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Reductive evolution of bacterial genomes

Reductive evolution of bacterial genomes. Bérénice Batut Advisors : Guillaume Beslon , Carole Knibbe, Gabriel Marais. Goals. Buchnera aphidicola Endosymbiont 70% genome reduction Small N e. Which forces drive such reductive evolution ?. Prochlorococcus marinus

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Reductive evolution of bacterial genomes

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  1. Reductive evolution of bacterial genomes • Bérénice Batut • Advisors : Guillaume Beslon, Carole Knibbe, Gabriel Marais B. Batut – Reductive evolution of bacterial genomes

  2. Goals Buchneraaphidicola Endosymbiont 70% genome reduction Small Ne Which forces drive such reductive evolution ? Prochlorococcusmarinus Free-living bacteria 30% genome reduction Large Ne • Moran et al., 2008 • Giovanonni et al., 2005 B. Batut – Reductive evolution of bacterial genomes

  3. Changer les slides filles Approaches • Simulating genomes under different scenarios (in silico experimental evolution) • The Aevolsimulator • Test of some hypotheses for reductive evolution • Analyzing real genomes (sequence analysis) • Reductive evolution inProchlorococcusmarinus • Other genomic features associated with reductive evolution B. Batut – Reductive evolution of bacterial genomes

  4. 2 types of investigation A changer • In silicoexperimental evolution • Aevol • Test of some hypotheses found in literature • Bioinformatics analysis • Prochlorococcusmarinus • Characterization of reductive evolution B. Batut – Reductive evolution of bacterial genomes

  5. AevolAn in silico experimentalevolutionplatform Generation 0 Generation 50,000 Generation 0 Generation 0 Possibility degree Possibility degree Possibility degree Possibility degree Proteome Proteome Genome Genome Biological function Biological function Biological function Biological function 5,000 bp 1 gene 99% non coding 5,000 bp 1 gene 99% non coding 8,979 bp 93 gene 38% non coding 5,000 bp 1 gene 99% non coding Possibility degree Possibility degree Possibility degree Possibility degree Phenotype Phenotype Phenotype Environment Environment Environment Environment Biological function Biological function Biological function Biological function 40,000 20,000 10,000 30,000 50,000 0 B. Batut – Reductive evolution of bacterial genomes

  6. AevolAn in silico experimentalevolutionplatform • Indirect selection of genome structure • Indirect selection of network complexity • Indirect selection of transcriptome structure B. Batut – Reductive evolution of bacterial genomes

  7. AevolAn in silico experimentalevolutionplatform B. Batut – Reductive evolution of bacterial genomes

  8. Changer les slides filles Simulating differentscenarioswith Aevol Reduction inpopulation size • ? Increase inmutation rate Environmentgetsmorestable Environment getsmore simple B. Batut – Reductive evolution of bacterial genomes Higher mutation rates Less varying environment Less demanding environment

  9. Changer Results Smaller population size • ? Higher mutation rates Lessvaryingenvironment Lessdemandingenvironment B. Batut – Reductive evolution of bacterial genomes Higher mutation rates Lessvaryingenvironment Lessdemandingenvironment

  10. Reduction in population size Genes are lost but the intergenicregionsget longer B. Batut – Reductive evolution of bacterial genomes Higher mutation rates Lessvaryingenvironment Lessdemandingenvironment

  11. Changer Results Smaller population size • ? Higher mutation rates Lessvaryingenvironment Lessdemandingenvironment B. Batut – Reductive evolution of bacterial genomes Higher mutation rates Lessvaryingenvironment Lessdemandingenvironment

  12. Increase in mutation rate Genes are lost Intergenicregionsgetsmaller All the genomegetsreduced B. Batut – Reductive evolution of bacterial genomes Higher mutation rates Lessvaryingenvironment Lessdemandingenvironment

  13. Changer Results Smaller population size • ? Higher mutation rates Lessvaryingenvironment Lessdemandingenvironment B. Batut – Reductive evolution of bacterial genomes Higher mutation rates Lessvaryingenvironment Lessdemandingenvironment

