We further consider two critical steps in targeting RNA/protein interactions: first, the integration of in silico and structural analyses to improve the efficacy of molecules by identifying scaffolds with high affinity, and second, increasing the likelihood of identifying on-target compounds in cells through a combination of high-throughput approaches and functional assays. We anticipate that the development of a new class of molecules targeting RNA: protein interactions to prevent physio-pathological mechanisms could significantly expand the arsenal of effective therapeutic compounds.In recent years, RNA has gained traction both as a therapeutic molecule and as a therapeutic target in several human pathologies. In this review, we consider the approach of targeting RNA using small molecules for both research and therapeutic purposes. Given the primary challenge presented by the low structural diversity of RNA, we discuss the potential for targeting RNA: protein interactions to enhance the structural and sequence specificity of drug candidates. We review available tools and inherent challenges in this approach, ranging from adapted bioinformatics tools to  Although RNA has emerged as a promising therapeutic target for many disease states, the development of small molecules targeting RNA remains in its very early stages . PotentiVarious strategies have been pursued for targeting RNA, which we categorize into two groups : 1) straSmall molecules offer significant advantages in terms of affordability, ease of delivery to patients, and potential oral administration . HoweverIn this review, we explore the possibility of targeting RNA:protein interfaces to improve the specificity of small molecules to RNAs in cells. Indeed, compared with individual RNA molecules, RNA:protein interfaces  have mucIn silico screening based on computer-aided approaches can be used, but must be developed in a rational manner , and provide atomic-level information about the interaction of small molecules with protein and/or RNA. The last point is critical for designing compounds based on derivatives of molecules entering the targeted pocket. With structural data, we can delineate the binding mode of small molecules and identify which amino acid residues and RNA bases are involved in the recognition of the small molecules , which cannot be easily translated into binding energy information, apart from defining the binding pocket. Molecular dynamics simulations are an interesting complement to both NMR and X-ray data by delineating possible models of interaction between small molecules, RNA, and proteins that can be probed by mutating key residues that are involved in the putative interactions.in vitro by other methods and, if possible, in cells. Besides using structural data to explore the structure-function relationship of small molecules by chemists, NMR and X-ray data serve as substantial evidence that the molecules are on target, even if the occurrence of off-target binding could be significant in cells.Gathering NMR or X-ray structural data on the interactions between small molecules and RNA:protein complexes is valuable but is not well suited for screening thousands of compounds due to the cost of these methods. Therefore, NMR and X-ray crystallography analyses should be limited to the most promising hits that have been validated In silico approaches can rarely reduce the number of putative hits down to thousands of compounds. The number of compounds selected in silico can be dramatically reduced if the selection is based on general criteria such as solubility, size, toxicity, and membrane crossing. Even if structural information based on NMR or X-ray crystallography data are used, the number of compounds selected is still high, from hundreds to thousands at least. With high-throughput assays, thousands of compounds can be screened. One general problem with the use of high-throughput assays in vitro is the solubility of RBPs. As in the case of using NMR and X-ray crystallography, the self-adhesive domains of the RBPs have to be removed.High-throughput assays are critical components of the screening pipeline . In siliin vitro high-throughput assays for RNA:protein interactions are described below and make use of recombinant proteins combined to short RNA molecules.The two most widely used Fluorescence polarization requires the use of purified protein, RNA, or RNA: protein complex. When light interacts with a RNA:protein complex, changes in polarization can be recorded in assay plates such as 384-well plates . When smin vitro without competitors, long RNAs with which many RBPs can be associated are not a good choice for FRET-based assays. In this case, many RBPs in the complex would be located some distance away from the RNA fluorescence label, which is generally located at the 3′ or 5′ ends of the RNA. Therefore, FRET assays require labeled proteins combined with short labeled RNA. HTRF assays and AlphaScreen are high-throughput alternatives to screen inhibitors of RNA:protein interaction (The short range energy transfer between a pair of fluorescence labels (probes) is inversely proportional to the sixth power of the distance between two dye molecules . Thus, Feraction  that alseraction .in vitro and to provide additional information regarding the interference of small compounds with RNA:protein interactions or the binding of selected compounds to protein and/or RNA.Complementing high-throughput assays, relatively low-throughput assays can be used to confirm the efficacy of selected hits A), stoichiometry (n), enthalpy (ΔH), and entropy (ΔS) changes. While this method is very useful, the sensitivity for the analysis of low affinity compounds (>10 µM) is limited. ITC is also not suitable for screening many compounds because it requires a large amount of proteins and RNAs, which also increases the cost of the screen. In addition, ITC has been rather used for investigating two-component interactions such as RNA: small molecules or RNA: protein interactions. To screen small molecules interacting with protein: RNA complex, the reading can be more complicated since a decrease/increase of RNA: protein interactions would provide additional changes in the thermodynamic parameters.Isothermal titration calorimetry (ITC) is a sensitive method to explore the thermodynamic properties of proteins or RNAs interacting with small molecules, as well as RNA:protein interactions . From a To probe the interactions of proteins, RNA, and small molecules, surface plasmon resonance (SPR) is a sensitive technique that uses biomolecules immobilized on a solid support. SPR assays are particularly useful for