Natural selection is not required to explain universal compositional patterns in rRNA secondary structure categories

Smit, Sandra; Yarus, Michael; Knight, Rob

doi:10.1261/rna.2183806

Cited by 83 publications

(77 citation statements)

References 39 publications

(50 reference statements)

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“…Many functional RNA molecules show a preference for purines (Elson and Chargaff 1955;Lao and Forsdyke 2000), and there is far more variation along the GC axis (i.e., the axis where the compositions of G and C are the same, as well as of A and U) than along the two other orthogonal axes of composition (Schultes et al 1997(Schultes et al , 1999Smit et al 2006). These patterns are replicated in both ribosomal RNA subunits from all three domains of life, although these key features may be due to selforganization of RNA during secondary structure assembly rather than due to selection for specific compositions (Smit et al 2006). Interestingly, RNAs can be artificially selected for functions using as few as three of the four standard nucleotides (Rogers and Joyce 1999) or as few as two nonstandard nucleotides (Reader and Joyce 2002), albeit with reduced efficiency.…”

Section: Introductionmentioning

confidence: 99%

Natural and artificial RNAs occupy the same restricted region of sequence space

Kennedy¹,

Lladser²,

Wu³

et al. 2009

RNA

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Different chemical and mutational processes within genomes give rise to sequences with different compositions and perhaps different capacities for evolution. The evolution of functional RNAs may occur on a ''neutral network'' in which sequences with any given function can easily mutate to sequences with any other. This neutral network hypothesis is more likely if there is a particular region of composition that contains sequences that are functional in general, and if many different functions are possible within this preferred region of composition. We show that sequence preferences in active sites recovered by in vitro selection combine with biophysical folding rules to support the neutral network hypothesis. These simple active-site specifications and folding preferences obtained by artificial selection experiments recapture the previously observed purine bias and specific spread along the GC axis of naturally occurring aptamers and ribozymes isolated from organisms, although other types of RNAs, such as miRNA precursors and spliceosomal RNAs, that act primarily through complementarity to other amino acids do not share these preferences. These universal evolved sequence features are therefore intrinsic in RNA molecules that bind small-molecule targets or catalyze reactions.

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Section: Introductionmentioning

confidence: 99%

Natural and artificial RNAs occupy the same restricted region of sequence space

Kennedy¹,

Lladser²,

Wu³

et al. 2009

RNA

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“…The RNA stem loops have two characteristic parts: stems that consist of base-paired nucleic acids and loops, bulges and junctions that consist of unpaired regions limited by stems. Most interesting from an evolutionary perspective are two recently found key features [44][45][46] : (1) Randomly associated RNAs that have no evolutionary history show the same structuredependent compositional bias as ribosomal RNAs. This means that the differences do not depend on selection processes but on the overall composition of the RNA consortium; and (2) The singular RNA stem loop behaves like a random assembly of nucleotides without selective forces and underlies physico-chemical laws exclsusively Only if stem loops build groups, they share a culture of interactional patterns and a history of defined timescales, i.e., they underlie biological selective forces.…”

Section: From Molecular Biological Entities To Social Groupsmentioning

confidence: 99%

“…The emergence of single RNA stem-loops solely depends on physico-chemical properties. As mentioned above, if stem-loop groups build complex consortia biological selection and social interactions emerge that are not present in a purely chemical world [44][45][46] . This looks coherent with the results of sociology and the evolution of natural languages.…”

Section: Remember Gödel: Natural Codes Are Open "Systems"mentioning

confidence: 99%

Pragmatic turn in biology: From biological molecules to genetic content operators

