This work was supported by NIH/NHGRI R00 HG006922 and NIH/NHGRI R01 HG008974 to J.G., and the Huntsman Cancer Institute. J.B.C. was supported by NIH Training Program in Genetics T32GM007464.

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The authors have nothing to disclose.

This protocol describes a simple and flexible method for dissecting enhancer function at the endogenous genomic locus without physically altering the DNA sequence. While similar in concept to previously published CRISPR interference protocols using dCas9-KRAB27, Enhancer-i differs from these protocols in 3 main ways. First, Enhancer-i utilizes the SIN3A interacting domain of MAD120 to achieve enhancer deactivation. Enhancer deactivation can be rescued using HDAC inhibitors, suggesting that the primary mechanism of deactivation is HDAC dependent. Unlike CRISPR interference with dCas9-KRAB, Enhancer-i does not lead to the deposition of H3K9me3. This is likely due to the fact that Enhancer-i relies on transient introduction of guide RNAs, with the cells being harvested at 3 days post transfection. In CRISPR interference, an increase in H3K9me3 is observed at 7 days post transduction12. Finally, the Enhancer-i protocol provides a strategy to target multiple sites simultaneously and monitor the efficiency of targeting. In Mosaic-seq17, dCas9-KRAB is used to target multiple enhancers simultaneously, but this technique relies on single-cell RNA sequencing to identify expression changes, and many genes (such as estrogen-responsive genes) go undetected due to the low sensitivity of single-cell RNA-seq. Enhancer-i provides a reliable method to study enhancers individually and in combination for any gene.
The most critical step of Enhancer-i is transfection, which should be optimized for the cell line of interest. This protocol relies on puromycin treatment to enrich for transfected cells, but it is possible that co-transfecting guide RNAs with a fluorescent protein and sorting for fluorescent cells using flow cytometry may prove to be a better enrichment method for some cell types. We recommend monitoring the expression level of guide RNAs and SID4x-dCas9-KRAB by qPCR to troubleshoot and confirm transfection. If guide RNA levels are low (cycle threshold &#62;30), users may also consider alternative guide RNA production strategies such as in vitro transcription28. It is also possible that despite high gRNA levels, guide RNA targeting of the SID4x-dCas9-KRAB protein is inefficient, in which case selecting different guide RNA sequences may be necessary. By performing ChIP-seq on the fusion protein with chromatin from Enhancer-i treated cells, the efficiency of targeting can be monitored. If there is high signal of SID4x-dCas9-KRAB at the region of interest, and no expression changes in its putative target gene are detected, then the region likely does not contribute to the expression of that gene under the conditions studied.
One potential limitation of Enhancer-i is that off-target effects may accumulate if too many sites are targeted simultaneously. Nonetheless, CRISPR interference strategies for knockdown have fewer off target effects than RNAi29, particularly when a polyclonal cell line expressing dCas9-KRAB is used. While we have seen off-target genomic binding of SID4X-dCas9-KRAB when targeting 10 sites simultaneously, we have not identified gene expression changes as a result of those binding events. As some enhancers may contact multiple promoters and/or other enhancers, it is possible that many genes may change expression upon targeting of a single enhancer, though it is unclear if this form of gene regulation is common. To confirm that the expression changes observed are due to targeting a specific enhancer, and not off-target effects, users can perform Enhancer-i with two distinct sets of non-overlapping guide RNAs targeting the same region. In addition, the genetic deletion of the region using nuclease-competent Cas9 can further confirm its effects on gene expression.
As Enhancer-i functions through histone deacetylation, it is possible that its deactivation abilities are limited to enhancers that have appreciable levels of histone acetylation. There are a variety of alternative repressive fusions that may be more effective at targeting specific enhancers. DNA methyltransferase fusions to dCas9 can be used to reduce gene expression when targeted to distal enhancers30, but this repression is often not transient. Another repressive fusion uses the Friend of GATA1 (FOG1) domain, which leads to histone H3 lysine 27 trimethylation and represses gene expression at levels similar to dCas9-KRAB across a variety of cell lines and promoters31. Interestingly, adding more copies of FOG1 to dCas9 reduced the repressive potential at promoters, suggesting that a single copy of the SID domain may provide more enhancer deactivation than the 4 copies currently used in Enhancer-i. It is possible that some loci may benefit from dual targeting by different combinations of the above dCas9 fusions. For example, stable long-term repression can be achieved by simultaneous transduction of dCas9-DNMT3a and dCas9-KRAB32. Most of these repressive fusions have only been targeted to a single locus at a time, and it remains unclear which is most effective at manipulating multiple enhancers simultaneously.
Enhancer-i, while a suitable method for studying combinations of enhancers for a handful of genes, is still somewhat limited in throughput if the user wishes to study putative enhancers for hundreds of genes. Future applications of this technique will incorporate imaging-based technologies to quantify multiple genes in multiple samples simultaneously. Importantly, these technologies are compatible with direct detection of RNA molecules from lysate, eliminating the need for time-consuming RNA isolation. These adaptations will facilitate the interrogation of larger sets of enhancers.

