Presented at the ICPP2018 International Congress of Plant Pathology Plenary Session - Plant Health is Earth’s Wealth, Monday, July 30, 2018. See notes and acknowledgments at http://kamounlab.tumblr.com/post/176385835530/the-edge-of-tomorrow-plant-health-in-the-21st

1. The Edge of Tomorrow -
Plant Health in the 21st Century
Sophien Kamoun
http:KamounLab.net
@KamounLab

2. The Edge of Tomorrow -
Plant Health in the 21st Century
Sophien Kamoun
http:KamounLab.net
@KamounLab

3. Pathogens are a recurrent threat to agriculture…

4. …and to the environment

5. Plant Health in the 21st Century
•Plant pathology as a modern and
dynamic branch of biology
•Knowledge and approaches we
didn't have a few years ago
•Opportunities and challenges

6. proportion against the total number of disease alerts, and discriminated
between plant- or animal-associated fungal pathogens (Supplementary
Table 2). We also searched the primary research literature for reports in
which EIDs have caused host extinction events, either at the regional
scale (extirpations) or globally (Supplementary Table 3). These analyses
show a number of positive trends associated with infectious fungi.
Overall, fungal alerts comprise 3.5% of the ,38,000 ProMED records
screened. However, over the period from 1995 to 2010, the relative
proportion of fungal alerts increased in the ProMED database from
1% to 7% of the database total (Fig. 1a and Supplementary Table 2).
This trend is observed for both plant-infecting (0.4% to 5.4%) and
animal-infecting (0.5% to 1.4%) fungi. HealthMap shows a recent
(2007–11) positive trend in the proportion of records of fungi infecting
animals (0.1% to 0.3%) and plants (0.1 to 0.2%), and fungal disease alerts
previously noted patterns in hum
trends are real. Therefore, the a
the data do indeed support the
plant and animal biodiversity
pathogen and hosts, and that th
Fungal-disease dynamics
Here we illustrate several key bio
to the epidemiological dynamics
disease emergence and host exti
High virulence
Fungi, like some bacterial and v
naive hosts with rates of mort
0
1
2
3
4
5
6
7
Percentageoftotalalerts
Plant-infecting
fungi
Animal-
infecting fungi
a b Figure
EIDs.
for path
the spa
(b). c, d
and/or
infectio
trends
sources
Inform
Plant disease outbreaks have increased in frequency…
•Increased global trade
•Climate change
•Pathogen host-jumps
This trend is observed for both plant-infecting (0.4% to 5.4%) and
animal-infecting (0.5% to 1.4%) fungi. HealthMap shows a recent
(2007–11) positive trend in the proportion of records of fungi infecting
animals (0.1% to 0.3%) and plants (0.1 to 0.2%), and fungal disease alerts
High virule
Fungi, like s
naive hosts
0
1
2
3
4
5
6
7
Percentageoftotalalerts
Year
Plant-infecting
fungi
Animal-
infecting fungi
Fungi
Protist
Viruses
Bacteria
Helminth
Other
0
5
10
15
20
25
30
35
Numberofextinction
orextirpationevents
a b
c d
1995
2000
2005
2010
1900–201920–401940–601960–80
1980–2000
2000–
Year
i
st
es
eria
minth
r
1 8 8 | N A T U R E | V O L 4 8 4 | 1 2 A P R I L 2 0 1 2
Macmillan Publishers Limited. All righ©2012
NATURE.COM/NATURE
12 April 2012 £10
Vol. 484, No. 7393
MEDICAL RESEARCH
CHILDREN OF
THE NINETIES
Pioneering birth cohort
study comes of age
PAGE155
FICTION
TO GREECE VIA
COPENHAGEN
Michael Frayn on science,
farce and uncertainty
PAGE163
INNOVATION
SCIENCE MEANS
BUSINESS
Getting to grips with
technology transfer
PAGE2XX
THE NINETIES
Pioneering birth cohort
COP
Michael Frayn on science,
farce and uncertainty
THE INTERNATIONAL WEEKLY JOURNAL OF SCIENCE
FEAR OF FUNGIEmerging pathogens threaten natural
ecosystems and food security PAGE186

