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Species Tree Inference: A Guide to Methods and Applications [Pehme köide]

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  • Formaat: Paperback / softback, 352 pages, kõrgus x laius: 254x178 mm, 101 b/w figures. 6 tables.
  • Ilmumisaeg: 14-Mar-2023
  • Kirjastus: Princeton University Press
  • ISBN-10: 0691207607
  • ISBN-13: 9780691207605
Teised raamatud teemal:
Species Tree Inference: A Guide to Methods and ApplicationsSuurem pilt
  • Formaat: Paperback / softback, 352 pages, kõrgus x laius: 254x178 mm, 101 b/w figures. 6 tables.
  • Ilmumisaeg: 14-Mar-2023
  • Kirjastus: Princeton University Press
  • ISBN-10: 0691207607
  • ISBN-13: 9780691207605
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780691207605.html
Märksõnad:
"Inferring evolutionary relationships among a collection of organisms -- that is, their relationship to each other on the tree of life -- remains a central focus of much of evolutionary biology as these relationships provide the background for key hypotheses. For example, support for different hypotheses about early animal evolution are contingent upon the phylogenetic relationships among the earliest animal lineages. Within the last 20 years, the field of phylogenetics has grown rapidly, both in the quantity of data available for inference and in the number of methods available for phylogenetic estimation. The authors' first book, "Estimating Species Trees: Practical and Theoretical Aspects", published in 2010, gave an overview of the state of phylogenetic practice for analyzing data at the time, but much has changed since then. The goal of this book is to serve as an updated reference on current methods within the field. The book is organized in three sections, the first of which provides an overview of the analytical and methodological developments of species tree inference. Section two focuses on empirical inference. Section three explores various applications of species trees in evolutionary biology. The combination of theoretical and empirical approaches is meant to provide readers with a level of knowledge of both the advances and limitations of species-tree inference that can help researchers in applying the methods, while also inspiring future advances among those researchers with an interest inmethodological development"--

An up-to-date reference book on phylogenetic methods and applications for evolutionary biologists

The increasingly widespread availability of genomic data is transforming how biologists estimate evolutionary relationships among organisms and broadening the range of questions that researchers can test in a phylogenetic framework. Species Tree Inference brings together many of today’s leading scholars in the field to provide an incisive guide to the latest practices for analyzing multilocus sequence data.

This wide-ranging and authoritative book gives detailed explanations of emerging new approaches and assesses their strengths and challenges, offering an invaluable context for gauging which procedure to apply given the types of genomic data and processes that contribute to differences in the patterns of inheritance across loci. It demonstrates how to apply these approaches using empirical studies that span a range of taxa, timeframes of diversification, and processes that cause the evolutionary history of genes across genomes to differ.

By fully embracing this genomic heterogeneity, Species Tree Inference illustrates how to address questions beyond the goal of estimating phylogenetic relationships of organisms, enabling students and researchers to pursue their own research in statistically sophisticated ways while charting new directions of scientific discovery.

Arvustused

"A very well-constructed reference book."---April Marie Wright, Trends in Ecology & Evolution "A very good and thorough overview of methods and applications to infer evolutionary relationship between recently diverged taxa." * Conservation Biology *