Large-scale sequencing projects such as ENCODE1, Roadmap Epigenomics2, and FANTOM3 have identified millions of putative enhancers within the human genome across hundreds of cell types. It is estimated that each promoter associates with an average of 4.9 enhancers and each enhancer contacts an average of 2.4 genes3, suggesting that gene expression is often the result of the integration of multiple distributed regulatory interactions. A significant remaining challenge is to define not only how individual enhancers contribute to gene expression, but how they combine to affect expression. Genetic approaches are commonly used to identify relationships between enhancers in model organisms from Drosophila4 to mice5. However, these experiments are time-consuming and low-throughput for the study of multiple enhancers at multiple genes.
One approach for studying enhancer function on a large scale involves massively parallel reporter assays. These assays allow for the simultaneous screening of thousands of DNA sequences for their ability to drive the expression of a reporter gene6. While these assays have shown that DNA sequence can alone be sufficient to convey gene regulation information7, they come with the caveats of being performed outside of the native chromatin context and with a heterologous promoter. In addition, the size of DNA sequence being analyzed in massively parallel reporter assays is usually less than 200 basepairs, which may exclude relevant surrounding sequence. Importantly, as reporter assays only measure the activity of one sequence at a time, they do not take into account the complex relationships that can exist between enhancers. Thus, while massively parallel reporter assays can be informative about the intrinsic activity of a DNA sequence, they do not necessarily inform us of the function of that DNA sequence in the context of the genome.
Recently developed CRISPR/Cas9 tools8 have facilitated the study of gene regulation as they allow for the deletion of enhancers at the endogenous locus. However, deleting multiple enhancers simultaneously may lead to genomic instability, and it is time consuming to generate successive enhancer deletions in a single cell line. In addition, new genomic sequence is created at the site of the deletion following repair, and this sequence may gain regulatory function. An alternative version of Cas9 has been developed specifically for modulating gene expression, relying on fusions of activating9,10 or repressing11,12 domains to the nuclease-deficient form of Cas9 (dCas9). These fusion proteins are ideal for studying multiple loci simultaneously as they do not physically alter the DNA sequence, and instead modulate epigenetics in order to interrogate a regulatory region. The most widely used repressive fusion is KRAB, which recruits the KAP1 co-repressor complex, promoting the deposition of the repression-associated histone H3 lysine 9 trimethylation (H3K9me3)13. dCas9-KRAB, also known as CRISPR interference14, has been used to target and screen individual enhancers for their contributions to gene expression15,16; however, it has not been optimized for targeting multiple regions simultaneously. One version of multiplex CRISPR interference for enhancers, Mosaic-seq17, uses single cell RNA-seq as a readout, but this technology is expensive and only suitable for the study of highly expressed genes due to the low sensitivity of single cell RNA-seq.
We sought to develop a CRISPR interference-based method for dissecting combinatorial enhancer function within the context of a transcriptional response to estrogen. About half of estrogen-responsive genes contain 2 or more enhancers bound by estrogen receptor alpha (ER) nearby18, suggesting that multiple enhancers may be participating in the estrogen response, and understanding the regulatory logic would require targeting multiple enhancers simultaneously. As initial studies using CRISPR interference at promoters suggested that not all promoters are equally responsive to KRAB-mediated repression19, we reasoned that the addition of a distinct repressive domain to dCas9 may facilitate the deactivation of diverse enhancers. We chose the Sin3a Interacting Domain of Mad1 (SID)20 as it leads to the recruitment of histone deacetylases21, which remove acetyl groups on histones that are associated with transcriptional activity. Importantly, the SID domain was effective at reducing gene expression when fused to dCas922 and TALEs23, and Sin3a has been shown to be a potent repressive co-factor in a variety of enhancer sequence contexts24. We used SID4x-dCas9-KRAB (Enhancer-i) to target 10 different enhancers bound by the ER, and identify ER binding sites (ERBS) that are necessary for the estrogen transcriptional response at 4 genes18. We also targeted the combinations of enhancers to identify the sites that cooperate in the production of the estrogen transcriptional response. We found that up to 50 sites can potentially be targeted simultaneously with detectable gene expression changes. Using ChIP-seq and RNA-seq, we demonstrated that Enhancer-i is a highly specific technique for studying multiple enhancers simultaneously.
In this protocol, we describe the steps involved in performing Enhancer-i, a flexible technique that enables the functional study of multiple enhancers simultaneously in a tissue culture setting. Enhancer-i is highly correlated with genetic deletion but provides transient deactivation that is dependent on histone deacetylases (HDACs). By delivering guide RNAs via transient transfection as opposed to stable integration via viral vectors, this protocol avoids deposition and potential spreading of H3K9me3. This protocol details guide RNA design and cloning via Gibson assembly, the transfection of guide RNAs using lipofection, and the analysis of resulting gene expression changes by qPCR. We also include the methods for evaluating the specificity of Enhancer-i targeting at the level of the genome and transcriptome. While this technique was developed to study gene regulation by ER bound enhancers in human cancer cell lines, it is applicable to the dissection of any mammalian enhancer.

