39 research outputs found

    Social interactions modulate the virulence of avian malaria infection

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    There is an increasing understanding of the context-dependent nature of parasite virulence. Variation in parasite virulence can occur when infected individuals compete with conspecifics that vary in infection status; virulence may be higher when competing with uninfected competitors. In vertebrates with social hierarchies, we propose that these competition-mediated costs of infection may also vary with social status. Dominant individuals have greater competitive ability than competing subordinates, and consequently may pay a lower prevalence-mediated cost of infection. In this study we investigated whether costs of malarial infection were affected by the occurrence of the parasite in competitors and social status in domestic canaries (Serinus canaria). We predicted that infected subordinates competing with non-infected dominants would pay higher costs than infected subordinates competing with infected dominants. We also predicted that these occurrence-mediated costs of infection would be ameliorated in infected dominant birds. We found that social status and the occurrence of parasites in competitors significantly interacted to change haematocrit in infected birds. Namely, subordinate and dominant infected birds differed in haematocrit depending on the infection status of their competitors. However, in contrast to our prediction, dominants fared better with infected subordinates, whereas subordinates fared better with uninfected dominants. Moreover, we found additional effects of parasite occurrence on mortality in canaries. Ultimately, we provide evidence for costs of parasitism mediated by social rank and the occurrence of parasites in competitors in a vertebrate species. This has important implications for our understanding of the evolutionary processes that shape parasite virulence and group living

    Cancer, Warts, or Asymptomatic Infections: Clinical Presentation Matches Codon Usage Preferences in Human Papillomaviruses

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    Viruses rely completely on the hosts' machinery for translation of viral transcripts. However, for most viruses infecting humans, codon usage preferences (CUPrefs) do not match those of the host. Human papillomaviruses (HPVs) are a showcase to tackle this paradox: they present a large genotypic diversity and a broad range of phenotypic presentations, from asymptomatic infections to productive lesions and cancer. By applying phylogenetic inference and dimensionality reduction methods, we demonstrate first that genes in HPVs are poorly adapted to the average human CUPrefs, the only exception being capsid genes in viruses causing productive lesions. Phylogenetic relationships between HPVs explained only a small proportion of CUPrefs variation. Instead, the most important explanatory factor for viral CUPrefs was infection phenotype, as orthologous genes in viruses with similar clinical presentation displayed similar CUPrefs. Moreover, viral genes with similar spatiotemporal expression patterns also showed similar CUPrefs. Our results suggest that CUPrefs in HPVs reflect either variations in the mutation bias or differential selection pressures depending on the clinical presentation and expression timing. We propose that poor viral CUPrefs may be central to a trade-off between strong viral gene expression and the potential for eliciting protective immune response

    Evolutionary Changes after Translational Challenges Imposed by Horizontal Gene Transfer

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    Genes acquired by horizontal gene transfer (HGT) may provide the recipient organism with potentially new functions, but proper expression level and integration of the transferred genes in the novel environment are not granted. Notably, transferred genes can differ from the receiving genome in codon usage preferences, leading to impaired translation and reduced functionality. Here, we characterize the genomic and proteomic changes undergone during experimental evolution of Escherichia coli after HGT of three synonymous versions, presenting very different codon usage preference, of an antibiotic resistance gene. The experimental evolution was conducted with and without the corresponding antibiotic and the mutational patterns and proteomic profiles after 1,000 generations largely depend on the experimental growth conditions (e.g., mutations in antibiotic off-target genes), and on the synonymous gene version transferred (e.g., mutations in genes responsive to translational stress). The transfer of an exogenous gene extensively modifies the whole proteome, and these proteomic changes are different for the different version of the transferred gene. Additionally, we identified conspicuous changes in global regulators and in intermediate metabolism, confirmed the evolutionary ratchet generated by mutations in DNA repair genes and highlighted the plasticity of bacterial genomes accumulating large and occasionally transient duplications. Our results support a central role of HGT in fuelling evolution as a powerful mechanism promoting rapid, often dramatic genotypic and phenotypic changes. The profound reshaping of the pre-existing geno/phenotype allows the recipient bacteria to explore new ways of functioning, far beyond the mere acquisition of a novel function

