Evolution of Daily Gene Co-expression Patterns from Algae to Plants.

Area of Science:

• Plant and algal biology
• Evolutionary genomics
• Transcriptome regulation

Background:

• Daily rhythms are essential for plant and microalgae metabolism and development, orchestrating responses to light transitions.
• Genome-wide transcriptomic data from plants and microalgae under light:dark cycles enable comparative analyses of daily rhythm evolution.

Purpose of the Study:

• To integrate and analyze transcriptomic data from *Arabidopsis thaliana*, *Chlamydomonas reinhardtii*, and *Ostreococcus tauri* to understand the evolution of daily rhythms in the green lineage.
• To identify conserved and divergent patterns of rhythmic gene expression across species with varying light dependencies.

Main Methods:

• Integration and analysis of RNA-seq and microarray data using gene co-expression networks.
• Application of a Multiple Bidirectional Best Hit (MBBH) algorithm to identify gene orthologs.
• Gene clustering and functional enrichment analysis to compare rhythmic expression patterns.

Main Results:

• The proportion of the daily rhythmic transcriptome decreases from ~90% in *Ostreococcus* (light-dependent) to ~40% in *Arabidopsis* (more light-independent).
• Gene duplication and divergence of rhythmic expression profiles are key evolutionary mechanisms for gene families like *PRRs*, *COLs*, and *DOFs*.
• While overall conservation of daily rhythmic patterns is low to moderate, gene clusters peaking during light transitions show strikingly high conservation.

Conclusions:

• The evolution of daily rhythms in the green lineage involves changes in the size and light dependency of the rhythmic transcriptome.
• Gene duplication and divergence contribute to the evolution of rhythmic gene families.
• Light transition-associated rhythmic gene expression patterns are highly conserved, suggesting a fundamental role in plant and algal evolution.