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This is to certify that the
dissertation entitled

FUSARIUM HEAD BLIGHT OF WHEAT: MECHANISMS OF
RESISTANCE IN NING 7840 AND IDENTIFICATION OF QTL
FROM A NEW SOURCE OF RESISTANCE

presented by
JANET M. LEWIS

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PhD. degree in Plant Breeding and Genetics -
Department of Crop and Soil

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FUSARIUM HEAD BLIGHT OF WHEAT: MECHANISMS OF RESISTANCE IN
NING 7840 AND IDENTIFICATION OF QTL FROM A NEw SOURCE OF
RESISTANCE
By

Janet M. Lewis

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
DOCTOR OF PHILOSOPHY
Plant Breeding and Genetics - Department of Crop and Soil Sciences

2004

ABSTRACT
FUSARIUM HEAD BLIGHT OF WHEAT: MECHANISMS OF RESISTANCE IN
NING 7840 AND IDENTIFICATION OF OTL FROM A NEw SOURCE OF
RESISTANCE
By

Janet M. Lewis

Fusan’um head blight (F HB), caused by Fusan’um spp. and Microdochium
nivale is a cereal disease threatening the wheat and barley industries in North
America as well as Europe, Asia and South America. F HB causes losses in yield
as well as reduced grain quality and contamination with mycotoxins that are a
serious danger to the health of humans and animals. Host plant resistance to
FHB in wheat is quantitative. To date, few sources have been identified that
confer a large amount of resistance to FHB. The most widely recognized and
used source of resistance is from the Chinese cultivar ‘Sumai 3’. The
mechanisms underlying Sumai 3 resistance are not understood. Although Sumai
3 provides a large amount of resistance to spread of F HB within infected spikes,
this partial resistance is insufficient to prevent the development of FHB under
high disease pressure. Identification and verification of other sources of
resistance to FHB is critical to enable breeders to combine sources of resistance
for a more effective resistance and to prevent the development of genetic
uniformity among elite germplasm. The objectives of this research were twofold:
1) to compare progression of disease in a Sumai 3 derived source of resistance
(‘Ning 7840’) versus a susceptible cultivar according to visual and bioassay

techniques, and 2) to map potentially novel quantitative trait loci (OTL) controlling

F HB resistance from a wheat line whose parents include a hexaploid wheat
artificially synthesized from wheat’s progenitor species. The spread of disease in
Ning 7840 was compared to a susceptible genotype, ‘Norm’, for visual symptoms
of spread in the spikelets, visual symptoms of spread in the rachis, and the
presence of the fungus in the rachis according to a bioassay. For both
genotypes, the spread of the fungus in the rachis preceded the development of
symptoms in the corresponding spikelets. For Ning 7840, spread of the fungus in
the rachis was either greatly restricted or equal to that of the susceptible
genotype Norm. Nonetheless, the number of scabby spikelets was smaller in
Ning 7840 than Norm. These results reveal that a primary mechanism of Sumai 3
resistance to the spread of scabby spikelets is the prevention of the infection of
non-inoculated spikelets from infected rachis tissue. For the identification of QTL
for resistance to FHB, a dihaploid (DH) wheat population from a cross of
CASSQ4 and Flycatcher was investigated. One-hundred and eight DH lines were
phenotyped in the greenhouse for resistance to spread of F HB, and 130 DH lines
were genotyped using simple sequence repeat (SSR) primer pairs. Single
marker analysis and composite interval mapping identified the locations of one
major QTL for resistance on chromosome arm 20L, and minor QTL for
resistance on chromosome 4A and chromosome arms 5AL and 50L. These
results unequivocally verify reports that a OTL controlling resistance to the

spread of scabby spikelets is present on chromosome arm 20L.

Copyright by
JANET M. LEWIS
2004

Dedicated to my wonderful parents Frances and Chester Lewis

ACKNOWLEDGEMENTS

I would specifically like to acknowledge Dr. Rick Ward for his guidance and
support in serving as my major professor. The guidance of Dr. James D. Kelly,
Dr. Dechun Wang and Dr. Ray Hammerschmidt are also greatly appreciated. In
addition, special thanks to friends and colleagues in the Plant Breeding and
Genetics Program and Department of Crop and Soil Sciences at Michigan State

University who have supported me.

vi

TABLE OF CONTENTS

LIST OF TABLES .................................................................................................. x
LIST OF FIGURES .............................................................................................. xi
KEY TO SYMBOLS AND ABBREVIATIONS ...................................................... xii
1 FUSARIUM HEAD BLIGHT IN WHEAT: IMPORTANCE, PATHOLOGY AND
HOST RESISTANCE ...................................................................................... 1
1.1 Wheat: Origin and Importance ............................................................. 1
1.2 Impact of Fusarium Head Blight .......................................................... 5
1.3 FHB Causal Organisms ....................................................................... 6
1.4 Invasion and Colonization of Wheat by Fusarium ............................... 7
1.5 Symptoms of FHB ............................................................................. 11
1.6 Fusan’um Mycotoxins and Infection ................................................... 12
1.7 FHB and Cell Wall Degrading Enzymes ............................................ 16
1.8 Chemical and Biological Controls of FHB .......................................... 17
1.9 Mechanisms of Resistance to FHB ................................................... 18
1.10 Artificial Inoculation Methods for F HB Induction ............................... 26
1.11 Genetics of Resistance .to FHB ........................................................ 28
1.12 References ....................................................................................... 31
2 CHARACTERIZATION OF NING 7840 TYPE 2 RESISTANCE BY VISUAL
AND BIOASSAY TECHNIQUES ................................................................... 46
2.1 Abstract .............................................................................................. 46
2.2 Introduction ......................................................................................... 47
2.3 Materials and Methods ....................................................................... 51
2.3.1 Plant Materials .................................................................... 51
2.3.2 Inoculum Production ........................................................... 51
2.3.3 Inoculation of Plants ........................................................... 52
2.3.4 Post-Inoculation Growth Conditions .................................... 53
2.3.5 Evaluation of Fusarium Head Blight on Spikes ................... 53
2.3.6 Experimental Design ........................................................... 55
2.3.7 Missing Data ....................................................................... 55
2.3.8 Data Analysis ...................................................................... 55
2.4 Results ............................................................................................... 56
2.4.1 SAS Analysis ...................................................................... 56
2.4.2 Comparisons among Measures of Disease Development
within a Genotype ............................................................... 56
2.4.3 SS, VIRS and BIRS between Genotypes ........................... 58
2.4.4 Bleached versus Not Bleached 'I'Issue ............................... 59
2.4.5 Limitations of SS, VIRS and BIRS ...................................... 59

vii

2.5 Discussion .......................................................................................... 60

2.5.1 SS, VIRS and BIRS within a Genotype ............................... 60
2.5.2 SS, VIRS and BIRS between Genotypes ........................... 65
2.5.3 Bleached versus Not Bleached Tissue ............................... 66
2.5.4 Limitation of Scoring Method .............................................. 68
2.5.5 Conclusions ........................................................................ 70
2.6 Acknowledgements ............................................................................ 71
Figure 2-1 ................................................................................................. 72
Figure 2-2 ................................................................................................. 74
Figure 2-3 ................................................................................................. 76
Table 2-1 .................................................................................................. 78
2.7 References ......................................................................................... 79
3 IDENTIFICATION AND MAPPING OF A OTL FOR RESISTANCE TO
FUSARIUM HEAD BLIGHT ON CHROMOSOME ARM 2DL OF WHEAT.

..3 1 Abstract ............................................................................................. 86
3.2 Introduction ........................................................................................ 87
3.3 Materials and Methods ...................................................................... 89
3.3.1 Plant Materials .................................................................... 89
3.3.2 Greenhouse Planting .......................................................... 89
3.3.3 Inoculum Production ........................................................... 91
3.3.4 Inoculation .......................................................................... 91
3.3.5 Evaluation of Disease ......................................................... 93
3.3.6 Data Analysis ...................................................................... 93
3.3.7 Independent Phenotyping of CASSQ4 ................................ 95
3.3.8 DNA Marker Analysis .......................................................... 96
3.3.9 Linkage Map Construction .................................................. 98
3.3.10 OTL Analysis ...................................................................... 99
3.4 Results ............................................................................................ 100
3.4.1 SSR data .......................................................................... 100
3.4.2 Linkage Map Construction ................................................ 101
3.4.3 Phenotypic Data ............................................................... 102
3.4.4 OTL Analysis .................................................................... 104
3.5 Discussion ....................................................................................... 107
3.5.1 QTL on 2DL ...................................................................... 107
3.5.2 Potential for Marker Assisted Selection ............................ 108
3.5.3 Combining Resistance ...................................................... 109
3.5.4 W14 Resistant Check ....................................................... 111
3.5.5 Transgressive Segregation ............................................... 112

3.5.6 Disease Measurement Methods and QTL
Detection Overall ............................................................ 112
3.5.7 Greenhouse Screening Design ......................................... 116
3.5.8 Marker Data ...................................................................... 117
3.5.9 Consistency of CASS94 Resistance ................................. 118
3.5.10 Conclusions ..................................................................... 118
3.6 Acknowledgements .......................................................................... 121

viii

Table 3-1 ................................................................................................ 122

Table 3-2 ................................................................................................ 123
Table 3-3 ................................................................................................ 124
Table 3-4 ................................................................................................ 125
Table 3-5 ................................................................................................ 126
Figure 3-1 ............................................................ 129
Figure 3-2 .................... 137
Figure 3.3 ............................................................................................... 142
.Figure3-4 ............................................................................................... 143
Figure 3-5 ............................................................................................... 148
Figure3-6 ............................................................................................... 151
Figure 3-7 ............................................................................................... 152
3.7 References ....................................................................................... 153

ix

LIST OF TABLES

TABLE 2-1: THE NUMBER AND PERCENTAGE OF OBSERVATIONS OF
NING7840 AND NORM SPIKES AT 7 AND 14DP| WITH 88, VIRS AND
BIRS VALUES THAT REACHED THE EXPREMES OF THE SPIKE. ..... 78

TABLE 3-1: PROBLEMATIC PRIMER PAIRS. ................................................. 122

TABLE 3-2: EMPIRICALLY DETERMINED LOD THRESHOLD VALUES FOR
EACH DISEASE MEASURE/DPI COMBINATION FOR P<0.01. ........... 123

TABLE 3-3: MAPPING LOCATIONS OF PREVIOUSLY UNMAPPED BARC
PRIMER PAIRS. .................................................................................... 124

TABLE 3—4: AVERAGE OF PHENOTYPIC MEANS AND THE PERCENT
REDUCTION FOR 99 DH LINES WITH EITHER THE CASSQ4 OR
F LYCATCHER ALLELE FOR XGWM539. ............................................. 125

TABLE 3-5: QTL AND PUTATNE QTL IDENTIFIED EITHER BY SINGLE
MARKER ANALYSIS (SMA) OR COMPOSITE INTERVAL MAPPING
(CIM). ................................................................................................... 126

LIST OF FIGURES

FIGURE 2-1: DIAGRAM OF THREE METHODS OF DISEASE
EVALUATION .......................................................................................... 72

FIGURE 2-2: EFFECT OF GENOYTPE, TIME OF ASSAY, AND METHOD
OF ASSAY ON THE NUMBER OF INFECTED SPIKELETS OR RACHIS
SECTIONS IN A RESISTANT (NING 7840) AND SUSCEPTIBLE (NORM)
WHEAT CULTNAR. ................................................................................ 73

FIGURE 2-3: RELATIVE FREQUENCY DISTRIBUTIONS OF DISEASE AS
DETERMINED BY THREE MEASURES IN NING 7840 AND NORM AT
7DPI (A) AND 14DPI (B). ......................................................................... 76

FIGURE 3—1: LINKAGE MAPS FOR 130 DH LINES ......................................... 129

FIGURE 3-2: FREQUENCY DISTRIBUTIONS OF 108 DIHAPLOID LINES
EVALUATED WITH SEVERAL DISEASE SCORING METHODS. ........ 137

FIGURE 3-3: FREQUENCY DISTRIBUTION OF THE AVERAGE TOTAL
NUMBER OF SPIKELETS PER SPIKE FOR 108 DH LINES. .............. 142

FIGURE 3-4: COMBINED LINKAGE MAP AND COMPOSITE INTERVAL
MAPPING LODGRAPHS FOR A REGION OF CHROMOSOME ARM
20L. ....................................................................................................... 143

FIGURE 3-5: COMBINED LINKAGE MAPS AND LOD GRAPHS FOR CIM
DERIVED QTL ON LINKAGE GROUPS OF CHROMOSOME 4A, AND
CHROMOSOME ARMS 5AL AND 5DL .................................................. 148

FIGURE 36: FREQUENCY DISTRIBUTION OF THE MEAN NUMBER OF
SCABBY SPIKELETS AT 1ODPI FOR 99 DH LINES WITH EITHER THE
CAS'894 ALLELE (STRIPED BARS) OR THE F LYCATCHER ALLELE
(BLACK BARS) FOR THE SSR LOCUS XGWM539 . ........................... 151

FIGURE 37: FREQUENCY DISTRIBUTION OF THE MEAN PERCENTAGE OF
SCABBY SPIKELETS AT 21 DPI FOR 99 DH LINES WITH EITHER THE
CASSQ4 (STRIPED BARS) OR THE FLYCATCHER ALLELE (BLACK
BARS) FOR SSR LOCUS XGWM539 .................................................... 152

xi

KEY TO SYMBOLS AND ABBREVIATIONS
AUDPC — Area under the disease progress curve
BARC - Beltsville Agricultural Research Center
BIRS - Bioassay infected rachis sections
CIM - Composite interval mapping
CIMMYT — International Center for the Improvement of Maize and Wheat
CMC — Carboxymethyl cellulose
DON - Deoxynivalenol
DH - Dihaploid
DPI - Days post inoculation
FHB - Fusarium head blight
GWM - Glatersleben Wheat Microsatellite
GDM - GIastenben D-genome Microsatellite
LOD — Log of odds ratio
MSU - Michigan State University
PCR - Polymerase chain reaction
PR - Pathogenesis related
QTL - Quantitative trait loci
R2 - Coefficient of determination
REC — Recombination frequency
SMA - Single marker analysis
SAR — Systemic acquired resistance

SS - Number of scabby spikelets

xii

SSR - Simple sequence repeat
VIRS — Visually infected rachis sections

WMC - Wheat Microsatellite Consortium

xiii

CHAPTER 1

FUSARIUM HEAD BLIGHT IN WHEAT: IMPORTANCE, PATHOLOGY AND
HOST PLANT RESISTANCE.

1.1 Wheat: in and Im rtance

Wheat domestication is thought to have initiated in the Fertile Crescent
over 10,000 years ago (Feldman, 2001 ). Today's common wheat (Triticum
aestivum L. ssp. aestivum) is a self-pollinating allohexaploid (2N = 6X = 42,
AABBDD) consisting of three genomes (2N = 2X = 14), A, B and D. These three
genomes (A, B and D). diverged from a common ancestor, and then converged
through hybridization followed by endoreduplication to give rise to Triticum
aestivum (Feldman, 2001). The extant diploid species Tn'tI'cum uraItu (AA) and
Aegilops tauschii are considred direct descendents of the A and D genomes,
respectively (Feldman, 2001; Kimber, 1993). The B genome, on the other hand,
is no longer found as a diploid species in nature (IGmber, 1993). It is
hypothesized that the B genome was derived from Aegilops speltoides (SS),
which is found in nature, or an extinct species with a similar genome (Feldman,
2001). However, the B genome is found in nature in combination with the A
genome in the tetraploid Tn’tI'cum turgidum, from which Triticum durum was
domesticated. T. turgidum is also the donor of the A and B genomes to T.
aestivum. The similarity of the three genomes of wheat is great enough that

apart from a single locus, Ph 1 (pairing homoeologous) on chromosome 58,

homoeologous chromosomes from the three genomes would pair during meiosis
(Kimber and Sears, 1987). The Ph 1 locus on chromosome 58 prevents non-
homologous chromosome pairing during meiosis (IGmber and Sears, 1987).
Thus, although 7'. aestivum is technically a hexaploid, it exhibits disomic
inheritance for individual loci.

The original polyploidization events leading to the tetraploid and hexaploid
wheats each represent a bottleneck and a dramatic form of a founder effect in
wheat (Ladizinsky, 1985). Interspecific and intergeneric crosses between T.
aestivum and its progenitors have proven to be valuable tools for introgression of
desirable traits into T. aestivum (Mean, 1987; Mujeeb-Kazi, 1993). Synthetic
wheats are one product of intersmcific crosses that have been particularly
successful for the introgression of traits (Mujeeb—Kazi, 1995). As described
above, hexaploid wheat is composed of the three genomes: A, B and D.
Synthetic wheats are hexaploids that are created by combining sources of the A,
B and D genomes into a single hexaploid. A common method of creating a
synthetic wheat is through hybridizing Triticum durum or Triticum turgidum
(tetraploids containing the A and B genomes) with Aegilops tauschii (a diploid of
the D genome) (Mujeeb-Kazi, 1993). Chromosome doubling, induced or
spontaneous, in the F1 hybrids of these crosses results in a hexaploid wheat
(Mujeeb-Kazi, 1995). A powerful application of synthetic wheats is the
exploitation of diversity present in Ae. tauschii that is not represented in
cultivated common wheat due to a founder effect during the natural evolution of

1'. aestivum (Ladizinsky, 1985; Lage et al., 2003b; Lubbers et al., 1991 ).

Synthetic wheats with desirable traits can be crossed with common wheat for the
improvement of elite cultivars. Examples of valuable traits that have been
identified in synthetic wheats include agronomimlly desirable traits such as high
yield (Gororo et al., 2002; Haung et al., 2003), pre-harvest sprouting resistance
(Gatford et al., 2002; Lan et al., 1997), resistance to waterlogging (Villareal et al.,
2001), tolerance to high temperatures (Yang et al., 2002), enhanced
photosynthetic performance (Del Blanco et al., 2000), ear emergence time
(Haung et al., 2003), plant height (Haung et al., 2003), increased grain weight
(Haung et al., 2003), increased grain element concentrations (Calderini and
Ortiz-Monasterio, 2003) and components of breadmaking qualities (Pfluger et al.,
2001; WIeser et al., 2003). In addition, valuable resistance to biotic factors have
been identified in synthetic wheats including resistance to Fusarium head blight
(Gilchrist et al., 1999; Mujeeb-Kazi et al., 1999), Karnal bunt (VIllareaI et al.,
1995a; VIlIareal et al., 1995b), Septoria tritici blotch (Arraiano et al., 2001), leaf
and stem rust (Innes and Kerber, 1994) and insects (Lage et al., 2003a; Smith

' and Starkey, 2003). Desirable traits of have been identified in Ae. tauschii
accessions through screening them directly before the creation of synthetics,
though some traits con not be practically screened in Ae. tauschii (Mujeeb-Kazi,
1993). However, it has been observed that many positive traits can be identified
in a synthetic without prior screening in Ae. tauschii, and that A and B genomes
can also affect the expression (positively or negatively) of desirable traits in the
synthetic wheat (Mujeeb—Kazi, 1993).

Intergeneric hyindizetions have also been used to introgress important
traits into Tn'ficum aestivum, however intergeneric crosses have a lower success
rate and therefore require more time than interspecfic crosses (Mujeeb-Kazi,
1993). Nonetheless, intergeneric hybrids have been successfully made between
Trificum and several other species including Secale, Agrypyron, Hordeum,
Haynaldia and Elymus (Bommineni and Jauhar, 1997; Mean, 1987; Mujeeb-Kazi,
1993)

Although wide crosses, such as interspecific and intergeneric crosses, can
be a good resource for genetic diversity and the identification and introgression
of valuable traits, there are disadvantages of using wide crosses between plant
species. Some disadvantages of these types of crosses include cross
incompatibility, poor vigor in the F1 hybrid, hybrid sterility (often because of a
lack of chromosome pairing during meiosis), poor vigor or fertility in the F2
generation (Hadley and Openshaw, 1990), and segregation distortion (Xu et al.,
1997). HoweVer, wheat synthetics have been observed to behave like common
wheat. The high similarity in genome structure between synthetic wheats and
domesticated wheats is illustrated by the fact that the wheat genetics community
today uses a synthetically derived population (from a synthetic crossed with a
common wheat) as its standard reference mapping population and the mapping
positions of marker loci are confirmed in other maps (Gupta et al., 2002; Hazen
et al., 2002; Mingeot and Jacquemin, 1999; Pestsova et al., 2000; Radar et al.,
1998; Waldron et al., 1999).