7. …yet many new outbreaks remain undiagnosed

8. We can’t afford to wait…
…genomes of emerging plant
pathogens need to be
immediately sequenced and
released to public domain as is
routinely done with human
pathogens
140
MICROBIOLOGYTODAYMAY2012
LAST YEAR during a visit to Colombia’s Zona Cafetera,
my host singled out one coffee farm amid the enchanting
rolling hills. That farm’s owner may have looked like the iconic
Juan Valdez, but he is far from being cherished by his ‘cafeteros’
colleagues. He is infamous for having brought into Colombia
a few coffee plants from Brazil. Unbeknown to him, a few
leaves bore small orange spots, the telltale sign of the terrible
coffee rust fungus, Hemileia vastatrix. Ever since that fateful
introduction in 1983, Colombian cafeteros have struggled
with managing this formidable foe. In recent years, after a brief
lull, coffee rust came back with a vengeance casting a shadow
on a critical Colombian agroindustry just as the country was
emerging from years of social instability.
The history of agriculture is replete with sorry tales like
the one of ‘la roya del café’. From the upheaval caused by the
Irish potato famine pathogen to recent epidemics such as
wheat yellow rust, sudden oak death and horse chestnut
canker, the British Isles have seen their share of plant pathogen
introductions. Elsewhere, emerging infectious plant diseases
cause havoc to world agriculture and threaten to slow laudable
efforts to launch a second green revolution to meet the food
security needs of a booming world population.
When faced with opponents like these, we need to know
SOPHIEN KAMOUN
Many of the plant patholo
the epidemics are not pro
genome data and may not b
funds. We simply cannot aff
plant pathogens need to
released into the public d
human pathogens.
A few months ago, I w
colleagues accessed within d
sequence of the Escherichia co
50 people in Germany. Th
genome analysis, during w
pored over the freely availab
their results on the internet,
similar exercise is yet to hap
Meanwhile, back in
scrape together enough fu
genome of the coffee rust
Bill Gates’ recent call to a
research, a philosophy we h
bury Laboratory over our
first – lets get the basics in p
and important plant patho
of emerging
plant
pathogens:
too little,
too late
We need to rapidly sequence and
the genomes of emerging plant pat
Food security and environmental prese
hang in the balance.
140
ICROBIOLOGYTODAYMAY2012
LAST YEAR during a visit to Colombia’s Zona Cafetera,
my host singled out one coffee farm amid the enchanting
rolling hills. That farm’s owner may have looked like the iconic
Juan Valdez, but he is far from being cherished by his ‘cafeteros’
colleagues. He is infamous for having brought into Colombia
a few coffee plants from Brazil. Unbeknown to him, a few
leaves bore small orange spots, the telltale sign of the terrible
coffee rust fungus, Hemileia vastatrix. Ever since that fateful
introduction in 1983, Colombian cafeteros have struggled
with managing this formidable foe. In recent years, after a brief
lull, coffee rust came back with a vengeance casting a shadow
on a critical Colombian agroindustry just as the country was
COMMENT
SOPHIEN KAMOUN
Many of the plant pathologists that sit on the front line of
the epidemics are not properly trained to fully exploit the
genome data and may not be inclined to lobby for sequencing
funds. We simply cannot afford to wait. Genomes of emerging
plant pathogens need to be immediately sequenced and
released into the public domain as is routinely done with
human pathogens.
A few months ago, I watched in awe as my bacteriologist
colleagues accessed within days of the first reports the genome
sequence of the Escherichia coli O104:H4 strain that killed about
50 people in Germany. The following ‘crowdsourcing’ of the
genome analysis, during which scientists around the world
Coffee berries. iStockphoto / Thinkstock
Genomics
of emerging
plant
pathogens:
too little,
too late
We need to rapidly sequence and release
the genomes of emerging plant pathogens.
Food security and environmental preservation
hang in the balance.

9. Genomics surveillance of plant pathogens
•More data —1000x
•Speed is critical
•Genome sequences directly from
the field
•Integrate genomics with other
types of data
•Open science and crowdsourcing
“Building resilience against crop diseases: a g
Rockefeller Conference Cent
Date: 12 to 16 Febru
Introduction
Crop diseases constantly affect farmers, consumers and societie
in product costs and damage to the environment and to human
globalization, industrialization of food production systems and c
emerging diseases. During 2015, a Cassava mosaic disease (CMD
cassava mosaic virus, was reported in cassava fields in Ratanakir
commodity for Cambodia and one of the most important crops i
Cambodia, a fungal disease outbreak was reported affecting
Magnaporthe oryzae. The disease emerged across eight district
causing yield losses reaching up to 100%. Moreover, a 2016 outb
a highly virulent race of the pathogen is posing a threat to crops
season. Early detection is essential to the control of emerging,
naturally occurring or intentionally introduced. However, to av
emergence of new ones in a profoundly interconnected world
signs of an outbreak, a rapid recognition of its presence, reliable
an appropriate and efficient response are urgently required.
conference in Bellagio will bring together experts in genetics
epidemiology, climate change, metadata analysis, geospatial a
synthesize, and share knowledge about emerging infectious dise
Main objectives
Reach a common understanding of the current situ
Identify gaps and consider how best to fill them
Listen to and discuss new relevant expertise/appro
Agree on the building blocks of a system for enhan
Develop the outline of a strategic plan
Discuss ideas for implementation
Review how to disseminate information and engag

