All NNS RNA viruses, including the human pathogens rabies, measles, respiratory syncytial virus, Nipah, and Ebola, possess an essential L-protein cofactor, required to access the N-RNA template and coordinate the various enzymatic activities of L. The polymerase cofactors share a similar modular organization of a soluble N-binding domain and a template-binding domain separated by a central oligomerization domain. Using a prototype of NNS RNA virus gene expression, vesicular stomatitis virus (VSV), we determined the importance of P oligomerization. We find that oligomerization of VSV P is not required for any step of viral mRNA synthesis but is required for efficient RNA replication. We present evidence that this likely occurs through the stage of loading soluble N onto the nascent RNA strand as it exits the polymerase during RNA replication. Interfering with the oligomerization of P may represent a general strategy to interfere with NNS RNA virus replication. RdRP, LPRNT, and LMT, an oligomeric phosphoprotein (P) is required. Vesicular stomatitis virus (VSV) P is dimeric with an oligomerization domain (OD) separating two largely disordered regions followed by a globular C-terminal domain that binds the template. P is also responsible for bringing new N protomers onto the nascent RNA during genome replication. We show VSV P lacking the OD (PΔOD) is monomeric but is indistinguishable from wild-type P in supporting mRNA transcription in vitro. Recombinant virus VSV-PΔOD exhibits a pronounced kinetic delay in progeny virus production. Fluorescence recovery after photobleaching demonstrates that PΔOD diffuses 6-fold more rapidly than the wild type within viral replication compartments. A well-characterized defective interfering particle of VSV (DI-T) that is only competent for RNA replication requires significantly higher levels of N to drive RNA replication in the presence of PΔOD. We conclude P oligomerization is not required for mRNA synthesis but enhances genome replication by facilitating RNA encapsidation.Nonsegmented negative-strand (NNS) RNA viruses possess a ribonucleoprotein template in which the genomic RNA is sequestered within a homopolymer of nucleocapsid protein (N). The viral RNA-dependent RNA polymerase (RdRP) resides within an approximately 250-kDa large protein (L), along with unconventional mRNA capping enzymes: a GDP:polyribonucleotidyltransferase (PRNT) and a dual-specificity mRNA cap methylase (MT). To gain access to the N-RNA template and orchestrate the LIMPORTANCE All NNS RNA viruses, including the human pathogens rabies, measles, respiratory syncytial virus, Nipah, and Ebola, possess an essential L-protein cofactor, required to access the N-RNA template and coordinate the various enzymatic activities of L. The polymerase cofactors share a similar modular organization of a soluble N-binding domain and a template-binding domain separated by a central oligomerization domain. Using a prototype of NNS RNA virus gene expression, vesicular stomatitis virus (VSV), we determined the importance of P oligomerization. We find that oligomerization of VSV P is not required for any step of viral mRNA synthesis but is required for efficient RNA replication. We present evidence that this likely occurs through the stage of loading soluble N onto the nascent RNA strand as it exits the polymerase during RNA replication. Interfering with the oligomerization of P may represent a general strategy to interfere with NNS RNA virus replication. RdRP) transcribes the RNP template into a 47-nucleotide (nt) 5′ triphosphate leader RNA and 5 monocistronic mRNAs that are indistinct to host cell mRNA with respect to their 5′ cap and 3′ polyadenylate (7PRNT) transfers the 5′ end of the nascent RNA chain onto a GDP acceptor through a covalent L-pRNA (L-monophosphate RNA) intermediate. The resulting GpppA cap structure is then modified by a dual-specificity L-encoded RNA cap methylase (LMT), which first modifies the ribose-2′-O position associated with first transcribed nucleotide generating GpppAm and subsequently methylate, the guanine ring of the cap at the N7 position, to yield 7mGpppAm (RdRP reiteratively copies one or more members of an oligo(U) tract resident at the end of each gene (The 241-kDa large (L) protein of vesicular stomatitis virus (VSV) contains all the enzymatic activities necessary to copy its viral ribonucleoprotein (RNP) template 14. That Renylate 710. The eenylate 7. During 7mGpppAm . The 3′ ach gene .RdRP and a continuous supply of soluble N protein that coats the nascent RNA chain during its synthesis , corresponding to residues 195 to 265, contacts the N-RNA template by binding at a unique interface that forms between adjacent N molecules on the template  comprising residues 107 to 177 (0), occluding binding of RNA  and PΔOD on denaturing and native protein gels reveals that deletion of the oligomerization domain yields a P variant whose mobility is altered, consistent with the loss of the 8-kDa OD . Both PWT and PΔOD elute as single monodisperse peaks . The weight-average molar mass (22.6 kDa) for PΔOD is in good agreement with the expected molar mass for a monomer (22.4 kDa). Thus, deletion of the oligomerization domain of VSV P renders the protein monomeric in solution.To probe the function of P protein oligomerization in assembly and function of the VSV replication machinery, we expressed and purified from bacteria a variant of P lacking residues 107 to 177, termed PΔOD  and B. C8-kDa OD . To provse peaks  and alloWT and PΔOD to stimulate LRdRP activity using an in vitro assay with chemically synthesized RNA as the template  as a marker of infection . The resque size  and a 4-que size . MoleculFU ratio . This reWT and VSV-eGFP-PΔOD to undertake primary transcription in cells. Cells were treated with cycloheximide and actinomycin D to block protein and cellular RNA synthesis, respectively, and infected with the indicated virus at a multiplicity of infection (MOI) of 100, and viral RNA synthesis was monitored by metabolic incorporation of [32P]orthophosphate. At various times postinfection, total cellular RNA was extracted and analyzed by acid-agarose gel electrophoresis, and the products of primary transcription were detected by phosphor image analysis. The abundance of each viral mRNA was similar for VSV-eGFP-PWT and VSV-eGFP-PΔOD , which allows visualization of the replication compartment  the oligomerization domain of VSV P results in its dimerization, (ii) P dimerization is dispensable for all aspects of viral mRNA transcription, and (iii) P dimerization stimulates RNA replication. We also present evidence in support of a mechanism where the dimerization-mediated stimulation of replication is likely accomplished by facilitating encapsidation of the nascent replicative product at an optimal N protein concentration that is lowered by the presence of the oligomerization domain. We suggest that this is a central function of the P proteins of all ΔOD confirming PΔOD is monomeric in solution and showing its global architecture is not affected by the loss of the OD   . In thatrotomers . The engΔOD, one or several of the viral cycle steps, including viral entry, primary transcription, genome replication, or particle assembly, must be affected. Using a similar recombinant virus, Gérard and colleagues did not see any strong effect of the loss of the OD on virion production  rather than intrinsic differences between PWT and PΔOD.For rabies virus, the Ped cells . This isin vitro on naked RNA or on purified N-RNA templates was unaffected by the loss of the OD. Consistent with this observation, measures of primary mRNA transcription by the polymerase molecules brought into cells with the infecting virus were also unaffected. Collectively, those data provide compelling evidence that no step of transcription, including initiation, cap formation, elongation, polyadenylation, termination, and reinitiation, require the presence of the OD. We consistently observed an increase in levels of transcription with PΔOD, although quantitation of the N mRNA indicated that this difference was not significant. Additional work will be required to understand the basis of this observation. An earlier model of migration of the polymerase complex of Sendai virus, a related virus in the family Paramyxoviridae, posited that the polymerase cartwheels along the N-RNA template via the interaction between the PCTD of its tetrameric P and the nucleocapsid   and AfriΔOD was cloned in a pET16b vector  coding for 6×His/PV1+-eGFP . pVSV1+-+-eGFP/PΔOD was derived from pVSV1+-eGFP/P  of 0.01. Virus suspensions were replaced by DMEM-2% FBS, and cell supernatants were harvested when 95% of the cells were infected and ready to detach (about 24 h for VSV-eGFP-PWT). For gradient-purified viruses, infected cell supernatant was first concentrated through a 15% sucrose cushion in NTE  at 110,000 × g for 2 h at 4°C. Pellets were resuspended overnight at 4°C in NTE, put on top of a linear 15 to 45% sucrose gradient in NTE, and centrifuged at 200,000 × g for 3 h at 4°C. Bands corresponding to virus were collected in 0.5-ml tubes by side puncture of the tube and diluted 10 times in NTE.VSV-eGFP-Peviously , 40. VSVprotocol  using pVΔOD were purified from BL21(DE3) Escherichia coli cells and the L protein from Spodoptera frugiperda 21 (Sf21) cells as previously described  by use of a Wyatt Dawn Heleos II multiangle light scattering detector and Optilab T-rEX refractive index detector at the Center for Macromolecular Interactions, Harvard Medical School. Data were processed using Astra 7, and weight-averaged molar mass was fit using the Zimm method and a protein refractive index increment of 0.185. Fitting errors of 0.7% and 1.4% were achieved for PIn vitro RNA synthesis assays on naked RNA were performed as previously described  for 30 min followed by a 30-min incubation in phosphate-free DMEM containing 10 μg/ml actinomycin D  and 100 μg/ml cycloheximide . Cells were then infected for 30 min with sucrose cushion-purified virus at an MOI of 100. Virus solutions were replaced by 1 ml phosphate-free DMEM containing 10 μg/ml actinomycin D, 100 μg/ml cycloheximide, and 10 μl of phosphorus-32 radionuclide . At 2, 3, 4, 5, and 6 h postinfection, RNA was extracted using TRIzol reagent  following the manufacturer’s protocol. RNA was boiled at 100°C for 1 min, incubated on ice for 2 min, mixed with a 1.33× loading buffer , and analyzed on a 25 mM citrate, pH 3, 1.75% agarose, 6 M urea gel run for 18 h at 4°C and 180 V. Gels were fixed (in 30% methanol and 10% acetic acid), dried, and exposed overnight to a phosphor screen , and the radiolabeled RNA products were visualized using a Typhoon FLA 9500 scanner .ΔOD (0.8 μg). Five hours later or at indicated hours, the medium was removed, and cells were incubated in 1 ml phosphate-free DMEM containing 10 μg/ml actinomycin D for 30 min before the addition of 10 μl of phosphorus-32 radionuclide. Cells were incubated for 3 h at 37°C before RNA was harvested by the use of TRIzol reagent following the manufacturer’s protocol. RNA was boiled at 100°C for 1 min, incubated on ice for 2 min, mixed with a 1.33× loading buffer , and analyzed on a 25 mM citrate, pH 3, 1.75% agarose, and 6 M urea gel run for 18 h at 4°C and 180 V. Gels were fixed (in 30% methanol and 10% acetic acid), dried, and exposed overnight to a phosphor screen , and the radiolabeled RNA products were visualized using a Typhoon FLA 9500 scanner . DI-T band intensities were quantified with ImageJ software.BSR-T7 cells were seeded in 6-well plates and infected 1 day later with a recombinant vaccinia virus expressing the T7 polymerase (vTF7-3) and DI-T particles for 1 h at 37°C in Dulbecco’s PBS . Cells were then transfected using Lipofectamine 2000 with plasmids expressing L (0.24 μg), N (2.9 μg or indicated amounts), and P or P5 cells per chamber in a 8-well chambered cover glass (Cellvis) and infected 20 and 24 h later at an MOI of 3 by VSV-eGFP/PΔOD and VSV-eGFP/PWT, respectively. Thirty hours after seeding, the photobleaching was performed using the Vector photomanipulation module attached to a Marianas spinning disk confocal platform . The images were acquired using a Plan-Apochromat 100×/1.4 oil lens . The incubation system  was set at 5% CO2 and 37°C. Four images were acquired prior to bleaching and imaging with the 488-nm laser.Vero cells were plated at 3 × 10Y(t) = Y0 + Afast(1 − e−Kfast*t) + Aslow(1 − e−Kslow*t).For data analysis, mean background fluorescence was measured from an area outside the cells and subtracted from other measurements. Mean fluorescence intensities of each photobleached area were also corrected for the photobleaching that occurred during image acquisition postbleach and normalized by the average fluorescence prebleach. Photobleaching postbleach was measured on nonbleached compartments. After normalization, mean recovery was calculated using EasyFRAP  and fit


Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strain UF-8, with an in-frame 12-nucleotide deletion within open reading frame 3a (ORF3a), was isolated from a 78-year-old COVID-19 patient in March 2020. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strain UF-8, with an in-frame 12-nucleotide deletion within open reading frame 3a (ORF3a), was isolated from a 78-year-old COVID-19 patient in March 2020. A 78-year-old woman with COVID-19 at the University of Florida hospital’s intensive care unit in March 2020 improved clinically and was discharged 6 days later. The studies were reviewed and approved by the University of Florida Institutional Review Board (IRB).https://www.cdc.gov/coronavirus/2019-ncov/lab/virus-requests.html), generating a quantification cycle (qC) value of 28 for primer set N1. As insufficient vRNA was extracted for direct sequencing using our standard next-generation sequencing (NGS) method, which requires a qC value of ≤20 to obtain adequate coverage, an aliquot of the NP specimen was inoculated onto Vero E6 cells in a T25 flask and incubated at 37°C for virus isolation and the preparation of larger amounts of vRNA for sequencing. The virus required 7 days to attain a virus titer of 2.5 × 106 PFU/ml and induce cytopathic effects (CPEs), whereas other wild-type strains usually attain a titer of ≥3 × 106 PFU/ml and induce CPEs 3 days postinoculation of the cells under the same conditions. RNA purified from the cell growth medium using a QIAamp viral RNA kit was subsequently submitted for NGS  from the patient using a QIAamp viral RNA minikit  tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA (vRNA) using the CDC real-time reverse transcriptase PCR (rRT-PCR) diagnostic test for COVID-19  in CLC Genomics Workbench v20.0.3, with default parameters, recovered the near-complete genome sequence, 29,847 nucleotides (nt) with a G+C content of 38% excluding the first 11 nt at the 5′ end and poly(A) tail. The virus was designated strain UF-8. The genomic sequence of UF-8 was confirmed by repeating the NGS process and by site-directed RT-PCR and Sanger sequencing of RNA extracted directly from the NP swab to confirm the 12-nt deletion. Phylogenetic analyses performed as previously described  of the Vero E6 cell host reads were removed using Kraken v2.0 with default parameters. Demultiplexing was automatically performed with the MiSeq software; no trimming was performed. escribed .Importantly, the 12-nucleotide in-frame deletion occurs within open reading frame 3a (ORF3a), which encodes viroporin 3a . ViroporAfter filtering, 2,452 genomes, including 30 new UF isolates (UF1 to UF30), were retained and aligned using MAFFT v7.407 , using tMW221275.1. The SRA accession number for the raw data is SRR13091823.The complete coding DNA sequence (CDS) of SARS-CoV-2/human/USA/UF-8/2020 has been deposited in GenBank under accession number


This study aims to compare the potential of standard RNA-sequencing (RNA-Seq) and 3′ massive analysis of c-DNA ends (MACE) RNA-sequencing for the analysis of fresh tissue and describes transcriptome profiling of formalin-fixed paraffin-embedded (FFPE) archival human samples by MACE. To compare MACE to standard RNA-Seq on fresh tissue, four healthy conjunctiva from four subjects were collected during vitreoretinal surgery, halved and immediately transferred to RNA lysis buffer without prior fixation and then processed for either standard RNA-Seq or MACE RNA-Seq analysis. To assess the impact of FFPE preparation on MACE, a third part was fixed in formalin and processed for paraffin embedding, and its transcriptional profile was compared with the unfixed specimens analyzed by MACE. To investigate the impact of FFPE storage time on MACE results, 24 FFPE-treated conjunctival samples from 24 patients were analyzed as well. Nineteen thousand six hundred fifty-nine transcribed genes were detected by both MACE and standard RNA-Seq on fresh tissue, while 3251 and 2213 transcripts were identified explicitly by MACE or RNA-Seq, respectively. Standard RNA-Seq tended to yield longer detected transcripts more often than MACE technology despite normalization, indicating that the MACE technology is less susceptible to a length bias. FFPE processing revealed negligible effects on MACE sequencing results. Several quality-control measurements showed that long-term storage in paraffin did not decrease the diversity of MACE libraries. We noted a nonlinear relation between storage time and the number of raw reads with an accelerated decrease within the first 1000 days in paraffin, while the numbers remained relatively stable in older samples. Interestingly, the number of transcribed genes detected was independent on FFPE storage time. RNA of sufficient quality and quantity can be extracted from FFPE samples to obtain comprehensive transcriptome profiling using MACE technology. We thus present MACE as a novel opportunity for utilizing FFPE samples stored in histological archives. RNA of sufficient quality and quantity can be extracted from formalin-fixed paraffin-embedded (FFPE) samples to obtain comprehensive transcriptome profiling using the 3′ massive analysis of c-DNA ends (MACE) RNA-sequencing technology. Thus, MACE provides an opportunity for utilizing FFPE samples stored in histological archives. Transcriptome-wide gene expression analysis of unfixed tissue samples has become an important tool in cancer research in recent years, improving our understanding of cancerogenesis and unveiling molecular diagnostic markers and potential therapeutic targets –3. The tRetrospective transcriptional analysis of formalin-fixed paraffin-embedded (FFPE) tumor samples could circumvent these limitations. Numerous FFPE samples of rare tumor entities have been collected over recent decades, and the associated clinical follow-up information about tumor recurrence, metastases, or death is available. However, whole-transcriptome profiling of FFPE samples by standard RNA-sequencing (RNA-Seq), especially regarding older samples , remainsMassive analysis of c-DNA ends (MACE) technology is an alternative high throughput sequencing method for FFPE specimens which requires only a short segment (50–800 bp) of each transcript (tag) adjacent to the poly-A-tail for gene mapping. MACE is termed a 3′ RNA-Sequencing method because only the fragment at the 3′ end of the RNA is sequenced (from 5′ to 3′), whereas standard RNA-Seq also sequences the fragments located further toward the 5′ end of the RNA. MACE thereby bypasses the obstacle of storage deterioration and associated mRNA degradation from the 5′ end. Furthermore, by sequencing only a single 3′-fragment of a transcript, the transcript length bias of standard RNA-Seq  is avoidIn this study, we carried out a comparative analysis of 3′ MACE sequencing and traditional RNA-Seq on fresh and FFPE human tissue samples. We also addressed the impact of paraffin storage on sequencing data elucidating time-dependent degradation. Our data suggests that RNA of sufficient quality and quantity can be extracted from FFPE samples to obtain comprehensive transcriptome profiling by MACE analysis.A total of 31 conjunctival samples from 24 patients were included in this study. All tissue samples were analyzed in an anonymized manner. Institutional Review Board/Ethics Committee approval was obtained for this study.n = 10), benign (n = 7) and malignant conjunctival tumors (n = 7) were sequenced. A detailed characterization of the enrolled patients can be found in Supplementary Fig. To compare standard RNA-Seq and MACE RNA-Seq on fresh tissue, four healthy conjunctival samples from four subjects were collected during buckling vitreoretinal detachment surgery, halved and immediately transferred to RNA lysis buffer  without prior fixation and then processed for either standard RNA-Seq or MACE RNA-Seq analysis. To assess the impact of FFPE-treatment on MACE, a third part was fixed in formalin and processed for paraffin embedding, as previously described , and itsTotal RNA was isolated from formalin-fixed and paraffin-embedded sections of all specimens using the Quick-RNA FFPE Kit . Following DNAse I digestion using the Baseline-ZERO kit , the RNA concentration was measured with the Qubit RNA HS Assay Kit on a Qubit Fluorometer . RNA quality was determined with the RNA Pico Sensitivity Assay on a LabChip GXII Touch .Standard RNA-Seq libraries were prepared by GenXPro GmbH, as previously described . The rRNMACE libraries were constructed by GenXPro GmbH, as previously described . Brieflyusegalaxy.eu)   from 24 patients with storage times lasting from 56 days to 13.4 years (4901 days). For comparison, we also included four healthy conjunctival samples without fixation. We found that the number of uniquely mapped reads (RNA STAR) decreased slightly from ~70% within the first 500 days to ~60% after 3000 days, including some variation Fig. . Even inR2 = 0.423, p < 0.001), the RNA degradation process in FFPE can be characterized by a half-life of ~1000 days within the first 2000 days. The degradation process seems to decelerate during the subsequent period (days 2000–5000).Next, we correlated the total storage time in paraffin (range: 0–4901 days) to the number of processed reads (after TrueQuant PCR bias elimination). We found that the number of reads decreased with time in paraffin Fig. , indicatAnalyzing the effect of storage time on the number of detected genes, we found a subtle decrease in the number of detected expressed genes over time Fig. . MACE stR2 = 0.120, p = 0.071, Fig. R2 = 0.869, p < 0.001, Fig. It is interesting to note that no statistically significant correlation between storage time and number of expressed genes detected was observable when analyzing the entire 5000-day period . Even with only ~100,000 reads, MACE still detected ~12,000 genes. Within the first 3000 days in FFPE we observed a mean number of reads of at least 1 million Fig. , indicatFFPE tissue is widely available in pathology archives, and a potential source of material for whole-transcriptome sequencing. Several studies have demonstrated the use of FFPE tissue for mRNA expression profiling using standard 5′ RNA-Seq technology , 25–27. To elaborate on the potential advantages and flaws of MACE sequencing, we first compared traditional RNA-Seq with MACE in fresh, unfixed tissue. The majority of the expressed genes in our samples were detected by both methods. Furthermore, we observed no advantage of either method in detecting genes of low, average or high abundance—MACE performed at least at the level of standard RNA-Seq in all three categories. When comparing DEGs between standard RNA-Seq and MACE, the significantly higher gene length  of the upregulated genes in standard RNA-Seq as well as the lesser gene length  of the downregulated genes in standard RNA-Seq indicate that at least some of the DEGs between both methods result from a length bias, which leads to an incorrectly increased expression of longer genes as well as an incorrectly lower expression of shorter genes in RNA-Seq, respectively  and FFPE tissue  are available. Recent studies claim that archival specimens with differing storage times do not seem to vary significantly in DNA quantity and quality  and thatOur study raises the question of the necessity of performing studies previously conducted with standard RNA-Seq methods again with the novel MACE technique. Since we did not detect a biologically relevant difference between both approaches, we do not consider repeating experiments a necessity in general. Nevertheless, the length bias in standard RNA-Seq, extensively approached in this study, should be considered especially when gene sets particularly enriched with short or long genes  are asseTaken together, this study comparing FFPE and fresh samples of the same tissue in parallel strongly suggests that MACE results are robust and rather insensitive to alterations by FFPE processing. Storage of FFPE tissue is associated with an initial loss of RNA amenable to MACE detection. However, detection patterns appear to be stable over time and MACE transcriptome analysis is feasible even after 13 years of storage. Thus, 3′-MACE-RNA sequencing allows to perform transcriptomic analyses in aged, archived FFPE tissue samples, which may have been considered unsuitable for RNA sequencing in the past. This offers novel opportunities, especially to advance the molecular characterization of rare specimens stored in histological archives.Supplementary Figure 1. Differentially expressed genes (DEG) upregulated in MACE and standard RNA-Seq.Supplementary Figure 2. Transcript types found with RNA-Seq or MACE (unfixed and fixed in FFPE).Supplementary Table 1. Study subjects.


