R C G T a A R R A A K N R G N C 1 a g u b h 0 BioSystems 140 (2016) 49–57 Contents lists available at ScienceDirect BioSystems jo ur nal home p age: www.elsev ier .com/ locate /b iosystems eview Article rucial steps to life: From chemical reactions to code using agents uenther Witzany ∗ elos-Philosophische Praxis, Vogelsangstr. 18c, 5111 Buermoos, Austria r t i c l e i n f o rticle history: eceived 18 November 2015 eceived in revised form 5 December 2015 ccepted 7 December 2015 vailable online 23 December 2015 a b s t r a c t The concepts of the origin of the genetic code and the definitions of life changed dramatically after the RNA world hypothesis. Main narratives in molecular biology and genetics such as the "central dogma," "one gene one protein" and "non-coding DNA is junk" were falsified meanwhile. RNA moved from the transition intermediate molecule into centre stage. Additionally the abundance of empirical data concerning nonrandom genetic change operators such as the variety of mobile genetic elements, persistent viruses andeywords: on-coding RNAs epeat sequences enetic parasites atural code users defectives do not fit with the dominant narrative of error replication events (mutations) as being the main driving forces creating genetic novelty and diversity. The reductionistic and mechanistic views on physico-chemical properties of the genetic code are no longer convincing as appropriate descriptions of the abundance of non-random genetic content operators which are active in natural genetic engineering and natural genome editing. © 2015 Elsevier Ireland Ltd. All rights reserved.ontents 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 2. Deficits of the old main narratives in molecular biology and genetics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 3. The agents of natural genetic engineering and natural genome editing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 3.1. Non-coding repeat syntax vs. coding non-repeat syntax . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 3.1.1. Genome fragmentation and assembly and the role of repeat syntax. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .51 3.2. Natural genome editors differentiate between self and non-self . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 3.3. RNA world agents: where the genotype is the phenotype . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 4. Infectious parasite lifestyle results in immune systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 5. Crucial steps to life: from abiotic chemistry to biotic code usage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 5.1. Interacting RNA groups generate the first natural code . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 5.2. Essential tools in RNA group building: ligase and endonuclease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 5.3. A new domain of life: natural genetic identity producers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 5.4. How to do things with sequences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 6. DNA innovation: unstable RNA productivity and stable DNA storage medium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 7. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 . Introduction While the RNA world hypothesis is strongly supported by an bundance of detailed results in RNA biology and virology the orii.e. coherent and essential use of nucleic acid codes for genetic information generation, storage and heredity, a breakthrough with convincing explanatory power is lacking (Lehman, 2015). The complementary features of genetic phenomena that are clearly absentin of biological selection in contrast to prebiotic chemistry remains nknown. Although several promising approaches investigate this orderline between life and non-life empirically and theoretically, ∗ Tel.: +43 62746805; fax: +43 62746805. E-mail address: witzany@sbg.at ttp://dx.doi.org/10.1016/j.biosystems.2015.12.007 303-2647/© 2015 Elsevier Ireland Ltd. All rights reserved.in prebiotics, such as usage of (i) combinatorial rules of nucleotide syntax, (ii) the context dependent (pragmatic) transcription that lead to (iii) the final function (semantics) of the transcription products are not part of quantitative analyses in molecular biology and genetics. Therefore it is less helpful to simply ignore these features and to propose a gradual emergence out of prebiotic chemistry into biology (Eigen and Schuster, 1982; Szathmary and Maynard 5 stems S 2 f n 2 a a r t a m d g e t c i i S w t o a r d 2 ( c " t c r o b " a o i n g a ( a c t m i c i i a a p t u l t l c 0 G. Witzany / BioSy mith, 1997; Mayr, 2004; Goldenfeld and Woese, 2011; Koonin, 011; Yarus, 2011; Wächtershäuser, 2014). This review will thereore look at essential features of natural codes that may lead to a ew definition of life. . Deficits of the old main narratives in molecular biology nd genetics For decades it was assumed that if the genetic code represents context-free universal grammar determined exclusively by natual laws, copying events can form only identical copies of the wild ype. If there is any change in such copies it is correct to term them s replication errors. Error replications (mutations) are a key eleent in explanatory models of the evolutionary origin of genetic iversity, being the ultimate resource for biological selection. More detailed, error-prone RNAs are a resource for generating enetic diversity followed by selection out of cumulative series of rror replications. If the error rate is too high, then genetic conent gets lost, followed by quasi-species collapse. Thus the genetic ode looks like an emergent property of self-organizing matter and nformation that underlies natural laws such as thermodynamcs, kinetics, atomic structure and their binding forces (Eigen and chuster, 1977, 1978, 1982). Therefore the natural genetic code as ell as human language can be fully investigated by