Since its domestication, wheat has become the most widely adapted
cereal crop (Briggle and Curtis, 1987) and a fundamental staple food crop around
the world. In the last forty years alone, global wheat production has increased
dramatically. In the 1990’s (1995-1999) global wheat production (in tones) was
more than double that in the 1960s (Marathee and Gomez—Macpherson, 2001).
In addition, wheat demands are expected to increase into the future. Projections
until 2030 suggest that imports of wheat in developing nations will continue to
grow in compensation for an increase in population as well as a shift towards
more wheat based products (Marathee and Gomez-Macpherson, 2001). The
United States is the largest exporter of wheat in the world (Marathee and Gomez-
Macpherson, 2001; Landes et al., 1998) even though the amount of wheat being
used domestically in the US (1996 to 2003) has been greater than the amount
of wheat exported (Wescott, 2004). Yield per unit area land is required to meet
projected demand since additional land for production is limited (Marathee and
Gomez-Macpherson, 2001).

1.2 Immct of Fusarium Head Blight
Fusarium head blight (F HB), caused by Fusarium spp. and Microdochium

nivale (Parry et al., 1995), is a disease of wheat and barley currently threatening
the wheat and bariey industries in North America as well as Europe, Asia and
South America (Cook, 1981; McMuIIen et al., 1997; Snijders, 1990; Stack, 2003).
F HB leads to reduction in yield and grain quality. Most critically, contamination of

grain with Fusarium mycotoxins (especially deoxynivalenol) poses health risks

and diminishes the value of FHB affected grain (McMuIIen et al., 1997; Snijders,
1990; Wannemacher and WIener, 1997). Fusarium head blight has been
observed in North America since 1884 (Arthur, 1891; Stack 2003), and frequent
outbreaks occurred throughout the twentieth century including particularly serious
episodes between 1928 and 1937 (McMuIIen et al., 1997). More recently, the
United States has seen an alarming increase in the frequency of F HB epidemics.
In the 1990’s alone, losses to the wheat and barley industries in the United
States due to FHB were estimated to be nearly three billion US dollars
(WIndeIs, 2000). Changes in agronomic practices in the United States, including
shorter crop rotations and reduced tillage, are considered important factors
contributing to the increased frequency of FHB epidemics in recent years (Dill-
Macky and Jones, 2000).

1.3 FHB Causal Organisms
Sixteen species of Fusarium, and one species of Microdochium (M. nivale,

formerly known as Fusarium nivale) have been associated with F HB of small
grains around the world (Parry et al., 1995). In North America and Asia, F HB is
predominantly caused by F. graminearum (Schwabe) (perfect stage Gibberella
zeae (Schw.) Petch) (Gale et al., 2002; Perry et al., 1995). In Northern Europe,
F. culmorum is the primary causal agent of FHB (Parry et al., 1995). FHB
research has increased recent years, and the majority of this research has
focused on F. graminearum and F. culmorum. The two species, F. graminearum

and F. culmorum, are considered closely related, and resistance to F.

graminearum and F. culmorum have been similar in both spring and winter
wheats (Mesterhazy, 1987; Snijders and Perkowski, 1990; Van Eeuwijk et al.,
1995). This review will focus on F. graminearum and F. culmorum. In addition,
although ascospores serve as the primary inoculum in natural field infections,
artificial inoculations in the greenhouse and field are often conducted with
macroconidia of Fusarium spp. Ascospores of G. zeae and conidia of F.
graminearum give similar levels of incidence and severity of disease (Stack,
1989) and both are considered in studies of infection and host plant resistance.
In this review, studies using ascospores as inoculum are not distinguished from

those using macroconidia.

1 .4 Invasion and Colonization of Wheat by Fusarium

Initial infection of Fusarium on wheat spikes often occurs during warm, wet
weather at the time of wheat anthesis (Andersen, 1948; Francl et al., 1999).
Ascospores of G. zeae are forcibly ejected from perithecia (often on corn or
wheat residue in the field) and land on wheat spikes (Andries et al., 2000). The
identification of the plant organs most often initially infected by the spores
remains unclear. Several studies suggest that anthers extruded during anthesis
are the primary target for initial infection, or are important factors in infection
(Andersen, 1948; Pugh et al., 1933; Ribichich et al., 2000; Strange and Smith,
1971 ). Pugh et al. (1933) found that the progression of infection followed the
general progression of anthesis, which begins in the center of the spike and

proceeds outward towards the tip and base of the spike. Andersen (1948)

confirmed that infection appeared to be dependent upon anthesis. Furthermore,
Pugh et al. (1933) found that spikelets that remained Closed (did not extrude their
anthers) were unlikely to become infected and their histological observations
revealed that early stages of colonization frequently began on the anthers and
not on the glumes. Similar results were found in a study by Strange and Smith,
1971, where by 48 hours after inoculation anthers were abundantly colonized
while other tissue was generally free of infection. In addition, a comparison of
the infection of emasculated and non-emasculated heads showed that extruded
anthers promotetheinfectionofotherpartsofthewheathead, andthatextracts
of anthers stimulated growth of F. graminearum more than extracts of other
wheat spike tissues (Strange and Smith, 1971). Schroeder and Christensen
(1963) found that different host genotypes varied in degree of susceptibility at
different stages of maturity (before, during and after anthesis) suggesting that
extruded anthers may not always be the only plant tissue to be initially infected
since anthers are not exposed before anthesis and are eventually lost after
anthesis. In addition, infection of other organs of the spike was observed in
several studies. Bennett (1931) induced infection with droplets of inoculum
placed on the edges of the glumes and palea. However, the thickness and
impenetrability of glumes are thought to impede successful colonization of wheat
by Fusarium (Pritsch et al., 2000; Pugh et al., 1933). Direct penetration of
glumes is rarely reported (Pritsch et al., 2000; Ribichich et al., 2000) although
hyphae were observed invading through the stomata of glumes and leaf tissue
(Kang and Buchenauer, 2000a; Kang and Buchenauer, 2000c; Pritsch et al.,

1998; Pritsch et al., 2000). F. culmorum dimctly penetrates epidermal cell walls
of the lemma and ovary (Kang and Buchenauer, 1999; Kang and Buchenauer,
2000b; Kang and Buchenauer, 2002b). Kang and Buchenauer (2002b) observed
infection hyphae develop on the inner surfaces of florets within 36 hours of
inoculation. These infection hyphae were outgrowths of hyphae in contact with
the inner surface of a floret’s lemma, palea and other internal serfaces of a floral.
A penetration peg developed from what they described as an infection hyphae
(infection hyphae appeared as short hyphae branched off of longer hyphae). The
penetration peg did not form from an appressorium, and penetration was direct
though not always complete.

From the collection of studies above, it appears that the extrusion of the
anthers at anthesis may allow for some initial growth of the fungus, as well as
give the fungus easier access to the inner surfaces of the lemma and palea
where it can more easily penetrate the host tissues, and that entrance of the
fungus through the stomata also occurs. There is, however, a clear and
compelling need for additional work to clarify the exacty means by which
Fusarium infects wheat spikes.

Once the fungus is established in the wheat spike, the fungus colonizes
several cell types both inter- and intracellulerly (Kang and Buchenauer, 1999;
Kang and Buchenauer, 2002b; Pugh et al., 1933; Ribichich et al., 2000;
Schroeder and Christensen, 1963). Pugh et al. (1933) found that the mycelia
primarily colonize chlorophyllous tissues, while Pritsch et al. (2000) found that

when glumes of wheat were inoculated, the fungus tended to colonize the

chlorenchyma and parenchyma. In addition, Pugh et al. (1933) found that
although hyphae did not heavily colonize the vascular cells, colonization was
greater in of the phloem as opposed to the xylem. In contrast, Schroeder and
Christensen (1963) reported that hyphae first colonized vascular bundles, then
the surrounding tissues. In a study of F. culmorum infection of a susceptible
host, the fungus reached the rachis and colonized the xylem vessels and phloem
sieve tubes, growing inter- and intracellularly through the parenchyma cells
outside the vascular bundles by four to six days post inoculation (Kang and
Buchenauer, 1999). From these studies, it is unclear to what extent F.
graminearum or F. culmorum colonizes or the vascular bundles, but it is apparent
that the fungus colonizes many different types of host cells.

Cytological investigations of infected wheat kernels have shown that the
extent of fungal colonization varies for different sections of the kernel (Pugh et
al., 1933; Seitz and Bechtel, 1985). Using serial sections of the kernels, Pugh et
al. (1933) observed a difference in colonization of kernels that were inbcted
earlier or later in their maturation. When the ovary was colonized early in seed
development, the fungus easily colonized the entire kernel. However, in later
infections, hyphae were confined to the pericarp near the embryo and to the
embryo itself, possibly because greater resistance of the pericarp to penetration.
In contrast, Seitz and Bechtel (1985) found that the fungus colonized throughout
the kernel and colonization was most concentrated in the pericarp. Histological
studies by Seitz and Bechtel (1985) also found that lightly colonized kernels had

hyphae in both the pericarp and the starchy endospenn.

IO

Disease generally progresses from the initially inoculated spikelet, through
the rachis to other spikelets on the wheat spike. Some studies have found that
the fungus primarily colonizes basipetally from the initial point of inoculation
through the rachis (Savard et al., 2000; TeKrony et al., 2000). Other studies
have showed substantial colonization both acropetally and basipetally from the
point of inoculation (Pritsch et al., 2000; Pugh et al., 1933; Schroeder and
Christensen, 1963). In addition, colonization of rachis sections does not always
result in infection of spikelets at that point (Pugh et al., 1933; TeKrony et al.,
2000).

1.5 m toms of FHB

Symptoms of FHB in wheat appear as brownish discoloration, water
soaked lesions and loss of chrlorophyll in spikelets and the rachis (Andersen,
1948; Pugh et al., 1933; Savard et al., 2000). In studies of infection with F.
culmorum, initial symptoms of infection appeared as light brown, water-soaked
spots on the glumes (Snijders and Krechting, 1992). Brown discoloration
appeared once F. culmorum began colonizing intracellularly in another study
(Kang and Buchenauer, 1999). However, symptoms, or lack of symptoms, from
infections by F. graminearum or F. Culmorum, are not necessarily indicative of
the presence or absence of the fungus (Pugh et al., 1933; Schroeder and
Christensen, 1963). Several researchers have observed that fungal infection in
lower portions of the rachis often results in a loss of chlorophyll, wilting and

shriveled kernels in acropetal tissues of the spike (Bel and Shaner, 1996; Kang

11

and Buchenauer, 1999; Pugh et al., 1933; Savard et al., 2000). Conversely, it
was observed that some varieties may have infection in the seed in the absence
of visible signs of damage to that tissue (Schroeder and Christensen, 1963).
Bushnell et al. (2003) suggests that asymptomatic stage of initial colonization of
wheat or barley tissue (Pritsch et al., 2000; Bushnell et al., 2000; Kang and
Buchenauer 1999) reflects a biotrophic phase of the pathogen, which is then
followed by a necrotrophic phase (killing host cells in advance of colonization) as

colonization proceeds (Kang and Buchenauer 2000a).

1 .6 Fusarium Mycotoxins and Infection

Fusan'um mycotoxins have been investigated for their involvement in
pathogenicity and virulence of the fungus during infection. Both F. graminearum
and F. culmorum produce trichothecenes (including Deoxynivalenol (DON), 3-
acetyldeoxynivalenol (3-ADON), Nivalenol, and T-2 toxin), which are nonvolatile,
low molecular weight sesquiterpenoids (Cole and Cox, 1981) that inhibit protein
synthesis in plants and many mammals (Wannemacher and Wrender, 1997). To
determine if trichothecenes are virulence factors or pathogenicity factors of F.
graminearum infection of wheat heads, Desjardins et al. (1996) compared the
colonizing ability and disease symptoms of a wild type isolate of G. zeae and a

mutant strain of G. zeae that lacked the ability to produce any trichothecene

, toxins on six different wheat cultivars. The mutant strain was able to infect the

wheat heads, but mused fewer disease symptoms. The authors concluded that

the trichothecenes are virulence factors and not pathogenicity factors. In a similar

12

study by Bai et al. (2001) a DON—minus mutant of F. graminearum was able to
infect wheat but was unable to spread throughout the wheat spike. Wanyoike et
al. (2002) tested fifteen different isolates of F. graminearum for virulence and
mycotoxins production on susceptible (‘Agent’) and moderately resistant (‘Arina’)
genotypes. DON was the primary trichothecene produced by all fifteen isolates.
Isolates differed for virulence on the two genotypes and DON content was
significantly correlated with the Area Under the Disease Progress Curve
(AUDPC) based on damaged spikelets. Mesterhazy (2002) showed that
virulence was associated with the trichothecene production of isolates of F.
culmorum and F. graminearum. Together these results support the hypothesis
that trichothecenes are important in the vimlence of F HB, but they are not
essential for initial infection. Zearalenone, a toxic mycoestrogen is also produced
by F. graminearum, but no correlation was found with either virulence or
pathogenicity in infection of wheat heads (Atanassov et al., 1994; Bagi et al.,
2000).

Several studies have examined the localization of trichothecenes with
respect to the growth of the fungus. In studies of F. culmorum by Kang and
Buchenauer (1999 and 2002b) DON and 3-ADON were produced by hyphae in
contactwiththesurfaceofthe hosttissue even before penetration ofthe host
DON was found near penetration pegs before infection, and near hyphae
subsequent to infection (Kang and Buchenauer, 1999, 2002b). Toxins were
found at lower concentrations in tissue further away from the hyphae (Kang and

Buchenauer, 1999, 2002b). Changes in the host call, such as the breakdown of

13

the organelles and convolution of the cytoplasm were correlated with the
presence of DON and 3-ADON (Kang and Buchenauer, 1999). DON and 3-
ADON mycotoxins can be translocated from areas colonized by the fungus either
through the xylem and phloem sieve tubes when translocated acropetally or
through the phloem sieve tubes when translocated basipetally (Kang and
Buchenauer, 2002b). By ten days post inoculation DON and 3-ADON were
found in rachis tissue above and below the point initially inoculated, as well as
beyond the area colonized by the fungus (Kang and Buchenauer, 1999).
Snijders and Krechting (1992) found similar results in a study of F. culmorum
infection where DON appeared to be transported from the chaff of the spike to
the developing kernel prior to the fungus invading the kernel in susceptible
genotypes. In a study by Savard et al. (2000) localization and concentration of
DON was examined in the intemodes of the rachis and the spikelets at regular
intervals after inoculation of a susceptible cultivar. DON began to accumulate in
high concentrations by 4 days post inoculation and the concentration of DON
was much higher in the rachis than in the spikelets. Interestingly, DON amounts
in the rachis were much higher below the spikelet initially inoculated as opposed
to above.

Toxin localization and concentration has also been examined with respect
to general symptoms of the disease. Several studies conclude that symptoms of
disease are correlated with the concentration of trichothecenes in the spike
(Atanassov et al., 1994; Bai et al., 2001; Lemper et al., 2000; Lemmens et al.,
1997; Miedaner et al., 2003; Seitz and Bechtel, 1985; Wong et al., 1995). Seitz

14

and Bechtel (1985) found that kernels that had the most “scabby' (i.e., shriveled
and moldy) appearance had the highest DON and ergosterol content (reflective
of fungal mass) and the lowest mass. However, kernels that were moderately
affected (normal size but lower mass) still had high ergosterol and DON content,
though these concentrations were lower than heavily infected kernels (Seitz and
Bechtel, 1985). In another study by Lemper et al., 2000, DON and ergosterol
content were positively correlated with each other, and DON and ergosterol
content were both positively correlated with the degree of kernel infection. Wong
et al. (1995) also found that DON content was highly correlated with the number
of shriveled or highly infected kernels. Atanassov et al. (1994) had similar results
when thirty strains of seven Fusarium species differing in their amount and type
of trichothecene produced (either DON, nivalenol and/or T-2 toxin) were used to
inoculate seven different wheat genotypes varying in FHB resistance. A
significant correlation was found between the reduction of grain weight and the
concentration of mycotoxins from infection by the most virulent strains of
Fusarium. However, for less virulent strains, the correlation between mycotoxin
concentration and grain weight reduction was weaker. In contrast, in a field
study of four wheat genotypes differing in levels of resistance higher levels of
resistance were correlated with reduced DON and visual symptoms of seed
damage, however DON levels were not well correlated with infection of the seed
(Argyris et al., 2003). The authors concluded that the resistance observed may
improve grain quality and reduce yield loss, but may not have a large effect on

actual seed infection (Argyris et al., 2003). In addition, infections of forty-five

15

resistant aid susceptible genotypes with a large number of F. graminearum and
F. culmorum isolates revealed that although the most resistant host genotypes
consistently accumulated very low concentrations of DON, moderately
susceptible and susceptible genotypes with similar visual disease ratings of F HB
had varying amounts of DON in grain (Mesterhazy et al., 1999). An in vitro
study by Seeland and Bushnell (2001) barley leaf segments treated with high
concentrations of DON in the light showed a loss of chlorophyll and carotenoids,
resulting in the “bleaching” effect, but cell death was delayed as much as five
days. Tissues with lower levels Of DON exhibited a reddish-brown color
(Seeland and Bushnell, 2001). These results support the role of trichothecenes
as important factors in the development of disease symptoms.

1.7 FHB and II Wall radin E s

Kang and Buchenauer (2000b and 2002b) used enzyme and immunogold
labeling of cellulose, xylan and pectin to assess the role of cell wall degrading
enzymes in wheat. The amounts of cellulose, xylan and pectin were significantly
reduced in portions of the floral and rachis colonized by F. culmorum. In
addition, reductions in cellulose, xylan and pectin were observed in areas not yet
colonized by the fungus. Furthermore, the reductions of cellulose, xylan and
pectin coincided with morphological changes in cell walls and middle Iamella.
These results suggest that cell wall degrading enzymes, either produced by the
fungus or induced by the host, may facilitate the spread of the fungus in the host

plant by weakening cell walls and the middle Iamella. However, these data are

16

from an indirect, correlative measure and more research is required to determine

the role of cell wall degrading enzymes are important in pathogenesis.

1.8 Chemical and Biolgglcal Controls of FHB
Chemical and biological controls have been investigated for their efficacy

in controlling FHB. This literature review will not go into detail about these types
of controls of FHB. For reviews of chemical and biological controls of FHB see
Mesterhazy (2003) and Da Luz et al. (2003) respectively. In short, many
different fungicides and biological controls have been evaluated for efficacy
against FHB (McMuIIen and Milus, 2002; Mesterhazy, 2003). Chemical and
biological controls have had limited but significant effects on FHB development.
Although chemical applications of fungicides have shown a reduction in F HB, no
chemical control has been identified that completely stops or prevents the
development of FHB (McMuIIen and Milus, 2002; Mesterhazy, 2003). In addition,
in fungicide trials on artificially inoculated wheat field plots, none of the chemical
controls limited the disease (and specifically, DON accumulation) to commercially
acceptable levels (Mesterhazy, 2003). Biological controls have also being
investigated for efficacy in reducing F HB. Da Luz et al. (2003) lists 12 bacteria,
six yeasts and two fungi identified as showing some degree of control of F HB.
The mechanisms by which these organisms are effective as biocontrols is not
clear, but antibiotic properties, competition, potential inhibition of mycotoxin
production by Fusarium , and induced host resistance are thought to be some of
the factors involved (Da Luz et al., 2003). Apart from the ability of a fungicide or

17

biocontrol agent to control F HB, there are complications in both method and
timing of application that have made the use of chemical and biological controls
difficult A major difficulty has been to identify, or create, equipment that enables
effective coating of the wheat head with the fungicide. The majority of equipment
available is designed to target the more horizontally oriented leaf tissue rather
than the vertically oriented wheat spike (Halley et al., 1999). Researchers have
worked to test, modify and create equipment that will spray biological and
chemical controls adequately on the wheat head (De Ackermann et al., 2002;
Draper et al., 2002; Halley et al., 1999; Halley et al., 2003; Kirk et al., 2003).
Another difficulty in applications of chemical and biological controls is timing of
applications. Most of the efficacious fungicides identified to date are not
translocated well in the plant, thereby requiring application of the control agent
after emergence of the spike (Mesterhazy, 2003). However, F HB develops best
under wet conditions (Francl et al., 1999), which are not conducive for ground-
based applicator equipment. In addition to the timing of application, the use of
biological control is also complicated by the ability of the biocontrol to survive in

the environment after application (Da Luz et al., 2003).

1.9 Mechanisms of Resistance to FHB

Host resistance to F HB has been categorized according to the specific
effect of the resistance (Mesterhazy, 1995; Schroeder and Christensen, 1963;
Wang and Miller, 1988). Resistanceto initial infection and resistance to spread

of infection are the most widely recognized and studied types of resistance and

18

are referred to as Type I and Type II, respectively (Schroeder and Christensen,
1963). Other types of resistance are postulated to include resistance to kernel
infection, tolerance to infection, resistance to mycotoxin accumulation and
avoidance (Mesterhazy, 1995; Schroeder and Christensen, 1963; Wang and
Miller, 1988).

Type II resistance (resistance to spread) is the most commonly reported
type of resistance. Two of the most studied sources of Type II resistance include
‘Sumai 3’ and ‘Frontana’ (Singh et al., 1995; Van Ginkel et al., 1996; Waldron et
al., 1999). These genotypes also show a low level of Type I resistance (Pritsch et
al., 2000; Siranidou et al., 2002).

