Functional interrogation of non-coding DNA through

Methods 121–122 (2017) 118–129

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Methods journal homepage: www.elsevier.com/locate/ymeth

Functional interrogation of non-coding DNA through CRISPR genome editing Matthew C. Canver a, Daniel E. Bauer a,b,c,⇑, Stuart H. Orkin a,b,c,d,⇑ a

Harvard Medical School, Boston, MA 02115, United States Division of Hematology/Oncology, Boston Children’s Hospital, Boston, MA 02115, United States c Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, United States d Howard Hughes Medical Institute, Boston, MA 02115, United States b

a r t i c l e

i n f o

Article history: Received 4 January 2017 Received in revised form 18 February 2017 Accepted 3 March 2017 Available online 10 March 2017

a b s t r a c t Methodologies to interrogate non-coding regions have lagged behind coding regions despite comprising the vast majority of the genome. However, the rapid evolution of clustered regularly interspaced short palindromic repeats (CRISPR)-based genome editing has provided a multitude of novel techniques for laboratory investigation including significant contributions to the toolbox for studying non-coding DNA. CRISPR-mediated loss-of-function strategies rely on direct disruption of the underlying sequence or repression of transcription without modifying the targeted DNA sequence. CRISPR-mediated gainof-function approaches similarly benefit from methods to alter the targeted sequence through integration of customized sequence into the genome as well as methods to activate transcription. Here we review CRISPR-based loss- and gain-of-function techniques for the interrogation of non-coding DNA. Ó 2017 Elsevier Inc. All rights reserved.

Contents 1. 2.

3.

4. 5.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Loss of function studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Loss of function approaches with DNA sequence modification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.1. Individual sgRNA targeting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.2. Dual sgRNA targeting for targeted genomic deletion, inversion, and translocations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.3. Tiling sgRNAs/Saturating mutagenesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Loss of function approaches without DNA sequence modification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Gain of function strategies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Gain of function approaches with DNA sequence modification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Gain of function approaches without DNA sequence modification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . General considerations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Author contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conflict of interest disclosures. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

⇑ Corresponding authors at: Boston Children’s Hospital, 300 Longwood Avenue, Boston, MA 02115, United States. E-mail addresses: [email protected] (D.E. Bauer), [email protected] (S.H. Orkin). http://dx.doi.org/10.1016/j.ymeth.2017.03.008 1046-2023/Ó 2017 Elsevier Inc. All rights reserved.

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1. Introduction The human genome consists of approximately 3.3 billion base pairs with only 1% protein coding sequence [1–3]. The remaining 99% of the non-coding genome potentially harbors function. However, unlike the coding genome, it lacks mRNA and protein production as functional intermediaries. Decades of research has sought to determine the rules to predict and identify functional elements within the non-coding genome including evolutionary, biochemical/epigenetic, and genetic approaches [2,4]. The understanding of the non-coding genome has been further hampered by a paucity of methods to definitively demonstrate function with reliance on such methods as correlative epigenetic marks [5], heterologous reporter assays including massively parallel reporter assays [6–8], and evolutionary conservation [2,9]. The development of genome editing technologies including zinc finger nucleases (ZFNs) and transcription activator-like effector nucleases (TALENs) offered new methods to identify functional non-coding sequences through loss- and gain-of-function genetic studies [10,11]. The rapid emergence of the clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 nuclease system as a facile genome editing platform has revolutionized genome editing approaches to study the non-coding genome [12–19]. The CRISPR/Cas9 nuclease system was originally discovered as a prokaryotic adaptive defense system that has been repurposed for eukaryotic genome editing [20]. The CRISPR/Cas9 platform requires an RNA molecule to guide the Cas9 nuclease for sitespecific cleavage upstream of a genomic protospacer adjacent motif (PAM) sequence [12,13]. The endogenous tracrRNA and crRNA have been synthetically fused to create a single chimeric guide RNA (sgRNA) to facilitate genome editing experiments. CRISPR-based editing originally relied on S. pyogenes Cas9 (SpCas9) with an NGG-restricted PAM sequence. However, the CRISPR tool-

box has been expanded to include a wide-range of PAM sequences with many validated for eukaryotic genome editing including engineered S. pyogenes and S. aureus Cas9’s to have altered PAM specificities [12,13,21–27]. Notably, Cpf1 and C2c1 offer alternative CRISPR nucleases to Cas9 as well as uniquely offer site-specific cleavage downstream of PAM sequences [28–30]. CRISPR-based genome editing to interrogate non-coding sequences relies on the endogenous DNA repair pathways that are engaged following double strand break (DSB) induction by a CRISPR-associated nuclease. These repair pathways principally include non-homologous end joining (NHEJ) and homologydirected repair (HDR). The HDR pathway can be exploited by supplying an extrachromosomal repair template to allow for the insertion of customized sequence as opposed to using the sister chromatid as the template for repair [31]. CRISPR-based genome editing systems have offered a host of strategies to study non-coding genomes through both loss-offunction and gain-of-function approaches. In particular, enhancers have been a large focus of study via genome editing [32]. Here we review CRISPR genome editing methodologies for the interrogation of the non-coding genome (Table 1).