information heory, i.e. a mathematical theory of communication, game theory r related mathematical concepts of language, because formalizble procedures are the best tools for depicting the logic of material eality (Eigen and Winkler, 1981). This logic of material reality etermines the physics and chemistry of natural codes (Schuster, 011) as well as natural code-generating systems like cells, organs e.g. the human brain) and organisms (Eigen and Winkler, 1981). If we look at the genetic code and its characters, the rules of ombination detected by Erwin Chargaff which were later termed Watson-Crick base-pairing" (Forsdyke and Mortimer, 2000), and he information-storing function essential for heredity, we can onfidently support Manfred Eigen's claim that the genetic code epresents a real language and not just a metaphor. "All the words f the molecular language compose a meaningful text that can e divided up into sentences" (Eigen and Winkler, 1981, p. 272). Nature's two great evolutionary processes – the development of ll forms of life and the evolution of the intellect – both depended n the existence of language" (Eigen and Winkler, 1981, p. 282). Yet the concept of language and communication Eigen used s based on Turing and von Neumann's machine concepts, Shanon and Weaver's information theory and Chomsky's universal rammar concept. Current empirical knowledge about language nd communication contradicts these assumptions fundamentally Witzany, 1995, 2014a). Real lifeworld communication by living gents cannot be depicted by mathematical equations because ommunicating living agents do not behave mechanistically and he syntactical structure of natural codes does not represent its eaning, which in most cases is not available in the superficial but n the hidden deep grammar (Witzany, 1995). In such outdated conepts a natural code like the genetic code is reduced to the sum of ts measurable and superficial attributes which can be computed n a digital and algorithm-based procedure. The coherent generation of de novo sequences by competent gents in real-life situations cannot be part of algorithm-based nalyses (Witzany, 2010a, 2012), because such non-random rocesses of competent productivity cannot be explained by quanitative analysis. Nevertheless, Manfred Eigen and Peter Schuster sed this concept to explain the evolution of quasi-species andife in general (Eigen and Schuster, 1977, 1978, 1982). Because heir theoretical assumptions on the essential features of natural anguages used in communication processes do not match the urrent empirical data about consortial interacting RNA agents,140 (2016) 49–57 the question arises how a new concept could explain the origin of the genetic code more coherently by integrating the role of viruses, mobile genetic elements and non-coding RNAs in parallel. Also, more recent approaches that identify the key players in the emergence of biological information such as polypeptides, RNA-like polymers, and lipids and the known parameters such as viable cores, connectivity kinetics, information control, scalability, resource availability, and compartmentalization which may guide the aggregate evolution of collectively autocatalytic sets remain on the molecular stage and cannot explain how the genetic code molecules emerged into a real natural code (Nghe et al., 2015; Shay et al., 2015) with three inherent levels of rules (syntax, pragmatics, semantics). Mathematical analyses of network formation cannot explain the rule-based real-life interactions of social groups that share genetic identities within historically grown ecospheres (Witzany, 2005, 2014b). 3. The agents of natural genetic engineering and natural genome editing Since Barbara McClintock's far-reaching detection of mobile genetic elements, the RNA world hypothesis followed by the rise of RNA biology and the comeback of virology, we have a variety of terms for RNA agents that play essential roles in natural genetic engineering and natural genome editing (Witzany, 2010a,b, 2015a). Crucial steps in systematizing the available empirical data that show an abundance of different pathways by which cells generate genetic diversity and gene regulations constituted the concept of natural genetic engineering outlined by Shapiro (2009, 2016). An abundance of investigations on non-random genetic content operators such as transposons, retrotransposons, long terminal repeats, non-long terminal repeats, various forms of introns, phages and plasmids is described in his publications (Shapiro, 1992, 2005, 2011). Of equal importance was the comeback of virology which coherently explained sub-cellular genetic content organization by persistent viruses, infectious DNA or RNA, genetic parasites, selfish DNA, and the techniques of insertion, deletion, restriction, modification, counterbalancing toxin and anti-toxin "addiction modules" that re-regulate their counterpart according to contextual needs (Villarreal, 2005, 2009a, 2012). Accordingly the concept of natural genetic engineering had to be completed by that of natural genome editing (Witzany, 2010a). Interestingly, all of these agents involved in natural genetic engineering share a common feature in genetic syntax: they represent repeated nucleotide composition (Shapiro and von Sternberg, 2005; von Sternberg and Shapiro, 2005; Jurka et al., 2007). Additionally we find this phenomenon in very conserved DNA genome content such as telomeres and centromeres (Witzany, 2008; Alliegro, 2011). 