Name: multiplexed single cell mrna sequencing analysis of mouse embryonic cells
Uploaded: 2020-01-07T14:00:00.000+00:00
Duration: 8 min 30 s
Description: Watch this Scientific Journal Video about Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells at JoVE.com

We thank David M. Patterson and Christopher S. McGinnis from Dr. Zev J. Gartner lab for their kind supply of the lipid based barcoding reagents and suggestions on the experimental steps and data analysis. This work was founded by the National Institutes of Health (HL13347202).

<ol>
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The authors have no conflicts of interest to disclose.

In this study, we have demonstrated a protocol to analyze single cell transcriptional profiles. We have also provided two optional methods to multiplex samples in the scRNA-Seq workflow. Both methods have proved to be feasible at various labs and provided solutions to run a cost-effective and batch effect-free single cell experiment18,26.
There are a few steps that should be followed carefully when going through the protocol. An ideal single cell suspension should have &#62;90% of viable cells and the cell density should also be within a specific range27. It is critical to obtain a good quality of cells to minimize the presence of cellular aggregates, debris, and fibers. Cellular aggregates have negative impact on sample multiplexing and have a potential risk to clog the droplet generating machine17. Generally speaking, a 30-40 &#181;m cell strainer is ideal for removing large clumps and debris while preserving the cell samples because most cells will shrink below 30 &#181;m after dissociation. Single cell nuclei are recommended to use instead if the cell diameter is larger than 30 &#181;m. At early embryonic stages, the cell size for all types of mouse cells should be smaller than 30 &#181;m. However, at later stages, the cardiomyocytes in the heart, neurons in the brain, muscle cells in limbs, and some fat cells may have a cell size larger than 30 &#181;m. Cell size should be measured for these types of cells before starting the single cell experiments.
The multiplexing strategies provide a way to simultaneously analyze a large number of samples in a cost-effective way. In addition, by profiling multiple samples together, we can significantly avoid the batch effects and identify cell doublets. These advantages will be very attractive to the single cell field. However, there are some factors that may limit their usage. As more cells are multiplexed in a single experiment, the cell doublet ratio will also increase. Although those doublets can be identified and removed by analyzing the multiplexing barcode data, it will lead to a large waste of sequencing reads. In addition, as more cells are pooled together, the cells are easier to break and cause an increase of the ambient mRNA, which will be captured into droplets with cells and interfere with the detection sensitivity. We are expecting that further optimization of the experimental workflow or bioinformatics analysis pipeline will resolve these two issues in the near future.

The transcriptional profile of each single cell varies among cell populations during embryonic development. Although single molecular in situ hybridization can be used to visualize the expression of a small number of genes1, single cell mRNA sequencing (scRNA-Seq) provides an unbiased approach to illustrate genome-wide expression patterns of genes in single cells. After it was first published in 20092, scRNA-Seq has been applied to study multiple tissues at multiple developmental stages in the recent years3,4,5. Also, as the human cell atlas has launched its developmental-focused projects recently, more single cell data from human embryonic tissues are expected to be generated in the near future.
The heart as the first organ to develop plays a critical role in embryonic development. The heart consists of multiple cell types and the development of each cell type is tightly regulated temporally and spatially. Over the past few years, the origin and cell lineage of cardiac cells at early developmental stages have been characterized6, which provide a tremendous useful navigation tool for understanding congenital heart disease pathogenesis, as well as for developing more technologically advanced methods to stimulate cardiomyocyte regeneration7.
The scRNA-Seq has undergone a rapid expansion in recent years8,9,10. With the newly developed methods, design and analysis of single cell experiments has become more achievable11,12,13,14. The method presented here is a commercial procedure based on the droplet solutions (see Table of Materials)15,16. This method features capturing cells and sets of uniquely barcoded beads in an oil-water emulsion droplet under control of a microfluidic controller system. The rate of cell loading into the droplets is extremely low so that the majority of droplet emulsions contain only one cell17. The procedure&#39;s ingenious design comes from single cell separation into droplet emulsions occurring simultaneously with barcoding, which enables the parallel analysis of individual cells using RNA-Seq on a heterogeneous population.
The incorporation of multiplexing strategies is one of the important additions to the traditional single cell workflow13,14. This addition is very useful in discarding cell doublets, reducing experimental costs, and eliminating batch effects18,19. A lipid based barcoding strategy and an antibody based barcoding strategy (see Table of Materials) are the two mostly used multiplexing methods. Specific barcodes are used to label each sample in both methods, and the labeled samples are then mixed for single cell capturing, library preparation, and sequencing. Afterwards, the pooled sequencing data can be separated by analyzing the barcode sequences (Figure 1)19. However, significant differences exist between the two methods. The lipid based barcoding strategy is based on lipid-modified oligonucleotides, which has not been found to have any cell type preferences. While the antibody based barcoding strategy can only detect the cells expressing the antigen proteins19,20. In addition, it takes about 10 min to stain the lipids but 40 min to stain the antibodies (Figure 1). Furthermore, the lipid-modified oligonucleotides are cheaper than antibody-conjugated oligonucleotides but not commercially available at the time of writing this article. Finally, the lipid-based strategy can multiplex 96 samples in one experiment, but the antibody-based strategy currently can only multiplex 12 samples.
The recommended cell number to multiplex in a single experiment should be lower than 2.5 x 104, otherwise, it will lead to a high percentage of cell doublets and potential ambient mRNA contamination. Through the multiplexing strategies, the cost of single cell capturing, cDNA generation, and library preparation for multiple samples will be reduced to the cost of one sample but the sequencing cost will remain the same.

