GABRA4 and CHIC1 RNAs to study intramolecular interactions between the repeat tracts that they contain. In vitro secondary structure probing results showed that the UAA and UUG repeat tracts, present in GABRA4 3′ UTR, form a double helix, which separates one of its structural domains. For the RNA CHIC1 ORF fragment containing four short AGG repeat tracts and the CGU tract, we proved the formation of quadruplexes that blocked reverse transcription.Among types of trinucleotide repeats, there is some disproportion in the frequency of their occurrence in the human exome. This research presents new data describing the folding and thermodynamic stability of short, tandem RNA repeats of 23 types, focusing on the rare, yet poorly analyzed ones. UV-melting experiments included the presence of PEG or potassium and magnesium ions to determine their effect on the stability of RNA repeats structures. Rare repeats predominantly stayed single-stranded but had the potential for base pairing with other partially complementary repeat tracts. A coexistence of suitably complementary repeat types in a single RNA creates opportunities for interaction in the context of the secondary structure of RNA. We searched the human transcriptome for model RNAs in which different, particularly rare trinucleotide repeats coexist and selected the  The RNA structure determines the activity of transcripts and their interactions with other molecules in cells. The presence and role of short repeat sequences in RNA are puzzling in the context of the structure of the transcripts. RNA repeats are derived from microsatellite sequences, also known as short tandem repeats (STR). They contain motifs of 1–10 nucleotides in length that repeat 5–50 times ,3,4,5. SIn 2013, the Weeks group demonstrated intramolecular pairing of RNA regions rich in CAG and CCG repeats for the first exon of the huntingtin transcript, proving the highly structured character of this RNA fragment . In the GABRA4  and CHIC1 (cysteine-rich hydrophobic domain protein 1), containing tandem repeats that may potentially interact. In both cases, we performed an attempt at secondary structure chemical mapping to determine the relationship between the present repeats and their effect on the secondary structure of the RNA molecule.Our research goal was to determine the folding and thermodynamic stability of pairing of various, predominantly rare RNA repeat types. We found that repeats which do not fold in secondary structure by themselves can pair with another similar type of repeat. Based on the analysis of the coexistence of rare repeats in a single transcript, we chose fragments of two RNAs: Characteristic sequences, such as repeated motifs, may play a special role in the context of RNA secondary and tertiary structure. We analyzed 23 types of RNA repeats by determining their preferred secondary structure, as well as their potential for forming structural motifs with other RNA repeats. For the thermodynamic studies, model oligonucleotides were used, containing three repeats and respective terminal base-pairs. For selected repeats, oligonucleotides containing six RNA repeats were also analyzed. The UV-melting experiments included the following RNA repeats: CAA, CGA, GCU, CGU, GCC, GCG, GCA, AGG, UGG, UAG, UAA, CAU, CUA, CUU, CCU, CCA, UUA, AUG, GAA, UUG, AAG, CCUG, and AUUCU. Collected thermodynamic results  indicate37) of 4.22, 5.29, 5.84, and 7.29 kcal/mol, respectively. The observed destabilizing effect of a single mismatch increased in the following order: G-G, U-U, C-C, and A-A, which is consistent with previous reports [37) of 4.27 and 8.65 kcal/mol, respectively.Duplexes were formed by eight types of repeats: CAA, CGA, GCU, CGU, GCA, GCC, GCG, and CCUG . Oligonu reports . The CAAThe oligonucleotides containing three consecutive AGG or UGG repeats formed quadruplexes with thermodynamic stability equal to −2.95 and −3.18 kcal/mol, respectively. For the remaining types of RNA repeats, UV-melting curves do not show transitions, which demonstrates the single-stranded character of melting. This large group of RNA repeats, that do not form any structure, includes UAG, UAA, CAU, CUA, CUU, CCU, CCA, UUA, AUG, GAA, UUG, AAG, and AUUCU repeats. However, for some of those repeats (CCA and UAG), a kind of very low Tm transition was observed. Detailed thermodynamic parameters of the analyzed RNA repeats are collected in 37) were 1.10, 2.14, and 0.61 kcal/mol, respectively. Conversely to the information listed above, an oligonucleotide containing six CGU repeats results in the simultaneous formation of duplex and hairpin structures with free energy equal to −9.46 and −1.50 kcal/mol, respectively.Increasing the number of repeats in the case of certain GC-rich RNA oligonucleotides promotes their folding into hairpins. A thermodynamic study of oligonucleotides containing six GCU or GCC repeats indicated the formation of a mixture of two hairpins in each case. The free energy of those hairpins was −1.87 and −3.27 (for GCU) or −2.60 and −3.03 kcal/mol (for GCC). The formation of various hairpins structure by oligonucleotides containing six CNG repeats was reported earlier ,14. OftePreviously it was shown that RNA composed of 5–69 CUG repeats forms hairpins whose melting temperatures (Tm) are similar (ca. 75 °C), no matter the number of repeats . Detaile37) self-complementary RNA duplexes (mostly six- and eight-mers) by ca. 1 kcal/mol. The presence of PEG changed the particular nearest-neighbor parameters for RNA duplexes in the range 0.03–0.17 kcal/mol; however, significant difference  was related to the free energy of initiation of RNA duplex formation.UV-melting performed in buffer containing 100 mM sodium chloride only partially reflects intracellular conditions. Cells contain a large number of nucleic acids, proteins, carbohydrates, and the total concentration of biomolecules is estimated to be 50–400 g/L, depending on the type of cells and cellular compartments ,23,24. TTherefore, we have also determined the thermodynamic stability of duplexes and quadruplexes formed by RNA repeats under molecular crowding conditions. In the case of duplexes, thermodynamic measurements in presence of 200 mM PEG400 (80 g/L) were performed only for the RNA repeats which in standard (PEG-free) melting buffer demonstrated cooperative (two-state) transition . ConsequOligonucleotide composed of three GCA repeats invariably presented two transitions of melting curves. UV-melting in buffer containing 200 mM PEG400 changed low- and high-temperature transition by 0.98 and −0.29 kcal/mol, respectively, reflecting destabilization of the weaker GCA duplex and stabilization of the GCA core duplex. For quadruplexes formed by AGG and UGG repeats, the presence of PEG in melting buffer changed their free energy by 0.43 and −0.28 kcal/mol, respectively.The results showed that the presence of the additional 200 mM of PEG 400 in the UV-melting buffer, already containing 100 mM sodium chloride, did not influence RNA structures formed by particular repeats. Moreover, the contribution of PEG400 to thermodynamic stability was also low, usually within 10% of original free-energy values.More than half of the analyzed oligonucleotides formed by the RNA repeats remain single-stranded. These repeats are rich in adenosine, uridine, and cytidine. Among them, we selected pairs that could potentially form duplexes and determined their thermodynamic stability by UV melting in two types of buffers . StandarThe free energy of those duplexes ranged from −3.4 to −4.8 kcal/mol, and their melting temperatures did not exceed 30 °C. About half of the analyzed duplexes melted in a two-state manner, which means that no intermediate states between the single-stranded form and the duplex were observed in the solution. For A, U, and C-rich repeats, the formation of a duplex is dependent on the types of mismatches occurring next to conventional Watson–Crick base pairs. For such duplex-forming repeats, the canonical, stabilizing pairs A-U may be insufficient to maintain a helix that contains highly destabilizing mismatches, e.g., C-C or A-A. For duplexes formed by such types of repeats, the G-U Wooble pair’s stabilizing role that supports these duplexes is significant. We observed a stronger destabilization of these duplexes in the presence of magnesium and potassium ions in comparison to the standard buffer, and the destabilizing effect was about 1.5–2 kcal/mol . However3G oligonucleotide forms a stable self-complementary duplex, but adding an equimolar amount of C(UGC)3U results in the formation of intermolecular duplex G(GCG)3G/C(UGC)3U of the stability of −15.35 kcal/mol. On the other hand, the mixing of G(GCG)3G with U(CUU)3C or U(CCU)3C did not disrupt self-complementary G(GCG)3G duplex 3C, U(CUU)3C, and U(CCU)3C repeats. These four oligonucleotides form stable, non-self-complementary duplexes with the G(AGG)3A oligonucleotide and prevent the quadruplex formation (no transition at 295 nm during UV-melting). All four non-self-complementary duplexes melted in a two-state manner. Their stability was significantly higher than the G(AGG)3A quadruplex alone. The most stable duplex was the G(AGG)3A/U(CCU)3C duplex, for which we could obtain parameters in 100 mM NaCl buffer solution but not in 1 M NaCl (the melting temperature was higher than 93 °C). The least stable was G(AGG)3A/U(CGU)3C duplex.Interestingly, we observed the impact of several single-stranded RNA repeats on the self-complementary structures of other repeats. For example, G(GCG)G duplex B. We alsplex 10 and (UAA)14; the second one contains thermodynamically stronger repeats (AGG)4 and (CGU)4, interleaved by AAG triplets. The selected RNAs represent two varied, thermodynamically interesting cases of RNA repeats’ interactions.Analysis of trinucleotide repeats coexistence in mRNAs and ncRNAs confirmed the earlier reports and showed that CNG-type repeats, usually located in the 5′UTR and ORF, are dominant ,26. It i10 and (UAA)14 repeats exist in all three variants of the GABRA4 transcript in its 3′UTR region and are approximately 400 nucleotides apart. The structure–function relationship of GABRA4 3′UTR is unknown; however, the relative closeness of the mentioned repeats suggests that they may interact with each other, playing a potential role for the molecule. Its 3′UTR region consists of over 9300 nucleotides, which suggests a wide range of regulation of its expression.As we showed above in thermodynamic studies, the oligonucleotides consisting of UUG and UAA repeats do not form secondary structures by themselves but can interact with each other to form a duplex. By screening the transcripts for the coexistence of rare unstructured repeats, we found that the (UUG)GABRA4 (9325 nt) using the RNAFold online tool [We performed in silico structure prediction of the whole 3′UTR region of ine tool ,28. It sGABRA4 3′UTR fragment. SHAPE data were introduced using “Read SHAPE reactivity—pseudo free energy” mode with slope 2.6 and intercept −0.8. From DMS, ketoxal, and CMCT mapping, only high reactive nucleotides were used as a chemical modification. The predicted model of secondary structure with the lowest free energy is highly structured (65% of the nucleotides are involved in base pairs). The 35% nucleotides are single-stranded and highly reactive with all chemical reagents  and 2 (region 306–360). The subdomains are branching from the internal loop located next to the helix stem formed by the TNR tracts. The subdomain 1 stem includes seven internal loops of different sizes and six small hairpins. Three