3.1. Non-coding repeat syntax vs. coding non-repeat syntax One of the key elements that provides RNA content to be translated into DNA is reverse transcriptase, which has polymerase, endonuclease and RNase H abilities, also represented by repeated sequence syntax. Therefore we should remember this feature because it contrasts all the protein-coding nucleic acid sequence syntax, which is coded in non-repetitive nucleotide sequences. In contrast with the concepts of former decades it is now acknowledged that, together with the large variety of non-coding RNAs, RNA agents represented by repeat sequences are key to all cellular and genetic regulatory processes (Shapiro, 2009; Mattick, 2009; Qureshi and Mehler, 2012; Moelling and Broecker, 2015). This means RNA agents share a repeat sequence syntax whereas the stems n b s i s ( c p l g f s g o s d t m c i r s ( o i g w l i l a a c n a r b 3 s t I i r e o b t s t u m o m d c n 2 m G. Witzany / BioSy ucleotide sequence of DNA that codes for proteins is characterized y non-repeat syntax. Recently it has been acknowledged that repetitive nucleotide yntax is a pre-requisite to recombination and rearrangements, .e. the module-like tool function of the genetic code depends omehow on the repeat grammar of nucleotide sequence order Sciamanna et al., 2009; Deng et al., 2012). The reason for this is urrently unknown, but if we look at cellular life constituted by rotein-based cells and coded by non-repeat syntax and its reguatory (repeat syntax) RNA agents we can differentiate a level of enetic information which contains competent regulation relevant or coded proteins by a non-repeat nucleotide syntax. In the early 1990s a research team from Boston Univerity investigated quantifiable aspects of coding and non-coding enetic sequences such as statistical measurements of nucleotides f the molecular alphabet. While coding DNA is predominantly hort-range correlated, the order in non-coding DNA is largely etermined by long-range correlations. The authors suggested that heir "results are consistent with the possible existence of one (or ore than one) structured biological language(s) present in nonoding DNA sequences" (Mantegna et al., 1994, p. 3172). From the action theoretical perspective a side result is more nteresting: The tests revealed that non-coding DNA more closely esembles everyday language, i.e. concrete speech acts, while the tructure of coding DNA more closely resembles that of artificial e.g. scientific) languages. Current knowledge about the functions f these two language domains suggests that everyday language s the medium of getting socialized within group interactions by etting the competence to correctly combine linguistic utterances ith the meaning function of words. In contrast to this artificial anguages are based on special conventions determining the meanng of certain words and narratives in limited (such as scientific) anguage communities. Whereas the first one is essential for any biotic group building s a primary tool for co-ordinating and organizing real-life situtions, the latter is a useful tool for constructing blueprints for omplex artificial objects (Witzany, 2010b). This fits with the role of on-coding (repeat) sequences representing key elements of interction, recombination, regulation and innovation and the coding egions (for proteins) as conserved blueprints for complex protein odies. .1.1. Genome fragmentation and assembly and the role of repeat yntax One interesting phenomenon is how genes that code for proeins in cellular organisms are dispersed throughout the genome. n alternative splicing pathways the separating (repeat syntax) ntrons are removed, and the remaining (non-repeat) exons that epresent genes that code for proteins are assembled into a cohernt line-up of coding regions to form an mRNA that is transported ut of the nucleus to the tRNAs for translation into proteins. As mentioned recently by Ricardo Flores, some RNA viruses ehave similarly to mRNAs (Minoia et al., 2015). They move owards the ribosome of a cell and provide instruction to the riboome to synthesize proteins. Interestingly, this ability is essential o many RNA agents for synthesizing new RNA molecules de novo sing the RNA-dependent RNA polymerase (McDonald, 2013). This ay indicate the evolutionary pathway from early RNA infections f cellular host organisms to it is new use as exapted tool in host essenger RNAs. Especially the eukaryotic genome full of repeat elements erived from former infectious RNA (Villarreal, 2005), that serve as rucial regulatory tools in a variety of non-coding RNAs of both long on-coding RNAs and micro RNAs (Delihas, 2011; Cox and Sullivan, 014). Why are such intronic regions or gene coding regions so uch dispersed throughout the genome? Or is this not restricted to140 (2016) 49–57 51 coding regions? Are there also long non-coding RNAs with important regulatory functions dispersed throughout the host genome (Wang et al., 2011)? What is the point of genome fragmentation as an evolutionary conserved technique? Is it for immunity against genetic parasites, in that an attack would probably reach only small fractions of the whole genetic identity? Then genetic fragmentation would be related to adaptive immunity systems such as VDJ and even CRIPRS/Cas systems (Sommer, 2005; Mojica et al., 2005). Is it because of energy optimization or maybe because the several parts may serve several functions at different loci? 3.2. Natural genome editors differentiate between self and non-self How did prebiotic chemistry start life? From the pragmatic action theoretical perspective the variety of RNA agents that share the competence to act on nucleic acid sequences by several techniques (de novo generation, ligation/degradation, insertion/deletion, silencing, amplification, epigenetic markings, etc.) is coherent with the general assumption that no natural code codes itself but needs some competent agents that act on this code (Witzany, 2011, 2012, 2014b; Witzany and Baluska, 2012; Salmena et al., 2011). Now we can ask how these agents evolve, how they interact, co-operate or compete, or even both, at different times, depending on the varying real life context. All such interactions depend on an ability to identify appropriate interaction partners and therefore differentiate between self and non-self, which means differentiating identity-sharing agents of proponents representing