FMR1 gene contains a polymorphic CGG trinucleotide sequence within its 5′ untranslated region. More than 200 CGG repeats (termed a full mutation) underlie the severe neurodevelopmental condition fragile X syndrome, while repeat lengths that range between 55 and 200 (termed a premutation) result in the conditions fragile X-associated tremor/ataxia syndrome and fragile X-associated premature ovarian insufficiency (FXPOI). Premutations in FMR1 are the most common monogenic cause of premature ovarian insufficiency and are routinely tested for clinically; however, the mechanisms that contribute to the pathology are still largely unclear. As studies in this field move towards unravelling the molecular mechanisms involved in FXPOI aetiology, we review the evidence surrounding the two main theories which describe an RNA toxic gain-of-function mechanism, resulting in the loss of function of RNA-binding proteins, or a protein-based mechanism, where repeat-associated non-AUG translation leads to the formation of an abnormal polyglycine containing protein, called FMRpolyG.The  FMR1 gene on the X chromosome. This repeat sequence is polymorphic in length, with categorization into four different size ranges  translation, drawing on parallels in FXTAS and advances made in that disease.Fragile X-associated premature ovarian insufficiency (FXPOI) is among a family of disorders caused by the expansion of a CGG trinucleotide repeat sequence located in the 5′ untranslated region (UTR) of the e ranges . HealthyFOXL2  is defined as the loss of ovarian hormonal function with evidence of follicle depletion before the age of 40 years . It thusFOXL2 . AbnormaFor many women, the most immediate and significant consequences of POI are amenorrhoea and an inability to conceive, however, some women present with intermittent ovarian function and conceive naturally  inadequate formation of the ovarian reserve during foetal life and (ii) alterations in follicle recruitment and maturation that cause abnormally extensive or fast depletion of the ovarian reserve during post-natal  life. While information from women is scarce, the development and use of model systems has gone some way towards addressing this, with data available from three published knock-in mouse strains, harbouring 130   repeat lengths. While these data are only correlative, these findings suggest that FMR1 mRNA accumulation in granulosa cells may be an important cause of follicle dysfunction and loss. A preliminary report of in vitro-based studies further demonstrated that transfection of the human granulosa cell tumour line COV434 with plasmid DNA expressing 88 CGG repeats decreased cell viability after 48 h . However, although the proteins discussed here are predicted to be also relevant in the pathogenesis of FXPOI, there has been no validation as yet of these proteins in ovary-specific premutation models. Furthermore, while a degree of overlap is expected given the parallels with FXTAS, it is probable that some deregulated proteins will be specific to granulosa cells, thus identification of these ovarian targets will be essential as they are likely to be key in understanding the RNA gain-of-function mechanism that may potentially contribute to FXPOI.Identification of the proteins that bind and are sequestered by CGG RNA within intranuclear inclusions in the brain has been an important step towards understanding the contribution of RNA gain-of-function toxicity to the pathogenesis of FXTAS. Several proteins have been identified that bind to CGG repeats in FXTAS-affected cells, unlike other disorders associated with unstable repeat expansions, which usually have a principle protein deposit . RNA binFMR1 locus also supports RNA toxic gain-of-function as one of the possible pathophysiologic mechanisms underlying FXPOI. Using genomic approaches   RNAs originating from the Met takes place. The 40S ribosome is now committed to its selection of start codon and is joined by the 60S ribosomal subunit, allowing the first peptide bond to be formed, thus beginning translation elongation     and Wellbeing of Women (PRF005 to R.R.). R.R. declares no conflict of interest. R.A.A. reports grants and personal fees from Roche Diagnostics and personal fees from Ferring Pharmaceuticals, IBSA, Merck Serono, outside the submitted work.


Arabidopsis thaliana (Arabidopsis) has two nuclear‐encoded plastid‐targeted organelle RNA recognition motif (ORRM) proteins: ORRM1 and ORRM6. In the orrm1 mutant, 21 plastid RNA editing sites were affected but none are essential to photosynthesis. In the orrm6 mutants, two plastid RNA editing sites were affected: psbF‐C77 and accD‐C794. Because psbF encodes the β subunit of cytochrome b559 in photosystem II, which is essential to photosynthesis, the orrm6 mutants were much smaller than the wild type. In addition, the orrm6 mutants had pale green leaves and reduced photosynthetic efficiency. To investigate the functional relationship between ORRM1 and ORRM6, we generated orrm1 orrm6 double homozygous mutants. Morphological and physiological analyses showed that the orrm1 orrm6 double mutants had a smaller plant size, reduced chlorophyll contents, and decreased photosynthetic efficiency, similar to the orrm6 single mutants. Although the orrm1 orrm6 double mutants adopted the phenotype of the orrm6 single mutants, the total number of plastid RNA editing sites affected in the orrm1 orrm6 double mutants was the sum of the sites affected in the orrm1 and orrm6 single mutants. These data suggest that ORRM1 and ORRM6 are in charge of distinct sets of plastid RNA editing sites and that simultaneous mutations in ORRM1 and ORRM6 genes do not cause additional reduction in editing extent at other plastid RNA editing sites.Plastid and mitochondrial RNAs in vascular plants are subjected to cytidine‐to‐uridine editing. The model plant species  In plants, RNA editing is restricted to plastids and mitochondria and is viewed as a correction mechanism to compensate for mutations in the haploid organelle genomes Lu, . A commonCXXC] motif, which is homologous to the signature zinc finger motif in classic cytidine deaminases  nuclear genome encodes nine functional RIPs/MORFs ‐type zinc finger domains and are found in many land plants  proteins Lu, . RRM proorrm1‐1 Arabidopsis mutant displayed near‐complete loss of editing at 12 plastid RNA editing sites and substantial reduction in editing extent at nine plastid RNA editing sites . Consequently, the orrm6‐1 and orrm6‐2 mutants displayed reduced PSII photochemical efficiency, small and pale green leaves, and stunted growth  T‐DNA insertion lines orrm1‐1 (SALK_072648), orrm6‐1 (SAIL_763_A05), and orrm6‐2 (WiscDsLox485‐488P23) in the Columbia ecotype were obtained from the Arabidopsis Biological Resource Center  and genotyping primers listed in Table −2 s−1, the temperature was 22°C, and the relative humidity was 50%. Unless otherwise stated, plants used for photographing, pigment extraction and measurements, chlorophyll fluorescence, as well as leaf total RNA extraction and subsequent RT‐PCR and Sanger sequencing, were four weeks old.2.2a and b and carotenoid per gram of fresh tissues were measured on a BioMate 3S UV‐Visible spectrophotometer (Thermo Scientific) at four wavelengths: 470, 646, 654, and 663 nm  of chlorophyll 2.3Fv/Fm  was determined on dark‐adapted plants at room temperature with the MAXI version of the IMAGING‐PAM M‐Series chlorophyll fluorescence system , as described previously /Fm, where Fv, Fm, and Fo are variable, maximal, and minimal fluorescence of dark‐adapted leaves, respectively , digested with the RNase‐free DNase I (QIAGEN), and reverse‐transcribed with random primers (Promega) and Moloney murine leukemia virus reverse transcriptase (Promega) to generate the mRNA:cDNA hybrids, as described previously . The orrm1‐1, orrm6‐1, and orrm6‐2 alleles were genotyped with primer combinations SALK_072648LP + SALK_072648RP and SALK_072648RP + LBa1, SAIL_763_A05LP + SAIL_763_A05RP and SAIL_763_A05RP + LB3, and WiscDsLox485‐488P23LP + WiscDsLox485‐488P23RP and WiscDsLox485‐488P23LP + p745, respectively  were also affected in rip1, rip2, rip9, and oz1 mutants , RIPs/MORFs , and OZ1 . CP31A and CP31B belong to a small group of chloroplast ribonucleoproteins that contain two RRM domains  was not affected by mutations in CP31A or CP31B. Further studies are needed to identify the plastid RRM‐containing protein(s) at these plastid RNA editing sites.It remains unknown what plastid RRM‐containing protein(s) participate in RNA editing at the 11 plastid RNA editing sites that were not affected in the s Figure . Two potA.M.S., M.B.S., J.P.O., and Y.L. conducted experiments. A.M.S. analyzed data. Y.L. conceived the project, designed and supervised the experiments, and wrote the article.Table S1Click here for additional data file.Table S2Click here for additional data file.Supplementary MaterialClick here for additional data file.


