Likewise, the sampling time did not influence the results of real-time PCR analysis of gene expression when comparing RNA samples prepared from adipose or muscle tissue immediately following either exsanguination or scalding (p > 0.92). However, sampling tissue prior to scalding resulted in a greater visual color score (p < 0.001) and lesser L* (p < 0.001) and b* (p < 0.001) values without impacting the 24 h pH (p < 0.41). These results suggested that if both RNA-based assays and meat quality endpoints are to be performed at the same anatomical location on an animal, tissue sampling to facilitate RNA-based assays should occur at a time point immediately following scalding. These findings demonstrated that sampling of adipose and muscle tissue can be delayed until after scalding/dehairing without decreasing the RNA integrity or altering the results of real-time PCR assays, while doing so was associated with little impact on measures of pork quality.Improving production efficiency while enhancing pork quality is pivotal for strengthening sustainable pork production. Being able to study both gene expression and indices of pork quality from the same anatomical location of an individual animal would better enable research conducted to study relationships between animal growth and carcass merit. To facilitate gene expression studies, adipose and muscle tissue samples are often collected immediately following exsanguination to maximize RNA integrity, which is a primary determinant of the sensitivity of RNA-based assays, such as real-time PCR. However, collecting soft tissue samples requires cutting through the hide or skin. This leaves the underlying tissue exposed during scalding, poses possible food safety issues, and potentially confounds pork quality measures. To overcome these limitations, the effect of tissue sample timing post-harvest on RNA integrity, real-time PCR results, and pork quality measurements was investigated by sampling subcutaneous adipose tissue and longissimus thoracis et lumborum muscle immediately following either exsanguination, scalding, or chilling. Sampling time did not affect RNA quality, as determined by the RNA integrity number of RNA samples purified from either adipose (RIN;  Enhancing pork quality and production efficiency is pivotal for strengthening the sustainability of pork production ,2,3. GenCorrelating RNA-based and carcass merit data, however, presents a conundrum in research abattoirs. The sensitivity of RNA-based assays is determined by RNA integrity, which can be greatly influenced by factors related to tissue sampling ,7,8,9,10On the other hand, cutting through the skin and leaving underlying tissue exposed before the carcass is scalded, de-haired, and further processed is likewise potentially problematic. For instance, such sampling presents potential food safety issues, promotes the separation of fat layers on the carcass during scalding, and potentially confounds the measurement of pork quality attributes, such as pH, color, and tenderness, near the sampling site due to the mechanical disruption of the tissue or through increased exposure to ambient temperature during subsequent carcass fabrication ,15.To address these issues, animal numbers are often increased to allow for some pigs to be used for tissue sampling, with the remaining pigs within a treatment being used for the measurement of carcass merit. Determining a sampling time that allows for optimized RNA integrity without confounding pork quality attributes would allow these endpoints to be measured within the same animal, greatly increasing the robustness of data while allowing for the use of fewer animals.Importantly, the pH decline associated with the conversion of muscle to pork is in fact compatible with the goal of preventing alkaline conditions during RNA extraction ,17,18. MTherefore, the objective of this study was to determine whether tissue sampling could occur immediately following scalding/dehairing of the carcass without altering the results of subsequent RNA-based assays and pork quality measurements. We hypothesized that if sampling subcutaneous adipose and longissimus dorsi tissue after scalding was indeed appropriate, then no differences in RNA integrity, real-time PCR results, or pork color and ultimate pH would be attributable to the scalding process.Sus domesticus; n = 32), sourced from the resident herd at the Auburn University Swine Research and Education Center (SREC), were reared according to typical industry practices to a body weight of 121.3 ± 3.6 kg. All experimental procedures were reviewed and approved by the Auburn University Institutional Animal Care and Use Committee . The Auburn University College of Agriculture is further accredited by the Association for Assessment and Accreditation of Laboratory Animal Care International (AALAC) and this study was conducted in accordance with the Federation of Animal Science Societies’ Guide for the Care and Use of Agricultural Animals in Research and Teaching. Purebred Yorkshire pigs  and then another tissue sample was collected from the same carcass above the tenth rib on the right side immediately following scalding/dehairing  so that pairwise comparisons could be made on the same carcasses to determine the effect of timing of sampling on RNA integrity and PCR results.2 and extending from the skin through the loin muscle to approximately 3 cm deep above the tenth rib. Tissue samples were then immediately snap-frozen via immersion in liquid nitrogen within 5 min of collection and subsequently stored at −80 °C until RNA was later extracted and analyzed. Regardless of the timing of sample collection, carcasses were subjected to scalding and dehairing (immersion for 5 min at 65 °C) following exsanguination. All scalded carcasses were then processed according to standard operating procedures of the Lambert-Powell abattoir. Indices of meat quality were then measured at the tenth rib on the right side at 24 h postmortem as described below.In both experiments, samples of subcutaneous adipose tissue and longissimus muscle were collected by cutting a plug of tissue from the carcass of approximately 2.54 cmL*, a*, and b* values. The Miniscan was calibrated prior to use according to the manufacturer’s recommendations with a black and white tile, using a D 65 light source, a 10° viewing angle, and a 35 mm viewing area. Group means are reported as the average value of the indices sampled across 8 individual animals per group with each animal value representing the mean of three replicates within the animal.The hot carcass weight was recorded after harvest and carcasses were chilled at 2 ± 1 °C for 24 h, at which point, carcasses were weighed again. At 24 h postmortem, carcass pH was recorded in the right loin using a portable pH spear probe meter . Carcasses were then split between the 10th and the 11th ribs for evaluation of back fat (BF), loin eye area (LEA), subjective color of the loin, and degree of marbling. Longissimus muscles were also evaluated for objective color measurements at the 10th and 11th rib interface using a Hunter Miniscan XE Plus  for Hunter ® RT , followed by a second purification using RNAeasy spin columns  according to the manufacturers’ recommendations.Total RNA for both pre- and post-scalding samples was extracted from adipose and muscle tissue using a two-step purification protocol with total RNA first being extracted from whole tissue using RNAzolRNA was quantified and assessed for purity using a BioTek Synergy 4 plate reader utilizing the Take3 system . Spectral scans ranging from 200 to 400 nm further verified the sample purity of all RNA samples as judged by the production of smooth curves exhibiting one peak at 260 nm. Total RNA integrity was accessed both (1) visually by resolving 2 μg of RNA on a denaturing formaldehyde gel stained with GelRed Nucleic Acid stain and (2) by determining an RNA Integrity Number (RIN) using an Agilent 2100 bioanalyzer . All samples demonstrating sharp ribosomal bands with a 28S to 18S ratio estimated to be greater than one and RIN values greater than 7.0 were judged intact and non-degraded.15 primers in a reaction volume of 20 μL also containing 1 μg RNA/reaction, 6 mM MgCl2, 0.5 mM each of dNTP, and 20 units RNasin with the reaction being performed in a single cycle with the following steps: heating for 5 min at 65 °C, annealing for 5 min at 25 °C, elongation for 50 min at 42 °C, and heating for 15 min at 70 °C. The cDNA was subsequently stored at −80 °C until used in gene expression assays.Total RNA was then reverse transcribed using 160 units of Superscript II reverse transcriptase  and 0.5 μg Oligo(dT)® 480 Real-time PCR machine and LightCycler® 480 SYBR Green I Master Mix  according to the manufacturer’s directions in a reaction volume of 20 μL consisting of 10 μL of master mix and 10 μL of H2O containing 50 ng of cDNA and 0.5 μM each of the forward and reverse primers under the following conditions: 1 pre-incubation step of 5 min at 95 °C followed by 45 cycles with each cycle consisting of a melting step of 10 s at 95 °C, and annealing step of 10 s at 54 °C, and an elongation step of 10 s at 72 °C. Each sample was run in three separate PCR runs with the resulting Cp values averaged across values obtained from three separate plates. All PCR reactions were performed using intron-spanning primers under optimized conditions with primer efficiencies ranging between 90 to 100% . Values were also normalized to 18S and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) mRNA expression as these also serve as common alternative control genes in the pig. Using neither 18S nor GAPDH mRNA to normalize target gene expression altered the results compared to using S15 as the control gene. Data are expressed as a fold change relative to baseline and calculated according to REST-MCS v2.0 [Real-time PCR was performed on the resultant cDNA using a Roche Lightcycler to 100% , as veriwas 100%  and S15 MCS v2.0 ,20,21. Phttp://rest.gene-quantification.info/, accessed on 5 March 2022). Carcass traits and RNA quality data were analyzed as a completely randomized block design using a mixed linear model of SAS v9.2  with an individual animal serving as the experimental unit .Changes in gene expression were calculated from the cycle threshold, after correction using S15 expression, and analyzed using the Pair Wise Fixed Reallocation Randomization Test of REST-MCS v2.0 (p > 0.93), hot carcass weight (p > 0.39), LEA (p > 0.33), nor marbling score (p > 0.71) differed between groups. The fresh pork ultimate pH was likewise uniform across groups (p > 0.57). However, both subjective and objective color scores differed with sampling time. Subjective color values were significantly darker in the pre-scald sampling group relative to carcasses that were either not sampled or those that were sampled following scalding (p < 0.0009). Likewise, objective instrumental color scores reflected a similar relationship. Both L* values (p < 0.0001) and b* values (p < 0.0001) were significantly lower in the pre-scald sampling group compared with carcasses within the control and post-scald sampling groups. Nonetheless, the sampling group did not alter the instrumental a* values (p > 0.81) of the collected pork tissue.Effects of timing for tissue sampling on indices of pork quality were measured on chilled carcasses that were either not sampled (no sample control), were sampled prior to scalding , or were sampled immediately following scalding . Pork quality traits were assessed 24 h post-harvest at the 10th rib on all chilled carcasses . Neitherp > 0.54) or longissimus muscle tissue (p > 0.43) based upon the RIN values  and then again above the 10th rib on the right side of the same carcass immediately following scalding  for all eight carcasses sampled. Total RNA was extracted from the tissue samples and analyzed for RNA integrity, both subjectively and objectively, before being used to measure mRNA abundance via real-time PCR. No differences in RNA integrity were detected subjectively when visualizing total RNA preparations via denaturing gel electrophoresis. All extracted total RNA samples were judged to be intact based upon (1) the presence of sharp ribosomal RNA (rRNA) bands with 28S rRNA that was approximately twice as prominent as 18S rRNA and (2) the general absence of smearing. No discernible differences between RNA samples were observed due to the time of sampling. Consistent with the subjective analysis, all electropherograms generated via capillary gel electrophoresis were indicative of fully intact RNA based upon the predominant abundance of large RNA fragments, as represented by the consistent presence of two predominant peaks associated with the two heavy ribosomal bands and the absence of short fragments below the 18S band. The RIN values ranged from 8.8 to 9.6 across all samples. Importantly, the electropherograms indicated that the time of sampling did not influence the integrity of the RNA preparations in any adipose or muscle samples analyzed. Likewise, RNA integrity did not differ by time of sampling in either the subcutaneous adipose , and glucose transporter 4 (GLUT4) mRNA were not different between the pre- or post-scalded subcutaneous adipose samples . Given that subcutaneous adipose tissue is more superficial anatomically than the underlying longissimus muscle tissue, the mRNA for several gene makers expressed by both adipose and muscle tissue were measured. The timing of tissue sampling did not alter the estimate of mRNA abundance of any such gene tested in either adipose tissue (CA3), flavin-containing monooxygenase 1 (FMO1), inter-alpha (globulin) inhibitor H3 (ITIH3), 6-phosphofructo-2-kinase/fructose-2, 6-biphosphatase 1 (PFKFB1), salivary lipocalin (SAL1), diacylglycerol O-acyltransferase 2 (DGAT2), pleiotropic factor beta (PTFβ), and tenascin-X (TN-X) genes.RNA was further assessed using the RNA-based endpoint assay, namely, real-time PCR, to determine whether the timing of tissue sampling impacted estimates of mRNA abundance. The expression of the adipogenic marker genes adiponectin, leptin, peroxisome proliferator-activated receptor gamma  are highly susceptible to hydrolysis enzymatically by cellular and environmental ribonucleases (RNAses) and chemically in response to alkaline pH, rendering RNA very sensitive to degradation by postmortem processes and inadequate sample handling or storage ,11,12,13Automated capillary electrophoresis allows for the quantification of RNA integrity through the calculation of an RNA integrity number (RIN). RIN values approaching 0 represent completely degraded RNA and values approaching 10 represent RNA of the highest integrity ,18,25,26Mammalian genes often display different sensitivities to RNA degradation (12). Furthermore, it is possible that the timing of sampling may impact RNA-based endpoint assays in a tissue-specific manner. Real-time PCR is a widely adopted method for quantifying mRNA levels from mammalian tissues ,11,26,27In the present study, total RNA was purified from sampled tissue using a well-established two-step extraction protocol that has been widely adopted due to the resulting yield of high-quality RNA preparations that can facilitate multiple RNA-based assays ranging from the use of real-time PCR to measure mRNA expression of a single target gene to RNAseq analysis of entire transcriptomes ,28. HoweIn conclusion, the effect of timing for tissue sampling on RNA quality, adipose and muscle tissue marker gene expression, and pork quality indices, such as color and ultimate pH, was investigated by comparing the effects of harvesting tissue at the tenth rib either immediately following exsanguination or immediately following scalding of the carcass. The sampling time did not affect the RNA quality or alter the expression of adipose or muscle genes. However, sampling tissue prior to scalding resulted in the perception of darker color in the muscle near the sampling site. These data indicated that delaying the timing of sampling until after scalding/dehairing posed no threat to optimal RNA integrity and subsequent analysis with RNA-based assays. Specifically, sampling subcutaneous adipose and muscle tissue immediately following scalding/dehairing during carcass fabrication facilitated the purification of high integrity total RNA preparations that were suitable to allow RNA-based assays to be conducted without impacting the meat quality endpoints. Furthermore, these data supported a best practice tissue sampling protocol, which allowed molecular endpoints and pork quality indices to be measured at the same anatomical location of individual carcasses. One limitation of the present study centered upon the use of total RNA and real-time PCR to assess RNA integrity. Recently non-coding RNA, such as microRNA and long non-coding RNA species, were implicated in regulating important developmental events in mammals. Future studies will aim to extend our present findings to characterize the impact of the timing of tissue sampling on non-coding RNA species. Nonetheless, this improved sampling strategy allowed for the use of fewer animals while increasing the fidelity of data in studies aimed at better understanding links between the regulation of adipose and muscle development and carcass merit in pigs.


Meiosis is specialized cell division during gametogenesis that produces genetically unique gametes via homologous recombination. Meiotic homologous recombination entails repairing programmed 200–300 DNA double-strand breaks generated during the early prophase. To avoid interference between meiotic gene transcription and homologous recombination, mammalian meiosis is thought to employ a strategy of exclusively transcribing meiotic or post-meiotic genes before their use. Recent studies have shown that R-loops, three-stranded DNA/RNA hybrid nucleotide structures formed during transcription, play a crucial role in transcription and genome integrity. Although our knowledge about the function of R-loops during meiosis is limited, recent findings in mouse models have suggested that they play crucial roles in meiosis. Given that defective formation of an R-loop can cause abnormal transcription and transcription-coupled DNA damage, the precise regulatory network of R-loops may be essential in vivo for the faithful progression of mammalian meiosis and gametogenesis. Mammalian spermatogenesis consists of distinct stages of differentiation: spermatogonia, spermatocytes, round spermatids, and elongating/elongated spermatids. Germ cells at each stage exhibit characteristic patterns of transcriptional regulation that trigger the expression of cell type-specific genes, which is critical for precise spermatogenic cell differentiation. Specifically, meiotic transcription occurs in complicated circumstances, as it proceeds in parallel with dynamic genomic changes, including meiotic DNA replication, double-strand breaks, and repair. Knockout of genes involved in these processes frequently results in meiotic defects and pachytene arrest due to the accumulation of DNA damage ,2,3,4. CSetx deficiency does cause the accumulation of DNA damage in somatic cell lines [Setx deficiency caused a massive accumulation of DNA damage in spermatocytes [An R-loop is a focal, highly ordered three-stranded structure composed of a stable RNA–DNA hybrid and a displaced DNA strand. While DNA–RNA hybrids are physiologically formed in certain regions with a physiological function, R-loops are generally considered pathological and detrimental products that interfere with the transcription process and subsequently contribute to genome instability because unstructured single-stranded DNA is targeted for damage . Among tll lines . Notablyll lines ,13 and all lines ,15. Howell lines ,17, suggatocytes ,17. ThisIn the past few years, significant progress has been made in the study of R-loops. They have been implicated in numerous cellular events, such transcription, DNA damage, and DNA replication ,24,25,26Rec8, is independent of STRA8/MEIOSIN [Meiosis is specialized cell division that occurs during gametogenesis that is distinct from the somatic cell cycle. During evolution, meiosis has been a critical driver of genetic diversity in healthy gametes . In mamm/MEIOSIN ,33. STRA/MEIOSIN ,34,35. N/MEIOSIN ,37 or im/MEIOSIN . Subsequ/MEIOSIN ,37,39,40Upon meiotic initiation, the meiosis-specific endonuclease SPO11 ,42 and iExclusive transcriptional activity coupled with HR in mammalian meiotic cells  requiresMeiotic DSBs and HR activity are preferentially observed in recombination hotspots, where progenitor cells show a high rate of homologous recombination, activated by the histone methyltransferase, PRDM9 . To avoiTranscription-associated R-loop formation is proposed to be divided into two classes. One is promoter-paused R-loops (Class I), and the other is elongation-associated R-loops in gene bodies (Class II) (Transcription-associated R-loop structures contain ssDNA susceptible to environmental stress and, thus, could be a source of DNA damage. Therefore, an R-loop must be resolved immediately by R-loop-specific ribonucleases RNaseH1/RNaseH2 and/or the DNA/RNA helicase SETX in collaboration with other R-loop-associated factors. Failure of R-loop resolution due to the defects of these molecules can compromise DNA repair in somatic ,62,63,64Structural analyses have attempted to determine the mechanism by which R-loop-binding proteins recognize DNA/RNA hybrids. Unlike mammalian RNASEH1, which recognizes DNA/RNA hybrids as a single molecule ,66, RNASSetx and RnaseH2a, are highly expressed during the late prophase in spermatogenesis (We currently lack studies in mice or other mammalian model that elucidate whether and where DNA/RNA hybrids or R-loops are formed during mammalian meiosis and the possible sex-specificity. However, given that several R-loop formation-associated genes, specifically ogenesis , these gDhx9 and Ddx39b, both of which are implicated in various type of cancers [A study on a homology search in a yeast model sheds light on the function of DNA/RNA hybrids during meiosis. In meiosis, single-end invasion by ssDNA, which occurs during strand exchange between a resected DSB end and its homolog, plays a crucial role in homology searches during meiosis . DNA/RNA cancers ,84, exhi cancers , DNA/RNA cancers ,58. FurtRNASEH2 [SETX genes [Setx is required for successful meiosis in male mice [Setx-deficient mice