Seventh International Congress of Hymenopterists

7 th International Congress of Hymenopterists
20-26 June 2010, Kszeg Hungary
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Countless molecular data of Hymenoptera species have been gathered over the last years,
constantly growing in size and number. Our knowledge on Hymenoptera phylogeny is
currently limited by the ability to combine these data in a fast, yet accurate and objective way.
We present a novel approach to overcome this problem and to exploit what was published
before and hence picture what we virtually already know. We used all molecular data of
Hymenoptera taxa accessible through GenBank and put them in a single analysis. Our study
combines approaches to several issues on different levels:
Firstly, we provide a methodical pipeline on how to acquire and prepare those enormous and
variable data for the final tree reconstruction, including automatic download, orthologue
search, sequence processing, quality management, alignment, partitioning, filtering
ambiguous or randomly similar sites and eliminating heterogeneity.
Secondly, we present the methods of tree reconstruction that can be performed with very large
datasets in a reasonable time and with high accuracy. Our method of choice is tree
reconstruction with a super distance matrix (SDM). The super distance matrix is obtained by
combining NJtrees of single genes with optimized branch lengths. Subsequently, the
phylogenetic tree is reconstructed from the matrix with a neighbour-joining algorithm. The
SDM method also provides a super variance matrix that allows identification and elimination
of unplaceable taxa.
Thirdly, we show our results on Hymenoptera phylogeny. Open questions include systematic
status and positioning of recognized superfamilies and of higher taxa, such as Aculeata,
Proctotrupomorpha, and Evaniomorpha. Additionally to our contribution to understanding the
origin and evolution of Hymenoptera these results allow us to point out open questions or
weakly supported nodes to guide future studies in terms of taxon and marker selection.
Our dataset comprises more than 300 nuclear and mitochondrial genes and some 2000
Hymenoptera species from more than 70 families from all 22 superfamilies currently
recognized.
The Hymenoptera are exceptionally numerous and diverse in terms of life history and feeding
habits, i.e. include parasitoids, predators, phytophaga, eusocial and solitary taxa, and are
known to be systematically challenging. This makes them an excellent exemplar clade for our
approach. However, the presented approach is designed as a general approach and can be
applied to all taxa following the presented pipelines of data preparation and analysis.
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The poverty of partitioned analyses and character-type chauvinism
Kurt M. Pickett 1 * & James M. Carpenter 2
1 Department of Biology, University of Vermont, 120A Marsh Life Science Building, 109 Carrigan Drive,
Burlington, VT 05405, USA; kurt.pickett@uvm.edu
2 American Museum of Natural History, NYC, USA; carpente@amnh.org
Phylogenetic analyses of individual partitions of data (gene fragments, parts of the
morphology, behavior, etc). sometimes give different results. This should be of no surprise,
as even small amounts of data from the same partition will do the same. However, the
common interpretation that is given is that morphology and molecules show fundamentally
different patterns, leading researchers to simply pick the phylogeny from whichever data
source they prefer, or to malign the utility of another data source entirely. Using social wasps
and their close relatives as examples, we show that multiple different analyses that combine
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