of the hairpins  showed high reactivity to mapping agents, whereas the remaining three  showed no reactivity. Within subdomain 1, high reactivity was also demonstrated by the internal loop regions 90–98 and 295–306. The subdomain 2 stem includes a single, seven-nucleotide-long poly-adenosine bulge, two uridine bulges, and a small, four-nucleotide-long loop (region 315–350), and each of the motifs was highly reactive. Regarding the base-pairing probability, it was the most structurally conservative region of the molecule. The region between the subdomains, which connects them, was also widely available for mapping reagents.The obtained secondary structure confirmed base pairing between the repeated tracts of UUG and UAA trinucleotides, which form a helix stem specifying the Secondary structure probability was performed using a partition function mode of the RNAstructure software. The results were visualized on the secondary structure with the lowest free energy. It was indicated that three hairpins show a very high probability of more than 99%, and one double-stranded region with internal loops (105–137 and 235–249) showed a probability higher than 95%. The TNR-containing helix structure showed a probability of more than 70%. The lower probability of base pairing in this region may suggest the potential lability of the helix and can be related to the dynamic function of this region. A three-dimensional model of the structure obtained in the RNAComposer program  showed tGABRA4, we have searched miRDB [3′UTRs are widely known as regulatory regions containing target sites for microRNAs. In the context of the huge 3′UTR of ed miRDB  for miRNed miRDB ,37,38. NGABRA4 3’UTR fragment show that rare unstructured repeats are also able to mutually interact and fold into secondary structures, determining functional regions within an RNA molecule.Our studies of the CHIC1, also known as BRX (Brain X-linked gene), is a rare transcript preferentially expressed in the brain [CHIC1 RNA ORF sequence, several short tracts of AGG repeats are present that are separated by short tracts of AAG and CGU repeats. These repeats cover the codons for glutamate (GAG and GAA) and cysteine (UCG). The accumulation of AGG triplets suggests the formation of quadruplexes (G4 sequences) in the RNA structure. It is not clear whether the trinucleotide repeat pattern present in the transcript is significant at the transcript level due to its secondary and tertiary structure, or whether it is important for the encoded protein. The RNA structure of this region seems to be important; glutamate could be encoded by the GAA codon exclusively, but such repeats do not form a quadruplex, as evidenced by the above thermodynamic studies. G4 sequences in ORFs frequently encode low-complexity amino acid sequences, amino acid repeats, or short motifs [CHIC1 ORF (region of 129–298 nt of the whole mRNA), containing cumulative repeats of AGG spaced by AAG, in the vicinity of (CGU)4 repeats, to define their structural relationships to one another. However, probing for the RNA secondary structure of this fragment failed in the first step due to the inability to obtain a cDNA. As predicted, the selected RNA fragment formed a quadruplex structure that effectively inhibited reverse transcription. The quadruplex formation was observed during UV-melting monitored at 295 nm, both in the presence of sodium and potassium ions; obtained curves were different, however. Due to the length of the analyzed CHIC1 RNA fragment, the observed G4 structure is intramolecular, in contrast with intermolecular quadruplexes formed in the case of the earlier analyzed short oligonucleotides. Direct evidence of quadruplex formation is the melting curve for the guanosine-rich sequence which shows a “reversed” transition at 295 nm. Intramolecular quadruplexes (and hairpins) do not show Tm dependence on RNA concentration, but intermolecular structures  do [CHIC1 RNA quadruplexes were also visualized on the non-denaturing gel stained using the NMM (N-Methylmesoporphyrin IX) reagent [CHIC1 RNA fragment have been observed, which suggests the existence of two differently migrating quadruplex structures  do ,50. That reagent . Two forructures B. The twCHIC1 ORF blocks mRNA-based processes, including the reverse transcription in our study. Further experiments are needed to explain the role of the quadruplex in this transcript, which might broaden the cognition perspective for the CHIC1 function.Prediction of the secondary structure of this RNA fragment indicates that the CGU and AGG repeats do not interact directly with each other over their full length, but only at the ends of the tracts A. UnfortOligoribonucleotides for UV-melting experiments, DNA primers for PCR reactions, and 5′-FAM labeled DNA primers for reverse transcription in SHAPE experiments were synthesized on a BioAutomation MerMade12 DNA/RNA synthesizer using β-cyanoethyl phosphoramidite chemistry as described previously , and com2EDTA, pH 7. The second buffer was used for the determination of the influence of the molecular crowding effect on oligonucleotides’ thermodynamic stability and also contained PEG 400 in a concentration of 80 g/L. If UV melting of the model repeat oligonucleotides in the buffers listed above indicated the formation of an unstable RNA structure, the oligonucleotides were analyzed in a buffer containing 1 M sodium chloride, 20 mM sodium cacodylate, and 0.5 mM Na2EDTA, pH 7. The physiological melting buffer contained 150 mM potassium chloride, 4 mM magnesium chloride, and 20 mM sodium cacodylate, pH 7. Oligonucleotide single-strand concentrations were calculated from the absorbance at 80 °C and single-strand extinction coefficients were approximated by a nearest-neighbor model. Absorbance vs. temperature melting curves was measured at 260 nm with a heating rate of 1 °C/min in the range of 4 to 90 °C on a JASCO V-650 spectrophotometer with a thermoprogrammer. Melting curves were analyzed and thermodynamic parameters were calculated from a two-state model with the program MeltWin 3.5. Statistical analysis of thermodynamic data was carried out using MeltWin 3.5 software. Based on results obtained for three to nine concentrations of analyzed oligonucleotides, thermodynamic parameters and melting temperatures were calculated.The thermodynamic stability of structures formed by oligonucleotides composed of RNA repeats was analyzed in four buffers. Basic buffer was used to determine thermodynamic stability of the structure formed by RNA repeats and contained 100 mM sodium chloride, 20 mM sodium cacodylate, and 0.5 mM NaTo determine the possible interactions between various RNA repeat tracts, we searched the human RefSeq RNA database (NCBI) for natural RNAs containing more than one repeat tract. The selection of model RNAs for structural studies was based on the following criteria: (i) the presence of a minimum of two different repeat tracts, (ii) the minimum number of repeats within the tract is four, (iii) relatively close neighborhood of the different tracts (up to 400 nt) within one functional RNA region and (iv) at least one of the repeats is predicted not to form a secondary structure by itself. The inquired sequence contained ten repeats of trinucleotide. A tetranucleotide CCUG repeat was also included in the search for the study, due to the potential for the formation of structures and the connections with human muscle diseases . In thisRNA fragments for structure probing were prepared by in vitro transcription from a DNA template prepared in a multistep PCR reaction from chemically synthesized oligonucleotides . The seqFor a single experiment, 2 pmol of RNA was used. The RNA was folded in a buffer containing 300 mM sodium chloride, 5 mM magnesium chloride, and 50 mM HEPES, pH 7.5 for 5 min at 65 °C, and slowly cooled down for 30 min. Four separate mapping reactions were conducted, each with different chemical reagents. The SHAPE method with NMIA (N-methylisatoic anhydride) was used to modify flexible 2′-hydroxyl of nucleotide residues. CMCT (1-cyclohexyl-3-(2-m-orpholinoethyl) carbodiimide metho-p-toluene sulfonate) alkylated the N3 of uridines not involved in base pairing and modified N1 of non-paired guanosine. Kethoxal alkylated the N1 and 2-amino group of non-paired guanosines, whereas DMS (dimethyl sulfate) was used to modify unpaired adenosines and cytidines. Depending on the reagent, RNA was treated with 8 mM NMIA for 60 min, 30 mM DMS for 60 min, 9.5 mM of CMCT for 30 min, or 6.7 mM of kethoxal for 20 min. All samples were incubated at 37 °C. A control reaction was performed in the same conditions without particular reagents. Mapping reactions were terminated by ethanol precipitation.Particular chemically mapped nucleotides were recognized by reverse transcription, starting from proper 5′-FAM labeled primers specific to tested RNAs . Some ofChemically mapping data, such as ABI files, were analyzed with the Peak Scanner 1.0 Program ). Reactive nucleotides were recognized by comparing dideoxy sequencing ladders along with a mass marker. The first 2% of the highest peaks was excluded and the next 8% of the peak intensities was used to calculate the average value. To receive proper nucleotide reactivity, all peak intensities were divided by the average. Reactivities were normalized on a scale of 0 to 1.5, where 0 suggests not reactive site and 1.5 is highly reactive. Reactivities >0.7 are considered as strong, 0.3–0.7 as medium, and <0.3 as weak. All calculated data were used for secondary structure prediction. For all four mapping reagents, NMIA, DMS, CMCT, and kethoxal, at least three datasets were collected.GABRA4 and CHIC1 RNAs, containing potentially interacting repeat tracts, were subjected to the chemical mapping of the secondary structure. The results obtained for the fragment of GABRA4 RNA confirmed the formation of structures observed in thermodynamic studies of short model oligonucleotides. The in silico predictions performed for analyzed RNAs distinguish motifs formed by the repeats, which are consistent with the in vitro secondary structure probing results. GABRA4 case showed that rare repeats consisting mainly of A and U residues can actively interact intramolecularly, forming a stem that separates a structural domain. The CHIC1 case showed that the presence of a short CGU repeat tract was not able to unfold the G4 structure intramolecularly, which, however, was probably more complex, as it was formed by four short, discontinuous AGG repeat tracts.Trinucleotide repeats are among the most common in the transcriptome in terms of motif length. The presented study focused on the poorly described trinucleotide repeats, which are less frequent in the human transcriptome. In our work, we examined the stability and folding of 23 types (different sequences) of trinucleotide repeats, determining their interaction potential within their sequence as well as between different repeat types. The tested RNA repeats form duplexes, quadruplexes, or stay single stranded. Our data show, next to the CNG repeats type, CAA repeats can also self-fold into duplex structures. The presence of PEG, imitating molecular crowding in melting buffer, does not influence the stability of the RNA repeat structures. AU-rich trinucleotide repeats do not fold themselves and remain single stranded in the analyzed buffers, including crowding conditions. We observed their considerable potential for interaction with other repeat types, as the presence of the other partially complementary repeat-type RNA resulted in formation of the weak