  14. The environmentgets more stable Intergenicregionsgetshorter But Thenumber of genesincreases B. Batut – Reductive evolution of bacterial genomes Higher mutation rates Lessvaryingenvironment Lessdemandingenvironment

  15. Changer Results Smaller population size • ? Higher mutation rates Lessvaryingenvironment Lessdemandingenvironment B. Batut – Reductive evolution of bacterial genomes Higher mutation rates Lessvaryingenvironment Lessdemandingenvironment

  16. The environmentgets more simple Genes are lost and intergenicregionsgetsmaller All the genomeisreduced B. Batut – Reductive evolution of bacterial genomes Higher mutation rates Lessvaryingenvironment Lessdemandingenvironment

  17. Summary of the results B. Batut – Reductive evolution of bacterial genomes Higher mutation rates Lessvaryingenvironment Lessdemandingenvironment

  18. Changer 2 types of investigation • In silicoexperimental evolution • Aevol • Test of some hypotheses found in literature • Bioinformatics analysis • Prochlorococcusmarinus • Characterization of reductive evolution B. Batut – Reductive evolution of bacterial genomes

  19. Changer les slides filles Reductiveevolution for endosymbionts Mettrecouleurdifferente pour biblio • Increase in AT content: Moran & Plague, 2004 • Rapid sequence evolution: Moran, 1996; Wernegreen & Moran, 1999 • Maladapted codon usage: Moran & Plague, 2004 • Stable genome organization: Tamas et al., 2002 • Decrease in gene size: Andersson et al., 2002 • Genome compactness: Moran & Plague, 2004 • And Prochlorococcusmarinus ? B. Batut – Reductive evolution of bacterial genomes

  20. Phylogenetictree of Prochlorococcusand Synechococcus B. Batut – Reductive evolution of bacterial genomes

  21. Gene loss and genomereductionin Prochlorococcus B. Batut – Reductive evolution of bacterial genomes

  22. Changer Reductiveevolution for endosymbionts • Richness in AT bases: Moran & Plague, 2004 • Rapid sequence evolution: Moran, 1996; Wernegreen & Moran, 1999 • Low codon usage bias: Moran & Plague, 2004 • Stable chromosome: Tamas et al., 2002 • Shortening of genes: Andersson et al., 2002 • Genome compactness: Moran & Plague, 2004 • And Prochlorococcusmarinus ? B. Batut – Reductive evolution of bacterial genomes

  23. Increase in AT content associatedwithgenomereduction in Prochlorococcus B. Batut – Reductive evolution of bacterial genomes

  24. Changer Reductiveevolution for endosymbionts • Richness in AT bases: Moran & Plague, 2004 • Rapid sequence evolution: Moran, 1996; Wernegreen & Moran, 1999 • Low codon usage bias: Moran & Plague, 2004 • Stable chromosome: Tamas et al., 2002 • Shortening of genes: Andersson et al., 2002 • Genome compactness: Moran & Plague, 2004 • And Prochlorococcusmarinus ? B. Batut – Reductive evolution of bacterial genomes

  25. dN/dS ratio tends to belower in reducedcompared to non-reducedProchlorococcusgenomes This is in agreement with lower dN/dS in reduced Prochlorococcus compared to Synechococcus found in Hu& Blanchard (2009) B. Batut – Reductive evolution of bacterial genomes

  26. Changer Reductiveevolution for endosymbionts • Richness in AT bases: Moran & Plague, 2004 • Rapid sequence evolution: Moran, 1996; Wernegreen & Moran, 1999 • Low codon usage bias: Moran & Plague, 2004 • Stable chromosome: Tamas et al., 2002 • Shortening of genes: Andersson et al., 2002 • Genome compactness: Moran & Plague, 2004 • And Prochlorococcusmarinus ? B. Batut – Reductive evolution of bacterial genomes

