Evidence map›Paper›PMID 40551218›Full record

ArticlePlant methods2025

SeedSeg: image-based transgenic seed counting for segregation analysis of T-DNA loci.

Santiago Hernández, Vivian Zhong, Jennifer A N Brophy

Abstract read
In one paragraph

Article in Plant methods, 2025. 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
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1 · What the graph read from it

What it found

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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

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

3 authors.

Santiago Hernández *Department of Computer Science, Stanford University, Stanford, CA, 94305, USA.
Vivian Zhong *Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA.
Jennifer A N BrophyDepartment of Bioengineering, Stanford University, Stanford, CA, 94305, USA. jennbrophy@gmail.com.

Funding

Burroughs Wellcome Fund CASIChan Zuckerberg Biohub - San Francisco InvestigatorU.S. National Science Foundation 2340175U.S. National Science Foundation Graduate Research Fellowship 2022291786
6 · The paper itself

Abstract

backgroundTransgenic plants are essential for both basic and applied plant biology. Recently, fluorescent and colorimetric markers were developed to enable nondestructive identification of transformed seeds and accelerate the generation of transgenic plant lines. Yet, transformation often results in the integration of multiple copies of transgenes in the plant genome. Multiple transgene copies can lead to transgene silencing and complicate the analysis of transgenic plants by requiring researcher to track multiple T-DNA loci in future generations. Thus, to simplify analysis of transgenic lines, plant researchers typically screen transformed plants for lines where the T-DNA inserted in a single locus - an analysis that involves laborious manual counting of fluorescent and non-fluorescent seeds for screenable markers.

resultsTo expedite T-DNA segregation analysis, we developed SeedSeg, an image analysis tool that uses a segmentation algorithm to count the number of transformed and wild-type seeds in an image. SeedSeg runs a chi-squared test to determine the number of T-DNA loci. Parameters can be adjusted to optimize for different brightness intensities and seed sizes.

conclusionsBy automating the seed counting process, SeedSeg reduces the manual labor associated with identifying transgenic lines containing a single T-DNA locus. SeedSeg is adaptable to different seed sizes and visual transgene markers, making it a versatile tool for accelerating plant research.

Indexed as

ArabidopsisImage segmentationPlant genetic engineeringSeed countingTransgene segregation analysisTransgenic

Identifiers

PMID40551218
PMCPMC12186423

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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.