Bamboo mosaic virus (BaMV)-infected tissue, we have identified the Nicotiana benthamiana photosystem II oxygen-evolving complex protein, NbPsbO1, which specifically interacted with the promoter of sgRNA but not that of genomic RNA (gRNA). Silencing of NbPsbO1 expression suppressed BaMV accumulation in N. benthamiana protoplasts without affecting viral gRNA replication. Overexpression of wild-type NbPsbO1 stimulated BaMV sgRNA accumulation. Fluorescent microscopy examination revealed that the fluorescence associated with NbPsbO1 was redistributed from chloroplast granal thylakoids to stroma in BaMV-infected cells. Overexpression of a mislocalized mutant of NbPsbO1, dTPPsbO1-T7, inhibited BaMV RNA accumulation in N. benthamiana, whereas overexpression of an NbPsbO1 derivative, sPsbO1-T7, designed to be targeted to chloroplast stroma, upregulated the sgRNA level. Furthermore, depletion of NbPsbO1 in BaMV RdRp preparation significantly inhibited sgRNA synthesis in vitro but exerted no effect on (+) or (−) gRNA synthesis, which indicates that NbPsbO1 is required for efficient sgRNA synthesis. These results reveal a novel role for NbPsbO1 in the selective enhancement of BaMV sgRNA transcription, most likely via direct interaction with the sgRNA promoter.Many positive-strand (+) RNA viruses produce subgenomic RNAs (sgRNAs) in the infection cycle through the combined activities of viral replicase and host proteins. However, knowledge about host proteins involved in direct sgRNA promoter recognition is limited. Here, in the partially purified replicase complexes from IMPORTANCE Production of subgenomic RNAs (sgRNAs) for efficient translation of downstream viral proteins is one of the major strategies adapted for viruses that contain a multicistronic RNA genome. Both viral genomic RNA (gRNA) replication and sgRNA transcription rely on the combined activities of viral replicase and host proteins, which recognize promoter regions for the initiation of RNA synthesis. However, compared to the cis-acting elements involved in the regulation of sgRNA synthesis, the host factors involved in sgRNA promoter recognition mostly remain to be elucidated. Here, we found a chloroplast protein, NbPsbO1, which specifically interacts with Bamboo mosaic virus (BaMV) sgRNA promoter. We showed that NbPsbO1 is relocated to the BaMV replication site in BaMV-infected cells and demonstrated that NbPsbO1 is required for efficient BaMV sgRNA transcription but exerts no effect on gRNA replication. This study provides a new insight into the regulating mechanism of viral gRNA and sgRNA synthesis. Positive-strand (+)RNA viruses cause widespread diseases in humans, animals, and plants. Although infecting hosts of different kingdoms, (+)RNA viruses undergo a similar replication cycle that consists of several distinct steps, including (i) recruitment of a (+)RNA template and switching from translation to replication mode, (ii) transportation of viral RNA-dependent RNA polymerase (RdRp) to the replication site, (iii) rearrangement of intracellular membranes and assembly of the viral replication complexes (VRCs), and (iv) synthesis of negative-strand (−) viral RNAs followed by that of (+) viral RNAs, or (v) for some (+)RNA viruses, also synthesis of one or more subgenomic RNAs (sgRNAs) via a (−) viral RNA intermediate . Because2–cis-acting elements containing functional sequences and structures recognized by replication complexes for initiation of transcription RNA viruses possess multicistronic genomes that produce sgRNAs to serve as messengers, allowing for the translation of downstream open reading frames (ORFs) in monocistronic host environments . The (−)cription –8. The eIn vitro RdRp systems are commonly used to investigate the components of host and viral proteins associated with RdRp complexes and for defining the minimal requirement of cis-acting RNA elements for replication (–lication –11. EffoBamboo mosaic virus (BaMV), belonging to the genus Potexvirus and family Alphaflexiviridae, has a single-stranded (+)RNA genome of approximately 6.4 kb with a 5′ cap structure and a 3′ poly(A) tail (–(A) tail . The RNA(A) tail , 14. ORF(A) tail . ORF2, −(A) tail . TGBp1 i(A) tail . ORF5 en(A) tail –20. LikeA) tail –. Two majA) tail –, whereascis-acting elements, also known as promoter regions, for BaMV (−)RNA and (+)RNA synthesis have been identified in the 3′ untranslated region (3′UTR) of (+)RNA (Ba 3′UTR) and the 3′-terminal 77 nucleotides (nt) of (−)RNA (Ba-77), respectively (S-transferase (GSTU4), whereas host factors that negatively regulate include elongation factor 1a (eEF1a) and glyceraldehyde 3-phosphate dehydrogenase (GAPDH)  . The pro (GAPDH) . HoweverNicotiana benthamiana photosystem II (PSII) oxygen-evolving complex protein, NbPsbO1, in the partially purified replicase complexes extracted from BaMV-infected tissues and demonstrated that NbPsbO1 specifically interacted with both BaSGP1 and BacpSGP. Results of gene overexpression and silencing analyses revealed that NbPsbO1 is required for efficient transcription of BaMV sgRNAs but exerts no effect on gRNA replication. We further demonstrated that NbPsbO1 could be redistributed to chloroplast stroma, where the VRCs reside, following BaMV infection and may thus participate in the positive regulation of BaMV sgRNA synthesis. Together, our results unveiled a novel role of NbPsbO1 in BaMV infection cycles and provided further insights into the mechanism for differential regulation of BaMV gRNA and sgRNA synthesis.In this study, we have identified the MluI, deficient in the transcription of TGBsgRNA, was used to map the promoter region for TGBsgRNA synthesis. The insertion of a hemagglutinin (HA) coding sequence upstream of the stop codon of the Rep gene in pKBRepHAMluI disrupted an octanucleotide element, GUUAAGUA, representing conserved promoter-like sequences required for TGBsgRNA transcription among potexviruses  . Howeverxviruses , 27. To restored . An inocrestored , at nt 4in vitro RdRp assay was performed with the minus strand (−) of nt −65 ∼ +113 relative to the TSS of TGBsgRNA, hereafter designated BaSGP1. In addition, Ba 3′UTR and Ba-77, containing promoter activities for initiation of (−) and (+) BaMV gRNA, respectively  had a crucial impact on the solubility of the recombinant PsbO  of Trx-His-mPsbO1 . Four isoforms of NbPsbO were reported to show high identity (NbPsbO1 highly conserved among the corresponding regions of other isoforms was cloned into a TRV-based silencing vector (N. benthamiana with TRV1 by Agrobacterium-mediated infiltration. NbPsbO1 expression was decreased to 17% of that of mock-infiltrated plants (TRV:luciferase [TRV:Luc]) at 10 days post-agroinfiltration (dpai)   . The accl plants . Thus, taffected . These raffected . The resa plants , indicatn plants  might han plants , which mn plants . To distN. benthamiana leaves coinfiltrated with NbPsbO1-T7 and BaMVGFP at 3 dpai. The ectopically expressed NbPsbO1-T7 was detected by Western blot analysis with antiserum against NbPsbO1 as the protein band with higher molecular weight than that of the endogenous NbPsbO1 (N. benthamiana to generate the mature forms of PsbO1 (mPsbO1) and PsbO1-T7 (mPsbO1-T7), respectively, with lower molecular weights than that of the full-length rPsbO1-His purified from E. coli , designated NbPsbO1-OFP, for transient expression in ytoplasm , the subructures , which sructures . To testructures , which sthamiana . At 3 dpthamiana . To confthamiana . The resthamiana . Thus, Bthamiana , consistthamiana .N. bemthamiana. At 3 dpai, the protein accumulation of endogenous mPsbO1 and exogenous dTPPsbO1-T7 was verified by immunoblotting  or the construct expressing dTPPsbO1-T7, and localization of PsbO1 was detected by immunoblotting. The results showed that neither the accumulation nor location of the endogenous NbPsbO1 protein was affected by dTPPsbO1-T7  and performed the following experiments. First, the dTPPsbO1-OFP was expressed in protoplasts and examined by confocal microscopy, which revealed its subcellular localization in the cytoplasm, demonstrating the requirement of the functional transit peptides for import of NbPsbO1 into the chloroplast thylakoid . To undeblotting . BaMV RNblotting . Thus, tPsbO1-T7 . This obN. benthamiana protoplasts  were verified by immunoblotting  on BaMV accumulation. The results of confocal microscopy examination showed colocalization of sPsbO1-OFP and the stroma marker RbcSTP-GFP, demonstrating the chloroplast stroma localization of sPsbO1 in toplasts . We thentoplasts  and pKBGblotting . BaMV sgblotting . Thus, tilencing . The trablotting . The accblotting . Thus, tN. benthamiana. Further validation of this observation requires an in vitro RdRp assay with exogenous RNA templates and different concentrations of NbPsbO1. To reduce the protein concentration of endogenous NbpsbO1, the purified BaMV RdRp preparation was subjected to immunodepletion (ID) with preimmune or anti-PsbO1 antibody. Removal of NbPsbO1 was quantified by Western blot analysis to reach about 70% to 80%  RNAs by refolding BMV RNAs, resulting in the separation of ribosomes and translation factors and the association with BMV replicase and host proteins for replication (Hepatitis C virus (HCV) RNA replication complex, polypyrimidine tract-binding protein (PTB), has also been shown to bind to the internal ribosome entry site (IRES) of HCV RNA and inhibit its translation. PTB has also been shown to play a central role in HCV RNA replication by binding to the poly(U/C) tract at the 3′ untranslated region of HCV RNA, which suggests that PTB is involved in the switch from translation to replication of HCV RNA (Sindbis virus (SIN) infection. HnRNP K coprecipitated with the sgRNA but not the gRNA of SIN. The interaction of hnRNP K with SIN sgRNA might upregulate the sgRNA synthesis that produces more sgRNA than gRNA (Mouse hepatitis virus (MHV)  Viral translation and replication use the same viral (+)RNA template, proceeding in opposite directions. (ii) Synthesis of progeny RNA and sgRNA use the same viral (−)RNA template with distinct promoters. These processes should be highly regulated and compartmentalized to avoid conflict . The invlication , 42. A c HCV RNA , 44. In han gRNA . Howeverus (MHV) . Howeverus (MHV) . In thisus (MHV)  and is rus (MHV)  and the us (MHV) . In contus (MHV) . These fus (MHV) .cis-acting RNA elements containing a functional sequence and structure to direct the virus-encoded RdRp and/or cellular host proteins to assemble transcription complexes (6cis-acting elements required for sgRNA synthesis were examined by using the satBaMV expression cassette (CAAUUCAA-5′) in the loop were essential for CPsgRNA synthesis (cis-acting element for TGBsgRNA synthesis was predicted to have SLs similar to those of BacpSGP. The conserved octamer motif (3′-CAAUUCAU-5′) is also located in the loop of SL2 (Potato virus X (PVX) sgRNAs . Th. Thcis-ap of SL2 . NbPsbO1p of SL2  and J. T) sgRNAs . We show) sgRNAs , which i) sgRNAs . Accordi) sgRNAs  and 7F. ) sgRNAs , which i) sgRNAs . Moreove) sgRNAs , in the ) sgRNAs . Thus, aIn situ hybridization and immunogold-labeling experiments revealed BaMV genomic RNA in chloroplasts of BaMV-infected leaf tissues of green bamboo (N. benthamiana protoplast cells (N. benthamiana by reverse transcription PCR (RT-PCR)  The nucleus-encoded chlPGK interacts with BaMV 3′UTR and moves the viral RNA into chloroplasts for replication , 52. (iin bamboo . In addiRT-PCR) . In the (RT-PCR) . Confoca(RT-PCR)  and C (5R . In th(RT-PCR) . Of note(RT-PCR)  to F. ThAlfafa mosaic virus (AMV) or disease-specific protein of Rice stripe virus (RSV). Overexpression of PsbP led to repression of AMV and RSV accumulation (Tobacco mosaic virus (TMV) and inhibits TMV replication in plants (Tobacco vein banding mosaic virus (TVBMV) replication  and Ba3572F (5′-ATGAAAGCAAGGCACCATG-3′). The purified megaprimer was used in the second PCR amplification, with pCB-RepHA as a template and a reverse primer, Ba5361R (5′-GGGCAGATGCTGTTGAAG-3′). The products of the second PCR were gel purified, digested with AflII and NsiI, and used to replace the corresponding fragment within the pCB-RepHA plasmid after digestion with the same restriction enzymes to generate pCBRepHAMluI. To construct pCBRepHA21, pCBRepHA50, and pCBRepHA80, the PCR products were amplified with PCB, an infectious clone of BaMV-S, as the template, with the forward primers of MluI/Ba4171 (5′-GCACGCGTGAAGGTTTATTCTC-3′), MluI/Ba4142 (5′-GCACGCGTCGCCAACCACGATG-3′), and MluI/Ba4112 (5′-GCACGCGTCCCTACATACAGAAG-3′), respectively, and reverse primer Ba5361R. The purified PCR products were digested with MluI and NsiI and used to replace the corresponding fragment within pCBRepHAMluI after digestion with the same restriction enzymes to generate pCBRepHA21, pCBRepHA50, and pCBRepHA80, respectively. The second step was to introduce these plasmids into the Agrobacterium tumefaciens binary vector pKn ; suspensions were adjusted to an optical density at 600 nm (OD600) of 0.1 and infiltrated by syringe into the leaves of each test plant.Plasmids pKB , pKBRepH32P-labeled probe was transcribed from HindIII-linearized pBaHB by using SP6 RNA polymerase . RNA samples were separated by electrophoresis and transferred to nylon membranes  for Northern blot analysis . Blots wlymerase .Total protein was extracted from leaf tissue, and protein samples were separated by 12% or 10% SDS-PAGE. For Western blot analysis, separated proteins were transferred to a polyvinylidene difluoride (PVDF) membrane  and incubated with laboratory-generated primary antiserum from rabbits against BaMV TGBp1 , NbPsbO1in vitro RdRp assay were purified from BaMV-infected N. benthamiana plants as described previously (TCGCCAACCACGATGCAATC-3′) and T7Ba(−)4312 (5′-TAATACGACTCACTATAGGGCACCAGCCACCGCGTGC-3′) for BaSGP1 and primer pair Ba5391 (5′-GAAATAATAATAAACGGGC-3′) and T7Ba(−)5617 (5′-TAATACGACTCACTATAGGGCTGGGCTGCAGCTTG-3′) for BacpSGP. The method for exogenous RdRp activity assay was as previously described  and irradiated with a UV lamp  at a 254-nm wavelength on ice for 20 min, followed by RNase A (10 μg) and RNase T1 (0.5 U) digestion at 37°C for 30 min. The UV cross-linked products were separated on a 12% SDS-PAGE gel. The gel was dried and observed under a phosphorimager. The protein bands corresponding to RNA-protein complexes were excised from the gel and subjected to liquid chromatography-tandem mass spectrometry (LC/MS-MS).The cross-linking assay was performed as described previously , except GCGGTACCGAAGGAGCTCCAAAACGTCTAAC-3′) and BamHI/NbPsbO1_cdsR (5′-GCGGATCCTCATTCAAGTTGGGCATACC-3′) by RT-PCR with N. benthamiana total RNA as a template. The gel-purified PCR products were digested with KpnI and BamHI and ligated to pET32a to create the expression vector pET32a-mPsbO1. The vectors pET32a and pET32a-mPsbO1 were introduced into Escherichia coli BL21 cells, and the control protein (Trx-His) and recombinant fusion protein (Trx-His-mPsbO1) were induced and purified per the manufacturer’s recommendations .A cDNA fragment corresponding to the mature form of the NbPsbO1 open reading frame was amplified from the primers KpnI/NbPsbO1_256F (5′-32P-labeled UTP. Various amounts of affinity-purified recombinant protein Trx-His-mPsbO1 was incubated with radioactively labeled RNA probe (20 fmol) in a binding buffer  at room temperature for 15 min. The reaction mixtures were subjected to electrophoresis on a 5% nondenaturing polyacrylamide gel, and the RNA-protein complexes were detected by a phosphorimager (GE Amersham Typhoon). For the competition assays, various amounts of unlabeled competitor RNA were preincubated with 2 μg of Trx-His-mPsbO1 for 15 min prior to the addition of 32P-labeled BacpSGP probe. For the preparation of BacpSGP mutants as competitors, the plasmids pyTABacpSGPM1 and pyTABacpSGPM2 harboring the regions of the BacpSGP mutants were constructed by two-step PCR amplification from pCB. The first PCR amplification was done with primer pair Ba5391 and cpSGPM1_R (5′-CAAAAGAAGGAATAAATCCAAACCCTAG-3′) for BacpSGPM1 and primer pair Ba5391 and cpSGPM2_R (5′-GTTTAATTTACAAAAGTACCAAACTTAAC-3′) for BacpSGPM2 purified as megaprimers. The megaprimers were used in the second PCR amplification with pCB as a template and a reverse primer, T7Ba(−)5617. The PCR products were gel purified and individually cloned into vector pyT&A. RNA competitors were prepared by in vitro transcription with the EcoRI-linearized plasmids with T7 RNA polymerase.RNA probes were synthesized by using T7 RNA polymerase-based transcription in the presence of Tobacco rattle virus (TRV)-based virus-induced gene silencing (VIGS) was used to knock down the expression of NbPsbO1 (35). Plasmids pTRV1 and pTRV2-Luc were kindly provided by David C. Baulcombe . For the construction of pTRV2-NbPsbO1, a 500-bp fragment of the NbPsbO1 coding sequence from N. benthamiana was amplified by PCR with N. benthamiana cDNA and gene-specific primers XbaI/NbPsbO1_VIGSF (5′-GCTCTAGACCCCAGATTTCCAGAAAACTAAG-3′) and BamHI/NbPsbO1_VIGSR (5′-CGGGATCCCACATCCTTGGGGACCTTTG-3′). The amplified PCR products were gel purified, digested with XbaI and BamHI, and cloned into the pTRV2 plasmid  containing pTRV2-Luc or pTRV2-NbPsbO1 was mixed with pTRV1-containing C58C1 at a 1:1 volume ratio and coinfiltrated by syringe onto three leaves of each test plant. At 10 days postagroinfiltration (dpai), the third and fourth leaves above the infiltrated leaves were isolated by using TriPure isolation reagent , per the manufacturer’s instructions. For measuring the knockdown efficiency of NbPsbO1 in plants, real-time quantitative RT-PCR was used with the primers, PsbO1-qF (5′-GACCGGTGAGGTCATTGGAG-3′) and PsbO1-qR (5′-CAATGCTTGTCCAAATTGAG-3′). To normalize the mRNA levels of target genes between samples, the relative mRNA levels of actin were determined with the primers actin-F (5′-GATGAAGATACTCACAGAAAGA-3′) and actin-R (5′-GTGGTTTCATGAATGCCAGCA-3′). At 10 dpai, A. tumefaciens cultures containing pKBG  were infiltrated into the third and fourth leaves above the TRV-infiltrated leaves. Total RNA was extracted from the BaMV-inoculated leaves of individual plants 2 dpai. NbPsbO1 . Plasmiding pKBG   and cpSGPM_R (5′-GTTTAATTTACAAAAGTACCTTTCGTAAGAAACCCTAGCTGGAG-3′). The purified megaprimer was used in the second PCR amplification with pCB as a template and a reverse primer, pCass3′ (5′-AGAGAGACTGGTGATTTCAG-3′). The products of the second PCR were gel purified, digested with NsiI and SacI, and used to replace the corresponding fragment within the pCB-RepHA  for PsbO1-T7 and dTPPsbO1-T7 were amplified by PCR with N. benthamiana cDNA and primer pairs . PCR products were gel purified, digested with XbaI and XhoI, and used to replace the corresponding fragment within pBI-mGFP (CGTTTTGGAGCTCCTTCCAAGTCCTTGAG-3′). The purified megaprimer was used in the second PCR with pBIPsbO1-T7 as a template, with the primer for XhoI/NbPsbO1 T7_cdsR. PCR products were gel purified, digested with XbaI and XhoI, and used to replace the corresponding fragment within pBI-mGFP to generate pBIsPsbO1-T7. The pBI-based plasmids for transient expression of NbPsbO1-T7, NbdTPPsbO1-T7, and NbsPsbO1-T7 were introduced into A. tumefaciens strain GV3850 individually by electroporation. A. tumefaciens cultures were collected by centrifugation and resuspended in infiltration buffer. Suspensions were adjusted to an OD600 of 0.5 and infiltrated by needleless syringe into the leaves of each test plant.To overexpress PsbO1 and PsbO1 mutants in pBI-mGFP  after diN. benthamiana protoplast cells, plasmids pEPsbO1-OFP, pEdTPPsbO1-OFP, and pEsPsbO1-OFP were generated. The CDSs for PsbO1 and dTPPsbO1 were amplified by PCR from the pBIPsbO1-T7 template with primer pairs . PCR products were gel purified, digested with XbaI and BamI, and cloned into pEpyon-OFP  with 543-, 633-, and 488-nm laser excitations for OFP, chloroplast autofluorescence, and GFP imaging, respectively.To visualize the localization of NbPsbO1 and NbPsbO1 mutants in pyon-OFP  to generor pt-gk  was infi2HPO4, 0.5 mM MgCl2, 35 mM HEPES-KOH, pH 8.3, and 1 mM dithiothreitol) and saved for total chloroplasts or further suspended in osmotic lysis buffer  and on ice for 15 min. Supernatant (stroma) and pellet (thylakoid) fractions were separated by centrifugation at 10,000 × g for 10 min. The pellet fraction was washed three times in lysis buffer. Stroma proteins were precipitated with ammonium acetate.The chloroplast isolation was done as described previously . The intg for 35 min at 4°C, and the supernatant (S100) was collected for the immunodepletion assay. S100 (0.5 ml) was mixed with 5 μg purified IgG from preimmune or anti-PsbO1 antiserum on a rotamixer for 4 h at 4°C. NbPsbO1 was depleted from S100 by precipitation by adding protein A magnetic beads . The samples from preimmune or NbPsbO1-depleted S100 underwent Western blot analyses with antibodies specific to NbPsbO1 or Hsp90.The micrococcal nuclease-treated solubilized BaMV RdRp was centrifuged at 100,000 ×


