Molecular Evolution, course # Final Exam, May 3, 2006

Size: px
Start display at page:

Download "Molecular Evolution, course # Final Exam, May 3, 2006"

Transcription

1 Molecular Evolution, course #27615 Final Exam, May 3, 2006 This exam includes a total of 12 problems on 7 pages (including this cover page). The maximum number of points obtainable is 150, and at least 85 points are required to pass. Note that different problems are worth different amounts of points. Problems should be answered in the space provided on these pages. The duration of the exam is 4 hours (13:00-17:00). All non-living resources may be used (books, internet including exercise web-pages, notes, etc. You should, however, not contact your uncle who is a professor of evolutionary biology at Harvard). You can work on your own, or in the groups you worked in during the computer exercises. Please do not discuss the test outside your group. Members of the group must sign below: Name Student ID number Signature 1

2 Table of chi-square critical values Significance level DF

3 1: (5 points) You are performing an experiment on a population of haploid, asexual organisms. Assume that the organisms exhibit exponential growth with discrete, non-overlapping generations, and that genetic drift can be ignored. At a certain locus you observe two alleles: Frequent and Rare. The absolute fitness of both alleles is R = 5 offspring/generation. At the start of the experiment the Rare allele is present in 7% of the population. What is the frequency of the Rare allele after 10 generations? 2: (10 points) Below we have listed four widely used nucleotide substitution models and a list of four PAUP model specifications. Use lines to connect the model names with the corresponding PAUP specifications: (A) Jukes and Cantor model (JC) (B) General Time Reversible model (GTR) (C) Felsenstein 81 (F81) (D) Kimura 2 parameter model (K2P) (1) lset nst=1 basefreq=empirical (2) lset nst=2 basefreq=equal tratio=estimate (3) lset nst=1 basefreq=equal (4) lset nst=6 basefreq=empirical rmatrix=estimate 3: (5 points) You have a strictly bifurcating, unrooted tree with 37 tips. In how many different positions can you place a root? 4: (15 points) You are using parsimony to reconstruct the phylogeny of a set of 9 sequences. Each of your sequences is 1 nucleotide long (!). What is the length of the two trees below? Which tree is the best one according to the parsimony criterion? 3

4 5: (15 points) Below is an alignment of two 45 bp long DNA sequences: Seq_1: AGCTGGCATTGCGTTATTATCATTGCATGCATCTTGTCATATGGC Seq_2: AGCAGAGTCTCCGCTGTTATCGATGTTTCCATCTTGCCTTACAGT What is the (uncorrected) distance between these two sequences? The above result does not take multiple substitutions into account. Assuming the Jukes and Cantor model of evolution, compute the estimated, corrected distance between the sequences: Now, assume the Kimura 2-parameter model of evolution, and again compute the estimated, corrected distance between the sequences: 6: (5 points) Under the so-called HKY85 model of evolution, the likelihood of a tree will depend on where the root is placed 1) True 2) False 7: (5 points) The likelihood of a model is (select one): 1) The probability of the data given the model P(Data Model) 2) The probability of the model given the data P(Model Data) 3) The probability of the model before any evidence has been collected P(Model) 4) The total probability of the data P(Data) 8: (5 points) Branch and bound searching of tree-space is guaranteed to always find the best possible tree: 1) True 2) False Heuristic searching of tree-space is guaranteed to always find the best possible tree: 1) True 2) False 4

5 9: (15 points) As a consequence of your graduate studies at the University of Copenhagen you have become interested in the pubic louse - Pthirus pubis. You therefore want to construct a maximum likelihood tree for a set of sequences from 35 species of lice. Your first step is to decide which model to use. Unfortunately your supervisor has run out of funding and you only have access to some extremely cheap Swedish software that is able to fit just two different models to your data: the Kimura 2-parameter model (K2P) and the general time reversible model (GTR). Below we have listed the number of free parameters in the different models (K) along with the maximal log likelihood (lnl) of the fitted models. Use likelihood ratio testing to decide which model is best (use a significance level of 5%). Model K lnl K2P GTR : (10 points) Below we have listed the names of five different methods for reconstructing phylogenies as well as five very brief descriptions of the methods. Use lines to connect the method names with the corresponding descriptions: (A) Maximum likelihood (B) Least squares (1) The ultimate goal of this method is to find the full posterior probability distribution over trees and other parameters (2) The best tree is the one implying fewest mutations (C) Parsimony (D) Bayesian (E) Minimum evolution (3) For a given tree topology, the best branch lengths are those having the smallest deviation between observed and patristic distances; the best tree is the shortest one. (4) The best tree, and the best branch lengths for a given tree, are those having the smallest deviation between observed and patristic distances. (5) The best tree is the one giving the highest probability of the alignment having evolved from some common ancestor. 5

6 11: (35 points) You are investigating an outbreak of Sundbus elsinorii virus. This virus attacks only Latvian chipmunks and is characteristic in having a genome that is merely 2 nucleotides long (its fascinating life-cycle involves heavy use of programmed frame-shifting during translation of the encoded poly-protein). From a population of chipmunks living in cages at the Latvia University of Agriculture (Latvijas Lauksaimniecibas Universitate) you have obtained 6 fullgenome sequences that are known to be related as shown on the unrooted tree below. Note that two of the sequences are placed at the ancestral nodes. All branches have the same length t 1. Indicated below the tree is the time-reversible substitution-probability matrix corresponding to this branch length (specifically, the matrix is of the F81 type). The equilibrium frequencies of the nucleotides are: π A =0.2, π C =0.3, π G =0.4, π T =0.1. Compute the probability of the data given the information provided here. (Tip: perform the computation one nucleotide position at a time and combine the results). to A C G T A From C t 1 G T

