The evolution of gene expression levels in mammalian organs

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Changes in gene expression are thought to underlie many of the phenotypic differences between species. However, large-scale analyses of gene expression evolution were until recently prevented by technological limitations. Here we report the sequencing of polyadenylated RNA from six organs across ten species that represent all major mammalian lineages (placentals, marsupials and monotremes) and birds (the evolutionary outgroup), with the goal of understanding the dynamics of mammalian transcriptome evolution. We show that the rate of gene expression evolution varies among organs, lineages and chromosomes, owing to differences in selective pressures: transcriptome change was slow in nervous tissues and rapid in testes, slower in rodents than in apes and monotremes, and rapid for the X chromosome right after its formation. Although gene expression evolution in mammals was strongly shaped by purifying selection, we identify numerous potentially selectively driven expression switches, which occurred at different rates across lineages and tissues and which probably contributed to the specific organ biology of various mammals.

At a glance


  1. Global patterns of gene expression differences among mammals.
    Figure 1: Global patterns of gene expression differences among mammals.

    a, Factorial map of the principal-component analysis of messenger RNA expression levels. The proportion of the variance explained by the principal components is indicated in parentheses. b, Mammalian gene expression phylogenies. Neighbour-joining trees based on pairwise distance matrices (1ρ, Spearman’s correlation coefficient) for cerebellum and testis (see Supplementary Fig. 2 for all six organs). Bootstrap values (5,636 1:1 orthologous amniote genes were randomly sampled with replacement 1,000 times) are indicated by circles: white, >0.9; yellow, ≤0.9. Species colour codes: platypus, light blue; opossum, dark blue; eutherians (mice and primates), black.

  2. Expression divergence rates across tissues and chromosomes.
    Figure 2: Expression divergence rates across tissues and chromosomes.

    a, Comparisons of total branch lengths of expression trees among the six tissues (br, brain; cb, cerebellum; ht, heart; kd, kidney; lv, liver; ts, testis), for the all-amniote and primate data sets. Errors, 95% confidence intervals based on bootstrapping analysis (1,000 replicates, with one individual per species sampled in each replicate). b, Spearman’s correlations between humans and the other species. Coloured envelopes show ranges of values obtained in 100 bootstrap replicates. c, Expression evolution rates on therian X chromosome versus autosomes. Rectangles reflect median branch lengths (1,000 bootstrap replicates) in X-chromosome expression trees (102 1:1 orthologues located in the X-chromosome conserved region34; red) relative to those in autosome trees (5,494 autosomal orthologues; white). P values are based on bootstrap replicates: an asterisk indicates two-tailed P<0.05 (that is, branch longer in X-chromosome tree in more than 97.5% of replicates) and a plus sign indicates P<0.1.

  3. Lineage-specific expression shifts of transcription modules and individual genes.
    Figure 3: Lineage-specific expression shifts of transcription modules and individual genes.

    a, Modules with specific expression states in human brain (prefrontal cortex; 259 genes) and primate cerebellum (189 genes) are shown. Bars represent the weighted average expression of all genes in a module, for each sample (horizontal grey line indicates average bar height). The horizontal red line represents the cut-off of the biclustering algorithm; samples above the red line are considered to have a distinct expression state. See Supplementary Note and our searchable database ( for details. b, Examples of genes that evolved new optimal expression levels in human prefrontal cortex (LIX1; ENSG00000145721), primate cortex (COL25A1; ENSG00000188517) and platypus cerebellum (TRMT1L; ENSG00000121486). Expression levels are indicated as log2-transformed RPKM (reads per kilobase of exon model per million mapped reads) (see Supplementary Tables 11–26 for details). Errors, range of expression values for the different individuals for a given species or tissue.

