Archival formalin-fixed, paraffin-embedded (FFPE) tissue samples with clinical and histological data are a singularly valuable resource for developing new molecular biomarkers. However, transcriptome analysis remains challenging with standard mRNA-seq methods as FFPE derived-RNA samples are often highly modified and fragmented. The recently developed 3′ mRNA-seq method sequences the 3′ region of mRNA using unique molecular identifiers (UMI), thus generating gene expression data with minimal PCR bias. In this study, we evaluated the performance of 3′ mRNA-Seq using Lexogen QuantSeq 3′ mRNA-Seq Library Prep Kit FWD with UMI, comparing with TruSeq Stranded mRNA-Seq and RNA Exome Capture kit. The fresh-frozen (FF) and FFPE tissues yielded nucleotide sizes range from 13 to > 70% of DV200 values; input amounts ranged from 1 ng to 100 ng for validation.The total mapped reads of QuantSeq 3′ mRNA-Seq to the reference genome ranged from 99 to 74% across all samples. After PCR bias correction, 3 to 56% of total sequenced reads were retained. QuantSeq 3′ mRNA-Seq data showed highly reproducible data across replicates in Universal Human Reference RNA  at input amounts from 1 ng to 100 ng, and FF and FFPE paired samples (R = 0.92) at 10 ng. Severely degraded FFPE RNA with ≤30% of DV200 value showed good concordance (R > 0.87) with 100 ng input. A moderate correlation was observed when directly comparing QuantSeq 3′ mRNA-Seq data with TruSeq Stranded mRNA-Seq (R = 0.78) and RNA Exome Capture data (R > 0.67).In this study, QuantSeq 3′ mRNA-Seq with PCR bias correction using UMI is shown to be a suitable method for gene quantification in both FF and FFPE RNAs. 3′ mRNA-Seq with UMI may be applied to severely degraded RNA from FFPE tissues generating high-quality sequencing data.The online version contains supplementary material available at 10.1186/s12864-021-08068-1. Transcriptome profiling analysis is widely used in cancer research and clinical settings, such as drug discovery, diagnosis testing, and molecular biomarker discovery –3. FormaHigh-quality RNA from fresh biological tissues is optimal to generate reliable transcriptome data. As FFPE samples are highly modified and fragmented with wide ranges of nucleotides, standard mRNA-Seq (poly-A selection) methods for transcriptome analysis are challenging , 7; totaThis study evaluates 3′ mRNA-Seq using the Lexogen QuantSeq 3′ mRNA-Seq Library Prep FWD Kit with unique molecular identifiers (UMI). The data are compared with TruSeq Stranded mRNA-Seq and RNA Exome Capture kit using Universal Human Reference RNA (UHR). RNA derived from fresh frozen (FF) and FFPE tissues with varying input amounts and nucleotide sizes range were used and compared with Exome Capture. Our results show that severely degraded FFPE RNA may be sequenced yielding accurate transcriptome profiling by 3′ mRNA-seq using UMI.Figure The QuantSeq 3′ mRNA-Seq kit has two protocols, standard input for high-quality RNA (> 10 ng) and low input/FFPE for degraded or small amounts of RNA (≤10 ng). We evaluated reproducibility with these two protocols using UHR. Total mapped reads were similar among the different input amounts and protocols . However, the unique reads after PCR bias correction gradually dropped as total input RNA decreased Fig. A, 56–10%QuantSeq 3′ mRNA-Seq data using the standard input protocol was compared with Illumina TruSeq Stranded mRNA-Seq kit at 100 ng input level, which is the minimum RNA input amount recommended by Illumina. The correlation between the two protocols was moderate  of DV200 at 10 ng input. Total mapped reads were 83 to 97% but dropped to 13 to 28% after PCR bias correction Fig. A. The toTo validate the performance of QuantSeq 3′ mRNA-Seq using highly degraded FFPE RNA with ≤30% (13–30%) of DV200 values, input amounts were increased to up to 100 ng to achieve sufficient unique reads after PCR bias correction. The unique reads at 10 ng input ranged from 10 to 17%, increased to ~ 40–50% after increasing the input amount to 100 ng  and R = 0.67  using the MACE-Seq with UMI method at the 1000 ng level. This supports the tenet that 3′ mRNA-Seq method for FFPE samples is a reliable method for gene expression study.The unique mapped reads and the total number of detected genes in the FFPE samples were dependent on RNA input, regardless of degradation levels. In this study, even severely degraded FFPE RNA may be used for QuantSeq 3′ mRNA-Seq with at least 100 ng input, and data were highly correlated with even in samples with ≤30% of DV200 values. Previously Turnbull et al.  reportedRNA exome capture detects more fusion genes and alternatively spliced genes compared to standard mRNA-Seq and total RNA-Seq in FFPE samples , 9, 12. This study evaluated QuantSeq 3′ mRNA-Seq using UMI in high-quality RNA comparing with TruSeq Stranded mRNA-Seq and with RNA Exome Capture using degraded RNA derived from FFPE tissue. We report that QuantSeq 3′ mRNA-Seq with PCR bias correction using UMI is a suitable method for gene quantification in both FF and FFPE RNAs. QuantSeq 3′ mRNA-Seq may be applied to even severely degraded RNA from FFPE tissues, generating high-quality sequencing data. QuantSeq 3′ mRNA-Seq using UMI is one means by which to investigate gene expression in a cost-effective manner, other approaches may yield more information and a greater number of detected genes, alternative splicing, and fusion genes. Thus, investigators should select the most suitable method based on the goals of the experiments and samples’ conditions because each platform has a different chemistry and sensitivity. Albeit, the QuantSeq 3′ mRNA-Seq using the UMI method provides an opportunity, particularly for gene expression analyses in severely degraded specimens, which may have not been feasible for RNA-Seq in the past.FFPE samples were cut to 10 μm thickness, and several tissue slices were put into a 1.5 ml tube. Xylene was added for deparaffinization, then total RNA was extracted with the Qiagen miRNeasy FFPE kit  following manufacturers’ protocol. Total RNA from fresh frozen (FF) Sample 6 was extracted using TRIzol  following manufacturers’ protocol. UHR was purchased from ThermoFisher Scientific. Total RNA was quantified by Qubit and qualified by Agilent 2100 BioAnalyzer . DV200 value (the percentage of RNA fragments > 200 nucleotides) was determined by 2100 expert software.There are two protocols for the library preparation for the QuantSeq 3′ mRNA-Seq Library Prep Kit-FWD . For the standard input protocol, UHR was incubated for 15 min at 42 °C to generate first-strand cDNA, and RNA was removed. The UMI second-strand synthesis mix was added to generate second-strand cDNA, followed by purification of double-stranded cDNA, and then PCR, using dual indices with 11 cycles for the library amplification was performed. UHR 10 ng and 1 ng, and all FFPE and FF samples were processed using the low input/FFPE protocol. Most processes are the same as standard input protocol for the low input/FFPE protocol, but incubation was increased to one hour for the first-strand cDNA and PCR was increased to 22 cycles for the library amplification.For the standard mRNA-Seq library, the TruSeq Stranded mRNA-Seq library kit  was used and followed manufactures’ protocol. Briefly, mRNA from 100 ng of UHR was isolated using mRNA isolation beads and fragmented for 4 min at 94 °C. The first-strand cDNA was synthesized at 42 °C, and the second-strand cDNA was synthesized at 16 °C for one hour with a second-strand marking buffer. Double strand cDNA was cleaned using DNA XP beads , then A-tailed, ligated with index, amplified library with 15 cycles, and then the final library was cleaned using DNA XP beads.For the RNA exome capture library, the TruSeq RNA Exome Capture kit  was used and followed manufactures’ protocol. Briefly, 500 ng of highly degraded RNA was used for the first-strand cDNA synthesis at 42 °C. The second-strand cDNA was synthesized at 16 °C for one hour with a second-strand marking buffer. Double strand cDNA was cleanup with DNA XP beads, A-tailed, ligated with index, amplified library with 15 cycles, and then the final library was cleaned with DNA XP beads. cDNA library was quantified using Qubit and Agilent 2100 BioAnalyzer D1000 chip, and 200 ng of each library was pooled for exome enrichment and capture. After finishing the second enrichment, the pooled final libraries were amplified with 10 cycles and then the final library was cleaned using DNA XP beads.The libraries were quantified by BioAnalizer 2100 system using the D1000 kit  and Qubit dsDNA BR Assay kits . All the libraries were sequenced 101 bp paired-end reads on Illumina HiSeq 4000 or MiSeq.2 (TPM + 1) values. Pearson R-value was used for sample correlation analysis after PCR bias-corrected data. Protein-coding genes were used for the comparison between 3′ mRNA-Seq and RNA exome capture method. The two-tailed student’s t- test was used for statistical analyses.For the 3′ mRNA-Seq data, ~ 1.5 to 8 million (M) of total reads were generated from each library. The Read 1 FASTQ files were uploaded into Partek Flow software , and primary QC was performed. The UMI reads were identified, and adapter and poly A/T sequences were trimmed. The STAR (2.6.1d)  aligner Additional file 1: Supplemental Data S1. Sample information and QC metrics of the QuantSeq 3′ mRNA-Seq with UMI.