studying RNA ligands  and RNA:Gel shift assays, in which RNA:protein complexes are run in acrylamide or agarose gels, have a long history of use by biochemists and biologists. Small molecules can change the electrophoretic mobility of the targeted RNA:protein complex . Howeverin vitro experiments are useful, ensuring that chemical compounds targeting RNA:protein interactions are indeed on target in cells is essential. Small molecules that have been selected in vitro from large libraries rarely have high affinity for RNA, RBPs, or RNA:protein complexes. Generally, compound affinities are several micromolar or even hundreds of micromolar. In the cell, these compounds may not cross cell membranes and may be degraded in the cell or in the extracellular environment. In addition, small molecules can also nonspecifically interact with other biomolecules to divert them from the intended RNA: protein complex. Finally, in vitro-selected molecules may not bind to their RNA:protein target in cells due to different folding of the RNA: protein complex in a cellular context that cannot be reproduced in vitro. Therefore, an interesting strategy would be to screen directly in cells whether selected compounds bind to the target in cells. However, only a very limited number of methods can provide this information  for most genes. The further development of FRET for RNA:protein interactions to date has been limited by the constraint that fluorescent molecules used as labels for proteins and RNAs must be located in close proximity, i.e., less than a few nanometers. RBPs can bind to many different RNAs in cells and often at different positions on the same RNA. For example, transcriptomic analyses  use antibodies that recognize endogenous proteins to detect their spatial proximity based on an amplification process. The amplification relies on a hybridization step followed by a DNA amplification step to incorporate fluorescent probes. When the separation distance between the two proteins is lower than ∼30 nm, the PLA signal is detected via the visualization of fluorescent spots in cells by microscopy. This method, like FRET, is especially suitable for detecting protein: protein interactions. It can be adapted to detect RNA: protein interactions if RNA can be detected with a dye, for example, by using an RNA probe labeled with digoxigenin to enable the detection of endogenous RNAs using antibodies. However, to date, very few studies have benefited from this method to explore RNA: protein interactions . First, in situ hybridization. The greater the number of RBPs on the microtubules, the greater the number of RNAs are detected. The enrichment of RNA on the microtubules is then recorded as a function of the number of bait proteins, providing an interaction score and a direct estimate of the protein’s affinity for RNA in cells. This method is relatively simple to set up and has already been validated in 96-well plates for detecting interactions with endogenous mRNAs , cell lysates or cell suspensions are heated at different temperatures. The stability of RBPs in the soluble fraction is then assessed by western blot analysis or by mass spectrometry if the target protein of the molecule is unknown. Molecules targeting RBPs may alter the stability of RNA: protein complexes . This mePull-down assays from cells treated with biotinylated molecules or biotinylated control molecules can be analyzed by western blot assays or by mass spectrometry . When thSeveral methods have been developed to detect intracellular interactions between RBPs with RNA at a genomic scale . The mosFunctional assays are also critical to further investigating the efficacy of small molecules. These assays can measure whether translation, splicing, transcription, or other cellular functions controlled by specific RNA: protein interactions can be modified by small molecules.Functional assays may involve the use of specific gene reporters where the RBP or RNA targets play a direct role. For example, to probe the inhibition of the complex formed by let-7 microRNA and Lin28 protein, dual luciferase reporter assays were used with eight tandem let-7 recognition sites in the 3′UTR to confer sensitivity to let-7 microRNA levels . SplicinRNA is now recognized as a major target that could pave the way for new therapies in various human diseases , includiSome RBPs are considered as target because of their involvement in human diseases including cancer  and neurTargeting RNA: protein interfaces offers several advantages. First, protein targets provide diversity in amino acid sequences and structures, both of which are limited in RNA molecules. RNA, when complexed with proteins, can reveal druggable pockets that are not as abundant in RBPs in isolation. Another advantage is the ability to target specific functions associated with RNA: protein interactions. One well-studied example is the interaction between let-7 and Lin28, which controls cell differentiation . Lin28 bin silico selection of molecules must be conducted to expand the repertoire of molecules that can target RNA: protein interfaces. In vitro, there is currently limited information about the selectivity of proposed molecules with respect to RNA. Studies should encompass different RNA sequences and secondary structures to assess whether molecules exhibit distinct effect in different contexts. These aspects must be addressed in vitro and in silico through molecular dynamic simulations to determine whether medical chemistry modifications can increase the specificity towards specific RNA targets. Finally, beyond functional cellular data indicating whether molecules alter RNA functions, it is essential to confirm whether molecules indeed target the intended RNA: protein interactions in a cellular context. Few methods allow for the measurement of RBP with RNAs in cells, and even fewer can detect interactions with specific RNAs. Ideally, the detection of these specific RNA: protein interactions should be amenable to high-throughput screening involving thousands of selected compounds or assessing specificity towards different RNAs.While the prospect of targeting RNA: protein interactions holds considerable appeal, many challenges remain to be addressed. Identifying pockets in which molecules can interfere with RNA: protein interactions is a crucial first step. If some compounds have already been identified, extensive screens based on structural data and


