Genome editing technologies that are currently available and described have a fundamental impact on the development of molecular biology and medicine, industrial and agricultural biotechnology and other fields. However, genome editing based on detection and manipulation of the targeted RNA is a promising alternative to control the gene expression at the spatiotemporal transcriptomic level without complete elimination. The innovative CRISPR-Cas RNA-targeting systems changed the conception of biosensing systems and also allowed the RNA effectors to be used in various applications; for example, genomic editing, effective virus diagnostic tools, biomarkers, transcription regulations. In this review, we discussed the current state-of-the-art of specific CRISPR-Cas systems known to bind and cleave RNA substrates and summarized potential applications of the versatile RNA-targeting systems. CRISPR-Cas system is the protection of natural populations of most bacteria and archaea to foreign nucleic acids . Cas proUnlike DNA editing, RNA editing offers an alternative to genome editing in certain applications in an invertible and controllable manner  Figure . First oBiosensing techniques provide the industrial importance to control biomolecules involved in physiological and pathological processes in living organisms, holding great value in basic biochemical research, drug discovery, pollutant detection and monitoring of disease and treatment. The surprising discovery of collateral nucleic acid cleavage by type V and type VI effectors ,25 enzymtrans-conjugative delivery system (Cas13a-based killing plasmid (CKP)) based on a trans-conjugative plasmid was effective in both in vitro and in vivo experiments. However, CRISPR-Cas13 acted on the transcriptome and had promiscuous RNA cleavage activity, resulting in the inability to eliminate plasmids carrying drug resistance genes. Finally, it had differential activation for different target sequences [The problem of the appearance of antibiotic-resistant pathogenic bacteria leads to the need to develop new methods to tackle them. The properties of the CRISPR-Cas system allow the possibility to adapt it to antibacterial protection. The first attempts to adapt CRISPR-Cas systems to target antimicrobial resistance (AMR) genes led to different outcomes including cytotoxicity and even cell death induction. It became possible to overcome these problems by creating an RNA-effector system. In contrast to DNA-targeting, the RNA targeting is not dependent on PAM sequences. Additionally, the reason why Cas13-based antimicrobial agents received widespread use is the target molecule. Since RNA and not DNA is targeted, the threat of developing resistance due to CRISPR-Cas-induced mutations in DNA is reduced. Finally, the obtained experimental data suggest that Cas13-based systems demonstrate higher efficiency compared to Cas9, because it is oblivious to the location of the gene on the chromosome or on the plasmid ,27,28,29equences .The ability to detect trace amounts of nucleic acids using the CRISPR-Cas system was used in molecular diagnostics since 2016 . CRISPR-Molecular diagnostics, based on the activity of collateral cleavage of single-stranded DNA in Cas effectors, made it possible to effectively identify various viral strains: ZIKA virus, Dengue and human papilloma. Additionally, such diagnostics are considered for the parasite infection ,34,35.The features of human-to-human transmission and a high percentage of asymptomatic infections caused the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread speedy and large-scale outbreaks worldwide, posing an extensive threat to health service . A rapidThe infection of significant crops with plant viruses causes economic losses by reducing crop quality and quantity globally. Therefore, it is required to develop multiple approaches to combat viral infection. At the same time, many antiviral strategies which were developed to date are limited to specific groups of viruses. Since single-stranded RNA (ssRNA) viruses are the most prevalent class of plant viruses, the application of CRISPR-Cas RNA-targeting systems is especially budding for crops. Nicotiana benthamiana [One of the Cas13 orthologues, CasRx, was found to be the most efficient and reliable variant for RNA virus interference in thamiana . Moreovethamiana .In recent times, the biotechnology revolution and industrial transformation grew rapidly. Genome editing technology is actively used to improve crops; however, the release of such crops on the market or in the environment is of concern . Thus, tThe feature of a number of CRISPR-based RNA-targeting Cas nucleases to specifically bind and cleave target RNAs in the presence of guide RNA allows researchers to manipulate specific RNAs, involving the tracking of target RNAs and the editing of specific bases of RNAs ,45. To dOver the past few years, there was a huge interest around approaches to cancer treatment. The RNA-guided RNA-targeting CRISPR-Cas13 system has a high possibility for cancer diagnosis and therapy. In most CRISPR-Cas-based cancer therapy experiments, the LwCas13a was successfully used ,45,46. NIn the last 35 years, considerable progress was made in understanding the mechanisms of RNA-editing events and regulation of expression . It is nTailor-made ASO constructs allow for knockdown and demonstrate their effectiveness in the treatment of diseases caused by dysregulation of splicing events . HoweverDue to their programmability and ability to cleave target RNAs through RNase activity, RNA-targeting CRISPR effector proteins can be used to suppress the expression of target genes. It was demonstrated that RfxCas13d silences expression of genes associated with neurodegenerative disorders  . The StCDespite the above successes in applying CRISPR effectors as a platform for suppressing gene expression, there were some limitations. It is obligatory for an effector protein to be constantly expressed in cells, so it can always interact with the target mRNA to maintain the effect. In addition, the rapid degradation of crRNA may become a problem which can be overcome by introducing chemical modifications to crRNA . FurtherOne approach to redirecting splicing is to target critical regions beside intron–exon junctions, which can block the recognition of splicing factors and control the production of mature mRNA. Such targeting can be achieved using RNA targeting Cas effectors, which was already shown for dCasRx . As one The ability to regulate gene expression at the translational level can be of considerable interest as a tool for studying fundamental biological phenomena, as well as a new therapeutic strategy. Although there are several effective strategies for manipulating gene expression at the genomic or transcriptional level, only a few of them are available for modulating translation.RNA-targeting CRISPR-Cas systems make it possible to target mRNA and can be used to regulate expression at the post-transcriptional level, which was demonstrated in a cell-free expression system. In a recent study, a significant reduction in protein expression was achieved through sgRNA targeting to the start codon of the sfGFP (superfolder green fluorescent protein) mRNA, thereby precluding ribosome binding . FurtherRNA editing can be performed through engineering RNA-targeting Cas effectors in the way that they retain the ability to bind target RNA in a controlled manner, additionally removing nuclease activity and fusing it with ADAR (adenosine deaminase acting on RNA). Cas-based RNA base editors can be applied for mutation correction in the treatment of various diseases. The dCas13X.1-based adenosine base editor was shown to exhibit high efficiency of A > G conversion and low frequency of off-target edits on mouse models of deafness . RNA editing tools provide reversible editing of mutant transcripts. On the one hand, it reduces the potential risk of permanent genetic changes, similar to DNA editing tools. On the other hand, RNA-editing therapy implies its continuous insertion.Since the discovery of RNA-targeting nucleases, much effort has been made to apply them as an RNA-target editing tool in eukaryotic cells. Nevertheless, many recent reports highly suggest that RNA-targeting CRISPR-Cas systems behave unpredictably in eukaryotic cells. RNA-targeting CRISPR effector proteins are toxic to cells due to their side RNase activity. Therefore, many developed systems for the regulation of gene expression have a critical drawback for in vivo applications. However, Cas13 variants were already generated that retained high target RNA cleavage activity but showed minimal collateral cleavage activity . CollateThe CRISPR-Cas13 system consists of single RNA-guided Cas13 effector nucleases that solely target single-stranded RNA (ssRNA) in a programmable way without altering the DNA . In receType V CRISPR-Cas systems are remarkable for a single RNA-guided RuvC domain-containing Cas12 effector. Cas12g is a recently identified type V RNA-guided endonuclease. Following activation by target molecular RNA, Cas12g shows collateral RNase and single-strand DNase activities, similar to the collateral activity of Cas12a and Cas13 nucleases. Cas12g effector displays a canonical bilobed architecture containing a recognition lobe (REC) and a nuclease lobe (NUC) ,69,70,71Type III CRISPR–Cas is believed to be the oldest member of the CRISPR–Cas family . RecentlThe type II CRISPR–Cas system belongs to class 2 and is divided into three subtypes . In addition to CRISPR array and Cas proteins, this type encodes additional trans-activating RNA (tracrRNA), which mediates interaction between crRNAs and Cas9 . Type IIThe past 10 years testified great progress in the understanding and manipulation of CRISPR-Cas systems, especially in the field of genome editing and RNA editing. The innovation of CRISPR-Cas changed the conception of biosensing systems and also allowed the CRISPR effectors to be used in various applications; for example, genomic editing, effective virus diagnostic tools, biomarkers, transcription regulations. In just a few years, RNA-targeting CRISPR-based biosensors evolved from a hypothetical nucleic acid sensing tool to an opportunity for diagnostic technology for the rapid, reasonable and ultrasensitive sensing of biomarkers. In addition, Cas13-based biosensors are not expensive, sensitive, selective and easy to apply for the detection of DNA, RNA and proteins in liquid biopsy samples. Technologies based on CRISPR-RNA targeting systems may become potent new tools for controlling protein expression in biological research and biopharmaceuticals production. Finally, CRISPR-Cas13d and engineered variants such as CasRx enable nucleic acid and transcriptome engineering for future development.trans-cleavage activity and it is mainly characterized in the frame of DNA targeting applications. Additionally, not all orthologs of Cas9 are PAM-independent. Each CRISPR-based RNA targeting method has complex and sometimes seemingly insurmountable challenges. Unfortunately, there are still some difficulties in applying well-characterized effector Cas13a for genome editing in mammalian cells. The rapidly growing interest in type III nucleases suggests that, in the future, we will have a versatile RNA-targeting tool, although it is currently not often used in practice. A satisfactory characterization of an effector in vitro cannot guarantee the same efficiency in living cells. As for Cas12g, their usage is limited with the lack of enough characterization data. Nuclease Cas9 does not have trans-cleavage activity guide RNA requirements and kinetic characteristics became available for us. All received data lay the groundwork for scientists to expand the scope of applications of previously obtained systems at the expense of an efficient design and directed evolution to offset any shortcomings existing in RNA-targeting systems. Finally, identification and characterization of new CRISPR-Cas RNA-targeting systems from metagenomic data may be considered to establish and consummate their employment. Despite all aforementioned problems, the CRISPR-Cas RNA-targeting systems already demonstrated their efficiency for a range of applications. In recent works, scientists from all over the world conducted much research on currently available effectors. Due to this, the structures, characterization of specificity and Deciphering the full range of RNA-targeting CRISPR-Cas systems, with its many uncharacterized proteins and functionalities, will provide scientists all over the world with experimental provocations for years to come as well as potential for new incredible applications. In the end, technologies based on RNA-targeting CRISPR-Cas systems will facilitate progress in scientific and treatment applications, paving the pathway for the creation of new technologies for research and biotechnology.


