All the procedures involving animals were in accordance with the regulations of the animal ethics committee of the Karolinska Institutet, Stockholm, Sweden.
1. Micro-patterned chip layout
<ol>
	<li>Use a custom-designed chip (Table of Materials) (Figure 1A): a 19.5 mm x 19.5 mm coverslip with activated micropatterns, printed by photolithography on borosilicate glass. 
	NOTE: These micropatterns are surrounded by a cytophobic area. Therefore, a seeded cell can only attach and grow on one of these micropatterns and capture the AR of that micropattern. The chip is divided into three zones and each zone consists of micropatterns with a specific AR. The chip layout is shown in Figure 1B. The geometry of the defined ARs is presented in Table 1. Magnified fluorescent images of the different shapes of the fibronectin micropatterns are shown in the lower images in Figure 1B.</li>
</ol>
2. Coating micropatterned chips
<ol>
	<li>Prepare 2x coating protein solution for each chip by adding 80 &#181;g of fibronectin to 2 mL of phosphate-buffered saline (PBS-/-).</li>
	<li>Transfer a chip to a 35 mm Greiner Petri dish and immediately add 2 mL of PBS-/-. Then add 2 mL of the 2x coating protein solution.</li>
	<li>Incubate the chips at room temperature for 2 h.</li>
	<li>Wash the coating solution by successive dilution steps with PBS-/-. The chip surface should always be wet. Then, replace the PBS with 2 mL of plating medium and incubate at 37 &#176;C until seeding cells.</li>
</ol>
3. Isolation of CMs
<ol>
	<li>Prepare the plating medium by supplementing DMEM:M199 (4:1) with 10% horse serum, 4% fetal bovine serum, 2% HEPES (1 M) and 1% penicillin/streptomycin (10,000 U/mL)22.</li>
	<li>Dissect the tissue from the left ventricle of 2-day-old neonatal rat hearts and transfer to a 10 cm dish containing PBS. Cut the tissue into approximately 1 mm3 pieces.</li>
	<li>Transfer the harvested tissue into a rotor-cap tube, equipped with a rotor in the cap for tissue dissociation (Table of Materials). Let the tissue settle down and then carefully remove the supernatant.</li>
	<li>Add 2.5 mL of the mixture of enzyme mix 1 and 2, prepared using the Neonatal Heart Dissociation Kit (Table of Materials), to the C Tube and close the cap tightly.</li>
	<li>Insert the rotor-cap tube onto the sleeve of the dissociator, equipped with heaters (Figure 2A and B) (Table of Materials). Run the incubation program 37C_mr_NHDK_1 (Figure 2C), which lasts about an hour.</li>
	<li>While the incubation program is running, prepare PEB buffer containing 2 mM EDTA and 0.5% bovine serum albumin (BSA) in PBS, pH 7.2, and keep it at 4 &#176;C.</li>
	<li>After termination of the incubation program, detach the rotor-cap tube (Figure 2D) and add 7.5 mL of pre-warmed plating medium.</li>
	<li>Resuspend the sample and filter the cell suspension using a 70 &#181;m strainer.</li>
	<li>Wash the strainer with another 3 mL of plating medium.</li>
	<li>Centrifuge the cell suspension at 600 x g for 5 min. Aspirate the supernatant completely.</li>
	<li>Resuspend the cell pellet in 60 &#181;L of cold PEB buffer.</li>
	<li>Add 20 &#181;L of Neonatal Cardiomyocyte Isolation Cocktail (Table of Materials), containing micron-sized beads that target non-CMs.</li>
	<li>Add 20 &#181;L of Anti-Red Blood Cell beads (Table of Materials).</li>
	<li>Mix the suspension and incubate at 4 &#176;C for 15 min.</li>
	<li>Add 400 &#181;L of PEB buffer.</li>
	<li>Apply the cell suspension onto the LD column (Table of Materials), which has been inserted vertically into a magnet stand and washed well with PEB buffer.</li>
	<li>Collect unlabeled cells and wash column with 0.5 mL of PEB buffer.</li>
	<li>Add 8 mL of plating medium and transfer the cell suspension into a 75-cm2 uncoated culture flask and incubate at 37 &#176;C for 1.5 h. The remaining non-CMs will start to adhere to the uncoated cell culture and the cell suspension will be enriched by the CM population.</li>
</ol>
4. Patterning CMs
NOTE: We compared single CMs with ARs of 1:1, 7:1 or 11:1. This is done by seeding the isolated neonatal rat CMs onto a specially designed chip filled with fibronectin-coated micropatterns with defined ARs of 1:1, 7:1 or 11:1. The micropatterns were coated by fibronectin, surrounded by cytophobic surface. Therefore, CMs will attach, spread and capture the defined AR of micropatterns by solely growing on the fibronectin substrate. Pattern the isolated CMs according to the following steps.
<ol>
	<li>Transfer the cell suspension to a 15 mL tube, count the cells and dilute to a concentration of 100,000 cells per mL by adding appropriate plating medium.</li>
	<li>Add 2 mL of cell suspension onto the chip, which has already been submerged in 2 mL of warm plating medium inside a 35 mm Greiner Petri dish.</li>
	<li>Incubate the dish at 37 &#176;C with 5% CO2 to let the CMs attach to the fibronectin-coated micropatterns and allow each CM to acquire the AR of its substrate micropattern.</li>
	<li>After 18 h, check the chip. If most of the cells have attached, detach and remove the debris and dead cells that are attached to the patterned cell. Do this by removing the plating medium and gently adding PBS-/- dropwise, starting from the center of the chip then moving towards the sides. Repeat 2 times.</li>
	<li>Aspirate the PBS with fresh maintenance medium by supplementing DMEM:M199 (4:1) with 4% horse serum, 4% fetal bovine serum, 2% HEPES (1 M) and 1% penicillin/streptomycin (10,000 U/mL).</li>
</ol>
5. Picking adherent CMs
NOTE: After a culturing period of 72 hours, patterned single CMs are picked from their fibronectin micropatterns using a semi-automated cell picker (Table of Materials) (Figure 3). The cell picker uses a software23 to control the motorized stage (Figure 3A). A 70 &#181;m glass microcapillary (Figure 3B) is used to pick and inject the patterned neonatal rat CMs. The cell picker sorts adherent cells by generating a vacuum and injecting the cells by applying pressure. The vacuum in syringe number 1 is applied by pulling the syringe using the syringe pump (Figure 3C). The hydrostatic pressure is based on gravity and induced by placing syringe number 2 at a distance of 87 cm over the microscope desk. Syringes 1 and 2 are respectively connected via PTFE tubes, to valves 1 and 2, which are embedded in the control unit (Figure 3D). The PTFE tubes are completely filled with RNase-free water. The picked single cell is then injected to the polymerase chain reaction (PCR) tube, containing 3.55 &#181;L of lysis buffer.
<ol>
	<li>After a culturing period of 72 hours, remove the old medium and gently flush the chip surface with warm DPBS-/-.
	<ol>
		<li>Keep the dish flat and aspirate the old medium gently with a 1000 &#181;L pipette from one side of the dish. Make sure that the chip remains wet at all times.</li>
		<li>Add 2 mL of DPBS-/- gently and drop-wise detach most of the dead cells that are attached to the patterned cells, starting from the center of the chip and then moving to its sides.</li>
		<li>Aspirate most of the DPBS to remove as many detached floating cells as possible, starting from the center of the chip and then moving to the sides.</li>
		<li>Repeat steps 5.1.2 and 5.1.3 once more.</li>
	</ol>
	</li>
	<li>Use angled forceps to grab the edge of the chip and immediately transfer it to a new sterile 35 mm Greiner Petri dish to reduce the number of floating cells while picking.</li>
	<li>Immediately add 1.5 mL of DPBS-/- so that the chip does not dry out.</li>
	<li>Add 1.5 &#181;L of Vibrant Dye Cycle green to visualize the nuclei of the live cells.</li>
	<li>Place the chip in the center of the Greiner Petri dish by using the tip of the forceps.</li>
	<li>Put a chamber (Table of Materials) over the chip. The chamber will fix the chip to the bottom of the dish, without blocking access to the cell patterns.</li>
	<li>Mount the Greiner Petri dish onto the dish holder of the cell picker stage and insert the magnetic cap.</li>
	<li>Calibrate the automated injection.
	<ol>
		<li>Locate the crosshair, which is engraved on the motorized stage in the middle of the image in the Live View window.</li>
		<li>Focus on the crosshair and select the Calibration for automated injection button in the Scanning and sorting window.</li>
	</ol>
	</li>
	<li>Replace the DPBS-/- with 1.5 mL of DPBS/trypsin-/- (1:1) while the dish is on the stage, to loosen the cells from the fibronectin so that a fluidic vacuum can be used to pick the cells.</li>
	<li>Scan the whole chip using the Scanning tab in the Scanning and sorting window. Locate the top left corner of the chip in the field of view and click on Get current microscope position in the top left corner row.
	<ol>
		<li>Then, move the motorized stage to the bottom right corner of the chip. Focus the microscope and click on Get current microscope position in the bottom right corner row.</li>
	</ol>
	</li>
	<li>Click on the Set sharpest plane button and on the popped up window click on the Go to the top right corner. Focus the microscope and click on Go to the bottom left corner and set the focus. When done click the Finish button and start scanning.</li>
	<li>When the scanning is terminated, go to the Analyzing tab and select the single cells that pass the study criteria.</li>
	<li>Make sure that the glass microcapillary is in the middle of the microscope&#8217;s live view.</li>
	<li>Control the syringe pump using the Pump window of the software. Create a vacuum by withdrawing 4 mL from a 50 mL number 1 syringe, which has a diameter of 27 mm.</li>
	<li>In the Sorting tab
	<ol>
		<li>Set the injection parameters of the valves. It was calculated that the injection volume that delivered a picked single cell was 1 &#956;l, if valve 2 was opened for 120 milliseconds and then valve 1 opened for 20 was milliseconds after a time lapse of 200 milliseconds. Due to the elasticity of the tubes, open valve 1 to stop injecting the flow.</li>
		<li>Set the pick-up parameters of the valves. It was calculated that if valve 1 was opened for 20 milliseconds and then valve 2 was opened for 10 milliseconds, after a time lapse of 10 milliseconds, most of the patterned cells can be picked up. This is because their fibronectin bindings were loosened after being treated by trypsin.</li>
		<li>Click on the Compute the path button. The software computes the fastest path from cell to cell, to pick up and inject the selected cells throughout the chip.</li>
		<li>Focus the microscope on a patterned cell on the chip surface.</li>
		<li>Using the joystick, move the microcapillary down carefully, so that the sharpest image of the tip of the microcapillary can be obtained without touching the cell.</li>
		<li>Click the Set button in the Micropipette offset section. A new window will pop up, showing the microcapillary cross section. Click on the exact center of the capillary. The software will then record the tip offset of the capillary in the x, y and z coordinates.</li>
		<li>Launch sorting using the Start sorting button.</li>
	</ol>
	</li>
</ol>