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Gene Expression Omnibus


  1. Kemp, T. S. The Origin and Evolution of Mammals (Oxford Univ. Press, Oxford, 2005)
  2. Ponting, C. P. The functional repertoires of metazoan genomes. Nature Rev. Genet. 9, 689698 (2008)
  3. King, M. C. & Wilson, A. C. Evolution at two levels in humans and chimpanzees. Science 188, 107116 (1975)
  4. Caceres, M. et al. Elevated gene expression levels distinguish human from non-human primate brains. Proc. Natl Acad. Sci. USA 100, 1303013035 (2003)
  5. Enard, W. et al. Intra- and interspecific variation in primate gene expression patterns. Science 296, 340343 (2002)
  6. Khaitovich, P., Enard, W., Lachmann, M. & Paabo, S. Evolution of primate gene expression. Nature Rev. Genet. 7, 693702 (2006)
  7. Gilad, Y., Oshlack, A., Smyth, G. K., Speed, T. P. & White, K. P. Expression profiling in primates reveals a rapid evolution of human transcription factors. Nature 440, 242245 (2006)
  8. Uddin, M. et al. Sister grouping of chimpanzees and humans as revealed by genome-wide phylogenetic analysis of brain gene expression profiles. Proc. Natl Acad. Sci. USA 101, 29572962 (2004)
  9. Liao, B. Y. & Zhang, J. Evolutionary conservation of expression profiles between human and mouse orthologous genes. Mol. Biol. Evol. 23, 530540 (2006)
  10. Wang, Z., Gerstein, M. & Snyder, M. RNA-Seq: a revolutionary tool for transcriptomics. Nature Rev. Genet. 10, 5763 (2009)
  11. Montgomery, S. B. et al. Transcriptome genetics using second generation sequencing in a Caucasian population. Nature 464, 773777 (2010)
  12. Pickrell, J. K. et al. Understanding mechanisms underlying human gene expression variation with RNA sequencing. Nature 464, 768772 (2010)
  13. Blekhman, R., Marioni, J. C., Zumbo, P., Stephens, M. & Gilad, Y. Sex-specific and lineage-specific alternative splicing in primates. Genome Res. 20, 180189 (2010)
  14. Babbitt, C. C. et al. Both noncoding and protein-coding RNAs contribute to gene expression evolution in the primate brain. Genome Biol. Evol. 2, 6779 (2010)
  15. Hubbard, T. J. et al. Ensembl 2009. Nucleic Acids Res. 37, D690D697 (2009)
  16. Chodroff, R. A. et al. Long noncoding RNA genes: conservation of sequence and brain expression among diverse amniotes. Genome Biol. 11, R72 (2010)
  17. Clark, M. B. et al. The reality of pervasive transcription. PLoS Biol. 9, e1000625 (2011)
  18. Goodman, M. The genomic record of humankind’s evolutionary roots. Am. J. Hum. Genet. 64, 3139 (1999)
  19. Caswell, J. L. et al. Analysis of chimpanzee history based on genome sequence alignments. PLoS Genet. 4, e1000057 (2008)
  20. Harcourt, A. H., Harvey, P. H., Larson, S. G. & Short, R. V. Testis weight, body weight and breeding system in primates. Nature 293, 5557 (1981)
  21. Li, W. H., Ellsworth, D. L., Krushkal, J., Chang, B. H. & Hewett-Emmett, D. Rates of nucleotide substitution in primates and rodents and the generation-time effect hypothesis. Mol. Phylogenet. Evol. 5, 182187 (1996)
  22. The. Chimpanzee Sequencing and Analysis Consortium. Initial sequence of the chimpanzee genome and comparison with the human genome. Nature 437, 6987 (2005)
  23. Warren, W. C. et al. Genome analysis of the platypus reveals unique signatures of evolution. Nature 453, 175183 (2008)
  24. Keightley, P. D., Lercher, M. J. & Eyre-Walker, A. Evidence for widespread degradation of gene control regions in hominid genomes. PLoS Biol. 3, e42 (2005)
  25. Marcus, G. The Birth of the Mind (Basic Books, 2004)
  26. Khaitovich, P. et al. Parallel patterns of evolution in the genomes and transcriptomes of humans and chimpanzees. Science 309, 18501854 (2005)
  27. Chan, E. T. et al. Conservation of core gene expression in vertebrate tissues. J. Biol. 8, 33 (2009)
  28. Kaessmann, H. Origins, evolution, and phenotypic impact of new genes. Genome Res. 20, 13131326 (2010)
  29. Birkhead, T. R. & Pizzari, T. Postcopulatory sexual selection. Nature Rev. Genet. 3, 262273 (2002)
  30. Veyrunes, F. et al. Bird-like sex chromosomes of platypus imply recent origin of mammal sex chromosomes. Genome Res. 18, 965973 (2008)
  31. Potrzebowski, L. et al. Chromosomal gene movements reflect the recent origin and biology of therian sex chromosomes. PLoS Biol. 6, e80 (2008)
