While DNA, ANA and HNA pools proved inert, RNA (and to a lesser extent AtNA) pools displayed diverse modes of spontaneous intermolecular recombination, connecting recombination mechanistically to the vicinal ring cis-diol configuration shared by RNA and AtNA. Thus, the chemical constitution that renders both susceptible to hydrolysis emerges as the fundamental determinant of an innate capacity for recombination, which is shown to promote a concomitant increase in compositional, informational and structural pool complexity and hence evolutionary potential.Recombination, the exchange of information between different genetic polymer strands, is of fundamental importance in biology for genome maintenance and genetic diversification and is mediated by dedicated recombinase enzymes. Here, we describe an innate capacity for non-enzymatic recombination (and ligation) in random-sequence genetic oligomer pools. Specifically, we examine random and semi-random eicosamer (N This property critically informs many aspects of biological function including the adaptability of biological systems as a function of combinatorial diversity ranging from bacterial populations to the mammalian immune system and to abiotically-generated sequence pools. In all such cases, ‘survival’ (in a Darwinian sense) depends on the availability of functional entities  within the combinatorial space available to the system (such as the number of circulating B-lymphocytes or the size of a phage display repertoire). The same concept is also of central importance to the proposed spontaneous emergence of function from prebiotic pools of informational polymers, a key conjecture of current scenarios for the origin of life. Indeed, the phenotypic richness of random-sequence pools of the natural nucleic acids RNA and DNA, as well as a variety of xeno nucleic acids (XNAs), has been studied by in vitro selection methods reliant on iterative rounds of enrichment and amplification, yielding ligands (aptamers) and catalysts . Extrapo10-1013) , suggest10-1013) . Togethe10-1013) ). Thus, 10-1013) . In agre10-1013) . Consequ10-1013)  would beStarting from the premise that the global potential of oligomer pools for function may have been underestimated by an undue focus on single ‘hit’ sequences (i.e. fitness peaks), we have sought to examine the innate, global functional potential of the pools themselves, which has never been measured directly. Specifically, we examine pools of short RNA oligomers of semi- and fully-random sequence (with or without activation chemistry) and compare them to equivalent pools of chemically related but distinct genetic polymers, including DNA as well as the xeno nucleic acids (XNAs) ANA (arabino-), HNA (hexitol-) and AtNA , with regards to a simple functional test: the ability to undergo intermolecular ligation and/or recombination. While DNA, ANA and HNA pools proved inert, we discover a pervasive tendency of diverse-sequence RNA (and to a lesser extent AtNA) pools to undergo ligation and/or recombination even in the absence of extraneous activation chemistry, and analyse the constitution and emergent properties of recombined pools by deep sequencing, bioinformatic analysis and in silico simulation. Our results suggest that RNA (and to a lesser extent AtNA) hold a privileged position among simple alternatives for genetic information storage and propagation due to an innate capacity for recombination enabled by energetically near-neutral transesterification chemistry . Further15-member pools of eicosamer (20 nt long) RNAs. While still within the range of oligomer lengths likely to be accessible via prebiotic chemistry (15-member eicosamer pool (1.7 nmol) comprises significant redundancy (909 copies) of each possible 20-mer sequence. Finally, as shown previously, naturally occurring 20-mer sequences can associate into non-covalent multimer complexes reconstituting function such as catalysis, when incubated in eutectic ice phases at −9 °C, as exemplified by the hairpin ribozyme  labelled N20>p to facilitate detection of ligation products) in ice without any organizing template and sought to detect higher molecular weight (MW) product bands by gel shift in denaturing gel electrophoresis (Urea-PAGE)  both in the presence or absence of magnesium (+ / - Mg2+) counterions , we first examined the reactivity of 2’, 3’-cyclic phosphate (>p)-activated random RNA pools. >p groups form as part of RNA degradation reactions, as well as during proposed prebiotic nucleotide synthesis  and can ea-PAGE) . We obse-1pN+1 ligation junction   . While tesented) ) aides >versus computer-generated sequence pools using the same post-ligation nucleotide distribution  flanked by (unstructured) 20 nt constant sequence primer binding sites . The use of such ‘bait’  and ‘prey’  oligonucleotides (2.5 µM each) enabled rapid detection and analysis of intermolecular bait × prey (B × P) ligation products with high sensitivity by RT-PCR using primers complementary to C120 and C220 as well as much shorter incubation times than needed for direct detection (20-N20-N20-C220-3’), with very similar features as in the fully-random pool, including the above described CpN ligation junction ‘fingerprint’ and the increased base-pairing bias at the ligation site  allowed us to dissociate motif structure from sequence-dependent effects such as the imprint of pairing with the conserved C20 termini. We clustered ligation junction structures according to (predicted) minimal free energy using 408 different secondary structure sub-motifs based on 25 main-motifs (Motif A - Motif Y) including internal loops and hairpins  of compatible junctions from a subpopulation of random segments  and at ambient conditions (strictly Mg2+-dependent) with an up to 10-fold enhanced apparent ligation rate (kobs) compared to a simple gapped duplex reaction under the same conditions  albeit with a 2- to 3-fold slower kobs than an equivalent gapped duplex-mediated reaction  sequence pools (2.5 µM each) each bearing different 2’, 3’- or 5’-substituents . As descIn order to explore the consequence of alternative activating groups, prey pool activation with a 5’-triphosphate (5’ppp-P) was also examined . These y20-N20-3’OH × 5’OH-N20-C220) - that is pure RNA pools devoid of phosphorylation or any other activation chemistry. Remarkably, these showed intermolecular assembly, yielding a similar distribution of truncated products as observed for bait-2’/3’p×5’OH prey reactions, suggesting intermolecular recombination via transesterification chemistry as outlined above , we observed comparable intermolecular reactivity in unmodified semi-random RNA sequence bait and prey pools (C1ed above .20 sequences (and PCR amplification bias), we next sought to directly observe reactivity of random RNA eicosamer pools devoid of any activation chemistry. In these (bait × prey: 5’FAM-N20-3’OH × 5’OH-N20A10-3’OH), the prey pool included an invariant A10 tail sequence to aid recovery and analysis (by poly-dT primed reverse transcription), and to allow detection of prey self-recombination products (P-P). After an extended incubation  we were able to directly visualize formation of two distinct recombination products by gel electrophoresis without any amplification  display an innate capacity for intermolecular recombination, yielding subsets with altered oligomer length distribution (including longer RNA oligomers), enhanced sequence diversity and structural stability.Comparison of Rec1 sequence pools with three random pools  of equal nucleotide distribution generated in silico again indicated that recombination sites were preferentially localized in base-paired (gapped duplex motif) regions . Furthertrans) position. Like RNA, both DNA and ANA are capable of forming functional catalytic motifs (2+), which had been shown to strongly promote DNA self-cleavage , with respect to intermolecular ligation or recombination. We first examined unmodified, semi-random sequence pools of DNA or prebiotically plausible ANA (arabino nucleic acid) . In thesc motifs , includic motifs . Therefoc motifs  and despc motifs . Even incleavage , did notcleavage .Next, we explored the reactivity of pools of two additional RNA congeners, in which the five-membered ribofuranose ring is replaced by six-membered ring analogues: D-altritol nucleic acid (AtNA), which shares an analogous vicinal 2’, 3’-cis-diol configuration with RNA , and its2, see Materials and methods), which, unlike commercial enzymes, is able to reverse transcribe both RNA as well as both HNA and AtNA oligomers, we analysed ligation products by RT-PCR. While HNA pools again proved inert, we now observed clear intermolecular recombination in the AtNA pools, although to a notably lesser extent than equivalent RNA pools.To test whether the AtNA vicinal hydroxyl can participate in transesterification reactions despite its different ring geometry, we first exposed defined-sequence HNA and AtNA  oligonucleotides to alkaline pH (NaOH). Indeed, while HNA proved inert, AtNA (like RNA) proved to be sensitive to alkaline pH-induced hydrolysis, albeit with an apparent 6-fold slower strand scission rate than RNA . This inDeep sequencing of the recombination products from both RNA and AtNA pools revealed a similar size distribution indicative of recombination but, in the case of RNA, biased towards smaller products, presumably due to increased hydrolytic degradation induced by exposure to alkaline pH . FurtherRecombination is a fundamental process in biology both central to genetic diversification and genome repair , as well20 pools examined herein , such combinatorial diversity amounts to >1024 potential binary and an even vaster number of potential tertiary or higher order interactions. In the case of random RNA as well as semi-random RNA and AtNA oligomer pools, a subset of these non-covalent intermolecular assemblies do not remain inert , but display a pervasive tendency to undergo spontaneous disproportionation reactions resulting in intermolecular recombination and ligation.Here, we show that a capacity for spontaneous ligation and recombination is an innate property of random RNA (and to a lesser extent AtNA) oligomer pools and requires neither recombinase enzymes nor extraneous activating chemistry. As we demonstrate, such non-enzymatic recombination and ligation involves, to some degree, specific sequence motifs (e.g. in RNA pools) that promote ligation with either 2’−5’ or 3’−5’ regioselectivity . However10-1013 (The discrepancy between the extent of ligation / recombination we observe (2–10 % of pool sequences  to the p10-1013 ) should 10-1013 , our resbona fide ligation and recombination products as PCR or sequencing artefacts can be ruled out on multiple grounds. For one, incubation at −80 °C, which freezes the eutectic phase in our buffer system , which r system .Previous reports of non-enzymatic RNA recombination with defined substrates suggests that the majority of such reactions are likely to involve either a concerted mechanism of direct in-line attack on an internal phosphodiester linkage or, more frequently, a two step-mechanism of two consecutive transesterification reactions via an >p intermediate generated by hydrolysis . In bothThe mechanistic basis for the distinctive sequence signature (CpN) in RNA is currently unclear, although CpA and UpA junctions have been shown to be generally more reactive . Thus, t2+, which have been shown to promote self-cleavage in DNA  all contain functional sequences, including highly active ribozymes , DNAzymee in DNA . While n and ANA . This in and ANA  and loca and ANA . Consist and ANA .Although >p is only weakly activated towards nucleophilic attack, in the context of high effective concentrations of a 5’OH nucleophile in a gapped duplex , intermolecular bond formation can be efficient . Crucial10 and N20 pools disproportionates pool sequences into a distribution of both shorter (cleavage) and longer (ligation) strands and spontaneously increases D under a wide range of boundary conditions (D) scale with pool redundancy, code complexity and oligomer length  polymer chains - is favoured by entropic factors . Remarkanditions . Furtherr length . Under tnditions . Thus, sIn the context of evolution of early random sequence oligomer pools , the impact of the above recombination processes is significant, in particular considering that such pools would at the same time likely to be