title: Achieving diverse and monoallelic olfactory receptor selection through dual-objective optimization design.
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 the 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 previously unidentified enhancer competition step. This model not only recapitulates monoallelic OR expression, but also elucidates how the olfactory system maximizes and maintains the diversity of OR expression, and has multiple predictions validated by existing experimental results. Through making an analogy to a physical system with thermally activated barrier crossing and comparative reverse engineering analyses, the study reveals that the olfactory receptor selection system is optimally designed, and particularly underscores cooperativity and synergy as a general design principle for multiobjective optimization in biology.
authors.affiliation: Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15260;
authors.forename: Xiao-Jun
authors.initials: XJ
authors.lastname: Tian
authors.affiliation: Genetics, Bioinformatics, and Computational Biology Program, Virginia Polytechnic Institute and State University, Blacksburg, VA 24060;
authors.forename: Hang
authors.initials: H
authors.lastname: Zhang
authors.affiliation: The TECBio Research Experiences for Undergraduates Program, University of Pittsburgh, Pittsburgh, PA 15260.
authors.forename: Jens
authors.initials: J
authors.lastname: Sannerud
authors.affiliation: Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15260; xing1@pitt.edu.
authors.forename: Jianhua
authors.initials: J
authors.lastname: Xing
mesh_terms: D000483:Alleles; D000818:Animals; D005786:Gene Expression Regulation / Q000502:physiology*; D006801:Humans; D008954:Models, Biological; D018035:Receptors, Odorant / Q000096:biosynthesis* / Q000235:genetics
chemical_list: D018035:Receptors, Odorant
keywords: barrier crossing; cooperativity; dual-objective optimization; enhancer competition; epigenetics