    Virus Infection Suppresses Nicotiana benthamiana Adaptive Phenotypic Plasticity

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    Competition and parasitism are two important selective forces that shape life-histories, migration rates and population dynamics. Recently, it has been shown in various pathosystems that parasites can modify intraspecific competition, thus generating an indirect cost of parasitism. Here, we investigated if this phenomenon was present in a plant-potyvirus system using two viruses of different virulence (Tobacco etch virus and Turnip mosaic virus). Moreover, we asked if parasitism interacted with the shade avoidance syndrome, the plant-specific phenotypic plasticity in response to intraspecific competition. Our results indicate that the modification of intraspecific competition by parasitism is not present in the Nicotiana benthamiana – potyvirus system and suggests that this phenomenon is not universal but depends on the peculiarities of each pathosystem. However, whereas the healthy N. benthamiana presented a clear shade avoidance syndrome, this phenotypic plasticity totally disappeared when the plants were infected with TEV and TuMV, very likely resulting in a fitness loss and being another form of indirect cost of parasitism. This result suggests that the suppression or the alteration of adaptive phenotypic plasticity might be a component of virulence that is often overlooked

    Reproductive Behaviour Evolves Rapidly When Intralocus Sexual Conflict Is Removed

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    Background Intralocus sexual conflict can inhibit the evolution of each sex towards its own fitness optimum. In a previous study, we confirmed this prediction through the experimental removal of female selection pressures in Drosophila melanogaster, achieved by limiting the expression of all major chromosomes to males. Compared to the control populations (C1-4) where the genomes are exposed to selection in both sexes, the populations with male-limited genomes (ML1-4) showed rapid increases in male fitness, whereas the fitness of females expressing ML-evolved chromosomes decreased [1]. Methodology/Principal Findings Here we examine the behavioural phenotype underlying this sexual antagonism. We show that males expressing the ML genomes have a reduced courtship level but acquire the same number of matings. On the other hand, our data suggest that females expressing the ML genomes had reduced attractiveness, stimulating a lower rate of courtship from males. Moreover, females expressing ML genomes tend to display reduced yeast-feeding behaviour, which is probably linked to the reduction of their fecundity. Conclusion/Significance These results suggest that reproductive behaviour is shaped by opposing selection on males and females, and that loci influencing attractiveness and foraging were polymorphic for alleles with sexually antagonistic expression patterns prior to ML selection. Hence, intralocus sexual conflict appears to play a role in the evolution of a wide range of fitness-related traits and may be a powerful mechanism for the maintenance of genetic variation in fitness

