Gene expression rearrangements denoting changes in the biological state

Area of Science:

• Genomics
• Systems Biology
• Computational Biology

Background:

• Gene expression signatures serve as unique markers for biological states.
• Understanding how these signatures change during biological transitions is crucial for disease and evolution research.

Purpose of the Study:

• To investigate modifications in gene expression distribution functions during biological state changes.
• To differentiate transition patterns based on the magnitude of gene expression alterations.

Main Methods:

• Characterizing biological states using principal component analysis.
• Analyzing gene expression distribution functions by maximal/minimal differential expression values.
• Employing Pareto law exponents to describe the tails of expression distributions.

Main Results:

• Identified two classes of biological transitions: gradual (e.g., E. coli evolution, Alzheimer's disease) and abrupt (e.g., cancer).
• Gradual transitions exhibit short-ranged differential expression distributions with few strongly varying genes.
• Abrupt transitions, like cancer, show heavy-tailed distributions with thousands of differentially expressed genes.

Conclusions:

• Biological state transitions have distinct gene expression distribution profiles.
• Cancer progression is characterized by a large-scale disruption of gene expression compared to other studied transitions.