Studies in diverse biological systems have indicated that host–parasite co-evolution is responsible for the extraordinary genetic diversity seen in some genomic regions, such as major histocompatibility (MHC) genes in jawed vertebrates and resistance genes in plants. This diversity is believed to evolve under balancing selection on hosts by parasites. However, the mechanisms that link the genomic signatures in these regions to the underlying co-evolutionary process are only slowly emerging. We still lack a clear picture of the co-evolutionary concepts and of the genetic basis of the co-evolving phenotypic traits in the interacting antagonists. Emerging genomic tools that provide new options for identifying underlying genes will contribute to a fuller understanding of the co-evolutionary process.
Your institute does not have access to this article
Open Access articles citing this article.
BMC Biology Open Access 18 February 2022
IMA Fungus Open Access 12 November 2021
Co-structure analysis and genetic associations reveal insights into pinworms (Trypanoxyuris) and primates (Alouatta palliata) microevolutionary dynamics
BMC Ecology and Evolution Open Access 20 October 2021
Subscribe to Nature+
Get immediate online access to the entire Nature family of 50+ journals
Subscribe to Journal
Get full journal access for 1 year
only $4.92 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Get time limited or full article access on ReadCube.
All prices are NET prices.
Majerus, M., Amos, W. & Hurst, G. Evolution: The Four Billion Year War (Addison, Wesley Longman, 1996).
Jack, R. & Du Pasquier, L. Evolutionary Concepts in Immunology (Springer Nature Switzerland, 2019).
Fumagalli, M. et al. Signatures of environmental genetic adaptation pinpoint pathogens as the main selective pressure through human evolution. PLoS Genet. 7, e1002355 (2011).
Karasov, T. L., Horton, M. W. & Bergelson, J. Genomic variability as a driver of plant–pathogen coevolution? Curr. Opin. Plant. Biol. 18, 24–30 (2014).
Apanius, V., Penn, D., Slev, P. R., Ruff, L. R. & Potts, W. K. The nature of selection on the major histocompatibility complex. Crit. Rev. Immunol. 37, 75–120 (2017).
Lenz, T. L., Hafer, N., Samonte, I. E., Yeates, S. E. & Milinski, M. Cryptic haplotype-specific gamete selection yields offspring with optimal MHC immune genes. Evolution 72, 2478–2490 (2018).
Penman, B. S. & Gupta, S. Detecting signatures of past pathogen selection on human HLA loci: are there needles in the haystack? Parasitology 145, 731–739 (2018).
Koenig, D. et al. Long-term balancing selection drives evolution of immunity genes in Capsella. eLife 8, e43606 (2019).
Guoy, A. & Excoffier, L. Polygenic patterns of adaptive introgression in modern humans are mainly shaped by response to pathogens. Mol. Biol. Evol. 37, 1420–1433 (2020).
Janzen, D. H. When is it coevolution. Evolution 34, 611–612 (1980).
Woolhouse, M. E. J., Webster, J. P., Domingo, E., Charlesworth, B. & Levin, B. R. Biological and biomedical implications of the co-evolution of pathogens and their hosts. Nat. Genet. 32, 569–577 (2002).
Kiester, A. R., Lande, R. & Schemske, D. W. Models of coevolution and speciation in plants and their pollinators. Am. Nat. 124, 220–243 (1984).
Wade, M. J. The co-evolutionary genetics of ecological communities. Nat. Rev. Genet. 8, 185–195 (2007).
de Vienne, D. M. et al. Cospeciation vs host-shift speciation: methods for testing, evidence from natural associations and relation to coevolution. N. Phytol. 198, 347–385 (2013).
Ebert, D. Host–parasite coevolution: insights from the Daphnia–parasite model system. Curr. Opin. Microbiol. 11, 290–301 (2008).
Charlesworth, D. Balancing selection and its effects on sequences in nearby genome regions. PLoS Genet. 2, 379–384 (2006). This paper is an authoritative review on the population genetics of balancing selection.
Zivkovic, D., John, S., Verin, M., Stephan, W. & Tellier, A. Neutral genomic signatures of host–parasite coevolution. BMC Evol. Biol. 19, 230 (2019).
Maynard Smith, J. & Szathmáry, E. The Major Transitions in Evolution (Oxford Univ. Press, 1995).
Dodds, P. N. & Rathjen, J. P. Plant immunity: towards an integrated view of plant–pathogen interactions. Nat. Rev. Genet. 11, 539–548 (2010).
Sironi, M., Cagliani, R., Forni, D. & Clerici, M. Evolutionary insights into host–pathogen interactions from mammalian sequence data. Nat. Rev. Genet. 16, 224–236 (2015).
Tellier, A., Moreno-Gamez, S. & Stephan, W. Speed of adaptation and genomic footprints of host–parasite coevolution under arms race and trench warfare dynamics. Evolution 68, 2211–2224 (2014).
Thrall, P. H., Barrett, L. G., Dodds, P. N. & Burdon, J. J. Epidemiological and evolutionary outcomes in gene-for-gene and matching allele models. Front. Plant Sci. 6, 1084 (2016).
Ebert, D. Open questions: what are the genes underlying antagonistic coevolution? BMC Biol. 16, 114 (2018).
Fischer, M. C., Foll, M., Heckel, G. & Excoffier, L. Continental-scale footprint of balancing and positive selection in a small rodent (Microtus arvalis). PLoS ONE 9, e112332 (2014).
