Domains for controlling post-transcriptional gene expression

Abstract

Provided herein are compositions, systems, and methods for the generation, identification, characterization, and use of domains for modulating RNA levels and / or gene expression, e.g., inducing RNA degradation or downregulating mRNA translation.

Description

[0001] DOMAINS FOR CONTROLLING POST-TRANSCRIPTIONAL GENE EXPRESSION

[0002] FIELD

[0003] Provided herein are compositions, systems, and methods for the generation, identification, characterization, and use of domains for modulating RNA levels and / or gene expression, e.g., inducing RNA degradation or downregulating mRNA translation.

[0004] CROSS REFERENCE TO RELATED APPLICATIONS

[0005] This application claims the benefit of U.S. Provisional Application No. 63 / 672,982, filed July 18, 2024, the content of which is herein incorporated by reference in its entirety.

[0006] SEQUENCE LISTING STATEMENT

[0007] The content of the electronic sequence listing titled STDU2_43467_601_SequenceListing.xml (Size: 297,545 bytes; and Date of Creation: July 15, 2025) is herein incorporated by reference in its entirety.

[0008] STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH

[0009] This invention was made with Government support under contracts CA287739, GM128947, and HG011866 awarded by the National Institutes of Health. The Government has certain rights in the invention.

[0010] BACKGROUND

[0011] Post-transcriptional gene regulation plays an integral role in tuning overall levels of cellular gene expression. RNA and protein levels in the cell are not tightly correlated, signifying the importance of controlling RNA degradation and translation rates to reach homeostasis. RNA-binding proteins (RBPs) are the largest class of post-transcriptional genetic regulators and are known to significantly impact the fates of the RNAs they bind. However, until recent advances in RNA targeting and editing technologies, it remained difficult to precisely control gene regulation in human cells at the RNA level, and compact protein tools that can regulate mRNA fate in a tunable manner are still lacking.SUMMARY

[0012] Provided herein are synthetic RNA regulatory proteins comprising one or more RNA regulatory domains fused to a heterologous nucleic acid binding domain.

[0013] In some embodiments, at least one of the one or more RNA regulatory domains comprises an amino acid sequence having at least 70% identity to any of SEQ ID NOs: 1-119, or a fragment thereof. In some embodiments, at least one of the one or more RNA regulatory domains comprises an amino acid sequence having at least 90% identity to any of SEQ ID NOs: 1-119, or a fragment thereof. In some embodiments, at least one of the one or more RNA regulatory domains comprises an amino acid sequence of any of SEQ ID NOs: 1-119, or a fragment thereof.

[0014] In some embodiments, at least one of the one or more RNA regulatory domains comprises at least 10 contiguous amino acids of any of SEQ ID NOs: 1-119. In some embodiments, at least one of the one or more RNA regulatory domains comprises an amino acid sequence of any of SEQ ID NOs: 239-312.

[0015] In some embodiments, at least one of the one or more RNA regulatory domains comprises an amino acid sequence having at least 70% identity to any of SEQ ID NOs: 120-238. In some embodiments, at least one of the one or more RNA regulatory domains comprises an amino acid sequence having at least 90% identity to any of SEQ ID NOs: 120-238. In some embodiments, at least one of the one or more RNA regulatory domains comprises an amino acid sequence of any of SEQ ID NOs: 120-238.

[0016] In some embodiments, at least one of the one or more RNA regulatory domains comprises an amino acid sequence having at least 70% identity to any of SEQ ID NOs: 1-312. In some embodiments, at least one of the one or more RNA regulatory domains comprises an amino acid sequence having at least 90% identity to any of SEQ ID NOs: 1-312. In some embodiments, at least one of the one or more RNA regulatory domains comprise an amino acid sequence of SEQ ID NOs: 1-312.

[0017] In some embodiments, at least one of the one or more RNA regulatory domains comprises at least 10 contiguous amino acids of any of SEQ ID NOs: 1-118. In some embodiments, the synthetic RNA regulatory protein comprises two or more RNA regulatory effector domains.In some embodiments, the heterologous nucleic acid binding domain is an RNA binding domain. In some embodiments, the heterologous nucleic acid binding domain is a DNA binding domain. In some embodiments, the heterologous nucleic acid binding domain is a programmable nucleic acid binding domain. In some embodiments, the heterologous nucleic acid binding domain is or is derived from a Clustered Regularly Interspaced Short Palindromic Repeats associated (Cas) protein. In some embodiments, the heterologous nucleic acid binding domain is inducible or part of an inducible binding system.

[0018] Also provided herein are nucleic acids encoding the synthetic RNA regulatory proteins disclosed herein, vectors comprising the nucleic acids, and cells comprising synthetic RNA regulatory proteins, nucleic acids, and / or vectors disclosed herein.

[0019] Further provided are compositions or systems comprising a synthetic RNA regulatory protein, a nucleic acid, a vector, or a cell as described herein. In some embodiments, the compositions or systems comprise two or more synthetic RNA regulatory protein, nucleic acids, vectors, or cells. In some embodiments, the composition or system further comprises a guide RNA or a nucleic acid encoding a guide RNA.

[0020] Additionally provided are methods of modulating RNA levels (e.g., mRNA levels) and methods of modulating the level of one or more target RNAs and / or expression (e.g., translation) of one or more target genes in a cell. In some embodiments, the methods comprise contacting a target nucleic acid encoding the target RNA or the target RNA with at least one synthetic RNA regulatory protein as disclosed herein. In some embodiments, the methods comprise introducing into the cell at least one synthetic RNA regulatory protein, nucleic acid, and / or vector as disclosed herein. In some embodiments, the cell is in a subject. In some embodiments, the methods comprise administering the at least one synthetic RNA regulatory protein, nucleic acid, vector, or composition or system to the subject.

[0021] In some embodiments, the levels of at least two RNAs and / or gene expression of at least two genes are modulated.

[0022] In some embodiments, the at least one synthetic RNA regulatory protein decreases the level of one or more target RNAs. In some embodiments, the at least one synthetic RNA regulatory protein increases degradation of one or more target RNAs. In some embodiments, the at least one synthetic RNA regulatory protein decreases the expression of one or more targetgenes. In some embodiments, the at least one synthetic RNA regulatory protein at least partially inhibits transcription and / or translation.

[0023] In some embodiments, the target RNAs and / or target genes are endogenous to the cell. In some embodiments, the target RNAs and / or target genes are exogenous to the cell.

[0024] Also provided are methods for treating a disease or condition in a subject. In some embodiments, the methods comprise administering to the subject an effective amount of at least one synthetic RNA regulatory protein, nucleic acid, vector, or composition or system as disclosed herein. In some embodiments, the subject is human. In some embodiments, the synthetic RNA regulatory protein decreases the level of a disease-related RNA or alters expression of a disease-related gene.

[0025] Other aspects and embodiments of the disclosure will be apparent in light of the following detailed description and accompanying figures.

[0026] BRIEF DESCRIPTION OF THE DRAWINGS FIGS. 1A-1H show high-throughput recruitment to RNA discovers hundreds of protein tiles with RNA-regulating capabilities. FIG. 1 A is an overview of an exemplary high-throughput RNA recruitment assay. A library of protein tiles is cloned as a pool to the MS2 capsid protein dimer and delivered to cells expressing a reporter gene encoding a surface marker that enables magnetic separation of cells, a Citrine reporter gene, and 24 copies of the MS2 stem loop for 3’UTR recruitment of the protein library. After 10 days of recruitment, cells are separated into ON and OFF populations and domains are sequenced. FIG. 1B is a schematic of RBP library design, which includes all possible 80 amino acid tiles for 367 human RBPs. FIGS. 1C is a graph of log2(OFF:ON) (positive = RNA downregulated) enrichment scores plotted per replicate of the human RBP screen in K562 cells. Light gray, all members; dark gray, random controls; green, tiles from NANOS 1 known RNA regulatory domain. FIG. ID is an example tiling plot of NANOS1, a known translational modulator. X-axis, position of tile along protein; y-axis, recruitment screen score. Line, length of tile; dot, tile score; vertical error bars, standard deviation of 2 biological screen replicates. The solid line represents the screen hit cutoff and dashed vertical lines represent the edges of the determined regulatory domain span. Inset: Flow cytometry plot of individual recruitment of top tile MCP-NANOS1_002 (green fill) versus MCP alone (grey line, no fill). FIG. IE shows individual validation measurements for 48 tested tiles.Grey dashed lines represent screen cutoff score (vertical) and corresponding Citrine OFF cutoff (horizontal). Red dot, MCP alone; blue dot, NANOS1_002. Error bars represent an average of two biological replicates. FIG. IF is a graph of the top 50 RBPs with tile hits in the recruitment screen, binned into categories of RNA-related function and ranked by top tile screen score. Starred proteins are those whose top tiles overlapped with previously reported regulatory domains. Dashed line, recruitment hit cutoff. FIG. 1G is a schematic describing the functions of putative RNA-regulatory effector domains (RREs). Some RBPs may act directly once bound to RNA, such as nucleases or proteins that sterically block translation factors. Other RBPs may consist of modular RREs, to be identified in this study, that will act to recruit larger-acting enzymatic complexes directly or via other cofactors. FIG. 1H is a tiling plot of CNOT2, known member of the CCR4-NOT deadenylation complex. Green box, newly identified RNA-regulatory region; red box, Pfam-annotated NOT domains from UniProt.

[0027] FIGS. 2A-2I show annotation of regulatory domains in human RNA binding proteins. FIG. 2A is a schematic of domain identification criteria. Single hit tiles at the N- or C-terminus or overlapping hit tiles were considered regulatory domains, but not single tiles with no overlapping neighboring hits. FIG. 2B is a bar chart of 101 identified regulatory domains. 78 did not overlap either an RNA-binding domain (RBD) or previously annotated regulatory domain, 6 overlapped RBDs, and 17 overlapped known domains. FIG. 2C is a tiling plot of TTP (ZFP36), known mRNA degradation activator. Identified C-terminal regulatory domain overlaps a known CNOT1 interaction motif (inset, right, cross-species conserved residues in yellow; SEQ ID NO: 315) and is disordered (structure, inset). FIG. 2D is a tiling plot of PKR (EIF2AK2). Inset: Flow cytometry plot of individual recruitment of top tile EIF2AK2_0222 (green fill) versus MCP alone (grey fine, no fill). FIG. 2E is an Alphafold predicted structure of PKR. Grey, annotated dsRM RBD; black, annotated kinase domain; green, the identified regulatory domain; yellow, computationally minimized sequence of regulatory domain (Methods); red, essential region as identified by deletion scanning mutagenesis in FIG. 2F. FIG. 2F shows deletion scanning mutagenesis of EIF2AK2 tile 22 (residue 211-290). Each line is a 5aa deletion, with x-axis showing the deleted residues; dot is the fraction OFF score for that deletion as measured by flow cytometry. Shading represents the fraction OFF for the wild-type (non-deleted) tile. Vertical error bars are the average of two biological replicates. Gradient shows the essential residues (SEQ ID NO: 316) whose deletion caused decreased RNA downregulation. FIG. 2G is a graph ofpredicted disordered character of 195 tested hit tiles (orange) vs. 195 non-hit tiles (green), as predicted by Jpred4. FIG. 2H is a 2-D schematic (left) and example Alphafold structure (right) of the LSm domains that were enriched in non-disordered hit tiles. A MEME suite rendering of the LSm motif sequence is shown below. FIG. 2I is a tiling plot of LSM14A (LSm domain structure shown in FIG. 2H).

[0028] FIGS. 3A-3L show regulatory domain identification and strength is dependent on recruitment positioning and stoichiometry. FIG. 3 A is a schematic of the 5’UTR recruitment RNA with site for changing numbers of MS2 stem-loops. FIG. 3B is log2(OFF:ON) enrichment scores plotted per replicate of the RBP library screen at 24 stem-loops in the 5’UTR. Grey dots, all tiles; purple contour lines, random control distribution. ‘High’ threshold (mean+1.5 standard deviations of the random population) in red dashed line, ‘low’ threshold in grey dashed line. FIG.

[0029] 3C shows individual validation measurements for 48 selected tiles in 5’UTR reporter cells. Red dashed lines represent the high screen cutoff and corresponding fraction OFF cutoff, grey dashed lines represent the same for low threshold. MCP alone is shown as a red dot, NANOS1_003 in blue, and selected random control random_set2_0603 in orange. FIG. 3D is a graph of the fraction Citrine OFF (y-axis) of cells harboring 5’UTR reporters with changing numbers of MS2 loops (x-axis), each with MCP alone or 3 different selected tiles. Shading is standard deviation from two biological replicates. FIG. 3E is log2(OFF:ON) enrichment scores plotted per replicate of the RBP hit library (n = 3,145) screen at 7 stem-loops in the 5’UTR. Grey dots, all tiles; green contour, random control; red dashed line, screen threshold (mean + 1.5 standard deviation of random population). FIG. 3F shows fraction Citrine OFF for selected tiles individually tested at cells expressing reporters with 24 (x-axis) vs. 7 (y-axis) stem-loops in the 5’ UTR. MCP alone is shown in red, and random_set4_0603 is again shown in orange. FIG. 3G shows fraction OFF scores (calculated using the fitted transformation from each set of individual validation experiments) for the full RBP library at 24 stem-loops in either the 3’UTR (x-axis) or 5’UTR (y-axis). Light grey, all tiles; dark grey, random controls; purple, tiles from CNOT4. Vertical grey dashed line, transformed cutoff for 3’ screen; horizontal red dashed line, transformed high cutoff for 5’ screen; horizontal black dashed line, transformed low cutoff for 5’ screen. FIG. 3H is a summary of 91 total RBPs that were annotated with regulatory domains in the 5’UTR screen, 3’UTR screen, or both. FIG. 3I is a tiling plot for DCP1B, an exemplary regulatory domain in the 5’ UTR, showing both 24 stem-loop 3’UTR scores (green) and 24 stem-loop 5’UTR scores(purple). 3’UTR domains are shaded in green, which contain the identified 5’UTR domain (purple shading). FIG. 3J is a tiling plot for FIP1L1, an exemplary regulatory domain in the 3’ UTR, with its 5’UTR domain (purple) and 3’UTR domains (green). FIG. 3K is a tiling plot for CNOT4, an exemplary regulatory domain in the 5’ and 3’ UTR. FIG. 3L is a tiling plot for HLTF, and exemplary regulatory domain with distinct domains in the 5’ and 3’ UTR.

[0030] FIGS. 4A-4H show DNA-level recruitment investigates dual DNA- and RNA-mediated control by RBP regulatory domains. FIG. 4A, top, is a schematic of MS2 reporter construct. FIG.

[0031] 4 A, bottom, is a schematic of TetO reporter construct. RBP tiles are cloned to the dox-inducible DNA-binding domain rTetR and recruited to a reporter expressing the same surface reporter and Citrine in the MS2 reporters. FIG. 4B shows the average log2(OFF:ON) enrichment scores (two replicates) for the RBP hit library in the TetO DNA screen (x-axis) and the batch-retest 3’UTR 24 stem-loop RNA screen (y-axis). Purple (lower right quadrant), DNA hits; green (upper left quadrant), RNA hits; yellow (upper right quadrant), dual hits; grey (lower left quadrant), rest of tiles; vertical dashed line, DNA screen cutoff; horizontal dashed line, RNA screen cutoff. FIG.

[0032] 4C is Alphafold predicted structures of the categories of non-random control dual hits. Blue (RBPs), tiles from known RNA regulators; yellow (RBP+CR), known RBP + chromatin regulator CHTOP; pink (TFs), KRAB domain structure. FIG. 4D is a tiling plot for CHTOP for the original RBP Library 3’UTR screen (green) and the DNA screen (purple). Stars represent tiles re-tested in the smaller batch screen at the 3’UTR, 24 stem-loop reporter. FIG. 4E is a summary of individual flow cytometry measurements of CHTOP deletions, with the identified putative DNA-inhibitory region shown in red on the schematics at left and each deletion shown as a dashed line. Green bars, fraction Citrine OFF when measured on the MCP-MS2 RNA recruitment system at 24 stem-loops in the 3’UTR; yellow bars, fraction Citrine OFF when measured on the rTetR-TetO DNA system. Bottom, sequence of CHTOP regulatory region (SEQ ID NO: 1) with inhibitory 5 amino acids in red. Error bars are standard deviations of two biological replicates. FIG. 4F, top, is a schematic of possible mechanisms of transcriptional vs. post-transcriptional regulation during RNA recruitment. FIG. 4F, bottom, is a schematic of DHFR-MCP degradation and TMP-induced stabilization. FIG. 4F is a graph of Citrine mRNA levels over time as measured by flow cytometry of HCR-Flow-RNA-FISH, normalized to timepoint 0 for each experiment for cells expressing the 5’UTR, 7 stem-loop reporter.

[0033] Timecourses are taken after the concurrent addition of actinomycin D and TMP (at time=0) forDHFR-MCP alone (grey), DHFR-MCP-ZNF10_KRAB (blue), and DHFR-MCP-NANOS1_003 (green). Shading is standard deviation of two biological replicates. FIG. 4H is a graph of relative H3K9me3 levels as measured by CUT& RUN, integrated over the 5kb locus of the 5’UTR, 7 stem-loop reporter, for TMP and dox recruitment of DHFR-MCP-NANOS1_003 (blue), DHFR-MCP-ZNF10_KRAB (green), and rTetR-ZNF10_KRAB (yellow). Error bars are standard deviations of two biological replicates.

[0034] FIGS. 5A-5J show a tunable RBP creates synthetic RNA-level gene regulation and expands gene expression models. FIG. 5A is a schematic of dose-tunable DHFR-MCP construct, which is expressed more stably with increasing TMP. FIG. 5B shows the model fit for relative MCP-NANOS1_003 levels, as measured using HaloTag staining, at different TMP doses to determine KD. TMP, or relative TMP dependence on RBP expression levels. FIG. 5C is flow cytometry distributions of DHFR-MCP-NANOS l_003 recruited to the 7 stem-loop 5’UTR reporter at varying concentrations of TMP. FIG. 5D is a schematic for a mathematical model of gene regulation at the RNA level, where an active gene (A) produces mRNA at a constant rate ktxn. mRNA is either degraded by a TMP-dependent RBP at a rate kreg, or by constant cellular mRNA degradation at a rate kdeg- Protein translation and protein degradation occur at constant rates ktriand kdeg, protein, respectively. FIG. 5E show the model fit to Citrine levels after recruitment of DHFR-MCP-NANOS l_003 at varying TMP doses after 4 days of recruitment. FIG. 5F is the model fit to Citrine levels after recruitment of DHFR-MCP-NANOS l_003 at varying TMP doses over time. FIG. 5G shows Gillespie simulation results for cells hypothetically expressing a dox-inducible transcriptional silencer and a TMP-inducible RNA regulator, for two dox doses (top row, 1 ng / mL; bottom row, 3.33 ng / mL) and three TMP doses (columns, L-R: 0, 0.1, and 10 M). Y-axis, number of simulated cells; X-axis, simulated Citrine fluorescence intensity. FIG. 5H is a schematic of RBFOX-NANOS creation and use. The strong RRE from synNANOS is fused to the RBD from RBFOX2, which is then transfected into K562 cells. Transcripts that are endogenously bound by RBFOX2 will then be bound by the chimeric RBFOX-NANOS and degraded. FIG. 51 is a volcano plot from RNA-seq of overexpression of RBFOX-NANOS vs. overexpression of synNANOS. Significantly upregulated genes and downregulated genes are shown after 48 hours of overexpression. FIG. 5J is a volcano plot from RNA-seq of overexpression of synNANOS vs. overexpression of MCP alone. Significantlyupregulated genes and downregulated genes are shown after 48 hours of overexpression; gene fragments from the mCitrine-magnetic separation reporter are labelled.

[0035] FIGS. 6A-6I show RBP library screen details, related to Figure 1. FIG. 6A is a full construct schematic of the RNA recruitment reporter integrated into the AA VS J safe harbor locus in the first intron of the PPP1R12C gene (top) and MCP-fusion vector for pooled domain cloning (bottom). puroR = puromycin resistance, TetO = tetracycline repressor binding sites, IgG-Fc = immunoglobulin G constant region, BSD = blasticidin resistance, LTR = long terminal repeats for lentiviral integration. FIG. 6B is flow cytometry distributions on day 10 of recruitment per replicate RBP library screen cells before and after magnetic separation. FIG. 6C is a summary of RNA downregulation for individually tested screen tiles as measured by flow cytometry, reported in fraction of cells OFF. Tiles are ranked (L-R) by decreasing screen score. FIGS. 6D-6F are exemplary flow cytometry distributions for tested tiles of varying strength: CNOT4_036 (FIG. 6D), FIP1L1_O17 (FIG. 6E), OASL_016 (FIG. 6D), (green fill) versus MCP alone (grey line, no fill). Vertical error bars are standard deviation of two biological replicates. FIG. 6G shows Protein vs. RNA level measurements for 8 selected validations, measured in Citrine fluorescence by flow cytometry (x-axis) and Alexa-674 fluorescence by flow cytometry of HCR-RNA-Flow-FISH (y-axis, normalized to levels of cells expressing MCP alone). Below, example Alexa-647 and mCitrine distributions for RNA and protein level measurements, respectively, of CHTOP_001 and MCP alone. FIG. 6H shows a comparison of 195 proteins tested in both this study and in Luo, E.-C., et al. (2020). Nat. Struct. Mol. Biol. 27, 989-1000, with x-axis the recruitment screen score of the top tile tested in this study and y-axis the RNA fold-change of the tethered full protein tested in Luo, et al. Green dots, non-hits in this study; blue dots, hits in this study. Horizontal dashed line is cutoff in previous study (below dashed line = downregulation hit), vertical dashed line is cutoff in this screen. FIG. 6I is flow cytometry measurements of Citrine reporter fluorescence after recruitment of (left-right) the top 80aa tile from NANOS1, MCP alone, FIP1L1 (whole protein) + / - the strongest 80aa tile identified in the screen, or NANOS1 (whole protein) + / - its strongest tile. Green dots, wild-type constructs; grey dots, constructs missing 80aa segments.

[0036] FIGS. 7A-7F show domain analyses and visualization, related to Figure 2. FIG. 7 A is a tiling plot for CNOT4, showing previously annotated CNOT1 interaction region and more specifically annotated regulatory domain in this study. FIG. 7B is an Alphafold predictedstructure of PKR regulatory domain alone. FIG. 7C is a graph of predicted number of alphahelical residues for 195 non-hit vs. hit tiles. FIG. 7D is a graph of predicted number of B-sheet residues for 195 non-hit vs. hit tiles. FIG. 7E is bar graphs of amino acid frequency enrichment in 195 hit tiles over frequencies in non-hit tiles. Top, all 195 hits; middle, hits with <35% structured residues; bottom, hits with >35% structured residues. FIG. 7F is a plot of all tiles (one dot = 1 tile) tested from LSm-domain-containing proteins in the RBP library screen. Horizontal dashed line: screen hit cutoff; vertical dashed line: delineating proteins with LSm domain hits (left) from those without (right).

[0037] FIGS. 8A-8K show 5’UTR screen details, related to Figure 3. FIG. 8A is flow cytometry distributions on day 10 of recruitment for replicate 24 stem-loop 5’UTR RBP library screen cells before infection and before and after magnetic separation. FIG. 8B is a summary of RNA downregulation for individually tested screen tiles as measured by flow cytometry, reported in fraction of cells OFF. Tiles are ranked (L-R) by decreasing screen score. FIG. 8C shows protein vs. RNA level measurements for 8 selected validations, measured in Citrine fluorescence by flow cytometry (x-axis) and relative values of qPCR against Citrine (y-axis, normalized to Ct values of cells expressing MCP alone). Vertical error is standard deviation of 3 technical replicates. FIG. 8D is the same as FIG. 3D, but reported in Citrine MFI normalized to MCP alone (y-axis) instead of fraction Citrine OFF cells. FIG. 8E is flow cytometry distributions on day 10 of recruitment for replicate 7 stem-loop 5’UTR RBP library screen cells before and after magnetic separation. FIG. 8F shows the distributions of transformed OFF screen scores for all random control tiles in the 5’UTR 24 (left) and 7 (right) stem-loop screens. FIG. 8G is a graph of the individual validation measurements for 22 selected tiles in 7 stem-loop 5’UTR reporter cells. Tiles are colored by whether or not they were hits in the original 24 stem-loop 5’UTR screen, the 7 stem-loop 5’UTR screen, both, or neither. MCP alone is shown in red. Error bars are standard deviation of two biological replicates. FIG. 8H is exemplary flow cytometry distributions for 4 selected tiles (blue / purple fill) at 7 stem-loops (top) or 24 stem-loops. MCP alone for each reporter line is shown in grey fill. Screen scores are reported for each tile on each reporter to the right of its distribution. FIG. 81 shows all RBP hit library members (n = 3,145) plotted with their transformed screen score in the 5’UTR at 24 stem-loops (x-axis) versus 7 stem-loops (y-axis). Grey dots, all tiles; green dots, random controls; vertical dashed line, transformed 24 stem-loophigh threshold; horizontal dashed line, transformed 7 stem-loop threshold. FIG. 8J is a tiling plot for ADAD2. FIG. 8K is a tiling plot for SETD1B.

[0038] FIGS. 9A-9L show DNA screen and follow-up details, related to Figure 4. FIG. 9A is flow cytometry distributions on day 5 of dox-mediate recruitment for replicate rTetR-TetO RBP hit library screen cells before dox addition and before and after magnetic separation. FIG. 9B is flow cytometry distributions on day 10 of recruitment for replicate 24 stem-loop 5’UTR RBP hit library screen cells before infection and before and after magnetic separation. FIG. 9C shows log2(OFF:ON) enrichment scores plotted per replicate of the RBP hit library screen in the rTetR-TetO system. Grey, all tiles; yellow, random controls; black dashed line, screen cutoff (mean + 3 standard deviations of random population). FIG. 9D shows individual validation measurements of 10 selected tiles over 5 days of dox recruitment in rTetR-TetO reporter cells, reported as fraction Citrine OFF for each line normalized to its paired no-dox recruitment control. FIG. 9E shows log2(OFF:ON) enrichment scores plotted per replicate of the RBP hit library screen on MCP at 24 stem-loops in the 3’UTR. Grey, all tiles; green, random controls; black dashed line, screen cutoff (mean + 3 standard deviations of random population). FIG. 9F shows average log2(OFF:ON) scores for RBP hit library members in the batch retest (x-axis) vs. the original RBP library screen (y-axis). Grey, all tiles; green, random controls; vertical dashed line, batch retest cutoff; horizontal dashed line, original screen cutoff. FIG. 9G shows average log2(OFF:ON) scores for the top scoring tile in the DNA (x-axis) or RNA (y-axis) screens per RBP tested. Purple, proteins with DNA hit tiles; green, proteins with RNA hit tiles; yellow, proteins with hit tiles in both screens. FIG. 9H is a summary of individual flow cytometry measurements of additional CHTOP tiles and deletions. Green, fraction Citrine OFF when tested fused to MCP in 24 stem-loop, 3’UTR reporter cells; yellow, fraction Citrine OFF when tested fused to rTetR in TetO reporter cells. Error bars are standard deviations of two biological replicates. FIG. 91 is flow cytometry distributions for selected CHTOP tiles and deletions on RNA (top, green fill) and DNA (bottom, red / yellow fill) vs. MCP alone (grey fill, top) and no dox (grey fill, bottom) recruitment controls. FIG. 9 J shows HaloTag fluorescence of DHFR-MCP-ZNF10_KRAB after various hours of TMP (blue) or DMSO (grey, control) addition, as measured by JaneliaFluor-647 fluorescence after staining of the HaloTag inserted C-terminal to MCP. Error bars are standard deviations of two biological replicates. FIG. 9K is genome traces showing normalized CUT& RUN reads against H3K9me3 as a function of distance around the5’UTR, 7 stem-loop reporter integration site (0 kb on x-axis) after recruitment of MCP-NANOS1_003 (top), MCP-ZNF10_KRAB (middle), or rTetR-KRAB (bottom). Bar plots are average of biological replicates. Bottom, schematic of genomic locus. FIG. 9L is the quantification of H3K9me3 levels at positive control KCNQ1 (known high levels of H3K9me3 modification in K562 cells) across the same conditions shown in FIG. 4H.

