Evidence map›Paper›PMID 38212773›Full record

ArticlePlant methods2024

Assessing data analysis techniques in a high-throughput meiosis-like induction detection system.

Tanner M Cook, Eva Biswas, Somak Dutta, Siddique I Aboobucker, Sara Hazinia, Thomas Lübberstedt

Open access · goldAbstract read
In one paragraph

Article in Plant methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 47% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
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

6 authors at 1 institution in 1 country.

Tanner M CookDepartment of Agronomy, Iowa State University, Ames, IA, USA.
Eva BiswasDepartment of Statistics, Iowa State University, Ames, IA, USA.
Somak DuttaDepartment of Statistics, Iowa State University, Ames, IA, USA.
Siddique I AboobuckerDepartment of Agronomy, Iowa State University, Ames, IA, USA.
Sara HaziniaDepartment of Agronomy, Iowa State University, Ames, IA, USA.
Thomas LübberstedtDepartment of Agronomy, Iowa State University, Ames, IA, USA. thomasl@iastate.edu.
Iowa State University · US

Funding

Foundation for Food & Agriculture Research CA19-SS 0000000128State of Iowa and USDA/NIFA the Iowa Agriculture and Home Economics Experiment Station, Ames, Iowa No. IOW04714USDA Hatch IOW03717
6 · The paper itself

Abstract

backgroundStrategies to understand meiotic processes have relied on cytogenetic and mutant analysis. However, thus far in vitro meiosis induction is a bottleneck to laboratory-based plant breeding as factor(s) that switch cells in crops species from mitotic to meiotic divisions are unknown. A high-throughput system that allows researchers to screen multiple candidates for their meiotic induction role using low-cost microfluidic devices has the potential to facilitate the identification of factors with the ability to induce haploid cells that have undergone recombination (artificial gametes) in cell cultures.

resultsA data analysis pipeline and a detailed protocol are presented to screen for plant meiosis induction factors in a quantifiable and efficient manner. We assessed three data analysis techniques using spiked-in protoplast samples (simulated gametes mixed into somatic protoplast populations) of flow cytometry data. Polygonal gating, which was considered the "gold standard", was compared to two thresholding methods using open-source analysis software. Both thresholding techniques were able to identify significant differences with low spike-in concentrations while also being comparable to polygonal gating.

conclusionOur study provides details to test and analyze candidate meiosis induction factors using available biological resources and open-source programs for thresholding. RFP (PE.CF594.A) and GFP (FITC.A) were the only channels required to make informed decisions on meiosis-like induction and resulted in detection of cell population changes as low as 0.3%, thus enabling this system to be scaled using microfluidic devices at low costs.

Indexed as

In vitro biologyMeiosis inductionPlant breeding and biotechnologySingle-cell analysis

Identifiers

PMID38212773
PMCPMC10785433
OpenAlexW4390766445

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.