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Evolutionary Biology Concepts

Evolutionary Biology Concepts. “What is behind is not important!”- or is it? Molecular Evolution Phylogenetic Inference. Evolution. Change in living organisms via reproduction. "Change over time"-Kentucky School Boards. Levels of Evolution. Species Population gene frequencies

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Evolutionary Biology Concepts

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  1. Evolutionary Biology Concepts “What is behind is not important!”- or is it? Molecular Evolution Phylogenetic Inference Chuck Staben

  2. Evolution Change in living organisms via reproduction "Change over time"-Kentucky School Boards Chuck Staben

  3. Levels of Evolution • Species • Population • gene frequencies • Organismal • genomic • Molecular Chuck Staben

  4. Branching Descent Evolutionary Tree Family Tree Chuck Staben

  5. Phylogeny Branching diagram showing the ancestral relations among species. “Tree of Life” History of evolutionary change FRAMEWORK for INFERENCE Chuck Staben

  6. Phylogenetic Inference Mom's hair color? Which form of reproduction? Chuck Staben

  7. Mom-Inferred vs Real • “Blonde” Phenotype • Recombination • Male/hair color • Multigenic hair color? • Potential Asexual Propagation • Date of vasectomy? courtesy, Ms. J. Rae Staben Chuck Staben

  8. Inferring the Framework • How do we describe phylogenies? • How do we infer phylogenies? Chuck Staben

  9. Classical Phylogeny Molecular Phylogeny Inheritance RNA Protein Function DNA Chuck Staben

  10. A B C D E F Node Internode Phylogenetic Trees Sister Taxa Terminal Taxa Ancestor Root Chuck Staben

  11. A B C D E F Paraphyletic Group Clade Monophyletic Group More Trees Chuck Staben

  12. A B C D E F Trees-3 Polyphyletic Group Chuck Staben

  13. Add Root Rooted vs Unrooted Trees Chuck Staben

  14. A B C D E F Extinction Chuck Staben

  15. Speciation • Poorly understood • “…the mystery of mysteries…”-Darwin • Reproductive isolation/divergence Chuck Staben

  16. Population Genetic Forces Hardy-Weinberg Paradigm p+q=1 p2 + 2pq + q2 =1 • Natural Selection (fitness) • Drift (homozygosity by chance) • much greater in small populations • Mutation/Recombination (variation) • Migration • homogenizes gene pools Chuck Staben

  17. DNA, protein sequence change Rate=1 change/6 aa sites per 108 yrs Rate=0.16 x 10-9 yrs (normal ~ 1 per 10-9 yrs per site) Chuck Staben

  18. Multiple Changes/No Change ..CCU AUA GGG.. ..CCC AUA GGG.. ..CCC AUG GGG.. ..CCC AUG GGC.. ..CCU AUG GGC.. ..CCU AUA GGC.. 5 mutations 1 DNA change 0 amino acid changes (net) Underestimate Evolution Chuck Staben

  19. Mechanisms of DNA Sequence Change Neutral Drift vs Natural Selection • For a 1000 base gene, 41000 sequences! Selection (Jukes) Neutral (Kimura) Chuck Staben

  20. Rate varies Gene-to-Gene Chuck Staben

  21. Rate varies Site-to-Site Coding>Silent??? Chuck Staben

  22. Constraints on “Silent” Changes • Codon Biases-translation rates • Transcription elongation rates • polymerase ‘pause’ sites • “Silent” regulatory elements • select for or against presence/absence • Overall genome structure Chuck Staben

  23. Neutralism in Eukaryotes vs Prokaryotes-“Slightly deleterious mutations” Models Most non-coding sites are neutral? Coding/noncoding can be flexible? Reconsider evolutionary mechanisms? Chuck Staben

  24. Evolutionary Genetic Forces Hardy-Weinberg Paradigm p+q=1 p2 + 2pq + q2 =1 • Natural Selection (fitness) • Drift (homozygosity by chance) • much greater in small populations • Mutation/Recombination (variation) • Migration • homogenizes gene pools Genome Recombination? Chuck Staben

  25. DNA, Protein Similarity • Similarity by common descent • phylogenetic • Similarity by convergence • functional importance • Similarity by chance • random variation not limitless • particular problem in wide divergence Chuck Staben

  26. Homology-similar by common descent Chuck Staben

  27. Inferring Trees and Ancestors CCCAGG CCCAAG-> CCCAAG CCCAAA-> CCTAAA CCTAAA-> CCTAAC MANY traps, problems Chuck Staben

  28. Paralogs Homology, Orthology, Paralogy Orthologs Chuck Staben

  29. Paralogy Trap Chuck Staben

  30. Improper Inference Man is a mouse, not a rat! Chuck Staben

  31. Convergence Globin Common Ancestor Convergence Leghemoglobin Chuck Staben

  32. Our Goals • Infer Phylogeny • Optimality criteria • Algorithm • Phylogenetic inference • (interesting ones) Chuck Staben

  33. Watch Out “The danger of generating incorrect results is inherently greater in computational phylogenetics than in many other fields of science.” “…the limiting factor in phylogenetic analysis is not so much in the facility of software applicaition as in the conceptual understanding of what the software is doing with the data.” Chuck Staben

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