Construction and Characterization of a Synthetic MicroRNA Cluster for

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Construction and characterization of synthetic microRNA cluster for multiplex RNA interference in mammalian cells Tingting Wang, Yue Xie, Aidi Tan, Shao Li, and Zhen Xie ACS Synth. Biol., Just Accepted Manuscript • DOI: 10.1021/acssynbio.5b00180 • Publication Date (Web): 07 Dec 2015 Downloaded from http://pubs.acs.org on December 8, 2015

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ACS Synthetic Biology

Construction and characterization of synthetic microRNA cluster for multiplex RNA interference in mammalian cells Tingting Wang, Yue Xie, Aidi Tan, Shao Li and Zhen Xie* MOE Key Laboratory of Bioinformatics and Bioinformatics Division, Center for Synthetic and System Biology, TNLIST/Department of Automation, Tsinghua University, Beijing 100084, China * To whom correspondence should be addressed: Tel: +86-010-62796050; Email: [email protected] (Z.X.).

ABSTRACT RNA interference (RNAi) technology is widely used in basic and translational research. By mimicking natural primary microRNA (pri-miRNA) cluster, multiple engineered hairpins can be transcribed as a single transcript from the same Pol-II promoter, enabling multiplex RNAi in mammalian cells. However, constructing synthetic miRNA cluster is still time-consuming, and the processing and function of miRNA cluster are incompletely understood. Here, we identified a miRNA precursor architecture that allowed precise miRNA maturation. We established a hierarchical cloning method for efficient construction of synthetic miRNA cluster harboring up to 18 miRNA precursors. We demonstrated that maturation and function of individual miRNA precursors were independent on their positions in the cluster. We then analyzed the integration efficiency of miRNA clusters with varying number of miRNA precursors by using CRISPR/Cas9 mediated integration, piggyBac transposon system, and lentiviral system. This synthetic miRNA cluster system provides an important tool for multiplex RNAi in mammalian cells.

INTRODUCTION MicroRNA (miRNA) is a key mediator of RNA interference (RNAi) in animals and other eukaryotes 1. The primary transcript of mature miRNA (pri-miRNA) is often transcribed from the Pol II promoter, and then cleaved into ~65-nt precursor miRNA (pre-miRNA) by the 2

protein complex of Drosha and DiGeorge syndrome chromosomal region 8 (DGCR8) . The pre-miRNA is exported into cytoplasm and processed by Dicer into a 21- to 26-nt RNA duplex 3

that is composed of antisense (5p) and sense (3p) strands . Either antisense or sense strand is incorporated into the RNA-induced silencing complex (RISC) as the mature miRNA and base-pairs to the target mRNA transcript, causing RNA degradation or translational inhibition 1, 3

. Two different expression systems have been established to trigger RNAi in mammalian

cells. Short hairpin RNA (shRNA) that mimics the stem-loop structure of the pre-miRNA can 4

be transcribed from a Pol III promoter . Alternatively, synthetic miRNA driven by Pol II promoters can be made by embedding short hairpin structure into natural miRNA backbone5, 6. The synthetic miRNA strategy offers several advantages over the shRNA strategy, including low cellular toxicity, versatility for stable and regulated expression and co-expression with a gene of interest

6-10

. A few sequence preferences of miRNAs and shRNAs have been shown

1 ACS Paragon Plus Environment


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to promote precise processing and asymmetry loading of antisense strand to the RISC complex, including a strong bias to A/U at 5’ end of the antisense, relative low G/C content and thermodynamic asymmetry 11-13. However, design of synthetic miRNA that triggers potent RNAi with high on-target efficacy and low off-target effect remains challenging due to incomplete understanding of miRNA biogenesis

14

.

Basic biological research and biomedical applications often require multiplex RNAi technology, including mapping the network of genotype-to-phenotype relationships in response to external stimulus genes

19

15-18

, studying functionally synergistic and compensational

, and engineering complex gene circuits

20, 21

. Several cloning methods that often

require repetitive cloning or PCR steps have been developed to fuse multiple synthetic 17, 18, 22-25

miRNA precursors into one transcript

. An alternative strategy is to replace the 5

hairpin structures with synthetic hairpins in the natural miRNA cluster . Despite the progress, facilitating the application of miRNA-based multiplex RNAi technology demands an efficient cloning method and a comprehensive functional characterization of a synthetic miRNA cluster. In this study, we found that the pri-miR-155 backbone allowed efficient and precise miRNA maturation by generating a series of miRNA precursors with different stem sequences. We developed an efficient hierarchical assembly method to construct synthetic miRNA clusters with up to 18 synthetic miRNA precursors in three rounds of cloning. We then characterized the miRNA maturation pattern and RNAi efficiency of individual miRNA precursors in the synthetic miRNA cluster by small RNA sequencing analysis and a functional reporter assay. In addition, we assayed genomic integration efficiency of the synthetic miRNA cluster with a varying number of synthetic miRNA precursors by using CRISPR/Cas9 mediated integration, piggyBac transposon system, and lentiviral system. Our results showed that the synthetic miRNA cluster system would be a modular and powerful tool for multiplex gene knockdown at posttranscriptional level, which might inspire new strategies for increasing needs of complex functional genomic studies and biomedical applications.

