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>
	<li>Raj, A., Van Den Bogaard, P., Rifkin, S. A., Van Oudenaarden, A., Tyagi, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Imaging+individual+mRNA+molecules+using+multiple+singly+labeled+probes.">Imaging individual mRNA molecules using multiple singly labeled probes.</a> Nature Methods. 5 (10), 877 (2008).</li><li>Tang, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=mRNA-Seq+whole-transcriptome+analysis+of+a+single+cell.">mRNA-Seq whole-transcriptome analysis of a single cell.</a> Nature Methods. 6 (5), 377 (2009).</li><li>Li, G., Plonowska, K., Kuppusamy, R., Sturzu, A., Wu, S. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identification+of+cardiovascular+lineage+descendants+at+single-cell+resolution.">Identification of cardiovascular lineage descendants at single-cell resolution.</a> Development. 142 (5), 846-857 (2015).</li><li>DeLaughter, D. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-cell+resolution+of+temporal+gene+expression+during+heart+development.">Single-cell resolution of temporal gene expression during heart development.</a> Developmental Cell. 39 (4), 480-490 (2016).</li><li>Li, G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single+cell+expression+analysis+reveals+anatomical+and+cell+cycle-dependent+transcriptional+shifts+during+heart+development.">Single cell expression analysis reveals anatomical and cell cycle-dependent transcriptional shifts during heart development.</a> Development. 146 (12), dev173476 (2019).</li><li>Meilhac, S. M., Buckingham, M. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+deployment+of+cell+lineages+that+form+the+mammalian+heart.">The deployment of cell lineages that form the mammalian heart.</a> Nature Reviews Cardiology. 1, (2018).</li><li>Liu, Z., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-cell+transcriptomics+reconstructs+fate+conversion+from+fibroblast+to+cardiomyocyte.">Single-cell transcriptomics reconstructs fate conversion from fibroblast to cardiomyocyte.</a> Nature. 551 (7678), 100 (2017).</li><li>Lafzi, A., Moutinho, C., Picelli, S., Heyn, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tutorial:+guidelines+for+the+experimental+design+of+single-cell+RNA+sequencing+studies.">Tutorial: guidelines for the experimental design of single-cell RNA sequencing studies.</a> Nature Protocols. 1, (2018).</li><li>The Tabula Muris Consortium. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-cell+transcriptomics+of+20+mouse+organs+creates+a+Tabula+Muris.">Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris.</a> Nature. 562 (7727), 367 (2018).</li><li>Gawad, C., Koh, W., Quake, S. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-cell+genome+sequencing:+current+state+of+the+science.">Single-cell genome sequencing: current state of the science.</a> Nature Reviews Genetics. 17 (3), 175 (2016).</li><li>Gr&#252;n, D., van Oudenaarden, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Design+and+analysis+of+single-cell+sequencing+experiments.">Design and analysis of single-cell sequencing experiments.</a> Cell. 163 (4), 799-810 (2015).</li><li>Ziegenhain, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparative+analysis+of+single-cell+RNA+sequencing+methods.">Comparative analysis of single-cell RNA sequencing methods.</a> Molecular cell. 65 (4), 631-643 (2017).</li><li>Hashimshony, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=CEL-Seq2:+sensitive+highly-multiplexed+single-cell+RNA-Seq.">CEL-Seq2: sensitive highly-multiplexed single-cell RNA-Seq.</a> Genome Biology. 17 (1), 77 (2016).</li><li>Islam, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characterization+of+the+single-cell+transcriptional+landscape+by+highly+multiplex+RNA-seq.">Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq.</a> Genome Research. 21 (7), 1160-1167 (2011).</li><li>Macosko, E. Z., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Highly+parallel+genome-wide+expression+profiling+of+individual+cells+using+nanoliter+droplets.">Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets.</a> Cell. 161 (5), 1202-1214 (2015).</li><li>Klein, A. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Droplet+barcoding+for+single-cell+transcriptomics+applied+to+embryonic+stem+cells.">Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells.</a> Cell. 161 (5), 1187-1201 (2015).</li><li>. Library Prep -Single Cell Gene Expression -Official 10x Genomics Support Available from: <a target="_blank" href="https://support.10xgenomics.com/single-cell-gene-expression/library-prep">https://support.10xgenomics.com/single-cell-gene-expression/library-prep</a> (2018)</li><li>McGinnis, C. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MULTI-seq:+sample+multiplexing+for+single-cell+RNA+sequencing+using+lipid-tagged+indices.">MULTI-seq: sample multiplexing for single-cell RNA sequencing using lipid-tagged indices.</a> Nature Methods. 1, (2019).</li><li>Stoeckius, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cell+hashing+with+barcoded+antibodies+enables+multiplexing+and+doublet+detection+for+single+cell+genomics.">Cell hashing with barcoded antibodies enables multiplexing and doublet detection for single cell genomics.</a> Genome Biology. 19 (1), 224 (2018).</li><li>Chan, M. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Molecular+recording+of+mammalian+embryogenesis.">Molecular recording of mammalian embryogenesis.</a> Nature. 570 (7759), 77-82 (2019).</li><li>. Agilent 4200 TapeStation System Available from: <a target="_blank" href="https://www.agilent.com/cs/library/datasheets/public/5991-6029EN.pdf">https://www.agilent.com/cs/library/datasheets/public/5991-6029EN.pdf</a> (2019)</li><li>. SPRIselect User Guide Available from: <a target="_blank" href="https://research.fhcrc.org/content/dam/stripe/hahn/methods/mol_biol/SPRIselect%20User%20Guide.pdf">https://research.fhcrc.org/content/dam/stripe/hahn/methods/mol_biol/SPRIselect%20User%20Guide.pdf</a> (2012)</li><li>. Qubit 4 Fluorometer User Guide Available from: <a target="_blank" href="https://assets.thermofisher.com/TFS-Assets/LSG/manuals/MAN0017209_Qubit_4_Fluorometer_UG.pdf">https://assets.thermofisher.com/TFS-Assets/LSG/manuals/MAN0017209_Qubit_4_Fluorometer_UG.pdf</a> (2018)</li><li>. Agilent High Sensitivity DNA Kit Guide Available from: <a target="_blank" href="https://www.agilent.com/cs/library/usermanuals/public/High%20Sensitivity_DNA_KG.pdf">https://www.agilent.com/cs/library/usermanuals/public/High%20Sensitivity_DNA_KG.pdf</a> (2016)</li><li>Butler, A., Hoffman, P., Smibert, P., Papalexi, E., Satija, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Integrating+single-cell+transcriptomic+data+across+different+conditions,+technologies,+and+species.">Integrating single-cell transcriptomic data across different conditions, technologies, and species.</a> Nature Biotechnology. 36 (5), 411 (2018).</li><li>Weber, R. J., Liang, S. I., Selden, N. S., Desai, T. A., Gartner, Z. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Efficient+targeting+of+fatty-acid+modified+oligonucleotides+to+live+cell+membranes+through+stepwise+assembly.">Efficient targeting of fatty-acid modified oligonucleotides to live cell membranes through stepwise assembly.</a> Biomacromolecules. 15 (12), 4621-4626 (2014).</li><li>. Single Cell Protocols Cell Preparation Guide Available from: <a target="_blank" href="https://support.10xgenomics.com/single-cell-gene-expression/sample-prep">https://support.10xgenomics.com/single-cell-gene-expression/sample-prep</a> (2017)</li></ol>