2. Loss of function studies CRISPR based loss-of-function studies focus on two different strategies that are distinguished by the requirement to disrupt the underlying sequences. The first strategy employs insertion/ deletion (indel) induction following genomic cleavage to disrupt putative regulatory sequences. Loss-of-function with indel production relies on indel-prone NHEJ repair with a typical deletion spectrum of 1–10 base pairs [12,13,33–35]. The second strategy relies on interference or repression of the underlying sequence without

Table 1 CRISPR approaches to study non-coding DNA. LOF = loss-of-function, GOF = gain-of-function. Approach

# of sgRNA

Strategy

Throughput

Efficiency

Advantages

Disadvantages

sgRNA mutagenesis via indel-prone NHEJ

1

Low-to-high

High

sgRNA with homologous extrachromosomal template for HDR sgRNA with homologous extrachromosomal template for MMEJ sgRNA with nonhomologous plasmid (NHEJ-integration) Targeted deletion, inversion using dual sgRNA

1

Low

Low

Efficient mutagenesis of individual loci; pooled screening Genome customization (e.g., variants, protein tagging)

Narrow regions; often depend on some prior knowledge to design informative targets Not suitable for non-dividing cells; low efficiency; low throughput of loci

Low

Low

Genome customization (e.g., variants, protein tagging)

Not suitable for non-dividing cells; low efficiency; low throughput of loci

Low

High

Low throughput of loci

Low-to-high

Low

Genome customization (eg, variants, protein tagging); high efficiency Large regions; pooled screening

Translocation induction using dual sgRNA

2

Low

Low

Creation of complex genomic rearrangements

Low efficiency; low throughput

Tiling sgRNA/Saturating mutagenesis

>1

High

High

dCas9-KRAB

1

Low-to-high

High

1

Low-to-high

High

dCas9-VP64

1

Low-to-high

High

High-resolution, highthroughput; compatible with any nuclease Reduction without knockout (cell lethal study); pooled screening Reduction without knockout (cell lethal study); pooled screening Pooled screening

Variable resolution as function of underlying sequence PAM availability and off-target potential Dosage; false negatives

dCas9-LSD1

dCas9-p300

1

LOF with genomic modification GOF with genomic modification GOF with genomic modification GOF with genomic modification LOF with genomic modification GOF with genomic modification LOF/GOF with genomic modification LOF without genomic modification LOF without genomic modification GOF without genomic modification GOF without genomic modification

Low-to-high

High

Pooled screening

Dosage; false negatives

1

1

2

Low-resolution; multifocal indels as competing genomic outcome

Dosage; false negatives

Dosage; false negatives

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a

b

Individual sgRNA Mutagenesis

5’ 3’

Tiling sgRNA/Saturating Mutagenesis

3’

5’ 3’

3’ 5’

c

Targeted Deletion/Inversion

5’ 5’ 3’

GATA

5’ 3’

3’ 5’

5’ 3’

3’ 5’

3’ 5’

e

d Transcriptional Repression

Individual sgRNA with Homologous Repair Template

KRAB 5’ 3’

GATA GAT ATA

5’ 3’

3’ 5’

5’ 3’

3’ 5’

3’ 5’

GFP

GTTA LSD1 5’ 3’

f

g

Base Editing

GTTA

5’ 3’

3’ 5’

5’ 3’

3’ 5’

h

Homology-Independent NHEJ-Integration

GFP

3’ 5’

Transcriptional Activation

AID

VP64

5’ 3’

C G

3’ 5’

5’

T A

3’

5’ 3’

3’ 5’

p300

3’

5’

5’ 3’

3’ 5’

5’ 3’

3’ 5’

Fig. 1. CRISPR strategies to study non-coding DNA. (a) Individual sgRNA mutagenesis targeting a chromatin mark (shown in red) and a transcription factor binding motif such as GATA. (b) Targeted deletion using a dual sgRNA approach. Deleted sequence is indicated by red dotted lines. Inverted sequence is indicated by red arrows. (c) Tiling sgRNA/ saturating mutagenesis utilizing all sgRNA within genomic loci in a pooled screening format. (d) CRISPR-mediated transcriptional repression. dCas9-KRAB and dCas9-LSD1 are shown. However, other repressive effectors are possible. Chromatin mark is shown in red and SpCas9 is shown in gray. (e) Individual sgRNA with a homologous repair template for such applications as SNP insertion or reporter knock-in. Custom sequences from homologous repair templates are inserted by exploiting HDR or MMEJ. Red sequences indicate homologous sequence and SpCas9 is shown in gray. GFP reporter sequence is shown in green. (f) Base editing. dCas9-AID is shown. However, other base editors are possible. SpCas9 is shown in gray. (g) Homology-independent NHEJ-integration. Shared sequences on plasmid (black circle) and genomic DNA are shown in red. (h) CRISPR-mediated transcriptional activation. dCas9-VP64 and dCas9-p300 are shown. However, other activation effectors are possible. Chromatin mark is shown in red and SpCas9 is shown in gray. (a–h) All schema are shown with SpCas9. The blue lines indicate the 20-mer sgRNA sequence. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