Joining oligonucleotides together (ligation) is a powerful means of retrieving information from the nanoscale. To recover this information, the linkages created must be compatible with polymerases. However, enzymatic ligation is restrictive and current chemical ligation methods lack flexibility. Herein, a versatile ligation platform based on the formation of urea and squaramide artificial backbones from minimally modified 3′‐ and 5′‐amino oligonucleotides is described. One‐pot ligation gives a urea linkage with excellent read‐through speed, or a squaramide linkage that is read‐through under selective conditions. The squaramide linkage can be broken and reformed on demand, while stable pre‐activated precursor oligonucleotides expand the scope of the ligation reaction to reagent‐free, mild conditions. The utility of our system is demonstrated by replacing the enzymatically biased RNA‐to‐DNA reverse transcription step of RT‐qPCR with a rapid nucleic‐acid‐template‐dependent DNA chemical ligation system, that allows direct RNA detection. 3′‐ and 5′‐amino oligonucleotides are chemically ligated through the formation of urea and squaramide artificial backbones. The squaramide linkage can be formed in mild reagent‐free buffered conditions, read‐through accurately by specific polymerases, and even cleaved and reformed on demand. To demonstrate its utility, the RNA‐to‐DNA reverse transcription step of RT‐qPCR is replaced with squaramide chemical ligation for direct RNA detection. Oligonucleotides provide the ideal means of storing information at the molecular level. From barcoding compounds in high‐throughput drug discovery,Our inspiration came from the excellent read‐through fidelity of an artificial amide backbone,m). For the urea, CDI was used as a solid in large excess, making optimisation of the urea ligation conditions challenging as the imidazole by‐product naturally buffers the system to neutral pH.To investigate the feasibility of our ligation strategy, oligonucleotides bearing a single terminal 3′‐amino dT and 5′‐amino dT were prepared using conventional solid‐phase oligonucleotide synthetic methods and commercial resins and monomers, which provided the modified oligonucleotides in good yields and purity.m) oligonucleotide concentrations . Assembly of large nucleic acids would require annealing of multiple oligonucleotides, thus requiring the mono‐squaramide monoesters to have reasonable temperature stability. When heated for 5 min at 95 °C in standard Taq polymerase buffer , 9 % and 18 % hydrolysis of the ester was observed for 5′‐ and 3′‐activated oligonucleotides, respectively . However, decreasing the temperature  reduces the hydrolysis rates to negligible levels.Pleasingly these pre‐activated oligonucleotides were stable to hindered amines such as tris(hydroxymethyl)aminomethane (Tris) that is used in buffers, but could be inactivated in the presence of primary amines, such as ethanolamine . For assembly of larger DNA constructs, it would be necessary to have oligonucleotides with both terminal 3′‐ and 5′‐amino groups. Pre‐activation in this case should avoid cyclic oligonucleotide formation but maintain activation of both terminal amino groups, which was indeed observed . Surprisingly RNA oligonucleotides required higher squarate ester concentrations for complete pre‐activation  and Taq (exo‐) polymerases, the premise being that read‐through of the modified backbone to generate the unmodified complementary strand is rate‐determining on the amount of PCR product generated. Hence detection of PCR product at lower cycles is indicative of higher read‐through efficiency.t) comparable to that of the canonical phosphodiester linkage  and ≈14 (Taq) cycles, which is equivalent to approximately 1000 and 10 000‐fold less PCR product, respectively assuming 100 % PCR efficiency). Optimisation of the PCR buffer to remove monovalent cations improved the situation but the amount of product was still significantly lower than the control (ΔCt control‐squaramide≈10 (Taq), Supporting Information, Figure S6). Changing the polymerase enzyme, however, was the most effective solution. Remarkably, Vent (exo‐) gave comparable Ct values for control and squaramide backbones with no alteration to the buffer supplied by the manufacturer  and the recovered vectors sent for Sanger sequencing  polymerase and synthetic squaramide‐ or urea‐containing templates, cloned into a vector, and transformed into The urea linkage also displayed four other single base mismatches but these were non‐conserved and occurred greater than 10 bases away from the modification site. For the squaramide, only one C‐to‐T mismatch mutation was observed 7 bases away from the modification, suggesting the dA deletion seen by mass spectrometry could be a terminal 3′ base deletion.Squaramide‐containing oligonucleotides have been reported to be susceptible to hydrolysis during ammonia‐mediated nucleobase deprotection.Finally, to demonstrate the utility of our enzyme‐free ligation platform, we focussed on RNA detection. RT‐qPCR is the current gold‐standard for RNA detection but the methodology has several limitations: 1) the priming strategy used for RNA‐to‐cDNA conversion  primers) is known to influence the results obtained;In designing our pair of RNA‐detecting DNA oligonucleotides Figure  A, we spm to 300 pm, five‐orders of magnitude) and the ligation allowed to proceed for 15 min before analysis of the product by qPCR. Promisingly, specific RNA‐target amplification was observed, with non‐specific primer‐only amplification limiting the sensitivity of the system  was within the generally accepted criteria of 95–110 % and gave comparable results to RT‐qPCR of the same samples . With these results in hand, we sought to push the limits of the system. To reduce primer‐only amplification, heat‐activated dNTPs were used due to the lack of a commercial heat‐activated Vent (exo‐) polymerase . Furthermore, a more complex system was investigated composed of a 2664‐mer target RNA prepared through in vitro transcription that was spiked into total RNA extracted from MCF‐7 cells. The target RNA was titrated into the total RNA, enabling the determination of the dynamic range and the detection limits of the system  a urea linkage that multiple polymerases can read‐through with excellent speed, or 2) a squaramide linkage whose formation can be reversed and offers accurate read‐through under selective conditions. For the latter, the linkage can also be formed from stable pre‐activated intermediates in mild buffered conditions in the absence of small‐molecule reagents. The diversity of this platform lends itself to many applications including DNA‐encoded libraries,The authors declare no conflict of interest.As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.SupplementaryClick here for additional data file.


The problem of treating viral infections is extremely relevant due to both the emergence of new viral diseases and to the low effectiveness of existing approaches to the treatment of known viral infections. This review focuses on the application of porphyrin, chlorin, and phthalocyanine series for combating viral infections by chemical and photochemical inactivation methods. The purpose of this review paper is to summarize the main approaches developed to date in the chemical and photodynamic inactivation of human and animal viruses using porphyrins and their analogues and to analyze and discuss the information on viral targets and antiviral activity of porphyrins, chlorins, of their conjugates with organic/inorganic compounds obtained in the last 10–15 years in order to identify the most promising areas. Over the past decades, the onset of epidemics and pandemics caused by SARS viruses , swine flu , bird flu , the Middle East virus (MERS-CoV 2013–2015), the Ebola virus 2014–2015), and the SARS-CoV-2 coronavirus conditioned the need to consider a healthcare system not only as a public sector organizing and protecting the health of the population of a particular country but also as a global international task. Change of priorities for threat evaluation takes place throughout a civilized society. The reason for this is the emergence of new viral infections that cause epidemics and pandemics, as well as the existence of drug-resistant infections, which are increasing each year -4-pyridiniumyl) porphyrin, tetrakis(N-[n-octyl]-4-pyridiniumyl) porphyrin, and anionic porphyrins (tetrakis(4-sulfonatophenyl) porphyrin) were evaluated as potential drugs for inactivation of nonenveloped viruses (hepatitis A virus and bacteriophage MS2). The authors set themselves the task of determining the effect of the charge and hydrophobicity of the P&A on its virucidal activity , b, b64], bThe way of linking porphyrins with DNA depends on the nature of the peripheral substituents of the P&A, on the metal of the complexing agent, the type of DNA ,66,67, eWhen changing the composition of the medium or the molar ratio R , the internal complex can transform into the external ,67,71. AThe thermodynamic stability of the complexes of P&A with DNA depends not only on the nature of P&A but also on the type of complex formed . This coAs our own  and lite1) are susceptible to oxidative damage, resulting in the formation of 8-oxo-7,8-dihydroguanine (2), one of the main products of type I photosensitized oxidation.In particular, the guanine fragments (N-methyl-3-pyridyl)porphin (TMPyP3) and TMPyP4 and is accompanied by photolysis of porphyrin (TMPyP3).The result of photoirradiation of complexes of P&A with DNA substantially depends on the type of complex being formed. For example, in , it was meso-tri-(4-N-methylpyridyl) monophenylporphyrin (TMPyMPP) to DNA is not a prerequisite for photoinactivation. The authors of [According to the researchers , the binthors of  considerthors of . This cothors of  inversiothors of . Having thors of . It is pthors of  by the eIn addition to the type of complex formed, an important influence is exerted by the intensity and duration of irradiation—these conditions are described in detail in the review .Prevention of viral replication and reduction of virulence after DNA damage by active oxygen forms, generated by the P&A, was shown in ,32,75,80In terms of targeting, RNA has many attractive properties similar to those of DNA and/or proteins. Both forms of nucleic acids take a regular helix with large and small grooves. However, the usual helix of the A-form of RNA is often disturbed by regions of inappropriate or unpaired bases; they lead to a change in the secondary structure of RNA .Compared with the small and large grooves of DNA, these structural motifs in RNA are much smaller, since the pitch of the helix and the inclination of the bases are smaller. According to ,84, the The first publication on the interaction of cationic TMPyP4 porphyrin with RNA duplexes dates back to 1997 . A similA series of works is devoted to MD modelling of the binding of TMPyP4 to RNA and oligonucleotides ,89, the The effect of the modification of the cationic porphyrin substituent  on the bTEtOHPyP4 and TAlPyP4 intercalate into duplexes poly(rA) poly(rU) and poly(rI) poly(rC), whereas TMetAlPyP4 binds to these RNA duplexes, forming an external complex with self-stacking . It is nAs a rule, P&A compounds form not very strong complexes with RNA due to structural factors, therefore, chemotherapeutic agents for the inactivation of RNA viruses have not yet been proposed. On the other hand, there remains the possibility of photoinduced inactivation of RNA viruses at the stage of transcription and replication of the viral genome. As shown above, in the case of DNA, all four bases are oxidized, but guanine is the most susceptible; it produces 8-oxo-7,8-dihydro-2′-deoxyguanosine under the influence of singlet oxygen. It is this compound that is often used as a marker of oxidative damage in DNA . In the meso-tetrakis(4-N-methylpyridyl)porphin, meso-tetrakis(para-N-trimethylanilinium)porphin, and meso-tetrakis(2-N-methylpyridyl) porphin and RNA and complexes of porphyrins with elements of the secondary structure of RNA [1O2 with viral RNA leads to the modification of nucleosides in the region of localization of porphyrins  in a modular manner to recognize predetermined DNA sequences with affinity and specificity comparable to DNA-binding proteins. The presence of such a peripheral substituent in the P&A can solve the problem of precise targeting of viral DNA.Perhaps, the solution to this problem is not far off. A chemical approach to DNA recognition  based onAnother possible solution to the problem of selectivity for targeting the P&A to the viral genome is to accurately target the sections of the genetic material of viruses, such as, e.g., G-quadruplexes. Guanine-rich RNA or DNA sequences are capable of folding and accepting four strands, called G-quadruplexes or “G4” E. UniqueN-methyl-2-pyridyl)porphin) (TMPyP2) were proposed as a complexing compound for G4 of a number of viruses [G4 structures are widely represented in the human genome, especially in telomeres and oncogenic promoters. In recent years, the presence of G4s in viruses has attracted increasing interest. G-quadruplexes were found in several viruses, including those associated with recent epidemics, such as Zika and Ebola viruses, SARS, and COVID-19 . Viral G viruses . TMPyP4  viruses  in inact viruses . It is i viruses . It is n viruses , but it The cationic porphyrins TMPyP2, TMPyP3, and TMPyP4 were considered as potential binding agents for Epstein–Barr virus G-quadruplex RNA. It turned out that TMPyP3 and TMPyP4 form a stable complex with G regions of the virus genome, and it does not allow to encode the EBNA1 protein, which is crucial for replication and maintenance of the genome during latency in proliferating cells .In numerous studies, it was shown that cationic porphyrins containing peripheral charged substituents in the para position, as a rule, demonstrate greater efficiency compared to both the ortho- and metaisomers. In this sense, the approach of the authors  comparinTMPyP4 was also used to study the role of G4s in EBOLA virus replication . For thiIf we compare the affinity of TMPyP4 with respect to G4-structures and duplex DNA, then it will be lower , respectIt is quite remarkable that in the vast majority of works on the inactivation of viruses, cationic porphyrins are considered as a binding agent for G-quadruplex structures. Although, as shown in , anionicAnd if the issue of the selectivity of virus inactivation in living organisms remains open, then one can definitely say that recently successful attempts have been made to use P&A to reduce the transmission of pathogenic microorganisms during blood transfusion. Viral infections, the potential risk of their transmission, narrowly targeted viral tests, and the lack of adequate and systematic screening for the virus and bacteria in the blood and red blood cells make the problem of increasing blood products safety very urgent. Impressive results were demonstrated by the authors of  by the eTrans-P(4) < Cis-P(4) < TMPyP4 < Mono-P(4). Moreover, the last three porphyrins caused the maximum destruction of red blood cells. Obviously, in addition to the photochemical properties of the photosensitizer, penetration (through the lipid membrane) and binding to RNA are significant.The most effective photosensitizer from the tested series, which at the same time maintained the integrity of red blood cells, was Tri-P (4). It caused the least hemolysis under conditions that led to a 5-fold decrease in the extracellular virus of vesicular stomatitis. All positively charged tested porphyrins were able to inactivate the extracellular virus of vesicular stomatitis, but caused a violation of the integrity of red blood cells during storage. Vesicular stomatitis virus is a single-stranded lipid RNA virus. Unfortunately, the authors did not advance in the analysis of the “structure (porphyrin)-property ,” but they only suggested that the cause is the interaction of porphyrins with RNA. Judging by the data presented , the virIn conclusion, we would like to note that the chemo- and photoinactivation of P&A in viruses is very promising and can become an alternative and highly effective way to treat viral infections. To increase the selectivity of the action of P&A on viral targets, a targeted modification of the structure of P&A is necessary. The complexity and versatility of the objects of research emphasize the need to combine the efforts of chemists, microbiologists, and virologists.


