Constraints and plasticity in genome and molecular-phenome evolution (original) (raw)

• Kimura, M. The Neutral Theory of Molecular Evolution (Cambridge Univ. Press, 1983).
  Book Google Scholar
• Lynch, M. The Origins of Genome Architecture (Sinauer Associates, Sunderland, Massachusetts, 2007). A definitive presentation of the population-genetic perspective on genome evolution, with an emphasis on effective population size as the dominant factor of evolution and a non-adaptive origin of genomic complexity.
  Google Scholar
• Loewe, L. A framework for evolutionary systems biology. BMC Syst. Biol. 3, 27 (2009).
  PubMed PubMed Central Google Scholar
• Koonin, E. V. & Wolf, Y. I. Evolutionary systems biology: links between gene evolution and function. Curr. Opin. Biotechnol. 17, 481–487 (2006).
  CAS PubMed Google Scholar
• Yamada, T. & Bork, P. Evolution of biomolecular networks: lessons from metabolic and protein interactions. Nature Rev. Mol. Cell Biol. 10, 791–803 (2009).
  CAS Google Scholar
• Snell-Rood, E. C., Van Dyken, J. D., Cruickshank, T., Wade, M. J. & Moczek, A. P. Toward a population genetic framework of developmental evolution: the costs, limits, and consequences of phenotypic plasticity. Bioessays 32, 71–81 (2010).
  CAS PubMed PubMed Central Google Scholar
• Palsson, B. Metabolic systems biology. FEBS Lett. 583, 3900–3904 (2009).
  CAS PubMed PubMed Central Google Scholar
• Erwin, D. H. & Davidson, E. H. The evolution of hierarchical gene regulatory networks. Nature Rev. Genet. 10, 141–148 (2009).
  CAS PubMed Google Scholar
• Shabalina, S. A. & Kondrashov, A. S. Pattern of selective constraint in C. elegans and C. briggsae genomes. Genet. Res. 74, 23–30 (1999).
  CAS PubMed Google Scholar
• Margulies, E. H. et al. Analyses of deep mammalian sequence alignments and constraint predictions for 1% of the human genome. Genome Res. 17, 760–774 (2007).
  CAS PubMed PubMed Central Google Scholar
• Petersen, L., Bollback, J. P., Dimmic, M., Hubisz, M. & Nielsen, R. Genes under positive selection in Escherichia coli. Genome Res. 17, 1336–1343 (2007).
  CAS PubMed PubMed Central Google Scholar
• Muzzi, A., Moschioni, M., Covacci, A., Rappuoli, R. & Donati, C. Pilus operon evolution in Streptococcus pneumoniae is driven by positive selection and recombination. PLoS ONE 3, e3660 (2008).
  PubMed PubMed Central Google Scholar
• Nielsen, R. et al. A scan for positively selected genes in the genomes of humans and chimpanzees. PLoS Biol. 3, e170 (2005).
  PubMed PubMed Central Google Scholar
• Turner, L. M., Chuong, E. B. & Hoekstra, H. E. Comparative analysis of testis protein evolution in rodents. Genetics 179, 2075–2089 (2008).
  CAS PubMed PubMed Central Google Scholar
• Worth, C. L., Gong, S. & Blundell, T. L. Structural and functional constraints in the evolution of protein families. Nature Rev. Mol. Cell Biol. 10, 709–720 (2009).
  CAS Google Scholar
• Grishin, N. V., Wolf, Y. I. & Koonin, E. V. From complete genomes to measures of substitution rate variability within and between proteins. Genome Res. 10, 991–1000 (2000). An early study that suggests that the evolutionary rates of orthologous genes from diverse life forms follow a universal distribution, and that derives a link between intra-gene and across-gene distributions of evolutionary rates.
  CAS PubMed PubMed Central Google Scholar
• Nielsen, R. Molecular signatures of natural selection. Annu. Rev. Genet. 39, 197–218 (2005).
  CAS PubMed Google Scholar
• Ohta, T. & Ina, Y. Variation in synonymous substitution rates among mammalian genes and the correlation between synonymous and nonsynonymous divergences. J. Mol. Evol. 41, 717–720 (1995).
  CAS PubMed Google Scholar
• Makalowski, W. & Boguski, M. S. Synonymous and nonsynonymous substitution distances are correlated in mouse and rat genes. J. Mol. Evol. 47, 119–121 (1998).
  CAS PubMed Google Scholar
• Ellegren, H. Comparative genomics and the study of evolution by natural selection. Mol. Ecol. 17, 4586–4596 (2008).
  PubMed Google Scholar
• Drummond, D. A. & Wilke, C. O. The evolutionary consequences of erroneous protein synthesis. Nature Rev. Genet. 10, 715–724 (2009).
  PubMed Google Scholar
• Lynch, M. & Conery, J. S. The origins of genome complexity. Science 302, 1401–1404 (2003). A seminal work that expounds the population-genetic perspective on the evolution of genomic complexity. The authors argue that genomic complexity is driven by weak purifying selection in populations with small Ne ; in such populations, slightly deleterious features, such as gene duplications or introns, cannot be efficiently eliminated. Collected data on Ne and genomic complexity in diverse life forms are shown to be compatible with this perspective, at least as a rough approximation.