<table border="0" cellpadding="0" cellspacing="0" width="742">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:344px;">ZR 96-well Quick-RNA Kit</td>
			<td style="width:112px;">Zymo Research</td>
			<td style="width:119px;">R1053</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Power SYBR Green RNA-to-CT 1-Step</td>
			<td>Applied Biosystems</td>
			<td>4389986</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:344px;">AflII restriction enzyme</td>
			<td style="width:112px;">NEB</td>
			<td style="width:119px;">R0520S</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:344px;">Phusion High-Fidelity PCR Master Mix with HF Buffer</td>
			<td style="width:112px;">NEB</td>
			<td style="width:119px;">M0531L</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:344px;">NEBuilder HiFi DNA Assembly Master Mix</td>
			<td style="width:112px;">NEB</td>
			<td style="width:119px;">E2621L</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:344px;">FuGENE HD</td>
			<td style="width:112px;">Promega</td>
			<td style="width:119px;">E2312</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:344px;">DNA Clean &#38; Concentrator Kit</td>
			<td style="width:112px;">Zymo Research</td>
			<td style="width:119px;">D4013</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:344px;">Buffer RLT Plus</td>
			<td style="width:112px;">Qiagen</td>
			<td style="width:119px;">1053393</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:344px;">b-estradiol</td>
			<td style="width:112px;">Sigma-Aldrich</td>
			<td style="width:119px;">E2758</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:344px;">Human: Ishikawa cells</td>
			<td style="width:112px;">ECACC</td>
			<td style="width:119px;">99040201</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:344px;">H3K27ac rabbit polyclonal</td>
			<td style="width:112px;">Active Motif&#160;</td>
			<td style="width:119px;">39133</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:344px;">H3K9me3 rabbit polyclonal</td>
			<td style="width:112px;">Abcam&#160;</td>
			<td style="width:119px;">ab8898</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:344px;">FLAG mouse monoclonal</td>
			<td style="width:112px;">Sigma-Aldrich&#160;</td>
			<td style="width:119px;">F1804</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:344px;">ER alpha rabbit polyclonal</td>
			<td style="width:112px;">Santa Cruz</td>
			<td style="width:119px;">sc-544</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:344px;">pGL3-U6-PGK-Puro plasmid</td>
			<td style="width:112px;">Addgene&#160;</td>
			<td style="width:119px;">51133</td>
			<td style="width:167px;">Shen et al., 2014</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:344px;">gRNA_cloningVector plasmid</td>
			<td style="width:112px;">Addgene&#160;</td>
			<td style="width:119px;">41824</td>
			<td style="width:167px;">Mali et al., 2013</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:344px;">AflII U6 puromycin plasmid</td>
			<td style="width:112px;">Addgene&#160;</td>
			<td style="width:119px;">106404</td>
			<td>Carleton et al., 2017</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:344px;">SID4X-dCas9-KRAB plasmid</td>
			<td style="width:112px;">Addgene&#160;</td>
			<td style="width:119px;">106399</td>
			<td>Carleton et al., 2017</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:344px;">2-Mercaptoethanol</td>
			<td style="width:112px;">Sigma-Aldrich</td>
			<td style="width:119px;">M6250-10ML</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:344px;">UltraPure DNase/RNase-Free Distilled Water</td>
			<td style="width:112px;">ThermoFisher Scientific</td>
			<td style="width:119px;">10977-023</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:344px;">Opti-MEM I Reduced Serum Medium</td>
			<td style="width:112px;">Gibco</td>
			<td align="right" style="width:119px;">31985070</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:344px;">KAPA Stranded mRNA-Seq Kit, with KAPA mRNA Capture Beads</td>
			<td style="width:112px;">Kapa Biosytems</td>
			<td style="width:119px;">KK8420</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:344px;">Pierce Protease and Phosphatase Inhibitor Mini Tablets</td>
			<td style="width:112px;">ThermoFisher Scientific</td>
			<td style="width:119px;">A32959</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:344px;">Formaldehyde solution</td>
			<td style="width:112px;">Sigma-Aldrich</td>
			<td style="width:119px;">252549-25ML</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:344px;">Geneticin Selective Antibiotic (G418 Sulfate) (50 mg/mL)</td>
			<td style="width:112px;">ThermoFisher Scientific</td>
			<td align="right" style="width:119px;">10131035</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:344px;">LB Broth</td>
			<td style="width:112px;">ThermoFisher Scientific</td>
			<td align="right" style="width:119px;">10855001</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:344px;">Quick-DNA Miniprep Kit</td>
			<td style="width:112px;">Zymo Research</td>
			<td style="width:119px;">D3020</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:344px;">Quick-Load Purple 2-Log DNA Ladder</td>
			<td style="width:112px;">NEB</td>
			<td style="width:119px;">N0050S</td>
			<td></td>
		</tr>
	</tbody>
</table>

dissection of enhancer function using multiplex crispr-based enhancer interference in cell lines

Multiple enhancers often regulate a given gene, yet for most genes, it remains unclear which enhancers are necessary for gene expression, and how these enhancers combine to produce a transcriptional response. As millions of enhancers have been identified, high-throughput tools are needed to determine enhancer function on a genome-wide scale. Current methods for studying enhancer function include making genetic deletions using nuclease-proficient Cas9, but it is difficult to study the combinatorial effects of multiple enhancers using this technique, as multiple successive clonal cell lines must be generated. Here, we present Enhancer-i, a CRISPR interference-based method that allows for functional interrogation of multiple enhancers simultaneously at their endogenous loci. Enhancer-i makes use of two repressive domains fused to nuclease-deficient Cas9, SID and KRAB, to achieve enhancer deactivation via histone deacetylation at targeted loci. This protocol utilizes transient transfection of guide RNAs to enable transient inactivation of targeted regions and is particularly effective at blocking inducible transcriptional responses to stimuli in tissue culture settings. Enhancer-i is highly specific both in its genomic targeting and its effects on global gene expression. Results obtained from this protocol help to understand whether an enhancer is contributing to gene expression, the magnitude of the contribution, and how the contribution is affected by other nearby enhancers.