exhibited unrepaired DSBs in the autosomes of meiotic spermatocytes at the pachytene stage, at a time when autosomal DSBs are repaired in wild-type pachytene spermatocytes. Because Setx-deficient spermatocytes exhibit unresolved R-loops, the aberrant DSBs found in Setx-deficient spermatocytes are probably derived from unresolved R-loops or aberrant DNA damage repair [Setx-deficient mice exhibit defective formation of the sex body, a chromatin domain in which the entire X and Y chromosomes are silenced [As R-loops play a crucial role in vivo ,20,51, eRNASEH2 ,91 and STX genes ,92 in huale mice ,17 and pale mice ,94. Setxe repair ,17. Furtsilenced ,96,97,98silenced .Setx-deficient mice have also suggested a direct association between SETX and HR. Setx-deficient spermatocytes showed an aberrant increase in the number of DNA damage repair-related markers, including RAD51, DMC1, and SPATA22, and the loss of MLH1, a marker for crossover [Setx-deficient pachytene spermatocytes are a consequence of inefficient homology searches via DNA/RNA hybrids at the DSB sites. In these ways, the Setx-mutant mice may provide unexpected insights into the formation and function of R-loops and any possible sexual dimorphism.Analyses of rossover ,17. In hrossover . Althougrossover . In somarossover , indicatrossover  that actrossover . Taken tR-loops are formed primarily on the GC-rich sequences ,104, altIn the testis, approximately 90% of protein-coding genes are transcribed , althougSpo11 and Rnf212, function in a dose-dependent manner [Some meiotic genes, including t manner ,112,113.t manner ,31 and St manner . Transcrt manner ,115,116.In conclusion, mammalian meiotic germ cells, at least in the male, appear to deploy a more complex R-loop regulatory network than somatic cells. This requires precise regulation to secure both the robust gene expression that supports gamete differentiation and the genome integrity that ensures continuity of germline cells. Recent studies reviewed here ,117,118


RNA motif classification is important for understanding structure/function connections and building phylogenetic relationships. Using our coarse-grained RNA-As-Graphs (RAG) representations, we identify recurrent dual graph motifs in experimentally solved RNA structures based on an improved search algorithm that finds and ranks independent RNA substructures. Our expanded list of 183 existing dual graph motifs reveals five common motifs found in transfer RNA, riboswitch, and ribosomal 5S RNA components. Moreover, we identify three motifs for available viral frameshifting RNA elements, suggesting a correlation between viral structural complexity and frameshifting efficiency. We further partition the RNA substructures into 1844 distinct submotifs, with pseudoknots and junctions retained intact. Common modules are internal loops and three-way junctions, and three submotifs are associated with riboswitches that bind nucleotides, ions, and signaling molecules. Together, our library of existing RNA motifs and submotifs adds to the growing universe of RNA modules, and provides a resource of structures and substructures for novel RNA design. For example, the discovery of the RNA interference (RNAi) pathway in the 1990s led to post-transcriptional gene expression regulation using microRNA or small interfering RNA , and cliloidosis ). Similaloidosis ,5,6. Witloidosis . In addiloidosis . Undoubtstems, while residues without A-U, G-C, or G-U pairing form different types of loops, including bulges, internal loops, hairpins, and junction loops.To accomplish these scientific achievements, knowing the target RNA structure is essential. Unlike DNA, which forms stable double helices, RNA is a flexible single strand that folds upon itself using Watson–Crick base pairs (A-U and G-C) and wobble base pair (G-U), and can thus form many complex structures in three dimensions (3D). Consecutive base pairs define Coarse-grained models, especially graphs, have long been used to represent these RNA structures, since the pioneering works of Waterman , ShapiroIn 2003, our group launched the “RNA-As-Graphs” (RAG) framework with both tree and dual graph representations . Our simThroughout these developments, our RAG toolkit has expanded to help define a motif atlas and design RNA motifs see . ImportaIn this work, we present an updated RNA motif atlas for “existing” dual graphs (last reported in 2019 ), with cTo identify existing dual graphs, we use the representative set defined by Bowling Green State University (BGSU) , which cWe develop a new search algorithm to identify all independently folded nucleic acid substructures within these 2775 PDB molecules. Previously, coupled RNA chains were extracted after optimizing factors such as resolution and steric clashes ,29. HoweTo solve these problems, we now consider all nucleic acid chains and work on the level of subchains. Indeed, we group subchains that interact with each other to define independent substructures and assign corresponding dual graphs . We also record whether a substructure is made of a single continuous subchain, or multiple subchains, and whether DNA is involved.For illustration, we show the analysis of a yeast spliceosome , we find five that correspond to certain RNA classes: tRNAs, riboswitches, and ribosomal 5S RNAs . A four-able arm , and it Comparing to the previous existing dual graphs, we now have 182 existing graphs versus 122 before 2019 , for duaIt is also interesting to examine in this light the 96 newly found existing dual graphs . There aWith slight 2D structure adjustments for 4 RNAs using additional screening , we now Importantly, in this new set of existing dual graphs, all 10 initial RNA-like dual graph candidates we proposed and designed in 2004 are now “existing” . Of thesBesides our 2004 graph classification , we propOur partitioning algorithm divides a dual graph into subgraphs while keeping pseudoknots and junctions intact  . Using tNevertheless, the subgraph compositions remain similar for all vertex numbers, with the majority (65–72%) coming from substructures of single RNA chains, some (20–26%) from those of multiple RNA chains, and few (7–9%) from those containing DNA chains. Considering that only 42.9% of the substructures are of single RNA chains, we see that these substructures contribute more subgraphs, mainly because there are many large ribosomal RNA chains. For example, a ribosomal 16S RNA (PDB ID: 4GKK) consisting of a single 1513-nt chain can be partitioned into 159 subgraphs of 2–9 vertices.n. By plotting the subgraph number in log scale, we see a linear relation with least squares regression The number of distinct existing subgraphs increases exponentially with the vertex number 79·2.24n B. SimilaE coli. (PDB ID: 7B5K).The most popular subgraphs are of two types C. One tyAll popular subgraphs mentioned above are also frequent in the existing dual graph list (weights ≥ 19), but there are also modules that only appear as subgraphs. These special modules mainly come from long rRNA chains. For example, the three large subgraphs 7_52 (weight 254), 7_814 (weight 168), and 8_19 (weight 309) are unique to the 16S and 18S rRNAs . Except Thermus thermophilus 16S rRNA (PDB ID: 4GKK). The two occurrences have different orientations, in the ordering of helices from the 5Both motifs 7_52 and 8_19 are unknotted composites of junctions . Motif 7Motif 7_814 contains two intertwined three-way junctions and a flanking stem . In it, Our updated library of existing dual graphs and their subgraphs allows us to easily identify representative motifs for functional RNA groups. Because these RNAs perform regulatory roles by binding to proteins, nucleic acids, or ions, their structures are often conserved, and cataloging their motifs helps understand associated mechanisms, trace evolutionary relationships, and discover new members. Here, we illustrate these ideas for viral frameshifting elements (FSE) and riboswitches.Viral frameshifting elements (FSEs) are small mRNA regions (<100-nt) that stall the ribosome and shift the reading frame to ensure correct translation of overlapped open reading frames. This strategy is commonly used by viruses like coronaviruses, and it is believed that the FSE RNA structure is essential for triggering frameshifting ,35,36. HThese FSEs either form long stems like the 2_2 motif, or intertwined pseudoknots like the 2_3 and 3_6 motifs (the latter is the SARS-CoV-2 FSE). These structures are difficult to unwind, and hence could provide mechanical barrier to stall the ribosome and facilitate frameshifting ,38. MoreLentivirus genus, and they are closely related in evolution [Solemoviridae family) have this motif. Thus, using our dual graph motif classification, we can identify and group similar RNAs to suggest phylogenetic connections among organisms.We also identify a phylogenetic relation between the motifs and the viruses. The 2_2 motif corresponds to HIV and SIV FSEs. Both viruses belong to the volution . The 2_3Similarly, for riboswitches, which are RNAs that bind ligands and alter their structures to regulate gene expression, we classify the 35 riboswitch types available in PDB into six groups based on their ligands , following . CorrespMotif 4_27 is only seen in nucleotide riboswitches. Indeed, of all PDB structures, this motif is specific to these riboswitches. This specificity could then be used to find novel nucleotide riboswitches. An illustrative nucleotide riboswitch that binds to adenine (PDB ID: 1Y26) is shown in Two other interesting motifs are 5_21 and 6_263, both unknotted. Motif 5_21 is found in ion riboswitches, and it contains a four-way junction (subgraph 4_19). Among all PDB structures, this 4_19 junction is also seen in tRNAs. A comparison between NiCo riboswitch (PDB ID: 4RUM) and bacterial tRNA (PDB ID: 3A2K) is shown in Using dual graph representations that can represent RNA pseudoknots, we have annotated the dual graph motif atlas up to 9 vertices to identify all existing RNA motifs and described their subgraphs. We improved our search algorithm to identify independently folded RNA substructures in the PDB by including interacting DNA chains and separating broken chains. The result is a list of 183 existing dual graphs of 1–9 vertices, containing all 10 RNA-like candidates we predicted in 2004 . The popAs an application of this RNA motif catalog, we have classified all available viral frameshifting elements in the PDB into three groups: unknotted 2_2, and pseudoknotted 2_3 and 3_6, and noted higher frameshifting efficiencies for the pseudoknots. For riboswitches, motifs specific to certain types of riboswitches were identified, such as 4_27 for nucleotide riboswitches and 5_21 for ion riboswitches. From both applications, we see how dual graph classification and partitioning can help catalog and analyze common motifs for functional RNAs. These common motifs not only suggest phylogenetic relations among different organisms, but also help in structure/function connections. Relating the motifs to important biological features such as the frameshifting efficiency can lead to enhanced understanding of the associated mechanisms. The application of relating frameshifting to energy landscape of coronaviruses