Self-rated health (SRH) is one of the most frequently used indicators in health and social research. Its robust association with mortality in very different populations implies that it is a comprehensive measure of health status and may even reflect the condition of the human organism beyond clinical diagnoses. Yet the biological basis of SRH is poorly understood. We used data from three independent European population samples  to investigate the associations of SRH with 150 biomolecules in blood or urine (biomarkers). Altogether 57 biomarkers representing different organ systems were associated with SRH. In almost half of the cases the association was independent of disease and physical functioning. Biomarkers weakened but did not remove the association between SRH and mortality. We propose three potential pathways through which biomarkers may be incorporated into an individual’s subjective health assessment, including (1) their role in clinical diseases; (2) their association with health-related lifestyles; and (3) their potential to stimulate physical sensations through interoceptive mechanisms. Our findings indicate that SRH has a solid biological basis and it is a valid but non-specific indicator of the biological condition of the human organism. In many studies SRH remains a significant predictor of mortality after adjustment for several other health indicators2. However, the wider the array of objectively measured health variables, the weaker is the independent predictive power of SRH4. Therefore it is plausible that the association between SRH and mortality is not causal but is due to the ability of the self-assessment to more exhaustively capture the realm of `health` and the objective bodily condition than most other health indicators5.Self-rated health (SRH) is one of the most frequently used measures in epidemiological, clinical and social research. It is known to predict mortality, future functional status and outcome of treatment in populations that vary by age, gender, social class, health status, country and culture1, but also experienced symptoms, medication and other signs of health problems, and particularly in the absence of any evident health problems, different health-related lifestyles and risk factors6.Jylhä (2009) has suggested that when asked to evaluate their general health status, respondents will take into account any individual relevant information that they think describes their “health”. This information is then considered in the context of the social and psychological situation. Empirical studies show that individuals will mainly take into account their medical diagnoses and functional status3, HDL cholesterol9, leptin10, TNF-α and IL-1ra11, CD19+ cells and IgG12, CRP15, IL-617, fasting plasma glucose and glycosylated haemoglobin18 and vitamin D20. The findings are fragmented, however, as each study usually addresses only a few indicators. Furthermore, most samples have been small, and in many cases other health data have been less than optimal. At least in part, these associations probably reflect the severity and symptoms of chronic diseases. Yet it is possible to hypothesize that the level of and changes in some biomarkers may, through interoceptive processes, be associated with sensations and symptoms that individuals take into account in their self-ratings of health. Overall, little is known about the experiential counterparts of variations in blood biochemistry, although the connections of fatigue with peripheral inflammation for example, are well described22.A number of studies have found associations between SRH and biomarker levels (i.e. quantities of biomolecules) in blood, such as white cell count, albumin and haemoglobinIn order to understand the potential of SRH as a measure of health in clinical practice and research, it is important to know how accurately SRH reflects the condition of the human body. In the present explorative study, we investigated the associations of SRH with a wide array of biomolecule levels measured in blood and urine. These biomarkers provide more detailed information about the condition of the human body than diagnostic names alone as they can reflect the stage and severity of current pathologies as well as the physiological processes taking place in individuals without clinical diagnoses. We hypothesize that the possible association between SRH and biomarkers is largely, but not entirely, explained by diseases and physical functioning, which at least to some extent reflects the severity of diseases. We also hypothesize that the association of SRH and mortality is partly explained by the measured biomarkers. We addressed the following questions: (i) to what extent are the biomarkers available in the study associated with SRH; (ii) to what extent are the associations between biomarkers and SRH explained by disease diagnoses and physical functioning; and (iii) do the biomarkers associated with SRH explain part of the association between SRH and mortality? Analyses i) and iii) were also performed for individuals without diagnosed diseases. We used three extensive population-based data sets: MARK-AGE, the Copenhagen Aging and Midlife Biobank (CAMB), and Health 2000, covering a total of approx. 15,000 individuals and 150 biomarkers.p < 0.001).In MARK-AGE n = 3,187) 12% rated their health as excellent, 35% as very good, 41% as good, 11% as fair and 1.4% as poor. In CAMB  the figures were 9.1%, 41%, 40%, 8.6% and 1.4%, respectively. In Health 2000  32% rated their health as good, 30% as rather good, 27% as moderate, 8% as rather poor and 3.5% as poor. Table 87 12% raOut of the 150 biomarkers investigated Fig.  and S2, When additionally adjusted for number of diseases and physical functioning (model ii), 26 biomarkers were still associated with SRH. Seven of these biomarkers were available in two or three data sets Table . A schemAs examples of replicated and new findings representing different biological domains, Fig. In the Health 2000 data the association between SRH and mortality (iii) was analysed using Cox regression analysis. Out of 5,957 participants with a full set of data for relevant variables, 1,207 (20%) died between 2000 and 2015. The average survival time for the deceased participants was 8.1 (SD 4.2) years.A graded relationship was found between SRH and mortality in models adjusting for age and gender, and then additionally for diseases Fig. . In the p < 0.05 in all data sets ) and 8 biomarkers that were available in one data set  were significantly associated with SRH . Descriptive statistics for these participants are shown in Supplementary information 2: Table For the subsample of individuals without diagnoses n = 2,408) in the Health 2000 data, the association between SRH and mortality was analysed using Cox regression analysis. During the 15-year follow-up the number of deaths was 193 (8%), and average survival time for the deceased participants in this sample was 9.2 (SD 4.0) years. In this subsample SRH was a significant dose-responsive predictor of mortality , lipid and glucose metabolisms (e.g. cholesterol and HbA1C), oxidative stress (e.g. protein carbonyls) and tissue damage (cell-free DNA), as well as of lifestyles and environmental exposures . Many of the biomarkers associated with SRH are also known to be biomarkers of ageing15. A few studies have also reported an association between poorer SRH and lower HDL cholesterol9 and higher HbA1C18 levels. In our study lower vitamin D level was associated with poorer SRH in both data sets where it was available, and a similar, strong association was also seen among individuals without chronic conditions. Previous studies with smaller samples have likewise shown an association between vitamin D and SRH20. Recent studies have connected low vitamin D concentration with multiple extra-skeletal processes such as cancer progression, coronary heart disease, depression and a range of immune functions26. The mechanisms of these associations are not well known, but it has been suggested that low vitamin D level should be understood as a marker of ill health rather than a causal factor28.When selected biomarkers—CRP, HDL cholesterol, HbA1C, 25-hydroxyl-vitamin-D, zeaxanthin, apolipoprotein-B, cell-free DNA and protein carbonyls—were picked up as examples and examined as quartiles, poorer biomarker levels were fairly constantly associated with higher odds for poorer SRH in all data sets  as well as cardiovascular diseases and cancer30. Apolipoprotein B is mostly known as the LDL carrier protein, and it is an important contributor to atherosclerosis and cardiovascular disease31. Circulating cell-free DNA is a marker of cellular death and tissue damage in many acute and chronic conditions 37. Elevated levels of protein carbonyls (i.e. plasma protein oxidation levels) are a marker of oxidative stress and observed in various pathologies such as Alzheimer’s disease, rheumatoid arthritis, diabetes, sepsis, renal dysfunction and respiratory failure38.This is the first study to report associations between SRH and e.g. zeaxanthin, apolipoprotein-B, cell-free DNA and protein carbonyls. Zeaxanthin is a carotenoid pigment present in the eye and obtained from the diet (e.g. egg yolk and orange peppers)We suggest that there are three main pathways through which biomarkers measured in blood or urine can affect SRH. First, several biomarkers are characteristics of clinical diagnoses. For certain biomarkers such as cholesterol or glucose levels the role is well-known as is their significance as risk factors of disease. Individuals who are asked to rate their own health may be inclined to interpret high values (if they know them) as signs of poorer health. Yet respondents may not necessarily consider their biomarker levels or even be aware of them when asked to assess their health, but instead consider their disease diagnoses, symptoms or decreased physical functioning caused by their diseases. In this case the association between biomarkers and SRH is indirect and mediated by the association of SRH with diseases known to the respondents. This hypothesis for disease pathway is supported by the finding that associations between biomarkers and SRH were more marked among individuals with disease than those without.39. In the present study better SRH was associated with higher levels of carotenoids  in plasma, and hippurate and trigonelline in urine. These molecules serve as markers of fruit and vegetable intake. Worse SRH was associated with higher cotinine and gamma-glutamyltransferase levels, which serve as markers for smoking exposure and alcohol consumption, respectively. Again it is plausible that the route from biomarkers to SRH is indirect, i.e. that respondents assess their health as good or poor not on the basis of their biomarker levels but rather particular health-related lifestyles that are considered healthy or unhealthy.Second, it is known that particularly individuals without major health problems take account of health-related lifestyles and behavioural risk factors as components of SRH41. Since these studies, research has continued to accumulate about the interoceptive processes through which information on internal states of the body is communicated to the brain to enable the regulation of vital inner processes and the maintenance of physiological stability44.Most of the research data on interoceptive signalling of humoral processes, i.e. changes in blood substance levels, concerns inflammation: higher circulating levels of inflammatory biomarkers, cytokines, are known to underlie symptoms such as fatigue, general malaise, poor appetite and low mood22, and they are known to be associated with poor SRH46. In our study, higher levels of inflammatory markers such as CRP and IL-18 showed associations with poor SRH, and for CRP this was