non-identity, which must be fought or precluded (Marraffini and Sontheimer, 2010). Others may represent co-operation partners; some are actually interaction partners. Others remain as silenced enemies which could destroy identity but may be useful tools for later co-opting or ex-apting processes. At different times formerly fought non-identity proponents may be useful tools for generating new partnership (Villarreal, 2011a,b, 2012, 2014). Several DNA and RNA degrading processes are not investigated under the assumption that they serve as useful resource for re-use and identity-building modules (Villarreal, 2014). Additionally important and a key feature of this agent based co-operativity are the fast-changing identities which lead to the question how a former enemy becomes a new co-operation partner. What does this mean for former co-operative partners which may turn into enemies, the fast-changing functional partnerships and the concurrent changes in organization and syntax order? As these interaction processes start from the beginning of RNA life (Hayden and Lehman, 2006; Mattick, 2011; Yarus, 2011; Higgs and Wu, 2012; Higgs and Lehman, 2015), i.e. life without unicellular organisms, in abundant ecospheres and additionally in indefinite processes, conserved DNA hereditary pathways may be used successfully to reproduce, so to speak, "selected works of RNA agency." If we subtracted all these RNA-based processes would cellular life function? 3.3. RNA world agents: where the genotype is the phenotype With the split into a RNA world and a DNA world that codes for proteins with a non-repeat genetic syntax the split between the genotype and the phenotype emerged. The genetic code now also codes for proteins and the protein enzymes form the protein bodies, which we know as cells, cellular parts that organize metabolism, tissues, organs and organisms, all of which we term life from the most primitive last universal common ancestor to human beings. The percentage of coding for such proteins in the human 3 billion base pairs is only 1.5%, however. All the other DNA contains non-coding RNAs (up to 45%) and non-coding areas with unknown 5 stems f u g w t d t t s M r ( i p ( s t a t c i 2 s K d e e m r i a b c a w n o a 4 c a r W w a " 2 s f d t I b p i i r o t 2 G. Witzany / BioSy unctions (55%) which I suggest represent non-coding RNAs of reglatory functions. This means in all organisms we can find the enotype and the encoded phenotype. The genotype contains the hole blueprint for the phenotype. The interesting thing is that he variety of parts that constitute the phenotype throughout its evelopmental stages as well as its regulation is coded in the genoype together with epigenetic markings. Epigenetics is an effective ool for expanding the informational content of a given nucleotide equence syntax with multiple meanings/functions (Slotkin and artienssen, 2007; Mattick, 2010; Conley and King Jordan, 2012) epresenting experiences in historical contexts of real life-worlds Donkin et al., 2016). We know that epigenetic markings silence or increase the varous outcomes of genetic information: a good example is the henotype of brain organs and their synaptic neuronal networks Barry and Mattick, 2012). This means a single genotype may have everal reading patterns which result in slightly different phenoypes. In contrast, in the previous pure RNA world the RNA world gents served as a template or active catalyst with several funcional domains such as RNA binding, protein-binding, DNA-binding, onformational switch and the important function of scaffolding nto a coordinated ribonucleoprotein function (Mercer and Mattick, 013). In the early RNA world proteins served to stabilize RNA tructures only not as building blocks of cellular bodies (Wolf and oonin, 2007). According the early emergence of the self/non-self ifferentiation competence in RNA groups we have to think on the volution of compartmentalization by membranes that serve as ssential tools for the emergence of identity (self/non-self). Such embrane encoding genes (env-genes) later on served as exapted egulatory elements in host organisms as documented in the varous roles of repetitive elements of endogenous retroviruses such s LTRs and non-LTRs (Villarreal, 2005). The double function of genotype and phenotype is unique in iology, where we can find most organisms divided into genetic oding and protein-based bodies within their real lifeworld interctions. In former times it was thought that the information transfer as a one-way road from genotype to phenotype but with epigeetics and RNA biology it became obvious that the reverse direction f information flow plays a crucial role in evolution, development nd adaptational flexibility (Mattick, 2010). . Infectious parasite lifestyle results in immune systems One main assumption of the current investigations of the preonditions of life is self-organized replication, which means that molecular-based entity that is coded in hereditary material can eplicate in other entities than itself (Cheng and Unrau, 2010). ithout ribozymes that are able to replicate themselves the RNA orld would not have prevailed. In this context we can differentite between a "dead" state controlled by prebiotic chemistry and a living" state controlled by autocatalytic replication (Larson et al., 012; Vaidya et al., 2013). Interestingly, a new perspective has arisen in which passive RNA erves as a template for active RNA that acts as a catalyst with diferent fitness values. RNA-based parasites that are predominant estroy the system (error threshold) because their error rate is oo high to be conserved (leading to a (quasi-)species collapse). n contrast, parasites that are not predominant enrich the system ecause they constitute nucleotide sequence novelty for adaptive urposes, such as efficient immune response tools in the host. The nfectious parasite livestyle uses and manipulates other agents than tself for