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

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2024-01-12
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Cook, Tanner M.
Biswas, Eva
Dutta, Somak
Aboobucker, Siddique I.
Hazinia, Sara
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BioMed Central Ltd
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AgronomyStatistics
Abstract
Background Strategies 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.
Results A 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.
Conclusion Our 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.
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This article is published as Cook, T.M., Biswas, E., Dutta, S. et al. Assessing data analysis techniques in a high-throughput meiosis-like induction detection system. Plant Methods 20, 7 (2024). https://doi.org/10.1186/s13007-023-01132-9. © The Author(s) 2024.

This article is licensed under a Creative Commons Attribution 4.0 International License.
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