Schroeder and Christensen (1963) did not identify any gross histological
or morphological differences when comparing resistant (Type II) and susceptible
genotypes, suggesting that the resistance was due to physiological activities of
the host. Kang and Buchenauer (2000c) using electron microscopy to study the
differences between resistant varieties (F rontana and ‘Arina’) and a susceptible
variety (‘Agent’), the resistant varieties developed a greater number of
observable physical barriers during the spread of infection - including a greater
degree of Iignification, more appositions and papillae, and the accumulation of
callose. Further investigations by Kang and Buchenauer (2000C) showed
similarities between the resistant (Arina and Frontana) and susceptible (Agent)
varieties in the initial infection process (i.e., no difference in resistance to initial
infection), but colonization of the pathogen from the rachilla to the rachis was

faster in the susceptible cultivar than in the resistant cultivars. In addition, the

19

resistant cultivars had a lower accumulation of DON in the beginning stages of
infection, which the authors postulated may be the result of defense mechanisms
that can restrict the translocation of the toxin. The susceptible genotype (Agent)
showed alterations of the host cells in contact or in advance of hyphae growing
intercellularly in the lemma and palea. An electron dense material was found in
the vacuoles, appositions were observed between the host secondary cell wall
and the plasmalemma, and the chloroplasts became enlarged subsequent to
infection of Agent (Kang and Buchenauer, 2002b). The fungus then began to
grow intercellularly. Thionins (which have antimicrobial activity) and
hydroxyproline-rich glycoproteins (which are structural proteins in plant cell walls)
increased more in the spike tissue of inoculated plants of Arina (resistant) than in
Agent (susceptible) (Kang and Buchenauer, 2003), further supporting the
supposition that active structural defenses may be induced to a greater degree in
resistant genotypes.

In a study by Ribichich et al. (2000) symptom development and rate of
hyphae colonization were slower in the resistant cultivar Sumai 3 (Type II
resistance) than the susceptible cultivar ’Pro-INTA Oasis’, thoud'l many of the
cellular changes observed in response to disease were similar. However, the
authors did find that the abaxial epidermis and hypodennis of the resistant line
became thicker than the susceptible line (Ribichich et al., 2000). They concluded
that this thickening delayed infection, instead of preventing it.

Pritsch et al. (2000) studied the transcription levels of Pathogenesis
Related (PR) proteins in the resistant line Sumai 3 (Type II) and a susceptible

20

line, ’Wheaton’, during the first 48 hours after inoculation of glumes. Although
several PR proteins had a similar level of transcription, Sumai 3 showed a
greater and earlier accumulation of PR4 and PR5 (thaumatin-Iike protein). In
addition, defense genes in the susceptible genotype began to decline 36 hours
after inoculation, whereas they remained stable or continued to increase in the
resistant Sumai 3. However, no significant difference was seen in the resistance
to fungal colonization between Sumai 3 and Wheaton. The authors suggest that
the induction of the PR proteins may reflect a general response to infection,
versus a specific resistance to invasion by F. graminearum. In a subsequent
study the researchers investigated if PR proteins and peroxidase are expressed
systemically in the wheat head via Systemic Acquired Resistance (SAR)
response after initial infection of the fioret (Pritsch et al., 2001). The authors
compared the accumulation of defense response gene transcripts with the
growth of the fungus on Sumai 3 (resistant), ‘Bobwhite’ (moderately susceptible)
and a Wheaton (susceptible). By forty-eight hours after inoculation they found an
accumulation of all four defense response gene transcripts investigated
(peroxidase, PR-1, PR-3 - a chitinase, and PR-5 - a thaumatin-like protein) in
both colonized and uncolonized regions of infected genotypes, suggesting that
these defense responses are expressed systemically. However, this
accumulation was not always statistically different from the control heads, nor
was it significantly different between resistant and susceptible genotypes. The
authors suggested that factors conferring resistance in the resistant genotype

must be active later in the infection process. Overall, they concluded that the

21

four defense genes evaluated are systemically induced in wheat after invasion by
the pathogen.

PR protein accumulation was also investigated for Sumai 3 and a Sumai
3—derived susceptible mutant by Li et al. (2001). Two chitinase and two 8-1-3
glucanase clones were isolated from a CDNA library constructed from wheat
spikelets inoculated with F. graminearum. Analysis of transcript accumulation
and protein accumulation after inoculation revealed a different pattern of PR
protein accumulation in the resistant line, Sumai 3, versus the susceptible Sumai
3-derived mutant (Li et al., 2001). However, both the wild type and mutant lines
accumulated these proteins. Further studies of near isogenic lines different in
F HB resistance would give a dearer picture into the involvement of these
proteins in defense response to F HB.

The prevalence and localization of chitinase and 8-1.3-glucanase were
also examined in inoculated versus control wheat heads of a resistant line (Arina)
and a susceptible line (Agent) (Kang and Buchenauer, 2002a). The resistant line
accumulated a greater amount of 8-1.3-glucanase and chitinase than the
susceptible cultivar after infection. The authors suggest that these antimicrobial
enzymes may be involved in resistance (Kang and Buchenauer, 2002a).
Together the above studies of PR proteins reveal that defense genes are
induced, though their involvement in resistance to FHB remains unclear.

Phenolic compounds have been found to be involved in antimicrobial
defense responses in plants in general (Agrios, 1997) and are also components

of cell walls in grasses (Wallace et al., 1995). McKeehen et al. (1999) measured

22

phenolic compound types and concentrations present in six wheat cultivars
differing in Type II resistance seven days after anthesis until maturity. The two
primary phenolic acids present during grain development were p-coumaric acid
and ferulic acid. Both compounds significantly inhibited growth of F.
graminearum and F. culmorum. Accumulation of these compounds was greatest
in the resistant varieties, suggesting that these phenolic compounds may be
involved in resistance. Siranidou et al. (2002) also examined the role of phenolic
compounds along with physically observed defense responses and symptom
development in resistant (including Frontana) and susceptible genotypes. They
found that there was a greater accumulation of phenolic compounds in Frontana
than in the susceptible line Agent. In addition, formation of cell wall appositions
was also more pronounced in Frontana than in Agent.

Response of cell wall proteins to Fusarium elicitors was investigated in
vitro by El Gendy et al. (2001). Calli were developed from a resistant line
(‘DH1015’) were treated with extracts from Fusan’um cultures. Ionically-bound
cell surface proteins were then purified and characterized. From their
observations of these proteins before and after treatment they concluded that two

proteins were deposited into the cell wall matrix after treatment with elicitors.

Subsequent exposure to H202 appeared to render these proteins insoluble. The

authors suggest that their data demonstrate the Involvement of these proteins in

defense response in a manner that may be H202 dependent pathway. The

composition of both putative cell wall structural proteins is high in glycine and

serine. Care should be taken in interpreting these results since calli are

23

undifferentiated cell cultures that do not exactly represent the plant tissue organs
that the fungus would infect.

Doohan et al. (2000) examined the constitutive antifungal activity of wheat
kernels. Soluble extracts were made from ground kernels of six resistant
(including Sumai 3, a Sumai 3-derived line ‘CM820036’ and Frontana) and five
susceptible lines. The extracts were added to fungal growth media and assayed
for inhibition of the growth of F. culmorum. They found that extracts from five of
the six resistant genotypes (including Sumai 3, F rontana, CM820036, ‘Anna’ and
‘WEK0609’) significantly inhibited growth of the fungus in comparison with only
one of the susceptible genotypes (‘Riband’). Heat treatment inactivated this
antifungal activity, suggesting that the potentially antifungal compounds could be
proteins. Comparisons of fractions of extracts from Arina (resistant) and Riband
(susceptible) showed two compounds associated with antifungal activity.
Although a correlation has been made between kernel extracts and antifungal
activity, it is not know if these compounds are found in other genotypes, either
resistant or susceptible. In addition, the compounds were extracted from mature
seeds, whereas F HB infection usually takes place during anthesis, therefore
these proteins may not be present during early stages of infection.

Peroxidase and polyphenol oxidase production were compared in
resistant (Sumai 3 and ’Wangshuibai’) and susceptible (‘Falat’ and ‘Golestan’)
wheat lines at different stages of maturity after single floret inoculation with F.
graminearum (Mohammadi and Kazemi, 2002). Peroxidase activity was induced

after inoculation, but did not show a consistent trend with respect to resistance

24

(Sumai 3 and Wangshuibai) or susceptibility (Falat and Golestan). Polyphenol
oxidase activity, on the other hand, was two times greater in resistant versus
susceptible lines, suggesting that polyphenoloxidase activity could be a defense
response against F HB.

Resistance to mycotoxin accumulation was attributed to DON degradation
in a study by Miller and Arnison (1986). Callus cultures of both a resistant line
(Frontana) and a susceptible line (‘Casavant’) were exposed to C14 labeled
DON. Cells from the resistant line showed an 18% decrease in DON, which had
been converted to three other compounds. Callus cells from the susceptible line
showed only a 5% decrease in DON, which had been converted to just one
compound (Miller and Arnison, 1986). However, this study should be interpreted
with caution because the callus cells may not directly reflect the reaction of
specific plant organs. In another study of DON by Snijders and Krechting (1992),
investigation of 22 genotypes varying in degrees of resistance showed that DON
translocation into developing kernels is inhibited in resistant lines inoculated with
F. culmorum, and fungal colonization of the kernels was less than in susceptible
genotypes. The authors suggested that resistant lines had a membrane-based
tolerance to trichotehecenes.

Although tolerance to infection is considered a mechanism of resistance to
F HB (Mesterhazy, 1995), no research has examined the molecular mechanisms
responsible for this resistance. Tolerance to infection would allow for wheat
plants to be heavily infected, but not show a significant impact of disease on the
plant as with shriveled grain. Sound grain that is heavily colonized by the fungus

25

is not in fact desirable for the wheat industry unless DON production is
suppressed.

Type I resistance, resistance to initial infection, is dependent on genetic
factors as well as host stage Of development (see “Invasion and Colonization of
Fusarium” above). Although a moderate level of Type I resistance has been
identified in some genotypes, the mechanisms underlying genetic resistance
have not been closely examined. However, histological studies by Schroeder
and Christensen (1963) suggested that the genetic component of Type I
resistance was due to physiological activities and not anatomical differences

present in resistant hosts prior to inoculation.

1.10 Artificial Inoculation Methods for FHB Induction

Three different general methodsare used for aritificial inoculation of wheat
spikes with Fusarium spp. to induce F HB: 1) single floret inoculation, 2) spray
inoculation of the head with a liquid spore suspension and 3) distribution of
infected grain (grain spawn) or other plant material. Single floret inoculation is a
controlled method of inoculating the wheat spike so the initial inoculation point is
restricted to a single fioret within one spike. This is typically done through using
a pipette or hypodermic needle to place a small quantity (e.g. 10pl) of liquid
fungal spore suspension beMen the lemma and palea of a floret (Rudd et al.,
2001; Schroeder and Christensen, 1963). A variation of this method is to place a
piece of cotton saturated with liquid inoculum inside the floret (Gilchrist et al.,

1997). Single fioret inoculation is used in both the greenhouse and the field for

26

observing resistance to the spread of die disease. Spray inoculation involves
using spraying equipment to coat the wheat spike with a liquid spore suspension
(Schroeder and Christensen, 1963). This type of inoculation is often used in both
the greenhouse and the field for assessing resistance to initial infection of the
disease (Type I resistance) (Rudd et al., 2001). Grain spawn inoculum is
generally conducted in field conditions. For grain inoculum, sterilized cereal
grains are inoculated with the pathogen and then spread over the surface of the
soil before anthesis (Rudd et al., 2001). This type of inoculation may best mimic
a natural type of inoculation, since natural primary inoculum develops on
colonized surface plant residue (Champeil et al., 2004).

WIth any of these inoculation methods, environmental conditions are
usually altered after inoculation to promote the development of disease. A high
relative humidity following inoculation (in the case of single floret or spray
inoculation) or both before and after anthesis (in the case of grain inoculum)
promotes disease development (Francl et al., 1999). Many researchers have
used overhead misting systems in growth chambers/greenhouses or in the field
to provide a high relative humidity (Anderson et al., 2001; Rudd et al., 2001;
Snijders and Perkowski, 1990). Another method of providing a high relative
humidity is to cover wheat spikes with a plastic bag (Anderson et al., 2001; Bai et
al., 2000; Bourdoncle and Ohm, 2003; Mohammadi and Kazemi, 2002; Shen et
al., 2003a).

Miedaner et al. (2003) compared the effects of spray and point inoculation

for 20 wheat genotypes across seven field environments. They found that

27

although repeatability of host response was high within a method, there was not
a significant relationship between the two methods. These results probably
reflect the ability of the different inoculation methods to reveal the action of

different types of resistance.

1.11 Genetics of Resistance to FHB

Van Eeuwijk et al. (1995) investigated F HB in 25 wheat genotypes in six
field locations over three different years using 17 strains of F. graminearum, F.
culmorum and F. nivale. One strain of F. culmorum was used as a check at all
locations. Their results indicated that although different strains varied for their
level of aggressiveness, very little variation among genotypes could be attributed
to differences between Fusarium strains. In a study by Mesterhazy et al. (1999),
seven isolates of F. graminearum and eight isolates of F. culmorum were used to
inoculate 20-25 wheat genotypes with different degrees of resistance. Their
results showed that within a genotype, similar responses were obtained
irrespective of isolate. However, in a study by Gilchrist et al. (2000) eight isolates
of F. graminearum inoculated across four resistant and one susceptible cultivar
showed significant differences between isolates in addition to cultivar x isolate
interactions.

In many studies, resistance has been confirmed to be quantitative, and no
complete resistance to infection has been identified for FHB (Anderson et al.,
2001; Bai et al., 1999; Bai et al., 2000; Ban, 2000; Bourdoncle and Ohm, 2003;
Buerstmayr et al., 1999a; Ittu et al., 2000; Rudd et al., 2001; Shen et al., 2003b;

28

Snijders, 1990; Steiner et al., 2004; Waldron et al., 1999). Many Quantitative
Trait Loci (QTL) for FHB resistance have been identified from different genetic
sources. Qflls.ndsu-3BS on chromosome arm 388 is the most widely studied
and verified F HB resistance OTL in wheat, and explains as much as 60% of the
FHB phenotypic variation in mapping populations (Anderson et al., 2001;
Buerstmayr et al., 2002; Buerstmayr et al., 2003; Chen et al., 2003; Del Blanco et
al., 2003; Zhou et al., 2003; Zhou et al., 2002a). The resistant allele of
Qfl'ls.ndsu-388 is from the genotype Sumai 3 (Anderson et al., 2001; Bai and
Shaner, 1994; Waldron et al., 1999). Among a diverse group of 66 cultivars from
several countries with different levels of resistance, AF LP and SSR analyses
revealed that the Sumai 3 haplotype in the Qflrs.ndsu-3BS region was present in
almost all the Sumai 3 derived lines, as well as a few other genotypes (Bai et al.,
2003). However, most other sources of resistance showed non-Sumai 3
haplotypes at the Qflts.ndsu-3BS region (Bai et al., 2003). In another study of
haplotype diversity of a collection of 79 genotypes from around the world (most of
which exhibit resistance or moderate resistance), the Sumai 3 haplotype at in the
Qflls.ndsu-388 region occurred in seven lines, one of which is known to be a
Sumai 3 - derived line (McCartney et al., 2004). These studies suggest that
resistance like that of Sumai 3 at Qflis.ndsu-3BS may exist in many other
genotypes, but there is also a large amount of diversity in the Qflrs.ndsu-3BS
region.

Other QTL with smaller effects for F HB resistance have been identified

through mapping studies on sixteen chromosomes of wheat: 2A (Gervais et al.,

29

2003; Paillard et al., 2004; Steiner et al., 2004; Waldron et al., 1999; Zhou et al.,
2002b), 3A (Anderson et al., 2001; Gervais et al., 2003; Paillard et al., 2004;
Shen et al., 2003b; Steiner et al., 2004), 4A (Paillard et al., 2004), 5A
(Buerstmayr et al., 2002; Buerstmayr et al., 2003; Gervais et al., 2003; Paillard et
al., 2004; Shen et al., 2003b; Somers et al., 2003; Steiner et al., 2004), 6A
(Anderson et al., 2001), 18 (Buerstmayr et al., 2002; Ittu et al., 2000; Shen et al.,
2003b; Steiner et al., 2004), 2B (Gervais et al., 2003; Steiner et al., 2004; Zhou
et al., 2002b), 3B (Gervais et al., 2003; Paillard et al., 2004; Shen et al., 2003a;
Somers et al., 2003), 4B (Somers et al., 2003; Steiner et al., 2004), 58 (Paillard
et al., 2004), 6B (Anderson et al., 2001; Shen et al., 2003a; Steiner et al., 2004),
1D (Ittu et al, 2000), ZD (Shen et al., 2003a; Somers et al., 2003), 3D (Paillard et
al., 2004; Shen et al., 2003b), 5D (Gervais et al., 2003) and 6D (Gervais et al.,
2003; Paillard et al., 2004). Chromosome substitution lines and monosomic
analyses have also implicated chromosomes with potential QTL influencing FHB
resistance, identifying chromosomes 2A, 3A, 4A, 5A, 7A, 18, 28, 38, 48, 58, 68,
78, 2D, 4D, 5D, 6D and 7D in FHB resistance (Buerstmayr et al., 1999b; Liao
and Yu, 1985 - see Bai and Shaner,1994;Yu et al., 1986 - see Buerstmayr et
al., 1999b; Yu, 1982; Yu, 1991 - see Bai and Shaner, 1994 and Buerstmayr et
al., 1999b; Zhou et al., 2002a).

30

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45

CHAPTER 2
BIOASSAY VS. CONVENTIONAL CHARACTERIZATION OF FUSARIUM
HEAD BLIGHT RESISTANCE IN NING 7840.

2.1 Abstract

Fusarium head blight (FHB), caused by Fusarium spp. is a devastating
disease of wheat and barley. Type II resistance (resistance to spread) to FHB is
the form of resistance most commonly assessed by wheat breeding programs.
Type II resistance is usually rated by observing visually diseased (scabby)
spikelets on a spike. However, visually scabby spikelets may not be an accurate
reflection of the spread of disease overall. Two wheat genotypes, ‘Ning 7840’
(resistant) and ‘Norm’ (susceptible), were evaluated at seven and fourteen days
post inoculation (dpi) for the number of 1) visually scabby spikelets (SS), 2)
visually infected rachis sections (VIRS) and 3) infected rachis sections according
to a bioassay (BIRS). The number of visually scabby spikelets was significantly
fewer than the number of infected rachis sections (either visual or bioassay) for
both genotypes at both 7 and 14 dpi. Ning 7840 had significantly lower mean
values than Norm for each measurement (SS, VIRS and BIRS) at both 7 and 14
dpi. Measurements (SS, VIRS or BIRS) above (apical) the point of inoculation
were lower than the respective measurements below (basal) the point of
inoculation for both genotypes at both 7 and 14 dpi, though this difference was
not always significant. In addition, Ning 7840 was significantly lower than Norm

for each corresponding measurement (SS, VIRS and BIRS) up from (towards the

46

terminal spikelet) and down from (toward the peduncle) the inoculated spikelet at
both 7 and 14 dpi except for SS spread down from the inoculated spikelet at 7
dpi, for which the difference was not significant. BIRS data of Ning 7840
revealed a bimodal trend in the spread of the Fusarium graminearum, suggesting
that the point of greatest resistance to spread in Ning 7840 may be the rachis
node.

2.2 Introduction

Fusarium head blight (F HB) caused by Fusarium spp. is a devastating
disease of wheat (Triticum aestivum and T. durum) and baney (Hordeum
vulgare) resulting in yield loss, reduced grain quality, and reduced test weight
(McMuIIen et al., 1997). More important is the contamination of the grain with
mycotoxins that are a serious health threat to humans and animals (Snijders,
1990). FHB is caused by several Fusarium species including F. graminearum
and F. culmorum (Parry et al., 1995). In North America FHB of wheat is caused
predominantly by F. graminearum (Schwabe) (perfect stage Gibberella zeae
Schw. and Patch) (Parry et al., 1995). Recently, FHB epidemics have
dramatically impacted the wheat and barley industries in the United States and in
have resulted in losses of nearly three billion US dollars to farmers since the
1990’s (Windels, 2000). In 1993, Minnesota, North Dakota, South Dakota and
Manitoba (Canada) combined suffered approximately $1 billion in losses in the
wheat and barley industries (McMuIIen et al., 1997). From 1998 through 2000,

US economic losses due to F HB in soft red winter wheat and hard red spring

47

wheat alone were estimated at $333 million and $330 million, respectively
(Nganje et al., 2001).

