Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Decoding cellular stress states for toxicology using single-cell transcriptomics.

NAM journal·2026
Same author

Snow Avalanches and the Impact of Climate-Linked Extreme Events on Mountain Wildlife Population Dynamics and Resilience.

Global change biology·2025
Same author

Life-history trade-offs and environmental variability shape reproductive demography in a mountain ungulate.

The Journal of animal ecology·2025
Same author

Decoding Cellular Stress States for Toxicology Using Single-Cell Transcriptomics.

bioRxiv : the preprint server for biology·2025
Same author

Comparison of whole transcriptome and targeted RNA sequencing for ecological high-throughput transcriptomics.

Regulatory toxicology and pharmacology : RTP·2025
Same author

Inherited chromosomally integrated human herpesvirus 6: regional variation in prevalence, association with angina, and identification of ancestral viral lineages in two large UK studies.

Journal of virology·2025

Related Experiment Video

Updated: Jun 4, 2025

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations
09:34

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

Published on: October 25, 2018

6.6K

High-throughput gene expression analysis with TempO-LINC sensitively resolves complex brain, lung and kidney

Dennis J Eastburn1, Kevin S White2, Nathan D Jayne2

  • 1BioSpyder Technologies, Inc., Carlsbad, CA, USA. denniseastburn@biospyder.com.

Scientific Reports
|December 29, 2024
PubMed
Summary

We developed TempO-LINC, a novel genomics platform for high-throughput single-cell transcriptomic analysis. This technology enables scalable, high-sensitivity gene expression profiling from fixed cells without cDNA generation, ideal for large-scale studies.

More Related Videos

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing
10:00

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

Published on: May 23, 2018

17.5K
Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation
12:54

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation

Published on: March 7, 2018

13.5K

Related Experiment Videos

Last Updated: Jun 4, 2025

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations
09:34

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

Published on: October 25, 2018

6.6K
An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing
10:00

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

Published on: May 23, 2018

17.5K
Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation
12:54

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation

Published on: March 7, 2018

13.5K

Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Single-cell transcriptomics is crucial for understanding cellular heterogeneity.
  • Existing methods often require complex protocols or lack scalability for large cell numbers.

Purpose of the Study:

  • To develop and validate TempO-LINC, a novel, high-throughput platform for single-cell and single-nucleus transcriptomic analysis.
  • To demonstrate the scalability and performance of TempO-LINC across diverse sample types and species.

Main Methods:

  • TempO-LINC utilizes a novel approach involving cell-identifying molecular barcodes added to gene expression probes within fixed cells.
  • An instrument-free combinatorial indexing strategy enables reconstruction of single-cell gene expression profiles.
  • The assay is designed for high-sensitivity gene detection and can be targeted to specific gene sets or profile the whole transcriptome.

Main Results:

  • TempO-LINC successfully profiled transcriptomes from over 90,000 cells across multiple species and tissue types (lung, kidney, brain).
  • The platform demonstrated a low multiplet rate (<1.1%) and a cell capture rate of approximately 50%.
  • Analysis identified and annotated over 50 unique cell populations, correlating cell type-specific markers.

Conclusions:

  • TempO-LINC is a robust, scalable, and high-sensitivity single-cell transcriptomic analysis platform.
  • It is well-suited for large-scale applications requiring high data quality and efficient cell population identification.
  • The technology facilitates deep insights into cellular heterogeneity across various biological systems.