Preface xvii
Acknowledgments xix
List of Contributors
xxi
Chapter 1 Introduction to Species Tree Inference
1(14)
1.1 Introduction
1(1)
1.2 Background and Terminology
2(7)
1.2.1 Definitions and Terminology
2(3)
1.2.2 An Introduction to the Multispecies Coalescent
5(1)
1.2.3 Data Types and Technologies for Generating Phylogenomic Data
6(3)
1.3 Overview of Current Methods for Species Tree Inference
9(3)
1.3.1 Controversies in the Estimation of Species Trees
11(1)
1.4 A Look to the Future
12(2)
1.4.1 Current Limitations and Future Prospects
12(1)
1.4.2 Beyond the Species Tree
13(1)
1.5 Organization of This Book
14(1)
PART I Analytical and Methodological Developments
15(130)
Chapter 2 Large-Scale Species Tree Estimation
19(24)
2.1 Introduction
19(2)
2.2 Species Tree Estimation Methods Addressing ILS
21(8)
2.2.1 Overview
21(1)
2.2.2 Summary Methods
21(3)
2.2.3 Coestimation Methods
24(2)
2.2.4 Site Based Methods
26(2)
2.2.5 Evaluation of Branch Support in Species Trees
28(1)
2.3 Species Tree Estimation under GDL
29(1)
2.4 Parallel Implementations for Species Tree Estimation
30(3)
2.4.1 ASTRAL-MP
30(1)
2.4.2 Multilocus Species Tree Estimation Using Maximum Likelihood
31(2)
2.5 Divide-and-Conquer Species Tree Estimation
33(3)
2.5.1 Divide-and-Conquer Using Supertree Methods
34(1)
2.5.2 Divide-and-Conquer Using Disjoint Tree Merger Methods
34(2)
2.6 Choice of Method
36(3)
2.6.1 Statistical Consistency
36(1)
2.6.2 Empirical Performance
37(2)
2.7 Summary, Challenges, and Future Directions
39(2)
2.8 Appendix: Big-O Analysis
41(2)
Chapter 3 Species Tree Estimation Using ASTRAL: Practical Considerations
43(25)
3.1 Introduction
43(3)
3.2 ASTRAL Algorithm
46(5)
3.2.1 Motivation and History
46(1)
3.2.2 ASTRAL Algorithm
47(3)
3.2.3 Summary of Known Theoretical Results Related to ASTRAL
50(1)
3.3 Accuracy
51(3)
3.4 Running Time
54(1)
3.5 Input to ASTRAL: Practical Considerations
54(7)
3.5.1 Gene Tree Estimation
55(2)
3.5.2 Filtering of Data
57(4)
3.6 ASTRAL Output
61(4)
3.6.1 Species Tree Topology and Its Quartet Score
61(1)
3.6.2 Branch Lengths in Coalescent Units
61(3)
3.6.3 Branch Support Using Local Posterior Probability (localPP)
64(1)
3.7 Follow-up Analyses and Visualization
65(1)
3.7.1 Tests for Polytomies
65(1)
3.7.2 Per Branch Quartet Support (Measure of Discordance)
65(1)
3.8 Conclusion
66(2)
Chapter 4 Species Tree Estimation Using Site Pattern Frequencies
68(21)
4.1 Introduction
68(1)
4.2 Estimation of the Species Tree Topology Using SVDQuartets
69(13)
4.2.1 Theoretical Basis
69(5)
4.2.2 Accounting of Incomplete Lineage Sorting in SVDQuartets
74(1)
4.2.3 Species Tree Inference: Quartet Sampling and Assembly
75(1)
4.2.4 Algorithmic Details
76(2)
4.2.5 Uncertainty Quantification
78(1)
4.2.6 Application to Species Relationships among Gibbons
78(1)
4.2.7 Properties of SVDQuartets
79(3)
4.2.8 Recommendations for Using SVDQuartets
82(1)
4.3 Estimation of Speciation Times
82(5)
4.3.1 Theoretical Basis
83(3)
4.3.2 Algorithmic Details
86(1)
4.3.3 Uncertainty Quantification
86(1)
4.3.4 Application to Species Relationships among Gibbons
87(1)
4.3.5 Recommendations for Using Composite Likelihood Estimators of the Speciation Times
87(1)
4.4 Conclusion and Future Work
87(2)
Chapter 5 Practical Aspects of Phylogenetic Network Analysis Using PhyloNet
89(31)
5.1 Introduction
89(2)
5.2 Reading and Interpretation of a Phylogenetic Network
91(1)
5.2.1 Phylogenetic Network Parameters and Their Identifiability
92(1)
5.3 Heuristic Searches, Point Estimates, and Posterior Distributions, or, Why Am I Getting Different Networks in Different Runs?
92(4)
5.4 Illustration of the Various Inference Methods in PhyloNet