RNAs are trafficked and localized with exquisite precision inside the cell. Studies of candidate messenger RNAs have shown the vital importance of RNA subcellular location in development and cellular function. New sequencing- and imaging-based methods are providing complementary insights into subcellular localization of RNAs transcriptome-wide. APEX-seq and ribosome profiling as well as proximity-labeling approaches have revealed thousands of transcript isoforms are localized to distinct cytotopic locations, including locations that defy biochemical fractionation and hence were missed by prior studies. Sequences in the 3′ and 5′ untranslated regions (UTRs) serve as “zip codes” to direct transcripts to particular locales, and it is clear that intronic and retrotransposable sequences within transcripts have been co-opted by cells to control localization. Molecular motors, nuclear-to-cytosol RNA export, liquid-liquid phase separation, RNA modifications, and RNA structure dynamically shape the subcellular transcriptome. Location-based RNA regulation continues to pose new mysteries for the field, yet promises to reveal insights into fundamental cell biology and disease mechanisms. Xenopus and Drosophila eggs, and were followed by similar demonstrations in yeast, mammalian neurons, and in developing Drosophila embryos. Such studies have revealed that sequences within  RNAs, also termed “zip codes,” direct the localization of mRNAs, typically by recruiting proteins .A eukaryotic cell is highly organized, with biomolecules localizing to specific regions of the cell that are integral to their function. For more than three decades, evidence has been accumulating to suggest that the RNAs for thousands of genes show pronounced subcellular localization, and that this localization is an essential mechanism for post-transcriptional regulation. RNA localization influences RNA folding, editing, splicing, degradation, translation, binding partner, catalytic activity, and even the fate of the protein that is encoded. Some of the earliest experiments examining the localization of messenger RNAs (mRNAs) were performed in cis and trans regulators of RNA localization. Although it now appears that RNA subcellular localization is the norm rather than the exception for both coding and noncoding RNAs , can direct localization of transcripts; these findings have since been extended to mammalian systems. For example, the Vg1 mRNA in Xenopus was found to localize to one  pole, whereas the bicoid mRNA in Drosophila egg cell was shown to localize to the anterior pole and to require the protein Staufen for localization  zip code region in the 3′ UTR that is essential for localization  can contain sequence elements within that direct them to subcellular locales , recognized by the protein hnRNPU, that aids in localizing it to chromatin  that localizes to a specific locale and then to systematically test whether sequences within are necessary and sufficient to direct localization . Such anspeckles . Similareriphery , likely eriphery . Anotherhromatin ; hnRNPU in  spanning the envelope has been extensively studied , with troskar mRNA in Drosophila  and outer mitochondrial membrane (OMM) has been through proximity-specific ribosome profiling, in which ribosomes in specific locations undergo proximity biotinylation . These rDespite these existing sequencing technologies, many critical locations within the cell, including membrane-bound and membrane-less organelles, continue to be difficult, if not impossible, to interrogate. Furthermore, unlike live-cell-imaging approaches, these sequencing-based approaches are generally not well suited to study the dynamics of transcript localization. However, a new approach discussed below using proximity labeling of RNAs in living cells provides an opportunity to investigate RNA subcellular spatial dynamics , albeit A recent approach to determine the RNAs at subcellular locales, called APEX-seq, yields an unbiased transcriptome that can be applied to study membrane-less and membrane-bound organelles. APEX-seq leverages an engineered enzyme called APEX2  that can be targeted to specific cellular locales by fusing it to a protein or peptide that is known to localize to the desired location. Upon providing the reagents biotin-phenol and hydrogen peroxide, APEX2 generates biotin-phenoxy radicals that result in the spatial tagging of nearby metabolites within cells with a biotin tag . For exaIn the initial demonstrations of obtaining subcellular RNAs using proximity labeling, APEX was used to label proteins, which were then cross-linked with RNAs nearby. These biotin-labeled proteins were then enriched by streptavidin-biotin pulldown, and the cross-linked RNAs were released and sequenced. Using this cross-linking approach, called APEX-RIP  and prox7G) cap-binding protein eIF4E1, while also obtaining subcellular proteomic information. In addition, changes in RNA localization upon heat shock and stress granule assembly on the timescale of minutes were tracked , derived from an antisense Alu element, which they named SIRLOIN , that promotes nuclear retention , in which tens of thousands of sequences, typically 75–200 nt in length, can be interrogated. Using MPRAs, along with machine-learning models, particularly convolutional neural networks (CNNs) , is likeetention . By screetention , they ider study .MPRA-based screens are likely going to be a powerful way to screen for zip code components, including sequence motifs and structural elements. Concomitantly, MPRA experimental and computational strategies continue to improve, and it is now possible to test more than 100 million sequences .6A) modification to be important for facilitating the nuclear export of mRNAs, with modified transcripts “fast-tracked” to the cytosol for translation (Next-generation-sequencing (NGS) approaches, including using the Illumina platform, continue to transform in biology. However, a significant limitation continues to be the relatively short sequencing reads  generated. Fortunately, the latest third-generation approaches such as Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio) provide much longer-read sequencing reads (>1000 bp) and can sequence RNA directly without having to reverse transcribe it to make complementary DNA (cDNA) . By beinnslation .Although RNA localization studies have a rich history spanning more than three decades, many critical issues in the field remain unanswered. The central question continues to persist: Why do cells localize their RNA contents? In some cell types, such as neuronal cells in which the distances involved for transporting biomolecules are vast, it is easy to rationalize that actively transporting mRNAs to their destination to be locally translated to make proteins would be convenient and efficient. However, it remains unclear why RNA subcellular localization is ubiquitously observed in almost all cell types, including ones in which the process of diffusion should be fast (seconds or less). To address the question of why cells localize their RNA contents, we must first explain the following questions.A vital issue in the field is ascertaining to what extent the observed subcellular RNA localization is translation-dependent, and whether RNAs can be transported, particularly actively by molecular motors, with the ribosome engaged in the translation of the mRNA. It was generally accepted that the transport of mRNAs occurs through mRNPs that are translationally repressed until they get to their destination . FurtherUnderstanding how RNAs find their destination continues to be a fascinating problem that will require imaging, sequencing, and biophysical insights. Cells rely on different approaches to transport mRNAs, and future studies will likely also focus on understanding how organelles are optimized and regulated to control the localization of transcripts to them .6A has been shown to influence the nuclear export of RNAs, with the m6A-binding protein YTHDC1 mediating this process (6A readers that promote export (6A-modified mRNAs are enriched in stress granules (SGs), and the m6A-binding YTHDF protein is critical for SG formation , will be important in understanding the regulation of these molecules. circRNAs have received a lot of interest in recent years, and it is known that they can code for proteins  and showSubcellular RNA localization is an essential but underappreciated aspect of gene regulation. This review focuses on the eukaryotic cell, but even prokaryotic cells are known to have highly localized RNAs . In prok


Long non-coding RNAs (LncRNAs) can bind to other proteins or RNAs to regulate gene expression, and its role in tumors has been extensively studied. A common RNA binding protein, UPF1, is also a key factor in a variety of RNA decay pathways. RNA decay pathways serve to control levels of particular RNA molecules. The expression of UPF1 is often dysregulated in tumors, an observation which suggests that UPF1 contributes to development of a variety of tumors. Herein, we review evidence from studies of fourteen lncRNAs interact with UPF1. The interaction between lncRNA and UPFI provide fundamental basis for cell transformation and tumorigenic growth. Historis-acting . There arby gene ; (2) regrby gene ; and (3)rby gene . There a regions ; (2) the regions ; and (3) regions . LncRNAs regions .Currently, about 2,000 RNA-binding proteins (RBPs) have been identified in humans . RBPs haUPF1 is a common RNA-binding protein, and is a critical molecule to the RNA decay pathway. The most common RNA decay pathways in which UPF1 participates are nonsense-mediated mRNA decay (NMD)  and stauIn this review, we primarily discuss dysregulated lncRNAs in tumors, and the way in which these lncRNAs interact with UPF1 to regulate gene expression in tumors .In order to understand the nature and effects of the interactions between lncRNA and UPF1, we can divide their mechanisms of action into the following four categories .SNHG6 is upregulated in hepatocellular carcinoma (HCC) tissues and cell lines, in which it promotes the proliferation, invasion and migration of hepatocellular carcinoma cells, inhibits apoptosis, and induces cell cycle . UPF1 isThe lncRNA ZFPM2-AS1 is upregulated in lung adenocarcinoma tissues and cell lines, promoting the invasion and epithelial-mesenchymal transition (EMT) of lung adenocarcinoma cells . ZFPM2, MALAT1 is one of the most studied lncRNAs . MALAT1 The upregulation of lncRNA NR4A1AS expression in colorectal cancer tissue is positively correlated with the expression of NR4A1 mRNA . NR4A1ASA considerable body of research shows that lncRNA is widely involved in tumorigenesis and the progression of various cancers. LncRNA regulates the expression and functions of other genes by binding to DNA, RNAs and proteins, and therefore participates in producing the tumor phenotype . As an RJH and XM contributed to the conception of the study, discussed, and improved the revised manuscript. JH wrote the manuscript. Both authors read and approved the final 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.