Leffler, E. M. et al. Multiple instances of ancient balancing selection shared between humans and chimpanzees. Science 339, 1578–1582 (2013). This study reports on many sites with TSPs and ancient balancing selection in genomes of humans and chimpanzees.
Key, F. M., Teixeira, J. C., de Filippo, C. & Andres, A. M. Advantageous diversity maintained by balancing selection in humans. Curr. Opin. Genet. Dev. 29, 45–51 (2014).
Schweizer, R. M. et al. Natural selection and origin of a melanistic allele in North American Gray Wolves. Mol. Biol. Evol. 35, 1190–120 (2018).
Bitarello, B. D. et al. Signatures of long-term balancing selection in human genomes. Genome Biol. Evol. 10, 939–955 (2018).
Cheng, X. & DeGiorgio, M. Detection of shared balancing selection in the absence of trans-species polymorphism. Mol. Biol. Evol. 36, 177–199 (2019).
Enard, D., Cai, L., Gwennap, C. & Petrov, D. A. Viruses are a dominant driver of protein adaptation in mammals. eLife 5, e124699 (2016).
Schirrmann, M. K. et al. Genomewide signatures of selection in Epichloe reveal candidate genes for host specialization. Mol. Ecol. 27, 3070–3086 (2018).
Persoons, A. et al. The escalatory Red Queen: population extinction and replacement following arms race dynamics in poplar rust. Mol. Ecol. 26, 1902–1918 (2017).
Mohd-Assaad, N., McDonald, B. A. & Croll, D. Genome-wide detection of genes under positive selection in worldwide populations of the barley scald pathogen. Genome Biol. Evol. 10, 1315–1332 (2018).
Badouin, H. et al. Widespread selective sweeps throughout the genome of model plant pathogenic fungi and identification of effector candidates. Mol. Ecol. 26, 2041–2062 (2017).
Obbard, D. J., Gordon, K. H. J., Buck, A. H. & Jiggins, F. M. The evolution of RNAi as a defence against viruses and transposable elements. Philos. Trans. R. Soc. Lond. B Biol. Sci. 364, 99–115 (2009).
Barrick, J. E. & Lenski, R. E. Genome dynamics during experimental evolution. Nat. Rev. Genet. 14, 827–839 (2013).
Hermisson, J. & Pennings, P. S. Soft sweeps and beyond: understanding the patterns and probabilities of selection footprints under rapid adaptation. Methods Ecol. Evol. 8, 700–716 (2017).
Hahn, M. W. Molecular Population Genetics (Sinauer Associates, 2018).
McCarthy, K. R., Kirmaier, A., Autissier, P. & Johnson, W. E. Evolutionary and functional analysis of old world primate TRIM5 reveals the ancient emergence of primate lentiviruses and convergent evolution targeting a conserved capsid interface. PLoS Pathog. 11, e1005085 (2015).
Elena, S. F., Cooper, V. S. & Lenski, R. E. Punctuated evolution caused by selection of rare beneficial mutations. Science 272, 1802–1804 (1996).
Anderson, T. J. C. et al. Population parameters underlying an ongoing soft sweep in southeast asian malaria parasites. Mol. Biol. Evol. 34, 131–144 (2017).
Garud, N. R., Messer, P. W., Buzbas, E. O. & Petrov, D. A. Recent selective sweeps in North American Drosophila melanogaster show signatures of soft sweeps. PLoS Genet. 11, e1005004 (2015).
Sanchez-Vallet, A. et al. The genome biology of effector gene evolution in filamentous plant pathogens. Ann. Rev. Phytopathol. 56, 21–40 (2018).
Moxon, E. R., Rainey, P. B., Nowak, M. A. & Lenski, R. E. Adaptive evolution of highly mutable loci in pathogenic bacteria. Curr. Biol. 4, 24–33 (1994).
Raffaele, S. et al. Genome evolution following host jumps in the Irish potato famine pathogen lineage. Science 330, 1540–1543 (2010).
Croll, D. & McDonald, B. A. The accessory genome as a cradle for adaptive evolution in pathogens. PLoS Pathog. 8, e1002608 (2012).
Clarke, B. C. in Genetic Aspects of Host–Parasite Relationships (eds A. E. R. Taylor & R. M. Muller) 87–104 (Blackwell, 1976).
Hamilton, W. D., Axelrod, R. & Tanese, R. Sexual reproduction as an adaptation to resist parasites. Proc. Natl Acad. Sci. USA 87, 3566–3573 (1990).
Fenton, A., Antonovics, J. & Brockhurst, M. A. Inverse-gene-for-gene infection genetics and coevolutionary dynamics. Am. Nat. 174, E230–E242 (2009).
Schmid-Hempel, P. Evolutionary Parasitology: The Integrated Study of Infections, Immunology, Ecology, and Genetics (Oxford Univ. Press, 2011). This textbook comprehensively summarizes the field of host–parasite evolution and co-evolution.
Ben Khalifa, M., Simon, V., Fakhfakh, H. & Moury, B. Tunisian potato virus Y isolates with unnecessary pathogenicity towards pepper: support for the matching allele model in eIF4E resistance–potyvirus interactions. Plant Pathol. 61, 441–447 (2012).
Luijckx, P., Fienberg, H., Duneau, D. & Ebert, D. A matching-allele model explains host resistance to parasites. Curr. Biol. 23, 1085–1088 (2013). This study provides an early example of a well worked out, matching allele host–parasite interaction matrix.
Bento, G. et al. The genetic basis of resistance and matching-allele interactions of a host–parasite system: the Daphnia magna–Pasteuria ramosa model. PLoS Genet. 13, e1006596 (2017).
