MicroRNAs are known to regulate 60% of genes at post translational level. MicroRNAs including Micro RNA-29 family play a vital role in cellular activities and have validate role in numerous metabolic disorders inclusive of diabetes mellitus and its complications. While micro RNA profile changes years before the occurrence of disease. This cross-sectional study was conducted in non-diabetic adults of diabetic and non-diabetic parents to explore the early changes in expression of micro RNA-29 family as it can be served as early biomarker of type 2 diabetes in non-diabetic adults. This study was conducted from January 2019 to January 2021. Micro RNA was extracted from plasma of 50 participants and expression was compared through qPCR. While data was analyzed through SPSS version 21.0..29a and 29b had lower expression in participants with family history of DM compared to those having no family history of DM (P < 0.0001). While micro RNA 29c was found to be significantly higher in participants with positive family history of type 2 diabetes as compared to those without family history of diabetes (P = 0.001)The online version contains supplementary material available at 10.1186/s13104-021-05703-8. Diabetes Mellitus is a complex and multi factorial disease which is caused either by insufficient production of insulin or insulin resistance by the cells or both . PresentThe miRNA-29 group has been known to become important regulator of glucose metabolism and has altered expression in diabetics due to its different targets –9. So, iThis was a cross-sectional study conducted from January 2019 to January 2021.Using Lahr’s theorem from NCSS PASS software, with 95% confident interval and 80% power of the test, the sample size came to be 25 for each group. Sampling technique was purposive convenient type.Participants were healthy non-diabetic workers and students of Dow University of Health Sciences, Karachi, Pakistan. Participants having age between 18 to 30 years were included after testing for HbA1c according to WHO criteria. While those having any metabolic disorder or HbA1c in rages of pre-diabetes were excluded. Informed written consent was taken from the participants. 50 blood samples were obtained. 25 from each category i.e. with and without parental history of type 2 diabetes mellitus.The study was approved by institutional review board (IRB) of Dow University of Health Sciences, Karachi, Pakistan (IRB letter no. 2018/1045).3 ml blood were collected from participants. Consent was taken from every patient and informed about the study. Sample was centrifuged at 6500 rmp for 5 min and plasma was separated and stored at -80 for further process.mirVana® micro RNA isolation kit  according to manufacturer’s guidelines.Micro RNA was extracted from samples by using a 2O, 0.5 µl (10 pmol/µl) of reverse and forward primers. Each sample was run in triplicate. A comparative delta delta-CT formula was used for comparison of targeted micro RNA. Expression of micro RNA was normalized with SnRNA-u6, and comparative values were expressed as 2−ΔΔCT.Extracted micro RNA was then used to form cDNA separately for microRNA 29-a, 29-b, 29c and internal control i.e. U6 using specific RT primers. The synthesized cDNA was used for qRT-PCR by using Maxima SYBR green qPCR master mix  according to manufacturer’s instructions and expression of MiR-29a, b and c of samples were normalized to U6. Total 25 µl of reaction volume was attained by adding 12.5 µl of SYBR green master mix, 2 µl of cDNA along with 9.5 µl of dHData were compiled in MS Excel and analyzed in SPSS version 21.0. Descriptive statistics expressed in terms of frequency with percentage for categorical variables such as sex, smoking status, exercise status, family history etc. while mean with standard deviation for continuous variables like age, BMI and micro RNA expression were taken.Repeated Measures ANOVA was used to compare average expression within three members Correlation coefficients between HbA1C, BMI and fold changes were measured by Spearman’s method. With 95% confidence interval, P value less than 0.05 was considered as significant.The demographic data of groups were summarized in Additional file When the expression was compared between the groups with respect to internal control SnRNA-U6, the result showed that micro RNA 29a, 29b and 29c showed significant difference between the both the groups i.e. participants with family history of T2DM and participants without family history of DM (P < 0.001). Additional analysis by post-hoc Tukey test showed marked difference of 29a between both groups (P < 0.0001), in which participants with family history of DM had lower expression of micro RNA-29a as compared to those having no family history of DM. Micro RNA 29b was also found to be down regulated in participants with family history of DM as compared to other group (P < 0.0001). However, Micro RNA 29c was found to be significantly higher in participants with positive family history of DM as compared to those without family history (P = 0.001) Fig. . The folSince the discovery of micro RNA, the initial studies were performed in animal modules to evaluate the functions and pathogenesis of diabetes mellitus related to micro RNA. Multiple studies were carried out to detect and compare the expression of different diabetes related micro RNA in diabetic, pre-diabetic and non-diabetic populations. This study is first of its kind that has evaluated the differential expression of micro RNA-29 in two different non-diabetic population i.e. with and without family history of T2DM to detect possible early changes in micro RNA expression. The effort was made as it can serve as a potential biomarker for early diagnosis of type 2 diabetes mellitus.This study shows the differential expression of micro RNA-29 family  between non-diabetic youngsters with and without family history of DM. This study was however, comprised of only non-diabetic youngsters, but its results correlate with many other studies from past which were performed in different study groups like diabetic, pre-diabetic and non-diabetics.. also reported down regulation of micro RNA 29a in plasma of type 1 diabetic patients [. reported the higher expression of micro RNA 29a in serum of newly diagnosed type 2 diabetic patients in order to identify the possible predictors of type 2 diabetes [. reported micro RNA 29a as positive regulator of insulin secretion in vivo and here in our study we found down regulation of micro RNA 29a which may lead to decreased insulin secretion in future and cause insulin insensitivity [This research showed micro RNA 29a was down regulated in participants with positive family history of diabetes which is in accordance with many studies; Lin et al. quantified miR-29a and was found down regulated in glomeruli of diabetic mice  while anpatients . Whereasdiabetes . Dooley sitivity .. reported the down regulation of micro RNA 29b in db/db mice which caused increased fibrosis and increased inflammation in the kidney of mice which leads to diabetic nephropathy, which definitely favor these results and also suggests the disturbed level of micro RNA 29 family may lead to diabetic complications [. also found decreased expression of micro RNA-29b in 83 type 2 diabetic patients [Here in this study it was found that micro RNA 29b also had low expression which is similar to a study performed on diabetic rats and reported that decreased micro RNA 29 family expression increases the blood glucose levels via interacting negatively with hepatic gluconeogenesis and increase levels of PGC-1ɑ and G6Pase, which are the direct targets of 29 family, which is strongly in favor of this study and lower expression of 29b may cause higher glucose levels in future . Chen etications . Peng etpatients . Interespatients . Howeverpatients .. found a positive correlation between BMI and FMI with miR-222, miR-486, miR-146b, miR-15b, miR-146a, miR-20a, miR-20b, and miR-197 [This study also focused on correlation of variables like BMI and HbA1c of diabetic patients with expression of miRNA-29 family but we did not find any correlation of age, BMI and HbA1c with miR-29 expression .Additional file 2: Figure S1. a b and c shows no correlation of micro RNA-29a, 29b and 29c with HbA1c of participants. (n = 50). Figure S2. a b and c shows no any correlation of micro RNA-29a, 29b and 29c with BMI of participants (n = 50).