Despite the recent precipitous decline in the cost of genome sequencing, library preparation for RNA-seq is still laborious and expensive for applications such as high throughput screening. Limited availability of RNA generated by some experimental workflows poses an additional challenge and increases the cost of RNA library preparation. In a search for low cost, automation-compatible RNA library preparation kits that maintain strand specificity and are amenable to low input RNA quantities, we systematically tested two recent commercial technologies—Swift RNA and Swift Rapid RNA, presently offered by Integrated DNA Technologies (IDT) —alongside the Illumina TruSeq stranded mRNA, the de facto standard workflow for bulk transcriptomics. We used the Universal Human Reference RNA (UHRR)  to benchmark gene expression in these kits, at input quantities ranging between 10 to 500 ng. We found normalized read counts between all treatment groups to be in high agreement. Compared to the Illumina TruSeq stranded mRNA kit, both Swift RNA library kits offer shorter workflow times enabled by their patented Adaptase technology. We also found the Swift RNA kit to produce the fewest number of differentially expressed genes and pathways directly attributable to input mRNA amount. Some of these methods were found to perform relatively poorly across several metrics when compared to the Illumina TruSeq kit de facto standard, while others were typically expensive or incompatible with automation, and thus not ideal for high throughput experiments designed for gene target validation or compound screening efforts.RNA sequencing (RNA-seq) is a common technology to profile the transcriptome of cells and observe gene expression variation in both natural and perturbed conditions. Typical experiments require the isolation of RNA from samples under study and the preparation of cDNA libraries, followed by sequencing and bioinformatic analysis. The choice of the RNA-seq library preparation method is dictated by several factors, such as cost, RNA quality, and RNA input amount. Low cost methods suitable for low input RNA amounts are of particular interest, as cost and material are two key limiting factors in high throughput gene expression experiments. Several studies have focused on bulk RNA-seq library preparation methods for low RNA inputs6 to ensure high coverage across the transcriptome and avoid bias towards any subset of genes. All three library preparation methods can be automated in order to increase productivity, ensure greater reproducibility, and minimize human error.Here we compare three different bulk RNA-seq library preparation methods, aiming to understand differences in both absolute and differential gene expression. We selected two recently developed methods, the Swift and the Swift Rapid library preparation methods, as well as the de facto standard, the Illumina TruSeq method, as a reference for comparison Table . The SwiAs bulk RNA-seq library preparation methods are known to be sensitive to RNA input amount, in this study we tested the three different methods with varying input amounts of RNA. While RNA is typically abundant in in vivo experiments, many human stem cell model systems that are used to mimic disease progression in human patients produce limited amounts of RNA. Therefore, methods capable of producing high quality libraries from small amounts of RNA (< 100 ng) are especially valuable.7. Newer generation RNA-seq methods however do retain strand information, thereby resolving read ambiguity in overlapping genes and producing more accurate and higher quality transcriptomic data9. Strand specificity is incorporated into these RNA-seq protocols by (i) ligation of 3′ pre-adenylated and 5′ adapters, (ii) labeling of the second strand with dUTP followed by enzymatic degradation, (iii) template-switch attachment of the 3′ adapter (the Peregrine method), or (iv) Breath Adapter Directional Sequencing (BrAD-seq)8. All three RNA-seq methods used in this study are strand-specific. While Illumina TruSeq library kit uses dUTP labeling to degrade the second strand, Swift and Swift Rapid RNA kits maintain strand-specificity by making only one functional strand which is immediately ligated with a 3’ truncated adapter.An additional consideration in library preparation is strand specificity. The human genome comprises several overlapping genomic loci that are transcribed from opposite strands and encode distinct genes with different functions . As such, the ability to distinguish which strand is expressed in a sample is of crucial interest. A serious shortcoming of the first generation RNA-seq protocols was that they did not retain strand specificity, making it challenging to quantify gene expression levels for overlapping genes10. These RNA subtypes can be isolated and enriched from total cellular RNA using protocols such as the oligo (dT) selection method to select for polyadenylated mRNA transcripts, ribodepletion protocols to remove ribosomal RNAs, or size selection to isolate small ncRNA. Ribodepletion is an ideal method to isolate low RIN (RNA Integrity Number) mRNA from degraded low-quality biological samples. Since in our experiments, we were interested in mRNA quantification and the input UHRR was verified to be high quality with RIN greater than 9.0, oligo (dT) selection was used for all three kits. For the Illumina TruSeq library prep, mRNA was isolated from total RNA as per the protocol guidelines, whereas for the Swift and Swift Rapid RNA library prep methods, an upstream NEBNext oligo (dT) selection module was used to isolate mRNA from total RNA.A crucial step in library preparation for typical RNA-seq experiments is the enrichment of mRNA. The mammalian transcriptome comprises multiple types of coding and non-coding (nc) RNA species, including small (micro) and long ncRNA, ribosomal RNA (rRNA), and messenger RNA (mRNA). While most RNA-seq experiments entail isolation of mRNA species, small and long ncRNAs which lack protein-coding potential have emerged as important regulators of gene expression networks11. This workflow takes 9 h. The Swift and Swift Rapid RNA library preparation methods, on the other hand, employ proprietary Adaptase technology12  that reduces the library preparation time to 4.5 h and 3.5 h, respectively  inserts are then adenylated. This is followed by adapter ligation and finally enrichment of DNA fragmentsIn our work, the final libraries prepared using the Illumina, Swift, and Swift Rapid workflows were sequenced at an average read depth of 20 million reads per library “”. These Swift RNA kit: 10, 50, and 100 ngSwift Rapid RNA kit: 50, 100, and 200 ngIllumina TruSeq Stranded mRNA kit: 50, 100, 200, and 500 ngWe selected three library preparation methods for comparison, the Swift RNA Library Prep, Swift Rapid RNA Library Prep, and Illumina TruSeq Stranded mRNA Library Prep. UHRR, a pool of equal quantities of RNA prepared from 10 different cancer cell lines, was used as input RNA. To ensure a fair comparison applicable to common laboratory settings, we prepared multiple libraries with input amounts of total RNA in ranges recommended by the manufacturer Table . In brieEach of these 10 groups was tested in replicates of 5 samples each, for a total of 50 samples. We found all three workflows produced high quality libraries at each input amount Fig. . After s13 showed high mapping efficiency, with greater than 80% of reads uniquely mapped to genes  genes having several splice variants could have different expression levels, (ii) duplicative regions (including pseudogenes) may complicate read alignments, and (iii) lower expression of upstream exons due to imperfect reverse transcription resulting in partial cDNA moleculesWe looked at the normalized expression of these housekeeping genes and found good agreement between the three kits and also across different input amounts from the same kits with few minor variations  yielded 10 curated signaling pathways20 18, we computed the average fold change of the genes in each of 186 KEGG pathways for each of the input amounts in each library prep method 2 fold change of approximately 0.15, corresponding to a change of + 11% for the KEGG Ribosome pathway. The Swift RNA and Swift Rapid RNA kits produced similar results, but with fewer differentially expressed pathways . Interestingly, both the KEGG lysosomal and spliceosomal pathways were significantly perturbed in the Swift kits, while many pathways commonly studied in neuroscience  were similarly perturbed in the Illumina TruSeq data. These results suggest that domain specific biases may exist for each library preparation method, and accurate measurement of neuroscience pathways may depend on input RNA amount. However, such biases can be avoided by increasing the amount of input mRNA or, when limited by input material, focusing attention on only those pathways with large fold change (absolute log2 fold change > 0.15).We found all methods performed well. For instance, at a significance level of 0.01 (adjusted for multiple pathway testing), the Illumina TruSeq kit produced 17 differentially expressed pathways, with a maximum logRNA sequencing is a powerful technology commonly used in fundamental biological research as well as clinical applications. High throughput RNA-seq experiments offer a unique opportunity to understand how diverse chemical and genetic perturbations affect the transcriptome. One limitation in performing these experiments is the preparation of cDNA libraries, which remains expensive and labor-intensive and often requires substantial amounts of RNA.2 show that the SMARTer kit, used in combination with ribodepletion kits, had decreased performance for the inputs of 100 and 10 ng on multiple metrics as compared to the TruSeq kits. Furthermore, when associated with the RiboZero step for ribodepletion, the method is rendered incompatible for automation. In contrast, the SMARTer Ultra-Low kit performed relatively well for ultra-low inputs < 1 ng and is automation-compatible; however, it is associated with higher per sample cost (currently about $100 per sample). Other RNA-seq library preparation methods evaluated for strand specificity and lower input compared the TruSeq kit include the Takara Bio SMART-Seq v4 Ultra Low Input RNA kit (V4) which sacrifices strand specificity, and the SMARTer Stranded Total RNA-Seq Kit v2—Pico Input (Pico) kit3. Although the Pico kit retains strand specificity and has good concordance with the TruSeq kit, libraries generated using the Pico kit showed 55% fewer differentially expressed genes3. Comparative analysis of the earlier-generation Ovation RNA-seq system with the Illumina TruSeq kits revealed that the kit performed well with almost equal gene representation for low inputs ranging from 500 pg–10 ng total RNA, however, these libraries exhibited a platform-specific 5’ or 3’ bias4. While the newer generation NuGen Ovation low input kits have reduced positional bias, they lack strand specificity1.Several low input RNA kits have been compared to the TruSeq mRNA kits, considered to be the gold standard for RNA-seq studies. Systematic analysis of TruSeq SMARTer and SMARTer Ultra-Low RNA-seq kitsIn this work, we have systematically compared three methods—Swift RNA, Swift Rapid RNA and Illumina TruSeq stranded mRNA kits—for developing libraries, focusing on the ease of the workflow, its promise for automation, and the accuracy of resulting bioinformatic analyses. The Swift RNA library kit accommodates a broader input range and offers consistent and reliable results across diverse samples. This is achieved through the use of the patented Adaptase technology which allows sequential adapter ligation and helps avoid adapter titration across inputs. This maintains uniform adapter concentrations at all inputs. Additionally, Adaptase performs simultaneous tailing and ligation of NGS adapters to ssDNA. Adaptase also allows for DNA inputs as low as a single cell and its high efficiency template-independent chemistry provides comprehensive coverage with minimal base composition bias. This technology supports a broad input range down to 10 ng total RNA. Consistent performance from damaged samples such as FFPE RNA has also been reported.The differences in workflow time across the Illumina and Swift kits are attributed to different kit chemistries. In the Illumina TruSeq Stranded mRNA kit, strand specificity is enforced by replacing dTTP with dUTP, followed by second strand cDNA synthesis using DNA Polymerase I and RNase H. This method works by employing Uracil-DNA-Glycosylase to excise the newly incorporated uracil base on the second strand, thus blocking this strand from being used as a template in PCR. On the other hand, the faster workflow for the Swift kits is facilitated by the proprietary Adaptase technology which supports library preparation from first strand cDNA, thereby eliminating the need for second strand synthesis. Furthermore, the Swift RNA workflow is also compatible with low quality, low RIN FFPE samples. While the Swift Rapid RNA method is the fastest workflow, it is best suited for samples with ample RNA yields.All methods we examined here produced high quality libraries, as measured by sequencing and alignment metrics. Further, quantified gene counts produced by these methods were in substantial agreement. However, these methods differed in their sensitivity to input RNA amount. Using the manufacturer-recommended RNA input amount as a reference, we assessed the accuracy of differentially expressed genes at 50 ng, a yield reasonably produced for instance by in vitro stem cell models. We