Apis mellifera
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA379344 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR6702485.fastq.gz | Fastqsanger.gz | |||
| SRR6702486.fastq.gz | Fastqsanger.gz | |||
| SRR6702487.fastq.gz | Fastqsanger.gz |
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Project description:Apis mellifera intermissa (Buttel-Reepen, 1906) is the native honeybee subspecies of Algeria. A.m.intermissa occurs in Tunisia, Algeria and Morocco, between the Atlas and the Mediterranean and Atlantic coasts (Ruttner, 1988), in an area of more than 2500 km long. Intermissa indicates the position through this bee races between tropical Africa and European breeds (Peyvel, 1994). The settlement area of the Tellian extends from Tunisia to Morocco. Ruttner et al (1978) describes the pure Tellian. It is a black hair of his coat poverty brings out the black color. It is a small size, there are some times light illumination on the tergites. This bee is very aggressive, nervous, sick to take part, as swarms huge fall and even produced many brood and can build up to one hundred queen cells (Le Conte, 2002). A.m.intermissa is prone to swarming, shows an aggressive behaviour and an abundant use of propolis (Ruttner 1988). This study is part of the project funded by the USAID Grant No. TA-MOU-08-M29-075.
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Project description:Venoms have convergently evolved in all major animal lineages and are ideal candidates to unravel the underlying genomic processes of convergent trait evolution. However, few animal groups have been studied in detail, and large-scale comparative genomic analyses to address toxin gene evolution are rare. Hyper-diverse hymenopterans are the most speciose group of venomous animals, but the origin of their toxin genes have been largely overlooked. We combined proteo-transcriptomics with comparative genomics compiling an up-to-date list of core bee venom proteins to investigate the origin of 11 venom genes in 30 hymenopteran genomes including two new stingless bees.
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Project description:In honey bees, Vitellogenin (Vg) is hypothesized to be a major factor affecting hormone signaling, food-related behavior, immunity, stress resistance and lifespan. Likewise microRNAs play important roles in posttranscriptional gene regulation and affect many biological processes thereby showing many parallels to Vg functions. The molecular basis of Vg and microRNA interactions is largely unknown. Here, we exploited the well-established RNA interference (RNAi) protocol for Vg knockdown to investigate its effects on microRNA population in honey bee forager’s brain and fat body tissue. To identify microRNAs that are differentially expressed between tissues in control and knockdown foragers, we used µParaflo® microfluidic oligonucleotide microRNA microarrays. Our results show 76 and 74 miRNAs were expressed in the brain of control and knockdown foragers whereas 66 and 69 miRNAs were expressed in the fat body of control and knockdown foragers respectively. Target prediction identified potential seed matches for differentially expressed subset of microRNAs affected by Vg knockdown. These candidate genes are involved in a broad range of biological processes including insulin signaling, juvenile hormone (JH) and ecdysteroid signaling previously shown to affect foraging behavior. Thus, here we demonstrate a causal link between Vg expression-variation and variation in the abundance of microRNAs in different tissues with possible consequences for regulation of foraging behavior.
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Project description:Recipe for a busy bee: MicroRNAs in honey bee caste determination
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Project description:In honey bees, Vitellogenin (Vg) is hypothesized to be a major factor affecting hormone signaling, food-related behavior, immunity, stress resistance and lifespan. Likewise microRNAs play important roles in posttranscriptional gene regulation and affect many biological processes thereby showing many parallels to Vg functions. The molecular basis of Vg and microRNA interactions is largely unknown. Here, we exploited the well-established RNA interference (RNAi) protocol for Vg knockdown to investigate its effects on microRNA population in honey bee forager’s brain and fat body tissue. To identify microRNAs that are differentially expressed between tissues in control and knockdown foragers, we used µParaflo® microfluidic oligonucleotide microRNA microarrays. Our results show 76 and 74 miRNAs were expressed in the brain of control and knockdown foragers whereas 66 and 69 miRNAs were expressed in the fat body of control and knockdown foragers respectively. Target prediction identified potential seed matches for differentially expressed subset of microRNAs affected by Vg knockdown. These candidate genes are involved in a broad range of biological processes including insulin signaling, juvenile hormone (JH) and ecdysteroid signaling previously shown to affect foraging behavior. Thus, here we demonstrate a causal link between Vg expression-variation and variation in the abundance of microRNAs in different tissues with possible consequences for regulation of foraging behavior.
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Project description:To determine the impact of quercetin on honeybee development and physiology, we conducted an RNASeq analysis of gene expression in neonate larvae exposed for three days to control “bee candy” diet (comprising sucrose and sugar syrup) or diets to which 0.1 mM or 0.25 mM quercetin was added.
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Project description:Purpose: Parts of Europe and the United States have witnessed dramatic losses in commercially managed honey bees over the past decade to what is considered an unsustainable extent. The large-scale loss of honey bees has considerable implications for the agricultural economy because honey bees are one of the leading pollinators of numerous crops. Honey bee declines have been associated with several interactive factors. Poor nutrition and viral infection are two environmental stressors that pose heightened dangers to honey bee health. Methods: We used RNA-sequencing to examine how monofloral diets (Rockrose and Chestnut) and Israeli acute paralysis virus inoculation influence gene expression patterns in honey bees. Results: We found a considerable nutritional response, with almost 2,000 transcripts changing with diet quality. The majority of these genes were over-represented for nutrient signaling (insulin resistance) and immune response (Notch signaling and JaK-STAT pathways). Somewhat unexpectedly, the transcriptomic response to viral infection was fairly limited. We only found 43 transcripts to be differentially expressed, some with known immune functions (argonaute-2), transcriptional regulation, and muscle contraction. We created contrasts to determine if any protective mechanisms of good diet were due to direct effects on immune function (resistance) or indirect effects on energy availability (tolerance). A similar number of resistance and tolerance candidate differentially expressed genes were found, suggesting both processes may play significant roles in dietary buffering from pathogen infection. We also compared the virus main effect in our study (polyandrous colonies) to that obtained in a previous study (single-drone colonies) and verified significant overlap in differential expression despite visualization methods showing differences in the noisiness levels between these two datasets. Conclusions: Through transcriptional contrasts and functional enrichment analysis, we add to evidence of feedbacks between diet and disease in honey bees. We also show that comparing results derived from polyandrous colonies (which are typically more natural) and single-drone colonies (which usually yield more signal) may allow researchers to identify transcriptomic patterns in honey bees that are concurrently less artificial and less noisy. Altogether, we hope this work underlines possible merits of using data visualization techniques and multiple datasets when interpreting RNA-sequencing studies.
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