RESULTS Characterization of synthetic miRNA precursor We chose the murine pri-miR-155 backbone as the basic architecture of synthetic miRNA precursor because of its short length

26

. This architecture consisted of a flanking

region, a 21-nt antisense strand paired to a sense strand with an arbitrary 2-nt bulge, and a terminal loop (Fig. 1A). To facilitate asymmetric processing, we ensured that the GC content of the first four nucleotides in the antisense strand was lower than that of the last four nucleotides in the antisense strand

11

. Based on this architecture, the expected mature

miRNA was generated from antisense strand, starting at 5p +1 position (Fig. 1A). To explore the relationship between the miRNA maturation and the architecture of the pri-miR-155 backbone, we designed and cloned 30 synthetic miRNA precursors into the pri-


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miR-155 backbone to assay whether pri-miR-155 backbone is suitable for expression of synthetic miRNAs (Fig. 1B and Fig. S1). Small RNA sequencing analysis showed that the synthetic miRNA precursors with a 19-nt stem made of the sense and antisense strands allowed a precise maturation pattern (Fig. S1A, S1B and S1C), while both decreasing the stem 15- or 17-nt, and increasing the stem to 21- or 23-nt, caused a large variation in mature miRNA processing, as well as an obvious reduction of mature miRNA levels (Fig. 1C, 1D and Fig. S1C). For the 24 synthetic miRNA precursors carrying a 19-nt stem, the starting sites of mature miRNAs were mainly fixed at 5p +1 position and 3p -1 position. More than 85% of mature miRNAs generated from 15 constructs had a precise starting site at 5p +1 position with a varying length, while more than 90% of mature miRNAs that were produced from the other 9 constructs started at either 5p +1 or 3p -1 position with a varying length (Fig. 1B, Fig. S1A and Fig. S1B). These results suggested that the stem length of the synthetic miRNA precursors played an important role in the miRNA biogenesis. We further demonstrated that the miRNA maturation pattern remained largely unchanged when we transiently expressed synthetic miRNAs in HEK293 cells, or integrated into the genome of HEK293 cells by using the lentiviral system (Fig. S1E). Therefore, we decided to use the pri-miR-155 backbone with a 19-nt stem as our synthetic pri-miRNA hairpin architecture in this study. Hierarchical assembly of synthetic miRNA cluster To enable high-throughput construction of synthetic miRNA cluster containing repetitive DNA fragments, we developed a hierarchical strategy based on the golden-gate cloning method

27

(Fig. 2). First, synthesized miRNA oligos were respectively cloned into six miRNA

precursor constructs (pMR1 to pMR6) that contained the flanking regions of the pri-miR-155 backbone to generate six pri-miRNA constructs (Fig. 2). Second, all six pri-miRNA constructs along with two adaptor constructs were cut by a type IIS restriction endonuclease to release the special designed DNA junctions, allowing ordered ligation to form the intermediate constructs (pMM1 to pMM3). In the last step, another similar golden-gate reaction was performed to assemble intermediate constructs into the final construct carrying synthetic miRNA cluster (Fig. 2). This cloning strategy was modular and flexible, allowing us to quickly construct a synthetic miRNA cluster with 2 to 18 hairpins coexpressed with a gene of interest in three rounds of cloning (Table S3). Characterization of synthetic miRNA cluster To characterize the function and maturation pattern of individual miRNA precursors in the cluster, we constructed 6 synthetic miRNA clusters that carried 6, 12 or 18 different synthetic miRNA precursors (Fig. 3A), by permuting the order of the intermediate pMM constructs in the second and third steps of cluster assembly (Fig. 2). Consequently, the same synthetic miRNA precursor was assembled at different positions in different clusters. By using quantitative RT-PCR, we found that the expression level of synthetic miRNAs was largely unchanged regardless their positions in the cluster (Fig. 3A). We then performed small RNA



