RAPID SPECIATION FOLLOWING RECENT HOST SHIFTS … · 2014-10-13 · RAPID SPECIATION FOLLOWING...

ORIGINAL ARTICLE

doi:10.1111/j.1558-5646.2008.00390.x

RAPID SPECIATION FOLLOWING RECENT HOSTSHIFTS IN THE PLANT PATHOGENIC FUNGUSRHYNCHOSPORIUMPascal L. Zaffarano,1,2,3 Bruce A. McDonald,1 and Celeste C. Linde4

1Plant Pathology, Institute of Integrative Biology, ETH-Zurich, LFW, CH-8092 Zurich, Switzerland2E-mail: [email protected]

4School of Botany and Zoology, Building 116, Daley Rd, Australian National University, Canberra ACT 0200, Australia

Received July 6, 2007

Accepted March 11, 2008

Agriculture played a significant role in increasing the number of pathogen species and in expanding their geographic range during

the last 10,000 years. We tested the hypothesis that a fungal pathogen of cereals and grasses emerged at the time of domestication

of cereals in the Fertile Crescent and subsequently speciated after adaptation to its hosts. Rhynchosporium secalis, originally

described from rye, causes an important disease on barley called scald, although it also infects other species of Hordeum and

Agropyron. Phylogenetic analyses based on four DNA sequence loci identified three host-associated lineages that were confirmed

by cross-pathogenicity tests. Bayesian analyses of divergence time suggested that the three lineages emerged between ∼1200

to 3600 years before present (B.P.) with a 95% highest posterior density ranging from 100 to 12,000 years B.P. depending on

the implemented clock models. The coalescent inference of demographic history revealed a very recent population expansion

for all three pathogens. We propose that Rhynchosporium on barley, rye, and Agropyron host species represent three cryptic

pathogen species that underwent independent evolution and ecological divergence by host-specialization. We postulate that the

recent emergence of these pathogens followed host shifts. The subsequent population expansions followed the expansion of the

cultivated host populations and accompanying expansion of the weedy Agropyron spp. found in fields of cultivated cereals. Hence,

agriculture played a major role in the emergence of the scald diseases, the adaptation of the pathogens to new hosts and their

worldwide dissemination.

KEY WORDS: Barley, coevolution, crop domestication, host shift, plant pathogens, TMRCA.

Agriculture began with the domestication of the plants and ani-

mals that enabled the rapid human population expansion of the

last 10,000 years (Cavalli-Sforza et al. 1994; Diamond 1997).

As agriculture spread, populations of pathogens on humans and

their domesticated animals and plants expanded. Agriculture may

also have contributed to the number of pathogen species and their

current geographic ranges through the anthropogenic modifica-

tion of the environment (Schrag and Wiener 1995; Kolar and

Lodge 2001; Diamond 2002; Anderson et al. 2004; Armelagos

and Harper 2005). The expansion of human pathogens follow-

ing the shift of human societies to agriculture has been explained

3Corresponding author.

by the corresponding increase in human population density that

allowed (1) the maintenance of stable pathogen populations, (2)

the increase of interspecies transmission from domesticated ani-

mals, and (3) the expansion of human populations into novel en-

vironments and resulting exposure to novel pathogens (Diamond

2002; Armelagos and Harper 2005). A similar process affected the

pathogens colonizing agricultural crops. The high host densities

and genetic uniformity of host populations coupled with cultiva-

tion practices and trade created more uniform environments that

maintained stable pathogen populations and were conducive for

disease development and transmission. The movement of domes-

ticated plants and their respective pathogens into new areas could

simultaneously introduce “domesticated” pathogens into new

1418C© 2008 The Author(s) . Journal compilation C© 2008 The Society for the Study of Evolution.Evolution 62-6: 1418–1436

RECENT PATHOGEN ORIGINS

areas in which they could colonize “wild” hosts and expose the

domesticated crops to new pathogens that could shift from wild

to domesticated hosts. Anthropogenic influences on the environ-

ment such as intensification of crop production and global trade

or other factors such as climate change are thought to promote

the emergence of new plant diseases (Anderson et al. 2004; Slip-

pers et al. 2005; Woolhouse et al. 2005; Money 2007). However,

the history and the processes that led wild pathogens to become

domesticated and vice versa have been poorly studied.

Many human pathogens may have originated since the rise

of agriculture as a result of host shifts from domestic animals

(Pearce-Duvet 2006; Wolfe et al. 2007). Although this hypothesis

has been widely proposed for many human diseases, unequivo-

cal evidence based on phylogenetics and estimates of divergence

times are rarely presented (Pearce-Duvet 2006 for review). For the

tuberculosis bacterium Mycobacterium tuberculosis, tapeworms

of the genus Taenia, and the protozoan Plasmodium falciparum

causing falciparal malaria, there is evidence that their progenitors

predate the rise of agriculture and may have already been hu-

man pathogens before animal domestication (Pearce-Duvet 2006

for review). In a similar way, the progenitors of modern plant

pathogens may have been present already on the progenitors of

crop plants and diverged with them after domestication (Munkacsi

et al. 2007). Alternatively, domestication might have strongly in-

fluenced host shifts leading to the emergence of new diseases on

crops (Couch et al. 2005). Agricultural practices might have sub-

sequently favored host specialization, reproductive isolation, and

speciation of plant pathogens on new hosts (Hansen 1987; Kohn

2005). The role that agriculture has played in the emergence of

a plant disease can be evaluated by dating the divergence of the

causal agent. For the most important group of plant pathogens, the

fungi, few studies have attempted to date divergence from their

progenitors (Couch et al. 2005; Munkacsi et al. 2007; Stukenbrock

et al. 2007), mainly due to the lack of fossil records and large er-

rors associated with molecular clocks. In contrast, the evolutionary

history and time of domestication has been well studied for most

of the important staple crops infected by these fungal pathogens.

The origins of the fungal pathogens Mycosphaerella gramini-

cola causing septoria leaf blotch on wheat and Magnaporthe

oryzae causing rice blast coincided with the domestication of their

current hosts (Couch et al. 2005; Stukenbrock et al. 2007), start-

ing ∼10,000 years before present (B.P.) for wheat in the Fertile

Crescent (Flannery 1973; Lev-Yadun et al. 2000; Salamini et al.

2002) and ∼7000 years B.P. for rice in East Asia (Flannery 1973;

Crawford and Shen 1998; Higman and Lu 1998). Domestication,

agricultural practices, and trade strongly influenced the pathogen’s

evolution and the diseases they cause on these crops (Couch et al.

2005; Stukenbrock et al. 2007). We refer to this very recent origin

of the pathogens associated with the domestication of the host

as the “domestication hypothesis.” The domestication hypothesis

was not supported for fungal pathogens of the genera Ustilago and

Sporisorium causing smut on Poaceae such as maize, sorghum,

and sugarcane. Divergence time estimates for these species were

millions of years, indicating that speciation occurred long be-

fore their hosts were domesticated less than 10,000 years ago

(Munkacsi et al. 2007).

Rhynchosporium secalis (Oudem.) J.J. Davis. causes an im-

portant disease called scald on barley, rye, and other grasses.

Analyses of nucleotide sequences of NIP1, a gene encoding a

toxin involved in pathogenicity, indicated that R. secalis started

to colonize barley ∼5000–7500 years after the domestication of

barley (Brunner et al. 2007) that occurred ∼10,000 B.P. (Badr

et al. 2000). This led to the hypothesis that domestication and

agricultural practices affected the emergence and global spread of

this barley pathogen. In this study we investigate how agriculture

shaped the demography of the pathogen through time and deter-

mine whether the emergence of the pathogen fits the domestication

hypothesis. The evolutionary history of R. secalis was investigated

using nucleotide sequences of several housekeeping genes not in-

volved in pathogenicity, in contrast to NIP1. We included 316

isolates from barley, rye, and uncultivated grasses from different

continents. Population genetic analysis, multiple gene genealo-

gies, coalescent-based approaches, and analyses of pathogenicity

were combined to determine if cryptic species exist on cultivated

and wild hosts of the pathogen. We then determined whether the

fungal populations on uncultivated grasses were ancestral to pop-

ulations on cereal hosts or originated from the same or different

ancestors. Divergence time between and within host-associated

populations was estimated and the demographic history of the

pathogen reconstructed. We present evidence that agriculture has

driven the evolution of R. secalis since the Neolithic through a

host shift from wild grasses to cultivated barley, falsifying the

domestication hypothesis for this plant pathogen.