true in all three data sets independently of diseases and physical functioning. Yet the empirical evidence on interoceptive signalling of humoral processes remains haphazard and for other blood-measured substances than inflammatory markers almost non-existent.Third, an interesting but poorly understood mechanism is the possibility that a biomarker level or change in biomarker level in the body might stimulate physical sensations, and that these sensations are interpreted as information about the state of one’s health. This is not a novel hypothesis but was suggested by Stenback as early as 1964 and later by Kaplan and Camacho in 1983 as one potential explanation for the association between SRH and mortalityIn our study, as in many previous ones, SRH showed a strong, robust association with mortality. Poorer SRH predicted mortality even after adjusting for chronic conditions in the total sample and in the subsample without chronic conditions. Adjusting for biomarkers weakened this association in both situations, which supports our initial hypothesis.49. In our analysis, the six clinical diagnoses available for analysis in the three study samples were common and chronic. However, several important diagnostic categories were absent from our analysis, and we had no information on disease severity other than physical functioning. Therefore, the data available was not ideal to adjust for disease. These are the major limitations of the study. In our exploratory analyses, linear regression models were used to provide an easily understandable overview on the associations of SRH, basically an ordinal variable, with biomarkers; this approach is consistent with several earlier studies, and based on observed continuity in its association with many other health variables. Further, because of the explorative approach, we decided not to construct organ-specific or cluster-based groupings of the biomarkers, and as the role of individual biomarkers in connection to SRH is not known, we decided to include all available measures in our analyses without selection. The mechanisms linking biomarkers with SRH were also beyond the scope of this study. Further studies are needed to shed light on the full pathways between SRH and the biological state of the body.We were able to utilize three large population-based data sets from multiple European countries, but, unfortunately, not all biomarkers were available in more than one data set, which would allowed the principles of conventional replication studies. For some of the biomarkers investigated the association with SRH had already been reported earlier. The strengths of our study included the fact that we had access to a large number of new biomarkers; that several of them were available in more than one data set; that we had access to data on chronic conditions and physical functioning; and that in one sample it was also possible to investigate mortality. Multimorbidity indicated by the number of disease diagnoses is an effective descriptive of health and has prognostic valueIn conclusion, our study demonstrated strong and logical associations of SRH with numerous biomarkers measured in blood and urine, even independently of chronic diseases and functional status. Poorer SRH was associated with worse biomarker levels and vice versa. These biomarkers were descriptive of many different organ systems and bodily processes. The findings suggest that SRH has a solid biological basis. Our results also lend support to the notion that SRH is a robust, comprehensive but non-specific indicator that can more exhaustively capture health-related processes than many conventional measures of health and disease. To verify the potential of SRH in research and in clinical practice, multidisciplinary research is needed to explore the mechanisms that convey messages from body biology to individuals’ subjective assessments.MARK-AGE, questionnaires and interviews were conducted and biological data collected between 2008 and 2012 at the following recruiting centres: Hall in Tyrol/Innsbruck (Austria), Namur (Belgium), Esslingen (Germany), Athens and surrounding regions (Greece), Bologna , Warsaw (Poland), Tampere (Finland) and Leiden (The Netherlands)51. The total number of participants in this analysis was 3,187 (age range 18–92 years).In CAMB collected questionnaire data and biological samples from 5,335 participants (age range 48–62 years) in 2009–2011. This data set comprises participants from three cohort studies: the Metropolit 1953 Danish Male Birth Cohort (MP), the Copenhagen Perinatal Cohort (CPC) born in 1959–1961, and the Danish Longitudinal Study on Work, Unemployment and Health (DALWUH) born in 1949 or 195952.Health 2000 is a nationwide survey conducted in 2000–2001 with a randomly selected sample  of the Finnish population aged 30 years or over53. For this analysis we used a subsample of 6,444 participants (age range 30– 99 years) with relevant information.No human participants were directly involved in the current study and only data was taken for the current study.SRH was assessed in interviews and questionnaires. In MARK-AGE and CAMB, SRH was inquired by asking: “In general, would you say your health is…?”; and in Health 2000 by asking: “Is your present state of health…?”. The response options were “poor”, “fair”, “good”, “very good” or “excellent” (CAMB and MARK-AGE) and “poor”, “rather poor”, “moderate”, “rather good” or “good” . In linear regression models, SRH was used as a continuous variable ranging from 0 to 4, with a higher value referring to poorer SRH. For the other analyses, the two poorest SRH categories  were combined into one. Then, as an outcome in logistic regression analyses , 0.25 mile (in CAMB) or 0.5 km ; (2) ability to run 100 m  or do vigorous activities such as running, lifting heavy objects, participating in strenuous sports (in MARK-AGE); and (3) hand grip strength . In each of these three components, more points corresponded to poorer functioning. The components of walking and running & vigorous activities were scored as 0 = no limitations, 1 = moderate limitations and 2 = highly limited or cannot do at all. Hand grip strength was grouped in tertiles . The scores from the three components were added together to obtain a sum score of physical functioning, ranging from 0 to 6.The indicator of physical functioning came from interviews, questionnaires and hand grip strength measurements. A summary variable for physical functioning was constructed out of three components: (1) Disease diagnoses, including cardiovascular diseases, hypertension, diabetes, cancer/tumour, respiratory diseases and arthritis were obtained from interview and questionnaire data. The variable “number of diseases” ranged from 0 to 6 diseases, but in the final analyses it was categorized as 0, 1, 2, 3 or 4 + diseases. In addition, subsamples with participants without any of the above mentioned diagnoses were extracted in each data set . SRH was the dependent variable, and the models were adjusted for (i) age as a continuous variable and gender, and (ii) additionally for the number of diseases and physical functioning. All MARK-AGE analyses were adjusted for recruitment centre. The nominal p-value threshold was set at 0.05 for biomarkers that were available in two or three data sets , and, to control the multiple testing problem, at Bonferroni-adjusted p-value of 0.05 for biomarkers that were available in one data set only. Additionally, logistic regression models were used to analyse the associations of eight selected biomarkers, categorized as quartiles, with poor SRH, adjusted for age and gender. The results of the eight selected biomarkers were visualized as forest plots . 1) The model was adjusted for (1) age and gender; (2) additionally for number of diseases; and 3) furthermore additionally for the biomarkers that were associated with SRH in the linear regression analysis (Model ii). The nominal p-value threshold was set at 0.05. These results were visualized as forest plot  and IBM SPSS software version 24.0 . In each model, participants with missing data for a biomarker, mortality, age, gender, SRH, physical functioning or number of diseases were excluded from the analyses.53.Human participants were not directly involved in the current study and only existing data was taken for the current analysis. The study was conducted in accordance with the Declaration of Helsinki ethical principles and all research participants gave their informed consent to be part of the study. The studies  were approved by the local ethics committeesSupplementary Information 1.Supplementary Information 2.Supplementary Information 3.


Drosophila, DNA elements termed Polycomb Response Elements (PREs) recruit PcG proteins. How PcG activities are targeted to PREs to maintain repressed states only in appropriate developmental contexts has been difficult to elucidate. PcG complexes modify chromatin, but also interact with both RNA and DNA, and RNA is implicated in PcG targeting and function. Here we show that R-loops form at many PREs in Drosophila embryos, and correlate with repressive states. In vitro, both PRC1 and PRC2 can recognize R-loops and open DNA bubbles. Unexpectedly, we find that PRC2 drives formation of RNA-DNA hybrids, the key component of R-loops, from RNA and dsDNA. Our results identify R-loop formation as a feature of Drosophila PREs that can be recognized by PcG complexes, and RNA-DNA strand exchange as a PRC2 activity that could contribute to R-loop formation.Polycomb Group (PcG) proteins form memory of transient transcriptional repression that is necessary for development. In  RNA is implicated in the targeting and function of Polycomb Group (PcG) chromatin regulators. Here the authors show that R-loops, three-stranded nucleic acid structures formed by DNA and RNA, are formed at some PcG binding sites in flies, as they are in mammals. Fly PRC2 can drive formation of RNA-DNA hybrids in vitro. Drosophila embryogenesis, transiently expressed transcription factors activate homeotic (Hox) genes in certain regions of the embryo and repress them in others to dictate the future body plan1. Polycomb Group (PcG) proteins form a memory of these early cues by maintaining patterns of Hox gene repression for the rest of development3. This paradigm for transcriptional memory is believed to be used by the PcG at many genes in Drosophila, and to underlie the conserved and essential functions of PcG proteins in cell differentiation and development from plants to mammals5. Polycomb response elements (PREs) are DNA elements that can recruit PcG proteins, but they also recapitulate the memory function of the PcG—when combined with early acting, region-specific enhancers in transgenes, they maintain transgene repression in a PcG-dependent manner only in regions where the early enhancer was not active7. PREs contain a high density of binding sites for transcription factors that can recruit PcG proteins through physical interactions7. However, the widespread expression, binding pattern, and properties of factors that bind PREs cannot explain how PREs can exist in alternate, transcription-history dependent states to maintain restricted patterns of gene expression, or how they can switch between states2. Furthermore, DNA sequences with PRE-like properties have been difficult to identify in other species9 despite the conservation of PcG complexes, their biochemical activities, and their critical roles in development.During 11. Both the direction and level of transcription have been correlated with the functional state of PREs12. The PcG complex Polycomb Repressive Complex 2 (PRC2) has a well-described high affinity for RNA17. RNA is suggested to recruit PRC2 to specific chromatin sites13, but RNA binding can also compete for chromatin binding and inhibit PRC2 activity20. One