<table><tbody><tr><td>10% Tween-20</td><td>Bio-Rad</td><td>1610781</td><td></td></tr><tr><td>10x Chip Holder</td><td>10x Genomics</td><td>120252 330019</td><td></td></tr><tr><td>10x Chromium Controller</td><td>10x Genomics</td><td>120223</td><td></td></tr><tr><td>10x Magnetic Separator</td><td>10x Genomics</td><td>120250 230003</td><td></td></tr><tr><td>10x Vortex Adapter</td><td>10x Genomics</td><td>330002, 120251</td><td></td></tr><tr><td>10x Vortex Clip</td><td>10x Genomics</td><td>120253 230002</td><td></td></tr><tr><td>4200 TapeStation System</td><td>Agilent</td><td>G2991AA</td><td></td></tr><tr><td>Agilent High Sensitivity DNA Kit</td><td>Agilent</td><td>5067-4626</td><td>University of Pittsburgh Health Sciences Sequencing Core</td></tr><tr><td>Barcode Oligo</td><td>Integrated DNA Technologies</td><td>Single-stranded DNA</td><td>25 nmol</td></tr><tr><td>Buffer EB</td><td>Qiagen</td><td>19086</td><td></td></tr><tr><td>CD1 mice</td><td>Chales River</td><td>Strain Code 022</td><td>ordered pregnant mice</td></tr><tr><td>Centrifuge 5424R</td><td>Appendorf</td><td>2231000214</td><td></td></tr><tr><td>Chromium Chip B Single Cell Kit, 48 rxns</td><td>10x Genomics</td><td>1000073</td><td>Store at ambient temperature</td></tr><tr><td>Chromium i7 Multiplex Kit, 96 rxns</td><td>10x Genomics</td><td>120262</td><td>Store at -20 &amp;deg;C</td></tr><tr><td>Chromium Single Cell 3&#039; GEM Kit v3,4 rxns</td><td>10x Genomics</td><td>1000094</td><td>Store at -20 &amp;deg;C</td></tr><tr><td>Chromium Single Cell 3&#039; Library Kit v3</td><td>10x Genomics</td><td>1000095</td><td>Store at -20 &amp;deg;C</td></tr><tr><td>Chromium Single Cell 3&#039; v3 Gel Beads</td><td>10x Genomics</td><td>2000059</td><td>Store at -80 &amp;deg;C</td></tr><tr><td>Collagenase A</td><td>Sigma/Millipore</td><td>10103578001</td><td>Store powder at 4 &amp;deg;C, store at -20 &amp;deg;C after it dissolves</td></tr><tr><td>Collagenase B</td><td>Sigma/Millipore</td><td>11088807001</td><td>Store powder at 4 &amp;deg;C, store at -20 &amp;deg;C after it dissolves</td></tr><tr><td>D1000 ScreenTape</td><td>Agilent</td><td>5067-5582</td><td>University of Pittsburgh Health Sciences Sequencing Core</td></tr><tr><td>DNA LoBind Tube Microcentrifuge Tube, 1.5 mL</td><td>Eppendorf</td><td>022431021</td><td></td></tr><tr><td>DNA LoBind Tube Microcentrifuge Tube, 2.0 mL</td><td>Eppendorf</td><td>022431048</td><td></td></tr><tr><td>Dynabeads MyOne SILANE</td><td>10x Genomics</td><td>2000048</td><td>Store at 4 &amp;deg;C, used in Beads Cleanup Mix (Table 1)</td></tr><tr><td>DynaMag-2 Magnet</td><td>Theromo Scientific</td><td>12321D</td><td></td></tr><tr><td>Ethanol, Pure (200 Proof, anhydrous)</td><td>Sigma</td><td>E7023-500mL</td><td></td></tr><tr><td>Falcon 15mL High Clarity PP Centrifuge Tube</td><td>Corning Cellgro</td><td>14-959-70C</td><td></td></tr><tr><td>Falcon 50mL High Clarity PP Centrifuge Tube</td><td>Corning Cellgro</td><td>14-959-49A</td><td></td></tr><tr><td>Fetal Bovine Serum, qualified, United States</td><td>Fisher Scientific</td><td>26140079</td><td>Store at -20 &amp;deg;C</td></tr><tr><td>Finnpipette F1 Multichannel Pipettes, 10-100&amp;mu;l</td><td>Theromo Scientific</td><td>4661020N</td><td></td></tr><tr><td>Finnpipette F1 Multichannel Pipettes, 1-10&amp;mu;l</td><td>Theromo Scientific</td><td>4661000N</td><td></td></tr><tr><td>Flowmi Cell Strainer</td><td>Sigma</td><td>BAH136800040</td><td>Porosity 40 &amp;mu;m, for 1000 uL Pipette Tips, pack of 50 each</td></tr><tr><td>Glycerin (Glycerol), 50% (v/v)</td><td>Ricca Chemical Company</td><td>3290-32</td><td></td></tr><tr><td>HBSS, no calcium, no magnesium</td><td>Thermo Fisher Scientific</td><td>14170112</td><td></td></tr><tr><td>Human TruStain FcX (Fc Receptor Blocking Solution)</td><td>BioLegend</td><td>422301</td><td>Add 5 &amp;micro;l of Human TruStain FcX per million cells in 100 &amp;micro;l staining volume</td></tr><tr><td>Isopropanol (IPA)</td><td>Fisher Scientific</td><td>A464-4</td><td></td></tr><tr><td>Kapa HiFi HotStart ReadyMix (2X)</td><td>Fisher