Fitness inference from short-read data: Within-host evolution of a reassortant H5N1 influenza virus

Molecular Biology and Evolution

Volumn 32, Issue 11, 2015, Pages 3012-3026

  Illingworth, Christopher J R ^a  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

fitness landscape; influenza; linkage disequilibrium; selection; within host evolution

Indexed keywords

ALLELE; ARTICLE; BINDING AFFINITY; EPISTASIS; FERRET; GENE FREQUENCY; GENE LINKAGE DISEQUILIBRIUM; GENE LOCUS; GENE SEQUENCE; GENETIC DATABASE; GENETIC REASSORTMENT; GLYCOSYLATION; HAPLOTYPE; INFLUENZA A VIRUS (H5N1); NATURAL SELECTION; NONHUMAN; RECEPTOR BINDING; VIROGENESIS; VIRUS CELL INTERACTION; VIRUS TRANSMISSION; ADAPTATION; ANIMAL; BIOLOGICAL MODEL; EVOLUTION; GENETIC SELECTION; GENETICS; HUMAN; INFLUENZA; MOLECULAR EVOLUTION; ORTHOMYXOVIRUS INFECTION; REPRODUCTIVE FITNESS; VIROLOGY;

INFLUENZA VIRUS HEMAGGLUTININ;

ADAPTATION, PHYSIOLOGICAL; ALLELES; ANIMALS; BIOLOGICAL EVOLUTION; EVOLUTION, MOLECULAR; FERRETS; GENETIC FITNESS; HEMAGGLUTININ GLYCOPROTEINS, INFLUENZA VIRUS; HUMANS; INFLUENZA A VIRUS, H5N1 SUBTYPE; INFLUENZA, HUMAN; LINKAGE DISEQUILIBRIUM; MODELS, GENETIC; ORTHOMYXOVIRIDAE INFECTIONS; REASSORTANT VIRUSES; SELECTION, GENETIC;

EID: 84946121204     PISSN: 07374038     EISSN: 15371719     Source Type: Journal    
DOI: 10.1093/molbev/msv171     Document Type: Article

References (50)

