Predicting Adaptive Evolution - Boston College
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McCarthy for assistance with Latin grammar.OPINIONPredicting adaptive evolutionRobin M. BushPhylogenetic trees reconstruct pastevolution and can provide evidence of pastevolutionary pressure on genes and onindividual codons. In addition to tracing pastevolutionary events, molecularphylogenetics might also be used to predictfuture evolution. Our ability to verify adaptivehypotheses using phylogenetics has broadimplications for vaccine design, genomicsand structural biology.It is well documented that some genesevolve more quickly than others; forinstance, in the human species, certain histone genes are highly conserved, whereasimmunoglobulin loci are extremely polymorphic1. A lack of genetic variation mightindicate the occurrence of purifying selection — a force that preserves the adaptedcondition and that is therefore typicallyobserved in functionally important genes.By contrast, extensive variation in genesindicates that the encoded protein mightbenefit from undergoing amino-acidNATURE REVIEWS GENETICSreplacements. Such positive selection hasbeen recently observed in genes that have anadaptive function. Until now, it has beendifficult to link the patterns of molecularvariation to the selective pressures responsible for them. However, in some systems,notably in viral species, sufficient sequencedata now exist to test adaptive hypothesesdirectly using phylogenetic analysis.Phylogenetic trees are a graphic means ofreconstructing evolution on the basis ofsimilarity between the characters of theindividuals under study; the length of a horizontal branch on the tree reflects theamount of change between an individualand its nearest ancestor (BOX 1). Evolutionarypressure on a gene or codon can be detectedby comparing the rates of synonymous(silent) and non-synonymous (amino-acidchanging, or non-silent) nucleotide substitutions across the branches of a tree. In theabsence of selection, the synonymous andnon-synonymous substitution rates shouldbe equal (FIG. 1a). Most coding genes show anVOLUME 2 MAY 2001 3 8 7 2001 Macmillan Magazines Ltd
PERSPECTIVESBox 1 Phylogenetic treesPhylogenetic trees are a graphicmeans of representing therelationships betweenindividuals on the basis of theirsimilarities. In the diagram, the1 NSACT GAA TTTsampled individuals are(T) (E) (F)represented by terminal nodes(purple dots) and are connectedby branches. Terminal nodes areconnected to their inferredACT GAT TTT1 NSGCT GAA TTTancestors, the internal nodes(T) (D) (F)(A) (E) (F)(brown dots), by terminalbranches, whereas internalnodes are connected to oneanother by internal branches.2SACC GAT TTCThe length of the horizontal(T) (D) (F)branches represents the geneticdistance between individuals. In the example above, the two uppermost nodes are consideredeach others’ nearest relative because they are identical at eight out of nine nucleotidepositions, the bottom sequence is evolutionarily more distant as it is identical to the topsequence at only five sites (single letters in brackets refer to amino acids), bold text highlightsa nucleotide substitution.Several methods exist to construct phylogenetic trees, but those most commonly used areknown as maximum parsimony, maximum likelihood and neighbour joining. Themaximum-parsimony approach to constructing an evolutionary tree operates on theprinciple that simple solutions are preferred to more complex ones. This means that thepreferred tree will be one that requires the smallest number of evolutionary events. In thisexample, a minimum of five nucleotide substitutions (in bold) are required to reconstructthe evolution history that links the three terminal nodes. Maximum-likelihood methodsinfer the tree topology (branching sequence) that is most consistent with the observed data.These methods calculate the possibility that any given topology will produce the observedsequences if calculated for all or many possible topologies that have been constructedaccording to pre-defined evolutionary hypotheses. Neighbour joining is a type of clusteranalysis in which pairs of nodes are iteratively combined to form larger and larger trees(starting with the two most closely related nodes) based on the minimal distance betweenclusters. For a thorough review of these and other phylogenetic methods, see REF. 25. (NS,non-synonymous; S, synonymous.)1 NSCCT GAA TTT(P) (E) (F)excess of synonymous substitutions, whichindicates that purifying (stabilizing) selection is operating to preserve the currentstructure and function of the protein (FIG.1b). Neutral or conserved substitution patterns provide limited insight into the evolutionary process, because the phylogenetictree provides no additional information asto why the gene evolved in this manner.Much more interesting studies are possiblewhen substitution rate analyses indicate theoccurrence of positive selection (FIG. 1c).Positive selection is natural selection thatfavours amino-acid change. Continual positive selection leaves a characteristic pattern ona phylogenetic tree in the form of a greaterrate of non-synonymous than synonymoussubstitution. Potentially, these trees can provide a great deal of additional informationabout the nature of adaptive change in a system. Typically, only a small number of codons388per gene seem to be positively selected. Inproteins of known structure, studying theeffects of changing these particular residuesmight lend insight into the functional role ofthe protein. In proteins of unknown structure, knowing the location of positively selected residues in the two-dimensional structureprovides a starting point to determine thethree-dimensional structure of the protein, asthese residues typically lie in positionsexposed to external selective forces. In addition, we can test adaptive hypotheses by correlating change over time (across the tree) atthe putative, positively selected codons withchanges in phenotype or in fitness. Given asufficient understanding of how a proteinresponds to selection in a particular system, itmight be possible to predict its response tofuture selective challenges.In this article, I outline the theoreticalbasis for the research into substitution rate MAY 2001 VOLUME 2analysis and summarize the biological systems in