Braconid parasitoids are extremely diverse and fascinating organisms - attacking a variety of insect groups.
Here is a link to an excellent video from National Geographic
Until recently, the phylogeny of Braconidae has been controversial and largely unresolved, especially at higher taxonomic levels. Our recent paper utilized multiple nuclear genes to examine evolutionary relationships within Braconidae. Data for this study can be accessed here.
Currently we are examining divergence times across the major braconid lineages and how parasitism has evolved within the family. Members of Braconidae attack a wide variety of hosts. Some lineages are limited to specific groups of closely related insects (e.g. Helconinae on Cerambycidae and Buprestidae), while others have experienced multiple instances of host switching (e.g. Doryctinae). We are examining patterns of host usage in Braconidae and how host shifts may have contributed to differential diversification.
Genomic information offers a powerful tool for inferring phylogeny and for understanding pattern and process in evolution utilizing a phylogenetic framework. We recently tested the utility of transcriptome data for inferring superfamilial relationships in Hymenoptera (bees, ants, wasps, and sawflies) See here for abstract and links to raw data.
Analyzed data for this study can be accessed here.
In the future, we hope to expand genomic approaches to include a larger sampling of taxa across Hymenoptera. Additionally, phylogenomics offers great potential for understanding evolution in Ichneumonidae and Ichneumonoidea as a whole. Evolutionary relationships in ichneumonids are poorly understood.
Konrad Lohse has also been instrumental in utilizing genomic data for understanding phylogeographic patterns in gall wasp parasitoids. See here.
We also produced a methods paper on how to develop EPIC markers from ESTs in non-model organisms. See here.
In my lab we are extending this research to examine how EPIC markers can be utilized for species delimitation and for determining host associations in parasitoids. In addition to evolutionary research, these methods have excellent utility in biocontrol, agriculture, and ecology.
How introns evolve over time and in specific lineages is poorly understood. In collaboration with Dr. Domaratzki (Computer Science), we are examining how intron location, size, phase, and presence or absence evolves in insects and how these features can be predicted using phylogenetic methods. Mamun Sharif (M.Sc candidate in Computer Science) is developing automated tools to predict intron location in non-model organisms from transcriptome data. This tool will aid in rapid EPIC marker development as well as contribute to the studies on intron evolution