under fractionation and/or adaptive pressure. Indeed, a number of physicochemical processes  pools are naturally predisposed to recombination via near energetically neutral transesterification chemistry enabled by their specific chemical structure. As a result, such pools have an unique innate capacity to ‘bootstrap’ themselves towards higher compositional, informational and structural complexity  and thus2O and stored at −30 °C until usage. All oligonucleotide concentrations were determined spectroscopically using the extinction coefficients at 260 nm calculated by OligoCalc  supplemented with 1 µM of FITC-labelled N20>p pool. For analytical experiments with defined RNA sequences  0.5 μM of a FITC-labelled 3’-fragment was mixed with 1 μM of non-fluorescent, >p activated 5’-ligation partner. For analytical trans reactions, RNA splints concentrations were 1 μM. For preparative-scale reactions, concentrations were increased 10-fold to improve ligation efficiencies and product yields. Naive FITC-N20 / N20A10 pools (2.5 µM each) were incubated at for 5 months before recovery and denaturing PAGE analysis. Partially hydrolysed semi-random RNA and AltNA bait/prey pairs (see below) were incubated at a final concentration of 0.6 µM for each oligonucleotide for 5 months at −9 °C.For semi-random bait/prey RNA pairs , 2.5 μM 20>p ligation products, band intensities were normalized using the expected oligonucleotide length  then analysed by denaturing PAGE using 20% (w/v) Acrylamide/Bis 19:1 TB/8 M urea gels. For ligation kinetics, reaction master mixes were aliquoted into 10 µl reactions and frozen/quenched independently to prevent repeated freeze-thaw cycles of individual reactions. Gels were imaged using a Typhoon Trio scanner . Percentage intensity of starting material and ligation products were determined using ImageQuant TL. For quantifications of SYBRgold-stained Ne length  before c20>p in 100 µl) from −9 °C long-term incubation experiments were thawed on ice. 5 µl were mixed with 4 volumes of denaturing gel loading buffer  bromophenol blue) and analysed by denaturing PAGE followed by fluorescent gel imaging. To phosphorylate free 5’-ends and dephosphorylate unreacted 3’-ends, the remaining 95 µl of the reaction was treated with 90 U T4-PNK (NEB) for 45 min at 37 °C in presence of 1 mM ATP and 1x T4-PNK reaction buffer. 10 pmol of fresh N20>p was treated the same way to obtain sequence information of the starting material. T4-PNK was quenched by the addition of 8.8 µmol EDTA and formamide . For in-ice ligation reaction, ligated products were separated from the N20>p starting material by preparative denaturing PAGE followed by staining with SYBR Gold RNA stain (ThermoFisher Scientific). The bands corresponding to the N40 ligation product were excised, eluted from the gel matrix in 0.3 M sodium acetate (pH 5) and precipitated using 2 volumes of isopropanol. To remove residual gel-contaminations, both RNA samples were further purified using the RNeasy Mini Kit (Qiagen). Next, 3.5 pmol of the RNA pools  were ligated to preadenylated adapter Appa-3RND-Cy5 , 5.5 µl of 50% PEG 8000, 1 µl of 20 µM 5_RNDM linker and 2 µl RNA Ligase 1 . The ligation mix was incubated for 2 hr at 25 °C and stored at −20 °C. RT-PCR (50 µl) was performed using 1 µl of the ligation reaction and 20 pmol of the recovery primers 5RNDM_fw/3RNDM_rv in a SuperScript III One-Step RT-PCR reaction supplemented with Platinum Taq DNA Polymerase (ThermoFisher Scientific) according to the supplier’s instructions. Amplified cDNA samples were prepared for Illumina deep sequencing by appending the bridge-amplification sequences by PCR using the NEBNext High-Fidelity 2X PCR Master Mix (NEB) using the primers P3_3RND and P5_5RND according to the supplier’s protocol. Libraries were barcoded using P5 primers containing 6 nt sequences from the NEXTflex series (Illumina).Ice pellets of preparative ligation reactions  followed by adapter ligation using miRNA Cloning Linker 1 (IDT) as described in the previous section. cDNA was generated by RT-PCR using primers C1_fw (or C3_fw) and miRNA_CL1_rev in a SuperScript III One-Step RT-PCR reaction supplemented with Platinum Taq DNA Polymerase (ThermoFisher Scientific) according to the supplier’s instructions. Libraries for Illumina deep sequencing were prepared by PCR using the NEBNext High-Fidelity 2X PCR Master Mix (NEB) using the primers P3_miRNA_CL1_rv and P5_C1 (or P5_C3) according to the supplier’s protocol. DNA libraries from the 5’OH-N20-C220 and 5’OH-N20-C420 pre-ligation semi-random RNA pools were generated using a two-step protocol: First, single stranded cDNA was prepared using C2_rv/C4_rv using the SuperScript III according to the supplier’s instructions. Next, miRNA Cloning Linker 1 was ligated to the purified cDNA and ds cDNA was generated using GoTaq Green mastermix (Promega). Finally, reverse complement cDNA libraries of the 5’OH-N20-C220 and 5’OH-N20-C420 were generated using P3_miRNA_CL1_rv and P5_C2 (or P5_C3).For semi-randomer RNA reactions, RT-PCR was performed using the SuperScript III One-Step RT-PCR System with Platinum Taq DNA Polymerase (Invitrogen), according to the manufacturer’s protocol. In each reaction, 1.25 pM of total RNA from ligation or control reactions was used as RT-template with forward and reverse primers complementary to the respective constant C1ng sites . Deep seFor selected reactions with fully random pools, polyU tails were added to provide a primer-binding site prior to RT-PCR. PolyU tailing was performed using 0.2 U/µl polyU polymerase (NEB) in 1X NEB Buffer 2, 0.5 mM UTP for 20 min at 37 °C, followed by heat inactivation for 1 min at 75 °C. Next, RT-PCR was performed (with or without prior polyU-tailing) using the SMARTer RT-PCR system (Clontech), according to the manufacturer’s protocol, using the supplied SMARTer oligo as forward primer, and an oligo containing either a polyA- or polyT as reverse primer . cDNA wa2, which will be described elsewhere. XNA RT reactions were isolated using streptavidin beads as described previously . 1.25 pmol RNA was used with 6 pmol C1_fwd and C2_rev primers in 30 μl reaction volume.http://hannonlab.cshl.edu/fastx_toolkit/commandline.html) and cutadapt  biases in the experimental data sets, large  datasets were generated with a custom Python script  using thRNAfold  using stRNAfold .20-N20>p × 5’OH-N20-C220 and C120-N20>p × 5’OH-N20-C420 ligation experiment was calculated using RNAfold 2.3.5 with default settings. Using custom bash scripts . No splint was necessary for enzymatic ligation of H4. Samples were incubated at 37 °C for 90 min followed by gel purification of the ligated RNA. Self-ligated H4 RNA was obtained by gel purification of the 80 nt band after large-scale self-ligation of 5H4>p and 3H4 at −9 °C in 25 mM NaCl, 1 mM Tris•HCl pH 8 in a TXF200-R3 refrigerated water-baths for 2 weeks. Similarly, self-ligated H4T was produced by in-ice ligation 5H4T>p and 3H4T in presence of equimolar amounts of H4_splintA.3’−5’-linked controls of full-length H4 or H4T1 were produced in 75 μl reactions containing 5 nmol of 5H4 or 5H4T1 and 3H4 or 3H4T1 RNA in T4 DNA Ligase Buffer (NEB). In a first step, the 3’-fragment was 5’ phosphorylated and the 5’-fragment dephosphorylated using 30 U of full-length T4 Polynucleotide Kinase (NEB) followed by incubation for 1 hr at 37 °C. After addition of an equimolar amount of H4_splintG (for H4T1) the reaction was heated to 80 °C for 1 min and transferred to 65 °C for 15 min. The sample volume was made up to 100 μl with 2.5 μl 10x T4 DNA Ligase Buffer, H2, 18.75 mM MnCl2) and incubated for 2 h hours at 37 °C. Reactions were quenched by adding 4 volumes quenching buffer  Bromophenol Blue) and analysed by Urea-PAGE followed by fluorescent imaging. For RNaseT1 cleavage, 0.15 μM ligated H4T1 was incubated at 55 °C in 25 μl RNase T1 Buffer . Samples were quenched at 0, 10 and 30 min using 4 volumes of quenching buffer and analysed using Urea-PAGE followed by fluorescence gel imaging.For analytical DNAzyme cleavage, 0.1 μM ligated H4 sample or control was mixed with 1 μM E5112_H4 designed to cleave the H4 GrA ligation junction  in E51122 and 5 mM MnCl2 . Cleavage of the 3’−5’ J4-shrt control at the J4 ligation junction was performed using the custom 8–17-derived DNAzyme under the same conditions. The same DNAzyme was also used to inhibit initial self-cleavage of in-ice self-ligated J4.An all 3’−5’-linked control for J4-shrt was generated by annealing 5 nmol of each J4_shrt-P and J4_shrt-F with 5 nmol of the DNA splint J4_shrt-splint followed by ligation using T4-RNA Ligase two as described above. Self-ligated J4-shrt product was generated by co-incubating J4_shrt>p and J4_shrt-F in 25 mM NaCl, 1 mM Tris•HCl pH 8 in a TXF200-R3 refrigerated water-baths equilibrated at −9 °C for 2 weeks. Both self-ligated and control ligation products were gel-purified. Self-cleavage of J4-shrt RNAs was probed in 25 mM HEPES•NaOH pH 7.5, 5 mM MgClFor experiments in which random oligonucleotide pools were partially hydrolysed prior to ligation reactions, purified 40mer oligonucleotides . Samples were infused at 3 µl/min and spectra were obtained in positive (or: negative) ionization mode with a resolution of 15000 (FWHM) using leucine enkephalin as lock mass.For all reactions, analytical grade solvents were used. All moisture-sensitive reactions were carried out in oven-dried glassware under NGeneral procedure for the synthesis of altritol nucleoside 5’ triphosphates: To an ice-cold solution or suspension of corresponding altritol nucleoside  (0.1 mmo31P NMR (D2O): δ −9.2 , −11.1 , −23.0 . ESIHRMS found: (M-H)- 520.0044. calcd for C11H18N5O13P3: (M-H)- 520.0041.1’,5’-ANHYDRO-2’-DEOXY-2’-(ADENIN-9-YL)-D-ALTRITOL 6’-TRIPHOSPHATE TRIETHYLAMMONIUM SALT . 31P NMR31P NMR (D2O): δ −8.4 , −10.9 , −22.5 . ESIHRMS found: (M-H)- 535.9991. calcd for C11H18N5O14P3: (M-H)-5359990.1’,5’-ANHYDRO-2’-DEOXY-2’-(GUANIN-9-YL)-D-ALTRITOL 6’-TRIPHOSPHATE TRIETHYLAMMONIUM SALT 31P NMR (D2O): δ −6.9 , −11.0 , −22.7 . ESIHRMS found: (M-H)- 495.9938. calcd for C10H18N3O14P3: (M-H)- 495.9928.1’,5’-ANHYDRO-2’-DEOXY-2’-(CYTOSIN −1-YL)-D-ALTRITOL 6’-TRIPHOSPHATE, TRIETHYLAMMONIUM SALT 31P NMR (D2O): δ −6.5 , −11.1 , −22.6 . ESIHRMS found: (M-H)- 496.9795. calcd for C10H17N2O15P3: (M-H)- 496.97681’,5’-ANHYDRO-2’-DEOXY-2’-(URACIL-1-YL)-D-ALTRITOL 6’-TRIPHOSPHATE, TRIETHYLAMMONIUM SALT D, of a population of sequences, we compute the Shannon index .Essential revisions:Reviewer 1: major comments 1 and 4.Reviewer 2, major comment 1: please provide clear arguments, supported by literature, why this study is of interest to a broader audience than nucleic acid chemists, by inserting a section into the introduction. The first paragraph of reviewer 3 (last sentence) could be used as starting point. Major comment 2: Based on this concern, please describe in additional sentences how the reactions monitored in the study could give rise to an overall increase in compositional complexity if both cleavage and ligation events are considered.Reviewer 3: all major comments.Reviewer #1:This study investigates the ability of random sequence pools of RNA, DNA, ANA, HNA, and AtNA to promote ligation and recombination reactions. The work is original, and explores important concepts related to the functional potential of polymers. However, from my perspective it could be significantly improved by considering the following issues.1) You used gel purification and high-throughput sequencing to identify molecules from different types of random sequence pools that undergo ligation or recombination reactions after long incubations. My major criticism of this work is that you did not show that these sequences react at enhanced rates relative to the average polymer sequence. Each pool probably contains a small number of molecules with enhanced ligation or recombination rates and a large excess of sequences that react at background levels. After a single purification , it is possible that these pools will still contain mostly inactive sequences. If this is the case, sequencing will not necessarily provide information about motifs that promote ligation/recombination (but see point two). The clearest way to address this point would be to experimentally measure the ligation/recombination rates of randomly chosen variants from at least one of the evolved pools. Are the ligation/recombination rates of these sequences higher than