Ontology highlight
ABSTRACT:
PROVIDER: PRJNA882911 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR21665163_1.fastq.gz | Fastqsanger.gz | |||
| SRR21665163_2.fastq.gz | Fastqsanger.gz | |||
| SRR21665164_subreads.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 3 of 3 |
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Project description:We utilized three ecologically diverse Drosophila species to explore the influence of ecological adaptation on transcriptomic responses to isocaloric diets differing in their relative proportions of protein to sugar. Drosophila melanogaster, a cosmopolitan species that breeds in decaying fruit, exemplifies individuals long exposed to a Western diet higher in sugar, while the natural diet of the cactophilic D. mojavensis, is much lower in carbohydrates. Drosophila arizonae, the sister species of D. mojavensis, is largely cactophilic, but also utilizes rotting fruits that are higher in sugars than cacti. We exposed third instar larvae for 24 hours to diets either (1) high in protein relative to sugar, (2) diets with equal amounts of protein and sugar, and (3) diets low in protein but high in sugar. As we predicted, based upon earlier interspecific studies of development and metabolism, the most extreme differences in gene expression under different dietary conditions were found in D. mojavensis followed by D. arizonae. No differential expression among diets was observed for D. melanogaster, a species that survives well under all three conditions, with little impact on its metabolism. We suggest that these three species together provide a model to examine individual and population differences in vulnerability to lifestyle-associated health problems such as metabolic syndrome and diabetes.
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Project description:Although the importance of host plant chemistry in plant-insect interactions is widely accepted, the genetic basis of adaptation to host plants is poorly understood. Here, we investigate transcriptional changes associated with a host plant shift in Drosophila mettleri. While D. mettleri is distributed mainly throughout the Sonoran Desert where it specializes on columnar cacti (Carnegiea gigantea and Pachycereus pringleii), a population on Santa Catalina Island has shifted to coastal prickly pear cactus (Opuntia littoralis). We compared gene expression of larvae from the Sonoran Desert and Santa Catalina Island when reared on saguaro (C. gigantea), coastal prickly pear, and laboratory food. Consistent with expectations based on the complexity and toxicity of cactus relative to laboratory food, within population comparisons between larvae reared on these food sources revealed transcriptional differences in detoxification and other metabolic pathways. The majority of transcriptional differences between populations on the cactus hosts were independent of the rearing environment, and included a disproportionate number of genes involved in processes relevant to host plant adaptation (e.g. detoxification, central metabolism, and chemosensory pathways). Comparisons of transcriptional reaction norms between the two populations revealed extensive shared plasticity that likely allowed colonization of coastal prickly pear on Santa Catalina Island. We also found that while plasticity may have facilitated subsequent adaptive divergence in gene expression between populations, the majority of genes that differed in expression on the novel host were not transcriptionally plastic in the presumed ancestral state. mRNA profiles of third instar larvae from two different populations reared on three food types was sequenced on two lanes of an Illumina HiSeq 2000 Please note that the de novo assembly gives names to transcripts with the following convention: compXXX_cX_seqX. The first two identifiers (compXX_cX) are equivalent to a gene while the 'seq' identifier might refer to different isoforms or splice variants, etc. Therefore, for example, a gene might be comp123_c0, and this could have multiple sequences corresponding to different isoforms or splice variants. Since the analysis was carried out at the gene level, the program internally merged the multiple sequences together for each gene to generate the count matrix (AllGenesint.counts.matrix.txt) (i.e. it only includes comp123_c0), while the file from the assembly (i.e. Trinity.fasta) also include the individual sequences with the 'seq' identifier.
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