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Supplementary material for Identification and Characterization of Three Chemosensory Receptor Families in the Cotton Bollworm Helicoverpa armigera
Supplementary data for the BMC Genomics paper titled: "Identification and Characterization of Three Chemosensory Receptor Families in the Cotton Bollworm Helicoverpa armigera"
Gene Expression (incl. Microarray and other genome-wide approaches)
The raw data used to produce these are derived and available from NCBI's BioProject PRJNA244590
Nai-Yong Liu and Wei Xu for phylogenetics
Alexie Papanicolaou for expression analysis
CSIRO Data Licence
CSIRO; Liu, Naiyong; Xu, Wei; Papanicolaou, Alexie; Dong, Shuang-Lin; Anderson, Alisha (2014): Supplementary material for Identification and Characterization of Three Chemosensory Receptor Families in the Cotton Bollworm Helicoverpa armigera. v2. CSIRO. Data Collection.
All Rights (including copyright) CSIRO Australia 2014.
The metadata and files (if any) are available to the public.
Catalytic Dissecting Adaptive Potential
Background: Chemosensory receptors including olfactory receptors (ORs), gustatory receptors (GRs) and ionotropic receptors (IRs) play a central role in sensing chemical signals and guiding insect behaviours, and are potential target genes in insect pest control. The cotton bollworm Helicoverpa armigera is one of the most destructive pest species th... moreat can feed on over 200 different plant species. This diversity of host plants is likely linked to a complex chemosensory system. Here we built on previous work to characterize crucial chemosensory tissues linked to environmental interactions including larval antennae, larval mouthparts, as well as male and female adult heads, male and female adult tarsi.
Results: Using transcriptome sequencing, Trinity RNA-seq assemblies and extensive manual curation, we identified a total of 91 candidate chemosensory receptors (60 candidate ORs, 10 GRs and 21 IRs). 35 of these candidates represent full-length transcripts. Further, we created extensive expression profiles using reverse transcription (RT)-PCR on a variety of adult and larval stages. We found that the expression profile of HarmOR51 was limited to adult male antenna suggesting a role in mating that was further supported by a phylogenetic analysis clustering it into the pheromone receptor clade. HarmOR51 in calcium imaging analysis did not show responses to either of the two H. armigera sex pheromone components (Z9-16:Ald or Z11-16:Ald) inviting a future detailed study. In addition, we found four novel HarmORs (OR1, 53, 54 and 58) that appeared to be larvae-antennal specific. Finally, our expression profiling showed that four “divergent” HarmIRs (IR2, 7d.1, 7d.2 and 7d.3) were expressed in both adult and larval antennae, suggesting a functional divergence from their Drosophila homologues.
Conclusions: This study explored three chemoreceptor superfamily genes using a curated transcriptomic approach coupled with extensive expression profiling and a more limited functional characterization. Our results have now provided an extensive resource for investigating the chemoreceptor complement of this insect pest and allow for targeted experiments to identify potential molecular targets for pest control and investigate insect-plant interactions. less
Alignments of amino acid sequences were performed by ClustalW2 and were visualized by Jalview 2.7 . Phylogenetic trees were constructed by PhyML based on Jones-Taylor-Thornton (JTT) model with Nearest Neighbour Interchange (NNI). Branch support was estimated by approximate likelihood ratio test (Chi2). In the OR data set, we selected the ORs with... more available genomic databases from B. mori , D. plexippus and H. melpomene . Due to the small number of HarmGRs, we only selected GRs from two species, a moth B. mori and a butterfly D. plexippus . In the IR data set, we selected IRs from lepidopteran species including B. mori , C. pomonella , D. plexippus , M. sexta , S. littoralis and S. nonagrioides but also IRs and iGluRs from a model insect D. melanogaster . Trees were viewed and edited using iTol . Networks using protein identity were generated using custom scripts and analyzed with CytoScape and clusterMarker . less
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