Scientific</td><td>NC0295239</td><td>Store at -20 &amp;deg;C, used in Lipid-tagged barcode library mix (Table 1)</td></tr><tr><td>Lipid Barcode Primer (Multi-seq Primer)</td><td>Integrated DNA Technologies</td><td>Single-stranded DNA</td><td>100 nmol</td></tr><tr><td>Low TE Buffer (10 mM Tris-HCl pH 8.0, 0.1 mM EDTA)</td><td>Thermo Fisher Scientific</td><td>12090-015</td><td></td></tr><tr><td>MasterCycler Pro</td><td>Eppendorf</td><td>950W</td><td></td></tr><tr><td>Nuclease-Free Water (Ambion)</td><td>Thermo Fisher Scientific</td><td>AM9937</td><td></td></tr><tr><td>PCR Tubes 0.2 ml 8-tube strips</td><td>Eppendorf</td><td>951010022</td><td></td></tr><tr><td>Phosphate-Buffered Saline (PBS) 1X without calcium &amp;amp; magnesium</td><td>Corning Cellgro</td><td>21-040-CV</td><td></td></tr><tr><td>Phosphate-Buffered Saline (PBS) with 10% Bovine Albumin (alternative to Thermo Fisher product)</td><td>Sigma-Aldrich</td><td>SRE0036</td><td></td></tr><tr><td>Pipet 4-pack (0.1&amp;ndash;2.5&amp;mu;L, 0.5-10&amp;mu;L, 10&amp;ndash;100&amp;mu;L, 100&amp;ndash;1,000&amp;mu;L variable-volume pipettes</td><td>Fisher Scientific</td><td>05-403-151</td><td></td></tr><tr><td>Selection reagent (SPRIselect Reagent Kit)</td><td>Beckman Coulter</td><td>B23318 (60ml)</td><td></td></tr><tr><td>Template Switch Oligo</td><td>10x Genomics</td><td>3000228</td><td>Store at -20 &amp;deg;C, used in Master Mix (Table 1)</td></tr><tr><td>The antibody based barcoding strategy is also known as Cell Hashing</td><td></td><td></td><td></td></tr><tr><td>The cell browser is Loup Cell Browser</td><td>10x Genomics</td><td></td><td>&lt;a href=&quot;https://support.10xgenomics.com/single-cell-gene-expression/software/visualization/latest/what-is-loupe-cell-browser&quot; target=&quot;_blank&quot;&gt;https://support.10xgenomics.com/single-cell-gene-expression/software/visualization/latest/what-is-loupe-cell-browser&lt;/a&gt;</td></tr><tr><td>The commercial available analysis pipline in step 8.1 is Cell Ranger</td><td>10x Genomics</td><td></td><td>&lt;a href=&quot;https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/what-is-cell-ranger&quot; target=&quot;_blank&quot;&gt;https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/what-is-cell-ranger&lt;/a&gt;</td></tr><tr><td>The lipid based barcoding strategy is also known as MULTI-seq</td><td></td><td></td><td></td></tr><tr><td>The well maintained R platform is Seurat V3</td><td>satijalab</td><td></td><td>&lt;a href=&quot;https://satijalab.org/seurat/&quot; target=&quot;_blank&quot;&gt;https://satijalab.org/seurat/&lt;/a&gt;</td></tr><tr><td>TipOne RPT 0.1-10/20 ul XL ultra low retention filter pipet tip</td><td>USA Scientific</td><td>1180-3710</td><td></td></tr><tr><td>TipOne RPT 1000 ul XL ultra low retention filter pipet tip</td><td>USA Scientific</td><td>1182-1730</td><td></td></tr><tr><td>TipOne RPT 200 ul ultra low retention filter pipet tip</td><td>USA Scientific</td><td>1180-8710</td><td></td></tr><tr><td>TotalSeq-A0301 anti-mouse Hashtag 1 Antibody</td><td>BioLegend</td><td>155801</td><td>0.1 - 1.0 &amp;micro;g of antibody in 100 &amp;micro;l of staining buffer for every 1 million cells</td></tr><tr><td>TotalSeq-A0302 anti-mouse Hashtag 2 Antibody</td><td>BioLegend</td><td>155803</td><td>0.1 - 1.0 &amp;micro;g of antibody in 100 &amp;micro;l of staining buffer for every 1 million cells</td></tr><tr><td>TotalSeq-A0302 anti-mouse Hashtag 3 Antibody</td><td>BioLegend</td><td>155805</td><td>0.1 - 1.0 &amp;micro;g of antibody in 100 &amp;micro;l of staining buffer for every 1 million cells</td></tr><tr><td>TrueSeq RPI primer</td><td>Integrated DNA Technologies</td><td>Single-stranded DNA</td><td>100 nmol, used in Lipid-tagged barcode library mix (Table 1)</td></tr><tr><td>Trypan Blue Solution, 0.4%</td><td>Fisher Scientific</td><td>15250061</td><td></td></tr><tr><td>Trypsin-EDTA (0.25%), phenol red</td><td>Fisher Scientific</td><td>25200-056</td><td></td></tr><tr><td>Universal I5</td><td>Integrated DNA Technologies</td><td>Single-stranded DNA</td><td>100 nmol</td></tr></tbody></table>