RNA splicing plays significant roles in fundamental biological activities. However, our knowledge about the roles of alternative splicing and underlying mechanisms during spermatogenesis is limited.Srsf2 by Stra8-Cre caused complete infertility and defective spermatogenesis. Further analyses revealed that deletion of Srsf2 disrupted differentiation and meiosis initiation of spermatogonia. Mechanistically, by combining RNA-seq data with LACE-seq data, we showed that SRSF2 regulatory networks play critical roles in several major events including reproductive development, spermatogenesis, meiotic cell cycle, synapse organization, DNA recombination, chromosome segregation, and male sex differentiation. Furthermore, SRSF2 affected expression and alternative splicing of Stra8, Stag3 and Atr encoding critical factors for spermatogenesis in a direct manner.Here, we report that Serine/arginine-rich splicing factor 2 (SRSF2), also known as SC35, plays critical roles in alternative splicing and male reproduction. Male germ cell-specific deletion of Taken together, our results demonstrate that SRSF2 has important functions in spermatogenesis and male fertility by regulating alternative splicing.The online version contains supplementary material available at 10.1186/s12915-023-01736-6. There are two outlets for As spermatogonia, self-renewal to maintain the germline stem cell pool and differentiation to enter meiosis after multiple rounds of mitotic divisions of undifferentiated spermatogonia [s spermatogonia undergo unconventional mitotic processes to produce Apaired (Apr) spermatogonia and Aaligned  spermatogonia [s, Apr, and Aal spermatogonia, are uniformly identified as undifferentiated spermatogonia. Then, Aal spermatogonia transform into type A1 spermatogonia and further go through a series of mitoses to form A2, A3, A4, intermediate (In) and B spermatogonia. These germ cells are called differentiating spermatogonia [Spermatogenesis is a consistent and highly organized developmental process by which male germline stem cells divide and differentiate to produce mature spermatozoa. In mammalian testes, this process consists of three phases: mitosis, meiosis and spermiogenesis . In the atogonia . As speratogonia . These satogonia , 6. Any atogonia .Alternative splicing (AS) is one of the most important transcriptional and post-transcriptional regulatory mechanisms to enrich the amount of mRNA and protein isoforms from a single gene, and these different protein isoforms always have different structural characteristics and functions –10. GeneThe serine/arginine-rich splicing factors (SRs) have an exceedingly critical role in the alternative splicing process of precursor RNAs. The SRs can identify the splicing components of precursor RNA, then recruit and assemble spliceosomes to promote or inhibit the occurrence of alternative splicing events . There iSrsf2Floxed/Floxed (Srsf2F/F) mice with Stra8-Cre mice to generate mutant mice with specific deletion of the Srsf2 gene in male germ cells, we found that the SRSF2 knockout caused complete infertility and germ cells were drastically lost during spermatogenesis. Further investigation revealed that deletion of the Srsf2 gene in germ cells affected the differentiation of spermatogonia and meiosis initiation. By combining advanced linear amplification of complementary DNA ends and sequencing (LACE-seq) and RNA-seq with bioinformatics analysis, we unbiasedly mapped the binding sites of SRSF2 at single-nucleotide resolution and revealed the changes of the transcriptome and transcripts splicing in SRSF2-null testes. Our results showed that SRSF2 deletion caused abnormal alternative splicing during spermatogenesis. In particular, we found that SRSF2 directly regulated the expressions of Stra8, Stag3 and Atr via AS, which have pivotal roles during spermatogenesis.Here, by crossing To investigate the function of SRSF2 in spermatogenesis, we first analyzed the expression of SRSF2 in the testis by using the anti-SRSF2 antibody. As a well-known marker of nuclear speckles, staining of cross-sections of seminiferous tubules in the adult mouse testis showed that SRSF2 was expressed in both germ cells and somatic cells of the testis Fig. A, suggesSrsf2 conditional knockout mice (referred to as Srsf2cKO) by crossing Srsf2Floxed/Floxed (Srsf2F/F) mice in which the first and second exons were floxed [Stra8-Cre mice in which cre activity is initiated at 3 days after birth [Srsf2 was specifically deleted  and antibodies against SOX9 and MVH, markers for the acrosomes of spermatids, Sertoli cells, and germ cells, respectively. Immunofluorescence results indicated that there were no PNA-positive signals in the seminiferous tubules of rol Fig. A. Sertolrol Fig. A.Fig. 3SSrsf2cKO testes at 8-week-old and P12, suggesting that meiosis initiation is disrupted after SRSF2 cKO  marker γH2AX. Similarly, immunofluorescence results indicated that there were no SYCP3 positive signals in the seminiferous tubules of Srsf2WT and Srsf2cKO group at P6  and the germ cell marker MVH (mouse vasa homologue) to characterize the first wave of spermatogenesis in mice at postnatal day 6 (P6), P8, P10, and P12. The results showed that nearly all the germ cells were undifferentiated spermatogonia in both the  P6 Fig. C. Then tP12 Fig. C, showinSrsf2WT and Srsf2cKO testes at P10 and then performed RNA sequencing (RNA-seq). RNA-seq results firstly showed the reduction of Srsf2 RNA in Srsf2cKO mice testes   Fig. C. Heatmates Fig. D. To obttes Fig. E. Meiotites Fig. E. In shoSrsf2WT and Srsf2cKO testes by using the rMATS computational tool. Compared with the Srsf2WT group, a total of 320 AS events were identified as significantly changed in the Srsf2cKO group . Among these 320 changed AS events, most (267) of AS events were skipped exons (SE). Moreover, there were 17 alternative 3′ splice sites (A3SS), 15 alternative 5′ splice sites (A5SS), 16 mutually exclusive exons (MXE), and 5 retained introns (RI)  are well-known for their regulatory function of splicing . The firSrsf2F/F mice with Stra8-Cre mice to generate mutant mice, we found that SRSF2 is essential for spermatogenesis and fertility in males.Recently, it has been found that RNA-binding proteins (RBPs) have important functions during germline and early embryo development. As a RBP, SRSF2 is also expressed in testis, however, its functions in male germ cells is still completely unknown. In this study, by crossing Sycp1, Rnf114, Setx, Hmgb2, Gata4, Sox8, Amh, Kitl, and Axl.The RBPs could serve post-transcriptional functions to determine cellular RNA and protein levels. For the past few years, high throughput sequencing techniques have become an increasingly essential tool for biological research. RNA immunoprecipitation with sequencing (RIP-seq) and crosslinking immunoprecipitation coupled with high-throughput sequencing (CLIP-seq or HITS-CLIP) are two major methods to identify RBPs targets from millions of cells , 36. TheStra8 has two different roles during spermatogenesis. On one hand, under the influence of RA, Stra8 functions as a transcriptional repressor of the pluripotency program during differentiation of spermatogonia. When differentiating spermatogonia are near the end of their mitotic phase, Stra8 switches to the second role and acts as a transcription activator of genes involved in meiosis initiation [Dazl is also regarded as a regulator of meiotic initiation [Srsf2cKO mice, the differentiation of spermatogonia and meiosis initiation were disrupted. Except for Stra8, Stag3 and Atr are crucial regulators of meiotic processes during spermatogenesis [Stra8, Stag3 and Atr in a direct manner, which are critical for the male germ cell development process. Also, we found that the reduced expression and abnormal AS of Dazl were indirectly cuased by SRSF2 deletion   is an important factor of spermatogenesis, with functions on spermatogonial differentiation and subsequently initiation of meiosis , 42. Theitiation –45. In aitiation . Of partogenesis –51. The Stra8, Stag3, Atr and Dazl, caused by SRSF2 deletion finally result in the failure of spermatogenesis and male infertility.In summary, our study has demonstrated for the first time that SRSF2 has important functions in male fertility and spermatogenesis, especially in the differentiation of spermatogonia and meiosis initiation. Mechanistic analyses reveal that SRSF2 is essential for posttranscriptional regulation by specifically adjusting the gene expression and AS in direct or indirect manners