    Assessing parallel gene histories in viral genomes

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    Background: The increasing abundance of sequence data has exacerbated a long known problem: gene trees and species trees for the same terminal taxa are often incongruent. Indeed, genes within a genome have not all followed the same evolutionary path due to events such as incomplete lineage sorting, horizontal gene transfer, gene duplication and deletion, or recombination. Considering conflicts between gene trees as an obstacle, numerous methods have been developed to deal with these incongruences and to reconstruct consensus evolutionary histories of species despite the heterogeneity in the history of their genes. However, inconsistencies can also be seen as a source of information about the specific evolutionary processes that have shaped genomes. Results: The goal of the approach here proposed is to exploit this conflicting information: we have compiled eleven variables describing phylogenetic relationships and evolutionary pressures and submitted them to dimensionality reduction techniques to identify genes with similar evolutionary histories. To illustrate the applicability of the method, we have chosen two viral datasets, namely papillomaviruses and Turnip mosaic virus (TuMV) isolates, largely dissimilar in genome, evolutionary distance and biology. Our method pinpoints viral genes with common evolutionary patterns. In the case of papillomaviruses, gene clusters match well our knowledge on viral biology and life cycle, illustrating the potential of our approach. For the less known TuMV, our results trigger new hypotheses about viral evolution and gene interaction. Conclusions: The approach here presented allows turning phylogenetic inconsistencies into evolutionary information, detecting gene assemblies with similar histories, and could be a powerful tool for comparative pathogenomics.IGB was funded by the disappeared Spanish Ministry for Science and Innovation (CGL2010-16713). Work in Valencia was supported by grant BFU2012-30805 from the Spanish Ministry of Economy and Competitiveness (MINECO) to SFE. BMC is the recipient of an IDIBELL PhD fellowship.Mengual-Chuliá, B.; Bedhomme, S.; Lafforgue, G.; Elena Fito, SF.; Bravo, IG. (2016). Assessing parallel gene histories in viral genomes. BMC Evolutionary Biology. 16:1-15. https://doi.org/10.1186/s12862-016-0605-4S11516Hess J, Goldman N. Addressing inter-gene heterogeneity in maximum likelihood phylogenomic analysis: Yeasts revisited. PLoS ONE. 2011;6:e22783.Salichos L, Rokas A. Inferring ancient divergences requires genes with strong phylogenetic signals. Nature. 2013;497:327–31.Zhong B, Liu L, Yan Z, Penny D. Origin of land plants using the multispecies coalescent model. Trends Plant Sci. 2013;18:492–5.Song S, Liu L, Edwards SV, Wu S. Resolving conflict in eutherian mammal phylogeny using phylogenomics and the multispecies coalescent model. Proc Natl Acad Sci U S A. 2012;109:14942–7.Nichols R. Gene trees and species trees are not the same. Trends Ecol Evol. 2001;16:358–64.Maddison WP. Gene trees in species trees. Syst Biol. 1997;46:523–36.Suh A, Smeds L, Ellegren H. The dynamics of incomplete lineage sorting across the ancient adaptive radiation of neoavian birds. PLoS Biol. 2015;13:e1002224.McBreen K, Lockhart PJ. Reconstructing reticulate evolutionary histories of plants. Trends Plant Sci. 2006;11:398–404.Dagan T, Martin W. The tree of one percent. Genome Biol. 2006;7:118.Beiko RG, Harlow TJ, Ragan MA. Highways of gene sharing in prokaryotes. Proc Natl Acad Sci U S A. 2005;102:14332–7.Cotton JA, Page RD. Going nuclear: Gene family evolution and vertebrate phylogeny reconciled. Proc Biol Sci. 2002;269:1555–61.Kuhner MK, Yamato J. Practical performance of tree comparison metrics. Syst Biol. 2015;64:205–14.Brochier C, Bapteste E, Moreira D, Philippe H. Eubacterial phylogeny based on translational apparatus proteins. Trends Genet. 