Dataset Information

RNA velocity of single cells.

ABSTRACT: RNA abundance is a powerful indicator of the state of individual cells. Single-cell RNA sequencing can reveal RNA abundance with high quantitative accuracy, sensitivity and throughput1. However, this approach captures only a static snapshot at a point in time, posing a challenge for the analysis of time-resolved phenomena such as embryogenesis or tissue regeneration. Here we show that RNA velocity-the time derivative of the gene expression state-can be directly estimated by distinguishing between unspliced and spliced mRNAs in common single-cell RNA sequencing protocols. RNA velocity is a high-dimensional vector that predicts the future state of individual cells on a timescale of hours. We validate its accuracy in the neural crest lineage, demonstrate its use on multiple published datasets and technical platforms, reveal the branching lineage tree of the developing mouse hippocampus, and examine the kinetics of transcription in human embryonic brain. We expect RNA velocity to greatly aid the analysis of developmental lineages and cellular dynamics, particularly in humans.

SUBMITTER: La Manno G

PROVIDER: S-EPMC6130801 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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RNA velocity of single cells.

La Manno Gioele G Soldatov Ruslan R Zeisel Amit A Braun Emelie E Hochgerner Hannah H Petukhov Viktor V Lidschreiber Katja K Kastriti Maria E ME Lönnerberg Peter P Furlan Alessandro A Fan Jean J Borm Lars E LE Liu Zehua Z van Bruggen David D Guo Jimin J He Xiaoling X Barker Roger R Sundström Erik E Castelo-Branco Gonçalo G Cramer Patrick P Adameyko Igor I Linnarsson Sten S Kharchenko Peter V PV

Nature 20180808 7719

RNA abundance is a powerful indicator of the state of individual cells. Single-cell RNA sequencing can reveal RNA abundance with high quantitative accuracy, sensitivity and throughput<sup>1</sup>. However, this approach captures only a static snapshot at a point in time, posing a challenge for the analysis of time-resolved phenomena such as embryogenesis or tissue regeneration. Here we show that RNA velocity-the time derivative of the gene expression state-can be directly estimated by distinguis ...[more]

PMID: 30089906

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Project description:BACKGROUND: Propagation of simulated action potentials (APs) was previously studied in short single chains and in two-dimensional sheets of myocardial cells 123. The present study was undertaken to examine propagation in a long single chain of cells of various lengths, and with varying numbers of gap-junction (g-j) channels, and to compare propagation velocity with the cable properties such as the length constant (lambda). METHODS AND RESULTS: Simulations were carried out using the PSpice program as previously described. When the electric field (EF) mechanism was dominant (0, 1, and 10 gj-channels), the longer the chain length, the faster the overall velocity (theta(ov)). There seems to be no simple explanation for this phenomenon. In contrast, when the local-circuit current mechanism was dominant (100 gj-channels or more), theta(ov) was slightly slowed with lengthening of the chain. Increasing the number of gj-channels produced an increase in theta(ov) and caused the firing order to become more uniform. The end-effect was more pronounced at longer chain lengths and at greater number of gj-channels. When there were no or only few gj-channels (namely, 0, 10, or 30), the voltage change (DeltaV(m)) in the two contiguous cells (#50 & #52) to the cell injected with current (#51) was nearly zero, i.e., there was a sharp discontinuity in voltage between the adjacent cells. When there were many gj-channels (e.g., 300, 1000, 3000), there was an exponential decay of voltage on either side of the injected cell, with the length constant (lambda) increasing at higher numbers of gj-channels. The effect of increasing the number of gj-channels on increasing lambda was relatively small compared to the larger effect on theta(ov). theta(ov) became very non-physiological at 300 gj-channels or higher. CONCLUSION: Thus, when there were only 0, 1, or 10 gj-channels, theta(ov) increased with increase in chain length, whereas at 100 gj-channels or higher, theta(ov) did not increase with chain length. When there were only 0, 10, or 30 gj-channels, there was a very sharp decrease in DeltaV(m) in the two contiguous cells on either side of the injected cell, whereas at 300, 1000, or 3000 gj-channels, the voltage decay was exponential along the length of the chain. The effect of increasing the number of gj-channels on spread of current was relatively small compared to the large effect on theta(ov).

Dataset Information

RNA velocity of single cells.

Publications

RNA velocity of single cells.

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