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This is to certify that the
dissertation entitled

GENETIC MAPPING OF QTLs UNDERLYING PARTIAL
SCLEROTINIA STEM ROT RESISTANCE IN SOYBEAN

presented by

Xiaomei Guo

has been accepted towards fulfillment
of the requirements for the

Ph. 0 degree in Plant Breeding and Genetics

 

 

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DATE DUE DATE DUE DATE DUE

 

 

J'Aixi 6 ti ZUiU

 

 

 

 

 

 

 

 

 

 

 

 

2/05 p:/ClRC/DaleDue,indd-p.1

 

GENETIC MAPPING OF QTLs UNDERLYING PARTIAL SCLEROTINIA STEM
ROT RESISTANCE IN SOYBEAN

By

Xiaomei Guo

A DISSERTATION

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Plant Breeding and Genetics Program
Department of Crop and Soil Sciences

2005

ABSTRACT

GENETIC MAPPING OF QTLs UNDERLYING PARTIAL SCLEROTINIA STEM
ROT RESISTANCE IN SOYBEAN

By

Xiaomei Guo

Sclerotinia stem rot, caused by Sclerotinia sclerotiorum, is an important yield
reducing disease of soybean in the Midwestern states of the US. The objective of my
study was to identify quantitative trait loci (QTLs) associated with partial Sclerotinia
stem rot resistance in soybean plant introduction (PI) 391589B and Asgrow 2506.

The PI 391589B with partial Sclerotinia stem rot resistance was crossed with a
susceptible cultivar IA 2053 to develop a mapping population of 94 F2 derived lines. The
population was evaluated for Sclerotinia stem rot resistance in the field in 2003 and 2004
and in the greenhouse in 2005. The population was also evaluated for genotypes with 109
polymorphic simple sequence repeat (SSR) markers. Both single marker analysis (SMA)
and composite interval mapping (CIM) methods were used to determine the locations of
the QTLs. The SMA revealed several markers from linkage group B significantly (P<0.05)
associated with Sclerotinia stem rot resistance. With the CIM method, a QTL was
identified near marker Satt185 on linkage group B in the 2005 greenhouse experiments.
The QTL explained about 15.5% of the total phenotypic variance. The resistance allele of

this QTL was from IA 2053. “6th the CIM method, another QTL was identified in the

2004 field experiment. The QTL is close to marker Satt212, which is also on linkage
group B but is 11.5 cM away from marker Satt185. The QTL explained 53.1% of the total
phenotypic variance. The resistance allele of this QTL was from P1 3915893.

The Asgrow 2506 with partial Sclerotinia stem rot resistance was crossed with another
resistant cultivar NKS 19-90 to develop a mapping population of 140 F4 derived lines.
The population was evaluated for Sclerotinia stern rot resistance in the field in 2001 and
2002 and in the greenhouse in 2002 and 2003. The population was also evaluated for
genotypes with 53 polymorphic SSR markers. The SMA revealed that marker Sat_327 on
linkage group C1 was significantly (P<0.05) associated with Sclerotinia stem rot
resistance. The CIM method also identified one QTL located near marker Sat_327 on
linkage group C1, which explained about 12.2% of the total phenotypic variance. The
resistance allele was from NKS 19-90. The QTLs identified can be used in maker assisted

selection (MAS) in soybean breeding for Sclerotinia stem rot resistance.

Dedicated to my husband Guobin, my little girl Michelle Kang, and my expecting boy.

And also to the Guo family in Hebei — China.

ACKNOWLEDGEMENTS
I would specially like to acknowledge my major professor Dr. Dechun Wang for his
guidance, financial support, and editorial assistance. I sincerely appreciate my committee
members, Dr. Mitch McGrath, Dr. Ray Hammerschmidt, and Dr. David Douches. I also
appreciate the help from Soybean Laboratory in the planting, inoculation and harvest. In
addition, 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.

TABLE OF CONTENTS

LIST OF TABLES ................................................................................. viii
LIST OF FIGURES ................................................................................. ix
CHAPTER 1
INTRODUCTION .............................................................................................................. 1
SOYBEAN ................................................................................................................... 1
SCLEROTINIA STEM ROT ....................................................................................... 2
SOURCES AND GENETICS OF RESISTANCE ....................................................... 4
MECHANISMS OF SOYBEAN RESISTANCE ........................................................ 6
SOYBEAN GENETIC LINKAGE MAP .................................................................... 6
MARKER ASSISTED SELECTION .......................................................................... 7
OBJECTIVES .............................................................................................................. 8
REFERENCES ........................................................................................................... 10
CHAPTER 2 .
GENETIC MAPPING OF QTLS UNDERLYING PARTIAL SCLEROTINIA STEM
ROT RESISTANCE IN SOYBEAN P1391589B ............................................................. 13
ABSTRACT ............................................................................................................... 13
INTRODUCTION ..................................................................................................... 14
MATERIALS AND METHODS ................................................................................ 15
Population genotyping ........................................................................................ 16
Population phenotyping ...................................................................................... 17
RESULTS ................................................................................................................... 21
Distribution of Phenotypic Data .......................................................................... 21
Identification of QTL for Sclerotinia stem rot resistance ................................... 23
DISCUSSION ............................................................................................................ 28
REFERENCES ........................................................................................................... 31
CHAPTER 3
GENETIC MAPPING OF QTLS UNDERLYING PARTIAL SCLEROTINIA STEM
ROT RESISTANCE IN SOYBEAN VARIETY ASGROW 2506 .......... ' .......................... 33
ABSTRACT ............................................................................................................... 33
INTRODUCTION ..................................................................................................... 34
MATERIALS AND METHODS ................................................................................ 35
Mapping population ............................................................................................ 35
Population genotyping ........................................................................................ 36
Population phenotyping ...................................................................................... 37
Linkage and QTL analysis .................................................................................. 39
RESULTS ................................................................................................................... 40