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This study used single-cell RNA sequencing, which is a novel and powerful technology that can detect the transcriptome of single cells. It was combined with an innovative approach to culturing single CMs, so that they took on different ARs that, otherwise, could only have been observed in vivo.
The study had some limitations. For example, neonatal CMs had to be used to generate different morphotypes, as it is exceptionally challenging to culture enough vital adult CMs for 72 hours in defined shapes. Furthermore, CMs were cultured for 72 hours ex vivo, which might have had an impact on the gene expression pattern. However, this culturing was necessary, so that the cells could form specific morphotypes. Moreover, only single cells that were mononucleated and fully covered the fibronectin micropattern were selected for sorting. Patterned cells on each chip must be sorted merely in one round of sorting. Finally, about 50 cells that is roughly one-third of the selected cells were successfully picked up from each chip. There are two reasons that restricted the number of successfully picked cells. First, some cells were too tightly attached to the fibronectin pattern and the pickup flow was not forcible enough to successfully pick them up. Second, due to the trypsin treatment, the attachment between some cells and fibronectin became too loose. Consequently, these cells were pushed away from their fibronectin micropatterns, when the microcapillary approached them, and they were not picked up. The authors do not claim that this setup is the same as an in vivo environment, but it proved to be a viable approach to answering the research question.
The proposed method is applicable on different cell types (e.g., for hiPS-CMs). However, the following factors should be optimized to study other cell-types. Suitable ECM adhesive molecules for attachment of the specific cell-type should be used for coating the micropatterns. The geometry of the micropatterns should be modified according to the study question and cell-type. The culturing period can be modified based on the study question. The detachment reagent and its incubation time should be optimized precisely for the study cell-type. For instance, Accutase can be used instead of TryplE for detachment of embryonic and neuronal stem cells. The opening time parameters of the valves should be scrutinized to pick cells successfully, but gently. In summary, we engineered a novel platform to study cell shape that can provide a valuable resource for researchers in the field. In this context, we designed an experimental approach that mimicked in vitro characteristic shapes imposed on CM in vivo by hemodynamic constraints to identify the interplay between cellular architecture and gene expression. We also report the development of a novel platform to study HF in vitro and the identification of cell shape as a powerful determinant of gene expression. This is a novel observation with far-reaching implications for biology and medicine.