7 12: (25 points) During a ski trip in Norway with 5 friends from your water polo team, you suddenly remember that your supervisor asked you to finish a Bayesian analysis of a set of mitochondrial sequences (obtained from a population of Latvian chipmunks) just before you left. Regrettably, you forgot to do this. However, you fortunately brought a printout of the full data set (in fasta-format) with you to Norway. Since there is no electricity (not to mention a computer) in the ski hut you decide to do the analysis by hand and then send the result to your supervisor by ordinary surface mail. To simplify the job somewhat, you decide to use the Kimura 2 parameter substitution model in a discretized version where only 6 possible values of the transition/transversion ratio are considered: T=1.0, T=2.0, T=3.0, T=4.0, T=5.0, and T=6.0. Based on your previous experience with mitochondrial sequences you have specified the following prior probabilities for the six possible parameter values: Prior probabilities: P(T=1.0) = 0.05 P(T=2.0) = 0.10 P(T=3.0) = 0.25 P(T=4.0) = 0.40 P(T=5.0) = 0.15 P(T=6.0) = 0.05 For each of these possible values you have furthermore computed the probability of the data given that particular parameter value (the likelihood): Likelihoods: P(D T=1.0) = 0.01 P(D T=2.0) = 0.05 P(D T=3.0) = 0.15 P(D T=4.0) = 0.23 P(D T=5.0) = 0.78 P(D T=6.0) = 0.15 Find the posterior probability of the six possible parameter values: P(T=1.0 D) = P(T=2.0 D) = P(T=3.0 D) = P(T=4.0 D) = P(T=5.0 D) = P(T=6.0 D) = 7

Phylogenetic Tree Reconstruction

Phylogenetic Tree Reconstruction I519 Introduction to Bioinformatics, 2011 Phylogenetic Tree Reconstruction Yuzhen Ye (yye@indiana.edu) School of Informatics & Computing, IUB Evolution theory Speciation Evolution of new organisms is driven

More information

Phylogenetics: Building Phylogenetic Trees

Phylogenetics: Building Phylogenetic Trees 1 Phylogenetics: Building Phylogenetic Trees COMP 571 Luay Nakhleh, Rice University 2 Four Questions Need to be Answered What data should we use? Which method should we use? Which evolutionary model should

More information

Phylogenetics: Building Phylogenetic Trees. COMP Fall 2010 Luay Nakhleh, Rice University

Phylogenetics: Building Phylogenetic Trees. COMP Fall 2010 Luay Nakhleh, Rice University Phylogenetics: Building Phylogenetic Trees COMP 571 - Fall 2010 Luay Nakhleh, Rice University Four Questions Need to be Answered What data should we use? Which method should we use? Which evolutionary

More information

POPULATION GENETICS Winter 2005 Lecture 17 Molecular phylogenetics

POPULATION GENETICS Winter 2005 Lecture 17 Molecular phylogenetics POPULATION GENETICS Winter 2005 Lecture 17 Molecular phylogenetics - in deriving a phylogeny our goal is simply to reconstruct the historical relationships between a group of taxa. - before we review the

More information

Phylogenetic Trees. What They Are Why We Do It & How To Do It. Presented by Amy Harris Dr Brad Morantz

Phylogenetic Trees. What They Are Why We Do It & How To Do It. Presented by Amy Harris Dr Brad Morantz Phylogenetic Trees What They Are Why We Do It & How To Do It Presented by Amy Harris Dr Brad Morantz Overview What is a phylogenetic tree Why do we do it How do we do it Methods and programs Parallels

More information

"Nothing in biology makes sense except in the light of evolution Theodosius Dobzhansky

Nothing in biology makes sense except in the light of evolution Theodosius Dobzhansky MOLECULAR PHYLOGENY "Nothing in biology makes sense except in the light of evolution Theodosius Dobzhansky EVOLUTION - theory that groups of organisms change over time so that descendeants differ structurally

More information

Some of these slides have been borrowed from Dr. Paul Lewis, Dr. Joe Felsenstein. Thanks!

Some of these slides have been borrowed from Dr. Paul Lewis, Dr. Joe Felsenstein. Thanks! Some of these slides have been borrowed from Dr. Paul Lewis, Dr. Joe Felsenstein. Thanks! Paul has many great tools for teaching phylogenetics at his web site: http://hydrodictyon.eeb.uconn.edu/people/plewis

More information

Amira A. AL-Hosary PhD of infectious diseases Department of Animal Medicine (Infectious Diseases) Faculty of Veterinary Medicine Assiut

Amira A. AL-Hosary PhD of infectious diseases Department of Animal Medicine (Infectious Diseases) Faculty of Veterinary Medicine Assiut Amira A. AL-Hosary PhD of infectious diseases Department of Animal Medicine (Infectious Diseases) Faculty of Veterinary Medicine Assiut University-Egypt Phylogenetic analysis Phylogenetic Basics: Biological

More information

Maximum Likelihood Tree Estimation. Carrie Tribble IB Feb 2018

Maximum Likelihood Tree Estimation. Carrie Tribble IB Feb 2018 Maximum Likelihood Tree Estimation Carrie Tribble IB 200 9 Feb 2018 Outline 1. Tree building process under maximum likelihood 2. Key differences between maximum likelihood and parsimony 3. Some fancy extras

More information

Probabilistic modeling and molecular phylogeny

Probabilistic modeling and molecular phylogeny Probabilistic modeling and molecular phylogeny Anders Gorm Pedersen Molecular Evolution Group Center for Biological Sequence Analysis Technical University of Denmark (DTU) What is a model? Mathematical

