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Imaging Center (BIOPIC), School of Life Sciences, Peking University, Beijing 100871, China. ACS Synth. Biol. , 2018, 7 (1), pp 176–186. DOI: 10...
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Multiplexed sgRNA Expression Allows Versatile Single Nonrepetitive DNA Labeling and Endogenous Gene Regulation Shipeng Shao, Lei Chang, Yuao Sun, Yingping Hou, Xiaoying Fan, and Yujie Sun ACS Synth. Biol., Just Accepted Manuscript • DOI: 10.1021/acssynbio.7b00268 • Publication Date (Web): 29 Aug 2017 Downloaded from http://pubs.acs.org on August 30, 2017

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Multiplexed sgRNA Expression Allows Versatile Single Non-

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repetitive DNA Labeling and Endogenous Gene Regulation

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Shipeng Shao1, Lei Chang1, Yuao Sun1, Yingping Hou 1, Xiaoying Fan1, Yujie Sun1,*

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1

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(BIOPIC), School of Life Sciences, Peking University, Beijing 100871, China.

State Key Laboratory of Membrane Biology, Biodynamic Optical Imaging Center

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*E-mail: [email protected]

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*Phone#: 86-10-62744060

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ABSTRACT: :

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The CRISPR/Cas9 system has made significant contribution to genome

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editing, gene regulation and chromatin studies in recent years. High-throughput

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and systematic investigations into the multiplexed biological systems require

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simultaneous expression and coordinated functioning of multiple sgRNAs.

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However, current co-transfection based sgRNA co-expression systems remain

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inefficient and virus-based transfection approaches are relatively costly and labor

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intensive. Here we established a vector-independent method allowing multiple

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sgRNA expression cassettes to be assembled in series into a single plasmid. This

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synthetic biology-based strategy excels in its efficiency, controllability and

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scalability. Taking the flexibility advantage of this all-in-one sgRNA expressing

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system, we further explored its applications in single non-repetitive genomic locus

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imaging as well as coordinated gene regulation in live cells. With its full potency,

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our method will facilitate the research in understanding genome structure,

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function and dynamics.

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Keywords: CRISPR/Cas9, Single-guide RNA, Chromosomal dynamics, Single

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non-repetitive gene, Golden Gate cloning, Transcription regulation

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INTRODUCTION

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Since its discovery, the clustered regularly inter-spaced short palindromic

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repeats (CRISPR)-associated Cas9 nuclease has largely revolutionized the fields

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in genome editing, gene regulation and chromatin studies in live cells

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Compared to protein-based recognition systems such as ZFN and TALE,

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CRISPR recognizes target DNA via Watson-Crick base pairing, allowing it to

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perform high-throughput chromatin targeting in an effective and efficient way 2.

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Emerging new versions of the CRISPR/Cas9 system have been adopted to

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expand our capacity for precise genome manipulation

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carry tremendous potentials in both biomedical researches and therapeutic

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genomic targeting 8.

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1

.

3-7

. These powerful toolkits

Simultaneous expression and coordinated functioning of multiple sgRNAs in 9

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live cells are often necessary in circumstances such as simultaneous knockout

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and regulation of multiple endogenous genes 10. Notably, CRISPR-based labeling

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and imaging of genomic loci with non-repetitive sequences in live cells also

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require to tile the loci with multiple sgRNAs 11.

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There are several approaches available for simultaneous delivery of multiple

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sgRNAs to scale up the targeting capacity of the CRISPR/Cas9 system. For

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instance, cells can be transfected with a mixture of multiple sgRNA plasmids by

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chemi-transfection or electro-transfection

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transfection of different plasmids is relatively inefficient and also results in

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variable expression levels of each sgRNA in single cells. Similarly, delivery of

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multiple sgRNAs using lentivirus infection

12, 13

. However, such transient co-

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can also lead to variable efficacy in

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delivery and expression. Alternatively, although microinjection can deliver multiple

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sgRNAs into a single cell without the limitation of plasmid type and number

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suffers from low throughput and requires special equipment and superb skills.

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With the evolution of synthetic biology, new cloning methods have emerged in the

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last two years to achieve high speed, efficiency and flexibility in assembly of

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multiple DNA fragments

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used for fast assembly of TALE repeats

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sgRNAs

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reaction is quite limited following current protocols as the assembly efficiency

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decreases dramatically as the number of cassettes increases. Even though a

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recently developed hierarchical assembly method could assemble multiple

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sgRNAs, as it relies on receptor plasmids for every step, the whole procedure

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requires several rounds of transformation, verification, plasmid extraction, and

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thus on average takes more than 20 days to assembly 20 sgRNA expression

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cassettes into a single plasmid

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sgRNA expression system needs to balance in ease of implementation, delivery

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efficiency, precise stoichiometry control, and cost of time.

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, it

15-17

. For instance, the Golden Gate cloning method was 18

and for assembly of short serial

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. However, the number of sgRNA cassettes assembled in one

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. Collectively, a well-rounded multiplexing

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In this work, we have developed a hierarchical cloning strategy to assemble

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multiple sgRNA expression cassettes into a single vector. We demonstrated that

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this new approach is not only robust and time-saving in assembly of different

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numbers of sgRNA expression cassettes at will but also able to assure precise

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control of stoichiometry of different sgRNAs. Using this all-in-one sgRNA

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expressing system, we successfully labeled and imaged non-repetitive genomic

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loci, MUC4 and HER2 genes, in living human cells. Additionally, we demonstrated

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that the all-in-one sgRNA expressing system is highly efficient in gene activation

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and repression. Using multiple sgRNAs to tile the promoter of endogenous gene

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SOX2 to recruit multiple transcriptional regulators, we found that the regulation

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efficiency by this synergistic gene regulation approach was superior to that by

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single sgRNA and co-transfection of multiple sgRNAs. We also showed that the

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all-in-one sgRNA expressing system allows parallel expression of different

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sgRNAs with relatively stable stoichiometry in their expression level, leading to

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reliable simultaneous activation and/or repression of multiple endogenous genes

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in the same cell. In summary, our modular sgRNA assembly system can be

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readily automated and will be highly useful for applications in cell biology and

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genetics, such as gene editing, gene regulation, pathway engineering and live cell

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chromatin labeling.