Material and MethodsFUNGAL ISOLATES

Isolates of R. secalis from nine different hosts including culti-

vated barley (Hordeum vulgare), rye (Secale cereale) and triticale

(× Triticosecale Wittmack), as well as six wild grasses; Agropy-

ron caninum, Agropyron repens, Bromus diandrus, Hordeum lep-

orinum, Hordeum murinum and Hordeum spontaneum, were in-

cluded in this study. Isolates of Rhynchosporium orthosporum (the

only other described Rhynchosporium species) infecting Dactylis

glomerata were included as outgroup. The R. secalis isolates orig-

inated from 21 countries representing five continents. Many of

these isolates were representatives of a collection of R. secalis that

was characterized previously (McDermott et al. 1989; McDonald

et al. 1999; Salamati et al. 2000; Linde et al. 2003; Zaffarano

et al. 2006). Detailed descriptions of the isolates are found in

Table 1. Each isolate had a unique multilocus genotype based on

EVOLUTION JUNE 2008 1419

PASCAL L. ZAFFARANO ET AL.

Table 1. Origin of the Rhynchosporium isolates used in the study.

Host Geographic No. of Previous publication or source andorigin isolates year of collection (in parentheses)

Agropyron caninum Switzerland 1 C.C. Linde (2002)Agropyron repens Switzerland 50 P. L. Zaffarano, M. Zala, C.C. Linde (2004–2005)Barley Australia 7 McDonald et al. (1999)Barley Azerbaijan 2 A. Yahyaoui (2003)Barley Ethiopia 13 A. Yahyaoui (2003), Zaffarano et al. (2006)Barley Eritrea 6 A. Yahyaoui (2003)Barley Finland 8 Salamati et al. (2000)Barley France 5 Zaffarano et al. (2006)Barley Germany 7 Zaffarano et al. (2006)Barley Jordan 4 Zaffarano et al. (2006)Barley Kyrgistan 2 A. Yahyaoui (2003)Barley New Zealand 8 M. Cromey (2004)Barley Norway 16 Salamati et al. (2000)Barley South Africa 3 Linde et al. (2003)Barley Sweden 1 S. Salamati (1996)Barley Switzerland 45 Linde et al. (2003)Barley Syria 5 Linde et al. (2003)Barley Tunisia 3 A. Yahyaoui (2003)Barley Turkey 2 Zaffarano et al. (2006)Barley United Kingdom 3 Zaffarano et al. (2006)Barley USA 6 McDermott et al. (1989)Bromus diandrus Australia 2 McDonald et al. (1999)Dactylis glomerata Italy 7 C.C. Linde (2004)Dactylis glomerata Switzerland 6 P. L. Zaffarano, M. Zala, C.C. Linde (2004–2005)Hordeum leporinum Australia 18 McDonald et al. (1999)Hordeum murinum Switzerland 4 C.C. Linde, P. L. Zaffarano (2004)Hordeum murinum USA 3 C.C. Linde (2003)Hordeum spontaneum Syria 5 M. Abang (2003)Rye Russia 25 L. Lebedeva (2003)Rye Switzerland 27 C.C. Linde (2002), Zaffarano et al. (2006)Triticale Switzerland 6 C.C. Linde (2002)Triticale France 16 A. Bouguennec, L. Jestin (2002)

Total 316

RFLP loci, RAPD fingerprints, mating types (Linde et al. 2003;

Zaffarano et al. 2006), and microsatellites (Linde et al. 2005).

DNA EXTRACTION, AMPLIFICATION, AND

SEQUENCING

Isolation and culturing of fungal isolates were as described in

McDonald et al. (1999). DNA was extracted from lyophilized tis-

sue with either the method described in McDonald et al. (1999)

or the DNeasy Plant Mini DNA extraction kit (Qiagen GmbH,

Hilden, Germany) according to the manufacturer’s instructions.

Four nuclear DNA loci were analyzed. Sequences of the ITS

region (ITS1, 5.8S rRNA gene, ITS2) were obtained by PCR

amplification of genomic DNA of isolates using the primers

ITS4 and ITS5 (White et al. 1990). The translation elonga-

tion factor 1 alpha (EF-1�) was amplified with primers EF1-

728F and EF1-986R (Carbone and Kohn 1999). Portions of �-

tubulin were amplified in three steps. The first primer set used

was ATUB-25F (5′-GAGAAGCTATTAGCATCAACG-3′) and

ATUB-649R (5′-CTCCTTTCCAACAGTGTAGTGAC-3′), the

second ATUB-540F (5′-TCCCTAGAACCATCTACTGCG-3′)and ATUB-1206R (5′-CTTTGGCGGCAGACAACTG-3′), and

the third ATUB-1103F (5′-ACAGTTGTCTCCTCCATTACCG-

3′) and ATUB-1603R (5′-TGGACGAAGGCACGCTTAGAG-

3′). Part of the �-tubulin gene was amplified with the

primers BTUB-21F (5′-ATGCGTGAAATCGTACGTCAC-3′)and BTUB-615R (5′-TGACCGAAAGGACCAGCACG-3′). PCR

reactions were carried out in 20 �l volumes containing 2 �l 10×PCR buffer, 0.1 mM of each dNTP, 0.5 �M of each primer,

0.5 U of Taq polymerase (New England BioLabs, Allschwil,

Switzerland), and 5 �l of genomic DNA (5–20 ng final DNA

1420 EVOLUTION JUNE 2008


concentration). PCR conditions for ITS included a denaturing

step at 96◦C for 2 min, followed by 35 cycles at 96◦C for 1

min, 55◦C for 1 min, and 72◦C for 1 min. Finally, a 5-min

PCR extension was carried out at 72◦C. PCR amplifications for

the other three genes were the same as for ITS except that an-

nealing cycles were carried out at 50◦C for EF-1�, at 56◦C for

�-tubulin and at 65◦C for �-tubulin. For the R. orthosporum

isolates the annealing temperature had to be lowered to 53◦C to

amplify �-tubulin and �-tubulin.

Amplification products were electrophoresed on 1% agarose

gels to verify the amplification of a single fragment of the appro-

priate length. Amplified products were purified using a Millipore

multiscreen PCR plate (MANU 030 PCR) following the manufac-

turer’s instructions. The purified PCR products were resuspended

in 20 �l of water and sequenced bidirectionally with ABI PRISM

BigDye Terminator v3.0 and 3.1 ready reaction cycle sequencing

kit (Applied Biosystems, Foster City, CA). The sequencing reac-

tion was conducted in a final volume of 10 �l containing 0.4 �l

ready reaction mix, 1.6 �l 5× reaction buffer (400 mM Tris-HCL,

pH 9.0, 10 mM MgCl2), 1 �M primer, and 5 �l of the purified

PCR product. The DNA samples were sequenced with an ABI-

3100 automated sequencer.

PHYLOGENETIC ANALYSES

DNA sequences were aligned and edited manually with Se-

quencher 4.5 (Gene Codes Corporation, Ann Arbor, MI). Iso-

lates were assigned to haplotypes, that is, to unique DNA

sequences at each sequence locus. Haplotypes and their frequen-

cies were obtained with the program MAP (Aylor et al. 2006)

and SITES version 1.1 (Hey and Wakeley 1997) by recoding

insertions or deletions (indels) and removing infinite site vi-

olations, as implemented in the SNAP Workbench (Price and

Carbone 2005). Redundant sequences were removed from the

datasets by choosing only one individual for each sequence

haplotype.

Two tree-building methods were used, namely maximum par-

simony (MP) and Bayesian maximum likelihood (BML), which

were performed in PAUP∗ version 4.0b10 (Swofford 2002) and

MrBayes 3.0b4 (Ronquist and Huelsenbeck 2003), respectively.

The program Modeltest 3.7 (Posada and Crandall 1998) was used

to assess which model of nucleotide substitution best fit the data

of each locus for BML under the Akaike information criterion

(AIC). The trees were rooted with sequences from the only other

described Rhynchosporium species, R. orthosporum. For MP anal-

ysis, gaps were treated as fifth character states in heuristic searches

that were conducted following 100 replicates of random step-

wise addition and tree bisection-reconnection (TBR) for branch-

swapping. Branch support for all parsimony analyses was esti-

mated by performing 1000 bootstrap replicates with a heuris-

tic search consisting of 100 random-addition replicates for each

bootstrap replicate. All characters were equally weighted and un-

ordered.

Combining several independent loci can increase the accu-

racy and confidence of phylogenetic inference (Pamilo and Nei

1988; Takahata 1989; Rosenberg 2002). To test whether the data

of individual loci might be combined, that is, whether the gene

genealogies from the four loci were significantly different from

each other, the partition homogeneity test (PHT) (Farris et al.