FHB is caused by the infection of wheat spikes by Fusarium ascospores
or conidia (Markell and Francl, 2001; Stack, 1989). Initial Fusarium infection on
wheat spikes occurs primarily at anthesis (Andersen, 1948; Pugh et al., 1933;
Strange and Smith, 1971) and is influenced by temperature and moisture
(Snijders, 1990). Many studies have been concluded on either F. graminearum
or F. culmorum, and histological investigation reveals that the two species are
similar for their infection and colonization processes of wheat spikes (Wanjiru et
al., 2002). Several routes of initial penetration by Fusarium spp. of the host floret
tissue have been observed including colonization of extruded anther, direct
penetration of the interior surfaces of the lemma, palea and ovary and stigma,
and penetration through stomates (Andersen, 1948; Bushnell et al., 2003; Kang
and Buchenauer, 2000a; Kang and Buchenauer, 2000c; Kang and Buchenauer,
2002b; Lewandowski and Bushnell, 2001; Pritsch et al., 2000; Ribichich et al.,
2000; Strange and Smith, 1971; Tu, 1950). After initial infection, some studies
have found that the fungus grows primarily basipetally in the rachis from the point
of inoculation (Savard et al., 2000; TeKrony et al., 2000). Other studies have
seen a large amount of movement both acropetally and basipetally in susceptible
cultivars (Kang and Buchenauer, 2000a; Schroeder and Christensen, 1963),
while in highly resistant cultivars the fungal colonization may be restricted to the
inoculated spikelet (Wang et al., 1982). Colonization of the rachis has been

suggested to cause bleaching (loss of pigment) and shriveled kernels in

48

uncolonized, upper portions of the spike or in adjoining spikelets (Bai and
Shaner, 1996; Kang and Buchenauer, 1999; Pugh et al., 1933; Savard et al.,
2000). In addition, some studies have shown that infection in the rachis is more
wide-spread than that in the floral organs (Edge et al., 2001; TeKrony et al.,
2000; TeKrony et al., 2001).

Breeding for disease resistance is considered to be the best method to
combat FHB (Ruckenbauer et al., 2001; Schroeder and Christensen, 1963).
Several types of resistance have been described for FHB (Mesterhazy, 1995;
Schroeder and Christensen, 1963; Wang and Miller, 1988). Type I resistance,
(resistance to initial infection) and Type II resistance (resistance to spread of
infection from a point of initial infection), as described by Schroeder and
Christensen, 1963, are the most widely accepted and researched types of
resistance. Other types of resistance have also been described: resistance to
kernel infection, tolerance to infection, and resistance to mycotoxin accumulation
(Mesterhazy, 1995). In addition, avoidance of infection via plant height or
flowering in the boot is considered a form of passive resistance (Mesterhazy,
1995). No complete resistance to the disease has been found, but several
sources of partial resistance are known. At this time, the genes conferring F HB
resistance in the Chinese cultivar ‘Sumai 3’ and its derivatives are used more
than any other source (Kolb et al., 2001; Rudd et al., 2001). Sumai 3 has strong
Type II resistance (resistance to spread), as well as some Type I resistance
(resistance to initial infection) (Ben and Suenaga, 2000; Rudd et al., 2001;

Wilcoxson et al., 1992). Inheritance of this resistance is quantitative and emibits

49

low heritability. A QTL explaining 25-60% of the variation for Type II FHB
resistance in Sumai 3 is present on Chromosome arm 388, (Anderson et at,”
2001; Bai et al., 1999; Waldron et al., 1999). That same QTL is present in ‘Ning
7840’, a Sumai 3 derivative (Bai et al., 2003; Bai et al., 1999; Sourdille et al.,
2000; Ziou et al., 2002).

The level of Type II resistance is usually determined by visual assessment
of the number of diseased ('scabbY') spikelets after inoculation of a single
spikelet under greenhouse or field conditions (Schroeder and Christensen,
1963). Visual symptoms of FHB appear as water soaked lesions, reddish
discoloration, chlorosis, necrosis and bleaching (complete loss of pigment) of
spikelet and rachis components (Andersen, 1948; Kang and Buchenauer, 2000a;
Pugh et al., 1933; Savard et al., 2000; Snijders and Krechting, 1992). Although
the number or proportion of scabby spikelets is a convenient method for scoring
genotypes for resistance, bioassay and histological studies of the infection
process show that visual ratings of disease may not be indicative of the presence
or absence of the fungus (Edge et al., 2001; Pugh et al., 1933; Schroeder and
Christensen, 1963; TeKrony et al., 2000; TeKrony et al., 2001).

Rachis measurements have also been used in a few breeding programs
when observing Type II resistance. Wang et al. (1982) used a four-grade level
rating system in which the highest level of resistance showed no visual
symptoms of disease, while the second highest level showed symptoms in the

rachis but no symptoms in other adjoining spikelets. Jiang et al. (2001) reported

50

a similar scoring system using visual symptoms in the rachis, in addition to
spread to adjoining florets from the initially inoculated floret.

Despite the wide-spread focus by plant breeders on Type II resistance,
little is known of the actual mechanism by which the rate of disease development
is retarded. This study was conducted to shed light on the mechanism of one
source of Type II resistance through a comparative analysis of the progression of

FHB in Ning 7840, a resistant cultivar, and Norm, a susceptible cultivar.

2.3 Materials and Methods
2.3.1 Plant Materials

Seeds of the cultivars Ning 7840 and Norm were hydrated at room
temperature in the dark for 24 hours in petri dishes containing Steel Blue Seed
Germination Blotter Paper (Anchor Paper, St Paul, MN) saturated with deionized
water. Petri dishes were then transferred to an unlighted cold room maintained
at ~2°C for 5 weeks. Deionized water was added to petri dishes as necessary.
After vemalization, petri dishes were kept at room temperature in the dark for 48
hours before transplanting.

Seeds were then transplanted into 4—inch plastic pots at a density of four
plants per pot (one genotype per pot). Pots were placed on greenhouse benches
in a manner that reduced the effects of environmental gradients within the

greenhouse. This included alternating rows according to genotype.

2.3.2 Inoculum Production

51

F. graminearum (Schwabe) isolate PH-1 (NRRL 31084) was isolated by
Dr. L. Patrick Hart, East Lansing, MI, from a Michigan wheat field during a FHB
epidemic in 1996. Inoculum was produced in Carboxymethyl Cellulose (CMC)
liquid medium (Cappellini and Peterson, 1965) as follows. The CMC liquid
medium was divided into 250 ml flasks each containing approximately 100ml of

CMC liquid, then autoclaved. Soil stock of PH-1, or a small block (~o.5em3) of

potato dextrose agar colonized by PH-1, was then added to a flask of CMC liquid
medium that was cool or at room temperature. The flask was shaken at 180-250 1
rpm at roOm temperature for 3 days to induce the production of macroconidia.
The macroconidia suspension was centrifuged to produce a pellet, from which

the CMC liquid medium was decanted and sterile water was added.

Macroconidia concentration was adjusted to 1.4 x 106 spores/ml.

2.3.3 Inoculation of Plants

Forty-four plants of each genotype with main stem spikes in growth stage
Feekes 10.5 (i.e., immediately prior to anthesis with anthers slightly yellow to
very yellow) were identified for use in the experiment. Only main stem spikes
were used, and preference was given to pots having more than one plant at
Feekes 10.5 to minimize space usage. Four plants of each genotype were
randomly selected as controls and were not inoculated. The remaining forty
spikes of each genotype were inoculated by pipetting 7ul of spore suspension

(equivalent to 10,000 macroconidia) into one of the two most basal florets of a

52

central spikelet. The inoculated spikelet was marked with black permanent black

ink for later identification.

2.3.4 Post-Inoculation Growth Conditions

Immediately after inoculation, pots were randomly positioned in a growth
chamber set to maintain a constant temperature of approximately 22°C. Plants
were subjected to overhead misting for 5 seconds every 5 minutes for 72 hours

after inoculation.

2.3.5 Evaluation of Fusarium Head Blight on Spikes

Seven and 14 days post inoculation (dpi), 20 inoculated and two control
spikes of each genotype were randomly chosen for harvest and processing for
disease evaluation. Each spike was sequentially evaluated for three measures
of disease as described below and illustrated in Fig. 2-1.

1. Number of Scabby Spikelets (SS): A spikelet was considered
scabby if there was visibly damaged tissue on any of its glumes,
lemmas or paleas. Counts of total SS were recorded for each
spike. Recorded data included the number of SS above, below,
and at the inoculated spikelet (Fig. 2-1 A)

2. Visual Infected Rachis Sections (V IRS): After the SS data was

collected, spikelets were removed from the spike (by twisting
spikelets off the rachis by hand) and each section of the rachis (as

53

defined below) was classified as symptomatic or asymptomatic of
disease. The composition of a rachis section depended on its
position relative to the inoculated spikelet The node to which the
inoculated spikelet was attached was designated the ‘inoculated
node’, and was treated as a distinct rachis section. Rachis
sections above the inoculated node included a single node and the
subtending intemode. Rachis sections below the inoculated node
were classic phytomers and included a single node and the
internode above it. Recorded data included the number of VIRS
above, below, and at the inoculated node rachis section. (Fig. 2-1 B)

Bioassay Infected Rachis Sections (BIRS): After VIRS data was
collected, the rachis of each spike was surface sterilized by soaking
in 20% bleach + 0.1% Tween 20 for 2 minutes followed by a rinse
with sterile water. The rachis was then cut into sections (as defined
in VIRS) using a sterile scalpel that was sterilized between each
cut. Rachis sections from a single spike were plated sequentially in
a circular pattern on a large petri dish (150 x 15mm) containing
potato dextrose agar (PDA). Petri dishes were placed (PDA side
down) on shelves under constant illumination (lamps placed
approximately 1 to 1 ‘A feet above cultures) at room temperature (~
68-72°F). Petri dishes were checked regularly for growth of F.

graminearum for many days following plating until it was clear

54

which rachis sections were and were not infected. Rachis sections
were Classified as infected or not infected on the basis of the
presence or absence of the growth of F. graminearum from each
section. Recorded data included the number of BIRS above, below,
and at the inoculated node rachis section. (Fig. 2-1 C)

2.3.6 Experimental Design

The experiment was replicated three times over a period of several
months. A group of forty inoculated and four control plants (both resistant and
susceptible) was considered a replication of the experiment. A random number
generator was used to determine pot placement in the growth chamber after

inoculation and to determine which spikes to harvest at 7 and 14 dpi.

2.3.7 Missing Data

Twenty-eight of the 240 inoculated spikes were discarded because of
escape, injury, missing data, suspected second infection points other than the
originally inoculated spikelet, or symptoms inconsistent with FHB. Surface
sterilization of spikes was ineffective in replication one at 7 and 14 dpi, and
replication two at 7 dpi. The resulting contamination pmcluded BIRS data

acquisition and those data were accordingly excluded from the analysis.

2.3.8 Data Analysis

55

The raw count data were transformed using a square root + 1
transformation. All analyses were performed with SAS® Version 8.2 (SAS
Institute 2000). Least square means of SS, VIRS and BIRS were calculated with
the Proc Mixed LSMeans procedure. Back trensfonnation was used to report the
estimated means. The trensfonned data was tested for normality using Proc
Univariate. Analysis of Variance was performed using Proc Mixed “repeated”
command since multiple response variables were determined on a single
experimental unit (i.e. SS, VIRS and BIRS data from a single spike). Pairwise
comparisons of means were determined using Proc Mixed LSMeans 'pdiff'

command.

2.4 Results
2.4. 1 SAS analysis
Plots of the residuals showed a near-nonnal distribution.
2.4.2 Comparisons among Measures of Disease Development within a
Genotype
The number of Scabby Spikelets (SS) was significame fewer (P < 0.05) than the
number of infected rachis sections (determined either visually, VIRS, or with
bioassay, BIRS) for both genotypes at 7 and 14 days post inoculation (dpi) (Fig.
2-2A). In contrast, there was no significant difference between VIRS and BIRS
for either genotype at either 7 or 14 dpi.
For a large proportion of Ning 7840 spikes, spread of the fungus and

symptoms was limited to the inoculated spikelet and associated node at both 7

56

and 14 dpi (Fig. 2-3). On the other hand, the BIRS values at 14 dpi for Ning
7840 showed a striking bimodal distribution (Fig. 2-38) Forty-four percent of the
Ning 7840 BIRS values were between 0 and 2 (referenced below as “mode 1"),
while the remainder were between 9 and 14 (referenced below as “mode 2”). To
investigate this further, each Ning 7840 spike was classified on the basis of the
aforementioned modes. Re-analysls of the Ning 7840 data for 14 dpi with
'mode” as a classification factor showed that the SS, VIRS and BIRS means for
mode 1 spikes were all significantly smaller than the respective measurements
for the mode 2 spikes (data not shown). WIthin mode 1 none of the
measurements (SS, VIRS and BIRS) were significame different from each other
(P > 0.14). However, within mode 2 88 was significantly less than VIRS and
BIRS (P < 0.0001), while VIRS was not significantly different from BIRS (P =
0.15).

The number of VIRS and BIRS was significantly greater at 14 dpi than at 7
dpi for both genotypes. The number of S8 for Norm was also significantly larger
at 14 dpi than at 7 dpi. In contrast, the numbers of SS at 7 and 14 dpi for Ning
7840 were not significantly different (see Fig. 2-2A and 2-2B).

The numbers of SS, VIRS and BIRS above the inoculated spikelet were
smaller than corresponding values for spikelets or rachis sections below the
inoculated node, though the differences were not always significant (Fig. 2-2C).
Overall, the number of SS, VIRS and BIRS above the inoculated node

represented 30-49% of the total spread from the inoculated node.

57

When comparing SS, VIRS and BIRS, SS up was significantly less than
VIRS or BIRS up (P < 0.01) in all cases except for Ning 7840 BIRS at 7 dpi (for
which the difference was not significant). Similarly, SS down was significame
less (P < 0.01) than VIRS or BIRS down for both genotypes at both 7 and 14 dpi.
In contrast, VIRS up was never significantly different from BIRS up, and VIRS
down was never significantly different from BIRS down (in all cases, P > 0.4

except Norm VIRS and BIRS up at 14 dpi, forwhich P > 0.05)

2.4.3 88, VIRS and BlRS between Genotypes

The mean SS, VIRS and BIRS of Ning 7840 were significantly lower than
the corresponding means for Norm at both 7 and 14 dpi (P < 0.05) (Fig. 2-28).
However, as reported above, BIRS revealed a bimodal trend for Ning 7840 at 14
dpi in which 44% of spikes have BIRS values between 0 and 2 (mode 1), while
56% of spikes have BIRS values between 9 and 14 (mode 2) (Fig. 2-3). When
analyzed separately, Ning 7840 mode 1 SS, VIRS and BIRS were all significantly
less than the respective measurements for Norm (P < 0.0001 ). In contrast, for
Ning 7840 mode 2, although SS was significantly less than Norm (P < 0.0001),
VIRS and BIRS were not significantly different than the respective measurements
for Norm (P > 0.24).

In all cases except one, the mean number of SS, VIRS and BIRS above
and below the inoculated node was significantly lower (p<0.05) for Ning 7840
than Norm at both 7 and 14 dpi (Fig. 2-2D). The one exception was for SS below

58

 

the inoculated node at 7 dpi, where Ning 7840 had a lower mean, but the

difference with Norm was only significant at p = 0.07.

2.4.4 Bleached versus Not Bleached Tissue

Bleached tissue was considered to be tissues that had a loss of
pigmentation, without an expectation of the accompanying presence of the
fungus in those specific tissues. Bleached tissues were not clearly observed in
Ning 7840 and were only observed in Norm above the node inoculated. Data
including and excluding bleached tissues were compared for differences in
results. The two data sets, one excluding bleached tissue and one including
bleached, showed the same trends (p < 0.05) for the analyses of SS, VIRS and
BIRS within the genotypes, as well as 88, VIRS and BIRS between the
genotypes. Since it is expected that most research programs do not distinguish
between bleached and colonized tissues, the results reported here include

bleached tissues.

2.4.5 Limitations of SS, VIRS and BIRS

The ability to measure spread using SS, VIRS and BIRS was limited by
the morphology of the wheat spike. The spread of SS, VIRS and BIRS can not
be measured beyond the spike itself. The average node inoculated was the
eighth node from the bottom of the spike for Ning 7840 and Norm. The average
number of spikelets on a spike was 17 in Ning 7840 and 15 in Norm. Therefore,
on average, the ability to measure the spread of SS, VIRS or BIRS was limited to

59

seven sections below the node inoculated, the node inoculated itself, and nine
(for Ning 7840) and seven (for Norm) sections above the node inoculated. The
data for each spike was inspected to determine the number of spikes in which
SS, VIRS or BIRS spread to the top or bottom of a spike, and therefore to the
extent of the measuring abilities. Table 2-1 shows the number and percentage of
observations of Ning 7840 and Norm spikes at 7 and 14 dpi with S8, VIRS and
BIRS values that reached the extremes of the spike (at tip or peduncle) by 7 or
14 dpi. Care should be taken in interpreting the data because not all spikes
represented in SS and VIRS are also represented in BIRS (BIRS at 7 dpi is only
representative of replication 3, while BIRS at 14 dpi includes replications 2 and
3). Overall, many spikes showed symptoms spreading to the top or bottom of the
spike, and more spikes showed symptoms spreading to the bottom than to the
top. No spikes had BIRS values extending to the top of the spike (in either
genotype at either 7 or 14 dpi), though some spikes had SS or VIRS data to the
top of the spike - revealing that visible symptoms at the top of the spike did not

always indicate of the presence of the fungus at that position.

2.5 Discussion
2.5.1 88, VIRS and BIRS within a Genotype

The results for SS, VIRS and BIRS Clearly demonstrate that in both
genotypes the fungus had spread internally through the rachis further than was
evident by visual symptoms in the spikelets. These data are consistent with

other studies that have shown that the spread of the fungus within the rachis is

more extensive than the spread of the fungus among the spikelets (Edge et al.,
2001; Pugh et al., 1933; TeKrony et al., 2000). Histological studies by Pugh et
al. (1933) showed that the fungus would advance from the point of infection
through the rachis, but would not always infect adjoining spikelets, and that the
visual symptoms of infection were not always indicative of the presence of the
fungus. Similarly, TeKrony et al. (2001) showed that fungal infection in the rachis
was more widespread than in the floral organs overall. However, in TeKrony et
al.’s study (2001) the bioassay results were poorly related to the visual estimation
of disease in the spikelets. In this experiment, BIRS was not significantly
different from VIRS for either genotype, revealing that visual estimations of the
disease in the rachis were reliable indicators of the presence of the fungus in the
rachis for Ning 7840 and Norm at 7 and 14 dpi. In addition, as a general rule the
development of scabby spikelets progressed sequentially from the point of
inoculation outward (is. an asymptomatic spikelet between two scabby spikelets
was almost never observed - data not shown).

These results showed a lower rate of spread up (towards the terminal
spikelet) as opposed to down (towards the peduncle) from the inoculated spikelet
in both Ning 7840 and Norm, which is in agreement with other studies (Savard et
al., 2000; TeKrony et al., 2000). However although the spread upward was less
than down, the data presented in this study still showed a substantial amount of
spread up from the inoculated spikelet, as is consistent with other studies (Kang
and Buchenauer, 2000a; Schroeder and Christensen, 1963). Furthermore, the

61

bioassay provided solid evidence that in this study, symptoms in the rachis above
the node inoculated were accompanied by the presence of the fungus.

From my knowledge, this is the first study to report a bimodal trend in the
disease symptoms of a resistant genotype, as observed for BIRS data of Ning
7840 at 14 dpi. In addition, the greater spread of symptoms in the rachis versus
the spikelets in both Ning 7840 and Norm, and the constancy of Ning 7840's SS
compared with an increase in Ning 7840's VIRS and BIRS between 7 and 14 dpi
suggests that different mechanisms may be responsible for these two
measurements, as has been proposed by Yu, 1990 (as referenced by Bai and
Shaner, 1996).

Many studies have investigated the biochemical differences between
inoculated and un-inoculated spikes, and between FHB resistant and susceptible
genotype (Kang and Buchenauer, 2000a; Kang and Buchenauer, 2000b; Kang
and Buchenauer, 2002a; Kang and Buchenauer, 2002b; Kang and Buchenauer,
2003; Mohammadi and Kazemi, 2002; Pritsch et al., 2000; Pritsch et al., 2001;
Savard et al., 2000; Siranidou et al., 2002). Conelations are reported between
degree of host plant resistance and the accumulation of several defense related
substances such as thionins, polyphenol oxidases, hydroxyproline-rich
glycoproteins, 8-1 ,3 glucanase, chitinase and thaumatin-like proteins (Kang and
Buchenauer, 2002a; Kang and Buchenauer, 2003; Mohammadi and Kazemi,
2002; Pritsch et al., 2000). In addition, structural differences have been
observed between inoculated and un-inoculated spikes, and between FHB

resistant and susceptible genotypes. Histopathological examinations of Sumai 3

62

 

(from which Ning 7840 was derived) shows occlusions forming in some xylem
vessels after infection, which were eventually overcome by the fungus, and
deposition of an amorphous substance in the phloem (Ribichich et al., 2000).
Similarly, Kang and Buchenauer (20000) observed the formation of wall
appositions and large papillae after infection, which were more pronounced in the
resistant than the susceptible cultivar, and an increase in lignin content in the
host cell walls, which was observed in the infected lemma and infected xylem
cells. Kang and Buchenauer (2000c) suggest that these physical barriers may
restrict the fungus as well as the movement of the trichothecene mycotoxins
(including DON and 3-ADON). Other studies show that Fusarium produced
trichothecene mycotoxins are translocated to uncolonized tissues through
phloem sieve tubes and xylem vessels (Kang and Buchenauer, 1999; Kang and
Buchenauer, 2002b). Fusarium mycotoxins are thought to be important in the
virulence and spread of the disease (Bai et al., 2002; Desjardins et al., 1996;
Eudes et al., 1997; Mesterhazy, 2002; Mirocha et al., 1997; Proctor et al., 2002).
Resistant genotypes of wheat, including Sumai 3, exhibit a lower accumulation of
DON (Kang and Buchenauer, 2000c; Mesterhazy, 2002), and a study of tissue
callus formation on DON containing media suggests that Sumai 3 may possess
some tolerance to DON (Yang et al., 1998).

