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ORIGINAL ARTICLE
Rapid phenotyping of adult plant resistance in barley
(Hordeum vulgare) to leaf rust under controlled conditions
Christopher T. Rothwell
1
|
Davinder Singh
1
|
Floris van Ogtrop
2
|
Chris Sørensen
3
|
Ryan Fowler
4
|
Silvia Germán
5
|
Robert F. Park
1
|
Peter Dracatos
1
1
Plant Breeding Institute, The University of
Sydney, Cobbitty, NSW, Australia
2
The University of Sydney, Australian
Technology Park, Sydney, NSW, Australia
3
Department of Agroecology, Aarhus
University, Slagelse, Denmark
4
Department of Agriculture and Fisheries,
Hermitage Research Facility, Warwick, Qld,
Australia
5
Instituto Nacional de Investigación
Agropecuaria, La Estanzuela, Colonia,
Uruguay
Correspondence
Peter Dracatos, Plant Breeding Institute, The
University of Sydney, Cobbitty, NSW,
Australia.
Email: peter.dracatos@sydney.edu.au
Funding information
Grains Research and Development
Corporation, Grant/Award Number:
US00074
Communicated by: Ernesto Igartua
Abstract
Breeding for adult plant resistance (APR) is currently impeded by the low fre-
quency of annual field‐based testing and variable environmental conditions. We
developed and implemented a greenhouse‐based methodology for the rapid phe-
notyping of APR to leaf rust in barley to improve the efficacy of gene discovery
and cloning. We assessed the effects of temperature (18 and 23°C) and growth
stage (1–5 weeks) on the expression of APR in the greenhouse using 28 barley
genotypes with both known and uncharacterized APR. All lines were susceptible
in week 1, while lines carrying Rph20 and several with uncharacterized resistance
expressed resistance as early as week 2. In contrast, lines lacking Rph20 and car-
rying either Rph23 and/or Rph24 expressed resistance from week 4. Resistant
phenotypes were clearest at 18°C. A subset of 16 of the 28 lines were assessed
for leaf rust across multiple national and international field sites. The greenhouse
screening data reported in this study were highly correlated to most of the field
sites, indicating that they provide comparable data on APR phenotypes for
screening purposes.
KEYWORDS
adult plant resistance, barley, leaf rust, phenotyping, Puccinia hordei, resistance screening
1
|
INTRODUCTION
Barley is the fourth most important cereal crop worldwide by area
harvested and yield (FAOSTAT, 2015). Leaf rust of barley (caused by
Puccinia hordei Otth.) is an economically significant disease in the
major cereal production regions worldwide (Clifford, 1985). In Aus-
tralian barley crops, leaf rust is the most common and damaging of
the rust diseases (Park et al., 2015). It has been estimated to cost
Australian barley growers $21 million per annum, with yield losses of
up to 62% in untreated susceptible varieties (Cotterill, Rees, Platz, &
Dillmacky, 1992; Murray & Brennan, 2009). Economic and ecologi-
cally sustainable control of leaf rust can be achieved through the use
of resistance genes (Golegaonkar, Park, & Singh, 2009). To date, 26
leaf rust resistance (Rph) genes have been designated. Two classes
of Rph genes are recognized: all stage resistance (ASR) genes (Rph1-
19, 21, 22, 25 and 26) and adult plant resistance (APR) genes
(Rph20, 23 and 24) (Kavanagh, Singh, Bansal, & Park, 2017; Park et
al., 2015; Ziems et al., 2017). Lines that carry APR genes are seedling
susceptible, but as adult plants show a medium to strong reduction
in the number and size of pustules (Smit & Parlevliet, 1990). Many
APR genes have demonstrated their ability to provide durable resis-
tance to cereal rusts, for example, gene Lr34/Yr18/Sr57/Pm18 in
wheat has provided pleiotropic resistance against multiple pathogens
for over 50 years (Dyck, 1987; Dyck & Samborski, 1982; Krattinger
et al., 2009).
Of the currently designated Rph genes, only three confer APR.
The main limitations that prevent rapid characterization and use
of barley APR genes include reliance on seasonal field trials and
Received: 18 July 2018
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Revised: 31 August 2018
|
Accepted: 22 September 2018
DOI: 10.1111/pbr.12660
Plant Breeding. 2018;1–11. wileyonlinelibrary.com/journal/pbr ©2018 Blackwell Verlag GmbH
|
1
phenotypic variation due to fluctuations in temperature and dis-
ease pressure. The plant response to disease under field condi-
tions is dependent on variable environmental conditions,
decreasing the reliability of year to year comparisons (Riaz,
Periyannan, Aitken, & Hickey, 2016). At present, most phenotyping
for APR is conducted in the field annually over successive seasons
(Singh, Dracatos, Derevnina, Zhou, & Park, 2015). This is a very
slow process in comparison with the greenhouse seedling trials
used for ASR gene discovery and characterization. A typical germ-
plasm survey for APR sources requires repeated measurements
across different locations and field seasons to elucidate useful
APR sources. This process is currently limited by the annual
turnover of standard in‐field testing (Dracatos, Singh, Bansal, &
Park, 2015),
In order to overcome the limitations associated with screening
germplasm for the presence of APR in the field, greenhouse‐based
screening of adult plants can be used. The efficacy and speed of
this approach has been demonstrated in several studies in diverse
pathosystems. Pretorius, Park, and Wellings (2000) utilized
accelerated growth conditions to produce flag leaves 28 days after
sowing in wheat for testing APR against leaf rust (caused by P.