1995) was used. The PHT used only informative characters and

100 replicates of simple stepwise-addition MP heuristic searches

(TBR; maxtrees = 500). However, methods to detect conflicts

among data partitions, such as the incongruence length difference

(ILD) test (implemented as the PHT in PAUP) could be poor indi-

cators of dataset combinability (e.g., Cunningham 1997; Dolphin

et al. 2000; Barker and Lutzoni 2002; Darlu and Lecointre 2002;

Dowton and Austin 2002). Therefore, congruence between gene

phylogenies was also estimated by visual inspection of topologies

and statistical support (Mason-Gamer and Kellogg 1996; Wiens

1998).

For BML analyses the optimal model selected under the AIC

implemented in Modeltest was specified as the prior for each

gene. MrBayes allowed different data partitions to be modeled

separately for the combined dataset (Ronquist and Huelsenbeck

2003). One cold and three incrementally heated Markov chains

were run simultaneously starting from random trees for 5,000,000

generations for the single loci, and for 10,000,000 generations for

the combined dataset. Trees were sampled every 500th generation

for the single loci and every 1000th generation for the combined

dataset, resulting in 10,000 trees of which 1000 were discarded

as the “burn-in.” At least two independent runs were performed

to ensure analyses were not converging on a local optimum. The

replicate runs were compared to confirm that the analyses reached

stationarity at similar likelihood scores by plotting the −lnL per

generation in the program Tracer 1.3 (Rambaut and Drummond

2003). After confirming that the replicate runs reached stationarity

at similar likelihood scores and that the topologies were similar,

the remaining trees of the separate runs were pooled together and

used for calculating the posterior probabilities in the 50% majority

rule consensus tree in PAUP.

COALESCENT ANALYSES

The ancestral history of the host-associated populations of the

fungus was inferred by coalescent-based gene genealogies. The

analysis was conducted in the SNAP Workbench (Price and Car-

bone 2005) that contains a series of programs described below

to reconstruct the history of haplotypes. Guidelines in Carbone

et el. (2004) were followed for each analysis. Sequences were

collapsed into unique haplotypes using SNAP MAP (Aylor et al.

2006) and SITES version 1.1 (Hey and Wakeley 1997) by recoding

indels and removing infinite site violations. Prior to the application



of coalescent methods, the absence of selection and recombina-

tion had to be verified. Therefore, deviation from neutrality was

measured by Fu and Li’s D∗ and Fu and Li’s F∗ (Fu and Li 1993)

and Tajima’s D (Tajima 1989) with DnaSP version 4.0 (Rozas

et al. 2003). Incompatibility matrices were generated to detect in-

compatibility among segregating sites in SNAP Clade (Markwordt

et al. 2004) and SNAP Matrix (Markwordt et al. 2004).

Migration matrices indicating the number and direction of

migrants exchanged between populations were constructed in

the program MIGRATE (Beerli and Felsenstein 1999, 2001).

MIGRATE estimates the product of effective population size and

mutation rate, and the amount and direction of gene flow between

the host-associated populations. The analysis included 20 short

chains with 500 sampled genealogies each and 5 long chains with

5000 sampled genealogies each. Chain heating was adaptive, with

four different temperatures. The migration matrices were used as

starting backward migration matrices for coalescent analysis with

population subdivision in the program GENETREE version 9.0

(Griffiths and Tavare 1994; Bahlo and Griffiths 2000) as incor-

porated in the SNAP workbench. GENETREE reconstructs the

ancestral history of haplotypes showing a coalescence tree with

relative time of divergence between host-associated pathogen pop-

ulations. The genealogy with the highest root probability was de-

termined by performing 500,000 simulations of the coalescent

with five different starting random number seeds. From these runs,

the tree with the highest root probability was selected showing

the distribution of mutations along the branches of the pathogen

populations.

DIVERGENCE TIME ESTIMATES AND DEMOGRAPHIC

ANALYSIS

The Bayesian Markov Chain Monte Carlo (MCMC) method im-

plemented in the program BEAST version 1.4.1 (Drummond and

Rambaut 2005) was used to estimate time of divergence between

host-associated populations of the pathogen, that is the time to

the most recent common ancestor (TMRCA), and past popula-

tion dynamics. Kasuga et al. (2002) proposed a range of mutation

rates for the Eurotiomycetes, a monophyletic class of Ascomycota.

We applied these mutation rates representing the lower end, the

mean, and the upper end of the range, that is, 0.9 × 10−9, 8.8 ×10−9, and 16.7 × 10−9 mutations per site and per year. The anal-

ysis was conducted with the multilocus dataset as the program

allows partitioning the combined datasets. Different evolutionary

substitution models can be included for each partition and ap-

plied simultaneously. The substitution models specified for each

gene were the same as obtained under the AIC in Modeltest. Esti-

mates assuming a strict molecular clock were compared to those

performed using the relaxed molecular clock option with uncor-

related, branch-specific rates following lognormal or exponen-

tial distribution (Drummond et al. 2006). BEAST also infers the

demographic history of lineages in a Bayesian coalescent-based

framework. The Bayesian skyline plot (BSP) (Drummond et al.

2005) was specified as demographic model because it can fit a

wide range of demographic scenarios. The MCMC analyses were

first performed with short runs with chain length of 106 to op-

timize the scale factors of the priors. The analysis was then run

for 108 generations sampling every 1000th iteration after an ini-

tial burn-in of 10%. The performance of the MCMC process was

checked for stationarity and large effective sample sizes in Tracer.

The mean and corresponding credibility intervals of the estimated

parameters and the BSP were depicted using Tracer.

PATHOGENICITY ASSAYS

To determine whether Rhynchosporium isolates from each phy-

logenetic lineage (see Results) could infect hosts of other phy-

logenetic lineages, barley, rye, and H. murinum were inoculated

with representative isolates from each lineage originating from the

same geographical region, in this case Switzerland. Pathogenic-

ity is here defined as the ability of a fungal isolate to infect a

host species. In this case pathogenicity was used as a phenotypic

marker to assess species boundaries and host specialization.

The isolates for the pathogenicity tests were a representa-

tive sample including different Swiss locations, collection years,

and genotypes. Two trials were undertaken. In the first trial,

only isolates from cultivated grasses were used. The 16 selected

isolates originated from fields planted to barley, rye, and triti-

cale. The seven barley-infecting isolates 99CH2A2B, 99CH5E4A,

99CH5E6B, 99CH5H10A, 99CH6C3A, 99CH6E3B, and 00A1B,

originated from collections of 1999 and 2000 that were de-

scribed previously (Linde et al. 2003; Zaffarano et al. 2006).

Four of the eight rye-infecting isolates (99CH1E7A, 99CH1B8,

99CH1H10B, and 99CH1D4A) were collected in 1999 as de-

scribed earlier (Zaffarano et al. 2006). The remaining isolates

(02CH4-14a.1, 02CH4-9a.2, 02CH4-5a.1, and 02CH4-6a.1) were

collected in 2002 from a rye field near Maur in the canton of

Zurich, whereas the isolate 02CH2-3c.1 was collected from triti-

cale at the experimental station of Changins in the canton of Vaud

in 2002.

To produce inoculum, all isolates were grown from sil-

ica gel storage onto Difco lima bean agar (Becton, Dickinson

and Co., Sparks, MD) amended with kanamycin (50 mg/L).

Plates were incubated for 14 days at 18◦C in the dark. Colonies

were then transferred to fresh lima bean agar plates and in-

cubated under the same conditions as above. After 14 days

spores were harvested by adding 2 mL of sterile water to each

plate and scraping spores off the agar surface with a steril-

ized microscope slide. A portion of the spores from each iso-

late was transferred into 1.8 mL CryoTubes (Nunc Cryoline Sys-

tems, Roskilde, Denmark) containing anhydrous silica gel (Fluka

Chemie GmbH, Steinheim, Germany) for long-term storage at



−80◦C. The rest of the spore suspension was spread across

the surface of 20–50 fresh lima bean agar plates. The plates

were incubated at 18◦C and after 14 days spores were harvested

as above and filtered through two layers of cheesecloth. Spore

concentrations were adjusted to 2 × 105 spores/mL with a hema-

cytometer (Thoma cell, 0.1-mm depth, 0.0025 mm2) in a spore

solution of 150 mL per isolate.

Inoculations were conducted on four barley (Chariot, Julia,

Pasadena, and Plaisant) and four rye varieties (Avanti, Born,

Danko, and Picasso). These varieties ranged from moderately to

highly susceptible to scald. All host varieties were grown in pots

with a diameter of 13 cm filled with soil mixture Rasenerde Top

Dressing (containing sand, compost, perlite, white peat, and min-

eral fertilizer; Ricoter AG, Aarberg, Switzerland). Seeds of each

host variety were sown separately in pots and thinned to five plants

per pot.