2002;18:1–5.Bapteste E, Susko E, Leigh J, MacLeod D, Charlebois RL, Doolittle WF. Do orthologous gene phylogenies really support tree-thinking? BMC Evol Biol. 2005;5:33.Leigh JW, Susko E, Baumgartner M, Roger AJ. Testing congruence in phylogenomic analysis. Syst Biol. 2008;57:104–15.Leigh JW, Schliep K, Lopez P, Bapteste E. Let them fall where they may: Congruence analysis in massive phylogenetically messy data sets. Mol Biol Evol. 2011;28:2773–85.de Vienne DM, Ollier S, Aguileta G. Phylo-mcoa: A fast and efficient method to detect outlier genes and species in phylogenomics using multiple co-inertia analysis. Mol Biol Evol. 2012;29:1587–98.Wang S, Luo X, Wei W, Zheng Y, Dou Y, Cai X. Calculation of evolutionary correlation between individual genes and full-length genome: A method useful for choosing phylogenetic markers for molecular epidemiology. PLoS ONE. 2013;8:e81106.Salichos L, Stamatakis A, Rokas A. Novel information theory-based measures for quantifying incongruence among phylogenetic trees. Mol Biol Evol. 2014;31:1261–71.Weyenberg G, Huggins PM, Schardl CL, Howe DK, Yoshida R. Kdetrees: Non-parametric estimation of phylogenetic tree distributions. Bioinformatics. 2014;30:2280–7.de Queiroz A. For consensus (sometimes). Syst Biol. 1993;42:368–72.Miyamoto MM, Fitch WM. Testing the covarion hypothesis of molecular evolution. Mol Biol Evol. 1995;12:503–13.Sanderson MJ, Purvis A, Henze C. Phylogenetic supertrees: Assembling the trees of life. Trends Ecol Evol. 1998;13:105–9.Bininda-Emonds ORP. Phylogenetic supertrees: Combining information to reveal the tree of life. Comput Biol. Dordrecht (The Netherlands): Kluwer Academic Publishers; 2004.Creevey CJ, Fitzpatrick DA, Philip GK, Kinsella RJ, O’Connell MJ, Pentony MM, et al. Does a tree-like phylogeny only exist at the tips in the prokaryotes? Proc Biol Sci. 2004;271:2551–8.Pisani D, Cotton JA, McInerney JO. Supertrees disentangle the chimerical origin of eukaryotic genomes. Mol Biol Evol. 2007;24:1752–60.Ane C, Larget B, Baum DA, Smith SD, Rokas A. Bayesian estimation of concordance among gene trees. Mol Biol Evol. 2007;24:412–26.Gordon AD. A measure of the agreement between rankings. Biometrika. 1979;66:7–15.de Vienne DM, Giraud T, Martin OC. A congruence index for testing topological similarity between trees. Bioinformatics. 2007;23:3119–24.Suchard MA, Weiss RE, Sinsheimer JS, Dorman KS, Patel M, McCabe ERB. Evolutionary similarity among genes. J Am Stat Assoc. 2003;98:653–62.Edwards SV, Liu L, Pearl DK. High-resolution species trees without concatenation. Proc Natl Acad Sci U S A. 2007;104:5936–41.Liu L, Pearl DK. Species trees from gene trees: Reconstructing bayesian posterior distributions of a species phylogeny using estimated gene tree distributions. Syst Biol. 2007;56:504–14.Liu L, Pearl DK, Brumfield RT, Edwards SV. Estimating species trees using multiple-allele DNA sequence data. Evolution. 2008;62:2080–91.Levasseur C, Lapointe FJ. War and peace in phylogenetics: A rejoinder on total evidence and consensus. Syst Biol. 2001;50:881–91.de Queiroz A, Gatesy J. The supermatrix approach to systematics. Trends Ecol Evol. 2007;22:34–41.Huson DH, Bryant D. Application of phylogenetic networks in evolutionary studies. Mol Biol Evol. 2006;23:254–67.Layeghifard M, Peres-Neto PR, Makarenkov V. Inferring explicit weighted consensus networks to represent alternative evolutionary histories. BMC Evol Biol. 2013;13:274.Stockham C, Wang LS, Warnow T. Statistically based postprocessing of phylogenetic analysis by clustering. Bioinformatics. 2002;18 Suppl 1:S285–93.Bonnard C, Berry V, Lartillot N. Multipolar consensus for phylogenetic trees. Syst Biol. 2006;55:837–43.Guenoche A. Multiple consensus trees: A method to separate divergent genes. BMC Bioinformatics. 2013;14:46.Duggal R, Cuconati A, Gromeier M, Wimmer E. Genetic recombination of poliovirus in a cell-free system. Proc Natl Acad Sci U S A. 1997;94:13786–91.Reiter J, Perez-Vilaro G, Scheller N, Mina LB, Diez J, Meyerhans A. Hepatitis c virus rna recombination in cell culture. J Hepatol. 2011;55:777–83.Desbiez C, Lecoq H. Evidence for multiple intraspecific recombinants in natural populations of watermelon mosaic virus (wmv, potyvirus). Arch Virol. 