altering the sequence itself. Interference approaches rely on an sgRNA to guide a catalytically inactive Cas9 (dCas9) to mediate locus-specific transcriptional repression through steric hindrance of biological processes such as blocking RNA polymerase binding/ progression or interfering with the binding of transcription factors [36–39]. Repression strategies extend this concept by fusing a repressive effector domain such as the Krüppel-associated box (KRAB) [36,40], Lys-specific histone demethylase 1 (LSD1) [41], or mSin3 interaction domains [42] to facilitate epigenetic-based repression of the underlying sequence. 2.1. Loss of function approaches with DNA sequence modification 2.1.1. Individual sgRNA targeting Individual sgRNA targeting can be utilized to identify functional non-coding sequences. Given the relatively narrow indel spectrum when using an individual sgRNA, this approach typically requires

additional insight to enhance the pre-experiment probability of successfully identifying functional sequences (Fig. 1a). For example, one study focused on transcription factor binding footprints to identify putative sites to target within the +58 DNase hypersensitive site (DHS) within the enhancer of BCL11A, a known repressor of fetal hemoglobin [43]. Specifically, this study identified 8 potential transcription factor binding sites within the 162 base pair DHS [43,44]. This study used ZFNs and TALENs to target all 8 candidate motifs and identified enhancer function in 1/8 sites. Using a functional genomic footprinting approach for analysis at nucleotide resolution, the region of enhancer function was further reduced to a GATA motif [43]. While this study utilized ZFNs and TALENs to engender DSBs, this strategy could be utilized to inform similar CRISPR-based targeting. Another example involved utilizing patient samples to assist with sgRNA targeting. Overlapping mutations within multiple patient samples were identified in an intergenic region 7.5 kilobases from the transcriptional start site of

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TAL1 that led to the creation on an oncogenic superenhancer [45]. These mutations suggested a narrow site to target via genome editing to study the activity of an aberrant super-enhancer element. Finally, other examples have involved targeting CTCF binding sites within insulators separating topologically associated domains (TADs). These studies have demonstrated that disrupting these CTCF binding sites with indels results in aberrant enhancer activity, changes in gene expression, and disruption of genomic topology [46,47]. Individual sgRNA targeting with Cas9 is also possible in vivo [48,49]. Similarly, in vivo targeting using the Cpf1 nuclease has also been demonstrated by both microinjection and ribonucleoprotein electroporation in mice [50,51]. New strategies for using Cpf1 may allow for multiplex targeting using a single construct. This approach has been used for the simultaneous editing of four targets in vitro and three in vivo [52]. Individual sgRNA targeting is useful for a small number of specific, narrow target(s) often informed by epigenetic marks or transcription factor binding motifs. However, it becomes laborious with multiple targets or to evaluate large regions since large deletions represent a low frequency event following individual sgRNA targeting [12,13,33–35]. The recent identification of regulatory elements lacking typical chromatin signatures highlights the potential shortcomings of targeting only a few predicted functional sequences based on incomplete current knowledge and emphasizes the potential benefits of high-throughput approaches for studying non-coding DNA [53]. 2.1.2. Dual sgRNA targeting for targeted genomic deletion, inversion, and translocations The usage of pairs of sgRNAs, or dual sgRNAs, to produce simultaneous DSBs have a large number of applications including induction of targeted genomic deletions, inversions, and more complex genomic rearrangements such as translocations (Fig. 1b) [54]. Two sgRNAs have been shown to reliably engender large genomic deletions in vitro, including greater than 1 megabase [33,55–59]. Deletions have also been engendered in vivo [60–62]. The use of targeted deletion has been used for a wide variety of applications to study non-coding elements. Notably, targeted deletion has been used to delete composite enhancers as well as enhancer substituents to identify functional sequence within large enhancer regions with characteristic epigenetic marks [63–65]. This strategy has also been used to generate genomic inversions with inverted sequences of greater than 1 megabase [33,55,66–69]. For example, inversion of CTCF binding sites induced dysregulation of genomic topology and alteration of enhancer-promoter contacts, which suggest that enhancers containing CTCF binding sites may not display the orientation independence traditionally ascribed to enhancer elements [70]. Similarly, inversions have validated in situ enhancer element orientation independence, which had been originally described using heterologous reporter constructs [9,63]. A dual sgRNA strategy has been successfully applied to in vivo applications, including mice [66,69,71–75], zebrafish [67], and C. elegans [76]. One study utilized a dual sgRNA approach to engender a 1.2 kilobase deletion and inversion of an insulator regulatory element 12 kilobases upstream of the murine tyrosinase (Tyr) gene, an enzyme necessary for melanin synthesis. CRISPR/Cas9 reagents were delivered through microinjection into fertilized mouse eggs. Using coat pigmentation as a readout, this study confirmed the functionality of this regulatory element as both deletion and inversion of the element resulted in a reduction in both Tyr expression and coat pigmentation [69]. Another study deleted individual DHS and a composite enhancer in mouse embryonic stem cells to ultimately generate germ-line transmitting chimeric mice to examine the role of the enhancer and its substituent components during development [77]. Another notable study disrupted bound-