Nidovirales comprise a genetically diverse group of positive-sense single-stranded RNA virus families that infect a range of invertebrate and vertebrate hosts. Recent metagenomic studies have identified nido-like virus sequences, particularly those related to the Coronaviridae, in a range of aquatic hosts including fish, amphibians, and reptiles. We sought to identify additional members of the Coronaviridae in both bony and jawless fish through a combination of total RNA sequencing (meta-transcriptomics) and data mining of published RNA sequencing data and from this reveal more of the long-term patterns and processes of coronavirus evolution. Accordingly, we identified a number of divergent viruses that fell within the Letovirinae subfamily of the Coronaviridae, including those in a jawless fish—the pouched lamprey. By mining fish transcriptome data, we identified additional virus transcripts matching these viruses in bony fish from both marine and freshwater environments. These new viruses retained sequence conservation in the RNA-dependant RNA polymerase across the Coronaviridae but formed a distinct and diverse phylogenetic group. Although there are broad-scale topological similarities between the phylogenies of the major groups of coronaviruses and their vertebrate hosts, the evolutionary relationship of viruses within the Letovirinae does not mirror that of their hosts. For example, the coronavirus found in the pouched lamprey fell within the phylogenetic diversity of bony fish letoviruses, indicative of past host switching events. Hence, despite possessing a phylogenetic history that likely spans the entire history of the vertebrates, coronavirus evolution has been characterised by relatively frequent cross-species transmission, particularly in hosts that reside in aquatic habitats.The  Several coronaviruses have emerged as highly pathogenic viruses in humans and other animals, the most recent and notable of which is severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)  and seemingly replicate with higher fidelity than other known positive-sense RNA viruses due to RNA proofreading associated with an exonuclease domain (The S-CoV-2) , which, e domain .Orthocoronavirinae that infect mammals and birds as well as a single virus identified in a reptilian host  termed Microhyla letovirus (Oncorhynchus tshawytscha) identified Pacific salmon nidovirus  (Cyprinus carpio) in Australia was also found to fall within this group  . More reis group .The central aim of the current study was to determine whether coronaviruses might be present in a wider range of fish hosts and from this reveal more of their evolutionary history, particularly whether coronaviruses have co-diverged with their hosts over many millions of years or whether there has been frequent cross-species transmission (i.e. host jumping) as underpins the emergence of SARS-CoV-2 and whether such cross-species transmission occurs in some hosts more frequently than others.Geotria australis) sampled from New Zealand—te reo Māori: kanakana (South Island) or piharau (North Island)—that displayed lamprey reddening syndrome (LRS). This syndrome is characterised by red lesions on their gills, fins, and body walls  data from jawless and bony fish. Jawless fish included the pouched lamprey  in 2012, 12 individuals (eight from this investigation and four more recently collected control samples) were subjected to meta-transcriptomic analysis. This led to the identification of a novel and divergent member of the Coronaviridae, the latter of which contains the viral RNA-dependent RNA polymerase (RdRp)  protein. However, the closest sequence match for the S protein transcripts were viruses from Porcine torovirus and Atlantic salmon bafinivirus, both non-coronavirus members of the Nidovirales (family Tobaniviridae), albeit these were highly divergent sequences with only ∼25–27 per cent amino acid sequence similarity ). No coronaviruses or other viruses were found in the remaining LRS sample nor the four control samples. However, we were only able to generate consensus virus sequences from three of these due to the low and fragmented virus abundance in the other samples. All three samples possessed virus transcripts with sequence similarity to the open reading frames 1a (ORF1a) and 1b (ORF1b) common to the e (RdRp) . We alsomilarity . Phylogemilarity . In partn events . In contvergence .Microhyla letovirus across all three genomic regions shows relatively high sequence similarity in ORF1b . These sequences were identified in blenny (Acanthemblemaria sp.), bluespotted mud hopper , Schizothorax waltoni, which were sampled from China, as well as the broadnosed pipefish (Syngnathus typhle), sampled from Europe. The new viruses were named blenny letovirus, mud hopper letovirus, waltoni letovirus, and broadnosed pipefish letovirus, respectively. Second, we identified a viral transcript in the trout perch (Percopsis omiscomaycus) that shared 39 per cent amino acid sequence similarity to Shrew coronavirus in ORF1b and 20 per cent amino acid sequence similarity to Bat coronavirus in the S protein (Letovirinae are not yet included in the non-redundant (nr) protein database. This was termed ‘trout perch letovirus’. Finally, two potentially novel virus sequences were identified that, upon further inspection, shared greater sequence similarity to viruses within the Tobaniviridae, in a similar manner to the S protein of kanakana letovirus. These two novel viruses, found in giant mudskipper  and golden Chinese loach (Botia superciliaris), had >50 per cent sequence similarity in the RdRp and ∼40 per cent sequence similarity in the S protein to other fish viruses in the Tobaniviridae  and Okuti River, Banks Peninsula, in 2019 (n = 2), both of which are separate catchments areas to locations sampled in 2012. These individuals displayed no signs of LRS that has never been recorded from the Mokau or Okuti rivers. These samples were used as controls. Muscle and skin subsamples from the control individuals were taken in the field and were preserved in RNALater (Thermo Fisher Scientific) and in a −80°C freezer. Sampling was conducted in consultation with local Māori (rūnanga and kaumatua).LRS describes pouched lamprey from the South Island of New Zealand that display red lesions on their gills, fins, and body walls . From 20Skin tissue was dissected from 26 FFPE blocks, representing 26 individuals. Total RNA was extracted using a Macherey-Nagel NucleoSpin® totalRNA FFPE XS kit following the NucleoSpin totalRNA FFPE XS protocol. Control samples from the Mokau and Okuti rivers were extracted separately using a Zymo Research Direct-zol RNA Miniprep Plus kit. The purity of the extracted RNA from all sample types was evaluated (NanoDrop and Qubit Fluorometer), and 12 of the highest scoring samples (eight LRS and four controls) were sent to Otago Genomics Facility for sequencing using the Truseq Total RNA Library Preparation Protocol (Illumina). Host ribosomal RNA was depleted using the Ribo-Zero-Gold Kit (Illumina) to enhance viral discovery. Libraries were quality checked and sequenced in one lane on the HiSeq 2500 V4 Illumina platform.4.2Danio rerio) runs from the screens due to the large number of experimental data sets. To reduce redundancy, we selected the first six runs for a given species in each experimental data set. In total, 1,279 libraries (both single- and paired-end reads) were selected. SRA runs were obtained through the European Nucleotide Archive (https://www.ebi.ac.uk/ena/browser/home) that mirrors the SRA but allows for reads to be downloaded directly in a FASTQ. Reads were then analysed using our coronavirus discovery pipeline. The pipeline consisted of an initial screen that aligned the reads against a custom database of Coronaviridae and other protein sequences within the Nidovirales using Diamond BLASTx (v.2.0.2)  to exclude spurious alignments to low-complexity regions. Where coronavirus-like reads were detected (n = 32), we quality trimmed and assembled de novo raw reads into contigs using Trinity RNA-Seq (v2.9.1) + -selected). We excluded zebrafish (v.2.0.2)  with an (v2.9.1) . The ass4.3de novo using Trinity RNA-Seq (v.2.11.0)  . The ass.2.11.0)  and Diam.2.11.0) .4.4Coronaviridae and the order Nidovirales. All these sequences were obtained from NCBI GenBank. The sequences retrieved were then aligned with those generated here using MAFFT (v7.4)   employinT (v7.4) . To estiT (v7.4) , selectiT (v7.4) , and usiCoronaviridae, we reconciled the co-phylogenetic relationship between coronaviruses and their hosts. A host phylogeny was manually constructed using topologies available in the appropriate literature, and a tanglegram connecting the host and virus trees was inferred using TreeMap v3.0  using Maxima Reverse Transcriptase kit (Thermo Scientific) and ReadyMade Random Hexamers (Integrated DNA Technologies). The Maxima Reverse Transcriptase (Thermo Scientific) protocol was followed and did not include the GC-rich template options: 1 μl template total RNA, 1 μl ReadyMade Random Hexamers (10 mM), 1 μl dNTP mix (10 mM), 11.5 μl nuclease-free water, 4 μl 5X RT Buffer, 0.5 μl (20U) RiboLock RNase Inhibitor (Thermo Scientific), and 1 μl Maxima Reverse Transcriptase. The final volume (20 μl) was stored at −20°C until used in PCRs. See 4.7Letovirinae.New viruses discovered in this study were tentatively named by drawing from their host species’ common names. The virus found in pouched lamprey used the Māori name, kanakana, since they were identified in the South Island of New Zealand and following discussions with representatives for iwi (Māori tribes). We suggest that all of these viruses be grouped within the subfamily veab050_SuppClick here for additional data file.