King, K. C., Jokela, J. & Lively, C. M. Parasites, sex, and clonal diversity in natural snail populations. Evolution 65, 1474–1481 (2011).
Ashby, B. & Boots, M. Multi-mode fluctuating selection in host–parasite coevolution. Ecol. Lett. 20, 357–365 (2017).
Papkou, A. et al. The genomic basis of Red Queen dynamics during rapid reciprocal host–pathogen coevolution. Proc. Natl Acad. Sci. USA 116, 923–928 (2019). This study of experimental evolution with nematodes and a bacterial pathogen demonstrates the complexity of co-evolutionary interactions emerging in seemingly simple systems.
Koskella, B. & Lively, C. M. Evidence for negative frequency-dependent selection during experimental coevolution of a freshwater snail and a sterilizing trematode. Evolution 63, 2213–2221 (2009).
Lively, C. M. Habitat heterogeneity, host population structure, and parasite local adaptation. J. Hered. 109, 29–37 (2018).
Ejsmond, M. J., Babik, W. & Radwan, J. MHC allele frequency distributions under parasite-driven selection: a simulation model. BMC Evol. Biol. 10, 332 (2010).
Fijarczyk, A. & Babik, W. Detecting balancing selection in genomes: limits and prospects. Mol. Ecol. 24, 3529–3545 (2015).
Bubb, K. L. et al. Scan of human genome reveals no new loci under ancient balancing selection. Genetics 173, 2165–2177 (2006).
Cagliani, R. et al. The signature of long-standing balancing selection at the human defensin β-1 promoter. Genome Biol. 9, R143 (2008).
Fumagalli, M. et al. Widespread balancing selection and pathogen-driven selection at blood group antigen genes. Genome Res. 19, 199–212 (2009).
Segurel, L. et al. The ABO blood group is a trans-species polymorphism in primates. Proc. Natl Acad. Sci. USA 109, 18493–18498 (2012).
Bergelson, J., Kreitman, M., Stahl, E. A. & Tian, D. C. Evolutionary dynamics of plant R-genes. Science 292, 2281–2285 (2001).
Hoerger, A. C. et al. Balancing selection at the tomato RCR3 guardee gene family maintains variation in strength of pathogen defense. PLoS Genet. 8, e1002813 (2012).
Llaurens, V., Whibley, A. & Joron, M. Genetic architecture and balancing selection: the life and death of differentiated variants. Mol. Ecol. 26, 2430–2448 (2017).
Croze, M. et al. A genome-wide scan for genes under balancing selection in Drosophila melanogaster. BMC Evol. Biol. 17, 15 (2017).
Buckley, J., Holub, E. B., Koch, M. A., Vergeer, P. & Mable, B. K. Restriction associated DNA-genotyping at multiple spatial scales in Arabidopsis lyrata reveals signatures of pathogen-mediated selection. BMC Genomics 19, 496 (2018).
Wu, Q. et al. Long-term balancing selection contributes to adaptation in Arabidopsis and its relatives. Genome Biol. 18, 217 (2017).
Unckless, R. L., Howick, V. M. & Lazzaro, B. P. Convergent balancing selection on an antimicrobial peptide in Drosophila. Curr. Biol. 26, 257–262 (2016).
Bartoli, C. & Roux, F. Genome-wide association studies in plant pathosystems: toward an ecological genomics approach. Front. Plant. Sci. 8, 763 (2017).
Power, R. A., Parkhill, J. & de Oliveira, T. Microbial genome-wide association studies: lessons from human GWAS. Nat. Rev. Genet. 18, 41–50 (2017).
Thomas, J. C., Godfrey, P. A., Feldgarden, M. & Robinson, A. Candidate targets of balancing selection in the genome of Staphylococcus aureus. Mol. Biol. Evol. 29, 1175–1186 (2012).
Zhang, L. F., Thomas, J. C., Didelot, X. & Robinson, D. A. Molecular signatures identify a candidate target of balancing selection in an arcD-like gene of Staphylococcus epidermidis. J. Mol. Evol. 75, 43–54 (2012).
Guttman, D. S., Gropp, S. J., Morgan, R. L. & Wang, P. W. Diversifying selection drives the evolution of the type III secretion system pilus of Pseudomonas syringae. Mol. Biol. Evol. 23, 2342–2354 (2006).
Castillo, J. A. & Agathos, S. N. A genome-wide scan for genes under balancing selection in the plant pathogen Ralstonia solanacearum. BMC Evol. Biol. 19, 123 (2019).
Ryabov, E. V. et al. Dynamic evolution in the key honey bee pathogen deformed wing virus: novel insights into virulence and competition using reverse genetics. PLoS Biol. 17, e3000502 (2019).
Andras, J. P., Fields, P. D., Du Pasquier, L., Fredericksen, M. & Ebert, D. Genome-wide association analysis identifies a genetic basis of infectivity in a model bacterial pathogen. Mol. Biol. Evol. https://doi.org/10.1093/molbev/msaa173 (2020).
Brackney, D. E., Beane, J. E. & Ebel, G. D. RNAi targeting of West Nile virus in mosquito midguts promotes virus diversification. PLoS Pathog. 5, e1000502 (2009).
Brackney, D. E., Schirtzinger, E. E., Harrison, T. D., Ebel, G. D. & Hanley, K. A. Modulation of flavivirus population diversity by RNA interference. J. Virol. 89, 4035–4039 (2015).
