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Identifying a developmental transition in honey bees using gene expression data.

ABSTRACT: In many organisms, interactions among genes lead to multiple functional states, and changes to interactions can lead to transitions into new states. These transitions can be related to bifurcations (or critical points) in dynamical systems theory. Characterizing these collective transitions is a major challenge for systems biology. Here, we develop a statistical method for identifying bistability near a continuous transition directly from high-dimensional gene expression data. We apply the method to data from honey bees, where a known developmental transition occurs between bees performing tasks in the nest and leaving the nest to forage. Our method, which makes use of the expected shape of the distribution of gene expression levels near a transition, successfully identifies the emergence of bistability and links it to genes that are known to be involved in the behavioral transition. This proof of concept demonstrates that going beyond correlative analysis to infer the shape of gene expression distributions might be used more generally to identify collective transitions from gene expression data.

SUBMITTER: Daniels BC

PROVIDER: S-EPMC10547183 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Identifying a developmental transition in honey bees using gene expression data.

Daniels Bryan C BC Wang Ying Y Page Robert E RE Amdam Gro V GV

PLoS computational biology 20230921 9

In many organisms, interactions among genes lead to multiple functional states, and changes to interactions can lead to transitions into new states. These transitions can be related to bifurcations (or critical points) in dynamical systems theory. Characterizing these collective transitions is a major challenge for systems biology. Here, we develop a statistical method for identifying bistability near a continuous transition directly from high-dimensional gene expression data. We apply the metho ...[more]

PMID: 37733808

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Project description:BackgroundMalnutrition is a major factor affecting animal health, resistance to disease and survival. In honey bees (Apis mellifera), pollen, which is the main dietary source of proteins, amino acids and lipids, is essential to adult bee physiological development while reducing their susceptibility to parasites and pathogens. However, the molecular mechanisms underlying pollen's nutritive impact on honey bee health remained to be determined. For that purpose, we investigated the influence of pollen nutrients on the transcriptome of worker bees parasitized by the mite Varroa destructor, known for suppressing immunity and decreasing lifespan. The 4 experimental groups (control bees without a pollen diet, control bees fed with pollen, varroa-parasitized bees without a pollen diet and varroa-parasitized bees fed with pollen) were analyzed by performing a digital gene expression (DGE) analysis on bee abdomens.ResultsAround 36, 000 unique tags were generated per DGE-tag library, which matched about 8, 000 genes (60% of the genes in the honey bee genome). Comparing the transcriptome of bees fed with pollen and sugar and bees restricted to a sugar diet, we found that pollen activates nutrient-sensing and metabolic pathways. In addition, those nutrients had a positive influence on genes affecting longevity and the production of some antimicrobial peptides. However, varroa parasitism caused the development of viral populations and a decrease in metabolism, specifically by inhibiting protein metabolism essential to bee health. This harmful effect was not reversed by pollen intake.ConclusionsThe DGE-tag profiling methods used in this study proved to be a powerful means for analyzing transcriptome variation related to nutrient intake in honey bees. Ultimately, with such an approach, applying genomics tools to nutrition research, nutrigenomics promises to offer a better understanding of how nutrition influences body homeostasis and may help reduce the susceptibility of bees to (less virulent) pathogens.

Project description:BackgroundHoney bees are known for several striking social behaviors, including a complex pattern of behavioral maturation that gives rise to an age-related colony division of labor and a symbolic dance language, by which successful foragers communicate the location of attractive food sources to their nestmates. Our understanding of honey bees is mostly based on studies of the Western honey bee, Apis mellifera, even though there are 9-10 other members of genus Apis, showing interesting variations in social behavior relative to A. mellifera. To facilitate future in-depth genomic and molecular level comparisons of behavior across the genus, we performed a microarray analysis of brain gene expression for A. mellifera and three key species found in Asia, A. cerana, A. florea and A. dorsata.ResultsFor each species we compared brain gene expression patterns between foragers and adult one-day-old bees on an A. mellifera cDNA microarray and calculated within-species gene expression ratios to facilitate cross-species analysis. The number of cDNA spots showing hybridization fluorescence intensities above the experimental threshold was reduced by an average of 16% in the Asian species compared to A. mellifera, but an average of 71% of genes on the microarray were available for analysis. Brain gene expression profiles between foragers and one-day-olds showed differences that are consistent with a previous study on A. mellifera and were comparable across species. Although 1772 genes showed significant differences in expression between foragers and one-day-olds, only 218 genes showed differences in forager/one-day-old expression between species (p < 0.001). Principal Components Analysis revealed dominant patterns of expression that clearly distinguished between the four species but did not reflect known differences in behavior and ecology. There were species differences in brain expression profiles for functionally related groups of genes.ConclusionWe conclude that the A. mellifera cDNA microarray can be used effectively for cross-species comparisons within the genus. Our results indicate that there is a widespread conservation of the molecular processes in the honey bee brain underlying behavioral maturation. Species differences in brain expression profiles for functionally related groups of genes provide possible clues to the basis of behavioral variation in the genus.

Dataset Information

Identifying a developmental transition in honey bees using gene expression data.

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Identifying a developmental transition in honey bees using gene expression data.

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