Download Targeting soil pathogens – opportunities and challenges for plant

Targeting soil pathogens – opportunities
and challenges for plant biotechnology
Anne Osbourn – John Innes Centre
Some examples of soil-borne diseases
Rhizomania
Scab
Root rot
Nematodes
Vascular wilts
Soil-borne diseases
• Causal agents - viruses, bacteria,
fungi, oomycetes and nematodes
• Spread - vegetative growth, water
(propagules), vectors (insect,
nematode, fungal), or agricultural
practices (ploughing)
• The soil:
– Protects against temperature extremes,
water fluctuations, pesticides
– A competitive environment
The impact of climate change
Mild wet winters and drier
summers will favour pathogen
multiplication and symptom
development
UKCIP08 report
Impact on sustainability: e.g. take-all disease
• Poor nutrient status
encourages the disease
- Fertilisation required
• Diseased plants are unable to absorb
nutrients; mineral N accumulates in the
soil at harvest, leading to eutrophication
Nitrate
nitrous oxide
Potent greenhouse gas (300 x worse than CO2)
Methods for control:
•
•
•
•
Crop rotation
Pesticides
Biological control
Genetic resistance
Take-all disease of wheat:
•The most damaging root
disease of wheat worldwide
•The most widespread and
costly disease problem faced by
UK cereal growers
•Conservative estimate of takeall associated yield losses in the
UK £75 m - £300 m
Take-all severity increases in successive wheats
Yield
Take-all level
1
2
3
4
Take-all can make growing
second and subsequent
wheats unviable
5
Years of cereal cropping
Wheat area (million ha)
% following wheat
2007
1.83
42%
Harvest year
2008
2009 2020
2.08
1.95
?
35%
52%
?
Current methods for take-all control rely on:
• Crop rotation
• Fungicides
• Biological control
None of these methods
provide effective and
durable protection
L Thomashow & D Weller
J Bacteriol. 1988 August; 170(8): 3499–3508.
Potential sources of take-all resistance
60
s.e.d. 8.56
FPr<0.01
Ease of transfer
Take-all index (max. 100)
50
40
30
20
10
Aegilops
Triticum
Triticeae species
Transgenesis
Introgressions
Wild
emmer
Synthetics
Hexaploid
wheat
Traditional crossing
Oa
t
Rye
Ry
e
Oat
He
0
re w
ard
Ro
big
us
T.m
.M
DR
03
7
Tr
T.m itical
e
.M
DR
T.m
22
9
.M
DR
04
6
Degree of resistance?
Defining and deploying genetic resistance to take-all
Take-all LoLa
Extreme resistance
Characterised
Oat genes
Oat
Transformation (GM)
Terpene metabolic engineering
Rapid test of other cloned genes
Systematic screens
Triticeae spp.
Introduction into
hexaploid wheat and
validation
Sources of take-all
resistance
T. monococcum
(WGIN2)
Multi-gene
technology for
wheat
Mechanisms of
resistance
Ae. tauschii
Genetic architecture of
take-all resistance
QTL and fine-mapping
Genotyping platforms
Alien Introgression
Platform
Wheat pre-breeding programme (WISP)
Anne Osbourn, Cristobal Uauy, Chris Ridout - JIC;
Kim Hammond-Kosack and Richard Gutteridge - Rothamsted Research;
Emma Wallington, Andy Greenland – NIAB
Plant breeders
HGCA
Sustainable take-all
resistance
(Durability, stacking)
Introduction into
hexaploid wheat
(beyond lifetime of takeall LoLa)
5-7
MYA
Triticum urartu
(AUAU)
Triticum
monococcum
(AmAm)
400,000
years
eg. Ae. speltoides
(“BB”)
T. turgidum ssp.
dicoccoides (AABB)
Wild emmer
Ae. tauschii
(DD)
10,000
years
T. turgidum ssp.
durum (AABB)
T. aestivum
(AABBDD)
Effectiveness and nature of resistance
60
s.e.d. 8.56
FPr<0.01
Take-all index (max. 100)
50
40
A
B
C
30
20
t
Oa
Ry
e
He
0
re w
ard
Ro
big
us
T.m
.M
DR
03
7
T ri
t
ica
T.m
le
.M
DR
T.m
22
9
.M
DR
04
6
10
Hexaploid
wheat
Benchmarking against standards
Cytological/molecular characterisation of
resistance mechanisms
•Phenotypic characterization
•Genetic characterization, validation and deployment
Oats have extreme
resistance to take-all and
are used as a break crop
in rotations
Can we engineer wheat for take-all resistance?