[0039] FIGS. 10A-10K show details of TMP-mediated recruitment and modeling, related to Figure 5. FIG. 10A is flow cytometry distributions of 7 stem-loop, 5’UTR reporter cells expressing DHFR-MCP-NANOS1_003 after initial addition of 10 μM TMP, after sorting the silenced cells and allowing reactivation for 5 days, and after re-addition of 10 μM TMP for 4 days (L-R). FIG. 10B is a schematic of dose-tunable rTetR construct, in which rTetR-KRAB binds at higher occupancy for increasing doses of dox. FIG. 10C is flow cytometry distributions of rTetR-KRAB recruited to the same reporter as in Fig. 5B at varying dox doses. FIG. 10D is the quantification of mean Citrine fluorescence levels for all doses of dox. FIG. 10E is a graph of predicted Citrine levels for varying levels of model extracted parameter a, proxy for RNA degradation rate upon expression of an RBP. FIG. 10F is a schematic overview of KRAB-mediated transcriptional silencing model: the gene can either be in the active (A) or silenced (S) state, the transition between which is controlled by a transcriptional silencer at a dox-dependent rate ks. Cells can produce mRNA in the A state at a constant rate ktxn, mRNA is then degraded at the constitutive rate kdeg. Protein is made and degraded at the constant rates ktriand kdeg, protein, respectively. FIG. 10G is a graph of a two-state transcription model fit to Citrine levels after recruitment of rTetR-KRAB at varying dox doses over time. FIG. 10H is a schematic overview of Gillespie simulation assumptions: the gene can either be in the active (A) or silenced (S) state, the transition between which is controlled by a transcriptional silencer at a dox-dependent rate ks. Cells can produce mRNA in either the A or S states at a constant rate ktxn', mRNA is then degraded by the TMP-controlled RBP at a rate kregor the constitutive rate kdeg. Protein is made and degraded at the constant rates ktriand kdeg, protein, respectively. FIG. 101 is a summary of predicted Citrine MFI and fraction cells with Citrine OFF from Gillespie simulation of the dual transcriptional / post-transcriptional regulator system at varying TMP doses (RBP control, colors) and dox doses (transcriptional repressor control, shapes). FIG. 10J shows a comparison of 186 proteins tested in both this study and in the manuscript by Luo, E.-C., et al. (Nat. Struct. Mol. Biol. 27, 989-1000 (2020), with x-axis the recruitment screen score of the top tile tested in thisstudy and y-axis the RNA fold-change of the tethered full protein tested in Luo, et al. Green dots, non-hits in this study; blue dots, hits in this study. Horizontal dashed line is cutoff in previous study (below dashed line = downregulation hit), vertical dashed line is cutoff in the screen. FIG.

[0040] 1 OK is a chart detailing the 12 proteins found as hits in both this work and previous full-length work, the location of their strongest downregulatory tile from this work (coordinates in amino acids), and whether that region had been previously annotated.

[0041] DETAILED DESCRIPTION RNA-binding proteins (RBPs) play integral roles in the coordination of mRNA fate and the post-transcriptional regulation of gene expression. Over 1,000 RBPs exist in human cells and coordinate each step of the mRNA lifecycle, making them the largest class of regulators of post-transcriptional gene expression. Past studies have identified RNA-binding domains within RBPs and constructed maps of their RNA binding profiles, but little has been done to systematically describe other domains within human RBPs that regulate RNA fate and the mechanisms by which they do so. Thus, a comprehensive list of the RBP domains that control mRNA regulation in human biology is lacking.

[0042] Here, a high-throughput, pooled recruitment assay in human cells was developed to measure RNA regulatory activity for tens of thousands of protein tiles. This approach was used to identify new RNA regulatory domains through unbiased tiling of over 300 human RBPs as well as testing all Pfam-annotated domains in known RBPs for regulatory activity. Furthermore, the synthetic system was used to systematically vary recruitment positioning and stoichiometry on the reporter RNA and demonstrate that RBP regulatory domain strength is dependent on both. In addition, a previously developed high-throughput DNA recruitment system was used to compare the transcriptional and post-transcriptional regulatory capacity of a subset of RBP tiles and find that the KRAB domain from ZNF10 is able to exert transcriptional silencing effects even when bound to RNA. Finally, a mathematical model was developed which characterizes the dose-dependence of RBP-mediated regulation and is capable of predicting protein expression over time for RNAs bound by regulatory RBPs, demonstrating their distinct contributions to tuning overall expression levels in endogenous systems.

[0043] Over 100 unique regulatory domains in 86 distinct RBPs were discovered, suggesting that RBPs are modular and comprised of functionally separable domains that dictate their post-transcriptional control of gene expression. Through systematic perturbations of RBP positioningand stoichiometry, regulatory activity of protein domains in low copy number and in both 5' and 3' UTRs were detected. Domains with both DNA-mediated and RNA-mediated regulatory capability were identified and their mechanisms of regulation were investigated.

[0044] Provided herein are synthetic RNA regulatory proteins comprising one or more RNA regulatory domains fused to a heterologous nucleic acid binding domain.

[0045] Section headings as used in this section and the entire disclosure herein are merely for organizational purposes and are not intended to be limiting.

[0046] 1. Definitions

[0047] The terms “comprise(s),” “include(s),” “having,” “has,” “can,” “contain(s),” and variants thereof, as used herein, are intended to be open-ended transitional phrases, terms, or words that do not preclude the possibility of additional acts or structures. As used herein, comprising a certain sequence or a certain SEQ ID NO usually implies that at least one copy of said sequence is present in recited peptide or polynucleotide. However, two or more copies are also contemplated.

[0048] The singular forms “a,” “and” and “the” include plural references unless the context clearly dictates otherwise. Further, unless otherwise required by context, singular terms shall include pluralities and plural terms shall include the singular. The present disclosure also contemplates other embodiments “comprising,” “consisting of’ and “consisting essentially of,” the embodiments or elements presented herein, whether explicitly set forth or not.

[0049] For the recitation of numeric ranges herein, each intervening number there between with the same degree of precision is explicitly contemplated. For example, for the range of 6-9, the numbers 7 and 8 are contemplated in addition to 6 and 9, and for the range 6.0-7.0, the number 6.0, 6.1, 6.2, 6.3, 6.4, 6.5, 6.6, 6.7, 6.8, 6.9, and 7.0 are explicitly contemplated.

[0050] Unless otherwise defined herein, scientific, and technical terms used in connection with the present disclosure shall have the meanings that are commonly understood by those of ordinary skill in the art. The meaning and scope of the terms should be clear; in the event, however of any latent ambiguity, definitions provided herein take precedent over any dictionary or extrinsic definition.

[0051] As used herein, a “nucleic acid” or a “nucleic acid sequence” refers to a polymer or oligomer of pyrimidine and / or purine bases, preferably cytosine, thymine, and uracil, and adenine and guanine, respectively (See Albert L. Lehninger, Principles of Biochemistry, at 793-800 (Worth Pub. 1982)). The present technology contemplates any deoxyribonucleotide, ribonucleotide, or peptide nucleic acid component, and any chemical variants thereof, such as methylated, hydroxymethylated, or glycosylated forms of these bases, and the like. The polymers or oligomers may be heterogenous or homogenous in composition and may be isolated from naturally occurring sources or may be artificially or synthetically produced. In addition, the nucleic acids may be DNA or RNA, or a mixture thereof, and may exist permanently or transitionally in single-stranded or double-stranded form, including homoduplex, heteroduplex, and hybrid states. In some embodiments, a nucleic acid or nucleic acid sequence comprises other kinds of nucleic acid structures such as, for instance, a DNA / RNA helix, peptide nucleic acid (PNA), morpholino nucleic acid (see, e.g., Braasch and Corey, Biochemistry, 41(14): 4503-4510 (2002)) and U. S. Pat. No. 5,034,506), locked nucleic acid (LNA; see Wahlestedt et al., Proc. Natl. Acad. Sci. U. S. A., 97: 5633-5638 (2000)), cyclohexenyl nucleic acids (see Wang, J. Am. Chem. Soc., 122: 8595-8602 (2000)), and / or a ribozyme. Hence, the term “nucleic acid” or “nucleic acid sequence” may also encompass a chain comprising non-natural nucleotides, modified nucleotides, and / or non- nucleotide building blocks that can exhibit the same function as natural nucleotides (e.g., “nucleotide analogs”); further, the term “nucleic acid sequence” as used herein refers to an oligonucleotide, nucleotide or polynucleotide, and fragments or portions thereof, and to DNA or RNA of genomic or synthetic origin, which may be single or doublestranded, and represent the sense or antisense strand. The terms “nucleic acid,” “polynucleotide,” “nucleotide sequence,” and “oligonucleotide” are used interchangeably. They refer to a polymeric form of nucleotides of any length, either deoxyribonucleotides or ribonucleotides, or analogs thereof.

[0052] A “peptide” or “polypeptide” is a linked sequence of two or more amino acids linked by peptide bonds. The peptide or polypeptide can be natural, synthetic, or a modification or combination of natural and synthetic. Polypeptides include proteins such as binding proteins, receptors, and antibodies. The proteins may be modified by the addition of sugars, lipids or other moieties not included in the amino acid chain. The terms “polypeptide” and “protein,” are used interchangeably herein.

[0053] As used herein, the term “percent sequence identity” refers to the percentage of nucleotides or nucleotide analogs in a nucleic acid sequence, or amino acids in an amino acid sequence, that is identical with the corresponding nucleotides or amino acids in a referencesequence after aligning the two sequences and introducing gaps, if necessary, to achieve the maximum percent identity. A number of mathematical algorithms for obtaining the optimal alignment and calculating identity between two or more sequences are known and incorporated into a number of available software programs. Examples of such programs include CLUSTAL-W, T-Coffee, and ALIGN (for alignment of nucleic acid and amino acid sequences), BLAST programs (e.g., BLAST 2.1, BL2SEQ, and later versions thereof) and FASTA programs (e.g., FASTA3x, FAS™, and SSEARCH) (for sequence alignment and sequence similarity searches). Sequence alignment algorithms also are disclosed in, for example, Altschul et al., J. Molecular Biol., 215(3): 403-410 (1990), Beigert et al., Proc. Natl. Acad. Sci. USA, 106(10): 3770-3775 (2009), Durbin et al., eds., Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids, Cambridge University Press, Cambridge, UK (2009), Soding, Bioinformatics, 21(7): 951-960 (2005), Altschul et al., Nucleic Acids Res., 25(17): 3389-3402 (1997), and Gusfield, Algorithms on Strings, Trees and Sequences, Cambridge University Press, Cambridge UK (1997)).

[0054] The terms “non-naturally occurring,” “engineered,” and “synthetic” are used interchangeably and indicate the involvement of the hand of man. The terms, when referring to nucleic acid molecules or polypeptides mean that the nucleic acid molecule or the polypeptide is at least substantially free from at least one other component with which they are naturally associated in nature and as found in nature.

[0055] A “subject” may be human or non-human and may include, for example, animal strains or species used as “model systems” for research purposes, such a mouse model as described herein. Likewise, subject may include either adults or juveniles (e.g., children). Moreover, subject may mean any living organism, preferably a mammal (e.g., human or non-human) that may benefit from the administration of compositions contemplated herein. Examples of mammals include, but are not limited to, any member of the Mammalian class: humans, non-human primates such as chimpanzees, and other apes and monkey species; farm animals such as cattle, horses, sheep, goats, swine; domestic animals such as rabbits, dogs, and cats; laboratory animals including rodents, such as rats, mice and guinea pigs, and the like. Examples of nonmammals include, but are not limited to, birds, fish, and the like. In one embodiment of the methods and compositions provided herein, the mammal is a human.As used herein, the terms “providing,” “administering,” “introducing,” are used interchangeably herein and refer to the placement into a subject by a method or route which results in at least partial localization to a desired site. The administered can be by any appropriate route which results in delivery to a desired location.

[0056] Preferred methods and materials are described below, although methods and materials similar or equivalent to those described herein can be used in practice or testing of the present disclosure. All publications, patent applications, patents and other references mentioned herein are incorporated by reference in their entirety. The materials, methods, and examples disclosed herein are illustrative only and not intended to be limiting.

[0057] 2. RNA regulatory proteins

[0058] The present disclosure provides synthetic RNA regulatory proteins comprising one or more RNA regulatory domains fused to a heterologous nucleic acid binding domain.

[0059] In some embodiments, at least one of the one or more RNA regulatory domains comprises an amino acid sequence having at least 70% (e.g., at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 98%, at least 99%) identity to any of SEQ ID NOs: 1-119, or a fragment thereof. In some embodiments, at least one of the one or more RNA regulatory domains comprises an amino acid sequence having at least 90% identity to any of SEQ ID NOs: 1-119, or a fragment thereof. In some embodiments, at least one of the one or more RNA regulatory domains comprises an amino acid sequence of any of SEQ ID NOs: 1-119, or a fragment thereof.

[0060] In some embodiments, at least one of the one or more RNA regulatory domains comprises at least 10 contiguous amino acids of any of SEQ ID NOs: 1-119. In some embodiments, at least one of the one or more RNA regulatory domains comprises an amino acid sequence of any of SEQ ID NOs: 239-312.

[0061] In some embodiments, at least one of the one or more RNA regulatory domains comprises an amino acid sequence having at least 70% (e.g., at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 98%, at least 99%) identity to any of SEQ ID NOs: 120-238. In some embodiments, at least one of the one or more RNA regulatory domains comprises an amino acid sequence having at least 90% identity to any of SEQ ID NOs: 120-238. In some embodiments, at least one of the one or more RNA regulatory domains comprises an amino acid sequence of any of SEQ ID NOs: 120-238.In some embodiments, each of the one or more RNA regulatory domains comprises an amino acid sequence having at least 70% (e.g., at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 98%, at least 99%) identity to any of SEQ ID NOs: 1-119, or a fragment thereof. In some embodiments, each of the one or more RNA regulatory domains comprises an amino acid sequence of any of SEQ ID NOs: 239-312. In some embodiments, each of the one or more RNA regulatory domains comprises an amino acid sequence having at least 70% (e.g., at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 98%, at least 99%) identity to any of SEQ ID NOs: 120-238. In some embodiments, each of the one or more RNA regulatory domains comprises an amino acid sequence of any of SEQ ID NOs: 1-312.

[0062] In some embodiments, the one or more RNA regulatory domains are identified by the methods disclosed herein.

[0063] In some embodiments, the synthetic RNA regulatory proteins comprise two or more RNA regulatory domains fused to a heterologous nucleic acid binding domain. The two or more RNA regulatory domains can be fused to the nucleic acid binding domain in any orientation, and may be separated from each other with an amino acid linker.

[0064] In some embodiments, each of the two or more RNA regulatory domains comprises an amino acid sequence having at least 70% (e.g., at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 98%, at least 99%) identity to any of SEQ ID NOs: 1-310. In some embodiments, each of the two or more RNA regulatory domains comprises an amino acid sequence of any of SEQ ID NOs: 1-310. In some embodiments, at least one of the two or more RNA regulatory domains comprises an amino acid sequence having at least 70% (e.g., at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 98%, at least 99%) identity to any of SEQ ID NOs: 1-310. In some embodiments, at least one of the two or more RNA regulatory domains comprises an amino acid sequence of any of SEQ ID NOs: 1-310.

[0065] In some embodiments, each of the one or more RNA regulatory domains comprises at least 10 contiguous amino acids of any of SEQ ID NOs: 1-118.

[0066] The nucleic acid binding domain may be an RNA binding domain or a DNA binding domain.The RNA binding domain is any polypeptide which is capable of binding double- and / or single-stranded RNA, generally or with sequence specificity. The heterologous RNA binding domains may be a natural binding domain. In some embodiments, the heterologous RNA binding domain comprises a programmable RNA binding domain, e.g., an RNA binding domain engineered, for example by altering one or more amino acid of a natural RNA binding domain to bind to a predetermined nucleotide sequence.

[0067] In some embodiments, the RNA binding domain is capable of binding directly to the target RNA sequence. Exemplary RNA binding domains include MS2 (also known as MS2 coat protein), Qbeta (also known as Qbeta coat protein), or PP7 (also known as PP7 coat protein).

[0068] In some embodiments, the RNA binding domain associates with the target RNA in concert with an exogenous factor. In some embodiments, the RNA binding domain is an RNA-programmable RNA binding domain. The term “RNA-programmable RNA binding domain” refers to a polypeptide that forms a complex with (e.g., binds or associates with) one or more protein-associating guide RNA molecules which guide the binding protein to target

[0069] an RNA molecule (e.g., a mRNA, rRNA, or tRNA molecule) having a sequence that is complementary to the one or more protein-associating guide RNA molecules. This concept embraces CRISPR / Cas proteins that have been modified or adapted to target RNA instead of DNA (e.g., spCas9 system), as well as native or naturally occurring RNA-targeting CRISPR / Cas protein (e.g., Casl3, including Casl3a, Casl3b, Casl3c, and Casl3d), and any homologs and derivatives thereof (e.g., nuclease-deficient variants) isolated or obtained from any organism or species.

[0070] The DNA binding domain includes any polypeptide which is capable of binding double-or single-stranded DNA, generally or with sequence specificity. DNA binding domains include those polypeptides having helix-tum-helix motifs, zinc fingers, leucine zippers, HMG-box (high mobility group box) domains, winged helix region, winged helix-tum-helix region, helix-loop-helix region, immunoglobulin fold, B3 domain, Wor3 domain, TAL effector DNA-binding domain and the like. The heterologous DNA binding domains may be a natural binding domain. In some embodiments, the heterologous DNA binding domain comprises a programmable DNA binding domain, e.g., a DNA binding domain engineered, for example by altering one or more amino acid of a natural DNA binding domain to bind to a predetermined nucleotide sequence.In some embodiments, the DNA binding domain is capable of binding directly to the target DNA sequences. The DNA-binding domain may be derived from domains found in naturally occurring Transcription activator-like effectors (TALEs), such as AvrBs3, Hax2, Hax3 or Hax4 (Bonas et al. 1989. Mol Gen Genet 218(1): 127-36; Kay et al. 2005 Mol Plant Microbe Interact 18(8): 838-48). TALEs have a modular DNA-binding domain consisting of repetitive sequences of residues; each repeat region consists of 34 amino acids. A pair of residues at the 12th and 13th position of each repeat region determines the nucleotide specificity and combining of the regions allows synthesis of sequence-specific TALE DNA-binding domains. In some embodiments, the TALE DNA binding domains may be engineered using known methods to provide a DNA binding domain with chosen specificity for any target sequence. The DNA binding domain may comprise multiple (e.g., 2, 3, 4, 5, 6, 10, 20, or more) Tai effector DNA-binding motifs. In particular, any number of nucleotide-specific Tai effector motifs can be combined to form a sequence-specific DNA-binding domain to be employed in the present transcription factor.

[0071] In some embodiments, the DNA binding domain associates with the target DNA in concert with an exogenous factor.

[0072] In some embodiments, the DNA binding domain is derived from a Clustered Regularly Interspaced Short Palindromic Repeats associated (Cas) protein (e.g., catalytically dead Cas9) and associates with the target DNA through a guide RNA. The gRNA itself comprises a sequence complementary to one strand of the DNA target sequence and a scaffold sequence which binds and recruits Cas9 to the target DNA sequence.

[0073] In the case of the CRISPR / Cas protein DNA or RNA binding domains described above, the guide RNA (gRNA) may be a crRNA, crRNA / tracrRNA (or single guide RNA, sgRNA). The gRNA may be a non-naturally occurring gRNA. The terms “gRNA,” “guide RNA” and “guide sequence” may be used interchangeably throughout and refer to a nucleic acid comprising a sequence that determines the binding specificity of the Cas protein. A gRNA hybridizes to (complementary to, partially or completely) the target sequence.

[0074] The gRNA or portion thereof that hybridizes to the target nucleic acid (a target site) may be any length necessary for selective hybridization. gRNAs or sgRNA(s) can be between about 5 and about 100 nucleotides long, or longer (e.g., 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45,46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 5960, 61, 62, 63, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91 92, 93, 94, 95, 96, 97, 98, 99, or 100 nucleotides in length, or longer).

[0075] To facilitate gRNA design, many computational tools have been developed (See Prykhozhij et al. (PLoS ONE, 10(3): (2015)); Zhu et al. (PLoS ONE, 9(9) (2014)); Xiao et al. (Bioinformatics. Jan 21 (2014)); Heigwer et al. (Nat Methods, 11(2): 122-123 (2014)). Methods and tools for guide RNA design are discussed by Zhu (Frontiers in Biology, 10 (4) pp 289-296 (2015)), which is incorporated by reference herein. Additionally, there are many publicly available software tools that can be used to facilitate the design of sgRNA(s); including but not limited to, Genscript Interactive CRISPR gRNA Design Tool, WU-CRISPR, and Broad Institute GPP sgRNA Designer. There are also publicly available pre-designed gRNA sequences to target many genes and locations within the genomes of many species (human, mouse, rat, zebrafish, C. elegans), including but not limited to, IDT DNA Predesigned Alt-R CRISPR-Cas9 guide RNAs, Addgene Validated gRNA Target Sequences, and GenScript Genome-wide gRNA databases.

[0076] The one or more RNA regulatory domains and the heterologous nucleic acid binding domain may be fused in any orientation. In some embodiments, the one or more RNA regulatory domains are N-terminal to the heterologous nucleic acid binding domain. In some embodiments, the one or more RNA regulatory domains are C-terminal to the heterologous nucleic acid binding domain. For example, in some embodiments, the N-terminus of the one or more RNA regulatory domains are fused to the C-terminus of the heterologous nucleic acid binding domain. In some embodiments, the C-terminus of the one or more RNA regulatory domains are fused to the N-terminus of the heterologous nucleic acid binding domain. In some embodiments, the N-terminus of the one or more RNA regulatory domains are fused to the N-terminus of the heterologous nucleic acid binding domain. In some embodiments, the C-terminus of the one or more RNA regulatory domains are fused to the C-terminus of the heterologous nucleic acid binding domain.

[0077] The one or more RNA regulatory domains and the heterologous nucleic acid binding domain may be fused via a linker polypeptide. The linker polypeptide may have any of a variety of amino acid sequences. Proteins can be joined by a spacer peptide, generally of a flexible nature, although other chemical linkages are not excluded. Suitable linkers include polypeptides of between 4 amino acids and 100 amino acids in length. These linkers can be produced by using synthetic, linker-encoding oligonucleotides to couple the one or more RNA regulatory domainsand the heterologous nucleic acid binding domain, or can be encoded by a nucleic acid sequence encoding the synthetic RNA regulatory protein.

[0078] In some embodiments, the linker peptides are flexible linkers. The linking peptides may have virtually any amino acid sequence, with preferred linkers having a sequence that results in a generally flexible peptide. A variety of different linkers are suitable for use, including but not limited to, glycine-serine polymers, glycine-alanine polymers, and alanine-serine polymers. In some embodiments, the linker comprises at least one glycine and at least one serine. In some embodiments, the linker comprises an amino acid sequence consisting of (Gly2Ser)n, where n is the number of repeats comprising an integer from 2-20.

[0079] In some embodiments, the synthetic RNA regulatory protein further comprises at least one additional nucleic acid (e.g., DNA or RNA) effector domain known in the art. A nucleic acid effector domain is any domain that can be detected (e.g., imaged) and / or that acts on a target nucleic acid. The nucleic acid effector domain may also refer to a protein or enzyme capable of making one or more modifications (e.g., deamination, methylation, demethylation, acetylation) to the nucleic acid (e.g., DNA or RNA). Exemplary nucleic acid effector domains include, but are not limited to a deaminase, a nuclease, a nickase, a recombinase, a methyltransferase, a methylase, an acetylase, an acetyltransferase, a transcriptional activator, or a transcriptional repressor domain.

[0080] In some embodiments, the synthetic RNA regulatory protein further comprises at least one additional RNA effector domain known in the art. Non-limiting examples of RNA effector domains include transcriptional regulatory functions (e.g., splicing, expression), post-transcriptional modification functions (e.g., methylation, demethylation), and other RNA processing functions (e.g., targeting, such as for degradation). Exemplary RNA effector domains include: RNA splicing factors, such as RBFOX1, U2 small nuclear RNA auxiliary factor 1 (U2AF35), U2AF2 (U2AF65), splicing factor 1 (SF1), U1 small nuclear ribonucleoprotein (snRNP), U2 snRNP, U4 snRNP, U5 snRNP, U6 snRNP, Ull, U12, U4atac, and U6atac; methylation or demethylation domains, such as from METTL3, METTL14, WTAP, VIRMA, ZC3H13, RBM15, RBM15B, HAKAI, METTL16, METTL5, FTO, and ALKBH5, RNA degradation domains; or an RNA processing domain (e.g., domains which carry out mRNA 5' capping, mRNA 3' polyadenylation, and / or histone mRNA processing).In some embodiments, the synthetic RNA regulatory protein further comprises a localization or signal sequence (e.g., nuclear localization sequence), a sequence tag (e.g., a tag for detection, purification, and / or monitoring expression), a protein transduction domain sequence, or a combination thereof.

[0081] In some embodiments, the synthetic RNA regulatory protein comprises one or more nuclear localization sequences (NLSs). The nuclear localization sequence may be appended, for example, to the N-terminus, a C-terminus, internally, or a combination thereof. In such cases when the engineered nuclease comprises two or more NLSs, the NLSs may be in tandem, separated by a linker, at either end of the protein, or one or more may be embedded in the protein.

[0082] The nuclear localization sequence may comprise any amino acid sequence known in the art to functionally tag or direct a protein for import into a cell’s nucleus (e.g., for nuclear transport). Usually, a nuclear localization sequence comprises one or more positively charged amino acids, such as lysine and arginine. The NLS may be appended by a linker. The linker may be a polypeptide of any amino acid sequence and length.

[0083] In some embodiments, the NLS is a monopartite sequence. A monopartite NLS comprises a single cluster of positively charged or basic amino acids. Exemplary monopartite NLS sequences include those from the SV40 large T-antigen, c-Myc, and TUS-proteins. In some embodiments, the NLS is a bipartite sequence. Bipartite NLSs comprise two clusters of basic amino acids, separated by a spacer of about 9-12 amino acids. Exemplary bipartite NLSs include the nuclear localization sequences of nucleoplasmin, EGL-12, or bipartite SV40.

[0084] The synthetic RNA regulatory protein may also comprise a tag (e.g., 3xFLAG tag, an HA tag, a Myc tag, a poly-histidine tag, a SNAP-tag, a CLIP-tag, and the like). The tags may be at the N-terminus, a C-terminus, or a combination thereof of the engineered nuclease. In some embodiments, the tag may be adjacent, either upstream or downstream, to a nuclear localization sequence.

[0085] The synthetic RNA regulatory protein may comprise another protein or protein domain. For example, the synthetic RNA regulatory protein may be fused to another protein or protein domain that provides for tagging or visualization (e.g., GFP).