triticina) and stripe rust (caused by P. striiformis f. sp. tritici) in the
greenhouse. In a similar study, Riaz et al. (2016) utilized
greenhouse accelerated growth conditions to screen for novel
APR phenotypes in wheat to leaf rust (P. triticina). Similar method-
ology was used by Wallwork, Butt, and Capio (2016) to screen a
significant number of barley accessions in the greenhouse under
accelerated growth conditions to assess APR responses to
Pyrenophora teres f. sp. teres, the causal agent of net form net
blotch.
While there has been some attention paid to greenhouse APR
screening for rust diseases in wheat, by comparison barley rust dis-
eases have received little attention. Several studies have focussed
singly on the APR gene Rph20, utilizing greenhouse screening in
parallel to field measurements. To map Rph20, a combination of
field and greenhouse screening was used. The greenhouse screen-
ing was shown to accurately reflect field screening, with similar
QTL results (Hickey et al., 2011). A separate study was conducted
to test the expression of Rph20 in the greenhouse at early growth
stages in a range of barley genotypes. Separate cohorts were rust
tested at 1‐week intervals for 5 weeks under standard greenhouse
conditions. The Rph20 phenotype was reliably observed in the
5‐week cohort, while some backgrounds clearly expressed the
Rph20 phenotype at 3–4 weeks (Singh, Macaigne, & Park, 2013).
While there has been some effort made to study Rph20,itis
unknown whether Rph23,Rph24 or other uncharacterized sources
of APR can be screened reliably in the greenhouse at early growth
stages. In this study, we aimed to ascertain whether this green-
house methodology could be applied to known and uncharacterized
APR genes. If such resistances can be phenotyped in a greenhouse
setting, this methodology will enable more rapid screening of
germplasm for the presence of APR and hence gene discovery and
cloning in barley.
2
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MATERIALS AND METHODS
2.1
|
Plant and pathogen material
A panel comprising 28 barley lines was assembled to characterize
APR to leaf rust under field and greenhouse conditions. These lines
were selected from Australian and international breeding lines and
cultivars, and included selected reference genotypes carrying known
APR genes (Table 1).
The pathogen material used for Australian field and greenhouse
testing was pathotype 5457 P+(virulent on Rph1-4, 6, 9, 10, 12, 19
and 25). A standard isolate of this pathotype (culture number = 612)
is maintained at PBI, Cobbitty, New South Wales (NSW). The patho-
type used in Uruguay for field screening was UPh3 (virulent on
Rph1-5,Rph9-12), maintained at the Instituto Nacional de Investi-
gación Agropecuaria (INIA), La Estanzuela, Colonia, Uruguay.
2.2
|
Seedling APR testing
Two seeds of each line were sown in individual cells of an 8 ×5 cell
seedling trays in a mixture of bark fines and coarse sand and fertil-
ized at sowing using Aquasol
®
(Hortico Pty Ltd, Revesby, NSW, Aus-
tralia) (100 g/10 L H
2
O). Twenty seedling trays were sown
simultaneously and maintained at 18°C in a rust free greenhouse
growth room. Four seedling trays were taken at weekly intervals for
inoculation, two trays for each of the temperature treatments. Inocu-
lation was conducted in a closed inoculation chamber. Uredin-
iospores (10 mg/10 ml) were suspended in light mineral oil (Isopar L,
Univar, Ingleburn, NSW, Australia) and sprayed above seedlings using
an atomizer with a hydrocarbon propellant pressure pack. After
5 min, seedlings were moved from the inoculation room to a dark
incubation chamber maintained at 100% humidity by an ultrasonic
humidifier for 12–18 hr. Plants were maintained at either 18 or
23°C in separate greenhouse microclimate chambers. Disease
response was measured 9 days post‐inoculation using a modified
Stakman “0–4”scale (Park et al., 2015). Both plants in each well
were scored separately as were the two trays in each temperature
treatment. Greenhouse scores were converted to a “0–9”scale for
analysis (Ziems et al., 2014) (Figure S1). Variations in infection type
(IT) were indicated using “+”(higher response than average for that
class), “−”(lesser response than average for that class), “c”(chlorosis
present) and “n”(necrosis present).