way for RNA to interact with the genome is by the formation of R-loops, three-stranded nucleic acid structures formed when an RNA hybridizes to a complementary DNA strand, thereby displacing the second DNA strand21. R-loops have been linked to regulation of transcription and chromatin previously, through a variety of mechanisms (reviewed in refs. 23). This includes links to PcG regulation in mammalian cells. The formation of R-loops over genes with low to moderate expression is associated with increased PcG binding and H3K27 trimethylation (H3K27me3) in human cells24 and R-loops have recently been implicated in promoting PRC1 and PRC2 recruitment in mammalian cells25, although other evidence suggests they antagonize recruitment of PRC226. We hypothesized that R-loop formation could biochemically link RNA to PcG-mediated silencing through PREs and tested this idea in the Drosophila system.RNAs may provide context specificity to PcG protein recruitment and function. Some PREs, and some PcG-binding sites in mammalian and plant cells, are transcribed into ncRNA, while others reside in gene bodies, and thus are transcribed when the gene is expressedDrosophila embryos and S2 cells and observe that ~25% of PREs form R-loops. Interestingly, PREs that form R-loops are more likely to be bound by PcG proteins compared with PREs that do not form R-loops, suggesting that R-loops may be involved in PcG targeting. In vitro, PRC1 and PRC2 recognize R-loops and open DNA-bubbles. Further, when provided dsDNA and RNA, PRC2 induces the formation of RNA–DNA hybrids, the key components of R-loops. These data suggest a mechanism for RNA to contribute to targeting of PcG proteins via R-loop formation induced by the RNA-DNA strand exchange activity of PRC2.Here, we identify R-loop forming sequencing in DNA-RNA Immunoprecipitation followed by next generation sequencing (DRIP-seq) in Drosophila embryos (2–6 and 10–14 hour (H)) and in S2 cells .To test whether R-loops are related to the functional state of PREs, we used publicly available ChIP-seq datasets to compare PcG protein binding over PREs as a function of R-loop formation in each of our three samples. For each PcG protein tested, the median read density for PcG proteins was higher over PREs with R-loops than that over PREs without R-loops Fig. . The binops Fig. . H3K27Acops Fig. . A smallops Fig. , suggestops Fig. ; these P25 so that we wondered if either complex might recognize R-loops. To measure the relative affinities of PRC1 and PRC2 for different nucleic acid substrates, we prepared dsDNA, R-loop or open DNA bubble templates from synthetic oligonucleotides corresponding to a sequence in the vestigial (vg) PRE , which would be visible by electron microscopy (EM) Fig. . We incuFinally, to functionally test whether PRC2 nuclease contaminants in PRC2 could account for RNA–DNA hybrid formation, we pre-treated DNA templates with PRC2, and used them in RNA–DNA hybrid forming assays in the presence or absence of PRC2 Fig. . If nuclTo determine the DNA and RNA substrate requirements for RNA–DNA strand exchange, we tested DNA templates with different ends (4 or 2 base pair (bp) 5′ or 4 bp 3′ overhangs, or blunt ends), prepared by digestion with different restriction enzymes. In all cases, the RNAs used overlap the end of the DNA Fig. . SimilarThe above experiments suggested that the overlap of the RNA with the ends of the dsDNA is important for PRC2-mediated RNA–DNA strand exchange. To further analyze this, we digested DNA templates with EcoRI such that the resulting products have eight non-complementary bases prior to the start of the RNA on the bottom DNA strand, and four on the top strand Fig. . For eac35, while functional assays are consistent with a single binding site that can bind chromatin, DNA or RNA, but has highest affinity for RNA so that RNA can compete for binding to DNA or chromatin18. To understand the role of RNA and DNA interactions in PRC2-mediated RNA–DNA strand exchange, we titrated each substrate and changed the order of addition in the reaction. Addition of RNA prior to DNA inhibited the reaction at low concentrations of PRC2. RNA–DNA strand exchange increased with increasing RNA concentration and decreased with increasing DNA concentration  and its retention on chromatin. PRC2 could then modify histones to maintain a repressive chromatin state  identified the gene for RNaseH140. RNA has been suggested to be important in switching PREs between OFF and ON states42, although this has been contested by experiments aiming to test whether transcription through a PRE can switch it to the active state44. Resolution of R-loops by cellular RNases or RNA–DNA helicases could contribute to switching PRE states, which will be intriguing to test. It is also likely that even in the simple model suggested in Fig. Observations in R-loop formation is observed at ~30% of PREs; these may represent a specific class of PREs. Most R-loops are believed to form co-transcriptionally, so that R-loops would be predicted to depend on PRE transcription. Indeed, >70% of R-loops formed at PREs overlap an annotated coding or non-coding RNA, and PREs with R-loops are more likely to have RNA Pol II signal in ChIP-seq experiments. However, ~67% of PREs where we did not observe R-loops also overlap an annotated transcript. Further, a fraction of PREs with R-loops  either do not overlap any annotated transcripts, or overlap a transcript in the opposite orientation as the R-loop. While some of these discrepancies likely reflect incomplete annotation of rare transcripts, they raise the intriguing possibility that the RNA used to form the R-loops could be supplied in trans. Careful analysis of the RNA component of R-loops at PREs will be needed to resolve this. Although speculative at this time, the ability of PRC2 to induce RNA–DNA hybrids could contribute to non-co-transcriptional R-loop formation.48 and PALB249, the human capping enzyme (CE)50, the viral protein ICP851 and the telomere-inding protein TRF252. Like the activity of PRC2, none of these reactions require ATP hydrolysis , and most use linear DNA substrates50 or an unpaired or ssDNA region48. The exceptions are TRF2 and ICP8. ICP8 can mediate R-loop formation from an RNA and a supercoiled plasmid51. TRF2 stimulates invasion of RNA oligos into a supercoiled plasmid encoding a telomeric DNA array52, but the mechanism is believed to be induction of positive supercoiling by TRF2 that facilitates DNA unwinding and RNA invasion53. RNA–DNA strand exchange has been investigated most closely for Rad52, and its homologue RecA48. Rad52 has been shown both to carry out “inverse strand exchange” where Rad52 first binds the dsDNA, allowing RNA strand exchange46, and to use an RNA-bridging mechanism, in which Rad52 first binds the RNA, and can bridge two dsDNA fragments by forming RNA–DNA hybrids with segments of each of them47. Both of these mechanisms are candidates to mediate RNA-mediated repair of DSBs47. PRC2 requires a DNA end for RNA–DNA strand exchange in vitro; for this activity to occur in vivo, either a DNA break would be required, or PRC2 would need to be able to use DNA opened by (an)other factors, or by transcription. These requirements may limit PRC2 strand exchange activity at PREs. In order to fully understand the impact of this activity in vivo and to what extent PRC2 contributes to R-loop formation at PREs, additional experiments will be necessary. Interestingly, Topoisomerase II interacts with a subunit of PRC1, colocalizes with PcG proteins in the BX-C, and is implicated in PRE-mediated silencing54; transient Topo II induced breaks have been implicated in regulation of transcription and chromatin compaction56, and could also be used by PRC2. It is also possible that the activity of PRC2 contributes to RNA–DNA strand exchange at DNA breaks where RNA–DNA hybrids have been shown to form57 and where PRC2 is recruited59.We find that PRC2 can induce RNA–DNA strand exchange from RNA and linear dsDNA in vitro. A small number of other proteins have been shown to have similar activity, using various types of substrates. These include the repair proteins Rad52/RecA60, but mechanisms beyond RNA binding by PRC2 have not previously been described. Our discovery of PRC2-mediated RNA–DNA strand exchange, suggests one mechanism to connect RNA to PcG targeting and function.The connection between RNA and PRC2 has been recognized for some time, in species from plants to humansDrosophila S2 cells were purchased from Invitrogen, and grown in Schneider’s media (Invitrogen) with 10% heat inactivated, insect cell tested FBS (Invitrogen). Cells were cultured at 27 °C in suspension in shaking flasks.2O and stored at −80 °C.Oregon R flies were grown at 25 °C. Embryos were collected on apple juice places and dechorionated for 2 min in 50% bleach before being washed with H7 S2 cells were washed with 1× PBS and resuspended in 10 mL TE. Cells were lysed O.N. at 37 °C in presence of 0.5% SDS and 62.5 µg/mL of proteinase K. After phenol-chloroform-isoamyl acohol extraction, total nucleic acids were precipitated in the presence of 0.3 M sodium acetate pH 5.2 and 2.4 volume of 100% ethanol. Nucleic acids were washed carefully five times with 70% ethanol, and resuspended in TE.8 × 1061 with the omission of RNaseA. After precipitation the nucleic acids were washed carefully five times with 70% ethanol, and resuspended in TE. This material was subsequently processed for DRIP analysis as described below.Total nucleic acids were extracted from 500 µL of Oregon R embryos as described in Ejsmont et al.62. Five hundred micrograms of total nucleic acid were divided in 3 and each treated with 150 µg of RNaseA in presence of 0.5 M NaCl for 3 h at 37 °C. gDNA was purified by phenol-chloroform extraction followed by ethanol precipitation and sonicated to 300 bp using a Covaris. Fragmented gDNA was treated with 2 U of RNaseIII27 (Thermo Fisher) +/−10 µg each of homemade RNaseH I and RNaseH II overnight at 37 °C. Immunoprecipitation was performed as described in Ginno et al.62. After elution, samples were purified with a PCR clean-up column (Macherey-Nagel) with NTB buffer to get rid of SDS followed by a DNA clean and concentrator column (Zymo Research). For sequencing library preparation, material from three immunoprecipitations were pooled. Libraries were prepared using the NEB next Ultra II kit for a directional library for Illumina (NEB). For strand specific DNA sequencing of the RNA–DNA hybrids, we started at the second strand synthesis step and ligated with NEB-next multiplex oligonucleotides for Illumina (NEB). Paired-end sequencing was performed on an Illumina HiSeq 2500 at Genome Quebec.The DRIP protocol was adapted from Ginno et al.2 values of 0.9 or higher. Oligonucleotides used for qPCR63 are list listed in Supplementary Table For qPCR, input was diluted 10-fold and IPs twofold in water. PCR was carried out in 5 µl reactions consisting of 2 µl DNA, 2.5 µl PowerUp SYBR Green master mix (Thermo Fisher) and 0.25 µl of a 1 µM stock of each primer diluted in water. Standard curves were generated using a log titration of Drosophila genomic DNA purified from S2 cells (25 to 0.025 ng). Data were collected using a Viaa7 PCR system (Thermo Fisher) with 40 cycles. The standard curve was used to calculate DNA amounts. All standard curves had R64. Reads with both mate pairs were aligned to the dm3 version of the Drosophila genome using Bowtie2/2.3.165. Sam files generated by Bowtie2 were converted to bam, sorted and indexed (samtools (v. 1.4.1)66 and Picard (http://broadinstitute.github.io/picard) MarkDuplicates (default parameters) was used to remove duplicates. To generate strand specific bam files, samtools was used as follows:FastQ files of DRIP-seq reads were trimmed with Trimmomatic (PE –phred33), using the GenPpipes