This document summarizes key findings from the genome sequencing of the oomycete plant pathogen Magnaporthe grisea, which causes rice blast disease. Some key points: - The draft genome sequence was 38.8 megabases in length and contained a large number of genes encoding secreted proteins and carbohydrate-binding domains that help the pathogen infect plants. - The genome also contained an expanded family of G-protein coupled receptors and many genes involved in secondary metabolism, both of which are important for fungal pathogenesis. - Expression of several of these genes increased during early infection, suggesting they play a role in M. grisea's ability to infect rice plants and cause disease.

1. Plant pathology in the post-genomics era
Sophien Kamoun
http:KamounLab.net
@KamounLab

2. Phytophthora
Irish potato famine pathogen
Greek for plant destroyer
fungus-like oomycete

3. Crop losses due to fungal/oomycete diseases
Fisher et al. Nature 2012
potato blight
rice blast
wheat rusts
corn smut
soybean rust
0 400 800 1200 1600
million people could be fed by lost food

4. Crop losses due to fungal/oomycete diseases
Fisher et al. Nature 2012
rice blast
wheat rusts
corn smut
potato blight
soybean rust
0 400 800 1200 1600
million people could be fed by lost food

5. Filamentous pathogens
• Fungi and oomycetes
• Highly adaptable - can
rapidly overcome
plant resistance
• Mixed modes of
reproduction (asexual
and sexual)
• Large population sizes

6. Why the misery?
The secret of these pathogens’ success is their
ability to rapidly adapt to resistant plant varieties
How did they keep on adapting to ensure their
uninterrupted survival over evolutionary time?