those of arbitrary sequences or the unevolved starting pool? Figure 2—figure supplement 4 shows that you can measure the rates of some of these sequences in a reasonable amount of time, but not whether they are enhanced relative to arbitrary sequences or the starting pool. The fact that the sequence compositions of the ligated/recombined pools are different from the starting pools is encouraging in this respect. On the other hand, because the results of many experiments in this study cannot be correctly interpreted without knowing why particular sequences reacted, additional characterization is needed. I would also consider putting at least some of these results in the main figures.2) I am aware of several studies  in which high-throughput sequencing was used to characterize pools after in vitro selection experiments. In these studies, sequenced pools contained multiple copies of some variants, and a key component of the analysis was to show that copy number was correlated with catalytic or binding activity. I could imagine analyzing your experiments in a similar way. Furthermore, showing that some sequences appear multiple times in the high-throughput sequencing reads would provide additional evidence that they have enhanced ligations/recombination rates. I suspect that your evolved pools contained too many sequences to perform this type of analysis, but these issues should be at least briefly discussed.3) It seems to me that a model of recombination in which a 5' hydroxyl group in one oligonucleotide attacks a phosphodiester bond in the other is simpler than the one proposed here (in which recombination requires both self-cleavage and ligation). I would recommend providing evidence from either experiments or the literature in support of your proposed mechanism.4) RNA secondary structure can only be predicted to a limited extent. For this reason, I am not convinced that the ligation junctions of these sequences typically occur in the context of duplexes. Can you demonstrate this experimentally? Furthermore, I am not aware of reliable methods to predict RNA tertiary structure. For this reason (and because it is does not change any of the main conclusions of the paper) I would remove the statement in the Results section that J4 forms a purine-rich 4x4 internal loop with a triple-shared GA motif.5) For me, one of the most exciting and interesting parts of the manuscript was your analysis of the reactivity of polymers other than RNA and DNA. However, the way in which the results were presented was not logical to me. I would recommend first comparing the ability of each of these polymers to promote ligation/recombination reactions under the same conditions, and then discuss new types of experiments (such as treating with base prior to incubation).Reviewer #2:Mutschler et al., have investigated spontaneous cleavage and ligation reactions among a diverse population of RNA  molecules. These reactions are well known, and the ability of a complementary template to accelerate the rate of ligation was first described over 40 years ago. Although these reactions have previously been carried out with mixed populations, this is the first study, to my knowledge, to apply deep sequencing to assess sequence preferences, especially for ligation. Not surprisingly, the authors find that there are some sequence preferences, which reflect a combination of intrinsic chemical reactivity and the potential for templated interactions. The reasons for the former are obscure, whereas the latter are due to both canonical and non-canonical templating effects. It is not surprising that DNA, ANA (arabino nucleic acid), and HNA (hexitol nucleic acid), all of which lack a vicinal cis-hydroxyl, do not undergo these reactions, whereas AtNA , which contains a vicinal cis-hydroxyl, does.eLife. The conclusions are generally well supported by the data. However, it is somewhat misleading to point to the "increase in the compositional and structural complexity of recombined pools" while ignoring the decrease in oligomer length that occurs due to the same reactions. If one considers only the ligated products, then those materials can be said to have increased complexity. But for the assembly of materials that involve both cleavage and ligation events , one must also consider the many shorter cleavage products that arise. It is not clear from this study how the reactions could achieve an overall increase in compositional complexity. Presumably this would require a fractionation process or means to shift the chemical equilibrium in favor of ligation. The present study would be more suitable for a specialized journal such as Nucleic Acids Research or Angewandte Chemie.This is a well-executed study that will be of interest to nucleic acid chemists, but will not have broader appeal, as would be required for publication in Reviewer #3:This manuscript describes and extensively analyzes the ability of random sequences to ligate and recombine. The testing was primarily performed with RNA sequences and then compared across multiple genetic polymers . The authors show (for the most part) that recombination via trans-ligation of two termini and via sequence displacement is detectable either directly using denaturing PAGE or, in cases when constant regions were added to the distal termini, using (RT)PCR. The reactions were performed in the eutectic phase of water-ice and control reactions incubated at -80 °C showed no activity. Overall this is a comprehensively designed and analyzed work with far-reaching importance, particularly for the Origin of Life field, but also for synthetic and chemical biology.The ligated junctions for RNA seem to favor a G on the downstream of the ligation site. The RNA ligation site is thus biased, though not completely, towards a C/G sequence, not just CN. The authors use the unligated pool as a control; however, sequencing of unligated prey sequences is strongly biased by the method of introducing sequencing primers on the 5′ end (which depends on cross-templating by the RT enzyme and the SMARTER oligo substrate), so the statistics of the ligated vs unligated nucleotide at the 3′ side of the junction are not reliable. I understand the authors are being careful with their interpretation of the data, but the biases of the trans-templating method are known and can therefore be incorporated into the analysis, at least at the level of discussion if not directly in the Results section.Figure 4B is key for the conclusions of this manuscript, but the bands for HNA are practically invisible and for AtNA the -80 control is very poorly visible. When intensified, both HNA and AtNA show bands corresponding to longer products. Ditto for DNA and ANA lanes in Figure Figure 4—figure supplement 1, where little to nothing is visible in either the experiment or the control lanes. These gels should be presented intensified as in Figure 3A. Related to this point, why are the -80 °C controls in Figure 4 invisible in the first place?2≈1012. Are these libraries exhaustive with respect to the potential diversity limit? Are there known biases in composition for the non-biological genetic polymers? The authors do not mention the amounts of material used, just concentrations. Clearly, sequencing of the entire starting pool (or even recombined and directly isolated ones) is not practical, but for the PCR-amplified pools, the sequencing results may be exhaustive. For that, however, an estimate of the starting diversity and the total amplification of the recombined products would have to be presented. The manuscript would be enhanced if these numbers were included for all experiments and pools, particularly for the RT-PCR-amplified pools, where the HTS results may represent nearly all ligated sequences.What are the diversities of libraries used? The theoretical limit of a 20-mer is 4The free energy of activation of a >p vs a triphosphate is known. Assuming similar activation energy for the ligation of a 5′-OH with >p and a triphosphate, the expected kinetics for the background reaction can be estimated from the Rohatgi and Szostak, 1996 paper. An estimate of the background ligation rate and acceleration by the individual motifs should be presented. [Editors’ note: the author responses to the first round of peer review follow.][…] Reviewer #1:This study investigates the ability of random sequence pools of RNA, DNA, ANA, HNA, and AtNA to promote ligation and recombination reactions. The work is original, and explores important concepts related to the functional potential of polymers. However, from my perspective it could be significantly improved by considering the following issues.1) You used gel purification and high-throughput sequencing to identify molecules from different types of random sequence pools that undergo ligation or recombination reactions after long incubations. Each pool probably contains a small number of molecules with enhanced ligation or recombination rates and a large excess of sequences that react at background levels. After a single purification , it is possible that these pools will still contain mostly inactive sequences. If this is the case, sequencing will not necessarily provide information about motifs that promote ligation/recombination (but see point 2). Figure 2—figure supplement 4 shows that you can measure the rates of some of these sequences in a reasonable amount of time, but not whether they are enhanced relative to arbitrary sequences or the starting pool. The fact that the sequence compositions of the ligated/recombined pools are different from the starting pools is encouraging in this respect. On the other hand, because the results of many experiments in this study cannot be correctly interpreted without knowing why particular sequences reacted, additional characterization is needed. I would also consider putting at least some of these results in the main figures.We welcome this comment, which touches upon key aspects of our work and are addressing it below in detail.The main criticism is based on a misinterpretation of the objective of the paper, which was not to bypass selection / SELEX strategies to isolate defined functional sequences (fitness peaks) (which has been done many times) but rather to investigate the global, systems-level fitness of random sequence pools as a whole . In a sense, what we are trying to determine is what the reviewer 1 refers to as the ‘background’. In this respect, our main findings are the following:1) Contrary to expectations, the global functionality of the pools exceeds what would be expected by extrapolation from SELEX-type experiments by orders of magnitude .2) RNA pools in particular show an unprecedented innate and spontaneous propensity for recombination. Recombination increases the compositional, structural and informational complexity of RNA pools (as we demonstrate) and hence their adaptive potential .3) Pools of other genetic polymers ) not found in nature are also capable of recombination, establishing (1) that RNA is not unique in this regard and (2) revealing key chemical and structural parameters required for spontaneous recombination .We would argue that all three of these are significant findings with the potential to fundamentally change our perspective on early evolution and indeed on the functional potential of diverse oligomer pools in both biology and chemistry, and as such are of broad interest. However, we do accept that our arguments were not presented in sufficient breadth. In the revised manuscript, we have endeavoured to set out our findings both more clearly for the general reader and discuss them more fully within the context of previous work and the fundamental importance of the observed processes such as recombination in biology.Please find below a more detailed examination of our main points:-10-10-13, see e.g. Bartel and Szostak, 1993; Wilson and Szostak, 1999 or Jiménez et al., 2013) depending on the study and functional criteria)). This is turn would suggest that such pools by themselves should be largely inert and that functional sequences would be impossible to discover in the absence of powerful selection methods involving i.e. efficient means for enrichment, replication and amplification. If true, this would clearly call into question one of the key conjectures about the origin of life, which posits a spontaneous emergence of function from random oligomer pools.I) in vitro