its purposes, which may lead to beneficial co-evolutionary esults as documented in the several immune systems of cellular rganisms (Villarreal, 2009a,b, 2012; Bushman, 2003). Especially his agent-based perspective will replace former narratives such as140 (2016) 49–57 "autocatalytic replications" (Kauffman, 2014) that reduced biological agent-behaviour to systems theoretical properties. Co-operation, Darwinian evolution, behaviour: are these biotic or prebiotic terms? Some authors suggest they are prebiotic (Pross, 2011) and others that they are clearly biotic (Larson et al., 2012). A chimaera seems to be the mixture of both such as "behavioural chemistry." Yet if behaviour is an integral feature of life and all organisms are built of molecules and atoms every biotic behaviour is intrinsically molecular behaviour as every organism replicates like an ensemble of chemicals (Cello et al., 2002.). However, do such generalizations lead to a convincing description of e.g. human poems by physics, chemistry and mathematics? In contrast to former concepts with the prebiotic "soup" and a central role of "hot steamers" that serve as candidates for the transition of prebiotic chemistry to life more recently it has been assumed Earth at the origin of biotic behaviour was an ice ball. This makes sense theoretically, because cold water and ice are ideal preconditions for RNA chemistry (Vlassov et al., 2004; Attwater et al., 2010; Yarus, 2012; Lehman, 2013), which facilitates nucleotide pairing and stabilizes RNA structures which otherwise would be destroyed. 5. Crucial steps to life: from abiotic chemistry to biotic code usage Short RNA nucleotide sequences have an intrinsic ability to fold back on themselves to form the tools essential for life: the RNA hairpin with its typical base-paired stems and the loop which is constituted by a single-stranded RNA nucleotide sequence (Moore, 1999; Hendrix et al., 2005; Gwiazda et al., 2012; Martin et al., 2015) both constituted in a repeat syntax. While the double-stranded stems are not very active in binding to RNAs that are not part of the stem, the loops are open for binding events to other RNA such as loops from both self and non-self RNAs (Smit et al., 2006). Most interestingly, RNAs that are able to fold back by themselves can co-operate (Muller et al., 2012; Petkovic and Muller, 2013), i.e. build cooperative groups with identity sharing as well as identity precluding abilities – switching back and forth even in short time events with far-reaching consequences: the RNA genotype may behave as a phenotype similar to viroids (Flores et al., 2012, 2014). A coherent genotype is possible because of strict adherence to the rules of molecular syntax, the base-pairing rules, which include that if the rules are not followed base pairing does not happen and loop building with non-base pairing nucleotide sequences occurs. This is at the core of identity building of RNA groups because this mix of two different forms (double-stranded stems and single-stranded loops) of nucleotide molecular syntax in the genotype is the essence of the phenotype that may interact as RNA consortium with other RNA consortia or even with DNA sequences or proteins (Mercer and Mattick, 2013; Behrouzi et al., 2012). Yet the crucial feature is not the sequence syntax but the function of the entire RNA stem loop and its tertiary folding, which means varying syntax combinations may lead to the same function (Doudna et al., 1989; Doudna and Rath, 2002; Atkins et al., 2011). If the interactions of individual RNA stem loops lead to groups of RNA consortia we can look at the crucial event of their becoming more than chemistry, i.e. real life. Exclusively the group interactions of RNA stem loops make the genotype evolve into semiotic biology, which means the emergence of natural code rules (syntax, pragmatics, semantics). The characters get their language-like feature only through the social interactions of RNAs. Because the binding relates not only to physical–chemical parts but also nucleotides they have an inherent opportunity to serve as semiotic signs, characters for a language/code-like property. This feature cannot be substantiated by quantifiable analyses because it is a socially interacting feature. As mentioned above social interaction patterns of living organisms can be measured by statistical procedures, G. Witzany / BioSystems Fig. 1. If base-paired stems of an RNA stem loop build bulges, the whole identity of the stem loop and the group of which this stem loop is part can change rapidly. Neither the fittest types nor selfish agents are successful early replicators but the group which is the result of cooperative RNA stem loops (quasispecies-consortia; QS-C). However, in the early RNA world they changed their identity rather fast and constantly. Through spontaneous single bulge loop productivity the whole identity may change and with it the interactional behaviour against related structures, possible c d a b i o p e i a i s g o b n t l a 5 i u d a s c F n e s s R t ooperators and enemies that do not fit into the realm as well as against formerly egraded agents (that may serve as appropriate tools for later group ensembles) and gainst real genetic parasites (from: Villarreal and Witzany, 2013b). ut such methods are less helpful for understanding consortial nteracting motifs and techniques because such real life motifs f biological agents are not fully computable by algorithm based rocedures (Witzany, 1995, 2010b). No other physico-chemical ntities share this property, only nucleic acid molecules. The social nteraction of RNAs turns this property into a coding capacity. In both cases, single RNA stem loops lacking biotic behaviour nd RNA groups with clear biotic behaviour by several cooperatng RNA stem loops we have the same chemicals, suggesting the tep from prebiotic chemistry to real life is a gradual one as sugested by several of the authors cited earlier. Yet