Trp53 levels. Evidence indicates that Hsf1, a master regulator of stress response, mediates B2 RNA processing in hippocampal cells and is activated during amyloid toxicity, accelerating the processing of SINE RNAs and gene hyper-activation. Our study reveals that in mouse, SINE RNAs constitute a novel pathway deregulated in amyloid beta pathology, with potential implications for similar cases in the human brain, such as Alzheimer’s disease (AD).The functional importance of many non-coding RNAs (ncRNAs) generated by repetitive elements and their connection with pathologic processes remains elusive. B2 RNAs, a class of ncRNAs of the B2 family of SINE repeats, mediate through their processing the transcriptional activation of various genes in response to stress. Here, we show that this response is dysfunctional during amyloid beta toxicity and pathology in the mouse hippocampus due to increased levels of B2 RNA processing, leading to constitutively elevated B2 RNA target gene expression and high  Trp53  RNAs called B2 SINE RNAs (The number of patients with Alzheimer’s disease (AD) is expected to skyrocket in the upcoming years . The exaTrp53  and, subval SRGs . Trp53 ag Mir34c . This mig Mir34c . In contal death . Given ttivation , high TrINE RNAs , raisingSINE non-coding RNAs are transcribed by repetitive small interspersed nuclear elements (SINEs), with the subclass B2-repetitive elements being one of the most frequent in mouse . SINE B2The above findings have revealed a novel role in cellular function for processing of SINE B2 RNAs (hereafter referred simply as B2 RNAs) through the activation of a number of SRGs regulated by them . However, an association of the processing and destabilization of B2 RNAs with any pathological cellular process remains unknown. Here, given the importance of SRGs in hippocampal neuronal function, we examine whether this newly described B2 RNA-SRG regulatory mechanism is linked with pathological processes, focusing on transcriptome response to amyloid beta toxicity and pathology. To this end, we investigate whether B2-SRGs are indeed deregulated during amyloid pathology, which would imply a role for B2 RNAs in this condition and we examine whether amyloid toxicity is connected with changes in B2 RNA processing. Subsequently, we investigate the further upstream molecular mechanisms underlying any potential deregulation of B2 RNA processing in response to amyloid toxicity in hippocampal neural cells.In a previous study, we have identified genomic locations that are subject to regulation by SINE B2 non-coding RNAs during response to thermal stress (heat shock) through binding and suppression of transcription by the RNA Pol II at the pre-stimulus state. Upon induction of cellular stress through the application of a stimulus, SRGs in these locations become activated through B2 processing and release of RNA Pol II suppression . A list As shown in Among the biological processes potentially affected by B2 RNAs that were identified above was learning. We and others have already shown that learning processes in the mouse hippocampus are connected with the transient activation of a number of learning-associated genes and pathways, including many known SRGs . For thiMir34c, which is induced among others by Trp53 and controls it in a negative feedback loop manner  pre-symptomatic stage with undetectable (very low) amyloid plaque load    . Differe3/group) , includi3/group) , of whic3/group) . These 73/group) . Consist3/group) . In partctively) . This isctively) . In contctively) . A validctively) , these actively) . Thus, aThese findings show a transcriptome wide hyper-activation of certain B2-SRGs during the active neurodegeneration phase of amyloid pathology.Given the role of B2 RNAs in the regulation of SRGs, we hypothesized that the observed hyperactivation of B2-SRGs in the hippocampus of 6-month-old APP mice may reflect a similar upstream deregulation at the level of the B2 RNAs.To test this, we employed a customized version of RNA sequencing and analysis used in our previous study  that all0.05, n = 3/group). This increase was observed only in the 6-month-old mice , a member of the PRC2 protein complex, Ezh2, was reported as being responsible for the B2-RNA-accelerated destabilization and processing during response to stress . HoweverIn our earlier study that described the induction of B2 RNA processing by Ezh2, it remained unclear how Ezh2 exerted its impact on B2 RNAs, since Ezh2 lacked any known RNAse activity . HoweverEzh2, Hsf1 is expressed in neural tissues and especially in hippocampus. These findings provided an indication that Hsf1 may be implicated in B2 RNA biology and that it is also expressed in neural cells, which urged us to test further its expression pattern in our biological context. Hsf1 levels were found to be upregulated in APP 6-month-old mice compared to control group of the same age    in the R3/group) . As mentTo check this, we investigated whether the interaction between B2 RNA and Hsf1 can accelerate B2 RNA destabilization. In particular, we incubated full-length B2 RNA with the Hsf1 protein in vitro. As shown in This data shows that Hsf1 has the potential to accelerate B2 RNA processing in vitro.The increased levels of Hsf1/B2 RNA processing in APP 6-month-old mice raised the question whether response to amyloid toxicity in hippocampal cells is connected with an Hsf1-mediated increase in B2 RNA processing. In order to test this, we employed a hippocampal cell culture model using the a HT-22 cell line, which has been used extensively in the past as hippocampal cell stress model . We incuFosb and Mitf that have been connected with AD  and include a well-known immediate early gene (Fosb), genes associated with sensitivity to amyloid toxicity   , as wellrs, Fosb).We then questioned whether by inducing an artificial degradation of B2 RNA, we would be able to induce expression of B2-SRGs in our model system of HT22 cells in the absence of any stimulus such as amyloid beta. To achieve this, we employed a similar approach and the same LNAs against B2 RNA that we used in our previous study . Application of the LNA against B2  was ableHsf1 or a scramble LNA (control) followed by incubation with the 1–42 peptides, that subject the cells to amyloid toxicity stress, or the respective control peptide . Treatment with with the anti-Hsf1 LNA during transfection with the amyloid beta peptides also led to a decrease in protein levels of Hsf1 . To get an indication whether such transcripts may contribute to our data, we have separated the B2 elements against which we map the RNA fragments into two categories, those that fall within exonic/genic regions and those outside these regions . AlthougHsf1 are certainly expected to affect transcription also through Hsf1’s conventional transcriptional factor function while there are still many SRGs that are not directly regulated by B2 RNA. Thus, B2 RNA processing described here does not constitute the only one but just one of the parameters in the equation of SRG regulation. It remains unclear which is the interplay between Hsf1 traditional transcription factor activities and its ability to affect B2 RNA processing and whether there is any overlap or synergies. For example, it remains unclear what percentage of activated genes are activated though Hsf1 DNA binding and what through binding of B2 RNA and subsequent release of suppressed Pol II activity.Our results suggest that B2 RNA regulation is a new process implicated in response to stress in amyloid pathology but it is definitely not the only one. Since B2-SRGs are highly interconnected and interweaved into various pathways, the impact of SRG hyperactivation by B2 RNA processing may extend to pathways that lie downstream of SRGs and affect various gene programs without binding directly B2 RNA. However, here it should be noted that high levels of Moreover, given how easily B2 RNA is processed in the presence of certain proteins, Hsf1 may be only one of the factors accelerating B2 processing in mouse hippocampus as we are just beginning to understand the implications of this form of SINE RNA regulation in cells. A broader role of SINE RNA processing in brain physiology and pathophysiology constitutes, thus, a significant possibility that could further revise our understanding of these RNAs as something more than just transcriptional noise and ‘junk DNA’ products.4OH at a concentration of 2.1 mg/mL, sonicated for 5 min, aliquoted, dried, and stored at −80°C for further use (see below).The amyloid beta 1–42 peptides and the respective control peptides (having the reverse aa sequence compared to 1–42 peptides) were synthesized by Sigma Aldrich’s custom synthesis service using the following sequences: DAEFRHDSGYEVHHQKLVFFAEDVGSNKGAIIGLMVGGVVIA (peptide 1-42) and AIVVGGVMLGIIAGKNSGVDEAFFVLKQHHVEYGSDHRFEAD (Reverse). Upon receiving, the peptides were dissolved in 10% NHImmunohistochemistry was done as described in our previous study  for the CVCL_0321). Cells were provided by the vendor tested negative for infectious diseases by a Mouse Essential CLEAR panel by Charles River Animal Diagnostic Services and verified to be of mouse origin and negative for inter-species contamination from rat, chinese hamster, Golden Syrian hamster, human, and non-human primate (NHP)  as well as negative for mycoplasma contamination. Cells were cultured in DMEM (Sigma) and 1% Penicillin/Streptomycin (Gibco). Cells were thawed and passaged at least 3 days before the transfection date in order to allow sufficient time for cells to recover from the stress of cryopreservation and not interfere with the assessment of cellular response to stress in subsequent experiments. For knocking down of Hsf1 mRNA levels, we used an LNA long RNA GapmeR against Hsf1 (Exiqon/Qiagen) with the following sequence: 5′-′GAAGGATGGAGTCAA-3′ and an LNA long RNA GapmeR with the following scramble sequence: 5′-CCTCAATTTTATCAC-3′. For knocking down B2 RNA transcripts, we used an anti-B2 LNA pool consisting of five LNAs, synthesized using the K and E DNA and RNA synthesizer: 1. 5' - G*T*T*A*CGGATGGTT*G*T*G* - 3′; 2. 5′- A*G*A*T*CTCATTACA*G*A*T*- 3′; 3. 5′ - A*G*A*T*CTCATTACG*G*A*T* - 3′’; 4. 5′ - A*G*A*T*CCCATTACA*G*A*T* - 3′; 5. 5′ - A*G*A*T*CCCATTACG*G*A*T* - 3′; 6. 