Deciphering Cis-Regulatory Element Mediated Combinatorial Regulation in Rice under Blast Infected Condition

Area of Science:

• Genomics
• Systems Biology
• Bioinformatics

Background:

• Gene expression is regulated by combinations of cis-regulatory elements (CREs) and transcription factors (TFs).
• The complexity of CRE-mediated transcriptional regulation has made combinatorial mechanisms difficult to elucidate.
• Understanding these combinatorial interactions is crucial for deciphering gene expression control.

Purpose of the Study:

• To develop and validate a novel computational methodology for quantifying CRE co-occurrence and inferring combinatorial gene regulation.
• To apply this methodology to rice gene expression data under fungal infection to understand regulatory networks.
• To explore higher-order regulatory combinatorics and their biological implications.

Main Methods:

• Developed a method to quantify CRE co-occurrence in promoter sequences.
• Applied statistical filtering to identify significant CRE pairs.
• Constructed co-occurrence networks to represent regulatory combinatorics.
• Analyzed networks in rice under Magnaporthe infection.

Main Results:

• Identified significant CRE pairs with strong co-occurrence tendencies and similar distribution patterns.
• Revealed auto and cross-regulation among transcription factor families.
• Uncovered cross-talk between hormone signaling pathways.
• Demonstrated tissue-specific regulatory differences in response to fungal attack.

Conclusions:

• The proposed network-based methodology effectively elucidates CRE-mediated combinatorial gene regulation.
• The findings highlight a distributed nature of gene regulation in response to fungal infection.
• This approach can be applied to study tissue- and condition-specific gene regulation in other eukaryotes.