  CAS PubMed Google Scholar
• Koonin, E. V. Evolution of genome architecture. Int. J. Biochem. Cell Biol. 41, 298–306 (2009).
  CAS PubMed Google Scholar
• Harrison, P. M. & Gerstein, M. Studying genomes through the aeons: protein families, pseudogenes and proteome evolution. J. Mol. Biol. 318, 1155–1174 (2002).
  CAS PubMed Google Scholar
• Monot, M. et al. Comparative genomic and phylogeographic analysis of Mycobacterium leprae. Nature Genet. 41, 1282–1289 (2009).
  CAS PubMed Google Scholar
• Darby, A. C., Cho, N. H., Fuxelius, H. H., Westberg, J. & Andersson, S. G. Intracellular pathogens go extreme: genome evolution in the Rickettsiales. Trends Genet. 23, 511–520 (2007).
  CAS PubMed Google Scholar
• Molina, N. & van Nimwegen, E. Universal patterns of purifying selection at noncoding positions in bacteria. Genome Res. 18, 148–160 (2008). A rigorous method for detecting purifying selection in groups of closely related prokaryotes was applied to the study of intergenic region evolution. Universal patterns of purifying selection were detected, and translation-initiation sites were found to be the elements subject to the strongest selective pressure.
  CAS PubMed PubMed Central Google Scholar
• Sella, G., Petrov, D. A., Przeworski, M. & Andolfatto, P. Pervasive natural selection in the Drosophila genome? PLoS Genet. 5, e1000495 (2009). A critical review of the evidence indicating that most sites in the fruitfly genome are subject to selection.
  PubMed PubMed Central Google Scholar
• Waterston, R. H. et al. Initial sequencing and comparative analysis of the mouse genome. Nature 420, 520–562 (2002).
  CAS PubMed Google Scholar
• Lunter, G., Ponting, C. P. & Hein, J. Genome-wide identification of human functional DNA using a neutral indel model. PLoS Comput. Biol. 2, e5 (2006).
  PubMed PubMed Central Google Scholar
• Wright, S. I. & Andolfatto, P. The impact of natural selection on the genome: emerging patterns in Drosophila and Arabidopsis. Annu. Rev. Ecol. Syst. 39, 193–213 (2008).
  Google Scholar
• Gossmann, T. I. et al. Genome wide analyses reveal little evidence for adaptive evolution in many plant species. Mol. Biol. Evol. 18 Mar 2010 (doi:10.1093/molbev/msq079).
  CAS PubMed PubMed Central Google Scholar
• Doolittle, W. F. & Sapienza, C. Selfish genes, the phenotype paradigm and genome evolution. Nature 284, 601–603 (1980).
  CAS PubMed Google Scholar
• Bowen, N. J. & Jordan, I. K. Exaptation of protein coding sequences from transposable elements. Genome Dyn. 3, 147–162 (2007).
  CAS PubMed Google Scholar
• Drake, J. A. et al. Conserved noncoding sequences are selectively constrained and not mutation cold spots. Nature Genet. 38, 223–227 (2006).
  CAS PubMed Google Scholar
• Shabalina, S. A., Ogurtsov, A. Y., Rogozin, I. B., Koonin, E. V. & Lipman, D. J. Comparative analysis of orthologous eukaryotic mRNAs: potential hidden functional signals. Nucleic Acids Res. 32, 1774–1782 (2004).
  CAS PubMed PubMed Central Google Scholar
• Proux, E., Studer, R. A., Moretti, S. & Robinson-Rechavi, M. Selectome: a database of positive selection. Nucleic Acids Res. 37, D404–D407 (2009).
  CAS PubMed Google Scholar
• Costa, F. F. Non-coding RNAs: new players in eukaryotic biology. Gene 357, 83–94 (2005).
  CAS PubMed Google Scholar
• Shabalina, S. A. & Koonin, E. V. Origins and evolution of eukaryotic RNA interference. Trends Ecol. Evol. 23, 578–587 (2008).
  PubMed PubMed Central Google Scholar
• Carthew, R. W. & Sontheimer, E. J. Origins and mechanisms of miRNAs and siRNAs. Cell 136, 642–655 (2009).
  CAS PubMed PubMed Central Google Scholar
• Ponting, C. P., Oliver, P. L. & Reik, W. Evolution and functions of long noncoding RNAs. Cell 136, 629–641 (2009). A detailed review of long non-coding (macro) RNAs, a recently discovered class of mammalian genes that comprise a substantial part of the RNome.
  CAS PubMed Google Scholar
• Bertone, P. et al. Global identification of human transcribed sequences with genome tiling arrays. Science 306, 2242–2246 (2004).