2008;153:1749–54.Larsen RC, Miklas PN, Druffel KL, Wyatt SD. Nl-3 k strain is a stable and naturally occurring interspecific recombinant derived from bean common mosaic necrosis virus and bean common mosaic virus. Phytopathology. 2005;95:1037–42.Valli A, Lopez-Moya JJ, Garcia JA. Recombination and gene duplication in the evolutionary diversification of p1 proteins in the family potyviridae. J Gen Virol. 2007;88:1016–28.Gottschling M, Bravo IG, Schulz E, Bracho MA, Deaville R, Jepson PD, et al. Modular organizations of novel cetacean papillomaviruses. Mol Phylogenet Evol. 2011;59:34–42.Woolford L, Rector A, Van Ranst M, Ducki A, Bennett MD, Nicholls PK, et al. A novel virus detected in papillomas and carcinomas of the endangered western barred bandicoot (perameles bougainville) exhibits genomic features of both the papillomaviridae and polyomaviridae. J Virol. 2007;81:13280–90.Chen X, Zhang Q, He C, Zhang L, Li J, Zhang W, et al. Recombination and natural selection in hepatitis e virus genotypes. J Med Virol. 2012;84:1396–407.Cadar D, Csagola A, Kiss T, Tuboly T. Capsid protein evolution and comparative phylogeny of novel porcine parvoviruses. Mol Phylogenet Evol. 2013;66:243–53.Smith LM, McWhorter AR, Shellam GR, Redwood AJ. The genome of murine cytomegalovirus is shaped by purifying selection and extensive recombination. Virology. 2013;435:258–68.Münk C, Willemsen A, Bravo IG. An ancient history of gene duplications, fusions and losses in the evolution of apobec3 mutators in mammals. BMC Evol Biol. 2012;12:71.Daugherty MD, Malik HS. Rules of engagement: Molecular insights from host-virus arms races. Annu Rev Genet. 2012;46:677–700.Edgar RC. Muscle: Multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004;32:1792–7.Castresana J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol Biol Evol. 2000;17:540–52.Stamatakis A, Ludwig T, Meier H. Raxml-iii: A fast program for maximum likelihood-based inference of large phylogenetic trees. Bioinformatics. 2005;21:456–63.Soria-Carrasco V, Talavera G, Igea J, Castresana J. The k tree score: Quantification of differences in the relative branch length and topology of phylogenetic trees. Bioinformatics. 2007;23:2954–6.Stern A, Doron-Faigenboim A, Erez E, Martz E, Bacharach E, Pupko T. Selecton 2007: Advanced models for detecting positive and purifying selection using a bayesian inference approach. Nucleic Acids Res. 2007;35:W506–11.Doron-Faigenboim A, Pupko T. A combined empirical and mechanistic codon model. Mol Biol Evol. 2007;24:388–97.Swanson WJ, Nielsen R, Yang Q. Pervasive adaptive evolution in mammalian fertilization proteins. Mol Biol Evol. 2003;20:18–20.Shukla DD, Ward CW, Brunt AA. The potyviridae. Wallingford (UK): CABI; 1994.Chung BY, Miller WA, Atkins JF, Firth AE. An overlapping essential gene in the potyviridae. Proc Natl Acad Sci U S A. 2008;105:5897–902.Tan Z, Wada Y, Chen J, Ohshima K. Inter- and intralineage recombinants are common in natural populations of turnip mosaic virus. J Gen Virol. 2004;85:2683–96.Bravo IG, de Sanjose S, Gottschling M. The clinical importance of understanding the evolution of papillomaviruses. Trends Microbiol. 2010;18:432–8.Klingelhutz AJ, Roman A. Cellular transformation by human papillomaviruses: Lessons learned by comparing high- and low-risk viruses. Virology. 2012;424:77–98.Bravo IG, Alonso A. Mucosal human papillomaviruses encode four different e5 proteins whose chemistry and phylogeny correlate with malignant or benign growth. J Virol. 2004;78:13613–26.Garcia-Vallve S, Alonso A, Bravo IG. Papillomaviruses: Different genes have different histories. Trends Microbiol. 2005;13:514–21.Bravo IG, Felez-Sanchez M. Papillomaviruses: Viral evolution, cancer and evolutionary medicine. Evol Med Public Health. 2015;2015:32–51.Aleman-Verdaguer ME, Goudou-Urbino C, Dubern J, Beachy RN, Fauquet C. Analysis of the sequence diversity of the p1, hc, p3, nib and cp genomic regions of several yam mosaic potyvirus isolates: Implications for the intraspecies molecular diversity of potyviruses. J Gen Virol. 