multiplexed single cell mrna sequencing analysis of mouse embryonic cells

Single cell mRNA sequencing has made significant progress in the last several years and has become an important tool in the field of developmental biology. It has been successfully used to identify rare cell populations, discover novel marker genes, and decode spatial and temporal developmental information. The single cell method has also evolved from the microfluidic based Fluidigm C1 technology to the droplet-based solutions in the last two to three years. Here we used the heart as an example to demonstrate how to profile the mouse embryonic tissue cells using the droplet based scRNA-Seq method. In addition, we have integrated two strategies into the workflow to profile multiple samples in a single experiment. Using one of the integrated methods, we have simultaneously profiled more than 9,000 cells from eight heart samples. These methods will be valuable to the developmental biology field by providing a cost-effective way to simultaneously profile single cells from different genetic backgrounds, developmental stages, or anatomical locations.

In this study, we used mouse embryonic heart as an example to exhibit how multiplexed single cell mRNA sequencing was performed to process the different samples from separate parts of an organ simultaneously. E18.5 CD1 mouse hearts were isolated and dissected into left atrium (LA), right atrium (RA), left ventricle (LV) and right ventricle (RV). The atrial and ventricular cells were then barcoded independently using a lipid-based barcoding procedure and mixed together before GEMs generation and reverse-transcription. The schematic overview is shown in Figure 1. We quantified the cDNA concentration before library construction (Figure 2A). One of the distinctions in performing multiplexed scRNA-Seq from the standard scRNA-Seq is that the endogenous cDNA library and the sample barcode cDNA library were acquired separately after cDNA amplification and purification (Step 4.2.1 and 4.2.2.2). The two libraries were also qualified in our experiment (Figure 2B,C). Next generation sequencing and data analysis were performed followed by library construction and QC.
We used HiSeqX platform to sequence both libraries in the same sequencing lane. With the sequencing data, we first separated the endogenous transcript data and barcode data using the BaseSpace program. Then we analyzed barcode expression in each single cell and found 8 groups of single cells that uniquely express one type of barcode, representing cells from 8 different samples (Figure 3A). In addition, we also found that some cells do not express any barcode, which we defined as negative cells, and some cells express two different barcodes, which represent doublets (Figure 3B). In summary, we found that around 70% of cells are singlets, 25% of cells are negative and 5% of the cells are doublets.
With the singlet cells, we can perform further downstream analyses to understand the cellular heterogeneity and molecular regulations. The potential analyses can be cell type annotation (Figure 4A), novel/rare cell type identification (Figure 4B), anatomical zone comparative analysis (Figure 4C), and gene ontology pathway analysis such as cell cycle phase separations (Figure 4D).
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/60647/60647fig1.jpg" /> 
Figure 1: Multiplexed single cell mRNA sequencing workflow. Embryonic day 18.5 stage hearts were analyzed using a multiplexed droplet-based single cell sequencing procedure. RT = reverse transcription. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60647/60647fig1large.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/60647/60647fig2a.jpg" /> 
Figure 2: Representative QC results at different steps. (A) QC analysis of cDNA from step 4.1.7. The target fragment size is 200 to 9000 bp. (B) Endogenous library and (C) barcode library were analyzed with an automated electrophoresis instrument. The target fragment size for the endogenous library is 300-600 bp, and the barcode library DNA size is around 172 bp. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60647/60647fig2large.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/60647/60647fig3.jpg" /> 
Figure 3: Demultiplexing the sequencing data from the lipid based barcoding strategy. (A) Unsupervised analysis of the barcode expression. X-axis represents single cells, and y-axis represents barcodes. Each of the 8 single cell populations were identified to uniquely express one of the 8 barcodes. Note some cells express more than one barcode, and some cells do not express any barcodes. (B) t-SNE plot of the singlet cells, doublet cells, and negative cells. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60647/60647fig3large.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/60647/60647fig4.jpg" /> 
Figure 4: Advanced analysis of single cell transcriptional data. (A-D) Single cell data can be analyzed in different ways to understand the cellular heterogeneity and molecular pathways. We have listed several applications here as examples. Single cells were loaded into an R package to identify cell types (A), rare cell populations (B), cell anatomical zones (C), and cell cycle phases (D). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/60647/60647fig4large.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>Mixture Name</td>
			<td>Composition</td>
		</tr>
		<tr>
			<td>Collagenase mixture</td>
			<td>10 mg/mL collagenase A and 10 mg/mL collagenase B, dissolved in HBSS++ with 40% FBS.</td>
		</tr>
		<tr>
			<td>2 &#956;M Anchor/Barcode stock solution</td>
			<td>Mix 50 &#956;M anchor and 10 &#956;M barcode strand in 1:1 molar ratio in PBS (without FBS or BSA) for a total volume of 25 &#956;L.</td>
		</tr>
		<tr>
			<td>2 &#956;M Co-Anchor stock solution</td>
			<td>Dilute 1 &#956;L 50 &#956;M Co-Anchor with 24 &#956;L PBS (without FBS or BSA).</td>
		</tr>
		<tr>
			<td>Staining buffer</td>
			<td>PBS containing 2% BSA, 0.01% Tween 20</td>
		</tr>
		<tr>
			<td>Master Mixture</td>
			<td>20 &#956;L RT Reagent, 3.1 &#956;L Oligo, 2 &#956;L Reducing Agent B, 8.3 &#956;L RT Enzyme C.</td>
		</tr>
		<tr>
			<td>Beads Cleanup Mixture</td>
			<td>182 &#956;L Cleanup Buffer, 8 &#956;L Selection Reagent, 5 &#956;L Reducing Agent B, 5 &#956;L Nuclease-free Water.</td>
		</tr>
		<tr>
			<td>Amplification Reaction Mixture</td>
			<td>1 &#956;L of 10 &#956;M Lipid-tagged additive primer, 15 &#956;L cDNA primer, 50 &#956;L Amp Mix</td>
		</tr>
		<tr>
			<td>Elution Solution</td>
			<td>98 &#956;L Buffer EB, 1 &#956;L 10% Tween 20, 1 &#956;L Reducing Agent B.</td>
		</tr>
		<tr>
			<td>Fragmentation Mixture</td>
			<td>5 &#956;L Fragmentation Buffer, 10 &#956;L Fragmentation Enzyme.</td>