intermolecular duplex. Such intermolecular repeat interactions were also able to unfold AGG repeats-formed quadruplexes, and this happened in the presence of CGU, CCG, CUU, and CCU repeats. In the presence of magnesium and potassium ions, which bring the analyzed conditions closer to the physiological ones, duplexes formed by AU-rich trinucleotide repeats were destabilized up to 2 kcal/mol. We verified the interactions of the selected repeat tracts, observed in UV-melting experiments, by examining the secondary structure of two exemplary fragments of natural RNAs, in which two different repeat types coexist. Fragments of GABRA4 example that duplexes formed from different, potentially weak RNA repeats might be structurally important for the molecule function and regulation. RNAs found with more than six repeats usually contain repeat types that themselves easily fold into secondary structures and localize in ORFs. As the RNA sequence context makes up the RNA structure, it is natural that self-unstructured repeats usually interact somewhere in the context in the most optimal manner. Our question in the case of GABRA4 was if the interaction of the repeat tracts UUG and AAU will be more thermodynamically favorable than the other interactions in their sequence context. The obtained experimental structure of the GABRA4 fragment confirmed the superiority of this interaction and its shaping role in the structure of this region.Trinucleotide repeats in a number above six, which themselves do not have secondary structures and remain single stranded, are very rare in the human transcriptome. Even more rare is the coexistence of such repeats within one transcript. CNG-type repeats, usually located in the 5′UTR and ORF, are dominant. However, we showed on the


Most of these 29 DM mRNAs are involved in immune-related pathways . Moreover, four lncRNAs were hypermethylated and one lncRNA was hypomethylated in the NAc of AUD subjects (≥2-fold changes and p ≤ 0.05). Additionally, three miRNAs were hypermethylated in the NAc of AUD subjects (≥2-fold changes and p ≤ 0.05). Conclusions: This study revealed RNA methylomic changes in the NAc of AUD subjects, suggesting that chronic alcohol consumption may lead to AUD through epitranscriptomic RNA modifications. Our findings need to be replicated in a larger sample.Background: The nucleus accumbens (NAc) is a key brain structure mediating the rewarding effect of alcohol and drug abuse. Chronic alcohol consumption may alter RNA methylome (or epitranscriptome) in the NAc, leading to altered gene expression and thus behavioral neuroadaptation to alcohol. Methods: This pilot study profiled the epitranscriptomes of mRNAs, long noncoding RNAs (lncRNAs), and microRNAs (miRNAs) in postmortem NAc of three male Caucasian subjects with alcohol use disorder (AUD) and three matched male Caucasian control subjects using Arraystar’s m6A-mRNA&lncRNA Epitranscriptomic Microarray assay. Differentially methylated (DM) RNAs and the function of DM RNAs were analyzed by biostatistics and bioinformatics programs. Results: 26 mRNAs were hypermethylated and three mRNAs were hypomethylated in the NAc of AUD subjects (≥2-fold changes and  Among over 170 different types of RNA modifications identified so far , the metThe nucleus accumbens (NAc) plays a central role in the mesolimbic reward pathway. It mediates the process of motivation and emotion as well as the rewarding effect of alcohol and drugs of abuse . There iTo identify alcohol-responsive genes expressed in the NAc, Flatscher-Bader et al. performed cDNA microarray analysis of the transcriptome in postmortem NAc and found that alcohol-responsive genes were associated with vesicle formation and regulation of cell architecture, suggesting a neuroadaptation to chronic alcohol exposure at the level of synaptic structure and function . In our To date, no study is known to have examined RNA methylomic (or epitranscriptomic) changes in AUD subjects. We hypothesize that chronic alcohol use could alter methylation levels of both coding and noncoding RNAs that are responsive to alcohol and expressed in reward-related brain regions (particularly the NAc). In this pilot study, we used the RNA methylation microarray assay to profile mRNA/lncRNA/miRNA methylation changes in postmortem NAc of AUD subjects.Freshly frozen autopsy brain tissue samples were obtained from the New South Wales Brain Tissue Resource Centre (NSWBTRC) in Australia. They were dissected from postmortem NAc of three male AUD and three matched male control subjects. All subjects were Caucasian Australians with no history of illicit drug abuse or major psychotic disorders (such as schizophrenia and bipolar disorder) according to the criteria in the Diagnostic and Statistical Manual of Mental Disorder 4th Edition (DSM-IV) . ControlTotal RNAs were isolated from 10–50 mg of postmortem NAc tissue samples using the miRNeasy Mini Kit . RNA integrity number (RIN) and concentration were measured using the Agilent 2100 Bioanalyser with the Agilent RNA 6000 Nano Kit . The mean RIN of RNAs isolated from AUD NAc tissue samples was 6.1 (±0.5), and the mean RIN of RNAs isolated from control NAc tissue samples was 7.4 (±2.4). Denaturing agarose gel electrophoresis showed good quality of RNAs extracted from both the case and control NAC tissue samples . The 28S1–3 μg total RNA and m6A spike-in control mixture were added to 300 μL of IP buffer  containing 2 μg of anti-m6A rabbit polyclonal antibody . The reaction was incubated with head-over-tail rotation at 4 °C for 2 h. 20 μL of Dynabeads™ M-280 Sheep Anti-Rabbit IgG suspension  per sample was blocked with freshly prepared 0.5% bovine serum albumin (BSA) at 4 °C for 2 h, washed three times with 300 μL of IP buffer, and resuspended in the total RNA-antibody mixture prepared above. The RNA binding to the m6A-antibody beads was carried out with head-over-tail rotation at 4 °C for 2 h. The beads were then washed three times with 500 μL of IP buffer and twice with 500 μL Wash buffer . The enriched RNA was eluted with 200 μL Elution buffer  at 50 °C for 1 h. The RNA was extracted by acid phenol-chloroform and ethanol precipitated.“IP” RNAs and “Sup” RNAs were added with an equal amount of calibration spike-in control RNA, separately amplified, and labeled with Cy3 (for “Sup”) and Cy5 (for “IP”) using the Arraystar Super RNA Labeling Kit . The synthesized cRNAs were purified by the RNeasy Mini Kit . The concentration and specific activity (pmol dye/μg cRNA) were measured with NanoDrop ND-1000 . 2.5 μg of Cy3 and Cy5 labeled cRNAs were mixed. The cRNA mixture was fragmented by adding 5 μL of Blocking Agent and 1 μL of 25× Fragmentation Buffer, heated at 60 °C for 30 min, and combined with 25 μL of 2× Hybridization buffer. 50 μL of hybridization solution was dispensed into the gasket slide and assembled to the m6A-mRNA&lncRNA Epitranscriptomic Microarray slide. The slides were incubated at 65 °C for 17 h in an Agilent Hybridization Oven . The hybridized arrays were washed, fixed, and scanned using an Agilent Scanner G2505C .2-scaled Spike-in RNA intensities. After Spike-in normalization, the probe signals having Present (P) or Marginal (M) QC flags in at least 1 out of 6 samples was retained as “All Targets Value” in the Excel sheet for further “m6A methylation level” analyses. The “m6A methylation level” for a transcript was calculated as the percentage of modified RNA (%Modified) in all RNAs based on the IP (Cy5-labelled) and Sup (Cy3-labelled) normalized intensities. Raw intensities of IP  and Sup  were normalized with the average of log2-scaled Spike-in RNA intensities.The Agilent Feature Extraction software (version 11.0.1.1) was used to analyze acquired array images. Raw intensities of IP  and Sup  were normalized with an average of logp-value) for each transcript. The threshold for statistical significance was set at |FC| ≥ 2 and p-value < 0.05.A t-test was used to compare two groups  for differential m6A modification and calculate the fold change (FC) and statistical significance of the difference  and the closeness of their relationships as displayed in the dendrogram on top of the heatmaps.p-value denotes the significance of GO terms or pathways enriched in differentially methylated mRNAs. The lower the p-value, the more significant the GO term or pathway.The web-based gene set enrichment analysis tool Enrichr  was usedp-value < 0.05), 26 mRNAs were hypermethylated, while three mRNAs were hypomethylated in the NAc of AUD subjects  are shown in Positive Regulation of Acute Inflammatory Response , Regulation of Neuroinflammatory Response , and Regulation of Acute Inflammatory Response . Other 15 were significant molecular function (MF) terms, including N-acetylgalactosamine 4-O-sulfotransferase activity , Anion:Sodium Symporter Activity , Oncostatin-M Receptor Activity , Ubiquinol-cytochrome-c Reductase Activity , Amidine-lyase Activity , Leukemia Inhibitory Factor Receptor Activity , Cytokine Receptor Binding , Interleukin-6 Receptor Binding , Phosphatidylinositol-4,5-bisphosphate 5-phosphatase Activity , Ciliary Neurotrophic Factor Receptor Activity , Phosphatidylinositol Phosphate 5-phosphatase Activity , Ciliary Neurotrophic Factor Receptor Binding , Potassium:Chloride Symporter Activity , Sodium:Chloride Symporter Activity , and Phosphatidylinositol-4,5-bisphosphate Phosphatase Activity . No significant cellular component (CC) terms with adjusted p < 0.05 were identified.The top 18 Gene Ontology (GO) enrichment terms (adjusted p < 0.05). The top 10 KEGG enrichment terms are shown in p ≤ 0.030 and adjusted p ≤ 0.200) included: IL-17 Signaling Pathway (unadjusted p = 3.4 × 10−4), Inflammatory Bowel Disease (unadjusted p = 0.004), Cytokine-cytokine Receptor Interaction (unadjusted p = 0.009), C-type Lectin Receptor Signaling Pathway (unadjusted p = 0.010), Th17 Cell Differentiation (unadjusted p = 0.010), TNF Signaling Pathway (unadjusted p = 0.011), Alzheimer’s Disease (unadjusted p = 0.016), Non-alcoholic Fatty Liver Disease (unadjusted p = 0.021), JAK-STAT Signaling Pathway (unadjusted p = 0.023), and Nitrogen Metabolism (unadjusted p = 0.024).None of the KEGG pathways reached the adjusted significance threshold (adjusted p < 0.05) in AUD subjects. The top GO terms and KEGG pathways in which the above 29 differentially methylated mRNAs were highly enriched included inflammatory or immune response. In other words, chronic alcohol consumption may alter the mRNA methylation status of inflammation or immune response-related genes.This pilot study explored the epitranscriptomic (or RNA methylomic) changes in postmortem NAc of male AUD subjects. We identified 29 mRNAs, 5 lncRNAs, and 3 miRNAs that were differentially methylated  is used. Second, this pilot study only analyzed the epitranscriptomic changes in the NAc of AUD subjects. Since several other critical brain regions  are also components of the brain reward center, AUD-associated epitranscriptomic changes in other brain regions should also be examined. Third, since both sex-specific gene expression  and sex-This pilot work is the first step to the further examination of RNA methylomic variation in the brain of subjects affected with AUD in order to understand the epitranscriptomic mechanisms of AUD. Given that the methylation status of mRNAs involved in inflammation or immune response was altered in the brain of AUD subjects, future studies may adopt novel approaches to modify the methylation of these mRNAs to reduce systemic inflammation and thus benefit AUD treatment outcomes and reduce alcohol relapse.