Syntaxin 18-Antisense 1 (STX18-AS1), appeared to be involved in an insulating promoter interaction with the neighbouring gene, MSX1. By knocking down STX18-AS1, the MSX1 promoter-PIR interaction was intensified and the target gene (MSX1) expression was down-regulated. Conversely, reduced MSX1 promoter-PIR interactions, resulting from CRISPR-Cas9 deletion of the PIR, increased the expression of MSX1. We conclude that STX18-AS1 RNA antagonised local CTCF-mediated insulating promoter interactions to augment gene expression. Such down-regulation of the insulating promoter interactions by this novel mechanism may explain the higher expression of genes interacting with RNA-PIRs linked to CTCF sites.The genome-wide promoter interactome is primarily maintained and regulated by architectural proteins such as CTCF and cohesin. However, some studies suggest a role for non-coding RNAs (ncRNAs) in this process. We aimed to characterise the regulatory role of RNA-mediated promoter interactions in the control of gene expression. We integrated genome-wide datasets of RNA-chromatin and promoter-genome interactions in human embryonic stem cells (hESCs) to identify putative RNA-mediated promoter interactions. We discovered that CTCF sites were enriched in RNA-PIRs  and genes interacting with RNA-PIRs containing CTCF sites showed higher expression levels. One of the long noncoding RNAs (lncRNAs) expressed in hESCs,  The occurrence of these long-range chromosomal interactions is not only mediated by protein factors that are key players in maintaining genome architecture such as CCCTC binding factor (CTCF), Yin Yang 1 (YY1) and the Mediator and cohesin complexes, but also the widespread non-coding RNAs (ncRNAs) transcribed in the genome3. For example, Thymocyte Differentiation factor (ThymoD) ncRNA activates cohesin-dependent looping to juxtapose the enhancer and promoter of B cell lymphoma/leukaemia 11b (Bcl11b) gene into a single loop domain for T cell fate specifying expression4. Functional intergenic repeating RNA element (Firre), a long intergenic noncoding RNA (lincRNA) localises across a 5 Mb domain around its transcription site and this domain interacts with several trans-chromosomal loci5. Deletion of the Firre locus leads to the loss of the trans-chromosomal interactions, suggesting a role for Firre lincRNA in 3D chromosomal organisation5.Gene regulation involves the formation of three dimensional (3D) chromosomal interactions to bring distal genomic regulatory elements to spatial proximity of gene promoters6. Architectural proteins such as the Mediator complex, CTCF and YY1 have been shown to associate with RNAs10. Depletion of Mediator’s subunits or activating ncRNAs reduces the chromatin looping between the activating ncRNAs and their target genes7, whilst mutations at CTCF’s RNA interaction sites cause the loss of chromatin loops10. In the case of cohesin, the positioning of the complex requires active transcription in the mouse genome11 and displacement of it depends on the ‘read-through’ transcription (extending past the 3′ ends of genes) in the host cell during the influenza A infection to decompact the locus12. This mechanism is an example of how the transcription itself, but not the resulting RNAs, can affect 3D genome organisation3.Although the mechanism by which ncRNAs facilitate long-range chromosomal interactions is largely unknown, it has been hypothesised that this function is made possible by their flexible modular domains that bind proteins, DNAs and other RNAs and bring these regulatory components to close proximity17. Promoter-genome and RNA-genome mapping have been performed on human embryonic stem cells (hESCs) and their differentiated cells to understand the maintenance of pluripotency and the differentiation process19. Here we integrate promoter capture HiC (PCHiC) and mapping RNA-genome interactions (MARGI) datasets of H9 hESCs to identify and investigate putative RNA-mediated promoter interactions 19, and elucidate the role of a functionally important long noncoding RNA (lncRNA), Syntaxin 18-Antisense 1 (STX18-AS1), in one of the promoter interactions of hESCs. SNPs in the region of the STX18-AS1 gene have been associated with atrial septal defects of the heart in multiple studies23.In this study, we aimed to characterise the regulatory role of RNA-mediated promoter interactions in the control of gene expression. Recently, genome-wide and targeted methods have been devised to map RNA–DNA contacts in the genome, providing the experimental capability to understand the role of RNAs in chromosomal interactions19, 20,984 of them overlapped with genomic regions that are interacting with RNAs as identified through proximity MARGI (pxMARGI)15  in the genome of H9 hESCs previously reported26 and intersected them with the PIRs (Supplementary Table −100). Similarly, 8.5% of RNA-PIRs contained YY1 binding sites, while 4.1% of nonRNA-PIRs contained these sites  .We obtained CTCF and YY1 binding sites of H1 hESCs from the Encyclopaedia of DNA Elements (ENCODE)PIRs are HindIII fragments and not the biological demarcations for the chromatin interacting regions. Therefore the intersection of PIRs and CTCF sites only indicates their physical proximity for the convenience of bioinformatic investigations, but not the actual sites where specific CTCF-mediated promoter interactions occur.19 and calculated average expression levels of genes interacting with the two categories of PIRs: (1) RNA-PIRs with CTCF or YY1 binding sites, or (2) nonRNA-PIRs with CTCF or YY1 binding sites , while genes interacting with nonRNA-PIRs with CTCF or YY1 sites had lower expression levels . The genes interacting with RNA-PIRs containing CTCF sites were significantly enriched in a wide range of development and cellular regulation processes , a transcription factor gene that plays a role in vertebrate embryogenesis28, and an RNA-PIR that is interacting with Syntaxin 18-Antisense 1 (STX18-AS1), an lncRNA in hESCs. STX18-AS1 gene contains genetic variants associated with atrial septal defects of the heart in genome-wide association studies (GWAS)23. As an RNA-PIR, We hypothesised that MSX1 promoter-PIR interaction is insulating the expression of MSX1 due to the association of RNA-RIRs with CTCF/YY1 sites as seen in Fig. MSX1 and the promoter of MSX1, but YY1 sites are very sparse in the region, suggesting that CTCF is the main factor that mediates this chromatin interaction. We also hypothesised that STX18-AS1 RNA upregulates MSX1 expression, as the RNA presence in CTCF-mediated promoter interactions led to higher expression levels of the target gene of promoter interactions as seen in Fig. We further investigated the RNA-CTCF co-regulation in promoter interactions by experimentally manipulating a promoter interaction between the promoter of STX18-AS1 RNA using paired guide RNA (gRNA) CRISPR-Cas9 technology29 to delete the first and second exons of STX18-AS1 gene  GapmeR technology30 targeting the second exon of STX18-AS1 gene. MSX1 was similarly down-regulated as a consequence  were avoided  of one of the putative RNA-mediated promoter-genome interactions (MSX1 promoter-PIR interaction), the promoter interaction was intensified and the expression of the target gene (MSX1) was down-regulated. This suggests that the promoter interaction is repressive or insulating. The majority of promoter-genome interactions are maintained by architectural proteins such as CTCF and cohesin; indeed most promoter-genome interactions are lost when CTCF and cohesin are degraded31. Given the abundance of CTCF sites in the genomic region and CTCF being the major insulating factor to mediate promoter interactions, they suggest that the RNA (STX18-AS1) represses a CTCF-mediated insulating interaction with the promoter of the target gene (MSX1). The expression level of MSX1 was up-regulated by knocking down the MSX1 promoter-PIR interaction through deleting part of the PIR, indicating that the promoter interaction is both necessary and sufficient to regulate MSX1 expression. Given the high expression levels shown by the genes interacting with RNA-PIRs containing CTCF sites, it supports the conclusion that the CTCF-mediated insulating promoter interactions can be suppressed by RNAs, just like the MSX1 promoter-PIR interaction that insulates the MSX1 expression is being suppressed by STX18-AS1 RNA in hESCs.By knocking down the RNA (H9 (WA09) hESC line was a publicly available cell line obtained from WiCell, cultured in monolayers and maintained according to WiCell Feeder-Independent Pluripotent Stem Cell Protocols (SOP-SH-002) using mTeSR1 medium (STEMCELL Technologies).STX18-AS1 gene and MSX1 PIR in H9 hESC were cloned into pLentiCRISPRv2  according to published paired gRNA design29 using human U6 promoter for both gRNA sequences. The cloned pLentiCRISPRv2 and second-generation packaging plasmids psPAX2  and pMD2.G  were co-transfected into HEK293T cells (cultured in DMEM (Gibco) supplemented with 10% FBS and 1 × penicillin–streptomycin at 37  ˚C and 5% CO2) in the proportion of 4:3:2 using Lipofectamine 2000 (Invitrogen) for lentivirus production. Lentivirus-containing media were collected 48 h after transfection, centrifuged to remove cell debris and 0.45 µm filtered before transducing H9 hESC monolayers (40–60% confluency) in the presence of 33% v/v mTESR1 media (STEMCELL Technologies), 8 µg/ml polybrene (Millipore) and 10 µM ROCK inhibitor. 24 h post-transduction, second transduction was repeated with fresh lentivirus-containing media. 24 h after the second transduction, the transduced H9 hESC were selected in 0.8 µg/ml puromycin media for 48 h. The strength of puromycin was less than the standard for better hESC survival, therefore the 48-h puromycin selection step was repeated every time the cells were passaged. The deletions of STX18-AS1 gene and MSX1 PIR were confirmed by PCR and Sanger sequencing (primers and product sizes are provided in Supplementary Table gRNA sequences (provided in Supplementary Table STX18-AS1/LOC100507266 lncRNA (NR_037888.1) was designed using EXIQON LNA GapmeR On-Line Design Tool (http://www.exiqon.com/gapmers). Both STX18-AS1 and negative GapmeRs  for 10 min at room temperature, quenched by cold 0.125 M glycine (5 min at room temperature followed by 15 min on ice), flash-frozen in liquid nitrogen and stored at − 80 °C. The cross-linked cells were lysed and the chromatin digested with HindIII at 37 °C for overnight. Then in-nucleus ligation was carried out at 16 °C for 4–6 h before reverse-crosslinking was achieved by overnight treatment of proteinase K at 65 °C. The DNA was purified by RNaseA treatment for 60 min at 37 °C, sequential phenol and phenol–chloroform extractions, and ethanol-precipitation at − 20 °C for overnight. On the following day, two further phenol–chloroform extractions and a second overnight precipitation were performed to further purify the DNA. The promoter interaction junctions between two HindIII fragments were confirmed by PCR and Sanger sequencing (primers and band sizes are provided in Supplementary Table MSX1 and ERCC Excision Repair 3 (ERCC3) interactions  are in Supplementary Figs. 3C libraries were prepared according to a published protocolImportin 8 (IPO8) was included as the internal control for expression quantification, while ERCC3 interaction was used as the positive/internal/positive control for interaction quantification33.Genomic DNA (gDNA) was extracted from cells using PureLink Genomic DNA Mini Kit (Invitrogen) and total RNA using Trizol (Invitrogen). First-strand complementary DNA (cDNA) was synthesised from DNase (Promega) treated total RNA using M-MLV Reverse Transcriptase (Promega) and both random hexamer and oligo(dT) primers (Promega). PCR was performed using OneTaq 2 × Master Mix (New England BioLabs) and the primers provided in Supplementary Table http://systemsbio.ucsd.edu/margi/ (pxMARGI)15. To compare to the promoter-PIR interactions, coordinates in hg38 were converted to hg19 using UCSC liftover function (https://genome.ucsc.edu/). RNA or DNA regions with ambiguous mapping between genome builds or that mapped to ‘unlocalized’ or ‘unplaced’ regions were removed from further analyses. This resulted in 734,970 unique RNA–DNA interactions and 601,055 unique RNA-interacting DNA regions. Unique PIRs from H9 hESCs19 excluding interchromosomal interacting regions  were then overlapped with these RNA–interacting DNA regions. A total of 20,984 of these PIRs were found to overlap RNA-interacting DNA regions, whereas the remaining 32,579 PIRs had no evidence of RNA interaction from these data.RNA-chromatin interactions were obtained from https://genome.ucsc.edu/; “Uniform TFBS” and “ENCODE 3 TFBS” tracks). For greater confidence in the overlaps, PIR and CTCF/YY1 overlaps were only counted if all datasets agreed . Any degree of intersection between the PIRs and these high-confidence feature sets was included. We performed binary logistic regression, using PIR length as a covariate, to determine statistical significance of the difference between PIRs with/without RNA and CTCF/YY1 intersection. For negative controls, we generated consensus genomic intervals from the 5 CTCF and 2 YY1 datasets respectively. These were randomly shuffled within the genome using Bedtools . 1000 randomly generated interval sets were then assessed for their intersection with PIRs through the same statistical analysis as the actual data.Promoter-PIR interactions with evidence of accompanying RNA interaction, and those without RNA interaction, were assessed for overlap with CTCF and YY1 sites using the ENCODE CTCF and YY1 sites from H1 hESC cells . CTCF or YY1 sites overlapping PIRs (RNA or non-RNA) were counted using a consensus of all 5 ENCODE CTCF and 2 ENCODE YY1 sets (downloadable from https://www.ensembl.org/). The mean expression values in terms of Transcripts Per Million (TPM) for genes identified in each overlapping PIR set  were calculated and compared.Gene promoters interacting with PIRs either associated with RNAs, CTCF or YY1 sites were assessed for the expression levels of their respective genes in H9 hESCs. H9 hESC RNA-seq dataset was downloaded from GEO (gene expression omnibus) accession GSE86821 . Raw data from the two replicates were pooled and transcript expression values determined using Kallisto  and the GRCh38 rel79 transcriptome from Ensembl (https://biit.cs.ut.ee/gprofiler/gost)27 was used to identify the overrepresentations of biological processes in gene lists. eQTLs were obtained from GTEx V8 .g:Profiler  method as previously describedhttps://github.com/keavneylab/PIR-RNA-CTCF.Standard statistical methods mentioned were performed with relevant R packages or other publicly available tools. Sample scripts and steps of this study are available on Supplementary Figures.Supplementary Tables.