  CAS PubMed Google Scholar
• Johnson, J. M., Edwards, S., Shoemaker, D. & Schadt, E. E. Dark matter in the genome: evidence of widespread transcription detected by microarray tiling experiments. Trends Genet. 21, 93–102 (2005).
  CAS PubMed Google Scholar
• Katzman, S. et al. Human genome ultraconserved elements are ultraselected. Science 317, 915 (2007). A rigorous demonstration of the exceptionally strong selection that affects ultraconserved elements of mammalian genomes that are located outside protein-coding genes.
  CAS PubMed Google Scholar
• Dermitzakis, E. T., Reymond, A. & Antonarakis, S. E. Conserved non-genic sequences — an unexpected feature of mammalian genomes. Nature Rev. Genet. 6, 151–157 (2005).
  CAS PubMed Google Scholar
• Elgar, G. Pan-vertebrate conserved non-coding sequences associated with developmental regulation. Brief. Funct. Genomic. Proteomic. 8, 256–265 (2009).
  PubMed Google Scholar
• Bejerano, G. et al. Ultraconserved elements in the human genome. Science 304, 1321–1325 (2004).
  CAS PubMed Google Scholar
• Baira, E., Greshock, J., Coukos, G. & Zhang, L. Ultraconserved elements: genomics, function and disease. RNA Biol. 5, 132–134 (2008).
  CAS PubMed Google Scholar
• Koonin, E. V., Aravind, L. & Kondrashov, A. S. The impact of comparative genomics on our understanding of evolution. Cell 101, 573–576 (2000).
  CAS PubMed Google Scholar
• Wuchty, S. & Almaas, E. Evolutionary cores of domain co-occurrence networks. BMC Evol. Biol. 5, 24 (2005).
  PubMed PubMed Central Google Scholar
• Basu, M. K., Carmel, L., Rogozin, I. B. & Koonin, E. V. Evolution of protein domain promiscuity in eukaryotes. Genome Res. 18, 449–461 (2008). A quantitative comparative analysis of promiscuous domains across eukaryotic lineages, including demonstration of a positive correlation between domain promiscuity and the strength of purifying selection.
  CAS PubMed PubMed Central Google Scholar
• Rogozin, I. B., Wolf, Y. I., Sorokin, A. V., Mirkin, B. G. & Koonin, E. V. Remarkable interkingdom conservation of intron positions and massive, lineage-specific intron loss and gain in eukaryotic evolution. Curr. Biol. 13, 1512–1517 (2003).
  CAS PubMed Google Scholar
• Roy., S. W. & Gilbert, W. The evolution of spliceosomal introns: patterns, puzzles and progress. Nature Rev. Genet. 7, 211–221 (2006).
  PubMed Google Scholar
• Roy., S. W. & Penny, D. Patterns of intron loss and gain in plants: intron loss-dominated evolution and genome-wide comparison of O. sativa and A. thaliana. Mol. Biol. Evol. 24, 171–181 (2007).
  CAS PubMed Google Scholar
• Carmel, L., Wolf, Y. I., Rogozin, I. B. & Koonin, E. V. Three distinct modes of intron dynamics in the evolution of eukaryotes. Genome Res. 17, 1034–1044 (2007). A detailed analysis of differential dynamics of intron gain and loss across eukaryotic lineages reveals three distinct modes of evolution characterized by pervasive intron loss, equilibrium and relatively rare intron gain, respectively.
  CAS PubMed PubMed Central Google Scholar
• Carmel, L., Rogozin, I. B., Wolf, Y. I. & Koonin, E. V. Patterns of intron gain and conservation in eukaryotic genes. BMC Evol. Biol. 7, 192 (2007).
  PubMed PubMed Central Google Scholar
• Koonin, E. V. & Wolf, Y. I. Genomics of Bacteria and Archaea: the emerging dynamic view of the prokaryotic world. Nucleic Acids Res. 36, 6688–6719 (2008).
  CAS PubMed PubMed Central Google Scholar
• Novichkov, P. S., Wolf, Y. I., Dubchak, I. & Koonin, E. V. Trends in prokaryotic evolution revealed by comparison of closely related bacterial and archaeal genomes. J. Bacteriol. 191, 65–73 (2009). This study provides a comparative analysis of selective and neutral evolutionary processes between multiple bacterial and archaeal lineages. The article demonstrates high, variable rates of genome rearrangement and the lack of correlation between genome streamlining and selective constraints on sequence evolution.
  CAS PubMed Google Scholar
• Eisen, J. A., Heidelberg, J. F., White, O. & Salzberg, S. L. Evidence for symmetric chromosomal inversions around the replication origin in bacteria. Genome Biol. 1, research0011.1–research0011.9 (2000).
  Google Scholar
• Zhou, F., Olman, V. & Xu, Y. Insertion sequences show diverse recent activities in Cyanobacteria and Archaea. BMC Genomics 9, 36 (2008).
  PubMed PubMed Central Google Scholar
• Rogozin, I. B. et al. Connected gene neighborhoods in prokaryotic genomes. Nucleic Acids Res. 30, 2212–2223 (2002).
