Topological data analysis reveals a core gene expression backbone that defines form and function across flowering...

Area of Science:

• Plant biology
• Genomics
• Evolutionary biology

Background:

• Flowering plants (angiosperms) evolved ~125 million years ago and dominate terrestrial ecosystems.
• Plant adaptations are driven by complex gene and pathway interactions.
• Connecting gene expression to physical traits (morphology) is a major biological challenge.

Purpose of the Study:

• To develop and apply a novel analytical framework for understanding gene expression patterns in flowering plants.
• To link gene expression data to plant tissues and stress responses using topological data analysis (TDA).

Main Methods:

• Implemented topological data analysis (TDA) to analyze high-dimensional gene expression data.
• Utilized lens functions within TDA to represent plant tissue types and stress conditions.
• Generated Mapper graphs to visualize topological structures of gene expression across diverse angiosperms.

Main Results:

• TDA successfully created topological representations of gene expression, showing gradients from leaves to seeds and healthy to stressed states.
• Identified conserved gene expression patterns across angiosperms that distinguish tissue types and stress responses.
• Genes correlated with tissue TDA were enriched in core functions like photosynthesis, growth, development, and stress response.

Conclusions:

• Topological data analysis (TDA) is a powerful tool for dissecting complex plant gene expression data.
• Revealed a conserved 'expression backbone' underlying plant form and function across angiosperms.
• This approach provides new insights into the genetic basis of plant adaptation and development.