		</tr>
		<tr>
			<td>Adaptor Ligation mixture</td>
			<td>20 &#956;L Ligation Buffer, 10 &#956;L DNA Ligase, 20 &#956;L Adaptor Oligos.</td>
		</tr>
		<tr>
			<td>Sample Index PCR Mixture</td>
			<td>50 &#956;L Amp Mix, 10 &#956;L SI Primer</td>
		</tr>
		<tr>
			<td>Lipid barcode library mixture</td>
			<td>26.25 &#956;L of 2&#215; Hot Start master mix, 2.5 &#956;L of 10 &#956;M RPIX primer, 2.5 &#956;L of 10 &#956;M TruSeq Universal Adapter primer (see table of materials)</td>
		</tr>
		<tr>
			<td>Antibody barcode library mixture</td>
			<td>50 &#956;L of 2&#215; Hot Start master mix, 2.5 &#956;L of 10 &#956;M RPIX primer, 2.5 &#956;L of 10 &#956;M P5-smart-pcr hybrid oligo</td>
		</tr>
	</tbody>
</table>
Table 1: The reagent mixtures used in the protocol.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Incubating Procedure</td>
			<td>Temperature(1)</td>
			<td>Time</td>
		</tr>
		<tr>
			<td>GEM-RT Incubation</td>
			<td colspan="2">Lid Temperature 53 &#176;C</td>
		</tr>
		<tr>
			<td>Step 1</td>
			<td>53 &#176;C</td>
			<td>45 min</td>
		</tr>
		<tr>
			<td>Step 2</td>
			<td>85 &#176;C</td>
			<td>5 min</td>
		</tr>
		<tr>
			<td>Step 3</td>
			<td>4 &#176;C</td>
			<td>Hold</td>
		</tr>
		<tr>
			<td>10x Genomics cDNA Amplification</td>
			<td colspan="2">Lid Temperature 105 &#176;C</td>
		</tr>
		<tr>
			<td>Step 1</td>
			<td>98 &#176;C</td>
			<td>3 min</td>
		</tr>
		<tr>
			<td>Step 2</td>
			<td>98 &#176;C</td>
			<td>15 s</td>
		</tr>
		<tr>
			<td>Step 3</td>
			<td>63 &#176;C</td>
			<td>20 s</td>
		</tr>
		<tr>
			<td>Step 4</td>
			<td>72 &#176;C</td>
			<td>1 min</td>
		</tr>
		<tr>
			<td>Step 5</td>
			<td colspan="2">Repeat steps 2 to 4 for 12 cycles in total (2)</td>
		</tr>
		<tr>
			<td>Step 6</td>
			<td>72 &#176;C</td>
			<td>1 min</td>
		</tr>
		<tr>
			<td>Step 7</td>
			<td>4 &#176;C</td>
			<td>Hold</td>
		</tr>
		<tr>
			<td>Library construction</td>
			<td colspan="2">Lid Temperature 65 &#176;C</td>
		</tr>
		<tr>
			<td>Pre-cool block</td>
			<td>4 &#176;C</td>
			<td>Hold</td>
		</tr>
		<tr>
			<td>Fragmentation</td>
			<td>32 &#176;C</td>
			<td>5 min</td>
		</tr>
		<tr>
			<td>End Repair and A-tailing</td>
			<td>65 &#176;C</td>
			<td>30 min</td>
		</tr>
		<tr>
			<td>Hold</td>
			<td>4 &#176;C</td>
			<td>Hold</td>
		</tr>
		<tr>
			<td>Adaptor ligation</td>
			<td colspan="2">Lid Temperature 30 &#176;C</td>
		</tr>
		<tr>
			<td>Step 1</td>
			<td>20 &#176;C</td>
			<td>15 min</td>
		</tr>
		<tr>
			<td>Step 2</td>
			<td>4 &#176;C</td>
			<td>Hold</td>
		</tr>
		<tr>
			<td>Sample index PCR</td>
			<td colspan="2">Lid Temperature 105 &#176;C</td>
		</tr>
		<tr>
			<td>Step 1</td>
			<td>98 &#176;C</td>
			<td>45 s</td>
		</tr>
		<tr>
			<td>Step 2</td>
			<td>98 &#176;C</td>
			<td>20 s</td>
		</tr>
		<tr>
			<td>Step 3</td>
			<td>54 &#176;C</td>
			<td>30 s</td>
		</tr>
		<tr>
			<td>Step 4</td>
			<td>72 &#176;C</td>
			<td>20 s</td>
		</tr>
		<tr>
			<td>Step 5</td>
			<td colspan="2">Repeat steps 2 to 4 for 12 cycles in total (3)</td>
		</tr>
		<tr>
			<td>Step 6</td>
			<td>72 &#176;C</td>
			<td>1 min</td>
		</tr>
		<tr>
			<td>Step 7</td>
			<td>4 &#176;C</td>
			<td>Hold</td>
		</tr>
		<tr>
			<td>Lipid barcode library PCR</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Step 1</td>
			<td>95 &#176;C</td>
			<td>5 min</td>
		</tr>
		<tr>
			<td>Step 2</td>
			<td>98 &#176;C</td>
			<td>15 s</td>
		</tr>
		<tr>
			<td>Step 3</td>
			<td>60 &#176;C</td>
			<td>30 s</td>
		</tr>
		<tr>
			<td>Step 4</td>
			<td>72 &#176;C</td>
			<td>30 s</td>
		</tr>
		<tr>
			<td>Step 5</td>
			<td colspan="2">Repeat steps 2 to 4 for 10 cycles in total (4)</td>
		</tr>
		<tr>
			<td>Step 6</td>
			<td>72 &#176;C</td>
			<td>1 min</td>
		</tr>
		<tr>
			<td>Step 7</td>
			<td>4 &#176;C</td>
			<td>Hold</td>
		</tr>
		<tr>
			<td>Antibody barcode library PCR</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Step 1</td>
			<td>95 &#176;C</td>
			<td>3 min</td>
		</tr>
		<tr>
			<td>Step 2</td>
			<td>95 &#176;C</td>
			<td>20 s</td>
		</tr>
		<tr>
			<td>Step 3</td>
			<td>60 &#176;C</td>
			<td>30 s</td>
		</tr>
		<tr>
			<td>Step 4</td>
			<td>72 &#176;C</td>
			<td>20 s</td>
		</tr>
		<tr>
			<td>Step 5</td>
			<td colspan="2">Repeat steps 2 to 4 for 8 cycles in total (5)</td>
		</tr>
		<tr>
			<td>Step 6</td>
			<td>72 &#176;C</td>
			<td>5 min</td>
		</tr>
		<tr>
			<td>Step 7</td>
			<td>4 &#176;C</td>
			<td>Hold</td>
		</tr>
	</tbody>
</table>
Table 2: The incubating procedure used in the protocol. (1) Pay attention to the different lid temperature used in every Procedure. (2) Set total cycle numbers according to the cell load: 13 cycles for &#60;500 cell load; 12 cycles for 500-6,000 cell load; 11 cycles for &#62;6,000 cell load. (3) Set total cycle numbers according to the cDNA input: 14-16 cycles for 1-25 ng cDNA; 12-14 cycles for 25-150 ng cDNA; 10-12 cycles for 150-500 ng cDNA; 8-10 cycles for 500-1,000 ng cDNA; 6-8 cycles for 1000-1500 ng cDNA. (4) Set total cycle numbers according to the cDNA input: 8-12 cycles. (5) Set total cycle numbers according to the cDNA input: 6-10 cycles.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td colspan="2">Lipid based barcoding Oligonucleotides</td>
		</tr>
		<tr>
			<td>Anchor LMO</td>
			<td>5&#39;-TGGAATTCTCGGGTGCCAAGGGTAACGATCCAGCTGTCACT-Lipid-3&#39;</td>
		</tr>
		<tr>
			<td>Co-Anchor LMO</td>
			<td>5&#39;-Lipid-AGTGACAGCTGGATCGTTAC-3&#39;</td>
		</tr>
		<tr>
			<td>Barcode Oligo</td>
			<td>5&#39;-CCTTGGCACCCGAGAATTCCANNNNNNNNA30-3&#39;</td>
		</tr>
		<tr>
			<td>Lipid barcoding Additive Primer</td>
			<td>5&#39;-CTTGGCACCCGAGAATTCC-3&#39;</td>
		</tr>
		<tr>
			<td>RPIX Primer</td>
			<td>5&#39;-CAAGCAGAAGACGGCATACGAGATNNNNNNGTGACTGGAGTTCC 
			TTGGCACCCGAGAATTCCA-3&#39;</td>
		</tr>
		<tr>
			<td>Universal Adapter Primer</td>
			<td>5&#39;-AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGAC 
			GCTCTTCCGATCT-3&#39;</td>
		</tr>
		<tr>
			<td colspan="2">Antibody based barcoding Oligonucleotides</td>
		</tr>
		<tr>
			<td>Antibody barcoding oligo</td>
			<td>5&#39;-GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTNNNNNNNNNN 
			NNBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA*A*A-3&#39;</td>
		</tr>
		<tr>
			<td>HTO additive Primer</td>
			<td>5&#39;-GTGACTGGAGTTCAGACGTGTGCTC-3&#39;</td>
		</tr>
		<tr>
			<td>ADT additive Primer</td>
			<td>5&#39;-CCTTGGCACCCGAGAATTCC-3&#39;</td>
		</tr>
		<tr>
			<td>P5-smart-pcr hybrid oligo</td>
			<td>5&#39;-AATGATACGGCGACCACCGAGATCTACACGCCTGTCCGCGGAA 
			GCAGTGGTATCAACGCAGAGT*A*C-3&#39;</td>
		</tr>
	</tbody>
</table>
Table 3: Oligonucleotide sequences used in this protocol. N = Barcode or index sequence; * = Phosphorothioate bond

