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

McGill University - MP3 Location

http://www.hrviews.ca http://blogs.mcgill.ca/iss/category/winter/

Montreal

Greenhouse McGill Biology Building Montreal Weather

• 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.



• Max. height for a plant 900 mm



• Max. width 600 mm



• Max. width if all pots are filled: 240 mm

Watering station Weighing station

NIR

VIS

IR

3D – Pots, support and Identification

3D pot registration screen Plant pot support adapters

Small Medium Large

Lemnatec Scanalyzer HTS – high- throughput screening

Growth chambers Growth chambers

Close to minimize plant movements 1.95 m 1.10 m 3.00m

Sensor arm

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 Capacity: 60 square petri dishes

HTS - Lights

 Near infrared light  Fluorescent light  Ring light  Top visible light  Bottom visible light

Bottom light Camera

HTS – sample identification system

Barcode reader

Assay ID Replicate / set Mutant / tray

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

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 1 frame 1 plate Visible bottom light 4 frames 1 plates

2448 images in total.

Arsenic – Image Analysis Pipeline

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

Arsenic - Clustering

Euclidean distance matrix Hierarchical cluster

Ward's minimum variance method

Group 1 Group 2

1 2 3 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

 Prof. Thomas Bureau

 Amadou Oury Diallo  Zoe Joly-Lopez  Ewa Forczek  Akiko Tomita  Douglas Hoen  CFI – Canada Foundation for

Innovation

 Genome Canada  Genome Quebec  LemnaTec  Prof. Daniel Schoen  Mark Romer

HTS – sample identification system

Bar Code

columns rows

(6,1) (0,0)

Bar code reader Assay id Replicate / set Mutant / tray