  CAS PubMed PubMed Central Google Scholar
• Ling, X., He, X. & Xin, D. Detecting gene clusters under evolutionary constraint in a large number of genomes. Bioinformatics 25, 571–577 (2009).
  CAS PubMed Google Scholar
• Wolf, Y. I., Rogozin, I. B., Kondrashov, A. S. & Koonin, E. V. Genome alignment, evolution of prokaryotic genome organization, and prediction of gene function using genomic context. Genome Res. 11, 356–372 (2001).
  CAS PubMed Google Scholar
• Lawrence, J. Selfish operons: the evolutionary impact of gene clustering in prokaryotes and eukaryotes. Curr. Opin. Genet. Dev. 9, 642–648 (1999).
  CAS PubMed Google Scholar
• Rocha, E. P. The organization of the bacterial genome. Annu. Rev. Genet. 42, 211–233 (2008).
  CAS PubMed Google Scholar
• Osbourn, A. E. & Field, B. Operons. Cell. Mol. Life Sci. 66, 3755–3775 (2009).
  CAS PubMed PubMed Central Google Scholar
• Hurst, L. D., Pal, C. & Lercher, M. J. The evolutionary dynamics of eukaryotic gene order. Nature Rev. Genet. 5, 299–310 (2004).
  CAS PubMed Google Scholar
• Liao, B. Y. & Zhang, J. Coexpression of linked genes in Mammalian genomes is generally disadvantageous. Mol. Biol. Evol. 25, 1555–1565 (2008).
  CAS PubMed PubMed Central Google Scholar
• Lemons, D. & McGinnis, W. Genomic evolution of Hox gene clusters. Science 313, 1918–1922 (2006).
  CAS PubMed Google Scholar
• Wong, S. & Wolfe, K. H. Birth of a metabolic gene cluster in yeast by adaptive gene relocation. Nature Genet. 37, 777–782 (2005).
  CAS PubMed Google Scholar
• Eichler, E. E. & Sankoff, D. Structural dynamics of eukaryotic chromosome evolution. Science 301, 793–797 (2003).
  CAS PubMed Google Scholar
• Koonin, E. V. Comparative genomics, minimal gene-sets and the last universal common ancestor. Nature Rev. Microbiol. 1, 127–136 (2003). This article demonstrates the difference between the shrinking set of ubiquitously conserved orthologous genes and the larger minimal set of functional niches. Minimal gene sets are also examined in relation to different prokaryotic lifestyles.
  CAS Google Scholar
• Moya, A. et al. Toward minimal bacterial cells: evolution vs. design. FEMS Microbiol Rev. 33, 225–235 (2009). The latest update on minimal gene sets and the promise of synthetic biology for de novo synthesis of custom genomes.
  CAS PubMed Google Scholar
• Koonin, E. V. Orthologs, paralogs, and evolutionary genomics. Annu. Rev. Genet. 39, 309–338 (2005).
  CAS PubMed Google Scholar
• Mushegian, A. R. & Koonin, E. V. A minimal gene set for cellular life derived by comparison of complete bacterial genomes [see comments]. Proc. Natl Acad. Sci. USA 93, 10268–10273 (1996).
  CAS PubMed PubMed Central Google Scholar
• Charlebois, R. L. & Doolittle, W. F. Computing prokaryotic gene ubiquity: rescuing the core from extinction. Genome Res. 14, 2469–2477 (2004).
  CAS PubMed PubMed Central Google Scholar
• Koonin, E. V., Mushegian, A. R. & Bork, P. Non-orthologous gene displacement. Trends Genet. 12, 334–336 (1996).
  CAS PubMed Google Scholar
• Nilsen, T. W. & Graveley, B. R. Expansion of the eukaryotic proteome by alternative splicing. Nature 463, 457–463 (2010).
  CAS PubMed PubMed Central Google Scholar
• Lynch, M. & Conery, J. S. The evolutionary fate and consequences of duplicate genes. Science 290, 1151–1155 (2000).
  CAS PubMed Google Scholar
• Lespinet, O., Wolf, Y. I., Koonin, E. V. & Aravind, L. The role of lineage-specific gene family expansion in the evolution of eukaryotes. Genome Res. 12, 1048–1059 (2002).
  CAS PubMed PubMed Central Google Scholar
• Huynen, M. A. & van Nimwegen, E. The frequency distribution of gene family sizes in complete genomes. Mol. Biol. Evol. 15, 583–589 (1998). The authors report the discovery that the sizes of paralogous gene families follow a power-law-like distribution. They also present a simple model of gene family evolution.
  CAS PubMed Google Scholar
• Karev, G. P., Wolf, Y. I., Rzhetsky, A. Y., Berezovskaya, F. S. & Koonin, E. V. Birth and death of protein domains: a simple model of evolution explains power law behavior. BMC Evol. Biol. 2, 18 (2002).