[0086] In some embodiments, the synthetic RNA regulatory protein may be fused with one or more (e.g., two, three, four, or more) protein transduction domains or PTDs, also known as aCPP - cell penetrating peptide. A protein transduction domain is a polypeptide, polynucleotide, carbohydrate, or organic or inorganic compound that facilitates traversing a lipid bilayer, micelle, cell membrane, organelle membrane, or vesicle membrane. A PTD attached to another molecule, facilitates the molecule traversing a membrane, for example going from extracellular space to intracellular space, or cytosol to within an organelle. In some embodiments, a PTD is covalently linked to a terminus of the RNA regulatory protein (e.g., N-terminus, C-terminus, or both). In some embodiments, the PTD is inserted internally at a suitable insertion site. Examples of PTDs include but are not limited to a minimal undecapeptide protein transduction domain (corresponding to residues 47-57 of HIV-1 TAT comprising); a polyarginine sequence comprising a number of arginines sufficient to direct entry into a cell (e.g., 3, 4, 5, 6, 7, 8, 9, 10, or 10-50 arginines); a VP22 domain (Zender et al. (2002) Cancer Gene Ther. 9(6):489-96); a Drosophila Antennapedia protein transduction domain (Noguchi et al. (2003) Diabetes 52(7): 1732- 1737); a truncated human calcitonin peptide (Trehin et al. (2004) Pharm. Research 21:1248-1256); polylysine (Wender et al. (2000) Proc. Natl. Acad. Sci. USA 97:13003-13008); Transportan, and the like.

[0087] The present disclosure also provides nucleic acids encoding a synthetic RNA regulatory protein or a regulatory domain, as disclosed herein. In some embodiments, the nucleic acid encodes one or more synthetic RNA regulatory proteins or one or more regulatory domains. Nucleic acids of the present disclosure can comprise any of a number of promoters known to the art, wherein the promoter is constitutive, regulatable or inducible, cell type specific, tissuespecific, or species specific. In addition to the sequence sufficient to direct transcription, a promoter sequence of the invention can also include sequences of other regulatory elements that are involved in modulating transcription (e.g., enhancers, Kozak sequences and introns). Many promoter / regulatory sequences useful for driving constitutive expression of a gene are available in the art and include, but are not limited to, for example, CMV (cytomegalovirus promoter), EFla (human elongation factor 1 alpha promoter), SV40 (simian vacuolating virus 40 promoter), PGK (mammatian phosphoglycerate kinase promoter), Ubc (human ubiquitin C promoter), human beta-actin promoter, rodent beta-actin promoter, CBh (chicken beta-actin promoter), CAG (hybrid promoter contains CMV enhancer, chicken beta actin promoter, and rabbit betaglobin splice acceptor), TRE (Tetracycline response element promoter), H1 (human polymerase III RNA promoter), U6 (human U6 small nuclear promoter), and the tike. Additional promotersthat can be used for expression of the components of the present system, include, without limitation, cytomegalovirus (CMV) intermediate early promoter, a viral LTR such as the Rous sarcoma virus LTR, HIV-LTR, HTLV-1 LTR, Maloney murine leukemia virus (MMLV) LTR, myeoloproliferative sarcoma virus (MPSV) LTR, spleen focus-forming virus (SFFV) LTR, the simian virus 40 (SV40) early promoter, herpes simplex tk virus promoter, elongation factor 1-alpha (EF1-α) promoter with or without the EF1-α intron. Additional promoters include any constitutively active promoter. Alternatively, any regulatable promoter may be used, such that its expression can be modulated within a cell.

[0088] Moreover, inducible expression can be accomplished by placing the nucleic acid encoding such a molecule under the control of an inducible promoter / regulatory sequence.

[0089] Promoters that are well known in the art can be induced in response to inducing agents such as metals, glucocorticoids, tetracycline, hormones, and the like, are also contemplated for use with the invention. Thus, it will be appreciated that the present disclosure includes the use of any promoter / regulatory sequence known in the art that is capable of driving expression of the desired protein operably linked thereto.

[0090] The present disclosure also provides for vectors containing the nucleic acids and cells containing the nucleic acids or vectors, thereof. The vectors may be used to propagate the nucleic acid in an appropriate cell and / or to allow expression from the nucleic acid (e.g., an expression vector). The person of ordinary skill in the art would be aware of the various vectors available for propagation and expression of a nucleic acid sequence.

[0091] To construct cells that express the present RNA regulatory proteins, expression vectors for stable or transient expression of the present system may be constructed via conventional methods and introduced into cells. For example, nucleic acids encoding the disclosed RNA regulatory proteins, or other nucleic acids or proteins, may be cloned into a suitable expression vector, such as a plasmid or a viral vector in operable linkage to a suitable promoter. The selection of expression vectors / plasmids / viral vectors should be suitable for integration and replication in eukaryotic cells.

[0092] In certain embodiments, vectors of the present disclosure can drive the expression of one or more sequences in mammalian cells using a mammalian expression vector. Examples of mammalian expression vectors include pCDM8 (Seed, Nature (1987) 329:840, incorporated herein by reference) and pMT2PC (Kaufman, et al., EMBO J. (1987) 6:187, incorporated hereinby reference). When used in mammalian cells, the expression vector's control functions are typically provided by one or more regulatory elements. For example, commonly used promoters are derived from polyoma, adenovirus 2, cytomegalovirus, simian virus 40, and others disclosed herein and known in the art. For other suitable expression systems for both prokaryotic and eukaryotic cells see, e.g., Chapters 16 and 17 of Sambrook, et al., MOLECULAR CLONING: A LABORATORY MANUAL. 2nd eds., Cold Spring Harbor Laboratory, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N. Y., 1989, incorporated herein by reference.

[0093] The vectors of the present disclosure may direct the expression of the nucleic acid in a particular cell type (e.g., tissue-specific regulatory elements are used to express the nucleic acid). Such regulatory elements include promoters that may be tissue specific or cell specific. The term “tissue specific” as it applies to a promoter refers to a promoter that is capable of directing selective expression of a nucleotide sequence of interest to a specific type of tissue (e.g., seeds) in the relative absence of expression of the same nucleotide sequence of interest in a different type of tissue. The term “cell type specific” as applied to a promoter refers to a promoter that is capable of directing selective expression of a nucleotide sequence of interest in a specific type of cell in the relative absence of expression of the same nucleotide sequence of interest in a different type of cell within the same tissue. The term “cell type specific” when applied to a promoter also means a promoter capable of promoting selective expression of a nucleotide sequence of interest in a region within a single tissue. Cell type specificity of a promoter may be assessed using methods well known in the art, e.g., immunohistochemical staining.

[0094] Additionally, the vector may contain, for example, some or all of the following: a selectable marker gene for selection of stable or transient transfectants in host cells; transcription termination and RNA processing signals; 5’-and 3 ’-untranslated regions; internal ribosome binding sites (IRESes), versatile multiple cloning sites; and reporter gene for assessing expression of the chimeric receptor. Suitable vectors and methods for producing vectors containing transgenes are well known and available in the art. Selectable markers include chloramphenicol resistance, tetracycline resistance, spectinomycin resistance, neomycin, streptomycin resistance, erythromycin resistance, rifampicin resistance, bleomycin resistance, thermally adapted kanamycin resistance, gentamycin resistance, hygromycin resistance, trimethoprim resistance, dihydrofolate reductase (DHFR), GPT; the URA3, HIS4, LEU2, and TRP1 genes of S. cerevisiae.When introduced into a cell, the vectors may be maintained as an autonomously replicating sequence or extrachromosomal element or may be integrated into host DNA.

[0095] Thus, the disclosure further provides for cells comprising at least one synthetic RNA regulatory protein, a nucleic acid, or a vector, as disclosed herein.

[0096] Conventional viral and non- viral based gene transfer methods can be used to introduce the nucleic acids into cells, tissues, or a subject. Such methods can be used to administer the nucleic acids to cells in culture, or in a host organism. Non-viral vector delivery systems include DNA plasmids, cosmids, RNA (e.g., a transcript of a vector described herein), a nucleic acid, and a nucleic acid complexed with a delivery vehicle.

[0097] Viral vector delivery systems include DNA and RNA viruses, which have either episomal or integrated genomes after delivery to the cell. A variety of viral constructs may be used to deliver the present nucleic acids to the cells, tissues, and / or a subject. Viral vectors include, for example, retroviral, lentiviral, adenoviral, adeno-associated and herpes simplex viral vectors. Nonlimiting examples of such recombinant viruses include recombinant adeno-associated virus (AAV), recombinant adenoviruses, recombinant lentiviruses, recombinant retroviruses, recombinant herpes simplex viruses, recombinant poxviruses, phages, etc. The present disclosure provides vectors capable of integration in the host genome, such as retrovirus or lentivirus. See, e.g., Ausubel et al., Current Protocols in Molecular Biology, John Wiley & Sons, New York, 1989; Kay, M. A., et al., 2001 Nat. Medic. 7(l):33-40; and Walther W. and Stein U., 2000 Drugs, 60(2): 249-71, incorporated herein by reference.

[0098] The nucleic acids or synthetic RNA regulatory proteins may be delivered by any suitable means. In certain embodiments, the nucleic acids or proteins thereof are delivered in vivo. In other embodiments, the nucleic acids or proteins thereof are delivered to isolated / cultured cells in vitro or ex vivo to provide modified cells useful for in vivo delivery to patients afflicted with a disease or condition.

[0099] Vectors according to the present disclosure can be transformed, transfected, or otherwise introduced into a wide variety of host cells. Transfection refers to the taking up of a vector by a cell whether or not any coding sequences are in fact expressed. Numerous methods of transfection are known to the ordinarily skilled artisan, for example, lipofectamine, calcium phosphate co-precipitation, electroporation, DEAE-dextran treatment, microinjection, viral infection, and other methods known in the art. Transduction refers to entry of a virus into the celland expression (e.g., transcription and / or translation) of sequences delivered by the viral vector genome. In the case of a recombinant vector, “transduction” generally refers to entry of the recombinant viral vector into the cell and expression of a nucleic acid of interest delivered by the vector genome.

[0100] Methods of delivering vectors to cells are well known in the art and may include DNA or RNA electroporation, transfection reagents such as liposomes or nanoparticles to delivery DNA or RNA; delivery of DNA, RNA, or protein by mechanical deformation (see, e.g., Sharei et al. Proc. Natl. Acad. Sci. USA (2013) 110(6): 2082-2087, incorporated herein by reference); or viral transduction. In some embodiments, the vectors are delivered to host cells by viral transduction. Nucleic acids can be delivered as part of a larger construct, such as a plasmid or viral vector, or directly, e.g., by electroporation, lipid vesicles, viral transporters, microinjection, and biolistics (high-speed particle bombardment). Similarly, the construct containing the one or more transgenes can be delivered by any method appropriate for introducing nucleic acids into a cell. In some embodiments, the construct or the nucleic acid encoding the components of the present system is a DNA molecule. In some embodiments, the nucleic acid encoding the components of the present system is a DNA vector and may be electroporated to cells. In some embodiments, the nucleic acid encoding the components of the present system is an RNA molecule, which may be electroporated to cells.

[0101] Additionally, delivery vehicles such as nanoparticle- and lipid-based delivery systems can be used. Further examples of delivery vehicles include lentiviral vectors, ribonucleoprotein (RNP) complexes, lipid-based delivery system, gene gun, hydrodynamic, electroporation or nucleofection microinjection, and biolistics. Various gene delivery methods are discussed in detail by Nayerossadat et al. (Adv Biomed Res. 2012; 1: 27) and Ibraheem et al. (Int J Pharm. 2014 Jan l;459(l-2):70-83), incorporated herein by reference.

[0102] As such, the disclosure provides an isolated cell comprising the vector(s) or nucleic acid(s) disclosed herein. Preferred cells are those that can be easily and reliably grown, have reasonably fast growth rates, have well characterized expression systems, and can be transformed or transfected easily and efficiently. Examples of suitable prokaryotic cells include, but are not limited to, cells from the genera Bacillus (such as Bacillus subtilis and Bacillus brevis), Escherichia (such as E. coli), Pseudomonas, Streptomyces, Salmonella, and Envinia. Suitable eukaryotic cells are known in the art and include, for example, yeast cells, insect cells, andmammalian cells. Examples of suitable yeast cells include those from the genera Kluyveromyces, Pichia, Rhino-sporidium, Saccharomyces, and Schizosaccharomyces. Exemplary insect cells include Sf-9 and HIS (Invitrogen, Carlsbad, Calif.) and are described in, for example, Kitts et al., Biotechniques, 14: 810-817 (1993); Lucklow, Curr. Opin. Biotechnol., 4: 564-572 (1993); and Lucklow et al., J. Virol., 67: 4566-4579 (1993), incorporated herein by reference. Desirably, the cell is a mammalian cell, and in some embodiments, the cell is a human cell. A number of suitable mammalian and human host cells are known in the art, and many are available from the American Type Culture Collection (ATCC, Manassas, Va.). Examples of suitable mammalian cells include, but are not limited to, Chinese hamster ovary cells (CHO) (ATCC No. CCL61), CHO DHFR-cells (Urlaub et al., Proc. Natl. Acad. Sci. USA, 97: 4216-4220 (1980)), human embryonic kidney (HEK) 293 or 293T cells (ATCC No. CRL1573), and 3T3 cells (ATCC No. CCL92). Other suitable mammalian cell lines are the monkey COS-1 (ATCC No. CRL1650) and COS-7 cell lines (ATCC No. CRL1651), as well as the CV-1 cell line (ATCC No. CCL70). Further exemplary mammalian host cells include primate, rodent, and human cell lines, including transformed cell lines. Normal diploid cells, cell strains derived from in vitro culture of primary tissue, as well as primary explants, are also suitable. Other suitable mammalian cell lines include, but are not limited to, mouse neuroblastoma N2A cells, HeLa, HEK, A549, HepG2, mouse L-929 cells, and BHK or HaK hamster cell lines.

[0103] Methods for selecting suitable mammalian cells and methods for transformation, culture, amplification, screening, and purification of cells are known in the art.

[0104] The present invention is also directed to compositions or systems comprising a synthetic RNA regulatory protein, a nucleic acid, a vector, or a cell, as described herein. In some embodiments, the compositions or systems comprise two or more synthetic RNA regulatory proteins, nucleic acids, vectors, or cells.

[0105] In some embodiments, the composition or system further comprises a gRNA. The gRNA may be encoded on the same nucleic acid as a synthetic RNA regulatory protein or a different nucleic acid. In some embodiments, the vector encoding a synthetic RNA regulatory protein may further encode a gRNA, under the same or different promoter. In some embodiments, the gRNA is encoded on its own vector, separated from that of the RNA regulatory protein.

[0106] 3. Method for identifying RNA regulatory domains

[0107] Disclosed herein are methods for identifying RNA regulatory domains.In some embodiments, the methods comprise: preparing a domain library comprising a plurality of nucleic acid sequences each configured to express a fusion protein comprising a protein domain linked to a nucleic acid (e.g., RNA or DNA) binding domain; transforming reporter cells with the domain library, wherein the reporter cells comprises a polynucleotide having two-part reporter gene comprising a surface marker and a fluorescent protein with a nucleic acid (e.g., RNA or DNA) binding domain target sequence in the 3’ or 5’ untranslated region; separating reporter cells based on level of expression of surface marker and / or the fluorescent protein; sequencing the protein domains from the separated reporter cells; and identifying protein domains as RNA regulatory domains when the level of expression of surface marker and / or the fluorescent protein is decreased as compared to a cell not comprising the fusion protein.

[0108] The methods comprise transforming reporter cells with the domain library, wherein the reporter cells comprises a polynucleotide having two-part reporter gene comprising a surface marker and a fluorescent protein with an RNA binding domain target sequence in the 3’ or 5’ untranslated region, wherein the two-part reporter gene is capable of being modulated by a putative RNA regulatory domain. For example, the mRNA of the two-part reporter gene is capable of being recognized by the RNA binding domain and regulated by the putative regulatory domain. Measurement of the mRNA of the reporter gene facilitates determination if the putative regulatory domain is increasing RNA degradation or inhibiting translation. Thus, in some embodiments, the methods comprise measuring the two-part reporter gene mRNA levels.

[0109] In some embodiments, the methods comprise: preparing a domain library comprising a plurality of nucleic acid sequences each configured to express a fusion protein comprising a protein domain linked to an inducible nucleic acid (e.g., RNA or DNA) binding domain; transforming reporter cells with the domain library, wherein the reporter cells comprises a two-part reporter gene comprising a surface marker and a fluorescent protein under the control of a promoter, wherein the two-part reporter gene is capable of being modulated by a RNA regulatory domain following treatment with an agent configured to induce the inducible nucleic acid (e.g., RNA or DNA)binding domain; treating the reporter cells with the agent for a length of time necessary for mRNA levels to be altered in the cell; sequencing the protein domains from the separated reporter cells; and identifying protein domains as RNA regulatory domains.The inducible nucleic acid (e.g., RNA or DNA) binding domain may use any system for induction of binding, including, but not limited to, tetracycline Tet / DOX inducible systems, light inducible systems, Abscisic acid (ABA) inducible systems, cumate systems, 40HT / estrogen inducible systems, ecdysone-based inducible systems, and FKBP12 / FRAP (FKBP12-rapamycin complex) inducible systems. In some embodiments, the inducible nucleic acid (e.g., RNA or DNA) binding domain is an inducible recruitment system.

[0110] The promoter may confer a high rate of transcription (a strong promoter) or confer a low rate of transcription (weak promoter). Many promoter libraries have been established experimentally and choice of promoter and promoter strength is dependent on cell type. In some embodiments, a strong promoter may be used.

[0111] In some embodiments, the reporter cells are treated with the agent for at least 24 hours. For example, the reporter cells may be treated with the agent for at least 24 hours (1 day), at least 36 hours, at least 48 hours (2 days), at least 3 days, at least 4 days, at least 5 days, at least 6 days, at least 7 days, at least 8 days, at least 9 days, at least 10 days, at least 14 days, or more. In some embodiments, the reporter cells at treated with the agent for 3-12 days, 3-10 days, 3-7 days, or 3-5 days.

[0112] The methods comprise preparing a domain library comprising a plurality of nucleic acid sequences each configured to express a fusion protein comprising a protein domain linked to a nucleic acid (e.g., RNA or DNA) binding domain. The protein domain may be less than or equal to 80 amino acids. In some embodiments, the protein domain may be about 75 amino acids, about 70 amino acids, about 65 amino acids, about 60 amino acids, about 55 amino acids, about 50 amino acids, about 45 amino acids, about 40 amino acids, about 35 amino acids, about 30 amino acids, about 25 amino acids, about 20 amino acids, about 15 amino acids, about 10 amino acids, or about 5 amino acids.

[0113] The protein domain may be derived from any known protein. In some embodiments, the known protein is an RNA binding protein. In some embodiments, the protein domain comprises a mutated amino acid sequence of a protein domain from a known protein (e.g., an RNA binding protein).

[0114] Cell surface markers include proteins and carbohydrates which are attached to the cellular membrane. Cell surface markers are generally known in the art for a variety of cell types and can be expressed in a reporter cell of choice based on known molecular biology methods. Thesurface marker may be a synthetic surface marker comprising marker polypeptide attached to a transmembrane domain. For example, the marker polypeptide may include an antibody or a fragment thereof (e.g., Fc region) attached to a transmembrane domain. In some embodiments, the marker polypeptide is human IgGl Fc region, and the synthetic surface marker comprises human IgGl Fc region attached to a transmembrane domain.

[0115] Fluorescent proteins are well known in the art and include proteins adapted to fluoresce in various cellular compartments and as a result of varying wavelengths of incoming light.

[0116] Examples of fluorescent proteins include phycobiliproteins, cyan fluorescent protein (CFP), green fluorescent protein (GFP), yellow fluorescent protein (YFP), enhanced

[0117] orange fluorescent protein (OFP), enhanced green fluorescent protein (eGFP), modified green fluorescent protein (emGFP), enhanced yellow fluorescent protein (eYFP) and / or monomeric red fluorescent protein (mRFP) and derivatives and variants thereof.

[0118] The methods comprise separating reporter cells based on presence or absence of the surface marker, the fluorescent protein, or a combination thereof. A number of cell separation techniques are known in the art are suitable for use with the methods disclosed herein, including, for example, immunomagnetic cell separation, fluorescent-activated cell sorting (FACS), and microfluidic cell sorting. In some embodiments, cell separation comprises immunomagnetic cell separation.

[0119] In some embodiments, the methods further comprise repeating the separating, sequencing, calculating, and identifying steps one or more times.

[0120] In some embodiments, the methods further comprise measuring expression level of protein domains. The expression level of the protein domains can be determined using any methods known in the art, including immunoblotting and immunoassays for the protein itself or any tags or labels thereof. In some embodiments, the expression level is determined by measuring a relative presence or absence of the tag on the binding domain.

[0121] 4. Methods of modulating RNA levels

[0122] The present disclosure also provides methods of modulating RNA levels. In some embodiments, the methods comprise contacting a target nucleic acid encoding the target RNA or the target RNA with at least one synthetic RNA regulatory protein as described herein. The present disclosure also provides methods of modulating the level of one or more target RNAs and / or expression of one or more target genes in a cell. In some embodiments, the methodscomprise introducing into the cell at least one synthetic RNA regulatory protein, nucleic acid, vector, or composition or system as described herein.

[0123] The target RNA may be any RNA. In some embodiments, the target RNA is messenger RNA.

[0124] In some embodiments, the methods induce RNA degradation and / or downregulate mRNA translation. In some embodiments, RNA degradation is increased by at least about 10%, at least about 20%, at least about 50%, at least about 75%, at least about 90%, or more, as compared to a method not comprising the RNA regulatory protein. In some embodiments, mRNA translation is downregulated by at least about 5%, at least about 10%, at least about 20%, at least about 30%, at least about 40%, at least about 50% or more, as compared to a method not comprising the RNA regulatory protein.

[0125] Modulation of expression may result in modulating gene expression compared to normal gene expression for the target gene. When the gene expression of at least two genes is modulated, both genes may be modulated in a similar manner (e.g., both genes may have decreased gene expression) to a similar to different degree (e.g., different values relative to control expression levels), or one gene may have increased gene expression and the other may have decreased gene expression.

[0126] In some embodiments, the methods result in decreased gene expression compared to normal gene expression for the target gene. In some embodiments, expression of the gene is reduced by at least about 10% (e.g., 90% of control expression), at least about 20% (e.g., 80% of control expression), at least about 50% (e.g., 50% of control expression), at least about 75 % (e.g., 25% of control expression), at least about 90 % (e.g., 10% of control expression). In some embodiments, expression of the gene is decreased to an undetectable level (e.g., 0% of control expression).

[0127] The synthetic RNA regulatory protein(s) and, accordingly, the methods of the present disclosure, may modulate target nucleic acids due to being associated with or bound to the target nucleic acid (e.g., mRNA). Alternatively, the synthetic RNA regulatory protein(s) and, accordingly, the methods of the present disclosure, may edit the target nucleic acid (e.g., RNA or DNA) to affect the RNA levels. Editing the target nucleic acid may be by any method including, but not limited to: cleaving or splicing, chemical modifications (e.g., methylation, demethylation, acetylation, etc.), targeting, or processing, such as for a target mRNA.The cell may be a prokaryotic or eukaryotic cell. In preferred embodiments, the cell is a eukaryotic cell. In some embodiments, the cell is in vitro. In some embodiments, the cell is ex vivo.

[0128] In some embodiments, the cell is in an organism or host, such that introducing the disclosed systems, compositions, vectors into the cell comprises administration to a subject. The method may comprise providing or administering to the subject, in vivo, or by transplantation of ex vivo treated cells, at least one synthetic RNA regulatory protein, nucleic acid, vector, or composition or system as described herein.

[0129] The synthetic RNA regulatory proteins, or nucleic acids encoding the synthetic RNA regulatory proteins, may be administered to a cell or subject with a pharmaceutically acceptable carrier or excipient as a pharmaceutical composition. In some embodiments, the synthetic RNA regulatory proteins, or nucleic acids encoding the synthetic RNA regulatory proteins, may be mixed, individually or in any combination, with a pharmaceutically acceptable carrier to form pharmaceutical compositions, which are also within the scope of the present disclosure.

[0130] The phrase “pharmaceutically acceptable,” refers to molecular entities and other ingredients of such compositions that are physiologically tolerable and do not typically produce untoward reactions when administered to a subject (e.g., a mammal, a human). Preferably, as used herein, the term “pharmaceutically acceptable” means approved by a regulatory agency of the Federal or a state government or listed in the U. S. Pharmacopeia or other generally recognized pharmacopeia for use in mammals, and more particularly in humans. “Acceptable” means that the carrier is compatible with the RNA regulatory proteins of the disclosure, or nucleic acids encoding the RNA regulatory proteins, and does not negatively affect the subject to which the composition(s) are administered. Any of the pharmaceutical compositions used in the present methods can comprise pharmaceutically acceptable carriers, excipients, or stabilizers in the form of lyophilized formations or aqueous solutions.

[0131] Pharmaceutically acceptable carriers, including buffers, are well known in the art, and may comprise phosphate, citrate, and other organic acids; antioxidants including ascorbic acid and methionine; preservatives; low molecular weight polypeptides; proteins, such as serum albumin, gelatin, or immunoglobulins; amino acids; hydrophobic polymers; monosaccharides; disaccharides; and other carbohydrates; metal complexes; and / or non-ionic surfactants. See, e.g.,Remington: The Science and Practice of Pharmacy 20th Ed. (2000) Lippincott Williams and Wilkins, Ed. K. E. Hoover.

[0132] The route by which the synthetic RNA regulatory proteins, or nucleic acids encoding the synthetic RNA regulatory proteins, are administered and the form of the composition will dictate the type of carrier to be used. The synthetic RNA regulatory proteins, or nucleic acids encoding the synthetic RNA regulatory proteins, may be administered systemically or topically, and therefore, the composition may be in a variety of forms, suitable, for example, for systemic administration (e.g., oral, rectal, nasal, sublingual, buccal, implants, or parenteral injections) or topical administration (e.g., dermal, pulmonary, nasal, aural, ocular, liposome delivery systems, or iontophoresis).

[0133] The methods described herein for modulating RNA levels and / or gene expression allow for therapeutic applications, e.g., treatment of genetic diseases; cancer; fungal, protozoal, bacterial, and viral infections; ischemia; vascular disease; arthritis; immunological disorders; etc., as well as providing components for functional genomics assays, and methods for developing plants with altered phenotypes, including disease resistance, fruit ripening, sugar and oil composition, yield, and color.

[0134] In some embodiments, the gene is known to be associated with a disease or disorder. In some embodiments, the methods disclosed herein alleviate a symptom associated with the disease or disorder. Thus, the methods, synthetic RNA regulatory proteins, or nucleic acids encoding the synthetic RNA regulatory proteins disclosed herein may be used for therapeutic or prophylactic purposes.