the emergence f biotic behavioural interactions is not gradual; it is fundamental ecause such behavioural patterns are completely absent in abiotic ature. Additionally RNA group behaviour is essential not only for he origin of life but is the key feature of gene regulation and celluar processes. If we stopped this behaviour no life would function s we know it (Fig. 1). .1. Interacting RNA groups generate the first natural code To escape the constant flux of unstable RNA sequences, DNA nnovation was the next important step in generating a fully natral code. However, let us recall that the single RNA stem loop oes not represent a natural code but solely the physico-chemical ssemblies of base-pairing molecules. If we look at the nucleotide equences of the single RNA stem loop from a purely physicohemical perspective the genetic code begins as abiotic chemistry. rom a biocommunication perspective no co-operativity is found, o biological selection occurred (Villarreal and Witzany, 2013a,b). Without RNA stem loop group building and group identity, howver, the chemicals do not become a natural code with its inherent yntactic, pragmatic ands semantic rules but remain on the abiotic tage determined by natural laws of physics and chemistry. Single NA nucleotides or a single RNA stem loop although built up of he characters of the nucleic acid language does not represent a140 (2016) 49–57 53 genetic code, but solely chemical molecules. Although we can identify all characters of the code, the genetic code does not function as a code but solely as chemical molecules. The genetic code with its typical language-like features (characters adopt syntactic, semantic, pragmatic rules) take the stage of a real natural language with the interactional group building of various RNA stem loops. The interactional and group building cooperativity of the RNA stem loops constitute the genetic code as a real natural code, not its physico-chemical key characters alone. The RNA stem loops are part of an identity which co-operates or precludes and by compartmentalization (within lipid membranes?) gets the same first stages of conservation. Until DNA was invented conservation would have been a rare event instead of a constant evolutionary innovation process of maximum productivity of nucleotide sequence novelties, which in former concepts has been termed error catastrophe. With the emergence of the first natural language/code, the participating RNA agents get a tool which is open for indefinite generation of new sequences, information processing and storing. The biotic agents of RNA stem loop groups display their behavioural motifs through the third level of real natural language/code: pragmatics, the context-dependent use of syntax structure that emerges semantic meanings, i.e. concrete functionality, that is not restricted to the syntax structure but determined by the group behavioural pattern in a real-life context with its historically derived background. In the case of pure chemical assemblage of RNA nucleotides without RNA group building and group identity, only the syntax structure can determine meaning, but this is prebiotic, not biotic, not life. Life starts with the real pragmatic use, i.e. the interaction in group building. This is not the primary goal of interacting RNAs, however. The primary goal is the interaction to become part of cooperative networks that may also be competing and restricting (Popovic et al., 2015), as documented in the predominant ligase function in contrast to the nuclease function (Hayden and Lehman, 2006; Díaz Arenas and Lehman 2010). This means the turn to life is also a behavioural pattern between becoming part of an identity of RNA groups that reject those that do not fit into this identity. Accompanying this is continued productivity in that new sequences are generated which form stems and single-stranded RNA sequences that base pair to others. Therefore the origin of life is a complementary building up of cooperative behaviour by RNA stem loop groups that may generate and change the identity of RNA groups. 5.2. Essential tools in RNA group building: ligase and endonuclease The basic RNA stem loop is solely a physical–chemical entity without any biotic behaviour lacking natural selection. But within several others it can use its loop to base pair to non-self agents and form groups ("gangen"). The loop is the biocommunicative interaction tool. A group is built up of different members that represent a group identity (like gangs), as suggested by Villarreal (2014). One main behavioural motif here is the "kissing loop" motif. The single-stranded loop RNA is open for interactions with other (self or even non-self) single-stranded RNAs via base pairing according to base-pairing syntax rules (Brunel et al., 2002; Cao and Chen, 2011). This may have highly dynamic aspects such as the loop–loop interaction within an RNA stem loop group (as represented by editosomes, spliceosomes, ribosomal subunits and viruses) or between RNA stem loops with non-related RNA loops present within the cell, tissue, organ or organism. Some of them may be remnants of formerly degraded RNAs. RNA recycling is an important resource for building and rebuilding RNA identity 5 stems g b p g 2 a n s c i 2 i R a a u ( R S o w r S t s 2 i f 5 i p a s r v o c s a S P v fi s w o s i i p b l R d o g l h 4 G. Witzany / BioSy roups, i.e. formerly foreign (non-self) RNA group members may ecome relevant parts of a new (self) identity. The essential tool for building groups or dissolving groups into arts is the ligase/endonuclease module which counter-regulates roup building in early and current RNA worlds (Ohmori et al., 011; Stoddard, 2011; Villarreal, 2014). The group buildings initite a new property of behavioural patterns of RNA groups that does ot exist in former pre-group stages of RNA worlds: the self/nonelf differentiation behaviour which is the appropriate tool for o-operating with groups