is underway [Rfam for non-coding RNAs and cis-regulatory elements [UTRdb for untranslated eukaryotic mRNA regions [ASD for alternative splicing sites [TRANSFAC for transcription factors [Our dual graph atlas is complementary to other RNA databases. Besides the PDB, there are databases that collect certain types of RNAs, such as elements , UTRdb f regions , ASD forng sites , and TRA factors . SimilarLike other databases, our dual graph atlas helps future motif search. Functional RNAs often rely on their structures to accomplish biological roles, such as binding proteins. For a novel RNA molecule, finding known RNAs that have similar structures can help decipher its function. Hence, using our dual atlas as an annotation and query tool, we can investigate other RNAs that have the same dual graph representation. Our RAG-3Dual database, which records available RNA fragments, can be further used to find 3D RNA structures and substructures that have these dual graph and subgraph representations .Another advantage of our dual graph representation is that we can partition the RNAs into biologically meaningful blocks. Specifically, we maintain junctions and pseudoknots intact. The freedom of combining adjacent blocks at different articulation points allows different levels of division. Since RNAs are modular, finding popular building blocks is important for RNA structural biology , especiaIn summary, our dual graph representation provides a quick and alternative way to collect and classify RNA motifs. Applications to functional RNAs can help trace family evolutions and interpret biological mechanisms. Future development of 3D dual graphs to compare and search similar RNA substructures containing pseudoknots can be fruitful, following similar protocols of 3D tree graphs . BuildinEach junction loop is denoted as an edge .Hairpin loops are denoted as self-edges .A single-stranded internal loop/bulge is denoted as two edges . A bulge of 1-nt or an internal loop of 1-nt on both sides is ignored.A stem of ≥2 consecutive base pairs  is denoted as a vertex. An isolated single base pair is ignored.The dangling 5Our dual graphs are defined by denoting RNA stems as vertices, and loops as edges. The exact representation rules are as follows (two examples shown in http://www.biomath.nyu.edu/?q=rag/home (accessed on 1 August 2022). In our prior study, we have enumerated by a heuristic method 110,668 dual graphs of 1–9 vertices by iteratively connecting small graphs [V are sorted in ascending order of their Fiedler values and assigned with IDs n are more connected/compact. Among all graphs enumerated, those corresponding to RNAs found in Nature are termed “existing”, and the number of corresponding structures are assigned as “weights”.Our RAG libraries are available on l graphs . Dual gre graphs , graphs In our new search algorithm, we identify independently folded nucleic acid substructures with two improvements: (1) include DNA chains that have strong interactions with RNA chains; and (2) separate broken subchains. For example, in a CRISPR system  to obtain more subgraphs. For example, dual graph 5_79 contains two articulation points S3 and S4, which separate the graph into three blocks (subgraphs) 2_3, 2_1, and 3_8 B. A comb


Lipid nanoparticles (LNPs) are an emerging vehicle for gene delivery that accommodate both nucleic acid and protein. Based on the experience of therapeutic liposomes, current LNPs have been developed based on the chemistry of lipids and RNA and on the biology of human disease. LNPs have been used for the development of Onpattro, an siRNA drug for transthyretin-mediated amyloidosis, in 2018. The subsequent outbreak of COVID-19 required a vaccine for its suppression. LNP-based vaccine production received much attention for this and resulted in great success. In this review, the essential technology of LNP gene delivery has been described according to the chemistry for LNP production and biology for its clinical application. Lipid nanoparticles (LNPs) represent a newly emerging type of drug formulation that encapsulates biological molecules such as nucleic acids and proteins, as well as a complex made with both ,2,3. LNPModern LNPs are more sophisticated and are essentially made with four different species of lipids . The preLNPs in an FDA-approved formulation target the liver ,8,9. UpoLastly, some previously used liposomal components are derived from naturally occurring lipids such as those originating in soy and eggs. These may contain a variety of analogs with different chain lengths and numbers of double bonds as well as isomers with different stereo- and regio-configurations. This composition may vary depending on the source of origin, diet, and even the season of harvest. To eliminate these factors, currently used lipids for LNPs are highly pure.The lipid is an essential component in LNPs, encapsulating nucleic acids and other components  Figure . For claAn ionizable cationic lipid, such as DLin-MC3-DMA, is a tertiary amine with hydrophobic tails . In FDA-DOPE and DSPC are two major phospholipids used as helper lipids in LNPs. These are used at a 10% of total lipids in mol basis. For in vivo use, DOPE seems to be preferentially used, whereas DSPC is used for in vitro use with an enhanced transfection efficiency ,13.Cholesterol is an essential component of LNP. It is used at a concentration of 30–40% of total lipids depending on the molar ratio of other lipid types. Cholesterol is known to maintain LNP in a rigid form.Added PEG-lipids make up 1–5% of total lipids. At these concentrations, PEG lipids make the LNP particle much smaller. PEG lipids localize at the surface of the LNP.RNA is an essential payload for LNP. Its efficacy is proven by the several vaccine products for COVID-19 with tremendous benefits for humans. RNA has long been thought to be an unstable biomolecule. However, an accumulating knowledge of ribonucleotides, nucleases, and the molecular mechanism of inflammation collectively is establishing an improved understanding on the stability of RNA . UridineThe 5′-end of mRNA is enzymatically modified and known as a 5′-capping structure A 14,15],1514,15]In mRNA, native bases of RNA strongly activate innate immunity ,17. ThusThe CRISPR/Cas9 system requires a guide RNA for the genome editing reaction. An sgRNA for CRISPR/Cas9 has a composed nucleotide sequence of a guide RNA and a trans-acting RNA. Usually these are used as a single strand RNA of approximately 100 nt. When extended half-life is desired, 2′-O-methylation and 5′/3′-phosphorothioation are performed ,21,22 FC. These As described earlier, conventional formulation of LNPs has been demonstrated to deliver genetic material to the liver . Such a Transthyretin-mediated amyloidosis is a major disease subtype of amyloidosis, and more than 30 genes have been identified as its cause . While tAnemia is caused by an improper production of red blood cells. To remedy this, the delivery of erythropoietin mRNA to the liver has been explored ,27,28. TCRISPR/Cas9 is a leading tool for genome editing in vitro and in vivo ,30. GeneAdenine base editor and prime editor is an attractive research toolkit in genome editing . EssentiThe original formulation of LNPs preferentially target the liver. Based on this fact, liver disorders have been considered as good targets for LNP-mediated therapeutics . Among vAn anti-cancer strategy based on the presentation of tumor peptides on the MHC class II by dendritic cells has been studied for more than a decade . Based oNear infrared (NIR) radiation-activatable LNP with a pH-sensitive dye is an emerging technique ,54. A reLysosomal storage disorders (LSDs) are characterized by an accumulation of unprocessed biochemicals in the lysosome involving 50–60 enzymes ,58,59. TFactor VII is involved in the clotting process of the blood. Thus, a failure of this leads to bleeding manifestations. In the murine model, an ED50 of 0.005 mg/kg siRNA was achieved in optimized LNP composition.SERPINC1 gene. Thus, the degradation of this gene is expected to treat both hemophilia A and B. In a murine model, the inactivation of Serpinc1 gene by LNP-encapsulated siRNA has been examined with a therapeutic outcome.Hemophilia A and B are caused by a defective activation of Factor VIII and IV, respectively, leading to improper activation of thrombin by antithrombin encoded by the DMD is a muscular disorder. DMD in approximately 10% of affected individuals is caused by pathogenic exon skipping. In these cases, an alteration of this followed by restoration of wild-type reading frame is known to be therapeutic in DMD even if some amino acids are still missing. Based on this fact, an originally established murine DMD model harboring human DMD exon 45 by a knock-in strategy was corrected by LNP-encapsulated Cas9 mRNA.HIV is a member of the Retroviridae family, which causes human immunodeficiency. Antibody-mediated neutralization of HIV is one effective therapeutic strategy. N. Pardi et al. administered LNP-encapsulated mRNA for both light and heavy chains of monoclonal antibody against HIV. An administration of 1.4 mg/kg of mRNA into mice resulted in an approximately 170 mg/mL monoclonal antibody. The efficacy of this treatment was further demonstrated with the intravenous HIV-1-challenge in a humanized HIV murine model.According to the results of preclinical studies, more than 10 clinical studies are now ongoing . Most noPatisiran is an approved RNA-interference therapeutic for hereditary transthyretin amyloidosis, a type of amyloidosis with a high prevalence of known etiology among more than 30 genes. The study was performed with patients with hereditary transthyretin amyloidosis at 0.3 mg/kg once every 3 weeks; ,62. Patin = 3) and 87% at 0.3 mg/kg (n = 3) in humans (NCT04601051). This clinical study was designed based on the preclinical study in the non-human primates at 1.5–6.0 mg/kg with no adverse events up to 12 months. There were seven putative targeting sites for this therapeutic CRISPR-Cas9 system. The authors reported that all these loci were located in non-coding regions as determined using established software such as Cas-OFFinder, GUIDE-seq, and SITE-seq, and there was no evidence of off-targeting when examined using primary human hepatocytes with a three-fold higher concentration of NTLA-2001.The results of Phase I of the clinical trial of CRISPR-Cas9-mediated in vivo gene editing for transthyretin amyloidosis (NTLA-2001) was recently reported . In thisCheckpoint inhibition through an interaction between PD-1/PD-L1 and CTLA-4 plays a key role in activating the tumor-killing activity of T cells . TherefoHepatic fibrosis is caused by a failure to maintain the balance between a wound process caused by inflammation and the subsequent healing process in the liver. A Phase 1b/2 clinical trial has been performed. In this study, 25 participants with moderate to extensive hepatic fibrosis were enrolled, and the safety and tolerability of LNP-encapsulated siRNA for HSP47 was examined (NCT02227459). The siRNA agent was administered to the subjects aged between 18 to 75 years old once or twice a week for 5 weeks.OTCD is an inherited metabolic disorder in the liver. The deficiency of ornithine transcarbamylase fails to synthesize citrulline at the second step of urea cycle, leading to hyperammonemia. Administration of therapeutic mRNA for ornithine transcarbamylase has been examined (NCT04416126/NCT04442347/NCT05526066). In a Phase 1 trial, 30 subjects aged between 18 to 65 years old were enrolled for a single ascending dose study with no reported adverse events.Tissue targeting is another issue for LNPs. It is well known that the initial formulation of LNP effectively delivers the payload to the liver . ConsistA dendrimer is a globular synthetic chemical with branched hydrophobic moiety. According to the SORT hypothesis, a series of novel ester-based dendrimers, such as 5A2-SC8, have been synthesized ,68 Tabl. During In a separate formulation of LNPs by Dahlman and colleagues, more than 50% of splenic endothelial cells were able to express exogenous genes . In thisSeveral studies have tested the possibility of polyesters for extrahepatic targeting of LNPs . Based oA study has examined the treatment of cardiac fibrosis by targeting LNPs to T cells . In thisCurrent LNP technology has an advantage in the encapsulation of larger mRNA for therapeutic use compared to AAV. Furthermore, LNPs are capable of delivering a gene into non-dividing cells. Specifically, for liver disease, there are multiple examples where LNP-based therapy has proven effective in preclinical and clinical studies . However