1. Acevedo A, Brodsky L, Andino R. 2014. Mutational and fitness landscapes of an RNA virus revealed through population sequencing. Nature 505:686-690.
2. Baccam P, Beauchemin C, Macken CA, Hayden FG, Perelson AS. 2006. Kinetics of influenza A virus infection in humans. J Virol. 80:7590-7599.
3. Beerenwinkel N, Sing T, Lengauer T, Rahnenfeuhrer J, Roomp K, Savenkov I, Fischer R, Hoffmann D, Selbig J, Korn K, et al. 2005. Computational methods for the design of effective therapies against drug resistant HIV strains. Bioinformatics 21:3943-3950.
4. Bush RM. 1999. Predicting the evolution of human influenza A. Science 286:1921-1925.
5. Casadevall A, Howard D, Imperiale MJ. 2014. An epistemological perspective on the value of gain-of-function experiments involving pathogens with pandemic potential. mBio 5:e01875-14.
6. Coombs D, Gilchrist MA, Ball CL. 2007. Evaluating the importance of within-And between-host selection pressures on the evolution of chronic pathogens. Theor Popul Biol. 72:576-591.
7. Cuevas JM, Domingo-Calap P, Sanjuan R. 2011. The fitness effects of synonymous mutations in DNA and RNA viruses. Mol Biol Evol. 29:17-20.
8. Das SR, Hensley SE, David A, Schmidt L, Gibbs JS, Puigb-o P, Ince WL, Bennink JR, Yewdell JW. 2011. Fitness costs limit influenza A virus hemagglutinin glycosylation as an immune evasion strategy. Proc Natl Acad Sci U S A. 108:20289-20290.
9. De Visser JAGM, Krug J. 2014. Empirical fitness landscapes and the predictability of evolution. Nat Rev Genet. 15:480-490.
10. Edgar RC. 2004. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32:1792-1797.
11. Eshaghi A, Duvvuri VR, Li A, Patel SN, Bastien N, Li Y, Low DE, Gubbay JB. 2013. Genetic characterization of seasonal influenza A (H3N2) viruses in Ontario during 2010-2011 influenza season: high prevalence of mutations at antigenic sites. Influenza Other Respir Viruses. 8:250-257.
12. Feder AF, Kryazhimskiy S, Plotkin JB. 2014. Identifying signatures of selection in genetic time series. Genetics 196:509-522.
13. Ferguson AL, Mann JK, Omarjee S, Ndung?u T, Walker BD, Chakraborty AK. 2013. Translating HIV sequences into quantitative fitness landscapes predicts viral vulnerabilities for rational immunogen design. Immunity 38:606-617.
14. Foll M, Poh Y, Renzette N, Ferrer-Admetlla A, Bank C, Shim H, Malaspinas A, Ewing G, Liu P, Wegmann D, et al. 2014. Influenza virus drug resistance: a time-sampled population genetics perspective. PLoS Genet. 10:e1004185.
15. Ganusov VV, Goonetilleke N, Liu MKP, Ferrari G, Shaw GM, McMichael AJ, Borrow P, Korber BT, Perelson AS. 2011. Fitness costs and diversity of the cytotoxic T lymphocyte (CTL) response determine the rate of CTL escape during acute and chronic phases of HIV infection. J Virol. 85:10518-10528.
16. Gong LI, Suchard MA, Bloom JD. 2013. Stability-mediated epistasis constrains the evolution of an influenza protein. eLife 2:e00631.
17. Hensley SE, Das SR, Gibbs JS, Bailey AL, Schmidt LM, Bennink JR, Yewdell JW, et al. 2009. Hemagglutinin receptor binding avidity drives influenza A virus antigenic drift. Science 326:734-736.
18. Herfst S, Schrauwen EJA, Linster M, Chutinimitkul S, de Wit E, Munster VJ, Sorrell EM, Bestebroer TM, Burke DF, Smith DJ, et al. 2012. Airborne transmission of influenza A/H5N1 virus between ferrets. Science 336:1534-1541.
19. Hill WG, Robertson A. 1966. The effect of linkage on limits to artificial selection. Genet Res. 8:269-294.
20. Hinkley T, Martins J, Chappey C, Haddad M, Stawiski E, Whitcomb JM, Petropoulos CJ, Bonhoeffer S. 2011. A systems analysis of mutational effects in HIV-1 protease and reverse transcriptase. Nat Genet. 43:487-489.
21. Illingworth CJ, Fischer A, Mustonen V. 2014. Identifying selection in the within-host evolution of influenza using viral sequence data. PLoS Comput Biol. 10:e1003755.
22. Illingworth CJ, Mustonen V. 2011. Distinguishing driver and passenger mutations in an evolutionary history categorized by interference. Genetics 189:989-1000.
23. Illingworth CJ, Mustonen V. 2012. A method to infer positive selection from marker dynamics in an asexual population. Bioinformatics 28:831-837.
24. Imai M, Watanabe T, Hatta M, Das SC, Ozawa, M, Shinya K, Zhong Z, Hanson A, Katsura H, Watanabe S, et al. 2012. Experimental adaptation of an influenza H5 HA confers respiratory droplet transmission to a reassortant H5 HA/H1N1 virus in ferrets. Nature 486(7403):420-428.