  32. Grützner, F. et al. In the platypus a meiotic chain of ten sex chromosomes shares genes with the bird Z and mammal X chromosomes. Nature 432, 913917 (2004)
  33. Potrzebowski, L., Vinckenbosch, N. & Kaessmann, H. The emergence of new genes on the young therian X. Trends Genet. 26, 14 (2010)
  34. Ross, M. T. et al. The DNA sequence of the human X chromosome. Nature 434, 325337 (2005)
  35. Rice, W. R. Sex chromosomes and the evolution of sexual dimorphism. Evolution 38, 735742 (1984)
  36. Charlesworth, B. Model for evolution of Y chromosomes and dosage compensation. Proc. Natl Acad. Sci. USA 75, 56185622 (1978)
  37. Zhang, Y. E., Vibranovski, M. D., Landback, P., Marais, G. A. & Long, M. Chromosomal redistribution of male-biased genes in mammalian evolution with two bursts of gene gain on the X chromosome. PLoS Biol. 8, e1000494 (2010)
  38. Wilson, M. A. & Makova, K. D. Evolution and survival on eutherian sex chromosomes. PLoS Genet. 5, e1000568 (2009)
  39. Bachtrog, D., Jensen, J. D. & Zhang, Z. Accelerated adaptive evolution on a newly formed X chromosome. PLoS Biol. 7, e82 (2009)
  40. Ihmels, J., Bergmann, S. & Barkai, N. Defining transcription modules using large-scale gene expression data. Bioinformatics 20, 19932003 (2004)
  41. Xiong, Y. et al. RNA sequencing shows no dosage compensation of the active X-chromosome. Nature Genet. 42, 10431047 (2010)
  42. Kemkemer, C., Kohn, M., Kehrer-Sawatzki, H., Fundele, R. H. & Hameister, H. Enrichment of brain-related genes on the mammalian X chromosome is ancient and predates the divergence of synapsid and sauropsid lineages. Chromosome Res. 17, 811820 (2009)
  43. Haygood, R., Babbitt, C. C., Fedrigo, O. & Wray, G. A. Contrasts between adaptive coding and noncoding changes during human evolution. Proc. Natl Acad. Sci. USA 107, 78537857 (2010)
  44. Schoenemann, P. T., Sheehan, M. J. & Glotzer, L. D. Prefrontal white matter volume is disproportionately larger in humans than in other primates. Nature Neurosci. 8, 242252 (2005)
  45. Duret, L. & Galtier, N. Biased gene conversion and the evolution of mammalian genomic landscapes. Annu. Rev. Genomics Hum. Genet. 10, 285311 (2009)
  46. Nielsen, R. et al. A scan for positively selected genes in the genomes of humans and chimpanzees. PLoS Biol. 3, e170 (2005)
  47. Fyfe, J. C. et al. An approximately 140-kb deletion associated with feline spinal muscular atrophy implies an essential LIX1 function for motor neuron survival. Genome Res. 16, 10841090 (2006)
  48. Tong, Y., Xu, Y., Scearce-Levie, K., Ptacek, L. J. & Fu, Y. H. COL25A1 triggers and promotes Alzheimer’s disease-like pathology in vivo. Neurogenetics 11, 4152 (2010)
  49. Vauti, F. et al. The mouse Trm1-like gene is expressed in neural tissues and plays a role in motor coordination and exploratory behaviour. Gene 389, 174185 (2007)
  50. Kircher, M., Stenzel, U. & Kelso, J. Improved base calling for the Illumina Genome Analyzer using machine learning strategies. Genome Biol. 10, R83 (2009)
  51. Trapnell, C., Pachter, L. & Salzberg, S. L. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 25, 11051111 (2009)
  52. Hubbard, T. J. et al. Ensembl 2009. Nucleic Acids Res. 37, D690D697 (2009)
  53. Wang, E. T. et al. Alternative isoform regulation in human tissue transcriptomes. Nature 456, 470476 (2008)
  54. Picard, F., Robin, S., Lebarbier, E. & Daudin, J. J. A segmentation/clustering model for the analysis of array CGH data. Biometrics 63, 758766 (2007)
  55. Vilella, A. J. et al. EnsemblCompara GeneTrees: complete, duplication-aware phylogenetic trees in vertebrates. Genome Res. 19, 327335 (2009)
  56. Blanchette, M. et al. Aligning multiple genomic sequences with the threaded blockset aligner. Genome Res. 14, 708715 (2004)
  57. Langmead, B., Trapnell, C., Pop, M. & Salzberg, S. L. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10, R25 (2009)
  58. Kaessmann, H., Vinckenbosch, N. & Long, M. RNA-based gene duplication: mechanistic and evolutionary insights. Nature Rev. Genet. 10, 1931 (2009)
  59. Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L. & Wold, B. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nature Methods 5, 621628 (2008)
  60. Paradis, E., Claude, J. & Strimmer, K. APE: analyses of phylogenetics and evolution in R language. Bioinformatics 20, 289290 (2004)