found the Swift RNA kit to produce the fewest “false positives”, genes differentially expressed due to technical considerations only, at typical levels of significance used in such analyses. Interestingly, the dependency of differential expression of genes and pathways on input amount differed between the kits we considered. The Swift RNA kit produced the fewest number of differentially expressed KEGG pathways with respect to input amount. Our study suggests that to avoid conclusions based on technical artifacts, researchers should focus on changes in expression of pathways of at least 10%. Furthermore, as KEGG pathways are commonly used in genomics studies as a reference to annotate gene sets, understanding the mechanism by which these biases originate would be a valuable endeavor for future work.SPRIselect beads from Beckman Coulter (B23318) were used for all magnetic bead DNA clean up steps. Universal Human Reference RNA (UHRR)  was diluted to 100 ng/ul with low TE buffer, aliquoted, and stored at − 80 °C.Swift RNA library prep. : 100, 50, and 10 ng of UHRR was used as direct input for NEBNext Poly(A) mRNA Magnetic Isolation Module . In the final elution step, mRNA was eluted off the beads into the IDT xGen Broad-range RNA Library Kit Fragmentation Buffer. Libraries were prepared and indexed  using Swift recommended protocol. cDNA libraries were diluted 1:5 in low TE buffer and analyzed on Agilent 4200 TapeStation using D5000 HS DNA screentape. Libraries that gave yields < 4 nM were amplified using the IDT Library Amplification Primer Mix (Cat. No. 10009867).Swift Rapid RNA library prep. : 200, 100 and 50 ng of UHRR was used as direct input for NEBNext Poly(A) mRNA Magnetic Isolation Module . In the final elution step, mRNA was eluted off the beads into the IDT xGen RNA Library Kit Fragmentation Buffer. Libraries were prepared and indexed  using Swift recommended protocol. cDNA libraries were diluted 1:1 in low TE buffer and analyzed on Agilent 4200 TapeStation using D5000 DNA screentape.Illumina TruSeq stranded mRNA library Prep. : 500, 200, 100 and 50 ng of UHRR was used as direct input for the Illumina TruSeq Stranded mRNA (20020594). Libraries were prepared and indexed  as outlined in the TruSeq Stranded mRNA Reference Guide.N = 3 technical replicates per sample. The standard curve generated using the six pre-diluted DNA standards is used to convert the average Cq value for diluted libraries to concentration, from which the working concentration of each library is calculated.Final libraries were diluted in low TE buffer and analyzed on the Agilent 4200 TapeStation using D5000 or D1000 DNA screentape. Library quantification was performed using KAPA qPCR. Six serially pre-diluted DNA standards and 1:10,000 or 1:20,000 diluted NGS libraries were amplified using platform-specific qPCR primers that target adapter sequences as per manufacturer’s instructions using Prepared libraries were pooled at 10 nM concentration each and sequenced using the NovaSeq SP sequencer , with a 2 × 100 bp paired-end read length and an average read depth of 20 million read pairs per library. Sequencing was performed at Seqmatic LLC .22. Subsampled reads were aligned with STAR version 2.7.2 to the reference genome GRCh38 with Ensembl gene annotations19 and the flags --outSAMtype BAM SortedByCoordinate --quantMode GeneCounts. We required genes to have a minimum 3 counts per million in at least 20% of samples. Genes not satisfying this requirement were removed. After filtering, approximately 12,000 genes remained. To compare absolute gene expression, reads were normalized via the regularized log transform20.10 million read pairs for each library were randomly sampled without replacement to account for differences in sequencing depth using the open-source software seqtkCounts ~ Treatment group. Log2 fold changes and significance were computed with the R software package DESeq220. p values were adjusted for multiple hypothesis testing by the Benjamini–Hochberg method21.Each of these sample groups was compared to the reference as specified in the main text using the linear model 17 (file name: c2.cp.kegg.v7.1.entrez.gmt). The statistical test for enrichment of these pathways among differentially expressed genes is due to Leeman et al.18. In this method, the test statistic for a gene set is the average t-statistic from DESeq2 of all genes in the set, and a permutation test is used to approximate the distribution of this test statistic. The null hypothesis for this test is that the genes in a given gene set show the same pattern of association with the phenotype compared with the rest of the genes. p values were adjusted for multiple hypothesis testing by the Benjamini–Hochberg method21.To test for pathway enrichment among differentially expressed genes, we collected a set of gene pathways curated by KEGG and available from MSigDBSupplementary Information.


Circulating extracellular RNAs (exRNAs) have great potential to serve as biomarkers for a wide range of diagnostic, therapeutic, and prognostic applications. So far, knowledge of the difference among different sources of exRNAs is limited. To address this issue, we performed a sequential physical and biochemical precipitation to collect four fractions  from each of 10 plasma samples. From total RNAs of the 40 fractions, we prepared ligation-free libraries to profile full spectrum of all RNA species, without size selection and rRNA reduction. Due to complicated RNA composition in these libraries, we utilized a successive stepwise alignment strategy to map the RNA sequences to different RNA categories, including miRNAs, piwi-interacting RNAs, tRNAs, rRNAs, lincRNAs, snoRNAs, snRNAs, other ncRNAs, protein coding RNAs, and circRNAs. Our data showed that each plasma fraction had its own unique distribution of RNA species. Hierarchical cluster analyses using transcript abundance demonstrated similarities in the same plasma fraction and significant differences between different fractions. In addition, we observed various unique transcripts, and novel predicted miRNAs among these plasma fractions. These results demonstrate that the distribution of RNA species and functional RNA transcripts is plasma fraction-dependent. Appropriate plasma preparation and thorough inspection of different plasma fractions are necessary for an exRNA-based biomarker study. Extracellular RNA (exRNA) profiling is a promising tool to recapitulate gene expression changes that result from disease-specific alterations. Previous studies have shown that exRNAs may be used as biomarkers for monitoring dynamic changes of disease status  and for Plasma is commonly used in clinical practice. Due to its complex compositions, plasma is also commonly used for biomarker discovery. Plasma is isolated from blood centrifuged at low speed. Although most red blood cells and mononuclear cells are effectively removed, a significant amount of cell debris and platelets remain after centrifugation. To isolate EVs in plasma, differential ultracentrifugation has been adopted . This deIn this study, we used a ligation-free RNA library preparation method and directly performed a sequencing analysis of the entire library, without size selection. We evaluated exRNA profile differences and identified unique features among different plasma fractions. We found that each plasma fraction had its own unique RNA composition as well as distribution of RNA species. The enrichment of specific RNA molecules or RNA species further emphasizes importance of quantifying full spectrum RNAs in each plasma fraction, since low abundance of biomarkers are often masked by the other components in the plasma . The prog for 10 min at room temperature and stored at –80°C until use. The use of the human biospecimens was approved by the Institutional Review Board of the Medical College of Wisconsin and H. Lee Moffitt Cancer Center and Research Institute. Hematology analyses were performed to test the plasma component .The objective of this study was to explore the potential differences of the RNA profiles in different plasma fractions. To accomplish this goal, 10 plasma samples  were colg at 4°C for 10 min to precipitate cell debris and platelets. The supernatant was transferred to a new tube, and the leftover pellet (platelets and cell debris fraction or the Precipitate 1) was mixed with QIAzol lysis buffer  for RNA extraction. 1/100 volume of thrombin  was added to the supernatant, which was then incubated at room temperature for 5 min and spun at 11,000g for 5 min at 4°C. After transferring the supernatant to a new tube, the pellet (the thrombin-treated fraction or the Precipitate 2) was mixed with QIAzol lysis buffer for RNA extraction. The supernatant was then mixed with 1/4 volume of Exoquick reagent (SBI), incubated at 4°C for 1 h, and then centrifuged at 1,500 g at 4°C for 30 min. After aliquoting the supernatant to a new tube, the pellet was suspended in 100 μl 1× phosphate buffer saline. QIAzol lysis buffer was added to the suspended pellet fraction (EV Precipitate) and a final supernatant fraction (leftover), separately. RNA isolation was performed as per the manufacturer’s standard protocol. DNase I was used to remove any residue DNA on the column before RNA elution. The extracted RNA was eluted in 14 μl of RNase-free water and stored at −80°C until use.Two hundred microliter of plasma of each sample was thawed from −80 to 4°C, and 100 U of RNA inhibitor  was added to the plasma sample before centrifugation. Samples were first centrifuged at 500 A nanoflow ultra-high performance liquid chromatograph  coupled to an electrospray bench top orbitrap mass spectrometer  was used for tandem mass spectrometry peptide sequencing experiments following a standard protocol. MaxQuant software was used to identify and quantify the proteins. This work was conducted by the Proteomics and Metabolomics Core Facility at the H. Lee Moffitt Cancer Center & Research Institute.Library preparation was performed using the CATS (Capture and Amplification by Tailing and Switching) kit  per manufacturer’s instructions. The ligation-free library preparation kit has been reported to reduce ligation bias and adaptor dimers . Eight mInitial quality check of the sequencing data (FASTQ files) was done with FastQC . Cutadapt (version 2.3.1) was used to trim the FASTQ files for removal of 5′-GGG, 3′ Poly(A) tails and 3′-adaptor sequences. Sequences of <16 bases were also discarded. DNASTAR Lasergene 15.3  was used for mapping. DESeq2 R package (version 1.26.0) was applied for data normalization.To comprehensively evaluate RNA profiles, we adopted a stepwise alignment strategy. For each new RNA species, unmapped sequence reads from the previous step were used. The order of mapping was miRNAs, piRNAs, tRNAs, ncRNAs, protein-coding RNAs, circRNAs, rRNAs, and genome reference. The miRNA databases (release 22.1) were downloaded from miRBase, piRNAs from piRNA Quest, tRNAs from gtRNAdb, and circRNAs from cirBase. The lincRNAs, snoRNAs, and snRNAs came from the GRCh38 ncRNA release 96. For protein-coding mRNA and other RNA types, sequence reads were mapped to the Gencode version 24. rRNA mapping was based on both of the GRCh38 ncRNA and 45S, 5S, and mt-rRNA sequences.Prior to comparative analysis among different fractions, we performed sample-level quality control using Principal Component Analysis (PCA). Samples with <1 million mapped reads were excluded. Outliers identified by the PCA were excluded from further analysis. Overall clustering and distribution of categorized RNA profiles through t-SNE plots were done by using Rtsne package (version 0.15). Heatmap visualization was generated by pheatmap package (version 1.0.12). Gene ontology (GO) analysis was performed with clusterProfiler package (version 3.14.3). After mapping to known RNA databases, unmapped reads were used for novel miRNA prediction by miRDeep2 package (version 2.0.1.2). The newly identified RNAs were validated by comparing to a small RNA sequencing database  v2.0 .p value <0.05 was considered significant. To correct for multiple testing, false discovery rate (FDR) was applied. FDR < 0.05 was defined as statistical significance.Statistical analyses of the fraction-specific transcript differences were performed using one-way ANOVA. If the data failed the Levene’s test for homogeneity of variances, Kruskal-Wallis test was applied. A To evaluate exRNA profiles in different plasma fractions, we performed sequential physical precipitation (centrifugation) and chemical precipitation (Thrombin and Exoquick exosome precipitation solution treatment) . The Pre3/mm3 in the initial plasma samples; the platelets were highly enriched in Precipitate 1 (391 PLT 103/mm3) and significantly deprived in the supernatant after first centrifugation (6 PLT 103/mm3) , most often used as specific exosome markers, were detected in EV Precipitate only. RNA binding proteins (Annexin A2 and trafficking/sorting associated proteins RAB1B) were also enriched in EV Precipitate while Lipoprotein particles such as ApoAI and ApoB100 were highly abundant in all plasma fractions . To conf103/mm3) .For each fraction of the 10 plasma samples, we made a separate sequencing library for a total of 40 libraries, and screened all raw reads with MultiQC . After tSeC). EV Precipitate had an average read count of 651.2 for tRNA: SeC-TCA-1-1—the highest among all four fractions. However, leftover fraction did not have any read count for this tRNA. The EV precipitate had the largest number of miRNA count and smallest deviation, which met our expectation. For piRNAs and circRNAs, the proportion of their