96(10)
5.4.1 Inference under the MDC Criterion
96(2)
5.4.2 Maximum Likelihood Inference
98(4)
5.4.3 Maximum Pseudolikelihood Inference
102(1)
5.4.4 Bayesian Inference
103(2)
5.4.5 Running Time
105(1)
5.5 Analysis of Larger Data Sets
106(5)
5.6 Comparison and Summarization of Networks
111(1)
5.6.1 Displayed Trees
111(1)
5.6.2 Backbone Networks
111(1)
5.6.3 Tree Decompositions
112(1)
5.6.4 Tripartitions
112(1)
5.6.5 Major Trees
112(1)
5.7 Reticulate Evolutionary Processes in PhyloNet
112(5)
5.7.1 Analysis of Polyploids
114(3)
5.8 Conclusions
117(3)
Notes
119(1)
Chapter 6 Network Thinking: Novel Inference Tools and Scalability Challenges
120(25)
6.1 Introduction: The Impact of Gene Glow
120(2)
6.2 Trees versus Networks
122(2)
6.3 Species Networks
124(5)
6.3.1 Explicit versus Implicit Networks
126(1)
6.3.2 Extended Parenthetical Format
127(1)
6.3.3 Displayed Trees and Subnetworks
128(1)
6.3.4 Comparison of Networks
128(1)
6.4 Fast Reconstruction of Species Networks
129(14)
6.4.1 Maximum Pseudolikelihood Estimation
130(6)
6.4.2 Rooting of Semidirected Networks
136(3)
6.4.3 Goodness of Fit Tools
139(1)
6.4.4 Bootstrap Analysis
140(3)
6.5 Appendix: Installation and Use of the PhyloNetworks Julia Package
143(2)
6.5.1 Main Functions in PhyloNetworks
143(2)
PART II Empirical Inference
145(66)
Chapter 7 Phylogenomic Conflict in Plants
149(12)
7.1 Introduction
149(3)
7.2 Two Examples of Gene Tree Conflict within Angiosperms
152(2)
7.3 The Consequences of Gene Tree Conflict in Phylogenomics
154(6)
7.3.1 Inference of Species Trees
154(3)
7.3.2 Gene Duplication and Genome Duplication
157(1)
7.3.3 Divergence Time and Comparative Analyses
158(2)
7.4 Resolution of the Tree of Plant Life
160(1)
Chapter 8 Hybridization in lochroma
161(14)
8.1 Introduction
161(2)
8.2 Methods
163(5)
8.2.1 Study System
163(2)
8.2.2 Experimental Design
165(1)
8.2.3 Target Capture and Assembly
166(1)
8.2.4 Detection of Patterns of Hybridization from Gene Tree Distributions
167(1)
8.2.5 Testing of Hybridization in Empirical Data Sets
168(1)
8.3 Results
168(4)
8.3.1 Addition of Hybrid Taxa Increases Discordance and Decreases Tree-Like Signal
168(2)
8.3.2 Tests of Hybridization Support Different Relationships than Expected
170(2)
8.4 Discussion
172(2)
8.4.1 Effects of Hybridization on Patterns of Gene Tree Discordance
172(1)
8.4.2 Challenges in Determining the Exact Hybrid Relationships
172(1)
8.4.3 Hybridization in lochrominae
173(1)
8.5 Conclusions
174(1)
Chapter 9 Hybridization and Polyploidy in Penstemon
175(16)
9.1 Introduction
175(1)
9.2 Approach
176(3)
9.2.1 Calculation of Quartet Concordance Factors
177(1)
9.2.2 Bootstrapping and Gene Tree Uncertainty
178(1)
9.2.3 Validation of QCF Estimation
178(1)
9.2.4 Implementation
179(1)
9.3 Materials and Methods
179(3)
9.3.1 Study System
179(1)
9.3.2 Sample Collection, DNA Extraction, and Amplicon Sequencing
180(1)
9.3.3 Species Tree Inference
181(1)
9.3.4 Candidate Hybridization Events from Rooted Triples
181(1)
9.3.5 Species Network Inference
182(1)
9.4 Results
182(4)
9.4.1 Nuclear Amplicon Data
182(1)
9.4.2 Species Tree Inference
182(4)
9.4.3 Tests for Hybridization and Species Network Inference
186(1)
9.5 Discussion
186(4)
9.5.1 Taxonomy of Subsections Humiles and Proceri
188(1)
9.5.2 Character Evolution and Biogeography
189(1)
9.5.3 Phylogenetics of Hybrids and Polyploids
189(1)
9.6 Conclusions
190(1)
Chapter 10 Comparison of Linked versus Unlinked Character Models for Species Tree Inference
191(20)
10.1 Introduction
191(1)
10.2 Methods
192(3)
10.2.1 Simulations of Error-Free Data Sets
192(1)
10.2.2 Introduction of Site Pattern Errors
193(1)