Obbard, D. J., Jiggins, F. M., Halligan, D. L. & Little, T. J. Natural selection drives extremely rapid evolution in antiviral RNAi genes. Curr. Biol. 16, 580–585 (2006).
Araki, H. et al. Presence/absence polymorphism for alternative pathogenicity islands in Pseudomonas viridiflava, a pathogen of Arabidopsis. Proc. Natl Acad. Sci. USA 103, 5887–5892 (2006).
Nygaard, S. et al. Long- and short-term selective forces on malaria parasite genomes. PLoS Genet. 6, e1001099 (2010).
Ochola, L. I. et al. Allele frequency-based and polymorphism-versus-divergence indices of balancing selection in a new filtered set of polymorphic genes in plasmodium falciparum. Mol. Biol. Evol. 27, 2344–2351 (2010).
Salathe, M., Kouyos, R. D., Regoes, R. R. & Bonhoeffer, S. Rapid parasite adaptation drives selection for high recombination rates. Evolution 62, 295–300 (2008).
Gokhale, C. S., Papkou, A., Traulsen, A. & Schulenburg, H. Lotka–Volterra dynamics kills the Red Queen: population size fluctuations and associated stochasticity dramatically change host–parasite coevolution. BMC Evol. Biol. 13, 254 (2013).
Schenk, H., Schulenburg, H. & Traulsen, A. How long do Red Queen dynamics survive under genetic drift? A comparative analysis of evolutionary and eco-evolutionary models. BMC Evol. Biol. 20, 8 (2020).
MacPherson, A., Keeling, M. J. & Otto, S. P. Coevolution does not slow the rate of loss of heterozygosity in a stochastic host-parasite model with constant population size. bioRxiv https://doi.org/10.1101/2020.04.07.024661 (2020).
Thrall, P. H. & Burdon, J. J. Effect of resistance variation in a natural plant host–pathogen metapopulation on disease dynamics. Plant. Pathol. 49, 767–773 (2000).
Brown, J. K. M. & Tellier, A. Plant–parasite coevolution: bridging the gap between genetics and ecology. Annu. Rev. Phytopathol. 49, 345–367 (2011).
Radwan, J., Babik, W., Kaufman, J., Lenz, T. L. & Winternitz, J. Advances in the evolutionary understanding of MHC polymorphism. Trends Genet. 36, 298–311 (2020).
Charlesworth, B., Nordborg, M. & Charlesworth, D. The effects of local selection, balanced polymorphism and background selection on equilibrium patterns of genetic diversity in subdivided populations. Genet. Res. Camb. 70, 155–174 (1997).
Eizaguirre, C., Lenz, T. L., Kalbe, M. & Milinski, M. Divergent selection on locally adapted major histocompatibility complex immune genes experimentally proven in the field. Ecol. Lett. 15, 723–731 (2012).
Rico, Y. et al. Spatial patterns of immunogenetic and neutral variation underscore the conservation value of small, isolated American badger populations. Evol. Appl. 9, 1271–1284 (2016).
Jousimo, J. et al. Ecological and evolutionary effects of fragmentation on infectious disease dynamics. Science 344, 1289–1293 (2014).
Crispo, E. et al. The evolution of the major histocompatibility complex in upstream versus downstream river populations of the longnose dace. Ecol. Evol. 7, 3297–3311 (2017).
Keller, M. F. et al. Trans-ethnic meta-analysis of white blood cell phenotypes. Hum. Mol. Genet. 23, 6944–6960 (2014).
Morgan, A. D., Gandon, S. & Buckling, A. The effect of migration on local adaptation in a coevolving host–parasite system. Nature 437, 253–256 (2005).
Thrall, P. H. et al. Rapid genetic change underpins antagonistic coevolution in a natural host–pathogen metapopulation. Ecol. Lett. 15, 425–435 (2012).
Kawecki, T. J. & Ebert, D. Conceptual issues in local adaptation. Ecol. Lett. 7, 1225–1241 (2004).
Croll, D. & McDonald, B. A. The genetic basis of local adaptation for pathogenic fungi in agricultural ecosystems. Mol. Ecol. 26, 2027–2040 (2017).
Laine, A. L., Burdon, J. J., Dodds, P. N. & Thrall, P. H. Spatial variation in disease resistance: from molecules to metapopulations. J. Ecol. 99, 96–112 (2011).
Bolnick, D. I. & Stutz, W. E. Frequency dependence limits divergent evolution by favouring rare immigrants over residents. Nature 546, 285–288 (2017). This experimental study with fish shows that rare immigrants have an advantage over resident genotypes and demonstrates elegantly that resistance genes have higher effective migration rates.
Phillips, K. P. et al. Immunogenetic novelty confers a selective advantage in host–pathogen coevolution. Proc. Natl Acad. Sci. USA 115, 1552–1557 (2018).
Rico, Y., Morris-Pocock, J., Zigouris, J., Nocera, J. J. & Kyle, C. J. Lack of spatial immunogenetic structure among wolverine (Gulo gulo) populations suggestive of broad scale balancing selection. PLoS ONE 10, e0140170 (2015).
Leducq, J. B. et al. Effect of balancing selection on spatial genetic structure within populations: theoretical investigations on the self-incompatibility locus and empirical studies in Arabidopsis halleri. Heredity 106, 319–329 (2011).
Castric, V., Bechsgaard, J., Schierup, M. H. & Vekemans, X. Repeated adaptive introgression at a gene under multiallelic balancing selection. PLoS Genet. 4, e1000168 (2008).
Hoban, S. et al. Finding the genomic basis of local adaptation: pitfalls, practical solutions, and future directions. Am. Nat. 188, 379–397 (2016).