7. Pathogenomics - an emerging field of plant pathology
The genome sequence of the rice blast
fungus Magnaporthe grisea
Ralph A. Dean1
, Nicholas J. Talbot2
, Daniel J. Ebbole3
, Mark L. Farman4
, Thomas K. Mitchell1
, Marc J. Orbach5
, Michael Thon3
,
Resham Kulkarni1
*, Jin-Rong Xu6
, Huaqin Pan1
, Nick D. Read7
, Yong-Hwan Lee8
, Ignazio Carbone1
, Doug Brown1
, Yeon Yee Oh1
,
Nicole Donofrio1
, Jun Seop Jeong1
, Darren M. Soanes2
, Slavica Djonovic3
, Elena Kolomiets3
, Cathryn Rehmeyer4
, Weixi Li4
, Michael Harding5
,
Soonok Kim8
, Marc-Henri Lebrun9
, Heidi Bohnert9
, Sean Coughlan10
, Jonathan Butler11
, Sarah Calvo11
, Li-Jun Ma11
, Robert Nicol11
,
Seth Purcell11
, Chad Nusbaum11
, James E. Galagan11
& Bruce W. Birren11
1
Center for Integrated Fungal Research, North Carolina State University, Raleigh, North Carolina 27695, USA
2
School of Biological and Chemical Sciences, University of Exeter, Washington Singer Laboratories, Exeter EX4 4QG, UK
3
Department of Plant Pathology and Microbiology, Texas A&M University, College Station, Texas 77843, USA
4
Department of Plant Pathology, University of Kentucky, Lexington, Kentucky 40546, USA
5
Department of Plant Pathology, University of Arizona, Tucson, Arizona 85721, USA
6
Department of Botany and Plant Pathology, Purdue University, West Lafayette, Indiana 47907, USA
7
Institute of Cell and Molecular Biology, University of Edinburgh, Edinburgh EH9 3JH, UK
8
School of Agricultural Biotechnology, Seoul National University, Seoul 151-742, Korea
9
FRE2579 CNRS-Bayer, Bayer Cropscience, 69263 Lyon Cedex 09, France
10
Agilent Technologies, Wilmington, Delaware 19808, USA
11
Broad Institute of MITand Harvard, Cambridge, Massachusetts 02141, USA
*Present address: RTI International, Research Triangle Park, North Carolina 27709, USA
...........................................................................................................................................................................................................................
Magnaporthe grisea is the most destructive pathogen of rice worldwide and the principal model organism for elucidating the
molecular basis of fungal disease of plants. Here, we report the draft sequence of the M. grisea genome. Analysis of the gene set
provides an insight into the adaptations required by a fungus to cause disease. The genome encodes a large and diverse set of
secreted proteins, including those defined by unusual carbohydrate-binding domains. This fungus also possesses an expanded
family of G-protein-coupled receptors, several new virulence-associated genes and large suites of enzymes involved in secondary
metabolism. Consistent with a role in fungal pathogenesis, the expression of several of these genes is upregulated during the early
stages of infection-related development. The M. grisea genome has been subject to invasion and proliferation of active
transposable elements, reflecting the clonal nature of this fungus imposed by widespread rice cultivation.
Outbreaks of rice blast disease are a serious and recurrent problem
in all rice-growing regions of the world, and the disease is extremely
difficult to control1,2
. Rice blast, caused by the fungus Magnaporthe
grisea, is therefore a significant economic and humanitarian
problem. It is estimated that each year enough rice is destroyed by
rice blast disease to feed 60 million people3
. The life cycle of the rice
