Evidence map›Paper›PMID 42086881›Full record

ArticleNature biotechnology2026

A single-cell screening platform accelerates functional genetics in plants.

Tara N Lowensohn, Will B Cody, Chun Tsai, Alexander E Vlahos, Connor C Call, Xiaojing J Gao, Elizabeth S Sattely

Abstract read
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In one paragraph

Article in Nature biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Tara N Lowensohn *Department of Chemistry, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0003-3195-1135
Will B Cody *Department of Chemical Engineering, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0009-0008-2565-1842
Chun TsaiHoward Hughes Medical Institute, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0003-1549-2522
Alexander E VlahosDepartment of Chemical Engineering, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-2154-8791
Connor C CallDepartment of Chemical Engineering, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0003-2394-7523
Xiaojing J GaoDepartment of Chemical Engineering, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-3094-1456
Elizabeth S SattelyDepartment of Chemical Engineering, Stanford University, Stanford, CA, USA. sattely@stanford.edu.ORCID http://orcid.org/0000-0002-7352-859X

Funding

National Science Foundation (NSF) DGE-2146755United States Department of Agriculture | National Institute of Food and Agriculture (NIFA) 2022-67012-36700
6 · The paper itself

Abstract

Elucidating gene function in highly redundant genetic programs such as signaling pathways is challenging in model and nonmodel plants with current whole-plant genetic screening tools. Many of these challenges could be overcome if screens were instead carried out using individual cells harboring genetic perturbations. Here we report a single-cell screening platform, PIVOT (protoplast isolation after virus overexpression in planta), to accelerate identification and functional characterization of plant genes. We use Nicotiana benthamiana as a heterologous host to test gene libraries arrayed in a single leaf. PIVOT harnesses viral superinfection exclusion to ensure single multiplicity of infection per cell during pooled library delivery. Additionally, we engineer a cell-surface protein as a phenotypic marker for isolating cells of interest from a heterogeneous population. Using this system, we recover regulators of cytokinin signaling from an Arabidopsis open reading frame library. We anticipate PIVOT will be broadly applicable for high-throughput, single-cell functional genetic screening across the plant kingdom.

Identifiers

PMID42086881

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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.