The plants were grown in a single greenhouse chamber with

a photoperiod of 14 h-day at 18◦C and a 10 h-night period at 15◦C.

Relative humidity was set at 60%. The seedlings were inoculated

when they had two to three fully emerged leaves. Two drops of

Tween 20 (Sigma-Aldrich, Buchs, Switzerland) were added to 150

mL of spore suspension. For each isolate, three pots of each variety

were inoculated. For inoculation, all 24 pots were placed onto a

rotating table in a semiautomatic inoculation chamber and the

leaves were sprayed with a fine mist until run-off. An additional

set of 96 pots, that is, 6 pots per each inoculated isolate, containing

all host varieties, was sprayed with sterilized water amended with

two drops of Tween 20 as a negative control. The inoculated pots

were kept for 48 h at a relative humidity of 90–100%.

After 14 days disease was assessed on the second and third

leaves following the scale described in Ali and Boyd (1973). The

ratings were 0 = no visible lesion or symptoms, 1 = small lesions

at the tip or on the margin and base of the leaf blades, 2 = nar-

row band of lesions extending down the length of the leaf blade,

3 = broad well-developed lesions covering large areas across leaf

blade, 4 = leaves wilted, no evidence of discrete lesions. Reac-

tion 0 was considered highly resistant, reaction 1 was resistant,

reaction 2 was intermediate, and reactions 3 and 4 susceptible

and highly susceptible, respectively. This inoculation trial was re-

peated one month later using a higher inoculum concentration of

106 spores/mL.

In the second trial, Rhynchosporium isolates from uncul-

tivated grasses were included for pathogenicity testing. Six

Rhynchosporium isolates from A. repens (Danikon-1.1.1, WPK-

5b.1A3.1, K2B-2C1.1, Brutten-3.1.2, RAC-2-A9.1, and SEG

A3.2.1.1) and two from H. murinum (WPK-2.1 and WPK-A8.4)

that were inoculated onto two of the previously used barley (Char-

iot and Pasadena) and rye varieties (Danko and Picasso), as well as

on H. murinum. The isolates from A. repens were collected at the

borders of cereal fields in the canton of Zurich and at the experi-

mental station of Changins in the canton of Vaude in Switzerland,

except SEG-A3.2.1.1 which was collected from A. repens plants

bordering the road on the Sattelegg pass in canton Schwyz in

Switzerland. The isolates from H. murinum were collected from

weedy plants growing alongside streets in Zurich. Seed was har-

vested from these plants for inoculation trials. Two previously used

isolates, one each from barley (00CHA1B) and rye (99CH1E7a),

were included as control isolates. The barley and rye varieties as

well as H. murinum were represented by three pots each with five

seedlings per pot. In total 10 inoculations were applied for a total

of 150 pots. The negative control, sprayed with water and Tween,

was represented by 60 pots, that is, six pots containing all host va-

rieties and H. murinum per inoculated isolate. The second trial was

repeated once. Procedures for the isolate culturing, inoculation,

and disease assessment were the same as for the first inoculation

trial, except that the spore concentration was 106 spores/mL for

both the first experiment and the repetition.

ResultsNUCLEOTIDE SEQUENCES AND PHYLOGENETIC

ANALYSES

The ITS region (848 bp), portions of the �-tubulin (1609 bp), �-

tubulin (609 bp), and the EF-1� (365 bp) (sizes including gaps)

were amplified for all isolates. Summaries of the phylogenetic in-

formation for the four loci are shown in Table 2. There were 24, 20,

15, and 11 parsimony informative characters, respectively for each

locus (Table 2). Haplotypes representing one of each set of iden-

tical sequences were used for analysis. The haplotypes defined by

the variable sites of the datasets are reported in the online Supple-

mentary Table S1. Haplotypes were shared only between either

populations from rye and triticale, or between populations from

barley, H. leporinum, H. murinum, and H. spontaneum (Hordeum

spp.) and B. diandrus for all loci. The single isolate from A. can-

inum always grouped with the haplotypes formed by the A. repens

isolates. Haplotype H1 occurred most frequently for each respec-

tive locus, and was represented in most of the sampled geograph-

ical populations originating from barley, as well as in Hordeum

spp. and B. diandrus. Conversely, many haplotypes were unique

to one population or host species (see online Supplementary

Table S1).

The MP and BML analyses were used to infer genealogies

of the haplotypes from the four single-locus alignments (Table 2,

Fig. 1, and see online Supplementary Figs. S1–S4). BML analysis

of the four loci followed an optimal evolutionary model selected

under the AIC in Modeltest. These models were different for each

gene (Table 2). All repeated runs of the BML analyses converged

on the same topology. The topological patterns were consistent

across the MP and BML estimations of the phylogeny for all loci

except for minor differences as described below.



Table 2. Phylogenetic information of the genomic regions used in this study for the individual and combined datasets.

DNA sequence region

�-tubulin �-tubulin EF-1� ITS Combinedb

Number of isolates 316 316 316 316 316Number of sites 1609 609 365 848 3066Number of haplotypes 18 25 15 25 46Nucleotide characters, excluding indels 1592 592 348 843 3027Coded characters (indels) 17 17 17 5 39Constant charactersa 1571 575 332 812 2958Parsimony informative charactersa 20 15 11 24 59Variable, parsimony uninformative 1 2 5 7 10charactersa

Percent informative characters (%)a 1.26 2.53 3.16 2.85 1.95MP tree length 233 135 106 105 488No. of equally parsimonious trees 30 >10,000 8 354 720

CIc 0.996 0.926 0.979 0.876 0.926RIc 0.997 0.963 0.987 0.935 0.974

Modeld F81+I HKY+I F81 Tnef+IBase frequencies

A 0.2635 0.2861 0.2492 Equal frequenciesC 0.2186 0.1929 0.3161G 0.2901 0.2702 0.1662T 0.2278 0.2508 0.2685

Substitution model All rates equal Ti/Tve ratio = 0.1688 All rates equal A→C = 1.000A→G = 3.184A→T = 1.000C→G = 1.000C→T = 8.649G→T = 1.000

Among-site rate variationIf 0.9315 0.9447 0 0.8583Gg Equal rates for Equal rates for Equal rates for Equal rates for

all sites all sites all sites all sites

aRefers to ingroup taxa only.bCombined �-tubulin, �-tubulin, ITS.cRefers to the strict consensus tree.dBest-fit evolutionary models and parameters for each dataset selected by the Akaike information criterion (AIC) in Modeltest (Posada and Crandall 1998).eRatio between transitions and transversions.fProportion of invariable sites.gVariable sites gamma distribution parameter.

�-tubulinBoth MP and BML methods showed three lineages of haplotypes

based on host association, although branch support and resolution

was poor (see online Supplementary Fig. S1). Lineage A consisted

of those haplotypes representing the isolates from barley, other

Hordeum spp. and B. diandrus, lineage B the haplotypes from

A. caninum and A. repens (Agropyron spp.), and lineage C those

from rye and triticale consisting of two monophyletic clades. Lin-

eage B was well supported (98% bootstrap support, 1.0 Bayesian

posterior probability, bpp), but formed a clade with lineage A.

This larger clade was well supported in the BML analysis (0.94

bpp) but less supported by the MP analysis (62% bootstrap sup-

port). Lineage C consisted of two clades with 85–99% bootstrap

support and 1.0 bpp, respectively.

�-tubulinThe tree topology was identical for the MP and the BML trees.

As for �-tubulin, three lineages of haplotypes were identified (see

online Supplementary Fig. S2). Again, lineage A contained all

haplotypes infecting barley, Hordeum spp., and B. diandrus. As

for �-tubulin, the bootstrap support for this monophyletic clade

was not high using the MP method (67%) but was high using



Figure 1. Phylogeny inferred by maximum parsimony from the combined �-tubulin, �-tubulin, and ITS DNA sequence loci. The 50%

majority-rule consensus tree is shown. Bayesian maximum-likelihood analysis recovered the same topology. The numbers above branches

are bootstrap frequencies of 1000 replicates and those below are Bayesian posterior probabilities. Branch lengths are proportional to

the number of steps (character changes) along the branch. Labels on the phylogeny are: H1–H45 haplotypes obtained from 316 DNA

sequences of 3066 bp representing Rhynchosporium isolates from different hosts (Agropyron spp., barley, Bromus diandrus, Dactylis

glomerata, Hordeum spp., rye and triticale). Haplotypes H2–H4 representing Rhynchosporium orthosporum were used as outgroup.



the BML method (0.97 bpp). The monophyletic lineage B in-

cluded haplotypes infecting Agropyron spp. (69% bootstrap

support, 1.0 bpp). Lineage C contained the haplotypes infect-

ing rye and triticale. This lineage could be distinguished from

lineages A and B, but resolution was poor and did not form a

monophyly.