According to the World Health Organization, cardiovascular disease (CVD) is a major cause of morbidity and mortality worldwide. CVD dramatically affects the quality of people&#8217;s lives and has a huge socioeconomic impact. Cardiomyopathies, such as HCM and DCM, are primary disorders of the heart muscle and major causes of HF have been associated with high morbidity and mortality. There are many causes of HF, including environmental effects, such as infections and exposure to toxins or certain drugs8. HF can also be caused by genetic predisposition, namely mutations9. It is believed that the changes in genetic composition that affect extracellular matrix (ECM) molecules, integrins or cytoskeletal proteins could be responsible for impaired mechanosensation and various types of cardiac disease10.
The main feature of HCM is unexplained hypertrophy of the left ventricle11, and sometimes of the right ventricle12, and this frequently presents with predominant involvement of the interventricular septum. HCM is also characterized by diastolic dysfunction and myocyte disarray and fibrosis13. In most cases, the contractile apparatus of the heart is affected by mutations in sarcomeric proteins, leading to increased contractility of the myocytes14. In contrast, DCM is characterized by dilatation of one, or both, ventricles and has a familial etiology in 30% to 50% of cases15. DCM affects a wide range of cellular functions, leading to impaired contraction of the myocytes, cell death and fibrotic repair16.
Genetics has shown that certain types of mutations force single CMs to adopt specific shape characteristics during HCM3, namely square-shaped cells with a length:width AR that is almost equal to 1:14 (AR1). The same is true for DCM, with elongated cells with an AR that is almost equal to 11:1 (AR11). In addition, HF can be caused by increased afterload (e.g., in hypertension). In these cases, hemodynamic demands force CMs to take on square shapes, according to the Laplace&#8217;s law, and the AR changes from 7:15 (AR7) to 1:16,7. HF can also be caused by an increase in preload (e.g., in conditions that lead to volume overload). When this happens, the biophysical constraints force CMs to elongate and the AR changes from 7:1 to 11:1.
Signaling activity at membranes depend on global cell geometry parameters, such as the cellular AR, size, the membrane surface area and the membrane curvature18. When neonatal rat CMs were plated on substrates that were patterned to constrain the cells in a specific length:width AR, they demonstrated the best contractile function when the ratios were similar to the cells in a healthy adult heart. In contrast, they performed poorly when the ratios were similar to those of myocytes in failing hearts19. In the early stages of hypertrophy, cells become wider, as reflected by an increase in the cross-sectional area. HF occurs in the later stages of hypertrophy and cells typically appear elongated. Therefore, it is not surprising that in vivo rat models of chronic hypertrophy have reported an increase in the left ventricular myocyte length of around 30%20, but adult CMs from transgenic mouse model that were acutely treated with hypertrophic stimuli in vitro demonstrated similar increases in cell width instead21.
Single-cell RNA sequencing, which allows precise analysis of the transcriptome of single cells, is currently revolutionizing the understanding of cell biology. This technology was the preferred method when it came to answering the question of how did individual cell shapes affect gene expression. We compared single cells with different shapes, in particular with ARs of 1:1, 7:1 or 11:1. This was done by seeding the neonatal rat ventricular CMs onto a specially designed chip filled with the fibronectin-coated micropatterns2 with defined ARs of 1:1, 7:1 or 11:1. The micropatterns were fabricated using photolithography technology. The micropatterns were coated by fibronectin, surrounded by cytophobic surface. Therefore, CMs will attach, spread and capture the defined AR of micropatterns by solely growing on the fibronectin substrate, while avoiding the cytophobic area. The micropatterns are not in a well-shaped format. Instead, the fibronectin level is exactly at the same height of the surrounding cytophobic area. This provided similar conditions to growing cells in a Petri dish, as there is no stress from the surrounding walls. In addition, the surface area of micropatterns with different ARs are equal.
There were two particularly important aspects of the experimental design, which led to the use of single-cell RNA sequencing instead of bulk RNA sequencing. First, only a few percentages of the micropatterns can be occupied by a single cell. Second, sometimes a single cell does not fully occupy the micropattern surface. Single cells that completely cover a micropattern surface must be picked for single-cell RNA analysis. Because only a subgroup of the plated cells on a chip satisfied both criteria, it was not feasible to simply trypsinize the whole chip and collect all the cells for bulk RNA sequencing. Qualified cells needed to be picked individually using a semi-automated cell picker.
It currently remains unknown whether CM shape, by itself, has an intra-functional impact on the myocardial syncytium. The main purpose of the methods proposed in this paper was to develop a novel platform to study whether cell shape per se had an impact on the transcriptome17. Although in vitro studies are different from in vivo studies, the purpose of this study was to investigate the effect of different cell shapes on gene expression, bearing in mind that comparing cells with different shapes in vivo is extremely demanding. These experiments were inspired by Kuo et al.19, who used a similar approach and reported that they observed changes in physiological parameters due to changes in cell shape.