Kang and Buchenauer (2000a) present a diagram of the intersection of the
spikelet and the rachis, showing what they call a vascular tissue “plexus” in the
rachis node, which consists of a cluster of vascular bundles in the rachis node

joining the rachis and the spikelet tissues. Although researchers have found

63

differing results with respect to the extent of fungal growth in the host’s vascular
tissues (Kang and Buchenauer, 2000a; Pugh et al., 1933; Ribichich et al., 2000;
Tu, 1950), the high concentration of vascular bundles in the plexus in
combination with an increased lignification of xylem cells (Kang and Buchenauer,
2000c) transient physical barriers (Ribichich et al., 2000) and other biochemical
defense responses together may contribute to the hindered spread of the fungus
into the rachis from the infected spikelet, as well as out of the rachis to adjoining
spikelets. These types of obstacles to spread, when present at the rachis node
may provide some explanation for the bimodal results in Ning 7840 in which the
fungus didn’t spread beyond the initially inoculated node in several spikes, while
in others it moved extensively in the rachis but did not invade many of the
adjoining spikelets.

A surpn’sing outcome of this study is that the fungus is equally able to
colonize the Ning 7840 and Norm rachis tissues in roughly half of the spikes.
Barriers in the rachis node, along with the other general biochemical defense
responses and a greater resistancei‘tolerance to DON may be sufficient to restrict
the fungus near the inoculated spikelet for about half of the Ning 7840 spikes.
However, for the other half of the Ning 7840 spikes the fungus was able to
spread past barriers in the rachis node earty in disease and spread successfully
in the rachis, but barriers at the rachis node prevented colonization of additional
adjoining spikelets. The idea that the rachis node may present a greater benier
for the fungus than other spike tissue could also explain the tendency for the

scabby spikelets symptoms to be less extensive than scabby rachis symptoms in

64

 

both resistant and susceptible genotypes, as was observed also in this and other
studies (Pugh et al., 1933; TeKrony et al., 2001). In susceptible genotypes, the
rachis node may not provide as great a barrier as in resistant genotypes such as

Ning 7840, resulting in a greater number of scabby spikelets.

2.5.2 SS, VIRS and BIRS between Genotypes

The comparison of the three measurements (SS, VIRS and BIRS)
between the Ning 7840 and Norm revealed that the total ss, VIRS and BIRS
were all effective at distinguishing between the two genotypes (p < 0.05) at 7 and
‘ 14 dpi. Similarly, the spread up or down for SS, VIRS and BIRS also
distinguished between the two genotypes, except for SS down at 7 dpi.
However, although the total Ning 7840 data showed significant differences
between Ning 7840 and Norm for all three measurements (SS, VIRS and BIRS),
the bimodal trend in Ning 7840's BIRS data at 14 dpi gave surprising results
when the two modes were analyzed separately. Separate analysis of the upper
and lower modes revealed that approximately half of the time the spread in the
rachis of Ning 7840 was no different from Norm, though this similarity was not
reflected in the number of scabby spikelets. Therefore, the earlier results of this
study, showing that SS, VIRS and BIRS were all effective in distinguishing
between the two genotypes, should be qualified by considering that this was due
to the average of the upper and lower modes of Ning 7840 at 14 dpi, and not
because symptoms in the rachis of Ning 7840 were always less than those of

Norm.

65

2.5.3 Bleached versus Not Bleached Tissue

Many researchers have observed bleached tissues (tissues with a loss of
pigment, appearing whitened as if drying out/wilting) above the point of
inoculation and have attributed this to colonization in the lower parts of the spike,
resulting in a lack of water and/or nutrients to the upper portion of the spike,
rather than to the presence of the fungus at the bleached portion itself (Bai and
Shaner, 1996; Kang and Buchenauer, 1999; Pugh et al., 1933; Savard et al.,
2000). Visual estimation of the presence of the fungus in a tissue, versus
bleaching in a tissue is hidily subjective. In this study, bleached tissues
suspected of being free from pathogen colonization, and tissues having disease
symptoms suggesting of the presence of the fungus (i.e. darker brownish/reddish
pigmentation accompanied by chlorosis and necrosis) were distinguish from each
other in the visual scoring of SS and VIRS. The purpose in distinguishing
bleached and not-bleached tissues was to determine if the values for SS and
VIRS would be significantly different when bleached tissues were included or
excluded from the data sets. In this studies, bleaching was only cleariy observed
in the susceptible genotype, Norm, and was not widespread. Data including
bleached tissues showed the same trends as data excluding bleached. Although
the data sets with and without bleached sections were not effectually different, it
is expected that more bleaching may have been observed if the plants were
harvested at later days post inoculation. In this study statistics from the data set

including bleached tissues are reported because it is expected that few

66

 

laboratories distinguish between bleached and not bleached tissues (since it is
laborious to make this distinction).

A possible explanation for the presence of bleaching in Norm and the
apparent absence of it in Ning 7840 is the interaction of each genotype with
mycotoxins produced by the fungus. A study by Seeland and Bushnell (2001)
indicated that application of DON on detached barley could alter leaf
pigmentation dramatically and could result in bleaching depending on the
concentration of DON applied and the presence or absence of light. Other
studies have shown that the mycotoxins produced by Fusarium can be
translocated in the wheat head from the area colonized by the fungus to
uninfected tissues (Kang and Buchenauer, 1999; Savard et al., 2000; Snijders
and Krechting, 1992). It has also been suggested that bleaching above infected
spikelets may be caused by toxin and/or fungal accumulation blocking movement
of water and nutrients (Bai and Shaner, 1996; Kang and Buchenauer, 1999;
Pugh et al., 1933). Considering resistant and susceptible genotypes, in a study
of F. culmorum infection of wheat, DON accumulation was significantly greater in
the susceptible cultivar examined than in the two resistant cultivars, though the
toxin was present in the same cellular structures in both resistant and susceptible
types (Kang and Buchenauer, 20000). Furthermore, resistant lines, including
Sumai 3, were found to have lower accumulation of DON and other Fusarium
produced toxins relative to more susceptible genotypes (Bai et al., 1998; Mirocha
et al., 1994). A study of tissue callus formation on DON containing media

suggests that Sumai 3 cells may possess some tolerance to DON (Yang et al.,

67

1998), and greater DON degradation appeared to be present in a resistant
genotype, ‘Frontana’, in comparison with a susceptible genotype, ‘Casavant’
(Miller and Arnison, 1986). Overall, the presence of bleaching in Norm may be
due to an accumulation of toxin, resulting in the blockage of the movement of
water and nutrients to apical portions of the spike and/or the presence of the
toxin itself in those tissues may be contributing to the bleaching. The absence of
bleaching in Ning 7840, on the other hand, may be due not only to a lower
accumulatiOn of this toxin and a restriction of the spread of mycotoxins (as

discussed above), but perhaps to a higher tolerance to the toxin itself.

2.5.4 Limitations of Scoring Methods .

There are some limitations to the phenotypic disease scoring methods
used in this study. The spread of SS, VIRS or BIRS to the extremes of many
spikes (either to the terminal spikelet or the peduncle) of Ning 7840 and Norm
results in an underestimation of SS, VIRS and BIRS at both 7 and 14 dpi. In
addition, the presence of spikes with $8 or VIRS values to the terminal spikelet,
in contrast to the lack of spikes with BIRS values up to the terr'ninal spikelet,
indicates that visual symptoms did not always correspond exactly with the
presence of the pathogen. However, VIRS and BIRS were not significantly
differeth overall, indicating that overall visual symptoms in the rachis reflected the
presence of the fungus for Ning 7840 and Norm at 7 and 14 dpi. In addition,
since VIRS and BIRS were significantly greater than the SS data, the inability to
track the spread of the fungus beyond the extremes of the spike is not expected

68

to affect the overall trend between SS, VIRS and BIRS because SS rarely
reached the terminal and basal spikelets (except for Norm at 14 dpi where it still
did not reach the ends of the spike the majority of the time).

Another limitation is that no differentiation was made between the two
bottommost florets on the inoculated spikelets during inoculations. Although the
two florets are not equidistant from the rachis node they were not distinguished
from one another since visual estimation of the positioning of the two florets was
not obvious from external examination. It is possible that the rate at which the
fungus reaches the rachis would be slightly different according to which fioret
was inoculated. In addition, for VIRS and BIRS, the rachis was sectioned
according to the position of the nodes. This method of scoring does not consider
if the intemode length is constant within a genotype, or whether the two
genotypes have a similar distance between nodes. However, since the grain is
of primary interest in the spike for production practices, the scoring system used
in this study may be more relevmt to the effect on the grain than would absolute
distance of spread in the head.

An additional limitation to the scoring methods of this study is that it is not
know if the visual symptoms of the spikelets (SS) correlate well with the presence
of the fungus or DON in the spikelets. TeKrony et al. (2000 and 2001) reported
that visual ratings of disease in the spikelets may not correlate well with the
presence of the fungus in those spikelets. In addition, studies have found that
the toxin can be translocated beyond areas of fungal colonization (Kang and

Buchenauer, 1999; Savard et al., 2000; Snijders and Krechting, 1992). However,

69

other studies have indicated that visual rafings of FHB are well correlated with
seed infection (Argyris et al., 2003) and/or DON contamination (Lemper et al.,
2000; Mesterhazy, 2002). This study showed good correlation between visual
symptoms and the presence of the fungus in the rachis, suggesting that visual
symptom in the spikelets in this study are likely well correlated with the presence
of the fungus.

2.5.5 Conclusions

The fungus spreads internally through the rachis more rapidly than is
exhibited by scabby spikelets, showing that there is a great amount of fungus in
the rachis that is not present in adjoining spikelets. The vast majority of the
spikelets were infected as a result of spread through the rachis, rather than
through contacting adjacent infected spikelets. As a general rule, the spread of
scabby spikelets was sequential from the point of initial infection, having very few
instances of spikelets being skipped in this progression of disease. A specific
mechanism appears to be responsible for preventing infection of non-inoculated
spikelets adjoining infected rachis sections. Further study needs to be conducted
to determine if this trend is reflected when fungal colonization and DON
contamination of spikelets (versus visual symptoms) is investigated, and what
mechanisms are responsible for preventing initial entry into the rachis, or later
entry into the spikelets from an infected rachis. In addition, additional studies
should be conducted to determine if similar results are obtained using different

isolates of F. graminearum and different species of Fusarium. This study

70

illustrates the need for researchers working with FHB to look for alternative

mechanisms of resistance.

2.6 Acknowledgements
I would like to acknowledge Dr. L. Patrick Hart, Michigan State University,

for providing laboratory space. Thank you also to Dr. Sasha Kravchenko,
Michigan State University, for statistical support. Thank you to Dr. Guo-Liang
Jiang, Michigan State University, and Dr. Jianrong Shi, Jiangsu Academy of
Agricultural Sciences, for their practical knowledge and support with respect to

 

FHB of wheat Special thanks to Dr. William R. Bushnell, USDA-ARS Adjunct
Professor Emeritus, The University of Minnesota, for his review of this study and

helpful suggestions.

71

Flg. 2-1. Diagram of three methods of disease evaluation. A) Scabby
Spikelets (SS). Spikelets examined for visual symptoms of infection.
Spikelet inoculated shown in black at anow. B) Visually Infected Rachis
Sections (VIRS). Rachis sections examined for visual symptoms of
infection. Borders of rachis sections indicated by horizontal lines. Node
inoculated indicated in black at arrow. C) Bioassay Infected Rachis Sections
(BIRS). Rachis sectioned according to horizontal lines and plated in a
circular pattern on petri dish containing PDA. Sections fiom which Fusarium
gramineanim grown are considemd infected. Tissues having no visual
symptoms of disease are white, while those having visual symptoms of

disease are either checked or black.

72

 

 

 

 

— = mm" 0'

 

 

 

 

 

 

 

 

 

 

 

Rachis Section
SS VIRS
S 5 Scabby 10 Visually
mt...“ 3...... W“
(Black) (Check Node Rachis
and Inoculated Sections
Black) (Black) (Check
and Black)
A B
C
Fig. 2-1l

73

 

Flg. 2-2. Effect of Genotype, tlme of assay, and method of assay on the
number of Infected spikelets or rachis sectlons In a reslstant (Nlng
7840) and susceptlble (Norm) wheat cultivar. A. Comparisons between
the number of scabby spikelets (SS) and the number of infected rachis
sections determined either visually (VIRS) or by bioassay (BI RS) within
genotypes at 7 and 14 dpi. Asterisks above a column indicate a significant
difference between that column’s mean and the if of scabby spikelets for
that genotype/dpi combination. B. Comparisons between Ning 7840 and
Norm for three measures of disease spread at 7 and 14 dpi. Asterisks
above a column indicate a significant difference between Ning7840 and
Norm for that measurement/dpi combination. C. Comparisons between
upward and downward spread from the inoculated node for three measures
of disease spread in Ning 7840 and Norm. Asterisks above a column
indicate a significant difference between the upward and downward spread
for that measurement/genotypeldpi combination. The ‘0' on the Y axis
represents the inoculated node. Spread up from the inoculated node is
represented by numbers >0, and down from the node inoculated is
represented by numbers <0. D. Comparisons between Ning 7840 and Norm
for upward and downward spread from the inoculated node for thme
measures of disease. Asterisks indicate a significant difference between
Ning7840 and Norm for the upward (asterisks above upper bars), or
downward (asterisks below lower bars) spread for that measurement/dpi
combination. The ‘0' on the Y axis represents the inoculated node. Spread
up from the inoculated node is represented by numbers >0, and down from
the inoculated node is represented by numbers <0. *p< 0.05, ** p < 0.01,
*“p< 0.001. 1. SS = Number of Scabby Spikelets. 2. VIRS = Visually
Infected Rachis Sections. 3. Bl RS = Bioassay Infected Rachis Sections.

74

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  

 

 

 

    
 

 

 

 

  
  
 

 

 

la. .7.

 

 

 

75

i a
‘2l :2 3
ca an =Ning7840 _
.8 310. =Nonn
*-
.a £84 * * *
i-
; g6, : . "l
"a" a
m m
44 c... -It-
0 O 2
“ "‘ ‘ 1
mg ss VIRS BIRS ss VIRS BIRS
A 7dpi 7dpi 14de l4dpi B 7dpi 7dpi 7dpi 14dpi l4dpi 14dpi
SSup Ning7840up
6 8- it
a l SSdown ** a gurg7840down * *
g VIRSup «II-4.. ,3 ounup at. :
on 4- . m 4-
mgz- £32-
a l _:
£1 =1 : git.
3.5-2- % E 3844
D- E "_ “'5
2’35 — 33%
£34. 7de 7dpi 14dpi £34.
.6. Norm £6— 7dpi 7dpi 7dpi l4dpi : g.
14dpi it- it-
vms B
C D mm ”13%
Fig.2-2

Flg. 2-3. Relative frequency distributions of disease as determined by
three measures in Ning 7840 and Norm at 7 dpi (A) and 14 dpi (B). The Y
axis represents the percent of observed spikes with a given X axis
category. Note that scaling of the Y axis values varies with the measure
of disease, but is consistent between the two dpi. ‘>’ indicates values of
the X axis greater than 17. Black bands = Ning 7840, White bands =

Norm.

76

 

V' - u‘r- '_~ r

 

 

°/c

o8886885‘88

o 2 4 e 810121416 >
subbyspikeietsrss)

O/. x.

 

o-

O 2 4 6 810121416 >
Visually Infected Rachb Sectio- (VIRS)
x-

5-
20.

'/c15-

 

0 2 4 6 810121416>
Bioassay InfectcdkachisSecflons (BIRS)

A: 7dpi H3387”

 

%

'/c

B: l4dpi

 

0 2 4 6 810121416>
so, swastika-ism

 

0 2 4 6 810121416 >
VnnmflylnfecmdkachisSectioWlRS)
a)-

5-

z)-

 

0 2 4 6 810121416>
Bioassay Infected Rachis Sectio- (BIRS)

=Ni 7840
Bars.

 

Fig. 2.3.

 

 

Table 2-1: the number and percentage of observations of Ning 7840 and
Norm spikes at 7 and 14de with SS, VIRS and BIRS values that reached
the extremes of the spike (top = terminal spike, bottom = peduncle) by 7 or
14dpi. Obs. = Observations.

 

 

 

 

 

 

 

 

 

 

 

 

 

Meas- I % i 96 Total #
Genotypeldpl urement Top Top Bottom Bottom Obs.
Nin97840 7de SS 0 o 1 2 46
VIRS 0 O 3 7 46
BIRS 0 0 3 27 1 1
Norm 7dpi ss 0 o o 58
VIRS 1 2 4 58
BIRS 0 O 4 21 19
Ningm 14de SS 0 0 1 2 50
VIRS 6 12 20 40 50
BIRS o o 18 56 32
Norm 14de SS 15 26 17 30 57
VIRS 16 28 38 67 57
BIRS 0 0 27 71 38

 

 

 

78

2.7 References

Andersen A. L. (1948). The development of Gibberella zeae head blight of wheat.
Phytopathology 38: 595-611.

Anderson J. A, Stack R. W., Liu S., Waldron B. L., Fjeld A D., Coyne C.,
Moreno-Seville B., Fetch J. M., Song Q. J., Cregan P. B., and Frohberg R.
C. (2001). DNA markers for Fusarium head blight resistance QTLs in two
wheat populations. Theoretical and Applied Genetics 102: 1164-1168.

Argyris J., Van Sanford D., and TeKrony D. (2003). Fusarium graminearum
infection during wheat seed development and its effect on seed quality.
Crop Science 43: 1782-1788.

I ‘1“..‘w

Bai G. H., Desjardins A E., and Plattner R. D. (2002). Deoxynivalenol-
nonproducing Fusan’um graminearum causes initial infection, but does not
cause disease spread in wheat spikes. Mycopathologia 153: 91 -98.

 

Bai G. H., Guo P. G., and Kolb F. L. (2003). Genetic relationships among head
blight resistant cultivars of wheat assessed on the basis of molecular
markers. Crop Science 43: 498-507.

Bai G. H., Kolb F. L., Shaner G., and Domier L. L. (1999). Amplified Fragment
Length Polymorphism markers linked to a major quantitative trait locus
controlling scab resistance in Wheat. Phytopathology 89: 343-348.

Bai G.-H., Plattner R., and Desjardins A. (1998). Relationship between visual
scab ratings and deoxynivalenol in wheat cultivars. In: Proceedings of the
National Fusarium Head Blight Forum; 1998 Oct 26-27, East Lansing, MI.
(L.P. Hart, R.W. Ward, R. Bafus, K Bedford, Eds). Michigan State
University, East Lansing, MI. pp. 21-23.

Bai G. H., and Shaner G. (1996). Variation in Fusarium graminearum and cultivar
resistance to wheat scab. Plant Disease 80: 975-979.

Ban T., and Suenaga K (2000). Genetic analysis of resistance to Fusarium head
blight caused by Fusarium graminearum in Chinese wheat cultivar Sumai
3 and the Japanese cultivar Saikai 165. Euphytica 113: 87-99.