EF-1�

Both MP and BML showed a tree topology consisting of host-

associated lineages A and B (see online Supplementary Fig. S3).

Resolution and branch support for the lineages were low (see

online Supplementary Fig. S3). Lineage A contained isolates in-

fecting barley, Hordeum spp., B. diandrus, rye, and triticale. The

support for this monophyletic lineage A was weak (bootstrap sup-

port 63% and 0.62 bpp).

ITSThe phylogeny of the ITS region (see online Supplementary Fig.

S4) showed the same host-associated lineages as �- and �-tubulin

for both the MP analysis and the BML analysis. However, the

rye- and triticale-infecting haplotypes(lineage C) formed a mono-

phyletic clade that was well supported (99% bootstrap support;

1.00 bpp). Similar tree topologies were obtained with MP and

BML. The BML analysis gave higher support, and in contrast to

the MP method, lineage C was placed into a larger clade with

lineage A. Furthermore, in the BML analysis not all haplotypes

from lineage B formed a unique monophyly.

Combined datasetPHTs were performed in pairwise comparisons and globally

to determine which datasets could be combined for phyloge-

netic analyses. The PHT of the full dataset, combining all four

loci, indicated that the datasets could not to be combined (P <

0.01). Although EF-1� had the highest percentage of informa-

tive characters (Table 2), these differences were mostly confined

to haplotypes associated with A. repens. When EF-1� was re-

moved from the dataset, the P-value increased to 0.18. The host-

associated haplotype distinctions were the same for all four in-

dividual loci (see online Supplementary Table S1). Therefore,

we believe that the short sequence length of the EF-1� gene

led to a low phylogenetic resolution detected by the PHT rather

than representing a different evolutionary history compared to

other genes. The P-value testing congruency between ITS and

�-tubulin was lower (0.35) than between ITS and �-tubulin

(P = 0.87). Compatibility between the �-tubulin and �-tubulin

datasets was low (P < 0.05), although the three sequence loci

could still be combined according to the PHT. The �-tubulin,

�-tubulin, and ITS datasets were combined despite the minor dif-

ferences in tree topologies because the PHT was not significant

and the associations between haplotypes and different hosts were

consistent.

The phylogeny of the combined �-tubulin, �-tubulin, and ITS

datasets resulted in three well-supported distinct monophyletic

lineages (Fig. 1) using both BML and MP analyses. Lineage A

consisted of haplotypes present on barley, Hordeum spp., and

B. diandrus. In contrast to the phylogenies of the single loci, this

lineage was well supported by the MP method (83% bootstrap

support) and by the BML analysis (1.0 bpp). Lineage B contained

all Agropyron spp. infecting haplotypes. Lineage C contained all

rye- and triticale-infecting haplotypes and was highly supported

(100% bootstrap support) in MP and BML trees (1.0 bpp). The

phylogenetic analyses thus support that R. secalis should be split

into three Rhynchosporium species, corresponding to isolates from

lineages A–C.

COALESCENT ANALYSES

Incompatible sites due to recombination or homoplasy were iden-

tified in the incompatibility matrix for all four loci and removed

from the datasets as follows: one site was removed for �-tubulin,

six sites for �-tubulin, two sites for EF-1�, and seven sites for ITS.

Both Fu and Li’s D∗ and F∗ tests, as well as Tajima’s D were not

significantly different from 0 (P > 0.10; see online Supplementary

Table S2). Therefore, the hypothesis of selective neutrality could

not be rejected for any of the four loci. The datasets from which

the incompatible segregating sites were removed were then used

for coalescent analysis. Independent estimates of gene flow for the

four single loci gave similar results (data not shown). Migration

matrices calculated by MIGRATE indicated low gene flow be-

tween the different Rhynchosporium host-associated populations

(i.e., Nm < 1) except between the populations on rye and triti-

cale (Nm = 1.46-7.85) and between populations on barley and

Hordeum spp. (Nm = 0.45-4.60).

Simulations in GENETREE provided coalescent-based ge-

nealogies for each locus showing the ancestral distribution of mu-

tations and coalescence events (Figures not shown). These results

were congruent with the phylogenetic trees inferred by MP and

BML. All four loci showed three distinct lineages as inferred by

the phylogenetic analysis. When included as an outgroup, the R.

orthosporum population branched at the deepest point of the ge-

nealogies for separate as well as combined sequence loci (Figures

not shown). All three lineages coalesced to a single common an-

cestor. To provide an enhanced resolution of the ancestral history

of these fungal populations, �-tubulin, �-tubulin, and ITS were

combined in another coalescent analysis. In this analysis, 26 in-

compatible sites had to be removed from the combined dataset

resulting in 27 haplotypes. The two distinct lineages A (on barley,

B. diandrus and Hordeum spp.), and B (on Agropyron spp.) were

derived from the same common ancestor (Fig. 2), with coales-

cence at a relative coalescent time of approximately 0.7. Most of

the mutations separating the three distinct lineages emerged re-

cently, that is, between the relative coalescent times of 0 to 0.2.



Figure 2. Coalescent-based gene genealogy of the combined �-tubulin, �-tubulin, and ITS DNA sequence loci showing the distribution

of mutations in Rhynchosporium populations on different hosts (barley; Hordeum spp. = H. leporinum, H. murinum, H. spontaneum; ∗ =

includes two isolates from Bromus diandrus; Agropyron spp. = Agropyron repens and Agropyron caninum; triticale, rye) that correspond

to the three phylogenetic lineages as shown in Figure 1. The numbers below the tree branches describe the different haplotypes and the

number of occurrences in total and on the different hosts. The temporal scale of divergence is given on the right. The scale is in coalescent

units of effective population size. The direction of the appearance of mutations and bifurcations is from the top (past) to the bottom

(present).



DIVERGENCE TIME ESTIMATES AND DEMOGRAPHIC

ANALYSIS

The Bayesian MCMC sampling procedures implemented in

BEAST allowed estimating the posterior distribution of the TM-

RCA and effective population size through time. The analysis

included credibility intervals [highest posterior density (HPD)]

representing both phylogenetic and coalescent uncertainty. The

posterior mean estimates of the TMRCAs and corresponding

95% HPDs are shown in Table 3. Estimates assuming a strict

molecular clock were similar to those based on a relaxed clock

with exponential distribution. Under the relaxed clock model with

log-normal distribution the majority of the divergence time esti-

mates were higher. No fossil ages were available for R. secalis

to be specified as node priors to estimate the mutation rates for

the three loci used. To compensate, three mutation rates span-

ning the entire range of mutation rates suggested for other fungi

(Kasuga et al. 2002) were chosen in the analysis. The posterior

mean estimate for the TMRCAs and corresponding HPDs that

were obtained using these three mutation rates were combined

and averaged in the program Tracer. Thus, we here refer to the av-

eraged posterior mean estimates of the TMRCA and 95% HPDs.

Depending on the clock model implemented, the posterior mean

estimates of the TMRCA of all isolates, including R. orthosporum,

were between 14,443 to 35,199 years B.P. (95% HPD, 1246 to

101,891) (Table 3) suggesting an older split from the ancestor

of the lineages A–C. The posterior mean estimates of the TM-

RCA of all three lineages A–C were between 1281 to 3627 years

B.P. (95% HPD, 113 to 12,431). The diversification within the

three lineages began more recently and started during a similar

time frame for all three lineages with posterior means of the TM-

RCA between 459 and 1139 years B.P. (95% HPD, 21 to 3,853)

(Table 3 and Fig. 3).

The historical demographic reconstructions (BSP) shown in

Figure 4 depict similar demographic histories for all three muta-

tion rates and clock options used (data not shown). The population

size of the three lineages started to decline almost simultaneously

with the split of the three lineages ∼ 1200 to 3600 years ago (Fig.

4) until they reached a maximum decline between ∼ 250 and

500 years ago, followed by a rapid expansion that recovered the

prebottleneck population sizes (Fig. 4).

PATHOGENICITY ASSAYS

A total of 24 isolates from different hosts were inoculated onto

barley and rye cultivars, and a subset of these isolates was inocu-

lated onto H. murinum. Isolate 02CH2-3c.1 from triticale was able

to infect the four rye cultivars and isolates WPK-2.1 and WPK-

A8.4 from H. murinum were able to infect two barley cultivars in

addition to H. murinum plants. All other isolates infected only the

host from which they were originally isolated. Thus there was no

cross pathogenicity on hosts of isolates from different phyloge-

netic lineages. Due to difficulties in propagating A. repens plants,

this host could not be included in the trial as a positive control for

isolates from A. repens. Disease severity on infected plants ranged

from 1 to 4 based on the disease assessment scale of Ali and Boyd

(1973) (Table 4).