Borg, A. A., Pedersen, S. A., Jensen, H. & Westerdahl, H. Variation in MHC genotypes in two populations of house sparrow (Passer domesticus) with different population histories. Ecol. Evol. 1, 145–159 (2011).
Novembre, J. et al. Genes mirror geography within Europe. Nature 456, 98–101 (2008).
Fields, P. D., Reisser, C., Dukic, M., Haag, C. R. & Ebert, D. Genes mirror geography in Daphnia magna. Mol. Ecol. 24, 4521–4536 (2015).
Thompson, J. N. The Geographic Mosaic of Coevolution (Univ. of Chicago Press, 2005).
Laine, A. L., Barres, B., Numminen, E. & Siren, J. P. Variable opportunities for outcrossing result in hotspots of novel genetic variation in a pathogen metapopulation. eLife 8, e47091 (2019).
Klein, J. Immunology (Blackwell, 1990).
Lenz, T. L., Eizaguirre, C., Kalbe, M. & Milinski, M. Evaluating patterns of convergent evolution and trans-species polymorphism at MHC immunogenes in two sympatric stickleback species. Evolution 67, 2400–2412 (2013). This study demonstrates TSP in two sympatric stickleback fish sharing the same parasites. The authors were able to rule out convergent evolution as an alternative explanation for TSP.
Tesicky, M. & Vinkler, M. Trans-species polymorphism in immune genes: general pattern or MHC-restricted phenomenon? J. Immunol. Res. https://doi.org/10.1155/2015/838035 (2015).
Mboup, M., Fischer, I., Lainer, H. & Stephan, W. Trans-species polymorphism and allele-specific expression in the CBF gene family of wild tomatoes. Mol. Biol. Evol. 29, 3641–3652 (2012).
Novikova, P. Y. et al. Sequencing of the genus Arabidopsis identifies a complex history of nonbifurcating speciation and abundant trans-specific polymorphism. Nat. Genet. 48, 1077–1082 (2016).
Azevedo, L., Serrano, C., Amorim, A. & Cooper, D. N. Trans-species polymorphism in humans and the great apes is generally maintained by balancing selection that modulates the host immune response. Hum Genomics 9, 21 (2015).
Lenz, T. L. Computational prediction of MHC II–antigen binding supports divergent allele advantage and explains trans-species polymorphism. Evolution 65, 2380–2390 (2011).
Eizaguirre, C., Lenz, T. L., Kalbe, M. & Milinski, M. Rapid and adaptive evolution of MHC genes under parasite selection in experimental vertebrate populations. Nat. Commun. 3, 621 (2012).
Gao, Z. Y., Przeworski, M. & Sella, G. Footprints of ancient-balanced polymorphisms in genetic variation data from closely related species. Evolution 69, 431–446 (2015).
Hedrick, P. W. Pathogen resistance and genetic variation at MHC loci. Evolution 56, 1902–1908 (2002).
Eizaguirre, C. & Lenz, T. L. Major histocompatibility complex polymorphism: dynamics and consequences of parasite-mediated local adaptation in fishes. J. Fish. Biol. 77, 2023–2047 (2010).
Osborne, M. J., Pilger, T. J., Lusk, J. D. & Turner, T. F. Spatio-temporal variation in parasite communities maintains diversity at the major histocompatibility complex class II in the endangered Rio Grande silvery minnow. Mol. Ecol. 26, 471–489 (2017).
Daugherty, M. D. & Malik, H. S. Rules of engagement: molecular insights from host–virus arms races. Annu. Rev. Genet. 46, 677–700 (2012).
Cagliani, R. et al. A positively selected APOBEC3H haplotype is associated with natural resistance to HIV-1 infection. Evolution 65, 3311–3322 (2011).
Davis, Z. H. et al. Global mapping of herpesvirus–host protein complexes reveals a transcription strategy for late genes. Mol. Cell 57, 349–360 (2015).
Lozano-Torres, J. L. et al. Dual disease resistance mediated by the immune receptor Cf-2 in tomato requires a common virulence target of a fungus and a nematode. Proc. Natl Acad. Sci. USA 109, 10119–10124 (2012).
Wessling, R. et al. Convergent targeting of a common host protein-network by pathogen effectors from three kingdoms of life. Cell Host Microbe 16, 364–375 (2014).
Wegner, K. M., Kalbe, M., Kurtz, J., Reusch, T. B. H. & Milinski, M. Parasite selection for immunogenetic optimality. Science 301, 1343–1343 (2003).
Matzaraki, V., Kumar, V., Wijmenga, C. & Zhernakova, A. The MHC locus and genetic susceptibility to autoimmune and infectious diseases. Genome Biol. 18, 76 (2017).
Karasov, T. L., Barrett, L., Hershberg, R. & Bergelson, J. Similar levels of gene content variation observed for Pseudomonas syringae populations extracted from single and multiple host species. Plos ONE 12, e0184195 (2017).
Bechsgaard, J., Jorgensen, T. H. & Schierup, M. H. Evidence for adaptive introgression of disease resistance genes among closely related arabidopsis species. Genes Genomes Genet. 7, 2677–2683 (2017).
Gluck-Thaler, E. & Slot, J. C. Dimensions of horizontal gene transfer in eukaryotic microbial pathogens. PLoS Pathog. 11, e1005156 (2015).
Campbell, M. C., Ashong, B., Teng, S. L., Harvey, J. & Cross, C. N. Multiple selective sweeps of ancient polymorphisms in and around LT alpha located in the MHC class III region on chromosome 6. BMC Evol. Biol. 19, 218 (2019).