1997;78(Pt 6):1253–64.Sakai J, Mori M, Morishita T, Tanaka M, Hanada K, Usugi T, et al. Complete nucleotide sequence and genome organization of sweet potato feathery mottle virus (s strain) genomic rna: The large coding region of the p1 gene. Arch Virol. 1997;142:1553–62.Tordo VM, Chachulska AM, Fakhfakh H, Le Romancer M, Robaglia C, Astier-Manifacier S. Sequence polymorphism in the 5’ntr and in the p1 coding region of potato virus y genomic rna. J Gen Virol. 1995;76(Pt 4):939–49.Verchot J, Carrington JC. Evidence that the potyvirus p1 proteinase functions in trans as an accessory factor for genome amplification. J Virol. 1995;69:3668–74.Salvador B, Saenz P, Yanguez E, Quiot JB, Quiot L, Delgadillo MO, et al. Host-specific effect of p1 exchange between two potyviruses. Mol Plant Pathol. 2008;9:147–55.Desbiez C, Lecoq H. The nucleotide sequence of watermelon mosaic virus (wmv, potyvirus) reveals interspecific recombination between two related potyviruses in the 5’ part of the genome. Arch Virol. 2004;149:1619–32.Majer E, Salvador Z, Zwart MP, Willemsen A, Elena SF, Daros JA. Relocation of the nib gene in the tobacco etch potyvirus genome. J Virol. 2014;88:4586–90.Pasin F, Simon-Mateo C, Garcia JA. The hypervariable amino-terminus of p1 protease modulates potyviral replication and host defense responses. PLoS Pathog. 2014;10:e1003985.Lopez-Lastra M, Rivas A, Barria MI. Protein synthesis in eukaryotes: The growing biological relevance of cap-independent translation initiation. Biol Res. 2005;38:121–46.Kang ST, Wang HC, Yang YT, Kou GH, Lo CF. The DNA virus white spot syndrome virus uses an internal ribosome entry site for translation of the highly expressed nonstructural protein icp35. J Virol. 2013;87:13263–78.Dolja VV, Haldeman-Cahill R, Montgomery AE, Vandenbosch KA, Carrington JC. Capsid protein determinants involved in cell-to-cell and long distance movement of tobacco etch potyvirus. Virology. 1995;206:1007–16.Carrington JC, Jensen PE, Schaad MC. Genetic evidence for an essential role for potyvirus ci protein in cell-to-cell movement. Plant J. 1998;14:393–400.Wei T, Zhang C, Hong J, Xiong R, Kasschau KD, Zhou X, et al. Formation of complexes at plasmodesmata for potyvirus intercellular movement is mediated by the viral protein p3n-pipo. PLoS Pathog. 2010;6:e1000962.Felez-Sanchez M, Trosemeier JH, Bedhomme S, Gonzalez-Bravo MI, Kamp C, Bravo IG. Cancer, warts, or asymptomatic infections: Clinical presentation matches codon usage preferences in human papillomaviruses. Genome Biol Evol. 2015;7:2117–35.Doorbar J, Gallimore PH. Identification of proteins encoded by the l1 and l2 open reading frames of human papillomavirus 1a. J Virol. 1987;61:2793–9.Hughes FJ, Romanos MA. E1 protein of human papillomavirus is a DNA helicase/atpase. Nucleic Acids Res. 1993;21:5817–23.Sarafi TR, McBride AA. Domains of the bpv-1 e1 replication protein required for origin-specific DNA binding and interaction with the e2 transactivator. Virology. 1995;211:385–96.Chen G, Stenlund A. Characterization of the DNA-binding domain of the bovine papillomavirus replication initiator e1. J Virol. 1998;72:2567–76.McBride AA. Replication and partitioning of papillomavirus genomes. Adv Virus Res. 2008;72:155–205.McBride A, Myers G. The e2 proteins: An update. In: Laboratory HPLAN. Los Alamos: Myers, G., and coworkers; 1997. p. III54–99.Kirnbauer R, Booy F, Cheng N, Lowy DR, Schiller JT. Papillomavirus l1 major capsid protein self-assembles into virus-like particles that are highly immunogenic. Proc Natl Acad Sci U S A. 1992;89:12180–4.Penrose KJ, McBride AA. Proteasome-mediated degradation of the papillomavirus e2-ta protein is regulated by phosphorylation and can modulate viral genome copy number. J Virol. 2000;74:6031–8.Poddar A, Reed SC, McPhillips MG, Spindler JE, McBride AA. The human papillomavirus type 8 e2 tethering protein targets the ribosomal DNA loci of host mitotic chromosomes. J Virol. 