More information

Phylogenetics: Distance Methods. COMP Spring 2015 Luay Nakhleh, Rice University

Phylogenetics: Distance Methods. COMP Spring 2015 Luay Nakhleh, Rice University Phylogenetics: Distance Methods COMP 571 - Spring 2015 Luay Nakhleh, Rice University Outline Evolutionary models and distance corrections Distance-based methods Evolutionary Models and Distance Correction

More information

Constructing Evolutionary/Phylogenetic Trees

Constructing Evolutionary/Phylogenetic Trees Constructing Evolutionary/Phylogenetic Trees 2 broad categories: istance-based methods Ultrametric Additive: UPGMA Transformed istance Neighbor-Joining Character-based Maximum Parsimony Maximum Likelihood

More information

Estimating Phylogenies (Evolutionary Trees) II. Biol4230 Thurs, March 2, 2017 Bill Pearson Jordan 6-057

Estimating Phylogenies (Evolutionary Trees) II. Biol4230 Thurs, March 2, 2017 Bill Pearson Jordan 6-057 Estimating Phylogenies (Evolutionary Trees) II Biol4230 Thurs, March 2, 2017 Bill Pearson wrp@virginia.edu 4-2818 Jordan 6-057 Tree estimation strategies: Parsimony?no model, simply count minimum number

More information

Reconstruire le passé biologique modèles, méthodes, performances, limites

Reconstruire le passé biologique modèles, méthodes, performances, limites Reconstruire le passé biologique modèles, méthodes, performances, limites Olivier Gascuel Centre de Bioinformatique, Biostatistique et Biologie Intégrative C3BI USR 3756 Institut Pasteur & CNRS Reconstruire

More information

Constructing Evolutionary/Phylogenetic Trees

Constructing Evolutionary/Phylogenetic Trees Constructing Evolutionary/Phylogenetic Trees 2 broad categories: Distance-based methods Ultrametric Additive: UPGMA Transformed Distance Neighbor-Joining Character-based Maximum Parsimony Maximum Likelihood

More information

How should we go about modeling this? Model parameters? Time Substitution rate Can we observe time or subst. rate? What can we observe?

How should we go about modeling this? Model parameters? Time Substitution rate Can we observe time or subst. rate? What can we observe? How should we go about modeling this? gorilla GAAGTCCTTGAGAAATAAACTGCACACACTGG orangutan GGACTCCTTGAGAAATAAACTGCACACACTGG Model parameters? Time Substitution rate Can we observe time or subst. rate? What

More information

9/30/11. Evolution theory. Phylogenetic Tree Reconstruction. Phylogenetic trees (binary trees) Phylogeny (phylogenetic tree)

9/30/11. Evolution theory. Phylogenetic Tree Reconstruction. Phylogenetic trees (binary trees) Phylogeny (phylogenetic tree) I9 Introduction to Bioinformatics, 0 Phylogenetic ree Reconstruction Yuzhen Ye (yye@indiana.edu) School of Informatics & omputing, IUB Evolution theory Speciation Evolution of new organisms is driven by

More information

7. Tests for selection

7. Tests for selection Sequence analysis and genomics 7. Tests for selection Dr. Katja Nowick Group leader TFome and Transcriptome Evolution Bioinformatics group Paul-Flechsig-Institute for Brain Research www. nowicklab.info

More information

Inferring Molecular Phylogeny

Inferring Molecular Phylogeny Dr. Walter Salzburger he tree of life, ustav Klimt (1907) Inferring Molecular Phylogeny Inferring Molecular Phylogeny 55 Maximum Parsimony (MP): objections long branches I!! B D long branch attraction

More information

C.DARWIN ( )

C.DARWIN ( ) C.DARWIN (1809-1882) LAMARCK Each evolutionary lineage has evolved, transforming itself, from a ancestor appeared by spontaneous generation DARWIN All organisms are historically interconnected. Their relationships

More information

Dr. Amira A. AL-Hosary

Dr. Amira A. AL-Hosary Phylogenetic analysis Amira A. AL-Hosary PhD of infectious diseases Department of Animal Medicine (Infectious Diseases) Faculty of Veterinary Medicine Assiut University-Egypt Phylogenetic Basics: Biological

More information

A (short) introduction to phylogenetics

A (short) introduction to phylogenetics A (short) introduction to phylogenetics Thibaut Jombart, Marie-Pauline Beugin MRC Centre for Outbreak Analysis and Modelling Imperial College London Genetic data analysis with PR Statistics, Millport Field

More information

Lab 9: Maximum Likelihood and Modeltest

Lab 9: Maximum Likelihood and Modeltest Integrative Biology 200A University of California, Berkeley "PRINCIPLES OF PHYLOGENETICS" Spring 2010 Updated by Nick Matzke Lab 9: Maximum Likelihood and Modeltest In this lab we re going to use PAUP*

More information

EVOLUTIONARY DISTANCES

EVOLUTIONARY DISTANCES EVOLUTIONARY DISTANCES FROM STRINGS TO TREES Luca Bortolussi 1 1 Dipartimento di Matematica ed Informatica Università degli studi di Trieste luca@dmi.units.it Trieste, 14 th November 2007 OUTLINE 1 STRINGS:

More information

Additive distances. w(e), where P ij is the path in T from i to j. Then the matrix [D ij ] is said to be additive.