selection experiments (SELEX etc.) have demonstrated repeatedly that diverse random sequence pools of RNA, DNA  oligomers comprise functional sequences including catalysts capable of RNA cleavage and ligation. We therefore may take it as a given that such functional sequences are present in those pools. However, various attempts at extrapolating the frequency of functional sequences all suggest that such functional sequences are extremely rare .12 unique sequences, there are 1012 x 1012 = 1024 potential binary interactions (larger than Avogadro’s number!).II) Another argument in favour of considering the importance of intrapool interaction networks in potentiating global pool functional potential is their truly vast potential combinatorial diversity. For example, within the eicosamer pools examined herein, which encode a potential diversity of 10Indeed, the data described in our manuscript indicates that such pools are far from inert but display a pervasive tendency (of between 2-10% of pool sequences) for disproportionation reactions through transesterification chemistry resulting in ligation and recombination reactions among pool members.III) As outlined above, our intent was never to “bypass” SELEX experiments but rather examine pools global functional potential. However, we accept that we may have given this impression inadvertently by our attempts to dissect the different RNA motifs contributing to pool functional potential in the case of RNA ligation via a 2’, 3’-cyclic phosphate intermediates. We now discuss these results more extensively and provide a more detailed breakdown of the different classes of reactive RNA molecules contributing to this result including an expanded Figure 2 and a new Figure 3 in the main text as suggested by the reviewer.My major criticism of this work is that you did not show that these sequences react at enhanced rates relative to the average polymer sequence.With regards to this specific point of reviewer 1, we would like to argue that we in fact did just that.Our argument runs as follows:1) The “average polymer sequence” is likely to be unreactive on the timescale examined , respectively 2%  of reactivity (depending on pre-activation)). Hence, all ligated or recombined random or semi-random sequence pools show enhanced reaction rates compared to the “average” sequence.2) Among these subsets of reactive sequences, we find that a majority of intermolecular ligation and recombination reactions proceed via a gapped helical intermediate , 3: 243 or Usher et al., 1976, Science, 192: 53). In these, intermolecular hybridization provides an internal template and ligation as well as recombination transesterification chemistry via a >p intermediate is accelerated by proximity due to mutual sequence complementarity at the ligation junction.To better illustrate point and the activity of these, we have now included data on four randomly picked sequence pairs as suggested by the reviewer. Of these, one pair (pair 1) is predicted to form a helical junction at the ligation site, whereas the other three sequence pairs (pairs 2-4) are predicted to form complexes but without a gapped duplex formation at the ligation junction. As expected, only pair 1 shows ligation under our experimental conditions (presumably ligation reaction promoted by proximity), while no ligation is observed for the other three pairs. This data is now shown in the new Figure 2—supplement 2.3) This naturally leads to the question if all reactions would proceed via a gapped duplex intermediate or if among reactive sequence pairs we could identify other, distinct RNA motifs that would also accelerate intermolecular ligation. Indeed, bioinformatics analysis of a subset of reactive pool sequences allowed us to identify putative secondary structure elements promoting ligation, two examples of which  we analysed in more detail. As we show, J4 clearly accelerates cleavage / ligation beyond the rate provided by simple sequence complementarity and could therefore be referred to as nascent catalytic motif. H4 accelerates the reaction compared to the vast bulk of the pool sequences. However, while it is somewhat slower than a comparable helical intermediate, it promotes formation of a canonical 3’-5’ linkage, which is disfavoured in the helical arrangement .We would therefore argue that we have not only shown that some sequences react with an enhanced rate compared to the average sequence/background rate but that among these, there are again specific motifs, which react with even higher rates and/or distinct regiochemistry. More motifs are very likely to exist but their frequency in the subpool of sequenced RNAs was too low to allow their unambiguous identification.In order to better illustrate the above arguments as suggested by the reviewer and outline this hierarchical analysis of RNA motifs involved in ligation, we have expanded this section of the manuscript including an expanded Figure 2 and a new Figure 3 in the main text.The clearest way to address this point would be to experimentally measure the ligation/recombination rates of randomly chosen variants from at least one of the evolved pools. Are the ligation/recombination rates of these sequences higher than those of arbitrary sequences or the unevolved starting pool? Figure 2As discussed above, there are potentially distinct levels of “background” reactivity. To better illustrate this point, we now specifically include analysis of two typical gapped duplexes as well as the two defined non-duplex RNA motifs identified by bioinformatic analysis. This data is now shown in the new Figure 2—supplement 2 and 6 and main text Figures 2 and 3.With regards to reconstruction of oligomer reactivities, we note that we can only recapitulate bimolecular reactivity. Any sequences ligated by a 3rd partner oligonucleotide (e.g. acting as a splint) or via more complicated interaction networks or trajectories cannot be reconstructed as the participating oligonucleotides do not form part of the product. Thus, our analysis likely underestimates the extent and diversity of reaction trajectories and reactive motifs as our method is unable to sample in “trans-ligases”. Furthermore, our analysis also excludes non-canonical intra- or intermolecular ligation trajectories that yield circles, lariats or branched products. The lack of reactivity among some randomly picked sequence pairs in Figure 2—supplement 2 should be viewed in this context. Nevertheless, we show that salient features of reactivity as well as individual motifs can be extracted by careful analysis of the data.Thus, our data unequivocally shows that random RNA sequence pools comprise a diverse range of functionalities both at the level of rare individual sequences (as was known before) and much more prominently at the systems-level / global pool level (which is a key result from the present work).2) I am aware of several studies  in which high-throughput sequencing was used to characterize pools after in vitro selection experiments. In these studies, sequenced pools contained multiple copies of some variants, and a key component of the analysis was to show that copy number was correlated with catalytic or binding activity. I could imagine analyzing your experiments in a similar way. Furthermore, showing that some sequences appear multiple times in the high-throughput sequencing reads would provide additional evidence that they have enhanced ligations/recombination rates. I suspect that your evolved pools contained too many sequences to perform this type of analysis, but these issues should be at least briefly discussed.We are of course aware of the work of Pitt and Ferré-D'Amaré, 2010 and Jiménez et al., 2013 but these studies differ from our work in that they sought to correlate the activity-sequence relationships in either a repertoire of mutants of a known small ribozyme motifs or in a population of selected anti-GTP aptamers. Thus, both of these studies sought to map fitness peaks centred around discrete sequences either identified previously or known to occur at high frequency upon selection in the pool examined.In contrast, our work is aimed at a better understanding not of individual fitness peaks for a given activity but rather the global pool reactivity and potential for function  as it arises from systems-level interaction networks within the pools.While we have also mapped reactivity to individual motifs, we did so as a means to better understand the underlying pool reactivity, not to map out fitness peaks.15 sequence pools, the maximum available sequencing depth (109) is insufficient to capture or map sequence enrichment without multiple rounds of selection. Taking this into account, we would therefore argue that the level of reactivity and identification of individual functional sequence pairs in our experiments is striking and unprecedented given the rarity of such sequences observed in previous selection experiments.With regard to sequencing coverage, reviewer 1 is indeed correct that, although there is ca. 1000-fold redundancy of 20-mer sequences in our 10The latter is due to the fact that standard SELEX experiments are designed, to iteratively deplete and disrupt the interaction networks underlying global pool reactivity and instead isolate the exceedingly rate unitary sequences capable of function. While such experiments have been ground-breaking in revealing the potential of RNA (as well as DNA and various XNA) sequences for complex catalytic or ligand-binding functions, our results show that back-extrapolation of their frequency leads to a gross underestimation of pool functionality as only single sequences are considered.Without wishing to overstretch the analogy, our results in many ways parallel similar findings in related fields such as chemistry, where increasingly systems-chemistry approaches are found to yield pathways to products believed to be impossible to obtain by conventional linear synthetic approaches.In conclusion, in this manuscript we map for the first the time the innate, global functional potential of oligomer pools ab initio. Rather than seeking to isolate the “winners” in an evolutionary experiment (“race”) through cycles of selection, enrichment and amplification, we seek an overview of the potential of all “starters”, i.e. all pool sequences. We have now expanded the discussion of these points to set our work (and its motivation and conclusions) much clearer apart from “conventional” SELEX-type experiments.3) It seems to me that a model of recombination in which a 5' hydroxyl group in one oligonucleotide attacks a phosphodiester bond in the other is simpler than the one proposed here (in which recombination requires both self-cleavage and ligation). I would recommend providing evidence from either experiments or the literature in support of your proposed mechanism.We welcome this insightful comment. Previous studies examining RNA ligation via 2’, 3’-cyclic phosphate activation (>p) on an instructing template  suggested a 2-step mechanism (whereby a first step generates RNA oligomers terminating in >p by hydrolysis). Our own experiments  of RNA ligation in >p activated random eicosamer pools provides a baseline for reactivity via this chemistry in a random pool setting.Our observation that recombination reactions in the same pools lacking >p proceeds on a ca. 10-fold slower timescale suggests that either a direct attack mechanism is kinetically slower or that recombination predominantly proceeds via a 2-step mechanism involving (1) (a slow step of) RNA hydrolysis generating >p and (2) ligation via >p. This has been our rationale for favouring this mechanistic trajectory over a direct in-line attack.Nevertheless, reviewer 1 is of course correct that both mechanisms are likely to occur and indeed may be operating concurrently. In the light of this, we have amended the text to make this clear and now discuss both reaction trajectories in the context of ours as well as published findings.4) RNA secondary structure can only be predicted to a limited extent. For this reason, I am not convinced that the ligation junctions of these sequences typically occur in the context of duplexes. Can you demonstrate this experimentally? Furthermore, I am not aware of reliable methods to predict RNA tertiary structure. For this reason (and because it is does not change any of the main conclusions of the paper) I would remove the statement