[0135] The synthetic RNA regulatory proteins, by nature of their nucleic acid binding domains, can be designed to recognize any suitable target site, for regulation of RNA levels or expression of any endogenous gene of choice. Suitable genes to be regulated include, but are not limited to: cytokines, lymphokines, growth factors, mitogenic factors, chemotactic factors, onco-active factors, receptors, potassium channels, G-proteins, signal transduction molecules, and other disease-related genes. Examples of endogenous genes suitable for regulation include, but are not limited to: VEGF, CCR5, ERa, Her2 / Neu, Tat, Rev, HBV C, S, X, and P, LDL-R, PEPCK, CYP7, Fibrinogen, ApoB, Apo E, Apo(a), renin, NF-KB, I-KB, TNF-a, FAS ligand, amyloid precursor protein, atrial naturetic factor, ob-leptin, ucp-1, IL-I, IL-2, IL-3, IL-4, IL-5, IL-6, IL-12, G-CSF, GM-CSF, Epo, PDGF, PAF, p53, Rb, fetal hemoglobin, dystrophin, eutrophin,GDNF, NGF, IGF-I, VEGF receptors fit and flk, topoisomerase, telomerase, bcl-2, cyclins, angiostatin, IGF, ICAM-I, STATS, c-myc, c-myb, TH, PTI-I, polygalacturonase, EPSP synthase, FAD2-1, delta- 12 desaturase, delta-9 desaturase, delta- 15 desaturase, acetyl-CoA carboxylase, acyl-ACP- thioesterase, ADP-glucose pyrophosphorylase, starch synthase, cellulose synthase, sucrose synthase, senescence-associated genes, heavy metal chelators, fatty acid hydroperoxide lyase, viral genes, protozoal genes, fungal genes, and bacterial genes.

[0136] In some embodiments, the RNA regulatory proteins and resulting methods target a “disease-associated” gene. The term “disease-associated gene,” refers to any gene or polynucleotide whose gene products are expressed at an abnormal level or in an abnormal form in cells obtained from a disease-affected individual as compared with tissues or cells obtained from an individual not affected by the disease. A disease-associated gene may be expressed at an abnormally high level or at an abnormally low level, where the altered expression correlates with the occurrence and / or progression of the disease. A disease-associated gene also refers to a gene, the mutation or genetic variation of which is directly responsible or is in linkage disequilibrium with a gene(s) that is responsible for the etiology of a disease. Examples of genes responsible for such “single gene” or “monogenic” diseases include, but are not limited to, adenosine deaminase, a-1 antitrypsin, cystic fibrosis transmembrane conductance regulator (CFTR), -hemoglobin (HBB), oculocutaneous albinism II (OCA2), Huntingtin (HTT), dystrophia myotonica-protein kinase (DMPK), low-density lipoprotein receptor (LDLR), apolipoprotein B (APOB), neurofibromin 1 (NF1), polycystic kidney disease 1 (PKD1), polycystic kidney disease 2 (PKD2), coagulation factor VUI (F8), dystrophin (DMD), phosphate-regulating endopeptidase homologue, X-linked (PHEX), methyl-CpG-binding protein 2 (MECP2), and ubiquitin-specific peptidase 9Y, Y-linked (USP9Y). Other single gene or monogenic diseases are known in the art and described in, e.g., Chial, H. Rare Genetic Disorders: Learning About Genetic Disease Through Gene Mapping, SNPs, and Microarray Data, Nature Education 1(1): 192 (2008); Online Mendelian Inheritance in Man (OMIM); and the Human Gene Mutation Database (HGMD). Diseases caused by the contribution of multiple genes which lack simple (e.g., Mendelian) inheritance patterns are referred to in the art as a “multifactorial” or “polygenic” disease.

[0137] Examples of multifactorial or polygenic diseases include, but are not limited to, asthma, diabetes, epilepsy, hypertension, bipolar disorder, and schizophrenia. Certain developmental abnormalities also can be inherited in a multifactorial or polygenic pattern and include, for example, cleftHp / palate, congenital heart defects, and neural tube defects. In another embodiment, the RNA regulatory protein and resulting methods target a cancer oncogene.

[0138] The amount of the RNA regulatory proteins required for use in the disclosed methods will vary not only with the regulatory domain(s) selected but also with the route of administration, the nature and / or symptoms of the disease and the age and condition of the patient and will be ultimately at the discretion of the attendant physician or clinician. The determination of effective dosage levels, the dosage levels necessary to achieve the desired result, can be accomplished by one skilled in the art using routine methods, for example, human clinical trials, in vivo studies, and in vitro studies. For example, useful dosages can be determined by comparing their in vitro activity, and in vivo activity in animal models.

[0139] It should be noted that the attending physician would know how to and when to terminate, interrupt, or adjust administration due to toxicity or organ dysfunctions. Conversely, the attending physician would also know to adjust treatment to higher levels if the clinical response were not adequate (precluding toxicity). The magnitude of an administrated dose in the management of the disorder of interest will vary with the severity of the symptoms to be treated and the route of administration. Further, the dose, and perhaps dose frequency, will also vary according to the age, body weight, and response of the individual patient. A program comparable to that discussed above may be used in veterinary medicine.

[0140] Regulation of RNA levels or gene expression in plants with RNA regulatory proteins can be used to engineer plants for traits such as increased disease resistance, modification of structural and storage polysaccharides, flavors, proteins, and fatty acids, fruit ripening, yield, color, nutritional characteristics, improved storage capability, and the like. In particular, the engineering of crop species for enhanced oil production, e.g., the modification of the fatty acids produced in oilseeds, is of interest. Thus, the methods, synthetic RNA regulatory proteins, or nucleic acids encoding the synthetic RNA regulatory proteins disclosed herein may be used for overall gene regulation in plants and for genetic engineering in plants.

[0141] The methods can be used to control expression of proteins and protein biologies in various scientific and medical contexts, e.g., to afford simple and immediate regulation of gene expression in cell biology studies. The methods may also be suitable for use in biological circuits, for example in clinical or industrial applications including but not limited to gene therapy or industrial bioengineering.As such, the synthetic RNA regulatory proteins may be part of an engineered biological circuit. The term “engineered biological circuit” is used herein to refer to a biological circuit where the biological components are designed to perform logical functions. Generally, an input activates a synthetic biological circuit, which subsequently produces an output as a function of the input. The biological circuit may be a synthetic gene circuit, a biological circuit that comprises at least one nucleic acid and can perform a function including, but not limited to, sensing, a logic function, and a regulatory function, due to direct or indirect interactions with another nucleic acid or other biomolecule. The nucleic acid(s) in the synthetic gene circuit can be naturally occurring or synthetic. The nucleic acid(s) in the synthetic gene circuit can comprise DNA, RNA, or an artificial nucleic acid analog thereof.

[0142] 5. Kits

[0143] Also within the scope of the present disclosure are kits including at least one or all of at least one nucleic acid encoding an RNA regulatory domain, or a nucleic acid binding domain, or a combination thereof, at least one synthetic RNA regulatory protein, or nucleic acid encoding thereof, vectors encoding at least one RNA regulatory domain or at least one synthetic RNA regulatory protein, a composition or system as described herein, a cell comprising an RNA regulatory domain, or a nucleic acid binding domain, or a combination thereof, at least one synthetic RNA regulatory protein, or a nucleic acid encoding any of thereof, a reporter cell as described herein and a two-part reporter gene as described herein or a nucleic acid encoding thereof.

[0144] The kits can also comprise instructions for using the components of the kit. The instructions are relevant materials or methodologies pertaining to the kit. The materials may include any combination of the following: background information, list of components, brief or detailed protocols for using the compositions, trouble-shooting, references, technical support, and any other related documents. Instructions can be supplied with the kit or as a separate member component, either as a paper form or an electronic form which may be supplied on computer readable memory device or downloaded from an internet website, or as recorded presentation.

[0145] It is understood that the disclosed kits can be employed in connection with the disclosed methods. The kit may include instructions for use in any of the methods described herein. The instructions can comprise a description of the use of the components for the methods ofmodulating the level of one or more target RNAs and / or expression of one or more target genes or methods of identifying RNA regulatory effector domains.

[0146] The kits provided herein are in suitable packaging. Suitable packaging includes, but is not limited to, vials, bottles, jars, flexible packaging, and the like.

[0147] Kits optionally may provide additional components such as buffers and interpretive information. Normally, the kit comprises a container and a label or package insert(s) on or associated with the container. In some embodiments, the disclosure provides articles of manufacture comprising contents of the kits described above.

[0148] The kit may further comprise a device for holding or administering the present system or composition. The device may include an infusion device, an intravenous solution bag, a hypodermic needle, a vial, and / or a syringe.

[0149] The present disclosure also provides for kits for performing the methods or producing the components in vitro. The kit may include the components of the present system. Optional components of the kit include one or more of the following: (1) buffer constituents, (2) control plasmid, (3) sequencing primers.

[0150] 6. Examples

[0151] Example 1

[0152] High-throughput recruitment identifies protein tiles with RNA-regulatory activity within RNA binding proteins (RBPs)

[0153] The well-established MS2 hairpin sequence and its cognate protein binder, MS2 phage capsid protein (MCP), were used to develop a high-throughput recruitment assay to RNA.

[0154] Twenty-four copies of the MS2 hairpin were installed in the 3’UTR of the RNA of a reporter gene expressing a synthetic surface marker and fluorescent marker Citrine, which was integrated into K562 cells at the AAVSl-Safe Harbor locus on chromosome 19 (Fig. 1A). Libraries of 80-amino acid protein domains are cloned as fusions to MCP (Fig. 6A) and delivered via pooled lentivirus to cells expressing the MS2 reporter. Recruitment of tiles that downregulate reporter RNA levels or inhibit translation lead to lower expression of both Citrine and the surface marker (Fig. 1 A), enabling magnetic separation of large numbers of ON (reporter-expressing) and OFF (non-expressing) cells (Fig. 6B).

[0155] An 1100-RBP census curated from the Pfam database and wide-scale RNA crosslinking and pulldown (eCLIP) experiments was used to formulate a smaller subset of RBPs toinvestigate for ‘effector’ domain activity. GO term annotations were used to exclude RBPs with no known cellular function, those annotated to be involved in DNA-templated transcription, and enzymatic components of the ribosome and spliceosome. RBPs involved in rRNA processing were also excluded and proteins involved in other nuclear processes like chromosome maturation were filtered out. What remained was a fist of 367 RBPs plus four negative control proteins (actin, albumin, tubulin, and IgG). Each protein was tiled along its length in 80aa windows with a lOaa tiling window to create 25,954 unique protein tiles (Fig. IB). Finally, the Pfam database was queried for any known domains in the original 1100 proteins and all of those <80 amino acids long (978 domains) were selected. For domains shorter than 80aa, neighboring sequence from the native protein on both ends were added to reach 80aa and keep a consistent tile size throughout the library. (Fig. IB). To this, 3,597 tiles of random protein sequence and 10 known well-expressing tiles that have transcriptional activating or repressing activity were added for a total library size of 30,539 members. This library was cloned in a pool as a fusion to 3x-FLAG-tagged MCP in a lentiviral vector and delivered to reporter-expressing K562 cells in two biological replicates.

[0156] After 10 days of selection and recruitment, magnetic separation and subsequent sequencing of the protein tiles expressed in the separated ON and OFF populations was performed. The log2(OFF:ON) ratio was computed for each tile using read counts in each population (Fig. 6B). The screen measurements were reproducible (Spearman’s r2= 0.13, p < 1x10-16), and consisted of 28,343 tiles that passed a sequencing depth threshold (Fig. 1C). A hit threshold 3 standard deviations above the mean of the random control population was defined (Fig. 1C), and 438 hit tiles were identified. Four of the top hit tiles in the screen overlap a known RNA regulatory domain in the protein NANOS 1, showing that the high-throughput method can reliably identify protein domains that act as RNA downregulators (Fig. ID). When cloned and recruited individually to the reporter RNA, the second tile of NANOS 1 (aa 11-90) led to a reduction of Citrine levels in all cells (Fig. ID, inset). To further confirm the validity of the calculated screen enrichment scores, 48 MCP-tile fusions were tested in individual cell lines and the fraction of cells that had no Citrine expression was measured (Fig. 6C-F). The individual Citrine measurements correlated well with the corresponding high-throughput enrichment scores (Spearman’s r2= 0.73) (Figs. IE, 6C-F). To measure reporter RNA levels directly, HCR-Flow-RNA-FISH was performed on individual cell lines made with several top hit tiles after MCP-mediated recruitment and all 8 tested tiles induced decreased RNA levels correlated with the observed decrease in Citrine fluorescence, indicating that at least this subset of tiles from the library is directly increasing RNA degradation rather than inhibiting translation (Fig. 6G). To confirm that some of the hit tiles confer RNA-downregulatory capacity in their full-length counterparts, the strongest 80-aa tile found in two proteins (FIP1L1 and NANOS1) was deleted and both the full-length proteins and their deletion mutants to MCP were fused. After recruitment of the full-length and mutant RBPs, in both cases, the full-length proteins downregulated the Citrine reporter more strongly than when the top hit tiles were deleted (Fig.

[0157] 61).

[0158] The hits in the screen overlapped with results from a previous large-scale tethering study performed using full-length RBPs (Luo, E.-C., et al. (2020). Nat. Struct. Mol. Biol. 27, 989-1000). Of the 186 proteins tested in both studies, 12 had hits in both studies, 133 were not hits in either, 21 were hits only in the present study (at the tile level), and 20 were hits only in the previous work (at the full-protein level) (Fig. 6H). The top tile hits from the 12 overlapping proteins comprised some of the strongest hits in this screen (Figs. 6H and 10J-10K).

[0159] Through literature review, a list of the biological processes that RBPs with top hit tiles were known to participate in was compiled (including nuclear processing, translation, deadenylation, splicing, antiviral, and degradation processes). The top 50 RBPs with strong hit tiles in this screen spanned a wide range of known RNA-related functions, from well-known members of the CCR4-NOT deadenylation complex (CNOT4, CNOT2; Fig. 1H) to those with known RNA-binding potential but with unknown function in controlling RNA fate (DZIP3, SETD1A; Fig. IF). Some of these top hit tiles were located within larger, previously-annotated protein regions known to regulate mRNA stability (Fig. IF, starred proteins), and expanded the analysis from looking solely at isolated tiles to searching for broader evidence of both previously-annotated or newly discovered regulatory domains.

[0160] Example 2

[0161] Annotation of RBP regulatory domains contextualizes protein structure and functions An RNA-regulatory ‘effector’ domain was defined as two or more overlapping hit tiles or a single most N- or C-terminal hit tile (Fig. 2A). These rules were used to define 101 continuous hit domains in 86 unique proteins from a subset of the 438 tiles that were hits in the screen. Due to the high amount of overlap between neighboring tiles, regions of activity within previouslyidentified RNA-regulatory domains could more precisely defined (Fig. IF, starred proteins). The protein CNOT4 was known to interact C- terminally with CNOT1, the catalytic member of the CCR4-NOT deadenylation complex, but an exact interaction motif or region has not been reported. This screen identified a C- terminal regulatory domain in CNOT4 at amino acids 331-480, giving a more specific range where an interaction motif may be located (Fig. 7A). 54 domains also overlapped annotations in the Pfam / Interpro database, of which 6 were known RNA-binding domains; however, the rest of the 48 known annotations did not designate RNA regulatory activity, such as chromodomains or kinase domains in enzymatic RBPs (Fig. 2B). This leaves 78 newly annotated regulatory domains for which no previous description of regulating mRNA translation or degradation was found (Fig. 2B).

[0162] Another protein with previously annotated regulatory regions is tristetraprolin (TTP, encoded by the gene ZFP36), which is also known to interact both N- and C-terminally with elements of the CCR4-NOT complex. N- and C-terminal regulatory domains in TTP that are each one tile long were identified, indicating that the specific interaction motifs are likely within the first and last 10-20 amino acids of the protein and would not be present in subsequent or preceding tiles (Fig. 2C). Focusing on the C-terminal regulatory domain, the most C-terminal tile overlaps a conserved CNOT1 interaction motif (RLPIXRIS (SEQ ID NO: 313), aa 315-323). This region is also predicted to have extremely disordered character by AlphaFold, consistent with previous structural evidence showing that disordered protein regions can tightly interact with structured regions of CNOT1 (Fig. 2D).

[0163] The screen also detected new unannotated domains within known RBPs. This annotation may associate a new domain with a known function of the RBP or introduce previously unknown function for the RBP. One newly identified RNA regulatory effector domain in the protein Protein Kinase R (PKR, encoded by the gene EIF2AK2) had high screen scores for each tile and is located between two other annotated domains: a dsRM double-stranded RNA binding domain (dsRBD) and the catalytic kinase domain (Fig. 2D). PKR binds via its dsRBD to non-native double-stranded RNAs over 30 nucleotides in length, normally those of RNA viral genomes. This induces dimerization of PKR kinase domains, autophosphorylation, and subsequent phosphorylation of eIF2a to inhibit host translation and induce apoptosis of infected cells.

[0164] However, PKR was not previously annotated to have a role in the direct degradation or regulation of RNAs that it binds. The discovered regulatory domain was mapped onto theAlphaFold structure of PKR and it corresponded with a disordered region directly between the dsRBD and kinase domain, suggesting that this domain is both functionally and structurally distinct and may play a role in PKR sensing and regulation of viral infection (Fig. 2E).

[0165] AlphaFold was used to predict the structure of the domain alone and its disorder is maintained when folded outside the context of the full protein (Fig. 7B). To identify smaller, specific regions within this annotated domain that facilitate its regulatory activity, both computational domain minimization (the intersection of overlapping tiles) and deletion scanning mutagenesis experiments were performed. By taking only the region of PKR that appeared in all overlapping hit tiles, the ‘minimized’ regulatory domain was computed to span from aa 220-249 in the larger disordered structural region. A set of mutants harboring sequential 5 aa deletions along the length of the top- scoring screen tile (aa 211-290) was created. After performing recruitment experiments with each mutant tile individually, three sequential deletion mutants at amino acids 236-251 abrogated regulatory activity (Fig. 2F). Mapping this region back onto the PKR structure shows that this region is disordered and is almost fully contained within the computationally identified minimized domain.

[0166] The Jpred4 secondary structure prediction server was used to query the expected secondary structure of 195 top hit tiles (those with screen score >=1.6) and 200 non-hit tiles to determine whether most regulatory tiles and domains were similarly disordered (Fig. 2G). A significant (p = 2.06 x 10-5, Kolmogorov-Smirnov statistic 0.24) disenrichment of structured amino acids was found in hit tiles compared to non-hits, concluding that RNA regulatory domains identified are more likely to be disordered than highly structured. Based on the rough bimodal appearance of the distribution of % structured amino acids for tested hit tiles, the tiles were then binned into structured (>35% structured amino acids, 94 tiles / 195 tested) and unstructured (<35% structured aa, 101 tiles / 195 tested) categories and each submitted to the MEME server for motif enrichment analysis. No significant motifs or significant differences in amino acid enrichment were identified in the unstructured tiles, signifying that they are unlikely to share a single interaction partner or other unifying traits (Figs. 7C-E).

[0167] A motif identified in the structured tiles was a conserved region in the LSM protein domain, found in LSm proteins and the protein components of snRNPs involved in splicing and RNA quality control in the nucleus. LSM domains have a distinct and conserved structure consisting of a short N-terminal alpha-helix followed by a five-stranded B-sheet, and appear inthe library in 9 LSm proteins and 8 SNRPs (Fig. 2H). Of those, the LSM domains of 5 LSm proteins and 4 SNRP proteins were hits in the screen (Figs. 21 and 7F).

[0168] Example 3

[0169] Regulatory domain identification and strength is dependent on recruitment position and stoichiometry

[0170] A version of the reporter identical to the one used in the first recruitment screen, but with the 24 MS2 stem-loop cassette installed -100 nucleotides upstream of the translational start site of the surface marker coding region (in the 5’UTR) rather than downstream of the Citrine coding region, was constructed (Fig. 3A). The two different reporter constructs are referred to hereafter as the 5’ and 3’ reporters. The high-throughput recruitment assay was repeated with the same 30,000-member RBP tiling library in cells harboring the 5 ’-recruitment reporter and again found the measurements to be reproducible (Fig. 3B, r2= 0.82, Fig. 8A). Unlike the initial 3’ screen, a large, highly populated range of tile scores (Fig. 3B) was observed, resulting in a clearly bimodal distribution of enrichment ratios even for random tiles designed as negative controls. The high proportion of random tiles that had activity in this screen compared to the 3’ screen indicated that there is likely non-specific regulatory activity associated with recruiting proteins in high copy number to the 5’UTR of an mRNA. To confirm that the wider range of screen scores and higher proportion of tiles with regulatory activity was not due to technical noise, 48 individual MCP-tile fusions were tested and the fraction of cells not expressing reporter protein correlated very well with their corresponding 5’ screen score (Fig. 3C, r2= 0.91, Fig. 8B). RT-qPCR against the Citrine reporter of selected individual validation lines also showed a direct correlation between mRNA and protein levels (Fig. 8C). After fitting a logistic regression curve to correlate the low-throughput validations with their respective screen scores (Fig. 3C), these results were used to calculate two thresholds for this screen: the first is a ‘low” threshold at screen score = 0.30, corresponding to where the recruitment negative control (MCP alone) would score as calculated using the model generated from validation data (Figs. 3B and 3C, black dotted line). The second “high’ threshold was calculated by using the mean + 1.5 standard deviations of the random tiles’ scores (Figs. 3B and 3C, red dotted line) population. Although this ‘high’ threshold excludes many tiles that have moderately high screen scores and clearly reduce Citrine levels in validation measurements (169 tiles above the ‘high’ threshold vs. 9,984 tiles between the two thresholds), using a more stringent cutoff for domain discovery ensures any annotated domains have strong regulatory activity and are not identified solely due to nonspecific modulation of reporter levels.To test how recruitment stoichiometry could affect regulatory domain strength, a set of reporters was built with varying numbers of MS2 stem-loops in the 5’UTR (still located 100 nt upstream of the translational start site of the reporter cassette). Either MCP alone or MCP fusions were recruited to two strong tiles from the 24 stem-loop 3’ and 5’ screens (NANOS1_003, and CNOT4_036) and a random tile that had no effect in the 3’ screen and a weak but abovethreshold score in the 5’ screen (random_set4_0603) to reporters with 1, 2, 3, 7, or the original 24 MS2 stem-loops in the 5’UTR of the reporter mRNA (Figs. 3D and 8D). Both strong hit tiles and the random tile led to increasing fractions Citrine OFF (Fig. 3D) and decreasing Citrine fluorescence (Fig. 8D) with increasing stem-loops, corresponding with their screen scores.

[0171] To investigate the effect of stoichiometry on domain function at the 5’UTR in high-throughput, a smaller library of the top 456 tiles from the 3’ and 5’ 24 stem-loop screens and an additional 2081 tiles that were hits in the 5’ screen, as well as 612 negative control tiles that had little effect in either screen, for a total of 3,149 members (named RBP Hit Library in further analysis and figures) were curated. This library was re-screened with a reporter mRNA that has 7 stem-loops in the 5’UTR (Fig. 3E, r2= 0.77, Fig. 8E). However, a clear bimodality in screen scores similar to the initial 24 stem-loop 5’UTR screen was observed, with many random tiles again having scores above what was expected for inert MCP only control (Figs. 3E and 8F). Individual validation experiments for the 7 stem-loop screen (Figs. 3F and 3G) showed again good correlation with screen scores (Fig. 8G), including for tiles with moderate scores: above MCP alone but under 1.5 standard deviations of random controls. It was not the case that tiles that had moderate effects in the 24-stem-loop screen dropped under the low threshold in the 7-stem-loop one (Figs. 3F, 8H, and 81). This finding suggested that reducing the number of stem loops from 24 to 7 does not eliminate the large number of tiles that nonspecifically decrease Citrine expression at moderate levels (but above MCP alone) when recruited at the 5 ’end (Fig.

[0172] 3E, population under red dotted line). Therefore, the high threshold (1.5 standard deviations above the random controls’ scores) was used when assigning 5’ hit tiles.

[0173] Individual validation curves were used for both the 3’ and 5’ 24 stem-loops reporters (Figs. IE and 3C, respectively) to calculate the fraction of cells with Citrine OFF for all tile scores. These transformed absolute fraction OFF scores can be used to directly compare tile effects between screens, as they are not affected by differences in magnetic separation purity or sequencing depth that affect calculated enrichment ratios between high-throughputmeasurements taken at different times. When comparing the 3’ vs. 5’ transformed OFF scores for each tile sequenced in both 24 stem-loop screens using the full RBP tile library, there was a strong 5’ bias with many more tiles having higher transformed OFF fractions in the 5’ screen (Fig. 3G), as expected from the tendency of 5’ recruitment to nonspecifically reduce Citrine at moderate levels. Once the higher 5’ hit threshold was applied and domains were searched, 32 proteins were found with strong 5’ regulatory domains. Six of these proteins had regulatory domains unique to 5’ recruitment (Fig. 3H), such as DCP1B, a component of the mRNA decapping complex (Fig. 31). Fifty-nine proteins were annotated with regulatory domains active only in the 3’ screen, though the majority of these domains had 5’ screen scores that were above the low detection threshold but under the high 5’ threshold (Figs. 3H and 3J). Twenty-three proteins had one or two strong domains active when recruited at either the 5 ’and 3’ UTR (Figs.

[0174] 3H and 3K). One protein (ADAD2, Fig. 8J) had one domain active only in the 5’ recruitment screen and one that was unique to the 3’ screen, and the remaining 2 proteins had multiple 3’ domains and a single domain active in both screens: HLTF (Fig. 3L) and SETD1B (Fig. 8K). In summary, this resulted in a total of 91 unique proteins annotated with 108 unique effector domains overall (Fig. 3K, Table 1).

[0175] Example 4

[0176] Discovery of domains that can downregulate gene expression when recruited to either RNA or DNA

[0177] Since the MS2 mRNA reporter is genomically integrated and transcribed, some of the effects seen with MS2-MCP-mediated recruitment could be a result of co-transcriptional interactions of the MCP-tile fusion with chromatin regulators or transcriptional machinery, thus affecting transcription rather than post-transcriptional regulation of RNA export, degradation, or translation. In order to test tiles for direct effects on transcription, tiles were recruited directly to DNA upstream of the reporter, by fusing the RBP hits and controls library (3,149 members, as in Fig. 3B) to rTetR, a doxycycline-inducible DNA-binding domain. This new fusion library was delivered to K562 cells expressing a reporter that encodes the same surface reporter and Citrine, but lacks the MS2 stem loops and instead contains a 9xTetO binding site array for rTetR upstream of the strong pEF promoter that drives its expression (Fig. 4A). After selection with blasticidin for 10 days and 24 hours of recovery in blasticidin-free media, doxycycline was added at 1,000 ng / mL to induce binding of rTetR and recruitment of the fused RBP hit library tiles to the reporter locus. Magnetic separation was performed identically to the MCP-fiisionscreens after 7 days of doxycycline treatment (Fig. 9A). At the same time, this smaller RBP hit+controls library fused to MCP was also re-screened and recruited at the 3’ UTR of the 24xMS2 stem loop reporter as an additional re-test of results from the large initial screen (Fig.

[0178] 9B). After performing both screens, which showed good reproducibility (Figs. 9C-9F), each tile’s average screen score was compared when recruited to DNA vs. RNA and the hits were found to be almost completely mutually exclusive (Fig. 4B): 145 tiles were hits only in the RNA-recruitment screen and 115 only in the DNA-recruitment screen. Of the 103 proteins with tiles in the library, 14 proteins had at least one tile called as a hit in both screens (though not necessarily the same tile), while 47 proteins had one or more RNA hit tiles only and 42 proteins had only DNA hit tiles (Fig. 9G). However, only 7 tiles showed strong regulatory activity both when recruited to 3’ RNA (via MCP) and to DNA (via rTetR): 3 KRAB domains from zinc-finger transcription factors, 1 random control tile, and 1 tile each from ubiquitin E3 ligase HUWE1, the 3’ RNA processing factor CSTF2, and CHTOP, a protein known to bind both chromatin regulator PRMT1 and act as a component of the nuclear export complex TREX (Fig. 4C).