  PubMed PubMed Central Google Scholar
• Koonin, E. V., Wolf, Y. I. & Karev, G. P. The structure of the protein universe and genome evolution. Nature 420, 218–223 (2002). A discussion of non-adaptive models of genome evolution — in particular, how patterns of gene birth and death reproduce the observed size distributions of paralogous gene families.
  CAS PubMed Google Scholar
• Putnam, N. H. et al. Sea anemone genome reveals ancestral eumetazoan gene repertoire and genomic organization. Science 317, 86–94 (2007).
  CAS PubMed Google Scholar
• Srivastava, M. et al. The Trichoplax genome and the nature of placozoans. Nature 454, 955–960 (2008).
  CAS PubMed Google Scholar
• Krylov, D. M., Wolf, Y. I., Rogozin, I. B. & Koonin, E. V. Gene loss, protein sequence divergence, gene dispensability, expression level, and interactivity are correlated in eukaryotic evolution. Genome Res. 13, 2229–2235 (2003).
  CAS PubMed PubMed Central Google Scholar
• Wang, X., Grus, W. E. & Zhang, J. Gene losses during human origins. PLoS Biol. 4, e52 (2006).
  PubMed PubMed Central Google Scholar
• Wolf, Y. I., Novichkov, P. S., Karev, G. P., Koonin, E. V. & Lipman, D. J. The universal distribution of evolutionary rates of genes and distinct characteristics of eukaryotic genes of different apparent ages. Proc. Natl Acad. Sci. USA 106, 7273–7280 (2009). This is the definitive demonstration of the universal character of the approximately log-normal distribution of the evolutionary rate of orthologous genes. The distribution of genes by age also follows a similar pattern. The article presents a simple, non-adaptive model according to which the universal distribution of gene-loss rates is a fundamental feature of genome evolution.
  CAS PubMed PubMed Central Google Scholar
• Pal, C., Papp, B. & Hurst, L. D. Highly expressed genes in yeast evolve slowly. Genetics 158, 927–931 (2001).
  CAS PubMed PubMed Central Google Scholar
• Drummond, D. A. & Wilke, C. O. Mistranslation-induced protein misfolding as a dominant constraint on coding-sequence evolution. Cell 134, 341–352 (2008). A comprehensive analysis of the anticorrelation between evolution rate and expression of protein-coding genes in a variety of model organisms. This is a definitive presentation of the mistranslation-induced misfolding hypothesis of protein evolution.
  CAS PubMed PubMed Central Google Scholar
• Pal, C., Papp, B. & Lercher, M. J. An integrated view of protein evolution. Nature Rev. Genet. 7, 337–348 (2006).
  CAS PubMed Google Scholar
• Grosjean, H. & Fiers, W. Preferential codon usage in prokaryotic genes: the optimal codon–anticodon interaction energy and the selective codon usage in efficiently expressed genes. Gene 18, 199–209 (1982).
  CAS PubMed Google Scholar
• Lipman, D. J. & Wilbur, W. J. Interaction of silent and replacement changes in eukaryotic coding sequences. J. Mol. Evol. 21, 161–167 (1984).
  PubMed Google Scholar
• Hershberg, R. & Petrov, D. A. Selection on codon bias. Annu. Rev. Genet. 42, 287–299 (2008).
  CAS PubMed Google Scholar
• Zhou, T., Weems, M. & Wilke, C. O. Translationally optimal codons associate with structurally sensitive sites in proteins. Mol. Biol. Evol. 26, 1571–1580 (2009).
  CAS PubMed PubMed Central Google Scholar
• Lobkovsky, A. E., Wolf, Y. I. & Koonin, E. V. Universal distribution of protein evolution rates as a consequence of protein folding physics. Proc. Natl Acad. Sci. USA 107, 2983–2988 (2010). The universal distribution of evolutionary rates among orthologues is reproduced under a simple model of protein folding and under the assumption that misfolding is the only source of fitness cost in protein evolution.
  CAS PubMed PubMed Central Google Scholar
• Wolf, Y. I., Carmel, L. & Koonin, E. V. Unifying measures of gene function and evolution. Proc. Biol. Sci. 273, 1507–1515 (2006). A systematic analysis of correlations between evolutionary and molecular phenomic variables leads to the idea of 'gene status', according to which genes with a high expression level, a large number of physical or regulatory interactions and high values of other phenomic variables evolve slowly and are rarely lost in the course of evolution.
  CAS PubMed PubMed Central Google Scholar
• Jordan, I. K., Wolf, Y. I. & Koonin, E. V. No simple dependence between protein evolution rate and the number of protein–protein interactions: only the most prolific interactors tend to evolve slowly. BMC Evol. Biol. 3, 1 (2003).
  PubMed PubMed Central Google Scholar
• Bloom, J. D. & Adami, C. Evolutionary rate depends on number of protein–protein interactions independently of gene expression level: response. BMC Evol. Biol. 4, 14 (2004).
  PubMed PubMed Central Google Scholar
• de Silva, E. et al. The effects of incomplete protein interaction data on structural and evolutionary inferences. BMC Biol. 4, 39 (2006).
