The Phylogenetic Handbook: A Practical Approach to Phylogenetic Analysis and Hypothesis Testing

751 Pages·2009·6.55 MB·English

by  Philippe Lemey

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The Phylogenetic Handbook
SecondEdition
The Phylogenetic Handbook provides a comprehensive introduction to theory and practice of
nucleotideandproteinphylogeneticanalysis.Thissecondeditionincludessevennewchapters,
coveringtopicssuchasBayesianinference,treetopologytesting,andtheimpactofrecombination
onphylogenies.Thebookhasastrongerfocusonhypothesistestingthanthepreviousedition,
withmoreextensivediscussionsonrecombinationanalysis,detectingmolecularadaptationand
genealogy-basedpopulationgenetics.Manychaptersincludeelaboratepracticalsections,which
have been updated to introduce the reader to the most recent versions of sequence analysis
andphylogenysoftware,includingBlast,FastA,Clustal,T-coffee,Muscle,Dambe,Tree-Puzzle,
Phylip,Mega4,Paup*,Iqpnni,Consel,ModelTest,ProtTest,Paml,HyPhy,MrBayes,Beast,Lamarc,
SplitsTree,andRdp3.Manyanalysistoolsaredescribedbytheiroriginalauthors,resultingin
clearexplanationsthatconstituteanidealteachingguideforadvanced-levelundergraduateand
graduatestudents.
PhilippeLemeyisaFWOpostdoctoralresearcherattheRegaInstitute,KatholiekeUniversiteit
Leuven,Belgium,wherehecompletedhisPh.D.inMedicalSciences.HehasbeenanEMBOFellow
andaMarie-CurieFellowintheEvolutionaryBiologyGroupattheDepartmentofZoology,
University of Oxford. His research focuses on molecular evolution of viruses by integrating
molecularbiologyandcomputationalapproaches.
MarcoSalemiisAssistantProfessorattheDepartmentofPathology,ImmunologyandLabo-
ratoryMedicineoftheUniversityofFloridaSchoolofMedicine,Gainesville,USA.Hisresearch
interests include molecular epidemiology, intra-host virus evolution, and the application of
phylogenetic and population genetic methods to the study of human and simian pathogenic
viruses.
Anne-Mieke Vandamme isaFullProfessorintheMedicalFacultyattheKatholiekeUni-
versiteit,Belgium,workinginthefieldofclinicalandepidemiologicalvirology.Herlaboratory
investigatestreatmentresponsesinHIV-infectedpatientsandisrespectedforitsscientificand
clinical contributions to virus–drug resistance. Her laboratory also studies the evolution and
molecularepidemiologyofhumanvirusessuchasHIVandHTLV.

