Molecular Insights to Crustacean Phylogeny

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Molecular Insights to Crustacean Phylogeny MOLECULAR INSIGHTS TO CRUSTACEAN PHYLOGENY DISSERTATION zur Erlangung des Doktorgrades (Dr. rer. nat.) an der Mathematisch-Naturwissenschaftlichen Fakultät der Rheinischen Friedrich-Wilhelms-Universität Bonn vorgelegt von BJOERN MARCUS VON REUMONT Bonn – Oktober 2009 Angefertigt mit der Genehmigung der Mathematisch-Naturwissenschaftlichen Fakultät der Rheinischen Friedrich-Wilhelms-Universität Bonn. Diese Dissertation wurden am Zoologischen Forschungsmuseum Alexander Koenig in Bonn durchgeführt. Tag der mündlichen Prüfung 29.01.2010 Erscheinungsjahr 2010 Betreuer Prof. Dr. Johann-Wolfgang Waegele Prof. Dr. Bernhard Y. Misof […] Make up your mind, plan before and follow that plan. […] An unforgivenable sin is quitting. Never give up and keep on going. The only struggle should be to solve the problem or survive. […] Focus on the task and on the moment. […] Excerpts of a cave diving manual This basic philosophy for cave diving is not only useful in cave diving but also generally in live and was indeed helping not only once conducting this thesis. And while diving… Dedicated to my family and all good friends – a permanent, safe mainline Contents Molecular insights to crustacean phylogeny CONTENTS SUMMARY / ZUSAMMENFASSUNG 1. INTRODUCTION 1 1.1 CRUSTACEANS AND THEIR CONTROVERSIAL PHYLOGENY – A SHORT OVERVIEW 2 1.2 CONTRADICTING PHYLOGENY HYPOTHESES OF MAJOR CRUSTACEAN GROUPS 6 1.3 EARLY CONCEPTS OF ARTHROPODS AND MAJOR CLADES IN A MODERN BACKGROUND 8 1.4 QUINTESSENCE OF RECENT ARTHROPOD STUDIES 11 1.5 METHODOLOGICAL BACKGORUND 13 1.5.1 THE FUNDAMENT OF ALL MOLECULAR ANALYSES – TAXON CHOICE & 14 ALIGNMENT RECONSTRCUTION 1.5.2 SINGLE GENE DATA – INCORPORATING BACKGROUND KNOWLEDGE TO rRNA ANALYSES 15 1.5.3 PHYLOGENOMIC DATA – A GENERAL OVERVIEW 16 1.6 AIMS OF THE THESIS 19 1.7 SHORT INTRODUCTION AND OVERVIEW OF ANALYSES [A-C] 20 2. MATERIAL AND METHODS 21 2.1 SPECIES CHOICE, COLLECTION AND FIELDWORK 21 2.2 LABORATORY METHODS 26 2.3 DATA ANALYSES METHODS PRIOR TO PHYLOGENETIC TREE RECONSTRUCTION 30 2.3.1 SEQUENCE PROCESSING AND QUALITY CONTROL 31 2.3.2 MULTIPLE SEQUENCE ALIGNMENT 32 2.3.3 ALIGNMENT OPTIMIZATION BASED ON SECONDARY STRUCTURE INFORMATION 32 2.3.4 EVALUATING STRUCTURE AND SIGNAL BY NETWORK RECONSTRUCTION 33 2.3.5 ALIGNMENT EVALUATION AND PROCESSING 33 2.4 ANALYSES [A]| CAN 16S, 18S AND COI IMPROVE CRUSTACEAN PHYLOGENY WITHIN 35 ARTHROPODS? COMPARING “USUAL” STANDARD VS. SECONDARY STRUCTURE BASED APPROACHES. 2.4.1 OBJECTIVES 35 2.4.2 TAXON SAMPLING 35 2.4.3 ANALYSIS DESIGN 35 2.4.4 PHYLOGENETIC TREE RECONSTRUCTION 37 2.5 ANALYSIS [B]: IS IMPLEMENTATION OF SECONDARY STRUCTURE BASED ALIGNMENT 40 OPTIMIZATION AND TIME-HETEROGENEITY A SOLUTION TO SOLVE PHYLOGENY WITHIN ARTHROPODS? 2.5.1 OBJECTIVES 40 2.5.2 TAXON SAMPLING 40 2.5.3 ANALYSIS DESIGN 41 2.5.4 PHYLOGENETIC TREE RECONSTRUCTION 42 2.6 ANALYSES [C]: ENLIGTHS PHYLOGENOMIC DATA CRUSTACEAN PHYLOGENY WITHIN ARTHROPODS 46 – OR STICK OLD PROBLEMS TO THE ANALYSES OF THIS NEW LARGE SCALE DATA? 2.6.1 OBJECTIVES 46 2.6.2 TAXON SAMPLING 46 2.6.3 ANALYSIS DESIGN 47 2.6.4 PHYLOGENETIC TREE RECONSTRUCTION 53 Molecular insights to crustacean phylogeny Contents 2.7 ANALYSIS OF HEMOCYANIN STRUCTURE IN REMIPEDIA 55 2.7.1 OBJECTIVES 55 2.7.2 ANALYSIS DESIGN 55 2.7.3 PHYLOGENETIC TREE RECONSTRUCTION 55 3. RESULTS 57 3.1 ANALYSES [A]| CAN 16S, 18S AND COI IMPROVE CRUSTACEAN PHYLOGENY WITHIN 57 ARTHROPODS? COMPARING “USUAL” STANDARD VS. SECONDARY STRUCTURE BASED APPROACHES. 