Polyploidy, especially allopolyploidy, which entails merging divergent genomes via hybridization and whole-genome duplication (WGD), is a major route to speciation in plants. The duplication among the parental genomes (subgenomes) often leads to one subgenome becoming dominant over the other(s), resulting in subgenome asymmetry in gene content and expression. Polyploid wheats are allopolyploids with most genes present in two (tetraploid) or three (hexaploid) functional copies, which commonly show subgenome expression asymmetry. It is unknown whether a similar subgenome asymmetry exists during translation. We aim to address this key biological question and explore the major contributing factors to subgenome translation asymmetry.Here, we obtain the first tetraploid wheat translatome and reveal that subgenome expression asymmetry exists at the translational level. We further perform in vivo RNA structure profiling to obtain the wheat RNA structure landscape and find that mRNA structure has a strong impact on translation, independent of GC content. We discover a previously uncharacterized contribution of RNA structure in subgenome translation asymmetry. We identify 3564 single-nucleotide variations (SNVs) across the transcriptomes between the two tetraploid wheat subgenomes, which induce large RNA structure disparities. These SNVs are highly conserved within durum wheat cultivars but are divergent in both domesticated and wild emmer wheat.We successfully determine both the translatome and in vivo RNA structurome in tetraploid wheat. We reveal that RNA structure serves as an important modulator of translational subgenome expression asymmetry in polyploids. Our work provides a new perspective for molecular breeding of major polyploid crops.The online version contains supplementary material available at 10.1186/s13059-021-02549-y. Allopolyploidization (hybridization concomitant with or followed by whole genome duplication) plays an important role in the diversification and speciation of vascular plants . The hybRecent studies in wheat genomics have focused on the subgenome patterns of transcriptional regulation, revealing asymmetries of RNA abundance in ~30% of homoeologous wheat genes between subgenomes . This trArabidopsis and rice showed that mRNAs with weak structure alongside the strong three-nucleotide periodic pattern in the coding region (CDS) tend to be highly translated, suggesting that mRNA structure may have a general function in modulating translation in plants [Over decades, several factors have been identified in regulating translation such as GC content, codon usage, and tRNA copy number, tightly linked with the sequence content , 17–21. n plants , 31. ThuThe extent of RNA structure folding largely depends on sequence context. The nature of wheat homoeologous genes copies (referred to as homoeologs) provides the perfect opportunity to investigate the impact of single-nucleotide variations (SNVs) on RNA structure where homoeologs from different subgenomes share a certain number of SNVs that fold into similar or different RNA structures within the same cellular environment. The presence of SNVs between wheat subgenomes has supported its extensive adaptation to global environments, through selective breeding by humans over 10,000 years , 32. It Triticum turgidum ssp. durum, BBAA) accessions compared to non-riboSNitches. We found that these riboSNitches were more strongly selected during domestication compared to non-riboSNitches. Further research demonstrated that selected riboSNitches could be shaped through human breeding for their modulation of translation. Based on the above, this study provides a new perspective for wheat genetic research and, more generally, for polyploid crop breeding in the future.Here, we obtained for the first time, both the translatome and in vivo RNA structurome in wheat. The translatome revealed subgenome asymmetry at the translational level. We found that the single strandedness of mRNA structure, particularly the 5′UTR mRNA structure, is associated with high translation efficiency, suggesting that mRNA structure may have a strong impact on translation in wheat. We discovered that the RNA structure difference between the two subgenomes significantly contributes to translational subgenomes asymmetry where RNA structure plays a prevalent role. We further revealed that the RNA structures of homoeologs sharing more SNVs tend to be more distinct. Subsequently, we identified 3564 SNVs which induced large structure disparities, as riboSNitches between the two subgenomes which are more highly conserved across durum wheat , by subjecting polysome-associated RNAs to deep sequencing , consistent with studies in other species [To uncover the translational landscape in wheat, we performed polysome profiling on the tetraploid durum wheat cultivar, Kronos , indicating mRNAs with high GC content are highly translated in comparison to mRNA with low GC content. Notably, a similar result was also reported in rice [r = 0.60, P < 10-16), suggesting codon usage may affect translation , indicating that codon preference is unlikely to be a major modulator of translation in wheat.We then explored the impact of GC content, codon usage, and tRNA copy number on translation. We found that GC content significantly correlated with TE . Notably, among 13,294 homoeologous pairs with TE values, we found that 7418 gene pairs (~55%) displayed a significant difference in TE values between their A and B subgenomes homoeologs, indicating the existence of translational subgenome asymmetry. We then examined whether the homoeologs with significantly different TEs in the seedling samples examined are associated with specific biological functions. We classified the 7418 genes pairs into individual biological functions and calculated the corresponding averaged TE differences. We found that those homoeologs from the A subgenome with significantly higher TE values than the B subgenome tend to be associated with biological functions related to developmental, cell wall, nucleic acid metabolism, photosynthesis, and primary metabolism  chemical profiling in the tetraploid durum wheat cultivar Kronos  and lower than that in rice (0.54) [ERFL1c  and PHYA  with high PPV  or low PPV , respectively, compared to the predicted in silico structure.To further assess RNA structure features, we folded the individual mRNAs with SHAPE reactivities and compared these in vivo RNA structures with in silico RNA structures, which are the most thermostable RNA structures. For each mRNA, we calculated the positive predictive value (PPV) , a metrie (0.54) , 31, suge (0.54) , to depiWe then compared mRNA structures between the A and B subgenome homoeologs. Due to different sequence lengths between some pairs of homoeologs, we calculated the base-pairing probability (BPP) for each nucleotide of homoeologs derived from in vivo RNA structures, which measures the likelihood of single-strandedness. We then compared the average BPP between homoeologs and found that 20.1% of homoeologs showed significantly higher average BPP in the A subgenome than that in the B subgenome, while 19.4% of homoeologous pairs showed significantly lower average BPP in the A subgenome compared to the B subgenome , indicating mRNAs with weaker structures in the 5′UTR or CDS regions tend to be highly translated . Among different genic regions, the association between RNA structure difference and TE difference was stronger in both 5′UTR and CDS while moderately in 3′UTR . To illustrate this association between RNA structure difference and TE difference, we plotted in vivo mRNA structure models highlighted with average BPP for these two factors. Protein translation factor SUI1 with a significantly higher TE in the A subgenome than in the B subgenome also had greater single-strandedness in its A subgenome RNA structure and lower BPPs and higher SHAPE reactivities, compared to the B subgenome , implying that the greater the number of SNVs between homoeologs led to greater differences in RNA structure. Conversely, the correlation between the length of inserted/deleted nucleotides and eSDC between subgenomes were low , suggesting a weak impact of nucleotide insertion/deletion in differentiating the RNA structure of homoeologs  has a strongly impact in affecting RNA structure folding . We founT. turgidum spp. durum. We found that riboSNitches in different genic regions were more conserved than non-riboSNitches ; T. turgidum ssp. dicoccum, is a major cereal grain used for pasta and couscous production. DEW was derived from wild emmer wheat (WEW), T. turgidum ssp. dicoccoides, in the Fertile Crescent about 10,000 years ago [ST) to measure the species differentiation for these riboSNitches [ST values of riboSNitches were significantly higher than those of non-riboSNitches in both 5′UTR and 3′UTR, suggesting a stronger selection of riboSNitches over non-riboSNitches across these three subspecies , ears ago . We examSNitches . We founies Fig. . The FSTion Fig. . Thus, oTRITD2Av1G193730 and TRITD2Bv1g159660. In the A subgenome homoeolog, the riboSNitch denotes the sequence of Cytosine (C41), while in the B subgenome homoeolog, it denotes the sequence of Adenine (A41)  