Despite the improvements in the survival rates observed in various types of cancer in recent years, the mortality rates remain high in ovarian cancer. This is primarily caused by the advanced disease stage at presentation and the lack of effective screening methods. An important clinical objective is represented by the ability to perform a post-surgical risk stratification to identify better and more effective intervention strategies to minimize recurrence and maximize survival. Here, we sought to leverage the availability of publicly available ovarian cancer RNA sequencing data and the use of bioinformatics methods to identify a prognostic gene panel in non-metastatic high-grade serous ovarian carcinoma. Moreover, we found an association between mortality rates and tumor-infiltrating immune cells.PLXNB2, HMCN2, NDNF, NTN1, TGFBI, CHAD, CLEC5A, PLXNA1, CST9, LOXL4, MMP17, PI3, PRSS1, SERPINA10, TLL1, CBLN2, IL26, NRG4, and WNT9A) by assessing the RNA sequencing data of 342 tumors available in the TCGA database. Using machine learning, we found that specific patterns of infiltrating immune cells characterized each risk group. Furthermore, we demonstrated the predictive potential of our risk score across different platforms and its improved prognostic performance compared with other gene panels.Ovarian cancer is the eighth global leading cause of cancer-related death among women. The most common form is the high-grade serous ovarian carcinoma (HGSOC). No further improvements in the 5-year overall survival have been seen over the last 40 years since the adoption of platinum- and taxane-based chemotherapy. Hence, a better understanding of the mechanisms governing this aggressive phenotype would help identify better therapeutic strategies. Recent research linked onset, progression, and response to treatment with dysregulated components of the tumor microenvironment (TME) in many types of cancer. In this study, using bioinformatic approaches, we identified a 19-gene TME-related HGSOC prognostic genetic panel (19 prognostic genes ( According to the most recent estimates, around 314,000 new ovarian cancer (OC) cases have been diagnosed in 2020, with more than 200,000 victims [The high-grade serous subtype (HGSOC) is the most common form of ovarian cancer and often results in fatalities . In non-Over the last two decades, high volumes of genomic and proteomic data have been acquired, resulting in deeper insights into carcinogenesis and cancer progression, as well as contributing towards the field of molecular targeted therapy . Cancer In the present study, we applied a bioinformatics protocol to analyze publicly available RNA-seq datasets from The Cancer Genome Atlas (TCGA) in order to identify a novel prognostic matrisomal gene signature for high-grade serous ovarian carcinoma (HGSOC). Using a Cox proportional hazard model on matrisome-associated genes, we first defined a risk score, the HGSOC Tumor Matrisome Index (HGSOC-TMI) and stratified early stage cancer patients into risk groups. We then validated the risk score internally by using bootstrapping validation and externally on two independent microarrays datasets. Furthermore, we analyzed the expression of the HGSOC-TMI genes in two single-cell datasets from HGSOC cancer tissue and ascites samples, respectively. Using a machine-learning deconvolution method, we investigated the role of infiltrating immune cells in each risk group. We then sought to demonstrate the predictive potential of the HGSOC-TMI in stratifying patients, even using data collected by using different platforms. Finally, we compared the prognostic performance of the HGSOC-TMI with other two-gene signatures recently identified for ovarian cancer.https://web.mit.edu/hyneslab/matrisome/ (accessed on 10 June 2021). The symbols of these 1068 matrisomal genes were inputted into the XENA browser [www.xenabrowser.net, accessed on 10 June 2021) where the study “GDC TCGA Ovarian Cancer” was selected and the normalized RNA-seq data, as well as the associated clinical annotation, were accessed and exported into a spreadsheet for further data curation and analysis. This dataset was used as a “discovery dataset”. Independent HGSOC “validation datasets” (accession numbers: GSE26712 and GSE49997) were accessed by using Phantasus . The “quantile normalization” and “Log2” transformations were applied to the data. Moreover, data were collapsed by using “Maximum Median Probe” with “gene symbol” as the collapse field to remove lowly expressed probes and to ensure that only one row per gene was present in the expression matrices.The list of human matrisome genes ,25 was r browser  : HGSOC − TMI = Gene-expression matrix and clinical annotation data for the stage III/IV cohort were imported into RStudio . The Cox proportional hazard model was independently applied to each of the 1068 matrisomal genes, using the “RegParallel” package (v1.8.0). The genes with log-rank onductor . The assonductor ).p-value ≤ 0.05 was considered statistically significant. The OS time was calculated as the time between the date of surgery and death.An optimal cutoff score, computed by using the “maxstat.test” function (“maxstat” package ), was usInternal validation of the HGSOC-TMI was performed by using the penalized Cox model  and visualized through the time-dependent AUCs . The external validation was conducted on the HGSOC GEO datasets GSE26712 and GSE49997, where the expression levels of the HGSOC-TMI genes were combined with the betas calculated in the discovery dataset.https://bioturing.com/, accessed on 19 August 2021).Data from a single-cell RNA-sequencing analysis  of high-https://cibersortx.stanford.edu/, accessed on 23 August 2021). Specifically, the analysis was conducted by selecting the “LM22 signature” as “signature gene file”, with 100 permutations, and without “quantile normalization”. Subsequently, box plots were generated to quantify the differences in infiltrated immune cells between the two risk groups, using “ggplot2” (v3.3.3). Two-sided unpaired two-sample Wilcoxon tests were performed.The relative estimated abundance of 22 infiltrating immune cell types in each of the HGSOC-TMI risk groups was computed by using the web-based tool CIBERSORTx . Specifically, tissue-specific (ovary) protein–protein interactions (PPIs) analysis was selected.Network analysis of the HGSOC-TMI genes was performed by using NetworkAnalyst (Using Orange (v3.29.3), the computational classification method recently developed by Belotti et al.  and furtThe goal of our study was to identify an ovarian-tissue-specific risk score based on matrisomal components, similar to what has been recently investigated in non-small-cell lung cancer  and squaPLXNB2, HMCN2, NDNF, NTN1, TGFBI, CHAD, CLEC5A, PLXNA1, CST9, LOXL4, MMP17, PI3, PRSS1, SERPINA10, TLL1, CBLN2, IL26, NRG4, and WNT9A) with prognostic values were identified by using a Cox proportional hazard model for each matrisomal gene in the dataset against overall survival (OS). The genes with log rank p < 0.01 . Kaplan–Meier (KM) curves were generated to test the prognostic values of the HGSOC-TMI. The low-risk group showed a longer survival probability, as shown in Focusing on RNA sequencing data accessed by using XENA browser, 341 stage III/IV, primary high-grade serous ovarian carcinoma samples were analyzed. A subset of 19 matrisomal genes  that were previously investigated by Schulz et al. [ETV7, GBP4, CXCL9, CD3E, and TAP1) that were recently found by Huo et al. [p-value in HGSOC, as shown in We sought to compare the prognostic performance of the HGSOC-TMI with other two-gene signatures previously identified for ovarian cancer. The first included the Galectin 1, 3, and 7 genes  promotes HGSOC‘s progression [PLXNB2 was previously associated with cell proliferation, invasion, and decreased phosphorylation of AKT and ERK1/2 in ovarian cancer cells [PLXNB2 downregulation on the cell-growth viability, cell colony, and cell invasion, suggesting that miR-126-3p affects ovarian cancer’s progression by direct regulation of PLXNB2. Dysregulation of PLXNs was associated with the existence of immune subtypes in various cancer types’ characterized by an anomalous level of immune and stromal-cell infiltrates in the TME, which is frequently associated with patient survival and drug responses [PLXNB2 encodes a cell surface receptor that plays an important role in controlling changes in the actin cytoskeleton, axon guidance, invasive growth, and cell migration [PI3) is a serine protease inhibitor with known anti-inflammatory, antimicrobial, and immune-modulatory properties [PI3 as a potential prognostic biomarker for OC [PLXNA1 encodes a co-receptor for semaphorins and plays a role in axon guidance, invasive growth, and cell migration [PLXNA1 was upregulated in many cancer types, and its increased expression was associated with poor prognostics and correlated with more aggressive subtypes of immune infiltrates [CLEC5A is closely related to the abundance of infiltrated immune cells and the expression of immune checkpoints in the OC microenvironment [CLEC5A in OC cells was linked with increased polarization of M2 macrophages. This gene encodes a member of the C-type lectin/C-type lectin-like domain (CTL/CTLD) superfamily that is involved in cell adhesion, glycoprotein turnover, cell–cell signaling, inflammation, and immune response [PRSS1 was overexpressed in the endoplasmic reticulum of a high-grade serous ovarian cancer cell line [HMCN2 was recently associated with the inhibition of cell invasion [NDNF was associated with longer survival [NTN1 was strongly upregulated in malignant ovarian tumors when compared with benign tumors [NTN1 in cancer and immunomodulation has been reviewed by Bruikman et al. [LOXL4 was associated with worse progression-free survival (PFS) in OC patients [SERPINA10, which encodes a protein that belongs to the serpin family, was recently found to be positively correlated with overall survival OS and PFS in HGSOC [SERPINA10 expression had longer platinum-free interval (PFI) than the patients with low expression. TLL1, which encodes an astacin-like, zinc-dependent metalloprotease that belongs to the peptidase M12A family [IL26 was recently demonstrated in OC [NRG4, which is involved in the activation of type-1 growth factor receptors [WNT9A is differentially expressed in tumor cells and TAMs [The development of novel methods to identify patients in need of further adjuvant treatment after surgical resection is an important goal in cancer-treatment management. In the pursuit of such a goal, we analyzed RNA sequencing data from a large public dataset of high-grade serous ovarian carcinoma and successfully identified a set of matrisomal genes with prognostic value. Specifically, by computing the HGSOC-TMI risk score, we managed to stratify patients into risk groups. Furthermore, using supervised machine-learning-based methods, we managed to demonstrate the high accuracy and robustness of the HGSOC-TMI in risk stratification, even across different platforms (microarrays and RNA-seq), with important clinical implications. Having identified the role of specific ECM components in HGSOC progression, we believe that future investigations of the HGSOC-TMI in both early stage and metastatic ovarian cancers could provide potential insights into novel druggable molecular targets. Prospective randomized interventional studies will better elucidate the clinical value of our findings in HGSOC progression and metastasis. The KEGG signaling network analysis revealed that the HGSOC-TMI genes are mostly associated with “axon guidance” and “proteoglycans in cancer” pathways , a findiadhesion , was preadhesion . This geadhesion . Moreoveadhesion . In anotgression . PLXNB2 er cells . Moreoveesponses . PLXNB2 igration ,46. Moreigration . The pepoperties  and was operties . Two recr for OC ,51. PLXNigration . A receniltrates . CLEC5A ironment . Specifiresponse . In receell line . Moreoveell line . Downreginvasion . This geinvasion . Downregsurvival . This prsurvival . The expn tumors . This gen tumors ,63. The n et al. . Overexppatients . This gepatients . SERPINAin HGSOC . MoreoveA family , was recA family . The proed in OC . This geed in OC . NRG4, weceptors , was foueceptors . A transand TAMs , and itsand TAMs .Upon stratification, differential expression between the two risk groups was found for most of the HGSOC-TMI genes, as shown in The single-cell analysis demonstrated the expression of the HGSOC-TMI genes in cancer cells, as well as in immune cells in HGSOC cancer tissue and ascites samples.Moreover, our results showed a superior prognostic value of the HGSOC-TMI risk score compared with the two gene signatures previously reported by Schulz et al.  and Huo One of the limitations of this study is that publicly available algorithms could be modified over time or no longer maintained. This might affect the reproducibility of this study. However, on the other hand, novel efficient algorithms and web-based interfaces are constantly developed; therefore, the analysis of sequencing data will likely be further simplified in the future. Moreover, further validation of the HGSOC-TMI signature by using data from large cohorts is required in the future. This will allow for the identification of a universal cutoff value  for patMolecular diagnostics, especially transcriptomics, is becoming one of the key drivers of personalized oncology, as it enables tumor phenotyping with unprecedented precision, with important clinical results . DirectIn conclusion, using bioinformatics approaches, a 19-gene TME-related HGSOC prognostic genetic panel was identified and further validated in two independent RNA-seq datasets. Moreover, using machine-learning-based methods, specific patterns of infiltrating immune cells were found to characterize different risk groups. The predictive potential of the HGSOC-TMI risk score was demonstrated across different platforms. We confirmed the expression of the HGSOC-TMI genes in both cancer and immune cells in scRNA-seq data from HGSOC tissue, as well as ascites, samples. Finally, improved prognostic performance of the HGSOC-TMI was found compared with two previously identified ovarian cancer gene panels. This study might have important implications in the prognosis and personalized adjuvant treatments of HGSOC.