Witzany¹

2014

WJBC

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Core tip: Meaning in natural languages/codes and communication is context dependent. In contrast, artificial formalizable (algorithm based) languages employ a "universal" syntax in order to determine meaning independent of the contextual circumstances. It is empirically evident that no natural language speaks itself as no natural code codes itself. It always requires living agents that share a competence to generate and interpret these natural codes. Therefore I suppose that changes in the genetic code, which are of evolutionary relevance, are rather the result of fine-tuned processes by a large network of mobile genetic elements, persistent viruses, its defectives and other genetic parasites that alter DNA sequences. In this respect DNA remains as ecosphere habitat for social interacting RNA inhabitants. This represents a pragmatic turn in biology from syntax centered molecular biology to pragmatics centered agents interactions. AbstractErwin Schrödinger's question "What is life?" received the answer for decades of "physics + chemistry". The concepts of Alain Turing and John von Neumann introduced a third term: "information". This led to the understanding of nucleic acid sequences as a natural code. Manfred Eigen adapted the concept of Hammings "sequence space". Similar to Hilbert space, in which every ontological entity could be defined by an unequivocal point in a mathematical axiomatic system, in the abstract "sequence space" concept each point represents a unique syntactic structure and the value of their separation represents their dissimilarity. In this concept molecular features of the genetic code evolve by means of self-organisation of matter. Biological selection determines the fittest types among varieties of replication errors of quasi-species. The quasi-species concept dominated evolution theory for many decades. In contrast to this, recent empirical data on the evolution of DNA and its forerunners, the RNA-world and viruses indicate cooperative agent-based interactions. Group behaviour of quasi-species consortia constitute de novo and arrange available genetic content for adaptational purposes within real-life contexts that determine epigenetic markings. This review focuses on some fundamental changes in biology, discarding its traditional status as a subdiscipline of physics and chemistry. Witzany G. Pragmatic turn in biology the new paradigm that information is physically embodied in DNA sequences of four different types [1] . In contrast to the years before 1953, the question of "information" now became central: the components of DNA are simple chemicals, but the biological complexity that can be generated by the information of different sequences is revolutionary. The fundamental concept that integrated this new biological "information" with matter and energy was enshrined in the universal Turing machine and von Neumann's self-reproducing machines [2][3][4] . Consequently it follows that biology is physics with computation [5] . This was the core paradigm of molecular biology for almost the n...

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“…Clear patterns of nucleotide composition have been noted in both natural and artificial RNA families (Wang and Hickey 2002;Gan et al 2003;Gevertz et al 2005;Knight et al 2005;Smit et al 2006Smit et al , 2007Smit et al , 2009, and one fascinating question is thus whether RNAs shaped by natural selection share similar features with those artificially selected in the laboratory. Comparing natural and artificial RNAs is important because such comparisons tell us whether we are seeing contingent features of organisms as they have evolved on Earth, or universal principles of RNA architecture (Yarus and Welch 2000).…”

Section: Introductionmentioning

confidence: 99%

RNASTAR: An RNA STructural Alignment Repository that provides insight into the evolution of natural and artificial RNAs

Widmann¹,

Stombaugh²,

McDonald³

et al. 2012

RNA

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Automated RNA alignment algorithms often fail to recapture the essential conserved sites that are critical for function. To assist in the refinement of these algorithms, we manually curated a set of 148 alignments with a total of 9600 unique sequences, in which each alignment was backed by at least one crystal or NMR structure. These alignments included both naturally and artificially selected molecules. We used principles of isostericity to improve the alignments from an average of 83%-94% isosteric base pairs. We expect that this alignment collection will assist in a wide range of benchmarking efforts and provide new insight into evolutionary principles governing change in RNA structural motifs. The improved alignments have been contributed to the Rfam database.

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Natural selection is not required to explain universal compositional patterns in rRNA secondary structure categories

Cited by 83 publications

References 39 publications

Natural and artificial RNAs occupy the same restricted region of sequence space

Natural and artificial RNAs occupy the same restricted region of sequence space

Pragmatic turn in biology: From biological molecules to genetic content operators

RNASTAR: An RNA STructural Alignment Repository that provides insight into the evolution of natural and artificial RNAs

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