Despite recent advances made in the functional and mechanistic understanding of RNA m5C modifications, the detection and quantification of methylated RNA remains a challenge. In this study, we compared four library construction procedures for RNA bisulfite sequencing and implemented an analytical pipeline to assess the key parameters in the process of m5C calling. We found that RNA fragmentation after bisulfite conversion increased the yield significantly, and an additional high temperature treatment improved bisulfite conversion efficiency especially for sequence reads mapped to the mitochondrial transcriptome. Using Unique Molecular Identifiers (UMIs), we observed that PCR favors the amplification of unmethylated templates. The low sequencing quality of bisulfite-converted bases is a major contributor to the methylation artifacts. In addition, we found that mitochondrial transcripts are frequently resistant to bisulfite conversion and no p-m5C sites with high confidence could be identified on mitochondrial mRNAs. Taken together, this study reveals the various sources of artifacts in RNA bisulfite sequencing data and provides an improved experimental procedure together with analytical methodology.The presence of 5-methylcytosine (m RNA m5Cy (NSUN) ,9–11, prgulation . Comparent years ,13–16. Sein YBX1 , and modein YBX1 . Moreoveebrafish , promotiebrafish , and driebrafish .5C modification at single nucleotide resolution  was developed and widely used for the identification of RNA msolution ,16,21,22in tRNAs ,23,24 anin tRNAs ,12 usingcriptome ,14–16,22rategies   was used as starting materials. The small size of mitochondrial transcriptome helps in producing sequences with sufficient read depth and minimizing artifacts resulted from multi-mapping, in addition to the cross-validation of methylation sites identified in previous studies , 20 ng/ml basic fibroblast growth factor .Adult mouse neural stem cells (NSCs) were isolated from the subventricular zone (SVZ) of the lateral ventricles as described previously . NSCs weMitochondria were isolated from NSCs using a mitochondrial isolation kit  following the manufacturer's instructions. RNA was extracted from the isolated mitochondria and subjected to DNase digestion. One round of poly(A) selection was performed to enrich mitochondrial molecules. ERCC RNA mixes (Thermo) and unmethylated Xef mRNA were spiked into the samples as external RNA controls. The mitochondrial BS-seq libraries were constructed using the NEBNext® Ultra™ II Directional RNA Library Prep Kit for Illumina  and bisulfite treatment was performed using the EZ RNA methylation kit (Zymo Research) under four different conditions: (A) bisulfite conversion using three cycles of 70°C for 10 min and 64°C for 45 min. After bisulfite conversion, RNA fragmentation and priming was performed by incubation at 94°C for 8 min in first strand reaction buffer and 6 bp random primers for first strand cDNA synthesis; (B) RNA fragmentation was performed before bisulfite conversion by incubation at 90°C for 50 s in 1× RNA fragmentation buffer and quenched by adding 1× stop buffer, then purified by Zymo Research RNA clean and concentrator-5 kit. Then, bisulfite conversion was performed using three cycles of 70°C for 10 min and 64°C for 45 min. After bisulfite conversion, RNA fragmentation was omitted and priming was performed by incubation at 65°C for 5 min in first strand reaction buffer and random primers for first strand cDNA synthesis; (C) RNA fragmentation was performed first, then bisulfite conversion was performed using three cycles of 95°C for 1 min, 70°C for 10 min and 64°C for 45 min. After bisulfite conversion, RNA fragmentation was omitted and priming was performed by incubation at 65°C for 5 min in first strand reaction buffer and random primers for first strand cDNA synthesis; (D) RNA fragmentation was performed first, then bisulfite conversion was performed using three cycles of 95°C for 1 min, 70°C for 10 min, and 64°C for 45 min. After bisulfite conversion, RNA fragmentation was omitted, and priming was performed by incubation at 65°C for 5 min in first strand reaction buffer and 6 bp ACT random hexamer primers for first strand cDNA synthesis.5C site was defined as any C→T variants (or G→A variants in the complementary strand) compared to the converted reference genome. All p-m5C sites with quality above Q30 and at least 10x (C + T) coverage were called using the parameters (-mBQ 30 -sc 10 -cr 1 -mr 0.00001 -mcov 10). To achieve high-confidence in methylation calling, a ‘standard filter’ was applied to each site: (i) at least three variants (C-cutoff) identified in a read, we calculated the Gini coefficient following the previously described procedure . ConcorRNA-seq libraries were filtered using the same parameters applied to BS-seq libraries and mapped to the reference genome using meRanGh. The expression values for each gene were calculated using featureCounts of the Subread package suite v2.0.0 using default parameters.5C sites among RNA BS-seq libraries.Statistical analyses were performed using SciPy v1.7 and R v4.1.1. Fisher Exact test was used to determine differentially methylated sites among mitochondrial replicates. Wilcoxon rank-sum was used to compare methylation levels of shared mvs ACT-only primers for first strand cDNA synthesis. NSCs were chosen in this study since previous reports identified RNA m5C methylation plays a critical role in stem cell differentiation  at each step of read pre-processing. For libraries generated in this study, the average Phred score of cytosine in unprocessed reads was 3 points lower than those of the other three kinds of nucleotides, and 6 points lower in the RNA BS-seq dataset generated with Huang libraries Figure . The ove. Figure . In HuanUsing the built-in mapper functions of the meRanTk toolkit , all cleUsing UMI adaptors and the mapping coordinates, uniquely mapped reads in this study's libraries were grouped using the ‘group’ command of the umi-tools package . Reads t5C sites ranged from 0.1% for MT-A libraries to 0.7% for MT-D libraries. This indicates that PCR and sequencing errors at p-m5C sites are very low, even with 20 cycles of PCR amplification in the RNA BS-seq procedure. We further examined the nucleotide ratios at each discordant p-m5C site and found that C/T was the discordance type most frequently observed  and ERCC-00096 (15 000 attomoles/ul). The read coverages of these two ERCCs were significantly below the expected concentrations in all mitochondrial BS-seq libraries .To determine the transcriptome-wide effect of the bisulfite sequencing procedure, the expression levels of all mapped transcripts were determined using featureCounts . For RNA5C sites in uniquely mapped reads, multi-level filters with various strategies were widely used to achieve highly confident methylation callings  correction removed 43–95% of the remaining p-m5C sites in the MT-B/C/D libraries but did not remove any in libraries with bisulfite conversion rates higher than 99.9%. For datasets generated in this study, the p-m5C sites were retained for downstream analysis if they passed all filters in another technical replicate.To delineate the filter effect on methylation calling, 100% was used as the initial number of p-ms Figure . All p-m filters . Therefo filters  with hunA previous study reported high methylation levels of mitochondria-related genes in heart and muscle tissues . The met5C sites, while the proportion of mitochondrial mapped reads without any p-m5C varied from 28% (MT-A) to 79% (MT-C)  Figure . While t regions . This su regions . This su5C sites shared in libraries generated with two different conditions   Figure  and B. R) Figure . Of highs Figure .5C sites of high confidence   Figure . Analysireported ,20,22. Areported . Our chaal mRNAs .Substantial differences in the prevalence and magnitude of mRNA methylation reported call into question whether the best practice of RNA BS-seq data generation and analysis has been achieved ,47. In t5C sites on mitochondrial mRNAs could be determined with high confidence for mouse neural stem cells, we confirmed a highly methylated cytosine on mitochondrial rRNA as previously reported  perform RNA fragmentation after bisulfite conversion; (ii) include a high-temperature denaturation step in bisulfite treatment cycling and (iii) include a UMI-deduplication strategy for low-input RNA samples or amplify the library with a low number (<16) of PCR cycling.Previous studies have conflicting viewpoints regarding performing RNA fragmentation before or after bisulfite conversion ,22. We f5C sites. The stringent filters employed to remove low quality reads and/or bases in the pre-processing steps help but cannot fully compensate the difference in sequencing quality between the p-m5C sites and the other three kinds of nucleotides. A previous study indicated that an upstream ‘GGG’ motif was frequently associated with false positive sites  an additional quality filter with Q30 as a cutoff for all p-m5C sites; (ii) a stringent m-bias correction and (iii) a combination of a ‘Standard filter’ with the C-cutoff filter. In summary, our study conducted a systematic evaluation of parameters used in RNA bisulfite sequencing and may shed new light on RNA methylation data generation and analysis. Further improvement may be achieved with improved characterization of false-positive sites .Data generated in this study have been submitted to the NCBI Gene Expression Omnibus under accession number GSE190614. Analyses in this study was performed using the R v4.1.1, and Python 3.9.4 packages Biopython v1.78, matplotlib v3.3.4, Seaborn v0.11, and Pysam v0.16. The software package developed in this study is available in GitHub repository (lqac045_Supplemental_FilesClick here for additional data file.