  PubMed PubMed Central Google Scholar
• Jordan, I. K., Wolf, Y. I. & Koonin, E. V. Duplicated genes evolve slower than singletons despite the initial rate increase. BMC Evol. Biol. 4, 22 (2004).
  PubMed PubMed Central Google Scholar
• Khaitovich, P. et al. A neutral model of transcriptome evolution. PLoS Biol. 2, e132 (2004).
  PubMed PubMed Central Google Scholar
• Jordan, I. K., Marino-Ramirez, L., Wolf, Y. I. & Koonin, E. V. Conservation and coevolution in the scale-free human gene coexpression network. Mol. Biol. Evol. 21, 2058–2070 (2004).
  CAS PubMed Google Scholar
• Denver, D. R. et al. The transcriptional consequences of mutation and natural selection in Caenorhabditis elegans. Nature Genet. 37, 544–548 (2005).
  CAS PubMed Google Scholar
• Jordan, I. K., Marino-Ramirez, L. & Koonin, E. V. Evolutionary significance of gene expression divergence. Gene 345, 119–126 (2005).
  CAS PubMed Google Scholar
• Liao, B. Y. & Zhang, J. Evolutionary conservation of expression profiles between human and mouse orthologous genes. Mol. Biol. Evol. 23, 530–540 (2006).
  CAS PubMed Google Scholar
• Gilad, Y., Oshlack, A. & Rifkin, S. A. Natural selection on gene expression. Trends Genet. 22, 456–461 (2006).
  CAS PubMed Google Scholar
• Schrimpf, S. P. et al. Comparative functional analysis of the Caenorhabditis elegans and Drosophila melanogaster proteomes. PLoS Biol. 7, e48 (2009).
  PubMed Google Scholar
• Weiss, M., Schrimpf, S., Hengartner, M. O., Lercher, M. J. & von Mering, C. Shotgun proteomics data from multiple organisms reveals remarkable quantitative conservation of the eukaryotic core proteome. Proteomics 10, 1297–1306 (2010). This work extends the pioneering study reported in reference 108. The authors applied quantitative, highly accurate proteomic methods to reveal that the abundance of orthologous proteins is — unexpectedly — highly correlated among distantly related model organisms.
  CAS PubMed Google Scholar
• Wolf, Y. I., Gopich, I. V., Lipman, D. J. & Koonin, E. V. Relative contributions of intrinsic structural-functional constraints and translation rate to the evolution of protein-coding genes. Genome Biol. Evol. 17 Mar 2010 (doi:10.1093/gbe/evq010).
  PubMed PubMed Central Google Scholar
• Barabasi, A. L. & Oltvai, Z. N. Network biology: understanding the cell's functional organization. Nature Rev. Genet. 5, 101–113 (2004).
  CAS PubMed Google Scholar
• Bergmann, S., Ihmels, J. & Barkai, N. Similarities and differences in genome-wide expression data of six organisms. PLoS Biol. 2, e9 (2004).
  PubMed Google Scholar
• Tsaparas, P., Marino-Ramirez, L., Bodenreider, O., Koonin, E. V. & Jordan, I. K. Global similarity and local divergence in human and mouse gene co-expression networks. BMC Biol. 6, 70 (2006).
  Google Scholar
• Jordan, I. K., Katz, L. S., Denver, D. R. & Streelman, J. T. Natural selection governs local, but not global, evolutionary gene coexpression networks in Caenorhabditis elegans. BMC Syst. Biol. 2, 96 (2008).
  PubMed PubMed Central Google Scholar
• Lynch, M. The evolution of genetic networks by non-adaptive processes. Nature Rev. Genet. 8, 803–813 (2007). A model of the evolution of biological networks that shows how characteristic network properties could evolve through non-adaptive processes of mutation, drift and recombination.
  CAS PubMed Google Scholar
• Kassen, R. Toward a general theory of adaptive radiation: insights from microbial experimental evolution. Ann. N. Y. Acad. Sci. 1168, 3–22 (2009).
  PubMed Google Scholar
• Jacob, F. Evolution and tinkering. Science 196, 1161–1166 (1977). A seminal conceptual analysis emphasizing the importance of contingency in evolution: evolution is construed as a bricolage that makes use of pre-existing states and is fundamentally unpredictable.
  CAS PubMed Google Scholar
• Mani, G. S. & Clarke, B. C. Mutational order: a major stochastic process in evolution. Proc. R. Soc. Lond. B 240, 29–37 (1990).
  CAS PubMed Google Scholar
• Weinreich, D. M., Delaney, N. F., Depristo, M. A. & Hartl, D. L. Darwinian evolution can follow only very few mutational paths to fitter proteins. Science 312, 111–114 (2006). A key study on the landscape of protein evolution that revealed an unexpected level of constraint on evolutionary trajectories, apparently caused by interactions between mutations (epistasis).
  CAS PubMed Google Scholar
• Novais, A. et al. Evolutionary trajectories of b-lactamase CTX-M-1 cluster enzymes: predicting antibiotic resistance. PLoS Pathog. 6, e1000735 (2010).