121

ary elements through deletions, inversions, and duplications to evaluate the effect on embryologic development. The resulting changes in enhancer-promoter interactions resulted in limb malformations [78]. Lastly, utilization of two sgRNA at different chromosomal loci can result in translocations both in vitro and in vivo [79–82], which can allow for chromosomal rearrangements resulting in aberrant enhancer/super-enhancer recruitment [83,84]. The dual sgRNA approach for targeted deletion is useful for interrogation of large regions at low resolution. It is also useful for creating precise deletion events, although indels may be observed at deletion junctions [33]. Dual sgRNA approaches are well suited for generating complex genomic rearrangements such as inversions and translocations. However, the dual sgRNA approach for targeted deletions, inversions, and translocations has been hampered by low throughput, efficiency, and resolution. Recent strategies have been developed for the cloning of pooled libraries consisting of dual sgRNA constructs to allow for pooled deletion/inversion screens [85,86]. This strategy was applied to 51 long non-coding RNAs (lncRNAs) to identify lncRNAs with roles in cancer cell proliferation [87]. These screens may serve as a reliable methodology to increase the throughput of targeted deletion strategies. However, a challenge may be that alternative repair outcomes, such as small indels at each of the dual sgRNA cleavage sites, may limit signal strength in pooled screens, where enrichment phenotypes may be easier to detect than dropout phenotypes. 2.1.3. Tiling sgRNAs/Saturating mutagenesis Pooled CRISPR screening has become widely available and allows for high-throughput and/or multi-loci studies [88–90]. In general, most pooled CRISPR screens have focused on gene knockout for in vitro and in vivo applications [86,91–113]. However, the number of pooled screens targeting non-coding DNA have increased [63,87,114–117]. Notably, a recently developed technique of tiling sgRNAs (‘‘saturating mutagenesis”) has provided a methodology to circumvent the low-throughput, efficiency, and resolution of targeted deletion to interrogate regulatory DNA (Fig. 1c). This approach relies on the same indel spectrum of 1–10 base pairs when utilizing an individual sgRNA [12,13,33–35]. Saturating mutagenesis becomes high-throughput and highresolution by using every sgRNA within a given region in a pooled screening format, which allows for saturating a region with indels to identify functional sequence. The resolution is a function of the number of sgRNA available within a given region. This methodology led to functional fine-mapping of 3.9 kilobases of DHS sequence within the 12 kilobase BCL11A enhancer using a 533 sgRNA library [63]. This study utilized distances between adjacent genomic cleavages between sgRNA within the library as a measure of degree of saturation. For the enhancer-targeted library, there was a median of 4 base pairs between adjacent genomic cleavages and 18 base pairs at 90th percentile. Another study utilized 18,315 sgRNA to mutagenize 715 kilobases of noncoding sequence adjacent to three genes to identify regions involved in resistance to pharmacologic inhibitors by disrupting transcription factor binding and long-range interactions [115]. Yet another group performed saturating mutagenesis of 174 cis regulatory elements including DHS, CTCF sites, and predicted enhancers within a one megabase TAD containing the gene POUF51. This work led to the identification of so-called temp enhancers, whereby the phenotypic effect of enhancer disruption is lost after several rounds of cell division [116]. A final study tiled sgRNA across binding motifs. Specifically, the study utilized 1,116 sgRNA to target p53 binding motifs within 685 genomic loci to identify enhancers required for oncogene-induced senescence. The same study also used 97 sgRNA tiling binding motifs within 73 enhancers for ERa, an estrogenactivated transcription factor implicated in breast cancer. This

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approach allowed for identification of novel enhancer elements within both regions [118]. Lastly, a similar strategy was used to tile sgRNAs across regulatory elements with delivery of library sgRNA via HDR to investigate four loci tagged by a fluorescent marker to aide detection of indel perturbations [53]. Enhanced resolution of tiling sgRNA/saturating mutagenesis can be achieved by design of a CRISPR library based on choosing the optimal PAM sequence (and corresponding CRISPR nuclease) for the sequence under study (eg, a GC-rich PAM for a GC-rich region or an AT-rich PAM for an AT-rich region). Alternatively, resolution can be enhanced by using multiple nucleases with unique PAM sequences in combination for the same region [119]. One notable study utilized the S. pyogenes NGG-restricted Cas9 and the S. pyogenes variant NGA-restricted Cas9 to perform saturating mutagenesis of all DHS within the HBS1L-MYB intergenic region [119]. In this study, the usage of NGG-restricted sgRNA alone (n = 2,166 sgRNA) led to a median and 90th percentile gap between adjacent genomic cleavages of 5 and 22.5 base pairs, respectively. The usage of NGA-restricted sgRNA targeting the same region (n = 2,564 sgRNA) led to a median and 90th percentile between adjacent genomic cleavages of 6 and 18 base pairs, respectively. The NGG- and NGA-restricted combination library led to the highest resolution with a total of 4,690 sgRNA resulting in a median of 3 base pairs and 90th percentile of 11 base pairs between adjacent genomic cleavages [119]. With the continual identification of novel Cas9 species and other nucleases with unique PAM sequences [12,13,21–29], the ability to enhance saturating mutagenesis resolution with the combination of nucleases will also continue to improve. Lastly, recent work has also highlighted the importance of taking variants into account during saturating mutagenesis library design for genetically implicated regions marked by common genetic variation. These variant aware libraries help minimize attenuation of sgRNA activity by variants in the cells used for study as well as aide in the detection of single nucleotide polymorphism (SNP)-marked functional sequence [119]. Tiling sgRNA/saturating mutagenesis provides a highthroughput, high resolution methodology to functionally dissect non-coding DNA. This technique has been validated for in vitro applications including large regions and multi-loci studies. While most published studies have utilized NGG-restricted Cas9 [63,114–116], recent work using the NGA-restricted Cas9 variant and Cpf1 have demonstrated that other species can be used for pooled CRISPR screening [119,120]. One potential pitfall encountered with utilizing all sgRNA within a given region is the potential for inclusion of guides with significant off-target potential, which can confound results. To this end, multiple studies have identified potential false positive hits due to targeting of repetitive DNA [119,121,122] including an example when performing saturating mutagenesis of non-coding DNA sequences [119]. Therefore, when performing saturating mutagenesis, it is essential to perform off-target analysis for all sgRNA in the library especially in regions involving repetitive sequences. In addition to off-target analysis, recent work has demonstrated that switching to a modified/adapted tracrRNA sequence can also improve the reliability of data obtained from dropout CRISPR screens and increases the efficacy of library sgRNA [40,123].