summary of the principal genome sequence data is provided in
Table 1 and Supplementary Table S1. The draft genome sequence
consists of 2,273 sequence contigs longer than 2 kilobases (kb),
ordered and orientated within 159 scaffolds. The total length of all
sequence contigs is 38.8 megabases (Mb), and the total length of the
scaffolds, including estimated sizes for the gaps, is 40.3 Mb. The
articles 2005!
2006!
conclusion is that the experiment is clearly in the
weak field limit and the laser field is not strongly
perturbing the underlying thermally populated
modes, but rather inducing their interference in
the excited-state surface. Isomerization yields were
also compared with and without phase control
(Fig. 6C), keeping spectral amplitudes constant
(Fig. 6D; spectral profiles were confirmed using
a tunable monochromator with 0.2-nm spec-
tral resolution). The data show a clear phase
dependence indicative of coherent control.
Pure amplitude modulation alters the temporal
profile of the pulse (fig. S5); therefore, removing
the phase modulation affects the isomerization
yield by only 5 to 7%. The phase sensitivity of
the control efficiency further illustrates the co-
herent nature of the state preparation.
The temporalprofiles of the shaped optimaland
anti-optimal pulses and the observed degree of the
isomerization yield control are consistent with the
known fast electronic dephasing of bR (10, 38).
The largest field amplitudes are confined to ap-
proximately 300-fs widths to yield 20% control. In
the case of transform-limited pulses, all the vibra-
tional levels within the excitation bandwidth are
excited in phase and there is a fast decoherence in
the initial electronic polarization (38). However,
with the phase-selective restricted bandwidths in
the shaped pulses, there is an opportunity to ma-
nipulate different vibrationalstates with much long-
er coherence times than the electronic polarization.
The resultant constructive and destructive interfer-
ence effects involving vibrational modes displaced
along the reaction coordinate offer the possibility of
controlling isomerization. Experimental obser-
vations presented here show that the wave proper-
tiesofmattercanplayaroleinbiologicalprocesses,
to the point that they can even be manipulated.
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36. The saturation energy is related to the absorption cross
section s as Es 0 1/strans (for a negligibly small
contribution of the excited-state emission), and s is
ratio between the number of absorbed photons np 0
Eexc  pd2
0/4 and the number of retinal molecules Nm 0
C Â V in an excited volume V0 ; l0 Â pd2
0/4, where the
concentration is C 0 2.303A0/strans, A0 is OD at 565 nm
(0.9), l0 0 0.04 cm is the path length in the cell used,
and d0 0 0.015 cm is the beam diameter in the sample.
This gives a fraction of excited molecules of 0.0236 (that
is, 1 out of 42.3 molecules will be excited during the
excitation pulse at a given fluence). The fraction of
double-excited molecules can be estimated from the
Poisson distribution f(k) 0 ejl(l)k/k!, where l 0 0.0236,
and k is the number of occurrences (k 0 1 for the
single excitation, k 0 2 for the double excitation, etc.).
Thus, the fraction of double-excited molecules
f(2)/f(1) 0 l/2; that is, 1.18%.
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40. This work was supported by the National Sciences and
Engineering Research Council of Canada. The authors