on page 5 that J4 forms a purine-rich 4x4 internal loop with a triple-shared GA motif.This is an important comment, but our arguments do not rely on accurate RNA tertiary (or even secondary) structure prediction.We very much agree with the referee that exact topologies of RNA secondary structures (that ultimately determine the tertiary structure) are poorly predicted by most software packages ). Physics-based free energy minimization approach of RNA secondary structure prediction has been evaluated in detail and found to have a base-pairing consistency of 70% between native and predicted secondary structures for moderately long RNAs .However, for our raw analyses only the accuracy of the base-pairing matters  while “average” tertiary structures are not (and cannot) be analysed using this method. Furthermore, our finding that >p ligation is favoured at helical junctions is not only in full agreement with the literature , but we have provide experimental verification in individual examples in this manuscript  suggesting that at the level of the comparatively short RNA oligomers examined herein, predictions are largely trustworthy.Deinococcus radiodurans (PDB ID: 2ZJR) / Escherichia coli adenosylcobalamin riboswitch (PDB ID: 4GMA)). These structures provide a rationale as to why and how J4 may promote ligation via a 2’, 5’ linkage . Thus, our statement is backed up by multiple lines of structural evidence and we have therefore not altered it in the revised manuscript. Nevertheless, we now provide more context and discussion on the structural folds of J4 and the other RNA motifs to present our arguments more clearly including main text Figure 2, Figure 3 and Figure 2—figure supplement 3, Figure 2—figure supplement, Figure 2—figure supplement 3, Figure 2—figure supplement 4, Figure 2—figure supplement 5 and – Figure 2—figure supplement 6.Finally, we note that our suggestion that the J4 motif folds into a 4x4-loop with a triple-sheared GA motif derives not from bioinformatic predictions, but from the fact that J4-like sequence motifs are found in several natural RNAs, for some of which high-resolution structural information is available (23S rRNA of 5) For me, one of the most exciting and interesting parts of the manuscript was your analysis of the reactivity of polymers other than RNA and DNA. However, the way in which the results were presented was not logical to me. I would recommend first comparing the ability of each of these polymers to promote ligation/recombination reactions under the same conditions, and then discuss new types of experiments (such as treating with base prior to incubation).We welcome this comment and agree that the differential reactivity of chemically closely related but distinct genetic polymers are a key finding.2+), where we only observed reactivity with RNA pools . We subsequently introduced modified conditions in order to expedite reactivity in the inert pools e.g. addition of Zn2+ in the case of DNA and ANA pools, which had previously been shown to be an essential cofactor in autocatalytic cleavage by small DNA motifs . However, we found that even in the presence of Zn2+, we observed no reactivity in the DNA (or ANA) pools. These negative results are now provided in Figure 6—figure supplement 1.As suggested by reviewer 1, we had originally compared all genetic polymers under the same conditions  in response to alkaline pH , we tested RNA, HNA and AtNA pool reactivity following a pulse of NaOH . Indeed, this revealed that AtNA, like RNA- is able to recombine, although reactivity was noticeably weaker (ca. 10-20-fold). In contrast, we did not observe recombination of AtNA (and HNA) in absence of NaOH. We had previously not included these negative results but now the data is presented in the new Figure 6—figure supplement 5. A direct comparison of the observed recombination yields between RNA and AtNA is also complicated by the fact that observed yields depend on the efficacy of the respective reverse transcriptase, the sensitivity of which undoubtedly better for RNA. We have now expanded the discussion of the above results in the revised manuscript to better outline the rationale for our different experimental strategies.Reviewer #2:Mutschler et al., have investigated spontaneous cleavage and ligation reactions among a diverse population of RNA  molecules. These reactions are well known, and the ability of a complementary template to accelerate the rate of ligation was first described over 40 years ago. Although these reactions have previously been carried out with mixed populations, this is the first study, to my knowledge, to apply deep sequencing to assess sequence preferences, especially for ligation. Not surprisingly, the authors find that there are some sequence preferences, which reflect a combination of intrinsic chemical reactivity and the potential for templated interactions. The reasons for the former are obscure, whereas the latter are due to both canonical and non-canonical templating effects. It is not surprising that DNA, ANA (arabino nucleic acid), and HNA (hexitol nucleic acid), all of which lack a vicinal cis-hydroxyl, do not undergo these reactions, whereas AtNA , which contains a vicinal cis-hydroxyl, does.1) This is a well-executed study that will be of interest to nucleic acid chemists, but will not have broader appeal, as would be required for publication in eLife.We would like to respectfully disagree with this assertion of reviewer 2. Recombination, the exchange of information between different genetic polymer strands, is of fundamental importance in biology  both for genetic diversification in the germline (meiosis) and soma (e.g. gene conversion in avian antibody generation) as well as genome maintenance and repair. It is furthermore of critical importance to guard against the progressive corruption of genetic information by the deleterious effects of genetic drift (i.e. Muller’s ratchet), enabling elimination of neutral or weakly deleterious mutations by backcrossing ).RNA recombination is widespread among RNA viruses . While generally attributed to template switching etc. recombination by inferred purely chemical processes has been observed in various viruses such as Poliovirus , rubella virus  or Qbeta bacteriophage , pointing to the possibility of a wider importance of non-enzymatic RNA recombination in present day biology with implications for non-viral transcriptome complexity and fluidity.We would therefore argue that our finding that RNA – due to its specific chemical constitution- has an innate capacity and tendency to recombine even in the absence of recombinase enzyme or extraneous activating chemistry has important implications both for origins research as well as indeed the analysis of all diverse RNA oligomer assemblies.In the context of primordial RNA pools, this innate capacity has fundamental implications as it provides for a progressive disproportionation of RNA sequences, which does increase pool complexity by the de novo generation of diversity of RNA oligomer length and sequence content and secondary structure driven by intrapool RNA base pairing networks .The potential for spontaneous recombination is likely innate to any diverse assembly of RNA sequences (including those found in biology) and should be considered when analysing such assemblies and their dynamics including studies of the transcriptome and viral populations and quasi-species.2) The conclusions are generally well supported by the data. However, it is somewhat misleading to point to the "increase in the compositional and structural complexity of recombined pools" while ignoring the decrease in oligomer length that occurs due to the same reactions. If one considers only the ligated products, then those materials can be said to have increased complexity. But for the assembly of materials that involve both cleavage and ligation events , one must also consider the many shorter cleavage products that arise. It is not clear from this study how the reactions could achieve an overall increase in compositional complexity.We welcome this insightful comment by reviewer 2 and agree that our claims of increased compositional and informational diversity/complexity need to be supported by a more comprehensive analysis of the impact of recombination on pool complexity.1) We would like to point out that while notions of spontaneous generation of increased informational and compositional complexity by RNA pools may seem counterintuitive, they are in fact both predicted and supported by theoretical arguments from statistical mechanics and thermodynamics, which suggest that under the right boundary conditions an increase in length and informational complexity of (RNA) polymer chains is favoured by entropic factors . We now outline these arguments as part of an expanded Discussion section in the revised manuscript.15- member eicosamer pools analysed herein are redundant with respect to encoded information, covering the total combinatorial diversity (420 =1.09 x 1012) ca. 1000-fold (i.e. there are approx. 900 copies of each eicosamer sequence within the pool).2) We now provide in silico simulations and analysis of the population level Shannon entropy ) of pre- and post-recombination pools. These calculations consider total pool informational content, under conditions of random oligomer cleavage and ligation and show that such recombination indeed increases the pool informational diversity under almost any boundary condition, provided that recombination is applied to a pool with significant sequence redundancy. Indeed, this applies to our experimental system: the 10Our finding that recombination diversifying parts of a redundant sequence pool generates new information is also intuitively understandable, as recombination of part of a redundant pool generates new sequences (both in length distribution and information content), while maintaining (i.e. not destroying) the previous sequence and information content (as redundancy persists but is reduced). In other words, sequence / compositional / informational complexity is increased at the expense of redundancy.Other outcomes of our calculations may be less obvious but no less interesting. These include the finding that the informational gains through recombination scale both with sequence code complexity (4 letter code > 2 letter code) and oligomer length as Recombination of longer oligomer pools generates more diversity. The simulations illustrate the trade-offs between enhanced cleavage rates, which generate more short fragments (loss of information) but also generate more ligatable fragments (and thus enable information gains) and ligation rates, which fix informational gains.In addition to detailed calculations, we now also provide an extended discussion of these points in our revised manuscript including a new Figure 7 and accompanying figure supplements.3) It is not clear from this study how the reactions could achieve an overall increase in compositional complexity. Presumably this would require a fractionation process or means to shift the chemical equilibrium in favor of ligation. The present study would be more suitable for a specialized journal such as Nucleic Acids Research or Angewandte Chemie.Reviewer 2 points out an important aspect of our study. While the above (see point 2) simply examines the generation of diversity as a theoretical concept of informational complexity in the context of early evolution, the impact of recombination on sequence pools under fractionation and / or adaptive pressure is more significant and more relevant to real world scenarios.Indeed, there are a number of physicochemical processes  surfaces etc.), which would favour length-extended oligomers over pool members or short cleavage products . However, the simplest fractionation process that favours more diverse and length extended oligomer sequences is selection for (higher order) function.Previous studies had established the importance of pool diversity as well as increased oligomer length not only for the discovery of functional motifs but, more importantly, for the discovery of the most active or complex functional motifs , even in the presence of trade-off from an increased tendency for ambiguous folding of longer RNA oligomers . Furthermore, the power of continued recombination of sequence pools under selective pressure to accelerate adaptive walks and evolutionary optimization