Development of High Throughput Plant
Phenotyping Facilities at Aberystwyth
Catherine Howarth, Alan Gay, John Draper,
Tom Bartlett, John Doonan
www.phenomics.org.uk
Department of Aberystwyth University
formed in 2008 –
Combines Institute of Grassland and
Environmental Research (IGER),
Institute of Biological Sciences (IBS)
and Institute of Rural Sciences (IRS)
What is phenomics and why do we need it?
Phenotyping as a bottleneck in exploiting genomic information
Next gen sequencing techniques
allow economic and deep
genotyping of whole populations
Phenotyping remains either low throughput, or low content,
and can be variably subjective
– needs a step change to match genomics
Automated imaging
systems for
systematic
objective, high
content , non-
destructive plant
phenotyping
High value
populations
in many crops
& models
Genetic Diversity,
Populations
Genomic
information
Phenotypic
description
Linking
genes to traits
Strategic drivers for automated
high content plant phenotyping
Food security & climate change
► accelerated and more efficient breeding
BioEnergy & Industrial Biotechnology
► improved biomass accumulation and/or chemical composition
The National Plant Phenomics Centre (NPPC) at Aberystwyth
University is a significant investment by the BBSRC and the Welsh
Assembly Government in infrastructure and skills aimed at linking
genomic technologies to emerging computer-aided technologies for
plant phenotyping
Plant breeding programmes Oats
Forage legumes
• White and red clover
Forage and amenity
grasses
Miscanthus
Delivery mechanism for our
science
Cross
Segregating
Population
Genotype Phenotype
QTL
Gene
discovery New variety
Improving the phenotype is the ultimate
aim for plant breeders- this is not new!
Currently a breeder will select for a wide
range of traits in a range of
environments both by eye and
quantitatively
e.g: Height
Grain yield
Disease resistance
Flowering time
Grain quality
Need accurate, objective, rapid, high-throughput
screening of the phenotype
Development of
image analysis tools
D2365s1a.jpg labeled by cluster index from kmeans on RGB with six classes, colours 3, 4 and 6 combined
1 black: background
2 white: lighter green leaf
3, 4 and 6 green: normal leaf
5 blue: necrotic area of leaf
D:\paul\00 Est Pics for Alan\09 03 24 2TT 102_R1_DSCN7887.jpg threshold 45
NDVI for file O:\overflights\2006-06-02\Tynpyn Tynpynfarch_g.pix
oPt-172020.0A13AE03D20.7oPt-1652824.0oPt-1527129.9oPt-566434.3oPt-1643635.6AME153A oPt-16678oPt-8771 oPt-0526oPt-15971 oPt-14205oPt-6646
37.0
RV045437.9oPt-1431743.6oPt-1827743.8oPt-13185 oPt-12921oPt-16284 oPt-5431oPt-1373 oPt-1968oPt-9936 oPt-13230oPt-12704
46.2
EUTK47.0oPt-1234647.3oPt-1399947.6AM10250.8LAM9054.2
BT1
oPt-10396 oPt-90860.0oPt-17501 oPt-42921.0oPt-9019 oPt-119591.1oPt-9440 oPt-0075oPt-15874 oPt-8819
1.2
oPt-6949 oPt-158141.6oPt-16745 oPt-66362.0oPt-089830.1oPt-1670930.7oPt-1657832.4oPt-972473.1oPt-1661873.8oPt-1345474.5oPt-14690 oPt-848375.2oPt-10101 oPt-10632oPt-12991 oPt-15397oPt-16165 oPt-16431oPt-18281 oPt-3030oPt-4523 oPt-7417
75.8
oPt-819679.2oPt-1806989.4oPt-1670690.6oPt-1009292.0oPt-15990 oPt-1641oPt-17493
104.0
oPt-9132 oPt-14317105.0oPt-16678 AM102oPt-8771 oPt-18277oPt-12704 oPt-13230oPt-16885 oPt-18190