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RESULTS

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Plasmid-independent hierarchical assembly of multiple sgRNA expression

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cassettes

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To achieve high-throughput assembly of multiple sgRNA cassettes, here we

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have developed a plasmid-independent, PCR-based hierarchical assembly

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strategy. Using a series of three one-pot Golden Gate cloning with type II

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restriction endonuclease, we demonstrated the robustness and high efficiency of

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our method in assembly of repeated units (Figure 1A). Firstly, PCR-amplified

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conventional or functionally modified sgRNA scaffolds and U6 promoter were

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ligated with respectively synthesized targeting oligos by Golden Gate cloning.

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Then the reaction mix was amplified by PCR with U6-forward and sgRNA-

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scaffold-reverse primers without purification (Figure 1B). Thirdly, we designed

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junctions allowing ordered ligation to form the intermediate fragments. We used

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these junctions to assemble five sgRNA cassettes into one by a second round of

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Golden Gate cloning (Figure 1C). Lastly, a third Golden Gate reaction was

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performed to assemble the five-cassette-intermediates into the final construct

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carrying all 20 sgRNAs. The whole assembly procedure takes about 4-5 days.

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Random selection of end clones were verified (Figure 1D). Aside from high-

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efficiency, high-speed and high-throughput in generating a multi-sgRNA cluster,

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our approach also provides the flexibility for assembling different numbers of

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sgRNAs using varied combinations of the forward and reverse primers. To see

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whether the multiplexing sgRNA expression system will influence the expression

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level of each sgRNA, we performed RT-PCR to quantify the expression level of

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individual sgRNA (Supplementary Figure 1). The results indicated that all sgRNAs

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were expressed at a similar expression level.

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Establishment of a stable cell line expressing the SunTag system

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We fused the SunTag signal amplification system

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to dCas9 for the

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enhancement of fluorescence signal that one sgRNA can recruit. A previous

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study has shown that telomeres labeled with dCas9-SunTag were nearly 20-fold

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brighter compared to those labeled by dCas9 without alteration of the telomere

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mobility

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SunTag has not been realized. We reasoned that with dCas9-SunTag,

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simultaneous expression of multiple sgRNAs in a single cell can realize non-

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repetitive chromosomal locus labeling with high quality and efficiency (Figure 2A).

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Transient expression of two components of the SunTag system usually

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results in either incomplete labeling or excessive background from unbound

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molecules. In order to minimize those effects, we integrated the SunTag

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expression cassette into the genome using the PiggyBac transposon system

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and generated a stable cell line with minimal expression level of dCas9-

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(GCN4)X24-P2A-BFP and scFV-sfGFP-GB1 (Figure 2B and Supplementary

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Figures 2 & 3). With the low expression level, diffusing dCas9 single molecules

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were able to be observed in the GFP channel (Supplementary Figure 4A) and

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repetitive chromosomal loci, such as telomeres or the 2rd exon of MUC4 gene,

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were successfully labeled with dCas9-SunTag in live MDA-MB-231 cells

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(Supplementary Figure 4B & C). In order to compare the signal-to-noise ratio

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(SNR) between dCas9-GFP and the dCas9-SunTag system, the tandem array of

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. However, labeling of non-repetitive chromosomal loci using dCas9-

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5S ribosomal DNA (5S rDNA) on chromosome 1, which consists of 17 repeats,

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was labeled and quantified (Supplementary Figure 5). The results showed that

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the SNR was improved nearly 6 folds with dCas9-SunTag. The significant

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improvement in SNR allows imaging with low laser power and short exposure

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time, enabling long-term tracking of chromosomal loci.

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Single non-repetitive sequence labeling by multiplexed sgRNA expression

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We next tried the multiple sgRNA expressing strategy for non-repetitive

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sequence labeling in living cells. We first chose MUC4 gene as a demonstration

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as it has tandem repeat regions advantageous for the validation by FISH.

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Specifically, 20 sgRNAs were deigned against a stretch of DNA (about 1.5 kb)

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and cloned into one plasmid by the hierarchical assembly method. The SunTag

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cell line was transfected with the all-in-one plasmid and imaged 24 h after

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transfection.

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To verify the specificity and efficiency of non-repetitive MUC4 gene labeling,

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we performed two-color imaging with CRISPR probes targeting the non-repetitive

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sequence in the first intron of MUC4 and FISH probes targeting the polymorphic

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tandem repeats in the third exon. Because the harsh conditions of FISH sample

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preparation disrupted the fluorescence signal of GFP, we performed immuno-

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fluorescence against GFP. Colocalization of the two channels indicated that the

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CRISPR probes indeed labeled the MUC4 locus (Figure 2C). In order to quantify

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the robustness of our method, we also measured the cell labeling efficiency and

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loci number per cell (Supplementary Figure 6).

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By labeling specific non-repetitive genomic loci with CRISPR, we could

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investigate chromosome reorganization at different cell cycle stages (Figure 2D &

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Supplementary Figure 7). Similar results were also obtained for another non-

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repetitive gene HER2 (Supplementary Figure 8). These results indicate that

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combination of the all-in-one sgRNA expression plasmid and SunTag signal

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amplification system can be used to label arbitrary sequences in the genome,

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visualize their positions in the nucleus, and study the relationship between the

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gene position and its expression 23.

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We further tracked the dynamics of the MUC4 locus labeled with dCas9-

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SugTag (Supplementary Movie 1). Two typical trajectories in the same cell were

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observed (Figure 3A). No obvious correlation was found between the two allelic

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loci, indicating the heterogeneity of the surroundings of allelic genes. We

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calculated the average mean square displacement of 17 different loci and

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extracted the anomalous diffusion scaling exponents (α = 0.34) (Figure 3B),

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indicating that the movement of chromosomal loci is subdiffusive. We also ruled

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out the possibility that the observed movement of chromatin locus was caused by

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localization error (Supplementary Figure 9) or stage drift (Supplementary Figure

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10).

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To obtain a more robust measurement of the subdiffusive behavior of the δ v(τ).

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MUC4 locus, we calculated the average velocity autocorrelation function C

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This function describes what degree the average velocity over a time interval δ is

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correlated with the average velocity over another time interval δ that is separated

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by τ from the first one

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. The correlation function C

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δ v(τ)

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different values of δ and plotted as a function of the time lag τ. For all δ, C

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dropped into negative values before finally decaying to zero, indicating the

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negative correlation of MUC4 loci (Figure 3C, left). We then analyzed the

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behavior of C

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shown (Figure 3C, right). This indicates that the motion of MUC4 segments

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possessed the same negative correlation property at different temporal scales.

