachy, an important process of protein evolution. Mol Biol Evol 19:1–7PubMedGoogle Scholar
  23. Lynch M, Conery JS (2000) The evolutionary fate and consequences of duplicate genes. Science 290:1151–1155PubMedCrossRefGoogle Scholar
  24. Lynch M, Conery JS (2003) The evolutionary demography of duplicate genes. J Struct Function Genom 3:35–44CrossRefGoogle Scholar
  25. Lynch M, Force A (2000) The probability of duplicate gene preservation by subfunctionalization. Genetics 154:459–473PubMedGoogle Scholar
  26. Messier W, Stewart CB (1997) Episodic adaptive evolution of primate lysozymes. Nature 385:151–154PubMedCrossRefGoogle Scholar
  27. Nielsen R, Yang Z (1998) Likelihood models for detecting positively selected amino acid sites and applications to the HIV-1 envelope gene. Genetics 148:929–936PubMedGoogle Scholar
  28. Ohno S (1970) Evolution by gene duplication. New York: Springer-VerlagGoogle Scholar
  29. Promponas VJ, Enright AJ, Tsoka S, Kreil DP, Leroy C, Hamodrakas S, Sander C, Ouzounis CA (2000) CAST: an iterative algorithm for the complexity analysis of sequence tracts. Bioinformatics 16:915–922PubMedCrossRefGoogle Scholar
  30. R Development Core Team (2005) R: A language and environment for statistical computing. R Foundation for Statistical Computing Vienna, Austria. ISBN 3-900051-07-0Google Scholar
  31. Rastogi S, Liberles DA (2005) Subfunctionalization of duplicated genes as a transition state to neofunctionalization. BMC Evol Biol 5:28PubMedCrossRefGoogle Scholar
  32. Rastogi S, Reuter N, Liberles DA (2006) Evaluation of models for the evolution of protein sequences and functions under structural constraint. Biophys Chem 124:134–144PubMedCrossRefGoogle Scholar
  33. Roth C, Betts MJ, Steffansson P, Saelensminde G, Liberles DA (2005) The Adaptive Evolution Database (TAED): a phylogeny based tool for comparative genomics. Nucleic Acids Res 33:D495–D497PubMedCrossRefGoogle Scholar
  34. Roth C, Liberles DA (2006) A systematic search for positive selection in higher plants (Embryophytes). BMC Plant Biol 6:12PubMedCrossRefGoogle Scholar
  35. Seoighe C, Johnston CR, Shields DC (2003) Significantly different patterns of amino acid replacement after gene duplication as compared to after speciation. Mol Biol Evol 20:484–490PubMedCrossRefGoogle Scholar
  36. Springer MS, Murphy WJ, Eizirik E, O’Brien SJ (2003) Placental mammal diversification and the Cretaceous-Tertiary boundary. Proc Natl Acad Sci USA 100:1056–1061PubMedCrossRefGoogle Scholar
  37. van de Peer Y, Taylor JS, Meyer A (2003) Are all fishes ancient polyploids? J Struct Functio Genom 3:65–73CrossRefGoogle Scholar
  38. Wolfe KH, Sharp PM (1993) Mammalian gene evolution: nucleotide sequence divergence between mouse and rat. J Mol Evol 37:441–456PubMedCrossRefGoogle Scholar
  39. Yang Z (1997) PAML: a program package for phylogenetic analysis by maximum likelihood. Comput Appl Biosci 13:555–556PubMedGoogle Scholar
  40. Yang Z (1998) Likelihood ratio tests for detecting positive selection and application to primate lysozyme evolution. Mol Biol Evol 15:568–573PubMedGoogle Scholar
  41. Yang Z, Nielsen R (1998) Synonymous and nonsynonymous rate variation in nuclear genes of mammals. J Mol Evol 46:409–418PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  1. 1.Computational Biology Unit, BCCSUniversity of BergenBergenNorway
  2. 2.Department of Molecular BiologyUniversity of WyomingLaramieUSA

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