Phylogenetics. Why you should care: Tree of Life Web Project 12/8/16. Reconstructing the Tree of Life

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1 Phylogenetics Reconstructing the ree of Life n the Speciation lecture, talked about a Phylogenetic Species oncept What is a Phylogeny? How do you construct one? Why on earth should care? 2 Why you should care: ll biological relationships can be determined by constructing phylogenies: Even if phylogenies are not always the best way to define species boundaries, they do tell you the genetic and evolutionary relationships among groups and individuals Your ancestry Diseases figure out evolutionary origins and evolutionary pathways of disease, like HV, Ebola, SRS, etc. rops and live stock (food security) rescue from inbreeding, create new varieties Endangered Species figure out how endangered populations are related and how to perform genetic rescue ree of Life Web Project extbook Version EUKRY Land plants Dinoflagellates reen algae Forams iliates Diatoms Red algae Updated ree of Life 2016 Hug et al Nature Microbiology moebas ellular slime molds nimals Fungi Euglena rypanosomes Leishmania acteria hermophiles Sulfolobus reen nonsulfur bacteria (Mitochondrion) Halophiles Methanobacterium RHE MMN NESR F LL LFE Spirochetes hlamydia reen sulfur bacteria ER yanobacteria (Plastids, including chloroplasts) rchaea Eukarya 1

2 12/8/16 utline hink about relationships among the major lineages of life and when they appeared in the fossil record 1. What is a phylogeny? 2. How do you construct a phylogeny? he Molecular lock Statistical Methods re enetic Distances and fossil record roughly congruent? Fossil Record vs Molecular lock Evolutionary History of HV HV evolved multiple times from SV (Simian Molecular clock and fossil record are not always congruent Fossil record is incomplete, and soft bodied species are usually not preserved Mutation rates can vary among species (depending on generation time, replication error, mismatch repair) ut they provide complementary information Fossil record contains extinct species, while molecular data is based on extant taxa Major events in fossil record could be used to calibrate the molecular clock harles Darwin ( ) n the rigin of Species (1859) Living species are related by common ancestry hange through time occurs at the population not the organism level he main cause of adaptive evolution is natural selection mmunodeficiency Syndrome) ime Evolutionary nalysis Freeman& Herron, 2004 Darwin envisaged evolution as a tree he affinities of all the beings of the same class have sometimes been represented by a great tree. believe this simile largely speaks the truth he green and budding twigs may represent existing species; and those produced during former years may represent the long succession of extinct species...the great ree of Life.covers the earth with ever-branching and beautiful ramifications harles Darwin, n the rigin of Species; pages

3 Reconstructing the ree of Life he only figure in he rigin of Species What did people believe before Darwin? Jean-aptiste Lamarck Lamarck proposed a ladder of life French Naturalist ( ) Professor of Worms and nsects in Paris Past Future he first scientific theory of evolution (inheritance of acquired traits) Lamarck s View of Evolution What is wrong with a ladder? ontinuum between physical and biological world (followed ristotle) Scala Naturae ( Ladder of Life or reat hain of eing ) eing Realm of eing Realm of ecoming Non-eing od ngels Demons Man nimals Plants Minerals Evolution is not linear but branching Living organisms are not ancestors of one another he ladder implies progress

4 What is right with the tree? Evolution is a branching process f a mutation occurs, one species is not turning into another, but there is a split, and both lineages continue to evolve he only figure in he rigin of Species So, evolution is not progressive - all living taxa are equally successful Phylogenies (rees) reflect the hierarchical structuring of relationships he ree of Life is a Fractal enealogical structures Phylogeny depiction of the ancestry relations between species (it includes speciation events) ree-like (divergent) Pedigree depiction of the ancestry relations within populations Net-like (reticulating) Four butterflies connected to their parents offspring parents Population ndividuals past future 4

5 Population What happened here? Lineage/ Species What happened here? Phylogeny Lineage-branching Speciation Extinction Representation of phylogenies? Some terms used to describe a phylogenetic tree axon (taxa) ip nternal branch nternode he rue History simplified representation Root Node (Speciation event) utline What is a Phylogeny? 1. What is a phylogeny? 2. How do you construct a phylogeny? he Molecular lock Statistical Methods phylogenetic tree represents a hypothesis about evolutionary relationships Each branch point represents the divergence of two taxa (e.g. species) Sister taxa are groups that share an immediate common ancestor 5

6 Molecular lock Phylogenies rely on the Molecular lock, namely the fact that Mutations on average, occur at a given rate So, on average, more mutational differences between taxa means that they branched from a common ancestor longer ago Example: Mitochondria: 1 So longer branches on mutation every phylogeny often à greater ~2.2%/million years evolutionary distance 1 Molecular lock Problem: mutation rate can vary among species Mutation rate is faster: Shorter generation time (greater number of meiosis or mitosis events in a given time) Replication Error (e.g. Sloppy DN or RN polymerase; poor 2 mismatch repair mechanisms) Phylogenetic rees with Proportional ranch Lengths n some trees, the length of a branch can reflect the number of genetic changes that have taken place in a particular DN sequence in that lineage So longer branches = greater evolutionary distance Neutral data are better for capturing genetic distances (the molecular clock) than genes that might be under selection Why? Phylogenetic nformative haracters (mutations) Neutral mutations: Mutations that are not subjected to selection etter for constructing phylogenies because selection could make unrelated taxa appear more similar or related taxa more different Examples: Noncoding regions of DN, rd codon position in proteins, introns, microsatellites ( junk DN ) 6