<table>
	<tbody>
		<tr>
			<td>2100 Bioanalyzer Instrument</td>
			<td>Agilent Technologies</td>
			<td>G2939BA</td>
			<td>Automated electrophoresis analyzer</td>
		</tr>
		<tr>
			<td>Anti-Red Blood Cell MicroBeads</td>
			<td>Miltenyi Biotec</td>
			<td>130-109-681</td>
			<td></td>
		</tr>
		<tr>
			<td>Axio Observer microscope</td>
			<td>Zeiss</td>
			<td>Z1</td>
			<td>Inverted microscope</td>
		</tr>
		<tr>
			<td>Betaine solution (5 M)</td>
			<td>Sigma-Aldrich, MERCK</td>
			<td>B0300</td>
			<td></td>
		</tr>
		<tr>
			<td>CellSorter</td>
			<td>CELLSORTER</td>
			<td>https://www.singlecellpicker.com/</td>
			<td>Cell picker</td>
		</tr>
		<tr>
			<td>CYTOOchamber</td>
			<td>CYTOO</td>
			<td>30-010</td>
			<td>Custom-designed chip</td>
		</tr>
		<tr>
			<td>CYTOOchip</td>
			<td>CYTOO</td>
			<td>10-950-00-18</td>
			<td>Chamber</td>
		</tr>
		<tr>
			<td>DMEM</td>
			<td>Thermo Fisher Scientific</td>
			<td>31966-021</td>
			<td>high glucose, GlutaMAX Supplement</td>
		</tr>
		<tr>
			<td>dNTP mix (25 mM)</td>
			<td>Thermo Fisher Scientific</td>
			<td>R1122</td>
			<td></td>
		</tr>
		<tr>
			<td>Donkey Anti-Mouse IgG Alexa Fluor 488</td>
			<td>Abcam PLC</td>
			<td>ab150105</td>
			<td></td>
		</tr>
		<tr>
			<td>DTT (100 mM)</td>
			<td>Thermo Fisher Scientific</td>
			<td>18064071</td>
			<td></td>
		</tr>
		<tr>
			<td>ERCC RNA Spike-In Mix</td>
			<td>Thermo Fisher Scientific</td>
			<td>4456740</td>
			<td></td>
		</tr>
		<tr>
			<td>Fetal Bovine Serum</td>
			<td>Thermo Fisher Scientific</td>
			<td>10082-147</td>
			<td></td>
		</tr>
		<tr>
			<td>Fibronectin</td>
			<td>Sigma-Aldrich, MERCK</td>
			<td>F4759</td>
			<td></td>
		</tr>
		<tr>
			<td>gentleMACS C Tube</td>
			<td>Miltenyi Biotec</td>
			<td>130-093-237</td>
			<td>Rotor-cap tube</td>
		</tr>
		<tr>
			<td>gentleMACS Octo Dissociator with Heaters</td>
			<td>Miltenyi Biotec</td>
			<td>130-096-427</td>
			<td>Dissociator with heater</td>
		</tr>
		<tr>
			<td>Greiner CELLSTAR Petri dish</td>
			<td>Sigma-Aldrich, MERCK</td>
			<td>P6987</td>
			<td></td>
		</tr>
		<tr>
			<td>HEPES (1 M)</td>
			<td>Thermo Fisher Scientific</td>
			<td>15630-056</td>
			<td></td>
		</tr>
		<tr>
			<td>Horse Serum</td>
			<td>Sigma-Aldrich, MERCK</td>
			<td>H0146</td>
			<td></td>
		</tr>
		<tr>
			<td>LD column</td>
			<td>Miltenyi Biotec</td>
			<td>130-042-901</td>
			<td></td>
		</tr>
		<tr>
			<td>Medium 199</td>
			<td>Thermo Fisher Scientific</td>
			<td>31150-022</td>
			<td></td>
		</tr>
		<tr>
			<td>NE-1000 syringe pump</td>
			<td>New Era Pump Systems</td>
			<td>NE-1000</td>
			<td>Syringe pump</td>
		</tr>
		<tr>
			<td>Neonatal Cardiomyocyte Isolation Cocktail, rat</td>
			<td>Miltenyi Biotec</td>
			<td>130-105-420</td>
			<td></td>
		</tr>
		<tr>
			<td>Neonatal Heart Dissociation Kit, mouse and rat</td>
			<td>Miltenyi Biotec</td>
			<td>130-098-373</td>
			<td></td>
		</tr>
		<tr>
			<td>Oligo-dT30VN oligonucleotides</td>
			<td>IDT Technology</td>
			<td>5&#8242;&#8211;AAGCAGTGGTATCAACGCAGAGTACT30VN-3&#8242;</td>
			<td></td>
		</tr>
		<tr>
			<td>RNAse inhibitor (40 U &#181;L-1)</td>
			<td>Clontech</td>
			<td>2313A</td>
			<td></td>
		</tr>
		<tr>
			<td>sarcomeric &#945;-actinin</td>
			<td>Sigma-Aldrich, MERCK</td>
			<td>EA-53</td>
			<td></td>
		</tr>
		<tr>
			<td>SP8 confocal microscope</td>
			<td>Leica Microsystems</td>
			<td>SP8</td>
			<td>Confocal microscope</td>
		</tr>
		<tr>
			<td>Superscript II first-strand buffer (5x)</td>
			<td>Thermo Fisher Scientific</td>
			<td>18064071</td>
			<td></td>
		</tr>
		<tr>
			<td>Superscript II reverse transcriptase (200 U &#181;L-1)</td>
			<td>Thermo Fisher Scientific</td>
			<td>18064071</td>
			<td></td>
		</tr>
		<tr>
			<td>Triton X-100</td>
			<td>Sigma-Aldrich, MERCK</td>
			<td>T9284</td>
			<td></td>
		</tr>
		<tr>
			<td>TryplE Express enzyme, no phenol red</td>
			<td>Thermo Fisher Scientific</td>
			<td>12604013</td>
			<td></td>
		</tr>
		<tr>
			<td>TSO (100 &#181;M)</td>
			<td>QIAGEN</td>
			<td>5&#8242;-AAGCAGTGGTATCAACGCAGAGTACATrGrG+G-3&#8242;</td>
			<td></td>
		</tr>
		<tr>
			<td>Vibrant Dye Cycle green</td>
			<td>Thermo Fisher Scientific</td>
			<td>V35004</td>
			<td></td>
		</tr>
	</tbody>
</table>