  27. The codon usage biasislower in reducedProchlorococcus B. Batut – Reductive evolution of bacterial genomes

  28. Predictedgrowth rate isdecreased in reducedProchlorococcus • Growthpred • (Viera-Silva & Rocha 2010) • Estimation of minimal generation time based on : • Optimal growth temperature • Estimator of the strength of selection acting on codon usage bias • Empirical estimator of the strength of selection acting on codon usage bias in highly expressed genes (ribosomal genes) A clarifier B. Batut – Reductive evolution of bacterial genomes

  29. Smallernumber of tRNAgenes in reducedProchlorococcus tRNAScanSE (Lowe & Eddy 1997) B. Batut – Reductive evolution of bacterial genomes

  30. Timing of tRNAgeneloss in reducedProchlorococcus B. Batut – Reductive evolution of bacterial genomes

  31. Changer Reductiveevolution for endosymbionts • Richness in AT bases: Moran & Plague, 2004 • Rapid sequence evolution: Moran, 1996; Wernegreen & Moran, 1999 • Low codon usage bias: Moran & Plague, 2004 • Stable chromosome: Tamas et al., 2002 • Shortening of genes: Andersson et al., 2002 • Genome compactness: Moran & Plague, 2004 • And Prochlorococcusmarinus ? B. Batut – Reductive evolution of bacterial genomes

  32. Genomesseem more stable afterreduction Dufresne et al 2005 B. Batut – Reductive evolution of bacterial genomes

  33. Changer Reductiveevolution for endosymbionts • Richness in AT bases: Moran & Plague, 2004 • Rapid sequence evolution: Moran, 1996; Wernegreen & Moran, 1999 • Low codon usage bias: Moran & Plague, 2004 • Stable chromosome: Tamas et al., 2002 • Shortening of genes: Andersson et al., 2002 • Genome compactness: Moran & Plague, 2004 • And Prochlorococcusmarinus ? B. Batut – Reductive evolution of bacterial genomes

  34. Genes have similar size in all Prochlorococcus (reduced or non-reduced) Marais et al 2007 B. Batut – Reductive evolution of bacterial genomes

  35. Changer Reductiveevolution for endosymbionts • Richness in AT bases: Moran & Plague, 2004 • Rapid sequence evolution: Moran, 1996; Wernegreen & Moran, 1999 • Low codon usage bias: Moran & Plague, 2004 • Stable chromosome: Tamas et al., 2002 • Shortening of genes: Andersson et al., 2002 • Genome compactness: Moran & Plague, 2004 • And Prochlorococcusmarinus ? B. Batut – Reductive evolution of bacterial genomes

  36. The fraction of non-coding DNA islower in reducedProchlorococcus B. Batut – Reductive evolution of bacterial genomes

  37. Changer Summary of the genomicfeatures of reducedProchlorococcusmarinus • Richness in AT bases Yes • Rapid sequence evolution No • Low codon usage bias Yes • Stable chromosome Yes • Shortening of genes No • Genome compactness Yes B. Batut – Reductive evolution of bacterial genomes

  38. Perspectives • Differences between endosymbiotic and free-living reduced bacterial genomes • Framework for comparing simulated and real genomes • Test of more hypotheses • Selective pressure, rearrangements, … • Adaptation to oligotrophy • Adaptation to phagic pressure • “Black queen” hypothesis B. Batut – Reductive evolution of bacterial genomes

  39. Thankyou ! Beagle team (LIRIS/Inria) BGE team (LBBE) Guillaume Beslon Gabriel Marais Carole Knibbe Vincent Daubin

  40. B. Batut – Reductive evolution of bacterial genomes

  41. B. Batut – Reductive evolution of bacterial genomes

  42. B. Batut – Reductive evolution of bacterial genomes

  43. B. Batut – Reductive evolution of bacterial genomes

  44. B. Batut – Reductive evolution of bacterial genomes

  45. B. Batut – Reductive evolution of bacterial genomes

  46. Rapidevolution of sequences? B. Batut – Reductive evolution of bacterial genomes

  47. Genomecompactness ? B. Batut – Reductive evolution of bacterial genomes

  48. Genomecompactness ? B. Batut – Reductive evolution of bacterial genomes

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