Evidence map›Paper›PMID 33376219›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2020

HyPR-seq: Single-cell quantification of chosen RNAs via hybridization and sequencing of DNA probes.

Jamie L Marshall, Benjamin R Doughty, Vidya Subramanian, Philine Guckelberger, Qingbo Wang, Linlin M Chen, Samuel G Rodriques, Kaite Zhang, Charles P Fulco, Joseph Nasser and 8 more

Open access · bronzeAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
2.2field-weighted citation impact, top 11% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

26 citing papers in PubMed, 43 citations in OpenAlex.

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  13. Approaches to probe and perturb long noncoding RNA functions in diseases.Current opinion in genetics & development · 2024
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors at 1 institution in 2 countries.

Jamie L MarshallBroad Institute of MIT and Harvard, Cambridge, MA 02142.ORCID 0000-0002-2364-391X
Benjamin R DoughtyBroad Institute of MIT and Harvard, Cambridge, MA 02142.ORCID 0000-0003-0447-4468
Vidya SubramanianBroad Institute of MIT and Harvard, Cambridge, MA 02142.
Philine GuckelbergerBroad Institute of MIT and Harvard, Cambridge, MA 02142.ORCID 0000-0002-1057-2518
Qingbo WangBroad Institute of MIT and Harvard, Cambridge, MA 02142.
Linlin M ChenBroad Institute of MIT and Harvard, Cambridge, MA 02142.
Samuel G RodriquesBroad Institute of MIT and Harvard, Cambridge, MA 02142.
Kaite ZhangBroad Institute of MIT and Harvard, Cambridge, MA 02142.
Charles P FulcoBroad Institute of MIT and Harvard, Cambridge, MA 02142.
Joseph NasserBroad Institute of MIT and Harvard, Cambridge, MA 02142.
Elizabeth J GrinkevichBroad Institute of MIT and Harvard, Cambridge, MA 02142.
Teia NoelBroad Institute of MIT and Harvard, Cambridge, MA 02142.
Sarah MangiameliBroad Institute of MIT and Harvard, Cambridge, MA 02142.
Drew T BergmanBroad Institute of MIT and Harvard, Cambridge, MA 02142.ORCID 0000-0002-8314-7088
Anna GrekaBroad Institute of MIT and Harvard, Cambridge, MA 02142.ORCID 0000-0001-5697-7791
Eric S LanderBroad Institute of MIT and Harvard, Cambridge, MA 02142; lander@broadinstitute.org chenf@broadinstitute.org engreitz@stanford.edu.
Fei ChenBroad Institute of MIT and Harvard, Cambridge, MA 02142; lander@broadinstitute.org chenf@broadinstitute.org engreitz@stanford.edu.ORCID 0000-0003-2308-3649
Jesse M EngreitzBroad Institute of MIT and Harvard, Cambridge, MA 02142; lander@broadinstitute.org chenf@broadinstitute.org engreitz@stanford.edu.ORCID 0000-0002-5754-1719
Broad Institute · US

Funding

Characterizing glioma heterogeneity with novel multiplexed nanoscale imaging technologiesDP5OD024583 · OD · BROAD INSTITUTE, INC. · PI CHEN, FEI · 2017 to 2021
$2.2M
Systematic mapping and prediction of gene-enhancer connectionsR00HG009917 · NHGRI · STANFORD UNIVERSITY · PI ENGREITZ, JESSE M · 2020 to 2022
$796k
Systematic mapping and prediction of gene-enhancer connectionsK99HG009917 · NHGRI · BROAD INSTITUTE, INC. · PI ENGREITZ, JESSE M · 2018 to 2019
$65k
NHGRI NIH HHS K99 HG009917NHGRI NIH HHS R00 HG009917NIH HHS DP5 OD024583
6 · The paper itself

Abstract

Single-cell quantification of RNAs is important for understanding cellular heterogeneity and gene regulation, yet current approaches suffer from low sensitivity for individual transcripts, limiting their utility for many applications. Here we present Hybridization of Probes to RNA for sequencing (HyPR-seq), a method to sensitively quantify the expression of hundreds of chosen genes in single cells. HyPR-seq involves hybridizing DNA probes to RNA, distributing cells into nanoliter droplets, amplifying the probes with PCR, and sequencing the amplicons to quantify the expression of chosen genes. HyPR-seq achieves high sensitivity for individual transcripts, detects nonpolyadenylated and low-abundance transcripts, and can profile more than 100,000 single cells. We demonstrate how HyPR-seq can profile the effects of CRISPR perturbations in pooled screens, detect time-resolved changes in gene expression via measurements of gene introns, and detect rare transcripts and quantify cell-type frequencies in tissue using low-abundance marker genes. By directing sequencing power to genes of interest and sensitively quantifying individual transcripts, HyPR-seq reduces costs by up to 100-fold compared to whole-transcriptome single-cell RNA-sequencing, making HyPR-seq a powerful method for targeted RNA profiling in single cells.

Indexed as

Nucleic Acid HybridizationSingle-Cell AnalysisAnimalsCRISPR-Cas SystemsDNA ProbesGene ExpressionHigh-Throughput Nucleotide SequencingHumansIntronsK562 CellsKidneyMicePolyadenylationRNARNA, MessengerTHP-1 CellsDNA ProbesRNARNA, Messengerenhancersgene regulationgenomicssingle cell

Identifiers

PMID33376219
PMCPMC7776864
OpenAlexW3113630028

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.