an approach to study shape-dependent transcriptomics at a single cell level

Different types of cardiac hypertrophy have been associated with an increased volume of cardiac myocytes (CMs), along with changes in CM morphology. While the effects of cell volume on gene expression are well known, the effects of cell shape are not well understood. This paper describes a method that has been designed to systematically analyze the effects of CM morphology on gene expression. It details the development of a novel single-cell trapping strategy that is then followed by single-cell mRNA sequencing. A micropatterned chip has also been designed, which contains 3000 rectangular-shaped fibronectin micropatterns. This makes it possible to grow CMs in distinct length:width aspect ratios (AR), corresponding to different types of heart failure (HF). The paper also describes a protocol that has been designed to pick up single cells from their pattern, using a semi-automated micro-pipetting cell picker, and individually inject them into a separate lysis buffer. This has made it possible to profile the transcriptomes of single CMs with defined geometrical morphotypes and characterize them according to a range of normal or pathological conditions: hypertrophic cardiomyopathy (HCM) or afterload/concentric versus dilated cardiomyopathy (DCM) or preload/eccentric. In summary, this paper presents methods for growing CMs with different shapes, which represent different pathologies, and sorting these adherent CMs based on their morphology at a single-cell level. The proposed platform provides a novel approach to high throughput and drug screening for different types of HF.

Tissue was dissected from the left ventricle of the 2-day-old neonatal rat hearts and divided into single cells. Then the enriched CMs were seeded on a chip containing fibronectin patterns with distinct ARs. After 72 hours of culturing, the medium was replaced by 1:1000 Vibrant Dye Cycle green in DPBS-/- for 2 min to visualize the nuclei of the live cells. Next, the cells were treated with DPBS-/-/trypsin (1:1) to loosen the cells from the fibronectin, so that a fluidic vacuum could be used to facilitate cell picking. Meanwhile, the entire chip was scanned at a magnification of 10x, using an inverted microscope connected to the cell picker. This was carried out before the cells became rounded due to trypsin treatment. The qualified cells were selected, based on the scanned image, and their coordinates were saved in the cell picker software. The micropatterns were only selected if they contained a mononucleated single cell and only when the cell fully covered its fibronectin micropattern. The cell sorter picked the selected cells one by one and each single cell that was successfully picked was immediately injected into an individual PCR tube and placed on the microscope stage. Each PCR tube contained 3.55 &#181;L of lysis buffer (Table 2). The sorting process, which started with removing the media, was completed within 40 minutes. The complementary deoxyribonucleic acid (cDNA) synthesis, PCR pre-amplification and purification were performed on the lysed single cells, based on the Smart-Seq2 protocol24 (Table 3). The quality of the purified cDNA was checked by an automated electrophoresis analyzer. The electropherogram of the pre-amplified cDNA of one picked single cell is presented in Figure 4. The RNA-Seq libraries were prepared according to the Smart-Seq2 protocol24.
To observe the sarcomere structure of the patterned CMs, the patterned CMs were stained with sarcomeric &#945;-actinin antibody. The cells were incubated with Donkey Anti-Mouse IgG Alexa Fluor 488 1:800 for 1 hour at room temperature for the secondary staining. Nuclei were stained with 1 &#181;g/mL DAPI. Immunofluorescent images were acquired with an inverted confocal microscope, using a 63x oil-immersion (NA 1.4) objective (Figure 5).
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/61577/61577fig01.jpg" /> 
Figure 1: Layout of the chip with fibronectin micropatterns. 
(A) Image of the custom-designed chip. The chip is a 19.5 mm x 19.5 mm coverslip with fibronectin micropatterns, printed by photolithography on a borosilicate glass. (B) Chip layout. The chip is divided to three zones and each zone consists of fibronectin micropatterns with specific AR. Fluorescent images of different shapes of fibronectin micropatterns are shown in magnified view for each zone. This figure has been modified from &#8220;supplementary material 1&#8221; by Haftbaradaran Esfahani et al.2, used under http://creativecommons.org/licenses/by/4.0/ . <a href="https://www.jove.com/files/ftp_upload/61577/61577fig01large.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/61577/61577fig02.jpg" /> 
Figure 2: Dissociator equipped with heaters apparatus. 
(A) The entire dissociator instrument used for the fully automated dissociation of 2-day-old neonatal rat left ventricles. (B) Heating unit. (C) Rotor-cap tube. (D) Ready-to-use programs for a fully automated workflow of tissue dissociation. <a href="https://www.jove.com/files/ftp_upload/61577/61577fig02large.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/61577/61577fig03.jpg" /> 
Figure 3: Cell picker apparatus. 
(A) Enlarged view of the motorized stage of the cell picker. A Petri-dish holder and 80 holes for 10 PCR strips and a hole for calibration crosshair is embedded on the stage. (B) Enlarged view of a glass microcapillary. (C) The syringe pump. (D) The control unit, which controls the opening and closing time window of valves 1 and 2, mounted inside the control unit. <a href="https://www.jove.com/files/ftp_upload/61577/61577fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/61577/61577fig04.jpg" /> 
Figure 4: The electropherogram of the pre-amplified cDNA of one picked single cell. 
19 PCR cycles of pre-amplification was used to obtain 15 &#181;L of 1 ng/&#181;L purified cDNA yield. A clear band in gel-like densitometry plot is observed which corresponds to the peak at 1852 bp in the electropherogram. The average size of fragments is 1588 bp. Moreover, the small amount of fragments that are shorter than 300 bp indicates a good cDNA library. <a href="https://www.jove.com/files/ftp_upload/61577/61577fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/61577/61577fig05.jpg" /> 
Figure 5: Immunofluorescent staining of &#945;-actinin sarcomeric structure (green) and nucleus (blue) of patterned CMs with different ARs. 
The chromatin was stained by DAPI. <a href="https://www.jove.com/files/ftp_upload/61577/61577fig05large.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>Morphotype</td>
			<td>AR</td>
			<td>Length (&#181;m)</td>
			<td>Width (&#181;m)</td>
			<td>Fibronectin area (&#181;m2)</td>
		</tr>
		<tr>
			<td>AR1</td>
			<td>1:1</td>
			<td>47</td>
			<td>47</td>
			<td>2209</td>
		</tr>
		<tr>
			<td>AR7</td>
			<td>7:1</td>
			<td>126</td>
			<td>18</td>
			<td>2268</td>
		</tr>
		<tr>
			<td>AR11</td>
			<td>11:1</td>
			<td>155</td>
			<td>14</td>
			<td>2170</td>
		</tr>
	</tbody>
</table>
Table 1: Geometry of patterned CMs.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Component</td>
			<td>Volume (&#181;L)</td>
		</tr>
		<tr>
			<td>Nucleas-free water</td>
			<td>0.65</td>
		</tr>
		<tr>
			<td>(0.4% vol/vol) Triton X-100</td>
			<td>1.8</td>
		</tr>
		<tr>
			<td>dNTP mix (25 mM)</td>
			<td>0.8</td>
		</tr>
		<tr>
			<td>RNase inhibitor (40 U &#181;L-1)</td>
			<td>0.1</td>
		</tr>
		<tr>
			<td>Oligo-dT30VN oligonucleotides (100 &#181;M)</td>
			<td>0.1</td>
		</tr>
		<tr>
			<td>ERCC RNA Spike-In Mix (2.5 x 105 dilution)</td>
			<td>0.1</td>
		</tr>
		<tr>
			<td>Injected single cell</td>
			<td>1</td>
		</tr>
		<tr>
			<td>Total volume</td>
			<td>4.55</td>
		</tr>
	</tbody>
</table>
Table 2: Single cell custom lysis buffer.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Component</td>
			<td>Volume (&#181;L)</td>
		</tr>
		<tr>
			<td>Superscript II first-strand buffer (5x)</td>
			<td>2</td>
		</tr>
		<tr>
			<td>DTT (100 mM)</td>
			<td>0.5</td>
		</tr>
		<tr>
			<td>Betaine (5 M)</td>
			<td>2</td>
		</tr>
		<tr>
			<td>Mgcl2 (1 M)</td>
			<td>0.1</td>
		</tr>
		<tr>
			<td>RNase inhibitor (40 U &#181;L-1)</td>
			<td>0.25</td>
		</tr>
		<tr>
			<td>Superscript II reverse transcriptase (200 U &#181;L-1)</td>
			<td>0.5</td>
		</tr>
		<tr>
			<td>TSO (100 &#181;M)</td>
			<td>0.1</td>
		</tr>
		<tr>
			<td>Total volume</td>
			<td>5.45</td>
		</tr>
	</tbody>
</table>
Table 3: Reverse transcription (RT) mix for one RT reaction to synthesize first-strand cDNA from the lysate of a single CM.