12. elifesciences.org
FEATURE ARTICLE
CUTTING EDGE
Lessons from Fraxinus,
a crowd-sourced citizen
science game in genomics
Abstract In 2013, in response to an epidemic of ash dieback disease in England the previous ye
launched a Facebook-based game called Fraxinus to enable non-scientists to contribute to gen
studies of the pathogen that causes the disease and the ash trees that are devastated by it.
a period of 51 weeks players were able to match computational alignments of genetic sequen
78% of cases, and to improve them in 15% of cases. We also found that most players were o
transiently interested in the game, and that the majority of the work done was performed by a
group of dedicated players. Based on our experiences we have built a linear model for the len
time that contributors are likely to donate to a crowd-sourced citizen science project. This m
could serve a guide for the design and implementation of future crowd-sourced citizen scienc
initiatives.
DOI: 10.7554/eLife.07460.001
GHANASYAM RALLAPALLI, FRAXINUS PLAYERS, DIANE GO SAUNDERS,
KENTARO YOSHIDA, ANNE EDWARDS, CARLOS A LUGO, STEVE COLLIN,
BERNARDO CLAVIJO, MANUEL CORPAS, DAVID SWARBRECK, MATTHEW CLA
J ALLAN DOWNIE, SOPHIEN KAMOUN, TEAM COOPER AND DAN MACLEAN
Introduction
Ash dieback is a disease caused by the fungal
pathogen Hymenoscyphus fraxineus, and it has
devastated populations of ash trees (Fraxinus
excelsior) across Europe in recent years. When
ash dieback was discovered in the wild in the
east of England for the first time, in 2012, the
present authors set up the OpenAshDieBack
(OADB) project as a crowdsourcing platform to
allow scientists across the world to contribute
to the genomic analysis of the pathogen and
the host (MacLean et al., 2013). Subsequently,
we developed and released Fraxinus, a Face-
book-based game, to allow non-specialists to
sequence is often considered to be a refe
sequence that should not be altered. The
cess of alignment requires the best o
match between the two sequences to be
first: this ‘global alignment’ is then follow
a finer-grained ‘local alignment’ that inv
modifying the short sequences by, for exa
inserting small gaps or deleting short stre
of the sequence.
Alignment is a computationally intensive
cess, and many computer programs (e.g.,
aligner [Li and Durbin, 2009]) have been de
that implement and optimize alignments ac
ing to various measures of similarity. A str
*For correspondence:
dan.maclean@tsl.ac.uk
Present address: †
Laboratory of
Plant Genetics, Kobe University,
Kobe, Japan
COMMENTARY Open Access
Crowdsourcing genomic analyses of ash and ash
dieback – power to the people
Dan MacLean1*
, Kentaro Yoshida1
, Anne Edwards2
, Lisa Crossman3
, Bernardo Clavijo3
, Matt Clark3
,
David Swarbreck3
, Matthew Bashton4
, Patrick Chapman5
, Mark Gijzen5
, Mario Caccamo3
, Allan Downie2
,
Sophien Kamoun1
and Diane GO Saunders1
Abstract
Ash dieback is a devastating fungal disease of ash trees that has swept across Europe and recently reached the UK.
This emergent pathogen has received little study in the past and its effect threatens to overwhelm the ash
population. In response to this we have produced some initial genomics datasets and taken the unusual step of
releasing them to the scientific community for analysis without first performing our own. In this manner we hope
to ‘crowdsource’ analyses and bring the expertise of the community to bear on this problem as quickly as possible.
Our data has been released through our website at oadb.tsl.ac.uk and a public GitHub repository.
Keywords: Crowdsource, Genomics, Ash dieback, Open source, Altmetrics
Main text
oadb.tsl.ac.uk: A new resource for the crowdsourcing of
genomic analyses on ash and ash dieback
Ash dieback is a devastating disease of ash trees caused
by the aggressive fungal pathogen Chalara fraxinea.
This fungus emerged in the early 1990s in Poland and
has since spread west across Europe reaching native for-
ests in the UK late last year. The emergence of Chalara
in the UK caused public outcry where up to 90% of the
more than 80 million ash trees are thought to be under
threat. The disease, which is a newcomer to Britain, was
first reported in the natural environment in October
2012 and has since been recorded in native woodland
throughout the UK. There is no known treatment for
ash dieback, current control measures include burning
infected trees to try and prevent spread [1] and the
implications for the UK environment and the economy
remain stark.
To kick start genomic analyses of the pathogen and
host, we took the unconventional step of rapidly gener-
ating and releasing genomic sequence data. We released
the data through our new ash and ash dieback website,
oadb.tsl.ac.uk, which we launched in December 2012.
Speed is essential in responses to rapidly appearing and
threatening diseases and with this initiative we aim to
make it possible for experts from around the world to
access the data and analyse it immediately, speeding up
the process of discovery. We hope that by providing data
as soon as possible we will stimulate crowdsourcing and
open community engagement to tackle this devastating
pathogen.
The transcriptomics and genomics data we have released
so far
We have generated and released Illumina sequence data
of both the transcriptome and genome of Chalara and
the transcriptome of infected and uninfected ash trees.
We took the unusual first step of directly sequencing the
“interaction transcriptome” [2] of a lesion dissected from
an infected ash twig collected in the field. This enabled
us to respond quickly, generating useful information
without time-consuming standard laboratory culturing;
the shortest route from the wood to the sequencer to
the computer.
The Chalara transcriptome data, generated at The
Sainsbury Laboratory (TSL, Norwich, UK) was derived
from two infected ash samples collected at Ash-
wellthorpe Lower Wood, near Norwich; the location of
the first confirmed case of ash dieback in the wild in the
* Correspondence: dan.maclean@sainsbury-laboratory.ac.uk
1