is clearly demonstrated both by examples from biology ) and protein engineering .Therefore, we would argue that this all leads to an inescapable conclusion, which is that the innate potential of RNA oligomer pools for recombination provides a route unique to RNA  to bootstrap themselves towards higher informational, compositional and structural diversity and hence evolutionary potential.Given the challenges of prebiotic chemistry to generate oligomer pools of substantial length  the innate potential of such pools to extend themselves in length and diversity by recombination is highly significant. In light of theoretical arguments, which suggest a sharp drop in the potential for folding into stable secondary (and by inference tertiary) structures needed for function below a certain oligomer length limit , recombination might have been of fundamental importance for the emergence of the first functional RNAs.Furthermore, in the presence of a fractionation process selecting for increased oligomer length (e.g. thermophoresis (see above)) or a given function , RNA pools capable of recombination would yield a continuous supply of extended, more structured and more functional motifs and thereby outcompeting putative rival genetic polymers (such as DNA) unable to recombine. Such process would be potentiated by an ongoing process of recombination during selection  as recombination has previously been shown to be a powerful means to accelerate adaptive walks (see above).Finally, having established the potentially profound importance of recombination for the emergence of function from oligomer pools, our work begins to define key chemical parameters required for the display of an innate potential for recombination. Among these, a vicinal diol geometry on the ring appears to be crucial enabling formation of a cyclic phosphate upon hydrolysis, which supports subsequent ligation.Reviewer #3:[…] The ligated junctions for RNA seem to favor a G on the downstream of the ligation site. The RNA ligation site is thus biased, though not completely, towards a C/G sequence, not just CN. The authors use the unligated pool as a control; however, sequencing of unligated prey sequences is strongly biased by the method of introducing sequencing primers on the 5′ end (which depends on cross-templating by the RT enzyme and the SMARTER oligo substrate), so the statistics of the ligated vs unligated nucleotide at the 3′ side of the junction are not reliable. I understand the authors are being careful with their interpretation of the data, but the biases of the trans-templating method are known and can therefore be incorporated into the analysis, at least at the level of discussion if not directly in the Results section.We welcome this perceptive comment.The bias of trans-templating is of course real and similar issues exist in other library preparation methods for diverse nucleic acid pools. However, we have several lines of evidence that the CpN dinucleotide signature is a direct result of the transesterification reaction. These are detailed below:1) We prepared ligated and recombined RNA pool fractions using a range of different methods  but observed the CpN bias regardless. Even the N20 x N20A10 products produced by polyT-primed SMARTer RT-PCR , which we do not compare to preligation material show a raw C-bias at the NpN recombination site in products ≤ 50 nts . Here, the random nucleotide at the position of the recombination event was never exposed to terminal adapter ligation or template switching.20>p and C1/C3-bait>p semi-random RNA  were prepared by dephosphorylation of the >p followed by adapter ligation of a preadenylated oligonucleotide and not by SMARTer RT-PCR. While this protocol is also prone to sequence biases at the 3’-end (and close to it), due to sequence preferences of the ligase, the reference pools used in Figure 1-supplement 1 are unbiased further upstream of the adapter-ligated 3’-end, where the comparison happens and where we observe the same CpN signature in all recombination reactions. Furthermore, even without taking the pre-ligation material as reference, , a raw C-bias is directly visible in all recombination products shown in the colour plot in Figure 4D, Figure 5C and the supplementary movie, where the C-bias follows the recombination “seam” of the differently sized products independently from the library preparation method.2) The reference pools of unligated N20>p experiments, this bias is not observed in all cases  and we have therefore not elaborated on it.Thus, the overall ligation junction sequence bias / motif CpN was apparent throughout all RNA recombination experiments with some (minor) variations as detailed in Figure 1, Figure 4, Figure 5 and Figure 1—figure supplement 1. While referee 3 is correct at noting the bias for a downstream G (CpG) in the NFigure 4B is key for the conclusions of this manuscript, but the bands for HNA are practically invisible and for AtNA the -80 control is very poorly visible. When intensified, both HNA and AtNA show bands corresponding to longer products. Ditto for DNA and ANA lanes in Figure 4—figure supplement 1, where little to nothing is visible in either the experiment or the control lanes. These gels should be presented intensified as in Figure 3A. Related to this point, why are the -80 °C controls in Figure 4 invisible in the first place?oC & -80 oC), AtNA (-80 °C), DNA (both -9 oC & -80 oC) and ANA (both -9 °C & -80 °C) are practically invisible. Indeed, these reactions are what we consider negative  were detected (in contrast with clear amplification products of RNA (-9 oC) and AtNA (-9 oC)).The reviewer is correct that bands for HNA  recombination / ligation activity in e.g. the DNA, ANA or HNA pools for a number of reasons:oC) and can therefore not be the consequence of a reaction occurring during the incubation period.The appearance of weak amplification products is a common occurrence in all PCR reactions, where (spurious) bands will eventually appear after sufficient PCR cycles, as even minute amounts of mispriming or cross-contamination are exponentially amplified. The problem is greatly increased in PCR amplifications from random (or semi-random) sequence pools due to the increased likelihood of mispriming events on the random sequence segments. Furthermore, the weak bands pointed out by the referee occur to the same extent in both the -9 °C samples (incubated for prolonged periods) and -80 °C negative controls (which were immediately deep frozen at -80bona fide recombination products in both RNA (and AtNA) (when incubated at -9 oC) is enhanced by NaOH (as would be expected).The typical low-molecular weight band seen in the -80 °C negative control reactions (likely due to mispriming of the RT-primer on the random sequence part of the bait fragment) is reduced or absent in Figure 6B , due a) to the pre-incubation NaOH treatment, which leads to fragmentation of semi-randomers (in the case of RNA and AtNA) and b) a lower sensitivity of the RT enzyme for HNA and AtNA. Both a) and b) cause less opportunity for spurious background mispriming of the RT primer in the experiment shown in Figure 6B. At the same time, the intensity of the We therefore stand by our previous conclusion that only RNA (and to a lesser extent AtNA) pools have an innate potential for ligation and recombination while this capacity is either absent or negligible in DNA, ANA and HNA pools.2≈1012. Are these libraries exhaustive with respect to the potential diversity limit? Are there known biases in composition for the non-biological genetic polymers? The authors do not mention the amounts of material used, just concentrations. Clearly, sequencing of the entire starting pool (or even recombined and directly isolated ones) is not practical, but for the PCR-amplified pools, the sequencing results may be exhaustive. For that, however, an estimate of the starting diversity and the total amplification of the recombined products would have to be presented. The manuscript would be enhanced if these numbers were included for all experiments and pools, particularly for the RT-PCR-amplified pools, where the HTS results may represent nearly all ligated sequences.What are the diversities of libraries used? The theoretical limit of a 20-mer is 4We thank reviewer 3 for this insightful comment and apologize for having omitted a fuller discussion of the diversities explored, which we now provide in the revised manuscript.14-1015 molecules), there is considerable redundancy within these pools (diversity 420 = 1.09 x 1012). Although we are unable to completely capture this within the current limits of NGS sequencing (ca. 109 reads), we can infer whole pool diversity from the degree of randomness of the partially sequenced pool.We chose eicosamer pools because, within the repertoire sizes explored within our experiments (1014 sequences) resp. 2% or 0.2%  of pool sequences ligated / recombined, NGS cannot provide full coverage. We are therefore, in all cases, observing a representative sample. Within that sample we can exploit similarities and redundancy such as is present in structural classes of RNA motifs. We leverage this in the bioinformatic RNA motif classification analysis we present  and show that it enables us to identify reactive motifs.Even within reacted pools where we observe 10% , XNA pools  need to be obtained by enzymatic synthesis using bespoke engineered polymerases, as solid phase synthesis is not available. While enzymatic synthesis is efficient on random DNA templates, inevitable biases are introduced, which reduce the diversity of XNA pools compared to DNA and RNA pools. Nevertheless, this is unlikely to significantly impact pool reactivity, given the considerable redundancy within eicosamer pools.The free energy of activation of a >p vs a triphosphate is known. Assuming similar activation energy for the ligation of a 5′-OH with >p and a triphosphate, the expected kinetics for the background reaction can be estimated from the Rohatgi and Szostak, 1996 paper. An estimate of the background ligation rate and acceleration by the individual motifs should be presented.2+ (which are absent in the majority of our reactions). Furthermore, in triphosphate-based ligations, the diphosphate leaving group renders the ligation reaction quasi-irreversible (kobs = kligation). In contrast, >p-dependent ligation is reversible due to the absence of a leaving group (kobs = kligation + kcleavage) and the  almost isoenergetic reaction equilibrium.We welcome this perceptive comment. However, we would like to refrain from using triphosphate dependent ligation as a reference as the activation energy is critically dependent on the presence and concentration of divalent metal ions like MgFinally, it is challenging to extrapolate triphosphate-dependent ligation rates determined under ambient in-solution conditions to reactions taking place at much lower temperatures in eutectic in-ice conditions.obs) for motif J4 and H4 to the kobs of three template / splinted ligation reactions (which may be considered the background ligation rate occurring in a gapped duplex) and summarize this data in the new Figure 2—figure supplement 6.In order to provide a (better) estimate of the rate acceleration, we now compare the apparent reaction rates (k