Watch this Scientific Journal Video about An Approach to Study Shape-Dependent Transcriptomics at a Single Cell Level at JoVE.com

An Approach to Study Shape-Dependent Transcriptomics at a Single Cell Level

This paper presents methods for growing cardiac myocytes with different shapes, which represent different pathologies, and sorting these adherent cardiac myocytes based on their morphology at a single cell level. The proposed platform provides a novel approach to high throughput and drug screening for different types of heart failure.

Different types of cardiac hypertrophy have been associated with an increased volume of cardiac myocytes (CMs), along with changes in CM morphology. While ...

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5.5K Views.  Karolinska Institutet. This paper presents methods for growing cardiac myocytes with different shapes, which represent different pathologies, and sorting these adherent cardiac myocytes based on their morphology at a single cell level. The proposed platform provides a novel approach to high throughput and drug screening for different types of heart failure.

Video: An Approach to Study Shape-Dependent Transcriptomics at a Single Cell Level

The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics

Terroir refers to the combination of environmental factors that affect the characteristics of crops such as grapevine (Vitis vinifera) according to particular habitats and management practices. This article shows how certain terroir signatures can be detected in the berry metabolome and transcriptome of the grapevine cultivar Corvina using multivariate statistical analysis. The method first requires an appropriate sampling plan. In this case study, a specific clone of the Corvina cultivar was selected to minimize genetic differences, and samples were collected from seven vineyards representing three different macro-zones during three different growing seasons. An untargeted LC-MS metabolomics approach is recommended due to its high sensitivity, accompanied by efficient data processing using MZmine software and a metabolite identification strategy based on fragmentation tree analysis. Comprehensive transcriptome analysis can be achieved using microarrays containing probes covering ~99% of all predicted grapevine genes, allowing the simultaneous analysis of all differentially expressed genes in the context of different terroirs. Finally, multivariate data analysis based on projection methods can be used to overcome the strong vintage-specific effect, allowing the metabolomics and transcriptomics data to be integrated and analyzed in detail to identify informative correlations.

This article describes the application of untargeted metabolomics, transcriptomics and multivariate statistical analysis to grape berry transcripts and metabolites in order to gain insight into the terroir concept, i.e., the impact of the environment on berry quality traits.

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Tools to Study the Role of Architectural Protein HMGB1 in the Processing of Helix Distorting, Site-specific DNA Interstrand Crosslinks

