Geneexpressionforagers

Methods & Techniques

• Utilized RNA-seq to profile gene expression in the brains of foragers from nine colonies.
• Applied supervised and unsupervised statistical approaches to analyze transcriptomic patterns.
• Conducted dimensional reduction techniques such as PCA and linear discriminant analysis to differentiate colonies.
• Performed gene ontology enrichment analyses to identify functional categories associated with expression patterns.

Key Findings

• Forager brain gene expression profiles varied significantly among colonies, reflecting functional differences in neurophysiology.
• Expression patterns were more similar among nestmates than between non-nestmates, indicating colony-specific factors.
• Gene expression variation correlated with colony traits, particularly sensitivity of foraging activity to humidity and dopamine-to-serotonin ratios.
• Coexpression analysis revealed modules of genes with coordinated expression patterns that were functionally enriched and associated with colony behavior.

Prerequisites

• Evolutionary biology and ecology fundamentals
• Social insect biology and colony organization

🎯 Consulting & Tutoring

Daniel Ari Friedman, PhD is available for AI Research Consulting and Tutoring related to this skill.

Related Skills

See BIBLIOGRAPHY.md for the complete publication catalog and related papers.