The faults of the landing gear retraction/extension(R/E) system can result in the deterioration of an aircraft’s maneuvering conditions; how to identify the faults of the landing gear R/E system has become a key issue for ensuring aircraft take-off and landing safety. In this paper, we aim to solve this problem by proposing the 1-D dilated convolutional neural network (1-DDCNN). Aiming at developing the limited feature information extraction and inaccurate diagnosis of the traditional 1-DCNN with a single feature, the 1-DDCNN selects multiple feature parameters to realize feature integration. The performance of the 1-DDCNN in feature extraction is explored. Importantly, using padding dilated convolution to multiply the receptive field of the convolution kernel, the 1-DDCNN can completely retain the feature information in the original signal. Experimental results demonstrated that the proposed method has high accuracy and robustness, which provides a novel idea for feature extraction and fault diagnosis of the landing gear R/E system. The landing gear R/E system is the significant subsystem for aircrafts, after long-term running under complex and variable conditions, with heavy loads and strong impact, the key parts in the landing gear R/E system will inevitably generate multifarious faults, which may affect take-off, landing, and flight safety.Firstly, Hinton proposed a deep learning method in 2006, which set off a new wave of research on artificial intelligence and its applications . In partThe main difference between the 1-DCNN and 2-DCNN lies in the dimension of input data and the sliding mode of the convolution kernel. Wu et al. proposed a 1-DCNN model for fault diagnosis of original vibration signals, for which test diagnosis accuracy reached 99.3% . Huang eFor the traditional CNN, the convolution and pooling operations are carried out alternately, which reduces the feature maps’ size while increasing the receptive field. However, for the pixel-level prediction problem of image segmentation, the final feature output size is required to be consistent with the original image size, which involves the down-sampling and up-sampling processes, image resolution reduction, and information loss. To solve these problems, dilated convolution came into being . Zhuang Analyze the aircraft landing gear R/E system’s main fault mode with its working principle.A conventional 1-DCNN was constructed to classify faults based on the actuator’s displacement; experimental results show the average accuracy of the test set reached 91.80%.The receptive field size affects the extraction of the original information by the model. There is a nonlinear relationship between the receptive field and the convolution kernel size for the expanded convolution. The convolution kernel size’s influence on classification accuracy is explored.There is a low classification result with a single feature; consequently, 1-DDCNNselects multi-feature parameters with the system pressure, the pressure at the right and left end of the actuator cylinder. Experimental results reveal that the average test accuracy of the model reaches 99.80%.In order to solve the above problems, this paper proposes a fault diagnosis method for the aircraft landing gear R/E system based on a 1-D dilated convolutional neural network (1-DDCNN). The main work of this paper is summarized as follows:The landing gear system of a typical aircraft mainly includes the following: front landing gear and cabin door, main undercarriage and cabin door, landing gear R/E system, wheels and brakes, turning control system, landing gear position indication system, etc. Among them, the R/E system mainly completes normal R/E and emergency R/E functions, and provides the landing gear position indication signal.The front landing gear R/E process is similar to that of the main landing gear; therefore, only the front landing gear retraction process is described here. The working status of the front landing gear is shown in The landing gear R/E system mainly includes the following components: constant pressure variable pump, tank, hydraulic motor, filter, accumulator, actuator, press control, throttle valve, and three-position four-way directional control valve.Through providing certain pressure and oil mass, the pump converts mechanical energy into hydraulic energy. The tank is used to store hydraulic oil. The filter is used to filter the hydraulic oil and remove its impurities. The accumulator not only supplies oil at both weak and heavy flows, it also compensates for leakage and maintains constant pressure. The actuator is a device that converts hydraulic energy into mechanical energy for linear reciprocating motion, which overcomes the load (including friction) and maintains the speed of motion using pressure-driven liquid flow. The relief valve is one of the common pressure valves used to regulate or limit the pressure in a hydraulic system. The throttle valve is a hydraulic component that regulates and controls the flow of oil in a hydraulic system. The function of the one-way throttle valve is to ensure that the oil flows in one direction, with no backflow, using the throttling effect. The solenoid directional valve is one of the frequently used hydraulic components in hydraulic systems, and is used to switch the direction of the hydraulic circuit. This article uses a three-position four-way solenoid directional valve. The “Position” refers to the working position of the spool. The “Way” marks the valve body of the oil port .The failure mode and effect analysis (FMEA), derived from typical civil aircraft design data in this subsection, can be used for parameter selection and fault injection into the simulation model, whereby fault datasets are obtained. The FMEA was carried out on the system’s main components for subsequent fault diagnosis, the results of which are shown in The receptive field is defined as the area size mapped on the original image by each pixel on the feature map output from each layer in the CNN. The neuron’s receptive field value decides the original range it can cover, meaning that it may contain more global features. Before inputting 1-D time series signals into 2-DCNN, the common method is to rearrange and combine signal sampling points, using a simple procedure, and convert them into 2-D matrix form. The 1-DCNN has the advantage that 1-Dtime series signals can be input directly without the need for cumbersome conversions.i-th layer filter.The output receptive field of the n-th layer is:n is even number, is:According to the receptive field’s design principle, the size of the neuron receptive field in the last layer is close to the input signal’s length, that is, it satisfies the condition According to the condition Dilated convolution is also called expanded convolution; it replaces the traditional CNN pooling operation by introducing the expansion ratio, which can completely retain the feature information in the original signal so that the convolution kernel of the same size can obtain a larger receptive field.k = 3). The step size is 1 × 1. The expansion rate is 2 . On the basis of Equation (5), the convolution kernel size of the first convolutional layer is 50. From the comparative test, the model with convolution kernel size 50, convolution number 4, and moving step size 1 at the first convolution layer, has the best diagnostic effect. The specific parameters of the traditional 1-DCNN model are shown in Zhou  analyzedDue to the limited feature information extraction and inaccurate classification of the traditional 1-DCNN model with a single-feature parameter (actuator cylinder displacement), the three features, e.g., system pressure and the pressure at the right and left end of actuating cylinder, are selected to jointly characterize six failure statuses.Referring to the traditional 1-DCNN, in 1-DDCNN we initially set the convolution kernel size as 50, the step size as 1, and the expansion factor as The network structure and initial settings are shown in According to Equation (7), once the expansion factor is determined, the parameter that has a decisive influence on the receptive field size is the convolution kernel size. Since the output size of each dilated convolution layer in the 1-DDCNN is 3201 × 1, the convolution kernel size does not affect the output features’ size of the dilated convolution layer, but has a great influence on the feature extraction degree of the original data. Therefore, it is necessary to investigate the convolutional kernel size’s effect on the classification accuracy. The convolution kernel size was set to 30, 40, 50, 60, and 70 in turn to investigate the diagnostic accuracy of the 1-DDCNN under different conditions, and to determine the final model hyper-parameters.−5.Considering the accuracy, stability, and training cost comprehensively, results are optimal when convolution kernel size is set as 40 × 1.To show the dilated convolution’s advantages in feature extraction and information loss prevention, the comparative experiments of three models, e.g., traditional 1-DCNN, 1-DDCNN, and 1-DDCNN II, with dataset A and dataset B, were conducted. Depending on whether the same size is maintained between the feature map and the input data, two types of convolution operations exist: VALID (without padding) and SAME (with padding) convolution operations. Compared to the 1-DDCNN, the 1-DDCNN II’s dilated convolution layer was VALID, and the convolution kernel size was uniformly set to 51 × 1. Inputting the dataset into 1-DDCNN II, the output size of the flattening layer was 3264 × 1 after six dilated convolution layers, which is slightly larger than the sequence length of the input samples. The model structure is similar to the 1-DDCNN, and specific parameter settings are shown in It can be seen from The training processes and confusion matrices for the three models are shown in In When the 1-DCNN model with dataset A was located at the 100th iteration, the training accuracy was 98.63%, and the training loss value was 0.0441. The validation accuracy was 98.61% and the validation loss value was 0.0609. The confusion matrix corresponding to the test set is shown in It can be seen in −5. In terms of training cost, the iteration number should be set as 63 in subsequent model training.It can be seen in Since the 2-DCNN cannot directly process one-dimensional time series data, which often requires complex pre-processing, a novel 1-DDCNN is proposed for landing gear R/E system fault diagnosis in this paper. Dilated convolution can exponentially increase the receptive field of the convolution kernel by adding the convolution layer, which could acquire more redundant information to alleviate the influence of randomness. The displacement of the actuator cylinder was selected as the feature parameter, and the diagnosis classification was carried out on the traditional 1-DCNN model, for which the average diagnosis accuracy reached 91.80%. Due to the limited feature information extraction and inaccurate diagnosis for a single feature in the traditional 1-DCNN, multiple feature parameters are selected to jointly represent the fault and to input into the proposed model for feature integration. The convolution kernel size’s influence on classification accuracy is explored. When the convolution kernel size is 50, the model has the highe ststability. The results show that the average diagnostic accuracy of the proposed model is 99.80%, compared with other models.Future work will be carried out on the following two aspects. Firstly, the system has noise in the actual working environment, and it is necessary to verify the robustness of the proposed model on noisy data. Secondly, this paper only considers the influence of a single parameter, such as oil mixing into the air or actuator leakage, on the system operating state. In the future, the complex situation of the simultaneous failure of multiple internal components, and the consequent effects on the system operating state, should be studied.