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sequencing analysis on HEK293 cells transfected with these synthetic miRNA clusters, respectively (Fig. 3B and 3C). The results showed that the synthetic pri-miRNAs that either expressed individually or derived from the clusters with varying number of miRNA precursors generated a similar portion of mature miRNAs starting at 5p +1 position (paired t-tested, Pvalue < 0.05), although we observed an increased variation in miRNA maturation pattern when mature miRNAs were produced from both antisense and sense strands in large quantity (Fig. 3B and 3C, Table S4). In addition, the length distribution of these mature miRNAs produced from different clusters also displayed a high consistency (Fig. S2). Next, we validated the change of miRNA expression level as the number of synthetic pri-miRNAs increased in synthetic miRNA cluster. Using the hierarchical cloning method, we constructed synthetic miRNA clusters that contained varying numbers of different pri-miRNA hairpins (Fig. 4A). Each of these clusters harbored a miR-FF3 precursor at the first position in the cluster and a miR-FF5 precursor at the last (Fig. 4A). We found that when the number of synthetic miRNA precursors increased from 2 to 18, the expression levels of miR-FF3 and miR-FF5 decreased within 3-fold, while the RNAi efficiency of miR-FF3 and miR-FF5 slightly reduced from 99% to 96% and 93% respectively (Fig. 4A). To test whether using multiple miRNAs to repress the same target gene could reduce the RNAi off-target effect, we fused the fully complementary target sites (on-targets) of synthetic miRNAs in tandem to the 3’-UTR of a red fluorescent reporter gene (mKate2) and respectively cloned two different artificial offtargets of miR-FF3 at the first position in the clusters into the 3’-UTR of a blue fluorescent reporter gene, EBFP2 (Fig. 4B and Fig. S3). In both cases, the off-target effects of miR-FF3 were gradually relieved when we increased the number of miRNA precursors in the cluster from 1 to 12 (Fig. 4B and Fig. S3). Genome integration of synthetic miRNA cluster Applications of RNAi technology often require genome integration of RNAi triggers instead of transient expression. However, the synthetic miRNA cluster contains multiple hairpin structures and a large amount of repetitive sequences due to reuse of the pri-miR-155 backbone, which might increase the difficulty in integrating the cluster into mammalian genome. To test the feasibility to integrate clusters with different number of synthetic miRNA precursors, we performed genome integration experiments in HEK293 cells by using three different systems, including CRISPR/Cas9 mediated site-specific integration into human AAVS locus

28

, the piggyBac transposon system

29

, and the lentiviral vector system (Fig. 5A

and Fig. S4). In the CRISPR/Cas9 mediated integration experiment, we chose the nonhomologous end joining (NHEJ) strategy (Fig. S4), which has been shown to induce a high knock-in efficiency via homology-independent DNA repair

30

. We screened the cells with

puromycin for 15 days after transfection, and then amplified the synthetic miRNA cluster using the genomic DNA template extracted from survived cells. We successfully amplified the intact clusters containing up to 18 synthetic miRNA precursors from cells integrated by using piggyBac and CRISPR/Cas9 systems, although the amplification efficiency strongly


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decreased when the clusters carried more than 9 synthetic miRNA precursors (Fig. 5B). However, we failed to detect intact clusters with more than 9 synthetic miRNA precursors from lentiviral infected cells after 7-day selection with puromycin, suggesting that the lentiviral integration system exhibited a low tolerance for repetitive sequences, which was similar to previous reports

25, 31

.

To investigate the integration efficiency at single cell level, we monitored the frequency of EYFP positive cells after we transfected either piggyBac or Cas9-mediated integration plasmids into HEK293 cells (Fig. 5A and 5C). When the cluster contained no more than 6 synthetic miRNA precursors, transfecting cells with both piggyBac transposon and transposase-expressing plasmids resulted in a higher frequency of EYFP positive cells over the control for up to 17 days without puromycin selection (Fig. 5C). However, we observed no obvious difference in the frequency of EYFP positive cells when we transfected clusters with varying number of synthetic miRNA precursors into HEK293 cells using the CRISPR/Cas9 system. The difference in integration efficiency may be due to the single copy integration by using the CRISPR/Cas9 system, while the piggyBac system often causes multiple copy integration 28, 29.

DISCUSSION Engineering synthetic miRNAs helped us gain insights into miRNA processing and maturation. We observed the 5’ end of mature miRNA precisely started at +1 position (Fig. 1 and Fig. S1), which might be due to accurate cleavage of synthetic miRNA precursors by both Drosha and Dicer in human cells 32. In contrast, the 3’ end of mature miRNA often stopped at +21 to +26 position (Fig. 1 and Fig. S1). Nevertheless, our results suggested that efficient RNAi in mammalian cells can tolerate a few unpaired sequences to the target gene at the 3’ end of mature miRNA. It has been reported that the precise cleavage of pre-miRNA by Dicer requires 2-nt distance between the cleavage site and the loop region, following a 19-nt stem region 4. Interestingly, our optimized pri-miRNA engineering strategy is similar to this premiRNA design strategy, which might allow the precise cleavage by both Dicer and Drosha. In mammalian genome, many miRNAs are grouped into clusters, sharing similar expression patterns, promoters and often target genes

1, 3

. However, whether miRNAs in the

cluster function differently from single miRNAs remains incompletely understood. By constructing and characterizing a series of synthetic miRNA clusters, we showed that miRNA maturation pattern was highly consistent regardless of miRNA precursor position in the cluster (Fig. 3), suggesting that microprocessing of miRNA precursors in the same transcript is highly modular and independent. We further demonstrated that individual miRNAs retained a potent RNAi efficiency while increasing the number of miRNA precursors in the cluster (Fig. 4A). Similar to previous finding by using an in vitro transcribed siRNA pool

33

, synthetic

miRNA cluster can be used to efficiently repress on-target gene expression and keep a low off-target effect when individual miRNAs repress the same target gene (Fig. 4B).