13. 30/03/2016 11:32Infected wheat plants on 357 acres destroyed | Daily sun
Update : 2016-03-28 23:35:37
‘Wheat Blast’
Infected wheat plants on 357 acres destroyed
A Correspondent
News (/News)
First report of blast disease on wheat in South Asia
By International Society for Infectious Diseases April 12, 2016 | 8:11 am EDT
NEWS " QUOTES + WEATHER " RESOURCE CENTERS " AGPRO UNIVERSITY " V
18/04/2016 12:06Wheat blast affects 15,500 hectares of land in 5 dists | The Daily Star
Home ∠ Country
12:00 AM, April 14, 2016 / LAST MODIFIED: 12:00 AM, April 14, 2016
Wheat blast affects 15,500
hectares of land in 5 dists
Crop worth Tk 130 crore damaged as the disease appears first time in the SW region
News (/News)
First report of blast disease on wheat in South Asia
By International Society for Infectious Diseases April 12, 2016 | 8:11 am EDT
Diseased wheat spikes carry shriveled or no grain at all.
One of the most fearsome and intractable wheat diseases in recent decades is wheat blast. First sighted in Brazil in 1985, blast is widespread
in South American wheat fields, affecting as much as 3 million hectares [about 7.4 million acres] in the early 1990s and seriously limiting the
potential for wheat cropping on the region's vast savannas. Currently, most [wheat] varieties being planted are susceptible and fungicides
have not been effective in controlling the disease.
Experts had feared the possible spread of blast from Latin America to regions of Africa and Asia where conditions are similar. A severe
outbreak of blast in key wheat districts of southwestern Bangladesh in early 2016 has confirmed the truth of these predictions. The
consequences of a wider outbreak in South Asia could be devastating to a region of 300 million people who consume over 100 million tons of
wheat each year.
For more detail regarding wheat blast disease, suggested control measures, and links to selected scientific literature, click here
(http://wheat.org/wp-content/uploads/sites/4/2016/04/Wheat-Blast-Priority-Brief-web-07Apr2016.pdf).
Wheat blast (or "brusone" in South America) is caused by the fungus _Pyricularia oryzae_ (synonym _Magnaporthe oryzae_, previously
classified as a strain of _M. grisea_). Although the fungus is currently classified as the same species as the one that causes rice blast, the wheat
blast pathogen is a distinct population (referred as _P. oryzae_ Triticum population) and does not cause disease in rice.
Over 50 species of grasses and sedges can be affected by related fungal strains which appear to be highly variable favouring the emergence of
new strains. Further work is needed regarding genotypic differentiation related to host range, including differences between the wheat and
rice pathovars. Wheat blast is now considered an emerging disease and a threat to global food security.
Blast symptoms on wheat (and barley) may be confused with fusarium head blight (see previous ProMED-mail posts in the archives and
AG PROFESSIONAL
(/) Search
NEWS " QUOTES + WEATHER " RESOURCE CENTERS " AGPRO UNIVERSITY " VIDEO "
18/04/2016 12:07'Wheat blast' threatens yield | The Daily Star
Amanur Aman
Wheat blast
disease has
become a serious
threat to grain
quality and yield,
Home ∠ Back Page
12:00 AM, March 01, 2016 / LAST MODIFIED: 03:44 AM, March 01, 2016
'Wheat blast' threatens yield
Farmers in 6 districts complain of infection
" NEWSPAPER BUSINESS OPINION SPORTS A & E LIFESTYLE BYTES SHOWBIZ SHOUT
EPAPER ALL SECTIONS

14. Field collection: March 16
RNA extractions, library
construction: March 24-31 Daniel Croll’s report: April 27
OWB Live! April 18
Field collection to genome analysis: 6 weeks

