Overview
The honey bee ( Apis mellifera ) is a pivotal species in both ecological and research contexts, serving as a model organism for studying complex social behavior and physiological processes. A critical aspect of understanding these complexities is the analysis of tissue-specific gene expression (TSGE), a challenging task due to the need to handle large bioinformatics data and manual tissue processing. In this study, we present a meta-analytic approach to investigate TSGE in A. mellifera , harnessing various open-source bioinformatics packages. From an initial pool of 4349 samples and 12,398 loci, our rigorous analysis resulted in a snapshot of 731 samples and 177 loci, representing high-quality estimates of TSGE patterns. This snapshot is publicly available, serving as a valuable resource for researchers interested in A. mellifera and beyond. Ongoing work will refine this analytical tool and expand its application to other species, thereby contributing to the broader understanding of gene expression patterns.
Overview source: Curated paper metadata.
Methods and contributions
Read the source for the full argument, qualifications, and evidence.
Findings and contributions
- From 4349 samples and 12,398 loci, AMALGKIT processing retained 731 samples and 177 loci, released as a public July 2023 TSGE snapshot.
- Curation reduced 133 uniquely named tissues to 54 groups; whole adult body, brain and mushroom body made up 62.3% of samples.
- Optional metadata fields were largely blank (e.g. 99.1% genotype, 67.5% sex, 77.8% age), limiting their use as surrogate variables in harmonization.
- Average library size increased over time, but publication date explained only a small fraction of variance in total bases (R2=0.061).
- The authors suggest several possible reasons for the heavy winnowing: heterogeneous experiments, asymmetric tissue coverage with single-tissue designs, and incomplete metadata that may have underpowered surrogate variable analysis.
Methods
- Entrez/NCBI SRA query for Apis mellifera Illumina RNA-seq samples — Public RNA-seq samples were gathered via an Entrez search filtered to A. mellifera, Illumina platforms, rnaseq type and SRA biosample.
- Six-script MetaInformAnt pipeline built on AMALGKIT — A versioned, openly available pipeline of six scripts covered environment setup, genome and metadata download, SRA download, quantification and curation.
- Metadata tissue-name harmonization script — A 2.5_update_metadata.py script corrected inconsistent tissue labels so equivalent samples (e.g. variants of 'whole body') were grouped together.
- fastp QC, kallisto pseudoalignment, amalgkit curation — Raw reads were QC'd with fastp, quantified with kallisto against Amel_HAv3.1, and merged/normalized into one dataset with amalgkit.
- PCA, clustering and differential expression descriptives — Post-processing scripts ran principal component, clustering and differential expression analyses on the curated expression data.
Summary sources: Paper metadata and evidence · Extracted source text.
PDF downloads
Archived files available directly from this site.
- 2023_HoneyBeeGeneExpression.pdf PDF · 0.66 MiB · extracted-text source
Citation
Citation metadata follows the unified bibliography.
Catalog details and resources
Related in Entomology
Other catalogued works in the same domain.