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Hairpin structures in synthetic miRNA and shRNA clusters may cause random 25, 31

. We also found that

sequence deletion when integrated into mammalian genome

integration efficiency of miRNA clusters decreased while increasing the number of miRNA precursors assembled in the cluster, and we failed to detect obvious genome integration when the cluster contained more than 9 miRNA precursors by using lentiviral system (Fig. 5). In addition, it has been recently shown that lentiviral vectors bearing transcription activatorlike effector (TALE) genes are prone to deletions and rearrangements in mammalian cells through recombination events involving TALE repeat domains

34

. In contrast, recoding TALE 35

with non-repetitive domains enables the generation of functional lentivirus

. It will be

interesting to assay whether replacing repeat pri-miR-155 backbones with non-repetitive miRNA backbones can increase the integration efficiency of synthetic miRNA cluster by using different integration methods. Recently, bacterial type II clustered regularly interspaced palindromic repeats (CRISPR) system has been repurposed as a tool for multiplex genome editing

28, 36

, and several

strategies have been developed to control gene expression at transcriptional level by using deactivated CRISPR associated nuclease 9 (dCas9)

37, 38

. Our synthetic miRNA cluster

system provides a modular and powerful tool for complex functional genomic studies to identify

multi-dimensional

gene

interactions

at

posttranscriptional

level,

which

is

complementary to the CRISPR/Cas technology. This cloning method can be further adapted to a hybrid RNAi and CRISPR/Cas system in mammalian cells, enabling simultaneous regulations at both transcriptional and posttranscriptional levels for tight and reversible control of gene expression. In addition, our synthetic miRNA cluster platform allows coexpression of multiple miRNAs and gene of interests driven by a single Pol II promoter, which would inspire new strategy to engineer complex gene circuits for basic biological research and biomedical applications.

MATERIAL AND METHODS Reagents and enzymes Restriction endonuclease, polynucleotide kinase (PNK), T4 DNA ligase, Quick DNA ligase, Q5 High-Fidelity DNA Polymerase were purchased from New England Biolabs. Oligonucleotides were synthesized by Genewiz and Sangon Biotech. Oligonucleotide sequences are listed in Table S1. Gateway LR reaction (Life technologies) were performed by following manufacturer’s protocol. Cell culture and transfection HEK293 (293-H) and HEK293FT cell lines were purchased from Life Technologies. HEK293 cells or HEK293FT cells were cultured in high-glucose DMEM complete media (Dulbecco’s modified Eagle’s medium (DMEM), 4.5 g/L glucose, 0.045 units/mL of penicillin


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and 0.045 g/mL streptomycin and 10% FBS (Life Technologies) at 37 ºC, 100% humidity and 5% CO2. One day before transfection, ~ 7.5 × 104 HEK293 cells in 0.5 mL of high-glucose DMEM complete media were seeded into each well of 24-well plastic plates (Falcon). Shortly before transfection, the medium was replaced with fresh DMEM complete media. The transfection experiments were performed as described

21

by using either Lipofectamine LTX

(Life technologies) or Attractene transfection reagent (Qiagen). pDT7004 (pUBI-linker-NOS) that contains a maize ubiquitin promoter (UBI) followed by a NOS terminator with no proteincoding sequences between UBI and NOS was used to ensure equal amount of plasmid DNA 39

. The amount of plasmid DNA is listed in the Table S2. Cells were cultured for 2 days before

flow cytometry analysis, total RNA extraction, or puromycin selection. Fluorescence-Activated cell sorting measurement Cells were trypsinized 48 hr after transfection and centrifuged at 300 g for 7 min at 4 ºC. The supernatant was removed and the cells were resuspended in 1× PBS that did not contain calcium or magnesium. Fortessa flow analyzers (BD Biosciences) were used for fluorescence-activated cell sorting (FACS) analysis as described

40

with the following set of

settings. EBFP2 and TagBFP were measured using a 405 nm laser and a 450/50 filter with a photomultiplier tube (PMT) 270 V. EYFP was measured with a 488 nm laser and a 530/30 filter using a PMT 210 V. mKate2 was measured with a 561 nm laser and a 670/30 filter using a PMT 380 V. iRFP was measured using a 640 nm laser and a 780/60 filter with a PMT 480 V. 5

5

For each sample, ~ 1 × 10 to ~ 5 × 10 cell events were collected. Construction of stable cell lines and genomic DNA extraction For the integration experiments mediated by CRISPR/Cas9, an integration vector expressing miRNA cluster (pT2 vector) was co-transfected with the human codon-optimized Cas9 expressing vector (pZD-CAG-hCas9) and T2 gRNA expressing vector (pgRNA-T2) into HEK293 cells. For piggyBac transposon system