Additive distances. w(e), where P ij is the path in T from i to j. Then the matrix [D ij ] is said to be additive. Additive distances Let T be a tree on leaf set S and let w : E R + be an edge-weighting of T, and assume T has no nodes of degree two. Let D ij = e P ij w(e), where P ij is the path in T from i to j. Then

More information

Molecular phylogeny - Using molecular sequences to infer evolutionary relationships. Tore Samuelsson Feb 2016

Molecular phylogeny - Using molecular sequences to infer evolutionary relationships. Tore Samuelsson Feb 2016 Molecular phylogeny - Using molecular sequences to infer evolutionary relationships Tore Samuelsson Feb 2016 Molecular phylogeny is being used in the identification and characterization of new pathogens,

More information

Discrete & continuous characters: The threshold model

Discrete & continuous characters: The threshold model Discrete & continuous characters: The threshold model Discrete & continuous characters: the threshold model So far we have discussed continuous & discrete character models separately for estimating ancestral

More information

Sequence Analysis 17: lecture 5. Substitution matrices Multiple sequence alignment

Sequence Analysis 17: lecture 5. Substitution matrices Multiple sequence alignment Sequence Analysis 17: lecture 5 Substitution matrices Multiple sequence alignment Substitution matrices Used to score aligned positions, usually of amino acids. Expressed as the log-likelihood ratio of

More information

BINF6201/8201. Molecular phylogenetic methods

BINF6201/8201. Molecular phylogenetic methods BINF60/80 Molecular phylogenetic methods 0-7-06 Phylogenetics Ø According to the evolutionary theory, all life forms on this planet are related to one another by descent. Ø Traditionally, phylogenetics

More information

Maximum Likelihood Until recently the newest method. Popularized by Joseph Felsenstein, Seattle, Washington.

Maximum Likelihood Until recently the newest method. Popularized by Joseph Felsenstein, Seattle, Washington. Maximum Likelihood This presentation is based almost entirely on Peter G. Fosters - "The Idiot s Guide to the Zen of Likelihood in a Nutshell in Seven Days for Dummies, Unleashed. http://www.bioinf.org/molsys/data/idiots.pdf

More information

Bayesian Inference using Markov Chain Monte Carlo in Phylogenetic Studies

Bayesian Inference using Markov Chain Monte Carlo in Phylogenetic Studies Bayesian Inference using Markov Chain Monte Carlo in Phylogenetic Studies 1 What is phylogeny? Essay written for the course in Markov Chains 2004 Torbjörn Karfunkel Phylogeny is the evolutionary development

More information

Bioinformatics 1. Sepp Hochreiter. Biology, Sequences, Phylogenetics Part 4. Bioinformatics 1: Biology, Sequences, Phylogenetics

Bioinformatics 1. Sepp Hochreiter. Biology, Sequences, Phylogenetics Part 4. Bioinformatics 1: Biology, Sequences, Phylogenetics Bioinformatics 1 Biology, Sequences, Phylogenetics Part 4 Sepp Hochreiter Klausur Mo. 30.01.2011 Zeit: 15:30 17:00 Raum: HS14 Anmeldung Kusss Contents Methods and Bootstrapping of Maximum Methods Methods

More information

Lecture 4. Models of DNA and protein change. Likelihood methods

Lecture 4. Models of DNA and protein change. Likelihood methods Lecture 4. Models of DNA and protein change. Likelihood methods Joe Felsenstein Department of Genome Sciences and Department of Biology Lecture 4. Models of DNA and protein change. Likelihood methods p.1/36

More information

Phylogenetics. BIOL 7711 Computational Bioscience

Phylogenetics. BIOL 7711 Computational Bioscience Consortium for Comparative Genomics! University of Colorado School of Medicine Phylogenetics BIOL 7711 Computational Bioscience Biochemistry and Molecular Genetics Computational Bioscience Program Consortium

More information

Integrative Biology 200 "PRINCIPLES OF PHYLOGENETICS" Spring 2016 University of California, Berkeley. Parsimony & Likelihood [draft]

Integrative Biology 200 PRINCIPLES OF PHYLOGENETICS Spring 2016 University of California, Berkeley. Parsimony & Likelihood [draft] Integrative Biology 200 "PRINCIPLES OF PHYLOGENETICS" Spring 2016 University of California, Berkeley K.W. Will Parsimony & Likelihood [draft] 1. Hennig and Parsimony: Hennig was not concerned with parsimony

More information

Phylogeny and systematics. Why are these disciplines important in evolutionary biology and how are they related to each other?

Phylogeny and systematics. Why are these disciplines important in evolutionary biology and how are they related to each other? Phylogeny and systematics Why are these disciplines important in evolutionary biology and how are they related to each other? Phylogeny and systematics Phylogeny: the evolutionary history of a species

More information

Phylogenetic analyses. Kirsi Kostamo

Phylogenetic analyses. Kirsi Kostamo Phylogenetic analyses Kirsi Kostamo The aim: To construct a visual representation (a tree) to describe the assumed evolution occurring between and among different groups (individuals, populations, species,

More information

Understanding relationship between homologous sequences

Understanding relationship between homologous sequences Molecular Evolution Molecular Evolution How and when were genes and proteins created? How old is a gene? How can we calculate the age of a gene? How did the gene evolve to the present form? What selective

More information

Quantifying sequence similarity

Quantifying sequence similarity Quantifying sequence similarity Bas E. Dutilh Systems Biology: Bioinformatic Data Analysis Utrecht University, February 16 th 2016 After this lecture, you can define homology, similarity, and identity

More information

Processes of Evolution

Processes of Evolution 15 Processes of Evolution Forces of Evolution Concept 15.4 Selection Can Be Stabilizing, Directional, or Disruptive Natural selection can act on quantitative traits in three ways: Stabilizing selection

More information

Phylogeny Estimation and Hypothesis Testing using Maximum Likelihood

Phylogeny Estimation and Hypothesis Testing using Maximum Likelihood Phylogeny Estimation and Hypothesis Testing using Maximum Likelihood For: Prof. Partensky Group: Jimin zhu Rama Sharma Sravanthi Polsani Xin Gong Shlomit klopman April. 7. 2003 Table of Contents Introduction...3

More information

Phylogenetic Analysis. Han Liang, Ph.D. Assistant Professor of Bioinformatics and Computational Biology UT MD Anderson Cancer Center

