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McGill Plant Phenomics Platform - MP3

McGill Plant Phenomics Platform - MP3. Emilio Vello. Overview. What tools do we use to get the phenotyping data? Greenhouse LemnaTec Scanalyzer 3D LemnaTec HTS How do we collect and analyze? Arsenic Tolerance Assay. McGill University - MP3 Location. Montreal. Greenhouse.

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McGill Plant Phenomics Platform - MP3

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  1. McGill Plant Phenomics Platform - MP3 Emilio Vello

  2. Overview • What tools do we use to get the phenotyping data? • Greenhouse • LemnaTec Scanalyzer 3D • LemnaTec HTS • How do we collect and analyze? • Arsenic Tolerance Assay

  3. McGill University - MP3 Location Montreal Greenhouse McGill Biology Building Montreal Weather http://blogs.mcgill.ca/iss/category/winter/ http://www.hrviews.ca -40°C 40°C

  4. Lemnatec Scanalyzer 3D Plant Phenomics 2.3 m 3.0 m Conveyor- Plants Cars “parking” 3.8 m Cameras Watering and weighing station Working Area – Load station

  5. 3D-Components Features: • Top and Side views • Angles from 0° to 360°. • Automatic Watering and weighting system • Small and big plants. • Near Infrared Scanning for water content • Infrared Scanning for temperature • RGB scanning for plant architecture. • Max. height for a plant 900 mm • Max. width 600 mm • Max. width if all pots are filled: 240 mm NIR VIS Weighing station IR Watering station

  6. 3D – Pots, support and Identification 3D pot registration screen Plant pot support adapters Medium Small Large

  7. Lemnatec Scanalyzer HTS – high-throughput screening Sensor arm Growth chambers 1.10 m 3.00m 1.95 m Close to minimize plant movements Growth chambers

  8. HTS-Sensors

  9. HTS-Plant supports Pot support / Free format support Capacity: 96 small pots Plate support Capacity: 60 square petri dishes

  10. HTS - Lights • Near infrared light • Fluorescent light • Ring light • Top visible light • Bottom visible light Camera Bottom light

  11. HTS – sample identification system Mutant / tray Replicate / set Barcode reader Assay ID

  12. How do we collect and analyze data? An example: arsenic tolerance assay

  13. Arsenic Tolerance Experimental design • Arabidopsis thaliana • 136 DNA targets / mutant lines (T-DNA knockout genes) • 3 replicates • 1 square petri dish per line • 36 seeds per petri dish • 750 µM arsenic • 408 plates in total • 14688 seeds/seedlings (Without counting the concentration tests) Objective: Identification of DNA target candidates showing a significant resistance or sensitivity to high concentration of arsenic. Bioinformatics Analysis. Proxy of germination

  14. Arsenic – Safety • The plates covers can't be removed because of the arsenic toxicity following the rule of the EHS. (McGill Environmental Health and Safety Office) • The covers fog because of the water condensation • High reflection due to the cover and water. Will we be able to classify the seeds?

  15. Arsenic – Image acquisition configuration Fluorescent light 1 frame 1 plate Visible bottom light 4 frames 1 plates 2448 images in total. Visible bottom light 1 frame 1 plate

  16. Arsenic – Image Analysis Pipeline RGB selection raw object list creation McGill development using java, ImageJ libraries and R Object size > 10 px Object circularity > 0.099 d(centroid,squareCenter)<130 Big Object HUE(HSB) 16 colour classification Object properties / features

  17. Arsenic - Clustering 1 2 3 Hierarchical cluster Ward's minimum variance method Euclidean distance matrix Group 2 Group 1 4

  18. Arsenic – Cluster Interpretation 103 Group 2 = Sensitive = Non Germination WT 152 Group 1 = Resistant = Germination

  19. Arsenic - Results 103 152 WT

  20. Arsenic Mutant 152 Mutant 152 = ARS5 is the strongest arsenic resistant mutant identified by Sung et al.

  21. Conclusion • Integrationand contribution of people from different domains have been a key for the success of the MP3. • Integration is also true for the different tools use in the digital phenotyping including hardware, software. • we need to findnew metricsfrom different kind of sensors to increase the spectrum of phenotypes.

  22. Acknowledgements • Prof. Thomas Bureau • Amadou Oury Diallo • Zoe Joly-Lopez • Ewa Forczek • Akiko Tomita • Douglas Hoen • CFI – Canada Foundation for Innovation • Genome Canada • Genome Quebec • Prof. Daniel Schoen • LemnaTec • Mark Romer

  23. HTS – sample identification system Mutant / tray Replicate / set Assay id Bar Code columns (0,0) Bar code reader (6,1) rows

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