41

, an integration vector expressing synthetic

miRNA cluster (pB vector) was co-transfected with the transponsase expressing vector (pBase) into HEK293 cells. Stable clones were selected with 1 µg/mL of puromycin (Life technologies) post-transfection 2 days. For the lentiviral system, a lentiviral vector expressing miRNA cluster (pLV vector) was co-transfected with a packaging vector pCMV-dR8.2 dvpr and an envelope vector pCMV-VSVG (Addgene) into HEK293FT cells in 12-well plates. Then the pseudovirus was harvested twice at 48 and 72 hr after transfection. ~ 0.5× 104 HEK293 cells were seeded into each well of 24-well plastic plates and grown for ~ 24 hr. After removing cell debris, the virus was added to HEK293 cells along with 8 µg/mL polybrene (Sigma). The medium was changed at 12 hr post-infection and stable clones were selected with 1 µg/mL of puromycin after infection for 2 days. Genomic DNA was extracted from stable cell lines by using TIANamp Genomic DNA Kit (Tiangen). The LA Taq DNA Polymerase with GC Buffer (Takara) was used for miRNA cluster



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integrity analysis. Genomic DNA from stable cells integrated with different miRNA cluster expression vectors were amplified at the different optimized conditions. The primer sets used in PCR are listed in Table S1. RNA extraction and quantitative RT-PCR The RT-PCR procedure was performed as described

40

. RNA was extracted from the

transfected cells by using the miRNeasy Mini Kit (Qiagen). The miScript II RT Kit (Qiagen) was used for miRNA expression analysis. The real-time PCR reactions were performed in triplicate, using SYBR Select Master Mix (Life Technologies). Relative changes in gene expression were calculated using the 2−∆∆CT method. The miR-FF8 expression level was used as a normalization control. The primers used in quantitative RT-PCR are listed in Table S1. RNA library preparation, sequencing and data analysis The plasmid information is listed in Table S2. Total RNA was extracted using TRIzol (Life Technologies) 48 hr post-transfection as described in the manual and the quantity of total RNA was analyzed by Agilent 2100 bioanalyzer (Agilent). The small RNA library preparation and single-end 50-bp sequencing were performed by Berry Genomics using Hiseq 2500 (Illumina). MirDeep2 was used to analyze the small RNA sequencing data

17

. Briefly, the Bowtie2

index was created based on the miRNA precursors, and single-end reads were aligned directly to this index using mirDeep2 with the default settings. Then, for each sample, the output files generated by mirDeep2 were merged and the scripts based on the Ruby language were used to integrate alignment information. Plasmid DNA constructs The information of plasmid DNA constructs is available at NAR Online.

ACCESSION NUMBERS The GEO accession numbers for small RNA sequencing data is GSE71088.

ACKNOWLEDGEMENT We thank members of Xie lab for helpful discussions. We thank Bing Liu and Huiya Huang for technical support. We thank Lian Shen, Jin Gu and Michael Q. Zhang for insightful discussions.


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FUNDING The research is supported by National Natural Science Foundation of China (31471255 to Z.X.; 91229201 to S.L.).

AUTHOR CONTRIBUTIONS Z.X. and T.W. conceived of the ideas implemented in this work. T.W. performed most of the experiments. Y.X. carried out small RNA sequencing and genome integration experiments. Z.X., T.W., A.T. and S.L. performed data analysis. Z.X. supervised the project. Z.X. and T.W. wrote the paper.

COMPETING FINANCIAL INTERESTS A pending patent application recently submitted by the authors is related to certain aspects of the work described in this manuscript.

SUPPLEMENTARY INFORMATION Supplementary information includes four figures and five tables.

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FIGURE LEGENDS Fig. 1. Design and characterization of synthetic miRNA precursor. (A) Schematic representation of synthetic miRNA precursor based on the murine pri-miR-155. Black letters indicate the flanking region; purple Ns designate the antisense (5p) strand; green Ns designate the sense (3p) strand; blue letters indicate the terminal loop. The expected mature miRNA is from 5p +1 to 5p +21, in which the GC content of the first four nucleotides was lower than that of the last four nucleotides. Blue ring, 5’-end of synthetic miRNA precursor; yellow ring, 3’-end of synthetic miRNA precursor. (B) Schematic representation of the maturation pattern of synthetic miRNA precursors analyzed by small RNA sequencing analysis (see details in Extended Experimental Procedure). (C) Schematic representation of the maturation pattern of synthetic miRNA precursors miR-RR13 with different stem length analyzed by small RNA sequencing analysis. Each precursor was drawn by using the same set of annotations shown in Fig. 1A. Orange and dark blue letters indicate the different nucleic acids in antisense and sense strands with varying stem length. For simplicity, dots represent the rest of flanking sequences of pri-miR-155 backbone. (D) The expression level of mature miRNAs generated from the precursors with varying stem length. MiR-FF8 was used as an internal control. The relative miRNA level was calculated by using the total reads of a given


