FLEXIBILITY IN GENE COEXPRESSION AT DEVELOPMENTAL AND EVOLUTIONARY TIMESCALES

Area of Science:

• Evolutionary biology
• Genomics
• Neuroscience

Background:

• Next-generation sequencing enables large-scale gene network studies.
• Understanding gene expression and interactions is crucial for evolutionary and developmental research.

Purpose of the Study:

• To investigate how genetic background and environment influence brain gene coexpression in Trinidadian guppies.
• To determine if gene connectivity predicts expression divergence and explore statistical challenges in high-dimensional gene expression data.

Main Methods:

• Characterized brain gene coexpression in two independent guppy lineages under different rearing environments.
• Applied rigorous statistical approaches to address challenges of high dimensionality and small sample sizes in gene expression analysis.

Main Results:

• Gene coexpression patterns were found to differ significantly based on both genetic background and rearing environment.
• Genes with lower connectivity exhibited greater expression divergence.
• Developed and detailed statistical methods for analyzing coexpression with small sample sizes.

Conclusions:

• Genetic background and developmental environment shape gene coexpression networks.
• Less connected genes may be more susceptible to expression divergence, a pattern potentially reinforced by selection.
• Highlights the importance of robust statistical methods for gene expression studies with limited sample sizes.