App. In summary, PIE-Seq provides an orthogonal approach and resource to uncover RBP targets in mice and human cells.RNA-binding proteins (RBPs) are essential for gene regulation, but it remains a challenge to identify their RNA targets across cell types. Here we present PIE-Seq to investigate Protein-RNA Interaction with dual-deaminase Editing and Sequencing by conjugating C-to-U and A-to-I base editors to RBPs. We benchmark PIE-Seq and demonstrate its sensitivity in single cells, its application in the developing brain, and its scalability with 25 human RBPs. Bulk PIE-Seq identifies canonical binding features for RBPs such as PUM2 and NOVA1, and nominates additional target genes for most tested RBPs such as SRSF1 and TDP-43/TARDBP. Homologous RBPs frequently edit similar sequences and gene sets in PIE-Seq while different RBP families show distinct targets. Single-cell PIE-PUM2 uncovers comparable targets to bulk samples and applying PIE-PUM2 to the developing mouse neocortex identifies neural-progenitor- and neuron-specific target genes such as  Tracking protein-RNA interaction across cell types is challenging. Here, Ruan et al develop a dual-deaminase method called PIE-Seq, where protein targets are marked by both C-to-U and A-to-I RNA base editors, and apply it to 25 human RNA-binding proteins. RBPs such as FMR1 and TARDBP are causal for neurological disorders2, and ablations of RBPs in mice have been shown to impair organ development such as the neocortex7. Conversely, mutations affecting regulatory pre-mRNA sequences have been shown to cause neurodevelopmental disorders10. Systematic identification of RBP target mRNAs in different cell and tissue types is key to understanding RBP functions and pathogenic mechanisms14. Methods based on UV crosslinking and immunoprecipitation (CLIP) have generated substantial insights18, but their applications to cell types in intact tissues are hindered by the requirements of UV light penetration, high-quality antibodies and a large number of input cells.RNA-binding proteins (RBPs) and their interactions with RNAs are central to gene regulation20. Fusing RNA deaminase domains with RBPs of interest would guide RNA editors to target RNAs and introduce nucleotide changes that can be detected by RNA sequencing (RNA-Seq). In 2016, the catalytic domain of Drosophila ADAR was fused with RBPs to identify mRNA targets (TRIBE) through A-to-I editing in fly cells21. An E488Q mutation in the ADAR C-terminal domain has been introduced to enhance the editing efficiency in HyperTRIBE, which uncovered 4E-BP and MUSASHI-2 targets in human cells23. Conceptually similar to TRIBE, the C-to-U deaminase Apobec1 was conjugated to a YTH domain to detect N6-Methyladenosine (m6A) sites through RNA-Seq24, and Apobec1-RBP-fusion proteins (STAMP) have been utilized to identify target mRNAs of RBFOX2, TIA1, SLBP and ribosome-subunits in cultured cells25. These studies indicate that RNA editing is a promising approach to studying protein–RNA interaction. While the single deaminase approaches bypass some of the limits for CLIP-based methods, their intrinsic bias toward A- or C-nucleobases, relative editing efficiency, scalability, and in vivo applications remain to be addressed26.RNA deaminases, such as Apobec1 and ADAR2, bind to RNA targets with auxiliary proteins and introduce C-to-U and A-to-I nucleobase changes, respectivelyHere we present PIE-Seq utilizing dual deaminases to enhance target detection: we fuse RBPs to A-to-I and C-to-U RNA deaminase domains and directly uncover RBP target genes by RNA-Seq. Dual deaminases in PIE-PUM2 enhance target discovery when compared with single deaminases. PIE-Seq successfully identifies target genes and binding motifs for PUM2, NOVA1, and 23 additional RBPs, demonstrating its consistency and scalability. We further show the applications of PIE-Seq to single cells and cell types isolated from the developing mouse neocortex. This study presents PIE-Seq as an orthogonal approach to studying protein–RNA interaction and provides a resource to investigate the target genes of 25 RBPs.C-to-U and A-to-I editing can potentially complement each other in different sequence or structure contexts and enhance target discovery. PIE-RBPs were constructed by fusing C-to-U and A-to-I RNA deaminase domains to RBPs with flexible linkers. Upon RBP binding to its RNA targets, the dual deaminases in PIE-RBPs are expected to catalyze C-to-U and A-to-I editing in adjacent sequences, which can be readily detected by bulk or single-cell RNA-Seq Fig. .Fig. 1Th27 to determine RNA deaminase activities for rat Apobec1, human APOBEC3A, human ADAR2 deaminase domain (ADAR2dd)28, and codon-optimized TadA variants (Methods). Apobec proteins introduce C-to-U editing in an AU-rich context29; the ADAR2 deaminase domain prefers to edit bulged A sites in double-stranded RNAs (dsRNAs)30 and evolved TadA variants (TadA* and TadA*(V82G)) have been reported to retain transcriptome-wide RNA editing activity31. We fused MCP to the deaminases and inserted a 2xMS2 sequence downstream of the mCherry coding sequence (CDS) to make the mCherry-2xMS2 reporter (Methods). When MCP-Apobec1 was co-expressed with mCherry-2xMS2, we detected significantly higher C-to-U editing rates (18–46%) surrounding the MS2 sites than the empty control (1.7–5.3%) or the non-targeting Apobec1 control  in 3′ untranslated regions (3′ UTRs) through its Pumilio homology domain and regulates gene expression36. We fused Apobec1 and ADAR2dd to the N- and C-terminus of PUM2, with XTEN37 and Glycine-Serine (GS) peptide-linkers to make the fusion protein conformationally flexible  to filter out stochastic editing events. When expressed in HEK293FT cells, the PIE-PUM2 fusion protein was enriched in the cytoplasm and displayed no observable adverse effect on cell growth or survival , suggesting that stochastic C-to-U editing events in APAD were reduced by PIE-PUM2 ; (2) The genes with target sites (C-to-U or A-to-I) were considered as target genes. In total, PIE-PUM2 uncovered 1975 target genes with 1811 genes reproduced between replicates -Seq in Hela cells42. These results indicate that the dual deaminases uncovered PUM2 target genes and reduced false negatives by single-base editors.Using PIE-PUM2 as an example, we defined PIE-Seq target sites and target genes with the following criteria (see details in Methods): (1) We designated editing sites as target sites if they show significantly higher mutation frequencies in PIE-RBP than the APAD group   were shared with PAR-CLIP PUM2 targets  Fig. , which s2G) Fig. . PIETadAets Fig. . The limTo compare the PIE-Seq dual-deaminase approach with single-deaminase methods such as TRIBE and STAMP, we cloned Apobec1-PUM2 (AP-PUM2) and PUM2-ADAR2dd (PUM2-AD), with AP-mCherry and mCherry-AD as deaminase-controls, respectively Fig. . The proThe nature of C-to-U and