Page 13 of 19

1 2 3 4 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 59 60


mature miRNA divided by the total reads of the mature miR-FF8 (see details in Extended Experimental Procedure). Fig. 2. The hierarchical assembly of synthetic miRNA cluster. Hairpin, synthesized miRNA precursor oligo; B in purple circle, BsaI; E in pink circle, Esp3I; numbers in orange bars, different overhangs released by Esp3I or BsaI digestion; 5’ and 3’ in blue bars, 5’ and 3’ flanking regions respectively; pMR, miRNA precursor construct; pAD, adapter construct; pMM, intermediate construct; pSMC, cluster carrier construct; TetR, tetracycline resistance gene; KanR, kanamycin resistance gene; AmpR, ampicillin resistance gene; GOI, gene of interest; ccdB, ccdB toxin coding gene. Fig. 3. Maturation pattern of synthetic miRNA in the cluster. (A) The expression level of each synthetic miRNA in clusters containing the same set of synthetic miRNA precursors but in different orders. The upper panel shows the schematic representation, the same letter above each hairpin structure indicates the same synthetic pri-miRNA. HEK293 cells were cotransfected with indicated plasmids in Fig. S1. Each bar shows the mean (± s.d.) expression level of indicated synthetic miRNA measured from three independent experiments by quantitative RT-PCR at 48 hr after transfection. (B) The percentage of mature miRNA starting at position 5p +1 produced either from single miRNA precursors or from indicated clusters is shown in the scatter plot. Heatmap shows the results of paired t-test that was performed to evaluate the maturation pattern of single miRNA precursors or indicated clusters. Raw data used in the scatter plot and heatmap are listed in Table S4. (C) Schematic representation of the maturation pattern of synthetic miR-FF4 precursor (upper panel) and miR-RR1 precursor (lower panel). Purple arrow, the percentage of mature miRNA starting at position 5p +1 produced from indicated construct; green arrow, the percentage of mature miRNA starting at position 3p -1 produced from indicated construct. Fig. 4. Expression and function of synthetic miRNA in the cluster. (A, B) HEK293 cells were cotransfected with indicated plasmids in Table S2, and then measured by using a flow cytometer 48 hr after transfection. Each block or each bar shows mean ± s.d. from three independent experiments. hEF1α, human elongation factor 1α promoter; CMV, a constitutive cytomegalovirus promoter. (A) Effect of the number of miRNA precursors. Left panel shows the design of the fluorescent reporter assay. Upper right panel shows the expression level of miR-FF3 and miR-FF5 measured by quantitative RT-PCR. The number on the horizontal axis indicates the number of synthetic miRNA precursors in the clusters, while 1 or 1’ represent the construct expressing only miR-FF3 or miR-FF5. Red bars and blue bars represent the knockdown efficiency of miR-FF3 and miR-FF5 in the lower right panel. (B) Fluorescent reporter assay for measuring on-target and off-target effect with varying number of synthetic miRNA precursors. Left panel, design of the functional assay; upper right panel, schematic representation of miR-FF3 off-target and on-target sequences. In the lower right panel, the red line and blue line represent the intensity of on-target and off-target, respectively.



1 2 3 4 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 59 60

Page 14 of 19

Fig. 5. Genome integration of synthetic miRNA cluster. (A) Schematic representation of synthetic miRNA cluster constructs used in genome integration experiments. The construct information is listed in Table S2 and S4. pB, piggyBac transposon construct; pT2, CRISPR/Cas9 construct; pLV, lentiviral construct. The schematic representation of CRISPR/Cas9 mediated integration into human AAVS locus is shown in Fig. S4. (B) Evaluation of the integrity of miRNA clusters by PCR amplification using genomic DNA template after integration experiments by piggyBac transposon system (pB, left panel); CRISPR/Cas9 system (AAVS-T2, middle panel) and lentiviral system (pLV, right panel). Clusters with indicated number of synthetic miRNA precursors were transfected into HEK293 cells and integrated cells were screened in the presence of 1 µg/mL of puromycin. NC, negative control by using genomic DNA extracted from wild-type HEK293 cell; M, DNA ladder. (C) Changing of the frequency of EYFP positive cells in cell population without puromycin selection after integration experiments performed by using piggyBac transposon system (left panel) and CRISPR/Cas9 system (right panel). With pBase, transfection with both piggyBac transposon and transposase-expressing plasmids; W/O pBase, transfection with only piggyBac transposon plasmid; with Cas9, transfection with both pT2, Cas9- and gRNAexpressing plasmids; W/O Cas9, transfection with only pT2 and gRNA-expressing plasmids.


Page 15 of 19


Fig.1 A

5’ flanking region

GC%(+1~+4) < GC%(+18~+21) -1

+1 +2 +3 +4

5’

1.16% 44.69%

9.23% 13.50%

MiR-LZ3

45.88%

AAGACGAAGUU-UCGCACGG 86.10%

Relative miRNA level

D

AUG UGGC UU CUG UAAGAACCA ACCGCCGUUU C GAC AUUCUUGGU-UGGCGGCAG A UC UC G (Few valid reads) AG CACA 5.91%

13.33% AUG UGGC UA CUGUAAGAACCAU CCAGGCCGUUU Stem_17nt C GACAUUCUUGGUA-GGUCCGGCAG A UC UC G AG CACA 3.24%

74.85%

AUG 94.39% CC UGGC CUGUAAGAACCAUUA AGAUGCCGUUU Stem_19nt C GACAUUCUUGGUAAU-UCUACGGCAG A U C G 4.39% CAGU CACA 24.35% 73.49%