Watch this Scientific Journal Video about Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells at JoVE.com

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

Here we presented a multiplexed single cell mRNA sequencing method to profile gene expression in mouse embryonic tissues. The droplet-based single cell mRNA sequencing (scRNA-Seq) method in combination with multiplexing strategies can profile single cells from multiple samples simultaneously, which significantly reduces reagent costs and minimizes experimental batch effects.

Single cell mRNA sequencing has made significant progress in the last several years and has become an important tool in the field of developmental ...

multiplexed-single-cell-mrna-sequencing-analysis-mouse-embryonic

Nanyang Technological University

Research

JoVE Journal

Developmental Biology

12.8K Views.  University of Pittsburgh School of Medicine. Here we presented a multiplexed single cell mRNA sequencing method to profile gene expression in mouse embryonic tissues. The droplet-based single cell mRNA sequencing (scRNA-Seq) method in combination with multiplexing strategies can profile single cells from multiple samples simultaneously, which significantly reduces reagent costs and minimizes experimental batch effects.

Video: Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

Analysis of Cardiomyocyte Development using Immunofluorescence in Embryonic Mouse Heart

During heart development, the generation of myocardial-specific structural and functional units including sarcomeres, contractile myofibrils, intercalated discs, and costameres requires the coordinated assembly of multiple components in time and space. Disruption in assembly of these components leads to developmental heart defects. Immunofluorescent staining techniques are used commonly in cultured cardiomyocytes to probe myofibril maturation, but this ex vivo approach is limited by the extent to which myocytes will fully differentiate in culture, lack of normal in vivo mechanical inputs, and absence of endocardial cues. Application of immunofluorescence techniques to the study of developing mouse heart is desirable but more technically challenging, and methods often lack sufficient sensitivity and resolution to visualize sarcomeres in the early stages of heart development. Here, we describe a robust and reproducible method to co-immunostain multiple proteins or to co-visualize a fluorescent protein with immunofluorescent staining in the embryonic mouse heart and use this method to analyze developing myofibrils, intercalated discs, and costameres. This method can be further applied to assess cardiomyocyte structural changes caused by mutations that lead to developmental heart defects.

Mutations that lead to congenital heart defects benefit from in vivo investigation of cardiac structure during development, but high-resolution structural studies in the mouse embryonic heart are technically challenging. Here we present a robust immunofluorescence and image analysis method to assess cardiomyocyte-specific structures in the developing mouse heart.

During heart development, the generation of myocardial-specific structural and functional units including sarcomeres, contractile myofibrils, intercalated ...

Generating CRISPR/Cas9 Mediated Monoallelic Deletions to Study Enhancer Function in Mouse Embryonic Stem Cells

Enhancers control cell identity by regulating tissue-specific gene expression in a position and orientation independent manner. These enhancers are often located distally from the regulated gene in intergenic regions or even within the body of another gene. The position independent nature of enhancer activity makes it difficult to match enhancers with the genes they regulate. Deletion of an enhancer region provides direct evidence for enhancer activity and is the gold standard to reveal an enhancer's role in endogenous gene transcription. Conventional homologous recombination based deletion methods have been surpassed by recent advances in genome editing technology which enable rapid and precisely located changes to the genomes of numerous model organisms. CRISPR/Cas9 mediated genome editing can be used to manipulate the genome in many cell types and organisms rapidly and cost effectively, due to the ease with which Cas9 can be targeted to the genome by a guide RNA from a bespoke expression plasmid. Homozygous deletion of essential gene regulatory elements might lead to lethality or alter cellular phenotype whereas monoallelic deletion of transcriptional enhancers allows for the study of cis-regulation of gene expression without this confounding issue. Presented here is a protocol for CRISPR/Cas9 mediated deletion in F1 mouse embryonic stem (ES) cells (Mus musculus129 x Mus castaneus). Monoallelic deletion, screening and expression analysis is facilitated by single nucleotide polymorphisms (SNP) between the two alleles which occur on average every 125 bp in these cells.

