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Evolutionary Biology Concepts

Evolutionary Biology Concepts. Molecular Evolution Phylogenetic Inference. Reading: Ch7. BIO520 Bioinformatics Jim Lund. Evolution. Evolution is a process that results in heritable changes in a population spread over many generations.

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Evolutionary Biology Concepts

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  1. Evolutionary Biology Concepts Molecular Evolution Phylogenetic Inference Reading: Ch7 BIO520 Bioinformatics Jim Lund

  2. Evolution Evolution is a process that results in heritable changes in a population spread over many generations. "In fact, evolution can be precisely defined as any change in the frequency of alleles within a gene pool from one generation to the next." - Helena Curtis and N. Sue Barnes, Biology, 5th ed. 1989 Worth Publishers, p.974

  3. Changes in allele frequencies within a species. Speciation. Molecular changes: Single bp changes. Genomic changes (alterations in large DNA segments). Levels of Evolution

  4. Branching Descent Evolutionary Tree Family Tree Populations Individuals

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

  6. How do we describe phylogenies? How do we infer phylogenies? The framework for phylogenetics

  7. Classical Phylogeny Molecular Phylogeny Inheritance RNA Protein Function DNA

  8. Common Phylogenetic Tree Terminology Terminal Nodes Branches or Lineages A Represent the TAXA(genes, populations, species, etc.) used to infer the phylogeny B C D Ancestral Node or ROOT of the Tree E Internal Nodes or Divergence Points (represent hypothetical ancestors of the taxa)

  9. Taxon B Taxon C No meaning to the spacing between the taxa, or to the order in which they appear from top to bottom. Taxon A Taxon D Taxon E This dimension either can have no scale (for ‘cladograms’), can be proportional to genetic distance or amount of change (for ‘phylograms’ or ‘additive’ trees). Phylogenetic trees diagram the evolutionary relationships between the taxa ((A,(B,C)),(D,E)) = The above phylogeny as nested parentheses These say thatBandCare more closely related to each other than either is toA, and thatA,B, andCform a clade that is a sister group to the clade composed of DandE. If the tree has a time scale, thenDandEare the most closely related.

  10. Two types of trees Cladogram Phylogram or additive tree 6 Taxon B Taxon B 1 Taxon C Taxon C 1 Taxon A Taxon A 5 Taxon D Taxon D genetic change no meaning Meaning of branch length differs. All show the same evolutionary relationships, or branching orders, between the taxa.

  11. Add Root Rooted vs Unrooted Trees

  12. Clade Monophyletic Group More Trees A B C D E F Paraphyletic Group

  13. A B C D E F Trees-3 Polyphyletic Group

  14. A B C D E F Extinction

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

  16. Many ways speciation can occur, among the most common are: Geographic isolation. Reproductive isolation. Sexual selection. Behavioral isolation. Modes of speciation

  17. DNA, protein sequence change

  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) Enumerating bp/aa changes underestimates evolutionary change

  19. Neutral Drift vs Natural Selection Mechanisms of DNA Sequence Change Traditional selection model Neutral (Kimura/Jukes) Pan-neutralism

  20. Rate of change (evolution) of hemoglobin protein Each point on the graph is for a pair of species, or groups of species. From Kimura (1983) by way of Evolution, Ridley, 3rd ed.

  21. Mutation rate varies Gene-to-Gene

  22. Rate varies Site-to-Site

  23. Rate varies Site-to-Site From Evolution. Mark Rdley, 3rd Ed.

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

  25. Similarity by common descent phylogenetic Similarity by convergence (rare) functional importance Similarity by chance random variation not limitless particular problem in wide divergence DNA, Protein Similarity

  26. Homology-similar by common descent CCCAGG CCCAAG CCCAAA CCTAAA

  27. Inferring Trees and Ancestors CCCAGG CCCAAG-> CCCAAG CCCAAA-> CCTAAA CCTAAA-> CCTAAC Not always straightforward. The data doesn’t always give a single, correct answer.

  28. Paralogs Homology, Orthology, Paralogy Orthologs

  29. Paralogy Trap

  30. Improper Inference Garbage in, garbage out!

  31. Infer Phylogeny Optimality criteria Algorithm Phylogenetic inference (interesting ones) Our Goals

  32. “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 application as in the conceptual understanding of what the software is doing with the data.” Watch Out

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