RNA flexibility is reflected in its heterogeneous conformation. Through direct visualization using atomic force microscopy (AFM) and the adenosylcobalamin riboswitch aptamer domain as an example, we show that a single RNA sequence folds into conformationally and architecturally heterogeneous structures under near-physiological solution conditions. Recapitulated 3D topological structures from AFM molecular surfaces reveal that all conformers share the same secondary structural elements. Only a population-weighted cohort, not any single conformer, including the crystal structure, can account for the ensemble behaviors observed by small-angle X-ray scattering (SAXS). All conformers except one are functionally active in terms of ligand binding. Our findings provide direct visual evidence that the sequence-structure relationship of RNA under physiologically relevant solution conditions is more complex than the one-to-one relationship for well-structured proteins. The direct visualization of conformational and architectural ensembles at the single-molecule level in solution may suggest new approaches to RNA structural analyses. RNA conformational heterogeneity is important to diverse functions. Here, the authors use AFM to directly visualize individual RNA molecules that are in various conformational states under near physiological solution conditions for the first time. This idea has been reinforced by the recent, rapid, and exciting developments in predicting protein structures from primary sequences and extensive knowledge available in structural databases4. For RNA, the functional roles of structural dynamics continue to emerge in a number of biological and cellular contexts3. RNA differs from protein in several fundamental aspects that dictate its folding. It is a negatively charged polyelectrolyte, highly hydrophilic, and made of only four different building blocks that result in a highly degenerate folding-energy landscape. That is, one RNA primary sequence may adopt multiple energetically degenerate secondary, tertiary, or higher-order structures, whose architectures, populations of various conformers, and motion timescales, contribute to the versatile functions of RNA5. Indeed, extensive and pioneering studies have revealed that RNA structures are far more dynamic and heterogeneous than what could be described by single conformers8. Nevertheless, those studies provide only time-averaged behaviors of ensembles, not explicit spatial descriptions about individual molecules or subgroups of conformers in low populations. Moreover, current high-resolution techniques for structure determination  rely on signal enhancements over a large number of molecules of the same or very similar conformations to improve the signal-to-noise ratio. These methods are limited to studies of relatively homogeneous samples by driving the molecules to a uniform conformation through extreme buffer conditions  or by removing heterogeneous species during or after purification . In either case, such an artificially selected conformation is insufficient to depict the conformational ensemble that exists in solution, thereby limiting the perception of RNA molecules as static structures. As a result, both the extent and nature of RNA structural heterogeneity under near-physiological solution conditions have remained largely unknown.Ever since the first protein structure was determined in 19589. This question is fundamental to the understanding of functional RNA structural dynamics, and the answer requires direct examination of individual molecules in solution. The recent evolution of atomic force microscopy (AFM) enables such direct visualization with several clear advantages18. Measurements can be performed in physiologically relevant buffer conditions; sample consumption is extremely low, requiring only microliter volumes at nanomolar concentrations; and molecules can be observed in their native states without any manipulation, e.g., labeling, freezing, staining, or crystallization12. Moreover, as data are recorded in real space, a high signal-to-noise level can be achieved from a single image. Thus, the solution AFM method is well-suited for studying highly heterogeneous molecular systems under near-native conditions.The question, therefore, of whether the description “one sequence, one structure” is appropriate for RNA remains to be answered, and becomes even more urgent given the major development in predicting RNA structures22. Chemical probing, analytical size-exclusion chromatography, and multi-angle light scattering (SEC-MALS) data showed that possible heterogeneous conformations for the RNA exist in solution25. In crystals, the structure of adenosylcobalamin riboswitch aptamer domain from Thermoanaerobacter tengcongensis (rCbl), in complex with adenosylcobalamin (AdoCbl), exhibited a compact tertiary fold stabilized by long-range kissing-loop (KL) interactions26. Using the rCbl RNA as a proof-of-principle, our solution AFM data show that a single RNA sequence can form multiple conformations and individually definable multimeric architectures under physiologically relevant Mg2+ concentration, thereby providing new insights into how RNA structures should be perceived and investigated.Cobalamin riboswitches are one of the most widely distributed riboswitches, regulating B12 biosynthesis in bacteriaY-shape (Y), P-shape (P), candy-shape (candy1 and candy2), compact), dimeric, or multimeric  and P (from 22.5 to 9.1%) monomer conformations, coupled with an increase (from 1.6 to 62.7%) in the dimer population, indicating that those monomer conformations may undergo ligand-induced structural changes that ultimately drive dimer formation. The third major species observed, Y, exhibits a very similar population (~22%) under both conditions, suggesting that its structure is independent of ligand and may represent a binding-incompetent or misfolded conformation. It is noteworthy to mention that, with direct visualization by AFM, minor species with only a single or few copies can be detected 26, with a cross-correlation score of ~0.87 (see “Methods”) between the AFM image and the crystal structure. Interestingly, however, this crystal-structure-like monomer is present at an extremely low population in both the presence and absence of ligand at 1 mM Mg2+ concentration. All other monomer classes reveal more extended conformations, where L13 is disengaged from L5  reflects that the majority of heterogeneous species are active in terms of ligand binding, and only ~22% of the RNA is incapable of ligand binding, which is consistent with the Y conformer population observed by AFM that did not respond to ligand  data Fig.  indicateand Fig. . Of the FF), one-leg-out (OLO), and hook (HK) dimers between two P-shape or two candy-shape homo-conformers, and P-Y and P-candy dimers between two hetero-conformers  or by replacing L13 with a tetraloop (M3) , where the P6 extension constitutes one leg, and the other two legs are comprised of P2 and P4/P5 (M2) or P2 and P13 (M3), respectively 23.The topological structures of  Y2 Fig. , both exM3) Fig.  and 7. Aers Fig. . M2 Y coant Fig. , which sand Fig. , once agity Fig. . The pre4 is that a primary sequence folds into a specific 3D structure under near-physiological buffer conditions. Such a one-to-one relationship is appropriate for well-folded protein classes, as clearly evidenced in the structure database and demonstrated through applications of AlphaFold2. Although these advances in protein-structure prediction provide hope and encouragement for overcoming unique challenges in elucidating RNA 3D structures9, abundant experimental evidence suggests that a given RNA sequence can adopt diverse structural folds under physiologically relevant conditions8. Many of these functionally important folds might have been precluded from structure determination using current methods that require homogeneous samples or under non-physiologically relevant conditions. The direct visualization by AFM presented here illustrates the heterogeneity in both conformation and higher-order architecture that can exist for a single RNA sequence. These findings were consistent for both thermophilic (rCbl) and mesophilic (aCbl) cobalamin-binding aptamers in this study. Of note is the propensity of these RNAs to form various dimers at nanomolar concentrations and under physiologically relevant buffer conditions, whose populations increase in the presence of ligand and primarily involve KL interactions. Such intermolecular species do highlight the promiscuity of degenerate RNA–RNA interactions. Our ITC data indicate that all in vitro transcribed RNA particles observed in this study, except for the Y conformer, represent functional and active species capable of ligand binding. Principal component analysis of the ITC data indicates a mixture of conformational species, some of which may be capable of binding ligand directly , whereas others likely undergo conformational changes through an induced-fit binding modality.Both RNA and protein can fold into three-dimensional (3D) structures. One of the basic premises of revolutionary protein-structure prediction methods25. More generally, an aptamer may adopt a more preferred conformation in response to a particular ligand. The use of AFM may aid in providing the structural basis for these differences and their biological implications.Being conformational switches, whether co-transcriptional or post-transcriptional, RNA aptamers must be capable of alternate conformations that are intrinsic to their function. Moreover, co-transcriptionally folded aptamers may inevitably form partially folded structures as they are being transcribed. Some of the conformers observed by AFM may indeed represent structures along the folding trajectory but are still active species  capable of ligand binding through induced-fit conformational changes. Such alternate conformations could be informative for better understanding ligand selectivity by riboswitches capable of binding ligand derivatives with varying affinities. For example, it was shown that the promiscuity of ligand binding by aCbl may be correlated with its structure, namely the organization of peripheral domains2+ concentration is known to significantly affect the structure and dynamics of virtually all classes of folded RNAs and long non-coding RNAs, highlighting the importance of studying RNA molecules under physiologically relevant Mg2+ conditions and at the individual molecule level. Moreover, solution AFM is amenable to large RNAs, which are more likely to adopt broader conformational space, and are often too dynamic for structure determination by X-ray crystallography or cryo-EM. Thus, we envision the use of AFM, in concert with high-resolution structural methods and computational simulation, as a new approach to analyze the conformational ensemble of a structured RNA beyond snapshots that are recorded under non-physiological conditions, and to provide a more realistic view of the solution conformational states relevant to biological function.Our findings should stimulate discussion about approaches to RNA preparation and methodologies for structural analysis, particularly with respect to the detection of conformational species. This includes potential implications for data interpretation of structural and biochemical experiments, which are often conducted under milli- to micromolar concentrations, as well as general considerations for understanding RNA structure-function relationships in their native contexts. In particular, Mg26:rCbl DNA templateTCTGATTCAGGAATTCCATAATACGACTCACTATAGGTTAAAGCCTTATGGTCGCTACCATTGCACTCCGGTAGCGTTAAAAGGGAAGACGGGTGAGAATCCCGCGCAGCCCCCGCTACTGTGAGGGAGGACGAAGCCCTAGTAAGCCACTGCCGAAAGGTGGGAAGGCAGGGTGGAGGATGAGTCCCGAGCCAGGAGACCTGCCATAAGGTTTTAGAAGTTCGCCTTCGGGGGGAAGGTGAACAForward