15. Field collection: March 16
RNA extractions, library
construction: March 24-31 Daniel Croll’s report: April 27
OWB Live! April 18
Field collection to genome analysis: 6 weeks
Emergence of wheat blast in Bangladesh was caused by a South American lineage of Magnaporthe oryzae | bioRxiv
HOME | ABOUT | SUBMIT |
Search
New Results
Emergence of wheat blast in Bangladesh was caused by a South American
lineage of Magnaporthe oryzae
Tofazzal Islam, Daniel Croll, Pierre Gladieux, Darren Soanes, Antoine Persoons, Pallab
Bhattacharjee, Shaid Hossain, Dipali Gupta, Md. Mahbubur Rahman, M Golam Mahboob,
Nicola Cook, Moin Salam, Vanessa Bueno Sancho, Joao Nunes Maciel, Antonio Nani,
Vanina Castroagudin, Juliana Teodora de Assis Reges, Paulo Ceresini, Sebastien Ravel, Ronny
Kellner, Elisabeth Fournier, Didier Tharreau, marc-henri Lebrun, Bruce McDonald, Tim
Stitt, Daniel Swan, Nicholas Talbot, Diane Saunders, Joe Win, Sophien Kamoun
doi: http://dx.doi.org/10.1101/059832
○ Previous
Posted June 19, 20
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Advanc
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" Preview PDF
e of wheat blast in Bangladesh was caused by a South American
Magnaporthe oryzae
am, Daniel Croll, Pierre Gladieux, Darren Soanes, Antoine Persoons, Pallab
Shaid Hossain, Dipali Gupta, Md. Mahbubur Rahman, M Golam Mahboob,
Moin Salam, Vanessa Bueno Sancho, Joao Nunes Maciel, Antonio Nani,
gudin, Juliana Teodora de Assis Reges, Paulo Ceresini, Sebastien Ravel, Ronny
abeth Fournier, Didier Tharreau, marc-henri Lebrun, Bruce McDonald, Tim
Swan, Nicholas Talbot, Diane Saunders, Joe Win, Sophien Kamoun
oi.org/10.1101/059832
eprint and has not been peer-reviewed [what does this mean?].
Info/History Metrics Data Supplements
ry 2016, a new fungal disease was spotted in wheat fields across eight
○ Previous
Subject Areas
All Articles
Posted June 19, 2016.
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Plant Biology

16. Field collection: March 16
RNA extractions, library
construction: March 24-31 Daniel Croll’s report: April 27
OWB Live! April 18
Field collection to genome analysis: 6 weeks
Emergence of wheat blast in Bangladesh was caused by a South American lineage of Magnaporthe oryzae | bioRxiv
HOME | ABOUT | SUBMIT |
Search
New Results
Emergence of wheat blast in Bangladesh was caused by a South American
lineage of Magnaporthe oryzae
Tofazzal Islam, Daniel Croll, Pierre Gladieux, Darren Soanes, Antoine Persoons, Pallab
Bhattacharjee, Shaid Hossain, Dipali Gupta, Md. Mahbubur Rahman, M Golam Mahboob,
Nicola Cook, Moin Salam, Vanessa Bueno Sancho, Joao Nunes Maciel, Antonio Nani,
Vanina Castroagudin, Juliana Teodora de Assis Reges, Paulo Ceresini, Sebastien Ravel, Ronny
Kellner, Elisabeth Fournier, Didier Tharreau, marc-henri Lebrun, Bruce McDonald, Tim
Stitt, Daniel Swan, Nicholas Talbot, Diane Saunders, Joe Win, Sophien Kamoun
doi: http://dx.doi.org/10.1101/059832
○ Previous
Posted June 19, 20
Tweet
Subject Area
Download PD$
Email%
Advanc
Search
" Preview PDF
e of wheat blast in Bangladesh was caused by a South American
Magnaporthe oryzae
am, Daniel Croll, Pierre Gladieux, Darren Soanes, Antoine Persoons, Pallab
Shaid Hossain, Dipali Gupta, Md. Mahbubur Rahman, M Golam Mahboob,
Moin Salam, Vanessa Bueno Sancho, Joao Nunes Maciel, Antonio Nani,
gudin, Juliana Teodora de Assis Reges, Paulo Ceresini, Sebastien Ravel, Ronny
abeth Fournier, Didier Tharreau, marc-henri Lebrun, Bruce McDonald, Tim
Swan, Nicholas Talbot, Diane Saunders, Joe Win, Sophien Kamoun
oi.org/10.1101/059832
eprint and has not been peer-reviewed [what does this mean?].
Info/History Metrics Data Supplements
ry 2016, a new fungal disease was spotted in wheat fields across eight
○ Previous
Subject Areas
All Articles
Posted June 19, 2016.
Tweet 0LikeLike
Subject Area
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RESEARCH ARTICLE Open Access
Emergence of wheat blast in Bangladesh
was caused by a South American lineage of
Magnaporthe oryzae
M. Tofazzal Islam1*
, Daniel Croll2
, Pierre Gladieux3
, Darren M. Soanes4
, Antoine Persoons5
, Pallab Bhattacharjee1
,
Md. Shaid Hossain1
, Dipali Rani Gupta1
, Md. Mahbubur Rahman1
, M. Golam Mahboob6
, Nicola Cook5
,
Moin U. Salam7
, Musrat Zahan Surovy1
, Vanessa Bueno Sancho5
, João Leodato Nunes Maciel8
,
Antonio NhaniJúnior8
, Vanina Lilián Castroagudín9
, Juliana T. de Assis Reges9
, Paulo Cezar Ceresini9
,
Sebastien Ravel10
, Ronny Kellner11,12
, Elisabeth Fournier3
, Didier Tharreau10
, Marc-Henri Lebrun13
,
Bruce A. McDonald2
, Timothy Stitt5
, Daniel Swan5
, Nicholas J. Talbot4
, Diane G. O. Saunders5,14
, Joe Win11
and
Sophien Kamoun11*
Abstract
Islam et al. BMC Biology (2016) 14:84
DOI 10.1186/s12915-016-0309-7