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Taken together, the results indicate that the MUC4 locus underwent a ‘back and

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forward’ movement, i.e. motion in one direction is likely to be followed by motion

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in the opposite direction, which may arise from restoring forces of its surrounding

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chromatin fiber.

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Synergistic regulation of endogenous genes by multiplexed sgRNA

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expression

δ v(τ)

as a function of the ratio (τ/δ), and a single master curve was

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Besides the single non-repetitive DNA sequence imaging, the multiplexed

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sgRNA expression strategy can also be used for synergistic regulation of

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endogenous genes as multiple sgRNAs can recruit multiple copies of proteins to

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function synergistically. We designed sgRNAs targeting the human SOX2 gene in

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HEK293T cells (Figure 4A). We found that the efficiency of synergistic activation

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of endogenous genes was much higher than that of single sgRNA-mediated

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activation or cotransfection of multiple sgRNAs. Furthermore, similar results were

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obtained for Cas9-KRAB mediated SOX2 repression experiments (Figure 4B).

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Coordinated activation and repression of endogenous genes by multiplexed

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sgRNA

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To examine the capability of coordinated gene regulation of our multiplexed

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sgRNA expression method, we designed 20 sgRNAs each targeting a randomly

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chosen gene. HEK293T cells were transfected with the all-in-one sgRNA

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expressing plasmid with dCas9-SunTag-VP64 or dCas9-KRAB for activation or

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repression, respectively. The results indicate that all 20 randomly chosen genes

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were up-regulated or down-regulated simultaneously (Supplementary Figure 11 &

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Supplementary Figure 12).

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At last, we tested the all-in-one plasmid for simultaneous activation and

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repression of different genes in the same cell. Simultaneous up-regulation of a

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subset of endogenous genes while down-regulation of another subset of

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endogenous genes in a defined manner can open up novel opportunities for

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systems biology as it raises the possibility of manipulating transcriptional

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networks. We used functional modified sgRNA for this application as different

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sgRNAs with different aptamers insertion can recruit different transcriptional

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regulators (Figure 5A). The sgRNAs targeting the first group of 10 genes were

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inserted with PP7 at their tetraloop and loop2, while sgRNAs targeting the second

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group of 10 genes were inserted with MS2 at the same position 6. With co-

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transfection of tdPCP-VPR

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expressing plasmid, regulation of different genes was as expected and the

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regulation result was orthogonal for the corresponding genes (Figure 5B). These

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results indicate that the multiplexed sgRNA expression strategy can be expanded

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with modified sgRNA for multi-function applications.

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, tdMCP-KRAB, dCas9, and the all-in-one sgRNA

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DISCUSSION

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CRISPR based technologies have revolutionized the fields of genome editing

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and gene regulation. Simultaneous expression and coordinated functioning of

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multiple sgRNAs will add a new dimension to the evolving CRISPR system,

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further facilitating our understanding of the physiological and pathological

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conditions.

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Here we have reported a hierarchical assembly strategy for rapid assembly

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of multiple sgRNA expression cassettes into a single vector. Compared to the

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current methods, this system ensures high speed, efficiency, capacity and

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flexibility. Based on Golden Gate cloning, our hierarchical assembly strategy only

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takes 4-5 days to assemble 20 sgRNA expression cassettes into one plasmid with

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high fidelity.

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Moreover, the hierarchical assembly strategy also offers the flexibility in

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tuning the number of sgRNAs assembled simply by choosing different

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combination of amplification primers. Meanwhile, the expression level of different

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sgRNAs in the all-in-one vector could also be differentiated by using different

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promoters

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sgRNA expression system can also be used in expressing sgRNAs for other

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orthogonal CRISPR systems, including SA Cas9

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single all-in-one vector can be used for multiplexing operations on the same

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genomic region, such as imaging, transactivation, repression and chromatin

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epigenetic modification 29.

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. Additionally, besides the SP CRISPR system, the multiplexed

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, Cpf1

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and C2c2

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. Lastly, a

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In this work, we have demonstrated assembly of 20 sgRNAs in one single

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vector. Regarding the capacity of the all-in-one sgRNA expression vector, as the

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upper limit of the sgRNA number that can be assembled is determined by the

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carrying capacity of the plasmid, there are several possible ways to enhance the

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system. Firstly, generating multiple sgRNAs from mRNA

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sgRNAs

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needed for the transcription of multiple sgRNAs. Secondly, since the longest

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fragment in our all-in-one construct is U6 promoter, using other expressing

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systems will further increase the capacity of our cloning methods. With the

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improvement of the DNA assembly methods, it is possible that a library of

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sgRNAs targeting a long DNA sequence can be assembled into one vector, which

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will greatly aid on the study of structure and dynamics of whole chromosomes or

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large chromatin domains in living cells. So far, we have only demonstrated the

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functionality of our all-in-one multiple sgRNA expression vectors in cultured cells.

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Due to the excessive length and repetition of the multiple sgRNA expression

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vector, it would be quite challenging to pack it in virus and apply it in in vivo

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studies.

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METHODS

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Hierarchical assembly of multiple sgRNA expression cassettes

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or tRNA-flanked

can make the construct much shorter because only one promoter is

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All primers were ordered from Ruibo Biotech (Beijing). The U6 promoter,

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conventional and modified sgRNA expression cassettes were amplified from

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plasmids

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psgRNA2.02-MS2-ccdB (Addgene #: 99911, Supplementary Map 2), and

psgRNA-ccdB

(Addgene

#:

99915,

Supplementary

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Map

1),

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psgRNA2.02-PP7-ccdB (Addgene #: 99912, Supplementary Map 3). The oligos

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(F + R, 100 µM each) for each targeting sgRNA were phosphorylated by T4 PNK

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(NEB) and annealed in a thermocycler by using the following parameters: 37 °C

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for 30 min; 95 °C for 5 min; ramp down to 25 °C at 5 °C min-1. The

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phosphorylated and annealed oligos were then diluted to 1:100 by adding 1 µl

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oligos to 99 µl ddH2O.