A-to-I base editing brings in confounding bias for Cs and As at the editing sites, which would profoundly skew the sequence motif analysis. In addition, Apobec1 preferably edited the C in ACH sequences, and ADAR2dd edited the A in WAS sequences in the non-targeting Apobec1-ADAR2dd controls , suggesting that PUM2 binding to RNA precluded ten nucleotides from deaminases  showed enriched UGUAM and UGUAHA motifs which represent the core PRE sequence Fig. . Interesses Fig. . There wses Fig. . PIE-PUMses Fig. , which iaks Fig. . These r46 to APAD and PIE-PUM2 to modulate the expression levels. The RNA-Seq and Western blot analyses confirmed that the levels of induced PUM2 expression were significantly lower than those observed in the transient expression group  compared to those not shared in PIE-PUM2 -inducible expression systemUM2 Fig. . The PREUM2 Fig. . These rWe performed RNA Immunoprecipitation (RIP) and qPCR to validate PIE-PUM2 targets. We selected 42 high-confidence target genes (see Methods), including 22 shown in PAR-CLIP data, for independent validation through RIP-qPCR. Twenty-seven genes showed significant enrichment in the PUM2 RIP group when compared to the IgG control, with 17 shown in PAR-CLIP, three unique to transient PIE-PUM2, and seven shared only between transient PIE-PUM2 and Tet-on sets Fig. . These r47, and consistently detected RNA editing sites in 10-cell and single-cell MCP-Apobec1 samples but not in the Apobec1 non-targeting controls  mouse dorsal forebrains using in utero electroporation (IUE). We dissected the electroporated dorsal cortical tissues at E15.5 and isolated EGFP-positive neural-progenitor cells  and neurons (CD24+)49 for RNA Sequencing  nearby a PRE motif in the NPC group but not in the neuron group  and serine (S) enriched RS domains and variable RNA recognition motifs (RRM)dle Fig. . To minidle Fig. .Fig. 6PIUsing PIE-SRSF1/2/3 constructs  homologous RBPs showed highly similar enriched motifs Fig. ; (2) Enr55 and extensive CLIP-Seq studies in the brain have shown that Nova1 binds YCAY sequences to regulate RNA splicing57. We studied the human NOVA1 and identified the bona fide YCAY as the most enriched motif surrounding both C-to-U and A-to-I target sites  of target genes are regulated by six or more RBPs, and that 24% (1888/7742) of genes were targeted by one or two RBPs  of target genes identified by PIE-RBPs are validated by CLIP or RIP datasets, on average, 37% of targets are unrevealed; we nominate more targets for RBPs such as TDP-43/TARDBP (1720 target genes), FMR1 (304), STAU2 (509), and LIN28A (2502)  PIE-MCP showed high on-site editing rates around MS2; (2) PIE-Seq uncovered canonical binding motifs for multiple RBPs such as PUM2, NOVA1 and SRSF1/2/3, and such motifs were consistently within the proximity of editing sites; (3) PIE-Seq target genes are highly concordant with CLIP-Seq, PAR-CLIP, RIP-Seq targets of the same RBPs, and have been further validated by RIP experiment; (4) PIE-Seq can be applied to intact tissues to identify cell-type-specific RBP targets; (5) Target sites, target genes, and enriched motifs show significant differences between RBP families, suggesting that RBPs are the main drivers for base editing; and (6) The majority of RBP isoforms and homologs display highly overlapping target genes and enriched binding motifs. These results indicate that PIE-Seq is robust for RBP target discovery and validation, serving as an orthogonal approach that complements CLIP-based methods.66. It is worth mentioning that C-to-U and A-to-I editing sites may call out the same target gene, but this is not always true due to imbalanced deaminase activities and sequence preferences. These results suggest that combining dual editors enhances RBP target detection.Comparisons of C-to-U and A-to-I editing sites using PIE-Seq led us to find that Apobec1 consistently introduced more editing sites than ADAR2dd in both non-targeting controls and 25 RBP-fusion proteins  PIE-Seq is convenient to implement because it involves transient protein expression and RNA sequencing, eliminating the requirement of UV crosslinking, immunoprecipitation, or other CLIP-Seq-specific experimental steps/reagents; (2) PIE-Seq constructs could be expressed in vivo and identify endogenous targets from cell types in animal tissues such as the embryonic brain; (3) PIE-Seq is applicable to a very small amount of input when combined with concurrent single-cell RNA-Seq methods. Thus, PIE-Seq makes it feasible to analyze protein–RNA interaction in vivo and among different cell types.Compared with CLIP-Seq-based methods6A binding proteins. Apobec1 has been fused with the YTH domain of YTHDF2 to identify m6A RNA methylation sites in cultured cells69, and here our results indicate that extra cautions are needed when the binding motif resembles or includes the deaminase residual sequence. In addition, PIE-Seq uncovered fewer targets than other methods for the YTH proteins, possibly due to the overlapping ACH motif, incompatible protein conformations, or YTHDF-mediated stress granule formation70, which may impair deaminase activity. Except for PUM2, PIE-Seq was performed here mostly in HEK293FT cells, which may not be the best model for neurological disorders. To minimize the residue sequence preferences of RNA deaminases and overcome the lower editing efficiency of ADAR2dd, we have screened other deaminase modules, including TadA*71, which has a distinct molecular origin from ADAR2dd or Apobec1. We have shown that TadA* had strong editing activities in the MCP-MS2 system but led to limited editing sites when benchmarked in cultured cells. Despite that, the majority of PIETadA*-PUM2 genes were reproduced in other PIE-PUM2 experiments  C-to-U and A-to-I editing sites in APAD and PIE-RBPs displayed reminiscent binding motifs of Apobec1 and ADAR2dd  of the University of Chicago .5 cells were transfected in suspension with lipofectamine 2000 (Fisher Scientific cat. No. 11668019) and changed to fresh medium 4 h after transfection. The cell line was validated for mycoplasma negative. More cell culture and transfection details are seen in Supplementary Note HEK293FT cells  were cultured at 37 °C in DMEM (Gibco cat. No. 10566024) supplemented with 10% fetal bovine serum (Gibco cat. No. 26140079) in a humidified incubator with 5% carbon dioxide. For each well in a 12-well plate (Fisher Scientific cat. No. 087723 A), 8 × 1072 and was approved by the IACUC of the University of Chicago . Briefly, DNA plasmids were prepared using an endotoxin-free isolation kit and diluted in DNase/RNase-free water. The surgery was performed on a pregnant mouse under aseptic