Figure 1 shows a schematic of the workflow described in the protocol. To determine the contributions of ER-bound enhancers near the estrogen-regulated gene MMP17, which has 3 binding sites nearby as defined by ChIP-seq (Figure 2A), guide RNAs were designed for each region. To design guide RNAs, a 600 - 900 bp window of sequence surrounding each ER binding site of interest was selected and put into a guide RNA design program. Resulting guide RNA sequences with 0-2 predicted off target sites were aligned to the human genome using BLAT. Four non-overlapping guide RNAs that spanned the region defined by ChIP-seq and DNaseI hypersensitivity were chosen for targeting (Figure 2B). Additional sequence (Table 1) was added to each end to facilitate downstream cloning and the resulting 59 nucleotide fragments were ordered. Upon arrival, guide RNAs were diluted and pooled by site, and a short PCR was performed to add homology regions prior to Gibson assembly. Figure 2C shows the expected guide RNA product after a short PCR using the &#34;U6_internal&#34; primers (Table 1), which will add 20 basepairs of sequence to each end of the 59 basepair guide RNA fragment, resulting in a ~100 basepair sequence. Following Gibson assembly, these guide RNA pools were transformed into bacteria and plasmid minipreps were prepared the following day. Figure 2D shows results from an enhancer dissection experiment, where multiple enhancers nearby MMP17 are targeted alone and in combination using Enhancer-i. Sites targeted by Enhancer-i are indicated with a black hexagon. Guide RNA plasmids targeting the indicated sites were transfected into an estrogen-deprived Ishikawa cell line stably expressing SID4X-dCas9-KRAB. Two days later, the media was changed and puromycin was added to enrich for transfected cells. The following day, the cells were harvested following an 8 h 10 nM estradiol treatment. RNA was isolated, and a one-step qPCR was performed. In this example, sites 1 and 2 are necessary for a complete estrogenic response of MMP17, while site 3 does not contribute under these conditions (Figure 2D, lanes ii-iv). When only sites 2 or 3 are active (vi and vii), the estrogen response is similar to when no sites are active (viii), suggesting that these sites cannot contribute independently. Site 1 can contribute some expression by itself (v), but the greatest activity is seen when sites 1 and 2 are active (iv).
To manipulate 10 enhancers near 4 different genes simultaneously (Figure 3A), complex pools of guide RNAs were generated containing 42 enhancer guides and 16 promoter guides. Guide RNA oligos were pooled before the initial guide RNA extension PCR (Step 3.3), and resulting PCR products were purified and combined with the empty puromycin U6 cloning vector using Gibson assembly. Following the Gibson assembly, multiple independent transformations were performed and plated. The plates were scraped into LB and allowed to grow out for 2 - 4 h prior to maxiprep. Figure 3B shows representative reductions in gene expression by qPCR when these guide RNA pools were transfected into an estrogen-deprived Ishikawa cell line stably expressing SID4X-dCas9-KRAB and treated as described above (Figure 2D). Reductions from Enhancer-i are similar to those obtained by targeting the promoter of the putative target gene. Figure 3C shows the effects of dilution of guide RNAs on reduction of the estrogen response using Enhancer-i. A 1:50 dilution of a guide RNA pool targeting the enhancer near G0S2 still yields significant reduction in gene expression, suggesting that Enhancer-i can be used to target up to 50 sites at once. However, the deactivation can be diluted out, indicating that hundreds of sites cannot be targeted simultaneously unless more sensitive detection methods are employed.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/57883/57883fig1.jpg" /> 
