Multiple coding and the evolutionary properties of RNA secondary structure.
This article evaluates evolutionary properties of the transition from RNA primary sequence to RNA secondary structure. It focuses on the restrictions that the conservation of a protein code in an RNA sequence puts on its potential to evolve towards a specific secondary structure. Restricting the mutations to those that do not affect the coding for a protein restricts both the accessibility and the connectivity of the sequence space. The accessibility is restricted because only certain point mutations are allowed. The connectivity is restricted because no insertions and deletions are allowed. Simulating an evolutionary search process for a specific secondary structure shows that (i) the reduction of allowable point mutations allows for adaptation to some large-scale topology, but strongly reduces the possibility of small-scale adaptations, (ii) the abolition of insertions and deletions has very little effect on the results of the search process. During the evolutionary search process for a secondary structure with a specific topology and a high frequency of base-pairing the quasispecies moves into a subspace in which the similarity between secondary structures of neighboring sequences is relatively high. Increased similarity between second structures of neighboring sequences is also found in the Rev responsive element (RRE) in the lentiviruses Caprine arthritis-encephalitis virus and Visna virus. In these viruses a biased nucleotide frequency in the RRE region suggests that selection for the RRE RNA secondary structure affects the amino acid sequence of the env gene. Our results show a variation in the ruggedness of fitness landscapes which are based on a high degree of epistatic interactions. Fitness landscapes play an essential role, not only in biotic evolution, but also in all kinds of optimization processes (Hill Climbing, Simulated Annealing, Genetic Algorithms, etc). Variation in their ruggedness should therefore be taken into account in the analysis of these processes.
Huynen
M A
MA
Bioinformatics Group, University of Utrecht, The Netherlands.
Konings
D A
DA
Hogeweg
P
P
D000595:Amino Acid Sequence; D000818:Animals; D005075:Biological Evolution; D003198:Computer Simulation; D005815:Genetic Code; D008957:Models, Genetic; D009690:Nucleic Acid Conformation; D012313:RNA / Q000235:genetics*
D012313:RNA