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Author information

  1. These authors contributed equally to this work.

    • David Brawand,
    • Magali Soumillon &
    • Anamaria Necsulea


  1. Center for Integrative Genomics, University of Lausanne, 1015 Lausanne, Switzerland

    • David Brawand,
    • Magali Soumillon,
    • Anamaria Necsulea,
    • Philippe Julien,
    • Manuela Weier,
    • Angélica Liechti &
    • Henrik Kaessmann
  2. Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland

    • David Brawand,
    • Magali Soumillon,
    • Anamaria Necsulea,
    • Philippe Julien,
    • Gábor Csárdi,
    • Sven Bergmann &
    • Henrik Kaessmann
  3. Department of Medical Genetics, University of Lausanne, 1005 Lausanne, Switzerland

    • Gábor Csárdi &
    • Sven Bergmann
  4. Department of Integrative Biology, University of California, Berkeley, California 94720, USA

    • Patrick Harrigan &
    • Rasmus Nielsen
  5. Max Planck Institute for Evolutionary Anthropology, 04103 Leipzig, Germany

    • Ayinuer Aximu-Petri,
    • Martin Kircher,
    • Frank W. Albert &
    • Svante Pääbo
  6. Chair of Systematic Zoology, Humboldt-University, 10099 Berlin, Germany

    • Ulrich Zeller
  7. CAS-MPG Partner Institute for Computational Biology, 200031 Shanghai, China

    • Philipp Khaitovich
  8. The Robinson Institute, School of Molecular and Biomedical Science, University of Adelaide, Adelaide, South Australia 5005, Australia

    • Frank Grützner
  9. The Bioinformatics Center, University of Copenhagen, 2200 Copenhagen, Denmark

    • Rasmus Nielsen
  10. Present address: Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey 08544, USA.

    • Frank W. Albert


D.B., G.C., H.K., A.N. and P.H. performed biological data analyses. M.S. organized the RNA-seq data production. D.B. and A.N. processed and mapped the reads. A.N. refined genome annotations and established definitions and alignments of constitutive exons. M.S., A.L., F.W.A. and A.A.-P. prepared samples and generated RNA-seq libraries. M.W. prepared samples. P.J. contributed ideas regarding data analyses. F.W.A. coordinated ape RNA-seq data production. M.K. processed ape RNA-seq data. U.Z. extracted and organized Monodelphis domestica samples and advised on this species’ biology. P.K. organized Macaca mulatta samples and provided general advice on gene expression evolution. F.G. organized and extracted platypus RNA samples and advised on this species’ biology. P.H. developed the gene expression selection method and performed all corresponding analyses under the guidance of R.N. G.C. performed analyses using the iterative signature algorithm under the guidance of S.B. S.P. guided ape RNA-seq data production and processing. The project was supervised and originally designed by H.K. The paper was written by H.K. with input from all authors.

Competing financial interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to:

Sequencing data have been deposited in the Gene Expression Omnibus under accession code GSE30352.

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Supplementary information

PDF files

  1. Supplementary Figures (614K)

    This file contains Supplementary Figures 1-9 with legends.

  2. Supplementary Information (1.6M)

    This file contains Supplementary Notes, which include Supplementary Methods, Supplementary Results and a Supplementary Discussion; Supplementary Tables 1-12, Supplementary Figures 1-27 with legends and additional references.

Zip files

  1. Supplementary Tables (2.8M)

    This zipped file contains 5 Supplementary Tables files as follows: Supplementary Tables 1-2 provide detailed information about all samples used in the study; Supplementary Table 3 provides examples of genes with sex-biased expression in various amniote species; Supplementary Tables 4-10 provide detailed data and overviews regarding transcription modules in the all-amniote and primate-specific datasets; Supplementary Tables 11-26 describe all statistically significant expression shifts of individual genes that occurred in the different amniote/primate lineages and Supplementary Tables 27-42 show the most overrepresented GO biological processes among lineage-specific expression changes of individual genes.

  2. Supplementary Data 1 (15.7M)

    This file provides all normalized expression values for all-amniote and primate-specific sets of orthologs.

  3. Supplementary Data 2 (23.7M)

    This file provides all normalized expression values for all-amniote and primate-specific sets of orthologs.

Additional data