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For the first assembly step, U6 promoter (10 ng), annealed oligos (1 µM) and

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sgRNA scaffold (5 ng) were mixed with BsmBI (1 µl, NEB) and T4 ligase (0.5 µl,

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NEB) together for Golden Gate reaction in 20 separate tubes by using the

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following parameters: 37 °C for 10 min; 16 °C for 10 min; 10 cycle; 55 °C for 10

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min; 85 °C for 10 min. The reaction mix was then diluted by 200 folds in ddH2O. 1

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µl diluted mix was used as template for PCR reaction. The primer sequence and

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allocation have been described in Supplementary Tables 1 and 2. After the PCR

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reaction, gel electrophoresis was used to check the reaction. After gel extraction,

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a QIAquick gel extraction kit was used to ensure that the product contains only

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the intended U6+oligos+sgRNA ligation product.

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For the second assembly step, the 20 ligation fragments (10 ng each) were

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mixed in 4 separate tubes (1-5 in tube #1, 6-10 in tube #2, 11-15 in tube #3, 16-

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20 in tube #4) with BsaI (1 µl, NEB) and T4 ligase (0.5 µl, NEB) together for

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Golden Gate reaction by using the following parameters: 37 °C for 10 min; 16 °C

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for 10 min; 10 cycle; 37 °C for 10 min; 85 °C for 10 min. The reaction mix was

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then diluted by 200 folds in ddH2O. 1 µl diluted mix was used as template for the

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PCR reaction. The primer sequences and allocation were described in

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Supplementary Tables 1 and 2. After the PCR reaction, gel electrophoresis was

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used to check the reaction. After gel extraction, a QIAquick gel extraction kit was

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used to ensure that the product contains only the intended 5 ligation length

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product. This PCR step needs to be optimized to ensure the maximum

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productivity due to the repetitive sequence of the 5 sgRNA expression cassettes.

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If the intermediates (5 sgRNA expression plasmids) were needed, the Golden

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Gate reaction should be performed with the corresponding receptor plasmids.

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For the third assembly step, the 4 ligated fragments (100 ng each) and 50 ng

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receptor plasmid pMulti-sgRNA-LacZα (Addegene #: 99913, Supplementary Map

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4) or pMulti-sgRNA-LacZα-DsRed (Addegene #: 99914, Supplementary Map 5)

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were mixed with BpiI (1 µl, Thermo Fisher Scientific) and T4 ligase (0.5 µl, NEB)

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together for Golden Gate reaction by using the following parameters: 37 °C for 10

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min; 16 °C for 10 min; 10 cycle; 37 °C for 10 min; 85 °C for 10 min. The

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competent E. coli strain Stbl3 (TransGen Biotech) was transformed with the final

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reaction mix and cultured in 30 °C to minimize the opportunity of losing the repeat

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units. The plasmids were linearized and checked by gel electrophoresis to ensure

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that the final plasmid contains the proper length of repeats. The more detailed

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information about the protocol to assemble 20 sgRNAs was included in

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Supplementary Information as Supplementary Protocol 1.

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Construction of other plasmids used in this work

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The NLSSV40-dCas9-(NLSSV40)X3-(GCN4-V4)X24-NLSSV40-P2A-BFP fragment

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was amplified by PCR from plasmid pHRdSV40-NLS-dCas9-(GCN4-V4)X24-NLS-

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P2A-BFP-dWPRE (Addgene #: 60910) and then ligated into PiggyBac plasmid

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pB-TRE3G-BsmBI-EF1α-PuroR-P2A-rtTA

by

Golden

Gate

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assembly with BsmBI and T4 ligase (NEB). The scFV-sfGFP-GB1-NLSSV40

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fragment was amplified from plasmid pHR-scFV-GCN4-sfGFP-GB1-NLS-dWPRE

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(Addgene #: 60906) and then ligated into PiggyBac plasmid pB-TRE3G-BsmBI-

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EF1α-HygroR-P2A-rtTA (home-made) by Golden Gate assembly with BsmBI and

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T4 ligase (NEB). The tdMCP fragment was amplified from phage-ubc-nls-ha-

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tdMCP-gfp (Addgene #: 40649), and the KRAB was amplified from pHAGE-EF1α-

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dCas9-KRAB (Addgene #: 40649) and then ligated into plasmid pB-CMV (home-

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made). The tdPCP fragment was amplified from phage-ubc-nls-ha-tdPCP-gfp (A

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Addgene #: 40650), and the VPR was amplified from SP-dCas9-VPR (Addgene

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#: 63798) and then ligated into plasmid pB-CMV (home-made). The telomere,

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rDNA10, MUC4-E2 targeting sgRNAs and other sgRNA expression plasmids

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were made according to procedures described previously 6. All primers and

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sequences used in this work were listed in Supplementary Tables 1-9.

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Cell Culture, Transfection, Stable Cell Line Construction

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Human breast cancer cell line MDA-MB-231 and HEK293T were maintained

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in Dulbecco’s modified Eagle medium (DMEM) with high glucose (Lifetech), 10%

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FBS (Lifetech), 1X penicillin/streptomycin (Lifetech). All cells were maintained at

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37 °C and 5% CO2 in a humidified incubator. All plasmids were transiently

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transfected with Lipofectamine 2000 (Lifetech) in accordance with the

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manufacturer’s protocol. To construct a stable cell line, MDA-MB-231 cells were

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spread onto a 6-well plate one day before transfection. On the next day, the cells

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were transfected with 500 ng pB-dCas9-(GCN4)X24, 500 ng pB-scFV-sfGFP, and

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200 ng pCAG-hyPBase using Lipo 2000. Hygromycin (200 µg/ml) and puromycin

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(5 µg/ml) were used for the selection of positive clone for about 2 weeks. Cells

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with proper expression level of dCas9-(GCN4)X24 and scFV-sfGFP were selected

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using fluorescence-activated cell sorting analysis (FACS). Cells were trypsinized

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and centrifuged at 300xg for 2 min at RT. The supernatant was removed, and the

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cells were resuspended in 1× PBS. Fortessa flow analyzers (BD Biosciences)

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were used for FACS with the following settings. BFP was measured using a 405

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nm laser and a 450/50 filter and sfGFP was measured using a 488 nm laser and

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a 530/30 filter. The FACS results were analyzed by FlowJo.