DiscussionIn a previous population study on R. secalis using RFLP markers,

high population subdivision and a low number of shared alleles

among barley- and rye-infecting populations were interpreted as

evidence for genetic isolation between the host populations de-

spite the geographical proximity of the two hosts in Switzerland

(Zaffarano et al. 2006). In this study additional isolates infect-

ing rye and other uncultivated grasses were included to further

investigate genetic isolation between host-associated populations

of the pathogen. Our analyses assigned R. secalis isolates to three

distinct lineages: Lineage A infecting cultivated barley, Hordeum

spp. and B. diandrus; Lineage B infecting rye and triticale, and;

Lineage C infecting Agropyron spp. We propose that these lin-

eages should be defined as three species of Rhynchosporium in

addition to R. orthosporum infecting D. glomerata.

Several lines of evidence support the proposed species split:

(1) population genetic data (Zaffarano et al. 2006) demonstrated

the absence of gene flow between populations of Rhynchosporium

from rye and Hordeum spp., (2) sequences from four independent

loci indicated that three evolutionary lineages could be assigned

to unique haplotypes according to their hosts, showing ecological

specialization, (3) the phylogeny of the combined loci showed a

highly supported monophyletic grouping of these haplotypes, (4)

coalescence analysis revealed independent evolution of the three

lineages, and (5) host-association for the three lineages was con-

firmed with pathogenicity tests. Because R. secalis was first de-

scribed on rye (Oudemans 1897), this name should be retained for

Rhynchosporium isolates infecting rye and triticale. Rhynchospo-

rium isolates infecting cultivated barley and other Hordeum spp.

and B. diandrus, belong to a different species that should be given

a new name. Similarly, isolates infecting Agropyron spp. should

also be described as a new species of Rhynchosporium.

The genetic isolation and subsequent speciation among these

lineages is likely due to host specialization, which is common

in pathogenic fungi (Leppik 1965; Parlevliet 1986; Wyand and

Brown 2003). Domestication of plant hosts can be a factor driv-

ing host specialization and subsequent fungal speciation (Kohn

2005). As the evolutionary history of a pathogen is often tightly

linked to that of its host (Fisher et al. 2001; Falush et al. 2003), re-

constructing the population history of one component of the host-

pathogen association may be useful to reconstruct the evolutionary

history of the other component if they have coevolved (Wirth et al.

2005; Blaser 2006; Nieberding and Olivieri 2006). We therefore



Table 3. Bayesian estimates of the time (in thousands of years) to the most recent common ancestor (TMRCA) of Rhynchosporium populations

on different hosts corresponding to three phylogenetic lineages A–C. Values in parentheses are 95% highest posterior densities intervals.

The divergence time estimates were calculated under the assumption of three mutation rates adopting different molecular clock models

as implemented in BEAST version 1.4.1 (Drummond and Rambaut 2005). The mean values of the three analyses were estimated with the

program TRACER 1.3 (Rambaut and Drummond 2003).

Mutation rates per site per year

TMRCA Clock model Combined 0.9×10−9 8.8×10−9 16.7×10−9

ClockAll sequences including Rhynchosporiumorthosporum

35.199 90.837 9.509 5.010orthosporum (3.628–101.891) (71.093–112.121) (7.407–11.773) (4.965–3.876)

Lineage A on barley/Hordeum spp./ 0.510 1.322 0.137 0.072Bromus diandrus (0.036–1.638) (0.775–1.952) (0.080–0.201) (0.042–0.106)Lineage B on Agropyron spp. 0.459 1.194 0.120 0.063

(0.021–1.636) (0.491–2.023) (0.052–0.206) (0.026–0.107)Lineage C on rye/triticale 0.463 1.194 0.127 0.067

(0.027–1.560) (0.566–1.922) (0.061–0.203) (0.032–0.106)Lineages A+B on barley/Hordeum 1.291 3.347 0.345 0.181spp./Bromus diandrus and onAgropyron spp.

(0.095–4.028) (2.127–4.632) (0.218–0.475) (0.116–0.252)

All three lineages A+B+C 1.399 3.625 0.375 0.198(0.120–4.247) (2.487–4.791) (0.260–0.498) (0.136–0.262)

Relaxed exponentialAll sequences including 14.443 37.800 3.577 1.953Rhynchosporium orthosporum (1.246–43.732) (25.419–48.987) (2.450–4.751) (1.376–2.570)Lineage A on barley/Hordeum spp./ 0.811 2.111 0.214 0.108Bromus diandrus (0.063–2.499) (1.398–2.878) (0.142–0.294) (0.072–0.148)Lineage B on Agropyron spp. 0.685 1.772 0.184 0.098



(0.104–3.669) (2.192–4.144) (0.226–0.426) (0.119–0.225)


Relaxed lognormalAll sequences including Rhynchosporiumorthosporum

26.853 69.562 7.281 3.715(1.685–89.040) (37.060–120.359) (3.844–12.519) (2.006–6.355)

Lineage A on barley/Hordeum spp./ 1.139 2.958 0.299 0.158Bromus diandrus (0.069–3.853) 1.411–4.855) (0.142–0.488) (0.079–0.258)Lineage B on Agropyron spp. 1.015 2.633 0.269 0.141



(0.101–12.019) (2.797–15.468) (0.257–1.551) (0.146–0.819)


evaluated what role the history of barley and rye cultivation played

in promoting genetic isolation of Rhynchosporium populations on

different hosts. Plant pathogens are usually assumed to have origi-

nated on the direct ancestors of their modern hosts and to have co-

evolved with them during domestication at the place of domestica-

tion (the domestication hypothesis). It was shown that M. oryzae,

an important pathogen on rice, originated from a host shift from

Setaria millet (Couch and Kohn 2002; Couch et al. 2005). This



Figure 3. Bayesian posterior probability densities (bppds) of the TMRCA of Rhynchosporium on different hosts corresponding to three

phylogenetic lineages A–C as shown in Figure 1. These bppds assumed a strict molecular clock model and a mutation rate of 0.9 × 10−9

per site per year. Higher mutation rates and relaxed molecular clock models gave similar values.

host shift was possibly associated with rice domestication and was

brought about by the loss of an avirulence gene that allowed the

fungus to adapt to rice and diverge from other ancestral lineages

(Couch et al. 2005). In another study (Stukenbrock et al. 2007),

the wheat pathogen M. graminicola was shown to be derived from

an ancestral population of Mycosphaerella species present on wild

grasses in the Middle East. Coalescent analysis indicated that the

pathogen started to infect wheat around 10,000 years ago, during

the same time frame when the progenitors of wheat began to be do-

mesticated in the Middle East. Gradual adaptation of the fungus to

domesticated wheat and a gradual decrease in gene flow between

the Mycosphaerella population infecting wheat and the population

on wild grasses led to today’s host-specialized M. graminicola,

which has spread to cultivated wheat populations around the

world. In both cases the pathogen species fit the domestica-

tion hypothesis, rapidly adapting to their modern host during

the process of host domestication, not longer than 10,000 years

ago.

Divergence time estimates were calculated for the three Rhyn-

chosporium lineages A–C in this study. The means of the com-

bined estimates calculated in BEAST indicated that the split

of the three lineages occurred recently, between ∼ 1200 and

∼ 3600 years B.P. with a 95% HPD ranging from ∼ 100

to ∼ 12,000 years B.P. depending on the implemented clock

models. These dates suggest that the emergence of the scald

pathogen was associated with the onset of agriculture. The up-

per ends of the HPD intervals indicate that the adaptation of

the pathogens to their hosts coincides with the beginning of the

domestication of barley around 10,000 years B.P. (Badr et al.

2000; Salamini et al. 2002) thus supporting the domestication

hypothesis. Similar to the Mycosphaerella pathogen on wheat,

the Rhynchosporium pathogen could have shifted and adapted



Figure 4. Bayesian Skyline Plots (BSP) (Drummond et al. 2005)

show fluctuations of effective population sizes through time. The

x-axis is in units of thousands of years before present, and the y-

axis is equal to Ne� (the product of the effective population size

and the generation length). The thick solid line is the median esti-

mate, and the gray areas show the 95% highest posterior density

(HPD) limits. The thin-dashed line shows the lower 95% HPD limit

of the time to the most recent common ancestor (TMRCA) and the

thick-dashed line the mean of the TMRCA of lineages A–C corre-

sponding to Figure 1. The presented BSPs were based on analyses

that assumed a strict molecular clock model and a mutation rate

of 0.9 × 10−9 per site per year. Higher mutation rates and relaxed

molecular clock models gave similar demographic histories. The

profiles indicate a decline of population size since the TMRCA of

all three lineages and rapid recoveries from the bottleneck ∼ 250

years B.P.

from an ancestral population on wild grasses onto domesticated

barley and rye during the beginning of agriculture in the Fertile

Crescent.

