NET-Seq

MARS-Seq

MARS-Seq profiles the transcriptional dynamics of single cells in an automated and massively parallel workflow with high resolution. MARS-Seq can be used with in vivo samples containing a wide variety of different cell subpopulations. Single cells are first isolated into individual wells using FACS. Each cell is lysed, and the 3' ends of mRNAs are annealed to unique molecular identifiers containing a T7 promoter. The mRNA is reverse-transcribed to generate the first cDNA strand and treated with exonuclease I to remove leftover RT primers. Next, the cellular lysates are pooled together and converted to double-stranded cDNA. The DNA strands are transcribed to RNA and treated with DNase to remove leftover DNA templates in the mixture. The RNA strands are fragmented and annealed to sequencing adapters, followed by RT to generate barcoded cDNA libraries that are ready for sequencing.

Similar methods: CEL-Seq, Quartz-Seq, Drop-seq, CytoSeq, inDrop.

Pros:

• High-throughput transcriptional profiling of single cells
• In vivo sampling of thousands of cells
• Three barcode levels (molecular, cellular, and plate-level tags) facilitate robust multiplexing capabilities
• Processes 100 to 1000 single cells
• Pooling all single cells into 1 flow cell reduces the cost to less than 50 cents per cell¹

Cons:

• 3' bias can occur during the purification step
• Fragmentation step eliminates strand-specific information²

• MARS-Seq: Jaitin D. A., Kenigsberg E., Keren-Shaul H., et al. Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types. Science. 2014;343:776-779
• 1. Jaitin D. A., Keren-Shaul H., Elefant N. and Amit I. Each cell counts: Hematopoiesis and immunity research in the era of single cell genomics. Semin Immunol. 2015;27:67-71
• 2. Hrdlickova R., Toloue M. and Tian B. RNA-Seq methods for transcriptome analysis. Wiley Interdiscip Rev RNA. 2016;

1. Hrdlickova R., Toloue M. and Tian B. RNA-Seq methods for transcriptome analysis. Wiley Interdiscip Rev RNA. 2016;
2. Wen L. and Tang F. Single-cell sequencing in stem cell biology. Genome Biol. 2016;17:71
3. Jaitin D. A., Keren-Shaul H., Elefant N. and Amit I. Each cell counts: Hematopoiesis and immunity research in the era of single cell genomics. Semin Immunol. 2015;27:67-71

1. Paul F., Arkin Y., Giladi A., et al. Transcriptional Heterogeneity and Lineage Commitment in Myeloid Progenitors. Cell. 2015;163:1663-1677
2. Baruch K., Deczkowska A., Rosenzweig N., et al. PD-1 immune checkpoint blockade reduces pathology and improves memory in mouse models of Alzheimer's disease. Nat Med. 2016;22:135-137