Mc Gill Plant Phenomics Platform MP 3 Emilio

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Mc. Gill Plant Phenomics Platform - MP 3 Emilio Vello

Mc. Gill Plant Phenomics Platform - MP 3 Emilio Vello

Overview What tools do we use to get the phenotyping data? Greenhouse Lemna. Tec

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

Mc. Gill University - MP 3 Location Montreal Greenhouse Montreal Weather http: //blogs. mcgill.

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

Lemnatec Scanalyzer 3 D Plant Phenomics 2. 3 m 3. 0 m 3. 8

Lemnatec Scanalyzer 3 D Plant Phenomics 2. 3 m 3. 0 m 3. 8 m C a m e r a s Conveyor. Plants Cars “parking” Working Area – Load station Watering and weighing station

3 D-Components Features: NIR VIS IR Top and Side views Angles from 0° to

3 D-Components Features: NIR VIS IR 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 Watering station Weighing station

3 D – Pots, support and Identification 3 D pot registration screen Plant pot

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

Lemnatec Scanalyzer HTS – highthroughput screening Sensor arm Growth chambers 1. 10 m 3.

Lemnatec Scanalyzer HTS – highthroughput screening Sensor arm Growth chambers 1. 10 m 3. 00 m 1. 95 m Close to minimize plant movements Growth chambers

HTS-Sensors Sensor Function Near Infrared Water content Infrared Temperature Fluorescence Chlorophyll Visual or RGB

HTS-Sensors Sensor Function Near Infrared Water content Infrared Temperature Fluorescence Chlorophyll Visual or RGB Architecture Laser scanner Height

HTS-Plant supports Pot support / Free format support Capacity: 96 small pots Plate support

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

HTS - Lights Camera Near infrared light Fluorescent light Ring light Top visible light

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

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

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

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

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

Arsenic Tolerance Objective: Identification of DNA target candidates showing a significant resistance or Experimental

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

Arsenic – Safety The plates covers can't be removed because of the arsenic toxicity

Arsenic – Safety The plates covers can't be removed because of the arsenic toxicity following the rule of the EHS. (Mc. Gill 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?

Arsenic – Image acquisition configuration Fluorescent light 1 frame 1 plate Visible bottom light

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

Arsenic – Image Analysis Pipeline RGB selection raw object list creation Mc. Gill development

Arsenic – Image Analysis Pipeline RGB selection raw object list creation Mc. Gill development using java, Image. J libraries and R Object size > 10 px Object circularity > 0. 099 d(centroid, square. Center)<130 Big Object HUE(HSB) 16 colour classification Object properties / features

Arsenic - Clustering 1 2 Euclidean distance matrix 3 Hierarchical cluster Ward's minimum variance

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

Arsenic – Cluster Interpretation 103 Group 2 = Sensitive = Non Germination WT 152

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

Arsenic - Results 103 152 WT

Arsenic - Results 103 152 WT

Arsenic Mutant 152 = ARS 5 is the strongest arsenic resistant mutant identified by

Arsenic Mutant 152 = ARS 5 is the strongest arsenic resistant mutant identified by Sung et al.

Conclusion Integration and contribution of people from different domains have been a key for

Conclusion Integration and contribution of people from different domains have been a key for the success of the MP 3. Integration is also true for the different tools use in the digital phenotyping including hardware, software. we need to find new metrics from different kind of sensors to increase the spectrum of phenotypes.

Acknowledgements Prof. Thomas Bureau Amadou Oury Diallo Zoe Joly-Lopez Ewa Forczek Akiko Tomita Douglas

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 Lemna. Tec Prof. Daniel Schoen Mark Romer

HTS – sample identification system Mutant / tray Replicate / set Assay id Bar

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