Spatiotemporal Developmental Trajectories in the Arabidopsis Root Revealed Using High-Throughput Single Cell RNA Sequencing

Abstract Background High throughput single-cell RNA sequencing (scRNA-Seq) has emerged as a powerful tool for exploring cellular heterogeneity among complex human cancers. scRNA-Seq studies using fresh human surgical tissue are logistically difficult, preclude histopathological triage of samples, and limit the ability to perform batch processing. This hindrance can often introduce technical biases when integrating patient datasets and increase experimental costs. Although tissue preservation methods have been previously explored to address such issues, it is yet to be examined on complex human tissues, such as solid cancers and on high throughput scRNA-Seq platforms. Methods Using the Chromium 10X platform, we sequenced a total of ~ 120,000 cells from fresh and cryopreserved replicates across three primary breast cancers, two primary prostate cancers and a cutaneous melanoma. We performed detailed analyses between cells from each condition to assess the effects of cryopreservation on cellular heterogeneity, cell quality, clustering and the identification of gene ontologies. In addition, we performed single-cell immunophenotyping using CITE-Seq on a single breast cancer sample cryopreserved as solid tissue fragments. Results Tumour heterogeneity identified from fresh tissues was largely conserved in cryopreserved replicates. We show that sequencing of single cells prepared from cryopreserved tissue fragments or from cryopreserved cell suspensions is comparable to sequenced cells prepared from fresh tissue, with cryopreserved cell suspensions displaying higher correlations with fresh tissue in gene expression. We showed that cryopreservation had minimal impacts on the results of downstream analyses such as biological pathway enrichment. For some tumours, cryopreservation modestly increased cell stress signatures compared to freshly analysed tissue. Further, we demonstrate the advantage of cryopreserving whole-cells for detecting cell-surface proteins using CITE-Seq, which is impossible using other preservation methods such as single nuclei-sequencing. Conclusions We show that the viable cryopreservation of human cancers provides high-quality single-cells for multi-omics analysis. Our study guides new experimental designs for tissue biobanking for future clinical single-cell RNA sequencing studies.

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Ultra-high-throughput single-cell RNA sequencing and perturbation screening with combinatorial fluidic indexing

Nature Methods ◽

10.1038/s41592-021-01153-z ◽

2021 ◽

Author(s):

Paul Datlinger ◽

André F. Rendeiro ◽

Thorina Boenke ◽

Martin Senekowitsch ◽

Thomas Krausgruber ◽

...

Keyword(s):

Single Cell ◽

Rna Sequencing ◽

High Throughput ◽

Single Cell Rna Sequencing

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Faculty Opinions recommendation of Hydro-Seq enables contamination-free high-throughput single-cell RNA-sequencing for circulating tumor cells.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.735763461.793573386 ◽

2020 ◽

Author(s):

Vijay Tiwari ◽

Mohammed Inayatullah

Keyword(s):

Single Cell ◽

Tumor Cells ◽

Rna Sequencing ◽

Circulating Tumor Cells ◽

High Throughput ◽

Single Cell Rna Sequencing

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Inertial-ordering-assisted droplet microfluidics for high-throughput single-cell RNA-sequencing

Lab on a Chip ◽

10.1039/c7lc01284e ◽

2018 ◽

Vol 18 (5) ◽

pp. 775-784 ◽

Cited By ~ 35

Author(s):

Hui-Sung Moon ◽

Kwanghwi Je ◽

Jae-Woong Min ◽

Donghyun Park ◽

Kyung-Yeon Han ◽

...

Keyword(s):

Single Cell ◽

Rna Sequencing ◽

High Throughput ◽

Droplet Microfluidics ◽

Single Cell Rna Sequencing ◽

Spiral Microchannel

We developed a modified high-throughput droplet barcoding technique for single-cell Drop-Seq via introduction of hydrodynamic ordering in a spiral microchannel.

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Microbial single-cell RNA sequencing by split-pool barcoding

Science ◽

10.1126/science.aba5257 ◽

2020 ◽

Vol 371 (6531) ◽

pp. eaba5257 ◽

Cited By ~ 2

Author(s):

Anna Kuchina ◽

Leandra M. Brettner ◽

Luana Paleologu ◽

Charles M. Roco ◽

Alexander B. Rosenberg ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Rna Sequencing ◽

High Throughput ◽

Single Cell Analysis ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Growth Stages ◽

High Throughput Analysis ◽

Single Cell Rna Sequencing

Single-cell RNA sequencing (scRNA-seq) has become an essential tool for characterizing gene expression in eukaryotes, but current methods are incompatible with bacteria. Here, we introduce microSPLiT (microbial split-pool ligation transcriptomics), a high-throughput scRNA-seq method for Gram-negative and Gram-positive bacteria that can resolve heterogeneous transcriptional states. We applied microSPLiT to >25,000 Bacillus subtilis cells sampled at different growth stages, creating an atlas of changes in metabolism and lifestyle. We retrieved detailed gene expression profiles associated with known, but rare, states such as competence and prophage induction and also identified unexpected gene expression states, including the heterogeneous activation of a niche metabolic pathway in a subpopulation of cells. MicroSPLiT paves the way to high-throughput analysis of gene expression in bacterial communities that are otherwise not amenable to single-cell analysis, such as natural microbiota.

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Single-cell transcriptome sequencing: recent advances and remaining challenges

F1000Research ◽

10.12688/f1000research.7223.1 ◽

2016 ◽

Vol 5 ◽

pp. 182 ◽

Cited By ~ 132

Author(s):

Serena Liu ◽

Cole Trapnell

Keyword(s):

Single Cell ◽

Rna Sequencing ◽

Developmental Trajectories ◽

Population Data ◽

Transcriptional Dynamics ◽

Single Cell Rna Sequencing ◽

Cell Assays ◽

Potential Applications ◽

Cell Transcriptome ◽

Single Cell Transcriptome

Single-cell RNA-sequencing methods are now robust and economically practical and are becoming a powerful tool for high-throughput, high-resolution transcriptomic analysis of cell states and dynamics. Single-cell approaches circumvent the averaging artifacts associated with traditional bulk population data, yielding new insights into the cellular diversity underlying superficially homogeneous populations. Thus far, single-cell RNA-sequencing has already shown great effectiveness in unraveling complex cell populations, reconstructing developmental trajectories, and modeling transcriptional dynamics. Ongoing technical improvements to single-cell RNA-sequencing throughput and sensitivity, the development of more sophisticated analytical frameworks for single-cell data, and an increasing array of complementary single-cell assays all promise to expand the usefulness and potential applications of single-cell transcriptomic profiling.

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