primer: 5′-TCTGATTCAGGAATTCCATAATACGACTCACTATAG-3′Reverse primer: 5′-TmGTTCACCTTCCCCCCGAAGGCGAAC-3′rCbl M2 DNA template:TCTGATTCAGGAATTCCATAATACGACTCACTATAGGUUAAAGCCUUAUGGUCGCUACCAUUGCACUCCGGUAGCGUUAAAAGGGAAGACGGGUGAGAAUCCCGCGCAGCCCCCGCUACUGUGAGGGAGGACGAAGCCCUAGUAAGCCACUGCCGAAAGGUGGGAAGGCAGGGUGGAGGAUGAGUCCCGAGCCAGGAGACCUGCCAUAAGGUUUUAGAAForward primer: 5′-TCTGATTCAGGAATTCCATAATACGACTCACTATAG-3′Reverse primer: 5′-TTmCTAAAACCTTATGGCAGGTCTCCTGGC-3′rCbl M3 DNA template:TCTGATTCAGGAATTCCATAATACGACTCACTATAGGUUAAAGCCUUAUGGUCGCUACCAUUGCACUCCGGUAGCGUUAAAAGGGAAGACGGGUGAGAAUCCCGCGCAGCCCCCGCUACUGUGAGGGAGGACGAAGCCCUAGUAAGCCACUGCCGAAAGGUGGGAAGGCAGGGUGGAGGAUGAGUCCCGAGCCAGGAGACCUGCCAUAAGGUUUUAGAAGUUCGCCUUCGAAAGAAGGUGAACAForward primer: 5′-TCTGATTCAGGAATTCCATAATACGACTCACTATAG-3′Reverse primer: 5′-TmGTTCACCTTCTTTCGAAGGCGAACTTCTAAAACCTTATGGCAGGTCTC-3′25:aCbl DNA templateGAAATTAATACGACTCACTATAGGTCAAATAGGTGCCGGTCCGTGAACAACAGCCGGCTTAAAAGGGAAACCGGTAAAAGCCGGTGCGGTCCCGCCACTGTAATTGGCCAAGCGCCAAGAGCCAGGATACCTGCCTGTTTGATCAGCACGAATTCTGCGAGGACAGATGAForward primer: 5′-GAAATTAATACGACTCACTATAGG-3′Reverse primer: 5′-mUmCATCTGTCCTCGCAGAATTCGTG-3′.2). The size and purity of RNA was confirmed by denaturing PAGE and mass spectrometry (Agilent 6250 Accurate—Mass Q-TOF LC/MS) . rCbl and mutant RNA samples were generated by in vitro T7 RNA polymerase transcription. Supplementary Fig. 2, 1 mM AdoCbl). To get high-resolution images, FASTSCAN-D-SS probes (Bruker) were used, which had a nominal tip radius of 1 nm, a resonance frequency of 80~140 kHz and a normal spring constant of 0.25 N/m. A pulsed blue laser (BlueDrive) was used for photothermal excitation, positioned at the base of the cantilever, while a superluminescent diode (SLD) was positioned near the head of the cantilever to detect cantilever deflection. Images were collected with a scan size of 500 × 500 nm2, 1024 × 1024 pixels2 and a scan rate of 1.0 Hz, with a typical initial set point of 450 mV and a free amplitude of 500 mV. The setpoint was changed after the tip approach and adjusted during the imaging based on the image quality. In total, 11 and 9 high-quality images were collected for rCbl in the absence or presence of ligand, respectively.All AFM experiments were performed under solution conditions using a Cypher VRS AFM  at 4 °C with amplitude-modulated AC mode (commonly known as tapping mode). To immobilize RNA, mica supports were treated with 1-(3-aminopropyl) silatrane (APS) (synthesized in-house) . 50 mM Ard-order polynomial leveling to the particle-free region, filtering by de-spiking to remove line artifacts, and Fast Fourier Transform (FFT) analysis to remove high-frequency noise. The final image resolution was increased to 4096 × 4096 pixels2 by doubling the number of pixels twice. Single-particle images were cropped from the processed images and converted to pseudoAFM images (*.txt) with 5-Å/pixel resolution in MountainsSPIP  for structure calculation. Tally analysis was done using the particle analysis function implemented in SPIP by manually selecting the particles for each class based on the topological surface. Particles with multimers or with linear nucleic acids were not counted.For images used for 3D topological structure calculation, the raw images were first processed with the following built-in settings in SPIP (Scanning Probe Image Processor) software (Metrology): plane correction by applying 327. The characteristic width and pitch of an RNA duplex are ~25 and 30 Å, respectively, which are on a scale similar to a sharp AFM probe and sensitive to AFM detection. Thus, an imaging resolution of 10-15 Å is routinely achievable11.The following is a brief description of the method. A survey of the RNA structure database indicates that A-form duplexes are highly conserved and that A-form-like duplexes are by far the predominant building blocks in folded RNA structures29. Since secondary structural information is generally available prior, 3D structures of folded RNA can be recapitulated from an AFM molecular surface using dynamic fitting, an approach similar to that used in X-ray crystallography and cryo-EM30. Only in the case of folded RNA is this approach particularly feasible, given the AFM resolution limit and characteristics of RNA hierarchical folding. The scoring functions that underpin the dynamic fitting to AFM images take both the Cross-Correlation (CC) between the AFM molecular surface and a structure (Eqs. VAFM(xyz)31 and energy E is empirically determined by scaling factors θc and θnc for covalent and noncovalent interactions, respectively  are the correlation, experimental and simulated intensities, respectively, of the ith pixel at the xyz position in the molecule; N and θAFM, θc, θstacking, θpairing, and θcontact are the scaling factors for AFM, covalent, secondary structural interactions (stacking and basepairing), and contacts, respectively.RNA structure is largely dictated by hierarchical folding. For a given primary sequence, the closest neighboring interactions generate secondary structural elements, including duplexes, hairpins, junctions, and other types of 3D motifs, followed by forming larger domains and global folds stabilized by long-range tertiary interactions34 as described briefly in the following. A structural model was generated using a coarse-grained MD calculation. The RMSD between the model and crystal structure is ~17 Å and the CC score between the simulated AFM molecular surface of the model and the crystal structure is between 0.4 and 0.5, depending on the percentage of noise added. The large RMSD relative to the known crystal structure and the low CC score indicate the two structures’ dissimilarity, which is required to evaluate the robustness of the method. Gaussian noise with 2 σ was added to the simulated AFM molecular surfaces. A total of twelve noise levels, ±5, ±10, ±15, ±20, ±30, ±40, ±50, ±60, ±70, ±80, ±90, and ±100% of the highest value in the Z-axis were simulated and randomly added to the AFM images. The crystal structure was used as the initial structure to dynamically fit the simulated AFM images. In the case of rCbl recapitulated structures, the starting model was the crystal structure (PDB: 4GMA) with missing residues added.Since no biomacromolecular structure has ever been determined using the information truly from a single molecule, no direct evaluation of the accuracy of the recapitulated structures from AFM images could be made. Thus, we performed extensive validation using simulated data of the 268-nt catalytic domain of RNase P RNA (PDB: 3DHS)The final recapitulated structure is identified and determined based on the lowest total energy and the highest CC scores  using a MATLAB script  at 25 °C, following a standard procedure of RNA-ligand titration as described previouslyript see . The theThe raw thermogram of AdoCbl binding to rCbl appeared unconventional, and differed from a typical exothermic binding heat compensation followed by an endothermic response . The choice of model, i.e., one-site, or two-site binding model, was determined using the F-test.To determine the number of states associated with the AdoCbl binding reaction and rationally reconstruct the ITC thermogram with all significant components  under the same solution conditions and experimental settings, except for RNA and ligand concentrations, which were 50 µM RNA and 500 µM, respectively.To confirm that the mutant λ = 0.932 Å). A sample-to-detector distance of 1.9 m was used to obtain a q range of 0.005 < q < 0.88 Å−1. Here, q is the magnitude of the scattering vector, q = (4π/λ)sinθ, where 2θ is the scattering angle and λ is the wavelength of the radiation. Ideally, the concentration of rCbl for SAXS should be the same as for the AFM experiments. However, the concentration of 20 nM for AFM is too low to produce reasonable SAXS signals. To select a concentration that is as low as possible and yet produces reasonable scattering curves after background subtraction, a wide range of RNA concentrations from 25 nM to 2 µM were analyzed. For RNA samples complexed with ligand, the concentrations of rCbl were in the same range of 25 nM to 2 µM, with the molar ratio of rCbl to the ligand of 1:10. Buffers containing ligand at concentrations in the range of 225 nM to 18 µM were measured accordingly, and used for background subtraction for ligand-containing samples. To minimize radiation damage and obtain a good signal-to-noise ratio, 225 images were taken for each sample and buffer using a flow cell with an exposure time of 1 s. The two-dimensional scattering patterns were collected using a Pilatus 2 M detector and converted to one-dimensional SAXS curves through radial averaging after solid angle correction and then normalizing with the intensity of the transmitted X-ray beam. Data were then averaged after the elimination of outliers using the software package developed at beamline 12-ID-B. The information about the samples for SAXS experiments, the SAXS data collection and analysis, and the software used are listed in Supplementary Table The SAXS experiments were carried out at the 12-ID-B beamline of the Advanced Photon Source (APS), Argonne National Laboratory. Photon energy was 13.3 keV , were generated from the Guinier plot in the range of qRg < 1.3. For comparison, Rg and I(0) were also calculated in real and reciprocal spaces using the program GNOM in the q range up to 0.30 Å−139. The pair-distance distribution function P(r) and maximum dimension (Dmax) were also calculated using GNOM. The molecular weights were estimated based on the method of correlation volume, Vc, using the formula for RNA40. The obtained structural parameters and molecular weights are listed in Supplementary Table The radius of gyration, The SAXS data for rCbl at the concentration of 1 µM were selected for the ensemble fitting as this was the lowest concentration with a reliable scattering signal , with the experimental one Isaxs(q).b is background offset, Nq is the number of experimental points, σ(q) is the experimental error.The goodness-of-fit of the synthesized scattering intensity from an ensemble to the SAXS experimental data was evaluated by comparing the synthesized profile, Further information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