Fig. . We exam41) Fig. . We furt41) Fig. . This suP < 10-10). Therefore, this C41/A41 riboSNitch was sufficient to significantly alter translational levels, indicating that this riboSNitch contributes to the translational subgenome asymmetry of the homoeologous pair TRITD2Av1G193730 and TRITD2Bv1g159660. Taken together, our results suggest that riboSNitches may have been adopted in modulating translational subgenome asymmetry during wheat domestication.This C41/A41 riboSNitch caused significant differences of RNA structure between A and B subgenome homoeologs in our SHAPE-Structure-seq Fig. . For theIn this study, we generated the translatome and RNA structurome for tetraploid wheat and discovered subgenome asymmetry in translation, similar to previously reported asymmetry in gene content and expression , 44–46. r= 0.21, P < 10-16) between TE and RNA abundance in wheat  [Compared to the transcriptome size in d wheat) , 59, 60.Arabidopsis, rice, yeast, human cells, mouse, and zebrafish [By comparing in vivo RNA structures with in silico predicted RNA structures which are predicted to be the most thermostable RNA structures, we found that in vivo RNA structures of most mRNAs in durum wheat were very different from in silico predicted RNA structures Fig. , as obseebrafish , 61, 62.ebrafish . It willArabidopsis and rice [In general, mRNAs with more single-strandedness along with a high magnitude of 3-nt periodicity of the structure pattern in the CDS region tend to be highly translated Fig. . Our resand rice , 31. A mand rice .in vivo RNA structures in GC-rich species tend to maintain structural flexibility [Considering that GC content affects RNA secondary structure based on thermodynamics , 63, 64,xibility . The pooFor transcription asymmetry, both gene-body CG methylation and histone modifications were suggested to be key factors in common wheat . SeveralmRNAs involved in biological functions related to abiotic and biotic stress responses, responses to metal ion and phytohormone signaling, preferred this RNA structure-mediated translational subgenome asymmetry Fig. . This prRiboSNitches were first proposed to interpret human disease-associated SNVs located on individual UTRs or non-coding RNAs . RecentlThe fundamental elements of RNA structure are the nucleotide pairs involved in making base pairs (G-C and A-U) . To mainThrough domestication humans have influenced the evolution of the wheat genome via selected breeding of favored agronomic traits . For exaFinally, we validated functional associations with these selected riboSNitches. We determined that a single riboSNitch between two homoeologs in the 5′UTR was sufficient to switch RNA structures, subsequently leading to significant differences at the translational level in a reporter assay Fig. . This riTranslational subgenome asymmetry occurs in tetraploid wheat, with ~55% of homoeologs showing non-balanced translation efficiencies. RNA structure plays a prevalent role in contributing to this translational subgenome asymmetry. We identified 3564 riboSNitches between the two subgenomes that had arisen upon polyploidization or during domestication, which might contribute to shaping the translation landscape of wheat. Our first translatome and in vivo RNA structurome of polyploid wheat presented here provides the context and basis for future studies of polyploid evolution and for developing new strategies for wheat molecular breeding.n = 4x = 28, BBAA) used in this study were Triticum turgidum ssp. durum cv. Kronos (durum wheat). Wheat seeds of tetraploid durum wheat cv “Kronos” were obtained from the John Innes Centre Germplasm Resource Unit. The seeds were washed with 70% ethanol for 30 s for surface sterilization, followed by washing 3 times with distilled water. The seeds were then soaked in distilled water for 24 h and plated to Petri dishes with 3 layers of wet filter paper. The Petri dishes were placed in a growth chamber at 22°C in the dark for 4 days, with distilled water added every day to keep the filter paper wet.The tetraploid wheats  fragments were amplified using CloneAmp HiFi PCR Premix (Clontech). PCR products were further introduced into the expression vector inter2 digested with BamHI and SmaI using In-Fusion (Clontech). The sequences of ssDNA and primers are listed in Additional file Single-stranded DNA (ssDNA) fragments of 5′UTRs of Polysome profiling was performed as described with optimization . BrieflyArabidopsis with modifications [The SHAPE chemical 2-methylnicotinic acid imidazolide (NAI) was synthesized as described . In vivoications . BrieflyLibraries of SHAPE-structure-seq were prepared as described . PolyA-s2, 5 mM DTT), and 0.5 μl Superscript III (Thermofisher) was added. Incubation at 50°C for 20 min was allowed for cDNA synthesis, followed by incubation at 85°C for 10 min to inactivate Superscript III. 0.5 μl of NaOH (2M) was added and incubated at 95°C for 10 min to degrade the cDNA hybridized RNA. 10 μl of 2X stopping dye , 20 mM Tris (pH 7.5), orange G) was added and incubated at 95°C for 5 min, and further kept on 65°C until loading to 8% Acrylamide:Bis-Acrylamide-Urea gel for electrophoresis. For the sequencing lanes, unprobed RNA was dissolved in 5 μl water and 1 μl 10mM of corresponding ddNTP (Roche) was added at the beginning of the reaction. The gel was scanned using Typhoon FLA 9500 system  and quantified using ImageQuant; SHAPE reactivity was normalized using a 2–8% standard method [One microgram of the total RNA of −NAI or +NAI probing was dissolved in 6 μl water; 1 μl of Cy5 labeled RT primer (5 μM) for 18S rRNA . The lysate was centrifuged at 13,000 rpm for 1 min before diluting the clear supernatant 20 times with PLB. The diluted supernatant was subjected to dual luciferase assay using the Dual-Luciferase Reporter Assay System (Promega) according to the manufacturer’s manual. To quantify the mRNA abundance of Firefly luciferase (F-luc) or Renilla luciferase (R-luc), RNA isolated with TRIzol or RNeasy Plant Mini Kit was digested using RNase-free TURBO™ DNase (Ambion). cDNA was synthesized using SuperScript III First-Strand Synthesis System (Thermofisher). Quantitative PCR was performed using a LightCycler 480 SYBR Green I Master (Roche) using CFX96 Touch Real-Time PCR Detection System (BIORAD) according to the manufacturer’s protocol. Translation efficiency (TE) of dual luciferase assay was calculated as described [Sequencing-confirmed vectors were transformed to escribed , 78. ProThe raw reads were filtered through both quality control and adaptor trimming. The trimmed reads were mapped to durum wheat genome assembly (Svevo RefSeq 1.0)  using HIArabidopsis thaliana which shares high sequence similarity [Given the absence of rRNA phylogenetic structure models for the tetraploid durum wheat cultivar, Kronos, we used the 18S rRNA structure model in milarity . We calcmilarity .The tRNA adaptation index (tAI) was calculated using the formula:wk denotes the relative adaptiveness of codon k [n denotes the length of CDS.where  codon k  and n deThe codon adaptation index (CAI) was calculated using the formula:fi denotes the frequency of codon i and max(fj) denotes the most frequent synonymous codon amino acid j [where o acid j .ST value of each SNV [ST value was calculated according to the following equation:To identify single-nucleotide variations (SNV) between homoeologous gene pairs, local sequence alignment was performed using the “Mafft” tool . Bases aeach SNV . The FSTπ is the mean allele frequency and σπ2is the variance in allele frequency among populations [where ulations .T. turgidum spp. Durum groups using the VCF files [To calculate the conservation ratio, we firstly calculated the frequency of each nucleotide of a given SNP from 13 tetraploid CF files .N represents the number of different nucleotides observed at the polymorphism and c denotes the counts. The nucleotide with the maximum allele frequency on a given SNP is regarded as the major allele.where For individual transcript, conservation ratio of riboSNitch SNP denotes to the rate of riboSNitch SNP counts which are major alleles, regarding to the total counts of riboSNitch SNPs. The conservation ratio of non-riboSNitch SNP denotes to the rate of non-riboSNitch SNP counts which are major alleles, regarding to the total counts of non-riboSNitch SNPs.http://www.r-project.org). Statistical methods and significance are indicated in the main text or figure legends for individual tests.All analyses were performed using R programming language  in A and B subgenome. Figure S7. Comparison of SHAPE reactivities in vivo for homoeologous pairs in wheat. Figure S8. SNV affects RNA structure in vivo.Additional file 2: TableS1. Translation efficiency of homoeologs of A and B subgenome in tetraploid Kronos.Additional file 3: TableS2. Base-pairing probability of RNA structures of homoeologs of A and B subgenome in tetraploid Kronos.Additional file 4: TableS3. The list of single nucleotide variations between homoeologs of A and B subgenome in tetraploid Kronos.Additional file 5: TableS4. The list of riboSNitch between homoeologs of A and B subgenome in tetraploid Kronos.Additional file 6: TableS5. Primers used in this study.Additional file 7. Review history.