during spermatogenesis. These abnormally expressed genes, such as Srsf2 in male germ cells (referred to as Srsf2cKO) were generated by crossing Srsf2Floxed/Floxed (Srsf2F/F) mice with Stra8-Cre mice. All transgenic mouse lines have C57BL/6 J genomic background. Genotyping PCR for Srsf2 was performed using the following primers: forward: GTTATTTGGCCAAGAATCACA, and reverse: TAGCCAGTTGCTTGTTCCAA. The PCR conditions were as follows: 94 ℃ for 5 min; 35 rounds of 94 ℃ for 30 s, 60 ℃ for 30 s, and 72 ℃ for 30 s; and 72 ℃ for 5 min. Genotyping PCR for Stra8-Cre was performed using the following primers: forward: ACTCCAAGCACTGGGCAGAA, wildtype reverse: GCCACCATAGCAGCATCAAA and reverse: CGTTTACGTCGCCGTCCAG. The PCR conditions were as follows: 94 ℃ for 5 min; 35 rounds of 94 ℃ for 30 s, 60 ℃ for 30 s, and 72 ℃ for 30 s; and 72 ℃ for 5 min. Four genotypes in the progeny, including Srsf2F/+, Srsf2F/−, Srsf2F/+; Stra8-Cre and Srsf2F/−; Stra8-Cre were identified. The Srsf2F/+ male mice were used as control group.Mice lacking The mice were maintained under specific-pathogen-free (SPF) conditions and housed under controlled environmental conditions with free access to water and food. All animal operations were approved by the Animal Care and Use Committee of the Institute of Zoology, Chinese Academy of Sciences (CAS).Β-actin antibody ; SYCP3 ; γH2AX ; MVH ; SOX9 antibody ; PLZF antibody ; SFRS2 polyclonal antibody ; SC35 antibody ; green-fluorescent Alexa Fluor® 488 conjugate of lectin PNA . Horseradish peroxidase–conjugated secondary antibodies were purchased from Zhongshan Golden Bridge Biotechnology Co, LTD (Beijing). Alexa Fluor 488–conjugated antibody, 594–conjugated antibody and Alexa Fluor 647–conjugated antibody were purchased from Life Technologies.Males of different genotypes (8 weeks) were used for the breeding assay. Each male mouse was caged with two wild-type ICR (Institute of Cancer Research) females (7 weeks), and their vaginal plugs were checked every morning. The number of pups in each cage was counted within a week of birth. Each male underwent six cycles of the above breeding assay.To prepare protein extracts, testes were homogenized in RIPA lysis buffer supplemented with protease and phosphatase inhibitor cocktail (Roche Diagnostics). After transient ultrasound treatment, the testis lysates were incubated on ice for 30 min and then centrifuged at 4 ℃, 12,000 rpm for 20 min. The supernatant was transferred to a new tube and quantified using a BCA reagent kit . Then equal volume loading buffer was added. After being boiled at 95 ℃ for 10 min, the protein lysates were used for immunoblotting analysis. Immunoblotting was performed as described previously . BrieflyFor histological analysis, at least three adult mice for each genotype were analyzed. Testes and caudal epididymides were dissected immediately following euthanasia. The tissues were then fixed in Bouin’s fixative  overnight at room temperature, dehydrated in an ethanol series, and embedded in paraffin wax. Then, 5 μm sections were cut with a microtome. After 48 ℃ overnight drying, the sections were deparaffinized in xylene, hydrated by a graded alcohol series and stained with Hematoxylin and Eosin for histological analysis. Images were collected with a Nikon inverted microscope with a charge coupled device (CCD) .Testes used for immunostaining were fixed in 4% paraformaldehyde (pH 7.4) overnight at 4 ℃, dehydrated, and embedded in paraffin. Paraffin-embedded testes were cut into sections of 5 μm thickness. Then, the sections were deparaffinized, immersed in sodium citrate buffer (pH 6.0) and heated for 15 min in a microwave for antigen retrieval. After blocking with 5% donkey serum albumin, sections were incubated with primary antibodies at 4 ℃ overnight. Then the sections were incubated with an appropriate FITC-conjugated secondary antibody. The nuclei were stained with DAPI. Images were captured using a laser scanning confocal microscope LSM880 .−ΔΔCt method to calculate the fold changes. β-actin was used as an internal control. At least three independent experiments were analyzed. All primer sequences are listed in the Additional file Total RNA was extracted from whole testes using TRNzol Universal Reagent  according to the manufacturer’s instructions. Then reverse transcription (RT) was performed using the 5X All-In-One RT MasterMix . RT-PCR was performed using the UltraSYBR Mixture  on a LightCycler 480 instrument (Roche). The results were analyzed based on the 2Gapdh was used as an internal control.Semiquantitative PCR experiment was carried out with primers  according to the manufacturer’s instructions. The quality of RNA samples was examined by NanoDrop 2000&8000 and Agilent 2100 Bioanalyzer, Agilent RNA 6000 Nano Kit. The high-quality RNAs were used to prepare the libraries, followed by high-throughput sequencing on an Illumina NovaSeq 6000. The RNA sequencing experiment was supported by Annoroad BioLabs.Total testes samples were used from P10 Srsf2 control and cKO samples were aligned to mouse genome (mm9) using HISAT2 with default parameters. Only non-RCR duplicate and uniquely mapped reads were used for subsequent analysis. Significantly changed genes were screened using DESeq2 with |log2FC|> 0.6 and FDR < 0.05. Alternative splicing events were identified by rMATS with default parameters. Only events with FDR < 0.001 and splicing difference > 0.05 were regarded as significant.After trimming adaptor sequence and rRNA, the retained reads from Total testes samples were used from P10 WT male mice for LACE-seq. LACE-seq method was performed as described recently by us . BrieflyThe adapter sequences and poly(A) tails at the 3′ end of raw reads were removed using Cutadapt (v.1.15) with two parameters: -f fastq -q 30,0 -a ATCTCGTATGCCGTCTTCTGCTT -m 18 –max-n 0.25 –trim-n., and -f fastq -a A -m 18 -n 2. Clean reads were first aligned to mouse pre-rRNA using Bowtie, and the remaining unmapped reads were then aligned to the human (hg19) or mouse (mm9) reference genome. For LACE-seq data mapping, two mismatches were allowed . Peaks were identified by Piranha with parameters: -s -b 20 -p 0.01. Peaks without IgG signal were selected for further usage. For motif analysis, LACE-seq peaks/clusters were first extended 30 nt to 5′ upstream, and overrepresented hexamers in the extended sequences were identified as previously described . The conP < 0.05(*), 0.01(**) or 0.001(***) was considered statistically significant.All of the experiments were performed at least three times independently. Paired two-tailed Student’s t-test was used for statistical analysis. Data analyses were carried out via GraphPad Prism 8.00  and presented as mean ± SEM and Additional file 1: Fig. S1. Spermatogenesis fails to progress into meiosis in Srsf2 deficient germ cells at P12 γH2AX (green) and SYCP3 (red) immunofluorescence analysis of the Srsf2WT and Srsf2cKO male mice at P12. Scale bar: (top) 50 μm; (bottom) 20 μm.Additional file 2: Fig. S2. SRSF2 regulates mRNA alternative splicing in testes Five AS events significantly affected by deletion of SRSF2 in the testes at P10. The different types of alternatively spliced events were shown.Additional file 3: Fig. S3. SRSF2 indirectly regulates splicing and expression of Dazl. (A) A magnified view showing RNA-seq signals of the Dazl gene. (B) Quantitative RT-PCR validation of the expression of Dazl. (C) Semiquantitative RT-PCR analysis of AS patterns of the changed spliced genes in Srsf2WT and Srsf2cKO testes at P10 (n = 4 per group). PCR primers are listed in Additional file Additional file 4: Fig. S4. The effect of SRSF2 deletion-introduced exon skipping. (A) The effect of SRSF2 deletion-introduced exon 2 skipping on Stra8 mRNA. The sequence of targeted exon was showed between Srsf2WT and Srsf2cKOgroups. (B) The effect of SRSF2 deletion-introduced exon 19 and exon 20 skipping on Stag3 mRNA. The sequence of targeted exon was showed between Srsf2WT and Srsf2cKOgroups. (C) The effect of SRSF2 deletion-introduced exon 34 skipping on Atr mRNA. The sequence of targeted exon was showed between Srsf2WT and Srsf2cKO groups. (D) The effect of SRSF2 deletion-introduced exon 8 skipping on Dazl mRNA. The sequence of targeted exon was showed between Srsf2WT and Srsf2cKO groups.Additional file 5: Table S1. Primer List.Additional file 6: Table S2. The top-10 enriched hexamers.Additional file 7: Table S3. Binding genes and DEGs.Additional file 8. Images of the original, uncropped gels/blots.Additional file 9. Individual data values.