Operon-like gene cluster
Control of take-all disease of wheat
Terpene toolkit
..and ultimately for other
complex multi-gene traits?
Genetic resistance for the control of take-all disease
of wheat
Non-GM
Promising leads
•John Innes Centre
•Rothamsted Research
•NIAB
•UK Plant Breeders
GM
Suite of different resistance
mechanisms
Extreme resistance
(genetically defined)
Take-all resistant wheat
•Conservative estimate, savings to UK wheat production > £75-300 m/annum
Take-all severity increases in successive wheats and
then declines (take-all decline – TAD)
Yield
Take-all level
1
2
3
4
5
Years of cereal cropping
Take-all isolates from field-grown wheat can be divided into
two subgroups of Gaeumannomyces graminis var. tritici (Ggt)
Genetic similarity (%)
80
85
90
95
100
G1
100
G2
Disease severity %
60
50
40
30
20
10
0
0
20
40
G2 frequency (%)
Adapted from Lebreton et al. (2004)
Environmental Microbiology 6:1174
Adapted from Lebreton et al. (2007)
Environmental Microbiology 9:492
60
Ggt population structure changes during take-all
epidemics in successive wheat crops
80
Isolate frequencies %
70
G1
R
G2
N
60
50
40
30
20
10
0
1st
3rd
Wheat crop
Adapted from Lebreton et al. (2007)
Environmental Microbiology 9:492
4th
6th
Take-all inoculum build-up (TAB)
Large plots of Avalon x Cadenza DH mapping
lines grown as a 1st wheat, then the entire
field over-sown with wheat
WGIN
TSB
Each QTL results in a considerable
yield increase
Avalon x Cadenza
62 DH
lines + 4lines
parental
seed multiplication
plots
Avalon
x Cadenza
in 2008,asoversown
with
in
2008,
sown
withRelationship
Oakley in between
2009
wheat
cv. over
Oakley
in 2009.
take-all patch score and yield
Relationship between take-all patch score and yield.
11
Cadenza
Avalon
10
R = 0.9245
Yield t/ha
9
8
7
6
5
4
0
20
40
60
80
100
Take-all patch score (% area of plot affected)
120
Genotype x environment interactions
From: Hardoim et al., Trends Microbiol (2008) 16: 463-471
1011 stars in our galaxy
Slide: Eddy Rubin, Joint Genome
Initiative, Walnut Creek, US
3/4 of sequenced genomes belong to just three
bacterial phyla
bacterial and archaeal phyla with Easy to culture isolates
Slide: Eddy Rubin, Joint Genome
Initiative, Walnut Creek, US
Phylum Level Soil v Wheat Rhizosphere
20000
18000
# Reads Assigned
16000
14000
12000
10000
8000
6000
Soil Mean Reads
Wheat Mean Reads
4000
2000
0
Phil Poole, JIC
# Hits
MG_RAST Metabolic Profiling
300
250
200
150
100
50
0
Subsystem Hierachy 1
176 reads in 13 other Subsystems
Phil Poole, JIC
Recent advances in epidemiological modelling:
Soil-borne pathogens
Modelling scale effects from
small scale to plant, patch, field
and regional
Epidemiological and Modelling
University of Cambridge: Prof Chris Gilligan
What modelling will enable us to do:
• Integrate a range of complex processes
• Identify when a chemical or genetic
“treatment” is likely to have a significant
effect on epidemic development
• Assess the likely effects of selection pressure
Towards disease control
• Exploit genetic resistance
• Understand mechanisms of disease
suppression/enhancement
• Understand broader genotype x environment
interactions (root exudates, rhizobiome)
• Exploit predictive modelling
• Explore other potential strategies for
engineered disease resistance, e.g. PAMPtriggered plant immunity