Figure 1. Protocol schematic for multiplex enhancer dissection using Enhancer-i. Guide RNAs (red and blue) are designed using e-crisp and selected using the UCSC genome browser. Four guide RNAs are chosen that span the regions of interest (transcription factor binding sites as defined by ChIP-seq). Guide RNA oligonucleotides that have been pooled by the region of interest (red and blue) undergo a PCR to add homology regions (orange) prior to the Gibson assembly and transformation. Resulting plasmid pools are transfected via lipofection into cell lines stably expressing SID4X-dCas9-KRAB or into wild-type cells in conjunction with SID4X-dCas9-KRAB plasmid. Guide RNA plasmid pools can be transfected individually to target one site at a time, or in combination to target multiple sites simultaneously. Transfected cells are treated with antibiotics to enrich for cells containing guide RNAs. At ~72 h post transfection, the cells are harvested. Nucleic acids can be extracted for qPCR, RNA-seq, or ChIP-seq. <a href="https://www.jove.com/files/ftp_upload/57883/57883fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/57883/57883fig2.jpg" /> 
Figure 2. Guide RNA design and enhancer dissection for MMP17. (A) Genome browser screenshot of the ER alpha-bound enhancers (gray) to be targeted near MMP17. This figure has been modified from Carleton, et al.18. (B) Guide RNA designs for the 3 binding sites18. The binding site for ER as defined by ChIP-seq is the target, and the 4 guide RNAs tile across this region. The DNaseI sensitivity signal, which spans the binding site, can also be used to define target sequence for guide RNA design. Both ChIP-seq and DNaseI HS data were obtained from Ishikawa cells treated with 10 nM estradiol for 1 h. (C) Representative guide RNA sequences that are ready for Gibson assembly, having undergone a short PCR to add homology regions. (D) Relative expression of MMP17 measured via qPCR following targeting of specific regions with Enhancer-i and an 8-h10 nM estradiol treatment. Expression is relative to CTCF and expression level of MMP17 in cells not treated with estradiol. Control guide RNAs target the promoter of IL1RN. All error bars represent SEM, double asterisks indicate p &#60;0.01 and single asterisks indicate p &#60;0.05 in a paired t-test. This figure has been modified from Carleton, et al.18. <a href="https://www.jove.com/files/ftp_upload/57883/57883fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/57883/57883fig3.jpg" /> 
Figure 3. Targeting multiple enhancers near different genes simultaneously with pooled Enhancer-i. (A) Schematic of the binding sites and promoters to be targeted in pooled Enhancer-i. (B) The effects on expression as measured by qPCR after E2 treatment on Ishikawa cells transfected with Enhancer-i plasmid pool (green), Promoter-i plasmid pool (blue) or control gRNAs (white)18. A significant reduction at all genes is observed with Enhancer-i. This figure was modified from Carleton, et al.18. (C) The effects on G0S2 expression levels after E2 treatment on Ishikawa cells transfected with different amounts of guide RNAs targeting G0S2. A significant reduction can be seen even with small amounts of guide RNA (1:50 dilution), suggesting that up to 50 sites may targeted simultaneously. All error bars represent SEM, double asterisks indicate p &#60;0.01 and single asterisks indicate p &#60;0.05 in a paired t-test. <a href="https://www.jove.com/files/ftp_upload/57883/57883fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Name</td>
			<td>Sequence</td>
		</tr>
		<tr>
			<td>U6_internal_F</td>
			<td>TTTCTTGGCTTTATATATCTTGTGGAAAGGACGAAACACCG</td>
		</tr>
		<tr>
			<td>U6_internal_R&#160;</td>
			<td>GACTAGCCTTATTTTAACTTGCTATTTCTAGCTCTAAAAC</td>
		</tr>
		<tr>
			<td>U6_PCR_F</td>
			<td>CCAATTCAGTCGACTGGATCCGGTA</td>
		</tr>
		<tr>
			<td>U6_PCR_R</td>
			<td>AAAAAAAGCACCGACTCGGTGCCA</td>
		</tr>
		<tr>
			<td>gRNA_qPCR_F</td>
			<td>GCTAGAAATAGCAAGTTAAAATAAGGCTAGTCCG</td>
		</tr>
		<tr>
			<td>gRNA_qPCR_R</td>
			<td>AAAAAGCACCGACTCGGTGCC</td>
		</tr>
		<tr>
			<td>dCas9_qPCR_F</td>
			<td>GTGACCGAGGGAATGAGAAA</td>
		</tr>
		<tr>
			<td>dCas9_qPCR_R</td>
			<td>AGCTGCTTCACGGTCACTTT</td>
		</tr>
		<tr>
			<td>pAC95_PCR_F</td>
			<td>AGAAGAGAAAGGTGGAGGCC</td>
		</tr>
		<tr>
			<td>pAC95_PCR_R</td>
			<td>CGTCACCGCATGTTAGAAGG</td>
		</tr>
		<tr>
			<td>SID4X_PCR_F</td>
			<td>CAATAGAAACTGGGCTTGTCG</td>
		</tr>
		<tr>
			<td>SID4X_PCR_R</td>
			<td>TCGTGCTTCTTATCCTCTTCC</td>
		</tr>
	</tbody>
</table>
Table 1. Primers used for guide RNA extension and sequencing, qPCR, and detection of the fusion protein.