transcripts to the total number of detected transcripts in the corresponding reference database was 14.0 and 9.2%, respectively , representing transcripts from all 11 categories . We alsop < 0.01)  .After mapping all sequence reads to known transcript databases, we examined the remaining reads to determine whether they contained any novel miRNAs. We applied miRDeep2 package and identified a total of 951 novel miRNAs, among which the Precipitate 2 showed the largest number of the predicted novel miRNAs (39.6 on average), whereas the Precipitate 1 had the largest number of total read count mapping to the novel miRNAs  . Interesin silico validation of these newly identified miRNAs using the DASHR 2.0 database and observed high-expression levels in these predicted miRNAs in the small RNA sequencing database  family that participates in the assembly of complexes on the inner surface of the plasma membrane at regions of cell-cell contact, and also plays a role in tight junction  can be found below: The studies involving human participants were reviewed and approved by Institutional Review Board of the Medical College of Wisconsin and Institutional Review Board of Moffitt Cancer Center. The patients/participants provided their written informed consent to participate in this study.LW, JJ, and HZ conceived the presented idea. JJ and JH performed the experiments and primary data analysis. SY verified the analytical work. JJ wrote the manuscript with support from HZ, YH, and LW. LW supervised the project. All authors discussed the results and contributed to the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Escherichia coli RNAP. Here we used Salinamide A, that we found inhibits RNAP catalytic domain Trigger Loop (TL), to show that the TL is required for RNA cleavage during proofreading of misincorporation events but plays little role during cleavage in sequence-dependent backtracked complexes. Results reveal that backtracking caused by misincorporation is distinct from sequence-dependent backtracking, resulting in different conformations of the 3′ end of RNA within the active center. We show that the TL is required to transfer the 3′ end of misincorporated transcript from cleavage-inefficient ‘misincorporation site’ into the cleavage-efficient ‘backtracked site’, where hydrolysis takes place via transcript-assisted catalysis and is largely independent of the TL. These findings resolve the controversy surrounding mechanism of RNA hydrolysis by E. coli RNA polymerase and indicate that the TL role in RNA cleavage has diverged among bacteria.Transcribing RNA polymerase (RNAP) can fall into backtracking, phenomenon when the 3′ end of the transcript disengages from the template DNA. Backtracking is caused by sequences of the nucleic acids or by misincorporation of erroneous nucleotides. To resume productive elongation backtracked complexes have to be resolved through hydrolysis of RNA. There is currently no consensus on the mechanism of catalysis of this reaction by  Transcription by multi-subunit DNA-dependent RNA polymerase (RNAP) can be interrupted by backtracking of RNAP, a phenomenon when the 3′ end of RNA disengages from the template DNA and active center and RNAP shifts backward along the template . BacktraDisengagement of the 3′ end of the transcript from the active site renders the complexes incompetent in NTP addition and thus causes a strong pause of transcription. Backtracking, if not resolved, frequently represents a dead-end event  and may 2+ ions of the active center that participate in RNA synthesis and is assisted by the flipped out 3′ end nucleotide of the transcript  (E. coli numbering)  and by orienting the RNA 3′ NMP for transcript-assisted hydrolysis (T. aquaticus RNAP led to >200-fold decrease in the rate of the reaction in either correct or misincorporated ECs (RNA hydrolysis by oop (TL) , the catoop (TL) . The TL oop (TL) . During mbering) . During drolysis . Mutatioated ECs .E. coli RNAP turned out to be controversial. Our results indicated that H936A substitution in the TL of E. coli RNAP significantly (>30-fold) slows down proofreading in ECs that are stabilized in 1 or 2 bp backtracked states after misincorporation of erroneous NMPs , the TL played little role in RNA hydrolysis (∼3 fold decrease in the rate of cleavage by H936Q mutant RNAP)  . This stE. coli RNAP holoenzyme in complex with SAL showed that SAL makes direct interactions with bridge-helix ‘cap’  , the most extensively studied molecule of structurally related antibiotics salinamides, selectively inhibits bacterial RNAP. The crystal structure of  region) . The autE. coli backtracked complexes, one efficient in RNA cleavage and another one not. The TL is required to convert the cleavage-inefficient into cleavage-efficient type of backtracked EC.Here, we show that SAL inhibits functions of the TL, and, using it as a molecular tool, demonstrate the existence of two distinct types of Streptomyces sp. CNB091 was cultivated in shake flasks for 8 days at 30°C in 10 L of sea water-based media 3, 100 mg/l KBr; all dissolved in sea water). The cell mass was removed by centrifugation and supernatant subjected to 20 g of Amberlite XAD-16 resin (Sigma-Aldrich) pre-washed with deionized water. The material was eluted from the beads with 1 L of methanol. The extract was concentrated to aqueous residue in vacuo and the pH was adjusted to 7. Organic extraction was performed with ethyl acetate at equal volume followed by evaporation of organic phase to dryness under reduced pressure. The dried extract was dissolved in 2 ml 10% aqueous acetonitrile and subjected to a HyperSep™ C8 cartridge (Thermo Scientific) using a vacuum manifold (Thames Restek). SAL was eluted from the cartridge by 60% aqueous acetonitrile. The solvent was removed under reduced pressure; the material was dissolved in 20% aqueous acetonitrile and separated on C18 column  in acetonitrile gradient. SAL containing fractions were evaporated under reduced pressure yielding 12 mg of SAL which was dissolved in 1 ml of methanol and stored at -20°C. For transcription reactions SAL was diluted in water.Escherichia coli RNAP lacking the TL was constructed by substituting residues 931-1135 with Gly in the overexpression plasmid pVS14  using Hescribed , except 1 was 5′ radiolabeled by T4 Polynucleotide Kinase and γ-[32P]-ATP prior to complex assembly, as described  and 2 h (ΔTL), respectively, for IC50 determination. RNA in misECs and backEC was radiolabeled by incorporation of α-[32P]-NMP  during walking of EC (see schemes in figures). The backEC3′A was obtained by supplying EC132 with 1 μM α-[32P]-CTP (3000mCi/mmol) and 10 μM ATP in the presence of 10 mM Mg2+ at 37°C for 15 min. To obtain misincorporated ECs (misEC3′A and misEC3′U), corresponding EC13s were supplied with 1 μM α-[32P]-GTP (3000 mCi/mmol) and 1 mM (WT RNAP) or 10 mM (ΔTL RNAP) ATP or UTP. Reactions were initiated by addition of 10 mM Mg2+ for WT RNAP or 10 mM Mg2+/Mn2+ mixture for ΔTL RNAP and were carried out at 37°C for times indicated in Figure 2+ were removed through washing with TB. 100 μg/ml SAL was added prior the cleavage reactions and they were activated with 10 mM Mg2+ at 37°C. The reactions were stopped after times indicated by addition of an equal volume of formamide-containing loading buffer. Products were resolved on 23% (20:3) denaturing polyacrylamide gel containing 8 M urea, revealed by PhosphorImaging (Cytiva) and analyzed using the ImageQuant software (Cytiva). Kinetic data were fitted using nonlinear regression in SigmaPlot. All experiments were repeated at least three times.ECs were assembled in 15 μl total volume. One pmol of template DNA (IDT) was incubated with 2 pmol of RNA (IDT) for 5 min at 45°C in transcription buffer , followed by cooling down at 4°C for 20 min. One pmol of WT or mutant RNAP was added and incubated at room temperature for 10 min. The complexes were then incubated with 10 pmols of non-template DNA bearing a 5′biotin tag for 5 mins at 37°C. The complexes were then immobilized on 5 μl of streptavidin beads slurry and washed first with TB containing high salt (1 M KCl) and then with TB. For Figure escribed . SAL andescribed ,C were tE. coli RNAP lacking the entire TL . Transcription elongation complexes were assembled with fully complementary template and non-template DNA strands, 13 nucleotide-long synthetic RNA   has not yet become significant. Also, as can be seen, WT RNAP managed to processively pyrophosphorolyze to EC81, while in the presence of SAL processive pyrophosphorolysis further than EC121 was completely blocked. Although ΔTL RNAP failed to perform processive pyrophosphorolysis beyond EC121, SAL had only little effect even on the rate of pyrophosphorolysis in EC131  ,22. SAL  (EC131) . As seenE. coli RNAP and this inhibition is linked to the functions of the TL. Taken together with the structural prediction  would be separated from bands of misEC3′A and GA, and would not affect quantification. Accordingly, during quantification we used only bands of misEC3′A and GA , suggesting the involvement of the TL in the reaction  is 10 times faster than reaction assisted by 3′UMP (misEC3′U) . This further supports the idea that the conformation of the 3′NMP of RNA (or other components of the active site that may be involved in transcript-assisted hydrolysis) is somewhat different in misEC3′A and backEC3′A, and SAL interferes with it only in the backEC3′A.Importantly, the rates of the reaction by WT RNAP in misECE. coli RNAP active center. Escherichia coli RNAP was shown to require the TL during RNA hydrolysis in misincorporated ECs  would clash with the folded TL, leading to a conclusion that the TL is not involved in RNA hydrolysis  may not be valid. Indeed, while RNA cleavage in correct 2 bp backtracked EC was almost independent of the TL , cleavagdrolysis . Howeverdrolysis .E. coli, the TL participates in conformational transition between two types of backtracked complexes thus activating hydrolysis, but plays modest role in the catalysis per se. In T. aquaticus, the TL orients 3′NMP, this time in any type of backtracked complexes but also directly participates in general acid-base catalysis (Transcript-assisted hydrolysis of phosphodiester bonds of the transcript appears to be conserved at least among bacteria and eukaryotes ,11,24, patalysis  and highatalysis . Interesatalysis .E. coli RNAP holoenzyme in complex with SAL, SAL was proposed to inhibit NMP incorporation by blocking dynamics of the Bridge Helix that was earlier suggested to be essential for the reaction (et al., (Another main finding of our study is the determination of the mode of action of antibiotic SAL. Based on the crystal structure of reaction . Our resreaction . We did (et al., , who obs(et al., , compare(et al., . Lack of


This makes such transporters valuable both as a means of targeting drugs (not least anti-infectives) to selected cells or tissues and also as drug targets. The same considerations apply to the exploitation of substrate uptake and product efflux transporters in biotechnology. We are also beginning to recognise that transporters are more promiscuous, and antiporter activity is much more widespread, than had been realised, and that such processes are adaptive . The purpose of the present review is to summarise the above, and to rehearse and update readers on recent developments. These developments lead us to retain and indeed to strengthen our contention that for transmembrane pharmaceutical drug transport “phospholipid bilayer transport is negligible”.Over the years, my colleagues and I have come to realise that the likelihood of pharmaceutical drugs being able to diffuse through whatever unhindered phospholipid bilayer may exist in intact biological membranes in vivo is vanishingly low. This is because (i) most real biomembranes are mostly protein, not lipid, (ii) unlike purely lipid bilayers that can form transient  This is the problem of de-orphanisation ,108,109.https://re-solute.eu/), the CEMM group studied 60 cytotoxic compounds. By using an SLC-focused CRISPR-Cas9 library, they identified a series of transporters whose absence induced resistance to the drugs tested );The poor correlation between the uptake of small molecules and simple physicochemical properties such as log P or log D The recognition that in real biological membranes the transbilayer transport through phospholipids of small molecule drugs, nutrients, and biotechnology products is negligible also explains straightforwardly the following well-established facts:de novo. In addition, given the success of so-called deep learning [The two chief questions posed earlier (“what are the substrates for a given trasporter?” and “what are the transporters for a given substrate?”) are normally addressed experimentally, using a variety of the methods described above. As intimated above, the exponential increase in computer power will eventually allow the methods of molecular dynamics to admit these “measurements” entirely by calculations based on simple force fields, learning ,629,630 learning ,644,645,learning ,649,650,learning ,664,665)On the basis of the present evidence, the transport of drugs and nutrients through phospholipid bilayers in real biomembranes is negligible. Progress in understanding drug distribution profiles is thus to be made by establishing which transporters they use, the expression profiles of those transporters, and the kinetic rate equations that they obey. Armed with these it will be possible to model, to analyse, to understand, and to exploit our principled knowledge of drug distributions both mechanistically and with confidence.