Although studies on the uptake of Adolescent sexual and reproductive health (ASRH) services in Ethiopia have been conducted they have failed to show the disparity in service uptake among rural and urban settings. Once the extent and determinants of ASRH service uptake in urban and rural contexts are known, it will be crucial to provide evidence-based information and recommendations for potential interventions to reduce the burden of disease and disability among adolescents. This study aimed at determining the level of SRH service utilization among urban and rural adolescents in the Guraghe zone, Southern Ethiopia.A community-based comparative cross-sectional study was undertaken from November 1 –30, 2020. A multi-stage sampling technique was employed and a total of 1083 adolescents  were selected randomly to take part in the study. Pre-tested, interviewer-administered, structured questionnaires were used to collect the data. The data were encoded and entered into Epi-Data version 3.1 and then exported to SPSS version 23 for analysis. χ2 test was computed to see a significant difference in SRH service utilization among urban and rural adolescents. In a bivariable logistic regression analysis, a variable with a p-value less than 0.25 has been selected for a multivariable logistic regression model. Variables with p-values less than 0.05 were declared statistically significant in multivariate logistic regression.p < 0.001). Residence, availability of youth clubs , taking part in peer education , having parental discussion , and being knowledgeable on SRH issues  were identified as a significant determinants of SRH service uptake. Having parental discussion, geographical accessibility, and knowledge on SRH were significant predictors of SRH service uptake among rural adolescents.A total of 1,075 adolescents  took part in the study, yielding a response rate of 99.3%. The overall SRH service utilization among the whole adolescents was 39.5% . There was a significant difference in SRH service utilization between urban 56.9%  and rural 30.8%  adolescents (χ2 = 68.3, Overall, ASRH service utilization in the study area was low, despite urban adolescent service uptake becoming higher than rural adolescents. Since the majority of adolescents were enrolled in schools, schools should be an area of intervention to improve adolescents' knowledge of SRH services through mass media, community networks, and interpersonal/group communication. Furthermore, promoting parent-adolescent discussions, as well as peer-to-peer discussions at the family and school level, should be emphasized. Stakeholders in the education and health sectors need to strengthen their efforts to establish youth clubs in places where they do not yet exist, especially in rural schools.The online version contains supplementary material available at 10.1186/s12889-022-12634-x. Adolescence is a crucial period of human development, characterized by rapid physical, psychosocial, intellectual, and emotional maturation, as well as erotic and reproductive maturation , 2. HealAdolescent sexual and reproductive health (ASRH) services are described as a set of strategies, procedures, and services aimed at preventing and treating sexual health problems in adolescents while also promoting their overall well-being , 5. It eAdolescents number up to 1.2 billion worldwide, with 513 million between the ages of 15 and 19, and 85 percent of them live in developing countries –12. In sWhile the Convention on the Rights of the Child (CRC) protects adolescents' right to SHR services, neither the providers of these services nor the systems under which they operate are equipped to recognize adolescents' needs and benefits –16. In dNeglecting adolescent SRH services has serious consequences; adolescent girls, in particular, are at higher risk of unintended pregnancy, HIV and sexually transmitted infections (STIs), sexual coercion, exploitation, and violence , 18. EveAccording to the 2019 Mini Ethiopian Demographic and Health Survey (mini-EDHS 2019), contraceptive usage among currently married women aged 15–19 years was just 36.5%, with injectable, implants, and IUD use of 27.5%, 5.9%, and 0.0%, correspondingly . With 75The Federal Ministry of Health (FMOH) of Ethiopia has introduced various strategies to facilitate national-level adolescent and youth reproductive health services to overcome SRH problems , 13. DesAlthough studies on the uptake of ASRH services in Ethiopia have been conducted –25, theythe smallest administrative unit next to a district in the Ethiopian government). There are 128 health facilities which are quantified as 74 health centers, 5 hospitals, 168 health posts, 30 private clinics.From November 1 to 30, 2020, a community-based comparative cross-sectional study has been undertaken in the Guraghe Zone, Southern Ethiopia. The zone is 158 km from Ethiopia's capital, Addis Ababa, and 337 km from Hawassa . For the fiscal year 2020, the Zone's total population was 1,807,689, with 1,468,940 (81.3%) and 338,749 (18.7%) living in rural and urban districts, respectively. Adolescents between the ages of 15 and 19 constituted 13.6%  of the total population. The zone is divided into nine rural districts and four urban administrative, comprised of 174 rural and 27 urban kebeles . The two selected town administrative (Urban) were Wolkite town (with 8kebeles) and Butajira town (with 9 kebeles). At stage two 20 rural kebeles, were randomly selected from a total of 59 kebeles in the four rural districts mentioned above. Of the 17 urban kebeles, 7 were selected by lottery method. Finally, the sample size was proportionally allocated to each selected kebele  in one of the unselected districts. Based on the results of the pre-test, all necessary changes were made to improve the completion of the questionnaires. Confusing and long questions were removed and shortened as a result of the pre-test.The principal investigator and field supervisors closely oversaw and coordinated the total data collection process. Before analysis, all of the data were double-checked for completeness and consistency. The data were taken in a quiet area of the study participant's home where there was no noise or disturbance.Sexual and reproductive health (SRH) service utilization: when adolescents received at least one of the five important elements of SRH services; information and education on SRH matters, consultation and provision of modern contraceptives; STIs diagnosis and management, getting VCT service, and abortion and/or post-abortion care within the last 12 months , 25.Adolescent: In this study, adolescents denote boys and girls between the ages of 15–19 , 26, 27.Parental Discussion on SRH issues: Adolescents who have discussed at least two SRH topics in the previous 12 months together with their parent/s .Sexual exposure history: Adolescents who had sex in their lives have been identified as having a sexual encounter history and not otherwise Modern contraceptive service utilization: Adolescents that during the past 12 months have used any of the modern methods of birth control , injectables, implants, intrauterine devices, emergency contraceptive pills, and spermicidal agents) , 26.Accessibility to SRH service: Applied to the perceived distance traveled by respondents to reach SRH service delivery points and/or time spent by them. Adolescents residing within a 1.6-km radius of the nearest SRH service center and/or reaching those service delivery points within a walking distance of fewer than 30 min were graded as having good and otherwise poor geographical mobility.Substance use: Using addictive substances such as alcohol, ‘khat’, or cigarettes with either frequency of; more repeated than daily, daily, weekly or monthly in the past 12 months before the study .Reproductive health service knowledge: Twelve questions were asked to adolescents encompassing the perceptions about SRH issues. An index that summarizes the level of knowledge and categorizes it as Knowledgeable if the summary index is equal to or greater than the mean , 24.Availability of Youth clubs: Accessibility of places/rooms where young people can meet and gather SRH information, SRH services such as contraceptives, physical activities, social support, peer-to-peer discussion, with the aid of trained workers and volunteers to protect adolescents from negative events, anti-social behavior, crime, drug, and alcohol abuse that are a problem in this community –30.p < 0.001), indicating that the factors associated with SRH utilization could be different among rural and urban groups. Therefore, the analysis was conducted separately. Bivariable logistic regression was used to find out the relationship between SRH service utilization and the independent variables, and variables with a p-value of less than 0.25 were selected candidates for a multivariable logistic regression(MLR) model. Variables with a p-value less than 0.05 were considered statistically significant in multivariable logistic regression analysis. The AOR and its 95%CI were used to report the association between SRH service utilization and explanatory variables. The model fitness was assessed using the Hosmer and Lemeshow goodness of fit tests, which yielded a score of 0.59. The variance inflation factors (VIF > 10) were used to check for multicollinearity amongst the explanatory variables.The data entry was done using EPI Data 3.1 and exported for analysis to SPSS version 23. Using descriptive statistical analysis, frequency, percentage, and mean for explanatory and response variables were run. Chi-square testing was done to see if there was any significant on SRH service uptake among urban and rural adolescents and a statistically significant difference was observed between the two groups  took part in the study, yielding a response rate of 99.3%. The mean (± SD) age of the adolescents was 17.0 ± 1.4 years. Females make up a majority of respondents , with 57.3% and 59.7% living in urban and rural areas, respectively. Over half of all respondents, 560(52.1%), attended high school, with 196 (54.7%) in an urban and 364 (50.8%) in a rural setting. The majority of adolescents in both groups belong to the Guraghe ethnic group  and followers of orthodox religion  (Table p < 0.001). Health centers and private clinics were among the service delivery points frequently accessed by 219 (61.2%) and 174 (48.5%) of urban adolescents, respectively .In terms of geographic accessibility, 264 (73.7%) of urban adolescents and 183 (25.5%) of rural adolescents were able to access SRH service delivery points within a 30-min walk of their home . Unwanted pregnancy was the most common topic addressed during a parental discussion among both urban and rural adolescents, with 134 (81.2%) and 141 (70.1%), respectively  adolescents reported having had a sexual partner/s in their lifetime, with 115 (urban: 57 (62.6%) and rural: 58 (42.6%) having