Bacillus species share a similar protein tertiary structure with a high degree of amino acid sequence conservation. However, they form dimers that differ in conformation and stability. Here, we have addressed the issues (1) whether the homologous RNases also have distinctions in catalytic activity towards different RNA substrates and interactions with the inhibitor protein barstar, and (2) whether these differences correlate with structural features of the proteins. Circular dichroism and dynamic light scattering assays revealed distinctions in the structures of homologous RNases. The activity levels of the RNases towards natural RNA substrates, as measured spectrometrically by acid-soluble hydrolysis products, were similar and decreased in the row high-polymeric RNA >>> transport RNA > double-stranded RNA. However, stopped flow kinetic studies on model RNA substrates containing the guanosine residue in a hairpin stem or a loop showed that the cleavage rates of these enzymes were different. Moreover, homologous RNases were inhibited by the barstar with diverse efficiency. Therefore, minor changes in structure elements of homologous proteins have a potential to significantly effect molecule stability and functional activities, such as catalysis or ligand binding.Small cationic guanyl-preferring ribonucleases (RNases) produced by the  RNA molecules represent promising therapeutic targets for a multitude of important human diseases including infections and cancer. In recent years, a few RNA-targeted drugs that can modulate RNA functions have been identified ,2. RibonBacillus pumilus, a member of the N1/T1/U2 family (IPR000026) [One of the widely known bacterial RNases is binase from R000026) . It was R000026) ,14,15,16R000026) . The stuR000026) ,17.Bacillus species, such as B. amyloliquefaciens (barnase) [B. altitudinis  [B. licheniformis  [B. amyloliquefaciens cells, the hydrolytic activity of barnase is controlled by the inhibitor protein barstar which is absent in B. pumilus, B. altitudinis and B. licheniformis; nevertheless, barstar can inhibit binase in vitro, though with a lower affinity than barnase [RNases homologous to binase are produced by some other barnase) , B. altibalnase) ,20 and Balifase) . The bacalifase) . RNA hydalifase) . The RNaalifase) . The levalifase) ,21,25. I barnase ,27.Bacillus form dimers in vivo [Recent studies have shown that the quaternary structure of RNases plays a key role in the functional activity of the enzymes, particularly, catalytic properties, protein–protein interaction and subsequent biological effects ,28. The  in vivo  and high in vivo . DespiteBacillus with their functional activities, such as the ability to interact with different RNA substrates and the inhibitor protein barstar. For the first time, the secondary structures of ribonucleases, their ability to form oligomers and hydrolyze different RNA substrates as well as to interact with barstar were characterized comparably.Here, we aimed to correlate the structural features of homologous RNases from Bacillus have quite similar three-dimensional structures [Being close homologs, the guanyl-preferring ribonucleases from ructures . Despiteructures . Binase ructures . It is cructures . Conformructures , which cructures .To gain the precise details on local conformations in the RNase protein structures, we have predicted and compared secondary structure profiles of binase, balnase and balifase . It shouThe different secondary structures correspond to different solvent accessibilities of residues, with β-sheets being the most inaccessible structures, the helical conformation having an intermediate value, and random coils and turns being the most accessible folds ,35. The In all folds, there is a noticeable difference between the hydrophobic and hydrophilic residues. To represent the hydrophobicity value of a polypeptide, a grand average of hydropathicity index (GRAVY) is used. Its values vary between −2 to +2 for most proteins, with the positively rated proteins being more hydrophobic. We have calculated that the GRAVY index is more negative for balifase (−0.643) than for binase (−0.416) and balnase (−0.393), suggesting a higher level of its hydrophilicity. This is due to the increased number of lysine and glutamic acid residues in balifase (8 lysines and 6 glutamic acids) as compared to binase and balifase (5 lysines and 3 glutamic acids) which are the most accessible, irrespective of secondary structures. So, it seems that homologous RNases have some distinctions in the size of solvent accessible regions. It is proposed that such differences may affect protein–protein interactions and/or protein activity ,37.To validate the predicted secondary structures of RNases, we have measured their circular dichroism (CD) spectra . The CD The obtained CD spectra have revealed that the short-wavelength minimum of ellipticity is quite wide in binase and falls at 216 nm, indicating an approximately equal contribution of β-structures and α-helices . In balnThe differences in secondary structures may account for differences in the folding and quaternary structure of homologous proteins. The differences in the CD spectra of homologous RNases are probably associated with distinctions in their quaternary structure. Different mechanisms of monomers binding are possible during the dimerization of RNases, resulting in various types of dimers . At highGuanyl-preferring RNases can form not only dimers of different conformations , but eveWe have also measured the zeta potential of RNases. It has shown that all of them have negative protein surface charges. Zeta potential values of binase, balnase and balifase were measured as −5.44 mV, −16.3 mV and −24.6 mV, respectively.Thus, substitutions in the primary structures of homologous RNases mediate the differences in their secondary structure which may influence protein stability, folding and aggregation as was shown for some proteins ,46,47.Various types of RNA serve as a substrate for RNases and represent their main molecular target in the cell. It was shown that various dimeric forms of RNase A have differences in catalysis of RNA substrates . Since bloop-substrate) or the stem (Gds-substrate)  . Oligoribstrate) . The cleloop substrate was 9-fold higher than that of balifase. At the same time, the rate constant for the formation of a catalytic complex with the Gds substrate was 30-fold higher for binase than for balifase. It should be noted that balifase was more sensitive to the location of the guanosine residue at the hairpin loop or stem. The rate constant value of the interaction of balifase with the Gloop substrate was 11-fold higher as compared to the Gds substrate. As for binase, this ratio was about 3 , which allowed calculating the values of the observed rate constants . The rat about 3 .Rana pipiens (onconase) degrades tRNA and dsRNA, α-sarcin (Aspergillus RNase) cleaves 28S rRNA and colicin E3 (Escherichia coli RNase) hydrolyzes 16S rRNA [Thus, the homologous guanyl-preferring RNases are capable of cleaving diverse RNA substrates but with different rates and efficiencies. The ability to hydrolyze different types of RNA was shown for many RNases. RNase from frog 16S rRNA . dsRNA iB. amyloliquefaciens produces a specific inhibitor of its RNase barnase termed barstar. Barstar is a small protein (10 kDa) which tightly binds to barnase at a 1:1 ratio [ds-substrate , B. altitudinis , B. licheniformis  and B. amyloliquefaciens (barnase) were obtained using previously described three-step procedure [Homogeneous protein preparations of RNases from rocedure ,30.B. amyloliquefaciens was extracted using Genomic DNA Purification Kit  according to the manufacturer’s protocol. Barstar gene was amplified from genomic DNA by polymerase chain reaction using Pfu DNA polymerase , forward (5′-TAGTCGGCTCAGCGTTTCCATATTGTTCATCTCC-3′) and reverse (5′-TACTCGCTCGAGATGAAAAAAGCAGTCATTAAC-3′) oligonucleotides, which included BlpI and XhoI restriction sites (underlined), correspondingly, for the subsequent cloning of barstar gene into the pET15b expression vector . The purified PCR product as well as pET15b vector were digested with BlpI and XhoI restriction endonucleases and ligated. Chemically competent cells of Escherichia coli JM109 were transformed with the resultant plasmid pET15b-brst. Recombinant clones were selected on Luria-Bertani agar plates containing 100 μg/mL ampicillin. The integrity and correctness of the insert on pET15b-brst plasmid were checked by PCR, restriction analysis and Sanger sequencing.Genomic DNA of E coli BL21 (λDE3) was transformed with pET15b-brst plasmid. Cells were grown with shaking on Luria-Bertani media containing 100 μg/mL ampicillin at 37 °C until the OD590 reached 0.4–0.8 units. Then 0.5 mM IPTG was added and cells were further grown for 3 h. Cells were harvested by centrifugation at 5000× g for 10 min. The cell pellet was resuspended in the binding buffer  and sonicated 10 times for 20 sec on ice bath. Lysed cells were centrifuged at 12,000× g at 4 °C for 30 min. Purification of barstar from the cell-free supernatant was done using NGC Chromatography System  using Ni-NTA Profinity IMAC resin  equilibrated with the binding buffer. The bound enzyme was eluted with the elution buffer . The collected fractions were desalted on Bio-Gel P-6 column  and analyzed by SDS-PAGE in 16% polyacrylamide gel with 0.1% SDS.For protein purification, the expression strain of 4OH in water at ambient temperature for 16 h. The 2′-O-TBDMSi protecting groups were removed by a freshly prepared NMP-Et3N-Et3N · 3HF mixture  at 65 °C with stirring for 1.5 h, followed by ethoxytrimethylsilane treatment and precipitation of oligoribonucleotides with diethyl ether. Deblocked oligoribonucleotides were isolated by denaturing 15% PAGE. The optical density of oligonucleotide solutions was measured on a NanoDrop 1000 spectrophotometer  relative to deionized water. The molar extinction coefficient of oligoribonucleotides or their conjugates at 260 nm was used to calculate the oligonucleotide concentrations in the initial solution. The model of oligoribonucleotides’ sequences are shown in Oligoribonucleotides were obtained via the solid-phase phosphoramidite methods on the ASM-800 synthesizer  using the corresponding phosphoramidites of N-protected 2′-O-tert-butyldimethylsilyl (2′-O-TBDMS) ribonucleotides . The 5′-end of oligoribonucleotide was tagged by fluorescein residue using fluorescein phosphoramidite . Oligonucleotides bearing a fluorescence quencher BHQ1 at the 3′-end were obtained using a modified 3′-BHQ-1 CPG (Black Hole Quencher) support . Oligoribonucleotides were deblocked under standard mild conditions using 30% NHloop substrate were used in concentration of 0.5 μM.The kinetics of the enzymatic process was registered through the change in a fluorescence intensity of the fluorescein residue, which is a part of the model substrates shown in F is the fluorescence intensity of FAM at time t; A is the coefficient; obsk is the determined rate constant; C is the fluorescence intensity at t → ∞.For calculation of the enzymatic reaction rate constants, each kinetic curve was approximated by the sum of exponents according to the Equation (1) using the OriginPro 8.0 software package :ds substrate by binase, balifase or RNase A at the presence of barstar was carried out using the following procedure. Ten microliters of the enzyme (0.7 μM) and barstar (0.33–5.3 μM) mixture in a buffer solution were added to 10 μL of buffer solution containing the substrate (1.0 μM) and Brst (0.33–5.3 μM). After the reaction mixture had been rapidly stirred for a set period of time , the reaction was stopped by adding 20 μL of the solution containing 9 M urea and 25 mM EDTA, and incubated for 2 min at 96 °C. SDS-PAGE was performed in a Protean II xi vertical thermostated chamber  at 50 °C and 200–300 V. The gel was visualized using an E-Box CX.5 TS gel documentation system . The substrate cleavage efficiency was determined using Gel-Pro Analyzer 4.0 . The cleavage efficiency was calculated as the ratio of the peak area of the cleavage product to the sum of peak area of the product and the initial oligoribonucleotide. The error in determining the modification extent was usually ≤20%.A kinetic analysis of the cleavage of GCD spectra of RNases were measured in the 190–260 nm wavelength range on the Jasco J-1500 spectrometer  as described in . The secE. coli  using a SmartSpec Plus Spectrophotometer , as described earlier [The catalytic activity of RNases was measured against yeast high-polymeric and transfer RNA, and double-stranded RNA extracted from  earlier . One uniThe average particle size and size distribution of RNases were determined by dynamic laser scattering (DLS) technology using Zetasizer Nano ZS . Particle size was presented by volume distribution, and size distribution was evaluated by polydispersity index (PDI). The solutions were suitably diluted with ultrapure water, filtered through 0.22 nm filter and sonicated for 2 min to form a uniform dispersion before placing the sample into a quartz cuvette. Measurements were performed by ten consecutive runs on individual sample, 30 s each. The zeta potential of RNases was determined by electrophoretic light scattering technique. A diluted sample of RNase in water was allowed to stabilize at 25 °C and was placed in clear disposable zeta cells. The electrophoretic mobility between the electrodes was converted to zeta potential based on Smoluchowski equation.http://raptorx.uchicago.edu/StructurePropertyPred/predict/ (accessed on 16 September 2021)). Visualization of secondary structure predictions was performed with the help of 2dSS webserver (http://genome.lcqb.upmc.fr/2dss/index.html (accessed on 20 September 2021)) and Inkscape software version 1.0.1 (https://inkscape.org (accessed on 20 September 2021)).The DeepCNF  algorithm at Raptor X server was used to predict secondary structure, solvent accessibility, and disorder regions in RNase proteins (http://www.jmol.org/ (accessed on 6 October 2021)) was used to visualize 3D structures.The modeling of protein–protein interaction was performed by the direct method through a search for structures with minimum Gibbs free energy using the ClusPro server . The algEach experiment was performed in triplicates. All data are presented as the mean ± standard deviation of the mean (SD). Statistical tests were performed using GraphPad Prism 8 software .RNases are considered as perspective therapeutics due to their biological effects. In this study, we have compared structural and functional features of homologous guanyl-preferring RNases from Bacillus, in order to address the point of whether distinctions in non-core amino acid residues can account for the dissimilarities in the structural organization of these proteins and their interaction with different molecules. We have identified that the activity levels of homologous RNases towards natural RNA substrates are similar and decrease in the row high-polymeric RNA >>> transport RNA > double-stranded RNA. However, kinetic studies on model RNA substrates have demonstrated that the cleavage rates of these enzymes are different and they are inhibited by barstar with diverse efficiency. Thus, despite the fact that RNases display the conservation of a number of active-site residues involved in substrate and inhibitor interactions, their binding rate constants differ significantly. Circular dichroism analysis has revealed significant distinctions in secondary structures of homologous RNases that can affect protein folding and oligomerization, as proved by the dynamic light scattering assay. Therefore, minor changes in structure elements of homologous proteins have a potential to significantly affect molecule structural organization, and stability and functional activities, such as catalysis or ligand binding. It should be taken into account for the developing of novel biotherapeutics based on homologous RNases since their biological effects, efficiency and safety can be changed.


