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Effects of flight on gene expression and aging in the honey bee brain and flight muscle

ABSTRACT: Honey bees move through a series of in-hive tasks (“nursing”) to outside tasks (“foraging”) that coincident with an intense increase in metabolic activity. Social context can cause worker bees to speed up, or slow down this process and foragers may revert back to their earlier in hive tasks accompanied by reversion to earlier physiological states. To determine if the transcriptional profile of forager bees can revert, or if the effects of flight on gene expression are irreversible, we used whole-genome microarrays. Brain tissue and flight muscle exhibited independent patterns of expression during behavioral transitions, with patterns of expression in the brain reflecting both age and behavior, while flight muscle exhibited primarily age-related patterns of expression. Our data suggest that the transition from little to no flight (nurse) to intense flight (forager), rather than the amount of flight has a major effect on gene expression. Following behavioral reversion there was a partial reversion in gene expression but some aspects of forager expression patterns, such as those for genes involved in immune function, remained. These data suggest an epigenetic control and energy balance role in honey bee functional senescence.

ORGANISM(S): Apis mellifera

PROVIDER: GSE40650 | GEO | 2012/10/01

SECONDARY ACCESSION(S): PRJNA174472

REPOSITORIES: GEO

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Project description:Honey bees move through a series of in-hive tasks (M-bM-^@M-^\nursingM-bM-^@M-^]) to outside tasks (M-bM-^@M-^\foragingM-bM-^@M-^]) that coincident with an intense increase in metabolic activity. Social context can cause worker bees to speed up, or slow down this process and foragers may revert back to their earlier in hive tasks accompanied by reversion to earlier physiological states. To determine if the transcriptional profile of forager bees can revert, or if the effects of flight on gene expression are irreversible, we used whole-genome microarrays. Brain tissue and flight muscle exhibited independent patterns of expression during behavioral transitions, with patterns of expression in the brain reflecting both age and behavior, while flight muscle exhibited primarily age-related patterns of expression. Our data suggest that the transition from little to no flight (nurse) to intense flight (forager), rather than the amount of flight has a major effect on gene expression. Following behavioral reversion there was a partial reversion in gene expression but some aspects of forager expression patterns, such as those for genes involved in immune function, remained. These data suggest an epigenetic control and energy balance role in honey bee functional senescence. Brains and thoraces from the same individuals of all behavioral groups were compared on a total of 132 arrays. The samples were hybridized against each other using a loop design. The groups tested are outlined as follows: Typical aged nurse 'YN' (8-10 days old; <1 day flight experience), Precocious forager 'PF' (8 to 10 days old; 2 to 3 days flight experience), Overaged nurse 'ON' (19 to 22 days old; < 1 day flight experience), Forager - low flight 'TFL' (19 to 22 days old; 2 to 3 days flight experience), Forager - high flight 'TFH' ( 19 to 22 days old; 7 to 9 days flight experience), Forager - old 'OF' (25 to 26 days old; 10 to 12 days flight experience), Reverted nurse 'RN' (25 to 26 days old; 7 to 9 days flight experience). The comparisons are outlined as follows: YN:ON (6 arrays), ON:RN (6 arrays), RN:TFH (6 arrays), TFH:TFL (6 arrays), TFL:PF (6 arrays), PF:YN (6 arrays), ON:TFL (12 arrays), YN:OF (6 arrays), OF:RN (6 arrays), RN:YN (6 arrays). Each comparison was done for individual brains and thoraces. Total: 132 arrays

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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Effects of flight on gene expression and aging in the honey bee brain and flight muscle

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