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 ...

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 border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<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 &#176;C</td>
		</tr>
		<tr>
			<td>Chromium Single Cell 3&#39; GEM Kit v3,4 rxns</td>
			<td>10x Genomics</td>
			<td>1000094</td>
			<td>Store at -20 &#176;C</td>
		</tr>
		<tr>
			<td>Chromium Single Cell 3&#39; Library Kit v3</td>
			<td>10x Genomics</td>
			<td>1000095</td>
			<td>Store at -20 &#176;C</td>
		</tr>
		<tr>
			<td>Chromium Single Cell 3&#39; v3 Gel Beads</td>
			<td>10x Genomics</td>
			<td>2000059</td>
			<td>Store at -80 &#176;C</td>
		</tr>
		<tr>
			<td>Collagenase A</td>
			<td>Sigma/Millipore</td>
			<td>10103578001</td>
			<td>Store powder at 4 &#176;C, store at -20 &#176;C after it dissolves</td>
		</tr>
		<tr>
			<td>Collagenase B</td>
			<td>Sigma/Millipore</td>
			<td>11088807001</td>
			<td>Store powder at 4 &#176;C, store at -20 &#176;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 &#176;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 &#176;C</td>
		</tr>
		<tr>
			<td>Finnpipette F1 Multichannel Pipettes, 10-100&#956;l</td>
			<td>Theromo Scientific</td>
			<td>4661020N</td>
			<td></td>
		</tr>
		<tr>
			<td>Finnpipette F1 Multichannel Pipettes, 1-10&#956;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 &#956;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 &#181;l of Human TruStain FcX per million cells in 100 &#181;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 &#176;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 &#38; 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&#8211;2.5&#956;L, 0.5-10&#956;L, 10&#8211;100&#956;L, 100&#8211;1,000&#956;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 &#176;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><a href="https://support.10xgenomics.com/single-cell-gene-expression/software/visualization/latest/what-is-loupe-cell-browser" target="_blank">https://support.10xgenomics.com/single-cell-gene-expression/software/visualization/latest/what-is-loupe-cell-browser</a></td>
		</tr>
		<tr>
			<td>The commercial available analysis pipline in step 8.1 is Cell Ranger</td>
			<td>10x Genomics</td>
			<td></td>
			<td><a href="https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/what-is-cell-ranger" target="_blank">https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/what-is-cell-ranger</a></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><a href="https://satijalab.org/seurat/" target="_blank">https://satijalab.org/seurat/</a></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 &#181;g of antibody in 100 &#181;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 &#181;g of antibody in 100 &#181;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 &#181;g of antibody in 100 &#181;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 generati...

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

Universidad de Cartagena UDEC

Research

JoVE Journal

Developmental Biology

12.7K 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 ...

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, ...

Imaging Cleared Embryonic and Postnatal Hearts at Single-cell Resolution

Single clonal tracing and analysis at the whole-heart level can determine cardiac progenitor cell behavior and differentiation during cardiac development, and allow for the study of the cellular and molecular basis of normal and abnormal cardiac morphogenesis. Recent emerging technologies of retrospective single clonal analyses make the study of cardiac morphogenesis at single cell resolution feasible. However, tissue opacity and light scattering of the heart as imaging depth is increased hinder whole-heart imaging at single cell resolution. To overcome these obstacles, a whole-embryo clearing system that can render the heart highly transparent for both illumination and detection must be developed. Fortunately, in the last several years, many methodologies for whole-organism clearing systems such as CLARITY, Scale, SeeDB, ClearT, 3DISCO, CUBIC, DBE, BABB and PACT have been reported. This lab is interested in the cellular and molecular mechanisms of cardiac morphogenesis. Recently, we established single cell lineage tracing via the ROSA26-CreERT2; ROSA26-Confetti system to sparsely label cells during cardiac development. We adapted several whole embryo-clearing methodologies including Scale and CUBIC (clear, unobstructed brain imaging cocktails and computational analysis) to clear the embryo in combination with whole mount staining to image single clones inside the heart. The heart was successfully imaged at single cell resolution. We found that Scale can clear the embryonic heart, but cannot effectively clear the postnatal heart, while CUBIC can clear the postnatal heart, but damages the embryonic heart by dissolving the tissue. The methods described here will permit the study of gene function at a single clone resolution during cardiac morphogenesis, which, in turn, can reveal the cellular and molecular basis of congenital heart defects.