Phylogenetic Analysis. Han Liang, Ph.D. Assistant Professor of Bioinformatics and Computational Biology UT MD Anderson Cancer Center Phylogenetic Analysis Han Liang, Ph.D. Assistant Professor of Bioinformatics and Computational Biology UT MD Anderson Cancer Center Outline Basic Concepts Tree Construction Methods Distance-based methods

More information

Natural selection on the molecular level

Natural selection on the molecular level Natural selection on the molecular level Fundamentals of molecular evolution How DNA and protein sequences evolve? Genetic variability in evolution } Mutations } forming novel alleles } Inversions } change

More information

How to read and make phylogenetic trees Zuzana Starostová

How to read and make phylogenetic trees Zuzana Starostová How to read and make phylogenetic trees Zuzana Starostová How to make phylogenetic trees? Workflow: obtain DNA sequence quality check sequence alignment calculating genetic distances phylogeny estimation

More information

Phylogenetic inference

Phylogenetic inference Phylogenetic inference Bas E. Dutilh Systems Biology: Bioinformatic Data Analysis Utrecht University, March 7 th 016 After this lecture, you can discuss (dis-) advantages of different information types

More information

BMI/CS 776 Lecture 4. Colin Dewey

BMI/CS 776 Lecture 4. Colin Dewey BMI/CS 776 Lecture 4 Colin Dewey 2007.02.01 Outline Common nucleotide substitution models Directed graphical models Ancestral sequence inference Poisson process continuous Markov process X t0 X t1 X t2

More information

Some of these slides have been borrowed from Dr. Paul Lewis, Dr. Joe Felsenstein. Thanks!

Some of these slides have been borrowed from Dr. Paul Lewis, Dr. Joe Felsenstein. Thanks! Some of these slides have been borrowed from Dr. Paul Lewis, Dr. Joe Felsenstein. Thanks! Paul has many great tools for teaching phylogenetics at his web site: http://hydrodictyon.eeb.uconn.edu/people/plewis

More information

Lecture 24. Phylogeny methods, part 4 (Models of DNA and protein change) p.1/22

Lecture 24. Phylogeny methods, part 4 (Models of DNA and protein change) p.1/22 Lecture 24. Phylogeny methods, part 4 (Models of DNA and protein change) Joe Felsenstein Department of Genome Sciences and Department of Biology Lecture 24. Phylogeny methods, part 4 (Models of DNA and

More information

The Idiot s Guide to the Zen of Likelihood in a Nutshell in Seven Days for Dummies, Unleashed

The Idiot s Guide to the Zen of Likelihood in a Nutshell in Seven Days for Dummies, Unleashed The Idiot s Guide to the Zen of Likelihood in a Nutshell in Seven Days for Dummies, Unleashed A gentle introduction, for those of us who are small of brain, to the calculation of the likelihood of molecular

More information

Tree of Life iological Sequence nalysis Chapter http://tolweb.org/tree/ Phylogenetic Prediction ll organisms on Earth have a common ancestor. ll species are related. The relationship is called a phylogeny

More information

Molecular phylogeny How to infer phylogenetic trees using molecular sequences

Molecular phylogeny How to infer phylogenetic trees using molecular sequences Molecular phylogeny How to infer phylogenetic trees using molecular sequences ore Samuelsson Nov 2009 Applications of phylogenetic methods Reconstruction of evolutionary history / Resolving taxonomy issues

More information

Letter to the Editor. Department of Biology, Arizona State University

Letter to the Editor. Department of Biology, Arizona State University Letter to the Editor Traditional Phylogenetic Reconstruction Methods Reconstruct Shallow and Deep Evolutionary Relationships Equally Well Michael S. Rosenberg and Sudhir Kumar Department of Biology, Arizona

More information

Molecular phylogeny How to infer phylogenetic trees using molecular sequences

Molecular phylogeny How to infer phylogenetic trees using molecular sequences Molecular phylogeny How to infer phylogenetic trees using molecular sequences ore Samuelsson Nov 200 Applications of phylogenetic methods Reconstruction of evolutionary history / Resolving taxonomy issues

More information

Anatomy of a tree. clade is group of organisms with a shared ancestor. a monophyletic group shares a single common ancestor = tapirs-rhinos-horses

Anatomy of a tree. clade is group of organisms with a shared ancestor. a monophyletic group shares a single common ancestor = tapirs-rhinos-horses Anatomy of a tree outgroup: an early branching relative of the interest groups sister taxa: taxa derived from the same recent ancestor polytomy: >2 taxa emerge from a node Anatomy of a tree clade is group

More information

Inferring Speciation Times under an Episodic Molecular Clock

Inferring Speciation Times under an Episodic Molecular Clock Syst. Biol. 56(3):453 466, 2007 Copyright c Society of Systematic Biologists ISSN: 1063-5157 print / 1076-836X online DOI: 10.1080/10635150701420643 Inferring Speciation Times under an Episodic Molecular

More information

Lecture 27. Phylogeny methods, part 4 (Models of DNA and protein change) p.1/26

Lecture 27. Phylogeny methods, part 4 (Models of DNA and protein change) p.1/26 Lecture 27. Phylogeny methods, part 4 (Models of DNA and protein change) Joe Felsenstein Department of Genome Sciences and Department of Biology Lecture 27. Phylogeny methods, part 4 (Models of DNA and

More information

Using algebraic geometry for phylogenetic reconstruction

Using algebraic geometry for phylogenetic reconstruction Using algebraic geometry for phylogenetic reconstruction Marta Casanellas i Rius (joint work with Jesús Fernández-Sánchez) Departament de Matemàtica Aplicada I Universitat Politècnica de Catalunya IMA