In recent years, immune checkpoint inhibitors (ICIs) had extremely rapid growth in anti-cancer and improved outcomes of many malignancies, specifically lung cancer. However, the incidence of ICIs-related adverse events also raised. Using this meta-analysis, ICIs-related respiratory disorders were investigated in lung cancer patients.Using Cochrane Library, Embase, and PubMed databases, we performed an integrated search for randomized controlled trials (RCTs) to compare respiratory disorders among different regimens. The data was prepared with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guideline, and the quality of included studies was evaluated based on the Cochrane manual.In total, 22 RCTs were involved in this meta-analysis. Compared with ICIs, chemotherapy reduced the risk of interstitial lung disease , pleural effusion , and pneumonitis . ICIs plus chemotherapy could provide a higher probability for patients to suffer pneumonitis than chemotherapy . In addition, single ICI brought a lower likelihood for patients suffering pneumonitis than double ICIs .ICIs-based treatment, such as ICIs alone, ICIs plus chemotherapy and double ICIs, can raise the incidences of some respiratory disorders in patients with lung cancer. It suggests that ICIs should be conducted based on a comprehensive consideration to prevent ICIs-related respiratory disorders. To a certain degree, this study might be provided to the clinician as a reference for ICIs practice.https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022378901, identifier (CRD42022378901). In most countries, cancer is currently the first or second most frequent cause of premature death. In 2022, the USA has experienced more than 1,900,000 new cancer cases and 600,000 cancer deaths, with lung cancer being the leading cause of these deaths , T cell engineering, oncolytic viruses, and vaccines. Immune checkpoint inhibitor (ICI) therapy includes programmed death-1 (PD-1) and programmed cell death 1 ligand 1/2 (PD-L1/2), cytotoxic T lymphocyte-associated antigen-4 (CTLA-4), lymphocyte-activation gene 3 (LAG3), and other potential targets. PD-1 is a transmembrane protein expressed in T, B, and NK cells and an inhibitory molecule that binds to PD-L1 and PD-L2. PD-L1 is represented on the cell surface of various tissue types, including many tumor and hematopoietic cells. Contrarily, PD-L2 is more restricted to hematopoietic cells. The combination of PD-1 and PD-L1/2 can directly inhibit tumor cell apoptosis and promote peripheral effector T cell depletion and conversion of effector T cells into Treg cells . CTLA-4 Despite the favorable clinical benefits of checkpoint inhibition, it has side effects known as immune-related adverse events (irAEs) , 14. IrAThe meta-analysis for ICIs-related respiratory disorders in patients with lung cancer was prepared in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses reporting guideline .A competent information specialist (HL) conducted an integrated search for RCTs between January 2000 and October 2022 using the Cochrane Library, Embase, and PubMed databases. According to the PICOS  guidelines (The inclusion criteria were as follows: (1) RCT on lung cancer ; (2) ICI intervention, including PD-1/PD-L1 or CTLA-4 inhibitors; and (3) comparison between single-agent ICI plus chemotherapy and chemotherapy, single-agent ICI and chemotherapy, as well as single-agent and double-agent ICIs. The exclusion criteria were as follows: (1) no report of ICIs-related respiratory disorders; (2) publications not written in English; (3) abstracts, case reports, comments, editorials, letters, and reviews; and (4) duplicate, missing, and overlapping datasets.Two investigators (SL and JJ) independently reviewed the titles and abstracts of the articles to obtain the qualified studies. Furthermore, two investigators (SW and LS) identified the potentially relevant studies to determine if they were eligible based on the inclusion and exclusion criteria. Disagreements as regards the study’s selection were resolved through discussion and compromise.Two investigators (HL and JJ) independently extracted the characteristic data, including publication year, first author name, number of clinical trial, drug name, clinical trial phase, lung cancer type, regiment of intervention, enrollment, and serious adverse events (SAEs), from the eligible studies. According to the analysis of SAEs, the top 10 most frequent ICIs-related respiratory disorders, including pneumonitis, dyspnea, pulmonary embolism, pleural effusion, chronic obstructive pulmonary disease, respiratory failure, hemoptysis, interstitial lung disease, pulmonary hemorrhage, and pneumothorax, were conducted as the main outcomes  . Funnel 2I < 30%), moderate (30% ≤ 2I < 50%), or high (2I ≥ 50%) . ICIs-related respiratory disorders, including pneumonitis, dyspnea, pulmonary embolism, pleural effusion, chronic obstructive pulmonary disease, respiratory failure, hemoptysis, interstitial lung disease, pulmonary hemorrhage, and pneumothorax, were evaluated using the mean differences with 95% confidence intervals (CIs). Based on the Cochrane collaboration network, a fixed-effects model was used to pool studies, and the inconsistency index was used to access heterogeneity as low ( ≥ 50%) , 26. SubIn total, 3884 potentially relevant studies were retrieved from databases as a result of the strategy performed in searching. 453 studies were recorded after duplicates removed. Then, 369 studies were excluded due to irrelevant topic, non ICIs-related or retrospective studies. The investigators removed 62 studies after screening the full texts. Four released updated results –30, and The characteristics of 22 RCTs from the 22 included studies are presented in The quality assessment of the included studies is presented in The incidence of ICIs-related respiratory disorders in different treatment regimens is presented in P = 0.67; SMD: 0.87; 95% CI: 0.46, 1.64) or ICIs  did not significantly change the incidence of chronic obstructive pulmonary disease with low evidence of heterogeneity among the studies (2I = 0% and 10%). Double ICIs  did not significantly change the incidence of chronic obstructive pulmonary disease when compared with single ICI with low evidence of heterogeneity among the studies (2I = 0%) . Compared with chemotherapy, ICIs plus chemotherapy  or ICIs  did not significantly change the incidence of dyspnea with low evidence of heterogeneity among the studies (2I = 0% and 0%). Double ICIs  did not significantly change the incidence of dyspnea when compared with single ICI with moderate evidence of heterogeneity among the studies (2I = 41%) . Compared with chemotherapy, ICIs plus chemotherapy  or ICIs  did not significantly change the incidence of hemoptysis with low evidence of heterogeneity among the studies (2I = 0% and 11%). Double ICIs  did not significantly change the incidence of hemoptysis compared with single ICI . Compared with chemotherapy, ICIs plus chemotherapy  did not significantly change the incidence of interstitial lung disease with low evidence of heterogeneity among the studies (2I = 0%). ICIs  significantly increased the risk of suffering interstitial lung disease with low evidence of heterogeneity among the studies (2I = 0%). Double ICIs  did not significantly change the incidence of interstitial lung disease when compared with single ICI with low evidence of heterogeneity among the studies (2I = 0%) . Compared with chemotherapy, ICIs plus chemotherapy  did not significantly change the incidence of pleural effusion with low evidence of heterogeneity among the studies (2I = 0%). ICIs  significantly increased the risk of suffering pleural effusion with low evidence of heterogeneity among the studies (2I = 0%). Double ICIs  did not significantly change the incidence of pleural effusion when compared with single ICI with low evidence of heterogeneity among the studies (2I = 0%) . Compared with chemotherapy, ICIs plus chemotherapy  and ICIs  significantly increased the risk of suffering pneumonitis with low evidence of heterogeneity among the studies (2I = 0% and 0%). Double ICIs  significantly increased the risk of suffering pneumonitis with low evidence of heterogeneity among the studies (2I = 0%) . Compared with chemotherapy, ICIs plus chemotherapy  or ICIs  did not significantly change the incidence of pneumothorax with low evidence of heterogeneity among the studies (2I = 0% and 0%). Double ICIs  did not significantly change the incidence of pneumothorax when compared with single ICI with low evidence of heterogeneity among the studies (2I = 0%) . Compared with chemotherapy, ICIs plus chemotherapy  or ICIs  did not significantly change the incidence of pulmonary embolism with low evidence of heterogeneity among the studies (2I = 0% and 0%). Double ICIs  did not significantly change the incidence of pulmonary embolism when compared with single ICI with low evidence of heterogeneity among the studies (2I = 0%) . Compared with chemotherapy, ICIs plus chemotherapy  or ICIs  did not significantly change the incidence of pulmonary hemorrhage with low evidence of heterogeneity among the studies (2I = 0% and 0%). Double ICIs  did not significantly change the incidence of pulmonary hemorrhage when compared with single ICI with low evidence of heterogeneity among the studies (2I = 0%) . Compared with chemotherapy, ICIs plus chemotherapy  or ICIs  did not significantly change the incidence of respiratory failure with low evidence of heterogeneity among the studies (2I = 0% and 0%). Double ICIs  did not significantly change the incidence of respiratory failure when compared with single ICI with high evidence of heterogeneity among the studies (I2 = 78%) . Compared with chemotherapy, ICIs plus chemotherapy . Pleural effusion has been reported as an irAE, but there are few studies on ICIs-related pleural effusion, most of which are case reports  for CTLA-4 inhibitors, 3.02% (95% CI: 2.31–3.93) for PD-1 inhibitors, and 7.09% (95% CI: 5.52–7.16) for PD-1 combined with CTLA-4 inhibitors , 96–114.This study has several limitations. First, NSCLC and SCLC were both investigated in the analysis. A retrospective study demonstrated that squamous cell cancer was a risk factor for ICIs-related pneumonitis . As a coIn conclusion, this study showed that ICI-based treatment, such as ICIs alone, ICIs plus chemotherapy, and double ICIs, can raise the incidences of some respiratory disorders in patients with lung cancer. It suggests that ICIs should be conducted based on a comprehensive consideration to prevent ICIs-related respiratory disorders. To a certain degree, this study might be provided to the clinician as a reference for ICI practice. Of course, more prospective and well-designed clinical trials, and larger sample size real-world studies on various ICIs are still needed to further evaluate therapeutic effects and ICIs-related adverse events.The original contributions presented in the study are included in the article/SW conducted the analysis, SL, JJ and LP collected and performed a preliminary analysis of references, HL designed the manuscript, SL and HL wrote the manuscript, LP, SW and LS revised the manuscript. All authors contributed to the article and approved the submitted version.