AUG CC UGGC CUGUAAGAACCAUUA AGAUUUGCCGUUU Stem_21nt C GACAUUCUUGGUAAU-UCUAAACGGCAG A U C G 1.48% CAGU CACA

3 2 miR-RR13 1 0

MiR-RR13

C Stem_15nt

MiR-RR1

-1

sense strand (3p)

98.51%

MiR-LZ1

+1 +2 +3 +4

3’ flanking region

B

terminal loop

antisense strand (5p)

+18 +19 +20 +21

3’

+18 +19 +20 +21

1 2 3 4 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 59 60

15nt

17nt

19nt 21nt Stem length

23nt

5.29% 4.46% 5.76%

AUG CA UGGC CUGUAAGAACCAUUAC GAUUUCAGCCGUUU Stem_23nt C GACAUUCUUGGUAAUG-CUAAAGUCGGCAG A UC UC G AG 71.49% CACA

ACS Paragon Plus Environment


Page 16 of 19

Fig.2 1 2 3 4 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 59 60

BsaI Esp3I n Overhangs released by BasI / Esp3I digestion 5’ 5’ flanking region B E

E

Step 1

E

E

a AD1 1 E

B B E 1 5’ ccdB 3’ 2

B B 2 5’ ccdB 3’ 3 E

E

E

B B 3 5’ ccdB 3’ 4 E

E

B B 4 5’ ccdB 3’ 5 E

E

B B 5 5’ ccdB 3’ 6 E

E

B B 6 5’ ccdB 3’ 7 E

pMR1

pMR2

pMR3

pMR4

pMR5

pMR6

TetR

TetR

TetR

TetR

TetR

TetR

E

1 miR-A 2 E

2 miR-B 3 E

E

3 miR-C 4 E

E

4 miR-D

5E

E

E

5 miR-E 6 E

6 miR-F 7 E

3’

E

3’ flanking region MiRNA precusor oligos

7 AD2 b E

pAD1

pMR1-A

pMR2-B

pMR3-C

pMR4-D

pMR5-E

pMR6-F

pAD2

TetR

TetR

TetR

TetR

TetR

TetR

TetR

TetR

B

B

B a AD1 1 miR-A 2 miR-B 3 miR-C 4 miR-D 5 miR-E 6 miR-F 7 AD2 b

E E a ccdB b B pMM1

pMM1-ABCDEF

KanR

KanR

Step 2

B

b AD3 1 miR-G 2 miR-H 3 miR-I

4 miR-J

B 5 miR-K 6 miR-L 7 AD4 c

pMM2-GHIJKL B

KanR B c AD5 1 miR-M 2 miR-N 3 miR-O 4 miR-P 5 miR-Q 6 miR-R 7 AD6 d pMM3-MNOPQR KanR

B

a lacZ d hEF1α GOI pSMC

Splicing donor site Splicing acceptor site Adaptor Synthetic miRNA precusors

B

AmpR

Step 3

hEF1α

GOI

Synthetic miRNA cluster AmpR


Page 17 of 19


Fig. 3

Percentage of mature miRNA starting at posiiton 5p +1 in miRNA clusters

18F hEF1α 18R hEF1α 1000 MiRNA expression level (a.u.)

12F 12R

a b c d e f

g h i

j k l

mn o p q r

g h i

mn o p q r

a b c d e f

Puro(R) j k l

Splicing donor site Splicing acceptor site Adaptor Synthetic miRNA precursors

Puro(R) The positions of miRNAs in the cluster

1 13 2 14 3 15 4 16 5 17 6 18 7 1

82

93

10 4 11 5 12 6 13 7 14 8 15 9 16 1017 1118 12

18F 18R

96.39%(single） 97.40%(12F）

96.94%(6F） 95.28%(18F）

MiR-FF4 3.26%(single） 2.24%(12F） 42.69%(single） 37.68%(12F）

2.72%(6F） 4.14%(18F）

37.77%(6F） 26.98%(18F）

MiR-RR1


47.42%(single） 53.73%(12F）

52.81%(6F） 63.11%(18F）

U6

miR-21

LZ3

FF5

RR12

RR2

RR8

RR1

FF7

RR11

LZ6

FF6

LZ5

LZ4

RR6

RR5

LZ1

C

RR4

1

FF4

10

FF3

U6

100

miR-21

LZ3

FF5

RR12

RR2

RR8

RR1

RR6

RR5

LZ1

RR4

FF4

FF3

U6

miR-21

FF5

RR2

RR1

FF4

RR6

FF3

MiRNA expression level (a.u.)

MiRNA expression level (a.u.)