had sexual intercourse at least once. Between urban and rural adolescents, there was a significant difference in having a parental discussion in the previous 12 months(urban = 165(46.1%); Rural = 208(29.1%), χ2 = 30.741, The level of knowledge of adolescents on SRH issues was assessed using eleven items. As a result, study participants had a mean (± SD) knowledge score of 5.4 ± 2.4 . Nearly half of the study participants, 508 (47.2%), had a good knowledge of SRH issues, with 186 (51.9%) in the urban and 322 (44.9%) in the rural. Nearly seven out of ten (69.3%) of urban and more than half (56.8%) of rural adolescents had information about SRH services and the school environment was found to be the most popular source of information among both urban and rural. At least one form of SRH service that should be provided to an adolescent is reported by 221 (61.7%) of urban and 343 (47.3%) of rural adolescents (Table p < 0.001). SRH information and education was the most frequent SRH service item received by both urban and rural adolescents, with 156 (43.6%) and 217 (30.3%) respectively. Only 13.7% of urban and 8.5% of rural respondents received STI Diagnosis and Management services . There was a significant difference in the rate of SRH service utilization between urban 204(56.9%)  and rural 221(30.8%)  adolescents  adolescents as the most prevalent hindrance to SRH service uptake (urban: 96 (62.3%) and rural: 356(71.8%). Lack of well-trained health care providers(HCPs) on SRH service was the other reason mentioned by 54(35.1%) of urban adolescents. Far distance to nearby health facilities was another prominent reason mentioned by 319(64.3%) of rural adolescents  units had a 4.7 times greater chance of using SRH services than their counterparts . It was revealed that having a parent discussion about SRH had a positive influence on SRH service adoption. Adolescents who had a parental discussion had a 3.3 times higher chance of using SRH services than those who did not . Furthermore, adolescents who were knowledgeable on SRH matters had a 2 times higher likelihood of using SRH services than their counterparts   program , 15. ThiThere was a significant difference between the two groups when it came to individual components of the SRH service. 43.6% of urban and 30.3% of rural adolescents received SRH information and education. As compared to studies conducted elsewhere in Ethiopia, these figures were lower , 26, 27.Residence, having a peer-to-peer education, having a parental discussion, the availability of a youth club, and being knowledgeable on SRH issues were identified as factors that influence the uptake of SRH services among the whole adolescents.Urban adolescents had a 2.64 times greater chance of utilizing SRH services than rural adolescents. The possible justification is that urban adolescents may have access to a variety of SRH programs tailored to their age in close surroundings through youth clubs and socio-cultural and economic contexts, which might improve service uptake . In EthiAccording to the results, getting a parental discussion has a positive impact on ASRH service adoption among all adolescents, including urban and rural. Adolescents who had a parental discussion about ASRH matters were more likely to use ASRH services than those who did not. Numerous research in Africa, including Ethiopia, supplemented this , 33, 36.Adolescents who engaged in peer education about ASRH issues had a higher likelihood of using the ASRH service. This is supported by similar studies done in Awabel district, Northern Ethiopia, Kenya, and Myanmar , 39, 40.The current study found that adolescents who are knowledgeable about SRH issues are more likely to use ASRH services than their counterparts. Furthermore, knowledgeable rural adolescents had a higher likelihood of using SRH services. This is supported by a similar study done in northern Ethiopia . This isThe existence of a youth club in their immediate environment determines whether or not they use the ASRH service. Adolescents who claimed that there were youth clubs in their immediate environment were more likely to use SRH services than those who reported that there was no youth club. This is in line with research undertaken in African countries –30. If yThe distance  was found to be a significant predictor of rural adolescents' use of SRH services. Adolescents who had to travel less than 30 min to get to the health facility were 2.1 times more likely to use SRH services than those who had to travel more than 30 min. This is supported by studies conducted in Mozambique and Nigeria , 45. ThiThis research has both strengths and limitations. This is the first study of its kind to compare the uptake of SRH services by adolescents in urban and rural settings and may have important policy implications for the further improvement of SRH services. Furthermore, adequate samples were taken to determine the contrast between the two groups. While every effort has been taken to reduce the study's flaws, readers should proceed with caution when interpreting the results. Respondents may be prone to social desirability biases, which may have contributed to underreporting of some SRH services, since that it involves some sensitive issues and was based on self-reports. Finally, there is a likelihood of recall bias because the adolescents in this study were inquiring about events that had already occurred.There was a significant difference in SRH service utilization between urban and rural adolescents. Residence, availability of youth clubs, taking part in peer education, having a parental discussion, and being knowledgeable on SRH issues were identified as significant determinants of SRH service uptake. Having parental discussion, geographical accessibility, and knowledge on SRH were significant predictors of SRH service uptake among rural adolescents. Since the majority of adolescents were enrolled in schools, schools should be an area of intervention to improve adolescents' knowledge of SRH services through mass media, community networks, and interpersonal/group communication. Furthermore, promoting parent-adolescent discussions, as well as peer-to-peer discussions at the family and school level, should be emphasized. Stakeholders in the education and health sectors need to strengthen their efforts to establish youth clubs in places where they do not yet exist, especially in rural schools.Additional file 1. Additional file 2.


Here we present a robust method based on immunofluorescence-guided laser capture microdissection (immuno-LCM-RNAseq) to acquire finely resolved transcriptional programs with as few as tens of cells from snap-frozen or RNAlater-treated clinical tissues sufficient to resolve even isoforms. The protocol is optimized to protect the RNA with a small molecule inhibitor, the ribonucleoside vanadyl complex (RVC), which thereby enables the typical time-consuming immunostaining and laser capture steps of this procedure during which RNA is usually severely degraded in existing approaches. The efficacy of this approach is exemplified by the characterization of differentially expressed genes between the mouse small intestine lacteal cells at the tip versus the main capillary body, including those that function in sensing and responding to local environmental cues to stimulate intra-cellular signalling. With the extensive repertoire of specific antibodies that are presently available, our method provides an unprecedented capability for the analysis of transcriptional networks and signalling pathways during development, pathogenesis, and aging of specific cell types within native tissues.The functioning of tissues is fundamentally dependent upon not only the phenotypes of the constituent cells but also their spatial organization in the tissue, as local interactions precipitate intra-cellular events that often lead to changes in expression. However, our understanding of these processes in tissues, whether healthy or diseased, is limited at present owing to the difficulty in acquiring comprehensive transcriptional programs of spatially- and phenotypically-defined cells  For the former, while directly imaging the FISH signals provides a straightforward means of detection and quantification, the transcriptomes determined by these methods only include those transcripts that are fully annotated and for which suitable probes can be designed, which limits the detectable transcripts, particularly those from novel genes   combinedwith LCM . To datewith LCM . This diwith LCM . Severalwith LCM . HoweverIn this method paper, we present a broadly applicable immuno-LCM-RNAseq method that enables high quality RNAseq with a variety of tissues for spatial transcriptome acquisition from sections of either snap-frozen or RNAlater preserved clinical tissues. The power of this approach is demonstrated here with an initial characterization of the differences in the transcriptional programs between the lacteal tip and main body cells in the mouse small intestine, which implicate several genes involved in sensing and responding to local environmental cues to stimulate intra-cellular signalling. We anticipate that this method will become indispensable in the acquisition of spatial transcriptomes of phenotype-defined cells in their native environment, such as developing embryos or aging tissues, to enable a thorough understanding of the intrinsic signalling networks that ultimately underlie tissue growth, functioning, and decline.(1) Tissue preservation with either snap-freezing or RNAlater treatment.(2) Preparation of tissue sections in a cryostat at appropriate temperatures.(3) After fixation and proper dehydration, standard two step immunostaining in a specially prepared solution that includes the small molecule RNase inhibitor .(4) Collection of immunofluorescence-defined cells with laser capture microdissection under controlled conditions.(5) RNA quality check using leftover materials to determine whether to proceed.(6) Extraction of RNA from collected cells to remove residual RNase inhibitor for subsequent steps.(7) Preparation of cDNA libraries using the Ovation SoLo system  for the analysis of full transcripts and isoforms.(8) Quality check of the cDNA libraries with a 2100 Bioanalyzer before next generation sequencing.