More information

Systematics - Bio 615

Systematics - Bio 615 Bayesian Phylogenetic Inference 1. Introduction, history 2. Advantages over ML 3. Bayes Rule 4. The Priors 5. Marginal vs Joint estimation 6. MCMC Derek S. Sikes University of Alaska 7. Posteriors vs Bootstrap

More information

Biology 559R: Introduction to Phylogenetic Comparative Methods Topics for this week (Jan 27 & 29):

Biology 559R: Introduction to Phylogenetic Comparative Methods Topics for this week (Jan 27 & 29): Biology 559R: Introduction to Phylogenetic Comparative Methods Topics for this week (Jan 27 & 29): Statistical estimation of models of sequence evolution Phylogenetic inference using maximum likelihood:

More information

Evolutionary Tree Analysis. Overview

Evolutionary Tree Analysis. Overview CSI/BINF 5330 Evolutionary Tree Analysis Young-Rae Cho Associate Professor Department of Computer Science Baylor University Overview Backgrounds Distance-Based Evolutionary Tree Reconstruction Character-Based

More information

Michael Yaffe Lecture #5 (((A,B)C)D) Database Searching & Molecular Phylogenetics A B C D B C D

Michael Yaffe Lecture #5 (((A,B)C)D) Database Searching & Molecular Phylogenetics A B C D B C D 7.91 Lecture #5 Database Searching & Molecular Phylogenetics Michael Yaffe B C D B C D (((,B)C)D) Outline Distance Matrix Methods Neighbor-Joining Method and Related Neighbor Methods Maximum Likelihood

More information

Evolutionary Models. Evolutionary Models

Evolutionary Models. Evolutionary Models Edit Operators In standard pairwise alignment, what are the allowed edit operators that transform one sequence into the other? Describe how each of these edit operations are represented on a sequence alignment

More information

Massachusetts Institute of Technology Computational Evolutionary Biology, Fall, 2005 Notes for November 7: Molecular evolution

Massachusetts Institute of Technology Computational Evolutionary Biology, Fall, 2005 Notes for November 7: Molecular evolution Massachusetts Institute of Technology 6.877 Computational Evolutionary Biology, Fall, 2005 Notes for November 7: Molecular evolution 1. Rates of amino acid replacement The initial motivation for the neutral

More information

Chapter 7: Models of discrete character evolution

Chapter 7: Models of discrete character evolution Chapter 7: Models of discrete character evolution pdf version R markdown to recreate analyses Biological motivation: Limblessness as a discrete trait Squamates, the clade that includes all living species

More information

What is Phylogenetics

What is Phylogenetics What is Phylogenetics Phylogenetics is the area of research concerned with finding the genetic connections and relationships between species. The basic idea is to compare specific characters (features)

More information

Bioinformatics 1 -- lecture 9. Phylogenetic trees Distance-based tree building Parsimony

Bioinformatics 1 -- lecture 9. Phylogenetic trees Distance-based tree building Parsimony ioinformatics -- lecture 9 Phylogenetic trees istance-based tree building Parsimony (,(,(,))) rees can be represented in "parenthesis notation". Each set of parentheses represents a branch-point (bifurcation),

More information

Bioinformatics tools for phylogeny and visualization. Yanbin Yin

Bioinformatics tools for phylogeny and visualization. Yanbin Yin Bioinformatics tools for phylogeny and visualization Yanbin Yin 1 Homework assignment 5 1. Take the MAFFT alignment http://cys.bios.niu.edu/yyin/teach/pbb/purdue.cellwall.list.lignin.f a.aln as input and

More information

THEORY. Based on sequence Length According to the length of sequence being compared it is of following two types

THEORY. Based on sequence Length According to the length of sequence being compared it is of following two types Exp 11- THEORY Sequence Alignment is a process of aligning two sequences to achieve maximum levels of identity between them. This help to derive functional, structural and evolutionary relationships between

More information

Homework Assignment, Evolutionary Systems Biology, Spring Homework Part I: Phylogenetics:

Homework Assignment, Evolutionary Systems Biology, Spring Homework Part I: Phylogenetics: Homework Assignment, Evolutionary Systems Biology, Spring 2009. Homework Part I: Phylogenetics: Introduction. The objective of this assignment is to understand the basics of phylogenetic relationships

More information

Substitution = Mutation followed. by Fixation. Common Ancestor ACGATC 1:A G 2:C A GAGATC 3:G A 6:C T 5:T C 4:A C GAAATT 1:G A

Substitution = Mutation followed. by Fixation. Common Ancestor ACGATC 1:A G 2:C A GAGATC 3:G A 6:C T 5:T C 4:A C GAAATT 1:G A GAGATC 3:G A 6:C T Common Ancestor ACGATC 1:A G 2:C A Substitution = Mutation followed 5:T C by Fixation GAAATT 4:A C 1:G A AAAATT GAAATT GAGCTC ACGACC Chimp Human Gorilla Gibbon AAAATT GAAATT GAGCTC ACGACC

More information

Molecular Phylogenetics (part 1 of 2) Computational Biology Course João André Carriço

Molecular Phylogenetics (part 1 of 2) Computational Biology Course João André Carriço Molecular Phylogenetics (part 1 of 2) Computational Biology Course João André Carriço jcarrico@fm.ul.pt Charles Darwin (1809-1882) Charles Darwin s tree of life in Notebook B, 1837-1838 Ernst Haeckel (1934-1919)

More information

Improving divergence time estimation in phylogenetics: more taxa vs. longer sequences

Improving divergence time estimation in phylogenetics: more taxa vs. longer sequences Mathematical Statistics Stockholm University Improving divergence time estimation in phylogenetics: more taxa vs. longer sequences Bodil Svennblad Tom Britton Research Report 2007:2 ISSN 650-0377 Postal

