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

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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

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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

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AM04.11669.0

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Fesc1287.8

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oPt-13229107.1

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oPt15127131.1

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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