thank J.T.M. Kennis, Vrije Universiteit Amsterdam, for
helpful discussions of preliminary results.
Supporting Online Material
www.sciencemag.org/cgi/content/full/313/5791/1257/DC1
Materials and Methods
Figs. S1 to S5
References
1 June 2006; accepted 10 August 2006
10.1126/science.1130747
Phytophthora Genome Sequences
Uncover Evolutionary Origins and
Mechanisms of Pathogenesis
Brett M. Tyler,1
* Sucheta Tripathy,1
Xuemin Zhang,1
Paramvir Dehal,2,3
Rays H. Y. Jiang,1,4
Andrea Aerts,2,3
Felipe D. Arredondo,1
Laura Baxter,5
Douda Bensasson,2,3,6
Jim L. Beynon,5
Jarrod Chapman,2,3,7
Cynthia M. B. Damasceno,8
Anne E. Dorrance,9
Daolong Dou,1
Allan W. Dickerman,1
Inna L. Dubchak,2,3
Matteo Garbelotto,10
Mark Gijzen,11
Stuart G. Gordon,9
Francine Govers,4
Niklaus J. Grunwald,12
Wayne Huang,2,14
Kelly L. Ivors,10,15
Richard W. Jones,16
Sophien Kamoun,9
Konstantinos Krampis,1
Kurt H. Lamour,17
Mi-Kyung Lee,18
W. Hayes McDonald,19
Mo´nica Medina,20
Harold J. G. Meijer,4
Eric K. Nordberg,1
Donald J. Maclean,21
Manuel D. Ospina-Giraldo,22
Paul F. Morris,23
Vipaporn Phuntumart,23
Nicholas H. Putnam,2,3
Sam Rash,2,13
Jocelyn K. C. Rose,24
Yasuko Sakihama,25
Asaf A. Salamov,2,3
Alon Savidor,17
Chantel F. Scheuring,18
Brian M. Smith,1
Bruno W. S. Sobral,1
Astrid Terry,2,13
Trudy A. Torto-Alalibo,1
Joe Win,9
Zhanyou Xu,18
Hongbin Zhang,18
Igor V. Grigoriev,2,3
Daniel S. Rokhsar,2,7
Jeffrey L. Boore2,3,26,27
Draft genome sequences have been determined for the soybean pathogen Phytophthora sojae and
the sudden oak death pathogen Phytophthora ramorum. Oo¨mycetes such as these Phytophthora
species share the kingdom Stramenopila with photosynthetic algae such as diatoms, and the
presence of many Phytophthora genes of probable phototroph origin supports a photosynthetic
ancestry for the stramenopiles. Comparison of the two species’ genomes reveals a rapid expansion
and diversification of many protein families associated with plant infection such as hydrolases, ABC
transporters, protein toxins, proteinase inhibitors, and, in particular, a superfamily of 700 proteins
with similarity to known oo¨mycete avirulence genes.
P
hytophthora plant pathogens attack a
wide range of agriculturally and orna-
mentally important plants (1). Late blight
of potato caused by Phytophthora infestans re-
sulted in the Irish potato famine in the 19th cen-
tury, and P. sojae costs the soybean industry
millions of dollars each year. In California and
Oregon, a newly emerged Phytophthora species,
P. ramorum, is responsible for a disease called
sudden oak death (2) that affects not only the live
www.sciencemag.org SCIENCE VOL 313 1 SEPTEMBER 2006 1261
LETTERS
Genome sequence and analysis of the Irish potato
famine pathogen Phytophthora infestans
Brian J. Haas1
*, Sophien Kamoun2,3
*, Michael C. Zody1,4
, Rays H. Y. Jiang1,5
, Robert E. Handsaker1
, Liliana M. Cano2
,
Manfred Grabherr1
, Chinnappa D. Kodira1
{, Sylvain Raffaele2
, Trudy Torto-Alalibo3
{, Tolga O. Bozkurt2
,
Audrey M. V. Ah-Fong6
, Lucia Alvarado1
, Vicky L. Anderson7
, Miles R. Armstrong8
, Anna Avrova8
, Laura Baxter9
,
JimBeynon9
,PetraC.Boevink8
,StephanieR.Bollmann10
,JorunnI.B.Bos3
,VincentBulone11
,GuohongCai12
,CahidCakir3
,
James C. Carrington13
, Megan Chawner14
, Lucio Conti15
, Stefano Costanzo16
, Richard Ewan15
, Noah Fahlgren13
,
Michael A. Fischbach17
, Johanna Fugelstad11
, Eleanor M. Gilroy8
, Sante Gnerre1
, Pamela J. Green18
,
Vol 461|17 September 2009|doi:10.1038/nature08358
2009