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To choose a “minimal expression level” of dCas9-SunTag stable clone, a

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window (as indicated by the yellow window in Supplementary Figure 2A) which is

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far lower than the averaged transient expression level (several hundred times

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lower) and slightly higher than the untransfected cells was applied while gating

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the cells. After the expansion of each clone, the expression level should be

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compared with the untransfected cells (Supplementary Figure 2B). A locus with

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low repetitive sequence or non-repetitive sequence was labeled to quantified the

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labeling results. Based on the labeling performance, optimization can be achieved

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by choosing a fluorescence intensity gradient. The clone with the best

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performance was chosen as the stable cell line in the following experiments.

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FISH and Immunofluorescence

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The FISH probe targeting the third exon of MUC4 was directly synthesized

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by Invitrogen with Cy5 labeled at the 5’ end. The sequence of the FISH probe

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was as following: 5’-Cy5-CTTCCTGTCACCGAC-3’. The transfected cells were 17

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washed with PBS briefly once and incubated with extraction buffer (0.1 M PIPS, 1

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mM EGTA, 1 mM MgCl2, 0.2% TritonX-100) for 1 min to extract cytoplasm

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diffusive proteins. Cells were then washed once with PBS and fixed with 4% PFA

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for 15 minutes. Cells were permeabilized with 0.1% saponin/0.1% Triton X-100 in

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PBS for 10 min at room temperature (RT) and then washed twice in PBS for 5

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min at RT. Cells were incubated for 1 h in 20% glycerol/ PBS at RT and then

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frozen/ thawed 3 times in liquid nitrogen. Cells were washed twice in PBS for 5

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min at RT, incubated in 0.1 M HCl for 30 min at RT and then washed in PBS for 5

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min at RT. Cells were permeabilized with 0.5% saponin/0.5% Triton X-100 in PBS

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for 30 min at RT and washed twice in PBS for 5 min at RT. Cells were

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equilibrated in 50% formamide/2x SSC for 20 min at RT. The probe was added in

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hybridization buffer and the dish was warmed to 78 °C for precisely 2 min. Cells

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were incubated overnight at 37 °C in a dark humidified chamber. The next day,

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cells were washed in the following buffer sequentially, 50% formamide/2X SSC

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for 15 min at 45 °C, 0.2X SSC for 15 min at 63 °C, 2X SSC for 5 min at 45 °C.

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and 2X SSC for 5 min at RT.

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For immunofluorescence, cells were incubated in 0.5% Triton followed by 30

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min 5% BSA blocking at RT. The cells were then stained with human anti-GFP

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antibodies (proteintech #66002-1-Ig) in blocking buffer for 60 min, washed with

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PBS, and then stained with Cy3-labeled secondary antibodies in blocking buffer

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for 1 h. The labeled cells were washed with PBS, post-fixed with 4% PFA for 10

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min at RT. Lastly, the cells were stained with DAPI (5 µg/ml in PBS) for 2 min in

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at RT and then wash 3 times with PBS.

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qRT–PCR About 48 h post transfection in six-well plates with proper amount of plasmids,

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total RNA were extracted by TRIzol (Invitrogen). Complementary DNAs (cDNAs)

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were synthesized using RevertAid First Strand cDNA synthesis Kit (Thermo

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Fisher Scientific) and qPCR was performed using SYBR Green PCR Master Mix

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(Roche). GADPH was used as the internal reference. All primers used in the

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qPCR step were designed by primer-BLSAT on NCBI website. We used the

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“semi-quantitative PCR” to analysis the data. Briefly, in each group (experimental

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and control), the GADPH and the gene to be examined (Sample) were amplified

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using corresponding primers in two different tubes with the same genomic DNA

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input (10 ng). Each group has three biological replicates. We performed a two-

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step qRT- PCR to quantify the expression level of the genes of interest. The

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program is comprised of two reactions: one reaction for the conversion of RNA to

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cDNA and a separate second reaction for qPCR amplification of the gene of

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interest. The set of thermal profiles for two-step qRT-PCR is given as following.

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Profile 1, directs cDNA synthesis by reverse transcriptase using a 30-minute,

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42°C synthesis protocol. Profile 2, Segment 1 directs a 95°C incubation, used for

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qPCR enzyme activation, and Segment 2 directs 40 cycles of qPCR amplification.

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To quantify the expression level of the genes of interest, the Ct values of

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both the sample and GAPDH were calculated by setting a cutoff of the relative

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fluorescence intensity. The threshold value has to be set at a point where all

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samples being analyzed display the same rate of increase in the fluorescence

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intensity, and ideally this increase responds to an exponential function. We used

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the amplification-based threshold algorithm (Default Method in the MxPro QPCR

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Software) to determine the Ct value automatically. Then the change of RNA

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expression level is calculated as follows:

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CtSample-CtGAPDH=∆Ct

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Relative sample RNA expression level = 2-∆Ct

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RNA expression level change = 2-∆Ct(experimental)/2-∆Ct(control)

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Image acquisition and analysis

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Briefly, all images were taken on a custom Olympus IX83 inverted

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microscope equipped with a 100X UPlanSApo, N.A. = 1.49, oil-immersion phase

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objective and Andor iXon Ultra897 EMCCD. The details about the configurations

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of the custom microscope was listed in Supplementary Table 10. The microscope

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stage incubation chamber was maintained at 37 °C and 5% CO2. A 405-nm laser

419

was used to excite BFP and DAPI; a 488-nm laser was used to excite sfGFP; a

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561-nm laser was used to excite Cy3; a 647-nm laser was used to excite Cy5.

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The laser power was modulated by an acousto-optic tunable filter (AOTF). Cells

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were washed three times by PBS and imaged in phenol red-free DMEM (Thermo

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Fisher, 21063029) for live cell imaging. Movies of short time scale chromatin loci

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dynamics in living MDA-MB-231 cells were acquired at 50 ms exposure time (20

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Hz) with only one layer. We used highly inclined thin illumination (HILO) to avoid

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stray-light reflection and to reduce background from cell auto-fluorescence in the

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live cell tracking experiment. For the experiment to count the number of loci in

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each cell and the percentage of positive cell, cells were fixed by 4% PFA and

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stained by DAPI for 2 min. Then images were acquired in PBS by 30 layers with a

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step size of 0.5 µm, each layer with a 500 ms exposure time in wide-field

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illumination mode.

