title: Gause's principle and the effect of resource partitioning on the dynamical coexistence of replicating templates.
abstract: Models of competitive template replication, although basic for replicator dynamics and primordial evolution, have not yet taken different sequences explicitly into account, neither have they analyzed the effect of resource partitioning (feeding on different resources) on coexistence. Here we show by analytical and numerical calculations that Gause's principle of competitive exclusion holds for template replicators if resources (nucleotides) affect growth linearly and coexistence is at fixed point attractors. Cases of complementary or homologous pairing between building blocks with parallel or antiparallel strands show no deviation from the rule that the nucleotide compositions of stably coexisting species must be different and there cannot be more coexisting replicator species than nucleotide types. Besides this overlooked mechanism of template coexistence we show also that interesting sequence effects prevail as parts of sequences that are copied earlier affect coexistence more strongly due to the higher concentration of the corresponding replication intermediates. Template and copy always count as one species due their constraint of strict stoichiometric coupling. Stability of fixed-point coexistence tends to decrease with the length of sequences, although this effect is unlikely to be detrimental for sequences below 100 nucleotides. In sum, resource partitioning (niche differentiation) is the default form of competitive coexistence for replicating templates feeding on a cocktail of different nucleotides, as it may have been the case in the RNA world. Our analysis of different pairing and strand orientation schemes is relevant for artificial and potentially astrobiological genetics.
authors.affiliation: Department of Plant Systematics, Institute of Biology, Eötvös University, Budapest, Hungary.
authors.forename: András
authors.initials: A
authors.lastname: Szilágyi
authors.forename: István
authors.initials: I
authors.lastname: Zachar
authors.forename: Eörs
authors.initials: E
authors.lastname: Szathmáry
mesh_terms: D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D050989:GATA2 Transcription Factor / Q000235:genetics; D005786:Gene Expression Regulation; D016179:Granulocyte Colony-Stimulating Factor / Q000235:genetics; D007377:Interleukin-3 / Q000235:genetics; D008957:Models, Genetic; D015233:Models, Statistical; D009010:Monte Carlo Method; D012333:RNA, Messenger / Q000235:genetics*; D011993:Recombinant Fusion Proteins / Q000235:genetics; D013269:Stochastic Processes
chemical_list: D050989:GATA2 Transcription Factor; D007377:Interleukin-3; D012333:RNA, Messenger; D011993:Recombinant Fusion Proteins; C404145:myelopoietin; D016179:Granulocyte Colony-Stimulating Factor