Escherichia coli Oligoribonuclease (ORN), suggesting that it plays a role in RNA turnover in mitochondria. However, how Rexo2 preferentially binds and degrades nanoRNA remains elusive. Here, we show that Rexo2 binds small RNA and DNA oligonucleotides with the highest affinity, and it is most robust in degrading small nanoRNA into mononucleotides in the presence of magnesium ions. We further determined three crystal structures of Rexo2 in complex with single-stranded RNA or DNA at resolutions of 1.8–2.2 Å. Rexo2 forms a homodimer and interacts mainly with the last two 3′-end nucleobases of substrates by hydrophobic and π−π stacking interactions via Leu53, Trp96, and Tyr164, signifying its preference in binding and degrading short oligonucleotides without sequence specificity. Crystal structure of Rexo2 is highly similar to that of the RNA-degrading enzyme ORN, revealing a two-magnesium-ion-dependent hydrolysis mechanism. This study thus provides the molecular basis for human Rexo2, showing how it binds and degrades nanoRNA into nucleoside monophosphates and plays a crucial role in RNA salvage pathways in mammalian mitochondria.Human RNA exoribonuclease 2 (Rexo2) is an evolutionarily conserved 3′-to-5′ DEDDh-family exonuclease located primarily in mitochondria. Rexo2 degrades small RNA oligonucleotides of <5 nucleotides (nanoRNA) in a way similar to  RNA decay and surveillance play key roles in gene expression regulation and RNA quality control . In humaEscherichia coli Oligoribonuclease (ORN) and Saccharomyces cerevisiae YNT20 -guanosine (pGpG) into GMP to complete the final step in the degradation of cyclic-di-GMP, an important bacterial secondary messenger molecule in controlling biofilm formation and bacterial pathogenesis , Acinetobacter baumannii (PDB code: 5CY4), and Haemophilus influenzae (PDB code 1J9A). However, the molecular basis of how Rexo2 preferentially binds and degrades nanoRNAs remains elusive.Human Rexo2 not only shares high sequence identity but also similar enzymatic activity to bacterial ORN, as Rexo2 also preferentially degrades nanoRNAs of <5 nt . Rexo2 aecycling . Rexo2 iecycling . Depletiecycling . Togethempestris   in complex with single-stranded RNA or DNA in the presence of Mg2+ at resolutions of 1.8–2.2 Å. Rexo2 interacts primarily with the last 2 nt bases at the 3′ end of nucleic acid substrates via hydrophobic and π−π stacking interactions. Thus, our results provide the molecular basis for the preference of Rexo2 for degrading small oligonucleotides by a two-Mg2+-dependent hydrolysis mechanism in mitochondria.Here, we show that Rexo2 preferentially degrades nanoRNAs of 2–4 nt in the presence of MgE. coli. For RNA-binding and cocrystallization experiments, we expressed an additional two inactive Rexo2 mutants; Rexo2–D199A in which the metal ion-binding residue is replaced and Rexo2–H194A in which the general base residue is replaced. We subsequently removed the His-tag of recombinant Rexo2 proteins using Thrombin. Final purified Rexo2 proteins, containing only residues 33–223, were stable dimers with a molecular weight (MW) of ∼44 kDa  or 12-nt RNA (5′-32P-A12-3′) in the presence of 5 mM MgCl2. For comparison, we expressed and purified E. coli ORN according to a previously described procedure  with either 5′-end-rocedure , and incrocedure D. Rexo2 rocedure D. Rexo2 rocedure E. Rexo2 rocedure C–E. Thesrocedure .2+  and 12-nt DNA (5′-32P-T12-3′) in the presence of 5 mM MgCl2. We used a higher concentration of Rexo2 (2 μM) in this instance (relative to the RNase activity assay), as its DNA degradation activity is lower than that for RNA. Consistent with the earlier finding . We also noted that Rexo2 had almost no DNase activity in degrading single-stranded DNA of poly(A) or poly(G) in the presence of Mg2+ (data not shown). Compared to Rexo2, ORN (2 μM) exhibited lower DNase activity for degrading either 4-nt or 12-nt DNA .Human Rexo2 has been shown to degrade small DNA oligonucleotides in the presence of Mn2+ . To test finding , we founKd = 24.4 nM), whereas it bound the 5-nt and 12-nt RNAs with similar lower affinities  (Kd = 29.9 nM), whereas it bound a mid-length 5-nt DNA and a long 12-nt DNA with lower affinities  . Previous studies showed that Rexo2 binds RNA and DNA with a similar Km but degrades RNA with a higher catalysis rate over DNA  F–H. Thisover DNA . The app2+. We obtained three complex cocrystals, referred to as Rexo2–RNA (Rexo2–D199A bound with a 12-nt U12 RNA and Mg2+), Rexo2–DNA1 (wild-type Rexo2 bound with a 5-nt T5 DNA), and Rexo2-DNA2 (Rexo2–D199A bound with a 10-nt T10 DNA and Mg2+). The crystal structures of these three complexes were determined by molecular replacement using the crystal structure of E. coli ORN (PDBID: 2IGI) as the initial search model. Due to ill-defined electron density at the 5′ ends of RNA or DNA fragments, we only modeled partial 3′-end nucleotides in our complex structures: 2 nt (U–U) in the Rexo2–RNA complex, 2 nt (T–T) in the Rexo2–DNA1 complex, and seven (T7) nucleotides in the Reox2–DNA2 complex . Protomers A and B share a similar conformation with an average RMSD of 0.52 Å (for 123 Cα atoms) in Rexo2–RNA, 0.41 Å (for 116 Cα atoms) in Rexo2–DNA1 and 0.14 Å (for 107 Cα atoms) in Rexo2–DNA2. However, several regions in protomer A were disordered, including residues 51–59, 85–114, and 190–193, in the Rexo2–RNA structure. As a result, the RNA substrate was modeled only in the active site of protomer B, but not modeled in protomer A due to the ill-defined electron density. Similarly, in Rexo2–DNA1 and Rexo2–DNA2 complex structures, DNA substrates were bound only in the active site of protomer B but not observed in protomer A.Rexo2 formed a homodimer with two protomers (chain A and B) in all three complexes, with a dimeric assembly similar to that of ORN dimer A. The di2+ ions, even though one of the metal-binding residues, D199, was mutated to Ala in two of the complexes. In the Rexo2–RNA and Rexo2–DNA1 complexes, only the last two 3′-end nucleotides were observed, i.e., U–U in Rexo2–RNA and T–T in Rexo2–DNA1, with the remainder of the substrates being disordered. In contrast, 7 nt (T4–T10) were observed in Rexo2–DNA2 complex, with additional interactions of the phosphate backbone (P5) with side chains of Lys189 and Lys190, and π–π stacking interactions between T4 nucleobase and Phe186 . The electrostatic surface of Rexo2 reveals a basic surface extending from the active site within which lie the two lysine residues (Lys189 and Lys190), suggesting that Rexo2 also binds long oligonucleotides for degradation (The 3′ end of the RNA or DNA chain was bound in the DEDDh active site in one of the protomers (chain B) together with two Mgd Phe186 D. Due toradation B. HoweveA close look at the interactions between Rexo2 and RNA/DNA revealed that the two nucleobases of the 3′-end di-nucleotide are sandwiched between three hydrophobic/aromatic side-chains of Leu53, Trp96, and Tyr164 (protomer B) in all three complexes . The 3′-RNA-specific interactions are observed in the Rexo2–RNA complex, where the 2′-OH (O2′) of the ribose group of the 3′-end nucleotide forms a hydrogen bond with the Met50 backbone (O atom). This interaction likely facilitates product release for nucleoside monophosphates, so RNA is cleaved more efficiently than DNA. Moreover, the 3′-end OH group (O3′) forms a hydrogen bond with the Met50 backbone (NH atom) and Glu49 (Oδ) in all three complexes, providing the structural basis for the preference of Rexo2 for cleaving oligonucleoties with a 3′-OH end A–C. In sSupplemental Fig. S1) revealed that Rexo2 degrades RNA and DNA in the presence of Mg2+. Therefore, Rexo2 is a Mg2+-dependent enzyme under physiological conditions. In the Rexo2–RNA complex, we used the inactive D199A mutant for cocrystallization with RNA in the presence of Mg2+. D199 is one of the metal-ion binding residues in the DEDDh active site, but we still identified two Mg2+ ions in the active site, one bound to Glu49  and another bound to Asp47 and Asp147   bound in the active site, likely representing endogenous Mg2+ from the E. coli host strain . Four DEDD residues—Asp47, Asp147, Asp199, and Glu49—coordinate two Mg2+ ions, which are further bound to the 3′-end scissile phosphate. His194 functions as the general base to activate a water molecule; we did not observe this water in all three complexes, likely because we used a low pH of 5.1 in the crystallization conditions, so His194 was in a protonated state not suitable for serving as a general base. Presumably, this His194-associated water  A. In thet strain B. We proIn this study, for the first time, we reveal the structural basis of how Rexo2 preferentially binds and degrades nanoRNAs of <5 nt to recycle their nucleoside monophosphates. Our results are applicable to Rexo2 homologs across species  that share a high sequence identity, the same dimeric structure and similar enzymatic activities as Rexo2. Small nanoRNAs are bound by Rexo2 with a high affinity because Rexo2 primarily interacts with only the last two 3′-end nucleobases via hydrophobic and π−π stacking interactions. Consequently, Rexo2 preferentially degrades nanoRNAs without sequence specificity. Mitochondrial nucleases, such as PNPase, degrade large RNA molecules and produce small RNAs of <5 oligonucleotides. Rexo2 may further degrade these nanoRNAs into monoribonucleotides for RNA salvage . Rexo2 dSupplemental Fig. S2). We superimposed the Rexo2–RNA complex structure with those of two baterial homologs, ORN (PDBID: 2IGI) and RNase T-DNA complex (PDBID: 3NH1). Rexo2 has a high structural resemblance to ORN, with an average RMSD of 1.14 Å (for 319 Cα atoms), but a lower resemblance to RNase T (average RMSD of 7.64 Å for 319 Cα atoms). The three hydrophobic and aromatic residues in ORN  are located at positions matching those of Rexo2, suggesting that they also participate in base stacking interactions with RNA substrates  are strictly conserved, demonstrating their crucial roles in substrate binding  RIPL cells and incubated at 37°C overnight in LB media supplemented with 50 μg/mL Kanamycin. The cells were then transferred into 1 L of LB medium and grown until the OD600 reached 0.6. Rexo2 protein expression was induced at 18°C for 18 h by 0.8 mM IPTG. Cells were harvested and disrupted by Microfluidizer (Microfluidics M-110P) in buffer A containing 50 mM Tris–HCl pH 8.0, 1 M NaCl, 5 mM imidazole, 10 mM β-mercaptoethanol. Supernatants were applied to HisTrap HP columns  and the bound proteins were eluted using an imidazole gradient between buffer A and buffer B . The eluted protein fractions were collected and Thrombin (1 unit/mL) was added, and the mixture was dialyzed into a buffer  overnight to remove the amino-terminal His-tag. Recombinant proteins were loaded again into HisTrap HP columns , and the flow-through fractions were collected to recover His-tag-free Rexo2. The recombinant Rexo2 protein samples were concentrated and purified by Superdex 75 10/300 GL columns  in a running buffer of 20 mM Tris–HCl pH 7.5, 150 mM NaCl, and 2 mM DTT. The purified protein samples were stored at −20°C or concentrated to 20 mg/mL for crystallization.The gene encoding human Rexo2 (residues 33–223) without the mitochondria localization sequence (residues 1–25), amino-terminal tail (residues 26–32) and carboxy-terminal tail (residues 224–237) was amplified by PCR using PfuUltra II (Agilent Techonologies), and the PCR products were subcloned into the NdeI/SalI sites of the pET28a vector (Invitrogen) with an amino-terminal 6xHistidine tag added to the construct. Plasmids encoding the Rexo2–D199A and Rexo2–H194A mutants were generated using QuickChange site-directed mutagenesis kits (Stratagene) from the wild-type construct. All plasmids were transformed into 32P-labeled ssRNA (5′-32P-A4-3′ or 5′-32P- A12-3′) at 37°C for 0–60 min in a reaction buffer containing 50 mM Tris–HCl (pH 7.5), 50 mM NaCl, 1 mM DTT, and 5 mM MgCl2 in a final reaction volume of 10 µL. ORN from E. coli was used as a control, with final concentrations of ORN in the assays being 50 nM for RNA degradation and 2 µM for DNA degradation. The reactions were stopped by adding 2× urea loading dye (Thermo Fisher Scientific) at different time-points , and the samples were loaded on 7.5 M urea/20% (w/v) polyacrylamide denaturing electrophoresis gels. All control reactions were stopped at the 60 min time-point. RNA degradation patterns were exposed on a FujiFilm Image plate and detected by Typhoon FLA 9000 . The same procedures were also applied for DNA degradation assays, with the DNA substrate being 5′-end-32P-labeled ssDNA (5′-32P-T4 -3′ or 5′-32P- T12-3′).Wild-type Rexo2, Rexo2–D199A, or Rexo2–H194A  was incubated with 2.5 nM 5′-end-2-3′), 5-nt RNA (5′-Cy3-A5-3′) and 11-nt RNA (5′-Cy3-AGCGCAGUACC-3′)—were labeled at the 5′-hydroxyl end with Cyanine-3 (Dharmacon). These RNA substrates (10 nM) were titrated with the indicated concentrations of the Rexo2–H194A mutant in binding buffer . Rexo2 and RNA were incubated for 15 min at room temperature (25°C), and the fluorescence polarization signals were excited at 535 nm and read at 595 nm. The RNA-binding affinities of Rexo2 were calculated by fitting the binding curve to a one-site-binding Hill slope using the software GraphPad PRISM 7. For DNA-binding assays, 3-nt DNA (5′-Cy3-T3-3′), 5-nt DNA (5′-Cy3-T5-3′), and 12-nt DNA (5′-Cy3-T12-3′) substrates were labeled at the 5′-hydroxyl end with Cyanine-3 (MD Bio), and the same fluorescence polarization method as used for the RNA-binding assays was applied.The RNA binding affinity of Rexo2 was measured by assessing changes in fluorescence polarization signals using a Paradigm plate reader (Molecular Devices). The single-stranded RNA substrates—2-nt RNA (5′-Cy3-AE. coli ORN structure (PDBID: 2IGI) as the search model. The oligonucleotide structural model was built using Coot and the Rexo2-oligonucleotide structures were refined in Phenix.All three Rexo2-oligonucleotide complexes were crystallized by the hanging-drop vapor diffusion method at room temperature in similar conditions by mixing 1 µL of protein-oligonucleotide mixture (protein to oligonucleotide ratio of 1:1.2) with 1 µL of reservoir solution . X-ray diffraction data were collected at BL-15A1 beamline at the National Synchrotron Radiation Research Center (NSRRC), Hsinchu, Taiwan, and the collected data were processed and scaled by HKL2000. Rexo2 structures were determined using the AutoMR function in the program Phenix, using the Structural coordinates and diffraction structure factors of Rexo2–RNA, Rexo2–DNA1, and Rexo2–DNA2 have been deposited in the RCSB Protein Data Bank with the PDB ID codes 6J7Z, 6J7Y, and 6J80, respectively.Supplemental material is available for this article.