that fit into group identity and rejectng RNAs that do not fit into these identities (Battle and Doudna, 002). Later on many such RNA stem-loop groups were conserved n DNA storage medium, ready to be transcribed from DNA into NA agents that enacted cellular replication, recombination, repair nd immunity (Guilliam et al., 2015). Other examples include the two halves of tRNAs (Maizels nd Weiner, 1993; Maizels et al., 1999), the two important subnits of the ribosome that emerged out of polymerase ribozymes Harish and Caetano-Anolles, 2012; McGary and Nudler, 2013; oot-Bernstein and Root-Bernstein, 2015; Caetano-Anolles and un, 2014). We think also of recombination tools that evolved out f repair abilities, not forgetting the several parts that diversified ithin cellular life such as group II introns that evolved into LTR egulatory tools (Lambowitz and Zimmerly, 2011; Zimmerly and emper, 2015) or even into the important spliceosome that funcions as a splicezyme (Matlin and Moore, 2007; Amini et al., 2014). A imilar cooperative unit is the editosome in RNA editing (Witzany, 011). Interestingly consortial interacting RNAs outcompete selfsh genetic elements which contradicts the selfish gene narrative undamentally (Vaidya, 2012; Vaidya et al., 2012). .3. A new domain of life: natural genetic identity producers Genetic parasites, parasite replicators, mobile genetic elements, ntrons, viruses, and several other entities that are involved in cometent genetic content arrangements and natural genome editing re known today. Where, how and when did they evolve? Do they hare common features inherited from common ancestors? Their ole has been investigated within the last three decades and a ariety of essential features are common to them, but about their rigins there is no consensus. For decades it has been assumed that viruses escaped from ellular organisms representing genetic parasites. There are everal good arguments why viruses evolved before cellular gents (Villarreal, 2005, 2009a,b; Villarreal and Witzany, 2010). ome argue that they co-evolved (Koonin, 2010; Forterre and rangishvili, 2010; Koonin and Dolja, 2014; Rohwer et al., 2014). In this review it is argued that the RNA consortia that led to iruses are older than cellular life. Viruses seem to represent the rst more complex genetic identities built up by co-operative RNA tem loops. Only in the virosphere we can find both, RNA groups ithout membranes such as viroids and with membranes, some f them with essential regulatory roles in cellular host organisms uch as LTRs/non-LTRs (Ryan, 2009). Only the infectious behaviour s shared by both RNA sequences and viruses. However, is it really nfection or is it primarily interaction which may lead to both a redator manipulating prey behaviour and also to co-operative ehaviour beneficial for both interaction partners? This means what we define as a virus may be older than cellular ife forms, although then we should not term them viruses at all, but NA consortia (Villarreal, 2014) later on followed by viruses, viral erived parts or defectives such as SINEs LINEs ALUs, LTRs non-LTRs r more commonly genetic parasites, parasite replicators, mobile enetic elements, introns. All of them are the result of RNA stem oop co-operations, with several conserved genetic identities, all ighly able to edit host genomes in various ways, all essential tools140 (2016) 49–57 of the different agents and sub-populations (Villarreal and Witzany, 2015). We may term these agents now as genetic identity producers, to describe their common competence to differentiate self from nonself, to co-operate, combine and recombine, to generate coherent nucleotide sequences de novo, insert or delete them into non-self genomes serve as exaptable tools for host cellular needs (Bushman, 2003; Witzany, 2009). This may lead to the acknowledgement as an essential domain of life affecting all known three domains of life fundamentally (archaea, prokarya, eukarya). Their identity and specificity changed dramatically with the invention of DNA and protein-based cell morphologies and the success story of co-evolution between RNA stem loop identities (commonly genetic parasites, parasite replicators, mobile genetic elements, introns) and cellular life forms. 5.4. How to do things with sequences The RNA stem loop groups not only generate and constitute nucleotide sequences that serve as information storage media, but primarily interact (Nicholson and White, 2014). The generation of RNA stem loop consortia is real entities not just genetic syntax, and they are active in contributing to the identity of such groups and rejecting agents that do not fit this identity. In several motifs the interactions depend on the context in which an interaction takes place (Przybilski and Hammann, 2007; Popovic et al., 2015). This may be evolutionary conserved in DNA as demonstrated in the cooperative behaviour of the two ribosomal subunits. The activity is crucial for the result of the co-operation (Doudna and Rath, 2002). In all these natural genetic identity producers (predator RNAs, infectious RNAs, viruses, genetic parasites and defectives) the common feature is the reverse transcriptase (RT) which copies the RNA nucleotide sequence into a DNA strand. Interestingly, defectives, i.e. infectious agent-derived RNAs that remain as exapted and coopted RNA elements in their host genome (Brosius and Gould, 1993; Cox and Sullivan, 2014) may serve for host gene regulation together with counterparts that regulate the regulatory tool. For example, this happened with the group II introns that remain as splicing only elements in mitochondria and chloroplasts: these parts lost their RT as documented in a variety of group II introns (Zimmerly and Semper, 2015). The abundance of retrovirus-derived LTRs are excellent examples of exapted gene regulation tools as are the Alu sequences of which we find a million copies within the human genome and are recently identified as key player to build up the nucleolus as important place for ribosomal subunit assembly (Carmo-Fonseca, 2015). Another excellent example are the telomere/telomerase tools for the genome maintenance and therefore for conservation of the whole genetic information of the cell which is reduced through the billion replications through ageing (Witzany, 2008). In all these examples genetic sequences of natural genome editors do something, with the result that they act as vital agents within cellular organisms. 