conditions and anesthesia, achieved by introducing 3% isoflurane at 0.8 L/min oxygen until the mouse was asleep and maintaining 1.5% isoflurane during the procedure. A proper concentration (about 1 μg/μl) of DNA solution with 0.05% Fast Green dye was injected into the E13.5 brain lateral ventricle in utero via glass micropipettes, and five square fixed-potential pulses with a duration of 50 ms per pulse were administered by an Electro Square Porator . After the surgery, the uterus was returned, and the wound was closed. The mouse received postoperative care, including monitoring, analgesics and ensuring proper healing.CD-1 mice were purchased from Charles River, housed and bred at the University of Chicago Animal Care Facility under a 12-h dark/12-h light cycle and ambient temperature. The day (noon) when a vaginal plug showed, was designated E0.5. IUE procedures were performed following previously described protocolsApobec1: rApobec1 was amplified from pCMV-BE3 (Addgene #73021) with primers XR001/XR189 and inserted into the pCAGIG backbone.pR059_pCAG-MCP-Apobec1: MCP sequence was amplified from MS2_GFP (Addgene #61764) with primers XR185/XR186, SGGS-XTEN-SGGS linker was amplified from pCMV_ABEmax (Addgene #112095) with primers XR187/XR188, and these two PCR fragments were assembled with rApobec1 into pCAGIG with Gibson Assembly .pR060_pCAG-mCherry-2XMS2: 2xMS2 sequence was amplified from a 24xMS2 reporter plasmid (Addgene #61762) with primers XR308/XR309 and inserted into the 3′ UTR of mCherry in the pCAG-mCherry backbone.pR087_pCAG-TadA-TadA*-dPspCas13b-Apobec1: TadA-GS-XTEN-GS-TadA*-GS-XTEN-GS was amplified from pCMV-ABEmax (Addgene #112095) with XR147/XR144, dPspCas13b was amplified from pC0055-CMV-dPspCas13b-GS-ADAR2DD(E488QT375G)-delta-984-1090 (Addgene #103871), GS-XTEN-GS-Apobec1 from pR060 with XR312/XR313, and these PCR fragments were assembled into the pCAGIG backbone.pR088_pCAG--TadA-TadA*-MCP: The TadA-GS-XTEN-GS-TadA*-GS-XTEN-GS from pCMV-ABEmax (Addgene #112095) was amplified with XR318 and XR319, and the MCP from MS2_GFP (Addgene #61764) was amplified with XR320 and XR321; these two fragments were assembled into the pCAGIG backbone.pR090_pCAGTadA*-MCP: TadA*-MCP from pR090 was amplified with XR356 and XR357 and inserted into the pCAGIG backbone.pR100_pCAG-TadA*(V82G)-MCP: TadA*(V82G)-MCP from pR090 was amplified with XR356/360 and XR361/357; these two fragments were assembled into the pCAGIG backbone.pR102_pCAG-MCP-ADAR2dd: hADAR2dd was PCR amplified from pC0055 with primers XR591/XR592, cut with BstE2 and Not1, and replaced rApobec1 CDS in the MCP-Apobec1 plasmid.pR163_pCAG-MCP-APOBEC3A: APOBEC3A was amplified from A3Ai-Cas9n-UGI-NLS (Addgene #109425) with XR892 and XR893 and then assembled into the pCAGIG backbone.pR284WT_pCAG-MCP-APOBEC3A(K30R/Y132G): APOBEC3A(Y132G/K30R) was amplified from A3Ai-Cas9n-UGI-NLS (Addgene #109425) by three segments: A3A_part1 with XR892/XR888, A3A_part2 with XR889/XR890, A3A_part3 with XR891/XR893, and these three fragments were assembled into the pCAGIG backbone.pR284Mut_pCAG-rApobec1-XTEN was amplified from pCMV-BE3 (Addgene #73021) with primers XR001/XR024, and hADAR2dd was amplified from pC0055 (Addgene #103871) with primers XR025/XR006. The two PCR fragments were assembled into pCAGIG.pR008_APAD: PUM2 and pR018_PIE-FMR1: PUM2 CDS was amplified from pFRT/FLAG/HA-DEST PUM2 (Addgene #40292) with primers XR058/XR059, and FMR1 CDS was amplified from pFRT-TODestFLAGHAhFMRPiso1 (Addgene #48690) with primers XR044/XR045, and these CDS sequence were inserted between rApobec1-XTEN and GS-linker-ADAR2dd in pCAGIG backbone with T4 ligation, respectively.pR023_PIE-pR203_AP-AD and additional PIE-RBPs: rApobec1-XTEN was amplified from pCMV-BE3 (Addgene #73021), and SGGS-XTEN-SGGS linker and hADAR2dd was amplified from pC0055 (Addgene #103871). The three PCR fragments above were assembled into pCAGIG with Gibson Assembly (NEB) to get pR203. The CDS of mCherry, dCas13b and more PIE-RBPs were inserted between Apobec1 and hADAR2dd through Gibson Assembly.pINDUCER21_APAD and pINDUCER21_PIE-PUM2 were constructed by Gateway LR cloning with pINDUCER21 (ORF-EG) backbone (Addgene #46948).Primer sequences are listed in Supplementary Data Immunofluorescence staining was done 24 or 48 h after transfection or electroporation. Cells were rinsed once with 1x PBS and fixed with 4% PFA at room temperature for 15 min. Fixed cells or brain slices were rinsed with 1x PBS, incubated with blocking buffer (1x PBS with 0.3% Triton-X-100 and 5% donkey serum) at room temperature for 30 min, and further incubated with primary antibodies diluted in blocking buffer overnight at 4 °C. After three brief rinses in 1x PBS, slides were incubated for 1 h at room temperature with fluorophore-conjugated secondary antibodies , donkey anti-mouse 488 , donkey anti-rabbit 594 , donkey anti-rat 647 ; 1:1000 dilution for all). Slides were scanned with a Leica SP5 inverted confocal microscope. The following primary antibodies were used: anti-HA , anti-GFP , anti-PUM2 , anti-CD24-PE , anti-CD133-APC , anti-PAX6 , anti-APP .Cells from each group were lysed with RIPA buffer  containing 1x cOmplete EDTA-free protease inhibitor cocktail (Sigma-Aldrich 11836170001) and shaken on ice for 20 min. The lysates were centrifuged, and the supernatants were denatured in 1x loading buffer at 95 °C for 10 min. Protein samples were then loaded and separated on SDS-PAGE gel in Tris/glycine/SDS buffer, transferred onto PVDF membrane, and incubated overnight at 4 °C with primary antibodies: anti-PUM2  and anti-LMNB1  and donkey anti-goat IgG  were used for detecting PUM2 and LMNB1 proteins, and the membranes were scanned with a LI-COR Odyssey DLx imager. Images were processed and quantified with Adobe Photoshop.Total RNA was extracted from transfected cells with a Direct-zol RNA microprep kit (ZYMO R2061), and reverse transcribed to first-stranded cDNA with SuperScript IV Reverse Transcriptase (Thermo Fisher 18090050) following manufacturer’s instructions. PCR products were purified, and Sanger sequenced.HEK293FT cells were washed with 1x DPBS without Calcium or Magnesium (Gibco 14190250) 24 or 48 h after transfection and digested with 0.25% Trypsin-EDTA (Gibco 25200114). Cells were diluted with 1x DPBS supplemented with 10% FBS and filtered through 70-µm cell strainers (Fisherbrand 22363548). IUE brains were dissected in cold 1x DPBS, digested with papain  for 15 min at a 37-degree incubator, and then resuspended in 1x DPBS with 1% BSA, filtered through 100-µm cell strainers (Fisherbrand 22363549). Flow cytometry was performed on an AriaIIIu with the FACSDiva operating system , except that NOVA1, FUBP1, TARDBP, CELF1/2/4, and KHDRBS1/2/3 were prepared with Stranded Total RNA Prep Ligation with Ribo-Zero Plus kit (Illumina 20040525). Each sample was barcoded using IDT for Illumina-TruSeq RNA UD Indexes (IDT 20040553). Libraries were sequenced on the Illumina Next-SEQ500 with 75 bp pair-end runs or Nova-Seq with 60 bp pair-end runs by the University of Chicago Genomics facility.38, raw Fastq files were trimmed, aligned and mapped to hg38 or mm10 with STAR73. Duplicate reads were identified with the MarkDuplicates tool in Picard (v2.19.1), and C-to-U and A-to-I editing variants were called with JACUSA2 (v2.0.0-RC23) with at least 5 reads covering each editing site as a cutoff. Known SNPs from human dbSNP version 138 or mouse dbSNP database (for the mouse brain study) and empty control sites were filtered out. The RBP target sites (C-to-T or A-to-G) were further analyzed with JACUSA2helper-1.99-9200 in R 4.2.0. The RBP target sites were called with the following filtering criteria: (1) For cultured cells, the editing rate was no less than 5% in PIE-RBP and at least twofold of that in APAD or APADcom control, log-likelihood z-score ≥4; (2) For in vivo mouse brain cells, the editing rate was no less than 5% in PIE-RBP, and at least 1.5-fold of that in deaminase control APAD, log-likelihood z-score >1. The genes with target sites were considered as RBP target genes. The control sites in APAD and APADcom were generated by comparison to empty control using the same pipeline. Detailed analysis pipeline in Supplementary Note Following the RNA variant calling pipeline with JACUSA2 package76. Reads were aligned to the customized GRCh38 genome that included transgene sequences. Raw counts were transformed into TPM values for comparison between groups.DGE analysis from RNA-seq data followed the fastp (v0.23.2), STAR (v2.6.1b) and DESeq2 (v3.12) (human samples), or Rsubread (v3.14) and limma (v3.42.1) (mouse samples) workflows77. Enriched motifs for PIE-RBPs were identified by DREME (v5.4.1)78 in sequences spanning ±50-nt of target sites, with the sequences ±50-nt of control sites in APAD or APADcom group as background. The deaminases editing sequence motifs (±4-nt flanking editing sites) were generated with HOMER (v4.11)79. The phylogenetic tree for RBP proteins was plotted with UPGMA (unweighted pair group method with arithmetic mean) method in MEGA1180.Genomic distribution of control sites in APAD or APADcom and target sites in PIE-RBPs was analyzed with “bed2annotation.pl” command in the CTK pipeline15 was reannotated with hg38 and then ranked by frequency of a crosslinking signal. RNA-seq data for QKI-6, IGF2BP1, IGF2BP2 PAR-CLIP from GEO accession code “GSE21578”15, RNA-seq data for FMR1 PAR-CLIP from GEO accession code “GSE39686”64, NOVA1 eCLIP RNA-seq data from BioProject under accession code “PRJNA670687”59 and mouse Nova1 HITS-CLIP RNA-seq data from GEO accession code “GSE69711“58 have been reanalyzed using the CTK pipeline77. CLIP peaks were called with statistical significance (FDR <0.05), and genes with significant CLIP peaks were considered RBP targets.Published CLIP data: PUM2 PAR-CLIP raw peak list7 HEK293FT cells were lysed in 100 μL of RIP Lysis Buffer (with protease inhibitors and the RNase inhibitor). About 5 µg of PUM2 and control IgG antibody were incubated with protein A/G magnetic beads for 30 min at room temperature with rotation. The lysates were incubated with the antibody-bead complex for overnight at 4 °C with rotation. We used a magnet to immobilize the beads, discarded the supernatant, washed the beads multiple times, and extracted RNA from the purified complexes. Then we analyzed targets with qRT-PCR. Sequences for RT-qPCR primers are listed in Supplementary Data We ranked the PIE-PUM2 target genes by calculating the sum of editing scores for each target site using the JACUSA package. Based on this ranking, 42 genes that emerged as the top-ranked targets were selected for validation with RIP-qPCR. For RIP, we used the Magna RIP RNA-Binding Protein Immunoprecipitation Kit (EMD Millipore 17-700) and followed the manufacturer’s protocol. Briefly, 2 × 10p values were described in the figure legend for each experiment. All data shown are representative of two or more independent experiments with similar results, unless indicated otherwise.No data were excluded from the analyses; The Investigators were not blinded to allocation during experiments and outcome assessment. All quantitative data were presented as the mean ± SD, as indicated by at least three independent experiments or biological replicates unless otherwise stated. The statistical tests and Further information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Reporting Summary


High-purity RNA serves as the basic requirement for downstream molecular analysis of plant species, especially the differential expression of genes to various biotic and abiotic stimuli. But, the extraction of high-quality RNA is usually difficult from plants rich in polysaccharides and polyphenols, and their presence usually interferes with the downstream applications. The aim of the study is to optimize the extraction of high-quality RNA from diverse plant species/tissues useful for downstream molecular applications.Prosopis cineraria, Conocarpus erectus, and Phoenix dactylifera. A reliable protocol for the extraction of high-quality RNA from mature leaves of these difficult-to-extract trees was optimized after screening nine different methods. The DNase I-, and proteinase K treatment-free modified method, consisting of extraction with CTAB method followed by TRIzol, yielded high-quality DNA-free RNA with an A260/A280 and A260/A230 ratios > 2.0. Extraction of RNA from Conocarpus, the most difficult one, was successful by avoiding the heat incubation of ground tissue in a buffer at 65 oC. Pre-warming of the buffer for 5–10 min was sufficient to extract good-quality RNA. RNA integrity number of the extracted RNA samples ranged between 7 and 9.1, and the gel electrophoresis displayed intact bands of 28S and 18S RNA. A cDNA library constructed from the RNA of P. cineraria was used for the downstream applications. Real-time qPCR analysis using the cDNA from P. cineraria RNA confirmed the quality. The extraction of good quality RNA from samples of the desert-growing P. cineraria (> 20-years-old) collected in alternate months of the year 2021  proved the efficacy of the protocol. The protocol’s broad applicability was further validated by extracting good-quality RNA from 36 difficult-to-extract plant species, including tissues such as roots, flowers, floral organs, fruits, and