Zea mays L.). Here, we cloned and analyzed the function of a P-subfamily PPR protein, PPR278. Loss-function of PPR278 led to a lower germination rate and other defects at the seedling stage, as well as smaller kernels compared to the wild type. PPR278 was expressed in all investigated tissues. Furthermore, we determined that PPR278 is involved in the splicing of two mitochondrial transcripts (nad2 intron 4 and nad5 introns 1 and 4), as well as RNA editing of C-to-U sites in 10 mitochondrial transcripts. PPR278 localized to the nucleus, implying that it may function as a transcriptional regulator during seed development. Our data indicate that PPR278 is involved in maize seed development via intron splicing and RNA editing in mitochondria and has potential regulatory roles in the nucleus.Pentatricopeptide repeat (PPR) proteins are a large protein family in higher plants and play important roles during seed development. Most reported PPR proteins function in mitochondria. However, some PPR proteins localize to more than one organelle; functional characterization of these proteins remains limited in maize ( Zea mays L.) [Oryza sativa L.), and Arabidopsis thaliana L., and functional analysis revealed that they could bind RNA and might play important roles in RNA metabolism, including RNA splicing and editing, cleavage, and maturation [Pentatricopeptide repeat (PPR) proteins are widely distributed in plants, with more than 400 members in maize (mays L.) , which wmays L.) ,3. PLS-smays L.) . PPR pronad1, 2, 4, 5, 7), and subunits of a complex involved in the biogenesis of cytochrome c: subunits F (CccmF), cytochrome c oxidase subunits2 (cox2), and ribosomal protein s3 (rps3) [nad1 introns 1, 3, and 4; nad2 intron 2; and nad5 introns 2 and 3 are post-transcriptionally modified via trans-splicing, while other introns of target spliced transcripts are modified through cis-splicing [Ongoing work has shown that PPR proteins splice 22 group II introns present within 8 protein-coding genes in mitochondria in maize, including NADH dehydrogenase subunits1, 2, 4, 5, and 7 (3 (rps3) ,7,8. Amosplicing . Loss-fusplicing ,24,25,26Empty pericarp 5 (EMP5), EMP7, EMP9, EMP18, EMP21, Defective kernel 10 (DEK10), DEK36, DEK39, PPR2263, Small kernel 1 (SMK1), SMK4, and SMK6 significantly altered the C-to-U editing efficiency in mitochondrial RNAs, leading to small or defective kernels [Cytidine-to-uridine (C-to-U) RNA editing in mitochondria is an important function of PPR proteins and is required for correcting mutations at the RNA level by recognizing specific transcripts through tandem repeat motifs ,28. The  kernels ,39,40,41Arabidopsis genome are predicted to localize in mitochondria and/or plastids, and very few localize in both nuclei and mitochondria [More than 99% of PPR proteins across the chondria ,5,42. SUchondria ,44,45. Ichondria ,47. Furtchondria . Thus, fnad2 and nad5 introns and C-to-U editing of 10 mitochondrial transcripts were affected in the ppr278 mutants. RNA-sequencing (RNA-seq) analysis revealed that the expression of nucleus-encoded genes associated with RNA splicing and editing was significantly altered in the ppr278 mutants. Our findings demonstrate that PPR278 affects seed development via effects on RNA intron splicing and editing in mitochondria and on gene expression in nuclei, expanding our limited knowledge about the function of P-subfamily PPR proteins that are capable of splicing introns.In this study, we isolated PPR278, a P-subfamily PPR protein with dual localization in nuclei and cytoplasm of maize. We discovered that splicing of ppr278-1 based on similar phenotypes with other ppr mutants in maize. Only ~5% of mutant kernels could germinate normally on average and grew to the seedling stage -based method, which produced smaller seeds compared to the wild type (WT) A–D, and ng stage . Howeverng stage . The 100rocesses F,G. The ve locus A,B. Zm00001d015156) (Zm00001d015156 (located on chromosome 5) that had the highest ΔSNP index among missense variants and the stop codon-gained variant [Zm00001d015156 as the candidate gene corresponding to PPR278. Sequence analysis revealed that Zm00001d015156 had one SNP (C-to-T mutation) in the ppr278-1 mutant. This SNP was located in the 15th exon at +2269 bp from the ATG start codon, causing a premature stop codon in Zm00001d015156  and observed that the SNP in the ppr278-1 mutant co-segregated with the low seed germination phenotype (ppr278-2) from the mutant libraries, which showed a similar phenotype as the ppr278-1 mutant  to isolate PPR278. Endosperm and embryos from M3 generation kernels at 12 days after pollination (DAP) were used to construct RNA-seq libraries of WT and mutant-type pools. High-quality single nucleotide polymorphism (SNP) markers were called by aligning RNA-seq reads to the B73 reference genome (V4). We identified 32 candidate genes including 14 missense variants, 10 synonymous variants, 5 3′ untranslated region (UTR) variants, 2 5′UTR variants, and 1 stop codon-gained variant (d015156) . Zm00001 variant ; therefo1d015156 A. To teshenotype . To furt1 mutant . We idenop codon A. Crossir PPR278 B. Expresr PPR278 D. Thus, https://www.ncbi.nlm.nih.gov/) (Accessed on 9 March 2022) or PPR energy (https://ppr.plantenergy.uwa.edu.au/) (Accessed on 9 March 2022) databases, and full-length protein sequences were used for phylogenetic analysis, in which PPR278 was clustered into the P-subfamily  (Accessed on 9 March 2022) and Cello (http://cello.life.nctu.edu.tw/) (Accessed on 9 March 2022), PPR278 was predicted to be in the nucleus and cytoplasm (Allium cepa L.) epidermal cells and maize protoplasts revealed that PPR278 targeted to both nuclei and cytoplasm, suggesting that the functions of PPR278 are more complex than those of other PPR proteins targeted to mitochondria or/and plastids  (Accessed on 9 March 2022)  C, which rps2A, nad5, NccmF, and apocytochrome b (cob), between ppr278-1 and WT plants (nad2 intron 4 (1383 bp) and nad5 introns 1 (870 bp) and 4 (952 bp) was affected in the ppr278-1 and ppr278-2 mutants , but it is also necessary for the cis-splicing of nad2 intron 4 and nad5 introns 1 and 4.PPR proteins are RNA-binding proteins involved in RNA metabolism, including intron splicing and RNA editing, in mitochondria and plastids . To testT plants A. Additi mutants . We deteT plants . PPR278 ppr278 mutants and identified 94 C-to-U RNA editing events %). The T/(T + C) ratio was reduced among all editing sites in atp8 and nad3 in the ppr278 mutant  (Accessed on 9 March 2022) to analyze the transmembrane domains of NccmF and determined that the lack of editing in NccmF disrupted the 1st, 4th, 5th, and 6th transmembrane domains in the ppr278 mutant  were identified as differentially expressed genes (DEGs). We identified 2466 DEGs between ppr278-1 and WT plants, including 1542 up-regulated DEGs and 924 down-regulated DEGs  (Accessed on 9 March 2022) analysis using the DEGs indicated that both down- and up-regulated DEGs were enriched in the term ‘post-embryonic development’ (GO: 0009791). The reason why this Go term was enriched might be interpreted as genes transcribed actively to regulate post-embryonic development rather than direct results of loss-function-of PPR278. The other down-regulated DEGs were mostly associated with energy-consuming processes, such as ‘metabolic process’, ‘nutrient reservoir activity’, ‘plant and seed development’, and ‘nucleosome assembly’ [ppr278-1 mutant is insufficient to maintain plant growth and seed development. The remaining up-regulated DEGs were closely related to ‘mitochondrial part’ (GO: 0044429), which is predicted to function in mitochondria. For example, ‘electron transport chain’ (GO:0022900), ‘mitochondrial respiratory chain complex Ⅰ’ (GO:0005747), ‘II’ (GO: 005749), and ‘III’ (GO:0005750), ‘ATP synthase activity’ , ‘mitochondrial respiratory chain complex assembly’ (GO:0033108), ‘precatalytic spliceosome’ (GO: 0071011), ‘U1 small nuclear ribonucleoprotein particle (snRNP)’(GO:0005685), ‘U2 snRNP’ (GO:0005686), ‘U4/U6×U5 tri-snRNP complex’ (GO:0046540), and ‘pre-catalytic spliceosome’ (GO:0071011)   were enrArabidopsis. For example, PPR596 influences editing efficiency at partial editing sites  in mitochondrial transcript rps3 and rps14, while another gene P-type protein, PPR-MODULATING EDITING (PPME), is responsible for C-to-U RNA editing at both sites nad1-898 and nad1-937 [nad2 intron 4 and nad5 introns 1 and 4. In addition, PPR278 was also recognized as an editing factor that is responsible for 94 sites of C-to-U RNA editing in mitochondrial transcripts.P-subfamily PPR proteins are generally involved in RNA splicing . Howevernad1-937 ,55. Herenad2 intron 4 and nad5 introns 1 and 4, which further highlights the role of P-subfamily PPR proteins in intron splicing. Multiple PPR proteins and other splicing factors may participate in splicing the same intron. For instance, nad2 intron 4 cis-splicing was also abnormal in emp16 and emp12 mutants in maize [nad5 introns 1 and 4 [nad5 intron 1 in maize. Thus, mutations in these PPR proteins affect the cis-splicing of mitochondrial nad5 introns [nad2 intron 1 [PPR278 is necessary for intron splicing of in maize ,17. ZmSM 1 and 4 . Further introns ,21,22. S introns ,14,15,16intron 1 ,56. ThesNccmF with 30 abolished C-to-U RNA editing sites in the ppr278 mutant  controlling mitochondrial RNA editing and splicing is essential for seed development in Arabidopsis [p and classification of PPR278 provide a plausible explanation for why PPR278 has both splicing and editing functions in mitochondria. Notably, no C-to-U editing sites were detected in nad2 and nad5 cDNA sequences in the ppr278 mutant, suggesting that nad2 intron 4 and nad5 introns 1 and 4 have no effect on the editing of the exon sequence. This implied that PPR278 might conduct C-to-U RNA editing and intron splicing independently [In general, P-subfamily members primarily function in splicing and PLS-subfamily members primarily function in editing. PPR278 is the first P-subfamily member determined to be involved in intron splicing of mitochondrial transcripts and C-to-U RNA editing in maize. However, several other PPR proteins act simultaneously as splicing and editing factors in plants. The E-type PPR protein DEK55 plays a crucial role in RNA editing at multiple sites as well as in the splicing of bidopsis ,16,19,59ppr278-1 mutant  and GO:function ,12,13,61gulation . This enZea mays L.) ppr278-1 and ppr278-2 mutants were obtained from our EMS-based mutant library. In brief, the mature pollen of inbred line B73 was treated with 0.015% ethyl methanesulfonate solution (vol/vol) in a 1:10 pollen:solution ratio for 30 min. The resulting M1 plants were self-pollinated, and M2 seeds showing a Mendelian segregation ratio were selected. M2 plants were further self-pollinated to obtain M3 progenies for bulked pools. The 12-DAP embryos and endosperms from 20 WT and 20 mutant-type kernels from segregating M3 ears were used for bulked