ChIP-seq pipeline (steps 1–3)Forward strand: samtools view –f 99; samtools view –f 147, followed by samtools merge.Reverse strand: samtools view –f 83; samtools view –f 163, followed by samtools merge.67 (v. 2.1.1) (-f BAMPE –bw 250 -g dm –mfold 10 30 -q 0.01). For strand specific peaks, strand specific files were used . Peaks present in both DRIP vs. input and DRIP vs. RNaseH were retained (BEDTools intersect)68 for each duplicate. Finally, BEDTools (intersect) was used to retain only peaks present in both duplicates, which were used for further analysis. The correlation between the replicates was examined using multiBigwigSummary on Galaxy (bin size: 1000 bp) followed by plotCorrelation using the Pearson correlation method. Correlations for replicates were: 2–6H 0.97, 10–14H 0.87, S2 0.99. Bigwig files were generated using DeepTools69 v 2.5.3 .Peaks were called for DRIP versus input and DRIP versus RNaseH treated using MACS270, PcG binding sites conserved through Drosophila species71, and additional PREs from recent reports72. Multiple PREs predicted in the repeated histone gene clusters were removed, although ChiP-seq peaks for PcG proteins are observed at these sites. Finally, overlapping or touching PREs were merged (using BEDTools). The list of genomic coordinates for PREs is in Supplementary Table A list of PREs , aligned with Bowtie2 as described above, duplicates removed (Picard), and RPKM-normalized bigwig files generated (DeepTools bamCoverage). BEDOPS74 (v2.4.34) was used to convert bigwig files to wig and then bed files, and read densities quantified using BEDOPS bedmap (bedmap –count –echo-ref-name). Read densities over each PRE were divided by the PRE length to obtain the final values. All data sets used to analyze R-loops are listed in Supplementary Table To analyze overlap of PREs with PcG protein, RNA Pol II, or H3K27me3 ChIP-seq peaks Fig. , previouTo analyze overlap with annotated genes and RNA, we first converted DRIP-seq peaks to the dm6 genome using the UCSC genome browser liftOver tool. DRIP-seq peaks mapping to heterochromatin, ChrU, and ChrMT were removed. Unstranded DRIP-seq peaks were overlapped with either all ESTs (“mRNA and EST”) or all genes  using bedtools –intersect to produce the table shown in Extended Data Fig. To analyze the overlap with annotated RNAs in a strand specific manner, we used the strand-specific peak calls. Files were prepared as described above. To remove peaks with R-loops called on both strands, we first intersected the F and R strand files, and removed DRIP-seq peaks that were called on both strands. The remaining peaks were overlapped with all ESTs using bedtools intersect with the –s or –S options to obtain overlaps with sense and anti-sense transcripts. The same process was carried out for PREs, except that PREs were first intersected with F and R DRIP-seq peaks. In the analysis shown in Extended Data Fig. E. coli based on a previously described protocol76, except that Ni-NTA beads were used for the first step instead of amylose beads.Human RNaseH1: A 6×-His tag was added to MBP-hRNaseH1, which was expressed in and purified from 76.hRNaseH2: The RNaseH2 trimer was produced using the multi-cistronic pMAR22 vector essentially as described79. For PRC1ΔPh, nuclear extracts were prepared from Sf9 cells infected with viruses for the 4 subunits79 but nuclei were purified through a sucrose cushion prior to nuclear extraction. During the purification, the 2 M KCl wash in the published protocol was replaced with a wash consisting of BC2000N + 1 M Urea . Additionally, prior to eluting the protein, anti-FLAG beads were incubated 3–5 volumes of BC300N with 4 mM ATP + 4 mM MgCl2 for 30 min. at room temperature. This step reduces the amount of HSC-70 that co-purifies with PRC1ΔPh.PRC1ΔPh, PRC2, dSxc, hNFY: PRC1ΔPh and PRC2 were expressed in and purified from Sf9 cells, with the following modifications to previously published protocols for anti-FLAG affinity purification78 followed by Ni-NTA. FLAG peptide elutions were carried out in BC300 without EDTA or DTT. FLAG elutions were passed over Ni-NTA beads twice, beads were washed with 30 volumes of BC300 (without EDTA or DTT) and eluted in BC300 + 250 mM Imidazole. Eluted protein was pooled and dialyzed through three changes of BC300 with EDTA, PMSF, and DTT. PRC2 was concentrated to ~1 mg/ml, NP40 was added to 0.05%, and protein was stored at −80 °C.For PRC2 expression and purification, E(Z) was tagged with 6-His, and either Esc or Su(Z)12 with FLAG, and baculovirus infected Sf9 cells were harvested after 3 days. PRC2 was purified by anti-FLAG affinity as describedExtract preparation and anti-Flag purification of F-Sxc and F-NFY were as described for PRC2.For glycerol gradient fractionation of PRC1ΔPh or PRC2 . Samples were purified by phenol-chloroform extraction, followed by purification through a G-25 spin column equilibrated with TE-50.DNA and RNA oligonucleotides described in Supplementary Table 80, using a nitrocellulose filter (to capture protein-nucleic acid complexes) (Biotrace) stacked on a charged nylon membrane (to capture free nucleic acids)  with a slot blot apparatus. Nitrocellulose filters were prepared by incubating in 0.4 M KOH for 10 min, washing extensively with H2O, and equilibrating at least one hour in binding buffer. Nylon filters were equilibrated at least 10 min. in 0.4 M Tris, pH 8.0. We first measured the active concentration of two preparations of PRC1ΔPh; concentrations reported in Fig. Filter binding was carried out essentially as describedPRC1ΔPh and PRC2 were titrated into reactions with 0.01 nM of DNA bubble, R-loop or dsDNA in the same reaction conditions as for filter binding except that 50 ng/μL BSA were included Reactions were resolved on 6% acrylamide 0.5 × TBE gel. Gels were dried and exposed to a phosphor imager screen and scanned on a Typhoon imager.PRC1ΔPh and PRC2 were titrated into reactions with 20 nM of DNA bubble, R-loop, dsDNA, ssDNA and RNA in the same conditions as for filter binding. Proteins were digested with 3 μL of DSB-PK (6.7 µg/µL of proteinase K (Biobasic), 1% SDS, 50 mM Tris-HCl pH 8.0, 25% glycerol and 100 mM EDTA) for 30 min at 50 °C, nucleic acids were resolved on 8% acrylamide 0.5× TBE gels and stained with SYBRGold (Thermo Fisher).Drosophila genomic DNA and cloned into the pET-Blue1 vector (Millipore) downstream of the T7 promoter. Detailed maps are available on request. For strand exchange, plasmids were digested with a single restriction enzyme, purified by phenol-chloroform extraction, and ethanol precipitated.PRE sequences were amplified by PCR from 3 pH 8.8 with murine RNase inhibitor (NEB) for 2 h at RT. RNAs were then precipitated with 0.3 M sodium acetate pH 5.3, glycogen and ethanol, washed with 70% ethanol, and resuspended in TE. RNAs were passed through a G50 column equilibrated with TE. The quality of labelled RNA and efficient removal of free dye were determined by loading the RNA on agarose gels.RNAs were produced from linear templates using the Ampliscribe T7-flash transcription kit (Lucigen) using the manufacturer’s protocol in the presence of 25 mM of amino-allyl UTP (Sigma). After purification, RNAs were labelled with NHS-Cyanin-5 (Kerafast) in 70 mM NaHCORadiolabelled RNAs were produced from circular templates by transcribing 600 ng of DNA in RNA polymerase buffer (NEB), 1 mM DTT, 625 µM of rNTP (NEB), 6.5 nmol of radiolabelled UTP, 200 U of RNase inhibitor, and 250 U of T7 or T3 RNA polymerases (NEB) in 100 µL O.N. at 37 °C. DNA was removed from the reaction by adding 4 U of DNaseI (NEB) and incubating 2 h at 37 °C. RNAs were extracted with phenol-chloroform, ethanol precipitated, washed with 70% ethanol, resuspended in TE, and stored at −20 °C.2, 1 mM DTT and with 50 ng/ µL BSA in 10 µL reaction. After incubation, samples were treated with 3 µL of DSB-PK for 30 min. at 50 °C and resolved on 0.8% agarose 0.5X TBE gel. Gels were stained with SYBRGold or ethidium bromide, and imaged on a Typhoon Imager. For experiments with radio-labelled RNA, gels were transferred to HYBOND membrane and exposed to a phosphor imager screen.PRC2, diluted in BC300N was incubated with the indicated amount of DNA and fluorescent- or radio- labelled RNA for 25 min. at 30 °C in 180 mM KCl, 5 mM MgClFor nuclease treatment of strand invasion products without phenol-chloroform extraction, after incubation with PRC2, samples were treated immediately with nucleases. For RNaseH treatment, 10× RNaseH buffer was added to a final concentration of 1×, followed by 2.5 U (radio-labelled RNA) or 1.25 U (fluorescently labelled RNA) of RNaseH. For RNaseA treatment, reactions were supplemented with 500 mM NaCl and 50 pg of RNaseA (Qiagen) were added. Reactions were incubated for 30 min. at 30 °C. For phenol-chloroform extracted samples, reactions were stopped with 3 μL of DSB-PK and incubated for 30 min at 50 °C. Nucleic acids were extracted with phenol-chloroform followed by ethanol precipitation and resuspension in TE. Nuclease digestion was carried out as described above. Nuclease digestions were stopped by the addition of 3 μL of DSB-PK, and samples were incubated 30 min at 50 °C before analyzing on agarose gels. When the order of DNA and RNA addition was tested, the first nucleic acid was added to PRC2 for 10 min at 30 °C before the addition of the second.For the pre-incubation assay shown in Fig. Ten micrograms of PRC2 and 330 ng of Cy5-labelled RNA were incubated 30 min. at 30 °C with respectively 0.5 and 1 unit of apyrase (NEB) in 15 or 30 μL reaction. Apyrase was remove by passing PRC2 and RNA on G50 column equilibrated respectively with BC300N and TE. PRC2 and RNA treated with apyrase were used in strand exchange reactions.DNA, RNA and PRC2 was incubated as describe for RNA–DNA strand exchange in 100 uL reactions. Reactions were stopped with 30 uL of DSB-PK and digested for 30 min. at 50 °C. Nucleic acids were extracted with phenol-chloroform, ethanol precipitated, washed with 70% ethanol and resuspended in TE. RNA–DNA hybrid containing fragment were immunoprecipitated by incubated O.N. at 4 °C with protein G beads pre-incubated with 2.5 μg S9.6 antibody (Kerafast ENH001 and M. Wilson) and competitor DNA . Beads were washed three times with 10 mM NaPO4 pH 7.0, 140 mM NaCl and 0.05% Triton X-100. Nucleic acids were eluted from the beads by incubating them 45 min at 50 °C in presence of 50 mM Tris pH 8.0, 10 mM EDTA, 0.5% SDS and 56 μg proteinase K. Samples were resolved on 0.8% agarose 0.5× TBE gels. Gels were stained with SYBRGold and imaged on a Typhoon Imager.2 was added and the [KCl] was 60 mM. Reactions were incubated for 25 min at 15 °C, and stopped by adding 200 nM of unlabelled ssDNA oligonucleotides and 25 ng of vg RNA and incubation for 10 min at 15 °C. Reactions were loaded on 8% acrylamide 0.5× TBE gels. Gels were stained with SYBRGold and imaged for Cy5 and SYBRGold on a Typhoon Imager.Phosphorylated ssDNA or RNA oligos corresponding to a sequence in the bxd PRE (Supplementary Table Oligonucleotides were phosphorylated with T4 PNK (NEB). dsDNA oligonucleotides were annealed by incubating equal amounts of ssDNA in TE-50, boiling for 5 min. and slow cooling over several hours. ssDNA oligonucleotides were boiled and transferred immediately to ice. PRC2, T7 endonuclease (NEB), Exonuclease I (NEB), λ exonuclease (NEB) or Exonuclease III (NEB) were incubated with phosphorylated ssDNA or dsDNA oligonucleotides under RNA–DNA hybrid forming conditions. Reactions were stopped by adding DSB-PK and incubated 1 h at 50 °C. Samples were denatured by addition of 26% formamide, 0.3 mM EDTA, 3.3 mM NaOH and boiled before loading on denaturing gels . Gels were stained with SYBRGold and imaged on Typhoon Imager.For quantification of DNA and RNA–DNA hybrids from phoshpor imager and SYBR gold scans using