[0179] Since CHTOP was previously annotated to interact with both chromatin and RNA regulatory pathways, the tile found to have dual repressive activity: CHTOP_002, spanning amino acids 11-90 (Fig. 4D), was further investigated. Another tile, CHTOP_001, from amino acids 1-80, is a consistently strong RNA regulator in each of the MS2-MCP recruitment screens but lacks any activity in the DNA-recruitment screen (Fig. 4D). Both of the following two tiles -CHTOP_003 or CHTOP_004 - were inert when recruited to either RNA or DNA (Fig. 4D). It was hypothesized that either: (1) the last 10 amino acids of CHTOP_002 (81-90) were conferring the transcriptional repressive activity unique to that tile, or (2) the first 10 amino acids of CHTOP_001 (1-10) were inhibiting its ability to repress when recruited to DNA. To this end, systematic deletions of these two tiles were created (Fig. 4E). Deleting the last 10 amino acids of CHTOP_002 had no effect on its activity (Fig. 9H), rejecting the first hypothesis above. Deleting amino acids 6-10 of CHTOP_001 led to a gain in DNA regulatory activity comparable to wildtype CHTOP_002, while maintaining its strong RNA regulating capability (Figs. 4E and 91). Deleting the first 5 amino acids of CHTOP_001 had no effect on either its RNA- or DNA-level activity (Fig. 9H). This led to the conclusion that the second five amino acids of CHTOP (APKVV; SEQ ID NO: 314) inhibited transcriptional repressive activity (Fig. 4E, schematic under graphs). The KRAB domain from ZNF10, which is commonly used as an epigeneticsilencing tool, was selected and asked if its effects in the RNA recruitment assay were due to increasing rates of RNA degradation or through in trans interactions with the reporter locus while bound to the reporter mRNA (Fig. 4F, top). To do so, a system for inducible recruitment with MCP-MS2 was developed to measure the dynamics of RNA regulation over time. The (trimethoprim) TMP-dependent DHFR degron was fused to the N-terminus of MCP and a HaloTag to its C-terminus, then cloned ZNF10 KRAB fused C-terminally to the HaloTag (Fig.

[0180] 4F, bottom). There was very little protein before TMP addition and that MCP-tile levels robustly stabilized as early as 6 hours (as measured by HaloTag stain) after addition of 10 μM TMP (Fig.

[0181] 9J). This system was then used to test the timescale of RNA degradation separate from putative transcriptional silencing. Actinomycin D (actD; to inhibit RNA polymerase activity and stop transcription) and TMP (to stabilize DHFR-MCP fusions) were added and the RNA life-time was measured with HCR-Flow-RNA-FISH (Fig. 4G). The reporter mRNA half-life when bound only by DHFR-MCP alone was 7.63 + / - 0.002 hours, consistent with measurements of a very similar reporter molecule (Fig. 4G). The half-life decreased to 3.83 hours when bound by DHFR-MCP-NANOS1_003 (a known interactor with RNA degradation machinery) but showed virtually no change when bound by DHFR-MCP-KRAB (8.36 + / - 0.003 hours) (Fig. 4G), suggesting that MCP-KRAB recruitment does not increase RNA degradation.

[0182] Finally, to test the chromatin-mediated transcriptional effect of KRAB when recruited to the locus via RNA, DHFR-MCP-KRAB was recruited and the abundance of histone H3, lysine 9 trimethylation (H3K9me3), a repressive histone mark, was measured at the reporter (Fig. 4H). KRAB domains are known to associate tightly with protein KAP1, which nucleates the assembly of a transcriptional repressive complex including the histone H3 methylase SETDB1. MCP-KRAB led to increased H3K9me3 levels after 1 day of RNA-mediated recruitment, similarly to rTetR-KRAB (DNA-mediated recruitment), and significantly higher than the MCP-NANOS1_003 negative control that acts via RNA degradation (Figs. 4H and 9K-L). Together, the increase in repressive histone modifications and unchanged RNA lifetime indicate that the repressive effect of KRAB is through transcriptional regulation at the DNA locus during, both when recruited to DNA and RNA (Figs. 4H and 9K-L).

[0183] Example 5

[0184] Synthetic RNA-level control of gene expression expands working models for gene regulationThe newly discovered RNA regulatory effector domains can be used to synthetically tune RNA levels. In order to use this type of regulation in synthetic circuits, a predictive mathematical model of RNA-mediated regulation was developed to compare it to classical synthetic transcriptional regulation, such as one mediated by KRAB. To test how different levels of the RNA effector domain change mRNA expression dynamics, a cell line stably expressing DHFR-MCP-HaloTag-NANOSl_003 (a strong hit tile in both 3’ and 5’ screens) was created, herein named synNANOS (Fig. 5A). synNANOS can efficiently downregulate reporter expression of the 7 stem-loop 5’UTR reporter in the presence of saturating TMP (Fig. 10A). By increasing the TMP concentration, the levels of synNANOS can be gradually increased, as measured by HaloTag staining (Fig. 5B). These data allow the dependence of synNANOS as a function of TMP concentration to be mathematically fit using a Michaelis-Menten equation (Fig. 5B). The TMP-dependent increase of stabilized synNANOS leads to a gradual decrease in the Citrine reporter mean fluorescence intensity (Fig. 5C): log-fold changes in TMP concentrations lead to linear decreases in measured Citrine expression for a wide range of TMP.

[0185] In contrast, transcriptional control is performed by recruiting the ZNF10 KRAB domain fused to rTetR at different concentrations of doxycycline at the 9xTetO response element upstream of the promoter (Fig. 10B), the response to the inducer is abrupt (Figs. IOC and 10D). Rather than gradual shifts in MFI, a sharp change in total MFI was observed between 2-10ng / ml of dox (Figs. IOC and 10D). This response likely comes from the previously observed and modeled single-cell stochasticity associated with chromatin-mediated gene silencing, and emphasizes the need for development of a new mathematical model incorporating RNA regulation that describes gradual MFI decreases mediated by RBPs (Fig. 5D).

[0186] Modeling RNA control began with a gene in the actively transcribing state (A), where cells produce mRNA at the rate of transcription ktrx- This mRNA can be naturally degraded by the cell at rate kdeg, or it can be degraded faster when bound by the RNA regulatory domain at a rate kreg(Fig. 5D). It can be assumed that any protein translated from existing mRNA is translated at a rate ktriand can subsequently be degraded at a rate kdeg, protein- This model can be used to calculate the steady state reporter levels, and the experimental data can be fit to the different rates in this model (Fig. 5E). Using HCR-Flow-RNA-FISH to measure RNA degradation kinetics after inhibiting transcription with actinomycin D (Fig. 4G), the reporter RNA degradation rate is approximated in the absence of synNANOS to be k eg = 0.1 / hr. Thepresence of synNANOS decreases the steady state reporter mRNA levels (mRNAss) compared to maximum levels (in its absence) in a manner that depends on its associated degradation rate (kreg, eq. 1).

[0187] mRNAsskdeg

[0188] (eq. 1)

[0189]

[0190] mRNAmaxkdeg+kreg

[0191] The synNANOS-associated rate of degradation (kreg) depends on the level of synNANOS, which changes with TMP and is described by eq. 2:

[0192] n

[0193] [TMP] \

[0194] [TMP]+KDTMP)

[0195] ~ ^egmax' z _ (eq 2),

[0196]

[0197] VTMP]+ / fDTMP /

[0198] where KD(TMP) is the Michaelis-Menten constant describing how the synNANOS concentration depends on TMP, kreg, max is the maximum synNANOS-associated degradation rate, K is the equilibrium binding of synNANOS to RNA, and n is the Hill coefficient.

[0199] KD(TMP) = 1.19 was extracted by directly fitting the synNANOS protein levels as a function of TMP (Fig. 5B). Then, using equations 1&2, the steady-state Citrine levels (normalized to maximum) as a function of TMP concentration can be fit (Fig. 5E, curve), with free parameters K and n describing the binding of synNANOS to RNA. kreg,max describes the rate of synNANOS-associated mRNA degradation at saturating synNANOS levels, with higher values of kreg, max corresponding to higher sensitivity to TMP and more mRNA degradation at lower concentrations of RBP (Fig. 10E), and can be tuned by changing the regulatory domain in a synthetic RBP to create a more or less potent RNA degrader.

[0200] Finally, the parameters fit to steady-state mRNA levels at varying TMP concentrations can be used to predict reporter mRNA degradation kinetics over time (Fig. 5F). The model predicts steady-state Citrine levels to be reached by 2-3 days of TMP treatment, and varying TMP doses allows steady-state relative Citrine levels from 1 to as low as 0.4. The RNA degradation model was compared to a model of KRAB-mediated transcriptional silencing, where varying dox concentration directly modulates ks(the probability of a cell to be in a completely silent transcriptional state) (Fig. 10F). By fitting this model to the rTetR-KRAB recruitment data, KRAB silencing over time at varying dox doses can be described (Fig. 10G). Unlike in the RNA regulation model, in the KRAB-mediated transcriptional regulation model Citrine levels are not predicted to reach intermediate steady state by 5 days of recruitment, and higher doses of dox trend sharply toward a normalized fluorescence of 0 as recruitment continues (Fig. 10G). Thedifferences in the transcriptional silencing vs. RNA degradation models accurately capture the different dynamics and magnitudes of KRAB and synNANOS recruitment effects on Citrine expression, and allow extraction of parameters that are most relevant to the different mechanisms of gene silencing employed by transcription factors vs. RBPs.

[0201] To determine whether RNA regulatory domains are truly modular and can be used with other RNA binding domains, NANOS1_003-DHFR was fused to an endogenous RNA binding domain (RBD) from the protein RBFOX2 and downregulation of endogenous RNA transcripts using RNA-seq was measured (Fig. 5H). The RBFOX2 RBD is well-annotated, spans 76 amino acids (aa 121-197) encapsulating an RRM (RNA recognition motif) domain, and binds the consensus sequence GCAUG reliably in cells and in vitro. After overexpression of DHFR-RBFOX2_RBD-NANOS1_003 (thereby RBFOX-NANOS) for 48 hours in the presence of TMP, transcriptome-wide RNA abundance was measured as compared to 48 hours of overexpression of synNANOS. 591 RNAs were downregulated only in cells expressing the RBFOX2 RBD fusion (Figs. 5I-5J), signifying that NANOS1_003 is a potent RNA-regulatory effector across multiple RNA-binding contexts. To evaluate the specificity of RBFOX-NANOS binding, previously published eCLIP data in K562 cells was used to identify which of the differentially expressed genes are bound by endogenous RBFOX2. Differentially depleted genes are enriched for RNAs bound by RBFOX2 (hypergeometric test, p-value = 0.02) and have significantly more RBFOX2 binding peaks compared to non-depleted genes (proportion test, p-value = 4*e-7), implying fusion to RBDs of interest may be a generalizable strategy for targeting endogenous RNAs.

[0202] Materials and Methods

[0203] Cell culture Cell culture was performed as described in DelRosso, N., et al., (2022, Preprint, 10.1101 / 2022.08.26.505496). Briefly, all experiments were carried out in K562 cells (ATCC, CCL-243, female), which were cultured in a controlled humidified incubator at 37°C and 5% CO2in RPMI 1640 (Gibco, 11-875-119) media supplemented with 10% FBS (Omega Scientific, 20014T) and 1% Penicillin-Streptomycin-Glutamine (Gibco, 10378016). All MS2 reporter cell lines were generated as in Tycko, J., et al., (Cell 183, 2020-2035. el6 (2020)).

[0204] Reporter DNA was integrated by TALEN-mediated homology-directed repair to integrate donor constructs into the AAVS1 locus by electroporation of 1 x 106cells with 1 pg of reporter donor plasmid and 0.5 pg of each TALEN-L (Addgene no. 35431) and TALEN-R (Addgene no.35432) plasmid using program T-016 on the Nucleofector 2b (Lonza, AAB-1001). After 48 hours of recovery, cells were treated with 500 ng ml-1puromycin antibiotic for 7 days to select for a stably integrated population. Fluorescent reporter integration and expression was measured by flow cytometry. HEK293T-LentiX (Takara Bio, 632180, female) cells were used to produce lentivirus (as described below) and were grown in DMEM (Gibco, 10569069) media supplemented with 10% FBS (Omega Scientific, 20014T) and 1% Penicillin-Streptomycin-Glutamine (Gibco, 10378016). These cell lines were not authenticated. All cell lines tested negative for mycoplasma.

[0205] Lentiviral production and transduction Small-scale lentiviral production was performed as described in Ludwig, Ch. H. et al., (Cell Syst. 2023 Jun 21;14(6):482-500.e8). Briefly, HEK293T Lenti-X cells were seeded at 5 x 105cells per well in 2 mL of DMEM in 6-well plates. After 24 hours, cells were transfected with 750 ng of an equimolar mixture of three third-generation production plasmids (pMD2. G: Addgene #12259; pRSV-Rev: Addgene #12253; pMDLg / pRRE: Addgene #12251; all gifts from D. Trono) and 750 ng of plasmid encoding the gene of interest. The 4 plasmids were incubated for 15 minutes with 5 pL of polyethylenimine (PEI, Polysciences #23966) before transfection. After 72 hours of incubation, lentivirus was harvested and collected, and supernatant was filtered through 0.45 pM PES filters (CELLTREAT #229749). Undiluted, filtered virus was added to K562 cells at a final concentration of 1-2 x 105cells / mL and centrifuged in 1.5 mL Eppendorf tubes at 1,000 x g for 2 hours, after which supernatant was discarded and cells were cultured for two days in fresh media. After 48 hours of culture, antibiotic selection was initiated with blasticidin (10 pg / mL, Gibco #A1113903) and infection and selection efficiency were monitored daily with flow cytometry on a Bio-Rad ZE5 Cell Analyzer (Bio-Rad #12004278).

[0206] Lentiviral production for screens was performed by seeding 9 x 106HEK293T Lenti-X cells into 15-cm dishes in 30 mL of DMEM. The next day, cells were transfected as above using 11.25 pg packaging plasmid mixture, 11.25 pg cloned library plasmids, and 150 μL PEI. 24 hours after transfection, a full media change was performed; 72 hours after transfection, supernatant was harvested and filtered with a 0.45 pm PES filter unit (Thermo Scientific #1680045).

[0207] Human RBP tiling library design The gene symbols of 1100 human RBPs were passed into the Python package Mygene to extract their Uniprot IDs and associated GO annotations.Uniprot was then accessed through its Python API to pair each gene symbol and Uniprot code with their corresponding amino acid sequence. The list of 1100 proteins was filtered to exclude the GO terms “'rRNA', 'No GO term found', 'splic', 'ribosom', 'transcription'”, and the proteins albumin, actin, tubulin, IgG, BRIX1, DDX31, PUM2, NANOS1, RRP36, and PKR were added as putative negative and positive controls. The 50 top proteins that were destabilizing hits in Luo, E.-C., et al., (Nat. Struct. Mol. Biol. 27, 989-1000 (2020)), were also included if not already included. 80aa-long protein tiles were generated in lOaa increments along all proteins and duplicates were removed using custom Python scripts. Annotated Pfam domains for all of the original 1100 proteins were collected using the package Prody, which accesses Interpro through a Python API, and filtered for domains under 80aa. Domains 80aa long were added directly to the list of tiles; those shorter than 80aa were expanded by adding native protein sequence on each side of the selected domain until 80aa was reached. 3,597 random tiles from the library generated in Ludwig, Ch. H. et al., and 10 well-expressing tiles known to be transcriptional activators or repressors were added to the resulting 26,932 tiles. All 30,539 tiles were then reverse-translated and codon-optimized as follows: codon use was matched to human codon frequencies; a GC content of 20-70% within 50bp windows and maximum 65% GC content was enforced; BsmBI sites were excluded; C homopolymers greater than 7 in length were excluded. Finally, BsmBI restriction sites and primer handles for PCR amplification were appended to all oligos, resulting in a uniform 300nt length for every library member. The library was ordered as a pool from Twist Biosciences.

[0208] RBP hit library design A hit library was built out of tiles that had been screened in the RBP library at both the 3’ and 5’ reporters and included the following: all tiles that were hits on both reporters (screen score >1.16 on 3’, 0.3 on 5’); tiles that were only hits on the 3’ reporter; the top tiles on the 5’ reporter that were not hits at 3’ (>1.2 on 5’, <1.16 on 3’), and a selection of non-hit tiles from both screens (scores <-0.75 at 3’, <0 on 5’) for a total of 3,149 members. All tiles were again codon-optimized following the constraints as above and ordered as a pool from Twist Biosciences.

[0209] Pooled library cloning All Twist oligo pools were resuspended to 10 ng / μL in water, and libraries were selectively PCR amplified using primers specific to their appended handles flanking the sequence of each library member. All reactions were prepared in a pre-PCR hood to reduce contamination. A test qPCR reaction was performed using 25 μL Q5 Ultra II High-Fidelity Polymerase (NEB #M0544L), 0.5 pL library pool, 2.5 pL of each 10 pM library amplification primer, 0.25 pL 20X EvaGreen dye (Fisher Scientific #NC0521178), and water to 50 pL. qPCR was performed on a Bio-Rad CFX machine and was analyzed to extract the halfmaximum cycle number for dye saturation using the following protocol: initial denaturation at 98°C for 30s; 35 cycles of 98°C for 10s, 58°C for 20s, and 72°C for 30s; final extension at 72°C for 2 minutes. Two to six PCRs were then performed, depending on library size, in identical conditions using 17 to 21 cycles depending on the qPCR results per library. Amplified libraries were purified with 0.9X SPRISelect (Beckman Coulter #B23317) and elution in 20 pL.

[0210] The pAT031 MCP recruitment lentiviral vector and the pJT126 rTetR recruitment vector (Addgene #161926) were digested with 10,000U / mL Esp3I (NEB #R0734L) for 15 minutes at 37°C, using 1 pL enzyme per 5 pg plasmid. After heat inactivation at 65°C for 20 minutes, predigested vector was run on a 0.5% TAE gel until a linearized band could be extracted using the QIAquick Gel Extraction Kit (Qiagen #28704). Amplified libraries were then cloned into their respective digested vectors using the NEBridge Golden Gate Assembly Kit (BsmBI-v2) (NEB #E1602L) as follows: 20 pL reactions were prepared using 2 pL lOx T4 DNA Ligase Reaction Buffer (NEB #B0202S), nuclease-free water, 75 ng of pre-digested vector, 5 ng of amplified library, and 2 pL assembly kit. 24 reactions were prepared to clone the RBP library; 8 reactions were used for the smaller RBP hit library. Each 20 pL reaction was placed in a thermocycler for 65 cycles of 42°C for 5 minutes and 16°C for 5 minutes, then a final digest at 42°C for 5 minutes and heat inactivation at 70°C for 20 minutes. Reactions for each library were pooled and purified using the Zymo Clean& Concentrate DNA kit (Zymo #D4004) eluted in 6 pL of water.

[0211] 25 pL aliquots of Endura DUO electrocompetent cells (Lucigen #60242-2) were thawed on ice and mixed with 2 pL of the purified Golden Gate product. Mixtures were transferred to Gene Pulse Electroporation Cuvettes with a 0.1cm band gap (Bio-Rad #1652089) and electroporated on a Gene Pulser Xcell Total System (Bio-Rad #1652660) under the following conditions: 1.8kV, 10 uF, 600 Ω, and 0.1 cm distance. Cells were recovered in 2 mL of 37°C SOC recovery medium (NEB #B9020S) at 37°C for 1 hour, after which they were plated across 4-8 10”xl0” luria broth agar plates with 100 pg / mL carbenicillin. Plates were incubated at 30°C for 14-18 hours, after which colonies were harvested by scraping and pelleted at 3,500xg for 20 minutes. Plasmid pools were extracted using the Qiagen Plasmid Maxi Kit (Qiagen #12162) andlibrary quality was assessed using Illumina sequencing after PCR amplification from the plasmid pool.

[0212] High-throughput recruitment assays K562 cells expressing either the 3’ 24 stem-loop, 5’ 24 stem-loop, 5’ 7 stem-loop, or 9xTetO reporters were infected with their corresponding lentiviral libraries by centrifugation at l,000xg for 2 hours. Libraries were infected in two replicates at ~300x infection coverage (starting with 45 x 106K562 cells for the RBP library screens and 10 x 106K562 cells for the RBP hit library screens, each at a resulting MOI of 0.3). Cells were treated with 10 pg / mL blasticidin (Gibco #A1113903) starting 48 hours post-infection and were selected for seven to nine days, until at least 94% of cells were positive for lentiviral integration as assessed by flow cytometry (BFP positivity for MCP lentivirus, mCherry positivity for rTetR lentivirus). For screens using the MCP-MS2 recruitment system (both RBP library screens, the RBP hit library re-test, and the 7 stem-loop RBP hit library screen), cells were allowed to recover for 24 hours in blasticidin-free media before magnetic separation and harvest (below). For the TetO-rTetR screen, 1000 ng / mL doxycycline was added once selection was complete and cells were maintained in doxycycline media for 7 days prior to magnetic separation.

[0213] For all libraries, cells were maintained in log growth conditions with daily media changes to ensure dilution to ~5 x 105cells / mL and replenishment of blasticidin during selection.

[0214] Maintenance library coverage was kept as high as possible and >l,000x for all of selection. Cells infected with the RBP library were cultured in IL spinner flasks with constant paddle rotation; cells infected with the RBP hit library were maintained in T225 flasks. The half-life of doxycycline in the TetO-rTetR screen was assumed to be 24 hours, and half the amount of doxycycline was replaced each day for the 7 days of recruitment.

[0215] Magnetic separation At the end of each recruitment assay, a number of cells equivalent to 12,000X coverage was removed from the flasks for each replicate and pelleted at 300xg for 5 minutes, then washed twice with DPBS to remove IgG from growth media. Pellets were resuspended in magnetic separation blocking buffer (2% BSA, 2mM EDTA pH 8.0 in DPBS) to a final concentration of 20 x 106cells / mL. Dynabeads M-280 Protein G (Thermo #10004D) were prepared by incubation on a magnetic stand, removal of supernatant, washing in 5x volume of blocking buffer, and subsequent buffer removal and resuspension in the cell mixture. 90 pL of beads were used per every 10 million cells pelleted. Cell-bead suspensions were incubated atroom temperature for 75-90 minutes on a nutator to allow for binding, and then incubated on a magnetic stand for 5 minutes to allow for separation of bead-bound and unbound cells. The ‘unbound’ cell fraction was removed as supernatant and placed in a new tube, which was subsequently re-incubated on the magnet and removed one more time to ensure high purity. The bead-bound fraction was resuspended in the same volume of blocking buffer and re-incubated on the nutator for 15 minutes, after which it was incubated on the magnet, the supernatant discarded, and the beads resuspended as the final ‘bound’ fraction. Bound, unbound, and pre-separated cells were analyzed by flow cytometry for separation purity, pelleted, and frozen at -20°C until further processing.

[0216] Library preparation and sequencing Genomic DNA was extracted from all pelleted magnetic separation fragments using the QiaAmp Blood& Cell Culture DNA Maxi Kit (Qiagen #13362) following manufacturer’s instructions, using no more than lxlO8cells per column. During extraction, beads were removed from the bead-bound fractions using a magnetic stand post-lysis to avoid column damage, and fractions were eluted in buffer EB (Qiagen #19086) rather than buffer AE to avoid PCR inhibition. Library members were amplified by PCR with primers containing Illumina adapter overhangs. Cycle numbers for PCR were determined by qPCR, in which one test reaction for each fraction was performed with the addition of 0.25 pL 20X EvaGreen dye (Fisher #NC0521178) and was analyzed to extract the half-maximum cycle number for dye saturation. Next, between 8 and 48 PCR reactions were set up for each fraction, with the number of reactions dependent on both the amount of extracted genomic DNA and on required coverage per library size. Reactions were set up as follows: 5-10 pg genomic DNA, 0.5 pL each primer, 50 pL Q5 Ultra II High-Fidelity Polymerase (NEB #M0544L), water to 100 pL. The thermocycling protocol used was as follows: initial denaturation at 98°C for 3 minutes; 17-25 cycles of 98°C for 10s, 63°C for 30s, and 72°C for 30s; and final extension at 72°C for 2 minutes. All reactions for each fraction were mixed and purified using a double-sided SPRIselect cleanup with an initial 0.5X left-sided cleanup and final ratio of 0.75X. Samples were quantified using the Qubit dsDNA HS Assay Kit (Thermo #Q33231) on a Qubit 4 Fluorometer (Fisher #Q33238), run on an Agilent TapeStation (Agilent #G2964AA) to assess library purity, pooled with 30% PhiX Control v3 (Illumina #FC-110-3001), and sequenced on an Illumina NextSeq 550 with 2x150 cycles, on an Illumina HiSeq 2000 with 2x150 cycles, or on an Illumina MiSeq with 2x150 cycles.High-throughput recruitment sequencing analysis All recruitment assay sequencing data was processed and analyzed using the HT-recruit- Analyze pipeline from (Tycko), available on GitHub (github.com / bintulab / HT-recruit-Analyze). Briefly, raw sequencing reads were demultiplexed using bcl2fastq (Illumina) and aligned using ‘makeCounts.py’ to a reference created with ‘makelndices.py’. The aligned reads were used to compute enrichment scores from the unbound (OFF) to bound (ON) populations for each library member using ‘makeRhos.py’. Depending on the sequencing depth of the assay, library members with fewer than 50-500 reads summed between replicates were excluded from further analysis. The hit threshold for each screen was determined either by using 3 standard deviations above the mean score of the random tile control population, or by adjustment for wide distribution of random control scorers.

[0217] Regulatory domain annotation Only the unbiased tiling screens (3’ and 5’ RBP library screens) were used to assess putative regulatory domains from tile scores. The starts of new domains were defined as the first tile in a string of two or more consecutive hit tiles. If a tile had dropped out of the screen due to low sequencing depth but the tiles on each side of it were hits, the missing tile was considered part of the same contiguous regulatory domain. Domain ends were annotated where the next successive tile in an ongoing domain was no longer a hit. The extended domain length was considered to be the first amino acid of the first hit tile to the last amino acid of the last hit tile. Single hit tiles were not considered to be domains unless they were the most N- or C-terminal tile of a given protein. Minimized regulatory domains were computed as the sequences fully contained within tiles that downregulated the RNA reporters. Amino acids not contained by two or more tiles in the same domain were excluded, leaving the last ten amino acids of the first hit tile spanning until the first ten amino acids of the last hit tile as the minimized region.

[0218] Individual recruitment assays Individual protein tiles that were selected for low-throughput validation were ordered as gene fragments from IDT and cloned into either the pAT031 (MCP) or pJT126 (rTetR) recruitment backbones using Golden Gate cloning. K562 cells expressing the appropriate reporter lines were transduced with lentivirus (prepared as described above) and selected with blasticidin (10 pg / mL) beginning 48 hours after infection. Selection continued for 5-9 days or until cells were >95% BFP / mCherry positive, after which the MCP lines were analyzed for Citrine fluorescence in biological replicate using a Bio-Rad ZE5 cytometer measuring >10,000 cells per sample. rTetR lines were split into two plates (all inbiological replicate); one plate was left untreated and one plate was treated with 1000 ng / mL doxycycline with half-media and doxycycline changes performed every day. Cells were analyzed using flow cytometry for Citrine fluorescence every day of doxycycline treatment. Data was analyzed using Cytoflow and additional analyses and visualizations were performed using custom Python scripts. All cells were gated for live cells, singlets, and mCherry / BFP positivity; from there, either an MCP-only or an rTetR-control / no-dox control was used as a negative control to compute the fraction of Citrine ON and OFF cells. These OFF scores were compared to screen enrichment ratios using a logistic expression; because OFF scores are not related to sequencing depth, they are a better metric for comparing between screens performed at different times (enrichment ratios are calculated having normalized for raw reads, but different screens can have different dynamic ranges depending on library number and magnetic separation purity that makes relative values consistent but absolute values difficult to compare).