432

Analysis of MSD and velocity autocorrelation was carried out using custom

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MATLAB scripts. The MSD analysis method has been described previously 6. To

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quantify the influence of localization error on the accuracy of MSD analysis, we

435

compared the localization error with displacement of successive frame. The

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localization error is calculated as followed:   A   ,  = B + ×   2πσ σ



    



437

s = (σx + σy)/2

438

Where B is the background level, A is the height of the Gaussian peak, x0 is

439

the x center of the Gaussian peak, y0 is the y center of the Gaussian peak, σx is

440

the x standard deviation, σy is the y standard deviation, and s is the localization

441

error.

442 443

We then calculated all displacements between of two successive frames in the trajectories as followed:  = ∆0 2 + ∆0 2 #$

444

where and ∆% and ∆% were the difference between two successive frames.

445

Average velocity autocorrelation function was calculated as described

446

previously by Joseph S. Lucas et al. 24. The function can be expressed as follows: & ' ( ) = < +, + ) ∙ +, > +, =

/, + 0 − /, 0

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Where /, is the two-dimensional coordinate at time point ,, δ is the time interval

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over which the average velocity is calculated and ) is the lag time over which the

449

correlation in velocities is calculated.

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AUTHOR INFORMATION

451

Corresponding Author

452

*Phone#: 86-10-62744060

453

Author Contributions

454

S.S. and Y.S. conceived and designed the experiments. S.S. and YA.S.

455

performed the cloning experiments. S.S., L.C. and Y.H. performed the FISH

456

experiments. S.S. and X.F. performed the qPCR experiments. S.S. analyzed all

457

the data. S.S. and Y.S. wrote the manuscript.

458

Notes

459

The authors declare no competing financial interests.

460

ACKNOWLEDGMENTS

E-Mail: [email protected]

461

We thank Dr. Ronald D. Vale (University of California, San Francisco) for

462

providing SunTag plasmids, Dr. Wensheng Wei (School of life sciences, Peking

463

University) for providing sgRNA expression plasmids, Dr. Feng Zhang (Broad

464

Institute) for providing plasmid px330 (Addgene Plasmid #42230), Dr. Scot Wolfe

465

(University of Massachusetts Medical School) for pHAGE-EF1α-dCas9-KRAB

466

(Addgene Plasmid #50919), Dr. George Church (Harvard University) for SP-

467

dCas9-VPR (Addgene Plasmid #63798) and Dr. Wei Guo (Department of Biology,

468

University of Pennsylvania) for providing the MDA-MB-231 cell line. We also

469

thank Ms Xuefang Zhang from the National Center for Protein Sciences Beijing

470

(Peking University) for her excellent assistance with FACS. This work is

471

supported by grants from the 863 Program SS2015AA020406 and National

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Science Foundation of China 21573013, 21390412, 31271423 and 31327901, for

473

Y.S.

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474

SUPPORTING INFORMATION

475

Supplementary protocol 1, Supplementary Figures 1-12, Supplementary Tables

476

1-10, and Supplementary Plamid Maps 1-5.

477

REFERENCES

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[1] Barrangou, R., and Doudna, J. A. (2016) Applications of CRISPR technologies in research and beyond, Nat. Biotechnol., 933-941. [2] Gaj, T., Gersbach, C. A., and Barbas, C. F., 3rd. (2013) ZFN, TALEN, and CRISPR/Cas-based methods for genome engineering, Trends Biotechnol. 31, 397-405. [3] Dominguez, A. A., Lim, W. A., and Qi, L. S. (2016) Beyond editing: repurposing CRISPR-Cas9 for precision genome regulation and interrogation, Nat. Rev. Mol. Cell Biol. 17, 5-15. [4] Fu, Y., Rocha, P. P., Luo, V. M., Raviram, R., Deng, Y., Mazzoni, E. O., and Skok, J. A. (2016) CRISPR-dCas9 and sgRNA scaffolds enable dual-colour live imaging of satellite sequences and repeat-enriched individual loci, Nat Commun 7, 11707. [5] Chen, B., Hu, J., Almeida, R., Liu, H., Balakrishnan, S., Covill-Cooke, C., Lim, W. A., and Huang, B. (2016) Expanding the CRISPR imaging toolset with Staphylococcus aureus Cas9 for simultaneous imaging of multiple genomic loci, Nucleic Acids Res. 44, e75. [6] Shao, S., Zhang, W., Hu, H., Xue, B., Qin, J., Sun, C., Sun, Y., Wei, W., and Sun, Y. (2016) Long-term dualcolor tracking of genomic loci by modified sgRNAs of the CRISPR/Cas9 system, Nucleic Acids Res. 44, e86. [7] Ma, H., Tu, L. C., Naseri, A., Huisman, M., Zhang, S., Grunwald, D., and Pederson, T. (2016) Multiplexed labeling of genomic loci with dCas9 and engineered sgRNAs using CRISPRainbow, Nat. Biotechnol. 34, 528-530. [8] Xiao-Jie, L., Hui-Ying, X., Zun-Ping, K., Jin-Lian, C., and Li-Juan, J. (2015) CRISPR-Cas9: a new and promising player in gene therapy, J. Med. Genet. 52, 289-296. [9] Sakuma, T., Nishikawa, A., Kume, S., Chayama, K., and Yamamoto, T. (2014) Multiplex genome engineering in human cells using all-in-one CRISPR/Cas9 vector system, Scientific reports 4, 5400. [10] Jusiak, B., Cleto, S., Perez-Pinera, P., and Lu, T. K. (2016) Engineering Synthetic Gene Circuits in Living Cells with CRISPR Technology, Trends Biotechnol. 34, 535-547. [11] Chen, B., Gilbert, L. A., Cimini, B. A., Schnitzbauer, J., Zhang, W., Li, G. W., Park, J., Blackburn, E. H., Weissman, J. S., Qi, L. S., and Huang, B. (2013) Dynamic Imaging of Genomic Loci in Living Human Cells by an Optimized CRISPR/Cas System, Cell 155, 1479-1491. [12] Cheng, A. W., Wang, H., Yang, H., Shi, L., Katz, Y., Theunissen, T. W., Rangarajan, S., Shivalila, C. S., Dadon, D. B., and Jaenisch, R. (2013) Multiplexed activation of endogenous genes by CRISPR-on, an RNA-guided transcriptional activator system, Cell Res. 23, 1163-1171. [13] Zalatan, J. G., Lee, M. E., Almeida, R., Gilbert, L. A., Whitehead, E. H., La Russa, M., Tsai, J. C., Weissman, J. S., Dueber, J. E., Qi, L. S., and Lim, W. A. (2015) Engineering complex synthetic transcriptional programs with CRISPR RNA scaffolds, Cell 160, 339-350. [14] Niu, Y., Shen, B., Cui, Y., Chen, Y., Wang, J., Wang, L., Kang, Y., Zhao, X., Si, W., Li, W., Xiang, A. P., Zhou, J., Guo, X., Bi, Y., Si, C., Hu, B., Dong, G., Wang, H., Zhou, Z., Li, T., Tan, T., Pu, X., Wang, F., Ji, S., Zhou, Q., Huang, X., Ji, W., and Sha, J. (2014) Generation of gene-modified cynomolgus monkey via Cas9/RNA-mediated gene targeting in one-cell embryos, Cell 156, 836-843. [15] Weninger, A., Killinger, M., and Vogl, T. (2016) Key Methods for Synthetic Biology: Genome Engineering and DNA Assembly, In Synthetic Biology, pp 101-141, Springer. [16] Engler, C., Gruetzner, R., Kandzia, R., and Marillonnet, S. (2009) Golden gate shuffling: a one-pot DNA shuffling method based on type IIs restriction enzymes, PLoS One 4, e5553. [17] Peccoud, J., Weber, E., Engler, C., Gruetzner, R., Werner, S., and Marillonnet, S. (2011) A Modular Cloning System for Standardized Assembly of Multigene Constructs, PLoS One 6, e16765. [18] Zhang, F., Cong, L., Lodato, S., Kosuri, S., Church, G. M., and Arlotta, P. (2011) Efficient construction of 25