(9) Construction of transcriptional programs and data analysis with publicly available software packages.The workflow of the immuno-LCM-RNAseq method consists of the following steps that are schematically presented in 6–8 weeks old C57BL/6 mice  were used in these experiments. All mice were euthanized by cervical dislocation. The stomach, small intestine, liver, kidney, colon, spleen and testis were freshly dissected and cleaned in ice-cold RNase-free phosphate-buffered saline (PBS) solution. After absorption of excess liquid, tissues were placed in 2.5 ml capped cryogenic vials individually, and sealed with Parafilm . Tissues were then snap-frozen in liquid nitrogen for 30 min and stored at −80°C.For snap-frozen tissues, the cryostat  was first defrosted and spray-cleaned with RNaseZap  and pure ethanol . The cryochamber temperature (CT) was set at -22°C and the specimen temperature (OT) was set at −20°C as commonly recommended . The OptAll immunostaining procedures were performed in a RNA-specific biological safety cabinet which was pre-cleaned by RNaseZap. However, antibody labelling was carried out at 4°C in a refrigerated chamber.For the Rapid protocol, we followed a previously established procedure . The airFor the high-salt protocol, we closely followed the original protocol presented in the reference . In shor3 and washed in ice-cold RNAlater solution, then left in the RNAlater solution at a RNAlater:sample volume ratio ≥10:1 at 4°C for 4–8 h. Excess RNAlater solution was then removed and the treated tissue was stored at −80°C. All experiments with animals were performed in compliance with the guidelines of the Institutional Animal Care and Use Committee of the Shanghai Jiao Tong University. The clinical human jejunum tissue was collected from a gastrectomy patient . The tissue was cut into small pieces and immediately placed into the RNAlater solution on ice. Tissue samples were stored at −80°C until use. Approvals were obtained from the Research Ethics Committee at Renji Hospital, Shanghai, China.For samples preserved in RNAlater  which protects RNA from degradation, tissues were first cut into pieces smaller than 0.5 × 0.5 × 0.5 cmFor RNAlater-preserved tissues, the CT and OT were kept below −28°C. This was achieved by flowing a stream of liquid nitrogen gas across the cryostat knife holder. The frozen RNAlater-preserved tissue often contained a thin layer of solidified RNAlater material on the surface, which prevented direct contact between the tissue and OCT, and often led to difficulties in proper sectioning. To remove this solidified RNAlater layer, we partially immersed the frozen RNAlater-preserved tissue in fresh ice-cold OCT, and after OCT solidified, removed the sample from the frozen OCT, which left a large portion of the RNAlater layer attached to the frozen OCT. This was performed repeatedly until the residual RNAlater layer was completely removed from the tissue. The tissue was then fully embedded within ice-cold OCT, cut into 12 μm-thick serial sections and mounted on a PET slide. The sections were dried for 2–3 min in the cryostat before fixation (for IF).2, 20 mM Tris•HCl, pH 7.4) in a RNA-specific biological safety cabinet. We refer to this 10 mM RVC solution as the RVC solution unless otherwise indicated. The sections were pre-blocked with an equal volume mixture of 20 mM RVC in buffer A and the ready-to-use protein block serum-free solution at 4°C for 15 min, followed by 3 times wash with the RVC solution. The slides were then incubated for 3.5 h with the primary antibody: either anti-mouse Pan Cytokeratin antibody (PanCK) , anti-mouse Lyve1 antibody  or anti-human Podoplanin antibody . After washing 3 times with the RVC solution, the slides were incubated with the secondary antibody, either Alexa Fluor 488 conjugated goat-anti-rabbit or donkey anti-mouse  or Fluor 568 conjugated donkey anti-mouse , in the dark for 1 h at 4°C. All antibodies were pre-diluted in the RVC solution and a 1:4 dilution of the ready-to-use protein block serum-free solution before use. After secondary antibody incubation, the slides were washed 10 times with the RVC solution and temporarily stored in a light-tight box until laser microdissection. For validation of the lymphatic vessel location in the small intestine or stomach tissue sections, we further stained with Hoechst  in the dark at 4°C for 10 min, then washed 10 times with the ice-cold RVC solution. For maximum RNA protection, the RVC solutions must be freshly prepared before use: long term storage, even at 4°C, can severely reduce its effectiveness.The sections on PET slides were first fixed with cold acetone in the cryostat: 30 s for snap-frozen tissues and 5 s for RNAlater-preserved tissues. For the snap-frozen tissue, longer times (from 1 to 5 min) led to decreased RNA yields, whereas shorter times (5 s) led to insufficient fixation of the tissue. For the RNAlater samples, we found that a fixation time of 5 s led to a greater yield of RNA and antibody labelling than a 30 s fixation, likely owing to some level of fixation produced by the RNAlater solution . The fixLaser capture microdissection was performed with the Zeiss PALM MicroBeam LCM system  housed in a Plexiglas housing. The fluorescence microscope of this system has a resolution of about 0.25 μm, while the laser cutting precision can reach down to 0.7 μm under the ×40 objective and 0.6 μm under the ×63 objective. As such, the system has a high enough resolution to select single cells, and even single nuclei . Desiredβ-Mercaptoethanol (β-Me)) followed by RNA extraction and examination with the 2100 Bioanalyzer.For all of the following, RNA was extracted using the RNeasy Micro Kit  and examined with the 2100 Bioanalyzer , which can detect as low as 200 pg/μl RNA. The RNA quality of the tissues was initially evaluated by extracting the total RNA from a few pieces of the sections of either the snap-frozen or RNAlater preserved tissues. Only those tissues with an RNA integrity number (RIN) greater than 9.0 were used. The RNA quality was also evaluated after microdissection by examining the leftover materials from the same section to make sure that there was no serious degradation during the procedure. Only those with RIN >7.0 were considered of sufficient quality for further analysis. As documented in literature, an RIN >6.5 is generally considered sufficient for transcriptomic analyses as lower RIN samples often result in the loss of library complexity . These lThe samples stored in the GITC lysis buffer were thawed on ice, pooled, and then additional GITC lysis buffer was added to bring the total volume to 200 μl. RNA/DNA was precipitated by incubation at −80°C for 2 h with 600 μl cold ethanol , 20 μl 3 M NaAc  and 1 μl Glycogen . The samples were then centrifuged for 30 min at 4°C and the precipitate was washed 3 times with 75% cold EtOH, followed by dissolution in 10 μl RNase-free water (including 2U/μl SUPERase• In™ RNase Inhibitor). The DNA was digested with HL-dsDNase in DNase buffer  at 39°C for 15 min. The cDNA library was constructed using the Ovation SoLo RNAseq Kit , according to the manufacturer’s instructions. The number of optimal PCR cycles was determined by qPCR following the manufacturer’s recommendations. The cDNA library quality was evaluated using the 2100 Bioanalyzer .The cDNA library was sequenced on the Illumina high-throughput sequencing platform with the 2 × 150 bp pair-end mode. Raw reads were first submitted to Cutadapt-1.16  with pa with pa was usedTo evaluate the reproducibility of the replicates, the mouse genome was partitioned into 1 kb bins and the number of clean reads in each bin was counted with bedtools (v2.27). The Pearson correlation coefficient was then calculated pairwise between the samples. Transcript and gene level expression was estimated with StringTie-1.3.3    and the tip samples (3 replicates) using the DESeq2 package (1.28.1)  with def(v3.0.1) . Tube-sp(v3.0.1) .For the analysis of the data from the recent LCM RNAseq study of bone marrow , we randWe first re-evaluated the image quality and extent of RNA protection of the existing approaches used for immuno-LCM, namely “Rapid Immunostaining”   and usinhttps://www.proteinatlas.org/ENSG00000129538-RNASE1/tissue), only the high-salt protocol provided good RNA protection, albeit with a moderate degradation with increased incubation time (RIN: 8.6 at 5 h vs. 7.0 overnight)  . Howeverernight) . This sternight) . We noteernight) .3   in a few studies previously . With the mouse small intestine, we found that 5 mM RVC was not sufficient to fully protect the RNA (RIN 6.3), but with 10 mM RVC, the quality of RNA was significantly improved (RIN 8.1) while the IF images remained excellent ) in which the Rapid protocol was used during immuno-labelling. Although the main focus of this work was the characterization of the transcriptomic details of mixtures of 200-300 cells in different niches, and not a comprehensive understanding of phenotype-specific cells, their results serve a useful indicator of what can be presently achieved with the Rapid protocol. From a comparable number of cells, and at a similar sequencing depth, we were able to identify more genes (13521 vs. 3266), with a lower rRNA mapping rate (14 vs. 65%) and a lower intergenic mapping rate (7 vs. 15%), as well as superior overall and exonic mapping rates . We pooled this material into three independent replicates, each with an estimated 150 cells. We obtained 50–58 million clean reads for each and the average overall mapping rate was 78% . As expeTnfsf15, an established activator of lymphatic endothelial cell growth , both encoding for actin-filament severing proteins, were not expressed in the tip of the lacteal but robustly expressed in the tube cells   offers aAlthough with the present approach, as few as ∼60 cells were demonstrated to be sufficient to acquire high quality transcriptomes, there should still be room for further improvement. Indeed, LCM has the ability to isolate single cells, and even single nuclei . In our in vivo conditions and environments, to be acquired. In comparison to the “standard” transcriptomes derived from scRNAseq profiles, the transcriptomes acquired with immuno-LCM-RNAseq are not only more comprehensive, but even more importantly, obtained under exactly the same conditions. In fact, potential artefacts owing to single cell preparation procedures notwithstanding (It should also be noted that with either snap-frozen or RNAlater preservation, the tissues should still retain their native state if the protocols are performed properly. Therefore, immuno-LCM-RNAseq allows for the native transcriptome, i.e., under standing , even thIn summary, we have established a powerful method for acquiring spatial transcriptional programs based on immuno-guided LCM with exceptional RNA quality to allow full length transcript analysis. With this unprecedented capability, rare cell types in particular or cells whose functioning is exquisitely sensitive to their positioning or local environment within the tissue can now be interrogated to obtain an understanding of their complete transcriptome, including transcript isoforms from which both cell intrinsic and cell-cell signalling networks may be delineated. It is only with such a systems-wide characterization of the cells within the native tissue can their inter-related functioning be fully understood, which is ultimately essential for an understanding of the functioning of the tissues as a whole, whether healthy or diseased.