We describe a protocol to volumetrically image fluorescent protein labeled cells deep inside intact embryonic and postnatal hearts. Utilizing tissue-clearing methods in combination with whole mount staining, single fluorescent protein-labeled cells inside an embryonic or postnatal heart can be imaged clearly and accurately.

Single clonal tracing and analysis at the whole-heart level can determine cardiac progenitor cell behavior and differentiation during cardiac development, ...

Clonal Analysis of Embryonic Hematopoietic Stem Cell Precursors Using Single Cell Index Sorting Combined with Endothelial Cell Niche Co-culture

The ability to study hematopoietic stem cell (HSC) genesis during embryonic development has been limited by the rarity of HSC precursors in the early embryo and the lack of assays that functionally identify the long-term multilineage engraftment potential of individual putative HSC precursors. Here, we describe methodology that enables the isolation and characterization of functionally validated HSC precursors at the single cell level. First, we utilize index sorting to catalog the precise phenotypic parameter of each individually sorted cell, using a combination of phenotypic markers to enrich for HSC precursors with additional markers for experimental analysis. Second, each index-sorted cell is co-cultured with vascular niche stroma from the aorta-gonad-mesonephros (AGM) region, which supports the maturation of non-engrafting HSC precursors to functional HSC with multilineage, long-term engraftment potential in transplantation assays. This methodology enables correlation of phenotypic properties of clonal hemogenic precursors with their functional engraftment potential or other properties such as transcriptional profile, providing a means for the detailed analysis of HSC precursor development at the single cell level.

Here we present methodology for the clonal analysis of hematopoietic stem cell precursors during murine embryonic development. We combine index sorting of single cells from the embryonic aorta-gonad-mesonephros region with endothelial cell co-culture and transplantation to characterize the phenotypic properties and engraftment potential of single hematopoietic precursors.

The ability to study hematopoietic stem cell (HSC) genesis during embryonic development has been limited by the rarity of HSC precursors in the early ...

Single-cell Photoconversion in Living Intact Zebrafish

Animal and plant tissue is composed of distinct populations of cells. These cells interact over time to build and maintain the tissue and can cause disease when disrupted. Scientists have developed clever techniques to investigate characteristics and natural dynamics of these cells within intact tissue by expressing fluorescent proteins in subsets of cells. However, at times, experiments require more selected visualization of cells within the tissue, sometimes at the single-cell or population-of-cells manner. To achieve this and visualize single cells within a population of cells, scientists have utilized single-cell photoconversion of fluorescent proteins. To demonstrate this technique, we show here how to direct UV light to an Eos-expressing cell of interest in an intact, living zebrafish. We then image those photoconverted Eos+ cells 24 h later to determine how they changed in the tissue. We describe two techniques: single cell photoconversion and photoconversions of populations of cell. These techniques can be used to visualize cell-cell interactions, cell-fate and differentiation, and cell migrations, making it a technique that is applicable in numerous biological questions.

Here, we present a protocol to show how cell photoconversion is achieved through UV exposure to specific areas expressing the fluorescent protein, Eos, in living animals.

Animal and plant tissue is composed of distinct populations of cells. These cells interact over time to build and maintain the tissue and can cause ...

Single-cell Transcriptomic Analyses of Mouse Pancreatic Endocrine Cells

Pancreatic endocrine cells, which are clustered in islets, regulate blood glucose stability and energy metabolism. The distinct cell types in islets, including insulin-secreting &#946; cells, are differentiated from common endocrine progenitors during the embryonic stage. Immature endocrine cells expand via cell proliferation and mature during a long postnatal developmental period. However, the mechanisms underlying these processes are not clearly defined. Single-cell RNA-sequencing is a promising approach for the characterization of distinct cell populations and tracing cell lineage differentiation pathways. Here, we describe a method for the single-cell RNA-sequencing of isolated pancreatic &#946; cells from embryonic, neonatal and postnatal pancreases.