2.3
|
Field APR testing
From the panel, 16 lines were selected for field testing (Table 1)
across five locations in 2016: La Estanzuela, (Uruguay), Cobbitty
(NSW; 2 sites), Gatton (QLD) and Toowoomba (QLD). Each line was
sown as a block as part of large scale field trials. The lines were
scored again in 2017 at one site in Cobbitty NSW. Field scoring in
NSW and Uruguay was conducted using the modified Cobb scale
(Peterson, Campbell, & Hannah, 1948), which was converted to a
Coefficient of Infection score (CI) by multiplying the modified Cobb
2
|
ROTHWELL ET AL.
score severity value (0–100) by the severity of the infection (0.10,
0.25, 0.50, 0.75 or 1.00 for host response ratings of R, MR, MR–MS
or S, respectively) (Pathan & Park, 2006). Field scoring in Queensland
was conducted using the Resistance Index (RI) 0–9 scale where
0 = immune and 9 = totally susceptible (Akhtar et al., 2002). RI
scores were converted to the CI scale through multiplication by a
factor of 10 (Figure S2).
2.4
|
Chitin assay and histology
The fungal biomass was determined in third leaves of the barley
genotypes “Zhoungdamei”,“Gus”,“Zug161”,“Volla”,“Tallon”,“Flag-
ship”,“ND24260”,“Gairdner”,“Baronesse”and “RAH1995”with
the method described in Ayliffe et al. (2013). Infected parts were cut
from three different plants (replicates) of each barley genotype main-
tained at 18°C 10 days after inoculation and placed individually in
15 ml Falcon tubes. The leaf material was weighed and 1 MKOH
added to fully cover the leaves. Samples were left for clearing at
room temperature for 48 hr with a change of KOH after the first
24 hr. The leaves were then washed twice in 50 mMTris‐HCl (pH =
7) buffer for neutralization. Fresh Tris‐HCl was added to a concen-
tration of 50 mg leaf per ml. The leaf material was homogenized by
sonication. Leaf homogenate (200 μl per sample) was added to PCR
tubes with three technical replicates per biological replicate. 10 μlof
WGA‐FITC (1 mg/ml) (Sigma‐Aldrich, St. Louis, MO, USA) was added
to each tube. Samples were spun at 184 gfor 2 min and the
TABLE 1 Summary of barley leaf rust APR and ASR gene information and pedigree for germplasm panel
Cultivar
a
APR gene(s)
b
ASR gene(s)
b
Identifier
c
Pedigree
Baronesse
+
Rph20+Rph24 (1) –PI 568246 Mentor/Minerva//Vada mutant/4/Carlsberg/Union//
Opavsky/Salle/3/Ricardo/5/Oriol/6153P40
Barque
+
Rph20 (2) Rph2+Rph12 –Triumph/Galleon
Beecher Rph23 (2) ––Atlas/Vaughn
ISR950.11 Rph23+Rph24 (3) ––Canadian breeding line
Clho9776 Uncharacterized APR (4) –AUS490069 Moroccan landrace
CPI 36396
+
Rph24 (3) ––Not known
Flagship
+
Rph20 (2) ––Chieftain/Barque//Manley/VB9104
Franklin
+
Uncharacterized APR (2) Rph12 –Shannon/Triumph
Fumai 8
+
Uncharacterized APR (5) ––76‐22///Zaoshu 3//Humai 1/8‐2
Gairdner
+
Rph23 (2) ––Onslow//Shannon/Triumph
Henley Rph20+Rph24 (2,3) Rph3 –Not known
Klimek
+
Rph20+? (2) Rph9.am ––
Lenka Rph20+Rph23+Rph24 (1) Rph3 –HVS‐5013‐74/Q‐496‐72
Morex J Uncharacterized APR (3) ––Cree/Bonanza
Nagrad
+
Rph20+? (5,3) ––RPB393173/Georgie
Tallon
+
Uncharacterized APR (3) –AUS 406324 Triumph/Grimmet
Volla
+
Rph20+Rph23 (6) Rph3 PI 280423 Breuns Wisa/Heines Haisa 1
YAN90260
+
Uncharacterized APR (5) ––Chinese breeding line
YAN90260XBaronesse F34632 Rph20 +? (3) ‐‐YAN90260/Baronesse F3 Line
YAN90260XBaronesse F34741 Rph20+? (3) ––YAN90260/Baronesse F3 line
Yerong
+
Rph23 (3) Rph2 –M22/Malebo
YF11 –––Yerong/Franklin DH line
YF229 –––Yerong/Franklin DH line
YF291 –––Yerong/Franklin DH line
YF70 –––Yerong/Franklin DH line
Zhoungdamei
+
Uncharacterized APR (5) ––Chinese landrace
Zug 161
+
Uncharacterized APR (5) ––Breeding lines from Zhejiang University, China
Gus
+
––PI494521 –
Note. APR: adult plant resistance; ASR: all stage resistance.
a
Lines selected for field testing denoted by +superscript.
b
Cultivars with unknown or nil resistance genes are represented by a dash, gene source reference in brackets.
c
Genotype identifier prefix; AUS—Australian Winter Cereals Collection number. PI—US National Small Grains Collection number.