More information

Molecular Evolution & Phylogenetics Traits, phylogenies, evolutionary models and divergence time between sequences

Molecular Evolution & Phylogenetics Traits, phylogenies, evolutionary models and divergence time between sequences Molecular Evolution & Phylogenetics Traits, phylogenies, evolutionary models and divergence time between sequences Basic Bioinformatics Workshop, ILRI Addis Ababa, 12 December 2017 1 Learning Objectives

More information

Preliminaries. Download PAUP* from: Tuesday, July 19, 16

Preliminaries. Download PAUP* from:   Tuesday, July 19, 16 Preliminaries Download PAUP* from: http://people.sc.fsu.edu/~dswofford/paup_test 1 A model of the Boston T System 1 Idea from Paul Lewis A simpler model? 2 Why do models matter? Model-based methods including

More information

Phylogenetics: Parsimony and Likelihood. COMP Spring 2016 Luay Nakhleh, Rice University

Phylogenetics: Parsimony and Likelihood. COMP Spring 2016 Luay Nakhleh, Rice University Phylogenetics: Parsimony and Likelihood COMP 571 - Spring 2016 Luay Nakhleh, Rice University The Problem Input: Multiple alignment of a set S of sequences Output: Tree T leaf-labeled with S Assumptions

More information

Taming the Beast Workshop

Taming the Beast Workshop Workshop and Chi Zhang June 28, 2016 1 / 19 Species tree Species tree the phylogeny representing the relationships among a group of species Figure adapted from [Rogers and Gibbs, 2014] Gene tree the phylogeny

More information

arxiv: v1 [q-bio.pe] 4 Sep 2013

arxiv: v1 [q-bio.pe] 4 Sep 2013 Version dated: September 5, 2013 Predicting ancestral states in a tree arxiv:1309.0926v1 [q-bio.pe] 4 Sep 2013 Predicting the ancestral character changes in a tree is typically easier than predicting the

More information

CREATING PHYLOGENETIC TREES FROM DNA SEQUENCES

CREATING PHYLOGENETIC TREES FROM DNA SEQUENCES INTRODUCTION CREATING PHYLOGENETIC TREES FROM DNA SEQUENCES This worksheet complements the Click and Learn developed in conjunction with the 2011 Holiday Lectures on Science, Bones, Stones, and Genes:

More information

Mutation models I: basic nucleotide sequence mutation models

Mutation models I: basic nucleotide sequence mutation models Mutation models I: basic nucleotide sequence mutation models Peter Beerli September 3, 009 Mutations are irreversible changes in the DNA. This changes may be introduced by chance, by chemical agents, or

More information

Lecture Notes: Markov chains

Lecture Notes: Markov chains Computational Genomics and Molecular Biology, Fall 5 Lecture Notes: Markov chains Dannie Durand At the beginning of the semester, we introduced two simple scoring functions for pairwise alignments: a similarity

More information

Phylogene)cs. IMBB 2016 BecA- ILRI Hub, Nairobi May 9 20, Joyce Nzioki

Phylogene)cs. IMBB 2016 BecA- ILRI Hub, Nairobi May 9 20, Joyce Nzioki Phylogene)cs IMBB 2016 BecA- ILRI Hub, Nairobi May 9 20, 2016 Joyce Nzioki Phylogenetics The study of evolutionary relatedness of organisms. Derived from two Greek words:» Phle/Phylon: Tribe/Race» Genetikos:

More information

Estimating Evolutionary Trees. Phylogenetic Methods

Estimating Evolutionary Trees. Phylogenetic Methods Estimating Evolutionary Trees v if the data are consistent with infinite sites then all methods should yield the same tree v it gets more complicated when there is homoplasy, i.e., parallel or convergent

More information

Effects of Gap Open and Gap Extension Penalties

Effects of Gap Open and Gap Extension Penalties Brigham Young University BYU ScholarsArchive All Faculty Publications 200-10-01 Effects of Gap Open and Gap Extension Penalties Hyrum Carroll hyrumcarroll@gmail.com Mark J. Clement clement@cs.byu.edu See

More information

Molecular Evolution and Phylogenetic Tree Reconstruction

Molecular Evolution and Phylogenetic Tree Reconstruction 1 4 Molecular Evolution and Phylogenetic Tree Reconstruction 3 2 5 1 4 2 3 5 Orthology, Paralogy, Inparalogs, Outparalogs Phylogenetic Trees Nodes: species Edges: time of independent evolution Edge length

More information

Likelihood Ratio Tests for Detecting Positive Selection and Application to Primate Lysozyme Evolution

Likelihood Ratio Tests for Detecting Positive Selection and Application to Primate Lysozyme Evolution Likelihood Ratio Tests for Detecting Positive Selection and Application to Primate Lysozyme Evolution Ziheng Yang Department of Biology, University College, London An excess of nonsynonymous substitutions

More information

林仲彥. Dec 4,

林仲彥. Dec 4, 林仲彥 cylin@iis.sinica.edu.tw Dec 4, 2009 http://eln.iis.sinica.edu.tw Coding Characters and Defining Homology Classical phylogenetic analysis by Morphology Molecular phylogenetic analysis By Bio-Molecules

More information

Inferring phylogeny. Today s topics. Milestones of molecular evolution studies Contributions to molecular evolution

Inferring phylogeny. Today s topics. Milestones of molecular evolution studies Contributions to molecular evolution Today s topics Inferring phylogeny Introduction! Distance methods! Parsimony method!"#$%&'(!)* +,-.'/01!23454(6!7!2845*0&4'9#6!:&454(6 ;?@AB=C?DEF Overview of phylogenetic inferences Methodology Methods