Bushnell W. R., Hazen B. E., and Pritsch C. (2003). Histology and physiology of
Fusarium head blight. In: Fusarium Head Blight of Wheat and Barley (K J.
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85

CHAPTER 3
IDENTIFICATION AND MAPPING OF A QTL FOR RESISTANCE TO
FUSARIUM HEAD BLIGHT ON CHROMOSOME ARM ZDL OF WHEAT

3.1 Abstract

F usarium head blight caused by Fusarium spp. and Michrodochium nivale
is a devastating disease of wheat and bartey resulting in major economic losses
in the wheat and bariey industries in North America. To date, few sources of

strong resistance have been identified and verified. The most recognized and

 

utilized source of resistance is from the Chinese cultivar ‘Sumai 3’. The ‘
identification and verification of other sources of resistance to FHB is critical to
enable breeders to combine sources of resistance for a more effective resistance
and to prevent the development of genetic uniformity among elite germplasm.
The objectives of this research were to identify and map quantitative trait loci
(QTL) for resistance from a synthetically derived wheat line. One hundred and
thirty dihaploid lines developed from a cross between ‘CASS94’ (a synthetic
derivative) and ‘Flycatcher’ were genotyped with 180 SSR primer pairs. One
hundred and eight of the dihaploid lines were phenotyped for Type II resistance
to F H8 in the greenhouse using what may be a new procedure for phenotyping
mapping populations for FHB resistance in the greenhouse. The strength of this
phenotyping procedure is reflected in the low LSD values relative to the
frequency distribution of the phenotypic means for each genotype. QTL mapping

by composite interval mapping revealed a major QTL on 2DL, unequivocally

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confirming the existing of an important QTL for Type II on 2DL. Additional QTL

were identified on chromosome 4A and chromosome arms 5AL and 5DL.

3.2 Introduction

Fusarium head blight (F H8) caused by Fusarium spp. and Michrodochium
nivale has caused major losses to the wheat and barley industries in North
America (McMuIIen et al., 1997; Stack, 2003). F H8 infection of wheat and barley
not only causes losses in yield, but reduced grain quality and contamination with
mycotoxins that are a serious threat to both humans and animals (McMuIIen et
al., 1997; Snijders, 1990; Wannemacher and Wiener, 1997). Economic losses
due to FHB in wheat and barley in the United States were estimated to be nearly
three billion dollars during the 1990’s alone (Windels, 2000).

Resistance to F H8 has been categorized according to the effect of the
resistance (Mesterhazy, 1995; Schroeder and Christensen, 1963; Wang and
Miller, 1988) with Type I, resistance to initial infection, and Type II, resistance to
spread being the most frequently studied forms of resistance (Schroeder and
Christensen, 1963). Known resistance to F H8 is partial and not highly heritable
with the phenotypic response to infection being greatly influenced by the
environment (Rudd at al., 2001). To date, no source of complete resistance to
F H8 has been identified, and strong resistance (i.e. resistance resulting in a
large reduction in disease severity) to F H8 in wheat has been confirmed for a
relatively small number of resistance sources (Kolb at al., 2001; Rudd at al.,

2001). The most widely recognized source of resistance is from the Chinese

87

wheat line ‘Sumai 3’, which has a major QTL (i.e. explaining a large proportion of
phenotypic variance), ths.ndsu-3BS, for Type II resistance to FHB mapped to
chromosome 388, which explains as much as 60% of the phenotypic variation
(Anderson et al., 2001; Buerstmayr et al., 2002; Buerstmayr et al., 2003; Chen at
al., 2003; del Blanco et al., 2003; Zhou et al., 2003; Zhou et al., 2002). Sumai 3
resistance is being actively employed in wheat breeding programs throughout the
world as wheat breeders work to develop cultivars with improved resistance to
FHB (Rudd et al., 2001).

Although Sumai 3 offers a source of strong Type II resistance, the
identification of other sources of resistance is important to enable breeders to
avoid genetic uniformity for resistance to FHB, as well as allow breeders to
pyramid resistance genes to develop cultivars with more effective and more
durable resistance (Ruckenbauer et al., 2001).

Wide crosses have been used to identify and introgress important traits
into cultivated crop species (Bommineni and Jauhar, 1997; Tanksley at al.,
1996). Synthetic wheats, created via the hybridization of Triticum turgidum L.
(AABB) with Aegilops tauschii Coss. (DD), have proven to be a powerful tool for
introgression of genes from the diverse accessions of Ae. tauschii into the fairly
narrow gennplasm pool of common wheat (Tfihbum aestivum, AABBDD)
(Ladizinsky, 1985; Lage at al., 2003; Lubbers at al., 1991; Mean, 1987; Mujeeb-
Kazi, 1993; Mujeeb-Kazi, 1995). The objective of this study was to map QTL for

Type II resistance to F HB using a dihaploid population of wheat developed from

88

a cross between a synthetic derivative (‘CASS94’) and a susceptible genotype
(‘Flycatchet").

3.3 Materials and Methods
3.3.1 Plant Materials:

A population of 171 putatively distinct dihaploid (DH) lines developed by
Dr. A Mujeeb-Kazi was employed in this study. The parents of the pop were
‘Flycatcher’, an FHB suswotibla common wheat (Triticum aestivum L. ssp.
aestivum), and CASS94Y000098-51PR-48-0M-1Y-0M (designated ‘CASS94’
from this point onward) (Mujeeb-Kazi, 1995). CASSQ4 had been identified as an
FHB resistant F6 line derived from a cross between ‘Mayoor‘, a moderately
resistant common wheat, and the synthetic hexaploid TK SN1081/Ae. tauschii
(222) (Mujeeb-Kazi at al., 1999). The pop was developed using wheat x maize
pollination (Laurie and Bennett, 1988) followed by doubling of the chromosomes
(induced with cholchicine or spontaneous).

One hundred and thirty distinct DH lines were used for construction of a
molecular marker map (see DNA Marker Analysis below). Of those 130 DH lines,

108 were evaluated for resistance to F H8.

3.3.2 Greenhouse Planting:
One hundred and eight DH lines, CASSQ4, Flycatcher, ‘W14’ (an F H8
resistant genotype - Chen et al., 2003; Jiang, 1997) and ‘Norm’ (an F HB

susceptible genotype) were evaluated for F HB resistance in sixteen replications

89

 

planted over a period of seven and a half weeks in the greenhouse at Michigan
State University in 2003. The experiment included 36 additional DH lines, which
were subsequently identified as likely duplicates of other DH lines (see DNA
Marker Analysis below). In total, the experiment included 148 treatments. One
to three seeds were planted per pot. Six to seven days after planting, seedlings
were vemalized (average temp of 25°C) for two weeks to accelerate the rate of
maturation and reduce the range in flowering times among the different
genotypes. After vemalization, seedlings were placed in a chamber at 156°C for
three days to prevent de-vernalization. Pots were retumed to the greenhouse for
the remainder of the experiment. Thinning and transplanting was conducted so
that each pot had only one plant Pots were arranged in rows according to
genotype, so that a single row would include the sequential planting dates for a
single genotype. Each DH line was arranged in a single row, while parent lines
(CASSQ4 and Flycatcher) and check lines (W14 and Norm) were arranged in
more than one row for better representations of different microenvironments in
the greenhouse (all within a single greenhouse room). An average of two plants
per DH line, 4 plants per parental line (CASSQ4 and Flycatcher) and an average
of 12 plants per resistant and susceptible check (W14 and Flycatcher,
respectively) were used from each planting date. For the first two planting dates,

seeds were sown in 3.5-inch square plastic pots, but these seedlings were

transplanted in the greenhouse after vemalization into D40 Deepotsm cells,

which were used for all other planting replications. Plants were maintained in the

90

 

greenhouse at an average temperature of 193°C (min 7.8°C and max 332°C)

with natural sun and artificial lighting providing a total daylength of 20hrs.

3.3.3 Inoculum Production

Two isolates of Fusarium graminearum were mixed to generate inoculum,
isolates PH-1 (NRRL 31084) and an isolate collected by Dr. Jianrong Shi from a
Michigan wheat field in 2002. Macroconidial spores of both isolates were
produced in mung bean liquid media (Bai and Shaner, 1996 modified). The
procedure was as follows. Mung beans were boiled in water until approximately
5-10% had burst. The liquid was then strained to remove the mung beans and
the liquid was aliquoted into flasks which were then autoclaved. After being
cooled, the liquid media was inoculated with a small amount of F. graminearum
mycelia and shaken at room temperature at 250-350rpm for approximately 10
days to induce sponilation. Macroconidia were counted using a hemacytometer
and the two isolates were mixed for a 1:1 ratio for a final concentration of 50,000

spores/ml (25,000 spores/ml per isolate).

3.3.4 Inoculation

Plants were inoculated by single floret inoculatiOn (Schroeder and
Christensen, 1963) using a micropipette to dispense 10pl of inoculum into a
single floret at anthesis. F Iorets were selected as close to the onset of anthesis
as possible, preferring florets just before dehiscenca. Florets in the center of the

spike were targeted, but florets in spikelets towards the top or bottom of the spike

91

 

were also used as necessary, excluding the terminal and basal spikelets.
Immediately after inoculation, plants were misled twenty seconds every six
minutes for 72 hours in a greenhouse misting chamber under natural light
conditions at an average temperature of 186°C (min 90°C, max 31 .0°C). During
and after misting, plants were arranged on the benches using a scheme devised
to avoid plants from the same genotype being clustered together during misting
and during evaluations of the plants later. This scheme was not a formal
statistical randomization of the genotypes, as it was impractical to do a formal
randomization with spikes selected on-the-spot. After misting, plants were
placed on benches in the greenhouse under natural light conditions (ranged from
112.27 to 15.11h) at an average temperature of 21 .8°C (min 97°C, max 307°C).
All plants inoculated on a single day were considered a single replication
of the experiment In total, twelve replications were conducted over a 10-week
period. Because different genotypes matured at different rates, a single
replication included plants from more than one of the sixteen planting dates. This
approach resulted in all spikes in a given replication being inoculated on the
same day, but not necessarily from the same planting date. In addition, not all
genotypes were represented in all replications, and different genotypes were
represented to a greater or lesser extent in different replications. Considering all
replications, in total 21 to 42 spikes were inoculated per DH line. In addition, 67
spikes of CASS94, 62 spikes of Flycatcher, 184 spikes of W14, and 193 spikes
of Norm were inoculated in total. At least one spike each of W14 and Norm was

inoculated in each replication. The largest replication included 620 spikes total,

92

 

while the smallest replication included 88 spikes. The average number spikes

per replication was 395.

3.3.5 Evaluation of Disease

The number of visually scabby spikelets on a spike was recorded at 7, 10,
14, 17 and 21 days post inoculation (dpi) (plus or minus approximately 12h) for
all replications except replication three, for which most spikes were not evaluated
at 14 dpi, and replication four, for which symptoms at 10 dpi were not evaluated
and symptoms were evaluated at 18 dpi, instead of 17 dpi. For all spikes, in
addition to the number of visually scabby spikelets the total number of spikelets

per spike was also recorded.

3.3.6 Data Analysis

Of the 4,737 spikes evaluated in the entire experiment, eighty-eight (<2%)
did not show any symptoms by 21 dpi and were not included in the analysis
based on the assumption that these spikes were not inoculated. In addition,
spikelets within an inoculated spike that appeared to be infected only due to
outside contact from an adjacent spikelet (i.e., not from spread through the
rachis) were not counted in the total number of spikelets considered infected
because it did not represent internal spread through the plant tissue, but instead '
represented another initial infection point. Overall, infection from contact on the
outside of the spike occurred very infrequently. Bleaching (a general loss of

pigment) and/or wilting symptoms (Bushnell at al., 2003) of spikelets apical of

93

colonized portions of a spike were not distinguished from symptoms physically
coinciding with colonization of the fungus in a spike.

The number of scabby spikelets and the total number of spikelets per
spike were used to determine three other measurements of disease: percentage
of scabby spikelets, area under the disease progress curve (AUDPC) for the
number of scabby spikelets, and AUDPC for the percentage of scabby spikelets.
The AUDPC was separately calculated as described in Shaner and Finney,
1977, for each of the observation dates after 7 dpi (i.e. 10, 14, 17 and 21 dpi).
Specifically:

n

AUDPC = Z [(Yi+1 + Yi)/21 [Xi+1-Xil
i=1

where Y; = either the number or percent of scabby spikelets, and X.- = the day

post inoculation of the i’th observation, and n = the total number of observations
(Shaner and Finney, 1977). Replication 4 was not included in the AUDPC
analyses because symptoms were not observed at 10 dpi. In addition, much of
replication 3 was not included in the analyses of AUDPC after 10 dpi because
symptoms for most spikes were not observed at 14 dpi.

Estimations of genotypic means and experiment-wise LSDs for all
measures of disease were determined with the Proc Mixed LSmeans procedure
of SAS® 8.2 (SAS Institute, 2000) with replication designated as a random factor
in the model. This analysis included all 148 treatments. For the number of

scabby spikelets and the percent of scabby spikelets, the observations at 18 dpi

94

 

in the fourth replication were evaluated with the observations at 17 dpi for the
other replications (though they were not included in the AUDPC analyses, as
mentioned above).

3.3.7 independent Phenotyping of CASS94

Investigation of the phenotypic data of CASS94 revealed that it did not
exhibit a high level of resistance (Fig. 3-2), in contrast to preliminary field data
obtained at CIMMYT (data not shown). A second shipment of CASS94 was sent
from CIMMYT to MSU. A small-scale phenotypic study was conducted to
compare the two different sources of CASS94, using Flycatcher, W14 and Norm
as checks. Seeds (treated with pentachloronitrobenzene) of each genotype were
sown at a rate of approximately 10 seeds per pot. Seven days after planting
seedlings were vemalized for two weeks at approximately 4.3°C (39.7°F).
Vemalized seedlings were then moved to an air conditioned room for two to three
days to prevent de-vernalization. These seedlings were then transplanted in the
greenhouse at a rate of 4 seeds per pot (4-inch square plastic pots). Genotypes
were arranged in rows according to genotype and planting date, but were re-
arranged into rows only according to genotype (i.e., combine all planting dates
for a single genotype) once the first group of inoculations were begun. Inoculum
production, inoculations and misting were performed as described above, except
that carboxymethylcellulose media (Cappellini and Peterson, 1971) was used for
inoculum production instead of mung bean media, and no specific method was

used for pot placement during or after misting. Plants inoculated on a single day

95

were considered a single replication and four replications were conducted total.
Terraguard ® 50W, a fungicide having the active ingredient triflumizole, was
accidentally applied to three of the four replications: two of which were exposed
at least 3 days after inoculation, and the third replication being exposed two days
before inoculation. Triflumizole is not listed as having efficacy on Fusarium spp.,
and disease progression appeared to be normal in all replications according to
the expected responses of the check varieties (W14, Norm and Flycatcher) as
well as the first source of CASS94. Plants were evaluated for the number of
scabby spikelets at either 14 or 17 dpi, depending on when a wide range of
disease symptoms within the replication was apparent. The total number of
spikelets on each spike was also recorded and the percentage of scabby
spikelets was calculated. An estimate of the means of each genotype, for the
number of scabby spikelets and the percent of scabby spikelets, as well as a
means separation test was conducted using the Proc Mixed procedure of SAS®
8.2. (SAS Institute, 2000), with replication as a random factor in the model.

3.3.8 DNA Marker Analysis

A cetyltrimethylammonium bromide procedure modified from Edwards at
al., 1991 (Edwards et al., 1991) was used for DNA extraction.

The population and parents were genotyped using microsatellite (SSR)
primer pairs. Four-hundred and fifty-seven BARC microsatellite primer pairs
(Song at al., 2002) were screened for polymorphism between CASSS4 and

Flycatcher. One hundred and sixty-nine (37%) of primer pairs screened were

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polymorphic and were used to genotype the population, the majority of which had
already been mapped genetically or physically (Shi at al., 2003). Eighteen GDM,
thirty-two GWM (Pestsova et al., 2000; Radar at al., 1998a; ROder et al., 1998b)
and three WMC primers (Wheat Microsatellite Consortium, 2004) that had been
identified by Dr. Kazuhiro Suenaga as being polymorphic between the parent
lines and some DH lines of the population were also used for genotyping the
population. In addition to the parent lines (CAS894, both sources analyzed
separately, and Flycatcher) and the 171 DH lines, Mayoor (the T. aestivum L.
parent of CAS894), the original synthetic (TKSN1081IAe. tauschii (222), cross id
#CIGM88.1217-OB) as well as the T. turgidum parent (TKSN1081, Triticum
turgidum ssp. durum) of the synthetic hexaploid were genotyped.

PCR amplification was conducted with a total volume mixture of 15ul
containing 37.5ng DNA 0.15pM of each primer, 1X PCR buffer (Promega),
1.5mM MgCl2 (Promega), 0.15 of each dNTP and approximately 1.8 units of
Taq. It should be noted that the Taq was not formally quantified, but the
concentration needed was empirically determined. PCR reactions were
performed on an MJ Research FTC-225 Thermocycler and an MJ-Resaarch
FTC-0220 DNA DYAD Thermocycler using a touchdown PCR program
(Sambrook and Russel, 2001) with the following parameters: three minutes at
95°C, then 10 cycles of: 95°C for 25s, annealing temperature + 10°C for 25s
(decreasing by 1°C each cycle) 72°C for 45s, followed by 35 cycles of: 94°C for
25s, annealing temperature for 25s, 72°C for 453, followed by 72°C for 10
minutes. PCR products were visualized on a CBS. Scientific “Mega-Gel High

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Throughput Vertical Unit” (model C-DASG-400-50) according to the method
detailed in Wang at al., 2003.

Inspection of the haplotypes of all DH lines revealed a number of
suspected duplicates. One DH per group of duplicates was arbitrarily selected
for use in linkage and QTL analysis. No phenotypic data was used to decide
which of the genotypes remained in the population. In total, 41 of the original 171
DH lines were excluded. Therefore a total of 130 DH lines were used for linkage
map and QTL analysis, of which 108 lines had been phenotyped.

Thirty four loci, amplified by thirty-two primer pairs (22 BARC, 3 GDM and
7 GWM), showed alleles of unknown origin (i.e., not matching those of either
parent) in the dihaploid population andior polymorphism between the DNA of the
two different sources of CASS94. These primer pairs were not used in linkage or
QTL analyses, but were examined for their putative mapping positions according
to previously reported maps (Pestsova at al., 2000; ROder et al., 1998b; Shi at
al., 2003; Somers, Isaac and Edwards, pers. comm.) (T able 3-1).

3.3.9 Linkage Map Construction

Linkage map construction was performed in JoinMap® 3.0 (Van Oijen
and Voorrips, 2001) using SSR data for 130 DH lines. Segregation ratios of loci
alleles were investigated and loci having extreme segregation ratio distortion (p <
0.001 or less, 8 markers total) were excluded at the onset of linkage map
construction. Unordered linkage groups with a LOD: 4.0 were selected for map

creation from the JoinMap "LOD groupings (tree)” generated with a LOD ranges

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set at 3.0 to 10.0. Ordered line maps were generated using the following criteria:
LOD threshold of 3.0, goodness- of-fit “jump score” threshold of 5.0 and a
recombination frequency threshold of 0.30 except for three linkage groups (3D,
the linkage groups closer to the short arm telomere on 5D and 1A) for which a
0.35 recombination frequency threshold was used. In many cases a single
ordered linkage map could not be created from a single unordered linkage group.
In these instances, more than one ordered linkage map was generated using
subsets of loci from the original unordered linkage group. Upon investigation,
these subsets of loci from a single unordered linkage group created non-
overlapping linkage maps for a single chromosome, as revealed by comparison
with a previously generated linkage map (Pestsova at al., 2000; Roder et al.,
1998b, Shi at al., 2003; Somers, Isaac and Edwards pers comm).

3.3.10 OTL Analysis

QTL analysis was performed in Windows QTL Cartographer V. 2.0
(Wang et al., 2001-2004). The trait data used in the analysis included the
number of scabby spikelets and the percentage of scabby spikelets at all five
days of evaluation (7, 10, 14, 17/18 and 21 dpi), plus the AUDPC calculated for
the number of scabby spikelets and the percentage of scabby spikelets at 10, 14,
17 and 21 dpi. Single Marker Analysis (SMA) was performed and markers
showing significance (p<0.05) were identified. Composite Interval Mapping (CIM)
was performed with forward and backward regression using a walking speed of
2cM and a window size of 10cM. The LOD threshold value of each trait was

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empirically derived for a 0.01 experiment-wise error rate using 1000
permutations, and this LOD threshold was used to declare significance using
CIM (T able 3-2). For putative QTL regions consistently identified using SMA but
not identified using CIM, the CIM p-values corresponding to these putative QTL
were determined and those with p-values<0.05 are reported. Epistatic
interactions of QTL were tested using Multiple Interval Mapping function in
Windows QTL Cartographer V. 2.0.

QTL were graphically displayed with line maps using MapChart (Voorrips,
2002). Support intervals were determined in MapChart for each QTL and
displayed graphically. Support intervals are determined relative to the highest
LOD score in the QTL region. A 1-LOD support interval shows the region of the
QTL whose LOD scores do not differ by more than 1 from the highest LOD score
in the QTL. A 2-LOD support interval shows the region of the QTL whose LOD
scores do not differ by more than 2 from the highest LOD score in the QTL.
These support intervals were determined to give a more accurate picture of the

region of the QTL of greatest significance.