segregant analysis. The plants were grown in the experimental field at Shangzhuang Experimental Base of China Agricultural University under natural conditions .The maize  according to the manufacturer’s instructions. The cDNA library was prepared with VAHTS Stranded mRNA-seq Library Prep Kit for Illumina V2  and sequenced on the Illumina X-ten platform. Raw reads were aligned to the B73 reference genome (V4) using HISAT2. The alignment files were converted to BAM format and sorted using Samtools. SNP calling, including C-to-T and G-to-A mutations, was performed by Samtools and Bcftools using unique reads. High-confidence SNPs were selected using the following criteria: (1) the SNP was supported by at least five reads, and (2) the SNP was detected in both the mutant pool and its corresponding WT pool. Functional annotation of SNPs was performed using SnpEff to screen SNPs between the two RNA pools. The SNP index was listed in Zm00001d015156) in WT and mutant pools from our bulked segregant analysis. Then the ΔSNP index (SNP index difference between the mutant bulk and WT for each SNP) was calculated for each SNP. Zm00001d015156 was considered as candidate gene because of its mutant type and the highest SNP index among these genes. To test the degree of linkage between the candidate gene Zm00001d015156 and the mutant phenotype in the M3 segregating population, we designed primers PPR278-1F/R and PPR278-2F/R closely linked with the mutant sites  epidermal cells and maize protoplasts. After culture for 20 h at 28 °C, the fluorescence signals were detected by a LSM710 confocal laser scanning microscope . AtAHL22-mCherry was used as a nuclear marker [The full-length PPR278 coding sequence without the stop codon was inserted into the vectors pSuper1300::eGFP and pSPYNE-35S::eGFP. Approximately 1 µg of the recombinant plasmid PPR278::GFP was transformed into onion  or PPR energy databases  ,50. The −ΔΔCt method as described previously [ZmActin as a control. The experiments were replicated two times, and the primers used in the qRT-PCR (PPR278-764F and PPR278-1003R) are listed in Total RNA was treated with RQ1-free DNase I  to completely remove DNA contamination. The cDNA was synthesized using oligo (dT) primers . Quantitative reverse transcription PCR (qRT-PCR) was performed using TB Green Premix Ex Taq  with an ABI 7500 system , and relative gene expression was calculated with the 2eviously . The datppr278-1 plants were compared by PCR using 18s RNA as the reference gene. The primers used for mitochondrial genes were described previously [ppr278-1 plants were normalized using ZmActin. The PCR reaction buffer and DNA polymerase were from Mei5bio . To further analyze RNA splicing, we chose the primers covering group II introns as described previously [Total RNA was extracted and reverse transcribed with random primers as described above. The expression differences of maize mitochondrial transcripts between WT and eviously . The expeviously .ppr278-1 and ppr278-2 kernels at 12-DAP were reverse transcribed and directly sequenced as described previously [ppr278-1 plants was compared. The editing sites identified in the ppr278-1 mutant were confirmed in the ppr278-2 mutant. The editing efficiency of atp8 and nad3 in WT, ppr278-1, and ppr278-2 plants was estimated by cloning the atp8 and nad3 coding sequences into vector B-zero  and sequencing more than 40 independent colonies for each gene. Mitochondrial RNA was reverse transcribed with random primers as described above. The full-length sequences of 35 mitochondrial transcripts in eviously . The C-tppr278-1 or WT biological samples were collected for construction of the RNA-sequencing library. The cDNA library was performed according to Hieff NGS MaxUp II Dual-mode mRNA Library Prep Kit for Illumina  and sequenced by the Illumina NovaSeq platform for 150-nucleotide paired-end reads. Raw reads were aligned to the B73 reference genome (V4) using HISAT2. Data were normalized as fragments per kilobase of exon per million fragments mapped (FPKM), since the sensitivity of RNA-seq depends on the transcript length. The significant DEGs were filtered with the criterion: fold change > 2 and p-value < 0.05.Total RNA of 18-DAP endosperm and embryo (4 µg) tissues was extracted as described above, and two


Nucleic acids underlie the storage and retrieval of genetic information literally in all living organisms, and also provide us excellent materials for making artificial nanostructures and scaffolds for constructing multi-enzyme systems with outstanding performance in catalyzing various cascade reactions, due to their highly diverse and yet controllable structures, which are well determined by their sequences. The introduction of unnatural moieties into nucleic acids dramatically increased the diversity of sequences, structures, and properties of the nucleic acids, which undoubtedly expanded the toolbox for making nanomaterials and scaffolds of multi-enzyme systems. In this article, we first introduce the molecular structures and properties of nucleic acids and their unnatural derivatives. Then we summarized representative artificial nanomaterials made of nucleic acids, as well as their properties, functions, and application. We next review recent progress on constructing multi-enzyme systems with nucleic acid structures as scaffolds for cascade biocatalyst. Finally, we discuss the future direction of applying nucleic acid frameworks in the construction of nanomaterials and multi-enzyme molecular machines, with the potential contribution that unnatural nucleic acids may make to this field highlighted. Nucleic acids demonstrated very unique properties and advantages to be used for constructing nanomaterials and scaffolds of multi-enzyme systems. For example, the structures of nucleic acids are well determined by their sequences, which allows straightforward control of their structures by customized sequence design . The feamachines . In recemachines . Hopefulin vitro and in vivo are summarized and discussed. A perspective on future development and application of novel nucleic acid frameworks in building nanostructures and multi-enzyme systems is provided in the end, with the potential contribution of unnatural nucleic acids highlighted.In this review article, we start from a brief introduction of the molecular structures and properties of natural and unnatural nucleic acids. Then the approaches and recent progresses on fabricating and applying complex nanostructures and multi-enzyme systems with nucleic acid scaffolds de novo synthesis of DNA and the invention of polymerase chain reaction (PCR) technology for exponential amplification of DNA have already laid the technical foundations for large-scale preparation of DNA, which is the prerequisite to extensively use DNA as a structural material  has greatly expanded the genetic alphabet . Introduormation . Moreovereagents .in vivo replication, transcription, and even translation , and the ssDNA was then reverse transcribed from the RNA by HIV reverse transcriptase, which was recruited by HTBS  effector staple proteins , four-way junction (4WJ), kink-turn motif, hairpins, pseudoknot, C-loops, right-angle motifs, tetraloop-receptors, paranemic motifs, and kissing loops, which can be directly employed in the design and construction of RNA nanostructures . Early emedicine . Mao andmedicine . Hermannmedicine . Since tmedicine . With inmedicine . In anotmedicine .in vivo construction and application of nanostructures more feasible. Geary et al. designed RNA tiles fabricated with a single-stranded RNA, and these RNA tiles can self-assemble into hexagonal lattices , for the treatment of triple negative breast cancers (TNBCs) . AlternaEfforts have also been made to fabricate RNA and DNA structural units together to produce novel RNA-DNA hybrid materials that possess characteristics, properties, and functions of both RNA and DNA. For example, Hermann and co-workers reported a self-assembled RNA-DNA hybrid polygonal nanostructure, the formation and stabilization of which were highly dependent on the binding of the DNA aptamer integrated in the nanostructure with its ligand AMP . Afonin in vivo production of RNA nanostructures via co-transcriptional assembly has also been demonstrated by several groups, which suggested the potential use of RNA as a scaffold material for organizing functional molecules in living cells. For example, Delebecque et al. assembled programmed RNA scaffolds in vivo, and applied them to guide the spatial organization of proteins , which mimicked peroxidase , which was composed of AMP and Ce3+ . The NCP3+ . Other t3+  20 oligonucleotide, was attached to the surface of the DNA tile in between these two enzymes, and behaved as a swinging-arm that facilitated hydride transfer between G6PDH and MDH 20 oligonucleotide had an obvious negative impact on the catalytic activity. Later, they expanded this work to the construction of an artificial 2D enzyme network of G6PDH and lactate dehydrogenase (LDH), in which the enzymes were immobilized on the nodes of a wireframe DNA origami grid, and the cofactor NAD+-coupled duplex swinging arms were immobilized halfway between each pair of G6PDH and LDH  and a malic dehydrogenase (MDH) were co-immobilized on a DNA double-crossover tile scaffold, and a NAD and MDH   and xylitol dehydrogenase (XDH) of xylose metabolic pathway on DNA origami nanostructures with different distribution patterns of protein binding sites  Ngo et . While Xin vitro construction of multi-enzyme systems, presumably due to the fact that RNA is not as stable and cheap as DNA. However, there are some examples of using RNA scaffolds for the in vivo construction of multi-enzyme systems, taking advantage of easy in vivo production of RNA via transcription and efficient co-transcriptional assembly of RNA nanostructures, which will be introduced in next section. Unnatural nucleic acid scaffolds have also not been used for the construction of multi-enzyme systems yet, since the efforts on the development of efficient tools to produce, amplify, and manipulate them, including unnatural nucleic acid polymerases, although already fruitful, are still in progress. The great potential of this field will be discussed in the end of this article.There is barely any example of using RNA scaffolds for the via in vivo construction of multi-enzyme systems with key enzymes in the metabolic pathways  cells. After being expressed in the cells, the zinc finger protein-fused enzymes spontaneously assembled onto the scaffold plasmid. They then optimized stoichiometric ratios of the enzymes and intervals between the enzymes for higher L-threonine production. With the optimal system, the production time of L-threonine was reduced by over 50%, and the growth rate of the host cells was also enhanced, presumably due to reduced accumulation of toxic intermediates. Chen and coworkers reported the application of similar strategy on spatial modulation of pathway enzymes for improved