High mobility group box 1 (HMGB1) protein is a non-histone architectural protein that is involved in regulating many important functions in the genome, such as transcription, DNA replication, and DNA repair. HMGB1 binds to structurally distorted DNA with higher affinity than to canonical B-DNA. For example, we found that HMGB1 binds to DNA interstrand crosslinks (ICLs), which covalently link the two strands of the DNA, cause distortion of the helix, and if left unrepaired can cause cell death. Due to their cytotoxic potential, several ICL-inducing agents are currently used as chemotherapeutic agents in the clinic. While ICL-forming agents show preferences for certain base sequences (e.g., 5&#39;-TA-3&#39; is the preferred crosslinking site for psoralen), they largely induce DNA damage in an indiscriminate fashion. However, by covalently coupling the ICL-inducing agent to a triplex-forming oligonucleotide (TFO), which binds to DNA in a sequence-specific manner, targeted DNA damage can be achieved. Here, we use a TFO covalently conjugated on the 5&#39; end to a 4&#39;-hydroxymethyl-4,5&#39;,8-trimethylpsoralen (HMT) psoralen to generate a site-specific ICL on a mutation-reporter plasmid to use as a tool to study the architectural modification, processing, and repair of complex DNA lesions by HMGB1 in human cells. We describe experimental techniques to prepare TFO-directed ICLs on reporter plasmids, and to interrogate the association of HMGB1 with the TFO-directed ICLs in a cellular context using chromatin immunoprecipitation assays. In addition, we describe DNA supercoiling assays to assess specific architectural modification of the damaged DNA by measuring the amount of superhelical turns introduced on the psoralen-crosslinked plasmid by HMGB1. These techniques can be used to study the roles of other proteins involved in the processing and repair of TFO-directed ICLs or other targeted DNA damage in any cell line of interest.

Targeted DNA damage can be achieved by tethering a DNA damaging agent to a triplex-forming oligonucleotide (TFO). Using modified TFOs, DNA damage-specific protein association, and DNA topology modification can be studied in human cells by the utilization of modified chromatin immunoprecipitation assays and DNA supercoiling assays described herein.

High mobility group box 1 (HMGB1) protein is a non-histone architectural protein that is involved in regulating many important functions in the genome, ...

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 ...

Laser Microirradiation to Study In Vivo Cellular Responses to Simple and Complex DNA Damage

DNA damage induces specific signaling and repair responses in the cell, which is critical for protection of genome integrity. Laser microirradiation became a valuable experimental tool to investigate the DNA damage response (DDR) in vivo. It allows real-time high-resolution single-cell analysis of macromolecular dynamics in response to laser-induced damage confined to a submicrometer region in the cell nucleus. However, various laser conditions have been used without appreciation of differences in the types of damage induced. As a result, the nature of the damage is often not well characterized or controlled, causing apparent inconsistencies in the recruitment or modification profiles. We demonstrated that different irradiation conditions (i.e., different wavelengths as well as different input powers (irradiances) of a femtosecond (fs) near-infrared (NIR) laser) induced distinct DDR and repair protein assemblies. This reflects the type of DNA damage produced. This protocol describes how titration of laser input power allows induction of different amounts and complexities of DNA damage, which can easily be monitored by detection of base and crosslinking damages, differential poly (ADP-ribose) (PAR) signaling, and pathway-specific repair factor assemblies at damage sites. Once the damage conditions are determined, it is possible to investigate the effects of different damage complexity and differential damage signaling as well as depletion of upstream factor(s) on any factor of interest.

Laser Microirradiation to Study In Vivo Cellular Responses to Simple and Complex DNA Damage

The goal of this protocol is to describe how to use laser microirradiation to induce different types of DNA damage, including relatively simple strand breaks and complex damage, to study DNA damage signaling and repair factor assembly at damage sites in vivo.

DNA damage induces specific signaling and repair responses in the cell, which is critical for protection of genome integrity. Laser microirradiation ...

Profiling DNA Replication Timing Using Zebrafish as an In Vivo Model System

DNA replication timing is an important cellular characteristic, exhibiting significant relationships with chromatin structure, transcription, and DNA mutation rates. Changes in replication timing occur during development and in cancer, but the role replication timing plays in development and disease is not known. Zebrafish were recently established as an in vivo model system to study replication timing. Here is detailed the protocols for using the zebrafish to determine DNA replication timing. After sorting cells from embryos and adult zebrafish, high-resolution genome-wide DNA replication timing patterns can be constructed by determining changes in DNA copy number through analysis of next generation sequencing data. The zebrafish model system allows for evaluation of the replication timing changes that occur in vivo throughout development, and can also be used to assess changes in individual cell types, disease models, or mutant lines. These methods will enable studies investigating the mechanisms and determinants of replication timing establishment and maintenance during development, the role replication timing plays in mutations and tumorigenesis, and the effects of perturbing replication timing on development and disease.

Profiling DNA Replication Timing Using Zebrafish as an In Vivo Model System

Zebrafish were recently used as an in vivo model system to study DNA replication timing during development. Here is detailed the protocols for using zebrafish embryos to profile replication timing. This protocol can be easily adapted to study replication timing in mutants, individual cell types, disease models, and other species.

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An Optogenetic Method to Control and Analyze Gene Expression Patterns in Cell-to-cell Interactions

Cells should respond properly to temporally changing environments, which are influenced by various factors from surrounding cells. The Notch signaling pathway is one of such essential molecular machinery for cell-to-cell communications, which plays key roles in normal development of embryos. This pathway involves a cell-to-cell transfer of oscillatory information with ultradian rhythms, but despite the progress in molecular biology techniques, it has been challenging to elucidate the impact of multicellular interactions on oscillatory gene dynamics. Here, we present a protocol that permits optogenetic control and live monitoring of gene expression patterns in a precise temporal manner. This method successfully revealed that intracellular and intercellular periodic inputs of Notch signaling entrain intrinsic oscillations by frequency tuning and phase shifting at the single-cell resolution. This approach is applicable to the analysis of the dynamic features of various signaling pathways, providing a unique platform to test a functional significance of dynamic gene expression programs in multicellular systems.

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A Novel Saturation Mutagenesis Approach: Single Step Characterization of Regulatory Protein Binding Sites in RNA Using Phosphorothioates

Gene regulation plays an important role in development. Numerous DNA- and RNA-binding proteins bind their target sequences with high specificity to control gene expression. These regulatory proteins control gene expression either at the level of DNA (transcription) or at the level of RNA (pre-mRNA splicing, polyadenylation, mRNA transport, decay, and translation). Identification of regulatory sequences helps understand not only how a gene is switched on or off, but also which downstream genes are regulated by a particular regulatory protein. Here, we describe a one-step approach that allows saturation mutagenesis of a protein binding site in RNA. It involves doping DNA template with non-wild-type nucleotides within the binding site, synthesis of separate RNAs with each phosphorothioate nucleotide, and isolation of the bound fraction following incubation with protein. Interference from non-wild-type nucleotides results in their preferential exclusion from the protein-bound fraction. This is monitored by gel electrophoresis following selective chemical cleavage with iodine of phosphodiester bonds containing phosphorothioates (phosphorothioate mutagenesis or PTM). This single-step saturation mutagenesis approach is applicable to the characterization of any protein binding site in RNA.