ImageQuant, RNaseA-treated samples were used. In cases where gel flaws obscured quantification of a lane, the gradient was excluded from analysis. Background subtraction was done using the rolling ball method. For band selection, the smallest possible “fixed width” bands that capture the whole signal were set for each gradient. These bands were placed in each lane so that every fraction was quantified. The signal from the bottom three fractions was divided by that for the total of the gradient for the fraction bound.RNA strand exchange assay gels of Cy5-labelled RNA were imaged using Typhoon Imager  were quantified using ImageQuant . Lanes were created manually, then background was removed using minimum profile method and bands were identified manually.E. coli SSB (NEB) at a ratio of 6 μg SSB per μg DNA on ice for 10 min81. Glutaraldehyde (Electron Microscopy Sciences) was added to a final concentration of 0.6% and samples incubated 10 min on ice. Samples were purified through a G-50 column equilibrated in TE. Samples were diluted 1:5 in 2 mM Spermidine, 150 mM NaCl, 1 mM MgCl2, and applied to glow-discharged 400-mesh grids coated with thin carbon  for 5 min. Grids were washed through two drops of 100 mM MgOAc, and stained with 3 drops of 2% Uranyl Acetate (Electron Microscopy Sciences), blotted and air-dried. Grids were photographed at 120 kV using an FEI Technai G2 Spirit BioTwin Cryo-TEM at the McGill Facility for Electron Microscopy Research. Note that both positively and negatively stained regions were observed on the grids; positive staining is shown in Fig. Two hundred nanograms of PRC2 or 20 units of exonuclease III were incubated with 1.9 nM of pFC53 DNA linearized with HindIII using RNA–DNA hybrid formation conditions. Reactions were stopped with 15 μL of DSB-PK and incubated O.N. at 50 °C. DNA was purified on PCR clean-up columns (Macherey-Nagel) with NTB buffer. DNA was incubated with Y = ABmax*(1−ek*X−) was used; for binding data, Y = (ABmax*X)/(X + Kd)+b was used. Fisher’s exact test was used to compare curve fits. For students t-tests .RegioneRFurther information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


We examined if the distribution of impaired or normal spermatogenesis differs along the length of seminiferous tubules in disorders of spermatogenesis. For this purpose, three-dimensional (3D) reconstruction of seminiferous tubules was performed in mice with experimental spermatogenesis disorder induced by intraperitoneal injection of busulfan, and the areas of impaired and normal spermatogenesis were analyzed microscopically. The volume of the testis and length of seminiferous tubules decreased, and the proportion of tubule areas with impaired spermatogenesis increased depending on the dose of busulfan. With the highest dose of busulfan, although the proportion of impaired spermatogenesis was similar among individual seminiferous tubules, it was slightly but significantly higher in shorter tubules and in tubule areas near branching points. The tubule areas with impaired and normal spermatogenesis consisted of many segments of varying lengths. With increasing doses of busulfan, the markedly impaired segments increased in length without changing in number, whereas normal segments, although reduced in number and length, remained even with the highest dose of busulfan. Individual remaining normal segments consisted of several different stages, among which stage I and XII were found at higher frequencies, and stage VI at a lower frequency than expected in normal seminiferous tubules. We also examined if the distribution of impaired or normal spermatogenesis differs among different 3D positions in the testis without considering the course of seminiferous tubules. Although the proportions of impaired spermatogenesis with the minimum dose of busulfan and normal spermatogenesis with the highest dose of busulfan greatly varied by location within a single testis, there were no 3D positions with these specific proportions common to different testes, suggesting that the factors influencing the severity of busulfan-induced spermatogenesis disorder are not fixed in location among individual mice. Approximately 15% of couples trying to conceive are infertile, with a male factor involved in 50% of cases . The mosMany clinical factors, such as testicular volume, serum follicle-stimulating hormone, and serum inhibin B, have been investigated as an accurate predictor, but none were useful. Recently, the ultrasonographically measured size of seminiferous tubules was reported as a strong predictor . IdentifIt is generally believed that the sites of preserved spermatogenesis in the testis with NOA are multi-focal and distributed diffusely and homogenously rather than being patch-like and distributed heterogeneously in particular regions . On the Our group recently reported the high-resolution 3D structure of all seminiferous tubules in animal testes using serial paraffin sections and high-performance 3D reconstruction software . MoreoveThe present animal study was approved by Kanazawa University  and conducted in accordance with the Guidelines for the Care and Use of Laboratory Animals of Kanazawa University. C57BL/6 strain male mice were purchased from Nippon SLC, Inc. , and reared under standard 12-h light/12-h dark laboratory conditions with free access to standard food and water.Busulfan  was dissolved in DMSO and diluted in an equal volume of sterile distilled water to a final concentration of 0, 1, 2, or 3 mg/mL immediately before injection. Six-week-old male mice (body weight approximately 20 g) received a single intraperitoneal injection of 0, 10, 20, or 30 mg/kg of busulfan .At 12 weeks after busulfan treatment, the mice were sacrificed by cervical dislocation. The testis and epididymis were dissected out en bloc, fixed in Bouin’s solution or 10% formalin neutral buffer solution overnight, dehydrated in a graded ethanol series, and embedded in paraffin. Using the Bouin’s-fixed paraffin blocks, serial 5-μm-thick sections with intervals of 40 or 50 μm were made by cutting the specimen longitudinally in parallel to the plane involving both the testis and epididymis using a microtome, and then mounted on glass slides. The sections were treated with periodic acid-Schiff-hematoxylin (PAS-H) to stain the basement membrane of seminiferous tubules, as previously described . The secUsing the formalin-fixed paraffin sections, immunohistochemistry (IHC) was performed as described previously , 2017b. 1) and Adobe Photoshop 2020 software . After extraction, the images were converted into gray scale in JPEG format with Adobe Photoshop 2020 software at a resolution of 1,816 nm⋅pixel–1. Using Amira 6.3.0 software , the serial images were aligned automatically followed by manual adjustment, and the inside of the outlines of a selected tubule was colored in using threshold processing and traced from section to section. This procedure was repeatedly applied to all seminiferous tubules with different colors and they were then 3D reconstructed. To draw the core lines of seminiferous tubules, individual traced tubules in cross-sections were shrunk concentrically by 16 pixels in all directions, their resolution was changed to 29,056 nm⋅pixel–1, and they were then reconstructed into thin tubules, in which the core lines were drawn using the same software. The whole testis was also 3D reconstructed by filling the inside of their outlines by threshold processing. The position of the rete testis was defined as the mean coordinate of the connections of all reconstructed seminiferous tubules with the rete testis and shown with a black sphere.The 3D reconstruction was performed as previously described  with sliSpermatogenesis is routinely divided into 12 stages in mice based on changes in the morphology of the acrosome and nucleus . The degpost hoc test, respectively, and differences with a P-value of less than 0.05 were considered to be significant. Pearson’s correlation coefficient test was performed to assess the magnitude and direction of the proportionality between two parameters, and a positive or negative relationship was acknowledged when the absolute r-value was greater than 0.2.Data are presented as the mean ± standard deviation (SD). Comparisons among multiple data were performed with one-way or one-way repeated measures analysis of variance (ANOVA) followed by Bonferroni’s or Dunnet’s P = 0.56, 0.92, and 0.98, respectively). On the other hand, the testis volume and total length of seminiferous tubules per testis significantly decreased in IP-20 and IP-30 (P < 0.05 between IP-0 and IP-20 or IP-30).To generate mice with different degrees of spermatogenesis disorder, 12 mice were divided into four groups of three mice each: IP-0 , IP-10 , IP-20 , and IP-30 , which received a single intraperitoneal injection of 0, 10, 20, and 30 mg/kg of busulfan, respectively. All seminiferous tubules were reconstructed in 12 testes, one from each mouse, at 12 weeks after busulfan treatment. Results in four representative testes, one from each group, are shown in P < 0.05 between IP-0 and IP-10; between IP-10 and IP20 or IP30) and that of abnormal segments without spermatocytes (red) increased  .To analyze the degree of spermatogenesis disorder, all seminiferous tubule areas observed in each testis section were classified into three types as described in section “Materials and Methods,” i.e., normal, abnormal with spermatocytes, and abnormal without spermatocytes, which were represented by green, yellow, and red, respectively. Moreover, the normal tubule areas were confirmed to undergo a complete spermatogenesis by immunofluorescence staining for specific markers of type A spermatogonia, spermatocytes, and spermatids . Thus, td IP-30) . On the r| < 0.2), but weak positive correlations  and a weak negative correlation (r = −0.27 for red) existed in IP-30.We next examined if the degree of spermatogenesis disorder differs among different seminiferous tubules in a testis that were numbered in the order of their connection with the rete testis from the top toward the bottom, or among different seminiferous tubules of varying lengths in IP-10 and IP-30 (three mice each) . There wP < 0.05), but remained unchanged in IP-30 compared with that in IP-20. The length of the red segments slightly increased in IP-20 compared with that in IP-10, although not significantly, and increased further significantly in IP-30 (P < 0.05). In contrast, the length of the yellow segments remained unchanged from IP-10 to IP-30 (P = 0.80). The number of green segments decreased significantly in IP-20 compared with that in IP-10 (P < 0.05) and slightly decreased further in IP-30, although not significantly. The number of red segments remained unchanged from IP-10 to IP-30 (P = 0.06). In contrast, the number of yellow segments significantly decreased in IP-20 compared with that in IP-10 and decreased further in IP-30 (P < 0.05).As shown in r = 0.19) (data not shown). The observed proportions of individual stages were compared with those expected, which were deduced from the duration of these stages in the total cycle of mouse spermatogenesis (35 days) reported previously  segments remained in markedly damaged seminiferous tubules of IP-30 without a significant reduction in length or number from those in IP-20. We then examined which stages of spermatogenesis are preferentially involved in these remaining normal segments. A total of 87 normal segments remaining in the three testes in IP-30 were analyzed for their cell associations to determine the stage . The aveeviously . The proeviously . In addiNext, we examined if the degrees of spermatogenesis disorder differ among different 3D positions in seminiferous tubules. The proportions of the three color segments were measured in three different areas of seminiferous