A Deep Learning-Based System (Microscan) for the Identification of Pollen Development Stages and Its Application to Obtaining Doubled Haploid Lines in Eggplant
Abstract
:1. Introduction
2. Materials and Methods
2.1. Plant Material
2.2. Experimental Layout and Workflow
2.3. Phase 1: Model Training
2.3.1. Microspore and Pollen Isolation
2.3.2. Digital Data Image Acquisition
2.3.3. Image Labelling
2.3.4. Preprocessing
2.3.5. Predictive Model
2.4. Phase 2: In Vitro Androgenesis Induction Test Using the Anther Selection Software
2.4.1. E6 Protocol
2.4.2. Cb Protocol
2.4.3. Flow Cytometry
2.4.4. Single Primer Enrichment Technology (SPET) Genotyping
3. Results
3.1. Phase 1: Model Training
3.2. Phase 2: In Vitro Androgenesis Induction Test Using the Microscan
4. Discussion
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Medium | MS + Vitamins (g/L) | Prepared C (g/L) | Prepared R (g/L) | Sucrose (g/L) | Zeatin Riboside (mg/L) | Kinetin (mg/L) | 2,4-D (mg/L) | Vitamin B12 (mg/L) | Gelrite (g/L) | Bacto-Agar (g/L) |
---|---|---|---|---|---|---|---|---|---|---|
E0 | 2.20 | - | - | 15.00 | - | - | - | - | 7.00 | - |
E6 | 2.20 | - | - | 15.00 | 2.00 | - | - | - | 7.00 | - |
Cb | - | 4.55 | - | 120.00 | - | 5.00 | 5.00 | 0.20 | - | 8.00 |
R | - | - | 4.55 | 30.00 | - | 0.10 | - | - | - | 8.00 |
Class | Total Cellular Events | Average Precision (%) |
---|---|---|
Tetrad | 290 | 87.40 |
Young Microspore | 641 | 86.28 |
Medium Microspore | 1893 | 81.97 |
Vacuolated Microspore | 1185 | 87.60 |
Young Pollen | 1876 | 82.32 |
Mature Pollen | 2186 | 92.19 |
mAP | 86.30 |
Protocol E6 | Protocol Cb | |||||
---|---|---|---|---|---|---|
Size Range/Genotype | Anthers (n) | Response (%) | Type of Response | Anthers (n) | Response (%) | Type of Response |
3.5–4 mm | ||||||
BC3 17-8 | 45 | 0.00 ± 0.00 | - | 45 | 0.00 ± 0.00 | - |
BC3 17-19 | 45 | 0.00 ± 0.00 | - | 45 | 0.00 ± 0.00 | - |
BC3 17-4 | 45 | 0.00 ± 0.00 | - | 45 | 0.00 ± 0.00 | - |
5.5–6 mm | ||||||
BC3 17-8 | 45 | 75.30 ± 0.04 | Embryo | 45 | 78.40 ± 0.04 | Callus |
BC3 17-19 | 45 | 60.40 ± 0.05 | Embryo | 45 | 80.50 ± 0.04 | Callus |
BC3 17-4 | 45 | 40.30 ± 0.05 | Embryo | 45 | 71.20 ± 0.05 | Callus |
>6 mm | ||||||
BC3 17-8 | 45 | 0.00 ± 0.00 | - | 45 | 3.20 ± 0.02 | Somatic callus |
BC3 17-19 | 45 | 0.00 ± 0.00 | - | 45 | 4.00 ± 0.02 | Somatic callus |
BC3 17-4 | 45 | 0.00 ± 0.00 | - | 45 | 4.30 ± 0.03 | Somatic callus |
Genotype | Embryos (n) | Acclimatized Plants (n) | n | n + 2n | 2n |
---|---|---|---|---|---|
BC3 17-8 | 42 | 12 | 9 | 3 | 0 |
BC3 17-19 | 26 | 12 | 8 | 1 | 3 |
BC3 17-4 | 9 | 7 | 6 | 1 | 0 |
Accession/Offspring | n | Missing SNPs | Heterozygosity (%) |
---|---|---|---|
ELE BC3 17-19 | 1 | 0.00 | 100.00 |
BC4 (ELE BC3 17-19 × MEL3) | 6 | 4.00 (0.00–6.00) | 55.07 (39.06–65.66) |
DH (ELE BC3 17-19 doubled haploids) | 10 | 5.00 (0.00–12.00) | 1.59 (0.19–3.95) |
ELE BC3 17-4 | 1 | 0.00 | 100.00 |
BC4 (ELE BC3 17-4 × MEL3) | 5 | 0.40 (0.00–2.00) | 53.87 (13.35–92.66) |
DH (ELE BC3 17-4 doubled haploids) | 7 | 1.14 (0.00–4.00) | 0.67 (0.19–1.70) |
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García-Fortea, E.; García-Pérez, A.; Gimeno-Páez, E.; Sánchez-Gimeno, A.; Vilanova, S.; Prohens, J.; Pastor-Calle, D. A Deep Learning-Based System (Microscan) for the Identification of Pollen Development Stages and Its Application to Obtaining Doubled Haploid Lines in Eggplant. Biology 2020, 9, 272. https://doi.org/10.3390/biology9090272
García-Fortea E, García-Pérez A, Gimeno-Páez E, Sánchez-Gimeno A, Vilanova S, Prohens J, Pastor-Calle D. A Deep Learning-Based System (Microscan) for the Identification of Pollen Development Stages and Its Application to Obtaining Doubled Haploid Lines in Eggplant. Biology. 2020; 9(9):272. https://doi.org/10.3390/biology9090272
Chicago/Turabian StyleGarcía-Fortea, Edgar, Ana García-Pérez, Esther Gimeno-Páez, Alfredo Sánchez-Gimeno, Santiago Vilanova, Jaime Prohens, and David Pastor-Calle. 2020. "A Deep Learning-Based System (Microscan) for the Identification of Pollen Development Stages and Its Application to Obtaining Doubled Haploid Lines in Eggplant" Biology 9, no. 9: 272. https://doi.org/10.3390/biology9090272