8. Phytophthora infestans has a repeat-bloated genome
with a “two-speed” architecture
P. infestans
P. sojae
P. ramorum
P. sojae
P. infestans
P. ramorum
gene-sparse,
repeat-rich regions
gene-dense,
repeat-poor
dN/dSameasureof
adaptiveevolution

9. Virulence (effector) genes populate repeat-rich regions
Sporangia Tomato 5 dpi
gene-sparse,
repeat-rich regions
gene-dense,
repeat-poor

10. Convergence towards a “two-speed” genome
architecture in independent pathogen lineages

11. Genome architecture underpins ability to rapidly
adapt to resistant plant genotypes.
• Structural genome variation – increased genome
instability and structural variation, deletions, duplications
etc.
• Horizontal gene/chromosome transfer – mobile
effectors
• Increased local mutagenesis – RIP mutation leakage
• Epigenetics – heterochromatin leakage?
• …more to be discovered
How?

12. New way of doing business
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
) yieldsone 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.
NLR$%
triggered%
immunity%
effectors%
bacterium%
fungus%
oomycete%
haustorium%
NB$LRR%
immune%receptors%plant%cell%
pathogen)associated.
molecular.pa3erns.(PAMPs).
Pa3ern.recogni9on.
receptors.(PRRs).

13. New way of doing business
Discovery pipelines
Effectors and immune receptors
study illustrating how plant pathogen genomes can be a
remarkable resource for basic and applied plant biology
(Figure 1).
Plant parasitic oomycete genome structure
Currently, draft genome sequences are available for ten
oomycete species, nine of which are plant pathogens [3,9-
16] (Figure 2). One striking feature of these oomycete
genomes is the considerable variability in size, ranging
from 37 Mb for the biotrophic plant pathogen Albugo
laibachii (an obligate parasite of the model plant
(a) Sequencing of the plant pathogen genome
(b) Computational prediction of pathogen effectors
(c) Library of effector clones
(d) In planta expression of effectors
(e) Insights into plant processes
TC C A ATC A GG TT CGA
TC C A A TC A GGTT CGA
TC C A A TC A GGTT CGA
(i) (ii)
Figure 1. High-throughput pipeline for using plant pathogen
effectors to unravel plant processes. (a) Genome sequences are
currently available for a variety of plant pathogens. (b) This allows
the computational prediction of candidate effector genes using the
knowledge gained from characterized effector proteins. In the case
of Phytophthora pathogens, prediction is facilitated by the presence
of effector genes in gene-sparse, repeat-rich regions of the genomes,
and by the modular structure of effectors. (c) Cloning of these
effector genes and (d) expression of candidate effectors in planta
using Agrobacterium-mediated transient expression systems such as
agroinfiltration (left) and wound inoculation (right). (e) These help us
understand diverse plant processes. For instance, (i) identification of
host proteins that interact with pathogen effectors can give insights
into the plant pathways targeted and perturbed during the infection
process. (ii) In addition, effectors can be used as molecular probes to
study the structural changes that occur during plant infection at a
subcellular level. For instance, effectors can be fused to fluorescent
proteins to assess their localization in planta. (iii) The suppression of
plant immune responses such as the production of reactive oxygen
species (ROS) can also be studied. Blue line shows induction of ROS
by flagellin peptide in the absence of effector proteins. This ROS burst
is reduced (red) by the expression of an oomycete effector. (iv) The
activation of host immunity by effector proteins helps the dissection
of plant susceptibility and resistance mechanisms. For example, the
hypersensitive response (brown spots on leaves) against effectors
transiently expressed in planta can be used to identify immune
receptors (R genes) of high value for plant breeding.
Now there is a new, strong weapon in the battle
against late blight (Phytophthora infestans),
which has been the scourge of potato ultivation
for centuries – Fortuna, the high performance
potato variety with in built special, natural resis-
tance! Late blight is the most common fungal
disease which affects potatoes. It is estimated
that late blight is responsible for around 20% of
potato harvest failures around the globe each
Until now, it was only possible to protect against
this fungal disease using fungicides. But nature
has had a solution at its fingertips for thousands
of years. In the high valleys of Mexico, a wild
potato was discovered which is completely
resistant to late blight. Breeders have been
trying for more than 50 years to integrate this
resistance into an agronomically useful potato
variety. They have not been successful, because
Fortuna, the potato variety for your peace of mind.
2|3
A new weapon against Phytophthora –
... for peace of mind
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UNDER DEVELOPMENTFOR YOURCONVENIENCE