[0219] Protein compositional analysis, motif finding, and structural analysis Amino acid composition and compositional biases were calculated by comparing the frequency of each amino acid in a group of interest (the top 195 hit tiles, unstructured hit tiles, and structured hit tiles) to that same amino acid frequency in a reference dataset (195 non-hit tiles, randomly chosen). Predicted structures were computed using the Jpred4 server, which assigns each amino acid of the submitted 195 hit or 195 non-hit sequences as “helical,” “sheet,” or “unstructured.” Motif finding analyses of each of the above groups was performed using the MEME suite server, taking the top 3 most confident motifs and excluding overlap between tiles as putative motifs.

[0220] HCR-Flow-RNA-FISH for Citrine reporter sequence HCR-FlowFISH was performed as described in Fulco, C. P., et al, (Science 354, 769-773(2016)). All reagents were prepared using the Molecular Instruments HCR RNA-FISH Bundle with custom probes against the Citrine reporter mRNA and Amplifier B3 (Alexa-647 fluorophore). Briefly, 2.5 x 106cells per condition were pelleted and resuspended in 4% formaldehyde, then fixed for one hour at room temperature with agitation. Cells were washed 4 times with PBST and resuspended in 70% cold ethanol, incubated at 4°C for 10 minutes, and washed twice again with PBST. Pellets were resuspended in Probe Hybridization Buffer and mixed with custom probes to incubate overnight at 37°C. After overnight incubation, cells were washed 4 times in Probe Wash solution, resuspended in 5x SSCT, and incubated at room temperature for 5 minutes, then spun down and resuspended in Amplification Buffer. While cells were incubating in Amplification Buffer for 30 minutes atroom temperature, fluorescent hairpins were prepared by snap cooling from 90°C to room temperature in the dark for 15 minutes. Hairpins were added to cells and incubated for 3 hours in the dark to allow the HCR to occur. Finally, cells were washed 6 times with SSCT, resuspended in 500 mL PBS, and analyzed on a BioRad ZE5 cytometer for Citrine and Alexa-647 fluorescence.

[0221] RT-qPCR against Citrine reporter mRNA RT-qPCR was performed using iScript reverse transcription mix (Bio-Rad #1708841) and the SsoAdvanced SYBR Green Supermix (Bio-Rad #1725271), following manufacturer’s specifications. Briefly, RNA was extracted from cell samples using the RNEasy+QiaShredder kits (Qiagen #74106); 500 ng of RNA per sample was added to iScript reverse transcription master mix and incubated for 5 minutes at 25°C, 20 minutes at 46°C, and 1 minute at 95°C. The resulting cDNA was diluted 1:2 and 2 microliters were carried forward into the qPCR reaction, performed using a BioRad CFX Connect Real-Time system (Bio-Rad #1855201). Data was analyzed using custom Python scripts.

[0222] Preparation of degron-expressing cell lines Cell lines expressing DHFR-MCP-tile fusions were selected for cells that responded completely to TMP inhibition of the degron. To isolate these populations, 10 pM TMP was added for 4 days, resulting in a bimodal population of Citrine fluorescence. The fully silenced cells were sorted and allowed to reactivate the mRNA reporter through TMP washout and degradation, after which the sorted and reactivated cells were able to fully repress Citrine translation upon addition of TMP.

[0223] Degron inhibition and HaloTag staining For all cell lines expressing DHFR-MCP-tile fusions, 10 pM TMP was used as a saturating dose for degron inhibition. A no-TMP (0 pM) control was included for all TMP dosing experiments. HaloTag staining was performed using the Janelia Fluor 646 HaloTag Ligand (Promega #GA1121) as follows: ligand was resuspended in 35.5 pL DMSO to prepare a 200 pM stock solution. The stock solution was diluted to 200 nM in warm RPMI. 2 x 105cells were pelleted per sample and resuspended in 200 pL diluted ligand solution. Samples were incubated for 15 minutes in a 37°C 5% CO2 incubator, after which they were pelleted and resuspended in 200 pL RPMI for flow cytometry analysis.

[0224] Transcriptional inhibition experiments Actinomycin D was used to inhibit transcription and measure RNA degradation rates. At each timepoint, TMP at a final concentration of 10 pM and actinomycin D at a final concentration of 1 pg / mL were added to 1 x 106cells. Cells were harvested at the end of the timecourse and HCR-Flow-RNA-FISH was performed as describedabove to measure Citrine mRNA levels. Degradation rates and half-lives were calculated using custom Python scripts.

[0225] CUT& RUN for detection ofH3K9me3 CUT& RUN was performed as described in Lensch, S. et al., (Elife 11, e75115 (2022)), using the CUT ANA CUT& RUN Kit (14-1048, EpiCypher) and Abeam anti-H3K9me3 antibody (Abeam abl76916). An input of 5xl05cells per sample were processed according to the manufacturer’s protocol. Digitonin was used at a final concentration of 0.01% for nuclear permeabilization. Sequencing libraries were prepared and dual-indexed using Illumina adapters (in the CUT ANA kit). Libraries were quantified with the Qubit dsDNA HS Assay Kit and fragment sizes assessed using an Agilent TapeStation. Libraries were sequenced using a NextSeq 550 system from Illumina. A custom human genome (hg38) with the reporter integration added was constructed using bowtie2-build. Alignment was performed using bowtie2, and Picard was used to remove duplicate reads. Bedgraph files were generated using bedtools and reads were normalized by total counts per sample, and reported as counts per million. Further analysis was performed using custom Python scripts. Processing scripts are available at github.com / bintulab / Spreading_Lensch_2022 / tree / main / CUT%26RUN%20Analysis.

[0226] RBP-mediated RNA degradation model Deterministic equations were derived for the Citrine levels of cells where transcriptional RBP-mediated RNA degradation affects the average mRNA, and consequently Citrine, level of the cell population. A differential equation describing transcription of the reporter gene was first derived, where ktrxis the rate of mRNA production from the reporter locus, kdegis the RBP-independent rate of mRNA degradation, kregis the RBP-mediated rate of mRNA degradation, and mRNA is the concentration of mRNA in the cell:

[0227] dmRNA

[0228] ktrx − mRNA · kdeg − mRNA · kreg.

[0229]

[0230] Assuming the maximum mRNA level in the cell occurs when kreg= 0, the steady-state mRNA levels normalized to the maximum mRNA are thus given by:

[0231] mRNAsskdeg

[0232]

[0233] mRNAmaxkdeg+ kreg

[0234] kreg is dependent on the average amount of RBP bound to the mRNA, which was modeled with a Hill binding function, n is the Hill coefficient indicating the degree of binding cooperativity and -DRBP is the binding affinity of RBP to mRNA:[RBP]n

[0235] kreg Kregmax_i_

[0236]

[0237] L J DRBP

[0238] An equation for the concentration of RBP in the cell given TMP concentration was also derived with the assumption that the addition of TMP directly inhibits the DHFR degron and controls the amount of stabilized RBP available to bind in the cell:

[0239] [RBP] > [TMP]

[0240] [RBP]max~ [TMP] + KDTMp- The equation above was fit using scipy.optimize.curve_fit() to extract Dntp, the dependence of RBP stabilization on TMP addition, from HaloTag staining data on DHFR-tagged MCPs at varying concentrations of TMP.

[0241] Therefore, kregcan be expressed as follows: )n

[0242] [TMP]

[0243] [TMP] + _

[0244] kreg ~ kregmaxn

[0245] [TMP]

[0246] + Kn

[0247]

[0248] [TMP] + KDTMP

[0249] where kreg_max is the maximum rate of RBP-mediated RNA degradation in units days1, K =Karbp(unitless) is the effective association rate of the RBP to RNA, and n is the Hill

[0250] KDDDrDmaxV Z’

[0251] coefficient.

[0252] Next, translation was incorporated into the model. An equation for the production of Citrine protein from mRNA was derived with the rates ktri, the constant rate of translation, and kdeg_protein, the constant rate of protein degradation and dilution:

[0253] dCitriTis

[0254] — — — = kM• mRNA - kdegproteln• Citrine.

[0255]

[0256] dCitrins

[0257] Solving the equation — — — = 0, the steady state Citrine level in the cell population was determined as shown below.

[0258] ktrlmRNAss

[0259] Citriness=

[0260] kdegprotein

[0261] ktriktrx

[0262] Citriness

[0263]

[0264] kdegprotein(kdeg + ^reg)

[0265] Citrine levels were assumed as maximum when kreg= 0. Therefore, Citriness / Citrinemax is equivalent to mRNAss / mRNAmax:Citrinesskdeg

[0266] Citrinemaxkdeg " kreg

[0267] The system of differential equations was solved with the initial condition Citrine(O) = Citrinemax to determine an equation for Citrine(t) / Citrinema:

[0268] Citrine(t) > kdegmRNAj kregCitrinemax(kdegmRNA+ kreg) (kdegmRNA~ kdegprotein+ kreg^

[0269] kreg ♦ kMlrrMn

[0270]

[0271] (.k<legmRNA+kreg} \ kdegmRNA~ kdegproteln+ kreg) The values of a, b, and n for DHFR-MCP-NANOS l_003 were extracted by fitting the equation for normalized steady-state Citrine levels using scipy.optimize.curve_fit() to normalized Citrine levels after 4 days of TMP addition and subsequent RBP recruitment, a, b, and n were substituted into the equation for kregand used this value to calculate normalized Citrine levels over time for varying TMP doses.

[0272] KRAB-dependent transcriptional silencing model First, the rate of Citrine degradation and dilution was estimated using the following equations fit to 5 days of KRAB recruitment and corresponding measurements of Citrine fluorescence:

[0273] dCitrine

[0274] dt= -Citrine • kdegcitrine

[0275] Citrine(t) = Citrinet=0• ekdegcitrine1

[0276] using scipy.optimize.curve_fit().

[0277] The change in Citrine fluorescence due to transcriptional silencing was derived from the following system of differential equations. A differential equation for the rate of silencing on the gene level dependent on ks, the rate of transcriptional silencing, was first derived:

[0278] dS

[0279] — = ks- (l - S).

[0280] at

[0281] The rate of transcriptional silencing was defined as dependent on dox concentration in an ultrasensitive manner with Hill coefficient n:

[0282] k = k [dox]n

[0283] S Ksmax•[dox]n + Kn ■

[0284]

[0285] L J udox

[0286] Differential equations describing transcription of genes in the active (non-silent) state and translation of the mRNA to Citrine were also derived as shown below.dmRNA

[0287] = ktrx• (1 - S) - kdegmRNA' mRNA

[0288] dCitriTis

[0289] — - — = ktrl• mRNA - kdegcltrlne• Citrine

[0290]

[0291] The system of differential equations was then solved with the initial condition Citrine(O) = Citrinemax to determine an equation for Citrine(t) / Citrinema:

[0292] C itrine (t) _ e~k^ kdegmRNAkdegcitrinecitrine1kdegmRNAksCitrinemax(kdegmRNA~ ks)(kdegcitrine ) KdegmRNA ^deg Citrine)^ <ieg c itrine,e~"'U‘mRM, kd> SCltrln.ks

[0293]

[0294] (kdeSmRHAkdffgcitrlnejCkd6SmRNAk^)‘ Scipy.optize.curve_fit() was used to fit the resulting function to 5 days of KRAB recruitment, and free parameters ks, ks,max, and n were extracted for each dox dose.

[0295] Stochastic Simulation of Simultaneous RBP-Mediated Degradation and KRAB Recruitment Stochastic simulations were performed according to the Gillespie algorithm.

[0296] Populations of n_cells were simulated expressing both an RBP RNA degrader and rTetR-KRAB repressor. During the active state, the reporter gene produced mRNA at rate kta. The reporter gene could become silenced at rate ksdependent on dox concentration. In all states, mRNA could be degraded at rate kreg dependent on TMP concentration. The base constants were chosen as follows: {ktrx: 50, kdeg: 2.39, kreg_ma: 10.8, b:0.99, HRBP: 0.72, s_ma:2.1, UKRAB: 2.7, kA_TMp:1.19, kA_doX:7.8}.

[0297] Data Analysis and Statistics Statistical analyses were performed in Python using the SciPy package, are two-sided (unless otherwise stated), and are indicated in text or figures / figure legends. “N” for each analysis is indicated in the text, figures, or legends where appropriate. No methods were used to determine whether the data met assumptions of the statistical approach.

[0298] Data and code availability Raw HT-recruit and CUT& RUN sequencing files (FATSQ) have been deposited at NCBI SRA. All other data reported herein will be shared upon request. Any additional information required to reanalyze the data reported in this paper is available upon request.Table 1

[0299] Protein domain sequence SEQID minimized sequence SEQID Representative high activity SEQID type NO NO tile sequence NO CHTOP 375' MAAQSAPKWLKSTTKMSLNERFTN 1 MAAQSAPKWLKSTTKMS 120

[0300] MLKNKQPTPVNIRASMQQQQQLASAR LNERFTNMLKNKQPTPVNI NRRLAQQMENRPSVQAALKLKQSLK RASMQQQQQLASARNRRL QRLGKSNIQARLGR AQQMENRPSVQAALKLKQ SLKQRLG NANOS1 375' MEAFPWAPRSPRRGRAPPPMALVPSA 2 PRRGRAPPPMALVPSARYV 121

[0301] RYVSAPGPAHPQPFSSWNDYLGLATLI SAPGPAHPQPFSSWNDYLG TKAVDGEPRFGCARGGNGGGGSPPSS LATLITKAVDGEPRFGCAR SSSSCCSPHTGAGPGALGPALGPPDYD GGNGGGGSPPSSSSSSCCSP EDDD HTG CNOT4 3' TESQSLFSDNFRHPNPIPSGLPPFPSSPQ 3 DDLGFDPFDV 239 LPPFPSSPQTSSDWPTAPEP 122

[0302] TSSDWPTAPEPQSLFTSETIPVSSSTDW QSLFTSETIPVSSSTDWQAA QAAFGFGSSKQPEDDLGFDPFDVTRK FGFGSSKQPEDDLGFDPFD ALADLIEKELSVQDQPSLSPTSLQNSSS VTRKALADLIEKELSVQDQ HTTTAKGPGNANSLNSTFSVLPQRFPQ PS FQ SNRPB 375' KSSKMLQHIDYRMRCILQDGRIHGTF 4 KSSKMLQHIDYRMRCILQD 123

[0303] KAFDKHMNLILCDCDEFRKIKPKNSK GRIFIGTFKAFDKHMNLILC QAEREEKRVLGLVLLRGENLVSMTVE DCDEFRKIKPKNSKQAERE G EKRVLGLVLLRGENLVSMT VEG CSTF2 375’ GAWPQGSRQVPVMQGTGMQGASIQ 5 SRQVPVMQGTGMQGASIQ 124

[0304] GGSQPGGFSPGQNQVTPQDHEKAALI GGSQPGGFSPGQNQVTPQ MQVLQLTADQIAMLPPEQRQSILILKE DHEKAALIMQVLQLTADQI QIEQIQKSTGAP AMLPPEQRQSILILKEQIQK STGAP SETD1A 3' SRAGGRGRLTEEEEAEPGTEVDLAVLA 6 VDLAVLADLALTP 240 SRAGGRGRLTEEEEAEPGT 125

[0305] DLALTPARRGLPALPAVEDSEATETSDE ARRGLPALPAVEDS EVDLAVLADLALTPARRGL AERPRPLLSHILLEHNYALAVKPTPPAP EATETSDEAERPRP PALPAVEDSEATETSDEAER ALRPPEPVPAPAALFSS LLSHILLEHNYALA PRPLLSHILLEHNYALAVKP VKPTP TP LSM4 375' MLPLSLLKTAQNHPMLVELKNGETYN 7 MLPLSLLKTAQNHPMLVEL 126

[0306] GHLVSCDNWMNINLREVICTSRDGDK KNGETYNGHLVSCDNWM

[0307]

[0308] FWRMPECYIRGSTIKYLRIPDEnDMVK NINLREVICTSRDGDKFWRMPECYIRGSTIKYLRIPDEn DMVK SNRPD1 375' MKLVRFLMKLSHETVTTELKNGTQVH 8 MKLVRFLMKLSHETVTIEL 127

[0309] GTITGVDVSMNTHLKAVKMTLKNREP KNGTQVHGTITGVDVSMN VQLETLSIRGNNIRYFILPDSLPLDTLL THLKAVKMTLKNREPVQL ETLSIRGNNIRYFILPDSLPL DTLL SNRPN 375' KSSKMLQHIDYRMRCILQDGRIHGTF 9 KSSKMLQHIDYRMRCILQD 128

[0310] KAFDKHMNLILCDCDEFRKIKPKNAK GRIFIGTFKAFDKHMNLILC QPEREEKRVLGLVLLRGENLVSMTVE DCDEFRKIKPKNAKQPERE G EKRVLGLVLLRGENLVSMT VEG CN0T2 3' STDGPKFPGDKSSTTQNNNQQKKGIQ 10 VTDQFGMIGLLTFI 241 GRVTNIPQGMVTDQFGMIG 129

[0311] VLPDGRVTNIPQGMVTDQFGMIGLLTF RAAETDPGMVHLA LLTHRAAETDPGMVHLAL IRAAETDPGMVHLALGSDLTTLGLNL LGSDLTTLGLNLN GSDLTTLGLNLNSPENLYP NSPENLYPKFASPWASSPCRPQDIDFHV KFASPWASSPCRPQDIDFH PSEYLTNIHTRDK VPSE DZIP3 3' WRPLTSQGPATWEGASNPDEEEEEEEP 11 WRPLTSQGPATWEGASNPD 130

[0312] CVICHENLSPENLSVLPCAHKFHAQCI EEEEEEEPCVICHENLSPEN RPWLMQQGTCPTCRLHVLLPEEFPGH LSVLPCAHKFHAQCIRPWL MQQGTCPTCRLHVLLPEEF PGH EIF2AK2 375' SVKSDYLSSGSFATTCESQSNSLVTSTL 12 SLNSSSLLMNGLR 242 DTSEINSNSDSLNSSSLLMN 131

[0313] ASESSSEGDFSADTSEINSNSDSLNSSS NNQRKAKRSLAPR GLRNNQRKAKRSLAPRFD LLMNGLRNNQRKAKRSLAPRFDLPD FDLP LPDMKETKYTVDKRFGMD MKETKYTVDKRFGMDFKEIELIGSGG FKEIELIGSGGFGQVFKAK FGQVFKAKHRIDGKTYVIKRVKY HRIDG ANKRD17 3' SPAPSSVPLGSEKPSNVSQDRKVPVPIG 13 RKVPVPIGTERSAR 243 RKVPVPIGTERSARIRQTGT 132

[0314] TERSARIRQTGTSAPSVIGSNLSTSVGH IRQTGTSAPSVIGS SAPSVIGSNLSTSVGHSGIW SGIWSFEGIGGNQDKVDWCNPGMGNP NLSTSVGHSGIWSF SFEGIGGNQDKVDWCNPG MIHRPMSDPGVFSQHQAM EGIGGNQDKVDW MGNPMIHRPMSDPGVFSQ CNPGMG HQAM ZFP36L2 3' APPSATLPAGAAAPPSPPFSFQLPRRLS 14 APPSATLPAGAAAPPSPPFS 133

[0315] DSPVFDAPPSPPDSLSDRDSYLSGSLSS FQLPRRLSDSPVFDAPPSPP GSLSGSESPSLDPGRRLPIFSRLSIFSRL DSLSDRDSYLSGSLSSGSLS SISDD GSESPSLDPGRRLPIFSRLS SYNE1 3' QEKWKSASMRLEEQKKKLAFLLKDW 15 GIADSLEKLRTFKK 244 LLKDWEKCEKGIADSLEKL 134

[0316] EKCEKGIADSLEKLRTFKKKLSQSLPD KLSQSLPDHHEEL RTFKKKLSQSLPDHHEELH HHEELHAEQMRCKELENAVGSWTDD HAEQMRCKELENA AEQMRCKELENAVGSWTD

[0317]

[0318] VGSWTDDLTQLTQLSLLKDTLSAYISADDISILNERVEL DLTQLSLLKDTLSAYISADD LQRQ ISIL RBM7 375' EADRTLFVGNLETKVTEELLFELFHQA 16 EADRTLFVGNLETKVTEEL 135

[0319] GPVIKVKIPKDKDGKPKQFAFVNFKHE LFELFHQAGPVIKVKIPKD VSVPYAMNLLNGIKLYGRPIKIQFRS KDGKPKQFAFVNFKHEVS VPYAMNLLNGIKLYGRPIKI QFRS ZFP36 3' PVCCPSCRRATPISVWGPLGGLVRTPS 17 PVCCPSCRRATPISVWGPL 136

[0320] VQSLGSDPDEYASSGSSLGGSDSPVFE GGLVRTPSVQSLGSDPDEY AGVFAPPQPVAAPRRLPIFNRISVSE ASSGSSLGGSDSPVFEAGV FAPPQPVAAPRRLPIFNRISV SE LSM14A 375' GTPYIGSKISLISKAEIRYEGILYTTDTEN 18 GTPYIGSKISLISKAEIRYEG 137

[0321] STVALAKVRSFGTEDRPTDRPIPPRDE ILYTTDTENSTVALAKVRSF VFEYIIFRGSDIKDLTVCEPPKP GTEDRPTDRPIPPRDEVFEY IIFRGSDIKDLTVCEPPKP CHD2 3' LGKKGATGASTTVYAIEANGDPSGDF 19 KVKGLKKLENFKK 245 WESEESLQQQKVKGLKKL 138

[0322] DTEKDEGEIQYLIKWKGWSYIHSTWE KEDEIKQ ENFKKKEDEIKQWLGKVS SEESLQQQKVKGLKKLENFKKKEDEI PEDVEYFNCQQELASELNK KQWLGKVSPEDVEYFNCQQELASELN QYQIVERVIAVKTSKSTLG KQYQIVERVIAVKTSKSTLGQTDFPAH QTDFPA SRKPAPSNE

[0323] P0P1 3' WIPHYRGVRVGGLKESAVHSQYKRSP 20 LFAEEQAKNLLEK 246 WIPFIYRGVRVGGLKESAV 139

[0324] NVPGDFPDCPAGMLFAEEQAKNLLEK YKRRPPAKRPNYV HSQYKRSPNVPGDFPDCPA YKRRPPAKRPNYVKLGTLAPFCCPWE KLGTLAPFCCPWE GMLFAEEQAKNLLEKYKR QLTQDWESRVQAYEEPSVASSPNGKES Q RPPAKRPNYVKLGTLAPFC DLRRSEVPCAPMPK CPWEQ TEP1 3' QFDEYQLAKYNPRKHRAKRHPRRPPR 21 SEKKNPPRFTLKKL 247 RYIGFLREEQRKFEKAGDT 140

[0325] SPGMEPPFSHRCFPRYIGFLREEQRKFE VQRLH1 VSEKKNPPRFTLKKLVQRL KAGDTVSEKKNPPRFTLKKLVQRLHTH HIHKPAQHVQALLGYRYPS KPAQHVQALLGYRYPSNLQLFSRSRLP NLQLFSRSRLPGPWDSSRA GPWDSSRAGKRMKLSRPETWERELSL GKRM RGNKAS TRIM39 375' MAETSLLEAGASAASTAAALENLQVE 22 ASAASTAAALENLQVEASC 141

[0326] ASCSVCLEYLKEPVHECGHNFCKACrr SVCLEYLKEPVIIECGHNFC RWWEDLERDFPCPVCRKTSRYRSLRP KACITRWWEDLERDFPCPV NRQLGSMVEIAKQLQAVKRK CRKTSRYRSLRPNRQLGSM VEI TRIM25 375' MAELCPLAEELSCSICLEPFKEPVTTPC 23 MAELCPLAEELSCSICLEPF 142

[0327]

[0328] GHNFCGSCLNETWAVQGSPYLCPQCR KEPVTTPCGHNFCGSCLNEAVYQARPQLHKNTVLCNVVEQFLQA TWAVQGSPYLCPQCRAVY D QARPQLHKNTVLCNWEQ FLQAD CHERP 3' GQPPHMRRQGPPHINHDDPSLVPNVPY 24 LEDHEYKPLDPKDI 248 PPHINHDDPSLVPNVPYFDL 143

[0329] FDLPAGLMAPLVKLEDHEYKPLDPKDI RLPPPMPPSERLLA PAGLMAPLVKLEDHEYKPL RLPPPMPPSERLLAAVEAFYSPPSHDRP AVEAFYSPPSHD DPKDIRLPPPMPPSERLLAA RNSEGWEQNGLYEFFRAKMRARRRK VEAFYSPPSHDRPRNSEGW GQEKRNSGPSRSR EQ FIP1L1 3' NIKTGGRVYGTTGTKVKGVDLDAPGS 25 EDKPWRKPGADLS 249 TTGTKVKGVDLDAPGSING 144

[0330] INGVPLLEVDLDSFEDKPWRKPGADLS DYFNYGFNEDTW VPLLEVDLDSFEDKPWRKP DYFNYGFNEDTWKAYCEKQKRIRMG KAYCEKQKRIRMG GADLSDYFNYGFNEDTWK LEVIPVTSTTNKITAEDCTMEVTPGAEI LE AYCEKQKRIRMGLEVIPVT QDGRFNLFKVQQGR STTNK SETD1A 3' MDQEGGGDGQKAPSFQWRNYKLIVD 26 MDQEGGGDGQKAPSFQW 145

[0331] PALDPALRRPSQKVYRYDGVHFSVND RNYKLIVDPALDPALRRPS SKYIPVEDLQDPRCHVRSKNRDFSLPV QKVYRYDGVHFSVNDSKY PK IPVEDLQDPRCHVRSKNRD FSLPVPK HLTF 3' PSGNDTPEELRKKLIRKMKLILSSGSDE 27 ILSSGSDEECAICL 250 ILSSGSDEECAICLDSLTVP 146

[0332] ECAICLDSLTVPVITHCAHVFCKPCICQ DSLTVPVITHCAHV VITHCAHVFCKPCICQVIQ VIQNEQPHAKCPLCRNDIHEDNLLECP FCKPCICQVIQNEQ NEQPHAKCPLCRNDIHEDN PEELARDSEKKSDMEWT PHAKCPLCRNDIH LLECPPEELARDSEKKSDM EDNLL EWT CSTF2 375' PEDAPESISKAVASLPPEQMFELMKQM 28 AVASLPPEQMFEL 251 AVASLPPEQMFELMKQMK 147

[0333] KLCVQNSPQEARNMLLQNPQLAYALL MKQMKLCVQNSP LCVQNSPQEARNMLLQNP QAQWMRIVDPEIALKILHRQTNIPTLI QEARNMLLQNPQL QLAYALLQAQWMRIVDP AGNPQPVHG AYALLQAQVVMRI EIALKILHRQTNIPTLIAGNP VDPEIALKILHRQT QPVHG NIPTL SETD1A 3' EEEEESSDSSSSSDGEGALRRRSLRSHA 29 PPRAYEPRSEFEQM 252 SSSDGEGALRRRSLRSHAR 148