Proteins that bind specific RNA sequences play critical roles in gene expression. Detailed characterization of these binding sites is crucial for our understanding of gene regulation. Here, a single-step approach for saturation mutagenesis of protein-binding sites in RNA is described. This approach is relevant for all protein-binding sites in RNA.

Gene regulation plays an important role in development. Numerous DNA- and RNA-binding proteins bind their target sequences with high specificity to ...

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

Immunophenotypic characterization and molecular analysis have long been used to delineate heterogeneity and define distinct cell populations. FACS is inherently a single-cell assay, however prior to molecular analysis, the target cells are often prospectively isolated in bulk, thereby losing single-cell resolution. Single-cell gene expression analysis provides a means to understand molecular differences between individual cells in heterogeneous cell populations. In bulk cell analysis an overrepresentation of a distinct cell type results in biases and occlusions of signals from rare cells with biological importance. By utilizing FACS index sorting coupled to single-cell gene expression analysis, populations can be investigated without the loss of single-cell resolution while cells with intermediate cell surface marker expression are also captured, enabling evaluation of the relevance of continuous surface marker expression. Here, we describe an approach that combines single-cell reverse transcription quantitative PCR (RT-qPCR) and FACS index sorting to simultaneously characterize the molecular and immunophenotypic heterogeneity within cell populations.
In contrast to single-cell RNA sequencing methods, the use of qPCR with specific target amplification allows for robust measurements of low-abundance transcripts with fewer dropouts, while it is not confounded by issues related to cell-to-cell variations in read depth. Moreover, by directly index-sorting single-cells into lysis buffer this method, allows for cDNA synthesis and specific target pre-amplification to be performed in one step as well as for correlation of subsequently derived molecular signatures with cell surface marker expression. The described approach has been developed to investigate hematopoietic single-cells, but have also been used successfully on other cell types.
In conclusion, the approach described herein allows for sensitive measurement of mRNA expression for a panel of pre-selected genes with the possibility to develop protocols for subsequent prospective isolation of molecularly distinct subpopulations.

Bulk gene expression measurements cloud individual cell differences in heterogeneous cell populations. Here, we describe a protocol for how single-cell gene expression analysis and index sorting by Florescence Activated Cell Sorting (FACS) can be combined to delineate heterogeneity and immunophenotypically characterize molecularly distinct cell populations.

Immunophenotypic characterization and molecular analysis have long been used to delineate heterogeneity and define distinct cell populations. FACS is ...

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture (4C-seq)

The identification of regulatory elements for a given target gene poses a significant technical challenge owing to the variability in the positioning and effect sizes of regulatory elements to a target gene. Some progress has been made with the bioinformatic prediction of the existence and function of proximal epigenetic modifications associated with activated gene expression using conserved transcription factor binding sites. Chromatin conformation capture studies have revolutionized our ability to discover physical chromatin contacts between sequences and even within an entire genome. Circular chromatin conformation capture coupled with next-generation sequencing (4C-seq), in particular, is designed to discover all possible physical chromatin interactions for a given sequence of interest (viewpoint), such as a target gene or a regulatory enhancer. Current 4C-seq strategies directly sequence from within the viewpoint but require numerous and diverse viewpoints to be simultaneously sequenced to avoid the technical challenges of uniform base calling (imaging) with next generation sequencing platforms. This volume of experiments may not be practical for many laboratories. Here, we report a modified approach to the 4C-seq protocol that incorporates both an additional restriction enzyme digest and qPCR-based amplification steps that are designed to facilitate a greater capture of diverse sequence reads and mitigate the potential for PCR bias, respectively. Our modified 4C method is amenable to the standard molecular biology lab for assessing chromatin architecture.

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture 4C-seq

The identification of physical interactions between genes and regulatory elements is challenging but has been facilitated by chromosome conformation capture methods. This modification to the 4C-seq protocol mitigates PCR bias by minimizing over-amplification of PCR templates and maximizes the mappability of reads by incorporating an addition restriction enzyme digest step.

The identification of regulatory elements for a given target gene poses a significant technical challenge owing to the variability in the positioning and ...

Generation of Cancer Cell Clones to Visualize Telomeric Repeat-containing RNA TERRA Expressed from a Single Telomere in Living Cells

Telomeres are transcribed, giving rise to telomeric repeat-containing long noncoding RNAs (TERRA), which have been proposed to play important roles in telomere biology, including heterochromatin formation and telomere length homeostasis. Recent findings revealed that TERRA molecules also interact with internal chromosomal regions to regulate gene expression in mouse embryonic stem (ES) cells. In line with this evidence, RNA fluorescence in situ hybridization (RNA-FISH) analyses have shown that only a subset of TERRA transcripts localize at chromosome ends. A better understanding of the dynamics of TERRA molecules will help define their function and mechanisms of action. Here, we describe a method to label and visualize single-telomere TERRA transcripts in cancer cells using the MS2-GFP system. To this aim, we present a protocol to generate stable clones, using the AGS human stomach cancer cell line, containing MS2 sequences integrated at a single subtelomere. Transcription of TERRA from the MS2-tagged telomere results in the expression of MS2-tagged TERRA molecules that are visualized by live-cell fluorescence microscopy upon co-expression of a MS2 RNA-binding protein fused to GFP (MS2-GFP). This approach enables researchers to study the dynamics of single-telomere TERRA molecules in cancer cells, and it can be applied to other cell lines.

Here, we present a protocol to generate cancer cell clones containing a MS2 sequence tag at a single subtelomere. This approach, relying on the MS2-GFP system, enables visualization of the endogenous transcripts of telomeric repeat-containing RNA (TERRA) expressed from a single telomere in living cells.

Telomeres are transcribed, giving rise to telomeric repeat-containing long noncoding RNAs (TERRA), which have been proposed to play important roles in ...