3.1.1 DATA SIGNAL AND SPLIT SUPPORTING PATTERNS 57 3.1.2 BASE COMPOSITIONS 60 3.1.3 PHYLOGENETIC RECONSTRUCTION 61 3.1.4 PROBLEMATICS OF THE DATA 65 3.2 ANALYSIS [B]: IS IMPLEMENTATION OF SECONDARY STRUCTURE BASED ALIGNMENT 66 OPTIMIZATION AND TIME-HETEROGENEITY A SOLUTION TO SOLVE PHYLOGENY WITHIN ARTHROPODS? 3.2.1 FINAL DATASET AND SPLIT SUPPORTING PATTERNS 66 3.2.2 COMPOSITIONAL HETEROGENEITY OF BASE FREQUENCY 68 3.2.3 PHYLOGENETIC MODEL TESTING & RECONSTRUCTIONS 69 3.2.4 RESULTING TOPOLOGIES 71 3.3 ANALYSES [C]: ENLIGTHS PHYLOGENOMIC DATA CRUSTACEAN PHYLOGENY WITHIN ARTHROPODS 75 – OR STICK OLD PROBLEMS TO THE ANALYSES OF THIS NEW LARGE SCALE DATA? 3.3.1 RESULTING TOPOLOGY OF THE UNREDUCED DATASET 75 3.3.2 RESULTING TOPOLOGIES OF THE REDUCED, OPTIMAL DATA SUBSET 76 3.3.3 DIFFERENCES IN ML AND BAYESIAN TOPOLOGIES OGF THE REDUCED DATA SUBSET 78 3.3.4 PROBLEMATICS IN RESULTING TOPOLOGIES OF THE BAYESIAN CHAINS 78 3.4 ANALYSIS OF HEMOCYANIN STRUCTURE IN REMIPEDIA 81 3.4.2 PHYLOGENETIC RECONSTRUCTION AND RESULTING TREE 81 4. DISCUSSION 83 4.1 SEPARATE METHODOLOGICAL DISCUSSION OF ANALYSIS [A-C] 83 4.1.1 ANALYSES [A] 83 4.1.2 ANALYSES [B] 85 4.1.3 ANALYSES [C] 88 4.2 PANCRUSTACEAN PHYLOGENY DISCUSSION 91 4.3 ARTHROPOD PHYLOGENY DISCUSSION 103 4.4 GENERAL MEHTODOLODICAL DISCUSSION 107 4.5 CONCLUSIONS AND FURTHER ASPECTS 114 5. REFERENCES 117 6. ABREVIATIONS 140 7. INDEX OF FIGURES AND TABLES 141 8. ACKNOWLEDGEMENT 143 9. SUPPLEMENT I 10. CURRICULUM VITAE –ERKLÄRUNG Above picture: Derocheilocaris typicus, a specimen of the Mystacocarida Cover picture: Some of the rather small but beautiful crustaceans (from above left: Branchiura, Mystacocarida, Copepoda, Ostracoda, Cladocera, Branchiopoda and Remipedia. Molecular insights to crustacean phylogeny Abstract / Zusammenfassung ABSTRACT A key role in arthropod phylogeny plays a group of organisms that was already in the focus of taxonomic research of Charles Darwin in the mid of the 19th century, namely the Crustacea. This extremely divers group comprises small species like the Mystacocarida (Derocheilocaris typicus) with only 0.3 mm body size or such big representatives like the Japanese giant crab (Macrocheira kaempferi) with a span width of almost 4 m. Generally accepted are six major crustacean taxa, the Malacostraca (Latreille, 1802), Branchiopoda (Latreille, 1817), Remipedia (Yager, 1981), Cephalocarida (Sanders, 1955), Maxillopoda (Dahl, 1956) and Ostracoda (Latreille 1802). The validity of the taxon Maxillopoda is to date still disputed. The monophyly of some crustacean groups like the Malacostraca and Branchiopoda is generally accepted, but for several other groups unclear. This thesis aims to resolve internal relationships of the major crustacean groups inferring phylogenies with molecular data. The crustaceans are in addition of eminent interest to enlight the question how land was successfully conquered by arthropod