[0334] RRRRPPPPPPPPPPRAYEPRSEFEQMTTL TILYDIWNSGLDSE RRRPPPPPPPPPPRAYEPRSE YDIWNSGLDSEDMSYLRLTYERLLQQ DMSYLRLTYERL FEQMTILYDIWNSGLDSED TSGADWLNDTHWVHHTITNLTTPKRK MSYLRLTYERLLQQTSGAD RRPQDGPREHQ WL PKN2 3' LVGESPFPGDDEEEVFDSIVNDEVRYP 30 NDEVRYPRFLSTE 253 DEEEVFDSIVNDEVRYPRF 149

[0335] RFLSTEAISIMRRLLRRNPERRLGASEK AISIMRRLLRRNPE LSTEAISIMRRLLRRNPERR DAEDVKKHPFFRLIDWSALMDKKVKP RRLGASEKDAEDV LGASEKDAEDVKKHPFFRL PFIPTIRGREDVSNFDDEF KKHPFFRLIDWSA IDWSALMDKKVKPPFIPTIR

[0336]

[0337] LMDKKVK GRADAR 3' VNHPKVGRVSIYDSKRQSGKTKETSV 31 TKETSVNWCLADGYDLEIL 150 NWCLADGYDLEILDGTRGTVDGPRNE DGTRGTVDGPRNELSRVSK LSRVSKKNIFLLFKKLCSFRYRRDLLRL KNIFLLFKKLCSFRYRRDLL SYGEAKKAARDYETAKNYFKKGLKD RLSYGEAKKAARDYETAK MGYGNWISKPQEEKNEEKNFYLCPV NYFK SRP68 3' FNKCKTIYEKLASAFTEEQAVLYNQRV 32 VLYNQRVEEISPNI 254 LASAFTEEQAVLYNQRVEEI 151

[0338] EEISPNIRYCAYNIGDQSAINELMQMRL RYCAYNIGDQSAIN SPNIRYCAYNIGDQSAINEL RSGGTEGLLAEKLEALITQTRAKQAAT ELMQMRLRSGGTE MQMRLRSGGTEGLLAEKL MSEVEWRGRTVPVKIDKV GLLAEKLEALITQT EALITQTRAKQAATMSEVE RAKQA WRG SETD1A 3' PVEVPVPERVAGSPVTPLPEQEASPARP 33 QEASPARPAGPTEE 255 QEASPARPAGPTEESPPSAP 152

[0339] AGPTEESPPSAPLRPPEPPAGPPAPAPRP SPPSAPLRPPEPPAG LRPPEPPAGPPAPAPRPDER DERPSSPIPLLPPPKKRRKTVSFSAIEVV PPAPAPRPDERPSSP PSSPIPLLPPPKKRRKTVSFS PAPEPPPATPPQAK IPLLPPPKKRRKTV AIEWPAPEPPPATPPQAK SF RPS9 3' KTYVTPRRPFEKSRLDQELKLIGEYGL 34 EKSRLDQELKLIGE 256 KTYVTPRRPFEKSRLDQEL 153

[0340] RNKREVWRVKFTLAKIRKAARELLTL YGLRNKREVWRV KLIGEYGLRNKREVWRVK DEKDPRRLFEGNALLRRLVRIGVLDEG KFTLAKIRKAAREL FTLAKIRKAARELLTLDEK KMKLDYILGL LTLDEKDPRRLFEG DPRRLFEGNALLRRLVRIG NALLRRLVRIGVL VLDEG DEG HLTF 3' NSLKDLWSLLSFLKLKPFIDREWWHR 35 PVTMGDEGGLRRL 257 SFLKLKPFIDREWWHRTIQ 154

[0341] TIQRPVTMGDEGGLRRLQSLIKNITLR QSLIKNITLRRTKTS RPVTMGDEGGLRRLQSLIK RTKTSKIKGKPVLELPERKVFIQHITLS KIKGKPVLELPERK NITLRRTKTSKIKGKPVLEL DEERKIYQSVKNEGRATIGRYFNEGTV VFIQHITL PERKVHQHITLSDEERKIY LA QS LSM1 375' YMPGTASLIEDIDKKHLVLLRDGRTLI 36 YMPGTASLIEDIDKKHLVL 155

[0342] GFLRSIDQFANLVLHQTVERIHVGKKY LRDGRTLIGFLRSIDQFANL GDIPRGIFVVRGENWLLGEIDLEKE VLHQTVERIHVGKKYGDIP RGIFWRGENWLLGEIDL EKE MARK2 3' SAHNISSSGGAPDRTNFPRGVSSRSTFH 37 SGSIFSKFTSKFVR 258 SGSIFSKFTSKFVRRNLSFR 156

[0343] AGQLRQVRDQQNLPYGVTPASPSGHS RNLSFR FARRNLNEPESKDRVETLR QGRRGASGSIFSKFTSKFVRRNLSFRFA PHWGSGGNDKEKEEFRE RRNLNEPESKDRVETLRPHWGSGGN AKPRSLRFTWSMKTTSSM DKEKEEFREAKPRSLRFTWSMKTTSS EPNEM MEPNEM PRRC2C 3' QDKPPRFRRLREREAASKSNEWAVPT 38 EWAVPTNGTVNN 259 EWAVPTNGTVNNVAQEPV 157

[0344] NGTVNNVAQEPVNTLGDISGNKTPDL VAQEPVNTLGDISG NTLGDISGNKTPDLSNQNS

[0345]

[0346] NKTPDLSNQNSSD SDQANEEWETASESSDFNESNQNSSDQANEEWETASESSDFNERRE QANEEWETASESS RRERDEKKNADLNAQTVV AQTWKVGEN DFNERRE KVGEN SETD1B 3' EPLAKEKPGTPPGPPPPDTNSMELGGR 39 GPEKPHDSLDSRIE 260 EPLAKEKPGTPPGPPPPDTN 158

[0347] PTFGWSPEPCDSPGTPTLESSPAGPEKP MLLKEQRTKLLFL SMELGGRPTFGWSPEPCDS HDSLDSRIEMLLKEQRTKLLFLREPDS REP PGTPTLESSPAGPEKPHDSL DTELQMEGSPISSSSSQLSPLAPFGTNS DSRIEMLLKEQRTKLLFLR QPGFRGPTPPSSRPSSTGLE EP ZFP36 375' MDLTAIYESLLSLSPDVPVPSDHGGTES 40 MDLTAIYESLLSLSPDVPVP 159

[0348] SPGWGSSGPWSLSPSDSSPSGVTSRLP SDHGGTESSPGWGSSGPW GRSTSLVEGRSCGWVPPPPGFAPLA SLSPSDSSPSGVTSRLPGRS TSLVEGRSCGWVPPPPGFA PLA PLEC 3' LLERWQAVLAQTDVRQRELEQLGRQL 41 QLGRQLRYYRESA 261 QLGRQLRYYRESADPLGA 160

[0349] RYYRESADPLGAWLQDARRRQEQIQA DPLGAWLQDARRR WLQDARRRQEQIQAMPLA MPLADSQAVREQLRQEQALLEEIERH QEQIQAMPLADSQ DSQAVREQLRQEQALLEEI GEKVEECQRFAKQYINAIKDYE AVREQLRQEQALL ERHGEKVEECQRFAKQYIN EEIERHGE AIKDYE UPF3B 3' EEMKKEKDTLRDKGKKAESTESIGSSE 42 EEMKKEKDTLRDKGKKAE 161

[0350] KTEKKEEVVKRDRIRNKDRPAMQLYQ STESIGSSEKTEKKEEWKR PGARSRNRLCPPDDSTKSGDSAAERK DRIRNKDRPAMQLYQPGA QISHRKEGGEE RSRNRLCPPDDSTKSGDSA AERKQ MTPAP 3' SQSQLQKFVDLARESAWILQQEDTDR 43 LARESAWILQQEDTDRPSIS 162

[0351] PSISSNRPWGLVSLLLPSAPNRKSFTKK SNRPWGLVSLLLPSAPNRK KSNKFAIETVKNLLESLKGNRTENFTK SFTKKKSNKFAIETVKNLL TSGKRTTSTSGKRTTSTQT ESLKGNRTENFTKTSGKRTI ST NUSAP1 3' AKSLGLRANLRATKLLKALKGYIKHE 44 RATKLLKALKGYI 262 RATKLLKALKGYIKHEARK 163

[0352] ARKGNENQDESQTSASSCDETEIQISN KHEARKGNENQDE GNENQDESQTSASSCDETE QEEAERQPLGHVTKTRRRCKTVRVDP SQTSASSCDETEIQI IQISNQEEAERQPLGHVTK DSQQNHSEIKI SNQEEAERQPLGH TRRRCKTVRVDPDSQQNH VTKTRRRCKTVRV SEIKI DPD HNRNPU 3' AAGKTTWAIKHAASNPSKKYNILGTN 45 KMRVMGLRRQRN 263 NILGTNAIMDKMRVMGLR 164 LI AIMDKMRVMGLRRQRNYAGRWDVLI YAGRWDVLIQQAT RQRNYAGRWDVLIQQATQ QQATQCLNRLIQIAARKKRNYILDQTN QCLNRLIQIAARKK CLNRLIQIAARKKRNYILD VYGSAQRRKMRPFEGFQRKAIVICPTD RNYILDQTNVY QTNVYGSAQRRKMRPFEG EDLKD FQRKAIV ADARB2 3' WWGSADLEIINATTGRRSCGGPSRLC 46 INATTGRRSCGGPSRLCKH 165

[0353]

[0354] KHVLSARWARLYGRLSTRTPSPGDTPS VLSARWARLYGRLSTRTPSMYCEAKLGAHTYQSVKQQLFKAFQK PGDTPSMYCEAKLGAHTY AGLGTWVRKPPPEQQQFLLTL QSVKQQLFKAFQKAGLGT WVRKPP DDX42 3' HGENRHGGSAGRHGENRGANDGRNG 47 HGENRHGGSAGRHGENRG 166

[0355] ESRKEAFNRESKMEPKMEPKVDSSKM ANDGRNGESRKEAFNRES DKVDSKTDKTADGFAVPEPPKRKKSR KMEPKMEPKVDSSKMDK WDS VDSKTDKTADGFAVPEPPK RKKSRWDS HUWE1 3' ASSESSSTRDSAVAISGADSRGILEEPLP 48 RGILEEPLPSTSSEE 264 ASSESSSTRDSAVAISGADS 167

[0356] STSSEEEDPLAGISLPEGVDPSFLAALP EDPLAGISLPEGVD RGILEEPLPSTSSEEEDPLA DDIRREVLQNQLGIRPPTRTAPSTNSSA PSFLAALPDDIRRE GISLPEGVDPSFLAALPDDI PAWGNPGVTEVSPE VLQNQLGIRPPTRT RREVLQNQLGIRPPTRTAPS APS PTCD3 3' INSYPKYFQKDIAEPHTPCLMPEYFEPQ 49 MPEYFEPQIKDISE 265 INSYPKYFQKDIAEPHIPCL 168

[0357] IKDISEAALKERIELRKVKASVDMFDQ AALKERIELRKVK MPEYFEPQIKDISEAALKER LLQAGTTVSLETTNSLLDLLCYYGDQ ASVDMFDQLLQA IELRKVKASVDMFDQLLQ EPSTDYHFQQTGQSEALEE GTTVSLETTNSLLD AGTTVSLETTNSLLDLLCY LLCYYGD YGD RTN4 3' DKKCFADSLEQTNHEKDSESSNDDTSF 50 ATESIATNIFPLLGD 266 PEGIKDRSGAYITCAPFNPA 169

[0358] PSTPEGIKDRSGAYITCAPFNPAATESIA PTSENKTDEKKIEE ATESIATNIFPLLGDPTSENK TNIFPLLGDPTSENKTDEKKIEEKKAQI K TDEKKIEEKKAQIVTEKNT VTEKNTSTKTSNPFLVAAQDSETDYVT STKTSNPFLVAAQDSETDY TDNLTKVTEEWANMPEGL V CPEB2 3' SWIEDNVFRTDNNSNTLLPLQVRSSLQ 51 WGSDSLQDSWCTA 267 SWIEDNVFRTDNNSNTLLP 170

[0359] LPAWGSDSLQDSWCTAAGTSRIDQDR AGTSRIDQDRSRM LQVRSSLQLPAWGSDSLQD SRMYDSLNMHSLENSLIDIMRAEHDPL YDSLNMHSLENSLI SWCTAAGTSRIDQDRSRM KGRLSYPHPGTDNLLMLNGRSSLFPID DIMRAEHDPL YDSLNMHSLENSLIDIMRA DGL EHDPL SAMD4A 3' PTIMKQGRQNLWFANPGGSNSMPSRT 52 PTTMKQGRQNLWFANPGG 171

[0360] HSSVQRTRSLPVHTSPQNMLMFQQPEF SNSMPSRTHSSVQRTRSLP QLPVTEPDINNRLESLCLSMTEHALGD VHTSPQNMLMFQQPEFQL GDGVDRTSTT PVTEPDINNRLESLCLSMTE HALGD HDLBP 3' IGPKGNSLQEILERTGVSVEIPPSDSISE 53 GQALTEVYAKANS 268 ILERTGVSVEIPPSDSISETVI 172

[0361] TVTLRGEPEKLGQALTEVYAKANSFTV FTVSSVAAPSWLH LRGEPEKLGQALTEVYAKA SSVAAPSWLHRFnGKKGQNLAKITQQ RFIIGKKGQNLAKI NSFTVSSVAAPSWLHRFnG MPKVHIEFTEGEDKITLEGPTEDVNVA KKGQNLAKITQQMPKVHI QEQIEGMVKD E TRNAU1A 3' GYDQNTGSYSYSYPQYGYTQSTMQT 54 GYDQNTGSYSYSYPQYGY 173

[0362]

[0363] P YEEVGDDALEDPMPQLDVTEANKEF TQSTMQTYEEVGDDALEDMEQSEELYDALMDCHWQPLDTVSSEI PMPQLDVTEANKEFMEQS PAMM EELYDALMDCHWQPLDTV SSEIPAMM UPF2 3' FCRHCGDDIAGLVPRKVKSAAEKFNLS 55 GLVPRKVKSAAEK 269 GLVPRKVKSAAEKFNLSFP 174

[0364] FPPSEnSPEKQQPFQNLLKEYFTSLTKH FNLSFPPSEIISPEK PSEnSPEKQQPFQNLLKEY LKRDHRELQNTERQNRRILHSKGELSE QQPFQNLLKEYFT FTSLTKHLKRDHRELQNTE DRHKQYE SLTKHLKRDHREL RQNRRILHSKGELSEDRHK QNTERQNRRILHS QYE KGE HSPB1 3' MTERRVPFSLLRGPSWDPFRDWYPHS 56 MTERRVPFSLLRGPSWDPF 175

[0365] RLFDQAFGLPRLPEEWSQWLGGSSWP RDWYPHSRLFDQAFGLPR GYVRPLPPAAIESPAVAAPAYSRALSRQ LPEEWSQWLGGSSWPGYV LSSGVSEIRHTADRWRVSLD RPLPPAAIESPAVAAPAYSR ALSRQ EIF4G1 3' VLEPGSEPNLAVLSIPGDTMTTIQMSV 57 TTIQMSVEESTPISR 270 VLEPGSEPNLAVLSIPGDTM 176

[0366] EESTPISRETGEPYRLSPEPTPLAEPILE ETGEPYRLSPEPTP TTIQMSVEESTPISRETGEP VEVTLSKPVPESEFSSSPLQAPTPLASH LAEPILEVEVTLSK YRLSPEPTPLAEPILEVEVT TVEIHEPNGMVPSEDL PVPESEFSSSPLQA LSKPVPESEFSSSPLQAPTP PTP SAMD4A 3' YLQLIDKCLIHEAFTETQKKRLLSWKQ 58 RLLSWKQQVQKLF 271 HEAFTETQKKRLLSWKQQ 177

[0367] QVQKLFRSFPRKTLLDISGYRQQRNRG RSFPRKTLLDISGY VQKLFRSFPRKTLLDISGY FGQSNSLPTAGSVGGGMGRRNPRQYQ RQQRNRGFGQSNS RQQRNRGFGQSNSLPTAGS IPSRNVPSARLGLLGTSGFV LPTAGSVGGGMGR VGGGMGRRNPRQYQIPSR RNPRQYQ NVPSAR DNAJC21 375' MKCHYEALGVRRDASEEELKKAYRK 59 MKCHYEALGVRRDASEEE 178

[0368] LALKWHPDKNLDNAAEAAEQFKLIQA LKKAYRKLALKWHPDKNL AYDVLSDPQERAWYDNHREALLKGG DNAAEAAEQFKLIQAAYD EDGE VLSDPQERAWYDNHREAL LKGGFDGE TNRC6B 3' KFPDYKSTWSPDPIGHNPTHLSNKMW 60 PDPIGHNPTHLSNK 272 PDPIGHNPTHLSNKMWKN 179

[0369] KNHTSSRNTTPLPRPPPGLTNPKPSSPW MWKNHISSRNTTP HISSRNTTPLPRPPPGLTNP SSTAPRSVRGWGTQDSRLASASTWSD LPRPPPGLTNPKPS KPSSPWSSTAPRSVRGWGT GGSVRPSYWL SPWSSTAPRSVRG QDSRLASASTWSDGGSVR WGTQDSRLASAST PSYWL WSD TDRD5 3' QDLLVFDADKKPLPPVQSDKKIEAKA 61 KPLPPVQSDKKIEA 273 KPLPPVQSDKKIEAKACVS 180

[0370] CVSSPPRNSLSTAAVKETVWNCPSKKQ KACVSSPPRNSLST SPPRNSLSTAAVKETVWNC KEPQQKICKKPNLWKPLQLQVETNKS AAVKETVWNCPSK PSKKQKEPQQKICKKPNLV ELNLAMANHD KQKEPQQKICKKP VKPLQLQVETNKSELNLA

[0371]

[0372] MANHDNLWKPLQLQVET

[0373] NKS SETD1A 3' EAPPPEPPEPGGGGGGGGPSPEREEVR 62 PAPETTNESVPFAQ 274 RPASPARSGSPAPETTNESV 181

[0374] TSPRPASPARSGSPAPETTNESVPFAQH HSSLDSRIEMLLKE PFAQHSSLDSRIEMLLKEQ SSLDSRIEMLLKEQRSKFSFLASDTEEE QRSKFSFLASDT RSKFSFLASDTEEEEENSS EENSSMVLGARDTGSEVPSGSGHGPC MVLGARDTGSEVPSGSGH TPPPAPANFEDVAPTGSGEPGATRESPK GPCT ANGQNQASPCSSGDDMEISDDDRGGS PPPAPTPPQQPPPPPPP POLQ 3' DTSFSLQLSQDGLQLTPASSSSESLSnD 63 SSESLSIIDVASDQN 275 DTSFSLQLSQDGLQLTPASS 182

[0375] VASDQNLFQTFIKEWRCKKRFSISLAC LFQTFIKEWRCKK SSESLSnDVASDQNLFQTH EKIRSLTSSKTATIGSRFKQASSPQEIPIR RFSISLACEKIRSLT KEWRCKKRFSISLACEKIR DDGFPIKGCDDTLV SSKTATIGSRFKQA SLTSSKTATIGSRFKQASSP SSP SEC23IP 3' LPTCKGFFNIYHPLDPVAYRLEPMIVPD 64 LKAVLIPHHKGRK 276 LPTCKGFFNIYHPLDPVAYR 183

[0376] LDLKAVLIPHHKGRKRLHLELKESLSR RLHLELKESLSRM LEPMIVPDLDLKAVLIPHH MGSDLKQGFISSLKSAWQTLNEFARA GSDLKQGHSSLKS KGRKRLHLELKESLSRMGS HTSSTQLQEELEKVANQIKEEEEKQW AWQTLNEFAR DLKQGHSSLKSAWQTLNE EA FAR HSP90AB 3' PEYLNFIRGVVDSEDLPLNISREMLQQ 65 SREMLQQSKILKVI 277 SREMLQQSKILKVIRKNIV 184 1 SKILKVIRKNIVKKCLELFSELAEDKEN RKNIVKKCLELFSE KKCLELFSELAEDKENYKK YKKFYEAFSKNLKLGIHEDSTNRRRLS LAEDKENYKKFYE FYEAFSKNLKLGIHEDSTN ELLRYHTSQSGDEMTSLS AFSKNLKLGIHEDS RRRLSELLRYHTSQSGDEM TNRRR TSLS DZIP3 3' PTEDEDLPTTFKDLLNNHKTTESNIMK 66 ICSYLDCERSCEAD 278 TTESNIMKQTICSYLDCERS 185

[0377] QTICSYLDCERSCEADILKNTSYKGFF ILKNTSYKGFFQL CEADILKNTSYKGFFQLMC QLMCSKSCCVYFHKICWKKFKNLKYP MCSKSCCVYFHKI SKSCCVYFHKICWKKFKN GENDQSFSGKKCLKEGCTGDMVRML CWKKFKNLKY LKYPGENDQSFSGKKCLKE QCDV GCTG TNRC6C 3' IKSTWSSGPTSHTQASLSHELWKVPRN 67 LWKVPRNSTAPTR 279 SHTQASLSHELWKVPRNST 186

[0378] STAPTRPPPGLTNPKPSSTWGASPLGW PPPGLTNPKPSSTW APTRPPPGLTNPKPSSTWG TSSYSSGSAWSTDTSGRTSSWLVLRNL GASPLGWTSSYSS ASPLGWTSSYSSGSAWSTD TPQIDGSTLRTLCLQHGPL GSAWSTDTSGRTSS TSGRTSSWLVLRNLTPQIDG WLVLRN STL TUT1 3' PVAGGLPSNLWEGLRLGPLNLQDPFDL 68 WEGLRLGPLNLQD 280 PVAGGLPSNLWEGLRLGPL 187

[0379] SHNVAANVTSRVAGRLQNCCRAAANY PFDLSHNVAANVT NLQDPFDLSHNVAANVTSR CRSLQYQRRSSRGRDWGLLPLLQPSSP SRVAGRLQNCCRA VAGRLQNCCRAAANYCRS SSLLSATPIP AANYCRSLQYQRR LQYQRRSSRGRDWGLLPL SSRGRDWGLLPLL LQPSSP

[0380]

[0381] QPSSPSETD1B 3' GPRPPPEPGPPDPAGLLSQTAEVALDLV 69 WTPGAAAVAAPS 281 RTPTSEKMDEGQQSSGED 188 GDRTPTSEKMDEGQQSSGEDMEISDD VLAPTLPLPPPPGF MEISDDEMPSAPITSADCP EMPSAPITSADCPKPMVVTPGAAAVAA PPL KPMWTPGAAAVAAPSVL PSVLAPTLPLPPPPGFPPLPPPPPPPPPQP APTLPLPPPPGFPPLPPPPPP GFPMPPPLPPPPPPPPPAHPAVTVPPPPL PPPQ PAPPGVPPPPGLFPVMQVDM SEC63 3' YKVSKTDREYQEYNPYEVLNLDPGAT 70 QEYNPYEVLNLDP 282 YKVSKTDREYQEYNPYEV 189

[0382] VAEIKKQYRLLSLKYHPDKGGDEVMF GATVAEIKKQYRLL LNLDPGATVAEIKKQYRLL MRIAKAYAALTDEESRKNWEEFGNPD SLKYHPDKGGDEV SLKYHPDKGGDEVMFMRI GPQATSFGIALP MFMRIAKAYAALT AKAYAALTDEESRKNWEEF DEESRKNWEEFGN GNPDGP PDGP RY1 3' KETKETKSKERQnEEDLEGKTEEEIE 71 KETKETKSKERQITEEDLE 190 (SNR27) MMKLMGFASFDSTKGKKVDGSVNAY GKTEEEIEMMKLMGFASFD AINVSQKRKYRQYMNRKGGFNRPLDF STKGKKVDGSVNAYAINVS IA QKRKYRQYMNRKGGFNR PLDFIA LSM11 3' MEERERGARSAGAGSPARPPSPRLDVS 72 AGAGSPARPPSPRLDVSSD 191

[0383] SDSFDPLLALYAPRLPPIPYPNAPCFNN SFDPLLALYAPRLPPIPYPN VAEYESFLRTGVRGGGRGRGRARGAA APCFNNVAEYESFLRTGVR AGSGVPAAP GGGRGRGRARGAAAGSG VPAAP

[0384] N0C3L 3' CCEAVKKLFKQDKLGQASLGVIKVISG 73 QDKLGQASLGVIK 283 QDKLGQASLGVIKVISGFV 192

[0385] FVKGRNYEVRPEMLKTFLCLRIKEVE VISGFVKGRNYEV KGRNYEVRPEMLKTFLCL VKKDTEDINKPKKFMTFKEKRKSLSR RPEMLKTFLCLRIK RIKEVEVKKDTEDINKPKK MQRKWKKAEEK EVEVKKDTEDINK FMTFKEKRKSLSRMQRKW PKKFMTFKEKRKS KKAEEK LSRM PDIA3 3' KIKKHQENIFGICPHMTEDNKDLIQGK 74 KNAKGSNYWRNR 284 KIKKFIQENIFGICPHMTED 193

[0386] DLLIAYYDVDYEKNAKGSNYWRNRV VMMVAKKFLDAG NKDLIQGKDLLIAYYDVDY MMVAKKFLDAGHKLNFAVASRKTFSH HKLNFAVASRKTFS EKNAKGSNYWRNRVMMV ELSDFGLESTAGEIPWAIRTAKGEKFV HE AKKFLDAGHKLNFAVASR MQEEFSRDGKALE KTFSHE PTCD1 3' GGCGRVGYLKKAFNLYNQMKKRDLE 75 KRDLEPSDATYTAL 285 KRDLEPSDATYTALFNVCA 194

[0387] PSDATYTALFNVCAESPWKDSALQSA FNVCAESPWKDSA ESPWKDSALQSALKLRQQ LKLRQQLQAKNFELNLKTYHALLKM LQSALKLRQQLQA LQAKNFELNLKTYHALLK AAKCADLRMCLDVFKEIIHKGHW KNFELNLKTYHAL MAAKCADLRMCLDVFKEI LKMAAKC IHKGHW TRMT1L 3' KSNEMITNLGKKQKTDVSTEHPPFYY 76 HSIKGMNMPKLKK 286 HSIKGMNMPKLKKFLCYL 195

[0388]

[0389] NIHRHSIKGMNMPKLKKFLCYLSQAG FLCYLSQAGFRVSR SQAGFRVSRTHFDPMGVRTFRVSRTHFDPMGVRTDAPLMQFKSILL THFDPMGVRTDAP DAPLMQFKSILLKYSTPTY KYSTPTYTGGQSESHVQSASEDTVTER LMQFKSILLK TGGQSESHVQSASEDTVTE VEMS RVEMS ZFP36L1 3' ASLFAPSMGLPGGGSPTTFLFRPMSESP 77 ASLFAPSMGLPGGGSPTTF 196

[0390] HMFDSPPSPQDSLSDQEGYLSSSSSSHS LFRPMSESPHMFDSPPSPQ GSDSPTLDNSRRLPIFSRLSISDD DSLSDQEGYLSSSSSSHSGS DSPTLDNSRRLPIFSRLSISD D WRN 3' PQGLKMLLENKAVKKAGVGIEGDQW 78 KAVKKAGVGIEGD 287 KAVKKAGVGIEGDQWKLL 197

[0391] KLLRDFDIKLKNFVELTDVANKKLKCT QWKLLRDFDIKLK RDFDIKLKNFVELTDVANK ETWSLNSLVKHLLGKQLLKDKSIRCSN NFVELTDVANKKL KLKCTETWSLNSLVKHLLG WSKFPLTEDQK KCTETWSLNSLVK KQLLKDKSIRCSNWSKFPL HLLGKQLLKDKSI TEDQK RCSNW