Watch this Scientific Journal Video about Dissection of Enhancer Function Using Multiplex CRISPR-based Enhancer Interference in Cell Lines at JoVE.com

Dissection of Enhancer Function Using Multiplex CRISPR-based Enhancer Interference in Cell Lines

This protocol describes the steps needed to design and perform multiplexed targeting of enhancers with the deactivating fusion protein SID4X-dCas9-KRAB, also known as enhancer interference (Enhancer-i). This protocol enables the identification of enhancers that regulate gene expression and facilitates the dissection of relationships between enhancers regulating a common target gene.

Multiple enhancers often regulate a given gene, yet for most genes, it remains unclear which enhancers are necessary for gene expression, and how these ...

dissection-enhancer-function-using-multiplex-crispr-based-enhancer

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Genetics

9.2K Views.  University of Utah. This protocol describes the steps needed to design and perform multiplexed targeting of enhancers with the deactivating fusion protein SID4X-dCas9-KRAB, also known as enhancer interference (Enhancer-i). This protocol enables the identification of enhancers that regulate gene expression and facilitates the dissection of relationships between enhancers regulating a common target gene.

Video: Dissection of Enhancer Function Using Multiplex CRISPR-based Enhancer Interference in Cell Lines

RNA Interference-based Investigation of the Function of Heat Shock Protein 27 during Corneal Epithelial Wound Healing

Small interfering RNA (siRNA) is among the most widely used RNA interference methods for the short-term silencing of protein-coding genes. siRNA is a synthetic RNA duplex created to specifically target a mRNA transcript to induce its degradation and it has been used to identify novel pathways in various cellular processes. Few reports exist regarding the role of phosphorylated heat shock protein 27 (HSP27) in corneal epithelial wound healing. Herein, cultured human corneal epithelial cells were divided into a scrambled control-siRNA transfected group and a HSP27-specific siRNA-transfected group. Scratch-induced directional wounding assays, and western blotting, and flow cytometry were then performed. We conclude that HSP27 has roles in corneal epithelial wound healing that may involve epithelial cell apoptosis and migration. Here, step-by-step descriptions of sample preparation and the study protocol are provided.

Herein, we present a protocol to use heat shock protein 27 (HSP27)-specific small interfering RNA to assess the function of HSP27 during corneal epithelial wound healing. RNA interference is the best method for effectively knocking-down gene expression to investigate protein function in various cell types.

Small interfering RNA (siRNA) is among the most widely used RNA interference methods for the short-term silencing of protein-coding genes. siRNA is a ...

Single-cell Gene Expression Using Multiplex RT-qPCR to Characterize Heterogeneity of Rare Lymphoid Populations

Gene expression heterogeneity is an interesting feature to investigate in lymphoid populations. Gene expression in these cells varies during cell activation, stress, or stimulation. Single-cell multiplex gene expression enables the simultaneous assessment of tens of genes1,2,3. At the single-cell level, multiplex gene expression determines population heterogeneity4,5. It allows for the distinction of population heterogeneity by determining both the probable mix of diverse precursor stages among mature cells and also the diversity of cell responses to stimuli.
Innate lymphoid cells (ILC) have been recently described as a population of innate effectors of the immune response6,7. In this protocol, cell heterogeneity of the ILC hepatic compartment is investigated during homeostasis.
Currently, the most widely used technique to assess gene expression is RT-qPCR. This method measures gene expression only one gene at a time. Additionally, this method cannot estimate heterogeneity of gene expression, since multiple cells are needed for one test. This leads to the measurement of the average gene expression of the population. When assessing large numbers of genes, RT-qPCR becomes a time-, reagent-, and sample-consuming method. Hence, the trade-offs limit the number of genes or cell populations that can be evaluated, increasing the risk of missing the global picture.
This manuscript describes how single-cell multiplex RT-qPCR can be used to overcome these limitations. This technique has benefited from recent microfluidics technological advances1,2. Reactions occurring in multiplex RT-qPCR chips do not exceed the nanoliter-level. Hence, single-cell gene expression, as well as simultaneous multiple gene expression, can be performed in a reagent-, sample-, and cost-effective manner. It is possible to test cell gene signature heterogeneity at the clonal level between cell subsets within a population at different developmental stages or under different conditions4,5. Working on rare populations with large numbers of conditions at the single-cell level is no longer a restriction.

This protocol describes how to assess the expression of a large array of genes at the clonal level. Single-cell RT-qPCR produces highly reliable results with a strong sensitivity for hundreds of samples and genes.

Gene expression heterogeneity is an interesting feature to investigate in lymphoid populations. Gene expression in these cells varies during cell ...

Detection of Copy Number Alterations Using Single Cell Sequencing

Detection of genomic changes at single cell resolution is important for characterizing genetic heterogeneity and evolution in normal tissues, cancers, and microbial populations. Traditional methods for assessing genetic heterogeneity have been limited by low resolution, low sensitivity, and/or low specificity. Single cell sequencing has emerged as a powerful tool for detecting genetic heterogeneity with high resolution, high sensitivity and, when appropriately analyzed, high specificity. Here we provide a protocol for the isolation, whole genome amplification, sequencing, and analysis of single cells. Our approach allows for the reliable identification of megabase-scale copy number variants in single cells. However, aspects of this protocol can also be applied to investigate other types of genetic alterations in single cells.

Single cell sequencing is an increasingly popular and accessible tool for addressing genomic changes at high resolution. We provide a protocol that uses single cell sequencing to identify copy number alterations in single cells.

Detection of genomic changes at single cell resolution is important for characterizing genetic heterogeneity and evolution in normal tissues, cancers, and ...

Chromatin Immunoprecipitation (ChIP) in Mouse T-cell Lines

Signaling pathways regulate gene expression programs via the modulation of the chromatin structure at different levels, such as by post-translational modifications (PTMs) of histone tails, the exchange of canonical histones with histone variants, and nucleosome eviction. Such regulation requires the binding of signal-sensitive transcription factors (TFs) that recruit chromatin-modifying enzymes at regulatory elements defined as enhancers. Understanding how signaling cascades regulate enhancer activity requires a comprehensive analysis of the binding of TFs, chromatin modifying enzymes, and the occupancy of specific histone marks and histone variants. Chromatin immunoprecipitation (ChIP) assays utilize highly specific antibodies to immunoprecipitate specific protein/DNA complexes. The subsequent analysis of the purified DNA allows for the identification the region occupied by the protein recognized by the antibody. This work describes a protocol to efficiently perform ChIP of histone proteins in a mature mouse T-cell line. The presented protocol allows for the performance of ChIP assays in a reasonable timeframe and with high reproducibility.

Chromatin Immunoprecipitation ChIP in Mouse T-cell Lines

This work describes a protocol for chromatin immunoprecipitation (ChIP) using a mature mouse T-cell line. This protocol is suitable to investigate the distribution of specific histone marks at specific promoter sites or genome-wide.