1 A a b c d e f a b c d e f g h i j k l 6F 12F 2 Puro(R) Puro(R) 3 hEF1α hEF1α d e f a b c g h i j k l a b c d e f 6R 12R 4 5 Puro(R) Puro(R) hEF1α hEF1α 6 The positions of miRNAs in the cluster The positions of miRNAs in the cluster 7 1000 1 4 2 5 3 6 4 1 5 2 6 3 6F 1000 1 7 2 8 3 9 4 10 5 11 6 12 7 1 8 2 9 3 10 4 11 5 12 6 6R 8 9 100 100 10 11 12 10 10 13 14 1 1 15 16 17 B 100% 18 Cluster 19 75% 6F 20 6R p-value 12F 18F 21 1.00 12R 50% 18F 22 12R 18R 12F 23 0.10 25% 6R 24 6F 25 0% single 0.01 26 0% 25% 50% 75% 100% 6F 6R 12F12R18F18R 27 Percentage of mature miRNA starting at position 5p +1 in single miRNA precursor 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 59 60


Page 18 of 19

A

miR-FF3 Puro(R)

hEF1α

miR-FF5 Puro(R)

hEF1α

Puro(R)

hEF1α

1, ...,16

Puro(R)

hEF1α CMV

iRFP iRFP

TagBFP hEF1α 4x FF5 TagBFP

mKate2 hEF1α 4x FF3 mKate2

B

100 miR-FF3 miR-FF5

80 60

miR-FF3 hEF1α

40 hEF1α

20 0

1

1.2 1

1’ 2 3 6 9 12 15 18 NC The number of miRNAs in the cluster mKate2 - 4x miR-FF3 target TagBFP - 4x miR-FF5 target

0.8

CMV

0.6 0.2 1

1’ 2 3 6 9 12 15 18 NC The number of miRNAs in the cluster

off-target 3’ A U A A C A U A A G U C G U A A G C 5’ G C C miR-FF3 5’ U A U U G U A U U C A G C C C A U A U C G 3’

on-target 3’ A U A A C A U A A G U C G G G U A U A G C 5’ 1, 2, ...,17 1

Puro(R)

Puro(R) iRFP iRFP

0.4

0

hEF1α

Puro(R)

C C A miR-FF3 5’ U A U U G U A U U C A G C A U U C G 3’

EBFP2 hEF1α 4x off-target EBFP2

mKate2 hEF1α 1x on-target mKate2


Fluorescence intensity (a.u.)

1 2 3 4 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 59 60

Fluorescence intensity (a.u.) miRNA expression level (a.u.)

Fig. 4

EBFP2 - 4x off-target mKate2 - 1x on-target

0.8 0.6 0.4 0.2 0

1 2

4 6 8 10 12 14 16 18 The number of miRNAs in the cluster

Page 19 of 19


Fig. 5 1, 2, ...,18

5’ITR hEF1α

EYFP

AAVS-T2 vector (pT2)

Puro(R) 2A

3’ITR

T2 hEF1α

10.0 5.0 3.0 2.0 1.5 1.0 .766 .500 .300 .150

0.75

2 miRNAs

3 miRNAs

With pBase 4 miRNAs

W/O pBase 5 miRNAs

0.5

6 miRNAs

0.75

9 miRNAs

12 miRNAs

15 miRNAs

18 miRNAs

0.5 0.25 0

2

6 10 14 18 2

6 10 14 182

6 10 14 18 2

6 10 14 18 2

6 10 14 18

WPRE 3’LTR Splicing donor site Splicing acceptor site Adaptor PCR primer sets Synthetic miRNA precursors

Lentiviral vector (pLV) Kb 10.0 5.0 3.0 2.0 1.5 1.0 .766 .500 .300 .150

Kb 10.0 5.0 3.0 2.0 1.5 1.0 .766 .500 .300 .150

0.25 0 1

Puro(R) 5’LTR SD cPPT hEF1α

T2

Kb 10.0 5.0 3.0 2.0 1.5 1.0 .766 .500 .300 .150

Integrated by pBase 1 miRNA

ψ

Puro(R) 2A

M 1 2 3 4 5 6 9 12 15 18 NC M Kb 10.0 5.0 3.0 2.0 1.5 1.0 .766 .500 .300 .150

Kb

1, 2, ...,18

Lentiviral vector (pLV)

AAVS-T2 vector (pT2)

PiggyBac vector (pB) M 1 2 3 4 5 6 9 12 15 18 NC M

1

EYFP

1, 2, ...,18

M 1 2 3 4 5 6 9 12 15 18 NC M

Kb 10.0 5.0 3.0 2.0 1.5 1.0 .766 .500 .300 .150

Integrated by Cas9

1 Freq. of EYFP+ cells (a.u.)

PiggyBac vector (pB)

Freq. of EYFP+ cells (a.u.)

1 A 2 3 4 5 6 B 7 8 9 10 11 12 13 14 15 16C 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 59 60

0.75

With Cas9

W/O Cas9

1 miRNA

2 miRNAs

3 miRNAs

4 miRNAs

5 miRNAs

6 miRNAs

9 miRNAs

12 miRNAs

15 miRNAs

18 miRNAs

0.5 0.25 0 1 0.75 0.5 0.25 0

2

5

8

11 2

5

8

11 2

5

8

11 2

Post-transfection (days)

Post-transfection (days)


5

8

11 2

5

8

11

Construction and Characterization of a Synthetic MicroRNA Cluster for

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