seeds.Extraction of RNA using commercially available RNA extraction kits and routine hexadecyltrimethylammonium bromide (CTAB) methods did not yield good quality DNA-free RNA from The modified DNase I and Proteinase K treatment-free protocol enables to extract DNA-free, high-quality, intact RNA from a total of 39 difficult-to-extract plant species belonging to 32 angiosperm families is useful to extract good-quality RNA from dicots and monocots irrespective of tissue types and growing seasons.The online version contains supplementary material available at 10.1186/s13007-023-01063-5. High-quality DNA-free RNA is mandatory for a number of plant molecular biology applications such as reverse transcription polymerase chain reaction (RT-PCR), real-time fluorescent quantitation polymerase chain reaction (qPCR), cDNA library construction, northern blot, RNase protection assay, in situ hybridization, subtractive hybridization, and gene expression analysis. Also, good-quality RNA is the prime requirement for RNA-seq analysis which is highly used for gene expression analysis in different tissues and plants under stress, detection of mutations, alternative splicing, and post-transcriptional modifications.Plants are very diverse in their biochemical profile, and the extraction of RNA at a quality desired for downstream applications is difficult with plants abundant in polysaccharides, proteins, and secondary metabolites , 2. PolyProsopis cineraria, Conocarpus erectus, Phoenix dactylifera was unsuccessful using different established protocols.Plant growth stage (immature and mature), physiological status of the samples, age of tissue , type of tissue , growing season especially under abiotic conditions, biochemical profile of the plants, type of plants  and conditions of the material  are the factors affecting the extraction of high-quality RNA , 5, 6. IProsopis cineraria (L.) Druce, a member of the legume family (Fabaceae), is one of the prime choices for desert afforestation programs due to their high adaptability to thrive in extreme environmental conditions of deserts . Prosopis spp. are rich in tannins and polysaccharides [Prosopis spp. has been documented by CTAB methods [charides , and the methods , 19 and Conocarpus erectus L., commonly known as button mangrove, belongs to the Combretaceae is an associate mangrove shrub growing on shorelines in tropical and subtropical regions around the world. The plant is a rich source of polyphenols and is reported to contain more than 12 phenolic compounds, mainly flavonoids and tannins [ tannins , 22. ThePhoenix dactylifera L. (Arecaceae), the Date palm, is a dioecious perennial monocot with several varieties and is the most important fruit-bearing crop in arid regions of the Middle East [dle East , 24. Paldle East , making dle East . Total Rdle East –29.To extract quality RNA from these plants for our downstream applications, we have tried different RNA extraction protocols such as Qiagen’s RNeasy Plant Mini kit, PureLink RNA Mini kit , Spectrum Plant Total RNA kit , Plant/Fungi DNA/RNA isolation kit , TRIzol ; TRI Reagent , CTAB-based , and hybProsopis cineraria (Fabaceae), Conocarpus erectus (Combretaceae), and Phoenix dactylifera cv. Fard (Arecaceae) were used to optimize a high-quality RNA extraction protocol. The leaf samples of P. cineraria were collected in August (42–47 oC temp.) 2020 from > 20-year-old trees growing in the desert of Sweihan area (24°17’18.3"N 55°43’36.2"E), Al Ain, UAE. The tissue samples for the extraction of the RNA with respect to the season from P. cineraria were collected in alternate months (January to December) of the year 2021. The leaf samples of C. erectus and Date palm were collected from the plants (> 20-years-old) growing nearby our Center. The plant tissues collected were frozen in liquid-Nitrogen (LN2) and stored at −80 °C to extract RNA for downstream studies.Mature leaves of Zap® RNase Decontamination Solution  was used to eliminate the RNase activity during the extraction of the RNA. In all protocols, the tissues were ground to a fine powder in a pre-chilled mortar and pestle using liquid nitrogen and used immediately or stored at −80 °C for later use.Stringent measures were taken to eliminate the RNase activity from the beginning of the extraction procedure until the end and thereafter in the handling of the RNA. RNaseThe extraction of total RNA using RNeasy Plant Mini Kit , PureLink RNA Mini kit , Spectrum Plant Total RNA kit , and Plant/Fungi DNA/RNA isolation kit  was performed as per the manufacturers’ instructions. An amount of 25–50 mg of finely powdered tissue was used to extract total RNA for the kit protocols.In the case of TRIzol  and TRI Reagent , ~ 50–100 mg/ml finely powdered tissue was transferred for the extraction and carried out as follows.Transferred 50–100 mg powdered, frozen tissue into 1 ml TRIzol/Sigma TRI Reagent in a 2 ml microcentrifuge tube. Mixed well by vigorous shaking and incubated for 5 min at room temperature .Centrifuged the tubes at 14,000 rpm for 10 min at RT.The aqueous phase was transferred into a 1.5 ml microcentrifuge tube and added 0.2 ml chloroform. Mixed well by vigorous shaking, incubated for 5 min at RT, and centrifuged for 10 min at 14,000 rpm.Transferred the aqueous phase into a 1.5 ml microcentrifuge tube and added 0.2 ml absolute ethanol (Added 1 vol. of isopropanol for Sigma TRI Reagent). Mixed well by inversion.Decanted the supernatant after centrifuging at 15,000 rpm for 20 min. The pellet was washed with 500 µl of 70% (v/v) ethanol for 3–5 min. Carefully decanted or pipetted out the supernatant and repeated the step.The air-dried pellet was dissolved in 50 µl of RNase-free water.In this method, TRIzol (Ambion) was used as it was found superior to Sigma TRI Reagent.Followed the TRIzol protocol up to step 4.5.Transferred the solution onto an RNeasy (pink) column of the Qiagen kit (or the column of PureLink RNA isolation kit/Spectrum RNA isolation kit).6.Centrifuged 1 min at 14,000 rpm and discarded the flow-through.7.Added 500 µl RPE buffer (Qiagen). Centrifuged 30–60 s at 12,000 rpm. Discarded the flow-through. Repeated the step.8.Centrifuged the column at 12,000 rpm for 1 min.9.Transferred the column to a new RNase-free 1.5 ml microcentrifuge tube. Added 50 µl of RNase-free water into the center of the column, incubated for 3–5 min at RT, and centrifuged for 1 min at 12,000 rpm.The hexadecyltrimethylammonium bromide  protocol of Chang et al.  was trieThe protocol reported as universal by Vennapusa et al.  was atteThe optimized protocol of the present study was a modification of Chang et al. . It consPrepared 5 ml CTAB