C. elegans hyperactive DEG/ENaC channels MEC-4(d) and UNC-8(d). microPublication Biology. 10.17912/micropub.biology.000412.For Johnson, CK; Miller, DD; Bianchi, L (2021). Effect of the protease plasmin on The authors correct the following:1. The name of the author David D. Miller should read David M. Miller III2. The affiliations1University of Miami2Vanderbilt Universityare corrected to:1Department Physiology and Biophysics, University of Miami Miller School of Medicine, Miami, Florida, USA.2Department of Cell and Developmental Biology, and Neuroscience Program, Vanderbilt University, Nashville, TN, USA.mec-4 and unc-8 are as follows:3. The allele names that were used as reference for the cDNA for u231– MEC-4(d) is MEC-4(A713T), corresponding to allele n491– UNC-8(d) is UNC-8(G387E), corresponding to allele https://www.dmbr.ugent.be/prx/bioit2-public/SitePrediction/) is added as follows:4. The reference for the SitePrediction website :319-23. doi: 10.1016/j.tibs.2009.04.001. Epub 2009 Jun 21. PMID: 19546006.These corrections do not alter the conclusions or discussion of this microPublication.


The emulsomes were characterized for entrapment efficiency (EE%), zeta potential (ZP), particle size (PS), morphology, and ex-vivo permeation through the nasal mucosa. The selected formula was evaluated in mice for its in-vivo bio-distribution in comparison with EH intranasal and intravenous solutions. Drug targeting efficacy (DTE%) and nose-to-brain direct transport percentage (DTP%) were calculated. The optimization formulation showed a nanoparticle size of 177.01 nm, EE 79.44%, and ZP = 32.12 ± 3.28 mV. In addition, in-vitro permeability studies revealed enhanced drug permeability with suitable mean residence time up to 120 ± 13 min. EH-emulsomes were stable under different storage conditions for three months. In vivo examination and pharmacokinetic drug targeting parameters revealed EH transport to the CNS after EH nanoparticle nasal administration. Histopathology study showed no ciliotoxic effect on the nasal mucosa. From the results, it can be confirmed that the emulsomes formulation of EH proved safe direct nose-to-brain transport of EH after nasal administration of EH emulsomes.Migraine is one of the major symptoms of many psychiatric and mental disorders like depression and anxiety. Eletriptan Hydrobromide (EH) is a well-tolerated drug in migraine treatment, but suffers from low oral bioavailability and low brain targeting after oral delivery. New nasal mucoadhesive EH-emulsomes development could be a new means to direct the drug from the nose-to-brain to achieve rapid onset of action and high drug concentration in the brain for acute migraine treatment. Eletriptan mucoadhesive emulsomes formulations were prepared using thin-film hydration method and 2 Migraine is a neurologic episodic headache attack, which directly affects over one billion people across all world regions . It was Eletriptan Hydrobromide (EH), a second generation triptan, is a well-tolerated drug in migraine treatment . It actsThe intranasal route introduces the drugs directly to the brain by direct neuronal transport, via olfactory and trigeminal nerves. Nasal route is considered a non-invasive brain targeting route of administration. It can overcome the oral route limitations: first-pass metabolism effect and limited -BBB passing ,12. In aEmulsomes are defined as colloidal carriers containing solid or semisolid inner core, stabilized by phospholipids in high concentration, in the form of o/w emulsions . They caHence, the goal of this project is to develop stable EH encapsulated emulsomes coated with mucoadhesive polymer aiming at a direct nose-to-brain targeting strategy to enhance migraine treatment. Suitable formulation components were selected after extensive investigations, then the developed formulation was characterized and optimized. The assessment of the in-vitro permeation from the prepared mucoadhesive emulsomes through nasal mucosa was performed in addition to the assessment of the brain-targeting efficiency of the prepared emulsomes through in-vivo study in rats. Evaluation of the histological effect of applying EH emulsomes formulation on the nasal mucosa was done to establish the safety and efficacy of EH in the treatment of migraine to ensure effective treatment of the major symptom of many psychiatric and mental disorders.® 888 ATO (CA) was obtained as a gift from GATTEFOSSE, Saint-Priest, France. Glyceryl mono-stearate (GMS), Tripalmitin (TP), Trilaurine (TL), Stearic acid (SA), Triton X100, and Tween 80 were purchased from El-Gomheria Co., Cairo, Egypt. Trimethyl chitosan (TMC) of low molecular weight, was purchased from Sigma Aldrich, Cairo, Egypt. All other chemicals were of analytical grade and were purchased from El-Gomhoria Co., Cairo, Egypt.EH was obtained as a gift from Pfizer, Cairo, Egypt. Phosphatidylcholine (PC) from soybean lecithin, containing not less than 94% (PC) was obtained from Alfa Aesar . Compritol® 888 ATO (CA), Glyceryl mono-stearate (GMS), Tripalmitin (TP), Trilaurine (TL), and Stearic acid (SA) was assessed as follows.Eletriptan Hydrobromide (EH) solubility in different solid lipids namely: CompritolAn excess amount of EH was added to 3 g of each lipid into a screw-capped vial and mixed using vortex . The mixture was shaken for 2 days using a thermostatically controlled shaker  at 70 ± 2 °C.The mixture was centrifuged at 3000 rpm for 20 min using a centrifuge with an integrated heating system adjusted at 70 ± 2 °C  then filtered using a 0.45 filter membrane . The whole filtration assembly was kept at 70 °C in a controlled oven for a period of 20–30 min to prevent lipid solidification at room temperature. From the filtered supernatant, an accurately weighed amount was taken and dissolved in 10 mL methanol and measured after suitable dilution (s) using a previously developed and validated HPLC method . In brie3 design. Three independent factors were screened, including phosphatidylcholine: compritol (PC: CA) molar ratio. (X1), EH: total lipids molar ratio (X2), and trimethyl chitosan concentration (TMC) w/v%. Each was screened at two levels. The high-level factor was coded as +1 while the low level was coded as −1, to give a design with minimum 8 formulations in addition to triple center points (mid-level) of independent factors for improved statistical significance  was implemented for statistical analysis of the responses, and statistical significance was at p = 0.05.Design Expert 10.0.1 Stat Ease.Inc. software  was used to design the experimental runs using full factorial 2ificance . The resv/v) in water, previously heated to 70 ± 2 °C, was used as a hydration medium with the aid of small glass beads  to facilitate the film hydration until suspension is formed. After cooling to room temperature, the mixture was sonicated using a probe sonicator  in an ice-bath for three cycles of 5 min  with 5 min intervals between cycles. The emulsomal mixture was stored at 4 °C for further evaluation. The detailed composition of EH-loaded emulsomes is shown in v/v) of the hydration medium.EH-loaded mucoadhesive emulsomes were formulated by using the thin-film hydration method formerly described by Zhou and Chen, 2015  with sliEE% = EH entrapped amount/EH initial amount × 100DLC was determined by the following Equation : DCL =  weight of emulsomes The experiment was done in triplicates and results were expressed as mean ± SDEntrapment Efficiency (EE%) and Drug Loading Capacity (DLC) determination of EH-loaded mucoadhesive emulsomes were evaluated for their EE% ratio through the direct method. EH-loaded mucoadhesive emulsomes were separated from the un-entrapped drug through a cooling centrifuge at 10,000 rpm for 45 min. A determined amount of the prepared emulsomes was disrupted completely into 10 mL 1% Triton X100 and 20 µL injected into a HPLC system for determination of EH concentration using a previously developed and evaluated method . EE% wasThe particle size of the prepared EH-loaded mucoadhesive emulsomes was determined by dynamic light scattering  after suitable dilution using distilled deionized water. All measurements and analytical settings were controlled using standard operating procedures. All measurements were carried out in triplicate, and the mean and standard deviation were calculated.n = 3) ± SD.Zeta potential of the prepared EH-loaded mucoadhesive emulsomes was measured under regular operating circumstances using a Zeta-sizer . Distilled deionized water was used to dilute the samples. The results are described as mean values , Variel Avenue, Chatsworth, CA, USA) using phosphate buffered saline (pH 7.4) medium .Less than 1 h after slaughtering the sheep, the nasal mucosa, except the septum part, was isolated and the fatty tissues and different tissues were removed gently. Obtained mucosa was washed gently with distilled water and kept into isotonic saline at −20 °C till use . The exp2 and 0.12 cm thickness was used for permeation study [The prepared mucosal specimen of appropriate size having an effective surface area of 1.55 cmon study . The speon study .Aliquots of 1 mL of the receptor medium were removed at appropriate time intervals and immediately replaced with fresh medium pre-heated to 37 ± 0.5 °C. Samples were injected into an HPLC system for the determination of EH concentration. Each experiment was performed in triplicates and obtained results were expressed as mean ± SD.2/h) was computed from the quantity of EH, which permeated through the nasal mucosa (Q) divided by the membrane surface and the time duration. The permeability coefficient  was calculated from Jss and the initial drug concentration (C0) as given below [The steady-state flux  6.4, were prepared and 100 mg of each formulation were centered on the agar plate, and to assure the sample, attachment was left for 5 min. After that, the agar plates were attached to USP disintegration test apparatus  and moved up and down in PBS pH 6.4 at 37 ± 0.5 °C. The residence time in seconds (RT) was recorded at the time the formulations were completely detached from the agar. The experiment was done in triplicates for each formulation and obtained results were expressed as mean ± SD.The residence time of the prepared mucoadhesive emulsomes was assessed by a formerly mentioned method . Agar pl® software  to obtain the optimized