14. Field pathogenomics - rapid assessment
of pathogen diversity from field samples
2. Purify and multiply field
isolates
3. Infect wheat lines and score
infection type
4.0
3.0
2.0
1.0
0.0
Susceptible
Resistant
Phenotype
2. Sequence genes with latest
technology
3. Assess pathogen
genotypic diversity
4. Determine
wheat variety
Traditional
Pathology
Field
Pathogenomics
1. Receive sample
from the field

15. 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

16. 0
1000
2000
3000
4000
All puzzles
0
5
10
15
20
25
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
High scoring user %,
who has aligned different to software
puzzlecount
0
1000
2000
3000
4000
SNP puzzles
0
200
400
600
INDEL puzzles
0
5
10
15
0
5
10
15
20
25
35
40
45
50
55
60
65
70
75
80
85
90
95
100
0
5
10
15
0
10
15
25
30
35
40
50
60
65
70
75
80
85
90
100
High scoring user %, who has aligned different to software
puzzlecount
% read
alignments
different
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
INDEL
(n=10348)
SNP
(n=47486)
ALL
(n=57834)
0% 25% 50% 75% 100% 0% 25% 50% 75% 100%
Identity Score
Player Better Both Equal Software Better
a b
c

17. • Genomics-enabled gene mapping and cloning
• From Marker Assisted Selection (MAS) to Genomic
Selection (GS)
• Next-generation crop (disease resistance) breeding
©2012NatureAmerica,Inc.Allrightsreserved.
A RT I C L E S
The world population is predicted to reach 9 billion within the next
40 years, requiring a 70–100% increase in food production relative
to current levels1. It is a major challenge to ensure sustainable food
production without further expanding farmland and damaging the
environment, in the midst of adverse conditions such as rapid climatic
changes. Crop breeding is important for improving yield and toler-
ance to existing and emerging biotic and abiotic stresses2. However,
current breeding approaches are mostly inefficient, and have not
incorporated the findings of the genomics revolution3.
Most crop traits relevant to agronomic improvement are con-
trolled by several loci, including quantitative trait loci (QTL), that
when disrupted lead to minor phenotypic effects4. To enable plant
breeding by marker-assisted selection, it is important to identify
the locus or chromosome region harboring each gene contributing
to an improved trait. However, compared with genes with major
effects that determine discrete characteristics, allelic substitutions
at agronomic trait loci lead to only subtle changes in phenotype.
Consequently, cloning genes that control agronomic traits is not
straightforward.
Here we describe MutMap, a method of rapid gene isolation using
a cross of the mutant to wild-type parental line, and apply it to a
large population of mutant lines of an elite Japanese rice cultivar. We
used MutMap to localize genomic positions of rice genes controlling
agronomically important traits including semidwarfism. As mutant
plants and associated molecular markers can be made available to
plant breeders, this approach could markedly accelerate crop breed-
ing and genetics.
RESULTS
MutMap method
We explain the principle of MutMap (Fig. 1) using the example of
rice. We first use a mutagen (for example, ethyl methanesulfonate) to
mutagenize a rice cultivar (X) that has a reference genome sequence.
Mutagenized plants of this first mutant generation (M1) are self-
pollinated and brought to the second (M2) or more advanced genera-
tions to make the mutated gene homozygous. Through observation of
phenotypes in the M2 lines or later generations, we identify recessive
mutants with altered agronomically important traits such as plant
height, tiller number and grain number per spike. Once the mutant is
identified, it is crossed with the wild-type plant of cultivar X, the same
cultivar used for mutagenesis. The resulting first filial generation (F1)
plant is self-pollinated, and the second generation (F2) progeny (>100)
are grown in the field for scoring the phenotype. Because these F2
progeny are derived from a cross between the mutant and its parental
wild-type plant, the number of segregating loci responsible for the
phenotypic change is minimal, in most cases one, and thus segrega-
tion of phenotypes can be unequivocally observed even if the pheno-
typic difference is small. All the nucleotide changes incorporated into
the mutant by mutagenesis are detected as single-nucleotide polymor-
phisms (SNPs) and insertion-deletions (indels) between mutant and
wild type. Among the F2 progeny, the majority of SNPs will segregate
in a 1:1 mutant/wild type ratio. However, the SNP responsible for
the change of phenotype is homozygous in the progeny showing the
mutant phenotype. If we collect DNA samples from recessive mutant
F progeny and bulk sequence them with substantial genomic coverage
Genome sequencing reveals agronomically important
loci in rice using MutMap
Akira Abe1,2,7, Shunichi Kosugi3,7, Kentaro Yoshida3, Satoshi Natsume3, Hiroki Takagi2,3, Hiroyuki Kanzaki3,
Hideo Matsumura3,4, Kakoto Yoshida3, Chikako Mitsuoka3, Muluneh Tamiru3, Hideki Innan5, Liliana Cano6,
Sophien Kamoun6 & Ryohei Terauchi3
The majority of agronomic traits are controlled by multiple genes that cause minor phenotypic effects, making the identification
of these genes difficult. Here we introduce MutMap, a method based on whole-genome resequencing of pooled DNA from a
segregating population of plants that show a useful phenotype. In MutMap, a mutant is crossed directly to the original wild-type
line and then selfed, allowing unequivocal segregation in second filial generation (F2) progeny of subtle phenotypic differences.
This approach is particularly amenable to crop species because it minimizes the number of genetic crosses (n = 1 or 0) and
