A quantitative approach relating emergent features of complex traits to protein expression

Area of Science:

• * Systems Biology
• * Genetics and Genomics
• * Biophysics

Background:

• * Understanding the relationship between protein activity and complex traits is crucial for medicine, agriculture, and forestry.
• * Current models often simplify protein contributions as additive, neglecting synergistic effects.

Purpose of the Study:

• * To present two novel algorithms for linking complex, multigenic traits to protein activity.
• * To introduce a framework for quantifying 'weak emergence' and 'strong emergence' in protein interactions.
• * To estimate the experimental resources needed for applying these formalisms.

Main Methods:

• * Development of two distinct algorithms to model protein-trait relationships.
• * Introduction of a coefficient (κ) to quantify emergent interactions in 'weak emergence'.
• * Formulation of a separate model for 'strong emergence' involving protein concentration thresholds.

Main Results:

• * The study defines 'weak emergence' through synergistic protein interactions and quantifies it using coefficient κ.
• * A model for 'strong emergence' is presented, where proteins form new traits above specific concentration thresholds.
• * The required experimental efforts, including high-throughput phenomics, are estimated.

Conclusions:

• * The presented algorithms provide a quantitative framework for understanding emergent properties in complex biological systems.
• * These models can advance research in medical sciences, agriculture, and forestry by linking genotype to phenotype.
• * Future work will address model limitations concerning temporal dynamics and spatial protein arrangements.