6. DNA innovation: unstable RNA productivity and stable DNA storage medium The innovation of DNA by the reverse transcriptase opened a new window in the evolution of life, i.e. completing unstable productivity with stable conservation. Additionally, the overwhelming number of interactions of RNA groups in the RNA world meant every transfer into DNA served as a kind of immune function; escape out of the continued possibility of information collapse in the RNA world into a world of conserved information. So DNA also became a habitat for RNA groups to hide in for some time or constantly (Witzany, 2009). There are good reasons why DNA arose stems t a w f w t l o u T r w l c b s w R o ( a 2 m d i t a o b c w b ( 7 u m T c p c n s d d c f n i e o p i a t T e n s G. Witzany / BioSy ogether with protein bodies, cells or cellular ensembles limited by membrane that protected them against invading parasites. This as the next step after proteins served only as stabilization tools or RNA sequence structures. The evolution of cellular morphology is another secret of life hich has not been investigated in this review, but is of imporance if we want a satisfactory answer to the question of what ife is. One main pathway is the translation process, the transfer f genetically encoded information into protein language, its reglation of all developmental processes (Wolf and Koonin, 2007). he initiation of the translation process is also regulated by longange RNA-RNA interactions, i.e. the interactions of RNA stem loops ithin one organism, triggered by internal and external factors, eads to the translation of genetic information into proteins that onstitute cellular bodies. Additionally, the new pathway of evolution, cellular proteinased phenotypes with their own behavioural patterns and success tories, represents a much more comfortable habitat for the RNA orld agents, not forgetting the variety of new RNPs and even NA groups that emerged in a co-evolutionary way with cellular rganisms, and expanded the matrix for colonization geometrically Witzany, 2009, 2015b). The emergence of DNA and protein-based cellular life created new biosphere with real cell-based organisms (Takeuchi et al., 011). Their own identity group building, evolution and developent from an RNA-only perspective opened up a completely new imension of genome-bearing entities as appropriate resources for nfectious/cooperative RNA settlements. Although RNAs function at he bottom of all genetic processes that regulate protein-based life, ll protein bodies interact independently through an abundance f phenotypic signalling processes (biocommunication) within and etween related and non-related organisms. The protein bodies of ellular organisms generate and constitute a planetary lifeworld hich by itself functions as the complementary part to feedack information and co-evolution to current RNA world agents Witzany, 2015b). . Conclusion As long as the DNA storage medium took centre stage in moleclar biology, genetics and evolution theory genetic changes that ay lead to genetic diversity were explained by replication errors. he abundance of empirical knowledge about non-random genetic ontent operators together with the rise of RNA Biology and the arallel comeback of virology took RNA at centre stage. RNAs can o-operate, built communities, generate nucleotide sequences de ovo and can insert/delete them into host genetic content. In this ense they determine host genetic identities throughout all kingoms and the planetary virosphere and represents a basic vertical omain of life. The natural genome editing competences of RNA onsortia contradict the random-like error replication narrative undamentally. This knowledge about the generation of new sequences that are ot the result of error replication rejects all attempts by mathematcal biology to fully explain the origin of the genetic code and the volution of life as well as the behavioural motifs of the core agents f life. Although it is possible to measure the physico-chemical roperties of nucleotide sequence molecules, cell biology, genetcs, computing their statistical features, essential properties such s de novo generation without gene duplication or error replicaion will have non-predictable, incomputable features in principle. his is the reason why mathematically and computation derived xplanations of the origin of life remain unsatisfactory. In parallel o creationist explanatory model is needed to explain and undertand the empirical data that represent the interactional motifs in140 (2016) 49–57 55 RNA group building. Both narratives of this traditional controversy are outdated now and a third way to explain biological evolution seems to have more explanatory power than the previous ones. The emergence of the genetic code is not the emergence of the nucleotides which constitute the code. The origin of the genetic code as a natural language occurs exclusively within co-operative interacting RNAs. So we can define life as an emergent property of social interacting RNAs. From this perspective life is coherent with the emergence of communication, i.e. interactions based on a natural code that underlies syntactic, pragmatic and semantic rules. References Alliegro, M.C., 2011. The centrosome and spindle as a ribonucleoprotein complex. Chromosome Res. 19, 367–376. Amini, Z.N., Olson, K.E., Muller, U.F., 2014. 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