mutant F2 progeny that are required. We applied MutMap to seven mutants of a Japanese elite rice cultivar and identified the
unique genomic positions most probable to harbor mutations causing pale green leaves and semidwarfism, an agronomically
relevant trait. These results show that MutMap can accelerate the genetic improvement of rice and other crop plants.
©2012NatureAmerica,Inc.Allrightsreserved.
The world population is predicted to reach 9 billion within the next
40 years, requiring a 70–100% increase in food production relative
to current levels1. It is a major challenge to ensure sustainable food
production without further expanding farmland and damaging the
environment, in the midst of adverse conditions such as rapid climatic
changes. Crop breeding is important for improving yield and toler-
ance to existing and emerging biotic and abiotic stresses2. However,
current breeding approaches are mostly inefficient, and have not
incorporated the findings of the genomics revolution3.
Most crop traits relevant to agronomic improvement are con-
trolled by several loci, including quantitative trait loci (QTL), that
when disrupted lead to minor phenotypic effects4. To enable plant
breeding by marker-assisted selection, it is important to identify
the locus or chromosome region harboring each gene contributing
to an improved trait. However, compared with genes with major
effects that determine discrete characteristics, allelic substitutions
at agronomic trait loci lead to only subtle changes in phenotype.
Consequently, cloning genes that control agronomic traits is not
straightforward.
Here we describe MutMap, a method of rapid gene isolation using
a cross of the mutant to wild-type parental line, and apply it to a
large population of mutant lines of an elite Japanese rice cultivar. We
used MutMap to localize genomic positions of rice genes controlling
agronomically important traits including semidwarfism. As mutant
plants and associated molecular markers can be made available to
plant breeders, this approach could markedly accelerate crop breed-
ing and genetics.
RESULTS
MutMap method
We explain the principle of MutMap (Fig. 1) using the example of
rice. We first use a mutagen (for example, ethyl methanesulfonate) to
mutagenize a rice cultivar (X) that has a reference genome sequence.
Mutagenized plants of this first mutant generation (M1) are self-
pollinated and brought to the second (M2) or more advanced genera-
tions to make the mutated gene homozygous. Through observation of
phenotypes in the M2 lines or later generations, we identify recessive
mutants with altered agronomically important traits such as plant
height, tiller number and grain number per spike. Once the mutant is
identified, it is crossed with the wild-type plant of cultivar X, the same
cultivar used for mutagenesis. The resulting first filial generation (F1)
plant is self-pollinated, and the second generation (F2) progeny (>100)
are grown in the field for scoring the phenotype. Because these F2
progeny are derived from a cross between the mutant and its parental
wild-type plant, the number of segregating loci responsible for the
phenotypic change is minimal, in most cases one, and thus segrega-
tion of phenotypes can be unequivocally observed even if the pheno-
typic difference is small. All the nucleotide changes incorporated into
the mutant by mutagenesis are detected as single-nucleotide polymor-
phisms (SNPs) and insertion-deletions (indels) between mutant and
wild type. Among the F2 progeny, the majority of SNPs will segregate
in a 1:1 mutant/wild type ratio. However, the SNP responsible for
the change of phenotype is homozygous in the progeny showing the
mutant phenotype. If we collect DNA samples from recessive mutant
F2 progeny and bulk sequence them with substantial genomic coverage
Genome sequencing reveals agronomically important
loci in rice using MutMap
Akira Abe1,2,7, Shunichi Kosugi3,7, Kentaro Yoshida3, Satoshi Natsume3, Hiroki Takagi2,3, Hiroyuki Kanzaki3,
Hideo Matsumura3,4, Kakoto Yoshida3, Chikako Mitsuoka3, Muluneh Tamiru3, Hideki Innan5, Liliana Cano6,
Sophien Kamoun6 & Ryohei Terauchi3
The majority of agronomic traits are controlled by multiple genes that cause minor phenotypic effects, making the identification
of these genes difficult. Here we introduce MutMap, a method based on whole-genome resequencing of pooled DNA from a
segregating population of plants that show a useful phenotype. In MutMap, a mutant is crossed directly to the original wild-type
line and then selfed, allowing unequivocal segregation in second filial generation (F2) progeny of subtle phenotypic differences.
This approach is particularly amenable to crop species because it minimizes the number of genetic crosses (n = 1 or 0) and
mutant F2 progeny that are required. We applied MutMap to seven mutants of a Japanese elite rice cultivar and identified the
unique genomic positions most probable to harbor mutations causing pale green leaves and semidwarfism, an agronomically
relevant trait. These results show that MutMap can accelerate the genetic improvement of rice and other crop plants.
1Iwate Agricultural Research Center, Kitakami, Japan. 2United Graduate School of Agricultural Sciences, Iwate University, Morioka, Japan. 3Iwate Biotechnology
Research Center, Kitakami, Japan. 4Gene Research Center, Shinshu University, Ueda, Japan. 5Graduate University for Advanced Studies, Hayama, Japan. 6The Sainsbury
Laboratory, Norwich Research Park, Norwich, UK. 7These authors contributed equally to this work. Correspondence should be addressed to R.T. (terauchi@ibrc.or.jp).
Received 28 July 2011; accepted 14 December 2011; published online 22 January 2012; doi:10.1038/nbt.2095