7 odon ias n the case of amino acids Mutations in Position 1, 2 lead to change Mutations in Position don t matter rder arnivora Family enus Panthera axidea Lutra anis Felidae Mustelidae anidae Species Panthera pardus axidea taxus Lutra lutra anis latrans anis lupus ranch point (node) axon monophyletic clade consists of an ancestral taxa and all its descendants NESRL LNEE axon axon axon D axon E Sister taxa roup D D D E E roup E F F F roup ommon ancestor of taxa F Polytomy (unresolved branching point) axon F (a) Monophyletic group (clade) (b) Paraphyletic group (c) Polyphyletic group Examples of Paraphyletic roups (not recognized as legitimate groups in the Phylogenetic Species oncept, which only recognizes monophyletic groups) D E F roup (a) Monophyletic group (clade) (in the lecture on species concepts we discussed that the smallest monophyletic group is a phylogenetic species ) 7

8 Synapomorphies Synapomorphies are shared derived homologous traits hey can be DN nucleotides or other heritable traits hey are used to group taxa that are more closely related to one another 8

9 synapomorphies Sometimes similar looking traits are not homologous, and are not synapomorphies, but are the result of convergent evolution 9

10 How do we construct Phylogenies? Phylogenetic Methods Parsimony: Minimize # steps Distance Matrix: minimize pairwise genetic distances Maximum Likelihood: Probability of the data given the tree ayesian: Probability of the tree given the data Parsimony Uses Discrete haracters (like mutations, or some heritable trait) Select the tree with the minimum number of character-state transitions summed across all characters Fig Parsimony: Example 1 Fig Species 1 Site 2 4 1/ 1/ Species Species ncestral sequence 1/ 1/ 1/ Species Species Species hree phylogenetic hypotheses: 10

11 Fig Fig Species 1 Site 2 4 1/ 1/ Species 1 Site 2 4 1/ 1/ Species Species ncestral sequence 2/ / / 1/ 2/ 1/ 1/ / 4/ Species Species ncestral sequence 2/ / / 1/ 2/ 1/ 1/ / 4/ 4/ / 4/ 4/ 2/ 2/ 4/ 2/ / 4/ / 4/ 4/ 2/ 2/ 4/ 2/ / 6 events 7 events 7 events Parsimony: Example 2 hree possible trees ree 1 ree 2 Map the characters (mutations) onto tree ree Map the characters (mutations) onto tree 1 ctually, there is more than one way to map character otal # number of steps = 6 Either way the character contributes 2 steps to the overall tree length 11

12 Map the characters onto tree 2 ree # steps = 5 Length = 6 steps Which tree had the shortest branch lengths (most parsimonious)? Most parsimonious tree Where do the Whales belong? Example from Freeman & Herron, Fig. 4.8 ree 1: length = 6 ree 2: length = 5 ree : length = 6 Freeman & Herron, Fig. 4.9: Using maximum parsimony, looks like the whales cluster with the hippos (and cows) Parsimony Simplest and fastest method of phylogenetic reconstruction an give misleading results if rates of evolution (rates that mutations occur) differ in different lineages ends to become less accurate as genetic distances get greater ould be mislead by reversals, homoplasy: ecause with only 4 nucleotides, after a while, same mutations occur repeatedly at a given site (called saturation ) multiple hits (mutations) per site 12

13 Distance Matrix ontinuous or Discrete haracters Distance Matrix alculate pairwise distances between taxa hoose the tree that minimizes overall distances between taxa proportion sequence distance at 2 genes (hypothetical data) mouse cat dog dolphin seal Mouse 1 at Dog Dolphin Seal Freeman & Herron, Fig. 4.10: Using genetic distances, looks like the whales again cluster with the hippos (and cows) Distance Matrix enerally more accurate than parsimony Like parsimony, it tends to be computationally fast Maximum Likelihood (R.. Fisher) Probability of the data given the tree his is a Frequentist method: one true answer (one true tree) Draw from the data (probability distribution of DN sequence data) to find the true tree hoose the tree (x, y axis) that maximizes the probability of the observed data (z axis) Z: Probability of the data Maximum Likelihood (R.. Fisher) Probability of the data given the tree he aim of maximum likelihood estimation is to find the parameter value(s) that makes the observed data most likely. For example: finding a mean. f you want to have a number that describes the data, like human height, you could find the mean P(data/tree) = likelihood(tree/data) ree = hypothesis Z: Probability of the data Felsenstein, J Evolutionary trees from DN sequences: a maximum likelihood approach. Journal of Molecular Evolution. 17(6): x,y: ree space Felsenstein, J Evolutionary trees from DN sequences: a maximum likelihood approach. Journal of Molecular Evolution. 17(6): x,y: ree space 1