extraction buffer by adding 5% (v/v) β-ME in a 15 ml Falcon tube and incubated at 65 °C for 5–10 min in a pre-heated heat block.Transferred the fine tissue powder (200–500 mg of ground tissue) into 5 ml extraction buffer, mixed well by vortexing (30 s), and shook thoroughly. Incubated for at least 5 min at RT on a Nutating mixer (or similar kind) and centrifuged at 12,000 rpm for 10 min.Transferred the aqueous phase to a new 15 ml tube and added an equal volume of CIA (24:1). Mixed by shaking the tube thoroughly, incubated at least 5 min at RT on a Nutating mixer and centrifuge at 12,000 rpm for 10 min.Repeated step 3.oC (or 4–6 h at -20 oC).Transferred the aqueous phase to a new tube and added 1/4 vol.  10 M LiCl, mixed by inversion, and precipitated overnight at 4 g) for 20–30 min at 4 oC, decanted and drained off all the supernatant by keeping the tube upside down on a paper towel or pipetted out.Centrifuged at 15,000 rpm , vortexed, and shook vigorously. Incubated for 3–5 min at RT.Centrifuged the tubes at 15,000 rpm for 10 min and transferred the aqueous phase into a 1.5 ml microcentrifuge tube.g).Added 0.2 ml of chloroform, mixed well by vortexing and vigorous shaking. Incubated for 3–5 min at RT and centrifuged for 10 min at 15,000 rpm . Mixed well by inversion.12.Centrifuged at 15,000 rpm for 10 min. Carefully decanted or pipetted out the supernatant.13.Washed the pellet with 500 µl of 70% (v/v) ethanol for 3–5 min. Centrifuged at 15,000 rpm for 1–2 min. Carefully decanted or pipetted out the supernatant. Repeated the step and air-dried the pellet.14.Added 50 µl of RNase-free water and dissolved the pellet completely.The quantity and purity of the extracted RNA samples were determined by measuring 2 µl in a Nanodrop spectrophotometer . The quality of the RNA samples was assessed by loading 1 µg total RNA on a Hydragreen  added 1% (w/v) agarose  gel, and were documented using GelDoc™ EZ Gel Documentation System .RNA integrity Number (RIN) values were determined based on the entire electrophoretic RNA sample trace on an Agilent 2100 Bioanalyzer (Expert B.02.10.SI764). One µl of extracted total RNA was loaded to determine the integrity and concentration in the Bioanalyzer with the Plant RNA Pico chip assay following the manufacturer’s instructions . The Bioanalyzer uses the electrophoretic technology on a chip to separate RNA fragments by size, read by laser-induced fluorescence, is translated into electropherograms (bands and peaks), and displays the distribution and relative amounts of differently sized RNAs. The measuring of the RNA integrity was carried out as reported earlier , based oDownstream analysis of the extracted RNA.a) cDNA synthesis, amplification of genes using PCR, and gene cloning.P. cineraria were reverse transcribed using Invitrogen SuperScript III Reverse Transcriptase using oligodT(20) according to the manufacturer’s instructions . PCR using the synthesized cDNA with gene-specific primers for HSF6a and HSF7b  following manufacturer’s instructions in a 20 µl reaction mixture and the cDNA synthesized was stored at −20 oC until use. RT-PCR analyses were carried out in reactions containing 2 µl of diluted (1:4) cDNA, 200 nM primers, and 5 µl of 2X Fast SYBR Green PCR master mix  in a 10 µl total volume using a StepOnePlus™ Real-Time PCR system . The HSF primers  as per the manufacturer’s instructions. The cDNA samples following the kit procedure were electroporated into ElectroMAXTM DH10BTM competent cells using Electroporator , and the entry clones derived from BP recombination with pDONRTM 222  were sequenced using M13(–20)-F and M13-R primers (Table oC were powdered into fine powder using LN2. RNA was extracted from the powdered tissue using the optimized (CTAB-TRIzol) protocol described.The applicability of the modified protocol was evaluated by extracting RNA from different plant species and tissues of various angiosperm (monocot and dicot) families, and the details are provided in Additional file P. cineraria, C. erectus and P. dactylifera were repeated five times, and three replicates of other plants/tissues. Data represent the mean ± SE and were evaluated at a 5% level of significance.All the RNA extraction procedures of Successful extraction of high-quality RNA with no degradation and traces of DNA, proteins, polyphenols, and polysaccharides accelerates fundamental and applied research on plant biology. Good quality RNA is essential for diverse downstream molecular studies such as gene expression profiling, subtractive hybridization, construction of cDNA libraries, and RNA-Seq analysis. Optimization of RNA extraction protocol specific to plant species or even to different tissues at high purity is mandatory for trustworthy end results in downstream molecular applications. Polyphenolic components during the extraction of RNA undergo oxidization readily and bind to RNA and co-precipitate, which further cause RNA degradation and become problematic in downstream studies .Arabidopsis, Brachypodium, Setaria, and tobacco [260/A280 and A260/A230 ratios were below 1.8 due to the presence of proteins and polysaccharides. In the present study, though TRIzol (Ambion) was better than TRI Reagent (Sigma), the quality was low  and 18S (1.9 kb), with a double intensity of 28S rRNA band to 18S rRNA band on the agarose gel were considered as good quality RNA , rice seeds, the endosperm of coconut, and different tissues of Date palm such as root, flowers, floral parts (anther and pollen), fruits (immature and mature), and seeds were attempted with the optimized protocol , tuber , northern blotting, and cloning authenticate a protocol. The RNA extracted from stress-tolerant P. cineraria. Heat shock factors (HSF6a and HSF7b) using gene-specific primers  with Actin as reference gene showed a significant difference in expression level  collected in every alternate month (triplicates) from January through December of the year 2021 (Table The samples of RNA extracted through the modified protocol from 21 Table  qualifieNo universal protocol is available for isolating total RNA as the plants vary significantly in their structural and biochemical profile. However, the modified protocol yielded high-quality DNA-free intact RNA from various plant species, tissue types, and with respect to season, which was authenticated by bioanalyzer results and successful downstream use. The protocol is useful for extracting DNA-free intact RNA from plants with high phenolics, starch, and polysaccharides.Below is the link to the electronic supplementary material.Additonal file 1: RNA extracted from different plant species/tissuesAdditional file 2: The sequences of HSFs