Experimental validation of enhancer activity is best approached by loss-of-function analysis. Presented here is an efficient protocol that uses CRISPR/Cas9 mediated deletion to study allele-specific regulation of gene transcription in F1 ES cells which contain a hybrid genome (Mus musculus129 x Mus castaneus).

Enhancers control cell identity by regulating tissue-specific gene expression in a position and orientation independent manner. These enhancers are often ...

Quantitative Analysis of Protein Expression to Study Lineage Specification in Mouse Preimplantation Embryos

This protocol presents a method to perform quantitative, single-cell in situ analyses of protein expression to study lineage specification in mouse preimplantation embryos. The procedures necessary for embryo collection, immunofluorescence, imaging on a confocal microscope, and image segmentation and analysis are described. This method allows quantitation of the expression of multiple nuclear markers and the spatial (XYZ) coordinates of all cells in the embryo. It takes advantage of MINS, an image segmentation software tool specifically developed for the analysis of confocal images of preimplantation embryos and embryonic stem cell (ESC) colonies. MINS carries out unsupervised nuclear segmentation across the X, Y and Z dimensions, and produces information on cell position in three-dimensional space, as well as nuclear fluorescence levels for all channels with minimal user input. While this protocol has been optimized for the analysis of images of preimplantation stage mouse embryos, it can easily be adapted to the analysis of any other samples exhibiting a good signal-to-noise ratio and where high nuclear density poses a hurdle to image segmentation (e.g., expression analysis of embryonic stem cell (ESC) colonies, differentiating cells in culture, embryos of other species or stages, etc.).

This protocol presents a method to perform quantitative, single-cell in situ analysis of protein expression to study lineage specification in mouse preimplantation embryos. The procedures necessary for collection of blastocysts, whole-mount immunofluorescent detection of proteins, imaging of samples on a confocal microscope, and nuclear segmentation and image analysis are described.

This protocol presents a method to perform quantitative, single-cell in situ analyses of protein expression to study lineage specification in mouse ...

Isolation of Murine Embryonic Hemogenic Endothelial Cells

The specification of hemogenic endothelial cells from embryonic vascular endothelium occurs during brief developmental periods within distinct tissues, and is necessary for the emergence of definitive HSPC from the murine extra embryonic yolk sac, placenta, umbilical vessels, and the embryonic aorta-gonad-mesonephros (AGM) region. The transient nature and small size of this cell population renders its reproducible isolation for careful quantification and experimental applications technically difficult. We have established a fluorescence-activated cell sorting (FACS)-based protocol for simultaneous isolation of hemogenic endothelial cells and HSPC during their peak generation times in the yolk sac and AGM. We demonstrate methods for dissection of yolk sac and AGM tissues from mouse embryos, and we present optimized tissue digestion and antibody conjugation conditions for maximal cell survival prior to identification and retrieval via FACS. Representative FACS analysis plots are shown that identify the hemogenic endothelial cell and HSPC phenotypes, and describe a methylcellulose-based assay for evaluating their blood forming potential on a clonal level.

Hematopoietic stem and progenitor cells (HSPC) derive from specialized (hemogenic) endothelial cells during development, yet little is known about the process by which some endothelial cells specify to become blood forming. We demonstrate a flow-cytometry based method allowing simultaneous isolation of hemogenic endothelial cells and HSPC from murine embryonic tissues.

The specification of hemogenic endothelial cells from embryonic vascular endothelium occurs during brief developmental periods within distinct tissues, ...

Preparation of Small RNA Libraries for Sequencing from Early Mouse Embryos

MicroRNAs (miRNAs) are important for the complex regulation of cell fate decisions and developmental timing. In vivo studies of the contribution of miRNAs during early development are technically challenging due to the limiting cell number. Moreover, many approaches require a miRNA of interest to be defined in assays such as northern blotting, microarray, and qPCR. Therefore, the expression of many miRNAs and their isoforms have not been studied during early development. Here, we demonstrate a protocol for small RNA sequencing of sorted cells from early mouse embryos to enable relatively unbiased profiling of miRNAs in early populations of neural crest cells. We overcome the challenges of low cell input and size selection during library preparation using amplification and gel-based purification. We identify embryonic age as a variable accounting for variation between replicates and stage-matched mouse embryos must be used to accurately profile miRNAs in biological replicates. Our results suggest that this method can be broadly applied to profile the expression of miRNAs from other lineages of cells. In summary, this protocol can be used to study how miRNAs regulate developmental programs in different cell lineages of the early mouse embryo.

We describe a technique for profiling microRNAs in early mouse embryos. This protocol overcomes the challenge of low cell input and small RNA enrichment. This assay can be used to analyze changes in miRNA expression over time in different cell lineages of the early mouse embryo.

MicroRNAs (miRNAs) are important for the complex regulation of cell fate decisions and developmental timing. In vivo studies of the contribution of miRNAs ...

Isolation and Genotyping of Gastrulating Mouse Embryo for Single-Cell Sequencing

Single-Cell RNA Sequencing of Mutant Whole Mouse Embryos: From the Epiblast to the End of Gastrulation

Over the last decade, single-cell approaches have become the gold standard for studying gene expression dynamics, cell heterogeneity, and cell states within samples. Before single-cell advances, the feasibility of capturing the dynamic cellular landscape and rapid cell transitions during early development was limited. In this paper, a robust pipeline was designed to perform single-cell and nuclei analysis on mouse embryos from embryonic day E6.5 to E8, corresponding to the onset and completion of gastrulation. Gastrulation is a fundamental process during development that establishes the three germinal layers: mesoderm, ectoderm, and endoderm, which are essential for organogenesis. Extensive literature is available on single-cell omics applied to wild-type perigastrulating embryos. However, single-cell analysis of mutant embryos is still scarce and often limited to FACS-sorted populations. This is partially due to the technical constraints associated with the need for genotyping, timed pregnancies, the count of embryos with desired genotypes per pregnancy, and the number of cells per embryo at these stages. Here, a methodology is presented designed to overcome these limitations. This method establishes breeding and timed pregnancy guidelines to achieve a higher chance of synchronized pregnancies with desired genotypes. Optimization steps in the embryo isolation process coupled with a same-day genotyping protocol (3 h) allow for microdroplet-based single-cell to be performed on the same day, ensuring the high viability of cells and robust results. This method further includes guidelines for optimal nuclei isolations from embryos. Thus, these approaches increase the feasibility of single-cell approaches of mutant embryos at the gastrulation stage. We anticipate that this method will facilitate the analysis of how mutations shape the cellular landscape of the gastrula.