(dCas9-KRAB) derived from Kox1 resulted in 5–15 fold gene repression with repression correlating with the levels of sgRNA expression (Fig. 1d). Notably, this approach also was successfully used to repress transcription via enhancer targeting [36]. While the dCas9-only effect was improved through modification of the sgRNA stem loop and hairpin structures, it still resulted in inferior gene repression as compared to the dCas9-KRAB fusion [40]. Another example of using dCas9-KRAB to interrogate noncoding DNA involved targeting the HS2 enhancer within the locus control region (LCR) of the b-globin locus. This led to a reduction in gene expression specific to globin genes and induction of H3K9me3 at HS2 without affecting the other four DHS within the LCR. There was also a decrease in enhancer/promoter accessibility as determined by DNase-sequencing at both HS2 as well as several globin gene promoters [124]. A similar approach was utilized to identify novel distal enhancer elements using a 98,000 sgRNA library of all sgRNA within a 1.29 megabase region flanking the GATA1 and MYC genes, which led to the identification of nine distal enhancer elements [125]. Finally, dCas9-KRAB has been used for genome wide screens for gene targets and lncRNAs, thus demonstrating proof-of-principle for high-throughput, large-scale repression screens [126,127]. Given the role of the histone demethylase LSD1 in enhancer repression, a dCas9-LSD1 fusion was targeted to a known enhancer of Oct4, a regulator of embryonic stem cell state, which resulted in downregulation of Oct4 expression (Fig. 1d). The dCas9-LSD1 fusion was then used to evaluate eight candidate enhancers for a role in regulating embryonic stem cell state ultimately leading to validation of four sites. One validated enhancer region was 10 kilobases upstream of Tbx3, a gene with a known role in the maintenance of pluripotency. Targeting the enhancer region with dCas9-LSD1 resulted in a reduction of Tbx3 at both the RNA and protein level. Notably, there were no changes in enhancerpromoter interaction frequencies. However, there was a 33- to 54-fold reduction in H3K27ac and a 6–8 fold reduction of H3K4me2 at the sgRNA binding site without any associated changes in repressive marks including H3K27me3 and H3K9me3. Surprisingly, upon investigation of the Tbx3 promoter, there was a reduction of H3K27Ac and elevation of H3K27me3 and H3K9me3 when targeting the enhancer with dCas9-KRAB; however, the effect at the promoter was not observed using dCas9LSD1 [41]. These non-indel forming approaches can be used for similar applications as the indel-forming approaches including individual targeting and large-scale screening. However, CRISPRi techniques may be advantageous for investigations where disruption of an enhancer or other regulatory DNA may be cell lethal. The resolution of using dCas9-KRAB or dCas9-LSD1 for saturating mutagenesis as compared to catalytically active Cas9 has yet to be explored. Another notable potential drawback to the CRISPRi approach is that the effect may be transient such that the chromatin may revert to its original state after the CRISPRi machinery is no longer present. However, recent reports have suggested that at least in certain cases the CRISPRi effect may be extremely durable, lasting for weeks to months, although the duration of epigenetic memory may depend on a number of variables including the specific locus, cellular context, and combinations of repressors [128].

2.2. Loss of function approaches without DNA sequence modification 3. Gain of function strategies The initial strategy for studying non-coding DNA without disrupting the underlying sequences relied on CRISPR interference (CRISPRi) to sterically hinder the binding of transcription factors or interference with transcriptional initiation or elongation [36–39]. This strategy led to an 2-fold reduction in gene expression [37]. This technique was enhanced by dCas9 fusion to chromatin modifiers [36,40]. In one study, dCas9 fusion with KRAB domain

Similar to CRISPR methods for loss-of function study, CRISPR based gain-of-function studies focus on two different strategies that are distinguished by the requirement to modify the underlying sequences. The first exploits the endogenous HDR pathway to stimulate repair from an extrachromosomal template to insert customized sequence into the genome. The second strategy relies on