The deep learning method for natural-image object detection tasks has made tremendous progress in recent decades. However, due to multiscale targets, complex backgrounds, and high-scale small targets, methods from the field of natural images frequently fail to produce satisfactory results when applied to aerial images. To address these problems, we proposed the DET-YOLO enhancement based on YOLOv4. Initially, we employed a vision transformer to acquire highly effective global information extraction capabilities. In the transformer, we proposed deformable embedding instead of linear embedding and a full convolution feedforward network (FCFN) instead of a feedforward network in order to reduce the feature loss caused by cutting in the embedding process and improve the spatial feature extraction capability. Second, for improved multiscale feature fusion in the neck, we employed a depth direction separable deformable pyramid module (DSDP) rather than a feature pyramid network. Experiments on the DOTA, RSOD, and UCAS-AOD datasets demonstrated that our method’s average accuracy (mAP) values reached 0.728, 0.952, and 0.945, respectively, which were comparable to the existing state-of-the-art methods. Object detection in ultra-high spatial resolution aerial images aims to rapidly determine a target’s location and classify the target. Object detection in aerial images is widely used in numerous important fields, including the localization and identification of military targets , naturalThe application of convolutional neural networks to computer vision and object detection has made significant strides in recent years. Successively, superior object detection algorithms, including the R-CNN series ,6,7,8, tIn this research, we focus on addressing the issues mentioned above to enhance the target detection performance in aerial images. In addition, the speed of detection is a significant obstacle for detection algorithms, as target detection from satellite imagery is typically performed in real time. A one-stage object detection algorithm, exemplified by the YOLO series ,10,11, cDET-YOLO is the name of the enhanced YOLOv4 variant. Experimental results showed that our proposed DET-YOLO outperformed the general YOLOv4 in detecting targets in aerial images.A new feature extraction network named a deformable embedding vision transformer (DEViT) is proposed, which has the excellent global feature extraction capability of transformers while using deformable embedding instead of normal embedding to efficiently extract features at different scales. In addition, a fully convolutional feedforward network (FCFN) is used to replace the feedforward neural network (FFN), and the extraction of location information is effectively enhanced by introducing zero padding and convolutional operations.The depthwise separable deformable convolution (DSDC) is proposed to reduce computational effort while preserving the deformable convolution’s ability to zero in on regions of interest. It is proposed that the depthwise separable deformable pyramid (DSDP) module extracts multiscale feature maps and prioritizes key features.Our proposed DET-YOLO achieved the highest accuracy among existing models, with mean average precision (mAP) values of 0.728 on the DOTA dataset, 0.952 on the RSOD dataset, and 0.945 on the UCAS-AOD dataset.This study’s contribution is summarized as follows:The rest of the paper is organized as follows: YOLOv4’s architecture comprises three primary components: the backbone, the neck, and the predicting head. The backbone extracts feature data from an image input. The neck collects and combines multiscale feature data to generate three distinct-scale feature maps. Based on these created feature maps, the predicting head detects objects. YOLOv4 employs the CSPDarknet53  frameworThese two aspects are elaborated upon below.C, H, and W represent the channel dimension, height, and width of the feature, respectively, a vanilla patch embedding splits X into N patches of size P P  is the operation for linear embedding and Reshape(∙) is the flattening function.As depicted in p(i) on feature map X′, a rectangular region of the input image with the area p(i) is denoted as For each patch offsetθ(∙), which has a single convolutional layer with a 1 offsetii channels represent the x- and y-axis offsets, respectively, for to the layer i channel of the original map. The offset associated with each position offsetθ (p(i) constitutes the new feature graph X′. X′ is substituted into Equation (2) to obtain the deformable embedding result p (i) is as follows:Feature map X is fed to the lightweight subnetwork Our proposed deformable embedding receives a 2D offset on each pixel for each patch, allowing it to extract the target information adaptively and effectively avoiding the issue of semantic information corruption during vanilla splitting.A vanilla feedforward neural network (FFN) of visual transformers consists of two layers of MLP composition and a GELU  activatiDue to the high computational cost of MLPs, they require a substantial amount of computation while effectively preserving the dimensionality of the feature channels. As shown in First, instead of MLP, we use two 1 olutions  to improolutions  demonstrTo visually demonstrate the improvement in the computational requirements of our FCFN over the FFN, we compare their computational costs and parameter counts.I) as an input and outputs a O), where n). The standard MLP output feature sequence is computed as follows:A standard MLP layer accepts a The standard MLP incurs the following computational cost:The standard MLP parameters are as follows:For FFN, the first MLP receives a D) as an input and generates an G) as an output, where W and H represent the width and height of the input feature map, A and B represent the width and height of the output feature map, and A standard convolutional layer receives an A standard convolutional layer incurs the following computational expenses:The parameters of a standard convolutional layer are:The computational cost of the depthwise separable convolution corresponding to the standard convolution is:The computational cost of the depthwise separable convolution corresponding to the standard convolution is:For the FCFN, the first DWConv takes a By substituting the FFN with the FCFN, the following reductions in computation and parameters are obtained:DEViT employs a deformable embedding with a patch size of 16 and accepts high- resolution RGB satellite images as inputs; consequently, each FCFN is Instead of FPN, we propose a depthwise separable deformable pyramid to obtain feature maps at various scales from a non-hierarchical network architecture such as DEViT. The following subsections are descriptions of the DSDC and the DSDP, which comprises the DSDC.DSDC is proposed by combining depthwise separable convolution  and defoBy adding an offset convolution layer, the vanilla deformable convolution layer learns offsets from the previous feature mapping. Using a convolution kernel of the same size as the corresponding convolution and an offset feature map with an output space the same size as the input feature map with twice as many channels as the original feature map, the offset of the convolution kernel relative to the x and y axes on each pixel of each channel is determined using the offset convolution.Thus, the deformation can concentrate on objects in a dense, adaptive, and local manner. However, the additional convolution operation requires a substantial amount of computation, which slows model inference and makes it difficult to meet the real-time requirement for aerial image object detection. Deformable convolution yields a spatially two-dimensional offset that is channel-independent and two-dimensional. Therefore, we can separate the calculation of the offset from the calculation of the channel, which drastically reduces the amount of computation required without affecting the effect.A standard convolution is decomposed into a depthwise convolution and a pointwise convolution by depthwise separable convolution. For each input channel, the depthwise convolution performs a separate convolution operation. The pointwise convolution then applies a 1 × 1 convolution to combine the outputs of the depthwise convolution. A depthwise separable convolution reduces the computational effort by decomposing a standard convolution into a channel-by-channel convolution kernel and a point-by-point convolution.A standard deformable convolution is decomposed by DSDC into a deformable depthwise convolution and a pointwise convolution. A deformable depthwise convolution learns the offset independently for each channel, whereas a pointwise convolution combines the output of the deformable depthwise convolution for each channel. DSDC replaces the depthwise convolution portion of the depthwise separable convolution with a deformable convolution to gain the ability to adaptively focus on the region of interest. DSDC strikes a balance between improved computational efficiency and the deformable convolution’s ability to extract features.Because DEViT employs a non-hierarchical transformer structure, it is only possible to obtain a single-scale feature map. Due to the varying scales of the targets, a multiscale feature acquisition capability is required in aerial images. The most prevalent method for constructing a multiscale feature map is a feature pyramid network, which employs a top-down architecture with skip connections to combine features at various levels. For non-hierarchical transformers, Li et al.  attempteWe propose a simple multiscale feature acquisition module, dubbed a depthwise separable deformable pyramid, which only performs simple upsampling, downsampling, and a 1 Subsequent experiments revealed that DSDP performed better than FPN on DET-YOLOv4, which will be discussed in detail in the ablation experiments subsection in To validate the efficacy of DET-YOLO, we conducted experiments on the widely used public datasets RSOD , UCAS-AOThe RSOD dataset includes 6950 annotated samples and 976 high-resolution RGB satellite images from Google Earth and Tianditu. The dataset includes four distinct types of objects, including an oil tank, an aircraft, an overpass, and a playground.The UCAS-AOD dataset is a high-resolution aerial image dataset designed to detect small and medium-sized targets. It consists of 1510 images and 14,596 annotated instances with a fixed image size of 1280 The DOTA-v1.5 dataset was derived from Google Earth, the JL-1 satellite, and the GF-2 satellite, among other platforms and sensors. It contains 2806 RGB images and 188,282 annotated instances with dimensions ranging from 800 To validate the generality of our model, we also conducted experiments on UAVDT . Unlike As evaluation metrics, we chose precision (P), recall (R), average precision (AP), and mean average precision (mAP), which are frequently employed in target detection.TP is true positive, FP is false positive, TN is true negative, and FN is false negative.P and R are defined as:AP is defined as the area of the P-R curve created using precision and recall as follows:K represents the number of categories and The mAP is the average of the APs for all categories and accurately reflects the model’s overall predictive performance. The definition is as follows:Using the aforementioned indicators, we could evaluate our strategy effectively.Our proposed DET-YOLO was implemented in Windows 10 using the 1.8.1 version of the PyTorch framework. The experiments were conducted on a desktop computer equipped with an Intel i9-7920X processor and an NVIDIA RTX 2080 ti graphics processing unit with 11 GB of memory.We proposed that DEViT serve as the backbone of DET-YOLO in place of CSPDarkNet53. As a pre-trained model for DEViT, we partially inherited the ViT model trained on ImageNet using the MAE method. According to , we usedTo determine the efficacy and universality of DET-YOLO, we compared it to the most representative methods on the DOTA, RSOD, and UCAS-AOD datasets. The experimental outcomes for three distinct datasets are shown in We plotted P-R curves and confusion matrices of DET-YOLO on the DOTA dataset to demonstrate the DET-YOLO detection performance for each category of the aerial targets. The AP of each category is the area below the corresponding P-R curve. The greater the AP, the better the detection performance for this category, and the larger the corresponding area. Each row of the confusion matrix represents an actual category of the sample, while each column represents the predicted category. The entire matrix reflects the model’s ability to classify the objectives of each category. The horizontal background represents FP, the negative sample proportion of the prediction error, and the vertical background represents FN, the positive sample proportion of the prediction error. In the confusion matrix, the diagonal data indicate the proportions of correctly classifiable categories. From the P-R curve, it can be seen that the prediction accuracy for container cranes was far lower than that of the other categories. Moreover, the confusion matrix in We tested the reasoning speeds of different methods on the DOTA dataset, as shown in As shown in In order to confirm the efficacy of the modifications we made, we conducted ablation experiments on each component; the results are presented in the On the basis of YOLOv4, we developed DET-YOLO to address the issues of diverse target sizes, complex background, and the large number of small targets in aerial images. We improved YOLOv4 from two perspectives, the network for feature extraction and the network for feature fusion, in order to better adapt it to the characteristics of aerial images. On one hand, we proposed DEViT to replace CSPDarknet53 as the network for feature extraction in order to improve the global capability for feature extraction. DEViT uses deformable embeddings instead of linear embeddings to effectively reduce the loss of feature information when processing targets at different scales compared to conventional vision transformers. We used FCFN rather than FFN in the DEViT encoder block to improve the extraction of location information while simultaneously reducing computational effort. On the other hand, we made a replacement for the FPN in the neck. As an alternative to the FPN, we proposed DSDC for extracting multiscale features from a single-scale feature map. DSDC is capable of adaptively focusing on key regions in order to enhance the ability to extract information about desired feature targets. DET-YOLO was evaluated using the widely used DOTAv1.5, RSOD, and UCAS-AOD datasets. For these datasets, the mAP values of the method proposed in this paper were 0.728, 0.952, and 0.945, which were superior to YOLOv4. The preceding results conclusively demonstrated the efficacy of the proposed DET-YOLO algorithm for object detection in aerial images. Experiments with ablation demonstrated that each of the proposed modules had a practical enhancement effect. In general, our proposed DET-YOLO model is a detector suited for aerial target detection tasks. In a subsequent work, we will enhance the linear embedding process of the transformer and attempt to apply deformable embedding to the hierarchical transformer model, thereby making the transformer model more suited to specific tasks in aerial imagery.