5′-T*G*TAGCTGTCTTCA*G*−3′. Nucleotides were ordered from Sigma Aldrich as DMT phosphoramidites. The day of LNA transfections, following 5-min incubation with TrypLE Express Enzyme (Gibco) (1x), cells were passaged and transferred to a six-well plate at a 100,000 cells/well density and LNA transfections were performed simultaneously, using the HiPerfect reagent (Qiagen). Transfection was performed as follows: Firstly, LNAs were reconstituted in nuclease-free water to 50 μM. Subsequently, 3 μL 50 µM LNA were mixed and incubated with 4 µL Hiperfect reagent and 30 µL nuclease-free water, at room temperature for 20 min, and then added drop-wise to cells that had just been plated in 1 ml of medium/well (still not attached) to a final LNA concentration of 150 nM. For anti-Hsf1 LNAs transfections, incubation with amyloid beta (peptide 1-42) and control peptides (Reverse) was performed 24 hr after transfection with LNAs. Peptides were initially dissolved in DMSO for incubation at 37°C for 1 hr and then added to cells to a final concentration of 30 µM for 6 hr before treating with 0.5 mL TrypLE (Gibco), pelleting cells at 1000 rpm for 5 min and resuspending the pellet in 1 mL Trizol reagent (Thermofisher) for RNA extraction based on Manufacturer’s instructions. For anti-B2 LNA, transfection and incubation lasted 6 hr before RNA extraction.HT22 cells, from an immortalized mouse hippocampal cell line  . Thermocycler conditions are as follows: 3 min at 95°C  × 40 cycles. Fluorometer readings were taken during extension and qPCR was performed using the Bio-Rad CFX384 Real-time detection system. Standard curves were prepared for relative expression and the analysis of PCR efficiency by pooling 2 µL of each cDNA sample and standard diluting SD1: 1:5, SD2: 1:10, SD3: 1:20, SD4: 1:40. Samples were either analyzed by standard curve relative expression or RNA was extracted using Trizol reagent as described and reverse transcribed using Superscript III  by the following method: 50 ng total RNA was mixed with 100 ng random primers  and 1 µL of 10 mM dNTP mix. The mixture was incubated for 5 min at 65°C and placed immediately on ice. The mixture was then incubated with 4 µL of 5x First strand buffer, 1 µL of 0.1M DTT and 0.4 µL Superscript III  for 5 min at 25°C, 60 min at 55°C and 15 min at 70°C. cDNA was analyzed by qPCR using 2 µL of 1:20 diluted cDNA, 0.5 µL of 10 µM of each gene-specific primer, 2 µL HGGGGCTGGTGAGATGGCTCAGTGGGTAAGAGCACCCGACTGCTCTTCCGAAGGTCCGGAGTTCAAATCCCAGCAACCACATGGTGGCTCACAACCATCCGTAACGAGATCTGACTCCCTCTTCTGGAGTGTCTGAAGACAGCTACAGTGTACTTACATATAATAAATAAATAAATCTTTAAAAAAAAA - 3′. The template was amplified by PCR using a T7 promoter sequence as the forward primer: 5′-TAATACGACTCACTATAG and the following sequence as reverse primer: 5′-TTTTTTTTTAAAGATTTATTTATTTATTATATGTAAGTACA. B2mut4b was transcribed from the following template (same primers): taatacgactcactataGGGCTGGTGAGATGGCTCAGTGGGTAAGAGCACCCGACTGCTCTTCCGAAGGTCCGGAGTTCAAATCCCAGCAACCACATGGTGGCTCACAACCATCCGTAACGAGATCTGACTCCCTCTTCTTCTGAAGACAGCTACAGTGTACTTACATATAATAAATAAATAAATCTTTAAAAAAAAA. Primers were diluted to 10 mM and PCR was performed using the NEB Q5 polymerase, Q5 reaction buffer (10x), Q5 high GC enhancer (10x). The reaction proceeded at hot start 98°C – 30 s  X35 cycles, 72°C – 10 min. The samples were then analyzed by agarose gel electrophoresis  and the bands were gel extracted at the desired size and purified using the BioBasic EZ-10 gel extraction kit (BS353). A subsequent PCR was then repeated and 1 µg of the amplified g-block was then in vitro transcribed by T7 RNA polymerase  for 2 hr at 37°C. The reaction was buffered using the T7 RNA polymerase buffer in addition to 10 mM NTPs  in a final 20 µL reaction. RNA was purified using the Zymo Research RNA Clean and Concentrator - 25 kit. Sequences of RNA controls used were as follows: Control #1(G-44U): 5′GCCCCGUUGCAAUGGAAUGACAGCGGGUAUGUUAAACAACCCCAUCCGUCAUGGAGACAGGUGGACGUUAAAUAUAAACCUGAAGAUUAAACAUGACUGAAUCUUUUGCUACUAGAAUGGUGAGCAAGGGCGAGGAGCUGUUC 3′, control #2:(5′ Zika UTR scramble):5′ UACAAUCACGAAAGUCAAUUAUAGUUUCGAGUCGUAACGAGAACAUUUCCCGCGGACCAAUUUAAGGAGUAACUAAAGUGUGAAAUGAUUCCGGAAUACUGUUGAAAUUGCGGAUCGAGCUUGCAGCCGUUAAAUUACCGGACGUUAGUGAAGUGCAGAUAUG 3′.B2 template for in vitro RNA transcription was ordered as IDT g-block (lower case denotes the T7 promoter sequence): 5′- taatacgactcactata 2, 0.02 mM EDTA, 0.01% NP-40, 1% glycerol, 0.2 mM DTT). Hsf1 protein incubations were performed with phosphorylated, recombinant, His-tagged Hsf1 . Hsf1 working concentrations were 250 nM unless otherwise specified, diluted in TAP buffer. PNK  was used as a control protein because it is an RNA-binding protein that is used in the construction of our short RNA libraries and we wanted show that short RNA seq data are free of such confounding factors that could potentially generate artificial fragments. PolyA  was used as control protein because it is an RNA-binding protein that should not process B2 RNAs. Denatured Hsf1 was prepared by diluting in TAP buffer as above and heating at 95°C for 3 min; denatured Hsf1 was used as a control to ensure buffer components of Hsf1 themselves were not responsible for B2 RNA processing.B2 RNA re-folding and B2 RNA – Hsf1 incubations were performed as described previously (14). In brief, in vitro-transcribed B2 RNA was folded with 300 mM NaCl through incubation for 1 min at 50°C and cooling at a rate of 1°C/10 s until 4°C. Subsequently, B2 RNAs were incubated at a final concentration of 0.4 µM unless otherwise stated with the addition of Hsf1 diluted in TAP buffer . Gel analysis occurred on Amersham Typhoon instruments. Band absorbance was analyzed using ImageJ area under the curve software and normalized by the ratio of experimental over initial as described previously .Using the miRvana miRNA size selection kit (Thermo Fisher) as described before, 1.5 μg total RNA was size separated into short and long fractions . In brieAB_10616511). After incubating primary antibody, blots were washed using 0.1% PBST and reprobed with anti-rabbit-HRP conjugate secondary antibody . Proteins were visualized using Pierce enhanced chemiluminescence detection system . Blots were imaged in an AI600 imager  and densitometry performed using ImageJ.HT22 cells were seeded at 100,000 cells per well and transfected with LNA in a six-well plate as described. Cells were harvested and lysed using RIPA lysis buffer with protease and phosphatase inhibitors added. Next, the cell suspension was centrifuged at 13,000 rpm for 20 min at 4°C, supernatant was aspirated and pellet discarded. Protein concentration was determined using a Bradford assay . Equal amounts of soluble protein were loaded (25 µg) for resolving with SDS-PAGE. Proteins were transferred onto nitrocellulose membrane , blocked for 1 hr with 1% milk in 0.02% PBST at room temperature. Individual proteins were detected using polyclonal rabbit HSF1 antibody  was run for quality control of generated reads in fastq format. Subsequently, standard Illumina adaptor sequences were trimmed off using cutadapt-1.18 (https://doi.org/10.14806/ej.17.1.200). Short-RNA-seq reads were mapped to mouse reference genome (UCSC mm10) (November 2017) using bwa-0.7.17 in single-end mode with default aln parameters  was used to obtain number of long reads overlapping with B2 loci , as well as the number of reads overlapping with tRNA loci from −5 to 15 bp. Processing ratio for each sample was calculated by processed B2 count obtained from the in house python scripts normalized by tRNA from −5 to 15 bp and small reads fastq read count, as well as B2 count and long reads fastq read count: [Small fragments (position 95–110)/ [tRNAs/small RNA fastq]]/[B2RNA/long RNA fastq]. The full length of B2 consensus sequence is 188nt, and this is the one we use for the in vitro experiments. However, structure of the RNA has been resolved only for the 155nt  were performed using an in house python script. In brief, the script constructs a read accumulation metagene model around a hypothetical set of genomic points, in our case the start site for all B2 elements (TSS), in which the numbers of reads (or read 5' ends) around each different TSS were calculated and attributed to defined points in the model. B2 element coordinates are based on the UCSC genome browser RepeatMasker track (as of November 2018). To calculate the B2 processing ratio, Babraham NGS analysis suite Seqmonk 1.38.2  or in the heatmap of the same figure, where each gene is presented in a separate row, and for which TPM values are used. For data visualization, statistics and differential expression analysis, we employed R (version 3.4.3) (https://www.R-project.org/) and the package DESeq2  and TPM (Transcripts Per Million) for genes were generated using StringTie-1.3.4d  with thee DESeq2 . DiffereHsf1 metagene analysis, we used peak.txt files of Hsf1 peaks for ChIP-seq from For Short- and long-RNA-seq raw data have been deposited to GEO with access number GSE149243. In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Review Commons.]After thorough discussion, the reviewers agreed that the manuscript by Zovoilis et al. is much improved from the original submission to Review Commons and that the authors have addressed many of the original concerns raised by reviewers. However, two major concerns remain, and reviewers agreed to encourage a resubmission addressing these.B2 RNAs encoded from SINE B2 elements have been directly implicated in stress response by its inherent ability to bind RNA Pol II and suppress stress response genes (SRG) in homeostatic conditions. However, upon stimuli, B2 RNAs are cleaved and degraded, resulting in the release of RNA polymerase II (RNAPII) and upregulation of SRGs. Previous work from the senior author of this manuscript identified the Polycomb repressive complex 2 (PRC2) component EZH2 to be the B2 RNA processing factor, cleaving B2 and releasing RNAPII. SRGs are upregulated upon stress, for example in age associated neuropathologies like Alzheimer's disease (AD). Considering that hippocampus is a primary target of amyloid pathologies and given that SRGs are suggested to be key for the function of a healthy hippocampus, the authors set out to understand the role of B2 RNAs that are linked to SRG regulation in the mouse hippocampus with amyloid pathology. They use disease relevant in vivo and in vitro models combined with unbiased RNA seq data analysis for this endeavor, which indicate the potential relevance of B2 RNAs in APP-mediated neuronal pathologies in mice while also identifying Hsf1 as the factor cleaving B2 RNAs in the hippocampus. The work is deemed interesting and identification of Hsf1 as the processing factor for B2 RNAs in the hippocampus is significant.1) Reviewers remain concerned that the bulk of the analyses relies on genes that were identified as B2-regulated SRGs in a prior experimental system (heat-shocked NIH3T3 cells) that is completely different from the amyloid pathology models used here. The authors sought to address this issue in the revised manuscript, but questions remain. Indeed, the new Supplementary tables 4 and 5 in Supplementary file 1 show that of the ~1600 B2-SRGs identified in NIH3T3 cells, only 72 show expression patterns consistent with the regulatory model proposed; moreover, this was using FDR<0.2. How many genes would be left with FDR<0.05? The authors did include important new data in the HT22 cell model showing that mRNA levels for four genes increase after treatment with a B2-targeted LNA. These data are compelling, but a few additional controls are needed. Figure 6F needs negative controls showing qRT-PCR of genes that are not thought to be B2-SRGs. In Figure 6E, it is important that the full length B2 RNA is being detected (i.e. a PCR product ~180 nt) since their model states that these genes are repressed by full length B2 RNA prior to its degradation. The data in Figure 6 support the model that these four genes are under B2 control, but they don't show the relationship with amyloid pathology. What do the expression patterns of the 4 genes in Figure 6F look like in the mouse RNA-seq data ? Does the amyloid beta peptide treatment of the HT22 cells no longer induce expression of these four genes in the presence of the B2 LNA?We thank the reviewers for this comment. We now provide more clarity and supporting data to address this comment. In particular:a) Our model does not propose that