Penicillium digitatum infection. The global mechanisms involved in the role of ABA in the P. digitatum–citrus fruit interaction are unknown. Here, we determine the transcriptome differences between the Navelate (Citrus sinensis (L.) Osbeck) orange and its ABA-deficient mutant Pinalate, which is less resistant to infection. Low ABA levels may affect both the constitutive mechanisms that protect citrus fruit against P. digitatum and early responses to infection. The repression of terpenoid, phenylpropanoid and glutation metabolism; of oxidation–reduction processes; and of processes related to the defense response to fungus and plant hormone signal transduction may be one part of the constitutive defense reduced in the mutant against P. digitatum. Our results also provide potential targets for developing P. digitatum-citrus fruit-resistant varieties. Of those up-regulated by ABA, a thaumatin protein and a bifunctional inhibitor/LTP, which are relevant in plant immunity, were particularly remarkable. It is also worth highlighting chlorophyllase 1 (CLH1), induced by infection in Pinalate, and the OXS3 gene, which was down-regulated by ABA, because the absence of OXS3 activates ABA-responsive genes in plants.Abscisic acid (ABA) protects citrus fruit against  Penicillium digitatum (Pers.:Fr.) Sacc. is this crop’s main postharvest pathogen, which causes green mold disease. The control of this fungus is carried out with synthetic fungicides, which increasingly have major drawbacks due to the emergence of fungal strains that resist commonly-employed fungicides; leading to consumer concerns about problems related to health and environmental pollution and the requirements from importing markets of ‘zero residue’ produce. Finding alternatives to these fungicides remains a priority [P. digitatum.Major food waste and economic losses are due to disease development caused by phytopathogenic fungi during postharvest handling and storage . Citrus priority . TherefoPlant hormones play important roles in the susceptibility of plants and fruit to infection by pathogens ,3,4. TheP. digitatum produce ABA, that fungal ABA is not a primary virulence factor, and that fruit ABA plays a protective role against P. digitatum infection [Citrus sinensis (L.) Osbeck) orange and its natural yellow mutant Pinalate, which contains very low ABA levels [P. digitatum and, therefore, its viability to infect fruit, while norflurazon damaged the fruit peel, which should increase disease incidence [We recently showed that both citrus fruit and nfection . This waA levels , to fruiA levels . In thisncidence . Therefoncidence ,13, and ncidence , access ncidence  and dehyncidence ,17 in cincidence .P. digitatum, which centered on the interrelation between ABA and specific phospholipases [P. digitatum, and the mechanisms regulated by ABA in the citrus fruit infected by this phytopathogenic fungus. To this end, we focused on the transcriptomic differences between the flavedo (outer part of peel) of Navelate and Pinalate oranges upon fruit harvest, and, before inoculating them with the pathogen, examined any changes induced by the fungus in the flavedo of both cultivars at the transcriptomic level. Moreover, and considering: (1) that applying ABA 1 mM reduces disease incidence in Pinalate orange but has a negligible effect on infection in Navelate, which already has very high ABA content [P. digitatum infection. Early response genes are key for perceiving and amplifying stress signals and for targeting downstream gene expression [P. digitatum in both orange cultivars, which occurred before disease and tissue degradation development.To the best of our knowledge, there is only one report that has focused on studying the mechanisms involved in the beneficial effect of ABA for increasing citrus fruit resistance to olipases . In the  content ; and (2) content ,17 indicpression . Moreovepression . TherefoP. digitatum in the flavedo of both cultivars and in the ABA-treated mutant.Pinalate fruit showed negligible initial infection symptoms by day 3 A, when dP. digitatum   B and the ≤ 0.05)  between  ≤ 0.05)  was foun ≤ 0.05) C. These  ≤ 0.05) , of whic ≤ 0.05) .As shown in p-value of ≤0.05 induced or repressed by wounding or infection, in relation to the FH fruit, were similar and very high in Pinalate  and a Pinalate A and NavPinalate B fruit, Pinalate C. As shoPinalate .The KEGG analysis of the up- and down-regulated genes in the FH Pinalate fruit vs. the FH Navelate oranges revealed that only the down-regulated genes grouped in the differential pathways or Brite Hierarchies categories. These genes mostly included those involved in secondary metabolism, including carotenoids, phenylpropanoids and terpenoids and polyketides , which sThe TopGO analysis also revealed that the most significant BP  and MF pP. digitatum infection in Pinalate fruit (IP vs. WP) were not differentially expressed in either their parental or the ABA-treated Pinalate fruit  further revealed the ABA-deficient mutant’s lack of an ability to induce or repress the expression of a set of up- and down-regulated DEGs, respectively, by infection in Navelate. While they play different roles, these DEGs mostly encode stress-related proteins . In genenfection . Likewisnfection  selectednfection . This peP. digitatum interaction and in those related to resistance elicitation against the pathogen [P. digitatum [P. digitatum and how this hormone influences the very early transcriptional outputs induced by the fungus. Therefore, by considering that disease development started by 3 dpi in Pinalate and later in its parental  DEGs, which could be related to the mutant’s lesser constitutive defenses against P. digitatum. In this regard, it is interesting to note that a citrus PR4 gene has been related to elicitation of resistance in Navelate orange [P. digitatum in citrus fruit [P. digitatum infection [P. digitatum [P. digitatum to colonize citrus fruit [P. digitatum infection [The analysis of the DEGs less expressed in the FH Pinalate fruit, respective to any other sample included in the RNA-Seq analysis Cluster 12) , suggeste orange . The Keg , suggese orange ,30,31 anus fruit ,25,26,31nfection , and ABAnfection . Likewisnfection  and incrnfection ,36. Acconfection . Anothernfection ,39. Funcigitatum ,41 and tus fruit . In the P. digitatum interaction. In line with this, we found that most of the processes induced in the FH Pinalate fruit, compared to the FH fruit of Navelate  , but alsNavelate , were asP. digitatum in the mutant and its parental fruit—was very restrictive because we focused on the very early responses to infection, even though we used a low conidial suspension concentration (104 conidia mL−1) to inoculate the fruit. Therefore, the number of DEGs regulated by infection in both cultivars was small, and much smaller than that found in the peel of other citrus fruit cultivars when a much higher conidial concentration (106 conidia mL−1) was used and RNA-Seq was performed at 3 dpi [P. digitatum infection. We cannot rule out the notion that the effect of ABA on such responses could be a consequence of its effect on reducing Pinalate susceptibility to the pathogen, but they might also be negatively modulated by ABA. The other DEGs up-regulated in Pinalate, which encoded ERF1 and an aspartyl protease, were also up-regulated in Navelate, and their expression did not increase when treating the mutant with ABA. Therefore, these DEGs were not regulated by ABA.Our experimental design—used to compare the mechanisms induced by at 3 dpi  rather tCA2, CA and ANNAT4, and of kunitz protease inhibitors (KPIs)—which show endopeptidase inhibitor activity  of the Lane Late Navel orange. This agrees with the findings of our group (unpublished results), which indicate the greater susceptibility of immature Navelina and Navelate oranges, whose peel was completely green, than that of mature fruit, in which chlorophyll has already degraded, to be infected by P. digitatum. These contrasting findings imply that the situation is not easy and other physiological factors related to fruit maturation or that occur in the mutant, such as loss of fruit firmness or accumulation of chlorophyll catabolic intermediates that lead to the burst of ROS [Of the DEGs up-regulated by infection in Pinalate fruit whose expression was reduced by ABA treatment , we idenactivity —because radation ,51 acts n plants  and stilre fruit . Neverthre fruit  which int of ROS , may inft of ROS ,56 and ct of ROS ,30, theyP. digitatum to colonize citrus fruit favored by the fruit ABA deficiency. These DEGs are related to cell wall and vesicle trafficking and to ribosomal proteins that are primarily involved in the translation of mRNA and lead to protein synthesis. The most repressed DEGs encoded an ATEXO protein, which was up-regulated in the parental and affects vesicle trafficking [PR gene expression [P. digitatum virulence to infect citrus fruit [The herein presented results also highlight that, in citrus, ABA may be necessary for reducing the repression of some genes involved in plant defenses against pathogens. Thus we found that the repression of the DEGs down-regulated by infection in Pinalate was alleviated by ABA treatment . Previous research indicated that H2O2 may attack P. digitatum, plays a role in targeting defense genes in plants and can make the cell wall stronger against microbial enzyme attack by favoring lignification [P. digitatum infection [P. digitatum. Other DEGs specifically up-regulated in the parental that could play a protective role against P. digitatum were a receptor-like protein kinase (RLK1), which is a key PRR component for the recognition of PAMPs, and the DEGs involved in phenylpropanoid metabolism (CYP75B1 flavonoid 3′-hydroxylase and UDP-glycosyltransferase) [P. digitatum [The set of DEGs and processes significantly induced in the parental  involvedfication ,61,62, anfection . The difnfection ,17, but nfection  when stusferase) ,28,37. Oigitatum  and in tigitatum , which wP. digitatum in citrus fruit. The repression of the RmlC-like cupin-encoding gene was also favored by ABA in Pinalate, although this repression was not statistically significant. Interestingly RmlC-like cupins constitute a pathogenicity factor in fungi that may counteract host defenses [Pinalate fruit also lacked diverse responses repressed by infection in its parental . It is idefenses  but, unfP. digitatum infection, which encourage future research to further the understanding of proteomic and metabolomics events, or in the potential role of specific genes, associated with the beneficial effect of ABA in reducing postharvest rots in citrus fruits.These overall results provide relevant information about the putative molecular mechanisms underlying the role of ABA in the protection of citrus fruit against a/b external color index 0.1) and Navelate (Citrus sinensis (L.) Osbeck)  oranges were harvested on the same day from the adult trees growing in the same experimental orchard at the The Spanish Citrus Germplasm Bank of the Instituto Valenciano de Investigaciones Agrarias . Three replicates of 10 FH fruit of each cultivar were used to determine the color index, as previously proposed by Lafuente et al. (2014) [a/b Hunter ratio. This ratio is classically used as a color index in citrus fruit [a and b values in an 8-mm measuring area at three locations around the equatorial plane of each fruit. Fruit from both cultivars free of damage were harvested and immediately delivered to the laboratory, where they were surface-sterilized by dipping fruit for 5 min in a 5% commercial bleach solution, which resulted in a final 0.19% sodium hypochlorite solution. Then, fruit were rinsed with water and dried at room temperature [P. digitatum in Pinalate fruit [P. digitatum is a wound pathogen, fruit peel was wounded with a flame-sterilized needle (4 mm depth) before inoculating them with either 10 µL of water or the conidial suspension per wound. Sixteen wounds were made in each fruit. Analyses were performed in flavedo samples because it is in this peel tissue where differences in the ABA levels between Navelate and Pinalate fruit are more evident. Only the flavedo taken from around the inoculation site was considered in the analyses. Therefore, 7-mm-diameter peel discs were taken around each inoculation site. Thus 16 peel discs were taken from each fruit and three replicates of 10 fruit per sampling period were selected in each replicate. The inner peel part  was removed with a razor blade from the peel discs and the flavedo discs in each replicate were frozen in liquid nitrogen, homogenized and kept at −80 °C for further analyses. Samples were taken at fruit harvest, and at 1, 2 and 3 d dpi in the fruit stored at 90–95% relative humidity (RH) and 20 °C.Full mature Pinalate (. (2014) , which wus fruit  and is pte fruit . Due to P. digitatum (Pers.:Fr.) Sacc fungus grown for 7 d at 24 °C on potato dextrose agar (PDA) . The conidial concentration was determined by a hemocytometer [4 conidia mL−1 to inoculate each wound.The conidial