The advent of next generation sequencing (NGS) has fostered a shift in basic analytic strategies of a gene expression analysis in diverse pathologies for the purposes of research, pharmacology, and personalized medicine. What was once highly focused research on individual signaling pathways or pathway members has, from the time of gene expression arrays, become a global analysis of gene expression that has aided in identifying novel pathway interactions, the discovery of new therapeutic targets, and the establishment of disease-associated profiles for assessing progression, stratification, or a therapeutic response. But there are significant caveats to this analysis that do not allow for the construction of the full picture. The lack of timely updates to publicly available databases and the “hit and miss” deposition of scientific data to these databases relegate a large amount of potentially important data to “garbage”, begging the question, “how much are we really missing?” This brief perspective aims to highlight some of the limitations that RNA binding/modifying proteins and RNA processing impose on our current usage of NGS technologies as relating to cancer and how not fully appreciating the limitations of current NGS technology may negatively affect therapeutic strategies in the long run. The advent of high-throughput technologies (HTTs) like DNA microarray technology and reverse-phase protein arrays (RPPAs), in the 1990s, revolutionized the manner in which a gene expression analysis was undertaken in the life sciences . Prior tAll RNA transcripts can undergo some form of post-transcriptional processing. In eukaryotes, the classic example involves mRNA capping, polyadenylation, and splicing. These processes involve the addition of a N7-methylated guanosine linked 5′-5′ to a second guanosine by a triphosphate linkage (7mGpppG) to the 5′ nucleotide of the pre-mRNA, the addition of a poly A tail to the 3′ end of the sequence, and the removal of introns to form the mature mRNA. Both 7mGpppG capping and polyadenylation influence the stability of the mRNA transcript, its nuclear export and subsequent translation, thus influencing the expression level of the encoded protein . In addicis- and trans-acting factors. The cis-acting factors consist of RNA sequences 5′ and 3′ of the intron–exon junction and the branch-point (BP) region located between 18-40 nucleotides upstream of the 3′ splice site. In addition to these, sequences present in the introns and exons serve as splicing enhancers or silencers based on the RNA binding proteins that preferentially associate at these sequences. The trans-acting factors consist of the small nuclear ribonucleoproteins (snRNPs) U1, U2, U4/6, and U5 as well as close to 300 additional proteins . SR. SRSRSF1The activity of the SRSF proteins is highly regulated by extensive and reversible phosphorylation of serine residues carried out by several kinases, including AKT family kinases, CDC-like kinases (CLKs), SRSF protein kinases (SRPKs), pre-mRNA splicing 4 kinase (PRP4K), and protein kinase A (PKA) ,29,30. THeterogeneous nuclear ribonucleoproteins assist in the maturation of pre-mRNA transcripts to mature mRNAs during nuclear to cytoplasmic transport, and their subsequent translation, by influencing alternative splicing and mRNA stability, transport, and folding. There are around 20 major types of hnRNPs and several minor families whose genes are scattered throughout the genome, some being sex-linked  37]. Th. Th37]. O-linked β-N-acetylglucosaminylation (O-GlcNAc), phosphorylations, succinylations, sumoylations, and ubiquitinations, whose roles in the cell are not clear , methylations, N-glycosylations, ot clear  31]. Ma. MaO-linPTEN). One must also keep in mind that as well as having an infinite number of splicing possibilities, we also have an infinite possibility of conditions that may influence alternate splicing and promote the production of novel isoforms. Moreover, the response to these conditions and the expression of alternate-spliced isoforms may be, and likely is, tissue/cell-type specific and highly influenced by the disease state of the tissue. Thus, it is not surprising that alterations in several splicing factors , and while many gene profiles from gene expression arrays and RNA-seq are available as open access, the information they provide in this context is only partial. One of the more direct methods is manually assembling transcript products from a specific gene. Manual mapping is a low-throughput method but has the highest probability of identifying all transcript products from an individual gene. In addition, validation and cloning of any alternate spliced forms identified can be undertaken with RNA isolation, gene-specific amplification of transcripts, and RNA-seq together with shotgun cloning and DNA-seq, giving a representation of all transcripts present that are related to a particular gene. Of course, this works for when the expression of only a handful of genes is of interest . When itRNA editing is an important post-transcriptional mechanism occurring in a wide range of organisms, which alters the primary RNA sequence through the insertion/deletion or modification of specific nucleotides. The most common modification in humans is deamination, leading to both a biochemical and functional change in the nucleotide . In RNA,Deamination of adenosine and cytidine residues in RNA is carried out by dedicated and specific enzymes classified according to the activity they catalyze as either adenosine deaminases or cytidine deaminases. The adenosine deaminases consist of the adenosine deaminase acting on the double-strand RNA (ADAR) family and the adenosine deaminase acting on the tRNA (ADAT) family, while the cytidine deaminases belong to the activation-induced cytidine deaminase/apolipoprotein B mRNA editing enzyme and the catalytic polypeptide (AID/APOBEC) family , Table 3Beyond modifying an RNA secondary structure, protein binding and changing protein coding and adenosine deamination are also known to alter splice donor–acceptor site selection by modifying key adenosine residues near the acceptor site, thus promoting alternative splicing of transcripts. In non-coding RNA, such as miRNAs, deamination can result in alteration of the seed region, thereby changing the target specificity of miRNAs. Similarly, cytidine deamination alters transcript coding, structure, and stability and may alter miRNAs, although generally at a much lower frequency compared to adenosine deamination. Therefore, the enzymes that carry out these activities have the potential to drastically enhance transcript variability on a small or large scale, depending on the tissue, process involved, and conditions, as well as promote disease  42,43].,43.42,43ADAR; 1q21.3), ADAR2 , and ADAR3 . These enzymes are composed of a series of tandemly arranged double-strand (ds) RNA binding domains  upstream of the catalytic domain. In addition, full-length ADAR1 also contains two Z-α domains in the amino terminus, which allow ADAR1 to associate with nucleic acids possessing a left-handed helical structure (Z-RNA/Z-DNA)  A 48]. A. AADAR; Similar to ADAR1, two main forms of ADAR2 have been characterized, ADAR2 long (ADAR2) and ADAR2 short (ADAR2-S). ADAR2-S results from the alternative splicing of an Alu element, producing an ADAR2 isoform that is missing amino acids 466-505. The lack of these 40 amino acids in ADAR2-S results in an enzyme with elevated catalytic activity. In contrast, only one form of ADAR3 has been significantly characterized ,55,56,57Beyond alternative splicing and homo-/heterodimerization, these editases are regulated by a number of post-translational modifications. In ADAR1p150, over 120 PTMs have been identified, mostly through high-throughput methods like mass spectrometry, but only a few of these PTMs have been characterized for their effect on ADAR1 activity . SumoylaUnlike the ADAR family, ADAT proteins, ADAT1, ADAT2, and ADAT3, carry out a minor portion of the RNA editing in the cell. As their name indicates, editing catalyzed by these enzymes is specific to tRNA, thus their influence is rather specific to translation and has no significant impact on a DNA/RNA-seq analysis and will not be further discussed here .In humans, cytidine deamination of RNAs is carried out by certain members of the APOBEC family. The family consists of APOBEC1, APOBEC2, APOBEC3 , APOBEC4, and activation-induced cytidine deaminase (AID). Similar to ADAR family proteins, the subcellular localization of APOBEC proteins dictates target selection. APOBECs 1, 2, 3A, 3C, 3G, and 3H are each cytosolic and nuclear with an enrichment of 3G and 3H in processing bodies (P-bodies). APOBEC3B is strictly nuclear while APOBECs 3D and 3F are cytosolic and often enriched in P-bodies ,64. The Although the first members of this family were identified for their RNA editing ability, not all members of this family edit RNA. APOBEC proteins function as monomers, homodimers, heterodimers, and tetramers depending on the family member  11]. Th. Th11]. Mostly expressed in lymphoid tissues and B-lymphocytes, AID (12p13.31) is a ssDNA deaminase that is responsible for Ig heavy chain class switching and hypermutations in variable regions, promoting antibody maturation . LocalizIn mice, APOBEC3 is encoded in a single gene that diverges and expands in humans to seven related genes in a cluster located on chromosome 22 (22q13.1). APOBEC3 proteins are widely expressed in tissues. Expression is most noted in lymphoid tissue and peripheral blood mononucleated cells as well as reproductive organs, suggestive of a significant role in innate immune signaling. While certain APOBEC3 members (3A and 3G) can edit ssRNAs, the primary purpose of these editases is the modification of ssDNAs arising during viral infection ,12. In aIn contrast to other APOBECs, the expression of APOBEC2 (6p21.1) is restricted to cardiac and skeletal muscle. APOBEC2 does not demonstrate any deaminase activity toward DNA or RNA yet strongly binds to DNA at specific promoters and is suspected of being a transcriptional repressor that regulates myoblast differentiation and myogenic stem satellite cell self-renewal ,86. FinaRNA editing presents many of the same issues that alternative splicing presents but with the potential for modifications much more difficult to clearly identify. Both WGS and single-cell techniques can remove a significant amount of potential variability in regards to editing. Our current understanding of the ADAR family is that adenosine deaminations catalyzed by ADAR1 and ADAR2 are restricted to RNA, although the association of ADAR1p110 and ADAR2 with DNA repair complexes and their involvement in the DNA repair process should at least be mentioned for consideration ,45,46,47Increasing use of high-throughput technologies for diagnoses, prognoses, and therapeutic responses of patients often has overlooked caveats…the transcriptome does not necessarily reflect the genome, nor will all transcript reads be correctly identified. Early studies using genome arrays based on short probe binding missed many alternatively spliced transcripts, and of the transcripts they recognize, the assay format was not adequate to distinguish the presence or absence of most alternatively spliced transcript isoforms, nor were these formats adequate at catching post-transcriptional edits of the transcripts. Using this approach, multiple transcript