all B2-SRGs are deregulated in APP mice or that all deregulated genes in APP mice are B2-SRGs. Instead, it shows that a subset of the B2 SRGs is deregulated in amyloid pathology. This may not have been clear in the model described in our initial manuscript , in which we have used the general term “Stress response genes” to describe genes under this regulatory mechanism. In the revised Figure 9 model we have now substituted this term with the more accurate term “Target genes” to prevent any confusion and denote that there may be a variety of B2 RNA-targeted genes in different biological contexts. Moreover, our current data addresses B2 RNA-mediated regulation only in the context of amyloid beta pathology and focuses on differentially expressed B2 SRGs based on a statistical modeling approach . Beyond this set of differentially expressed genes, we searched for additional SRGs that are expressed in the hippocampus, yet, they may be associated with other hippocampal functions that are independent from amyloid beta pathology. The expression of hippocampal B2-SRGs would be expected to correlate with B2 RNA processing. As shown in the new Figure 8—figure supplement 1E and the respective table (new Supplementary table 12 in Supplementary file 1) a detailed breakdown of these B2-SRGs with regard to expression in hippocampal cells and correlation with B2 RNA processing reveals 659 B2-SRGs that are sufficiently expressed in our tested hippocampal samples and, of those, more than 63% shows a weak (11%) or strong (52%) correlation between expression levels and B2 RNA processing ratio. This data suggests that, for a large number of the B2-SRGs previously identified in the context of heat shock, correlation between gene expression and B2 RNA processing ratio holds true also in the context of hippocampal cells, independently of the presence of amyloid beta pathology.b) By applying DESeq2 to statistically model the expression changes observed between 6m old WT and APP mice we obtained 72 B2-SRGs upregulated in 6m old APP mice (listed in Supplementary table 5 in Supplementary file 1). All of those B2-SRGs have a p-value < 0.05, with 34 of them belonging to the group with an FDR value threshold below 5% and the rest 38 to the group with an FDR value at least below 20%. We used a more flexible FDR threshold since expression dynamics of the 72 differentially expressed genes  show an almost identical pattern with those ones of several other B2-SRGs that may have been missed by the DESeq2 . This strongly suggests that use of DESEq2 is rather conservative in our case for reasons listed in the respective note in the legend of Figure 2—figure supplement 3. In order to mitigate any concerns for an increased number of false positives in our data due to selection of a higher FDR threshold, in the new Figure 2—figure supplement 2, we now provide validation through RT-qPCR of the DESeq2 results. We have selected 12 of the differentially expressed genes  and tested them through RT-qPCR . The majority of the genes tested have been intentionally selected from the group with the higher FDR threshold (8 out of 12 have an FDR more than 5% and less than 20%). The resulting RT-qPCR data presented in Figure 2—figure supplement 2B are in alignment with the RNA-seq results for the same genes presented in Figure 2—figure supplement 2A. Thus, through the use of an orthogonal validation technique, the differentially expressed genes identified by DESeq2 in 6m APP mice indeed correspond to true positive findings. This data, together with data in Figure 2—figure supplement 3, support further that application of a standard RNA-seq differential expression statistical model such as DEseq2 in our case may indeed be a rather conservative approach. Nevertheless, given the widespread use of DESeq2, we still suggest the use of this approach in the main body of the study in order to facilitate comparison of our data with those from other groups in the future.c) In order to substantiate further the connection between B2-SRGs previously identified in heat shocked NIH/3T3 cells and B2 RNA destabilization we have increased the number of B2-SRGs tested through RT-qPCR in the B2 KD assay in hippocampal cells . In the new Figure 7C, we now show that, as previously observed in NIH/3T3 cells, also in hippocampal cells, destabilizing B2 RNA leads to increase in the expression of these genes. In addition to these 11 genes, we now include 5 negative controls (non-B2 SRGs) that showed no change during treatment. Among the negative controls we have also intentionally included non-B2-SRGs such as Adcyl1 and Kalrn, both of which are upregulated in amyloid beta pathology, to support further the specificity of our findings (i.e. being upregulated in amyloid beta pathology does not mean regulation by B2 RNA unless being a B2-SRG).d) Indeed, in Figure 7A we test the unprocessed B2 RNA encompassing the full Pol II binding region (80-132) including all cutting points. The reverse primer is located downstream at position 142. Making a reverse primer beyond the position 142 is not possible as it overlaps with B2 RNAs poly-A repeats. The primers are now listed in the Materials and methods.e) Data for the expression patterns of all genes in the new Figure 7C  that are differentially expressed in mouse APP and WT mice are now presented in Figure 2—figure supplement 2A for all three ages and conditions.Does the amyloid beta peptide treatment of the HT22 cells no longer induce expression of these four genes in the presence of the B2 LNA?”. To our understanding, we are asked whether treating the HT22 cells with amyloid beta and B2 LNA induces expression of these genes. Based on the data presented in the manuscript the amyloid beta treatment induces expression of these four genes  as does the B2 LNA independently . Thus, we are a little unsure on the scope of such as experiment as we feel that inoculating B2 LNA together with amyloid beta would not add any additional information regarding our model. Such an experiment would have been informative if B2 LNA treatment was inhibiting SRG activation as in case of Hsf1 LNA , however, since both the amyloid and B2 LNA activate SRGs, we did not see any reason for combining them in one experiment as we did in case of Hsf1 in Figure 8, in which we combined LNA treatment with amyloid beta treatment.f) “2) Reviewers remain concerned about the strength of the data regarding the role of Hsf1 in B2 RNA processing  The negative controls with recombinant proteins prepared similarly to Hsf1, and with similarly sized control RNAs are critical. In addition, the full gels for these experiments need to be shown so the formation of short B2 RNA products can be evaluated in conjunction with the loss of the full length B2 RNA. This will help distinguish between specific processing controlled by the B2 ribozyme/Hsf1 activity versus non-specific breakdown. Moreover, the sizes of the in vitro processed products should correlate with the 5' end peaks from Figure 3A if the cellular and in vitro processing indeed arises from the same mechanism.We are grateful to the reviewers for this comment. Although some of these controls had already been presented in our previous studies, including control proteins not inducing B2 RNA processing and control RNAs not destabilized as rapidly as B2 RNA, we fully understand that it is due to the proposed biochemistry of B2 RNA as a potential ribozyme, and the difficulty to distinguish from non-specific RNA degradation, that additional data are required. To this end we respond below to the reviewer’s questions, and additionally we further test the effect of (i) changes in B2 RNA sequence itself and, (ii) denaturation of the Hsf1 protein on B2 RNA processing. In detail:a) In new Figure 5F-I we now provide the following:– Incubation of a mutant B2 RNA in the presence and absence of Hsf1 and comparison with the same incubations with the original B2 RNA, that showed that acceleration of B2 RNA processing by Hsf1 is sequence-specific and, thus, not the result of non-specific RNA degradation.– Incubation of two control RNAs in the presence and absence of Hsf1 and comparison with same incubations with the B2 RNA, that also confirmed that Hsf1-induced processing is limited to B2 RNA.– Incubation of B2 RNA in the presence of a denatured Hsf1 and a control protein of similar size, that failed to accelerate B2 RNA processing as the native Hsf1 did.b) In order to exclude non-specific RNA destabilization due to degradation, hydrolysis or B2 RNA endogenous self-cleavage, we have included in Figure 5 a number of control RNA incubations without protein in the same buffer (TAP) and for the same time as the samples treated with Hsf1 or control proteins. Full gels are also included now as two source files.c) We have now performed short RNA-seq of the in vitro processed B2 RNA and compared the resulted fragments with those observed in vivo, now presented in the new Figure 5—figure supplement 1 A. This data reveals a similar processing pattern between the two conditions.


In the history of nucleic acid research, DNA has always been the main research focus. After the sketch of the human genome was completed in 2000, RNA has been started to gain more attention due to its abundancies in the cell and its essential role in cellular physiology and pathologies. Recent studies have shown that RNAs are susceptible to oxidative damage and oxidized RNA is able to break the RNA strand, and affect the protein synthesis, which can lead to cell degradation and cell death. Studies have shown that RNA oxidation is one of the early events in the formation and development of neurodegenerative disorders, including Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis. However, its molecular mechanism, as well as its impact on these diseases, are still unclear. In this article, we review the different types of RNA oxidative damage and the neurodegenerative diseases that are reported to be associated with RNA oxidative damage. In addition, we discuss recent findings on the association between RNA oxidative damage and the development of neurodegenerative diseases, which will have great significance for the development of novel strategies for the prevention and treatment of these diseases.  RNA is known to be essential for all living cells and performs many other functions besides protein synthesis. Contrary to DNA damage studies, RNA damage has only recently been concerned . AlthougBecause the structure of ribonucleic acid is similar to deoxyribonucleic acid, the nucleotide structures of RNA and DNA are still similar after oxidation modification, especially guanosine. 8-oxidized guanosine is the most studied oxidized RNA damage marker at present. 8-oxidized guanosine exists widely in various tissues and body fluids  ,10,11. R·−O2), hydrogen peroxide (H2O2), and the hydroxyl radical (·OH) produced by the normal mitochondrial electron transport chain through normal cell metabolism will threaten neurons, leaving the neurons of the brain continuously exposed to ROS [·OH can only diffuse a few nanometers in the tissue [·−O2 can hardly penetrate cell membrane [Due to the following four reasons, the brain is more susceptible to oxidative damage. 