2009;83:640–50.Lai MC, Teh BH, Tarn WY. A human papillomavirus e2 transcriptional activator. The interactions with cellular splicing factors and potential function in pre-mrna processing. J Biol Chem. 1999;274:11832–41.Zou N, Lin BY, Duan F, Lee KY, Jin G, Guan R, et al. The hinge of the human papillomavirus type 11 e2 protein contains major determinants for nuclear localization and nuclear matrix association. J Virol. 2000;74:3761–70.Steger G, Schnabel C, Schmidt HM. The hinge region of the human papillomavirus type 8 e2 protein activates the human p21(waf1/cip1) promoter via interaction with sp1. J Gen Virol. 2002;83:503–10.Hughes AL, Hughes MA. Patterns of nucleotide difference in overlapping and non-overlapping reading frames of papillomavirus genomes. Virus Res. 2005;113:81–8.Ahola H, Bergman P, Strom AC, Moreno-Lopez J, Pettersson U. Organization and expression of the transforming region from the european elk papillomavirus (eepv). Gene. 1986;50:195–205.Chen Z, Schiffman M, Herrero R, Desalle R, Burk RD. Human papillomavirus (hpv) types 101 and 103 isolated from cervicovaginal cells lack an e6 open reading frame (orf) and are related to gamma-papillomaviruses. Virology. 2007;360:447–53.Nobre RJ, Herraez-Hernandez E, Fei JW, Langbein L, Kaden S, Grone HJ, et al. E7 oncoprotein of novel human papillomavirus type 108 lacking the e6 gene induces dysplasia in organotypic keratinocyte cultures. J Virol. 2009;83:2907–16.Stevens H, Rector A, Bertelsen MF, Leifsson PS, Van Ranst M. Novel papillomavirus isolated from the oral mucosa of a polar bear does not cluster with other papillomaviruses of carnivores. Vet Microbiol. 2008;129:108–16.Stevens H, Rector A, Van Der Kroght K, Van Ranst M. Isolation and cloning of two variant papillomaviruses from domestic pigs: Sus scrofa papillomaviruses type 1 variants a and b. J Gen Virol. 2008;89:2475–81.Dyson N, Howley PM, Munger K, Harlow E. The human papilloma virus-16 e7 oncoprotein is able to bind to the retinoblastoma gene product. Science. 1989;243:934–7.Werness BA, Levine AJ, Howley PM. Association of human papillomavirus types 16 and 18 e6 proteins with p53. Science. 1990;248:76–9.Huibregtse JM, Scheffner M, Howley PM. A cellular protein mediates association of p53 with the e6 oncoprotein of human papillomavirus types 16 or 18. EMBO J. 1991;10:4129–35.Hartley KA, Alexander KA. Human tata binding protein inhibits human papillomavirus type 11 DNA replication by antagonizing e1-e2 protein complex formation on the viral origin of replication. J Virol. 2002;76:5014–23.Ilves I, Kadaja M, Ustav M. Two separate replication modes of the bovine papillomavirus bpv1 origin of replication that have different sensitivity to p53. Virus Res. 2003;96:75–84.Narahari J, Fisk JC, Melendy T, Roman A. Interactions of the cellular ccaat displacement protein and human papillomavirus e2 protein with the viral origin of replication can regulate DNA replication. Virology. 2006;350:302–11.Barrow-Laing L, Chen W, Roman A. Low- and high-risk human papillomavirus e7 proteins regulate p130 differently. Virology. 2010;400:233–9.White EA, Sowa ME, Tan MJ, Jeudy S, Hayes SD, Santha S, et al. Systematic identification of interactions between host cell proteins and e7 oncoproteins from diverse human papillomaviruses. Proc Natl Acad Sci U S A. 2012;109:E260–7.Nomine Y, Masson M, Charbonnier S, Zanier K, Ristriani T, Deryckere F, et al. Structural and functional analysis of e6 oncoprotein: Insights in the molecular pathways of human papillomavirus-mediated pathogenesis. Mol Cell. 2006;21:665–78.Zanier K, ould M’hamed ould Sidi A, Boulade-Ladame C, Rybin V, Chappelle A, Atkinson A, et al. Solution structure analysis of the hpv16 e6 oncoprotein reveals a self-association mechanism required for e6-mediated degradation of p53. Structure. 2012;20:604–17.Briddon RW, Patil BL, Bagewadi B, Nawaz-ul-Rehman MS, Fauquet CM. Distinct evolutionary histories of the DNA-a and DNA-b components of bipartite begomoviruses. BMC Evol Biol. 2010;10:97.Chen JM, Sun YX, Chen JW, Liu S, Yu JM, Shen CJ, et al. Panorama phylogenetic diversity and distribution of type a influenza viruses based on their six internal gene sequences. J Virol. 2009;6:137