17. Field pathogenomics (RNAseq) of symptomatic vs
asymptomatic wheat leaves from Bangladesh
0.5% align to M. oryzae 18.6% align to M. oryzae

18. Wheat blast outbreak was caused by a South
American lineage of Magnaporthe oryzae

19. Multiplex amplicon sequencing for genotyping Bangladesh
samples — Has the wheat blast lineage jumped to other hosts?
85 SNPs
BD

20. NLR$%
triggered%
immunity%
effectors%
bacterium%
fungus%
oomycete%
haustorium%
NB$LRR%
immune%receptors%plant%cell%
pathogen)associated.
molecular.pa3erns.(PAMPs).
Pa3ern.recogni9on.
receptors.(PRRs).
PRR#$
triggered$
immunity$
How to exploit basic knowledge to
address emerging plant diseases?
Pathogen and host genomes
Integrated conceptual model
increased numbers of mobile elements across diverse families as
compared to P. sojae and P. ramorum, with ,5 times as many LTR
retrotransposons and ,10 times as many helitrons (Supplemen-
tary Fig. 7).
Consistentwithamodelofrepeat-driven expansionoftheP.infestans
genome, the vast majority of repeat elements in the genome are highly
similar to their consensus sequences, indicating a high rate of recent
transposon activity (Supplementary Fig. 8). In addition, we have
observed and experimentally confirmed examples of recently active
elements (Supplementary Figs 9–11).
Phytophthora species, like many pathogens, secrete effector
proteins that alter host physiology and facilitate colonization. The
genome of P. infestans revealed large complex families of effector
genes encoding secreted proteins that are implicated in patho-
genesis10
. These fall into two broad categories: apoplastic effectors
that accumulate in the plant intercellular space (apoplast) and cyto-
plasmic effectors that are translocated directly into the plant cell by a
specialized infection structure called the haustorium11
. Apoplastic
effectors include secreted hydrolytic enzymes such as proteases,
lipases and glycosylases that probably degrade plant tissue; enzyme
inhibitors to protect against host defence enzymes; and necrotizing
pseudogenes (Supplementary Table 9). This high turnover in
Phytophthora is probably driven by arms-race co-evolution with host
plants5,13,14,17
.
RXLR effectors show extensive sequence diversity. Markov cluster-
ing (TribeMCL18
) yields one large family (P. infestans: 85, P. ramorum:
75, P. sojae: 53) and 150 smaller families (Supplementary Fig. 14). The
largest family shares a repetitive C-terminal domain structure
(Supplementary Figs 15 and 16). Most families have distinct sequence
homologies (Supplementary Fig. 14) and patterns of shared domains
(Supplementary Fig. 17) with greater diversity than expected if all
RXLR effectors were monophyletic.
In contrast to the core proteome, RXLR effector genes typically
occupy a genomic environment that is gene sparse and repeat-rich
(Fig. 2g and Supplementary Figs 18 and 19). The mobile elements
contributing to the dynamic nature of these repetitive regions may
enable recombination events resulting in the higher rates of gene gain
and gene loss observed for these effectors.
CRN cytoplasmic effectors were originally identified from P. infestans
transcripts encoding putative secreted peptides that elicit necrosis
in planta, a characteristic of plant innate immunity19
. Since their dis-
covery, little had been learned about the CRN effector family. Analysis
P. ramorum (65 Mb)
scaffold_51
100,000 200,000
P. sojae (95 Mb)
scaffold_16
500,000600,000700,000800,000
P. infestans (240 Mb)
scaffold1.16
1.5 Mb 1.6 Mb 1.7 Mb 1.8 Mb 1.9 Mb 2 Mb 2.1 Mb 2.2 Mb 2.3 Mb
Figure 1 | Repeat-driven genome expansion in Phytophthora infestans.
Conserved gene order across three homologous Phytophthora scaffolds.
Genome expansion is evident in regions of conserved gene order, a
consequence of repeat expansion in intergenic regions. Genes are shown as
turquoise boxes, repeats as black boxes. Collinear orthologous gene pairs are
connected by pink (direct) or blue (inverted) bands.