More information

Andrew/CS ID: Midterm Solutions, Fall 2006

Andrew/CS ID: Midterm Solutions, Fall 2006 Name: Andrew/CS ID: 15-780 Midterm Solutions, Fall 2006 November 15, 2006 Place your name and your andrew/cs email address on the front page. The exam is open-book, open-notes, no electronics other than

More information

Molecular Evolution & Phylogenetics

Molecular Evolution & Phylogenetics Molecular Evolution & Phylogenetics Heuristics based on tree alterations, maximum likelihood, Bayesian methods, statistical confidence measures Jean-Baka Domelevo Entfellner Learning Objectives know basic

More information

Phylogenies Scores for Exhaustive Maximum Likelihood and Parsimony Scores Searches

Phylogenies Scores for Exhaustive Maximum Likelihood and Parsimony Scores Searches Int. J. Bioinformatics Research and Applications, Vol. x, No. x, xxxx Phylogenies Scores for Exhaustive Maximum Likelihood and s Searches Hyrum D. Carroll, Perry G. Ridge, Mark J. Clement, Quinn O. Snell

More information

Phylogenetic Trees. Phylogenetic Trees Five. Phylogeny: Inference Tool. Phylogeny Terminology. Picture of Last Quagga. Importance of Phylogeny 5.

Phylogenetic Trees. Phylogenetic Trees Five. Phylogeny: Inference Tool. Phylogeny Terminology. Picture of Last Quagga. Importance of Phylogeny 5. Five Sami Khuri Department of Computer Science San José State University San José, California, USA sami.khuri@sjsu.edu v Distance Methods v Character Methods v Molecular Clock v UPGMA v Maximum Parsimony

More information

进化树构建方法的概率方法 第 4 章 : 进化树构建的概率方法 问题介绍. 部分 lid 修改自 i i f l 的 ih l i

进化树构建方法的概率方法 第 4 章 : 进化树构建的概率方法 问题介绍. 部分 lid 修改自 i i f l 的 ih l i 第 4 章 : 进化树构建的概率方法 问题介绍 进化树构建方法的概率方法 部分 lid 修改自 i i f l 的 ih l i 部分 Slides 修改自 University of Basel 的 Michael Springmann 课程 CS302 Seminar Life Science Informatics 的讲义 Phylogenetic Tree branch internal node

More information

CHAPTERS 24-25: Evidence for Evolution and Phylogeny

CHAPTERS 24-25: Evidence for Evolution and Phylogeny CHAPTERS 24-25: Evidence for Evolution and Phylogeny 1. For each of the following, indicate how it is used as evidence of evolution by natural selection or shown as an evolutionary trend: a. Paleontology

More information

KaKs Calculator: Calculating Ka and Ks Through Model Selection and Model Averaging

KaKs Calculator: Calculating Ka and Ks Through Model Selection and Model Averaging Method KaKs Calculator: Calculating Ka and Ks Through Model Selection and Model Averaging Zhang Zhang 1,2,3#, Jun Li 2#, Xiao-Qian Zhao 2,3, Jun Wang 1,2,4, Gane Ka-Shu Wong 2,4,5, and Jun Yu 1,2,4 * 1

More information

Algorithmic Methods Well-defined methodology Tree reconstruction those that are well-defined enough to be carried out by a computer. Felsenstein 2004,

Algorithmic Methods Well-defined methodology Tree reconstruction those that are well-defined enough to be carried out by a computer. Felsenstein 2004, Tracing the Evolution of Numerical Phylogenetics: History, Philosophy, and Significance Adam W. Ferguson Phylogenetic Systematics 26 January 2009 Inferring Phylogenies Historical endeavor Darwin- 1837

More information

Week 5: Distance methods, DNA and protein models

Week 5: Distance methods, DNA and protein models Week 5: Distance methods, DNA and protein models Genome 570 February, 2016 Week 5: Distance methods, DNA and protein models p.1/69 A tree and the expected distances it predicts E A 0.08 0.05 0.06 0.03

More information

Evolutionary Analysis of Viral Genomes

Evolutionary Analysis of Viral Genomes University of Oxford, Department of Zoology Evolutionary Biology Group Department of Zoology University of Oxford South Parks Road Oxford OX1 3PS, U.K. Fax: +44 1865 271249 Evolutionary Analysis of Viral

More information

What Is Conservation?

What Is Conservation? What Is Conservation? Lee A. Newberg February 22, 2005 A Central Dogma Junk DNA mutates at a background rate, but functional DNA exhibits conservation. Today s Question What is this conservation? Lee A.

More information

MULTIPLE SEQUENCE ALIGNMENT FOR CONSTRUCTION OF PHYLOGENETIC TREE

MULTIPLE SEQUENCE ALIGNMENT FOR CONSTRUCTION OF PHYLOGENETIC TREE MULTIPLE SEQUENCE ALIGNMENT FOR CONSTRUCTION OF PHYLOGENETIC TREE Manmeet Kaur 1, Navneet Kaur Bawa 2 1 M-tech research scholar (CSE Dept) ACET, Manawala,Asr 2 Associate Professor (CSE Dept) ACET, Manawala,Asr

More information

"PRINCIPLES OF PHYLOGENETICS: ECOLOGY AND EVOLUTION" Integrative Biology 200B Spring 2009 University of California, Berkeley

PRINCIPLES OF PHYLOGENETICS: ECOLOGY AND EVOLUTION Integrative Biology 200B Spring 2009 University of California, Berkeley "PRINCIPLES OF PHYLOGENETICS: ECOLOGY AND EVOLUTION" Integrative Biology 200B Spring 2009 University of California, Berkeley B.D. Mishler Jan. 22, 2009. Trees I. Summary of previous lecture: Hennigian

More information