Achieving Diverse and Monoallelic Olfactory Receptor Selection Through Dual-Objective Optimization Design
Xiao-Jun Tian, Hang Zhang, Jens Sannerud, and Jianhua Xing

TL;DR
This paper presents a comprehensive, physically-based model of olfactory receptor gene selection that explains monoallelic expression, maximizes receptor diversity, and reveals an evolutionarily optimized three-layer regulatory mechanism.
Contribution
It introduces a novel, integrated model incorporating physical interactions and multiple regulatory layers, explaining both monoallelic expression and receptor diversity in olfactory neurons.
Findings
The model recapitulates monoallelic OR expression.
It explains how OR diversity is maximized and maintained.
Predictions are validated by experimental data.
Abstract
Multiple-objective optimization is common in biological systems. In the mammalian olfactory system, each sensory neuron stochastically expresses only one out of up to thousands of olfactory receptor (OR) gene alleles; at organism level the types of expressed ORs need to be maximized. Existing models focus only on monoallele activation, and cannot explain recent observations in mutants, especially the reduced global diversity of expressed ORs in G9a/GLP knockouts. In this work we integrated existing information on OR expression, and constructed a comprehensive model that has all its components based on physical interactions. Analyzing the model reveals an evolutionarily optimized three-layer regulation mechanism, which includes zonal segregation, epigenetic barrier crossing coupled to a negative feedback loop that mechanistically differs from previous theoretical proposals, and a…
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