References: 1: Drijepondt et al. (1991), 2: Kavanagh et al. (2017), 3: Singh & Park unpublished, 4: Smit and Parlevliet (1990), 5: Singh et al. (2015), 6:
Hickey et al. (2011).
ROTHWELL ET AL.
|
3
supernatant removed. Samples were resuspended in 200 μl50mM
buffer, spun and again the supernatant was removed. This washing
step was repeated three times. Samples were then transferred to
black 96‐well plates suitable for fluorometry. After the first run sam-
ples were diluted 4x within linear range of the standard curve as
described in Ayliffe et al. (2013), fluorescence was measured with a
Wallac Victor 1420 multilabel counter (Perkin‐Elmer Life Science,
MA, USA) using 485 nm adsorption and 535 emission wavelengths
and a 1.0 s measurement time. Leaf samples for histological observa-
tions were collected and cleared in the same way as described for
the biomass assay. The staining method followed that described in
Ayliffe et al. (2011). In brief, the KOH was poured off after clearing
and samples were neutralized in 50 mMTris‐HCl (pH = 7) buffer.
New buffer was added to fully cover the leaves. WGA‐FITC (1 mg/
ml) (Sigma‐Aldrich) was added to a final concentration of 20 μg/ml
Tris‐buffer in order to stain the fungal structures. Samples were then
rinsed in buffer and mounted for microscopy. The specimens were
examined under blue light with a Zeiss Axio Imager 2 microscope.
2.5
|
Statistical methods
Statistical analyses were conducted using Genstat 18th Edition (VSN
International Ltd). A linear mixed model (REML) was used to investi-
gate interactions between experimental effects in the greenhouse.
Converted CI scores from the greenhouse and field trials were evalu-
ated using a fitted multiple linear regression model to assess the
relationship between field and greenhouse response. A correlation
contingency table was generated using the greenhouse and field
scores. A principal component analysis (PCA) was performed and
visualized using a biplot. Analysis of the data from the chitin assay
was performed using R (R Development Core Team, 2017). A one‐
way ANOVA model was utilized for analysing the general effect of
the explanatory factor “variety”on the dependent variable “fluores-
cent units.”Model assumptions were evaluated graphically and data
were log‐transformed to meet the assumptions of equal variance and
normality. Multiple comparisons were performed using a Tukey hon-
estly significant differences test.
3
|
RESULTS
3.1
|
Greenhouse screening
The timing and expression of APR under greenhouse conditions in
the barley accessions used in this study was dependent mainly on
the specific genotype and gene combination present. A REML analy-
sis found a significant interaction between plant growth stage and
gene combination (p<0.001), reflecting the clear groupings of geno-
types by their gene combination and variable effects of each gene
0
1
2
3
4
5
6
7
8
9
12345
Disease response
Age (weeks)
Gus nil Barque Rph20 Flagship Rph20 Beecher Rph23
Gairdner Rph23 CPI 36396A Rph24 Volla Rph20+23 Baronesse Rph20+24
Henley Rph20+24 Canada ISR950.11 Rph23+24 Lenka Rph20+23+24
FIGURE 1 Mean disease response of characterized adult plant resistance lines to leaf rust under controlled greenhouse (18°C treatment).
Gus is included as a susceptible control. Error bars are the standard error of the mean
4
|
ROTHWELL ET AL.
across the growth stage of the plants tested. Out of the 18°C treat-
ment group, eight of the 10 characterized APR lines showed suscep-
tibility (IT score 7–9) at the seedling stage (Figures 1 and 2). Both
Beecher and Henley produced IT score 6, outside the susceptible
range, indicating that there may be minor effect partial resistance
genes present in addition to the known APR genes or epistasis
between ASR and APR genes. The susceptible standard Gus was
susceptible at all growth stages tested. Lines with Rph20 were seen
to express resistance at earlier growth stages than lines without
Rph20. All lines carrying Rph20 were classed as resistant in the sec-
ond week with IT scores in the range of 2–4. Lines lacking Rph20
(Beecher, Gairdner, CPI 36396A, Canada ISR950.11) had a higher
disease response (IT scores of 6–7) in the second week. The leaf rust
response of lines carrying Rph20 was consistent (IT score of 2–3)
across weeks 2–5. The one exception was the cultivar Baronesse,
which had an IT score of 4 in the second week. Non‐Rph20 lines
produced high IT scores (6–7) in the second week. Only one line
included in this study (Canada ISR950.11) carried both Rph23 and
Rph24 in combination. Our data suggested that when both genes
are present singly that resistance was expressed in later weeks and
was more pronounced at 23°C, however Canada ISR950.11 was
more resistance suggesting a possibly additive effect of Rph23 and
Rph24. In the 23°C treatment, the IT scores were higher for all gene
combinations while still exhibiting the same trends (Figures 3 and 4).