  PubMed PubMed Central Google Scholar
• Barrick, J. E. & Lenski, R. E. Genome-wide mutational diversity in an evolving population of Escherichia coli. Cold Spring Harb. Symp. Quant. Biol. 23 Sep 2009 (doi: 10.1101/sqb.2009.74.018). A summary of a series of long-term, extensive studies of bacterial populations in controlled experimental conditions. The studies revealed that evolutionary trajectories are affected by an interplay between contingency and constraint.
  CAS PubMed PubMed Central Google Scholar
• Stanek, M. T., Cooper, T. F. & Lenski, R. E. Identification and dynamics of a beneficial mutation in a long-term evolution experiment with Escherichia coli. BMC Evol. Biol. 9, 302 (2009).
  PubMed PubMed Central Google Scholar
• Blount, Z. D., Borland, C. Z. & Lenski, R. E. Historical contingency and the evolution of a key innovation in an experimental population of Escherichia coli. Proc. Natl Acad. Sci. USA 105, 7899–7906 (2008).
  CAS PubMed PubMed Central Google Scholar
• Stewart, C. B., Schilling, J. W. & Wilson, A. C. Adaptive evolution in the stomach lysozymes of foregut fermenters. Nature 330, 401–404 (1987).
  CAS PubMed Google Scholar
• Yokoyama, R. & Yokoyama, S. Convergent evolution of the red- and green-like visual pigment genes in fish, Astyanax fasciatus, and human. Proc. Natl Acad. Sci. USA 87, 9315–9318 (1990).
  CAS PubMed PubMed Central Google Scholar
• Zhang, J. Parallel adaptive origins of digestive RNases in Asian and African leaf monkeys. Nature Genet. 38, 819–823 (2006).
  CAS PubMed Google Scholar
• Li, Y., Liu, Z., Shi, P. & Zhang, J. The hearing gene Prestin unites echolocating bats and whales. Curr. Biol. 20, R55–R56 (2010).
  CAS PubMed Google Scholar
• Mustonen, V. & Lassig, M. Fitness flux and ubiquity of adaptive evolution. Proc. Natl Acad. Sci. USA. 107, 4248–4253 (2010). A reformulation of the principles of population genetics analogous to the transition from classic to non-equilibrium thermodynamics. The concept of fitness is replaced by fitness flux, and fitness landscape becomes a time-dependent seascape.
  CAS PubMed PubMed Central Google Scholar
• Lynch, M. The frailty of adaptive hypotheses for the origins of organismal complexity. Proc. Natl Acad. Sci. USA 104 (Suppl. 1), 8597–8604 (2007).
  CAS PubMed PubMed Central Google Scholar
• Lynch, M. The origins of eukaryotic gene structure. Mol. Biol. Evol. 23, 450–468 (2006).
  CAS PubMed Google Scholar
• Irimia, M., Penny, D. & Roy., S. W. Coevolution of genomic intron number and splice sites. Trends Genet. 23, 321–325 (2007). A comparative analysis of splice sites showing that intron-poor organisms possess highly conserved splice sites that adhere to a strict consensus, whereas intron-rich genomes contain weak splice sites. A crucial corollary is that the evolution of alternative splicing is conditioned on relatively inefficient splice sites that are prevalent in organisms with weak selective pressure.
  CAS PubMed Google Scholar
• Irimia, M. & Roy, S. W. Evolutionary convergence on highly-conserved 3′ intron structures in intron-poor eukaryotes and insights into the ancestral eukaryotic genome. PLoS Genet. 4, e1000148 (2008).
  PubMed PubMed Central Google Scholar
• Irimia, M. et al. Complex selection on 5′ splice sites in intron-rich organisms. Genome Res. 19, 2021–2027 (2009).
  CAS PubMed PubMed Central Google Scholar
• Lynch, M. Streamlining and simplification of microbial genome architecture. Annu. Rev. Microbiol. 60, 327–349 (2006).
  CAS PubMed Google Scholar
• Wagner, A. Robustness, evolvability, and neutrality. FEBS Lett. 579, 1772–1778 (2005).
  CAS PubMed Google Scholar
• Dobrindt, U. et al. Analysis of genome plasticity in pathogenic and commensal Escherichia coli isolates by use of DNA arrays. J. Bacteriol. 185, 1831–1840 (2003).
  CAS PubMed PubMed Central Google Scholar
• Lozada-Chavez, I., Janga, S. C. & Collado-Vides, J. Bacterial regulatory networks are extremely flexible in evolution. Nucleic Acids Res. 34, 3434–3445 (2006).
  CAS PubMed PubMed Central Google Scholar
• Kazakov, A. E. et al. Comparative genomics of regulation of fatty acid and branched-chain amino acid utilization in proteobacteria. J. Bacteriol. 191, 52–64 (2009).
  CAS PubMed Google Scholar
• Wagner, A. Neutralism and selectionism: a network-based reconciliation. Nature Rev. Genet. 9, 965–974 (2008). A conceptual perspective on (nearly) neutral networks that reconciles the neutralistic and adaptationist paradigms of evolution by showing how initially neutral mutations form the basis for subsequent adaptation.