We describe a method for the isolation of endocrine cells from embryonic, neonatal and postnatal pancreases followed by single-cell RNA sequencing. This method allows analyses of pancreatic endocrine lineage development, cell heterogeneity and transcriptomic dynamics.

Pancreatic endocrine cells, which are clustered in islets, regulate blood glucose stability and energy metabolism. The distinct cell types in islets, ...

Efficient Neural Differentiation using Single-Cell Culture of Human Embryonic Stem Cells

In vitro differentiation of human embryonic stem cells (hESCs) has transformed the ability to study human development on both biological and molecular levels and provided cells for use in regenerative applications. Standard approaches for hESC culture using colony type culture to maintain undifferentiated hESCs and embryoid body (EB) and rosette formation for differentiation into different germ layers are inefficient and time-consuming. Presented here is a single-cell culture method using hESCs instead of a colony-type culture. This method allows maintenance of the characteristic features of undifferentiated hESCs, including expression of hESC markers at levels comparable to colony type hESCs. In addition, the protocol presents an efficient method for neural progenitor cell (NPC) generation from single-cell type hESCs that produces NPCs within 1 week. These cells highly express several NPC marker genes and can differentiate into various neural cell types, including dopaminergic neurons and astrocytes. This single-cell culture system for hESCs will be useful in investigating the molecular mechanisms of these processes, studies of certain diseases, and drug discovery screens.

Presented here is a protocol for the generation of a single-cell culture of human embryonic stem cells and their subsequent differentiation into neural progenitor cells. The protocol is simple, robust, scalable, and suitable for drug screening and regenerative medicine applications.

In vitro differentiation of human embryonic stem cells (hESCs) has transformed the ability to study human development on both biological and molecular ...

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 Time-Lapse Imaging of Primary Mouse Embryonic Palatal Mesenchyme Cells to Analyze Collective Movement Attributes

Development of the palate is a dynamic process, which involves vertical growth of bilateral palatal shelves next to the tongue followed by elevation and fusion above the tongue. Defects in this process lead to cleft palate, a common birth defect. Recent studies have shown that palatal shelf elevation involves a remodeling process that transforms the orientation of the shelf from a vertical to a horizontal one. The role of the palatal shelf mesenchymal cells in this dynamic remodeling has been difficult to study. Time-lapse-imaging-based quantitative analysis has been recently used to show that primary mouse embryonic palatal mesenchymal (MEPM) cells can self-organize into a collective movement. Quantitative analyses could identify differences in mutant MEPM cells from a mouse model with palate elevation defects. This paper describes methods to isolate and culture MEPM cells from E13.5 embryos-specifically for time-lapse imaging-and to determine various cellular attributes of collective movement, including measures for stream formation, shape alignment, and persistence of direction. It posits that MEPM cells can serve as a proxy model for studying the role of palatal shelf mesenchyme during the dynamic process of elevation. These quantitative methods will allow investigators in the craniofacial field to assess and compare collective movement attributes in control and mutant cells, which will augment the understanding of mesenchymal remodeling during palatal shelf elevation. Furthermore, MEPM cells provide a rare mesenchymal cell model for investigation of collective cell movement in general.

We present a protocol for isolation and culture of primary mouse embryonic palatal mesenchymal cells for time-lapse imaging of two-dimensional (2D) growth and wound-repair assays. We also provide the methodology for analysis of the time-lapse imaging data to determine cell-stream formation and directional motility.

Development of the palate is a dynamic process, which involves vertical growth of bilateral palatal shelves next to the tongue followed by elevation and ...