1) High oxygen consumption of the brain: the oxygen consumption of the human brain accounts for 20–25% of the total oxygen consumption of the human body . (2) Thed to ROS ,15,16. Te tissue  and ·−O2membrane . When th High oxymembrane . Therefomembrane . All of membrane  is also membrane .−OH, which is likely to cause a lot of the oxidative damage of biological macromolecules including RNAs. The most common source of −OH in cells is the Fenton and Haber-Weiss reaction [−OH generated near RNA can readily modify RNA because they are so active that they cannot diffuse from where they are formed. Therefore, the modification caused by the hydroxyl group is the most diverse type of RNA damage. There are more than 20 distinct types of −OH that destroy substrates [−) and proton (H+). According to the chemical structure of all known modified RNA nucleosides, they are divided into four categories base on the following chemical properties [As a product of normal metabolism and obtaining from exogenous sources, living cells produce highly active reaction . −OH genbstrates . Currentoperties : (1) Theoperties . The modoperties . Under ooperties ,29, knowoperties . This cooperties . In addioperties ,21.+mRNA accounts for only a small portion (about 1–2%) of the total cellular RNAs. RNA inside cells is primarily made up of rRNAs and tRNAs. Additionally, there are many different types of non-coding RNAs, such as microRNAs (miRNAs), small nucleolar RNAs (snoRNAs), and small nuclear RNAs (snRNAs) [(1)Direct RNA strand breaks: Jacobs et al. found that the most common form of damage to RNA is the direct strand break . The pos(2)Translation errors caused by oxidized RNA: Oxidized mRNA can induce translation errors, which can lead to premature termination of translation or degradation of peptide chains, resulting in short-chain polypeptides and protein variation . In addi(3)RNA oxidative damage can cause protein synthesis disorders: Experiments in rat primary nerve cell culture showed that the RNA in nerve cells is selectively oxidized when oxidative damage occurs. Generally, mRNA is more likely to be oxidized. During the transcription process, the presence of oxidized bases on the oxidized mRNA chain will cause transcription errors in the body, which will lead to the next translation error. Once an error occurs during translation, the expression of the corresponding protein will change. Ding et al.  demonstrWe have known for decades that poly (A)(snRNAs) . These n(snRNAs) . In regi(snRNAs) . Oxidati(snRNAs) . There aE. coli enzyme AlkB and human homologous enzyme hABH3 can directly reverse the alkylation damage of RNA by hydroxylating methyl groups on damaged RNA bases, and oxidized bases on RNA may be repaired [In previous studies, it was believed that RNA only served as a messenger in the expression of genetic material, while ignoring the occurrence of oxidative damage to RNA may have important physiological and pathological effects . Cells prepaired .Neurodegenerative Disorders are characterized by delayed onset and dysfunction of selective neurons. They are a type of irreversible neurological diseases caused by the loss of neuronal cells in the brain and spinal cord, including AD, PD, amyotrophic lateral sclerosis (ALS), and Huntington’s disease (HD)  Table 1Table 1. The dysfunction of nerve cells in specific areas caused by RNA oxidation is an important pathogenesis of neurodegenerative diseases . StudiesAlzheimer’s disease, discovered by German psychiatrist and neuroanatomist Alois Alzheimer in 1907, is one of the main types of neurodegenerative disorders . Most reMTH1 with oxidized purine nucleoside triphosphatase activity is expressed [PD, which was discovered by James Parkinson in 1817, was described as rest tremor, bradykinesia, muscular rigidity, and postural and gait impairment . Since txpressed . During xpressed . All of xpressed . In the xpressed . In ordeIn addition to AD and PD, HD and ALS are also common neurodegenerative diseases . As a puALS is a neuromuscular disease among various neurodegenerative diseases, which usually occurs after the age of 50 and fatal respiratory paralysis occurs within 3–5 years after diagnosis, which is life-threatening ,88. In tTo sum up, in patients with AD, PD, HD, ALS, and other neurodegenerative diseases, it is suggested that RNA is highly oxidized in the early stage of the illness before cell death, and this non-random and selective damage may affect the translation process ,33,63. FWith the rapid development of technology, people gradually realize that RNA is more susceptible to oxidative damage, and the oxidative damage of RNA is related to the early development of various neurodegenerative diseases such as AD, PD, and ALS . This phOxidative damage to RNA can lead to interruption of the translation process and impaired protein synthesis. However, we are still in the preliminary stage of understanding the role of RNA oxidation in protein synthesis inhibition and cell death. We believe that the direction of further research can focus on the following issues. Under normal physiological conditions, whether oxidatively damaged RNA is degraded or repaired by the body and what protein is involved in the process is a very challenging question, and thus further research is needed ,94. It mIn addition, recent research on RNA oxidation has a more interesting point: RNA oxidation is a feature of aging brain neurons, and it is more prominently observed in the early fragile neurons of age-related neurodegenerative diseases . This su


Background: RNA editing is a highly conserved posttranscriptional mechanism that contributes to transcriptome diversity. In mammals, it includes nucleobase deaminations that convert cytidine (C) into uridine (U) and adenosine (A) into inosine (I). Evidence from cancer studies indicates that RNA-editing enzymes promote certain mechanisms of tumorigenesis. On the other hand, recoding editing in mRNA can generate mutations in proteins that can participate in the Major Histocompatibility Complex (MHC) ligandome and can therefore be recognized by the adaptive immune system. Anti-cancer treatment based on the administration of immune checkpoint inhibitors enhance these natural anti-cancer immune responses. Results: Based on RNA-Seq datasets, we evaluated the editome of melanoma cell lines generated from patients pre- and post-immunotherapy with immune checkpoint inhibitors. Our results reveal a differential editing in Arthrobacter luteus (Alu) sequences between samples pre-therapy and relapses during therapy with immune checkpoint inhibitors. Conclusion: These data pave the way towards the development of new diagnostics and therapies targeted to editing that could help in preventing relapses during immunotherapies. The diversification of messenger RNA (mRNA) sequences from genomic DNA relies on posttranscriptional mechanisms, such as alternative splicing and RNA editing ,2. In maA-to-I RNA editing is essential in maintaining cellular homeostasis ,15,16 anADARs are also associated with immunity in several ways. First, the elongated form of ADAR1 is located in the cytosol and is induced by type I interferon, while constitutive ADAR2 and the short form of ADAR1 are nuclear. Second, by editing dsRNA, ADARs avoid the stimulation of innate immune responses by endogenous dsRNA  and therAlthough ADARs affect immunity, studies investigating the potential relationship between editome and cancer immune evasion are lacking. Melanoma is the most aggressive form of skin cancer and is currently best treated through the administration of immune checkpoint inhibitors: monoclonal antibodies blocking negative signals generated by cytotoxic T-lymphocyte-associated protein 4 (Ipilimumab) or programmed cell death-1  in activated T lymphocytes . Since sThe study was approved by the Kantonale Ethikkommission under approval number KEK-ZH Nr. 2014-0425, EK647 and EK800. After informed consent was given by the patients, biopsies were used to generate melanoma cell lines as described . DNA wasCell line purity was estimated based on the mutant allele frequency (MAF) calculated as follows: MAF = mutant copies/(wild-type copies + mutant copies). Mutations in BRAF (V600E) and NRAS  in melanoma are reported to be heterozygous, and thus cell line purity was calculated as 2 × MAF. RNA was extracted with the QIAGEN RNeasy kit. RNA capture was performed with the TruSeq RNA library Prep Kit v2 (Illumina). RNA sequencing was sequenced at 125 bp paired end on a HiSeq4000 at the FGCZ.Datasets for 14 patients were available for analysis. The samples were grouped by treatment: 12 samples were assigned to the group not yet subjected to Ipilimumab and Pembrolizumab therapy (12 cell lines taken from 10 patients) and 11 samples were assigned to the relapsed group (11 cell lines taken from 4 relapsing patients during treatment by Ipilimumab and Pembrolizumab). Those relapses happened during immunotherapy as they appeared within less than one month after the last antibody injection. For two patients, we collected cell lines before immunotherapy and at the point of relapse.https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE162095).Raw sequencing reads and RNA counts can be retrieved with GEO accession number GSE162095  to the total number of reads [p value of <0.05 was considered significant.Gene-level counts were quantified from pair-end reads aligned to the GRCh38 genome using the quantMode option implemented in STAR  . A diffe ExpEdit ,32,33,34 ExpEdit . The pro ExpEdit . The obt ExpEdit . Principof reads . Correlap values of less than 0.05 and q values of less than 0.05 were used , and 11 datasets were collected from cell lines made from biopsies of relapsing melanoma in patients treated with Ipilimumab and Pembrolizumab (“relapsed”) . Clinicaere used . In addiere used . Thus, were used .Adar1 and Adarb1 genes corresponding to the ADAR1 and ADAR2 enzymes, respectively. The analysis shows that ADAR1 gene expression (long and short forms of ADAR1 combined) remained unchanged between the groups . Thus, Clinically relevant recoding editing in cancer has been reported. Corresponding levels of editing are shown in The global noncoding editome represented by the Alu editing indexes shows no differences between the two groups . Additiot-test) provided by the Qlucore software and the following parameters: filtering by variance 0.15, p value was 0.05, and q value was 0.775. The outcome by the software was 57 Alu editing sites in 57 genes for the sample representation in a 3D PCA plot and heatmap representation of Alu editing sites (To obtain an overview of potential differences in editing patterns observed between “Before IT” tumors and “Relapsed” during treatment with checkpoint inhibitors, we applied a principal component analysis. It was done using the two group comparison statistical analysis (ng sites . Editingng sites A,B. Convng sites .Collectively, our study reveals an editing signature in Alu elements that characterizes tumors relapsing during treatment with immune checkpoint inhibitors . SurprisOur study points to differential editing in Alu sequences between melanoma cell lines obtained before therapy and melanoma cell lines made from relapses during treatment with immune checkpoint inhibitors. Those findings may be of relevance for diagnostic and prognostic tools as well as for the development of drugs or treatments that may lower the risks of relapses during therapy with immune checkpoint inhibitors.