tubules, i.e., Rete (positions within 10 mm from the terminating points with the rete testis), Branch (positions within 10 mm from the branching points), and Others (positions more than 10 mm apart from the terminating points and branching points), and compared with those in the whole seminiferous tubules (Whole) . In IP-1X-Y-Z-axes, and the proportions of green, yellow, and red segments in all seminiferous tubule areas involved in each slice were measured. In the present study, special attention was paid to the distribution of red  segments in IP-10 and green  segments in IP-30 (Lastly, we examined if the degree of spermatogenesis disorder differs among different 3D positions in a testis without considering the course of seminiferous tubules. Using the 3D reconstruction software, each testis was divided into 200-μm-thick serial slices along the perpendicular planes formed by the in IP-30 . There wIn the present study, we reconstructed seminiferous tubules in 12 mice treated with varying doses of busulfan and analyzed the 3D distribution of spermatogenesis, in order to examine if spermatogenesis disorder occurs preferentially at specific sites in seminiferous tubules. The testis volume and total length of seminiferous tubules were reduced depending on the dose of busulfan. The positive correlation between the tubule length and the proportion of markedly impaired spermatogenesis with the highest dose of busulfan suggests that the length of seminiferous tubules is shortened due to massive degeneration. However, busulfan treatment caused no change in the basic structure of seminiferous tubules, including the numbers of tubules, terminating points, branching points, and blind ends.Although the proportion of markedly impaired spermatogenesis increased and that of normal spermatogenesis decreased in a busulfan dose-dependent manner in all seminiferous tubules, the increased proportion of markedly impaired spermatogenesis with the highest dose of busulfan was accompanied by a decreased proportion of moderately impaired spermatogenesis and unchanged proportion of normal spermatogenesis when compared with a moderate dose of busulfan. Furthermore, analysis of the length and number of segments revealed that when the dose of busulfan increased from moderate to the highest, the segments with markedly impaired spermatogenesis increased in length, but not in number, those with moderately impaired spermatogenesis decreased in number, but not in length, and those with normal spermatogenesis remained unchanged in length and only slightly decreased in number. These phenomena suggest that the markdly damaged segments fuse with each other, whereas the moderately damaged segments further impair spermatogenesis and fuse with neighboring markedly damaged segments, resulting in an increased length of segments with markedly impaired spermatogenesis at the highest dose of busulfan. Furthermore, weakly damaged segments do not further impair spermatogenesis and instead recover and remain as segments of a certain length and number with normal spermatogenesis even at the highest dose of busulfan.Busulfan is an alkylating agent that kills differentiated spermatogonia and spermatogonial stem cells . Wang etRegarding the 3D localization of the sites of spermatogenesis disorder, the proportion of markedly impaired spermatogenesis, although not notably different among individual ordered seminiferous tubules in a testis, was slightly but significantly higher in the tubule areas near the branching points, suggesting that these positions in the seminiferous tubules are more vulnerable to busulfan-induced damage. On the other hand, analysis of the whole testis without considering the course of seminiferous tubules revealed that both the sites of markedly impaired spermatogenesis with the lowest dose of busulfan and those of normal spermatogenesis with the maximum dose of busulfan largely differed among different positions in a testis. These sites are considered to represent the most vulnerable portions of the testis where degeneration of tubules preferentially occurs and the least vulnerable portions of testis where regeneration of tubules preferentially occurs, respectively. However, these sites were not consistent in location among different testes from individual mice.The factors responsible for the site-specific disorder of spermatogenesis may reside outside of seminiferous tubules. In the human testis with NOA, several groups reported that the least vulnerable positions, i.e., the sperm containing-regions, receive more abundant blood supply . In the The present study revealed the detailed 3D structure of seminiferous tubules in busulfan-induced experimental disorder of spermatogenesis in mice. The present methods can be readily applicable to investigating other types of mouse spermatogenesis disorder, including that due to aging, which may have different mechanisms from those in the busulfan model. Although there are large limitations for comparing the mouse models with human NOA that has unknown mechanisms, our ultimate goal is application of the present methods to the study of human NOA. The structure of the testis differs between humans and mice in several aspects: the human testis, which is approximately 150-times larger in volume than the mouse testis, is divided into many lobules by connective tissue septa that separate individual seminiferous tubules, whereas no such septa exist in the mouse testis; human seminiferous tubules are considered to be composed of numerous anastomosed thin loops and run in random directions , whereasThe original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.The animal study was reviewed and approved by the Kanazawa University.HN designed the project and performed the study. HN, TN, and SI analyzed the data. HN and SI wrote the manuscript. All authors discussed the data and commented on the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The RNA world hypothesis is probably the most extensively studied model for the emergence of life on Earth. Despite a large body of evidence supporting the idea that RNA is capable of kick-starting autocatalytic self-replication and thus initiating the emergence of life, seemingly insurmountable weaknesses in the theory have also been highlighted. These problems could be overcome by novel experimental approaches, including out-of-equilibrium environments, and the exploration of an early co-evolution of RNA and other key biomolecules such as peptides and DNA, which might be necessary to mitigate the shortcomings of RNA-only systems. For somvolution .in vitro selection of ribozymes has over the years revealed the impressive catalytic repertoire of nucleic acids, despite their conformal and sequence-based limitations compared with proteins [Breakthroughs in prebiotic chemistry demonstrating how the essential building blocks of RNA (and other biomolecules) may have formed under different primordial scenarios address many concerns about the plausibility of RNA or related nucleic acid emergence in a prebiotic world –9. Similproteins . RNA is Tm) of long RNA duplexes, such as those that arise from template-directed replication, results in the formation of dead-end duplex complexes in the absence of highly evolved helicases. When complementary RNA strands are separated, for example, by heat denaturation, reannealing occurs orders of magnitudes faster than known copying reactions [Despite these rebuttals, it has not yet been possible to demonstrate robust and continuous RNA self-replication from a realistic feedstock (i.e. activated mono- or short mixed-sequence oligonucleotides). Major obstacles for RNA copying such as efficiency, regiospecificity and fidelity and are discussed elsewhere ,19 but aeactions .In the case of ribozymes, only ‘simple’ ligation or recombination-based RNA replication from defined oligonucleotides has been demonstrated –23. SuchThe search for an RNA replicase ribozyme, a cornerstone of the RNA world hypothesis, is largely founded on improvements of the scaffold of the R18 RNA polymerase ribozyme, which itself is an optimised version of the complex class I ligase ribozyme . The disRNA is capable of this process but more time is needed to identify either conditions or replicators of sufficient complexity that are able to solve the various problems associated with protein-free RNA replication.RNA in isolation (including ribozymes) is simply not sufficient to catalyse its own replication, and substantial help from either other molecules or the environment is essential.RNA replication was never really central during early molecular evolution but rather the late result of a (crudely) replicating non-enzymatic metabolism –37 or anFor the first possibility, it may only be a matter of time and combined efforts to identify experimental model scenarios that are convincing enough to please critics of the field. In the worst case, the formation of life as we know it from RNA could be the result of a ‘frozen accident’, similar to the genetic code [ex situ [a priori sequence information and can, therefore, emerge spontaneously under suitable environmental and chemical conditions (e.g. a continuous supply of activated monomers and processes that enable repeated strand separation). Assuming the remaining experimental problems of continuous enzyme-free nucleic acid replication are solved, natural selection should spontaneously produce systems that are better or ‘good enough’ to persist under the given conditions. Whether these new replicators will necessarily evolve into more complex systems with advanced  properties (e.g. cooperative ribozyme networks) is of course another matter, although simulations predict that genomic complexity is forced to increase in a fixed environment [Looking back at the long history of the field, one might wonder why we have yet to achieve (self-sustained) RNA replication and transcription, despite its centrality to the RNA world hypothesis. There are three possibilities:tic code , that is[ex situ . This noironment –45.Tm, which could provide an environmental route to overcoming the strand dissociation problem [To identify suitable conditions for such an in-laboratory origin, a ‘flexible’ approach is probably the best choice in light of the large number of possible geochemical conditions that have been proposed to host the emergence of life . In othe problem . It remaSimilar combined efforts will also be necessary if RNA alone is insufficient to drive continuous self-replication and evolution. In this case, it may be necessary to diversify the pool of feedstock molecules by taking into account the chemical and conformational heterogeneities found in many experimental scenarios. For example, nucleic acid polymers with non-inheritable backbone heterogeneities  Nearly,There remains the hope for origin of life scenarios where RNA plays a major role as an information carrier and catalyst. New experimental approaches using out-of-equilibrium settings could finally result in genuine RNA-based self-replicating systems capable of open-ended evolution. More complex scenarios involving RNA, DNA, peptides, simpler polynucleotides, chimeric intermediates or other yet unknown helper molecules may also be required, which will complicate the analytical understanding of the model systems and may ultimately render the term ‘RNA world’ in its traditional sense obsolete.Despite advances in prebiotic chemistry, it has not yet been possible to demonstrate robust and continuous RNA self-replication from a realistic feedstock.RNA in isolation may not be sufficient to catalyse its own replication and may require help from either other molecules or the environment.Non-equilibrium environments, backbone heterogeneity and polypeptide cofactors may address some of the remaining problems in the RNA world hypothesis.