As H. spontaneum is the progenitor of cultivated barley (Zo-

hary and Hopf 1988; Badr et al. 2000) and still widely distributed

in the Fertile Crescent, the Middle Eastern populations from

H. spontaneum included in this study were expected to represent

the closest relatives of the ancestral population of the pathogen

on barley. Moreover, as domesticated rye is a younger crop

than barley (Zohary and Hopf 1988; Bushuk 2001), the fungal

populations on rye were expected to be derived from those on

H. spontaneum or cultivated barley. Surprisingly, the coales-

cent analysis indicated that the mutations found in isolates in-

fecting H. spontaneum were all relatively recent. Furthermore,

Rhynchosporium associated with rye did not originate from

Hordeum spp. or cultivated barley populations, but instead the lin-

eages evolved in parallel. The rooted coalescent genealogy showed

that all three lineages A–C split from a common ancestor and none

of the lineages can be regarded as ancestral to the other. Thus the

barley- and rye-infecting populations most likely did not origi-

nate from each other, or from H. spontaneum, but instead origi-

nated from an unidentified common ancestor. Rhynchosporium

orthosporum diverged from the other Rhynchosporium lin-

eages prior to the domestication of cereals. Hence the split of

R. orthosporum from the ancestor of lineage A–C is ancient and

not associated with the advent of agriculture.

In contrast, the means of the divergence time estimates and

the lower ends of the HPD intervals suggest an even more re-

cent emergence of the scald pathogen. These values are consistent

with the divergence time estimates based on the nucleotide se-

quences of the NIP1 avirulence gene present in R. secalis. The

sampled isolates from barley fields were shown to coalesce back

to a common ancestor that occurred between 2500 and 5000 years

B.P. (Brunner et al. 2007). We hypothesize that the ancestor of

the pathogen came into contact with the crops after the hosts had

been domesticated and probably after the hosts were introduced

into Europe, hence the recent divergence time. We support this

hypothesis with the findings of our previous studies (Zaffarano

et al. 2006; Brunner et al. 2007). Genetic diversity is expected to

be greatest in ancient populations compared to more recent, de-

rived populations because of their long-standing accumulation of

polymorphism. Allele richness measured at RFLP loci (Zaffarano

et al. 2006), microsatellite loci (C. C. Linde and B. A. McDonald,

unpubl. ms), and additional sequence loci (P. L. Zaffarano, B. A.

McDonald, and C. C. Linde, unpubl. ms) was shown to be highest

in the Rhynchosporium populations from northern Europe and low

in regions of ancient barley cultivation including the Middle East

and Ethiopia (Zaffarano et al. 2006). These findings are consistent

with a center of origin located away from the Fertile Crescent and

most probably in northern Europe as suggested in Zaffarano et al.



Table 4. Reaction of Rhynchosporium secalis isolates from different hosts on barley and rye varieties, and on Hordeum murinum.

Source of Isolate Disease reactiona

isolateBarley cultivars Rye cultivars H. murinum Control

plantsChariot Julia Pasadena Plaisant Avanti Born Danko Picasso seedlings

Barley 99CH2A2b 3–4 1–4 3–4 3–4 0 0 0 0 0 099CH5E4a 2–4 2–4 3–4 2–4 0 0 0 0 − 099CH5E6b 4 2–4 3–4 4 0 0 0 0 − 099CH5H10a 3–4 3–4 4 3–4 0 0 0 0 − 099CH6C3a 2–4 1–3 3–4 4 0 0 0 0 − 099CH6E3b 3–4 1–4 3–4 2–3 0 0 0 0 − 000CHA1b 2–4 1–4 1–4 1–4 0 0 0 0 − 0

Rye 99CH1E7a 0 0 0 0 3–4 3–4 2–4 1–4 0 099CH1B8 0 0 0 0 2–4 2–4 3–4 2–4 − 099CH1H10b 0 0 0 0 1–4 3–4 2–4 3–4 − 099CH1D4a 0 0 0 0 2–4 3–4 1–4 3–4 − 002CH4-5a.1 0 0 0 0 1–4 1–4 3–4 2–4 − 002CH4-6a.1 0 0 0 0 2–4 2–3 2 1–4 − 002CH4-9a.2 0 0 0 0 3–4 3–4 3–4 1–4 − 002CH4-14a.1 0 0 0 0 2–4 2–4 3–4 2–4 − 0

Triticale 02CH2-3c.1 0 0 0 0 3–4 2–4 1–4 1–4 − 0A. repens Brutten-3.1.2 0 − 0 − − − 0 0 0 0

Danikon-1.1.1 0 − 0 − − − 0 0 0 0K2B-2C1.1 0 − 0 − − − 0 0 0 0RAC-2-A9.1 0 − 0 − − − 0 0 0 0SEG-A3.2.1.1 0 − 0 − − − 0 0 0 0WPK-5b.1A3.1 0 − 0 − − − 0 0 0 0

H. murinum WPK-2.1 0–3 − 3 − − − 0 0 2–3 0WPK-A8.4 2–4 − 3–4 − − − 0 0 3–4 0

aDisease assessment was according to the scale described in Ali and Boyd (1973). Host-isolate combinations marked with ”-”were not tested.

(2006). Archeological remains of barley grains suggest that bar-

ley was first domesticated around 10,000 years B.P. (Badr et al.

2000; Salamini et al. 2002) in the Fertile Crescent. As a result of

Neolithic migrations, agriculture was brought to Europe ∼ 7500

B.P. (Salamini et al. 2002; Haak et al. 2005). The emergence of

the pathogen lineages coincides with the introduction of barley

and rye cultivation into northern Europe which has been dated to

∼5000 to 3000 B.P. (Price 1996; Bushuk 2001). Given that the

highest diversity for all genetic markers is in northern Europe pop-

ulations and that there is a decreasing gradient of genetic diversity

running from northern Europe to the Middle East (Brunner et al.

2007), we consider it most likely that Rhynchosporium emerged

recently as a barley and rye disease via a host shift that occurred

in northern Europe ∼ 1200 to 3600 years ago. Under this scenario

we falsify the domestication hypothesis, although the spread of

agriculture played a significant role in bringing a host into contact

with a new pathogen.

For other plant pathogens it was suggested that their center

of origin does not necessarily coincide with the center of origin

of their hosts. For example, the oomycete Phytophthora infestans

causing late blight on potatoes and the fungus Colletotrichum lin-

demuthianum causing anthracnose in common bean both have

their highest levels of genetic diversity in Mesoamerica whereas

their hosts originated in the Andes (Fry et al. 1992; Sicard et al.

1997; Grunwald and Flier 2005). However, coalescent analy-

ses showed that ancestral mutations in P. infestans originated

from the Andes, suggesting a South American origin of the

pathogen (Gomez-Alpizar et al. 2007). For C. lindemuthianum,

incongruence between the geographical origin of the pathogen

and its hosts is not completely confirmed because the com-

mon bean experienced independent domestication events in both

Mesoamerica and the Andes, and both areas developed into cen-

ters of diversity (Debouck 1986; Kami et al. 1995; Pickersgill

2007). It is important to note that general conclusions regard-

ing geographical origins of pathogens based solely on compar-

isons of genetic diversity are problematic. In this study, how-

ever, a combination of genetic diversity studies and divergence

time estimates for Rhynchosporium populations provide support

for a recent origin of the pathogen outside the host’s center of

origin.



An alternative scenario considers the possible loss of genetic

diversity in Rhynchosporium through a series of selective sweeps

associated with adaptation to its domesticated hosts. The BSPs

indicate a decline in population size for all three lineages after

they started diverging from each other. This could reflect a bottle-

neck that was experienced after the host shift from the ancestral

population onto the domesticated hosts through a combination of

selection for host specialization and genetic drift. Under this alter-

native scenario, the pathogen populations currently present on the

sampled hosts would have lost most of their ancient diversity, lead-

ing to an inability to reconstruct the true lines of descent among

the host-specialized lineages through the last 10,000 years. In this

case a divergence time coinciding with the beginning of barley

domestication would favor an origin of the pathogen in the Fertile

Crescent (i.e., supporting the domestication hypothesis). We con-

sider this alternative scenario to be less likely because it suggests

that selective sweeps occurred independently in all three lineages

and affected all the genes used in this study and in Brunner et al.