BMP-15. This paper describes the use of the High-Resolution Melting method in quick identification of the known mutation in the BMP-15 gene, which affects high prolificacy in the Olkuska breed of sheep.According to the available literature, high prolificacy in sheep breeds could be caused by differences in many genes (polygenic trait) or as in some sheep breeds to a difference in one gene such as BMP-15 gene, we can use molecular biology tools to identify this causative mutation affecting prolificacy. In our research, we used the High-Resolution Melting (HRM) and Sanger sequencing methods to identify the genotypes of the studied animals. The result obtained by the HRM method is identical to those obtained by the sequencing method, which confirms the effectiveness of the HRM method and the possibility of quick and cheap identification of individuals with a FecXO mutation.Olkuska is a highly prolific sheep breed in Poland. Thanks to earlier identification of the genetic basis of its prolificacy, a mutation in the  Ovis aries allows the use of this specie as a model for research into biological process in mammals which is reproduction. Reproductive traits are especially crucial for sheep production because they determine the profitability of breeding [BMPR-1B (bone morphogenetic protein receptor 1B), BMP-15 (bone morphogenetic protein 15), GDF-9 (growth differentiation factor 9) and B4GALNT2  have been identified in sheep. Although to date, many mutations increasing sheep prolificacy have been identified in various breeds and various genes [BMP-15 and GDF-9 genes influence ovulation rate (OR) and follicular growth [BMP-15 gene and four in the GDF-9 gene affecting ovulation rate have been found in different sheep breeds [Sheep play an important role in modern agriculture. Moreover, differences in reproduction trait between breeds of breeding ,2,3. Thebreeding ,4,5. A nus genes  around tus genes . Oocytesus genes . It has r growth . To datep breeds ,11. Theyp breeds .BMP-15 gene, named FecXO, which increases the ovulation rate and litter size in ewes with FecXO mutation on both alleles. The mutation results in an asparagine to histidine change in the amino acid sequence of the mature BMP15 protein. As a result, the polarity and molecular weight of BMP15 have been disturbed, which influences the three-dimensional structure and alters BMP15 signaling reducing its activity by half [O mutation increases ewe prolificacy by 0.7 lambs in heterozygous ewes and 1.07 lambs in homozygous recessive ewes [O does not cause sterility like in other mutations identified in the BMP-15 gene, which makes it so valuable in sheep breeding [O in Olkuska sheep was detected using Sanger Sequencing and TaqMan probe methods, which still are expensive. Therefore, in the present study, we propose a low cost, quick and sensitive High-Resolution Melting (HRM) method for identification of the FecXO mutation in Olkuska sheep, which can increase the attractiveness of molecular tools in sheep breeding program and allow for more accurate selection of animals for breeding. HRM analysis is a method used for identification of genetic mutations in nucleic acid sequences. This technique is based on PCR reaction with presence of fluorescence dye that binds to double-stranded DNA (dsDNA). When dye is unbound it is shows a low level of fluorescence compared to dye bound to dsDNA when the fluorescence level increases greatly. After PCR reaction, the amplicon  is denatured gradually  from 65 °C to 95 °C with ramping by 0.2 °C. During this stage, the amplicon releases the fluorescent dye, allowing its detection. Amplicons from different samples with sequence changes (even differing by one base pair) will release fluorescent dye at different temperatures. Comparison with a reference control sample allows the sample to be assigned to the correct genotype group. The HRM method can discriminate DNA sequences based on their nucleotide composition, length, GC content, or strand complementarity and allows identification of deletions, insertions, and substitutions, as well as the detection of SNP (single nucleotide polymorphism) [The Olkuska breed  is a hig by half . The Fecive ewes ,14. The Blood samples for the analysis were obtained from 100 randomly selected female sheep of the Olkuska breed from five different flocks . Blood was collected from the jugular vein into 10 mL Vacutainer tubes with EDTA and stored at −20 °C prior to DNA isolation. Animal procedures were approved by the Local Animal Care Ethics Committee No. II in Kraków—permission number 1293/2016 following EU regulations.DNA isolation was performed using the A&A Biotechnology Sherlock AX reagent kit , according to the protocols provided by the manufacturer. Sample DNA concentration and purity were quantified using a Nanodrop 2000 spectrophotometer . All DNA samples were normalized to 100 ng/µL. http://www.bioinformatics.nl/cgi-bin/primer3plus/primer3plus.cgi) based on the BMP-15 ovine reference sequence (NCBI accession number: NC_040278). HRM curves were normalized, and the genotype was assigned based on the shape of the HRM curve with the use of the High Resolution Melting software  and by visual examination. Three samples of known genotype are required for automatic genotyping so for this purpose, we selected three samples with AA, AC, CC genotypes that were previously sequenced and had a known genotype and those samples were used as references samples.A Quant Studio 7k Flex Real Time PCR System  was used in HRM analysis. Reaction was carried out using MeltDoctor™ HRM Master Mix ; in detail 5 µL MeltDoctor™ HRM Master Mix, 0.5 µL Primer mix (10 pM each) , 3.5 µL BMP-15 gene fragment was used for validation of the HRM method. Before Sanger sequencing, the PCR reaction was performed in 25 μL volume containing: 12 µL of PCR-grade water, 2.5 µL of PCR buffer with 15 mM MgCl2 , 5 µL of Q-Solution , 3 µL of 10 mM dNTPs , 0.25 µL of primer mix (each 100 pmol/µL) . The Sanger sequencing of the pmol/µL) , 0.25 µLhttp://quantpsy.org/chisq/chisq.htm. The Hardy–Weinberg equilibrium was tested using the Court Lab-HW calculator (Michael H. Court (2005–2008) and Chi-square test using O mutations is in linkage with other reproductive traits and under selective pressure for improvement of prolificacy. The selection was probably previously conducted based only on phenotypic observations however, A high frequency of the A allele indicates there is still selective potential. Differences in genotype distribution between analyzed Olkuska flocks based on the Chi-square test are presented in For all 100 samples we obtained results from HRM analysis . Using cO  mutation increasing prolificacy in Olkuska sheep. Compared with the other methods , HRM is characterized by high technical accuracy, fast detection, low cost and easier identification of results making it highly useful to automatically detect SNP c.A1009C in the BMP-15 gene. The identification of prolificacy genes and their effects on reproduction traits in farm animals, including small ruminants, is considered a first step towards the improvement of reproductive traits . In the HRM is a method that has many advantages but also some disadvantages and limitations. Thanks to the various limitations of this method described in the available literature ,18,19, wAnother important factor affecting HRM analysis is the correct design of primers. Primers should be prepared in accordance with accepted principles of primer design  . It shouAnother important factor often discussed in the literature is the length of the amplicon. Products larger than 400 bp may have lower sensitivity than smaller amplicons. A sufficient amplicon length may be between 80 and 250 bp for routine analysis . TechnicComparing the HRM and Sanger sequencing detection methods for SNP analysis, the HRM method is characterized by about 60% lower cost and 80% shorter analysis time, which gives significant advantages for practical use.O mutation can be used to improve the reproductive capacity of Olkuska sheep, and the proposed detection method has potential utility in large-scale sheep breeding because it is cheap and not labor intensive. Genotyping of sheep carrying a FecXO mutation is useful not only in ewes but also in rams. Due to the fact that the FecXO mutation is located on the X chromosome [The FecXromosome , each daO mutation in commercial flocks.In conclusion, we recommend the HRM method, using the protocol developed in the present study, in Okulska sheep breeding programs. HRM is a rapid and cheap method for identification of the FecX


Millepora, a hydrozoan coral, is a common component in modern tropical reefs throughout the world. In ecological and palaeoecological surveys, it is often grouped with scleractinian corals, which are the prevailing builders of coral reefs. On modern, current-exposed reefs in the Red Sea, Millepora can become the dominant coral. However, it is rarely found in fossil reefs and if present, its abundance is usually considerably lower than in modern reefs. The mismatch is often explained by a low preservation potential of the milleporid skeleton in the fossil record. We explore Millepora abundances in Pleistocene reefs of Egypt using 29 line transects , and find its abundances to be comparable to that of adjacent modern reefs (between 0 and 18.8 ± 8.5% per site). Comparisons between sites with and without Millepora suggest that site specific environmental characteristics determine the presence of Millepora in the fossil reef. We conclude that a lack of preservation of habitats preferred by Millepora instead of the preservation potential of the hydrozoan itself is the most plausible reason for the mismatch between modern and fossil abundances. Millepora, the fire coral, is a common extant hydrozoan coral on tropical reefs throughout the world. The genus is distinct due to its gastrozooids emerging from the gastropores, which are surrounded by several dactylozooids protruding from dactylopores  and often shallow environments. The Millepora zone in the Caribbean is on high energy reef crests , and packstone, filling the gaps between the coral framestone.The investigated fossil reefs were all located on the Egyptian coast of the Red Sea between 26.2°N and 24.6°N . The R pCeraesignum cf. maximum , which is an indicator for shallow reef habitats  the encrusting gastropod Pocilloporidae we were not able to distinguish between the genera Pocillopora and Stylophora due to poor preservation. Every occurrence of Pocilloporidae indet was therefore proportionally split according to their overall abundances in all transects . Molluscs, coralline algae, and tilted corals were included in the category ‘sediment’ for the purpose of this study. The percent abundance of the categories sediment, Millepora, and other corals (Scleractinia and Sinularia holdfast) were calculated for each transect  were calculated for each transect : a tape measure was laid out at a random starting point following the depth contour. We aimed for a length of 20 metres per transect . Corals transect . Transectransect . AdditioMillepora were excluded a priori to avoid circular reasoning and nonmetric multidimensional scaling (NMDS) based on the Bray-Curtis dissimilarity was used to visualize differences between the predefined groups . To test for differences between groups we used permutational multivariate analysis of variance (PERMANOVA)  . Furtherillepora . All staillepora  using thMillepora sp. was found in 20 of 29 transects (~69%)  . The sitMillepora (65.1%) is LT02, a pre-MIS5e reef in Wadi Igla, followed by a much lower Millepora abundance (19.4%) in LT01 at the same locality and 19.4% in LT75  .The transect with the highest abundance of , MIS5e) . The traMillepora, followed by the MIS5e reef edge in Sharm El Bahari .Transects grouped by locality, age and palaeodepth show that the pre-MIS5e reef transects in Wadi Igla had the highest abundance of l Bahari . MillepoPorites are the most abundant categories in reefs with and without Millepora , while reefs that contain Millepora have higher percentages of Pocillopora  and Lobophyllia  (Sediment and illepora . However 0.0312) .Millepora abundances excluded a priori) showed a clear distinction between reefs with and without Millepora and explained 14.3% of the variation in the dataset   and 9.6%  of the variation, respectively. Reef edge and reef slope of the MIS5e reefs also differed significantly   . For theR2~0.10) . Simper Millepora in the fossil reef is with a blade-shaped growth form, as is typical for Millepora platyphylla Hemprich & Ehrenberg, 1834  is characteristic of a so-called ‘Millepora reef’ described by Millepora reef is defined by the high abundances of the fire coral and is typical for current-exposed reefs in the Red Sea.The site with the highest abundance of Porites  had lower percentages of milleporids than Wadi Igla, but all of the localities had high abundances of Porites , which wMillepora in Sharm El Luli and Sharm El Quibli, which were both dominated by Porites. The two sites are today in protected bays  and as exposed, high energy reefs with shallow water depth in the Empalme trend (Pleistocene) in Costa Rica. Millepora alcicornis from a former high-energy reef crest from the Pliocene of Southeastern Florida, and Millepora dichotoma together with Pocillopora verrucosa in reef crest facies from the Pleistocene. All of those records suggest a similar palaeoenvironment: a shallow, highly to moderately exposed reef crest to reef slope. Acropora palmata and which he reconstructed as the reef crest, he found Millepora. Interestingly, he found Millepora even though the limestone was diagenetically altered.Furthermore, we investigated the palaeo-habitat in some fossil reefs in which we could confirm Millepora in the fossil record. Site specific differences explain a high percentage of the variability of our data (43.5%) and exposure is one key parameter distinguishing modern Red Sea reef localities  and concluded a higher susceptibility of the hydrozoan skeleton to diagenesis. However, they also mentioned another possibility for the mismatch between the modern and the Pleistocene assemblage: differences in the environmental setting between the modern and the fossil reef. The habitat they investigated in the modern reef is a mid-shelf patch reef, while the fossil reef habitat represents a protected back reef and reef tract. Based on this information and the modern preference of exposed habitats by the fire coral, we would expect the milleporids in the fossil site investigated by It is difficult to reconstruct palaeoenvironmental settings from fossil reefs, especially the exposure. However, to deduce the presence or absence of the hydrozoan genus in the past, it is essential to investigate habitats, which fulfill the niche requirements of the genus. ironment . This haMillepora could be the ecological succession and frequency of disturbance on a reef, as in the Red Sea it has been described as an opportunistic species and rapid colonizer after disturbances  is usually described as the most common milleporid  the fire coral itself; and (2) of habitats, which are preferred by Millepora in fossil reefs could serve as a proxy for exceptionally good preservation of the reefs . However, as described earlier in detail, fossil Millepora was found in other parts of the world with a higher precipitation rate such as Costa Rica  in both time periods must match for meaningful comparisons.Therefore, we conclude that an arid climate can facilitate the preservation of Millepora abundances of Pleistocene and modern Red Sea reefs and conclude that the fire coral does not have an exceptionally low preservation potential in fossil reefs. Rather, the preservation of palaeoenvironments, which reflect the niche of the milleporid, is necessary to find fire corals in the fossil record. The physical factor most decisive for Millepora presence is exposure to water energy, combined with a depth with sufficient light availability. Other factors increasing the preservation potential at our fossil sites might be the young geological ages and a geographical location with an arid climate, which is advantageous to preservation. High initial abundances of Millepora, as they are known for the modern Red Sea, may further mitigate a lower preservation potential of the hydrozoan skeleton.We found no major difference between