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Sniffing out Evolution

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Sniffing out Evolution WAGENINGEN NIFFING OUT VOLUTION UR S E Congruence of Fragrances and Phylogenetic Relationships in Annonaceae Jeike L. van de Poel BSc. – MBI 890421659010 Under supervision of Dr. Lars Chatrou and Dr. Kate Goodrich Biosystematics group, October 2012 Course code: BIS-80439 Abstract The flowering plants are a relatively young group that has reached high levels of diversity and harbors an enormous assortment of chemical components. Annonaceae encompass an astounding amount of different flower fragrances. Floral odor is important in the attraction of pollinators, especially if the pollinators in question are beetles, which is the case for most Annonaceae. A floral fragrance consists of approximately 100 Volatile Organic Compounds. From two genera within the Annonaceae (Asimina Adans. and Deeringothamnus Small) the complete chemical composition of the floral scent has been studied. These chemical data were provided in order to perform optimizations over a simplified version of an existing phylogenetic tree based on chloroplast markers (ITS, accD-psal, matK-trnK, psbA-trnH, psbM-ycf6, rpL16 intron, rpl32-trnl, rpoB-trnC, trnC-ycf6, trnL-trnL-trnF, trnS-psbC, trnS-trnfM, ycf1). Due to a lack of previous studies in which phylogenetic analysis and extensive collection of fragrance data are combined, there is no real agreement as to what is the best method to use fragrance data in phylogenetic analyses. The aim of this study is to find out which method (within Maximum Parsimony and Maximum Likelihood optimization) is best to use for optimization of components from floral fragrances, and whether it is possible to use chemical data as a means to resolve polytomies. Two major biosynthetic pathways of floral volatiles are reconstructed with the help of the KEGG-database and the Plant Metabolic Network. These pathways enable the creation of stepmatrices, which assign costs to the transition of one volatile organic compound into another. Chemical components are treated as character states (polymorphic characters) or all components from one species’ fragrance are grouped together into a different character state, which is called a ‘scenario’. Maximum Parsimony optimization with an asymmetric stepmatrix as a cost-model was expected to lead to the best results. However, a symmetric stepmatrix performs better during tests. Scenarios are interesting, but optimization-results are hard to interpret, due to the large amount of components that are present in one scenario. Therefore it is suggested to do a Maximum Likelihood optimization (with a symmetric Mk1-model) as a follow up. Optimization of chemical data seems apt to resolve polytomies. However, a lot of improvements have to be implemented in future studies, before these (somewhat preliminary) conclusions can be fully supported. Keywords Annonaceae, Asimina, chemical pathways, cladogram, Deeringothamnus, floral fragrance, optimization, volatile organic compounds. 1 | P a g e Table of Contents Abstract ................................................................................................................................... 1 List of Tables and Figures ............................................................................................................ 4 Preface ..................................................................................................................................... 5 Introduction .............................................................................................................................. 6 Floral Fragrance ...................................................................................................................... 6 Annonaceae ........................................................................................................................... 7 Algorithms ............................................................................................................................. 7 Questions and Hypotheses ........................................................................................................ 8 Materials and Methods ................................................................................................................ 9 Scent sampling ....................................................................................................................... 9 Dynamic Headspace Sampling ................................................................................................ 9 Static Headspace Sampling (SPME) ......................................................................................... 9 GC-MS ................................................................................................................................ 9 Data .................................................................................................................................... 10 Tree ................................................................................................................................. 10 Chemical components ......................................................................................................... 10 Data Editing ....................................................................................................................... 10 Simulation............................................................................................................................ 12 Fiction .............................................................................................................................. 14 Maximum Parsimony (MP) ................................................................................................... 16 Maximum Likelihood (ML) .................................................................................................... 19 Recommendations .............................................................................................................. 21 Computational Methods .......................................................................................................... 21 Stepmatrices ..................................................................................................................... 21 Optimizations ..................................................................................................................... 22 Results ................................................................................................................................... 24 Lead-up ............................................................................................................................... 24 Resolved trees ................................................................................................................... 24 Stepmatrices ..................................................................................................................... 24 MP, polymorphic characters .................................................................................................... 24 Chorismate-pathway ........................................................................................................... 24 Terpenes-pathway .............................................................................................................. 25 MP, scenarios ....................................................................................................................... 26 Chorismate-pathway ........................................................................................................... 26 Terpenes-pathway .............................................................................................................. 28 MP, pScores ......................................................................................................................... 32 ML ...................................................................................................................................... 33 Rates ................................................................................................................................ 33 Scenario-components .......................................................................................................... 33 Optimizations ..................................................................................................................... 34 Discussion .............................................................................................................................. 36 2 | P a g e Components ......................................................................................................................... 36 Pollination ............................................................................................................................ 36 GC-AED ............................................................................................................................ 36 Quantities ......................................................................................................................... 36 Environmental Issues ............................................................................................................. 36 Chemical pathways ................................................................................................................ 37 Stepmatrices ..................................................................................................................... 37 Mesquite .............................................................................................................................
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