isoforms may bind to the same oligonucleotide probe and vice versa; some expressing alternatively spliced transcripts may exclude the sequences necessary to bind to a gene’s specific oligonucleotide probe, and thus, their expression fails to be identified. The re-use of most older genome array datasets requires updating/re-aligning the oligonucleotide probes to the genome prior to re-analyzing as well as a focused analysis of oligonucleotide probes demonstrating no significant homology to the genome but demonstrating significant change during the assay.With the advancement of RNA-seq technology that provides longer reads, many of these points are now resolvable but require significant attention on the part of those conducting the analysis. A streamlined RNA-seq analysis often uses database matching with annotated transcripts reported by the NCBI or ENSEMBL, but unique transcripts in an analysis that have yet to be annotated are not assigned and “discarded”. Alternative splicing resulting from the altered expression/regulation of splicing-associated proteins or RNA editing enzymes can have a significant effect on this aspect. Since many splicing factors and RNA/DNA editing enzymes are affected by and regulate the innate immune/inflammatory response, the effects elicited by alternative splicing factors and RNA editing enzymes become even more applicable under inflammatory/cell stress conditions where innate immune signaling and activation of the integrated stress response become paramount. In addition, high-throughput techniques are not designed to analyze the potential downstream effects that alternative splicing or single-nucleotide editing of the RNA have on the function of specific proteins. Single nucleotide changes observed in RNA-seq need to be defined and compared to WGS/WES to differentiate RNA or DNA editing from polymorphisms  . Thus, i


Tgo DNA polymerase mutant to present SegModTeX — a versatile, one-pot, copy-and-paste approach to address these challenges. By precise, stepwise construction of a diverse set of RNA molecules, we demonstrate the technique to be superior to RNA polymerase driven and ligation methods owing to its substantially high yield, fidelity, and selectivity. We also show the technique to be useful for incorporating fluorescent- and a wide range of other probes, which significantly extends the toolbox of RNA biology in general.RNA performs a wide range of functions regulated by its structure, dynamics, and often post-transcriptional modifications. While NMR is the leading method for understanding RNA structure and dynamics, it is currently limited by the inability to reduce spectral crowding by efficient segmental labeling. Furthermore, because of the challenging nature of RNA chemistry, the tools being developed to introduce site-specific modifications are increasingly complex and laborious. Here we use a previously designed  Additionally, more and more nucleotide modifications at predefined sites are known to further expand the structural, mechanistic, and functional repertoire of RNA4. It is therefore important to understand RNA structures in their various conformations and in the correct chemical context to gain complete insights into its function and the biology it governs.RNA is positioned at a critical cross-section of biology: it not only disseminates genetic information but also folds into structures to mediate many biological functions. This is due to its capacity to form numerous basepair-types beyond the canonical Watson-Crick pairs, often providing the ability to sample multiple conformations that are critical to drive function6-methyl-adenosine (m6A), 5-methyl-cytosine (m5C), pseudouridine (Ψ), etc., are difficult to add site-specifically using an enzymatic approach. Third, many biochemical techniques, such as FRET, have limited options on where the probe can be placed and hence are mostly confined to the termini, thus restricting complete characterization of the molecule.5However, current RNA structural characterization methods suffer from three major drawbacks. The first is specific to NMR; while it is strongly positioned to provide structural data across the full folding landscape of a molecule, it is not conducive for working on large RNAs due to signal overlap and broad linewidths. Second, it is challenging to construct functionally relevant chemical states of RNAs; for example, modifications like N6. There are three methods currently in use for segmental and site-specific labeling. First, individually synthetized RNA fragments can be ligated with T4 DNA or RNA ligase, which has been successfully used in several studies including an NMR study of 100 kDa HCV IRES RNA8. It has recently been extended to allow for site-specific addition of single bases at the ligation site using chemical or T7 RNA polymerase synthesis.10 However, ligation itself has shortcomings such as low yields in individual ligation and preparatory steps, sequence constraints at and around the ligation site, and minimum segment lengths, all of which severely limit its use7. Second, position-selective labeling of RNA (PLOR) uses T7 polymerase to extend RNA stepwise by using different unlabeled, labeled, or modified rNTP pools in individual steps11. T7 polymerase starts transcription de novo and cannot reengage with an RNA:DNA duplex. PLOR tries to circumvent this by keeping the RNA polymerase engaged with the duplex while the rNTP pools are washed on and off13. However, due to its technical complexity, use of saturating amounts of labeled rNTP pools per wash/step, and limited yield, it has not found widespread use.One way to overcome both the size limitations of NMR and site-specific incorporation of modified nucleotides is to construct RNA segments sequentially, each of which can be manipulated for selective incorporation of isotopes  and/or modified rNTPs and analogues14. However, chemical synthesis has a length constraint of ~70 nt for NMR spectroscopy. This limitation is imposed by the current step-wise coupling efficiency of ~98% in each step, which leads to overall low yields further diminished by side products during the deprotection steps16. Furthermore, many phosphoramidite versions of modified rNTPs are not commercially available and thus off limits to most labs17. Together, these methods have found limited application in overcoming the size and crowding limitations of NMR as only ~2% of deposited NMR structures in the RCSB database are greater than 70 nucleotides (April 2023) with the largest being 155 nt8. Out of these, almost half required the use of segmental labeling via ligation to unambiguously assign resonances. Additionally, all deposited structures that incorporate site-specific RNA modifications either used short, chemically synthesized RNAs or RNAs extracted from biological material, both of which severely limits the type and composition of RNAs that can be studied.Finally, a third approach involves chemical RNA synthesis using phosphoramidite nucleotide analogues. This method easily allows for selective incorporation of modified or isotopically labeled nucleotides18. On the other hand, virtually all RNA polymerases initiate transcription de novo and are not thermostable, making segmental additions or melting steps impossible. Nevertheless, Cozens et al. reported a mutant DNA polymerase (TGK) from Thermophilus gorgonarius (Tgo) with a unique capability to not only efficiently incorporate rNTPs, but importantly, also extend an RNA primer that is annealed to a DNA template19. Building on that work, we characterized and optimized the enzyme’s fidelity, accuracy, versatility, and yield for extending RNA primers/segments. Here we present a method for ‘Segmental labeling and site-specific Modifications by Template-directed eXtension’ , tRNAlys3 (20seg1), and 7SK snRNA (41seg1). Each seg1 was annealed to a ssDNA template with a complementary 3′-end  and encoding the sequence of seg2 at the 5′-end. TGK was then used to extend the various seg1 to produce seg1-seg2: HBV-ε (+1 to 26seg1-seg2), tRNAlys3 (+12 to 32seg1-seg2), and 7SK snRNA (+29 to 70seg1-seg2). We rigorously tested all relevant parameters, including concentration of template, segments, rNTPs, enzyme, and divalent ions and additionally optimized buffer, pH, annealing conditions, temperature, and time for extension. Unlike T7 polymerase, all SegModTeX reactions were robust and went to completion under the same optimized reaction conditions of 0.1 mM template:seg1, 1.5 mM rNTPs, 0.1 mg/ml TGK, 15 mM MgSO4, 1x ThermoPol buffer (pH: 7.1), at 72 °C for < 90 min. The turnover of the various seg1 to seg1-seg2 appears to be 100% as evidenced by the complete absence of seg1 in the enzymatically extended lanes  of the various lengths and compositions were either made by T7 polymerase or by chemical synthesis, including HBV-epsilon (HBV-ε) (25ed lanes .seg1) using different combinations of rNTPs  and checked if the enzyme stalls at the predicted site , or if the polymerase extends beyond that by using the wrong rNTPs. Remarkably, the predicted extensions occurred exactly as delimited by the complementary rNTPs, indicating a low promiscuity of the polymerase  with different versions of mismatched 3′-end base pairs  and performed extension assays. Mismatched segments are not extended 25. 7SK-SL1apical is especially enriched with bulges and non-Watson base pairs which are readily discernable by NMR. Our comparative analysis  was left protonated while domains C and D were extended using deuterated rNTPs, rendering these domains invisible to NMR   required four specifically deuterated samples, four , 101nt) . Thus, u180/253) (148/178)  . In the 148/178) . After erge RNAs , 4b.180/253 , N1-methyladenosine (m1A), inosine (I), 2′-O-methylation (2′-O-m), 5-hydroxymethylcytosine (hm5C), 5-methylcytosine (m5C), and pseudouridine (Ψ)31. Cozen et al. showed that the latter two could substitute for Cs and Us19. Given that SegModTeX can be used for multi-segment extension, we wanted to test if we can site-specifically introduce these and other biologically relevant modifications.Many RNAs are modified in cells to control function. The most prevalent modifications are Nlys3 and m6A at position 26 (HBV-genome: 1907) in the distal HBV-ε stem-loop33. Both Ψ and m6A are widely used modifications and occur naturally in these constructs. In the first step, we used the same template:seg1 setup as before 3, which is absent in the sample made by T7 polymerase without an m6A modification , we also introduced 2-A148/178 , left. Wseg1) extends by 7 nucleotides . Extension stalls at expected lengths in the absence of the specified NTPs, whereas it goes to completion with most modified NTPs: The HBV-ε  or 10 nfor CTP- . As expe17, is severely limited due to the complexity of assigning spectra without the ability to isotopically label individual segments. Finally, biochemical methods such as FRET, RNA-crosslinking, etc., are confined to end-labeling or cumbersome ligation techniques to achieve site-specific incorporation. In this paper we showcase the use of a mutant Tgo DNA polymerase for ‘Segmental labeling and site-specific Modifications by Template-directed eXtension’ (SegModTeX) — a one-stop protocol to address all these limitations.RNA biology is a rapidly advancing field; however, the construction of RNA samples with native modifications remains challenging. Furthermore, NMR, one of the main methods for structural analysis