The Phylogenetic Handbook
A Practical Approach to Phylogenetic
Analysis and Hypothesis Testing
Second Edition
Editedby
Philippe Lemey
KatholiekeUniversiteitLeuven,Belgium
Marco Salemi
UniversityofFlorida,Gainesville,USA
Anne-Mieke Vandamme
KatholiekeUniversiteitLeuven,Belgium
CAMBRIDGEUNIVERSITYPRESS
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Cambridge University Press
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Published in the United States of America by Cambridge University Press, New York
www.cambridge.org
Information on this title: www.cambridge.org/9780521877107
© Cambridge University Press 2009
This publication is in copyright. Subject to statutory exception and to the
provision of relevant collective licensing agreements, no reproduction of any part
may take place without the written permission of Cambridge University Press.
First published in print format 2009
ISBN-13 978-0-511-71963-9 eBook (NetLibrary)
ISBN-13 978-0-521-87710-7 Hardback
ISBN-13 978-0-521-73071-6 Paperback
Cambridge University Press has no responsibility for the persistence or accuracy
of urls for external or third-party internet websites referred to in this publication,
and does not guarantee that any content on such websites is, or will remain,
accurate or appropriate.
Contents
Listofcontributors pagexix
Foreword xxiii
Preface xxv
Section I: Introduction
1
1 Basic concepts of molecular evolution 3
Anne-MiekeVandamme
1.1 Geneticinformation 3
1.2 Populationdynamics 9
1.3 Evolutionandspeciation 14
1.4 Datausedformolecularphylogenetics 16
1.5 Whatisaphylogenetictree? 19
1.6 Methodsforinferringphylogenetictrees 23
1.7 Isevolutionalwaystree-like? 28
Section II: Data preparation
31
2 Sequence databases and database searching 33
Theory 33
GuyBottu
2.1 Introduction 33
2.2 Sequencedatabases 35
2.2.1 Generalnucleicacidsequencedatabases 35
2.2.2 Generalproteinsequencedatabases 37
2.2.3 Specializedsequencedatabases,referencedatabases,and
genomedatabases 39
2.3 Compositedatabases,databasemirroring,andsearchtools 39
2.3.1 Entrez 39
v
vi Contents
2.3.2 SequenceRetrievalSystem(SRS) 43
2.3.3 Somegeneralconsiderationsaboutdatabasesearching
bykeyword 44
2.4 Databasesearchingbysequencesimilarity 45
2.4.1 Optimalalignment 45
2.4.2 BasicLocalAlignmentSearchTool(Blast)4 7
2.4.3 FastA 50
2.4.4 Othertoolsandsomegeneralconsiderations 52
Practice 55
MarcVanRanstandPhilippeLemey
2.5 DatabasesearchingusingENTREZ 55
2.6 Blast 62
2.7 FastA 66
3 Multiple sequence alignment 68
Theory 68
DesHigginsandPhilippeLemey
3.1 Introduction 68
3.2 Theproblemofrepeats 68
3.3 Theproblemofsubstitutions 70
3.4 Theproblemofgaps 72
3.5 Pairwisesequencealignment 74
3.5.1 Dot-matrixsequencecomparison 74
3.5.2 Dynamicprogramming 75
3.6 Multiplealignmentalgorithms 79
3.6.1 Progressivealignment 80
3.6.2 Consistency-basedscoring 89
3.6.3 Iterativerefinementmethods 90
3.6.4 Geneticalgorithms 90
3.6.5 HiddenMarkovmodels 91
3.6.6 Otheralgorithms 91
3.7 Testingmultiplealignmentmethods 92
3.8 Whichprogramtochoose? 93
3.9 Nucleotidesequencesvs.aminoacidsequences 95
3.10 Visualizingalignmentsandmanualediting 96
Practice 100
DesHigginsandPhilippeLemey
3.11 Clustalalignment 100
3.11.1 Fileformatsandavailability 100
3.11.2 AligningtheprimateTrim5αaminoacidsequences 101
vii Contents
3.12 T-Coffeealignment 102
3.13 Musclealignment 102
3.14 ComparingalignmentsusingtheAltAVisTwebtool 103
3.15 Fromproteintonucleotidealignment 104
3.16 Editingandviewingmultiplealignments 105
3.17 Databasesofalignments 106
Section III: Phylogenetic inference
109
4 Genetic distances and nucleotide substitution models 111
Theory 111
KorbinianStrimmerandArndtvonHaeseler
4.1 Introduction 111
4.2 Observedandexpecteddistances 112
4.3 Numberofmutationsinagiventimeinterval*(optional) 113
4.4 NucleotidesubstitutionsasahomogeneousMarkovprocess 116
4.4.1 TheJukesandCantor(JC69)model 117
4.5 DerivationofMarkovProcess*(optional) 118
4.5.1 Inferringtheexpecteddistances 121
4.6 Nucleotidesubstitutionmodels 121
4.6.1 Rateheterogeneityamongsites 123
Practice 126
MarcoSalemi
4.7 Softwarepackages 126
4.8 Observedvs.estimatedgeneticdistances:theJC69model 128
4.9 Kimura2-parameters(K80)andF84geneticdistances 131
4.10 Morecomplexmodels 132
4.10.1 Modelingrateheterogeneityamongsites 133
4.11 EstimatingstandarderrorsusingMega4 135
4.12 Theproblemofsubstitutionsaturation 137
4.13 Choosingamongdifferentevolutionarymodels 140
5 Phylogenetic inference based on distance methods 142
Theory 142
YvesVandePeer
5.1 Introduction 142
5.2 Tree-inferencemethodsbasedongeneticdistances 144
5.2.1 Clusteranalysis(UPGMAandWPGMA) 144
5.2.2 Minimumevolutionandneighbor-joining 148
5.2.3 Otherdistancemethods 156
viii Contents
5.3 Evaluatingthereliabilityofinferredtrees 156
5.3.1 Bootstrapanalysis 157
5.3.2 Jackknifing 159
5.4 Conclusions 159
Practice 161
MarcoSalemi
5.5 Programstodisplayandmanipulatephylogenetictrees 161
5.6 Distance-basedphylogeneticinferenceinPhylip 162
5.7 InferringaNeighbor-Joiningtreefortheprimatesdataset 163
5.7.1 Outgrouprooting 168
5.8 InferringaFitch–MargoliashtreeforthemtDNAdataset 170
5.9 BootstrapanalysisusingPhylip 170
5.10 Impactofgeneticdistancesontreetopology:anexampleusing
Mega4 174
5.11 Otherprograms 180
6 Phylogenetic inference using maximum likelihood methods 181
Theory 181
HeikoA.SchmidtandArndtvonHaeseler
6.1 Introduction 181
6.2 Theformalframework 184
6.2.1 Thesimplecase:maximum-likelihoodtreefor
twosequences 184
6.2.2 Thecomplexcase 185
6.3 Computingtheprobabilityofanalignmentforafixedtree 186
6.3.1 Felsenstein’spruningalgorithm 188
6.4 Findingamaximum-likelihoodtree 189
6.4.1 Earlyheuristics 190
6.4.2 Full-treerearrangement 190
6.4.3 DNamlandfastDNAml 191
6.4.4 PhyMLandPhyMl-SPR 192
6.4.5 Iqpnni 192
6.4.6 RAxML 193
6.4.7 Simulatedannealing 193
6.4.8 Geneticalgorithms 194
6.5 Branchsupport 194
6.6 Thequartetpuzzlingalgorithm 195
6.6.1 Parameterestimation 195
6.6.2 MLstep 196
6.6.3 Puzzlingstep 196
6.6.4 Consensusstep 196
6.7 Likelihood-mappinganalysis 196