Karasov, T. L. et al. The long-term maintenance of a resistance polymorphism through diffuse interactions. Nature 512, 436–440 (2014).
Rabajante, J. F. et al. Red Queen dynamics in multi-host and multi-parasite interaction system. Sci. Rep. 5, 10004 (2015).
Kamath, P. L., Turner, W. C., Kusters, M. & Getz, W. M. Parasite-mediated selection drives an immunogenetic trade-off in plains zebras (Equus quagga). Proc. Biol. Sci. 281, 20140077 (2014).
Nadeem, A. & Wahl, L. M. Prophage as a genetic reservoir: promoting diversity and driving innovation in the host community. Evolution 71, 2080–2089 (2017).
Fortuna, M. A. et al. Coevolutionary dynamics shape the structure of bacteria–phage infection networks. Evolution 73, 1001–1011 (2019).
Silva, J. C. et al. Genome sequences reveal divergence times of malaria parasite lineages. Parasitology 138, 1737–1749 (2011).
Galen, S. C. et al. The polyphyly of Plasmodium: comprehensive phylogenetic analyses of the malaria parasites (order Haemosporida) reveal widespread taxonomic conflict. Roy. Soc. Open Sci. 5, 171780 (2018).
Otto, T. D. et al. Genomes of all known members of a Plasmodium subgenus reveal paths to virulent human malaria. Nat. Microbiol. 3, 687–697 (2018).
Pacheco, M. A. et al. Mode and rate of evolution of haemosporidian mitochondrial genomes: timing the radiation of avian parasites. Mol. Biol. Evol. 35, 383–403 (2018).
Bartha, I. et al. A genome-to-genome analysis of associations between human genetic variation, HIV-1 sequence diversity, and viral control. eLife 2, e01123 (2013). This study describes a pioneering method in co-genomics, applied to interacting genomic sites in hosts and parasites.
Lees, J. A., Tonkin-Hill, G. & Bentley, S. D. GENOME WATCH stronger together. Nat. Rev. Microbiol. 15, 516–516 (2017).
Märkle, H. & Tellier, A. Inference of coevolutionary dynamics and parameters from host and parasite polymorphism data of repeated experiments. PLoS Comput. Biol. 16, e1007668 (2020).
Otto, S. P. & Nuismer, S. L. Species interactions and the evolution of sex. Science 304, 1018–1020 (2004).
Tellier, A. & Brown, J. K. M. Polymorphism in multilocus host–parasite coevolutionary interactions. Genetics 177, 1777–1790 (2007).
Engelstadter, J. & Bonhoeffer, S. Red Queen dynamics with non-standard fitness interactions. PLoS Comput. Biol. 5, e1000469 (2009).
Best, A. et al. The evolution of host–parasite range. Am. Nat. 176, 63–71 (2010).
Fenton, A., Antonovics, J. & Brockhurst, M. A. Two-step infection processes can lead to coevolution between functionally independent infection and resistance pathways. Evolution 66, 2030–2041 (2012).
Kwiatkowski, M., Engelstadter, J. & Vorburger, C. On genetic specificity in symbiont-mediated host–parasite coevolution. PLoS Comput. Biol. 8, e1002633 (2012).
Flor, H. H. Host–parasite interaction in flax rust — its genetics and other implications. Phytopathology 45, 680–685 (1955).
Märkle, H., Tellier, A. & John, S. Cross-species association statistics for genome-wide studies of host and parasite polymorphism data. Preprint at bioRxiv https://doi.org/10.1101/726166 (2019).
Balmer, O. & Tanner, M. Prevalence and implications of multiple-strain infections. Lancet Infect. Dis. 11, 868–878 (2011).
Ansari, M. A. et al. Genome-to-genome analysis highlights the effect of the human innate and adaptive immune systems on the hepatitis C virus. Nat. Genet. 49, 666–673 (2017). This study describes a strong example of the application of co-genomics to find interacting loci in humans infected with hepatitis C virus.
Lees, J. A. et al. Joint sequencing of human and pathogen genomes reveals the genetics of pneumococcal meningitis. Nat. Commun. 10, 2176 (2019).
Naret, O. et al. Correcting for population stratification reduces false positive and false negative results in joint analyses of host and pathogen genomes. Front. Genet. 9, 266 (2018).
Ansari, M. A. et al. Interferon λ4 impacts the genetic diversity of hepatitis C virus. eLife 8, e42463 (2019).
McHenry, M. L. et al. Interaction between host genes and mycobacterium tuberculosis lineage can affect tuberculosis severity: evidence for coevolution? PLoS Genet. 16, e1008728 (2020).
Wang, M. Y. et al. Two-way mixed-effects methods for joint association analysis using both host and pathogen genomes. Proc. Natl Acad. Sci. USA 115, E5440–E5449 (2018). This study describes the development of a powerful co-genomics method that utilizes data from an interaction matrix of all combinations of host and parasite genotypes to find the genomic sites that underlie the interaction.
Hill, A. V. S., Jepson, A., Plebanski, M. & Gilbert, S. C. Genetic analysis of host–parasite coevolution in human malaria. Phil. Trans. R. Soc. Lond. B Biol. Sci. 352, 1317–1325 (1997).
Lacroix, R., Mukabana, W. R., Gouagna, L. C. & Koella, J. C. Malaria infection increases attractiveness of humans to mosquitoes. PLoS Biol. 3, e298 (2005).