suspension used to inoculate Navelate and Pinalate oranges, either treated or not with ABA, was prepared in sterile distilled water from isolate Pd1 (CECT 20795)  of the Pytometer  and then2). To follow disease incidence and severity, all the fruit were stored at 90–95% RH and 20 °C in plastic boxes in the dark.Disease incidence was estimated by periodically determining the number of wounds showing disease and expressed as a percentage in relation to the total wounds inoculated with the pathogen. Four equidistant inoculations per fruit were performed on the equatorial axis of each orange and 60 wounds (three replicates of five fruit each) were considered in this analysis. Disease severity was also estimated in the same wounds by measuring the lesion diameter of each macerated zone in two perpendicular directions with a flexible ruler and was expressed as the lesion area  . BrieflyTotal RNA extraction was performed as previously described  from 1 gP. digitatum and with water . RNA-Seq raw reads from the Navelate samples were retrieved from NCBI Bioproject PRJNA749665. For the Pinalate samples, three biological replicates of each sample were used. A TruSeq Stranded mRNA Library Prep Kit® with PolyA selection for ribosomal RNA depletion  was utilized, and the manufacturer’s recommendations were followed. Libraries were sequenced by employing the Illumina NextSeq 500 platform, and 75-bp single-end reads were generated by the Genome Facility at the SCSIE-UV . The raw sequence reads quality was examined by FastQC v0.11.8 (http://www. bioin-formatics.babraham.ac.uk) and FastP . Clean data were obtained by removing the reads that contained only adaptors. Sequence reads were filtered by a mean Q20. The Citrus sinensis genome (Phytozome release Csinensis_154_v1.1) https://genome.jgi.doe.gov/portal/pages/dynamicOrganismDownload.jsf?organism=Phytozome, accessed on 6 March 2020) with the default settings in the TopHat2 v2.1.0 software was used to map the trimmed sequences . The Seqmonk v1.46 software was employed for quality control, visualization and quantification purposes . The differential expression analysis between two experimental conditions was run with the edgeR R/Bioconductor package (v3.20.9) in the R (v3.4.4) environment . Only the genes that met an adjusted p-value ≤ 0.05 in each comparison were considered to be differentially expressed genes (DEGs). These values were estimated as proposed by Benjamini and Hochberg (1995) [2 RPM method. A cut-off of |Log2 FoldChange| ≥ 1 was established to select the DEGs to be included in the Venn diagrams, which show the number of DEGs induced or repressed by infection or wounding (mock control), and for the following bioinformatics analyses. The Seqmonk tool was employed to select highly variable genes by a standard deviation cutoff above 0.6. The selected genes were hierarchically clustered by the average linkage method with the Pearson Correlation distance metric and are represented on the heatmap and by the HCA using the MultiExperiment Viewer . The PCA was plotted by plot.ly  and the Log2 RPM values were used in the analysis. The TBtools.KeggBackEnd package (TBtools v 1.046) [p-value (pgoFisher) was <0.05.RNA-Seq analysis, data processing and normalization were performed as previously described by Romero and Lafuente (2020) . In shorg (1995) , and thev 1.046)  was emplv 1.046)  with thehttps://www.lynnon.com/dnaman.html, accessed on 11 January 2021) was used to design the gene-specific forward and reverse primers, which are shown in http://rest.gene-quantification.info, accessed on 5 October 2021). The cDNA obtained from 25 ng of RNA, the gene-specific primer pairs and SYBR Green 1 Master , were employed to obtain the relative gene expression data in a Light Cycler480 II System  instrument. cDNA amplification was monitored during 40 cycles at 95 °C (10 s), 60 °C (5 s) and 72 °C (10 s). The values were the means of three biological replicates samples, with two technical replicates ± standard error.Total RNA was treated with Ribonuclease-free DNase  according to the manufacturer’s instructions to remove genomic DNA contaminations for subsequent gene expression analyses. To validate the RNA-Seq results, and to determine the expression pattern of the genes selected for the validation in response to wounding (control) or infection, an RT-qPCR analysis was performed by following the method described by Romero and Lafuente (2020) . cDNA wap < 0.05) (p ≤ 0.05) were run to determine if infection induced significant differences in relation to the mock-wounded samples, in Navelate fruit and in the fruit of its mutant Pinalate, either treated or not with ABA, for the same storage time. The results are the means of three biological replicated samples ± standard error.The Statgraphics Plus 4.0 software  was used to perform the statistical analyses. An analysis of variance (ANOVA) and a Tukey’s test (P. digitatum-resistant varieties, but also new insights into the role of ABA in the interaction mechanisms between citrus fruit and the necrotrophic fungus P. digitatum. Of those targets regulated by ABA, we wish to highlight a thaumatin protein and a bifunctional inhibitor/LTP, which are both relevant in plant immunity. Moreover, the genes that play protective roles against the fungus that encoded the ATEXO, RPL27 and Pel proteins, which affect vesicle trafficking, translational regulation and favor the release of elicitors of PR gene expression, respectively, were repressed by infection in the ABA-deficient mutant, but not in its parental. It is also worth highlighting the CLH1 gene, induced by infection in Pinalate, and that encoding OXS3, which was negatively regulated by ABA, because OXS3 family proteins repress ABA signaling in plants, and the lack of OXS3s might favor the activation of ABA-responsive genes. To conclude, our findings provide not only new potential targets for developing


Keloids are pathologic wound healing conditions caused by fibroblast hyperproliferation and excess collagen deposition following skin injury or irritation, which significantly impact patients by causing psychosocial and functional distress. Extracellular matrix (ECM) deposition and human fibroblast proliferation represents the main pathophysiology of keloid. Long non-coding RNAs (LncRNAs) play important roles in many biological and pathological processes, including development, differentiation and carcinogenesis. Recently, accumulating evidences have demonstrated that deregulated lncRNAs contribute to keloids formation. The present review summarizes the researches of deregulated lncRNAs in keloid. Exploring lncRNA-based methods hold promise as new effective therapies against keloid. Keloids are pathological scars characterized by firm, raised, erythematous plaques or nodules following cutaneous injury, which under normal conditions results in wound healing with a flat scar . KeloidsRecent advances have proved that most human genome is transcribed to RNAs that lack the capacity to encode proteins (non-coding RNAs). Long non-coding RNAs (LncRNAs), are defined as transcripts longer than 200 nucleotides in length without protein-coding capacity . IncreasLiang et al. found that more than 2,500 lncRNAs were differentially expressed between keloid tissue and the normal human skin by microarray analysis and qRT-PCR. Among them, 1,731 lncRNAs was upregulated and 782 lncRNAs was downregulated . FurtherAnother study identified a total of 319 keloid-specific lncRNAs using RNA-seq and miRNA-seq . The stuTo identify lncRNAs differentially expressed during keloid formation, secondary analysis of keloid-related sequencing and microarray data were downloaded from the open-source Gene Expression Omnibus (GEO) database. A total of 2356 lncRNAs was changed before and after injury in keloid-prone groups . Among tA recent study identified 11 differentially expressed 11 EMT-related lncRNAs and 16 mRNA in keloid tissues versus normal tissues . These 1The development of keloid was significantly related with HKFs proliferation, migration, invasion, and apoptosis. LncRNAs and miRNAs can communicate with and co-regulate each other . These lLncRNA-H19 was one of the first reported lncRNAs and associated with proliferation in many tumors . H19 canLncRNA homeobox (HOX) A11 antisense, HOXA11-AS, was recently proved to promote keloid formation through inducing type I collagen (ColI) synthesis. HOXA11-AS and ColI expression levels were increased in human keloid tissues and HKFs . FurtherLncRNA Calcium voltage-gated channel subunit alpha1 G antisense RNA 1  is the antisense RNA of CACNA1G, mRNA of the T-type channel protein Cav3.1 . CAS1 exin vivo. TGF-β1 was proved to be a direct and functional target of miR-3141.Accumulating reports demonstrated that long non-coding RNA LINC01116 was associated with the development of various malignancies . A recenLncRNA-activated by TGF-β (lncRNA-ATB) has been proved to promote tumor cell invasion and metastasis, exhibiting oncogenic functions in several cancers . LncRNA-The lncRNA AC073257.2 and its upstream target gene Gli2 were both upregulated in keloid. LncRNA AC073257.2 and HNF1A-AS1 might regulate keloid cell growth and proliferation by its target gene GLI2 and HNF1A respectively. The differentially expressed Hh signaling pathway-related lncRNAs and mRNAs may help to uncover the pathogenesis of keloid .LINC00937 suppresses HKFs proliferation and ECM deposition by targeting the miR-28-5p/MC1R axis . LINC009Wingless type (Wnt) signaling pathway was demonstrated to play a role in the pathogenesis of wound healing . Using aHedgehog (Hh) signaling pathway plays important roles in several biological and pathological processes, especially in malignant tumors . Huang eIn this review, we summarized the published research data about the role of lncRNAs in the pathogenesis of pathological scars, including keloid and HS. In particular, we discussed the regulatory relationships between lncRNAs and miRNAs in the progression of keloid. These researches strongly support the potential role of lncRNAs keloid and HS. Some lncRNAs were upregulated and they promoted skin fibrosis while other lncRNAs were downregulated and suppressed skin fibrosis. LncRNAs regulate key processes involved in keloid and HS, including fibroblast proliferation, ECM deposition, Wnt signaling, Hh signaling and TGF-βsignaling. However, the knowledge about lncRNA-miRNA crosstalk remains largely unexplored in keloid. Investigating the expression and function of lncRNAs will help to increase our understanding about the molecular mechanisms of pathological scars. Recent studies have identified circular RNAs (circRNAs) as important regulators in human keloid . LncRNAs