106.0
oPt-17202107.0oPt-6646 oPt-14144111.0oPt-5664112.0oPt-16436 oPt-0526oPt-12921 oPt-1373oPt-10013 oPt-13431oPt-15048 oPt-16979oPt-17223 oPt-2754oPt-4877 oPt-5642oPt-7238
114.0
oPt-17658 oPt-7774118.0oPt-12320 oPt-14316oPt-3348 oPt-7424oPt-9160
132.0
oPt-15453142.0oPt-8693143.0oPt-12339 oPt-5272144.0oPt-11426 oPt-11625146.0oPt-4939 oPt-5064oPt-9929
148.0
oPt-14108151.0oPt-6715155.0
KO22_44_18
oPt-9440 Cgc10.0oPt-6949 oPt-00753.2
LpHCA18z25.4
oPt-149400.0oPt-80331.5oPt-168283.9oPt-089810.1
BT16
RV1411x0.0
AM04.11616.6AM04.113 oPt-333721.0AM2324.1oPt-7716 A13AA07B25.0oPt-1479826.2oPt-646728.5oPt-1744036.2oPt-1145144.1
oPt-17430 oPt-166152.4oPt-1019054.7oPt-888657.0oPt-11795 oPt-1537760.4Bmag80863.1oPt-1483267.4RV0154X73.7oPt-0354 oPt-996282.2oPt-1322982.7
HVARGHN95.4oPt-693599.2
oPt-15127108.3
AGCCGCA132.5AggCggB138.3oPt-8744140.2ACTCGCAz MCgc1143.6
AHEAF03C155.5
BT3
oPt-1439517.8oPt-1522218.2oPt-632418.8oPt-1661 oPt-17430oPt-8886 oPt-9956
30.3
oPt-10190 oPt-14832oPt-0918
34.5
oPt-1032535.0oPt-675035.1oPt-874435.3oPt-811336.5oPt-1179537.4oPt-3337 oPt-7716oPt-15377
37.9
oPt-3655 oPt-69930.0oPt-5740 oPt-81863.3oPt-13747 oPt-1727211.3oPt-1346011.8oPt-613721.6oPt-10485 oPt-1590422.1oPt-1525722.3oPt-1618229.8oPt-408431.7oPt-002831.8oPt-2019 oPt-589731.9oPt-13973 oPt-14984oPt-14995 oPt-15647oPt-16107 oPt-16408oPt-16660 oPt-2978
32.0
oPt-14172 oPt-1786632.6oPt-696133.5oPt-521733.7oPt-723134.9oPt-927035.5oPt-399935.6oPt-360036.2oPt-693554.6
KO32
AM02A0.0
RV1411x53.8
AM04.11669.0
oP-_771683.2
Fesc1287.8
Bmag80892.8
RV0154X100.7
oPt-13229107.1
oPt-6935117.4HVARGHN121.2
oPt15127131.1
AM30B139.4
AHEAF03C148.2
ACTCGCAz157.1
oPt-8744161.2
AGCCGCA171.1AM04.113171.5
Gra
inW
idth
Gra
inL
en
gth
BT3
KO19_25_27
Imaging and
mapping of grain
dimensions
Extensive discussions with potential
users both at Aberystwyth and
elsewhere
What plant species?
Size, number, weight of plants?
Treatments required?
Requirement for flexibility
Capacity for future expansion
Development of NPPC at
Aberystwyth
Gogerddan Site – Campus Masterplan Option 1 8
NPPC Capabilities:
• Conveyor based system
• c900 radio-tagged carriages
• Automated delivery to imaging stations
A platform for non-destructive dynamic imaging of plant growth & development
• Climate controlled glasshouses
•High performance computational facilities to allow analysis, storage and retrieval of datasets
• Bio-informatics/ ontology framework
• Flexible layout:- randomisation in time and place
Layout
Imaging
suite
Spraying station
Smart House ~450 carriages
Loading/
sampling loop
Weigh and water point
NPPC: an infrastructure
for automated systematic trait measurement
Visual imaging
Dynamic measurement of leaf area
Plant “volume”-> estimate of biomass
Structure/development
Senescence, lesions/cell death
Relative chlorophyll content,
Far IR imaging
leaf temperature -> water use
Fluorescence imaging
Plant health
GFP
Near IR imaging
Tissue water content
Root imaging
Water use
Soil water content
Laser scanning
3-D plant morphology
5 automated imaging stations
Computer controlled weighing & watering station
Sampling suite
Links to other facilities and analyses available within
IBERS
chemical phenotyping and genotyping facilities in Aberystwyth.
