Information theory, gene expression, and combinatorial regulation: a quantitative analysis

Area of Science:

• Molecular Biology
• Systems Biology
• Bioinformatics

Background:

• A functional definition of a gene emphasizes its role in producing polypeptides, not its DNA sequence alone.
• Gene expression and regulation necessitate information on the timing and quantity of polypeptide production.

Purpose of the Study:

• To develop a conceptual framework and formal models for gene expression and regulation.
• To quantify and compare the product and regulatory information involved in gene expression.

Main Methods:

• Analysis of biochemical data to inform a conceptual framework.
• Development of formal models for coordinated gene expression.
• Investigation of transcript and mRNA interactions with proteins via a regulatory code.

Main Results:

• Genes are assembled from heterogeneous pieces during RNA processing, not present as complete units at the DNA level.
• Nucleotides in transcripts and mRNA function both in coding amino acids and in regulatory oligomotifs for protein binding.
• A precise regulatory code governs the interaction of transcripts, mRNAs, and proteins.

Conclusions:

• Gene expression is a dynamic process involving RNA assembly and complex regulatory interactions.
• Formal models can quantify the information flow in gene regulation.
• This framework provides a new perspective on gene function and regulation.