Coding Flexibility or : How Evolution Shapes the Structure and Complexity of Coding

Abstract

We addressed the evolution of complexity by looking at the possibilities to accumulate, contain and/or use more information in replicators through either a division of labor or a ‘smart’ coding. We have shown that both these mechanisms can evolve in relatively simple evolutionary models and that both these mechanisms can be identified in biotic systems. Multiple coding, is widely observed in biotic systems: genetic information is often used to code for distinct biological roles and many different gene-products are produced by post-transcriptional and post-translational modifications. Moreover, the genotype-phenotype mapping may be more important than the coding of information itself, as supported by experimental data, which shows that over different organisms, protein coding sequences are highly conserved, while the relative amount of non-protein-coding sequence increases consistently with complexity. On the other side of the spectrum, an intriguing parallel with our ecosystem based solutions comes from the recently developing field of meta-genomics, where rather than individual based diversity, the number of species and population diversity are responsible for the molecular functional composition of these communities . We only studied strict vertical inheritance, however in the light of an ecosystem as a ‘parts-list’, including a mechanism for horizontal gene transfer would allow for an interesting mix of population based diversity and individual based diversity. That is, there are organisms, which have been identified to use horizontal gene transfer as an important way of information accumulation and an overrepresentation of transfers of defense mechanisms and transcription-regulation genes is linked with more ecological interactions in species-rich communities. This ecological, as opposed to vertical, signal of genetic information, suggests that ecosystems, consisting of species with distinct roles, might ‘choose’ which genes are shared, and which are not. Moreover, it is the ecosystem as a whole which evolves, and it has been suggested that the high level of novelty required to evolve cell designs is a product of ecosystems, through horizontal gene transfer, rather than intralineage variation. In early replicators, such horizontal gene transfer could lead to the rapid spread of new genes and allow the build-up of larger, fitter genomes than could be achieved by purely vertical inheritance. The question if we ‘solved’ the problem of the information threshold, unfortunately can only be answered with a rather unsatisfactory “Yes and no”. The error threshold, in the sense of “a critical size, beyond which lethal numbers of deleterious mutations accumulate and information in subsequent generations will be destroyed”, still limits genomic size, as the mutational load which replicators can sustain, did not increase. However, we showed that both a population based as an individual based solution exists to increase the information processing potential, despite high mutation rates: even under severe mutation rates information may still be processed, either by a division of information or by enabling multiple coding through the use of a primitive form of RNA-modification (not to be confused with a repair mechanism). Thus, if we consider the information threshold as “the maximum amount of information, which can be maintained on a genome of critical size given a certain mutation rate” , the boundaries are clearly shifted. Concluding, rather than solving the problem of the information threshold, our results show that the information threshold should be considered as a dynamic property of evolving systems, shaping the structure of information and by including enough degrees of freedom (degrees which are supposed to be present in biological evolution), more is possible in ecosystems and/or with small-sized genomes.