10.2.3 Assessment of Sensitivity to Errors
194(1)
10.2.4 Project Repository
194(1)
10.3 Results
195(2)
10.3.1 Behavior of Linked (StarBEAST2) versus Unlinked (Ecoevolity) Character Models
195(1)
10.3.2 Analysis of All Sites versus SNPs with Ecoevolity
195(2)
10.3.3 Coverage of Credible Intervals
197(1)
10.3.4 MCMC Convergence and Mixing
197(1)
10.4 Discussion
197(14)
10.4.1 Robustness to Character-Pattern Errors
207(1)
10.4.2 Relevance to Empirical Data Sets
208(1)
10.4.3 Recommendations for Using Unlinked-Character Models
209(1)
10.4.4 Other Complexities of Empirical Data in Need of Exploration
209(2)
PART III Beyond the Species Tree
211(66)
Chapter 11 The Unfinished Synthesis of Comparative Genomics and Phylogenetics: Examples from Flightless Birds
215(17)
11.1 Introduction
215(3)
11.1.1 Phylogenetics of Modern Birds
216(2)
11.1.2 Paleognathous Birds as a Test Case for Post-Genomic Phylogenetics
218(1)
11.2 Building of a Whole-Genome Species Tree for an Ancient Radiation of Birds
218(7)
11.3 The Unfinished Synthesis of Comparative Genomics and Genomic Heterogeneity
225(6)
11.3.1 A Species Tree for Paleognathous Birds as a Foundation for Comparative Genomics
225(1)
11.3.2 Accommodation of Uncertainty into Whole-Genome Alignments
225(3)
11.3.3 Gene Tree Heterogeneity and Detecting Rate Variation in Genes and Noncoding Regions
228(2)
11.3.4 Phylogenetic Analysis of Quantitative `Omics Data: Gene Expression and Epigenetics'
230(1)
11.4 Conclusions
231(1)
Chapter 12 Phylogenetic Analysis under Heterogeneity and Discordance
232(19)
12.1 Introduction
232(1)
12.2 The Origin of Discordance
232(6)
12.2.1 A History of Systems and Methods
232(2)
12.2.2 Concepts of Harmony and Discordance
234(2)
12.2.3 The Species Tree
236(2)
12.2.4 Comparison of the Incomparable
238(1)
12.3 Characterization and Quantification of Phylogenetic Heterogeneity
238(5)
12.3.1 Quantification and Visualization of Discordance
238(2)
12.3.2 Quantification of Conflict and Tree Evaluation
240(1)
12.3.3 Visualization of Conflict
241(2)
12.4 Analysis under Phylogenetic Heterogeneity
243(7)
12.4.1 Testing of Introgression and Hybridization under Phylogenetic Heterogeneity
243(2)
12.4.2 Testing of Selection under Phylogenetic Heterogeneity
245(2)
12.4.3 Testing of Traits under Phylogenetic Heterogeneity
247(2)
12.4.4 Testing of Coevolution under Phylogenetic Heterogeneity
249(1)
12.5 Conclusion
250(1)
Chapter 13 The Multispecies Coalescent in Space and Time
251(9)
13.1 Introduction
251(1)
13.2 Coalescent Simulations
252(4)
13.2.1 Units, Space, and Time
253(2)
13.2.2 Tree Size, Tree Space, and Phylogenetic Decay
255(1)
13.3 Linked Genealogies and Gene Tree Inference
256(2)
13.4 Conclusions
258(2)
Chapter 14 Tree Set Visualization, Exploration, and Applications
260(17)
14.1 Introduction to Visualizing and Exploring Tree Sets
260(4)
14.1.1 Tree Set Visualization
261(1)
14.1.2 Detection of Structure in Tree Sets
262(2)
14.2 Applications to Gene Trees, Species Trees, and Phylogenomics
264(11)
14.2.1 Sensitivity to Models of Sequence Evolution
264(4)
14.2.2 Joint versus Independent Inference of Gene Trees
268(3)
14.2.3 Understanding of Variation across Genomes
271(4)
14.2.4 Prospects for Future Development and Application
275(1)
14.3 Appendix
275(2)
Bibliography 277(40)
Index 317
Laura S. Kubatko is Professor of Statistics and of Evolution, Ecology, and Organismal Biology at The Ohio State University. L. Lacey Knowles is the Robert B. Payne Collegiate Professor of Ecology and Evolutionary Biology and Curator of Insects at the University of Michigan. They are the coeditors of Estimating Species Trees: Practical and Theoretical Aspects.