Constructing an atlas of cell types in complex organisms will require a collective effort to characterize billions of individual cells. Single cell RNA sequencing (scRNA-seq) has emerged as the main tool for characterizing cellular diversity, but current methods use custom microfluidics or microwells to compartmentalize single cells, limiting scalability and widespread adoption. Here we present Split Pool Ligation-based Transcriptome sequencing (SPLiT-seq), a scRNA-seq method that labels the cellular origin of RNA through combinatorial indexing. SPLiT-seq is compatible with fixed cells, scales exponentially, uses only basic laboratory equipment, and costs one cent per cell. We used this approach to analyze 109,069 single cell transcriptomes from an entire postnatal day 5 mouse brain, providing the first global snapshot at this stage of development. We identified 13 main populations comprising different types of neurons, glia, immune cells, endothelia, as well as types in the blood-brain-barrier. Moreover, we resolve substructure within these clusters corresponding to cells at different stages of development. As sequencing capacity increases, SPLiT-seq will enable profiling of billions of cells in a single experiment.Over three hundred years have passed since the discovery of the cell, yet we still do not have a complete catalogue of cell types or their functions. While transcriptomic profiling of individual cells has emerged as a promising solution to characterizing cellular diversity (1, 2), increases in throughput are needed before a complete "atlas" of cell types can be generated. Recent single cell RNA-seq (scRNA-seq) methods have profiled tens of thousands of individual cells (3-6), revealing new insights about the immune system (7) and identifying new cell types in the brain (8-11). However, since these methods require cell sorters and custom microfluidics or microwells, throughput is still limited, experiments are costly, and access is limited to a small number of labs.peer-reviewed)
Cells use spatial constraints to control and accelerate the flow of information in enzyme cas-1 cades and signaling networks. Here we show that spatial organization can be a similarly into circuits that establish the universality of our approach. Because reactions preferen-7 tially occur between neighbors, identical DNA hairpins can be reused across circuits. Co-8 localization of circuit elements decreases computation time from hours to minutes compared 9 to circuits with diffusible components. Detailed computational models enable predictive cir-10 cuit design. We anticipate that our approach will motivate the use of spatial constraints in 11 molecular engineering more broadly, bringing embedded molecular control circuits closer to 12 1 . CC-BY-NC-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under aThe copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/110965 doi: bioRxiv preprint first posted online Feb. 23, 2017; applications. 13Human-engineered systems, from ancient irrigation networks to modern semiconductor cir- architecture that exploits the advantages of spatial organization is still lacking. 53Here we experimentally demonstrate a modular design strategy -the "DNA domino" archi- The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/110965 doi: bioRxiv preprint first posted online Feb. 23, 2017; Localized signal propagation mechanism 61To illustrate how information is propagated spatially, we consider the "DNA domino effect" in a 62 minimal two-hairpin wire comprised of an Input and Output hairpin attached to a DNA origami 63 scaffold (Fig. 1b). In each reaction step, a hairpin stem is unwound and a toehold that is initially (Fig. 1c). We first confirmed that a signal could rapidly propagate across proxi-75 mally positioned Input and Output hairpins (single spacing) in a two-hairpin wire (t 1/2 <3 mins). 76No observable signal transfer was observed without input addition. We then doubled the distance 77 between Input and Output hairpins (double spacing) on the same origami, and showed that separat-78 ing the hairpins beyond their theoretical maximum reach resulted in minimal signal transfer (Fig. 79 1c, Supplementary Fig. S4). Furthermore, we found that interactions between Input and Output 80 hairpins on two different origamis were significantly slower than single-spaced hairpin interactions 81 on the same origami, and comparable to the double-spaced hairpin interactions. Crucially, decreas-82 ing the operating concentration of the origamis did not affect the speed of localized intra-origami 83 signal propagation, but significantly reduced the speed of non-localized inter-origami interactions 84 ( Supplementary Fig. S5). 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/110965 doi: bioRxiv preprint first posted online Feb. 23, 2017;We quantified the kinetics of domino circui...
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.