production of N-acetylglucosamine in Bacillus subtilis (in vitro or in vivo by simply fusing enzymes with TALE proteins and immobilizing them onto a DNA scaffold with multiple TALE binding sequences. Zhu et al. reported the in vivo construction of TALE-based multi-enzyme system for the synthesis of indole-3-acetic acid (E. coli (Whole cell biocatalysts have been broadly used in bioindustry for the production of valuable chemicals, and their catalytic efficiency can be significantly improved pathways . Biomacr ligands . Many of ligands  (Lee et  ligands . Plasmidsubtilis  (Liu et subtilis . The zinsubtilis  (Conradosubtilis . TALEs asubtilis . Taking tic acid . In this(E. coli . After oin vivo construction of multi-enzyme systems have been reported yet, mainly due to the lack of efficient and user-friendly methods for in vivo production and assembly of singles-stranded nucleic acid components, as well as methods for in vivo immobilization of enzymes of interest site-specifically onto these nanostructures. Sliver et al. pioneered an effort to construct multi-enzyme systems in vivo based on RNA nanostructures (in vivo constructed 2D RNA scaffolds for enhanced pentadecane and succinate production (Up to now, not many examples of applying complex nucleic acid nanostructures for ructures . RNAs wioduction .in vitro and in vivo.In the past decades, a variety of elegant artificial structures based on nucleic acids have been designed and constructed, and some of them have found broad application in the construction of elegant nanomaterials or as highly programmable scaffolds for multi-enzyme systems. In this article, we started from the introduction of basic characteristics and properties of natural and unnatural nucleic acids, which demonstrated the uniqueness and superiority of nucleic acids to be used as structural materials. The progress in the development of polymerases for the efficient synthesis of nucleic acids with unnatural moieties, which are essential for broader application of unnatural nucleic acids, was also discussed. We then summarized representative approaches in the application of DNA, RNA, and unnatural nucleic acids for the construction of various artificial nanostructures, ranging from simple one or two-dimensional structures to complicated 3D origami nanostructure assemblies. In the end, we reviewed the construction of multi-enzyme systems using nucleic acid structures as scaffolds, as well as the application of these multi-enzyme systems for efficient catalysis of cascade reactions, both de novo synthesis technology, will facilitate the acquirement of more and better oligonucleotide sequences to be used as components for the construction of nucleic acid nanostructures in the future (Rapid development of DNA and RNA nanotechnology has enabled the construction and broad application of various nucleic acid nanostructures. However, more efforts still need to be made to make the procedures and the computational programs for the design and construction of complicated nanostructures more robust and user-friendly . Recentle future .in vitro or in vivo. However, these systems are still far from perfect, and a lot of efforts need to be made to further improve their performance. For instance, new chemistry may be developed to achieve efficient site-specific immobilization of the enzymes onto the scaffolds and precise control of the orientation of the enzymes, which is obviously very important for the accessibility of substrates or intermediates to the active sites. Smarter nucleic acid nanostructures may also be designed for better regulation of the stoichiometric ratio and relative positions of the enzymes based on their kinetic parameters to achieve optimal overall catalytic performance. Development of better computational tools to assist the design, assembly, and behavior simulation of versatile nucleic acid nanostructures will also greatly promote these efforts (in vitro, complex DNA origami nanostructures are rarely used as scaffolds for in vivo construction of multi-enzyme systems. Most of the nucleic acid scaffold-based multi-enzyme system constructed in vivo are still simply based on the immobilization of DNA-binding protein elements on linear double strands of DNA. Further exploitation of methods for constructing complicated nucleic acid nanostructures in vivo and combining these nanostructures with well-designed nucleic acid-binding proteins may lead to much better scaffolds for in vivo assembly of highly programmable multi-enzyme systems, and facilitate the engineering of cellular metabolic pathways.In order to immobilize and organize two or more enzymes for efficient catalysis of cascade reactions, multi-enzyme systems have employed various materials to fabricate the scaffolds, including inorganic materials, organic frameworks, and biological materials. Among those, nucleic acid has proven one of the most promising scaffold materials. Numerous artificial structures have been constructed with nucleic acids, and many of them are already well suited for the construction of multi-enzyme systems for efficient catalysis of cascade reactions  efforts . Despitein vitro application of unnatural nucleic acids, the efforts on construction of semi-synthetic organisms have opened the gate for in vivo application of unnatural nucleic acids (in vitro and in vivo.Although natural nucleic acid frameworks have already been broadly used in the construction of nanomaterials or as the scaffolds of multi-enzyme systems, there still remain many challenges in the construction and application of better nucleic acid scaffolds that fulfill the requirements of more programmable and robust nanostructures or multi-enzyme systems. For example, the number of nucleobases in natural DNA and RNA is quite limited compared to the number of amino acids in protein, which results in limited sequences, structures, and designability of DNA and RNA. Moreover, natural nucleic acids have low tolerance against nuclease degradation and reduced stability under various chemical or physical conditions, which restricts the application of nucleic acid nanostructures or multi-enzyme systems with nucleic acid scaffolds in biological solutions or harsh environments. The fast development of unnatural components has provided a generous toolbox for the structural and functional expansion and augmentation of nucleic acids, and thus offered a great potential for the design and construction of better nucleic acid-based nanostructures and multi-enzyme scaffolds. As mentioned above, newly developed unnatural base pairs are already able to pair, replicate and transcribe as efficiently as natural base pairs . The intic acids , so we c


Alkbh5 increases the level of total m6A methylation and causes male infertility. In this study, comprehensive analyses of MeRIP-seq and RNA-seq data revealed differences between wild-type (WT) and Alkbh5 knockout (KO) mice. In pachytene spermatocytes (PA), 8,151 m6A peaks associated with 9,959 genes were tested from WT and 10,856 m6A peaks associated with 10,016 genes were tested from KO mice. In the round spermatids (RO), 10,271 m6A peaks associated with 10,109 genes were tested from WT mice and 9,559 m6A peaks associated with 10,138 genes were tested from KO mice. The peaks were mainly concentrated in the coding region and the stop codon of the GGAC motif. In addition, enrichment analysis showed significant m6A methylation genes in related pathways in spermatogenesis. Furthermore, we conducted joint analyses of the m6A methylome and RNA transcription, suggesting an m6A regulatory mechanism of gene expression. Finally, seven differentially expressed mRNAs from RNA-seq data in both PA and RO were verified using qPCR. Overall, our study provides new information on m6A modification changes between WT and KO in PA and RO, and may provide new insights into the molecular mechanisms of m6A modification in germ cell development and spermatogenesis.Spermatogenesis, an efficient and complex system in male germline development, requires a series of elaborately regulated genetic events in which diploid spermatogonia differentiate into haploid spermatozoa. N6-methyladenosine (m6A) is an important epigenetic RNA modification that occurs during spermatogenesis. ALKBH5 is an m6A eraser and knocking out  In mammals, spermatogenesis consists of a series of tightly controlled processes, including mitosis, meiosis, and spermiogenesis . The appAlkbh5, the fertility of male mice was impaired due to apoptosis of pachytene and metaphase-stage spermatocytes and aberrant spermiogenesis. Significantly reduced numbers of PA and RO were observed in Alkbh5 knockout (KO) mice , and shorter transcripts, suggesting that transcripts with longer 3ʹ-UTR have much higher levels of m6A than those with shorter 3ʹ-UTR near the stop codon (Alkbh5 knockout (KO) mice stagnated at the round spermatozoa phase, and occasionally, some sperm were found in the caudal epididymis of KO mice. These KO sperm were malformed and displayed various structural abnormalities. However, currently, the function of m6A methylation in PA and RO is unclear.N6-methyladenosine (m6A) modification is implicated in the regulation of expression at the post-transcriptional level, including pre-mRNA splicing, mRNA nuclear export, stability, decay, and translation . In mammKO) mice . Anotherop codon . FurtherAlkbh5 KO and wild-type (WT) adult mouse testes using the STA-PUT method. RNA-Seq and MeRIP-Seq were used to uncover the impact of the Alkbh5 gene on transcriptome-wide m6A methylation levels in mouse spermatogenesis and to find out whether the functional role of m6A methylome varies between different spermatogenic stages. We also identified the molecular functions within the cell type-specific differential methylation peaks in spermatogenesis, which provides a useful reference for further study into underlying mechanisms in male germline development.In the present study, we aimed to investigate the role of m6A modification, to facilitate future functional studies of mammalian m6A, and to explore the pathogenic mechanism of spermatogenic disorder. To do this, we examined the m6A peaks in the RNA of PA and RO purified from Alkbh5+/− mice were a gift from Dr. Yamei Niu, Institute of Basic Medical Sciences, Chinese Academy of Medical Science, and were purchased from The Jackson Laboratory . Homozygous Alkbh5 mice were produced by intercrossing of heterozygous Alkbh5 mice. Mice were housed in a temperature-and humidity-controlled cages with 12-h light/dark cycles. All WT and Alkbh5 KO mice used in this study were C57BL/6J (B6) mice. Male Alkbh5 KO mice have been previously reported . The reported .Alkbh5 KO mice, and washed and immersed in phosphate buffered saline (PBS). After weighing the testis and recording its morphology, the cauda epididymitis was punctured several times with a needle, and the sperm was released into a PBS solution at 37°C for 30 min. Sperm motility was determined using computer-assisted sperm analysis (CASA) and the measurements were repeated thrice. Sperm concentration was measured in triplicate using a hemacytometer.Testes and whole epididymis were dissected from 12-week-old WT and Alkbh5 KO mice testes using the STA-PUT method as described previously  solution. Finally, the micrographs were obtained using a light microscope .Total protein lysates were extracted from whole testes of WT and KO mice using RIPA lysis buffer. The Pierce BCA Protein Assay Kit  was used to determine the protein concentration. Protein lysates (30 μg) were resuspended in sodium dodecyl sulphate (SDS) sample buffer, subjected to electrophoresis on a 10% SDS-polyacrylamide gel, and then transferred onto nitrocellulose membranes. The membranes were blocked with skimmed milk at a 5% concentration and incubated at 20°C for 1 h. Next, the membrane was incubated with anti-Alkbh5  and anti-β-tubulin  antibodies overnight at 4°C, washed in PBS-T the next day, incubated with goat anti-rabbit HRP  at 20°C for 1 h. Proteins were finally visualized using an Odyssey infrared imaging system (Li-Cor Biosciences).