25. Kass RE, Raftery AE. 1995. Bayes factors. J Am Stat Assoc. 90:773-795.
26. Kessinger TA, Perelson AS, Neher RA. 2013. Inferring HIV escape rates from multi-locus genotype data. Front Immunol. 4:252.
27. Kryazhimskiy S, Bazykin GA, Dushoff J. 2008. Natural selection for nucleotide usage at synonymous and nonsynonymous sites in influenza A virus genes. J Virol. 82:4938-4945.
28. Kryazhimskiy S, Dushoff J, Bazykin GA, Plotkin JB. 2011. Prevalence of epistasis in the evolution of influenza A surface proteins. PLoS Genet. 7:e1001301.
29. Kryazhimskiy S, Rice DP, Jerison ER, Desai MM. 2014. Global epistasis makes adaptation predictable despite sequence-level stochasticity. Science 344:1519-1522.
30. Linster M, van Boheemen S, de Graaf M, Schrauwen EJA, Lexmond P, Meanz B, Bestebroer TM, Baumann J, van Riel D, Rimmelzwaan GF, et al. 2014. Identification, characterization, and natural selection of mutations driving airborne transmission of A/H5N1 virus. Cell 157:329-339.
31. Lipsitch M, Galvani AP. 2014. Ethical alternatives to experiments with novel potential pandemic pathogens. PLoS Med. 11:e1001646.
32. Luksza M, Leassig M. 2014. A predictive fitness model for influenza. Nature 507:57-61.
33. Marshall N, Priyamvada L, Ende Z, Steel J, Lowen AC. 2013. Influenza virus reassortment occurs with high frequency in the absence of segment mismatch. PLoS Pathog. 9:e1003421.
34. Matrosovich M, Tuzikov A, Bovin N, Gambaryan A, Klimov A, Castrucci MR, Donatelli I, Kawaoka Y. 2000. Early alterations of the receptorbinding properties of H1, H2, and H3 Avian influenza virus hemagglutinins after their introduction intomammals. J Virol. 74: 8502-8512.
35. Miralles R, Gerrish PJ, Moya A, Elena SF. 1999. Clonal interference and the evolution of RNA viruses. Science 285:1745-1747.
36. Morse SS, et al. 2012. Zoonoses 3: prediction and prevention of the next pandemic zoonosis. Lancet 380:1956-1965.
37. Murcia PR, Baillie GJ, Daly J, Elton D, Jervis C, Mumford JA, Newton R, Parrish CR, Hoelzer K, Dougan G, et al. 2010. Intra-And interhost evolutionary dynamics of equine influenza virus. J Virol. 84:6943-6954.
38. Murcia PR, Baillie GJ, Stack JC, Jervis C, Elton D, Mumford JA, Daly J, Kellam P, Grenfell BT, Holmes EC, et al. 2013. Evolution of equine influenza virus in vaccinated horses. J Virol. 87:4768-4771.
39. Mustonen V, Leassig M. 2009. From fitness landscapes to seascapes: non-equilibrium dynamics of selection and adaptation. Trends Genet. 25:111-119.
40. Neher RA, Russell CA, Shraiman BI. 2014. Predicting evolution from the shape of genealogical trees. eLife 3:e03568.
41. Russell CA, Fonville JM, Brown AEX, et al. 2012. The potential for respiratory droplet-Dransmissible A/H5N1 influenza virus to evolve in a mammalian host. Science 336:1541-1547.
42. Russell CA, Kasson PM, Donis RO, et al. 2014. Improving pandemic influenza risk assessment. eLife 3:e03883.
43. Sanjuan R, Nebot MR, Chirico N, Mansky LM, Belshaw R. 2010. Viral mutation rates. J Virol. 84:9733-9748.
44. Schwarz G. 1978. Estimating the dimension of a model. Annals Statistics 6:461-464.
45. Seifert D, Di Giallonardo F, Metzner KJ, Geunthard HF, Beerenwinkel N. 2015. A framework for inferring fitness landscapes of patient-derived viruses using quasispecies theory. Genetics 199(1):191-203.
46. Strelkowa N, Leassig M. 2012. Clonal interference in the evolution of influenza. Genetics 192:671-682.
47. Watson SJ, Welkers MRA, Depledge DP, Coulter E, Breuer JM, de Jong MD, Kellam P. 2013. Viral population analysis and minority-variant detection using short read next-generation sequencing. Philos Trans R Soc Lond B Biol Sci. 368:20120205-20120205.
48. Wilker PR, Dinis JM, Starrett G, et al. 2013. Selection on haemagglutinin imposes a bottleneck during mammalian transmission of reassortant H5N1 influenza viruses. Nat Commun. 4:1-11.
49. Wright S. 1932. The roles of mutation, inbreeding, crossbreeding, and selection in evolution. Proceedings of the Sixth International Congress of Genetics, 1:356-66.
50. Wylie CS, Shakhnovich EI. 2011. A biophysical protein folding model accounts for most mutational fitness effects in viruses. Proc Natl Acad Sci U S A. 108:9916-9921.