formulation.After the all responses were analyzed, constraints  on dependent (responses) and independent variables (factors) were applied using Design-ExpertThe morphological evaluation of the optimized EH-loaded emulsomal formulation was conducted by (TEM)  operating at an accelerating voltage of 80 kV. A drop of the sample was deposited on a carbon-coated copper grid to form a thin film. Before the film dried on the grid, it was negatively stained with 1% phosphotungstic acid (PTA). A drop of the staining solution was applied to the film, and the excess was drained off with filter paper. The grid was allowed to air dry thoroughly and samples were viewed in a transmission electron microscope.Samples of the optimized formulation were stored in a tightly closed vial at two different conditions; the first was at 4 °C and controlled humidity of 75% RH and the second at 25 ± 2 °C and controlled humidity of 75% RH. After 3 months, samples were taken and stability study was assessed through EE%, particle size, and Zeta potential measurements in addition to visual examination of the formulation for any color change or sedimentation .Formulation (F10) was selected, based on statistical optimization, to be evaluated in-vivo for its biodistribution in mice in comparison with EH nasal and intravenous solutions.Mus musculus) weighing 25–30 g provided by the National Research Centre’s animal house colony  were used in the current study. Animals were offered free access to a standard diet and tap water ad libitum. They were housed for one week before the experiment for acclimatization at room temperature and natural light/dark conditions. The National Institutes of Health Guide for the Care and Use of Laboratory Animals  and the National Research Center–Medical Research Ethics Committee (NRC-MREC) for the use of animals were followed in this investigation. The study protocol was approved by the ethical committee of Al-Taif University, KSA, Approval number: 43-021, 29-9-2021.Adult male Swiss Albino mice  aqueous solution of EH  (10 µL in each nostril).Group 2: Intravenous (i.v) aqueous EHsolution  that was injected through the lateral tail vein of the mice.Group 3: The selected EHformulation at a dose equivalent to 1 mg/kg body weight was instilled into the nose of the mice fixed in a prostrate position.Ninety-six mice were randomly allocated into three equal groups (32 mice each) and were administered to the tested treatments as follows:Intranasal administration (i.n) was done using a micropipette at a constant volume 10 µL in each nostril  attached to 0.1 mm polyethylene tube and was performed on rats laid on their backs in a slanted position gently with allowing the animals to inhale all the preparation [The experiments extended for 8 h, and at each predetermined time interval , blood samples were obtained under anesthesia from each group (four mice) via retro-orbital venous plexus into-heparinized test tubes. Blood samples were collected and left to remain at room temperature for 10 min before being centrifuged at 4 °C using a cooling centrifuge  at 3000 r/min for 10 min and plasma was obtained. Mice were then sacrificed by cervical dislocation under anesthesia. Brains were dissected out, washed three times with normal saline, and then freed from any adhering tissues or fluids and weighed. Brains were homogenized separately with normal saline using a tissue homogenizer . Plasma samples and brain homogenates were stored at 20 °C until use.brain/AUCblood after intranasal administration to that after intravenous administration. The drug targeting efficacy (DTE%) and nose-to-brain direct transport percentage (DTP%) were calculated as follows [(0–8) fraction contributed by systemic circulation through the BBB following intranasal administration.EH concentration in both plasma and brain samples was measured using a standardized and validated high-performance liquid chromatography method . EH brai follows :(1)DTE%=(0–8) (brain) following intravenous administration and intranasal administration, respectively, while Pi.v and Pi.n are the AUC (0–8)(blood) following intravenous and intranasal administration, respectively.Bi.v and Bi.n are the AUC To study the effect of the selected EH emulsomes formulation on the integrity of the nasal mucosa in mice, the mice noses were separated at the end of the in vivo biodistribution study and specimens from the nasal mucosa were collected. Nasal specimens were fixed in 10% neutral buffered formalin before being washed, dehydrated, clarified, and embedded in paraffin. For histological investigation, the paraffin blocks were sectioned at 4–5-micron thickness and stained with hematoxylin and eosin. The sections were examined under ×400 magnification using a binocular Olympus CX31 microscope .p < 0.05 was judged significant with 95% percent confidence intervals.The data from all experiments were reported as the mean value ± SD. One-way analysis of variance (ANOVA) was used to assess the statistical data, and EH was found to have the highest solubility in Compritol (CA), 37.04 ± 2.23 mg/g, followed by Tripalmitin (TP), 27.90 ± 2.10 mg/g, The main goal of emulsomes formulation is to obtain formulae with uniform nanoparticle size, maximum stability, and entrapment efficiency. All the selected lipids should be biocompatible, biodegradable, non-toxic, and with appropriate concentrations. The prepared emulsomes should not be irritant or cause nasal mucosa damages .v/v to improve the bilayer formation of the emulsomes and improve the carrying capacity of the lipid particles, even in the presence of an aqueous solution of the drug [Cholesterol was incorporated in all formulations to act as a stabilizing agent as it can induce the liquid crystal phase formation by altering the core packaging structure. Also, it can stabilize the outer phospholipid layers resulting in entrapment efficiency increasing and drug leakage reduction . Tween 8the drug .In this study, trimethyl chitosan (TMC), which is the simplest form of quaternized chitosan, was used as it is water-soluble over a wide pH range, has higher bio-adhesive and permeation properties than chitosan . Results2 value > 0.97. Statistical analysis results are shown in ANOVA results indicated that all studied linear terms , corresponding to the investigated variables, have a significant effect on all the tested responses at a 95% level of significance. The interaction between TMC concentration and either PC: CA molar ratio or EH: T. lipids molar ratio was also found to be significant at the same level. The average EE% of the prepared EH emulsomes ranged from 79.73 ± 2.96 to 35.42 ± 3.84%, All the investigated factors were found to provide a significant effect on the particle size of the formulated EH emulsomes as indicated in Increasing EH concentration to the lipid ratio led to a significant increase in the EE% and consequently increases the particle size due to increasing the drug content entrapped in the prepared emulsomes.TMC is a positivly charged polysaccharide. This positive charge causes electrical repulsion among polymeric chains resulting in steric hinderance, which contributes to the size expansion of the particles ,44, espeThe zeta potential value was represented in Higher ZP values observed after increasing the amount of TMC confirm the incorporation of the polyelectrolyte (TMC) in the vesicles’ structure, more possibly as a layer on the surface of the vesicles .w/v resulted in a significant increase in the RT at constant PC: CA and EH: T. lipids ratios. TMC is a mucoadhesive material, its higher water uptake and swelling results in increasing the adhesiveness of the prepared emulsomes and elongated the RT [Increasing the TMC ratio from 0.25 to 0.5 d the RT . Unlike Although a higher TMC ratio resulted in longer RT, it resulted in significantly lower Kp at constant PC: CA and EH: T. lipids ratios. This may be related to the fact that interaction between TMC and the phospholipid layer resulted in more stable vesicles, which delayed the drug release and thus decreased the permeability coefficient  in additThere was an inverse relationship between the vesicular size and permeability coefficient as vesicles with smaller sizes had higher Kp. It has previously been noted that when vesicular size reduces, the attributed surface area: volume ratio increases; indicating that more drugs could be closer to the particle surface, potentially leading to improved drug release and permeation .EH- emulsomes chitosan-coated particles have the ability to regulate EH release, minimize its toxicity, and improve its therapeutic effectiveness. There was an interaction between increasing the PC: CA molar ratio and EH: T. lipids molar ratio, The optimum levels of the variables were predicted by applying response constraints. The computed desirability was 0.972. The prepared optimized formulation was subjected to characterization. No major residual error was found indicating the validity of numerical optimization for this study. The optimized formulation levels are demonstrated in The capability of emulsomes to maintain the EH entrapment efficiency and to preserve their particle size, during refrigerated storage and at room temperature for three months was assessed. Non-significant difference was found concerning the EE%, particle size, or Zeta potential of the stored formulation (F10) at both conditions, 4 °C and ambient temperature, as shown in max and AUC(0–8) than i.v and i.n EH solution. The higher drug concentration in the brain after EH-emulsomes administration could be attributed to the nano vesicle size, which allows drug particles to be transported deeper into the olfactory epithelial cells layers [EH concentration in mice plasma and brain after administration of different treatments against time is shown in s layers  and trans layers . The pers layers ,56.max in the brain than in plasma after EH-emulsomes administration indicated the rapid passage and targeting of the drug to the brain. The previous result could also be proved by the high DTE% and DTP% values. The latter demonstrates the capacity of the EH-emulsomes formula to deliver EH directly to the brain with greater concentrations and a faster onset of action.The shorter TEnhanced in vivo bioavailability of EH from the prepared nasal emulsomes can be correlated to the in vitro enhancement of