3.4 Results
3.4.1 SSR Data

The bending patterns for the two sources of CASSQ4 were the same in
91% of the primers evaluated. The bending patterns of Mayoor (the T. aestivum
parent of CAS894) were similar to CASS94 (from either source) for

approximately 84% of the primer pairs investigated. The synthetic wheat parent

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of CASS94, however, had banding patterns matching that of CASS94 in only
approximately 15% of the primer pairs investigated. In addition, the T. turgidum
parent of CASS94 had banding patterns matching that of CASS94 in
approximately 16% of the primer pairs investigated, and matched that of the
synthetic wheat (for which it is a parent) for only approximately 47% of the primer
pairs for which the durum parent was amplified (i.e., excluding primers for which
the durum did not amplify, which would be expected for D gamma primers since
the dumm wheat only possesses the A and B genomes).

or the BARC primers screened, 37% were polymorphic, 49% percent
were monomorphic and 14% were indeterminable (inadequate amplification)
between CASSQ4 and Flycatcher. A total of 180 primer pairs (117 BARC primers
pairs, and 63 GWM/GDM or WMC primer pairs) were used to genotype the
population, amplifying a total of 191 putative loci. However, of these 191 putative
loci, 33 (17.3%) showed inconsistencies in banding patterns between the two
different sources of CASS94 (received in 2002 and 2003), and/or the population
displayed multiple allele (more than two) banding patterns (T able 3-1), primarily
due either to differences beMen the two sources of CASSQ4 or a second allele
in Mayoor, a parent of CASS94. These problematic loci were not used in

mapping or QTL analysis.

3.4.2 Linkage Map Construction

Of the 158 putative loci (amplified by 149 primer pairs) investigated 85.4%

fit a 1:1 segregation ratio at p<0.05, an additional 7% fit a 1:1 segregation ratio at

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p<0.01, 2.5% fit a 1:1 segregation ratio at p<0.001, and the remaining 5% did not
fit a 1:1 segregation ratio at p<0.001. Those that did not fit a 1:1 segregation
ratio at p<0.001 were removed from linkage analysis, and the majority of the
other putative loci mapped to expected positions on the basis of previous reports
(Pestsova et al., 2000; ROder et al., 1998b; Shi et al., 2002; Somers, Isaac and
Edwards pers comm). Nine BARC SSR primer pairs were mapped that had not
been previously mapped (to my knowledge) (I' able 3-3). Overall, one hundred
and twenty -nine loci, amplified by 123 primer pairs were mapped to 26 linkage
groups on 16 chromosomes, covering a total of 700.8 CM (Fig. 3—1).

The putative locations of markers showing inconsistencies in banding
patterns between the two sources of CASSQ4 and/or multiple allelic banding
patterns was also investigated. Nine of these problematic primers have putative
mapping locations on chromosomes 2A and 3A Furthermore, all the SSRs
identified for chromosomes 2A and 3A were problematic, and hence neither of
these chromosomes is included in the final linkage map. Four additional
problematic primers were identified with putative mapping positions flanking one
of the linkage groups associated with chromosomes 2D (Xbarc168 to ngm6),

and a number of other problematic markers scattered across the remainder of

thegenome.

3.4.3 Phenotypic Data
There were simificant differences among progeny for all disease scoring,

methods at all dpi. LSDs (p<0.05) and frequency distributions of means are

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presented in Fig. 3-2. The LSD (p<0.05) and frequency distribution of the
average spike size for each genotype is shown in F lg. 3-3.

Neither CASS94 nor Flycatcher exhibited a high level of resistance and
both appear to be susceptible by 21 dpi according to the percentage of scabby
spikelets. In addition, although CASSQ4 had consistently lower means than
Flycatcher for each type of disease measure, the means were not significantly
different (p< 0.05) for the number of scabby spikelets and the AUDPC of the
number of scabby spikelets at 17 and 21 dpi, or for the percent of scabby
spikelets and the AUDPC of the percent of scabby spikelets at 21 dpi.
Furthermore, CASS94 was not significantly different from the susceptible check,
Norm for the number of scabby spikelets and the AUDPC of the number of
scabby spikelets at 14, 17 and 21 dpi, or for the AUDPC of the percent of scabby
spikelets at 21 dpi. With respect to the resistant check, W14, the mean of
CASS94 was significantly greater for all types of disease measurements at all
dpi.

No significant difference was detected between the phenotypic means for
the two sources of CASS94, suggesting that the initial source of CASS94
provided an accurate measure of the CASS94 parent of the population. Thus,
the population appears to exhibit a high level of transgressive segregation,
revealed through the wide distribution around the means of the parent genotypes
for most of the dpi for the different disease measurement methods.

For all days post inoculation and for all disease measures, except for the

percentage of scabby spikelets at 21 dpi and the AUDPC of the percentage of

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scabby spikelets at 21 dpi, there were genotypes of the population that had
disease rating scores that were not significame different from W14 (p<0.05), but
no genotypes were identified that had a significantly less spread of disease than
W14. For the number of scabby spikelets at 21 dpi, two genotypes were
identified that were not significantly different from W14, and for the AUDPC of the
number of scabby spikelets there was an additional third genotype that was not
significantly different from W14. The haplotypes of these three very resistant
genotypes showed that they all carried the CASS94 allele at ngm539, but they
differed for alleles at ngm30 and mec41lear0228. For these three
genotypes, the total number of spikelets on a spike (i.e. the overall spike size)

was significantly less than W14.

3.4.4 QTL Analysis
Single Marker Analysis (SMA) and Composite Interval Mapping (CIM) both

revealed a prominent QTL for FHB resistance on chromosome arm 2DL, having

LOD scores as high as 25.1 and Ft2 values (i.e., the proportion of the phenotypic

variance explained by the QTL) ranging between 0.29-0.60 (Fig. 3-4, Table 3-4).
This QTL was identified in every type of analysis that was used for every dpi of
the disease evaluation. The QTL analysis reveals that this QTL is most closely
linked to ngm539 and resistance is from CASS94. The average phenotypic
mean for 99 of the 108 DH lines (data for this locus was unavailable for 9 lines)
with the CASS94 allele versus the Flycatcher allele at ngm539 is shown in

Table 3-4. The average percent reduction in phenotypic means for genotypes

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with the CASSQ4 versus Flycatcher allele at ngm539 was between 24 and 60%
(Table 3-4). The frequency distribution of the 99 DH lines with and without the
CASS94 allele for ngm539 was determined for the number of scabby spikelets
at 10 dpi (Fig. 3-6) and the percent of scabby spikelets at 21 dpi (Fig. 3-7). As an
additional confirmation of these results, phenotypic data that were excluded from
QTL analysis due to duplication were averaged according to duplication group
(i.e. genotypes suspected to be duplications of one another were averaged
together). These averages were treated as single individuals in an average of
the phenotypic data for progeny having the CASSQ4 or the Flycatcher alleles at
ngm539. These new averages also showed a reduction in disease of 24 —
60% with the CASS94 allele, supporting the suspicion that these genotypes are
duplications, and supporting the evidence of the QTL on chromosome arm 2DL.
Other regions with putative QTL were identified (T able 3-5). A QTL was
detected (with both SMA and CIM) spanning the centromere on chromosome 4A
at 14 dpi for the AUDPC of the percent of scabby spikelets where the resistance

allele came from Flycatcher [SMA A-value (i.e., the effect of substituting one

CASSQ4 allele with a Flycatcher allele) = -18.24 area units and CIM R2 = 0.07]

(Fig. 3-5). However, although this QTL was only detected for a single measure,
all loci on the linkage group spanning the centromere on chromosome 4A were
identified with SMA for every disease measure at all dpi. A smaller linkage group
on 4AL (consisting of only Xbaro104 7 and Xbarc343) was identified with SMA as
significant for every dpi for the percent of scabby spikelets and the AUDPC of the
percent of scabby spikelets (CIM p<0.016 for the AUDCP of the percent of

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scabby spikelets at 10de, SMA A-value -1259 area unites, CIM R2 = 0.15). QTL

were also identified (with both SMA and CIM) on chromosome arms 5AL (SMA

A-value = -1.06 spikelets, CIM R2 = 0.12) and 5DL (SMA A-value = 1.12

spikelets, CIM R2 = 0.11), for the number of scabby spikelets at 21 dpi (Fig. 3-5).

Flycatcher provides the resistant allele for the 5AL QTL at 21 dpi, whereas
CASS94 provides the resistant allele for the 5DL QTL at 21 dpi. For
chromosome arm 5AL, a different QTL was identified with CIM at 10 dpi for the

percent of scabby spikelets (SMA p <0.21, SMA A-value = 2.58%, CIM R2 value

= 0.06) and 14 dpi for the AUDPC of the percent of scabby spikelets (SMA

p<0.20, A-value = 7.44 area units, CIM R2 value = 0.06) for which resistance is

provided by the CASS94 allele (Fig. 3-5). WIth SMA, although one locus
(ngm271) was detected as significant for this QTL region for the percent of
scabby spikelets at 7de, the corresponding CIM value was not significant (CIM
p< 0.28). Chromosome arm 38S was identified by SMA for the number and
percent of scabby spikelets as well as the AUDPC of both the number and
percent of scabby spikelets at 14, 17 and 21 dpi (CIM p<0.034 for the permnt of
scabby spikelets at 14de, SMA A-value = -5.47 percent of scabby spikelets, CIM

R2 value = 0.04; CIM p<0.039 for the AUDPC of the percent of scabby spikelets

at 17de, SMA A-value = -1o.oe area units, CIM R2 value = 0.05). Chromosome

arm 18L was regularly identified as significant using SMA (CIM p<0.032 for the
AUDPC of the percent of scabby spikelets at 10dpi).

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Tests for epistasis were conducted using Multiple Interval Mapping
function of QTL Cartographer V 2.0 for the QTL being significant with CIM
(p<0.01) or significant with SMA and also having a CIM p<0.05. No epistatic

interactions were identified between any of these QTL.

3.5 Discussion
3.5.1 QTL on 2DL

These results provide extremely strong confirmation of the presence of a
QTL on chromosome arm 2DL, as first reported by Somers et al., 2003. This
QTL has been named QfllSCtC-ZD and this name will be used to refer to this QTL
for the remainder of this article.

In this study, Qfilscro—ZD was identified with CIM LOD scores between
10.5 and 25.1 for all four disease measurement methods and each dpi, including
7 dpi which had a frequency distribution that was dramatically skewed towards

zero. The greatest R2 values (as high as 0.60) occurred at 10 dpi for all types of

disease scoring methods except for the percent of scabby spikelets, for which the

R2 value at 14 dpi was the highest. This trend Of high R2 values at 10 and 14 dpi

might reflect a greater precision in identifying the means of the genotypes at 10
and 14 dpi, or could indicate that this resistance is more pronounced at 10 and
14 dpi in this study. In either case, the effect of Qflis.crc-2D was consistently
identified throughout the development of the disease between 7 and 21 dpi.
Somers et al., 2003, investigated FHB resistance in a dihaploid population

developed from a cross between ‘Wuhan-1’ and ‘Maringa’. Their study also

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reported this QTL as being associated with Type II resistance (resistance to
spread). In their population, resistance was associated with the genotype
Wuhan-1’, which is a Chinese accession of unknown pedigree (Daryl Somers
pers comm). Wuhan-1 is not part of the pedigree of CASS94, from which
resistance is derived in the population reported here. Somers et al., 2003

detected this QTL with a LOD between 2.5 and 3.0 and an R2 value of 0.09,

revealing that this QTL explained a relatively small amount of the phenotypic
variance observed. However, when the mean percent of scabby spikelets at 21
dpi was compared for genotypes having the Wuhan-1 versus the Maringa allele
at ngm539, the average of the phenotypic means was 23.2% and 33.1% for the
Wuhan-1 and Maringa alleles, respectively, revealing an overall reduction of
29.9%. The percent reduction observed by Somers at al., 2003 is comparable to
the percent reduction observed in this study at 21 dpi (26.1%, see Table 3-4) at
Qfllscrc-ZD.

3.5.2 Potential for Marker Assisted Selection

One critical requirement for marker assisted selection is that the markers
used in selection are polymorphic between the parents of a cross (Koorneef and
Stern, 2001). ngm539 has been identified as having an especially high level of
polymorphism in two different studies across diverse collections of gennplasm
(McCartney et al., 2004; Quarrie et al., 2003). Quarrie et al., 2003, used 37 SSR
primer pairs amplifying loci across the genome to genotype a diverse collection

of 96 genotypes from different countries. On average, each primer pair detected

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8 alleles per locus, while four primer pairs, including ngm539, detected over 15
alleles per locus. Furthermore, ngm539 only amplified a single locus across
the 96 genotypes. McCartney at al., 2004, used 41 SSR primer pairs (amplifying
loci in regions of known F H8 QTL) to genotype a diverse collection of 79 wheat
cultivars, most of which have been identified as resistant or moderately resistant
to FHB. In their study, the ngm539 locus revealed the highest number of
alleles (20) of all loci examined. These studies indicate that the ngm539 locus
is highly polymorphic across a broad range of genotypes and is likely to only
amplifying a single locus. Such a locus is ideal for marker assisted selection
because it is tightly linked to a major QTL for resistance, it is likely to be
polymorphic between parents of a cross and it is likely to amplify a single locus
(therefore eliminating confusion that can occur when more than one locus is

amplified by a single primer pair).

3.5.3 Combining Resistance

Many minor QTL have been identified for resistance to FHB (Anderson et
al., 2001; Bourdoncle and Ohm, 2003; Gervais at al., 2003; Shen et al., 2003;
Waldron et al., 1999). To date the Qflis.ndsu-3BS QTL confers the greatest
proportion of resistance to FHB of QTL that have been identified and verified.
Previous QTL analyses of Type II resistance conferred by the Sumai 3 and or
Sumai 3-derived line alleles at ths.ndsu-3BS has suggested that these alleles
contribute as much as a 60% reduction in disease severity (Anderson et al.,

2001; Bai et al., 1999; Buerstmayr et al., 2002; Waldron et al., 1999). Even with

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a Iago reduction of disease, this source of resistance is still not considered
adequate to prevent FHB during years with severe epidemics (Buerstmayr et al.,
1999; Hall and Van Sanford, 2003). Furthermore, dependence of resistance
from Sumai 3 and Sumai-3 derived lines can lead to genetic vulnerability that
could be overcome by the fungus (Ruckenbauer et al., 2001).

Studies of the Sumai 3 resistance report QTL analyses conducted using
AUDPC data at 21/22dpi, percent scdiby spikelets at 21 dpi, or the number of
scabby spikelets at 22de (Anderson et al., 2001; Bai et al., 1999; Buerstmayr et
al., 2002; del Blanco et al., 2003; Waldron et al., 1999). In this study, however,

thscrc-ZD alone contributes the greatest proportion of resistance at 10-14 dpi,

according to the R2 values. It is unknown if a similar trend is present with

Qflls.ndsu-3BS resistance, such that an earlier stage of resistance would detect
a greater proportion of the resistance being explained by Qihs.ndsu-3BS, or if
these two different QTL confer resistance at different stages of FHB
development. If ths.ndsu-3BS and ths.crc-2D both contribute a greater
proportion of resistance in earlier stages of disease (versus later) then it
suggests that an earlier dpi could be used for phenotyping populations for F H8.
However, if the Sumai 3lSumai-3 derived ths.ndsu-3BS alleles contribute the
greatest proportion of resistance in later stages of disease (in contrast with
Qfl'ls.crc-20) then a combination of these two sources of resistance could confer
a combined resistance that is greater than either QTL alone.

An advantage of pyramiding Qflis.crc-ZD and Qflis.ndsu-3BS is that in
addition to the ngm539 being highly polymorphic, the Qflrs.ndsu-3BS region

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has been densely populated with markers (Liu and Anderson, 2003), the Sumai 3
haplotype is relatively rare throughout the world (Liu and Anderson, 2003), and
marker assisted selection has already shown success with a Sumai-3 derived
line (Zhou et al., 2003). A potential difficulty that could be encountered with
pyramiding resistance alleles between Officers-20 and Qflis.ndsu—3BS is that
although additive gene action has been identified as being the most prevalent
and important in FHB resistance (Anderson et al., 2001; Bai at al., 2000), the
type of gene-action of Qflis.crc-20 is unknown and the type of interaction that will
be observed through pyramiding these QTL is also unknown. However, Somers
et al., 2003 found that genotypes having both a resistant allele at thscrc-ZD in
and a resistant allele at a QTL that appears to coincide with Qflrs.ndsu-388 have

a greater resistance than genotypes with either of the two QTL alone.

3.5.4 W14 Resistant Check

The presence of three transgressive segregants that were not significantly
different from W14 for the percent and/or AUDPC of scabby spikelets at 21 dpi
supports the fact that Qflrs.ch-2D provides a source of strong resistance. The
significant difference between these three genotypes and W14 for the percent
and the AUDPC of the percent of scabby spikelets at 21 dpi can be explained by
the fact that the W14 has a significantly larger spike than any of these genotypes,
and therefore the percent of infection is reduced. Recombination events
detected beMen ngm539 and neighboring loci for these three transgressive

segregants further supports the strength of the linkage of ngm539 to ths.crc-

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20 and the evidence that ngm539 is the closest molecular marker (of those

' examined in this study) linked to ths.ch-20.

3.5.6 Transgressive Segregation

Transgressive segregation is frequeme observed for FHB resistance
(Anderson et al., 2001; Ban, 2000; Singh et al., 1995; Somers at al., 2003; Van
Ginkel et al., 1996; Waldron et al., 1999), and resistant progeny have previously
been identified in dihapliod lines developed from crosses between moderately
susceptible and a very susceptible parents (Ban, 2000). The presence of the
transgressive segregation in the CASSQ4lFlycatcher population could be caused
by a number of factors such as epistasis or parent lines being fixed for alleles
with opposite effects at loci where effects are mutually independent (Lynch and
Walsh, 1998). Genome coverage in this study was only partial, and in some
cases entire chromosomes were excluded. The limited coverage of the genetic
map in this study leaves many areas of the genome unexplored for potential
QTL. Therefore, transgressive segregation due to epistatic QTL cannot be n.IIad
out. In addition, several of the minor QTL and putative QTL identified had
positive alleles flom Flycatcher, revealing that QTL existed in opposing

relationships in the parents.
3.5.7 Disease Measurement Methods and 011. Detection Overall

In this study, four different measurements of disease (number of scabby

spikelets, percent of scabby spikelets, and the AUDPC of the number or percent

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of scabby spikelets) and five different dpi were investigated to determine whether
or not different disease measurements and/or different stages of disease would
be more effective for QTL identification, and whether or not these different
measurement/dpi combinations would enable the identification of different QTL.
Although the analyses were not independent of one another (i.e., different
experiments were not conducted for each measurement method and dpi), all
disease measurements and all dpi identified Gilmore-20 as a major QTL, even
though the disease had not manifested strongly by 7 dpi (as reflected by the
skewed distribution of the phenotypic means) and disease was skewed towards
100% for the percent of scabby spikelets at 21 dpi. These results reflect the
importance of this QTL in resistance and suggest that major QTL for Type II
resistance can be adequately identified using any one of these disease
measurement methods and dpi.

In contrast to Qflis.0rC-20, other QTL (and putative QTL) identified were
not detected in every measurement method and every dpi. The detection of
significant loci on 4A (spanning the centromeric region) with all disease
measurement methods and dpi using SMA, compared with the detection of a
QTL in that region only at 14 dpi for the AUDPC of the percent of scabby
spikelets using CIM, suggests that there is a QTL in that region and that it is most
influential at 14 dpi. Sparse linkage map coverage of chromosome 4A may be
hindering the detection of this QTL using other disease measurement methods
and at different dpi using CIM. Paillard et al., 2004, also identified a QTL on
chrom050me 4A for F H8 resistance according to the AUDPC for the percent of

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scabby spikelets after spray inoculation in the field, but the QTL was identified in
a different region of chromosome 4A ’

The detection of QTL on 5AL and 5DL (SMA and CIM) at 21 dpi for the
number of scabby spikelets, but not for the percent of scabby spikelets at the
same dpi, may reflect the influence of spike size on the ability to detect this QTL.
At 21 dpi, the distribution was skewed towards 100% for the percent of scabby
spikelets, for which over twenty percent of the genotypes had spread an average
of between 90-100% of the spike. Comparison of the frequency distribution for
the percent of scabby spikelets versus the number of scabby spikelets at 21 dpi
reveals that variation exists in spike size between genotypes since a similar
skewedness is not apparent for the number of scabby spikelets at 21 dpi. The
distribution of the AUDPC for the number and percent of scabby spikelets,
however, were more similar to each other at 21 dpi, revealing that the overall
progression of disease development was not very different between the number

and percent of scabby spikelets when considering all dpi. Although the AUDPC
were more reflective of the total spread of disease, the QTL on 5AL and 50L
were not detected with either AUDPC measurement at 21 dpi. The results
suggest that the QTL on 5AL and 5DL are most influential at 21 dpi and the
confounding effects of spike size hinder detection of this QTL using the percent
of scabby spikelets. An alternate explanation is that the QTL identified on 5AL
and 5DL for the number of scabby spikelets at 21 dpi are artifacts of the
confounding effects of spike size for the number of scabby spikelets. Two other
studies reported the identification of a QTL in the same region of chromosome

114

arm 5AL based on scabby spikelets observed in the field after spray inoculation,

having R‘2 values of 0.087 and 0.108 (Gervais et al., 2003; Paillard et al., 2004).