21. PRR-
triggered
immunity
NLR-
triggered
immunity
effectors
bacterium
fungus
oomycete
haustorium
pathogen-associated
molecular patterns (PAMPs)
Pattern
recognition
receptors (PRRs)
NB-LRR
immune receptorsplant cell
targets
Principles of plant-pathogen interactions

22. PRR-
triggered
immunity
NLR-
triggered
immunity
effectors
bacterium
fungus
oomycete
haustorium
pathogen-associated
molecular patterns (PAMPs)
Pattern
recognition
receptors (PRRs)
NB-LRR
immune receptorsplant cell
targets
Principles of plant-pathogen interactions
R
R

23. PRR-
triggered
immunity
NLR-
triggered
immunity
effectors
bacterium
fungus
oomycete
haustorium
pathogen-associated
molecular patterns (PAMPs)
Pattern
recognition
receptors (PRRs)
NB-LRR
immune receptorsplant cell
targets
Principles of plant-pathogen interactions
R
R
S

24. Crystal structure of Magnaporthe oryzae effector
in complex with rice immune receptor
Maqbool et al. eLife 2015
De La Conception et al. Nature Plants 2018
Pikp1-HMA
AVR-PikD

25. Crystal structure of Magnaporthe oryzae effector
in complex with rice immune receptor
Maqbool et al. eLife 2015
De La Conception et al. Nature Plants 2018
Pikp1-HMA
AVR-PikD

26. Towards engineering Pik-1+ synthetic mutants
that bind and respond to APikL2
wild-type
expanded effector
recognition
plant cell
Disease Resistance
wild-type
expanded effector
recognition
combination
plant cell
Disease Resistance
sensitized
“trigger happy”
Beyond natural genetic variation—
synthetic R+ genes with improved activities

27. Beyond natural genetic variation—CRISPR crops
S gene knock-outs for enhanced disease resistance
Clade III
Clade IV
Clade V
Clade VI
Clade VII
Powdery
mildew
interactions
Green algae
>490 Mya
Cytoplasm
Calmodulin
binding
COOH
NH2
Plasma
membrane
Plasma
membrane
c d48-bp deletion
SlMLO1
...NNNNGGNNNNNNNNNNNNNNNNNNNNNNNNNNNNNGGNNNN...
PAM
sgRNA1
PAM
sgRNA2
e
WT
2 4 6
kb
8 10 12
slmlo1 8-2
slmlo1 8-4
slmlo 8-6
(T-DNA)
T-DNA
LB RB
g
ACATAGTAAAAGGTGTACCTGTGGTGGAGACTGGTGACCATCTTTTCTGGTTTAATCGCCCTGCCCTTGTCCTATTCTTGATTAACTTTGTACTCTTTCAGG
ACATAGTAAAAGGTGTACCTGTGGTGGAGACTGGTGACCATCTTTTCTGGTTTAATCGCCCTGCCCTTGTCCTATTCTTGATTAACTTTGTACTCTTTCAGG
ACATAGTAAAAGGTGTACCTGTGGTGGA------------------------------------------------CTTGATTAACTTTGTACTCTTTCAGG -48
ACATAGTAAAAGGTGTACCTGTGGTGGA------------------------------------------------CTTGATTAACTTTGTACTCTTTCAGG -48
ACATAGTAAAAGGTGTACCTGTGGTGGA------------------------------------------------CTTGATTAACTTTGTACTCTTTCAGG -48
ACATAGTAAAAGGTGTACCTGTGGTGGA-------------------------------------------------TTGATTAACTTTGTACTCTTTCAGG -49
WT
Plant 1
*Plant 2
*Plant 8
*Plant 10
PAM PAMTarget 1 Target 2
f
500
400
300
bp
1 2 8 10WT
SlMLO1 (WT)
slmlo1
Annu.Rev.Phytopathol.2018.56.Downloadedfromwww.annualreviews.org
AccessprovidedbyAustralianNationalUniversityon07/06/18.Forpersonaluseonly.

28. • Community – more interactions between
different branches of plant pathology
• Training – computational plant pathologists:
bioinformatics, data science, AI etc.
• Research assessment – new incentives
and publishing models
• Politics – evidence-based decision making
in the age of idiocracy
• Funding – burst the biomedical bubble
What are the challenges?
The Biomedical
Bubble
Richard Jones and James Wilsdon
July 2018
Why UK research and
innovation needs a greater
diversity of priorities, politics,
places and people

29. Traditional structures of science are
too slow for emergencies
• Funding – discretionary funds vs.
applying for research grants
• Collaboration – crowdsourcing vs.
individual groups
• Open science – immediate release of
data vs. after journal publication
• Publication – live peer review and
preprints vs. classical journal peer review