18. %
or
le
he
ld
ds.
on
ype reads. If we define the
r of reads of a mutant SNP
ing to the SNP, we expect
the expected number of clusters of SNPs with SNP index of 1 ( k)
would be approximately pkL = 10−3kL. In our case, the maximum
estimate of L is 2,225 (Supplementary Table 1), and the probability
EMS mutagenesis
Wild-type
parental line
Mutant
Selfing
F2 progeny
Sequence the bulked DNA
F2 progeny showing mutant phenotype
Sequence
(reference)
SNP mapping
WT
Seq.
SNPs not linked to
the phenotype
SNP index = 3/7 = 0.43 SNP index = 7/7 = 1
SNPs linked to
the phenotype
Mapping of
SNPs
X
F1
e
d,
he
s
ex
Semi-dwarf
Salt tolerant
Next-Gen crop breeding - MutMap

19. Kaijin!
• Salt tolerant rice variety
“Kaijin” bred in just two years
• Seawater contaminated
paddies/groundwater after
2011 tsunami
• MutMap revealed the causal
gene
• Kaijin differs from parental
variety Hitomebore by only
201 SNPs
mutantWT
WT
mutant
Kaijin
WT
mutant
Kaijin
Control Treated with
0.375% NaCl

20. BACTERIA MAY NOT ELICIT MUCH SYMPA-
thy from us eukaryotes, but they, too, can get
sick. That’s potentially a big problem for the
dairy industry, which often depends on bac-
teria such as Streptococcus thermophilus to
make yogurts and cheeses. S. thermophilus
breaks down the milk sugar lactose into tangy
lactic acid. But certain viruses—bacterio-
phages, or simply phages—can debilitate the
pany now owned by DuPont, found a way to
boost the phage defenses of this workhouse
microbe. They exposed the bacterium to
a phage and showed that this essentially
vaccinated it against that virus (Science,
23 March 2007, p. 1650). The trick has
enabled DuPont to create heartier bacterial
strains for food production. It also revealed
something fundamental: Bacteria have a
become important for more than food scien-
tists and microbiologists, because of a valu-
able feature: It takes aim at specific DNA
sequences. In January, four research teams
reported harnessing the system, called
CRISPR for peculiar features in the DNA of
bacteria that deploy it, to target the destruc-
tion of specific genes in human cells. And in
the following 8 months, various groups have
The CRISPR CrazeA bacterial immune system yields a potentially
revolutionary genome-editing technique
FSCIENCE/SCIENCESOURCE
Fighting invasion. When
viruses (green) attack
bacteria, the bacteria
respond with DNA-targeting
defenses that biologists
have learned to exploit
for genetic engineering.
onAugust23,2013www.sciencemag.orgDownloadedfrom
www.sciencemag.org SCIENCE VOL 341 23 AUGUST 2013
BACTERIA MAY NOT ELICIT MUCH SYMPA-
thy from us eukaryotes, but they, too, can get
sick. That’s potentially a big problem for the
dairy industry, which often depends on bac-
teria such as Streptococcus thermophilus to
make yogurts and cheeses. S. thermophilus
breaks down the milk sugar lactose into tangy
lactic acid. But certain viruses—bacterio-
phages, or simply phages—can debilitate the
bacterium, wreaking havoc on the quality or
quantity of the food it helps produce.
In 2007, scientists from Danisco, a
Copenhagen-based food ingredient com-
pany now owned by DuPont, found a way to
boost the phage defenses of this workhouse
microbe. They exposed the bacterium to
a phage and showed that this essentially
vaccinated it against that virus (Science,
23 March 2007, p. 1650). The trick has
enabled DuPont to create heartier bacterial
strains for food production. It also revealed
something fundamental: Bacteria have a
kind of adaptive immune system, which
enables them to fight off repeated attacks
by specific phages.
That immune system has suddenly
become important for more than food
tists and microbiologists, because of
able feature: It takes aim at specifi
sequences. In January, four research
reported harnessing the system,
CRISPR for peculiar features in the D
bacteria that deploy it, to target the d
tion of specific genes in human cells.
the following 8 months, various grou
used it to delete, add, activate, or suppr
geted genes in human cells, mice, rats
fish, bacteria, fruit flies, yeast, nem
and crops, demonstrating broad utility
The CRISPR CrazeA bacterial immune system yields a potentially
revolutionary genome-editing technique
CREDIT:EYEOFSCIENCE/SCIENCESOURCE
for genetic engineerin
Published by AAAS
infects plant scientists

21. REVIEW Open Access
Plant genome editing made easy: targeted
mutagenesis in model and crop plants using the
CRISPR/Cas system
Khaoula Belhaj†
, Angela Chaparro-Garcia†
, Sophien Kamoun*
and Vladimir Nekrasov*
Abstract
Targeted genome engineering (also known as genome editing) has emerged as an alternative to classical plant
breeding and transgenic (GMO) methods to improve crop plants. Until recently, available tools for introducing
site-specific double strand DNA breaks were restricted to zinc finger nucleases (ZFNs) and TAL effector nucleases
(TALENs). However, these technologies have not been widely adopted by the plant research community due to
complicated design and laborious assembly of specific DNA binding proteins for each target gene. Recently, an
easier method has emerged based on the bacterial type II CRISPR (clustered regularly interspaced short palindromic
repeats)/Cas (CRISPR-associated) immune system. The CRISPR/Cas system allows targeted cleavage of genomic DNA
guided by a customizable small noncoding RNA, resulting in gene modifications by both non-homologous end
joining (NHEJ) and homology-directed repair (HDR) mechanisms. In this review we summarize and discuss recent
applications of the CRISPR/Cas technology in plants.
Keywords: CRISPR, Cas9, Plant, Genome editing, Genome engineering, Targeted mutagenesis
Introduction
Targeted genome engineering has emerged as an alter-
native to classical plant breeding and transgenic (GMO)
methods to improve crop plants and ensure sustainable
food production. However, until recently the available
methods have proven cumbersome. Both zinc finger
nucleases (ZFNs) and TAL effector nucleases (TALENs)
can be used to mutagenize genomes at specific loci, but
based on the Cas9 nuclease and an engineered single
guide RNA (sgRNA) that specifies a targeted nucleic acid
sequence. Given that only a single RNA is required to gen-
erate target specificity, the CRISPR/Cas system promises
to be more easily applicable to genome engineering than
ZFNs and TALENs.
Recently, eight reports describing the first applications
of the Cas9/sgRNA system to plants have been published
PLANT METHODS
Belhaj et al. Plant Methods 2013, 9:39
http://www.plantmethods.com/content/9/1/39