McGill University - MP3 Location Montreal McGill Biology Building - PowerPoint PPT Presentation

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

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.  NIR Max. height for a plant 900 mm  VIS Max. width 600 mm  Max. width if all pots are filled: 240 mm  Weighing IR station Watering station

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

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

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 Plate support Capacity: 96 small pots Capacity: 60 square petri dishes

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

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

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

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?

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 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

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

Arsenic - Results 103 152 WT

Arsenic Mutant 152 Mutant 152 = ARS5 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 the success of the MP3.  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  CFI – Canada Foundation for  Prof . Thomas Bureau  Amadou Oury Diallo Innovation  Zoe Joly-Lopez  Genome Canada  Ewa Forczek  Genome Quebec  Akiko Tomita  Douglas Hoen  Prof. Daniel Schoen  LemnaTec  Mark Romer

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