Aldo-keto reductase 1C3 (AKR1C3) is known for multiple functions including its catalytic activity towards producing extra-testicular androgen. The present study is towards understanding interaction between biological, lifestyle and genetic impacts of AKR1C3 and their influence on clinical factors in a prostate cancer (PC) cohort from New Zealand (NZ).AKR1C3 rs12529 single nucleotide polymorphism (SNP). The leukocyte AKR1C3 activity was measured in a sub-cohort. Variability of leukocyte AKR1C3 activity between biological, lifestyle and clinical features as well as correlation between biological and clinical features were assessed with and without genetic stratification.Characteristics of 516 PC patients were collected from the Auckland Regional Urology Facility, NZ. These men were genotyped for the AKR1C3 rs12529 CC genotype carriers . Significant correlation between leukocyte AKR1C3 activity and age at PC diagnosis was also observed (correlation coefficient 0.20 and P = 0.02). Ever- smoking impacted both age and PSA at PC diagnosis among AKR1C3 rs12529 GG and CG genotype carriers respectively. Age at diagnosis significantly correlated with PSA at diagnosis in the main  and sub-cohorts ; and those carrying the AKR1C3 rs12529 CG and GG genotypes in both the main  and sub-cohorts ; but not with those carrying the CC genotype.The leukocyte AKR1C3 activity was associated with age at diagnosis ; and with anatomic stage/prognostic grouping among the AKR1C3 rs12529 CG and GG genotypes in this NZ cohort.Age dependent PSA thresholds in PC screening could have been valid only in men carrying the  When stenotypes   and CG (correlation coefficient -0.33 and P = 0.01) genotypes . The AKR1C3 rs12529 CG genotype group of the sub-cohort showed a significant correlation between age and PSA at diagnosis (correlation coefficient 0.43 and P<0.01)  in the sub-cohort. This was not reproduced in the main cohort, although in the main cohort, age at diagnosis and Gleason sum showed a marginal correlation within the GG genotype group (correlation coefficient 0.21 and P = 0.05) (AKR1C3 rs12529 CC and CG genotypes (correlation coefficient 0.48 and P<0.01 and correlation coefficient 0.45 and P<0.01 respectively) in the sub- cohort .Increasing age was negatively correlated with BMI in the sub-cohort (correlation coefficient -0.30 and P<0.01) as well as when stratified by the enotypes . In the enotypes . Age at enotypes . No corr P<0.01) . The AKR P<0.01) . As in t = 0.05) . BMI and = 0.05) . PSA at - cohort . The cor- cohort . In addiAKR1C3 rs12529 genotypes, biological and clinical features in a PC cohort from Auckland, NZ. The leukocyte AKR1C3 activity was measured only in a sub-cohort. Due to the sub-cohort showing significantly higher age and PSA at PC diagnosis as well as a higher PC severity as shown by Gleason sum data, the former is not entirely representing the main cohort. The sub-cohort and those with the AKR1C3 rs12529 CC and CG genotypes within the sub-cohort showed a negative correlation of BMI with age at PC diagnosis, although this was not seen in the main cohort except for a marginal negative trend shown among those carrying the AKR1C3 rs12529 CC genotype in the main cohort. As age dependent BMI change is not directly relevant to the theme of this manuscript, it is considered towards the end of the discussion.This study presents an analysis of interaction between AKR1C3 activity, AKR1C3 rs12529 genotypes are similar to that of the European Americans and African Americans recorded before [AKR1C3 rs12529 G allele in our cohort was 0.463 which is marginally lower than the frequencies recorded in the Genome Aggregation Database (0.499); but similar to the Trans-Omics for Precision Medicine Database (0.476); and higher than the TWINSUK Database (0.385) and Avon Longitudinal Study of parents and Children Database from the University of Bristol (0.382) (https://www.ncbi.nlm.nih.gov/snp/rs12529). According to a study from Taiwan, the AKR1C3 rs12529 G was the major allele (G = 0.988) in an Asian cohort [The frequencies between the d before , 28. Then cohort .th and 75th percentiles at 0.21 and 0.73 respectively) and was approximately three times the level produced by the positive control LNCaP+ cell line .To our knowledge, this is the first recording of the AKR1C3 activity measurements made in leukocytes extracted from -80°C stored blood samples as well as in leukocytes from PC patients. When stratified by median age at PC diagnosis, men in ≥69y age group showed higher AKR1C3 activity compared to those at <69y. This is the first ever age based variation in leukocyte AKR1C3 activity recorded in men. However, when data were further stratified for the AKR1C3 rs12529 genotype, none of the genotypes showed significant variation of AKR1C3 activity based on this age stratification. In this sub-cohort, AKR1C3 activity in leukocytes showed no variability with lifestyle factors . The AKR1C3 promoter constructs of the HepG2 cells have previously shown that the promoter activity of this gene is associated with promoter SNP rs3763676 [AKR1C3 rs12529 SNP.The median AKR1C3 activity measured in leukocytes was 0.41μM coumberol per million cells . It is a possibility that with increasing age, men with the AKR1C3 rs12529 GG genotype have a potential to produce higher AKR1C3 activity compared to those with other genotypes, and subsequently support a higher proportion of extra-testicular androgen production that increases the androgen pool.Those with anatomic stage/prognostic group <IIB showed a higher AKR1C3 activity compared to those with ≥IIB group, when data were stratified by the d before . It has d before . In the d before . HoweverAKR1C3 rs12529 GG genotype which shows a prominent increase in age at diagnosis among ever-smokers compared to never- smokers. In the main cohort, PSA at diagnosis was not significantly different between ever- and never-smokers. However, when stratified by genotypes it was only the AKR1C3 rs12529 CG genotype that showed a significantly higher PSA at diagnosis among ever-smokers compared to never-smokers. Involvement of AKR1C3 in metabolizing polycyclic aromatic hydrocarbons (PAH) leading to the formation of pro-reactive oxygen species such as catechols and quinones have been documented [AKR1C3 rs12529 GG genotype was more susceptible to lung cancer risk in those exposed to smoke derived from coal burning [et al 2018 [et al 2008 [AKR1C3 rs12529 G allele when compared to similar cohorts from the US [AKR1C3 rs12529 G allele for screen detected PC due to their lower PSA levels is a possibility with a subsequent delayed diagnosis with high-risk PC. Those carrying the AKR1C3 rs12529 CG genotype getting diagnosed at a higher PSA level especially among ever-smokers as reported here could also be due to these men not getting captured earlier with low risk PC at a lower PSA level. For those carrying the AKR1C3 rs12529 G allele and are ever-smokers, their AKR1C3 activity may not be able to catalyse the production of extra-testicular androgens at the same rate as their never-smoker counterparts and those with the CC genotype and are ever-smokers.In the main cohort ever-smokers showed a marginally significant increase in age at diagnosis compared to never-smokers. When this feature was stratified by genotypes, it is the cumented –34. Mean burning .Tobacco  burning . Impacts al 2018 . The aut al 2008  have evaAKR1C3 rs12529 CG and GG genotypes and not the CC genotype. It is a possibility that for at least the AKR1C3 rs12529 GG genotype carriers, this may be related to their potential to produce higher levels of AKR1C3 activity with age. This can be also interpreted as those with the AKR1C3 rs12529 G alleles could have significant PCs that go undetected at lower ages due to lower PSA levels. It has been shown that physiological levels of DHT (10nm) treatment in LNCaP PC cell line, causes a 70% reduction in AKR1C3 activity [AKR1C3 rs12529 CG and GG genotypes, general reduction in androgen around 65-75y [In both the sub- and main cohort, the age at diagnosis significantly correlated with the PSA at diagnosis. However, it was shown to be relevant only to those with the activity  that cand 65-75y , 41 promd 65-75y . NZ has d 65-75y , 43. Addd 65-75y , meaningd 65-75y  and thatd 65-75y .AKR1C3 rs12529 CC and CG genotypes. This was also the same with the GG genotype group in the main cohort. A similar PSA at diagnosis and Gleason sum correlation has been reported by Yarney et al 2013 for an African cohort with a mean age at presentation at 65.4y [et al 2006 have reported PSA level as a predictive factor for high-grade disease (Gleason score ≥ 7) [In both the sub- and main cohorts, PSA at diagnosis and the Gleason sum correlated significantly including when stratified by the at 65.4y . Thompsoore ≥ 7) . A studyore ≥ 7) . Althouget al 2008 [et al [BMI increases from young age to middle age due to increasing fat mass and subsequent decrease from middle to old age due to decrease in lean mass are well known –52. Ther al 2008  have mon8 [et al  study ha8 [et al . Age-rel8 [et al . Bone mi8 [et al , 57. How8 [et al , 59. TheAKR1C3 rs12529 CG and GG genotypes. This means for those men carrying the AKR1C3 rs12529 CC genotype (which is 32% of our cohort), an age based PSA increase is not a valid concept. Age dependant PSA correlation was stronger in the sub-cohort that recorded more severe disease. When this sub-cohort was stratified, it was only the AKR1C3 rs12529 CG  and the GG  genotypes that showed correlation between age and PSA at diagnosis. In this sub-cohort and the AKR1C3 rs12529 CG genotype of this sub-cohort, as well as the GG genotype of the main cohort, age dependant correlation of Gleason sum was also significant. It is a possibility that with increasing age, men carrying the AKR1C3 rs12529 G allele has an increasing potential to produce more AKR1C3 activity, thereby adding a higher proportion of adrenal derived extra-testicular androgen to the androgen pool. Such increases could be the reason behind age dependant PSA increases seen in the AKR1C3 rs12529 G allele carriers. The AKR1C3 rs12529 G allele is the major allele in Asian, Maori and Pacific men in our cohort [AKR1C3 rs12529 G allele. Among the draw backs in our study are the small sample size used for the leukocyte AKR1C3 measurement; pooling all types of ADT based management options under one category in our assessment and non-availability of TNM staging for 36% and 23% respectively for the main and sub-cohorts. It is possible with a significantly larger sample size, with better patient stratification, a better assessment between genotype based leukocyte AKR1C3 activities can be confirmed and compared against biological, lifestyle and clinical features and pave way for a more stringent genetically stratified PSA-based PC screening.Although PSA was considered as the gold standard for screening for PC, it has reached a controversial status since 2008 , 61. Thir cohort . TherefoS1 Table(Details provided as a requirement of the Standard Strengthening the Reporting of Genetic Association Studies (STREGA)–An Extension of the STROBE Statement.).(DOCX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.