which evidence of positive selectionhas been detected. I discuss the cases in whichpredicting evolution might be realistic, alongwith some of the potential pitfalls encountered in this type of work. Last, I present somepractical applications of substitution rateanalysis: for epitope identification in vaccinedesign, for the determination of proteinstructure, and as a tool for interpreting theresults of whole-genome sequencing projects.Positive selectionThe study of adaptive evolution using substitution rate analysis involves two basic steps.The first involves reconstructing the evolutionary history of a gene in the form of aphylogenetic tree. A tree depicts the changesthat occur as sequences descend from a common ancestor (BOX 1). In the second step, thetree is used to estimate the non-synonymousand synonymous nucleotide substitutionrates over time (BOX 2). A substitution ratemight be calculated for the entire gene bysumming substitutions across codons; however, with sufficient data, rates might also beestimated for each individual codon. Teststhat sum substitutions across codons mightfail to identify positively selected genes if highnon-synonymous substitution rates occur atonly a few codons. Despite this drawback,genic level studies have identified a numberof putative, positively selected genes (see REF. 2for a comprehensive list). Most of these genesfall into two principal groups: pathogen surface proteins, and sperm proteins of aquaticanimals that practice external fertilization.The surface proteins of pathogens mustchange their three-dimensional structure toavoid recognition by antibodies that areraised in response to previous antigen exposure. Therefore, it is likely that evasion of thehost immune system drives repeated aminoacid replacements in surface proteins.Indirect support for this assumption hasbeen found: the codons in genes with a highnon-synonymous substitution rate typicallycode for residues that are exposed on thesurface of the pathogen. Examples includethe porB gene of the gonorrhoea-inducingbacterium Neisseria gonorrhoea3, whichencodes protein channels in the lipopolysaccharide layer of Gram-negative bacteria, andthe gp120 envelope gene of the humanimmunodeficiency virus (HIV-1)4. The sameis true of haemagglutinin (HA), which,along with neuroaminadase (NA), is one ofthe most antigenic surface proteins of theinfluenza virus. Here, the positively selectedresidues lie on the surface of the protein,within known antibody-binding sites5.www.nature.com/reviews/genetics 2001 Macmillan Magazines Ltd
PERSPECTIVESabcNeutraldriftNS/S 3/3PositiveselectionNS/S 6/0PurifyingselectionNS/S 0/6the sperm has penetrated the egg jelly.Enforcement of species-specific sperm recognition might be the principal selective forcefor change in bindin and lysin, as host specificity for sperm recognition requires correctmatching of the sperm surface with receptorson the egg. Positively selected codons inabalone lysin lie on the surface of the molecule and are associated with structural features that are thought to be involved in binding13. In terms of the need for specificmatching, this system shares many similarities with the host–pathogen studies above.In summary, reasonable adaptivehypotheses have been proposed to explainhow certain patterns of genetic change mighthave been produced by positive selection. Buthow do we test whether positive selectionactually occurred?Testing adaptive hypothesesFigure 1 Effects of selection on substitutionrates. Non-synonymous (NS) and synonymous(S) nucleotide substitutions that typify threeselective regimes: a selective neutrality (NS S),b purifying (stabilizing) selection, whichconserves the present sequence (NS S), andc positive selection, which favours amino-acidreplacement (NS S). Non-synonymoussubstitutions are represented by coloured dotsand synonymous substitutions are indicated byblack dots.Pathogens exert strong selective pressureon their hosts so, not surprisingly, there is evidence of positive selection from various hostdefence systems. Human major histocompatibility complex (MHC) antigen-recognitionsites seem to be positively selected6. Althoughplants use resistance genes and chitinases(enzymes that degrade fungal cell walls) fordefence rather than the T cells, MHC and antibodies that are used by animals, surface proteins of plant pathogens show signs of positiveselection7,8 as do plant-defence systems9. Thesestudies suggest that host–pathogen systemsinvolve exquisite matching between thepathogen and host receptors.Proteins that are involved in the reproduction of externally fertilizing marine organismsprovide another class of genes under positiveselection. The two most extensively studiedcases are the lysin gene of abalones (a shellfish)10–13 and the bindin gene in seaurchins14–17. Lysin, which is released fromsperm at fertilization, dissolves the vitellinecoat of the egg in a species-specific manner;bindin is a sperm acrosomal protein thatmediates species-specific recognition andbinding between the sperm and the egg afterPositive selection produces an excess of nonsynonymous substitutions on a phylogenetictree. However, this excess alone is not sufficient evidence to invoke positive selection.Support for the hypothesis requires anincrease in fitness caused by amino-acidreplacements at the putative, positively selected sites. So far, there has been only one test ofthis hypothesis, using the gene for haemagglutinin, the principal surface antigen of theH3N2 subtype of human influenza A (H3N2refers to the particular HA and NA gene variants that it contains).Human influenza evolves so rapidly thatvaccine strains must be updated almostyearly. Selection favours haemagglutininvariants that escape recognition by the antibodies that are formed in response to pastinfection or vaccination. New lineages ofH3N2 influenza A that differ in theirhaemagglutinin arise frequently. As shownin FIG. 2
Predicting adaptive evolution Robin M. Bush OPINION Phylogenetic trees reconstruct past evolution and can provide evidence of past evolutionary pressure on genes and on individual codons. In addition to tracing past evolutionary events, molecular phylogenetics might also be used to predict future evolution. Our ability to verify adaptive
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