The lines with uncharacterized APR components exhibited a wide
range of leaf rust responses. Lines carrying Rph20 in addition to an
uncharacterized gene exhibited high levels of resistance, similar to
the resistance observed in lines carrying only Rph20. Only one line
carrying Rph23 plus additional uncharacterized APR was assessed,
which exhibited moderate (IT score 5 in week 5) resistance. The
remaining lines with uncharacterized APR showed a wide range of
leaf rust responses, from moderately susceptible to highly resistant.
3.2
|
Correlation of field and greenhouse disease
scores
The correlation between field scores and greenhouse screening was
calculated using a fitted multiple linear regression models (Table 2).
The majority of the sites had high correlation values (R
2
= 0.65–
0.77), with the two outliers being Gatton (R
2
= 0.51) and Too-
woomba (R
2
= 0.36). Field sites within NSW and Uruguay were bet-
ter correlated to the greenhouse scores than those in Queensland
(Gatton and Toowoomba). A correlation contingency table was gen-
erated (Table 3) to assess how the greenhouse scores correlated to
each field site and to compare how well this fitted with the correla-
tion between different field sites. The correlation values between
both temperature treatments and the field site scores reflected the
variation in correlation seen among the different field treatments.
0
1
2
3
4
5
6
7
8
9
12345
Disease response
Age (weeks)
Gus nil Barque Rph20 Flagship Rph20 Beecher Rph23
Gairdner Rph23 CPI 36396 Rph24 Volla Rph20+23 Baronesse Rph20+24
Henley Rph20+24. Canada ISR950.11 Rph23+24 Lenka Rph 20+23+24
FIGURE 2 Mean disease response of characterized adult plant resistance lines to leaf rust under controlled greenhouse (23°C treatment).
Gus is included as a susceptible control. Error bars are the standard error of the mean
ROTHWELL ET AL.
|
5
The field sites with the lowest correlation values were again Too-
woomba and Gatton, in addition to Cobbitty B (2016) (Table 3).
A PCA biplot was generated to assess the correlation between
different field sites and greenhouse treatments (Figure 5). The hori-
zontal axis (PC‐1 73.5%) accounted for the majority of the variation
between the individuals. The susceptible control genotype Gus is at
the right extreme of the horizontal axis, while the most resistant
lines, primarily comprised of lines carrying Rph20, are located on the
opposite extreme as expected. The field sites are displayed as the
biplot axes, with the most closely correlated axis being those with
the smallest angle between them. The two greenhouse temperature
treatments (GH_18 and GH_23) are closely aligned to each other.
The most highly correlated field site to the greenhouse treatments is
Cobbitty_A_2017. As with the previous regression analysis, the least
correlated sites are Gatton and Toowoomba (Figure 5).
3.3
|
Fungal biomass and histology
The assessment of APR based on the chitin assays confirmed the
strong effect of the resistance gene Rph20 observed in the green-
house and field trials (Figure 6). All varieties with Rph20 either singly
or in combinations had a significantly lower level of chitin compared to
varieties with Rph23 and Rph24. The variety Flagship with only Rph20
was as resistant as the varieties with other resistance genes in addition
to Rph20. The varieties with only unidentified resistance genes
showed variable responses as for the IT assessment. The resistance in
Tallon equalled that in varieties with Rph20 whereas Zhoungdamei
was level with the most susceptible varieties. The resistance in
Zug161 was in between that of Tallon and Zhoungdamei. The varieties
with Rph23 and Rph24 could not be differentiated from the suscepti-
ble control (Gus) based on the assay. Histological observations indi-
cated a correlation between the chitin level and the relative number of
colonies with pustule formation at the time of sampling (Figure S3).
4
|
DISCUSSION
In order for controlled environment greenhouse screening to capture
adult plant response accurately, several criteria must be met. The
effect of any ASR needs to be eliminated so as to screen purely for
APR genes. It is clear that none of the lines carry ASR effective
against the pathotype used for this test given their susceptible
scores in the seedling stage (first week) for both temperature treat-
ments. As the effect of ASR was overcome by the pathotype used,
the greenhouse methodology used clearly permitted the detection of
APR within 5 weeks.