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activation of the underlying sequence without direct modification. This approach relies on dCas9 coupled to transcriptional activation domains [129,130]. 3.1. Gain of function approaches with DNA sequence modification HDR has been an extremely useful tool to study sequence function, but is hampered by low efficiency [131–133]. However, induction of DSBs has been shown to greatly stimulate HDR [134,135]. Inducing HDR is further complicated by cell-cycle regulation such that HDR only occurs during the G2 and late S phase while absent during the G1 phase [136–139]. A variety of strategies have been developed to increase the efficiency of HDR, which have included inhibition of NHEJ machinery, cell cycle synchronization, and optimization of CRISPR and repair template reagents [136,137,139–146]. Despite these technical challenges, HDR has been used for a variety of applications for non-coding DNA including the insertion/knock-in of variants, large fragments of DNA, and reporters at endogenous loci (Fig. 1e) [147–150]. One notable study used single cell labeling of proteins via HDR within neuronal progenitors to allow for imaging of endogenous proteins [151]. HDR has also been successful in vivo for the creation of customized knock-in mice [49,152–155]. Recent work demonstrated 50% of successful HDR alleles to correct a pathogenic SNP using delivery of CRISPR/Cas9 as ribonucleoproteins and adeno-associated virus (AAV) delivery of the repair template. Furthermore, this approach was able to achieve HDR-mediated SNP correction in repopulating hematopoietic stem cells, a quiescent cell type traditionally resistant to HDR [146]. In a similar fashion, one study created four different SNP knock-in mice to examine the effect of these SNPs that had previously been implicated in human infertility [156] while another study created knock-in of two disease risk-associated SNPs implicated for lipid levels both in vitro and in vivo [157]. Finally, HDR approaches have also been used to engender genomic deletions as an alternative to dual sgRNA with NHEJ repair as discussed above. In one study, a rex site was deleted at a TAD boundary through HDR replacement with a NcoI restriction site, which facilitated identification of the desired mutation [158]. One longstanding technical challenge has been identification of causal SNPs and their target genes that have been implicated by genome-wide association studies in human traits and disease [159]. One study proposed a four step pipeline for the identification of causal SNPs through (1) fine-mapping of putative causal variants in conjunction with (2) epigenetic profiling. The study identified rs339331 as a candidate causal SNP that was suggested to be located within a regulatory element controlling RFX6 expression. Then the authors used (3) epigenetic editing to demonstrate that targeting the rs339331 region with TALE-LSD1 fusion reduced RFX6 expression, a finding consistent with enhancer function as discussed above. Finally, rs339331 was inserted into cell lines via (4) TALE-mediated HDR to evaluate its functional consequences [160]. This pipeline provides a systematic approach for the evaluation of genetically implicated variants marking regulatory DNA. Recent reports have suggested an alternative approach to the stimulated HDR following nuclease cleavage paradigm to insert/ alter sequence. Specifically, two studies fused cytidine deaminase enzymes to dCas9 for site-specific C to T or G to A substitutions in an 5 base pair window in the absence of nuclease-mediated cleavage [161,162]. To further this technique, other groups used a variant dCas9-AID fusion that was capable of creating C and G substitutions to the three other bases at appreciable frequencies (Fig. 1f). This system was used to identify previously reported and novel mutations associated with resistance to the tyrosine kinase inhibitor imatinib [163]. Finally, another group used dCas9-AID with its nuclear export signal deleted in conjunction

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with an sgRNA with two MS2 activation domains to generate significant levels of genomic diversity to drive directed evolution [164]. Saturation mutagenesis, distinct from the tiling sgRNA/saturating mutagenesis discussed above, is an HDR-based technique for comprehensive mutagenesis of narrow regions. To be explicit, we are using the term ‘‘saturating mutagenesis” to describe design of all possible sgRNAs for a given nuclease within a given target sequence, and the term ‘‘saturation mutagenesis” to describe introduction of all possible sequence variants via HDR within a given target sequence. Saturation mutagenesis has been used for a 6 base pair region within exon 18 of the BRCA1 gene to generate all possible single nucleotide variants via HDR from a library of single nucleotide substituted templates to examine the effects of each substitution on transcript levels [165]. This approach provides a comprehensive interrogation of a given region. While this approach has only been demonstrated in coding sequence, this could be used for non-coding regions such as for the evaluation of transcription factor binding motifs. While this strategy benefits from its comprehensive approach to a region, it is limited in its throughput and requirement for narrow regions. Lastly, another recent report demonstrated the use of HDR to integrate a library of 12,000 175 base pair donors with 100 base pair variable regions into heterochromatin to confirm computationally predicted sequences associated with chromatin accessibility in situ [166]. Several studies have attempted to circumvent the HDR requirement for the insertion of exogenous sequence into the genome. One study achieved sequence knock-in of a fluorescent marker from a repair template by exploiting microhomology-mediated end joining (MMEJ), a repair process present during G1 and early S phases that relies on nearby microhomologous sequences of 2– 25 bp in length (Fig. 1e). This approach was also successful in vivo in both silkworms and frogs [167]. It had been previously shown that simultaneous ZFN-mediated cleavage of both a genomic locus and a plasmid containing the same cleavage recognition site led to integration of the plasmid (Fig. 1g) [168]. Using a similar strategy, others demonstrated homology-independent integration in zebrafish with simultaneous CRISPR/Cas9-mediated DSB induction at a genomic locus with concurrent plasmid linearization [169,170]. Finally, recent work showed that an NHEJ-mediated targeted integration approach involving concurrent genomic locus and plasmid cleavage outperformed HDR and MMEJ integration, which could be used in both dividing and non-dividing cells. The authors also demonstrated its use in vivo [171]. 3.2. Gain of function approaches without DNA sequence modification The initial strategies for gain-of-function study of non-coding DNA without modifying the underlying sequences have relied on CRISPR activation (CRISPRa) to augment transcription. One initial study created a fusion of VP64 activation domain to the Cterminus of Cas9, which led to transcriptional activation (Fig. 1h). In this study, the 3’ end of the sgRNA was also modified with two copies of MS2 bacteriophage coat protein-binding aptamers to allow for sgRNA recruitment of activation domains [130]. Taken together, these two modifications allowed for CRISPR-mediated gene activation. Other studies have used alternative activation domains such as VP160 [172]. This approach was furthered in a subsequent study that modified Cas9 to include MS2 protein-interacting RNA aptamers on the sgRNA’s tetraloop and stem loop 2, which outperformed dCas9-VP64 fusion 3–5 fold individually and a 12-fold increase when both aptamers were included. The combination of these modifications with dCas9-VP64 further increased activation of gene expression [173]. Notably, the MS2 aptamer modification on the tetraloop and stem loop 2 was more effective than the 3’