Bonneaud, C. et al. Rapid evolution of disease resistance is accompanied by functional changes in gene expression in a wild bird. Proc. Natl Acad. Sci. USA 108, 7866–7871 (2011).
Bonneaud, C. et al. Rapid antagonistic coevolution in an emerging pathogen and its vertebrate host. Curr. Biol. 28, 2978–2983 (2018).
Tschirren, B. et al. Polymorphisms at the innate immune receptor TLR2 are associated with Borrelia infection in a wild rodent population. Proc. R. Soc. Lond B Biol Sci. 280, 20130364 (2013).
Heeney, J. L., Dalgleish, A. G. & Weiss, R. A. Origins of HIV and the evolution of resistance to AIDS. Science 313, 462–466 (2006).
Hertz, T. et al. Mapping the landscape of host–pathogen coevolution: HLA class I binding and its relationship with evolutionary conservation in human and viral proteins. J. Virol. 85, 1310–1321 (2011).
Schwander, T., Libbrecht, R. & Keller, L. Supergenes and complex phenotypes. Curr. Biol. 24, R288–R294 (2014).
Lenz, T. L. et al. Widespread non-additive and interaction effects within HLA loci modulate the risk of autoimmune diseases. Nat. Genet. 47, 1085–1090 (2015).
Salathe, M., Kouyos, R. D. & Bonhoeffer, S. The state of affairs in the kingdom of the Red Queen. Trends Ecol. Evol. 23, 439–445 (2008).
da Silva, J. & Galbraith, J. D. Hill–Robertson interference maintained by Red Queen dynamics favours the evolution of sex. J. evol. Biol. 30, 994–1010 (2017).
Kubinak, J. L. et al. Experimental viral evolution reveals major histocompatibility complex polymorphisms as the primary host factors controlling pathogen adaptation and virulence. Genes Immun. 14, 365–372 (2013).
Brockhurst, M. A. & Koskella, B. Experimental coevolution of species interactions. Trends Ecol. Evol. 28, 367–375 (2013).
Retel, C. et al. The feedback between selection and demography shapes genomic diversity during coevolution. Sci. Adv. 5, eaax0530 (2019).
Figueroa, F., Gúnther, E. & Klein, J. MHC polymorphism pre-dating speciation. Nature 335, 265–267 (1988).
Mcdonald, J. H. & Kreitman, M. Adaptive protein evolution at the Adh locus in Drosophila. Nature 351, 652–654 (1991).
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).
Nielsen, R. Molecular signatures of natural selection. Ann. Rev. Genet. 39, 197–218 (2005).
Siewert, K. M. & Voight, B. F. Detecting long-term balancing selection using allele frequency correlation. Mol. Biol. Evol. 34, 2996–3005 (2017).
Voight, B. F., Kudaravalli, S., Wen, X. & Pritchard, J. K. A map of recent positive selection in the human genome. PLoS Biol. 4, e72 (2006).
Messer, P. W. & Petrov, D. A. Population genomics of rapid adaptation by soft selective sweeps. Trends Ecol. Evol. 28, 659–669 (2013).
DeGiorgio, M., Lohmueller, K. E. & Nielsen, R. A model-based approach for identifying signatures of ancient balancing selection in genetic data. PLoS Genet. 10, e1004561 (2014).
Kim, Y. & Stephan, W. Detecting a local signature of genetic hitchhiking along a recombining chromosome. Genetics 160, 765–777 (2002).
Kim, Y. & Nielsen, R. Linkage disequilibrium as a signature of selective sweeps. Genetics 167, 1513 (2004).
DeGiorgio, M., Huber, C. D., Hubisz, M. J., Hellmann, I. & Nielsen, R. SweepFinder 2: increased sensitivity, robustness and flexibility. Bioinformatics 32, 1895–1897 (2016).
Pavlidis, P., Živković, D., Stamatakis, A. & Alachiotis, N. SweeD: likelihood-based detection of selective sweeps in thousands of genomes. Mol. Biol. Evol. 30, 2224–2234 (2013).
Alachiotis, N., Stamatakis, A. & Pavlidis, P. OmegaPlus: a scalable tool for rapid detection of selective sweeps in whole-genome datasets. Bioinformatics 28, 2274–2275 (2012).
Csilléry, K., Blum, M. G. B., Gaggiotti, O. E. & François, O. Approximate Bayesian computation (ABC) in practice. Trends Ecol. Evol. 25, 410–418 (2010).
Schrider, D. R. & Kern, A. D. Supervised machine learning for population genetics: a new paradigm. Trends Genet. 34, 301–312 (2018). This paper offers an accessible description of both present applications and possible future developments of supervised machine learning for understanding signatures of selection in genomic-scale data.
Raynal, L. et al. ABC random forests for Bayesian parameter inference. Bioinformatics 35, 1720–1728 (2018).
Rasmussen, M. D., Hubisz, M. J., Gronau, I. & Siepel, A. Genome-wide inference of ancestral recombination graphs. PLoS Genet. 10, e1004342 (2014).
Kelleher, J., Etheridge, A. M. & McVean, G. Efficient coalescent simulation and genealogical analysis for large sample sizes. PLOS Comput. Biol. 12, e1004842 (2016).
Haller, B. C., Galloway, J., Kelleher, J., Messer, P. W. & Ralph, P. L. Tree-sequence recording in SLiM opens new horizons for forward-time simulation of whole genomes. Mol. Ecol. Resour. 19, 552–566 (2019). This paper describes the implementation of tree-sequence recording into the already multifaceted and powerful SLiM simulation framework, and provides one of the most important schemes needed to model neutral and non-neutral dynamics on genome-scale data.