The formation, growth, division and proliferation of protocells containing RNA strands is an important step in ensuring the viability of a mixed RNA–lipid world. Experiments and computer simulations indicate that RNA encapsulated inside protocells can favor the protocell, promoting its growth while protecting the system from being over-run by selfish RNA sequences. Recent work has also shown that the rolling-circle replication mechanism can be harnessed to ensure the rapid growth of RNA strands and the probabilistic emergence and proliferation of protocells with functionally diverse ribozymes. Despite these advances in our understanding of a primordial RNA–lipid world, key questions remain about the ideal environment for the formation of protocells and its role in regulating the proliferation of functionally complex protocells. The hot spring hypothesis suggests that mineral-rich regions near hot springs, subject to dry–wet cycles, provide an ideal environment for the origin of primitive protocells. We develop a computational model to study protocellular evolution in such environments that are distinguished by the occurrence of three distinct phases, a wet phase, followed by a gel phase, and subsequently by a dry phase. We determine the conditions under which protocells containing multiple types of ribozymes can evolve and proliferate in such regions. We find that diffusion in the gel phase can inhibit the proliferation of complex protocells with the extent of inhibition being most significant when a small fraction of protocells is eliminated during environmental cycling. Our work clarifies how the environment can shape the evolution and proliferation of complex protocells. The RNA world hypothesis, according to which an RNA-based life preceded the DNA and protein-based life on prebiotic earth, has been an important hypothesis regarding the origin of life. The abiotic synthesis of ribonucleotides ,2,3 in sComputer simulations have shown that the evolution of functional RNA sequences within protocells offers several advantages ,26,27,28J) as There are two major hypotheses regarding a suitable environment for life’s origins: the hydrothermal vent hypothesis  and the pol/Khyd . Howeverpol/Khyd . It causs Lavg∝J . Therefos Lavg∝J . Neverths Lavg∝J . Therefos Lavg∝J ,43. In as Lavg∝J ,45, the s Lavg∝J ,46. Lipis Lavg∝J . During s Lavg∝J ,48. An is Lavg∝J . Figure Along with laboratory-based experiments, recently, few experiments conducted near hot springs have provided confirmation of the spontaneous assembly of vesicles and formation of long RNA polymers in such locations ,49,50. AIn our previous work , we consWe found that in the presence of dry and wet phase only, the initial population of protocells can evolve toward a state where protocells containing multiple types of ribozymes dominate. However, when the process of long polymer diffusion in the gel phase is taken into account, there is a significant slow down in the evolution of the protocell population, suggesting an inhibitory effect of gel phase diffusion. This effect is most pronounced when we consider degradation of entire protocells in the wet phase with small probabilities. The long polymer diffusion process in the gel phase then becomes the primary reason for the gradual decay and ultimately elimination of RNA strands, and as a result, the protocell population fails to evolve. On the other hand, the dry and wet phase alone or a dry, wet and gel phase that does not facilitate long polymer diffusion can sustain the evolution even in the presence of protocell degradation processes. Finally, in the presence of the dry and wet phase and absence of diffusion in the gel phase, we also observed a spatial expansion of the protocell population when initially one or very few of the sites contain circular templates, even when protocells are allowed to degrade in the wet phase. The growth of RNA strands inside those protocells followed by their subsequent division and occupation of neighboring sites by daughter protocells eventually lead to the outward spread of the protocell population with multiple ribozymes until it covers almost the entire lattice. Our work provides quantitative support for the viability of the hot spring environment in creating and sustaining an evolving population of protocells characterized by increasingly complex functionality.s) template of length 200 nt [According to the hot spring hypothesis ,43, lipih 200 nt  at each K was determined from sequence-based simulations by fully extending a primer using the experimental primer extension rates [L) of the template and the relative amount of mismatch  by attaching with a small complementary primer (∼8 nt) followed by non-enzymatic, template-directed extension of the primer. We assume the lipid membrane of the lamellae to be permeable to monomers and short oligomers  (≤8 nt) on rates ,52,58 onl) are diverse in terms of secondary structures [r), cyclase (c), nucleotide synthase (n) and peptidyl transferase (p). Recent work by Dingle et al. [The newly created, open-ended single strands , whemeasured , for extb is the number of monomers in units of 200 mers that a single nucleotide synthase can create . These reactions form the basis of our coarse-grained model and can be represented as the following set of equations D=PhoThe diffusion of molecules from one site to another also depends on the difference in the number of strands between them. The molecules from the central site are more likely to diffuse to the neighbor that is relatively empty. The size of the lattice site is et phase ,63. AlthWe first simulated the evolution of RNA strands and protocells in the dry and wet phase after inactivating the gel phase in order to understand the dynamics in the absence of long-strand diffusion. Such a scenario also provides a benchmark for evaluating the impact of diffusion in the gel phase when it is subsequently switched on. We find that the strands in a few sites which happen to contain faster replicating circular templates initially increase and become encapsulated in vesicles during the subsequent wet phase. However, at most other sites, the initial circular templates have low–medium replication rates as a result of which new RNA strands including ribozymes are not produced at a rate that is faster compared to the degradation process. As a consequence, those sites become devoid of RNA strands. This results in the concentration of a large number of strands at a few sites, while most of the remaining sites become empty. Eventually, as the vesicles originating from those few sites start to divide when the threshold volume is attained, the newly created daughter vesicles occupy the empty nearest neighbor sites. Through this vesicle division process, the RNA molecules gradually spread over the entire lattice, and we find that ∼90% sites (and subsequent protocells) contain all four types of ribozymes at equilibrium , D=0. Thibozymes . The SupD = 0 case, the time at which the curve starts rising steeply from 0 occurs at different times for different trial runs even for the same diffusion coefficient. Nevertheless, we observed that the time evolution for non-zero D values is still much slower than the D = 0 case across all trials. We therefore show the curves for only one trial for each diffusion coefficient in When the gel phase is switched on, allowing for the diffusion of long RNA polymers in that phase, the evolution toward equilibrium is much slower. The plots for the percentage of sites with four types of ribozymes vs. time for two diffusion coefficients are shown in absence of the relocation, a few initial vesicles with faster replicating strands cross the threshold volume, leading to vesicle division, which spreads some of their contents encapsulated in newly formed daughter protocells to neighboring sites. This process happens from a few locations on the lattice, and as the process continues, it leads to the formation and outward growth of clusters of vesicles containing all four ribozymes. This happens because dividing vesicles located on the edge of the cluster are more likely to contain larger numbers of ribozymes with one of the daughter protocells more likely to eliminate vesicles neighboring the boundary of the cluster (that have relatively fewer ribozymes) than those in the interior or edge of the cluster (that have a relatively larger number of ribozymes). Eventually, the spread of functionally complex protocells occurs through the merging of these expanding clusters. This is evident from As mentioned in the methods section, the presence of water in the wet phase will cause the vesicles to undergo rapid Brownian motion. Therefore, a vesicle which originates from a site on the lattice will not deposit on the same site after the wet phase. The Brownian motion of vesicles during each wet phase will effectively result in random relocation of the vesicles on the lattice. To account for this phenomenon, we randomly shuffle the vesicle positions on the lattice at the beginning of each wet phase. Protocell division occurs after reshuffling in those protocells where the number of RNA strands has crossed the threshold volume. So far, we have assumed that the protocells remain intact during the wet phase, but in reality, some protocells will degrade in every wet phase. To account for this effect, we include the process of protocell destruction in our simulation at the beginning of every wet phase. This is likely to inhibit the spread of protocells of increasing complexity in a manner that is dependent on the protocell killing probability. Each protocell can degrade along with its contents with a probability D = 0 and We also plot the total number of strands vs. time of a random site and its eight nearest neighbors for the case of ill=0.01 . As evidill=0.01 , which dill=0.01  or the pill=0.01 , both ofing site C becomesone non-empty site, even starting with 50 templates is inadequate to ensure the proliferation of protocells when strand diffusion is present. Therefore, strand diffusion in the gel phase can prevent the gradual spatial expansion of a functionally complex protocellular population. However, when the protocell relocation process in the wet phase was allowed to occur instead (with strand diffusion turned off), 2% of the initial sites containing one template each were able to evolve and expand, indicating that this process does not hamper spatial expansion. Finally, to check if initially starting with templates in fewer number of sites can lead to the evolution and expansion of the protocell population even when protocells can degrade in the wet phase, we varied both the fraction of non-empty sites and the number of initial templates in them. We found that expansion is possible when there are at least 10% non-empty sites with at least five random templates in each of them, and such expansion is possible even in the presence of the protocell relocation process.Given how a protocell can divide and its daughters can occupy a nearest neighbor site, we wanted to ascertain if the protocell population can proliferate across the entire lattice, starting from an initial state where only a few sites contain the initial templates. We first checked for the case with strand diffusion in the gel phase (Any compelling model of protocell evolution in a primordial RNA world must account for plausible environmental conditions in which such processes occurred and address the constraints imposed on the evolutionary processes by such conditions. The hot spring hypothesis of the origin of life provides an interesting test-bed to study evolutionary processes and assess the viability of such processes in aiding the formation, growth, division and eventual proliferation of protocells of increasing functional complexity. The ecological niche around hot springs when subject to dry–wet cycling provides suitable conditions for the formation of long RNA polymers which can then be encapsulated into vesicles. The encapsulation of RNA sequences by protocells and the replication of RNA via the rolling circle mechanism can lead to rapid growth of number of RNA strands and also increase the likelihood of the creation of ribozymes of diverse functionality . In thisThe hot spring hypothesis emphasizes the importance of the gel phase when protocells compartments can exchange molecules with each other by the strand diffusion process through their fused membranes. A question that can be raised in the light of our analysis is whether a gel phase characterized by the diffusion of long RNA sequences is essential for the spatial proliferation of functionally complex protocells containing multiple ribozymes. It has been argued  that theExperimental studies ,48,51 ha