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end fusion of MS2 [130,173]. In this same study, dCas9 was modified to add additional activation domains including VP64, the NFjB trans-activating subunit p65, and the activation domain from human heat shock factor 1 (HSF1). Collectively, the optimal system for transcriptional activation was demonstrated to include sgRNAs with MS2 aptamer modifications on the tetraloop and stem loop 2, dCas9-VP64, and the addition of activators MS2-p65-HSF1. This system was successfully used at both individual loci and for genome scale activation screening [173,174]. A recent study applied the CRISPRa strategy to non-coding regions by using the dCas9-VP64 system for an unbiased screen to identify functional enhancer sequences by tiling sgRNA across a >100 kilobase genomic region genetically implicated to play a role in autoimmunity. This approach led to the identification of multiple enhancer elements [175]. Finally, another approach to transcriptional activation is the fusion of dCas9 to the catalytic core of the human acetyltransferase p300 to allow for the catalysis of H3K27Ac at target loci (Fig. 1h). dCas9-p300 outperformed dCas9-VP64 to increase gene expression when targeting multiple promoters. Notably, targeting of the HS2 enhancer within the bglobin locus by dCas9-p300 led to increased expression of globin genes at levels higher than dCas9-VP64. The authors further showed that activation correlated with increased H3K27Ac at both promoters and enhancer regions [176]. 4. General considerations There are many general considerations that are applicable to both loss-of-function and gain-of-function approaches to studying non-coding DNA. While these considerations are beyond the scope of this review, we will briefly highlight several important issues. For example, several studies have investigated methods to predict/enhance sgRNA activity at both the individual sgRNA level [94,98,177–188] and for large-scale pooled screening [94,189]. In addition, many methods have been developed to predict/detect off-target cleavages [35,178,190–193]. Other methods to minimize off-targets have been developed including the use of truncated sgRNAs, dimeric RNA-guided FokI nucleases, and high-fidelity Cas9 mutants [34,54,194–197]. Recent work has provided further insight to the targeting specificity of Cpf1 [120,198,199]. It is important to maximize sgRNA activity and minimize off-target cleavages as allowed by the experimental design. Methodologies continue to emerge that allow for increased spatiotemporal control of genome editing experiments, such as chemical- and light-inducible Cas9 [200–202] as well as identification of naturally occurring inhibitors of Cas9 that may be exploited as an on/off switch [203]. Furthermore, combining CRISPR pooled screens with RNA-sequencing at the single cell level will aid both loss-of-function and gain-of-function experiments [204–206]. Finally, systems for simultaneous repression and activation of gene expression through the use of scaffold RNAs may usher in an era where combinatorial loss- and gain-of-function studies are possible to dissect complex transcriptional networks [207]. 5. Conclusions The study of regulatory DNA has been plagued by a paucity of methods to interrogate non-coding sequences in their native chromatin, chromosomal, and cellular context. CRISPR-based technologies continue to emerge at a rapid pace, which offer new methodologies to study non-coding DNA for laboratory experiments and therapeutic applications [43,63,208–210]. CRISPRbased strategies allow for efficient loss- and gain-of-function studies, which includes approaches with and without modification of the targeted DNA sequences. Advancements have continued to