Signaling pathways regulate gene expression programs via the modulation of the chromatin structure at different levels, such as by post-translational ...

Genome Editing in Mammalian Cell Lines using CRISPR-Cas

The clustered regularly interspaced short palindromic repeats (CRISPR) system functions naturally in bacterial adaptive immunity, but has been successfully repurposed for genome engineering in many different living organisms. Most commonly, the wildtype CRISPR associated 9 (Cas9) or Cas12a endonuclease is used to cleave specific sites in the genome, after which the DNA double-stranded break is repaired via the non-homologous end joining (NHEJ) pathway or the homology-directed repair (HDR) pathway depending on whether a donor template is absent or present respectively. To date, CRISPR systems from different bacterial species have been shown to be capable of performing genome editing in mammalian cells. However, despite the apparent simplicity of the technology, multiple design parameters need to be considered, which often leave users perplexed about how best to carry out their genome editing experiments. Here, we describe a complete workflow from experimental design to identification of cell clones that carry desired DNA modifications, with the goal of facilitating successful execution of genome editing experiments in mammalian cell lines. We highlight key considerations for users to take note of, including the choice of CRISPR system, the spacer length, and the design of a single-stranded oligodeoxynucleotide (ssODN) donor template. We envision that this workflow will be useful for gene knockout studies, disease modeling efforts, or the generation of reporter cell lines.

CRISPR-Cas is a powerful technology to engineer the complex genomes of plants and animals. Here, we detail a protocol to efficiently edit the human genome using different Cas endonucleases. We highlight important considerations and design parameters to optimize editing efficiency.

The clustered regularly interspaced short palindromic repeats (CRISPR) system functions naturally in bacterial adaptive immunity, but has been ...

Manipulation of Gene Function in Mexican Cavefish

Cave animals provide a compelling system for investigating the evolutionary mechanisms and genetic bases underlying changes in numerous complex traits, including eye degeneration, albinism, sleep loss, hyperphagia, and sensory processing. Species of cavefish from around the world display a convergent evolution of morphological and behavioral traits due to shared environmental pressures between different cave systems. Diverse cave species have been studied in the laboratory setting. The Mexican tetra, Astyanax mexicanus, with sighted and blind forms, has provided unique insights into biological and molecular processes underlying the evolution of complex traits and is well-poised as an emerging model system. While candidate genes regulating the evolution of diverse biological processes have been identified in A. mexicanus, the ability to validate a role for individual genes has been limited. The application of transgenesis and gene-editing technology has the potential to overcome this significant impediment and to investigate the mechanisms underlying the evolution of complex traits. Here, we describe a different methodology for manipulating gene expression in A. mexicanus. Approaches include the use of morpholinos, Tol2 transgenesis, and gene-editing systems, commonly used in zebrafish and other fish models, to manipulate gene function in A. mexicanus. These protocols include detailed descriptions of timed breeding procedures, the collection of fertilized eggs, injections, and the selection of genetically modified animals. These methodological approaches will allow for the investigation of the genetic and neural mechanisms underlying the evolution of diverse traits in A. mexicanus.&#160;

We describe approaches for the manipulation of genes in the evolutionary model system Astyanax mexicanus. Three different techniques are described: Tol2-mediated transgenesis, targeted manipulation of the genome using CRISPR/Cas9, and knockdown of expression using morpholinos. These tools should facilitate the direct investigation of genes underlying the variation between surface- and cave-dwelling forms.

Cave animals provide a compelling system for investigating the evolutionary mechanisms and genetic bases underlying changes in numerous complex traits, ...

Mass Spectrometry-Based Proteomics Analyses Using the OpenProt Database to Unveil Novel Proteins Translated from Non-Canonical Open Reading Frames

Genome annotation is central to today's proteomic research as it draws the outlines of the proteomic landscape. Traditional models of open reading frame (ORF) annotation impose two arbitrary criteria: a minimum length of 100 codons and a single ORF per transcript. However, a growing number of studies report expression of proteins from allegedly non-coding regions, challenging the accuracy of current genome annotations. These novel proteins were found encoded either within non-coding RNAs, 5' or 3' untranslated regions (UTRs) of mRNAs, or overlapping a known coding sequence (CDS) in an alternative ORF. OpenProt is the first database that enforces a polycistronic model for eukaryotic genomes, allowing annotation of multiple ORFs per transcript. OpenProt is freely accessible and offers custom downloads of protein sequences across 10 species. Using OpenProt database for proteomic experiments enables novel proteins discovery and highlights the polycistronic nature of eukaryotic genes. The size of OpenProt database (all predicted proteins) is substantial and need be taken in account for the analysis. However, with appropriate false discovery rate (FDR) settings or the use of a restricted OpenProt database, users will gain a more realistic view of the proteomic landscape. Overall, OpenProt is a freely available tool that will foster proteomic discoveries.

OpenProt is a freely accessible database that enforces a polycistronic model of eukaryotic genomes. Here, we present a protocol for the use of OpenProt databases when interrogating mass spectrometry datasets. Using OpenProt database for analysis of proteomic experiments allows for discovery of novel and previously undetectable proteins.

Genome annotation is central to today's proteomic research as it draws the outlines of the proteomic landscape. Traditional models of open reading frame ...