0
1
2
3
4
5
6
7
8
9
12345
Disease response
Age (weeks)
Gus nil Klim ek Rph20+ ? Nagrad Rph20+? YAN90260 x BaronesseB Rph20+?
YAN90260 x BaronesseA Rph20+? Yerong Rph23 +? CIh o 97 76 Un known APR Franklin Unkno wn APR
Fumai 8 Unknown APR Morex J Unkn own APR Tallon Unknown APR YAN9026 0 Unknown AP R
YF1 1 U nknown APR YF2 29 Unknown APR YF291 Unknown APR YF70 Unk no wn APR
Zh ou ngd amei U nk n own AP R Zu g 161 Unkn own AP R
FIGURE 3 Mean disease response of uncharacterized adult plant resistance (APR) lines to leaf rust under controlled greenhouse (18°C
treatment). Gus is included as a susceptible control. Lines with a question mark (?) are hypothesized in prior studies (see Table 1) to carry
additional uncharacterized APR. Error bars are the standard error of the mean
6
|
ROTHWELL ET AL.
In order to classify lines according to the possible gene combina-
tion they carry based on disease response, clear variation in pheno-
type among different genes is required. The differences between the
three characterized APR genes were apparent by the second week,
particularly in the 18°C treatment. Lines carrying Rph20 were more
resistant at earlier growth stages than those lacking Rph20 (Fig-
ure 1). The additive nature of the characterized APR genes (Rph20,
Rph23, Rph24) was also observed in this study, with lines such as
Henley (Rph20+Rph24) and Lenka (Rph20+Rph23+Rph24) showing a
stronger resistant response than lines carrying Rph20 only, such as
Flagship. The additive relationship between Rph20 and a number of
characterized and uncharacterized APR genes was described previ-
ously by Derevnina, Singh, and Park (2013), while Ziems et al. (2017)
demonstrated additivity between Rph20 and Rph24. Our results
were in agreement with Ziems et al. (2017); Rph24 provided a very
low level of resistance on its own, however when combined with
Rph20 additivity was observed in all cases. Similarly, additive effects
were also observed in lines with gene combinations Rph20+Rph23
and to a lesser extent Rph23+Rph24. An additive effect between
Rph23 and Rph24 was observed in the line carrying this combination
(Canada ISR950.11). This line was more resistant from the third
week onward that lines carrying Rph23 or Rph24 singly in the 18°C
treatment group. This effect was not observed in the 23°C treat-
ment group, indicating that low temperature may increase the addi-
tive effect. The combination of all three known APR genes did not
provide a higher level of resistance than that conferred by Rph20
and Rph24 (Ziems et al., 2017), indicating that the interaction
between Rph23 and Rph24 is likely masked by presence of Rph20.
Caution however must be taken interpreting variations in additivity
between gene combination lines in this study as they are not near‐
isogenic and therefore may carry additional minor effect alleles that
0
1
2
3
4
5
6
7
8
9
12345
Age (weeks)
Gus nil Klimek Rph20+? Nagrad Rph20+? YAN90260 x BaronesseA Rph20+?
YAN90260 x BaronesseB Rph20+? Yerong Rph23+? CIho 9776 Unknown APR Franklin Unkno wn APR
Fumai 8 Unknown APR Morex J Unkn own APR Tal lon Unkn own APR YAN9 0260 Unkn own APR
YF1 1 U nknown APR YF 229 Unkn own APR YF2 91 Unknown APR YF70 U nknown APR
Zh ou ngda m ei U nk n own AP R Zug 161 Unknown APR
FIGURE 4 Mean disease response of uncharacterized adult plant resistance (APR) lines to leaf rust under controlled greenhouse (23°C
treatment).Gus is included as a susceptible control. Lines with a question mark (?) are hypothesized in prior studies (see Table 1) to carry
additional uncharacterized APR. Error bars are the standard error of the mean
TABLE 2 Greenhouse adult plant resistance scoring to field
scoring regression models correlation values
Field location
Fitted regression
model correlation to
greenhouse scores (R
2
)
Uruguay (La Estanzuela, Uruguay) 0.71
Cobbitty_A (2017) (NSW, Australia) 0.71
Cobbitty_A (2016) (NSW, Australia) 0.65
Cobbitty_B (2016) (NSW, Australia) 0.76
Gatton (QLD, Australia) 0.51
Toowoomba (QLD, Australia) 0.36
ROTHWELL ET AL.
|
7
modify the resistance phenotype. The strong effect of Rph20 was
also observed when a chitin assay was used for resistance assess-
ment. The additive effect of different genes could not be detected
with this method which indicates that chitin assays require support
by IT assessment for a more accurate APR evaluations.