Author Spotlight: A Pipeline to Analyze Lineage-Specific Mutant Embryos at Single-Cell Resolution

This paper establishes a pipeline for high-quality single-cell and nuclei suspensions of gastrulating mouse embryos for sequencing of single cells and nuclei.

Over the last decade, single-cell approaches have become the gold standard for studying gene expression dynamics, cell heterogeneity, and cell states ...

Single Cell Transcriptional Profiling of Adult Mouse Cardiomyocytes

While numerous studies have examined gene expression changes from homogenates of heart tissue, this prevents studying the inherent stochastic variation between cells within a tissue. Isolation of pure cardiomyocyte populations through a collagenase perfusion of mouse hearts facilitates the generation of single cell microarrays for whole transcriptome gene expression, or qPCR of specific targets using nanofluidic arrays. We describe here a procedure to examine single cell gene expression profiles of cardiomyocytes isolated from the heart. This paradigm allows for the evaluation of metrics of interest which are not reliant on the mean (for example variance between cells within a tissue) which is not possible when using conventional whole tissue workflows for the evaluation of gene expression (Figure 1). We have achieved robust amplification of the single cell transcriptome yielding micrograms of double stranded cDNA that facilitates the use of microarrays on individual cells. In the procedure we describe the use of NimbleGen arrays which were selected for their ease of use and ability to customize their design. Alternatively, a reverse transcriptase - specific target amplification (RT-STA) reaction, allows for qPCR of hundreds of targets by nanofluidic PCR. Using either of these approaches, it is possible to examine the variability of expression between cells, as well as examining expression profiles of rare cell types from within a tissue. Overall, the single cell gene expression approach allows for the generation of data that can potentially identify idiosyncratic expression profiles that are typically averaged out when examining expression of millions of cells from typical homogenates generated from whole tissues.

Single cell expression profiling allows the detailed gene expression analysis of individual cells. We describe methods for the isolation of cardiomyocytes, and preparing the resulting lysates for either whole transcriptome microarray or qPCR of specific targets.

While numerous studies have examined gene expression changes from homogenates of heart tissue, this prevents studying the inherent stochastic variation ...

Biology

Single-cell RNA Sequencing of Fluorescently Labeled Mouse Neurons Using Manual Sorting and Double In Vitro Transcription with Absolute Counts Sequencing (DIVA-Seq)

Single-cell RNA sequencing (RNA-seq) is now a widely implemented tool for assaying gene expression. Commercially available single-cell RNA-sequencing platforms process all input cells indiscriminately. Sometimes, fluorescence-activated cell sorting (FACS) is used upstream to isolate a specifically labeled population of interest. A limitation of FACS is the need for high numbers of input cells with significantly labeled fractions, which is impractical for collecting and profiling rare or sparsely labeled neuron populations from the mouse brain. Here, we describe a method for manually collecting sparse fluorescently labeled single neurons from freshly dissociated mouse brain tissue. This process allows for capturing single-labeled neurons with high purity and subsequent integration with an in vitro transcription-based amplification protocol that preserves endogenous transcript ratios. We describe a double linear amplification method that uses unique molecule identifiers (UMIs) to generate individual mRNA counts. Two rounds of amplification results in a high degree of gene detection per single cell.

Single-cell RNA Sequencing of Fluorescently Labeled Mouse Neurons Using Manual Sorting and Double In Vitro Transcription with Absolute Counts Sequencing DIVA-Seq

This protocol describes the manual sorting procedure to isolate single fluorescently labeled neurons followed by in vitro transcription-based mRNA amplification for high-depth single-cell RNA sequencing.

Single-cell RNA sequencing (RNA-seq) is now a widely implemented tool for assaying gene expression. Commercially available single-cell RNA-sequencing ...

Neuroscience

Profiling Individual Human Embryonic Stem Cells by Quantitative RT-PCR

Heterogeneity of stem cell population hampers detailed understanding of stem cell biology, such as their differentiation propensity toward different lineages. A single cell transcriptome assay can be a new approach for dissecting individual variation. We have developed the single cell qRT-PCR method, and confirmed that this method works well in several gene expression profiles. In single cell level, each human embryonic stem cell, sorted by OCT4::EGFP positive cells, has high expression in OCT4, but a different level of NANOG expression. Our single cell gene expression assay should be useful to interrogate population heterogeneities.

Single cell gene expression assay is needed for understanding stem cell heterogeneities.

Heterogeneity of stem cell population hampers detailed understanding of stem cell biology, such as their differentiation propensity toward different ...

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Powerful next generation sequencing techniques offer robust and comprehensive analysis to investigate how retinal gene regulatory networks function during development and in disease states. Single-cell RNA sequencing allows us to comprehensively profile gene expression changes observed in retinal development and disease at a cellular level, while single-cell ATAC-Seq allows analysis of chromatin accessibility and transcription factor binding to be profiled at similar resolution. Here the use of these techniques in the developing retina is described, and MULTI-Seq is demonstrated, where individual samples are labeled with a modified oligonucleotide-lipid complex, enabling researchers to both increase the scope of individual experiments and substantially reduce costs.

Here, the authors showcase the utility of MULTI-seq for phenotyping and subsequent paired scRNA-seq and scATAC-seq in characterizing the transcriptomic and chromatin accessibility profiles in retina.

Powerful next generation sequencing techniques offer robust and comprehensive analysis to investigate how retinal gene regulatory networks function during ...