Hejase, H. A., Dukler, N. & Siepel, A. From summary statistics to gene trees: methods for inferring positive selection. Trends Genet. 36, 243–258 (2020). This paper is an exceptionally comprehensive review of both historical and present approaches for detecting forms of positive selection. Although the focus is on positive selection, many of the focal methodologies would, with some modification, be applicable for detecting the many signatures of host–parasite co-evolution.
The authors thank the Ebert laboratory for fruitful discussion and S. Zweizig for comments on the language of the manuscript. This work is supported by a grant from the Swiss National Science Foundation.
The authors declare no competing interests.
Peer review information
Nature Reviews Genetics thanks A. Tellier and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Organisms, including pathogens, that take advantage of other organisms (hosts), thereby instigating a process of selection by the host to defend against the parasite.
- Genomic signatures
Characteristic patterns of genetic variation, observed at a genomic region in a sample of genomes.
- Selective sweep
The spread of a beneficial mutant and the hitch-hiking of genetic variants close to it in the genome. Beneficial mutants may have arisen de novo or were segregating in the population before the sweep and become beneficial after a change in conditions.
- Balancing selection
Selection that occurs because the alleles involved have, on average, a selective advantage that correlates negatively with their frequency within a population or species. This term does not include loci that are at a balance between gaining and losing variants, such as mutation-drift and mutation-selection balance.
- Linked selection
The evolution of (nearly) neutral SNPs influenced by selection on loci physically linked to them.
- Genetic hitch-hiking
The process by which a genetic variant changes in frequency because it is physically linked to another variant that is changing in frequency due to selection.
The simultaneous analysis of the function, structure and evolution of pairs of associated genomes in closely interacting organisms, such as host and parasites.
The scenario in which heterozygotes have a more extreme phenotypic trait value than all homozygotes. Overdominance for fitness results in balancing selection for the alleles causing the advantage for the heterozygote genotypes.
- Local adaptation
If the effect of an allele is habitat-specific, such that it is beneficial in one habitat and detrimental in another, and vice versa for the alternative allele, local adaptation may evolve with directional selection within each population. Local adaption is a powerful mechanism to maintain genetic diversity within species.
- Direct negative frequency-dependent selection
The selective benefit of an allele depends directly and negatively on its frequency, for example at sex-determining loci and plant self-incompatibility loci.
- Indirect negative frequency-dependent selection
The selective benefit of an allele depends on the frequency of an allele in a co-evolving species.
- Selective interference
In clonal, but not in sexual, populations, beneficial mutations interfere with each other, such that at a given moment the fittest mutation will outcompete weaker beneficial mutations. Interference can also affect the spread of mutants in genomic regions with low recombination rates.
- Linkage disequilibrium
A statistical measure of the distribution of combinations of alleles at different loci, which is zero if this distribution follows the expectation based only on allele frequencies. Non-zero values of linkage disequilibrium can arise due to hitch-hiking, selection on allele combinations and stochastic processes, and may occur among loci without physical linkage.
- Selection coefficient
A measure of fitness of genotypes or alleles relative to a reference, such as the ancestral form.
- Tajima’s D
A population genetic summary statistic describing the frequency distribution of polymorphisms in a population, with D being zero under neutral evolution and positive under balancing selection.
- Genetic drift
A neutral evolutionary process that influences allele frequencies based on the random sampling of genetic variants during reproduction.
Random mating within a population.
- Fixation index
A measure of genetic differentiation of spatially structured populations, usually estimated from SNP or microsatellite data.
- Directional selection
A mode of natural selection by which a genetic variant is predicted to spread to fixation (also known as positive selection).
A group of tightly linked genes on a chromosome that are inherited together as a haplotype and often have reduced recombination.
- Functional guilds
Groups of organisms with similar lifestyle characteristics that perform the same ecological function, such as gut parasites, pollinators and filter-feeders.
Resistance genes of plants that convey resistance against diseases by producing R proteins.
- Approximate Bayesian computation
A Bayesian statistical approach wherein parameter inference and model selection are conducted in the absence of likelihood functions. Instead, approximate Bayesian computation relies on summary statistics and simulations to infer posterior distributions of parameters and/or models of interest.
- Likelihood function
The analytical formulation of a set of parameters that can be used to assess the fit of a given observed data set to a predetermined model.
- Supervised machine learning
Machine learning is a statistical methodology that uses artificial intelligence to automate inferential processes with minimal explicit instruction. Supervised machine learning is a type of machine learning that uses (labelled) training sets to generate a target function when the correspondence between the function of interest and the response variable is known. This target function can then be applied to unclassified (unlabelled) data to make statistical inferences.
- Ancestral recombination graph
(ARG). A genealogical or phylogenetic representation of the network of coalescence and recombination events in a collection of orthologous DNA sequences.
About this article
Cite this article
Ebert, D., Fields, P.D. Host–parasite co-evolution and its genomic signature. Nat Rev Genet 21, 754–768 (2020). https://doi.org/10.1038/s41576-020-0269-1
BMC Biology (2022)
Nature Reviews Immunology (2022)
Transcriptional response to host chemical cues underpins the expansion of host range in a fungal plant pathogen lineage
The ISME Journal (2022)
Co-structure analysis and genetic associations reveal insights into pinworms (Trypanoxyuris) and primates (Alouatta palliata) microevolutionary dynamics
BMC Ecology and Evolution (2021)
IMA Fungus (2021)