Plants will be delivered on the conveyor system to a work station where plants can be sampled for DNA or metabolite analysis.
Samples will be taken from plants for analyses using infrared (IR), near-infrared (NIR) and mid-infrared Fourier-transform (FT-IR) spectroscopy and a range of mass spectroscopy techniques including
Computing science department with strong research interest in 3-D imaging
PYGCMS
Programmable pyrolysis on
continuously weighed samples
with gasses fed to a state of
the art GC/MS analyser. In
addition to
providing novel information on
cell wall composition this
instrumentation allows mass
closure and better
quantification than by using
pyrolysis alone.
FTIR/NIR
Near infrared and mid‐infrared
analyser with predictive tools
which allow estimation of cell
wall composition from
powdered
material. and measurement at
high‐throughput of cell wall
bound non‐lignin aromatics,
WSC and lipids
Micro‐Raman
Chemical mapping of fresh
samples e.g. leaves and
confocal fine mapping of
cryogenically sectioned
samples to a resolution of < 1
μm including sub surface
layers.
.
Combining Mapping Populations, Phenotyping and other data sets
to identify the underlying molecular basis of adaptation
• Mathematical/bio-info methods to link QTL data with other data sets such microarrays
(Gegas, Pesquet, Paul & Doonan, unpublished
• Incorporate climatic datasets to model possible explanatory factors (winter cold)
QTL
Chromosome
Expression
differences
Hypothesis – expression levels changes in response to
environment, maybe allowing northern plants to modulate their
growth depending on season
T-DNA in candidate gene
Wt
T-DNA
16oC 25oC
Can we extend this approach to other high value mapping populations
in a systematic manner using Phenomics?
What can we use this technology for?
What can we use this technology for?
Example: dissecting traits & biodiversity in cereals & grasses
Sphaerococcum
Capelle
- Many well-defined mapping populations available for
elite bread wheats
- Extensive biodiversity available (primitive strains,
landraces and wild relatives)
- Strategic species in terms of UK food security & climate
change: traits include yield, height, tillering, drought
tolerance
Genome currently being sequenced
Other cereals/grasses: oats, Lolium, Brachypodium
Timeline for NPPC development
2009 2010 2011 2012 2013 2014
Architect
Plans
Funding
agreed
Glasshouse
Build
Installation of
Robotics &
Imaging
Equipment
Commissioning
& testing
Pilot & full
experiments
Software
development
IBERS crop & model plants
Organisation and External access to the NPPC
Core phenotyping team
External interface
team
Image analysis, informatics, robotics and machine learning
Informatics databases, ontologies
External users (UK academics & agro-biotec
international
Scientific Advisory Board
Web site http://www.phenomics.org.uk
International access to the NPPC: EPPN, a FW7 transnational
access consortium 14 labs (inc 1 in Australia)
Aberystwyth NPPC:
1.Integration of biological and chemical phenomics
1.Development of laser scanning technologies
1.Calibrating technology for grasses & perennial
crops
2.Providing transnational access to NCCP
Phenotyping at different scales within IBERS
NPPC Public good
plant
breeding
Genomics
Forage grasses
Biofuel species
Cereals
Legumes
Field phenotyping
Ecology, Land
use and crop
management
Landscape &
environmental imaging
Controlled
environment
phenotyping
Mechanistic understanding of
Biological processes involved in:
Yield (= profit)
Secondary products
Resource use efficiency (N, P,
H2O)
Senescence/photosynthesis
Stress tolerance/response
Metabolomics
Centre
Data
Integration
(Bio-
informatics)
Need to validate results obtained in NPPC
with field data- can measurements on single
plants in a controlled environment translate
to plants in a field?
Need to design questions appropriate for use
of phenomics
Need to consider data analysis and storage-
converting data into information
• Keen to collaborate on phenotyping, image
analysis and software development to
maximise use of resources
• Also keen to explore possibilities of specific
links (joint experiments, proposals, develop
standards, algorithms, analyses ....)
Thank you
Web site http://www.phenomics.org.uk