    Experimental test of the conditions of maintenance of polymorphism under hard and soft selection.

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    International audienceA recommendation of: Gallet R, Froissart R, Ravigné V. 2017. Things softly attained are long retained: dissecting the impacts of selection regimes on polymorphism maintenance in experimental spatially heterogeneous environments. bioRxiv 100743; doi: 10.1101/10074

    Identification of a gene cluster amplification associated with organophosphate insecticide resistance: from the diversity of the resistance allele complex to an efficient field detection assay

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    A recommendation – based on reviews by Diego Ayala and two anonymous reviewers – of the article: Cattel, J., Haberkorn, C., Laporte, F., Gaude, T., Cumer, T., Renaud, J., Sutherland, I. W., Hertz, J. C., Bonneville, J.-B., Arnaud, V., Noûs, C., Fustec, B., Boyer, S., Marcombe, S., and David, J.-P. (2020) A genomic amplification affecting a carboxylesterase gene cluster confers organophosphate resistance in the mosquito Aedes aegypti: from genomic characterization to high-throughput field detection. bioRxiv, 2020.06.08.139741, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. https://doi.org/10.1101/2020.06.08.13974

    A new statistical tool to identify the determinant of parallel evolution

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    International audienceA recommendation – based on reviews by an anonymous reviewer and Bastien Boussau – of Bailey SF, Guo Q and Bataillon T. 2018. Identifying drivers of parallel evolution: A regression model approach. bioRxiv, 118695, ver. 4 peer-reeviewed by PCI Evol Biol. doi: 10.1101/11869

    Emerging viruses: why they are not jacks of all trades?

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    3 gráficasIn order to limit the impact of the recent pandemics ignited by viral host jumps, it is necessary to better understand the ecological and evolutionary factors influencing the early steps of emergence and the interactions between them. Antagonistic pleiotropy, i.e. the negative fitness effect in the primary host of mutations allowing the infection of and the multiplication in a new host, has long been thought to be the main limitation to the evolution of generalist viruses and thus to emergence. However, the accumulation of experimental examples contradicting the hypothesis of antagonistic pleiotropy has highlighted the importance of other factors such as the epistasis between mutations increasing the adaptation to a new host. Epistasis is pervasive in viruses, affects the shape of the adaptive landscape and consequently the accessibility of evolutionary pathways. Finally, recent studies have gone steps further in the complexity of viral fitness determinism and stressed the potential importance of the epistatic pleiotropy and of the impact of host living conditions.We thank our lab mates for exciting discussions on the topic of this review. This work was supported by the Spanish Secretaría de Estado de Investigación,Desarrollo e Innovación grant BFU2012-30805.Peer reviewe
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