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Constraints and plasticity in genome and molecular-phenome evolution

Key Points

  • Different classes of genome sequence, genome architectures, gene repertoires and molecular phenomes are subject to diverse evolutionary constraints that greatly vary in strength and in the nature of the underlying selective and neutral factors.

  • Sequences coding for proteins and structural RNAs typically include the most strongly conserved sites in genomes.

  • Most of the non-coding sequences are less strongly constrained than coding sequences, with the exception of some regulatory sites.

  • Genome architecture is weakly constrained with the exception of the strong association seen between genes in operons, which is partly maintained by horizontal gene transfer.

  • Principles of genome evolution widely differ between groups of organisms: prokaryotic genomes consist mostly of coding sequences and so are on average highly constrained; genomes of multicellular eukaryotes are much larger and contain large fractions of unconstrained, 'junk' DNA; and genomes of unicellular eukaryotes evolve under an intermediate regime that is closer to the prokaryote mode.

  • Some molecular-phenomic features, such as the abundance of proteins encoded by orthologous genes, seem to be subject to surprisingly strong constraints.

  • Evolutionary trajectories that lead to a particular phenotype are substantially constrained, limiting the potential of evolutionary tinkering.

  • The overall level of constraint that affects a given evolving lineage depends on the intensity of selection: this is primarily determined by the characteristic effective population size, although selection is also strongly modulated by the lifestyle properties of the respective organisms.

  • Despite the diversity of evolutionary constraints acting at different levels of biological organization, comparative-genomic and molecular-phenomic analyses reveal universal patterns that could be compatible with relatively simple, general models of evolution.

  • The evolutionary constraints on genome and molecular-phenome evolution are complemented and partially offset by the robustness of biological systems, which is manifested at different levels and is likely to be an evolved feature.


Multiple constraints variously affect different parts of the genomes of diverse life forms. The selective pressures that shape the evolution of viral, archaeal, bacterial and eukaryotic genomes differ markedly, even among relatively closely related animal and bacterial lineages; by contrast, constraints affecting protein evolution seem to be more universal. The constraints that shape the evolution of genomes and phenomes are complemented by the plasticity and robustness of genome architecture, expression and regulation. Taken together, these findings are starting to reveal complex networks of evolutionary processes that must be integrated to attain a new synthesis of evolutionary biology.

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Figure 1: Approximate distribution of evolutionary constraints across genomes with different architectures.
Figure 2: The universal distribution of evolutionary rates across orthologous gene sets.
Figure 3: Genomic and phenomic constraints on different levels of biological organization.


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The authors thank A. Lobkovsky for providing part of the data used in the figure in Box 3 and T. Senkevich for critical reading of the manuscript. We apologize to the many colleagues whose work is not cited here because of space constraints. The authors' research is funded by the Intramural Research Program of the US Department of Health and Human Services (National Library of Medicine, US National Institutes of Health).

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The ability to maintain a phenotype or function in the presence of internal or external perturbations.

Purifying selection

(Also known as negative or stabilizing selection.) Mode of natural selection that eliminates deleterious mutations and preserves the status quo; in protein-coding genes, it is manifested as Ka/Ks << 1.

Non-synonymous substitutions

Nucleotide substitutions in protein-coding genes that lead to amino acid changes in the encoded protein.

Synonymous substitutions

Nucleotide substitutions in protein-coding genes that occur in synonymous positions of codons and accordingly do not lead to amino acid changes in the encoded protein.

Positive selection

(Also known as directional or Darwinian selection.) Mode of natural selection that increases the frequency of initially rare beneficial alleles in a population; in protein-coding genes, this often leads to Ka > Ks.

Ultraconserved elements

Sequences in animal genomes that have retained their identity throughout long evolutionary spans, such as the entire course of vertebrate evolution.

Evolutionary domains

Distinct units of gene/protein evolution that form combinations with varying degrees of evolutionary stability. Evolutionary domains may or may not correspond to structural domains (that is, an evolutionary domain could encompass one or more structural domains).

Promiscuous domain

A protein domain that combines with diverse other domains in numerous proteins, providing malleable connections in interaction and regulatory networks and complexes.


Genes that evolved from a single ancestral gene in the last common ancestor of the compared genomes (in contrast to paralogues).

Selfish operon concept

A hypothesis according to which the presence of the same or similar operons in different prokaryotes is due more to the horizontal transfer of operons as distinct units than to selection for co-expression and co-regulation. When a transferred piece of DNA includes an entire operon consisting of genes encoding a complete pathway or functional system, the chances of fixation dramatically increase.

Minimal gene set for cellular life

The minimal set of genes that is sufficient to maintain a functional cell.

Non-orthologous gene displacement

The utilization of unrelated or distantly related (not orthologous) genes for the same function.

Toolbox model of evolution

A model according to which enzymes for utilizing new metabolites, together with their dedicated regulators, are added (primarily by horizontal gene transfer) to a progressively versatile reaction network. Because of the growing complexity of the pre-existing network that provides enzymes for intermediate reactions, the ratio of regulators to regulated genes grows steadily.

Paralogous gene families

Gene families that evolved by duplication.

Neutral sequence network

A network of sequences connected by effectively single-step mutation distances (although not necessarily by single replacements), and in which there is a negligible fitness difference between neighbours.

Evolutionary anticipation

(Also known as the look-ahead effect.) A scenario for the evolution of complex traits that require multiple mutations. In this scenario, the fixation of the final, beneficial mutation that leads to the emergence of the complex feature is enabled by a preceding random mutational walk over the neutral sequence network or by phenotypic mutations, such as mistranslation.

Experimental evolution

The evolution of organisms with precisely defined genetic backgrounds and known evolutionary histories under controlled laboratory conditions.


When non-allelic genes interact to produce a joint phenotype that differs from the one that would have been produced if the two genes had acted independently.


Describes the multiple functions or mutation consequences of a single gene.

Fitness landscape

A multidimensional surface defining the relationships between the fitness and the genotype spaces.

Fitness seascape

A generalization of the concept of a fitness landscape, in which the dependence of fitness on sequence evolves over time.

Effective population size

The size of an idealized panmictic population whose evolutionary behaviour is equivalent to that of the analysed population.

Pathogenicity islands

Large clusters of genes in bacterial genomes that are typically transferred horizontally and contain pathogenicity determinants.

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Koonin, E., Wolf, Y. Constraints and plasticity in genome and molecular-phenome evolution. Nat Rev Genet 11, 487–498 (2010).

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