taxa. New molecular and neuroanatomical data support the scenario that the Hexapoda might have evolved from Crustacea. The thesis further seeks to address the possible close relationship of Crustacea and Hexapoda. That issue is closely linked to the partly still debated position of crustaceans within arthropods and the supposable sister-group of the Crustacea. Most molecular studies of crustaceans relied on single gene or multigene analyses in which for most cases partly sequenced rRNA genes were used. However, intensive data quality and alignment assessments prior to phylogenetic reconstructions are not conducted in most studies. Additionally, a complex modeling and the implementation of compositional base heterogeneity along lineages are missing. One methodological aim in this thesis was to implement new tools to infer data quality, to improve alignment quality and to test the impact of complex modeling of the data. Two of the three phylogenetic analyses in this thesis are also based on rRNA genes. In analysis (A) 16S rRNA, 18S rRNA and COI sequences were analyzed. RY coding of the COI fragment, an alignment procedure that considers the secondary structure of RNA molecules and the exclusion of alignment positions of ambiguous positional homology was performed to improve data quality. Anyhow, by extensive network reconstructions it was shown that the signal quality in the chosen and commonly used markers is not suitable to infer crustacean phylogeny, despite the extensive data processing and optimization. This result draws a new light on previous studies relying on these markers. In analyses (B) completely sequenced 18S and 28S rRNA genes were used to reconstruct the phylogeny. Base compositional heterogeneity was taken into account based on the finding of analysis (A), additionally to secondary structure alignment optimization and alignment assessment. The complex modeling to compare time-heterogeneous versus time- homogenous processes in combination with mixed models for an implementation of secondary structures was only possible applying the Bayesian software package PHASE. The results clearly demonstrated that complex modeling counts and that ignoring time- Abstract / Zusammenfassung Molecular insights to crustacean phylogeny heterogeneous processes can mislead phylogenetic reconstructions. Some results enlight the phylogeny of Crustaceans, for the first time the Cephalocarida (Hutchinsoniella macracantha) were placed in a clade with the Branchiopoda, which morphologically is plausible. Unfortunately, the internal relationships of most crustacean groups were still poorly supported. Compared to the time-homogeneous tree the time-heterogeneous tree gives lower support values for some nodes. It can be suggested, that the incorporation of base compositional heterogeneity in phylogenetic analysis improves the reliability of the topology. The Pancrustacea are supported maximally in both approaches, but internal relations are not reliably reconstructed. One result of this analysis is that the phylogenetic signal in rRNA data might be eroded for crustaceans. Recent publications presented analyses based on phylogenomic data, to reconstruct mainly metazoan
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