Designing Automated, High-throughput, Continuous Cell Growth Experiments Using eVOLVER

Continuous culture methods enable cells to be grown under quantitatively controlled environmental conditions, and are thus broadly useful for measuring fitness phenotypes and improving our understanding of how genotypes are shaped by selection. Extensive recent efforts to develop and apply niche continuous culture devices have revealed the benefits of conducting new forms of cell culture control. This includes defining custom selection pressures and increasing throughput for studies ranging from long-term experimental evolution to genome-wide library selections and synthetic gene circuit characterization. The eVOLVER platform was recently developed to meet this growing demand: a continuous culture platform with a high degree of scalability, flexibility, and automation. eVOLVER provides a single standardizing platform that can be (re)-configured and scaled with minimal effort to perform many different types of high-throughput or multi-dimensional growth selection experiments. Here, a protocol is presented to provide users of the eVOLVER framework a description for configuring the system to conduct a custom, large-scale continuous growth experiment. Specifically, the protocol guides users on how to program the system to multiplex two selection pressures &#8212; temperature and osmolarity &#8212; across many eVOLVER vials in order to quantify fitness landscapes of Saccharomyces cerevisiae mutants at fine resolution. We show how the device can be configured both programmatically, through its open-source web-based software, and physically, by arranging fluidic and hardware layouts. The process of physically setting up the device, programming the culture routine, monitoring and interacting with the experiment in real-time over the internet, sampling vials for subsequent offline analysis, and post experiment data analysis are detailed. This should serve as a starting point for researchers across diverse disciplines to apply eVOLVER in the design of their own complex and high-throughput cell growth experiments to study and manipulate biological systems.

The eVOLVER framework enables high-throughput continuous microbial culture with high resolution and dynamic control over experimental parameters. This protocol demonstrates how to apply the system to conduct a complex fitness experiment, guiding users on programming automated control over many individual cultures, measuring, collecting, and interacting with experimental data in real-time.

Continuous culture methods enable cells to be grown under quantitatively controlled environmental conditions, and are thus broadly useful for measuring ...

Pooled CRISPR-Based Genetic Screens in Mammalian Cells

Genome editing using the CRISPR-Cas system has vastly advanced the ability to precisely edit the genomes of various organisms. In the context of mammalian cells, this technology represents a novel means to perform genome-wide genetic screens for functional genomics studies. Libraries of guide RNAs (sgRNA) targeting all open reading frames permit the facile generation of thousands of genetic perturbations in a single pool of cells that can be screened for specific phenotypes to implicate gene function and cellular processes in an unbiased and systematic way. CRISPR-Cas screens provide researchers with a simple, efficient, and inexpensive method to uncover the genetic blueprints for cellular phenotypes. Furthermore, differential analysis of screens performed in various cell lines and from different cancer types can identify genes that are contextually essential in tumor cells, revealing potential targets for specific anticancer therapies. Performing genome-wide screens in human cells can be daunting, as this involves the handling of tens of millions of cells and requires analysis of large sets of data. The details of these screens, such as cell line characterization, CRISPR library considerations, and understanding the limitations and capabilities of CRISPR technology during analysis, are often overlooked. Provided here is a detailed protocol for the successful performance of pooled genome-wide CRISPR-Cas9 based screens.

CRISPR-Cas9 technology provides an efficient method to precisely edit the mammalian genome in any cell type and represents a novel means to perform genome-wide genetic screens. A detailed protocol discussing the steps required for the successful performance of pooled genome-wide CRISPR-Cas9 screens is provided here.

Genome editing using the CRISPR-Cas system has vastly advanced the ability to precisely edit the genomes of various organisms. In the context of mammalian ...

Identification of Enhancer-Promoter Contacts in Embryoid Bodies by Quantitative Chromosome Conformation Capture (4C)

During mammalian development, cell fates are determined through the establishment of regulatory networks that define the specificity, timing, and spatial patterns of gene expression. Embryoid bodies (EBs) derived from pluripotent stem cells have been a popular model to study the differentiation of the main three germ layers and to define regulatory circuits during cell fate specification. Although it is well-known that tissue-specific enhancers play an important role in these networks by interacting with promoters, assigning them to their relevant target genes still remains challenging. To make this possible, quantitative approaches are needed to study enhancer-promoter contacts and their dynamics during development. Here, we adapted a 4C method to define enhancers and their contacts with cognate promoters in the EB differentiation model. The method uses frequently cutting restriction enzymes, sonication, and a nested-ligation-mediated PCR protocol compatible with commercial DNA library preparation kits. Subsequently, the 4C libraries are subjected to high-throughput sequencing and analyzed bioinformatically, allowing detection and quantification of all sequences that have contacts with a chosen promoter. The resulting sequencing data can also be used to gain information about the dynamics of enhancer-promoter contacts during differentiation. The technique described for the EB differentiation model is easy to implement.

Identification of Enhancer-Promoter Contacts in Embryoid Bodies by Quantitative Chromosome Conformation Capture 4C

We report the application of quantitative chromosome conformation capture followed by high-throughput sequencing in embryoid bodies generated from embryonic stem cells. This technique allows to identify and quantitate the contacts between putative enhancers and promoter regions of a given gene during embryonic stem cell differentiation.

During mammalian development, cell fates are determined through the establishment of regulatory networks that define the specificity, timing, and spatial ...