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sequence-specific TAL effectors for modulating mammalian transcription, Nat. Biotechnol. 29, 149-153. [19] Kabadi, A. M., Ousterout, D. G., Hilton, I. B., and Gersbach, C. A. (2014) Multiplex CRISPR/Cas9-based genome engineering from a single lentiviral vector, Nucleic Acids Res. 42, e147. [20] Vad-Nielsen, J., Lin, L., Bolund, L., Nielsen, A. L., and Luo, Y. (2016) Golden Gate Assembly of CRISPR gRNA expression array for simultaneously targeting multiple genes, Cell. Mol. Life Sci. 73, 43154325. [21] Tanenbaum, M. E., Gilbert, L. A., Qi, L. S., Weissman, J. S., and Vale, R. D. (2014) A protein-tagging system for signal amplification in gene expression and fluorescence imaging, Cell 159, 635-646. [22] Ding, S., Wu, X., Li, G., Han, M., Zhuang, Y., and Xu, T. (2005) Efficient transposition of the piggyBac (PB) transposon in mammalian cells and mice, Cell 122, 473-483. [23] Kumaran, R. I., Thakar, R., and Spector, D. L. (2008) Chromatin dynamics and gene positioning, Cell 132, 929-934. [24] Lucas, J. S., Zhang, Y., Dudko, O. K., and Murre, C. (2014) 3D trajectories adopted by coding and regulatory DNA elements: first-passage times for genomic interactions, Cell 158, 339-352. [25] Chavez, A., Scheiman, J., Vora, S., Pruitt, B. W., Tuttle, M., E, P. R. I., Lin, S., Kiani, S., Guzman, C. D., Wiegand, D. J., Ter-Ovanesyan, D., Braff, J. L., Davidsohn, N., Housden, B. E., Perrimon, N., Weiss, R., Aach, J., Collins, J. J., and Church, G. M. (2015) Highly efficient Cas9-mediated transcriptional programming, Nat. Methods 12, 326-328. [26] Kleinstiver, B. P., Prew, M. S., Tsai, S. Q., Topkar, V. V., Nguyen, N. T., Zheng, Z., Gonzales, A. P., Li, Z., Peterson, R. T., Yeh, J. R., Aryee, M. J., and Joung, J. K. (2015) Engineered CRISPR-Cas9 nucleases with altered PAM specificities, Nature 523, 481-485. [27] Zetsche, B., Gootenberg, J. S., Abudayyeh, O. O., Slaymaker, I. M., Makarova, K. S., Essletzbichler, P., Volz, S. E., Joung, J., van der Oost, J., Regev, A., Koonin, E. V., and Zhang, F. (2015) Cpf1 is a single RNA-guided endonuclease of a class 2 CRISPR-Cas system, Cell 163, 759-771. [28] Abudayyeh, O. O., Gootenberg, J. S., Konermann, S., Joung, J., Slaymaker, I. M., Cox, D. B., Shmakov, S., Makarova, K. S., Semenova, E., Minakhin, L., Severinov, K., Regev, A., Lander, E. S., Koonin, E. V., and Zhang, F. (2016) C2c2 is a single-component programmable RNA-guided RNA-targeting CRISPR effector, Science 353, aaf5573. [29] Morita, S., Noguchi, H., Horii, T., Nakabayashi, K., Kimura, M., Okamura, K., Sakai, A., Nakashima, H., Hata, K., Nakashima, K., and Hatada, I. (2016) Targeted DNA demethylation in vivo using dCas9peptide repeat and scFv-TET1 catalytic domain fusions, Nat. Biotechnol. 34, 1060-1065. [30] Angelici, B., Mailand, E., Haefliger, B., and Benenson, Y. (2016) Synthetic Biology Platform for Sensing and Integrating Endogenous Transcriptional Inputs in Mammalian Cells, Cell reports 16, 25252537. [31] Port, F., and Bullock, S. L. (2016) Augmenting CRISPR applications in Drosophila with tRNA-flanked sgRNAs, Nat. Methods 13, 852-854.