Circular RNAs (circRNAs) are involved in various biological processes and disease pathogenesis. However, only a small number of functional circRNAs have been identified among hundreds of thousands of circRNA species, partly because most current methods are based on circular junction counts and overlook the fact that a circRNA is formed from the host gene by back-splicing (BS). To distinguish the expression difference originating from BS or the host gene, we present differentially expressed back-splicing (DEBKS), a software program to streamline the discovery of differential BS events between two rRNA-depleted RNA sequencing (RNA-seq) sample groups. By applying to real and simulated data and employing RT-qPCR for validation, we demonstrate that DEBKS is efficient and accurate in detecting circRNAs with differential BS events between paired and unpaired sample groups. DEBKS is available at https://github.com/yangence/DEBKS as open-source software. Circular RNAs (circRNAs) are a class of long non-coding RNAs with a covalently closed continuous loop structure that is formed via back-splicing (BS). Although circRNAs are believed to play important regulatory roles in a number of biological processes Previously developed software, such as find_circ merge for reformatting junction counts from circRNA detection software, count for quantifying expression level of circRNA linear counterpart, anno mainly for estimating circRNA length, and dec for detecting DECs. Using public, in-house, and simulated RNA-seq datasets, we demonstrate that DEBKS effectively improves the BS ratio calculation and has a better performance in DEC detection than current methods.Some programs, such as DCC merge, count, anno, and dec , if available, which is defined as junction counts across flanking introns of candidate back-spliced sites. Alternatively, count is employed for calculating LJCs from BAM files produced by RNA-seq aligners, such as HISAT2 ψ), which is estimated by:lI represents the effective linear length and cI represents the effective back-spliced length  with a user-defined threshold between the paired or unpaired sample groups.DEBKS is designed to analyze DECs from rRNA-depleted RNA-seq data without erasing linear RNA. DEBKS includes four modules:  and dec A. After d length B. The vaADAR1 and ADAR2 by RNAi (ADAR1/2 knockdown) and four untreated samples. SRP156355 includes five invasive ductal carcinoma (IDC) samples and five paired normal samples.Two public rRNA-depleted RNA-seq datasets from the NCBI Sequence Read Archive database (SRA: SRP050149 and SRP156355) were employed to verify the performance of DEBKS. SRP050149 includes four samples of HEK293 cells with the co-depletion of Transient focal ischemia of three male mice  was induced by middle cerebral artery occlusion (MCAO) using the endovascular suture method Total RNA of the ischemic core and normal areas was extracted by the FastPure Cell/Tissue Total RNA Isolation Kit  with 10–20 mg of brain tissue according to the manufacturer’s instructions.The library construction and sequencing of rRNA-depleted RNA were performed by Annoroad Gene Technology . A total of 3 μg RNA per sample was used as the input material for rRNA removal with the Ribo-Zero rRNA Removal Kit . Libraries were generated using the NEBNext Ultra Directional RNA Library Prep Kit for Illumina , followed by sequencing on an Illumina HiSeq X platform with 150-bp paired-end reads.Actb was used as an internal reference gene. Then, ψ was calculated by determining the ratio of the relative expression level of the circular junctions to the sum of the circular junctions and the average of the upstream and downstream linear junctions.Total RNA (500 ng) was reverse-transcribed into complementary DNA (cDNA) by using HiScript III RT Strand SuperMix for qPCR (+gDNA wiper) . For each circRNA, two primers inside the back-spliced site and two primers outside the back-spliced site were designed to detect circular junctions and upstream and downstream linear junctions . RT-qPCR≥ 2 were kept in the following differential expression analysis. DECs and DEGs between the two groups were analyzed using DEBKS and DESeq2, respectively.For each RNA-seq dataset, raw reads were mapped to the reference genome  by STAR (v2.5.3a). Next, the LJCs of circRNAs were calculated by DEBKS, while CJCs of circRNAs and counts of host genes were calculated by CIRCexplorer2 vs. 3 sample groups. We assumed that each host gene contained only one linear product but that half genes contained one circular product, while the other half contained two circular isoforms (same back-spliced site with exon skipping in one isoform). For each gene, the total number of linear and circular RNA molecules was sampled from a normal distribution, with the mean and the standard deviation (SD) being derived from the sum of CJCs and LJCs of the in-house MCAO mouse RNA-seq data. For the two sample groups, the ratios of BS events were simulated with 9500 pairs from a beta distribution  and 500 pairs from a beta distribution . Half of the ratio pairs had differences greater than 5% as DECs, and the ratio of BS events for each sample was simulated with the mean equal to the group ratio and the SD at five different levels, that is, 0.01, 0.02, 0.05, 0.10, and 0.20. Next, the number of circular and linear molecules was calculated with the total number of molecules and the ratio of BS events. For circRNAs with AS, the percentage of one circRNA isoform against total circular molecules was simulated with uniform distribution. Next, the number of each circular isoform molecule was calculated with the percentage and the total number of circular molecules. Finally, simulated rRNA-depleted RNA-seq dataset1 was generated with simulated numbers of circular and linear molecules.For the simulated RNA-seq dataset1, we randomly selected 10,000 circRNA host genes based on human gene annotation (GENCODE v19) for 3 vs. 3 sample groups. Each gene contained one linear product and two circular isoforms from the same back-spliced site. The total number of linear and circular RNA molecules was sampled as described in dataset1. The ratio pairs between groups of each circular isoform against the circular and the linear isoforms were simulated with beta distribution . For the two circular isoforms from the same gene, there was one and only one isoform that had a difference of more than 5% from a DEC at the isoform level. Next, the number of circular and linear molecules was calculated with the total number of molecules and the ratio of BS events. Finally, simulated rRNA-depleted RNA-seq dataset2 was generated with a number of circular and linear molecules.For the simulated RNA-seq dataset2, again, 10,000 circRNA host genes based on human gene annotation (GENCODE v19) were randomly selected for 3 For each RNA-seq dataset, raw reads were mapped to the reference genome (hg19) by BWA mem ADAR1 and ADAR2. Given that RNA editing is exclusive to circRNA formation ADAR1/2 knockdown treatment. With |Δψ| > 0.01 at false discovery rate (FDR) < 0.05, DEBKS detected 14 DECs, all of which were up-regulated in ADAR1/2 knockdown cells as expected  were identified using rRNA-depleted RNA-seq data by DEBKS with a paired statistical model. Among highly expressed DECs (average CJC ≥ 10), five were randomly selected for validation by RT-qPCR, and they were all consistent with the RNA-seq data  were also detected by DEBKS. In addition, the host genes of DECs detected by DESeq2 were considerably more likely to be DEGs  compared to those detected by DEBKS with the paired model  and the unpaired model , suggesting that DEBKS identifies DECs with less influence from host gene expression.Given the low abundance of circRNAs in rRNA-depleted RNA-seq data, ratio-based methods were considered to be more likely to detect DECs than CJC-based methods, such as DESeq2. By using DESeq2 at FDR < 0.05, we failed to detect any DECs in the , which normalizes CJCs with local LJCs. In addition to CJC-based methods, ratio-based methods may help to identify potential functional circRNAs based on the biogenesis mechanism of circRNAs 2 fold change of expression level (log2 FC) was observed between circRNA and the host gene  , suggesting that BS events measured by |Δψ| were less strongly influenced by the expression level of the host gene.Given that circRNAs are BS isoforms of host genes, we developed DEBKS to identify DECs at the splicing level by BS ratio× 10−16) , indicatAt present, several software, including CircTest and CIRIquant, can detect DECs with ratio-based methods. Compared with simulated data, DEBKS shows better performance for length adjustment of smaller circRNAs and employment of the statistical framework of rMATS. In addition, DEBKS could be applied in paired or unpaired groups with replicates, which is distinct from CIRIquant, which utilizes a ratio-based test to detect DECs between groups without replicates.Because DEBKS is based on the ratio of CJCs and LJCs, it is only applicable in RNA-seq analyses of both circRNAs and linear RNAs, such as rRNA-depleted or exome-capture RNA-seq All experimental animals were purchased from the Experimental Animal Center of Peking University, China. All protocols involving animals, behavioral testing, surgery, and animal care were approved by the laboratory animal welfare ethics committee.https://github.com/yangence/DEBKS.The source code of DEBKS and the script to simulate the RNA-seq dataset are available at CRA002696), which are publicly accessible at https://ngdc.cncb.ac.cn/gsa.RNA-seq data of the mouse MCAO model have been deposited in the Genome Sequence Archive Zelin Liu: Conceptualization, Software, Formal analysis, Writing - original draft, Writing - review & editing, Visualization. Huiru Ding: Methodology, Validation, Writing - review & editing. Jianqi She: Investigation, Data curation, Writing - original draft. Chunhua Chen: Resources, Project administration, Funding acquisition. Weiguang Zhang: Supervision, Resources, Writing - review & editing. Ence Yang: Conceptualization, Supervision, Resources, Funding acquisition, Writing - original draft, Writing - review & editing. All authors have read and approved the final manuscript.The authors have declared that they have no competing interests.