accounting for 35% of deposited RNA structures34, leading to homogeneous 3′-ends to the extent that the ssDNA template is accurate. In fact, use of asymmetric PCR to make high quality ssDNA template renders the process independent of any sequence length constraints that arise from restrictions of chemical synthesis. Third, since all extensions require the same optimized conditions, no further optimization for reaction conditions or special sequence considerations are required. Moreover, compared to even a single-step ligation protocol, which involves separate preparation of the two segments that are appropriately protected or primed for ligation followed by splinting and addition of ligase, SegModTeX allows for a one-step reaction to achieve segment joining. Fourth compared to T7 polymerase-driven RNA production, this method has an additional advantage that no base-type restrictions exist for the initiating nucleotide. Furthermore, the retention of DNA-primed extension by the enzyme allows seg1 to have no minimum length requirement because the RNA segment alone does not have to be long enough to anneal. Finally, the salient feature of SegModTeX is the ability to use multi-step extensions to site-specifically incorporate a plethora of modified NTPs at any desired position(s) without sequence constraints around the modified site(s). For example, one could specifically modify or label any cytosine, even if it is flanked by other cytosines, via single nucleotide extensions.First, unlike ligations, the extension reaction goes to completion, which addresses the biggest hurdle of segmental labeling. Thus, insofar as the product is recovered efficiently, the yield can approach 100%. This in principle allows for multiple rounds of extensions. Second, although the enzyme has been mutated to accommodate rNTPs, it has not resulted in a loss of complementary base recognition, maintaining the high fidelity of polymerases. This directly benefits junction homogeneity because mismatched 3′-ends are consequently selected against for extension; therefore, the end product only contains the desired sequences. Similarly, unlike RNA polymerases, no RNA self-templating occurs35. In addition, this technique can be used to build more sophisticated tools for existing methods. For example, currently RNA FRET is mostly limited to labels at the two ends, whereas SegModTeX permits easy incorporation of fluorescent labels at any position on an RNA, thus granting access to the whole molecule. We see similar potential for selective halogeno labeling for x-ray crystallography, crosslinking, or affinity tags.This versatility and ease of SegModTeX has the potential to transform RNA structure determination by NMR, as structures of smaller domains can be solved in its larger context due to the drastic reduction of spectral crowding. This, along with the current progress in assignment prediction software can allow for a rapid workflow for characterizing large RNAs currently outside the scope of solution NMR™ BL21 Star™ cells and grown to 2L from overnight cultures. Subsequent IPTG induction at ~O.D. 0.7 was followed by 3–4 h growth. Cells were concentrated by centrifugation, resuspended in 40 ml lysis buffer , and sonicated on ice with six 1-min cycles at 60%−70% duty, with 1 min cool down between each pulse. Lysate was incubated with washed Pierce™ Glutathione Agarose slurry from ThermoFisher (cat. #16101) in lysis buffer for 2 h at 4 °C. Subsequently, the beads were washed with 750 ml lysis buffer and cleaved overnight in 10 ml of elution and storage buffer  with 60 μl aliquot of PreScission protease (13 mg/ml made inhouse). After elution from the column, TGK was stored at 4 °C for short-term or diluted with one volume glycerol at −20 °C for long-term.The plasmid for TGK-polymerase expression was cloned to encode an N-terminal Glutathione-S-transferase, a PreScission protease cleavage site, and the polymerase insert between the BamHI and NotI restriction sites of a pGEX-6P-3 vector. Plasmid DNA was transformed into One Shotm) of ~65 °C, though lower melting temperatures are possible if the reaction is run at lower temperatures (see below). Longer hybridization regions do not affect SegModTeX. As the template is single-stranded, it is advised to avoid long self-complementarity at the 3′ends to avoid the template serving as primer for the TGK polymerase in an off-target reaction, however, as the reaction occurs at 72 °C, we have not encountered this problem in any tested construct thus far. Moreover, if self-templating is observed non-extendable ssDNAs with di-deoxy or 3′-monophosphate ends can be used.The ssDNA templates contain a 3′end reverse complementary to the 3′ end of the RNA segment for their hybridization. The length should translate to a melting temperature  and 70% ethanol precipitation, and subsequently washed and concentrated with H2O in Amicon® Ultra-15 Centrifugal Filter Units.For SegModTeX templates shorter than 100 nt, ssDNA was ordered from Integrated DNA Technologies (IDT) and if necessary, purified on a 6% polyacrylamide 25% formamide sequencing gel. SegModTeX templates longer than 100 nt were prepared using asymmetric PCR as described in36. For the longer 7SK snRNA samples, plasmids containing the T7 promoter, insert, and SmaI recognition sequence were cloned in between the EcoRI and BamHI restriction sites of a PUC19 vector. Plasmid DNA was prepared for PCR amplification from a 2mL overnight culture of NEB 5α Competent E. coli (C29871) transformed with the plasmid. Subsequently, the precise template sequences were amplified using primers ordered from IDT and EconoTaq® PLUS 2X Master Mix. PCR products were extracted via a 2-step ammonium acetate (2.5M) and 70% ethanol precipitation.Similarly, for control samples made by T7 polymerase, shorter templates were ordered from IDT, with 2′-O-methylated 5′-endsin vitro transcription using T7 RNA polymerase. Chemically synthesized RNAs were also tested for constructs with RNA seg1 smaller than 26 nt (ordered from IDT). Resuspended RNA segments from in vitro transcription and ethanol precipitation or chemical synthesis were directly used for SegModTeX. For most reactions, the RNA was PAGE purified before every round of SegModTeX to avoid any carry-over of rNTPs from previous reactions which SegModTeX might mistakably incorporate into the new segment as well. However, we found that for smaller RNA constructs (<70nt) ammonium acetate – ethanol precipitation successfully removes rNTPs from the previous step.RNA seg1 for the various constructs were synthesized by ™ RNase Inhibitor was added according to the manufacturer’s specifications.All SegModTeX reactions were conducted according to the following optimized protocol: 1x ThermoPol buffer (NEB), 15 mM MgSO4, 1.5 mM rNTPs, 0.1 mM RNA seg:ssDNA template, and TGK polymerase to a final concentration of ~0.1 mg/ml were mixed at 4 °C. For large RNAs, SUPERase•InThe NTP mix contained the individual bases at concentrations according to their demand in the extension reaction. For rare or expensive NTPs, ratios as low as 15-fold excess per base incorporation were successfully tested. Higher concentrations of NTPs require special considerations for the DNase treatment step (see below).m of the template hybridization sequence of less than 63 °C) or else 72 °C. If experimental design requires very short RNA:DNA hybridization regions (< ~15nt), extension can be started at lower temperatures to allow for the addition of initial bases so as to increase the Tm, after which the temperature can be increased to allow for fast completion. Under optimized conditions, we observed SegModTeX starting to extend RNAs even at room temperature (data not shown).The reaction mixture was incubated at either 65 °C  to up to 90 min. Extended incubation time of up to 90 min can be beneficial for long extensions or highly structured segments but did not impact RNA integrity in our experiments. As TGK is a thermostable polymerase, heat-denaturation, either at the beginning or in between the incubation, akin to PCR cycles, was successfully tried and can be used for reaction optimization but was not required for any RNA sample shown. Moreover, we found that increasing the polymerase concentration was an easier and effective way to achieve extension completion.2+ concentration and denatured at 95 °C for 2 min.Template DNA was digested with Turbo DNase according to the manufacturer protocol . It is important to note that incomplete DNA digestion has a detrimental impact on data quality due to the difficulty in separating it from the RNA in subsequent steps. Hence, for the digestion, special consideration should be given to the maximum allowed DNA concentration as specified in the Turbo DNase protocol, as high template and NTP concentration are inhibitory. This also limited the amount of SegModTeX product added in polyacrylamide gel wells due to volume constraints. In most cases, three-fold dilution of the reaction mix was necessary and sufficient to insure complete digestion. To stop the reaction, EDTA was added equimolar to the Mg2O. The sample was then ready for another round of SegModTeX.For purification without PAGE, ½ volumes 7.5 M ammonium acetate was added, the sample vortexed for 10 s, placed on ice for 10 min and centrifuged at 15,000 g for 20 mins, 4 °C. This step is necessary to remove the enzymes in the sample, which might interfere with applications downstream. In a new tube, the supernatant and 4 volumes ethanol were added, mixed, and precipitated for 2 h at −80 °C. The centrifuged pellet was washed twice with 80% cold ethanol, dried at room temperature for 6 h, and resuspended in HFor PAGE purification, the digestion reaction was precipitated using 0.3 M sodium acetate in 4 volumes ethanol at −80 °C and subsequently resuspended in RNA gel-loading buffer  and purified using urea-PAGE with 25% formamide. The choice of purification method depends on the subsequent use of the RNA. As the extension of RNA in SegModTeX is essentially 100%, size-based separation of the RNA product is not necessary in general. However, as the sample is in a mix of salts, proteins, NTPs, dNMPs and DNA oligos, precipitation or filter-based methods might be insufficient for highly sensitive applications, such as NMR.2O, pH: 7.0, 25 °C; tRNA: 10 mM Tris•HCl, 10 mM NaCl, 7 mM MgCl2, pH: 7.5 buffer, 37 °C). All NMR experiments were acquired in 5 mm Shigemi tubes with Bruker 700 and 800 MHz instruments containing cryogenic probes. Spectra for observing non-exchangeable protons were collected in 100% D2O, for exchangeable protons in 90% H2O.RNA samples were suspended in the appropriate buffer . PCR amplification of the RT product was done with EconoTaq® PLUS (LGC Biosearch Technologies #300331) with the RT primer and primers complementary to the 5′ start of 7SK snRNA. The agarose-gel purified PCR products were sent for Sanger sequencing.The DNA oligo (5′TAATACGACTCACTATAGGGTCTCTTGTTCATGAGTCATGG3′) was 5′ phosphorylated with T4 PNK  and ligated onto the 3′ ends of PAGE purified SegModTeX and T7 constructed 7SK snRNA NMR samples with T4 RNA ligase 1  according to the manufacturer’s protocols. Reverse transcription was performed with a short (25 nt) primer (5′TCCATGACTCATGAACAAGAGACCC3′) using GoScriptGel band intensities for MANT-GTP and Alexa-Fluor-647-ATP were measured by ImageJ (NIH). Intensity of top band divided by the total intensity of top and bottom band.