[0392] C14orf93 3' PFKGLKEKEEKKLRSRRYRLFANRSSI 79 KKLRSRRYRLFAN 288 PFKGLKEKEEKKLRSRRYR 198

[0393] MRHFGPEDQRLWNDVTEELMSDEEDS RSSIMRHFGPEDQR LFANRSSIMRHFGPEDQRL LNEPGVWVARPPRFRAQRLTELCYHL LWNDVTEELMSDE WNDVTEELMSDEEDSLNE DANSKHGTKAN EDSLNEPGVWVAR PGVWVARPPRFRAQRLTEL PPRFRAQRLTELCY CYHLD HLD PLEC 3' RTLARPGPEPAPATDERDRVQKKTFTK 80 QKKTFTKWVNKH 289 QKKTFTKWVNKHLIKAQR 199

[0394] WVNKHLIKAQRHISDLYEDLRDGHNLI LIKAQRHISDLYED HISDLYEDLRDGHNLISLLE SLLEVLSGDSLPREKGRMRFHKLQNV LRDGHNLISLLEVL VLSGDSLPREKGRMRFHK QIALDYLRHRQVKLVNIRND SGDSLPREKGRMR LQNVQIALDYLRHRQVKL FHKLQNV VNIRND FANCM 3' QDQITRDANSFKSRDQRGVQEEKVKN 81 FKSRDQRGVQEEK 290 QDQITRDANSFKSRDQRGV 200

[0395] HEDIFDCSRDLFSVTFDLGFCSPDSDDE VKNHEDIFDCSRD QEEKVKNHEDIFDCSRDLF ILEHTSDSNRPLDDLYGRYLEIKEISDA LFSVTFDLGFCSPD SVTFDLGFCSPDSDDEILEH NYVSNQAL SDDEILEHTSDSNR TSDSNRPLDDLYGRYLEIK PLDDLYGRYLEIKE EIS IS PLEC 3' QAKARQAEAAERSRLRIEEEIRWRLQ 82 ERSRLRIEEEIRWR 291 ERSRLRIEEEIRVVRLQLEA 201

[0396] LEATERQRGGAEGELQALRARAEEAE LQLEATERQRGGA TERQRGGAEGELQALRAR AQKRQAQEEAERLRRQVQDESQRKR EGELQALRARAEE AEEAEAQKRQAQEEAERL QAEVELASRVKA AEAQKRQAQEEAE RRQVQDESQRKRQAEVEL RLRRQVQDESQRK ASRVKA RQA RPL22 3' DGIMDAANFEQFLQERIKVNGKAGNL 83 VNGKAGNLGGGWTIERS 202

[0397] GGGWTIERSKSKITVTSEVPFSKRYLK KSKITVTSEVPFSKRYLKYL

[0398]

[0399] TKKYLKKNNLRDWLRVVAYLTKKYLKKNNLRDWLRVANSKESY NSKESYELRYFQINQDEEE ELRYFQINQDQDEEEEEDED EEDED SETD1B 3' MENSHPPHHHHQQPPPQPGPSGERRN 84 MENSHPPHHHHQQPPPQP 203

[0400] HHWRSYKLMIDPALKKGHHKLYRYD GPSGERRNHHWRSYKLMI GQHFSLAMSSNRPVEIVEDPRWGIWT DPALKKGHHKLYRYDGQH KN FSLAMSSNRPVEIVEDPRV VGIWTKN TRMT10A 3' MSSEMLPAHETSNVDKKQGINEDQEE 85 MSSEMLPAHETSNVDKKQ 204

[0401] SQKPRLGEGCEPISKRQMKKLIKQKQ GINEDQEESQKPRLGEGCE WEEQRELRKQKRKEKRKRKKLERQC PISKRQMKKLIKQKQWEE QM QRELRKQKRKEKRKRKKL ERQCQM EIF3C 3' MSRFFTTGSDSESESSLSGEELVTKPVG 86 MSRFFTrGSDSESESSLSGE 205

[0402] GNYGKQPLLLSEDEEDTKRWRSAKD ELVTKPVGGNYGKQPLLLS KRFEELTNLIRTIRNAMKIRDVTKCL EDEEDTKRWRSAKDKRFE ELTNLIRTIRNAMKIRDVTK CL ANKRD17 3' ANVEDRGIKGDITPLMAAANGGHVKI 87 DITPLMAAANGGH 292 ANVEDRGIKGDITPLMAAA 206

[0403] VKLLLAHKADVNAQSSTGNTALTYAC VKIVKLLLAHKAD NGGHVKIVKLLLAHKADV AGGYVDWKVLLESGASIEDHNENGH VNAQSSTGNTALT NAQSSTGNTALTYACAGG TPLMEAGSAGHV YACAGGYVDWK YVDWKVLLESGASIEDHN

[0404] O) VLLESGASIEDHNE ENGHTP

[0405] NGHTP ADAD2 3' PVAPSEPTPDTCRGLSLNWSLGDPGIE 88 VATGRVKANAALG 293 PVAPSEPTPDTCRGLSLNW 207

[0406] WDVATGRVKANAALGPPSRLCKASF PPSRLCKASFLRAF SLGDPGIEWDVATGRVKA LRAFHQAARAVGKPYLLALKTYEAAK HQAARAVGKPYLL NAALGPPSRLCKASFLRAF AGPYQEARRQLSLLLDQQGLGAWPSK ALKTYEAAKA HQAARAVGKPYLLALKTY PLVGK EAAKA SRP54 3' LTQYTKFAQMVKKMGGIKGLFKGGD 89 LTQYTKFAQMVKKMGGIK 208

[0407] MSKNVSQSQMAKLNQQMAKMMDPR GLFKGGDMSKNVSQSQMA VLHHMGGMAGLQSMMRQFQQGAAG KLNQQMAKMMDPRVLHH NMKGMMGMKGMMGFNNM MGGMAGLQSMMRQFQQG AAGNMKGMMG RPS27A 3' MQIFVKTLTGKTITLEVEPSDTIENVKA 90 MQIFVKTLTGKTTTLEVEPS 209

[0408] KIQDKEGIPPDQQRLIFAGKQLEDGRT DTIENVKAKIQDKEGIPPD LSDYNIQKESTLHLVLRLRGGAKKR QQRLIFAGKQLEDGRTLSD YNIQKESTLHLVLRLRGGA KKR SYNE1 3' LEREAQSSALFKQKHQELLACQENCK 91 FKQKHQELLACQE 294 FKQKHQELLACQENCKKT 210

[0409]

[0410] KTLTLIEKGSQSVQKFVTLSNVLKHFD NCKKTLTLIEKGSQ LTLIEKGSQSVQKFVTLSNQTRLQRQIADIHVAFQSMVKKTGDWK SVQKFVTLSNVLK VLKHFDQTRLQRQIADIHV KHVETNSRLMK HFDQTRLQRQIADI AFQSMVKKTGDWKKHVE HVAFQSMVKKTGD TNSRLMK WKK ARHGEF1 375' VLSLKQLLFPAEEDNGAGPPRDGDGV 92 SLKQLLFPAEEDNGAGPPR 211

[0411] PGGGPLSPARTQEIQENLLSLEETMKQ DGDGVPGGGPLSPARTQEI LEELEEEFCRLRPLLSQLGGNSVPQPG QENLLSLEETMKQLEELEE GNSVPQPGCT EFCRLRPLLSQLGGNSVPQ PGCT TDRD6 3' ATEEEEPETSQSQSPAEEVDEEISLPALR 93 EEISLPALRSIRLKM 295 ATEEEEPETSQSQSPAEEVD 212

[0412] SIRLKMNAFYDAQVEFVKNPSEFWIRL NAFYDAQVEFVKN EEISLPALRSIRLKMNAFYD RKHNVTFSKLMRRMCGFYSSASKLDG PSEFWIRLRKHNV AQVEFVKNPSEFWIRLRKH WLKPEPDDLCCVKWKEN TFSKLMRRMCGFY NVTFSKLMRRMCGFYSSA SSASKL SKL TRMT2A 3' DLVPTLVSRLASQHLVAILDPPRAGLHS 94 ASQHLVAILDPPRA 296 ASQHLVAILDPPRAGLHSK 213

[0413] KVILAIRRAKNLRRLLYVSCNPRAAM GLHSKVIL AIRRAK VILAIRRAKNLRRLLYVSC GNFVDLCRAPSNRVKGIPFRPVKAVAV NLRRLLYVSCNPR NPRAAMGNFVDLCRAPSN DLFPQTPHC AAMGNFVDLCRA RVKGIPFRPVKAVAVDLFPQ PSNRVKGIPFRPVK TPHC AVA ZC3H14 3' MEIGTEISRKIRSAIKGKLQELGAYVDE 95 MEIGTEISRKIRSAIKGKLQ 214

[0414] ELPDYIMVMVANKKSQDQMTEDLSLF ELGAYVDEELPDYIMVMV LGNNTIRFTVWLHGVLDKLRSVTTEP ANKKSQDQMTEDLSLFLG NNTIRFTVWLHGVLDKLRS VTTEP DDX3Y 3' GSRGRSKSNRFSGGFGARDYRQSSGSS 96 GSRGRSKSNRFSGGFGARD 215

[0415] SSGFGASRGSSSRSGGGGYGNSRGFG YRQSSGSSSSGFGASRGSSS GGGYGGFYNSDGYGGNYNSQGVDW RSGGGGYGNSRGFGGGGY WGN GGFYNSDGYGGNYNSQGV DWWGN RPL35 3' MAKIKARDLRGKKKEELLKQLDDLK 97 MAKIKARDLRGKKKEELL 216

[0416] VELSQLRVAKVTGGAASKLSKIRWRK KQLDDLKVELSQLRVAKV SIARVLTVINQTQKENLRKFYKGKKYK TGGAASKLSKIRWRKSIA P RVLTVINQTQKENLRKFYK GKKYKP OASL 3' VTIVPAYRALGPSLPNSQPPPEVYVSLI 98 GPSLPNSQPPPEVY 297 VTTVPAYRALGPSLPNSQPP 217

[0417] KACGGPGNFCPSFSELQRNFVKHRPTK VSLIKACGGPGNF PEVYVSLIKACGGPGNFCP LKSLLRLVKHWYQQYVKARSPRANLP CPSFSELQRNFVKH SFSELQRNFVKHRPTKLKS PLYALELLT RPTKLKSLLRLVK LLRLVKHWYQQYVKARSP

[0418]

[0419] RANLHWYQQYVKARSP

[0420] RANL RBM11 3' EADRTVFVGNLEARVREEILYELFLQA 99 EADRTVFVGNLEARVREEI 218

[0421] GPLTKVTICKDREGKPKSFGFVCFKHP LYELFLQAGPLTKVTICKD ESVSYAIALLNGIRLYGRPINVQYRF REGKPKSFGFVCFKHPESV SYAIALLNGIRLYGRPINVQ YRF NQ01 3' HTPADARIQILEGWKKRLENIWDETPL 100 HTPADARIQILEGWKKRLE 219

[0422] YFAPSSLFDLNFQAGFLMKKEVQDEE NIWDETPLYFAPSSLFDLNF KNKKFGLSVGHHLGKSIPTDNQIKAR QAGFLMKKEVQDEEKNKK K FGLSVGHHLGKSIPTDNQI KARK FASTKD3 3' MALITLRKNLYRLSDFQMHRALAALK 101 MALITLRKNLYRLSDFQMH 220

[0423] NKPLNHVHKWKERLCPWLCSRQPEP RALAALKNKPLNHVHKW FGVKFHHAHCKKFHSKNGNDLHPLG KERLCPWLCSRQPEPFGVK GPV FHHAHCKKFHSKNGNDLH PLGGPV ADAD2 5' MASASQGADDDGSRRKPRLAASLQIS 102 DGSRRKPRLAASLQISPQP 221

[0424] PQPRPWRPLPAQAQSAWGPAPAPATYR RPWRPLPAQAQSAWGPAPA AEGGWPQVSVLRDSGPGAGAGVGEL PATYRAEGGWPQVSVLRD GAARAWENLGEQ SGPGAGAGVGELGAARAW ENLGEQ YTHDF2 5' DDDFEPYLSPQARPNNAYTAMSDSYL 103 MSDSYLPSYYSPSI 298 DDDFEPYLSPQARPNNAYT 222

[0425] PSYYSPSIGFSYSLGEAAWSTGGDTAM GFSYSLGEAAWST AMSDSYLPSYYSPSIGFSYS PYLTSYGQLSNGEPHFLPDAMFGQPG GGDTAMPYLTSYG LGEAAWSTGGDTAMPYLT ALGSTPFLGQHGFNFFPSGID QLSNGEPHFLPDA SYGQLSNGEPHFLPDAMFG MFGQPGA QPGA DCP1B 5' AQPPQAYFNGSLPPQTVGHQAHGREQ 104 ELLKKLQIVQQEQ 299 AHGREQSTLPRQTLPISGSQ 223

[0426] STLPRQTLPISGSQTGSSGVISPQELLK QLHASNRPALAAK TGSSGVISPQELLKKLQIVQ KLQIVQQEQQLHASNRPALAAKFPVL FPVL QEQQLHASNRPALAAKFPV AQSSGTGKPLESWINKTPNTEQQTPLF LAQSSGTGKPLESWINKTP QVISPQRIPATAAPSLLMSPMVF NT SETD1B 5' EPLAKEKPGTPPGPPPPDTNSMELGGR 105 GTPTLESSPAGPEK 300 EPLAKEKPGTPPGPPPPDTN 224

[0427] PTFGWSPEPCDSPGTPTLESSPAGPEKP PHDSLDSRIEMLLK SMELGGRPTFGWSPEPCDS HDSLDSRIEMLLKEQRTKLLFLREPDS EQRTKLLFLREP PGTPTLESSPAGPEKPHDSL DTELQMEGSPISSSSSQLSPLAPFGTNS DSRIEMLLKEQRTKLLFLR QPGFRGPTPP EP CHERP 5' HCPPWNNSHEGMWGEQRGDPGWNG 106 GWNGQRDAPWNN 301 GWNGQRDAPWNNQPDAA 225

[0428]

[0429] QRDAPWNNQPDAAWNSQFEGPWNSQ QPDAAWNSQFEGP WNSQFEGPWNSQHEQPPWHEQPPWGGGQREPPFRMQRPPHFRGP WNSQHEQPPWGG GGGQREPPFRMQRPPHFRG FPPHQQHPQFNQPPHPHNFNRFPPR GQREPPFRMQRPP PFPPHQQHPQFNQPPHPHN HFRGPFPPHQ FNRFPPR CHERP 5' GQPPHMRRQGPPHINHDDPSLVPNVPY 107 PAGLMAPLVKLED 302 PPHINHDDPSLVPNVPYFDL 226

[0430] FDLPAGLMAPLVKLEDHEYKPLDPKDI HEYKPLDPKDIRLP PAGLMAPLVKLEDHEYKPL RLPPPMPPSERLLAAVEAFYSPPSHDRP PPMPPSERLLAAVE DPKDIRLPPPMPPSERLLAA RNSEGWEQNGLYEFFRAKMRARRRK AFYSPPSHD VEAFYSPPSHDRPRNSEGW GQE EQ CN0T4 5' FRHPNPIPSGLPPFPSSPQTSSDWPTAPE 108 QSLFTSETTPVSSST 303 LPPFPSSPQTSSDWPTAPEP 227

[0431] PQSLFTSETIPVSSSTDWQAAFGFGSSK DWQAAFGFGSSKQ QSLFTSETIPVSSSTDWQAA QPEDDLGFDPFDVTRKALADLIEKELS PEDDLGFDPFDVT FGFGSSKQPEDDLGFDPFD VQDQPSLSPTSLQNSSSHTTTAKGPG RKALADLIE VTRKALADLIEKELSVQDQ PS HSPB1 5' MTERRVPFSLLRGPSWDPFRDWYPHS 109 MTERRVPFSLLRGPSWDPF 228

[0432] RLFDQAFGLPRLPEEWSQWLGGSSWP RDWYPHSRLFDQAFGLPR GYVRPLPPAAIESPAVAAPAYSRALSRQ LPEEWSQWLGGSSWPGYV LSSGVSEIRH RPLPPAAIESPAVAAPAYSR ALSRQ CN0T2 5' STDGPKFPGDKSSTTQNNNQQKKGIQ 110 GRVTNIPQGMVTD 304 GRVTNIPQGMVTDQFGMIG 229 n VLPDGRVTNIPQGMVTDQFGMIGLLTF QFGMIGLLTHRAA LLTHRAAETDPGMVHLAL — IRAAETDPGMVHLALGSDLTTLGLNL ETDPGMVHLALGS GSDLTTLGLNLNSPENLYP O) NSPENLYPKFASPWASSPCRPQDIDFHV DLTTLGLNLN KFASPWASSPCRPQDIDFH PSE VPSE EIF4G3 5' GDGVTFPFKPESWKPTDTEGKKQYDR 111 KKQYDREFLLDFQ 305 KKQYDREFLLDFQFMPACI 230

[0433] EFLLDFQFMPACIQKPEGLPPISDWLD FMPACIQKPEGLPP QKPEGLPPISDWLDKINQP KINQPKLPMRTLDPRILPRGPDFTPAFA ISDWLDKINQPKL KLPMRTLDPRILPRGPDFTP DFGRQTPGGRGVPLLNVG PMRTLDPRILPRGP AFADFGRQTPGGRGVPLLN DFTPA VG HLTF 5' RKKLIRKMKLILSSGSDEECAICLDSLT 112 ILSSGSDEECAICL 306 ILSSGSDEECAICLDSLTVP 231

[0434] VPVITHCAHVFCKPCICQVIQNEQPHA DSLTVPVITHCAHV VITHCAHVFCKPCICQVIQ KCPLCRNDIHEDNLLECPPEELARDSE FCKPCICQVIQNEQ NEQPHAKCPLCRNDIHEDN KKSDMEWT PHAKCPLCRNDIH LLECPPEELARDSEKKSDM EDNLLECPPEELAR EWT D PRPF3 5' RLRTKAQLEKLQAEISQAARKTGIHTS 113 KTGIHTSTRLALIA 307 KTGIHTSTRLALIAPKKELK 232

[0435] TRLALIAPKKELKEGDIPEIEWWDSYII PKKELKEGDIPEIE EGDIPEIEWWDSYnPNGFD PNGFDLTEENPKREDYFGITNLVEHPA WWDSYIIPNGFDLT LTEENPKREDYFGITNLVEH QLNPPVDNDTPVTLGVYL EENPKREDYFGITN PAQLNPPVDNDTPVTLGVY LVEH L

[0436]

[0437] GRWD1 5' AGHMGEGFALDWSPRVTGRLLTGDCQ 114 DWSPRVTGRLLTG 308 AGHMGEGFALDWSPRVTG 233 KNIHLWTPTDGGSWHVDQRPFVGHTR DCQKNIHLWTPTD RLLTGDCQKNIHLWTPTDG SVEDLQWSPTENTVFASCSADASIRIW GGSWHVDQRPFV GSWHVDQRPFVGHTRSVE DIRAAPSKACM GHTRSVEDLQWSP DLQWSPTENTVFASCSADA TENTVFASCSADAS SIRIWD IRIWD GANAB 5' WCWPGSAGYPDFTNPTMRAWWANM 115 WANMFSYDNYEG 309 WCWPGSAGYPDFTNPTMR 234

[0438] FSYDNYEGSAPNLFVWNDMNEPSVFN SAPNLFVWNDMN AWWANMFSYDNYEGSAP GPEVTMLKDAQHYGGWEHRDVHNIY EPSVFNGPEVTML NLFVWNDMNEPSVFNGPE GLYVHMATADGLRQRSGGMERPFVL KDAQHYGGWEHR VTMLKDAQHYGGWEHRD DVHNIYGLYVH VHNIYGLYVH SRP68 5' FNKCKTIYEKLASAFTEEQAVLYNQRV 116 LASAFTEEQAVLYN 310 LASAFTEEQAVLYNQRVEEI 235

[0439] EEISPNIRYCAYNIGDQSAINELMQMRL QRVEEISPNIRYCA SPNIRYCAYNIGDQSAINEL RSGGTEGLLAEKLEALITQTRAKQAAT YNIGDQSAINELM MQMRLRSGGTEGLLAEKL MSEVEWRG QMRLRSGGTEGLL EALITQTRAKQAATMSEVE AEKLEALITQTRAK WRG QA SRP68 5' EAAIVQAESEETKERLFESMLSECRDA 117 LSECRDAIQVVREE 311 LSECRDAIQVVREELKPDQ 236

[0440] IQVVREELKPDQKQRDYILEGEPGKVS LKPDQKQRDYILE KQRDYILEGEPGKVSNLQY NLQYLHSYLTYIKLSTAIKRNENMAKG GEPGKVSNLQYLH LHSYLTYIKLSTAIKRNEN LQRALLQQQPEDDSKRSPR SYLTYIKLSTAIKR MAKGLQRALLQQQPEDDS NENMAK KRSPR DSP 5' TLVIQLPGYPQHQTVTTTEITHHGTCQ 118 QHQTVTTTEITHH 312 QHQTVTTTEITHHGTCQDV 237

[0441] DVNHNKVIETNRENDKQETWMLMEL GTCQDVNHNKVIE NHNKVIETNRENDKQETW QKIRRQIEHCEGRMTLKNLPLADQGSS TNRENDKQETWM MLMELQKIRRQIEHCEGR HHITVKINELK LMELQKIRRQIEHC MTLKNLPLADQGSSHHITV EGRMTLKNLPLAD KINELK QGSSH SNRPE 5' VQKVMVQPINLIFRYLQNRSRIQVWLY 119 VQKVMVQPINLIFRYLQNR 238

[0442] EQVNMRIEGCITGFDEYMNLVLDDAEE SRIQVWLYEQVNMRIEGCII IHSKTKSRKQLGRIMLKGDNITLLQS GFDEYMNLVLDDAEEIHSK TKSRKQLGRIMLKGDNITL LQS

[0443]

Claims

CLAIMSWhat is claimed is:

1. A synthetic RNA regulatory protein comprising one or more RNA regulatory effector domains fused to a heterologous nucleic acid binding domain,wherein at least one of the one or more RNA regulatory domains comprises an amino acid sequence having at least 70% identity to any of SEQ ID NOs: 1-119, or a fragment thereof.

2. The synthetic RNA regulatory protein of claim 1, wherein at least one of the one or more RNA regulatory domains comprises an amino acid sequence having at least 90% identity to any of SEQ ID NOs: 1-119, or a fragment thereof.

3. The synthetic RNA regulatory protein of claim 1 or 2, wherein at least one of the one or more RNA regulatory domains comprises an amino acid sequence of any of SEQ ID NOs: 1-119, or a fragment thereof.

4. The synthetic RNA regulatory protein of any of claims 1-3, wherein at least one of the one or more RNA regulatory domains comprises at least 10 contiguous amino acids of any of SEQ ID NOs: 1-119.

5. The synthetic RNA regulatory protein of any of claims 1-4, wherein at least one of the one or more RNA regulatory domains comprises an amino acid sequence of any of SEQ ID NOs: 239-312.

6. The synthetic RNA regulatory protein of any of claims 1-5, wherein at least one of the one or more RNA regulatory domains comprises an amino acid sequence having at least 70% identity to any of SEQ ID NOs: 120-238.

7. The synthetic RNA regulatory protein of any of claims 1-6, wherein at least one of the one or more RNA regulatory domains comprises an amino acid sequence of any of SEQ ID NOs: 120-238.

8. The synthetic RNA regulatory protein of any of claims 1-7, wherein the synthetic RNA regulatory protein comprises two or more RNA regulatory effector domains.

9. The synthetic RNA regulatory protein of any of claims 1-8, wherein the heterologous nucleic acid binding domain is an RNA binding domain or a DNA binding domain.6410. The synthetic RNA regulatory protein of any of claims 1-9, wherein the heterologous nucleic acid binding domain is a programmable nucleic acid binding domain.

11. The synthetic RNA regulatory protein of any of claims 1-10, wherein the heterologous nucleic acid binding domain is or is derived from a Clustered Regularly Interspaced Short Palindromic Repeats associated (Cas) protein.

12. The synthetic RNA regulatory protein of any of claims 1-11, wherein the heterologous nucleic acid binding domain is inducible or part of an inducible binding system.

13. A nucleic acid encoding a synthetic RNA regulatory protein of any of claims 1-12.

14. The nucleic acid of claim 13, wherein the nucleic acid in under control of an inducible promoter and / or a tissue specific promoter.

15. A vector comprising a nucleic acid of claim 13 or 14.

16. The vector of claim 15, wherein the vector is a viral vector.

17. A cell comprising a synthetic RNA regulatory protein of any of claims 1-12, a nucleic acid of claim 13 or 14, or a vector of claim 15 or 16.

18. The cell of claim 17, wherein the cell comprises two or more synthetic RNA regulatory proteins, nucleic acids, or vectors.

19. The cell of claim 17 or 18, wherein the cell is a prokaryotic cell.

20. The cell of claim 17 or 18, wherein the cell is a eukaryotic cell.

21. The cell of claim 20, wherein the cell is a human cell.

22. A composition or system comprising a synthetic RNA regulatory protein of any of claims 1-12, a nucleic acid of claim 13 or 14, a vector of claim 15 or 16, or a cell of any of claims 17-21.

23. The composition of claim 22, wherein the composition comprises two or more synthetic RNA regulatory protein, nucleic acids, vectors, or cells.

24. The composition or system of claim 22 or 23, further comprising one or more guide RNAs or one or more nucleic acids encoding thereof.

25. A method for modulating RNA levels comprising contacting a target nucleic acid encoding the target RNA or the target RNA with at least one synthetic RNA regulatory protein of any of claims 1-12.

26. A method of modulating the level of one or more target RNAs and / or expression of one or more target genes in a cell comprising introducing into the cell at least one synthetic RNA regulatory protein of any of claims 1-12, a nucleic acid of claim 13 or 14, a vector of claim 15 or 16, or composition or system of any of claims 22-24.

27. The method of claim 26, wherein the cell is in a subject.

28. The method of claim 27, wherein the method comprises administering the at least one synthetic RNA regulatory protein, nucleic acid, vector, or composition or system to the subject.

29. The method of any of claims 25-28, wherein the at least one synthetic RNA regulatory protein decreases the level of one or more target RNAs.

30. The method of any of claims 25-29, wherein the at least one synthetic RNA regulatory protein increases degradation of one or more target RNAs.

31. The method of any of claims 25-30, wherein the at least one synthetic RNA regulatory protein decreases expression of one or more target genes.

32. The method of any of claims 25-31, wherein the at least one synthetic RNA regulatory protein at least partially inhibits transcription and / or translation.

33. The method of any of claims 25-32, wherein the levels of at least two RNAs and / or gene expression of at least two genes is modulated.

34. The method of any of claims 26-33, wherein the target RNAs and / or target genes are endogenous to the cell.

35. The method of any of claims 26-33, wherein the target RNAs and / or target genes are exogenous to the cell36. A method for treating a disease or condition in a subject in need thereof, the method comprising: administering to the subject at least one synthetic RNA regulatory protein of any of claims 1-12, a nucleic acid of claim 13 or 14, a vector of claim 15 or 16, or composition or system of any of claims 22-24.

37. The method of claim 36, wherein the subject is human.

38. The method of claim 36 or 37, wherein the synthetic RNA regulatory protein alters expression of a disease-related gene.

39. Use of a synthetic RNA regulatory protein of any of claims 1-12, a nucleic acid of claim 13 or 14, a vector of claim 15 or 16, or composition or system of any of claims 22-24 for modulating he level of one or more target RNAs and / or expression of one or more target genes.67

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