(2007). Moreover, although the sexual stage of the fungus has not

been observed in the field or induced in vitro, there is strong in-

direct evidence for regular sexual reproduction in the field (Linde

et al. 2003; Zaffarano et al. 2006). A recombining genome would

prevent single haplotypes from becoming fixed in field popula-

tions of the pathogen. The selective sweep scenario is therefore

considered less likely.

The diversification within lineages started between ∼ 460 and

1100 years B.P. with the 95% HPDs ranging from ∼ 20 to 3800

years B.P. The accumulation of polymorphism in the pathogen

populations likely increased with the expansion of the host popu-

lations in Eurasia and later in other continents. The demographic

growth reconstructions shown by the BSPs point to a recent re-

covery of the pathogen populations from the bottleneck that was

experienced after the host shift onto domesticated hosts. The rapid

increase in pathogen population sizes occurred during the last ∼250 years, coinciding with the global expansion and industrializa-

tion of agriculture and the Green Revolution. Recent population

expansion and diversification is also supported by the finding that

the majority of the mutations present in all three lineages were lo-

cated at the tips of the coalescent-based genealogies. As a result of

intensified cereal production, changed cultivation practices, and

increased global seed trade, populations of the fungus reached a

magnitude that allowed scald to become one of the most impor-

tant diseases on barley. The scald disease was first described at

the end of the 19th century (Frank 1897; Oudemans 1897; Hein-

sen 1901). It is not known whether the scald disease was already

present before that time. However, it is possible that the disease

was perceived only about 100 years ago after the pathogen popu-

lations increased and began to cause significant yield losses.

Although Agropyron spp. are weeds and not cultivated, Rhyn-

chosporium on these host species experienced a similar demo-

graphic history as on the other domesticated hosts. Agropyron spp.

are commonly found in cereal fields and pastures. Their close as-

sociation with cereal crops might have allowed this host species

to increase in population size and spread globally as a weed while

the barley and rye populations increased. The coalescent genealo-

gies showed that lineages A and C infecting barley and Agropyron

spp., respectively, share a common ancestor from which they di-

verged soon after their ancestor split from lineage B infecting rye.

It is probable that lineage C mirrored the demographic develop-

ment of lineage A and was spread globally through barley cultiva-

tion and trade. Interestingly, the geographic area from which iso-

lates infecting Agropyron spp. were obtained is small (only from

Switzerland) compared to that of rye-infecting isolates (Russia,

Switzerland, France) or barley-infecting isolates (many fields on

five continents). However, lineage C contained more than half of

the haplotype diversity present in lineage A and more haplotype

diversity than present in lineage B. It is possible that the genotypic

diversity of the scald pathogen on Agropyron spp. is higher than

on cultivated hosts because of a higher genetic diversity in mainly

outbreeding Agropyron hosts, compared to genetically uniform

cultivated crops.

Agriculture played a crucial role in the evolution of the scald

pathogen by first bringing the new hosts and the pathogen together

and then by driving the pathogen adaptation and transmission on a

global scale. The expansion of agriculture and resulting increase

in host population size allowed these new pathogens to diverge

rapidly into new species with large population sizes. This study

highlights the importance of agriculture in the emergence of fungal

pathogens of crops and illustrates how the introduction of a crop

to new areas can select for new pathogens that emerge through

host shifts. A short time frame was sufficient to allow the scald

pathogens to adapt to new hosts and to evolve into new species.

Although this study has focused on Rhynchosporium pathogens

of cereals, it is likely that many other plant pathogens with life

histories similar to Rhynchosporium have emerged in the same

way. It also is likely that more pathogens will emerge via host shifts

in the future as old crops are introduced into newly developed

agricultural areas around the world.

Further evidence that agriculture is driving the adaptation of

fungal pathogens to their hosts can be found in the rye/triticale-

infecting populations. The genealogies suggest that rye- and

triticale-infecting isolates belong to the same gene pool and

thus share a common origin. The crop triticale (× Triticosecale

Wittmack) is a man-made crop derived from hybridizing wheat

(Triticum aestivum L.) with rye (S. cereale L.). Triticale is of very

recent origin and was commercialized at the end of the 1960s

(Ammar et al. 2004; Oettler 2005). Although the disease was first

recorded on rye in the late 19th century (Oudemans 1897), it was

only noticed on triticale in the 1990s, 30 years after the introduc-

tion of triticale as a crop (Welty and Metzger 1996). This recent



host shift from rye to triticale may have occurred due to the loss of

scald resistance in the genome supplied by the wheat parent or be-

cause new pathogenic forms of Rhynchosporium recently emerged

from the rye-infecting population (Welty and Metzger 1996). In

the latter case, 30 years were sufficient to allow the rye-infecting

population to adapt to triticale. By breeding a new host species

and expanding its population size in the field, a new disease might

have emerged that may expand to become a significant disease on

triticale in the future.

ACKNOWLEDGMENTSThis work was funded by grant TH-23/02-4 from the Swiss Federal Insti-tute of Technology (ETH Zurich). The Genetic Diversity Center Zurichprovided facilities for data collection. We thank the collaborators listed inTable 1 involved in collecting infected leaves. We also thank two anony-mous reviewers, who offered many helpful suggestions to improve themanuscript.

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Associate Editor: J. Bergelson

Supplementary MaterialThe following supplementary material is available for this article:

Figure S1. Phylogeny inferred by maximum parsimony from the �-tubulin DNA sequence locus. The 50% majority-rule

consensus tree is shown. Bayesian maximum likelihood analysis recovered the same topology. The numbers above branches are

bootstrap frequencies of 1000 replicates and those below are Bayesian posterior probabilities. Branch lengths are proportional

to the number of steps (character changes) along the branch. Labels on the phylogeny are: H1-H18 haplotypes obtained from

316 DNA sequences of 1609 bp representing Rhynchosporium isolates from different hosts (Agropyron spp., barley, Bromus

diandrus, Dactylis glomerata, Hordeum spp., rye and triticale). Haplotypes H2-H4 representing Rhynchosporium orthosporum

were used as outgroup.

Figure S2. Phylogeny inferred by maximum parsimony from the �-tubulin DNA sequence locus. The 50% majority-rule

consensus tree is shown. Bayesian maximum likelihood analysis recovered the same topology. The numbers above branches are

bootstrap frequencies of 1000 replicates and those below are Bayesian posterior probabilities. Branch lengths are proportional to

the number of steps (character changes) along the branch. Labels on the phylogeny are: H1-H25 haplotypes obtained from 316

DNA sequences of 609 bp representing Rhynchosporium isolates from different hosts (Agropyron spp., barley, Bromus diandrus,

Dactylis glomerata, Hordeum spp., rye and triticale). Haplotypes H2-H4 representing Rhynchosporium orthosporum were used

as outgroup.

Figure S3. Phylogeny inferred by maximum parsimony from the EF-1� DNA sequence locus. The 50% majority-rule consensus

tree is shown. Bayesian maximum likelihood analysis recovered a similar topology. The numbers above branches are bootstrap

frequencies of 1000 replicates and those below are Bayesian posterior probabilities. Branch lengths are proportional to the

number of steps (character changes) along the branch. Labels on the phylogeny are: H1-H15 haplotypes obtained from 316



as outgroup.

Figure S4. Phylogeny inferred by maximum parsimony from the ITS DNA sequence locus. The 50% majority-rule consensus

tree is shown. Bayesian maximum likelihood analysis recovered a similar topology. The numbers above branches are bootstrap

frequencies of 1000 replicates and those below are Bayesian posterior probabilities. Branch lengths are proportional to the

number of steps (character changes) along the branch. Labels on the phylogeny are: H1-H25 haplotypes obtained from 316



as outgroup.

Table S1. Distribution of the different haplotypes of Rhynchosporium species on different hosts corresponding to three phylo-

genetic lineages A–C and Rhynchosporium orthosporum based on four DNA sequence loci.

Table S2. Results from neutrality tests [Tajima’s D (Tajima 1989) and Fu and Li’s D∗ and Fu and Li’s F∗ (Fu and Li 1993)].

This material is available as part of the online article from:

http://www.blackwell-synergy.com/doi/abs/10.1111/j.1558-5646.2008.00390.x

(This link will take you to the article abstract).

Please note: Blackwell Publishing is not responsible for the content or functionality of any supplementary materials supplied by

the authors. Any queries (other than missing material) should be directed to the corresponding author for the article.


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