−ΔΔCt method and normalized to β-actin mRNA levels.Total RNA was extracted from the testicular tissues of WT and KO mice using TRIzol reagent . A total of 1 μg of total RNA was reverse transcribed using the HiScript Ⅱfirst Strand cDNA Synthesis Kit . Real-time PCR was performed using TB Green™ Premix Ex Taq™ II  according to the manufacturer’s instructions. All primers for genes were synthesized by Genewiz and are shown in Tissue samples were isolated using grinding beads and a high-speed reciprocating shaking device (Tissuelyser-24) in a low-temperature grinding environment, and total RNA from three sets of PA and RO was isolated using TRIzol™ Reagent . The isolated RNA was treated with DNase I  to remove genomic DNA contamination. Extracted RNA was precipitated in glycogen  and isopropanol at −30°C for 2 h. The pellet was rinsed twice with 70% ethanol, dried, and dissolved in ultra-pure water, then the RNA was fragmented. Briefly, 2 μl 10× RNA fragmentation buffer  was added, and 2 μl 0.5 M EDTA was added immediately after 6 min incubation at 70°C to terminate the reaction . The frap-value < 0.05 for de novo motif analysis.The bioinformatics data analysis were performed by Guangzhou Epibiotek Co., Ltd. Cutadapt (v2.5) was used to trim adapters and filter for sequences. The remaining sequence reads were aligned to the mouse Ensembl genome GRCm38. We used Hisat2 aligner (v2.1.0) under the parameters: “--rna-strandness RF” . m6A peaAlkbh5 KO mice, we first analysed testicular development from gross morphology and histological perspectives. The shape and mass of the testes in the KO mice were smaller and lower respectively than those in the WT group . The Alkbh5-KO RO had 1,589 significantly upregulated methylation peaks, while 1,602 were downregulated compared with that in the WT RO  RNA , a start codon (4.7% vs. 4.3%), 3ʹ-UTR (20% vs. 17.8%), 5ʹ-UTR (1.6% vs. 1.4%), and TSS (0.6% vs. 0.3%), and a notable decrease in the coding DNA sequences (CDS) (56.5% vs. 51.8%) (Alkbh5 contributed to a larger change in the distribution of lncRNA in RO than in PA (Alkbh5-KO RO indicate a significantly different pattern from peaks in the WT RO with a relative increase in the number of methylation peaks in the CDS (51.6% vs. 49.7%), 5ʹ-UTR (1.4% vs. 1.2%), and a relative decrease in the 3ʹ-UTR (21.4% vs 22%), TSS (0.4% vs 0.7%), stop codon (21.1% vs 21.4%), and start codon (4.3% vs. 5.1%)  RNA . Specifi. 51.8%) . Comparean in PA . The diss. 5.1%) . In addis. 5.1%) .Alkbh5-KO and WT spermatogenic cells, GO and REACTOME pathway analyses for differentially methylation peaks were performed , we compared the transcriptome profiles of reliable . We founin WT RO . Thereaf binding . Next, wactivity . Additioesponses .Alkbh5 on spermatogenesis, we performed an association analysis of the genes with significant changes in methylation and mRNA expression levels. The results were divided into four parts: hypermethylated-down, hypermethylated-up, hypomethylated-down, and hypomethylated-up. Alkbh5-KO PA and WT PA (Alkbh5-RO and WT RO (Mroh4, Prm1, Lrrc7, Dbil5, H1fnt, Catsperd, and Odf4 were greatly downregulated in the testes in the Alkbh5 KO (To further investigate the influence of nd WT PA , as wellnd WT RO . Thereaflkbh5 KO .Alkbh5-KO mice show abnormal spermatogenesis and subfertility (Alkbh5 only focused on the overall changes in spermatogenesis but not on the specific changes in RNA and m6A methylation changes at each stage of spermatogenesis. To address this question, we performed high-throughput sequencing to reveal the m6A landscape in the spermatogenic stages of PA and RO in Alkbh5-KO and WT mice. Using MeRIP-seq, we identified that Alkbh5-KO PA had 1,929 noticeably upregulated methylation peaks relative to that in the WT PA, while 326 were downregulated. The Alkbh5-KO RO had 1,589 noticeably upregulated methylation peaks relative to that in the WT RO, while 1,602 were downregulated. We then used GO and REACTOME pathway enrichment analyses to explore the potential functions of differentially methylated transcripts. Finally, we found a difference in the genes in methylation peaks and synchronous differential expression genes enriched in the spermatogenesis-related pathway.Modification of m6A demethylases plays a critical role in mammalian spermatogenesis. ALKBH5 was highly expressed in mouse testis as an m6A eraser, and loss of ALKBH5 significantly increased the level of m6A in testicular cells. ertility . An indeertility . HoweverAlkbh5 on spermatogenesis from the perspective of differences in methylation and gene expression. We found that the effects of Alkbh5 on PA and RO differed considerably. First, we found that ALKBH5 is a demethylase has different effects on the methylation of transcripts in PA and RO. In PA, we found that the number of significantly upregulated methylation peaks was far larger than that of significantly downregulated methylation peaks in the Alkbh5 KO, which is consistent with our previous knowledge about Alkbh5 that the degree of RNA methylation significantly increases in the testes of Alkbh5 KOs (Alkbh5 KO, the number of significantly upregulated methylation peaks was very close to the number of significantly downregulated methylation peaks. We found that the distribution of methylation peaks in PA and RO differed considerably. In particular, in the Alkbh5 knockout, we found that the proportion of methylation peaks distributed in the CDS region of PA increased significantly, while the proportion of methylation peaks distributed in the CDS region of RO reduced. Moreover, lncRNAs, as epigenetic regulators, play an essential role in spermatogenesis (Alkbh5. The expression of lncRNA was characterized by a sharp increase in the number of expression sites and the overall expression level with the development of spermatogenesis, and reached a peak in the round spermatogenesis stage (In this study, since the analytical results of MeRIP-seq include the results of RNA-seq, our analysis reveals the impact of kbh5 KOs . Howeverogenesis , such asogenesis  and sperogenesis . Our obsis stage .Alkbh5 knockout, both the upregulated and downregulated methylation peaks in PA and RO were closely related to covalent chromatin modification and histone modification. Histone modification influences chromatin structure and function. Previous studies have indicated various histone modifications are involved in the regulation of spermatogenesis (Here, we used GO enrichment analysis to further explore differentially methylation peaks. We found that after ogenesis , but theogenesis . In mousogenesis . Based oogenesis . TCP1, wogenesis . Actin fogenesis . Our resAlkbh5 knockout. However, the number of upregulated and downregulated genes in RO was close. In the enrichment analysis, we found that the differential genes of PA and RO are closely related to spermatogenesis. Therefore, this result reveals that knocking out Alkbh5 affects gene expression in PA and RO. Further molecular experiments should be performed to verify the differentially methylated genes in mouse PA and RO. Next, we found that the top 20 DEGs in Alkbh5-KO PA, WT PA, Alkbh5-RO, and WT RO were closely related to spermatogenesis. Moreover, after intersecting these genes, we found that more than half of these genes appeared in both comparisons. In the qPCR experiment, we found that transcripts related to spermatogenesis were significantly downregulated because of Alkbh5 KO. One of these was, Prm1, which is a protamine substitute for histones in the chromatin of sperm during the haploid phase of spermatogenesis, compacts sperm DNA into highly condensed, stable, and inactive complexes (Odf4, which encodes a protein that is localized in the outer dense fibres of the tails of mature sperm. This protein is thought to play an important role in the sperm tail (H1FNT, which was also downregulated in Alkbh5 KO, is a germ cell-specific linker histone variant expressed during spermiogenesis, specifically in round and elongating spermatids (Alkbh5 greatly contributes to the development of spermatogenesis at both the epigenetic and mRNA levels.In the DEG analysis, we detected several the DEGs related to many important biological pathways. REACTOME pathway analysis revealed that transcripts related to fertilization and reproduction genes were downregulated in PA and RO during spermatogenesis, showing that the expression of genes related to spermatogenesis in PA and RO both are affected by the increase in methylation level after knockout of the methylase. This further illustrates that m6A methylation is necessary during spermatogenesis. Using MeRIP-seq results, we analysed the differences from the perspective of RNA. The RNA differential analysis results were similar to the methylation results. We found that the number of upregulated genes in PA was significantly greater than that in the downregulated genes in the omplexes . In addierm tail . Furtherermatids . In concAlkbh5 is also widely expressed in the human testis. In humans, Alkbh5 expression is higher in PA compared with other stages, implying that it affects semen quality and a perturbation in its function increases the risk of male infertility (While the causes of approximately 50% of human male infertility are unknown, genetic causes, in particular, often remain undiagnosed . Our curertility . HoweverAlkbh5-KO mice relative to the corresponding WT mice, and demonstrated a strong association between m6A modification and spermatogenesis. Furthermore, in the Alkbh5 KO, m6A levels were increased, affecting many spermatogenesis-related genes, very likely leading to spermatogenesis disorders. In addition, the data show that the m6A methylation level and mRNA expression level in mouse PA and RO were significantly different; further research is needed to uncover the underlying mechanisms that affect male fertility.In summary, we analysed the differential m6A methylome in PA and RO in