Screening lines with all three known APR genes at 18°C provided
a stronger, more stable disease response than 23°C. A stronger resis-
tance response at lower temperature has been shown previously for
Rph20 (Singh et al., 2013); however, this effect has not been demon-
strated for Rph23 and Rph24. Research on genes conferring APR to
rust in wheat also found a relationship between temperature and
expression of APR. The expression of the pleiotropic APR locus
Lr34/Yr18/Sr57/Pm18 in wheat was tested at both the seedling and
adult stage in the Thatcher background across a range of tempera-
tures in the greenhouse by Singh and Gupta (1992). They found that
Lr34/Yr18/Sr57/Pm18 was most strongly expressed in seedlings at
7°C. Adult plants were most resistant at 15°C in studies by Drije-
pondt, Pretorius, and Rijkenberg (1991). A similar study using Mexi-
can‐derived pathotypes of P. triticina saw the strongest expression
of resistance in seedlings at post‐inoculation temperatures of 14–
17°C (Singh & Gupta, 1992). Our study suggests the expression of
Rph20 in barley and other uncharacterized APR genes such as
RphTallon and RphZug161 is enhanced under cooler temperatures
either when deployed on their own or in combination with other
minor APR loci. However, the cooler temperature treatment (18°C)
used in our study had no effect on the expression of Rph23 or
Rph24 either singly or in combination.
A range of disease responses was expressed by the genotypes
carrying uncharacterized APR. Several lines exhibited high levels of
TABLE 3 Correlation contingency table for field sites and greenhouse scores
Cob_A_2016_F 1 –
Cob_B_2016_F 2 0.3807 –
Cob_A_2017_F 3 0.4261 0.5111 –
Uruguay_F 4 0.4947 0.4704 0.6802 –
Gatton_F 5 0.8051 0.7236 0.6269 0.6201 –
Toowoomba_F 6 0.6670 0.5447 0.5950 0.6424 0.7576 –
Wk5_18degC_G 7 0.5507 0.2294 0.7026 0.2550 0.5151 0.3354 –
Wk5_23degC_G 8 0.5121 0.3916 0.8517 0.5154 0.6120 0.4165 0.8787 –
12345678
Note. Field site (_F) or greenhouse (_G) data are indicated. Cob_A and Cob_B are two field sites located at Cobbitty, NSW.
FIGURE 5 Principal component analysis biplot generated from a
combined field and greenhouse screening dataset. The individual
cultivars are denoted by the labelled red circles arrayed along the
horizontal (PC‐1, accounting for 73.58% of observed variation) and
vertical (PC‐2, accounting for 9.14% of observed variation) axes. The
field trial sites and greenhouse treatments for all cultivars are
represented by the biplot axes intersecting at the centre of the
figure. Axes with the smallest angle at the intersection point are the
most correlated to each other
FIGURE 6 The relative level of fungal biomass in 10 barley
varieties with either no (susceptible) or different genes for adult
plant resistance (Rph20, Rph23, Rph24 and unknown
APR = unidentified gene[s]) assessed as fluorescent units after chitin
staining. Bars with different letters are significantly different at
α= 0.05. “+”= denotes additional but unknown resistance gene(s)
8
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ROTHWELL ET AL.
resistance, providing similar levels of resistance to lines with Rph20.
Derevnina et al. (2013) reported that three of the lines used in the
present study (Zug161, Zhoungdamei and Yan 90260) carried mod-
erate levels of APR under field conditions. A previous survey of Afri-
can germplasm found the line CIho9776 exhibited high levels of APR
under field conditions, consistent with results obtained in the green-
house in the present study (Elmansour, Singh, Dracatos, & Park,
2017). A number of other lines carried weaker APR components.
The line Fumai8 was among lines with the lowest level of APR, mir-
roring the field response seen in a previous germplasm survey
(Derevnina et al., 2013). The range of APR responses seen in this
study are indicative of the spectrum of potential APR sources in
international germplasm that could be identified and exploited
through utilizing greenhouse APR screening.
The greenhouse response of the lines tested also needs to corre-
late with their field response in order for this methodology to be
truly representative of resistance under field conditions. Multiple lin-
ear regression analysis demonstrated a high degree of correlation
between field and greenhouse response for the lines tested. The R
2
values for the most highly correlated field sites from this analysis are
similar to those found in a similar study conducted on wheat leaf
rust (R
2
= 0.77) (Riaz et al., 2016). The measurements in Riaz et al.
(2016) were taken at the flag‐2 leaf stage under accelerated growth
conditions, indicating that scores taken at 5 weeks of age can pro-
vide a similar picture to those taken at a much later growth stage in
the greenhouse. The correlation analysis also illustrated the accurate
reflection of field trial scores by greenhouse APR screening. There
were similar levels of correlation between different field sites when
the two temperature treatments were compared to each other, indi-
cating that greenhouse screening data provide an accurate approxi-
mation of field response, just as one field site will give an
approximation of field response at another site. Greenhouse APR
screening can thus provide rapid, accurate estimation of APR
response under controlled environmental conditions.