The present use of mRNA vaccines against COVID-19 has shown for the first time the potential of mRNA vaccines for infectious diseases. Here we will summarize the current knowledge about improved mRNA vaccines, i.e., the self-amplifying mRNA (saRNA) vaccines. This approach may enhance antigen expression by amplification of the antigen-encoding RNA. RNA design, RNA delivery, and the innate immune responses induced by RNA will be reviewed. Traditional vaccines are mainly based on inactivated or attenuated pathogens and need long development times, which makes a fast response to newly emerging pathogens difficult. However, vaccines based on nucleic acids can circumvent this shortcoming, and RNA was first suggested as a vaccine candidate more than 30 years ago . The useThe production of mRNA vaccines is technically simple, fast, cost-effective, cell- and animal-material free, and easy to adapt  mRNA vacMoreover, in contrast to DNA-based vaccines, there is no risk of mRNA integrating into the host genome . mRNA isThe mRNA vaccines consist of an open reading frame (ORF) encoding for the immunogenic antigen, a 5′- and a 3′-untranslated region (UTR), a 5′-cap structure, and a 3′-polyadenylated tail (poly-A) . Like ceTo be efficacious, mRNA vaccines needed several alterations to enhance mRNA stability, modulate the innate immune responses to RNA, and enable efficient delivery of mRNA in vivo. Several elements were optimized: The 5′- and 3′-UTR sequences from viral or eukaryotic genes modulate the half-life and translation of mRNAs, and therefore the UTR sequences were optimized for use in mRNA vaccination ,16,17,18The 5′-UTR is primarily involved in recognition of the RNA by ribosomes and the translation of the downstream gene. A Kozak sequence is usually added to improve translation efficiency . The 3′-Moreover, the length of the 3′-poly-A tail regulates mRNA stability and enhances translation . The polOne mechanism by which eukaryotic cells can differentiate between self and non-self mRNA is the cap structure . The eukIn addition, the antigen sequence can be codon optimized to increase antigen expression. For this purpose, synonymous mutations are introduced into the genes with the intention of eliminating rare codons that may slow translation efficiency. Codon optimization also affects GC content and RNA secondary structure, which both influence translation efficiency and can thereby be optimized .For in vivo applications, RNA-based vaccines need to be taken up by cells. This passage through the phospholipid bilayer of the cell membrane is challenging due to their large molecular weight, negative charge, and fast degradation by nucleases. Different methods can be used for the in vivo delivery of mRNA.The simplest delivery method is naked mRNA. It can be taken up by cells via scavenger receptor-mediated endocytosis; however, only small mRNA amounts are released into the cytoplasm . TherefoHowever, improved methods for delivery are needed to obtain high mRNA levels in cells and to deliver mRNA to a large number of cells. The intracellular uptake can be increased by electroporation, using for example a gene gun . TransfemRNA formulations have been developed for in vivo delivery that increase mRNA stability and cellular uptake . The mosForeign RNA is recognized in cells by the innate immune system, which normally results in the suppression of antigen expression . HoweverDuring in vitro transcription, the RNA-dependent RNA polymerase activity of the T7 RNA polymerase and the rebinding of the RNA allow self-priming at the 3′ end for complementary RNA synthesis resulting in double-stranded RNA (dsRNA) ,50,51. TThe DNA template might also affect innate sensing of mRNA vaccines, although most of the DNA should have been removed by purification steps or DNase treatment. Foreign cytosolic DNA is recognized by several DNA sensors like cGAS and IFI16, which mainly operate via the adaptor protein STING (for a review see ). HoweveThe current COVID-19 mRNA vaccines require storage temperatures of –60 or –80 °C for Comirnaty or –50 °C for Spikevax . These lAntigen expression correlates with the amount of mRNA delivered to antigen-presenting cells; however, mRNA is also degraded by RNases . Thus, tTogaviridae family. The alphavirus genome comprises 11–12 kb with a 5′-methylguanylated cap and a 3′-poly-A tail , which fulfills essential functions for viral replication . nsP1 iscis-acting or conserved sequence elements (CSEs)  A. The 5′s (CSEs) B. This sFor the construction of saRNA vaccines, the alphavirus structural proteins are replaced by the antigen gene, which is inserted under the control of the SGP A,B 88]..88]. In Toxoplasma gondii [Several preclinical trials using saRNA vaccine candidates have been reported, predominately aiming to prevent infectious diseases. Here, the saRNA encodes the viral glycoproteins as the target for neutralizing antibodies and cellular immune responses. Alphavirus-based saRNAs were successfully tested in animal models as vaccine candidates for SARS-CoV-2 infections ,92,93,94a gondii , and cana gondii . For reva gondii ,70,110.clinicaltrials.gov, of which nine target SARS-CoV-2 . When packaged in VPs, they can, in principle, be considered as attenuated viruses. They should show a limited replication in humans but should still be able to induce a good immune response without signs of disease. Vaccine candidates using this delivery method have been described for CHIKV. Several deletions in CHIKV genes have been reported, such as a large deletion in nsP3 (Δ5nsP3) or in the capsid, and some of these attenuated viruses have entered clinical development ,125,126.In preclinical models, immunizations with taRNA have mainly been performed by intra-dermal injection of RNA diluted in RNase-free PBS ,120. SimAs non-self molecules, RNA vaccines are sensed by cellular pathways and are effective activators of the innate immune system . As depiIn contrast to mRNA vaccines, the intracellular RNA amplification results in dsRNA and thus a stronger activation of innate immune responses. RNA can be recognized by multiple pattern-recognition receptors including TLR3, TLR7, RIG-I-like receptors, melanoma differentiation-associated protein 5 (MDA5), PKR, and OAS . The resStrategies to reduce the IFN activation have been described for saRNA vaccines. For example, the expression of proteins derived from viruses that avoid immune sensing can inhibit innate responses . EncodinAlphaviruses counteract innate immune responses by shutting off host cell transcription and translation . TherebyBesides strategies to reduce IFN activation, the modulation of immune responses after saRNA vaccination through the use of adjuvants has also been explored. For example, saRNA formulated with a cationic nanoemulsion based on the adjuvant MF59 or formulations with TLR agonists have been evaluated ,140. AltThe preclinical development of saRNA vaccines resulted in the first clinical trials of saRNA vaccines against SAR-CoV-2 and influenza. The clinical trial data for completed saRNA-based COVID-19 vaccine candidates look encouraging, and a first phase I trial was conducted recently . The VEEThe use of mRNA vaccines during the COVID-19 pandemic has demonstrated their feasibility in preventing infectious diseases. saRNA vaccine candidates will further improve this strategy and they hold the promise of being effective with less RNA. However, further research is still required, in particular, to improve the efficiency of RNA delivery and investigate the role of innate sensing. It is also still not certain whether using less RNA, which is amplified in situ, is clinically advantageous compared to standard mRNA vaccines. Comparative preclinical studies demonstrating the advantages of saRNA over mRNA were performed in mouse models, which do not properly recapitulate the innate immune responses in humans. The first clinical trials of saRNA vaccines have just been completed and direct comparisons of mRNA with saRNA remain to be carried out. Like RNA vaccines, saRNA vaccines might not be limited to infectious diseases but might also be used in gene therapy, to fight cancer, or to deliver protein-based therapeutics.


Caenorhabditis elegans is an excellent research model whose populations have been used in many studies to address various biological questions. Although worm-to-worm phenotypic variations in isogenic populations have been persistently observed, they are not well understood and are often ignored or averaged out in studies, masking the impacts of such variations on data collection and interpretation. Single-worm RNA sequencing that profiles the transcriptomes of individual animals has the power to examine differences between individuals in a worm population, but this approach has been understudied. The integrity of the starting RNA, the quality of the library and sequence data, as well as the transcriptome-profiling effectiveness of single-worm RNA-seq remain unclear. Therefore, more studies are needed to improve this technique and its application in research.In this study, we aimed to develop a single-worm RNA-seq method that includes five steps: worm lysis and RNA extraction, cDNA synthesis, library preparation, sequencing, and sequence data analysis. We found that the mechanical lysis of worms using a Qiagen TissueLyser maintained RNA integrity and determined that the quality of our single-worm libraries was comparable to that of standard RNA-seq libraries based on assessments of a variety of parameters. Furthermore, analysis of pathogen infection-induced gene expression using single-worm RNA-seq identified a core set of genes and biological processes relating to the immune response and metabolism affected by infection. These results demonstrate the effectiveness of our single-worm RNA-seq method in transcriptome profiling and its usefulness in addressing biological questions.C. elegans and have applied this method to study C. elegans responses to pathogen infection. Key aspects of our single-worm RNA-seq libraries were comparable to those of standard RNA-seq libraries. The single-worm method captured the core set of, but not all, infection-affected genes and biological processes revealed by the standard method, indicating that there was gene regulation that is not shared by all individuals in a population. Our study suggests that combining single-worm and standard RNA-seq approaches will allow for detecting and distinguishing shared and individual-specific gene activities in isogenic populations.We have developed a single-worm RNA-seq method to effectively profile gene expression in individual The online version contains supplementary material available at 10.1186/s12864-022-08878-x. Caenorhabditis elegans is a 1-mm-long roundworm that has been used as a model organism in biological research for more than half a century. In many studies, experiments were performed on isogenic worm populations. Although worm-to-worm phenotypic variations in these populations were persistently observed, such variations were either ignored or averaged out in the final measurements. However, some variations are significant and should be taken into account during data collection and interpretation. For example, in aging research, individual wild-type worms may die at as early as 10 days, while some individuals may live up to 30 days, resulting in a 300% difference in lifespan in the same wild-type population [hsp-16.2 was used to accurately predict variance in longevity and resistance to stress in isogenic populations [pulation . Interesulations . Becauseulations . HoweverC. elegans, for example, single-cell RNA-seq has been used to define consensus expression profiles of various cell types at different developmental stages [C. elegans, single-worm RNA-seq that profiles the transcriptome of the whole animal may have the power to probe individual-to-individual variations within a worm population. Indeed, Dillman and colleagues have adapted a single-cell RNA-seq protocol, Smart-seq2 [Steinernema carpocapsae, as well as individual embryos and L1 larvae from two Steinernema and two Caenorhabditis species including C. elegans [In recent years, single-cell RNA-seq has been rapidly developed and widely used to detect cell-to-cell variations in gene activities within a cell population. In l stages , 7; examl stages , 9; and l stages . These aart-seq2 , for sin elegans –15. DespCompared to standard RNA-seq that uses RNA from hundreds to thousands of worms as input, single-worm RNA-seq faces two major technical challenges: low input RNA from a single worm and low accessibility of that RNA due to the nematode’s thick surrounding cuticle. While the limited amount of input RNA can be overcome by adapting library preparation methods from single-cell RNA-seq, the harsh chemical lysis condition commonly used to penetrate the worm cuticle and access the RNA could potentially cause RNA degradation –15. In tPseudomonas aeruginosa infection. The RNA-seq analysis of the single-worm samples was conducted in the current study. The RNA-seq analysis of the bulk samples was conducted by us in a previous study [The workflow of our single-worm RNA-seq method includes five major steps, namely, worm lysis and RNA extraction, cDNA synthesis, library preparation, sequencing, and sequence data analysis. The scheme of our workflow is depicted in Fig. us study  and usedIn the single-worm RNA-seq method developed by Dillman and colleagues , 15, a wWith the isolated RNA from single worms as input, we generated cDNA samples using the SMART-Seq v4 Ultra Low Input RNA Kit because of its sensitivity  and itsC. elegans reference genome  using HISAT2 [In next-generation sequencing (NGS), a key factor affecting sequence data quality is library quality, i.e., sequence data can only be as good as the input library. Besides the above-mentioned library size and concentration, library quality can be additionally assessed by examining several key parameters, including alignment rate, rRNA content, read coverage over the position of transcripts, and duplicates. Here, we evaluated these parameters in our single-worm RNA-seq libraries and compared them to those observed in standard RNA-seq libraries. To this end, we aligned our sequence data to the g HISAT2  and theng HISAT2 . On averg HISAT2 , 23.Fig.2(cpm + 1) values, which showed that all of the standard sample points were aligned along the diagonal  fragments mapped to exons were used for the concordance evaluations. The correlation coefficients were greater than 0.99 between the standard samples and 0.97—0.98 between the single-worm samples, indicating that the expression quantification was consistent within each of the two methods, with the standard method having slightly better consistency. These results agree with the scatter plots of the log2cpm +  values, 2cpm +  values, nal Fig. C. Princinal Fig. D. In eitnal Fig. D. These C. elegans mainly consists of four tissues, namely, hypodermis, intestine, muscles, and neurons. Kaletsky et al. identified specific genes that are highly expressed and significantly enriched in these tissues, which included 584, 519, 426, and 867 genes in hypodermis, intestine, muscle, and neurons, respectively [A source of variance among the single-worm samples could be different efficiency in cell dissociation and/or lysis during the mechanical lysis of worms. To examine this possibility, we compared the expression of tissue-specific genes among the five replicates of single-worm RNA-seq samples. ectively . Comparivit-1, vit-2, vit-3,4,5 (detected with the same primers), and vit-6) , as vitellogenin expression is tightly regulated and is adult-specific . For theTo further investigate the differences in expression quantification between the standard and single-worm samples, we evaluated the concordance of their expression quantification using Spearman rank correlation and scatter plots. Although the quantifications of these two groups of samples appeared to be consistent based on the Spearman rank correlation coefficients (0.96–0.97), a careful examination of their scatter plots revealed that a large number of genes split to the two sides of the diagonal, possibly canceling out the negativity of Spearman rank correlation Fig. SC. To finC. elegans upon P. aeruginosa infection, compared to the standard RNA-seq method. To this end, five replicates of four group samples (single and bulk worms with or without exposure to P. aeruginosa for 24 h) were subjected to RNA-seq analysis. Our results showed that in total, 29,921 genes were identified and quantified with a false discovery rate (FDR) of 5% by the single-worm method, while 22,389 genes were identified by the standard method. The fact that 7,532 fewer genes were identified using the standard method than the single-worm method is surprising given that the RNA input in the single-worm RNA-seq was much lower than that used in the standard RNA-seq (10 ng vs. 2.5 µg), thus the opposite trend was expected. However, the lower RNA input may have brought out the presence of low-copy-number transcripts that was reflected in the sequencing data, indicating that the single-worm method may maintain gene diversity better than the standard method where information regarding low-copy-number transcripts could possibly be lost or diminished due to the presence of more high-copy-number transcripts. A pairwise scatter plot of log2 ratio values of differential gene expression indicates that the overall differential expression measured by these two methods had little correlation with each other (R2 for linear regression = 0.21)  at least 1.5-fold in the single-worm RNA-seq, whereas 10,565 genes were significantly regulated at least 1.5-fold in the standard RNA-seq, four times higher than the number in the former. These data suggest that the genes found by the single-worm method were indeed diversified among the 10 individual worms (5 infected worms and 5 uninfected control worms), and that the standard method had greater power to detect DEGs. An unsupervised hierarchical clustering of the DEGs detected in the standard RNA-seq showed that the genes were similarly up- or down-regulated upon pathogen infection in all five biological replicates of the standard samples, indicating great uniformity across the standard samples  Fig. A. When tTo further investigate why the single-worm RNA-seq failed to detect a large number of DEGs that were detected in the standard RNA-seq, we performed data analysis at two levels. At the first level, we compared the read counts and variance of expression quantification between fail-to-detect DEGs and DEGs in the single-worm RNA-seq. At the second level, we compared the read counts and variance of expression quantification of fail-to-detect DEGs between the single-worm and standard RNA-seq. In the single-worm RNA-seq, the average read counts of DEGs were higher than those of fail-to-detect DEGs Fig. SA, while P. aeruginosa is pathogenic to C. elegans and can trigger a strong immune response in the worm [P. aeruginosa infection. Taken together, our results suggest that the single-worm method could be used to identify commonly regulated genes among individual worms and such gene regulation may mediate a population’s core physiological responses to endogenous or environmental stimuli.We next investigated the biology of the gene regulation revealed by the two methods. Among the significantly regulated genes in the single-worm RNA-seq, 1,385 genes were up-regulated and 562 genes were down-regulated at least 1.5-fold in infected worms relative to uninfected controls. GO analysis of the 1,385 up-regulated genes identified 26 significantly enriched biological processes, 22 of which involve the immune response or response to stimulus  following the “Purification of RNA or Multiple Analytes from Animal and Human Tissues” protocol in the manufacturer’s manual. Briefly, worms immersed in 30 µL of RNALater solution were transferred to a 2 mL microcentrifuge tube that was precooled with dry ice and contained one stainless steel bead (5 mm mean diameter). The sample was then incubated on dry ice for 15 min and placed into the insert of the TissueLyser LT Adapter. After incubation at room temperature for 2 min, 600 µL of Buffer RLT from the RNeasy Mini Kit were added. The worms were then disrupted in a TissueLyser LT for 4 min at 50 Hz. The resulting lysate was immediately subjected to RNA purification using the RNeasy Mini Kit following the “Purification of Total RNA from Animal Tissues” protocol in the manufacturer’s handbook. Briefly, the lysate was centrifuged at 16,873 × 2, 0.45% Triton X-100, 0.45% Tween-20, 0.11% gelatin (w/v), 100 µg/mL proteinase K, 200 units of RNasin Ribonuclease Inhibitor), heated at 65 °C for 10 min, followed by 1 min at 85 °C, and then held at 4 °C in a thermocycler. The worms were then transferred to a 2 mL microcentrifuge tube that was precooled with dry ice and contained one stainless steel bead. Homogenization using a TissueLyser LT and RNA extraction using the RNeasy Mini Kit were performed as described in Condition 1.Condition 2 – Thirty worms were resuspended in 30 µL of Lysis Buffer . Briefly, 600 µL of Buffer RLT were added to the worms, and then they were transferred to a QIAshredder spin column with a 2 mL collection tube. The column was centrifuged at 16,873 × Following extraction, the resulting RNA samples were subjected to concentration measurements using a Qubit fluorometer with the RNA HS assay Kit (Life Technologies) as well as integrity checks using a Fragment Analyzer with the DNF-472 RNA Kit (15 nt) (Agilent).Our single-worm RNA-seq workflow includes five steps: worm lysis and RNA extraction, cDNA synthesis, library preparation, sequencing, and sequence data analysis. Below is a description of these steps.One worm per group immersed in 10 µL of RNALater solution was disrupted and homogenized using a TissueLyser LT under the conditions described in Condition 1 above. The isolated RNA was used for cDNA synthesis using the Takara SMART-Seq v4 Ultra Low Input RNA Kit per the manufacturer’s protocol. Briefly, first-strand cDNA was synthesized from 9.5 µL of extracted RNA. The cDNA was then amplified using SeqAmp DNA polymerase by running the LD PCR program . The amplified cDNA was purified using AMPure XP beads (Beckman Coulter) and resuspended in 15 µL of Elution Buffer. Finally, 2 µL of cDNA was aliquoted for validation using a Fragment Analyzer with the High Sensitivity NGS Fragment Analysis Kit (Agilent), and the remaining cDNA was used for sequencing library preparation.A sequencing library was generated for each sample using the Nextera XT DNA Library Preparation Kit (Illumina). Briefly, 200 pg of cDNA was tagmented and then amplified using a limited-cycle PCR program per the manufacturer’s instructions. The resulting library was purified using AMPure XP beads and resuspended in 50 µL of Resuspension Buffer . The library was then subjected to concentration measurements using a StepOnePlus Real-Time PCR System (ThermoFisher Scientific) along with the KAPA Library Quantification Kit (Kapabiosystems). A quality check was also performed using a Fragment Analyzer with the High Sensitivity NGS Fragment Analysis Kit.Sequencing was done on a HiSeq2500 sequencer (Illumina) as previously described . BrieflyC. elegans reference genome  using HISAT2 (version 2.2.1) [http://cbl-gorilla.cs.technion.ac.il/) [Sequence data (FASTQ files) were aligned to the n 2.2.1) . Libraryn 2.2.1) . Gene exn 2.2.1)  and DESen 2.2.1) , respectn 2.2.1) . An unsun 2.2.1)  followinn 2.2.1) ; the clu.ac.il/) .CT (2−ΔΔCT) method and normalized to pan-actin . Cycle thresholds of amplification were determined by StepOne Software v2.3 (Applied Biosystems). All samples were run in triplicate. Primer sequences for vit-1, vit-2, vit-3,4,5, and vit-6 were described in Dowen et al. [Total RNA was obtained as described above and subjected to qRT-PCR following our published protocol with modifications . Brieflyn et al.  and are P. aeruginosa-infected or uninfected control worms using QIAzol lysis reagent (Qiagen) and purified with the RNeasy Plus Universal Kit (Qiagen). RNA samples (2.5 µg per sample) with RQNs ranging from 8 to 10 were used for sequencing library preparation using the TruSeq Stranded mRNA Library Prep Kit (Illumina). Libraries were quantified, pooled, denatured, and sequenced on a HiSeq 2500 sequencer. On average, 40 million reads with a read length of 2 × 100 bp were generated for each sample. Sequence data (FASTQ files) were subjected to bioinformatics analysis as described above for the single-worm RNA-seq.Standard RNA-seq was done in the study of Sellegounder et al. . Sequenct test was conducted for the pairwise comparisons shown in Figs. p values < 0.05 were considered significant [The two-sample nificant .Additional file1: Fig. S1-S5.Additional file 2: Table S1. Five biological replicates of four group samples used in this study.Additional file 3: Table S2. Tissue-specific genes detected in single-worm samples.Additional file 4: Table S3. Enriched biological processes revealed by standard RNA-seq relative to single-worm RNA-seq.Additional file 5: Table S4. Enriched biological processes revealed by single-worm RNA-seq relative to standard RNA-seq.Additional file 6: Table S5. Enriched biological processes revealed by single-worm RNA-seq (infected samples relative to uninfected samples).Additional file 7: Table S6. Attenuated biological processes revealed by single-worm RNA-seq (infected samples relative to uninfected samples).Additional file 8: Table S7. Enriched biological processes revealed by standard RNA-seq (infected samples relative to uninfected samples).Additional file 9: Table S8. Attenuated biological processes revealed by standard RNA-seq (infected samples relative to uninfected samples).