Evidence map›Paper›PMID 39732835›Full record

ArticleScientific reports2024

High-throughput gene expression analysis with TempO-LINC sensitively resolves complex brain, lung and kidney heterogeneity at single-cell resolution.

Dennis J Eastburn, Kevin S White, Nathan D Jayne, Salvatore Camiolo, Gioele Montis, Seungeun Ha, Kendall G Watson, Joanne M Yeakley, Joel McComb, Bruce Seligmann

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Dennis J EastburnBioSpyder Technologies, Inc., Carlsbad, CA, USA. denniseastburn@biospyder.com.
Kevin S WhiteBioSpyder Technologies, Inc., Carlsbad, CA, USA.
Nathan D JayneBioSpyder Technologies, Inc., Carlsbad, CA, USA.
Salvatore CamioloBioSpyder Technologies, Inc., Carlsbad, CA, USA.
Gioele MontisBioSpyder Technologies, Inc., Carlsbad, CA, USA.
Seungeun HaBioSpyder Technologies, Inc., Carlsbad, CA, USA.
Kendall G WatsonBioSpyder Technologies, Inc., Carlsbad, CA, USA.
Joanne M YeakleyBioSpyder Technologies, Inc., Carlsbad, CA, USA.
Joel McCombBioSpyder Technologies, Inc., Carlsbad, CA, USA.
Bruce SeligmannBioSpyder Technologies, Inc., Carlsbad, CA, USA.

Funding

TempO-LINC high throughput high sensitivity single cell gene expression profiling assay Ph IIR44GM140771 · NIGMS · BIOSPYDER TECHNOLOGIES, INC. · PI SELIGMANN, BRUCE E. · 2023 to 2024
$2.5M
TempO-LINC high throughput, high sensitivity single cell gene expression profiling assayR43GM140771 · NIGMS · BIOSPYDER TECHNOLOGIES, INC. · PI SELIGMANN, BRUCE E. · 2021 to 2021
$402k
NIGMS NIH HHS R43 GM140771NIGMS NIH HHS R44 GM140771NIH HHS R44GM140771
6 · The paper itself

Abstract

We report the development and performance of a novel genomics platform, TempO-LINC, for conducting high-throughput transcriptomic analysis on single cells and nuclei. TempO-LINC works by adding cell-identifying molecular barcodes onto highly selective and high-sensitivity gene expression probes within fixed cells, without having to first generate cDNA. Using an instrument-free combinatorial indexing approach, all probes within the same fixed cell receive an identical barcode, enabling the reconstruction of single-cell gene expression profiles across as few as several hundred cells and up to 100,000 + cells per sample. The TempO-LINC approach is easily scalable based on the number of barcodes and rounds of barcoding performed; however, for the experiments reported in this study, the assay utilized over 5.3 million unique barcodes. TempO-LINC offers a robust protocol for fixing and banking cells and displays high-sensitivity gene detection from multiple diverse sample types. We show that TempO-LINC has a multiplet rate of less than 1.1% and a cell capture rate of ~ 50%. Although the assay can accurately profile the whole transcriptome (19,683 human, 21,400 mouse and 21,119 rat genes), it can be targeted to measure only actionable/informative genes and molecular pathways of interest - thereby reducing sequencing requirements. In this study, we applied TempO-LINC to profile the transcriptomes of more than 90,000 cells across multiple species and sample types, including nuclei from mouse lung, kidney and brain tissues. The data demonstrated the ability to identify and annotate more than 50 unique cell populations and positively correlate expression of cell type-specific molecular markers within them. TempO-LINC is a robust new single-cell technology that is ideal for large-scale applications/studies with high data quality.

Indexed as

BrainGene Expression ProfilingKidneyLungSingle-Cell AnalysisAnimalsHigh-Throughput Nucleotide SequencingHumansMiceTranscriptome

Identifiers

PMID39732835
PMCPMC11682069

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.