The correlation between field and greenhouse scores from the
fitted regression model was strongest for the Uruguay and NSW
field sites. The two Queensland field sites, Toowoomba (R
2
= 0.36)
and Gatton (R
2
= 0.51), were the least correlated. The remaining
field sites all had high regression scores, indicating that the green-
house screening was representative across the range of field sites
tested. The Gatton field site had the highest mean maximum daily
temperature and lowest rainfall of any field site during the scoring
window, which may have had a negative impact on APR gene
expression (Table 4). Toowoomba in contrast had similar average
temperature and rainfall readings to the southern Australia sites. The
only clear difference to the southern field sites is the northern lati-
tude and altitude at Toowoomba, which may have some effect on
the APR expression. The trends seen in the fitted regression model
were mirrored in the PCA. The field sites that are most closely corre-
lated with the greenhouse testing are La Estanzuela‐Uruguay and
Cobbitty, particularly Cobbitty_A_2017. The two 2016 Cobbity field
sites, especially Cobbity_B, were less well correlated. This is poten-
tially due to the fact that 2016 was a drier field season than 2017
(Table 4). While Cobbity_A is located next to a small river, Cobbity_B
is located several hundred metres from water, potentially leading to
differing exposure to overnight moisture that could affect disease
progress. The two Queensland sites in contrast were again not
highly correlated with the greenhouse data.
The two greenhouse temperature treatments in the PCA biplot
(GH_18°C and GH_23°C) and the correlation contingency table
(18°C_Wk5, 23°C_Wk5) are clearly associated to each other, indicat-
ing that they are fairly equivalent measures of field response. There-
fore, the methodology developed in this study can be seen to
capture the effect of novel APR genes both alone and in combina-
tion with known APR genes. Given the similar levels of correlation
to field response the cooler temperature treatment provides a better
platform for APR screening due to the clearer APR phenotype seen
at lower temperatures.
The presented APR phenotyping methodology allows for rapid
greenhouse‐based screening of APR candidate lines under controlled
conditions without the temporal and environmental constrains of tra-
ditional field screening. Screening APR candidate lines in the green-
house at 5 weeks post sowing captured APR expression. Maintaining
lines post‐inoculation at 18°C provided the clearest phenotype.
Greenhouse scores were shown to correlate with field measure-
ments from a number of sites. Greenhouse‐based screening was thus
validated as a representative methodology for APR phenotyping.
Taken together the effect of temperature on resistance gene expres-
sion has important implications for the deployment of cultivars
across different growing environments. The data from this study can
be used to propose varietal deployment across diverse barley grow-
ing environments as well as greatly improving the rate of APR phe-
notyping and hence gene discovery.
ACKNOWLEDGEMENTS
This research was supported by the Australian Grains Research &
Development Corporation (Grant: US00074) and an Australian Fed-
eral Research Training Program Scholarship.
CONFLICTS OF INTEREST
The authors declare that they have no conflict of interests.
TABLE 4 Climatic summary for field sites for the month when
field scoring took place (October)
Field site
Mean
maximum
daily
temperature
(Celsius)
Mean
minimum
daily
temperature
(Celsius)
Cumulative
rainfall (mm)
Elevation
above
sea level
(m)
Cobbitty 2016 24.4 9.2 18.4 61
Cobbitty 2017 26.1 12 51.2 61
Gatton 28.7 10.6 16 89
Toowoomba 23.7 11.2 29 641
LE, Uruguay 21.2 11.3 111 72
ROTHWELL ET AL.
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9
AUTHORS’CONTRIBUTIONS
CR contributed to the experimental design and conducted the green-
house testing, statistical analysis and manuscript composition. DS
carried out field testing at Cobbity. FvO was a major contributor to
the statistical analysis. RF carried out field testing at Gatton and
Toowoomba. CS carried out the histology. SG carried out field
testing in Uruguay. RP contributed to the study design and
manuscript drafting. PD designed the study and contributed to the
manuscript drafting.
ORCID
Christopher T. Rothwell http://orcid.org/0000-0002-6360-1589
Davinder Singh http://orcid.org/0000-0003-1411-9291
Peter Dracatos http://orcid.org/0000-0002-4199-7359
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SUPPORTING INFORMATION
Additional supporting information may be found online in the
Supporting Information section at the end of the article.
How to cite this article: Rothwell CT, Singh D, van Ogtrop F,
et al. Rapid phenotyping of adult plant resistance in barley
(Hordeum vulgare) to leaf rust under controlled conditions.
Plant Breed. 2018;00:1–11. https://doi.org/10.1111/
pbr.12660
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