improve throughput, efficiency, and specificity of CRISPR-based methodologies. CRISPR technologies will continue to unmask and further the understanding of the non-coding genome. Author contributions M.C.C. reviewed the literature. M.C.C., D.E.B., and S.H.O. wrote the manuscript. Conflict of interest disclosures M.C.C, D.E.B., and S.H.O. declare no competing financial interests. Acknowledgments M.C.C. is supported by a National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Award (F30DK10335901A1). D.E.B. is supported by NIDDK (K08DK093705, R03DK109232), NHLBI (DP2OD022716), Burroughs Wellcome Fund, Doris Duke Charitable Foundation Innovations in Clinical Research Award, ASH Scholar Award, Charles H. Hood Foundation Child Health Research Award, and Cooley’s Anemia Foundation fellowship. S.H.O. is supported by an award from the NHLBI award (P01HL032262) and an award from the NIDDK (P30DK049216, Center of Excellence in Molecular Hematology). References [1] E.S. Lander, L.M. Linton, B. Birren, C. Nusbaum, M.C. Zody, J. Baldwin, K. Devon, K. Dewar, M. Doyle, W. FitzHugh, R. Funke, D. Gage, K. Harris, A. Heaford, J. Howland, L. Kann, J. Lehoczky, R. LeVine, P. McEwan, K. McKernan, J. Meldrim, J.P. Mesirov, C. Miranda, W. Morris, J. Naylor, C. Raymond, M. Rosetti, R. Santos, A. Sheridan, C. Sougnez, N. Stange-Thomann, N. Stojanovic, A. Subramanian, D. Wyman, J. Rogers, J. Sulston, R. Ainscough, S. Beck, D. Bentley, J. Burton, C. Clee, N. Carter, A. Coulson, R. Deadman, P. Deloukas, A. Dunham, I. Dunham, R. Durbin, L. French, D. Grafham, S. Gregory, T. Hubbard, S. Humphray, A. Hunt, M. Jones, C. Lloyd, A. McMurray, L. Matthews, S. Mercer, S. Milne, J.C. Mullikin, A. Mungall, R. Plumb, M. Ross, R. Shownkeen, S. Sims, R.H. Waterston, R.K. Wilson, L.W. Hillier, J.D. McPherson, M.A. Marra, E. R. Mardis, L.A. Fulton, A.T. Chinwalla, K.H. Pepin, W.R. Gish, S.L. Chissoe, M.C. Wendl, K.D. Delehaunty, T.L. Miner, A. Delehaunty, J.B. Kramer, L.L. Cook, R.S. Fulton, D.L. Johnson, P.J. Minx, S.W. Clifton, T. Hawkins, E. Branscomb, P. Predki, P. Richardson, S. Wenning, T. Slezak, N. Doggett, J.F. Cheng, A. Olsen, S. Lucas, C. Elkin, E. Uberbacher, M. Frazier, R.A. Gibbs, D.M. Muzny, S.E. Scherer, J.B. Bouck, E.J. Sodergren, K.C. Worley, C.M. Rives, J.H. Gorrell, M.L. Metzker, S. L. Naylor, R.S. Kucherlapati, D.L. Nelson, G.M. Weinstock, Y. Sakaki, A. Fujiyama, M. Hattori, T. Yada, A. Toyoda, T. Itoh, C. Kawagoe, H. Watanabe, Y. Totoki, T. Taylor, J. Weissenbach, R. Heilig, W. Saurin, F. Artiguenave, P. Brottier, T. Bruls, E. Pelletier, C. Robert, P. Wincker, D.R. Smith, L. DoucetteStamm, M. Rubenfield, K. Weinstock, H.M. Lee, J. Dubois, A. Rosenthal, M. Platzer, G. Nyakatura, S. Taudien, A. Rump, H. Yang, J. Yu, J. Wang, G. Huang, J. Gu, L. Hood, L. Rowen, A. Madan, S. Qin, R.W. Davis, N.A. Federspiel, A.P. Abola, M.J. Proctor, R.M. Myers, J. Schmutz, M. Dickson, J. Grimwood, D.R. Cox, M.V. Olson, R. Kaul, C. Raymond, N. Shimizu, K. Kawasaki, S. Minoshima, G.A. Evans, M. Athanasiou, R. Schultz, B.A. Roe, F. Chen, H. Pan, J. Ramser, H. Lehrach, R. Reinhardt, W.R. McCombie, M. de la Bastide, N. Dedhia, H. Blocker, K. Hornischer, G. Nordsiek, R. Agarwala, L. Aravind, J.A. Bailey, A. Bateman, S. Batzoglou, E. Birney, P. Bork, D.G. Brown, C.B. Burge, L. Cerutti, H.C. Chen, D. Church, M. Clamp, R.R. Copley, T. Doerks, S.R. Eddy, E.E. Eichler, T.S. Furey, J. Galagan, J.G. Gilbert, C. Harmon, Y. Hayashizaki, D. Haussler, H. Hermjakob, K. Hokamp, W. Jang, L.S. Johnson, T.A. Jones, S. Kasif, A. Kaspryzk, S. Kennedy, W. J. Kent, P. Kitts, E.V. Koonin, I. Korf, D. Kulp, D. Lancet, T.M. Lowe, A. McLysaght, T. Mikkelsen, J.V. Moran, N. Mulder, V.J. Pollara, C.P. Ponting, G. Schuler, J. Schultz, G. Slater, A.F. Smit, E. Stupka, J. Szustakowski, D. ThierryMieg, J. Thierry-Mieg, L. Wagner, J. Wallis, R. Wheeler, A. Williams, Y.I. Wolf, K.H. Wolfe, S.P. Yang, R.F. Yeh, F. Collins, M.S. Guyer, J. Peterson, A. Felsenfeld, K.A. Wetterstrand, A. Patrinos, M.J. Morgan, P. de Jong, J.J. Catanese, K. Osoegawa, H. Shizuya, S. Choi, Y.J. Chen, International human genome sequencing, initial sequencing and analysis of the human genome, Nature 409 (2001) 860–921. [2] M. Kellis, B. Wold, M.P. Snyder, B.E. Bernstein, A. Kundaje, G.K. Marinov, L.D. Ward, E. Birney, G.E. Crawford, J. Dekker, I. Dunham, L.L. Elnitski, P.J. Farnham, E.A. Feingold, M. Gerstein, M.C. Giddings, D.M. Gilbert, T.R. Gingeras, E.D. Green, R. Guigo, T. Hubbard, J. Kent, J.D. Lieb, R.M. Myers, M.J. Pazin, B. Ren, J. A. Stamatoyannopoulos, Z. Weng, K.P. White, R.C. Hardison, Defining

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