| 1. |
- Richards, Stephen, et al.
(author)
-
The genome of the model beetle and pest Tribolium castaneum.
- 2008
-
In: Nature. - 1476-4687. ; 452:7190, s. 949-55
-
Journal article (peer-reviewed)abstract
- Tribolium castaneum is a representative of earth’s most numerous eukaryotic order, a powerful model organism for the study of generalized insect development, and also an important pest of stored agricultural products. We describe its genome sequence here. This omnivorous beetle has evolved an ability to interact with a diverse chemical environment as evidenced by large expansions in odorant and gustatory receptors, as well as p450 and other detoxification enzymes. Developmental patterns in Tribolium are more representative of other arthropods than those found in Drosophila, a fact represented in gene content and function. For one, Tribolium has retained more ancestral genes involved in cell-cell communication than Drosophila, and some are expressed in the growth zone crucial for axial elongation in short germ development. Systemic RNAi in T. castaneum appears to use mechanisms distinct from those found in C. elegans, but nevertheless offers similar power for the elucidation of gene function and identification of targets for selective insect control.
|
|
| 2. |
- Doublet, Vincent, et al.
(author)
-
Unity in defence : honeybee workers exhibit conserved molecular responses to diverse pathogens
- 2017
-
In: BMC Genomics. - : BIOMED CENTRAL LTD. - 1471-2164. ; 18
-
Journal article (peer-reviewed)abstract
- Background: Organisms typically face infection by diverse pathogens, and hosts are thought to have developed specific responses to each type of pathogen they encounter. The advent of transcriptomics now makes it possible to test this hypothesis and compare host gene expression responses to multiple pathogens at a genome-wide scale. Here, we performed a meta-analysis of multiple published and new transcriptomes using a newly developed bioinformatics approach that filters genes based on their expression profile across datasets. Thereby, we identified common and unique molecular responses of a model host species, the honey bee (Apis mellifera), to its major pathogens and parasites: the Microsporidia Nosema apis and Nosema ceranae, RNA viruses, and the ectoparasitic mite Varroa destructor, which transmits viruses.Results: We identified a common suite of genes and conserved molecular pathways that respond to all investigated pathogens, a result that suggests a commonality in response mechanisms to diverse pathogens. We found that genes differentially expressed after infection exhibit a higher evolutionary rate than non-differentially expressed genes. Using our new bioinformatics approach, we unveiled additional pathogen-specific responses of honey bees; we found that apoptosis appeared to be an important response following microsporidian infection, while genes from the immune signalling pathways, Toll and Imd, were differentially expressed after Varroa/virus infection. Finally, we applied our bioinformatics approach and generated a gene co-expression network to identify highly connected (hub) genes that may represent important mediators and regulators of anti-pathogen responses.Conclusions: Our meta-analysis generated a comprehensive overview of the host metabolic and other biological processes that mediate interactions between insects and their pathogens. We identified key host genes and pathways that respond to phylogenetically diverse pathogens, representing an important source for future functional studies as well as offering new routes to identify or generate pathogen resilient honey bee stocks. The statistical and bioinformatics approaches that were developed for this study are broadly applicable to synthesize information across transcriptomic datasets. These approaches will likely have utility in addressing a variety of biological questions.
|
|