  CAS PubMed Google Scholar
• Masel, J. & Siegal, M. L. Robustness: mechanisms and consequences. Trends Genet. 25, 395–403 (2009).
  CAS PubMed PubMed Central Google Scholar
• Bergman, A. & Siegal, M. L. Evolutionary capacitance as a general feature of complex gene networks. Nature 424, 549–552 (2003).
  CAS PubMed Google Scholar
• Levy, S. F. & Siegal, M. L. Network hubs buffer environmental variation in Saccharomyces cerevisiae. PLoS Biol. 6, e264 (2008). An experimental demonstration of the unexpectedly large number of evolution capacitors among yeast genes, a finding that validates the theoretical predictions of reference 141.
  PubMed PubMed Central Google Scholar
• Wang, Z. & Zhang, J. Abundant indispensable redundancies in cellular metabolic networks. Genome Biol. Evol. 2009, 23–33 (2009).
  Google Scholar
• Koonin, E. V. Darwinian evolution in the light of genomics. Nucleic Acids Res. 37, 1011–1034 (2009).
  CAS PubMed PubMed Central Google Scholar
• Frank, S. A. The common patterns of nature. J. Evol. Biol. 22, 1563–1585 (2009).
  CAS PubMed PubMed Central Google Scholar
• Wilkins, A. S. Between 'design' and 'bricolage': genetic networks, levels of selection, and adaptive evolution. Proc. Natl Acad. Sci. USA 104 (Suppl. 1), 8590–8596 (2007).
  CAS PubMed PubMed Central Google Scholar
• Resch, A. M. et al. Widespread positive selection in synonymous sites of mammalian genes. Mol. Biol. Evol. 24, 1821–1831 (2007).
  CAS PubMed Google Scholar
• Parsch, J., Novozhilov, S., Saminadin-Peter, S. S., Wong, K. M. & Andolfatto, P. On the utility of short intron sequences as a reference for the detection of positive and negative selection in Drosophila . Mol. Biol. Evol. 27, 1226–1234 (2010).
  CAS Google Scholar
• Ellegren, H., Smith, N. G. & Webster, M. T. Mutation rate variation in the mammalian genome. Curr. Opin. Genet. Dev. 13, 562–568 (2003).
  CAS PubMed Google Scholar
• Charlesworth, J. & Eyre-Walker, A. The McDonald–Kreitman test and slightly deleterious mutations. Mol. Biol. Evol. 25, 1007–1015 (2008).
  CAS PubMed Google Scholar
• Eyre-Walker, A. & Keightley, P. D. Estimating the rate of adaptive molecular evolution in the presence of slightly deleterious mutations and population size change. Mol. Biol. Evol. 26, 2097–2108 (2009).
  CAS PubMed Google Scholar
• Hurst, L. D. The Ka/Ks ratio: diagnosing the form of sequence evolution. Trends Genet. 18, 486–487 (2002).
  PubMed Google Scholar
• van Nimwegen, E. Scaling laws in the functional content of genomes. Trends Genet. 19, 479–484 (2003). A key study that reveals distinct scaling laws for different functional classes of genes and their virtual universality across a broad range of taxa.
  CAS PubMed Google Scholar
• Molina, N. & van Nimwegen, E. Scaling laws in functional genome content across prokaryotic clades and lifestyles. Trends Genet. 25, 243–247 (2009).
  CAS PubMed Google Scholar
• Maslov, S., Krishna, S., Pang, T. Y. & Sneppen, K. Toolbox model of evolution of prokaryotic metabolic networks and their regulation. Proc. Natl Acad. Sci. USA 106, 9743–9748 (2009). A simple model of evolution of metabolic networks that explains the universal scaling laws for regulators and enzymes.
  CAS PubMed PubMed Central Google Scholar
• Lipman, D. J. & Wilbur, W. J. Modelling neutral and selective evolution of protein folding. Proc. Biol. Sci. 245, 7–11 (1991).
  CAS PubMed Google Scholar
• Drummond, D. A., Bloom, J. D., Adami, C., Wilke, C. O. & Arnold, F. H. Why highly expressed proteins evolve slowly. Proc. Natl Acad. Sci. USA 102, 14338–14343 (2005).
  CAS PubMed PubMed Central Google Scholar
• Kramer, E. B. & Farabaugh, P. J. The frequency of translational misreading errors in E. coli is largely determined by tRNA competition. RNA 13, 87–96 (2007).
  CAS PubMed PubMed Central Google Scholar
• Whitehead, D. J., Wilke, C. O., Vernazobres, D. & Bornberg-Bauer, E. The look-ahead effect of phenotypic mutations. Biol. Direct 3, 18 (2008). A modelling study that demonstrates the possibility of evolutionary capacitation through synergistic interactions between mutations and errors of transcription and translation (phenotypic mutations).
  PubMed PubMed Central Google Scholar