14 ften yields more accurate tree than parsimony or distance Relies on an accurate assumption of which mutations are more probable (-> more often than -> or? i.e. accurate model of molecular evolution) Maximum Likelihood (R.. Fisher) omputationally intensive ayesian nference Reverend homas ayes ( ) Probability of a tree given the data Uses prior information on the tree Does not assume that there is one correct tree Will modify estimate based on additional information Uses ayes heorem P(/) = P(/)P() P() ayesian nference Reverend homas ayes ( ) Probability of a tree given the data: Will modify estimate based on additional information: so as you get more data, you update your hypothesis for the tree Uses prior information on the tree: this is where you start he sequential use of the ayes' formula (recursive): when more data become available after calculating a posterior distribution, the posterior becomes the next prior Does not assume that there is one correct tree ayesian nference Reverend homas ayes ( ) Uses ayes heorem P(/) = P(/)P() = P(tree/data) = P(data/tree)P(tree) P() P(data) P() = prior probability, probability of a tree P(/) = posterior probability probably of tree given the data P(/) = the probability (data) of observing given (tree), is also known as the likelihood. t indicates the compatibility of the evidence with the given hypothesis. P() = probability of the data ayesian nference Like Likelihood, often yields more accurate tree than parsimony or distance omputationally more intensive than parsimony or distance matrix, but less intensive than likelihood Needs a prior probability for the tree and a model of evolution Potential problems of Phylogenetic Reconstruction Sufficient mount of Data: With enough data most statistical methods usually yield the same tree nsufficient data would yield a tree that lacks resolution (lacks statistical power) ene trees vs species trees Evolutionary history of individual genes are not necessarily the same Should try to get data from many genes, or the whole genome 14

15 hallenges of Phylogenetic Reconstructions Different parts of the genome might have different evolutionary histories (different gene genealogies, horizontal gene transfers, allopolyploidy, etc) So, there might not be one true tree for a group of taxa, and relationships might be difficult to resolve because they are inherently complex urrent trend is to use whole genome data to reconstruct phylogenies ain a comprehensive picture of the evolutionary relationships among taxa for the whole genome Phylogenetic Reconstructions ypically, evolutionary biologists will use a variety of methods to reconstruct a phylogeny. Maximum likelihood and ayesian methods are considered more robust. ree is only as good as the data. Having many homoplastic characters (due to convergent evolution, reversals, etc.) will make the reconstruction less robust Standard to use ootstrapping to assess the validity of the tree Understanding statistics is fundamental to understanding evolution Much of statistics was in fact developed in order to model evolutionary processes (such as NV, analysis of variance) 1. Sometimes the Molecular lock (based on genetic data) conflicts with the eological Record. Why would this happen? () Sometimes there are gaps in the geological record, because fossils do not form everywhere, and mutation rate might vary between different species () Radiometric dating relies on chance events in the preservation of isotopes, making the timing events in the geological time scale less accurate than the molecular clock () Mutation rates slow down as you go back in time, making estimation of timing of events less accurate as you go back in time (D) he molecular clock is calculated from radioisotopes, while the geological record is obtained from fossil data. he two can conflict when fossils end up displaced from their original sedimentary layer 2. You are a medical researcher working on HV. novel strain has appeared in Madison, Wisconsin. o determine which drugs would be most effective in treating this new strain (because different strains are resistant to different drugs), you need to determine its recent evolutionary history. You decide to reconstruct the evolutionary history of HV by using a phylogenetic approach. hus, you collect samples from patients in various geographic locations and sequence a fragment of RN. Using parsimony, which is the correct phylogeny for HV-1 based on the data below? HV-1, Uganda, frica HV-1, San Francisco, US HV-1, Madison, US HV-1, New York, US HV-1, Paris HV-2 frica (ancestral outgroup): U UU U U U U. Which of the following is most RUE regarding phylogenetic reconstructions? () Phylogenetic reconstruction based on any gene would yield the same tree () Parsimony is the most accurate method for reconstructing phylogenies () Some DN sequence data is better for phylogenetic reconstruction than others, such as those that tend to be less subjected to selection (rd codon, introns) (D) Maximum likelihood relies on maximizing distances among taxa 15

16 4. Which of the following types of data would be most optimal for constructing a phylogeny? (a) Non-coding and regulatory sequences (b) Non-coding and non functional sequences (c) Paralogous genes (d) enes that have undergone purifying selection (e) ntron sequences within rapidly evolving genes 5. Which of the following reasons is FLSE on why the type of data chosen in the question above would be optimal for constructing a phylogeny? (a) ecause selection might make taxa seem more closely related due to convergent evolution (b) ecause selection might make taxa seem more distantly related due to disruptive evolution (c) ecause selection might make taxa seem more closely related due to purifying selection (d) ecause non-coding regulatory sequences are likely to be neutral (e) ecause coding sequences are likely to be under selection nswers D 16

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