drug permeation through the nasal mucosa. This enhancement is related to high mucoadhesive effect of TMC, which leads to longer residence time with lower mucociliary clearance enabling the emulsomes particles to remain attached to the nasal mucosa, resulting in improved drug permeation . In addiThe higher DTI and DTP indicate that there is more EH concentrated in the brain rather than in blood plasma, which means that the drug concentration does not depend on drug bio-distribution, but the drug transport is by a direct axonal CNS drug transport  and more3 design to evaluate the effects of formulations variable on dependent variables. Prepared EH emulsomes containing phosphatidylcholine: Compritol (CA) molar ratio equal to 2, EH to total lipids molar ratio 0.5, and trimethyl chitosan concentration 0.25% w/v were spherical in shape with particle size 178.42 ± 21.36 nm, 79.73 ± 2.96 entrapment efficiency percent, and positive zeta value of 32.12 ± 3.28, which facilitate the nose-to-brain targeting. The shorter brain’ Tmax after EH-emulsomes administration indicates rapid targeting of drug to the brain. The higher DTI and DTP facilitates higher paracellular contribution and admission through the BBB, which means increasing the apparent EH brain permeability and targeting with non-ciliotoxic safe effect on the nasal mucosa. The efficient EH concentration in the brain could improve its effectiveness in migraine treatment.EH emulsomes were prepared using a thin-film hydration method and the formulations were optimized using full factorial 2


RNA folding is an intrinsic property of RNA that serves a key role in every step of post-transcriptional regulation of gene expression, from RNA maturation to translation in plants. Recent developments of genome-wide RNA structure profiling methods have transformed research in this area enabling focus to shift from individual molecules to the study of tens of thousands of RNAs. Here, we provide a comprehensive review of recent advances in the field. We discuss these new insights of RNA structure functionality within the context of post-transcriptional regulation including mRNA maturation, translation, and RNA degradation in plants. Notably, we also provide an overview of how plants exhibit different RNA structures in response to environmental changes. In the past decades, research into gene regulation has been focused on DNA and proteins. Little attention has been paid to RNA since RNA was regarded as the intermediator between DNA and proteins. However, numerous studies have shown that mRNA levels only partially correlate with protein levels ,2. More in vitro RNA structure profiling method, parallel analysis of RNA structure (PARS), was achieved by coupling enzymatic probing with high-throughput sequencing [in vivo RNA structure profiling methods merged chemical probing methods with high-throughput sequencing. These chemical probing methods include the DMS-based method, which uses dimethyl Sulfate to probe for single-stranded A and C nucleotides; and the SHAPE -based method, which utilizes a variety of chemicals, e.g. 2-methylnicotinic acid (NAI), to probe the single-strandedness of all four RNA nucleotides [Since 2010, several high-throughput RNA structure profiling methods have transformed the scope of RNA structure studies, enabling genome-wide structurome analyses . The firquencing . Enzymatquencing . Next, iIn this review, we summarize how new technologies that reveal the RNA structurome have provided unique insights into the functional roles of RNA structure regarding the whole post-transcriptional process — from mRNA maturation, translation, through to RNA degradation. We also include additional findings relating to ancillary roles of RNA structure in other post-transcriptional regulatory pathways. In parallel, we provide an overview of several exciting studies that focus on how plants adopt RNA structures to facilitate regulatory responses to various environmental stresses including heat, light and salt stress.7-methylated guanosine to the first nucleotide of the RNA via a reverse 5′ to 5′ triphosphate linkage [in vitro RNA structurome in Arabidopsis thaliana nuclear RNAs [Following transcription, nascent RNAs undergo a maturation process that involves intron splicing, 5′ capping and 3′ polyadenylation to create mature mRNA that can be exported to the cytoplasm ,12. 5′ c linkage . RNA spl linkage . Thus, m linkage ,12. It i linkage ,16. To aear RNAs . They foear RNAs . No signear RNAs .in vivo RNA structure study using in vivo SHAPE chemical probing on Arabidopsis thaliana nuclear RNAs, revealed various structural features [in vitro RNA structure approaches were not able to reflect the proper folding status of RNAs in living cells. The in vivo nuclear RNA structurome revealed a two-nucleotide single-stranded RNA structure feature upstream of 5′ss that is strongly associated with splicing and the selection of alternative 5′ss, while the single-strandedness of branch sites is also associated with 3′splice site (3′ss) recognition [In contrast, a recent features , indicatognition   [Following nascent mRNA processing, mature mRNAs are exported to the cytoplasm where they undergo translation. Both itiation ,24. Furtitiation . This tritiation . Notably sativa) . These g sativa) ,24,26.in vitro RNA structure study reported the first highly conserved plant RG4 located in the 5′ untranslated region (UTR) of ATAXIA TELANGIECTASIA-MUTATED AND RAD3-RELATED (ATR) and revealed that translation is inhibited when stable GQS structures are formed [- SUPPRESSOR OF MAX2 1-LIKE4/5 (SMXL4/5) [SMXL4/5, thus restricting phloem differentiation [In addition to RNA secondary structures, RNAs also fold into complex tertiary structures ,28. One e formed   ,31. Thisntiation ,31  translation was enhanced under the phosphate-deficient conditions when the expression of its antisense RNA (cis-NATpho1.2) increased [PHO1.2 downstream of its start codon generated a strong structure which inhibited binding of the 60S subunit to the 40S [cis-NATpho1.2, a localized sense–antisense inter-molecular interaction rearranged this inhibitory structure to allow the 60S access to the translation initiation site, increasing 80S initiation complex formation and subsequently enhancing PHO1.2 translation [An antisense-mediated regulatory mechanism was identified in rice, where translation of the phosphate transporter ncreased . A recen the 40S . In the nslation   RNA changes anti-correlated with alterations of RNA secondary structures in response to salt stress [RNA structures can comprise single-stranded regions, hairpin loops, internal loops, bulges and so forth. These structural motifs have different thermodynamic properties that together determine the overall RNA stability ,39. A rebundance . In contbidopsis . They obt stress . Interest stress . These ct stress ,42. The t stress ,42.in vivo structures of mRNAs before cleavage using the terminator exonuclease treatment for the enrichment of intact RNAs [Arabidopsis thaliana [in vivo [in vivo [Target Adjacent nucleotide Motif (TAM), is capable of triggering miRNA cleavage but not miRNA binding, thus uncoupling target site binding from cleavage [The microRNA (miRNA)-mediated gene silencing pathway including both translation inhibition and RNA degradation is highly specific in plant but poorly specific in animals . MiRNAs act RNAs . This methaliana . Surpris[in vivo   participate in every step of post-transcriptional regulation of gene expression and interact with their targeted RNAs in a sequence- and structure- specific manner . A previ6A has been identified as the most abundant RNA modification in eukaryotic mRNAs [6A around the start codon, stop codon and 3′UTR region in Arabidopsis [6A modification sites tend to have less RNA structure [6A association is likely to alter RNA structure to favour single-strandedness and suggests fascinating functions for RNA modification in post-transcriptional gene regulation.Modification of RNA plays an important role in mRNA metabolism and translation . m6A hasic mRNAs  with recbidopsis ,50. Thisbidopsis   between different cell types using single molecule RNA FISH (smFISH) [SHR mRNA in stele cells, while aggregated, phase separation-like signals for SHR RNA were observed in neighbouring endodermis cells [SHR RNA contained a strongly folded RG4 structure which was shown to trigger RNA-driven phase separation in vitro [Phase separation is suggested as a means for ensuring appropriate molecular levels in the cells for tight regulation of gene expression . A recen(smFISH) . They obis cells  (Figure in vitro . TherefoNew methods for studying RNA structure have resulted in tremendous progress being made in our knowledge of RNA structure functionality at every step of post-transcriptional regulation of gene expression in plants. However, limitations posed by short read sequencing platforms still pose challenges for obtaining accurate profiles of full-length structural landscapes and distinguishing structures in shared regions between isoforms. RNA structural heterogeneity is another major challenge that must be overcome in the future to improve the accuracy of RNA structure predictions. Despite efforts being made to partially resolve these issues indirectly through statistical modelling and machine learning methods , direct Importance of the field. Functional roles of RNA structure in post-transcriptional gene regulation provide novel mechanistic insights in regulating gene expression.Current thinking. New insights from recent RNA structure studies have revealed a pervasive role for RNA structure in every step across post-transcriptional processes including mRNA maturation, translation, and RNA degradation. Plants adopt these functional RNA structures as key regulators in response to environmental changes.Future direction. Technological advances that distinguish distinct RNA isoformic and conformational structures could improve structure predictions. Comprehensive studies on RNA structure-mediated regulatory mechanisms in response to environmental challenges could also shed light on how RNA structure may be fine-tuned to modulate plant growth and development in response to varying environmental conditions. This has the potential to inform crop improvement strategies for mitigating the global impact on crops due to climate change.