Consensus Coexpression Network Analysis Identifies Key Regulators of Flower and Fruit Development in Wild Strawberry

Area of Science:

• Plant biology
• Genomics
• Molecular biology

Background:

• The diploid strawberry (Fragaria vesca) is a model for Rosaceae fruit crops.
• Strawberry fruit development involves complex phytohormone regulation and cross-tissue communication.
• Understanding gene expression is crucial for improving fruit development.

Purpose of the Study:

• To generate robust coexpression networks from existing transcriptome data for Fragaria vesca.
• To provide a web-based resource for exploring gene networks in strawberry.
• To facilitate hypothesis generation and experimental design in Rosaceae fruit research.

Main Methods:

• Combined 46 RNA-seq libraries for Fragaria vesca.
• Applied Weighted Gene Co-Expression Network Analysis (WGCNA) and consensus clustering.
• Utilized bootstrapping for robust cluster validation.
• Experimentally tested network-derived hypotheses, including iron transport and floral mutants.

Main Results:

• Developed robust and reproducible coexpression gene clusters for Fragaria vesca.
• Identified potential mechanisms of post-fertilization iron transport from receptacle to seed.
• Characterized a Fragaria vesca floral mutant and identified a candidate gene.
• Created a web interface (www.fv.rosaceaefruits.org) for network exploration.

Conclusions:

• The study presents a validated methodology for generating and analyzing large-scale transcriptome data.
• The developed coexpression networks serve as a valuable resource for strawberry and Rosaceae fruit research.
• This work supports hypothesis-driven research and experimental design in fruit crop improvement.