Regarding 5DL, Gervais at al., 2003, also identified a QTL in the same region
according to the proportion of scabby spikelets after spray inoculation in the field.

Gervais et al., 2003 reported an R2 value of 0.07 for the QTL on SDL. This study

confirms the presence of a minor QTL for F HB resistance on 5AL and 50L.

The identification of a putative QTL on 4AL for the percent and AUDPC of
the percent of scabby spikelets for all dpi for SMA (and CIM p<0.016 for the
percent of scabby spikelets at 10de) also reflects the influence and confounding
effect of spike size on QTL detection. To my knowledge, no other QTL mapping
study to date has reported a QTL in this region of 4AL.

The identification of a putative QTL on 5AL (CIM) for the percent of
scabby spikelets at 10 dpi and the AUDPC of the percent of scabby spikelets at
14 dpi, in the absence of SMA identification of significant loci for these two
dpi/disease measuring methods, may be the result of relatively large gaps
(>100M) between loci present on these linkage groups and the weak contribution
of the putative QTL to resistance. This QTL does not appear to correspond with
other reported QTL according to the LOD graph of the QTL illustrated in Fig. 3—5,
which suggests that the QTL is most closely linked to Xbarc151.

The putative QTL identified on 383 by SMA for all disease measurement
methods at 14, 17 and 21 dpi (CIM p<0.034 and 0.039 for the percent of scabby
spikelets at 14de and AUDPC of the percent of scabby spikelets at 17dpi,

respectively) suggests that the alleles for resistance in this region may have

115

some small influence in later stages of disease. The 388 region identified here
corresponds with Qflis.ndsu-3BS detected in many studies as having a major
QTL for Type II resistance to FHB (Anderson et al., 2001; Bai et al., 1999;
Buerstmayr at al., 2003; Chen et al., 2003; Somers et al., 2003; Waldron at al.,
1 999).

The putative QTL identified on 18L by SMA (CIM p<0.032 for the AUDPC
of the percent of scabby spikelets at 10de) for several disease measurement
methods at various dpi suggests that a minor QTL may also reside on this

chromosome. Buerstmayr et al., 2002, and Shen et al., 2003 also reported the

detection of a QTL for Type II resistance in the same region of 18L having R2

values between 0.072 and 0.16.

Overall, the use of different disease measurement methods and different
dpi has enabled the identification of different QTL, including minor and putative
QTL that have also been detected in other studies. The QTL explaining the
largest proportion of phenotypic variance, Qflrs.crc-ZD, was identified using any

measurement method at any dpi.

3.5.8 Greenhouse Screening Design

The phenotyping scheme described here is different from those reported
by other researchers for screening FHB resistance in the greenhouse. It is
accepted that error variance is large in experiments characterizing FHB
resistance. The approach described here was devised in an attempt to reduce

the confounding effect of environment on the spread of disease for each

116

genotype. To accomplish this, a short period of vemalization was applied to
condense the flowering period between different genotypes (as it was known that
the population did exhibit some response to vemalization) and each genotype
was planted a total of sixteen different times over a period of several weeks. The
result was that the plants for a replication flowered and were inoculated on the
same day. This means that the inoculum and post inoculation environment were
the same for all plants in a give replication. This approach is effective for
reducing the error variance and thus increases the proportion of phenotypic

variance attributed to genotypic variance.

3.5.9 Marker Data

The population shmd the expected 1:1 segregation ratio for the majority
of loci. The presence of additional alleles detected with some primer pairs, in
addition to occasional polymorphism detected between different sources of
CASS94, suggests that CASSQ4 is likely not completely homogeneous. The
putative clustering of some problematic loci on chromosomes 2A and 3A may
reflect the fact that the heterogeneity is more centralized to certain areas of the
genome. Similar phenomena were encountered by Kammohlz et al., 1998 and
2001, where segregation ratios in wheat x maize derived dihaploid populations
conformed to those expected overall, but Won distortion could usually be
attributed to heterogeneity in one of the parents or alien introgression.

The high percentage of CASS94 alleles with anplicons matching those in

its common wheat parent Mayoor, as opposed to its synthetic wheat parent, may

117

reflect selection for agronomic and quality traits after the initial cross. Analysis of
the banding patterns of CASSQ4, its immediate parents and the T. turgidum
parent of the synthetic wheat parent suggest the positive allele for Qflis.ch-20
arises from Mayoor. It cannot be ruled out, however, that Ae. tauschii may be

the source since that ancestors DNA was not evaluated.

3.5. 10 Consistency of CASS“ Resistance

Althougt the sources of CASSB4 tested at MSU did not show a high level
of resistance, as had been identified previously at CIMMYT (Toluca, Mexico) the
conditions under which the resistance was screened were very different from
those used here. At CIMMYT single floret inoculation is conducted in the field at
a high elevation, low latitude research station in Mexico (T oluca) using a cotton
inoculation method (i.e., soaking a cotton wad in inoculum and placing this wed
in a floret) followed by covering the spike with a glassine bag (Gilchrist et al.,
1997). The difference of environmental conditions, in addition to heterogeneity in
CASS94 as discussed earlier and the use of different isolates of F. gramimarum
could greatly contribute to the different responses of CASSQ4 in the two
locations. However, even though CASS94 did not show strong resistance in the
greenhouse at MSU, the CASS94/Flycatcher population showed dramatic,
repeatable variation for resistance and many highly resistant progeny were

observed.

3.5.11 Conclusions

118

This work unequivocally confirms that presence of a major QTL for FHB
Type II resistance at Qfl'rs.crc—20. Currently, the ths.cr0-2D is mapped on this
population in a 23.4 cM region between ngm30 and mec41learc228, with
ngm539 approximately in the center of that region. The density of the genetic
map in the region of Officers-20 needs to be increased. Either this QTL has an
even greater effect than indicated here, or ngm539 is extremely closely linked
to the QTL. A higher density of markers would potentially enable the
identification of flanking markers closer to the QTL. This, in turn, would be a very
powerful tool for marker-assisted selection.

Exploitation and further study of this source of resistance at ths.crc-20 is
likely to be most effective using highly resistant progeny of this population as
opposed to using CASS94 directly. In this study, the lack of strong resistance in
CASSQ4 and the large amount of transgressive segregation observed in the
population suggests that this source of resistance may be affected greatly by the
genetic background with which it is associated. The Type II resistance
contributed by CASS94 at QflIS.CIC-ZD needs to be verified in additional genetic
backgrounds as well as other environments. Furthermore, this study was
conducted in a controlled greenhouse environment, but resistance observed in
the greenhouse may not be an accurate reflection of what will be observed in a
field environment, as may be suggested by the difference in the ratings of
CASS94 in the greenhouse at MSU versus the field at CIMMYT, as well as from
the results of other researchers (Hall and Van Sanford, 2003).

119

In addition to Type II resistance, the CASS94 source of Qfliscrc-ZD
should be examined for its contribution to other types of resistance (i.e., Type I -
resistance to initial infection, resistance to DON accumulation, resistance to
kernel infection and the ability to degrade DON). Somers et al., 2003, tested
DON accumulation and field resistance in the Wthan-1 x Maringa population. In
their study, Type II resistance conferred by Wuhan-1 at Qfl‘Is.crc-2D was
independent of QTL identified for DON accumulation and field resistance.

However, the percent of phenotypic variance explained by the genotypic variance
(i.e. R2) was much lower in their population than in the CASSQ4IFchatcher

population reported here. Therefore, although they were unable to detect an
effect on DON accumulation and field resistance coinciding with ths.crc-ZD,
CASS94 may have a different allele than Wuhan-1 with more effective resistance
at Qflls.cr0-20, which can be useful for determining, with greater certainty, the
involvement of ths.crc-2D in other types of resistance. A number of other
researchers have investigated the correlations of phenotypic data of DON
accumulation and visual symptoms of disease, showing that visual symptoms of
disease are often correlated highly with DON accumulation (Bai et al., 2001;
Lemmens at al., 1997; Mesterhazy, 2002; Miller and Arnison, 1986), as well as
'kemel infection (Bai et al., 2001; Snijders and Perkowski, 1990) though not
always (Lemmens et al., 2004). Determining If thscrc-ZD has an effect on
DON accumulation is critical, since high DON levels in grain are currently the

greatest threat F H8 presents to the wheat industry.

120

3.6 Acknowledgements
This material is based upon work supported by the US Department of

Agriculture, under Agreement No. 59-0790-9-074. This is a COOperative project
with the US Wheat & Barley Scab Initiative. Sincere thanks to Dr. A Mujeeb-
Kazi, CIMMYT, for providing the dihaploid population. Thank you also to Dr.
Lucy Gilchrist and Dr. Maarten Van Ginkel, CIMMYT for support with this project
and sharing their knowledge and data from working with this population. Thank
you to Dr. Kazuhiro Suenaga, National Research Institute of Agrobiological
Resources, for providing some genotypic data for GWM, GDM and WMC primer
pairs. My sincere thanks to Dr. Dechun Wang, Dr. J.D. Kelly and Dr. Yiwu Chen,
Michigan State University, for sharing supplies and equipment. Thank you to Dr.
Jianrong Shi, Jiangsu Academy of Agricultural Sciences, for help with inoculum
production and genotyping. I also thank Dr. Guo-Liang Jiang, Michigan State
University, for his suggestions and knowledge of phenotypic screening. Thank
you to Dr. Sasha Kravchenko, Michigan State University, for guidance with
statistical analysis. I would also like to thank Dr. Daryl Somers, Agriculture and
Agri-Food Canada-Cereal Research Center, for sharing his consensus map with
us before publication. Special thanks also to Lee Siler, Michigan State University
for his support and for constructing the misting chamber for phenotyping. Thank
you to the QTL Cartographer programmers for making their program freely

available on the web and for providing support.

121

Table 3-1. Problematic primer pairs. Primer
pairs amplifying loci with alleles of unknown
origin (indicated with an "A”) and/or
polymorphism between the two sources of
CASSQ4 (indicated with a "P’). Mapping
locations of these loci, according to previously

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

ublished maps, are shown.
Primer Pair Putative Problem?

Mapping

Locations
BARC4 588 A
BARC12 3AS A
BARC45 3AS P, A
BARC57 3AS/SAL P
8ARC67 3AS P
BARC70 4AL P
8ARC134 6BS/6BL A
BARC136 Unknown A
8ARC164 38L P, A
BARC173 6DS P, A
8ARC177 5DL P
8ARC203 38L P
BAR0212 2AS P, A
8ARC253 Unknown P, A
BARC273 6DL P, A
BARC278 78L P
BARC294 3AS P, A
BARC301 Unknown P, A
BARC310 3AS A
BARC32‘I 3ASI3DS P, A
BARCI 169 68S P
BARC1138 2AS P, A
GDM93 2DL A
GDM132 6DS P, A
GDM136 1ASI1BUSDL P
GWM2 3AS A
GWM1 1 1 7DS A
GWM261 2DS P
GWM296 2ASIZDS P
GWM349 2DL A
GWM469 5DU6DS P, A
GWM583 5DL A

 

 

122

 

Table 3-2. Empirically determined LOD threshold
values for each disease measure/dpi combination

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

for p<0.01.
Disease Measure DPI LOD
Threshold
7 3.8
Number of Scabby :2 33
Spikelets 17 3.5
21 3.4
7 3.5
10 3.6
Percent Scabby Spikelets 14 3.5
17 3.6
21 3.6
10 3.4
AUDPC of the Number of 14 3.7
Scabby Spikelets 17 3.6
21 3.5
10 3.4
AUDPC of the Percent of 14 3.5
Scabby Spikelets 17 3.6
21 3.8

 

 

 

 

123

 

Table 3-3. Mapping locations of previously

 

 

 

 

 

 

 

 

 

 

unmapped BARC primer pairs.
Xbarc Loci Chromosome
Xbarc1 155 28
Xbarc132 3D
Xbar0266 58
Xbarc365 6D
Xbar0357 6D
Xbar0281 7A
Xbarc338 7B
Xbarc224 7D
Xbarc336 7D

 

 

 

 

124

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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128

Fig 3-1. Linkage maps for 130 DH lines. Positions are indicated
according to cM distance from the 0.0cM position on a given
linkage group. The 0.0cM positions represent the locus of the
linkage group that is closest to the telomere of the short arm of
that chromosome. In cases where two or more distinct linkage
groups were known to be part of a single chromosome, all were
displayed as one chromosomes delineated with parallel zig-zag
lines. Linkage groups assigned to a single chromosome are
arranged so that the linkage groups above are closer to the
telomere of the short arm of the chromosome than linkage groups

below on the same chromosome.

129

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1A 10
0.0 ngm33-1A 0.0 ngm33-1D
2.4 Xbarc263
9.4 Xbarc149
30.8 Xbarc152
35.1 x m106
36.9 Xbarc83 9”
N
0 0 Xbar0213 ngm497.2
' ngm99 43.8 ngm337
48.9 \../Xbarc229
. m1
18 53.8 /E Xbarc169
8(1) >3<|§Ercfie750 Xb 128 N
. 1-1 l'C arc
1.7 f—QXbarc24o 0.0—0.! Xbar<=287 Xbar062
3.3 _ Xbarc181 X9dm111
6.4/ \Xbarc1131
11.8 Xbarc61
22.3 Xbarc81
25.9 Xbarc188

 

 

 

Fig 3-1 (cont’d)

130

 

 

 

 

 

 

 

 

 

 

 

 

 

 

28 20
0.0 ngm210 0.0 :D: ngn35
3.2 Xbarc297 1-5 “3095
M g a
0.0 Xbarc200 0.0 Xbarc168
22.1 Xbarc230 20.5 X m30
22.9 §94 Xbarc361 gw
23 7 /5\'Xbarc1114 Xbarc91
' / \Xbarc18
24.5 Xbarc1 155 Xbarc1064
30.7 Xbarc101
32.2 ' ‘ngm114-2B 33.8 ngm539
43.9 1mec41 XbacmZ8
49.4 ngm6

Fig 3-1 (cont’d)

131

 

 

 

 

 

 

 

 

 

 

33
0.0 Xbarc75 0.0
3.7 /Xbarc133
3.8 7 \Xbarc147 6-4
6.7 / \ngm493
10.5 Xbarc131
0.0 Xbaroea
3.9 Xba'c344
33.2
39.6
47.8
54.9 /
80.3
93.0
Fig 3-1 (oont’d) 117_1

3D

 

ngm71

 

ngm161

 

Xbarc1 32

 

ngm72

 

mwm341
/ Xbarc125

 

m456

\ng
ngm114-30

 

X9wm383

 

 

ngm314

 

 

132

ngm3

4A 4B

 

 

0.0 > / ngm192-4A 0.0 / XbacmO
0.1 T\ ngm165 0.8 52/ me48
3 3 /~ Xbarc106 Xbarc224 1.4 7~§ngm192-4B
' Xbarc233 2.4 Xbarc199
8.3 — Xbarc163
9.9 XbarcGO
16.9 ngmG

 

 

 

 

 

 

21 .3 Xbarc170
M

0.0 Xbac1 047

 

 

 

 

4.7 Xbac343

Fig 3-1 (cont’d)

133

5A 5D

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

0.0 .xngm3
0'0 Xba'C151 0.8 ?'\Xbarc143
6.8 ngm271
17.8 Xbarc319
25.2 ngm63-5A
27.1 ngm174
53 39.7 Xbarc347
0.0 Xbarc74 N
3.9 Xbarc88 0'0 ngmZ92
N
0.0 Xbarc156
14.3 >_/ Xbarc322
14.4 wach7
16.8 1‘ ngm116-50
18.7 / \XQdm133
21.9 ngm63-5D

 

 

Xbar0275
H ngm1 16—58 Xbarc266
Xbarc142

 

 

(AJODN

4.8m

QNA
\/
rrr

Fig 3-1 (cont’d)

134

 

6D

 

00\irXbarc54

1 1 / \ngm127
5.7 ngm325
7.5 Xbarc365

 

 

1 5.2 Xbarc357

 

 

 

25.0 Xbar0204

Fig 3-1 (cont’d)

135

0.0

6.3

29.9

0.0

9.0

7A

 

Xba r0222

 

Xbarc281

 

 

 

Xbarc1 92

7B

 

Xba r0267

 

 

Xbarc1 76

 

/ngm36
\ Xbarc338

7D

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

0.0 ngm130
16.5 Xbarc352
31 .0
38.7 Xbarc244
54.9 )=< Xbarc184
55.0 Xbarc336

M

0 ngm44

10.9 Xbar0214
15.7 Xbarc260
39.9 ngm67
44.5 Xbarc305
58.0 Xbarc11 1

M

0.0 ngm428
10.6 ngm37

Fig 3-1 (cont’d)

136

iXbarc153 ngm1 30

Fig 3-2. Frequency distributions of 108 dihaploid lines evaluated
with several disease scoring methods. A) number of scabby
spikelets at 7, 10, 14, 17 and 21 dpi. 8) percent of scabby
spikelets at 7, 10, 14, 17 and 21dpi. C) AUDPC of the number of
scabby spikelets at 10, 14, 17 and 21 dpi. D) AUDPC of the
percent of scabby spikelets at 10, 14, 17 and 21 dpi. The means
of CASSQ4 and Flycatcher for each rating system and each dpi
are indicated with a star (CASS94) or circle (Flycatcher). The
Least Significant Differences (LSD) values in the legends are
based on a = 0.05. The X-values of a given bin reflect the upper

limit of that bin.

137

 

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138

 

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Fig 3-3. Frequency distribution of the average total
number of spikelets per spike for 108 DH lines. The
mean of CASSQ4 (star), Flycatcher (circle) W14
(triangle), and Norm (square) are shown. The LSD for
p< 0.05 is indimted. The X-axes values for a given bin
reflect the upper limit of that bin.

142

Figure 3-4. Combined linkage map and Composite lntewal
Mapping LOD graphs for a region of chromosome arm 2DL.
LOD graphs for A) number of scabby spikelets at 7, 10, 14, 17,
21dpi. 8) percent of scabby spikelets at 7, 10, 14, 17, 21dpi.
C) AUDPC of the number of scabby spikelets at 10, 14, 17,
21dpi and D) AUDPC of the percent of scabby spikelets at 10,
14, 17, 21dpi. The maximum R2 value for the QTL region
from Composite Interval Mapping analysis is indicated next to
the LCD graph key for each corresponding dpi. Distances on
the linkage map are indimted in cM. The support interval of
the QTL at each dpi are shown by black bar/line drawings
placed between the linkage map and the LCD graphs. The
inner 1-LOD support interval is indicated by a black bar, and
the inner 2-LOD support interval is indicated by lines extending
on either side of the 1-LOD support interval. For each LOD
graph, a beaded horizontal line at LOD 3.0 is drawn as a
reference. Dashed arrowed lines are drawn to show the

corresponding position of the linkage map and the QTL graph.

143

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Figure 3-5. Combined linkage maps and LOD graphs for CIM
derived QTL on linkage groups of chromosome 4A, and
chromosome arms 5AL and 50L. LOD graphs are placed to the
right of the corresponding linkage map. For each LOD graph, a
key is shown for the dpi/measurement combinations. 10dpi-P is
the percent of scabby spikelets at 1 Odpi. 14dpi-AP is the AUDPC
of the percent of scabby spikelets at 14dpi. 21 dpi-SS is the
number of scabby spikelets at 21 dpi. The maximum R2 value for
the QTL region according to Composite Interval Mapping results is
indicated next to the LCD graph key for each corresponding
dpi/measurement combination. Distances on the linkage map are
indicated in cM. The support interval of the QTL at each dpi are
shown by black bar/line drawings plawd between the linkage map
and the LOD graphs. The inner 1-LOD support interval is
indicated by a black bar, and the inner 2-LOD support interval is
indicated by lines extending on either side of the 1-LOD support
interval. For each LOD graph, a beaded horizontal line at LOD
3.0 is drawn as a reference. Dashed arrowed lines are drawn to
show the corresponding position of the linkage map and the QTL

graph.

148

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Fig 36. Frequency distribution of the mean number of
swbby spikelets at 10dpi for 99 DH lines with either the
CASSQ4 allele (striped bars) or the Flycatcher allele (black
bars) for the SSR locus ngm539. The mean of CASSQ4
(star) and Flycatcher (circle) at 10dpi for the percentage of
scabby spikelets are also indicated. The X-value for a given
bin reflects the upper limit of that bin.

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Fig 3-7. Frequency distribution of the mean percentage of
scabby spikelets at 21dpi for 99 DH lines with either the
CASSQ4 (striped bars) or the Flycatcher allele (black bars)
for SSR locus ngm539. The mean of CASSQ4 (star)
and Flycatcher (circle) at 21dpi for the percentage of
scabby spikelets are also indicated. The X value for a
given bin reflects the upper limit of that bin.

152

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