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Figure 1. Hierarchical assembly of multiplexed sgRNA expression plasmid. (A). Workflow for the hierarchical assembly of 20 sgRNAs. U6 promoter and sgRNA scaffold are PCR amplified and then ligated with each annealed oligo in 20 separated Golden Gate reactions with a type IIs restriction endonuclease BsmBI (Step 1). Each Golden Gate reaction mix was then used as template for amplification without purification by 20 pair of primers, which can be grouped into 4 categories, each member in a group with different adaptors (Step 2). The purified 20 sgRNAs expression cassettes were then separated into 4 group and implemented with the second round Golden Gate reaction using BsaI (Step 3). The four fragments each carried 5 sgRNAs expression cassettes were purified and then ligated together into a third round Golden Gate reaction with a receptor plasmid using BpiI (Step 4). Due to the repetitive sequence of each sgRNA expression cassette, each step should be verified by agar gel electrophoresis to guarantee that each reaction was carried out successfully. (B). A typical gel of the first round PCR result for the successful ligation of U6, annealed oligos, sgRNA scaffold. Trans2K plus II DNA ladder (TransGen Biotech) was shown in the left. The 20 individual sgRNA

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expression cassettes all show the expected length on the gel, indicating that this cloning method is quite robust. A detail to note is that the first and fifth sgRNA in each group are slightly longer than the remaining one. This is because two handles are added to the 5’ of the first sgRNA and 3’ of the fifth sgRNA to facilitate the PCR of the five sgRNAs in the following step. (C). A typical gel of the second round PCR result for the successful ligation of five sgRNA expression cassettes into one fragment. Trans2K plus II DNA ladder was shown in the left. Due to the repetitive nature of the five sgRNAs fragment, laddering effect was observed. The indicated repeat number was shown in the right. (D). A typical gel of the verification of the final all-in-one plasmid. Trans15K DNA ladder (TransGen Biotech) was shown in the left. All the plasmids were linearized by endonuclease enzyme BsaI. The empty vector was also shown as a control. All the tested six plasmids have the right insertion size, suggesting the high efficiency of the assembly process.

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Figure 2. Single non-repetitive sequence labeling by multiplexed sgRNAs expression. (A). Schematic diagram of a non-repetitive sequence labeling of the genome. With the cell line that expressed proper level of SunTag system and 20 different sgRNAs tiling a short range sequence, arbitrary target loci can be labeled. The all-in-one plasmid carries 20 sgRNAs expression cassette each with a U6 promoter and poly U terminator so that individual sgRNA can be expressed independently. Six sgRNAs are shown as a demo here. The background fluorescent signal arises from the unbound dCas9 with multiple sfGFP molecules and the free sfGFP single molecules. Minimal level and proper stoichiometry (1:24) of SunTag system is the key point for the successful labeling. In principle, the 20 sgRNAs can direct 20 dCas9sunTag molecule, that is 480 sfGFP molecules, to the target loci to gather the fluorescent signal. (B). Workflow for the establishment of live imaging system with proper expression level. Piggybac plasmids dCas9-(GCN4)X24-P2A-BFP and scFV-sfGFP were used to construct the stable cell line. The MDA-MB-231 cells were co-transfected with SunTag expression plasmids in PiggyBac backbone and transposase expression plasmid, followed by puromycin and hygromycin selection for about 2 weeks. sfGFP and BFP

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double positive single clones with minimal background expression and high labeling efficiency were selected and transient transfected with multiple sgRNA expression plasmid to test the performance of each clone in subsequent live imaging experiment. (C). The labeling result of non-repetitive sequence in human cells. By transfection of 20 sgRNAs from an allin-one plasmid targeting the first intron of human MUC4 gene, bright fluorescent puncta (indicated by arrow) can be visualized. A Cy5-labeled probe was used to perform DNA fluorescence in situ hybridization against the third exon of MUC4 to verify the labeling result of CRISPR. The nucleus was stained with DAPI. The merged image showed the colocalization of CRISPR signal and FISH signal. The region targeted by CRISPR is about 1.5 kb which has 20 binding sites, while the region targeted by FISH is about 9 kb which has 67 binding sites. Because the FISH probes target region is a repetitive sequence, so we only need one probe to get high signal-to-noise ratio image. All scale bars are 5 µm. (D). Single non-repetitive sequence can be labeled in different cell cycle stages. In G1 of interphase, two loci can be visualized. In G2 of interphase, four loci appeared as closely located pairs. During mitosis, the duplicated loci were allocated into two cells. In anaphase and telophase, the position of MUC4 loci nearly mirrored each other. All scale bars are 10 µm.

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Figure 3 Live cell tracking of single non-repetitive genomic locus. (A). Typical image and trajectories of the MUC4 locus in live cell. Trajectories were displayed by the colorcoded time points with green for the starting, blue for the intermediate and red for the ending frames. The time lookup table was in the right. Scale bar: 5 µm. (B). Time-averaged MSD plotted as a function of time lag (delay) for the MUC4 region in live cells. MSD was shown for delay up to 10 % of total imaging time. 17 trajectories were analyzed individually (left) or averaged among all the trajectories (right). Dashed lines indicate a subdiffusive scaling exponent (α) of 0.34, demonstrating the locus was undergoing constraint diffusion. (C). Velocity autocorrelation analysis of MUC4 locus in live cells. Velocity was calculated over discretization intervals (δ) ranging from 0.05 s to 5 s in 0.05 s intervals (left). Velocity autocorrelation curves for different values of δ, plotted against a rescaled timelag (t/δ) (right). The color scheme represents the values of δ from small (blue) to large (red).

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Figure 4 Synergy activation of the endogenous genes by multiplexed sgRNAs targeting one region. (A). Synergy gene activation by 20 sgRNAs targeting the promoter region of SOX2 gene. HEK293T cells were transfected with either individual plasmid (single or all-in-one) or cocktail of five plasmids. dCas9SunTag-VP64 are used for the maximum activation efficiency. qRT-PCR were used for the quantification of the activation results. (B). Synergy gene repression by 20 sgRNAs targeting the promoter region of SOX2 gene in HEK293T cells. The same plasmids are used as in (A) except dCas9-KRAB are used instead. Cells without transfection were used as control. All values are mean ± s.e.m. with n = 3 biological replicates.

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Figure 5 Multiplexed modified sgRNA expression activate and repress multiple endogenous genes simultaneously. (A). 10 sgRNA-MS2 (2.02) and 10 sgRNA-PP7 (2.02) were assembled into one plasmid. dCas9, tdPCP-VPR, tdMCP-KRAB and all-in-one sgRNA expression plasmid were cotransfected to HEK293T cells. 10 genes were activated and 10 other genes were repressed simultaneously in one cell. (B). HEK293T Cells were analyzed by qRT-PCR 2 days after transfection. The genes that are targeted with sgRNA-PP7 (2.02) were upregulated while the gene that are targeted with 10 sgRNA-MS2 (2.02) were downregulated without crosstalk. All values are mean ± s.e.m. with n = 3 biological replicates.

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