30. New models of communication and research assessment—
open science, preprints, live/post-publication peer-review etc.

31. Foundational and Translational Research Opportunities
to Improve Plant Health
White Paper
Foundational and Translational Research Opportunities
to Improve Plant Health
Richard Michelmore,1
Gitta Coaker,2
Rebecca Bart, Gwyn Beattie, Andrew Bent, Toby Bruce,
Duncan Cameron, Jeffery Dangl, Savithramma Dinesh-Kumar, Rob Edwards,
Sebastian Eves-van den Akker, Walter Gassmann, Jean T. Greenberg, Linda Hanley-Bowdoin,
Richard J. Harrison, Ping He, Jagger Harvey, Alisa Huffaker, Scot Hulbert, Roger Innes,
Jonathan D. G. Jones, Isgouhi Kaloshian, Sophien Kamoun, Fumiaki Katagiri, Jan Leach,
Wenbo Ma, John McDowell, June Medford, Blake Meyers, Rebecca Nelson, Richard Oliver,
Yiping Qi, Diane Saunders, Michael Shaw, Christine Smart, Prasanta Subudhi, Lesley Torrance,
Bret Tyler, Barbara Valent, and John Walsh
1
The Genome Center and Departments of Plant Sciences, Molecular & Cellular Biology, and Medical
Microbiology & Immunology, University of California, Davis, California, U.S.A.
2
Department of Plant Pathology, University of California, Davis, California, U.S.A.
A full list of all workshop participants and their affiliations is provided at the end of the document.
This workshop was sponsored by the UK Biotechnology and Biological Sciences Research
Council (BBSRC), the US National Science Foundation, Directorate for Biological Sciences (NSF BIO),
and the US Department of Agriculture, National Institute of Food and Agriculture (USDA NIFA), the UK
Science Innovation Network, and the Research Councils UK in the US in partnership with the University
of California, Davis and the British Consulate-General, San Francisco.
All authors contributed ideas to many of the sections through participation in breakout sessions
focused on the molecular basis of plant-pathogen/pest interactions, variation in and the evolution of plant-
pathogen/pest interactions, and translational strategies for more durable disease or pest control. Major
contributors in addition to the first two authors to the writing of each section are shown.
In recognition that a small group of researchers cannot adequately cover all aspects of this large
field, additional domain experts were invited to provide input and contributors were added to the list of
authors. Furthermore, online feedback provided by the international community at large within the first
four weeks of the paper’s online publication will be collated and included as an addendum.
Monitoring pathogens, pests, and
weeds.
Real-time monitoring of
pathogens. New detection
technologies to diagnose and
quantify diseases. Gobal
collections of pathogen
isolates/ecotypes/biotypes.
Advances in remote sensing,
sequencing technologies, and
computational power.
Opportunities to test germplasm
using relevant pathogen isolates.
Development of global networks for
monitoring key pathogens of major
crops. High throughput sequencing
of field samples of pathogens and
crops. Integration with remote
sensor data. Establishment of global
pathogen collections.
Linking remote sensing data with ground-
truthing data on disease and pathogen
presence. Identification of pathosystems
requiring investment in monitoring.
Deployment of co
driven by knowled
variation. Germpl
widespread effica
Assessing the impacts of climate
change on pathosystems.
Understanding the impacts of
climate change. Data to inform
the pathogen layer of climate
models.
Advances in tools for organism
level measurements. Increasing
sophistication of climate models.
Detailed phenomic and molecular
analyses under controlled
perturbations and field experiments.
Characterizing the impact of
environmental conditions on pathogen
epidemiology and on resistance in major
crops.
More accurate pre
Global approache
management. M
with efficacy unde
conditions. Atten
mycotoxin contam
Translational activities. Two way knowledge exchanges.
Tools for handling
unprecedented amounts of data.
Development of decision trees.
Coordinated efforts of multiple
entities.
Tools for handling big datasets
from electronic social media.
Recruitment of bioinformaticans and
computer scientists to the plant
health area.
Meta-analysis of plant, pathogen, and
phytobiome compnents influencing crop
productivity.
More effective tra
Building capacity in developing
countries.
Increased capacity building.
Models for successful
partnerships in knowledge
transfer.
Social media capabilities. On-going
activities of professional societies,
foundations, research universities,
and government agencies.
Establishment of bidirectional
partnerships. Two-way exchanges of
information between partners.
Engagement of extension and farmer
networks.
Training of graduate students from
developing coutries. Short-term training of
research scientists from developing
countries in collaboration with CGIAR.
Targeting relevant
hotpsots.
GMO deployment. Increased discourse to promote
GMO acceptance. Rational,
evidence-based decisions. Public
appreciation and enthusiasm for
improved crops.
Traits that appeal to consumers.
Genome editing as a non-GM
technology.
Improved communication with
decision makers and general public.
Assistance for publicly-funded projects
and those aimed at minor crops to comply
with regulatory hurdles.
More efficient pat
GM and edited cro
consumer trust. R
environmental im
Genome editing. Efficient methods for allele
replacement and knock-ins.
Technologies for reagent delivery
that do not involve tissue culture.
Generation of stacks of R, DR,
and/or S genes.
Technology development through
multi-institutional collaborations
with private sector and exchange of
information and protocols.
Technologies for non-DNA-mediated
genome editing of crops. Non-tissue
culture based protocols.
Genome-edited, n
crops with enhanc
resistance.
Translational opportunities, needs and challenges:

32. Thanks to the International Advisory Committee

33. Team NRC
Team BLASTOFF
Team ERIN
JOE
@KamounLab

34. @TheSainsbury Lab
Dan
Frank
Matt
Peter @2BladesCyril
Matthew
Mark
Jonathan Ksenia
Nick