Phenotypic Data .................................................................................................. 40

Identification of QTL for Sclerotinia stem rot resistance ................................... 47
DISCUSSION ............................................................................................................ 52
REFERENCES ........................................................................................................... 54

APPENDIX ....................................................................................................................... 56

vii

LIST OF TABLES

Table 2-1. Markers significantly associated with Sclerotinia stem rot resistance in single
marker analysis. Markers significant at the 5%, 1%, 0.1% and 0.01% levels were
indicated by *, **, ***, and **** respectively. Linkage group names and relative position
for the markers were assigned according to the Soybean Composite Map (Song et al.,
2004) .................................................................................................. 25

Table 3-1. Markers significantly associated with Sclerotinia stem rot resistance at the
0.01 probability level at least in one environment in single marker analysis. Markers
significant at the 5%, 1%, 0.1% and 0.01% levels were indicated by ‘, **, ***, and ****
respectively. Linkage group names and relative position for the markers were assigned
according to the Soybean Composite Map (Song etal., 2004) ................................ 48

Table 1. Information about all polymorphic simple sequence repeat (SSR) markers from
Fz-derived population of PI 391589B X IA 2053 ............................................... 63

Table 2. Information about all polymorphic simple sequence repeat (SSR) markers from
Iii-derived population of Asgrow 2506 X NKS 19-90 .......................................... 67

viii

LIST OF FIGURES

Figure 2-1. Distributions of the AUDPC values in the 2003 field evaluation and the
2005 greenhouse evaluation and the D81 in the 2004 field evaluation of the 94
F2—derived lines fi'om the cross P13915893 x IA 2053 ......................................... 22

Figure 2-2. Putative QTLS associated with Sclerotinia stem rot resistance on linkage
group B from 2003 and 2004 field and 2005 greenhouse experiments. The map distances
between the markers are given in cM (centiMorgans). The linkage groups are named
according to Song et al. (2004). One QTL was identified around SSR marker Satt263 and
Satt185 on linkage group B in 2003 field and 2005 greenhouse experiments (A) and a
second QTL was identified around SSR marker Satt651 on linkage group B in 2004 field
experiment (B) ....................................................................................... 27

Figure 3-1. The DSI distributions of 140 F4—derived lines from a cross between

Asgrow 2506 and NKS 19-90 in 1998, 1999, and 2002 field experiments. The DSI was
the average of the two replications with 30 plants in each replication ....................... 44

Figure 3-2. Distributions of the average AUDPC of 140 F4—derived lines from a cross
between Asgrow 2506 and NKS 19-90 in the 2002 and 2003 greenhouse experiments.
The plants at late and early V2 stages in 2002 and'2003, respectively, were inoculated
with the cut-petiole method. The AUDPC depends on the percentage of wilted plants and
the observation days after inoculation. The observation period was 20 and 10 days after
inoculation in 2002 and 2003, respectively. The AUDPC was calculated based on 10
plants in each replication with four replications ................................................ 45

Figure 3-3. Putative QTL associated with Sclerotinia stem rot resistance on linkage
group C1 and the map distances between the markers are given in cM (centiMorgans).
The linkage group was named according to Song et a1. (2004). A QTL was identified
around SSR marker Sat_327 in 2002 field and 2003 greenhouse environments. The LCD
threshold after 1000 permuatation was 3.4 and 3.5, respectively ............................ 49

Figure 1. Linkage maps of 94 Fz-derived lines from cross PI 391589 B and IA 2053
constructed using JoinMap 3.0 with a LCD grouping threshold 3.0. The linkage groups
were named according to Song et a1. (2004) and the map distances between the markers
are given in cM (centiMorgans) .................................................................. 56

Figure 2. Linkage maps of 140 F4-derived lines from cross Asgrow 2506 and NKS 19-90
constructed using JoinMap 3.0 with a LCD grouping threshold 3.0. The linkage groups
were named according to Song et a1. (2004) and the map distances between the markers
are given in cM (centiMorgans) ................................................................... 61

CHAPTER 1

INTRODUCTION

SOYBEAN

Soybean, Glycine max (L.) Merr., was domesticated in China from the wild annual
soybean, G soja, during the Chou Dynasty, from the 11th to the 7th century BC. Soybean
was introduced into North America by Samuel Bowen in the 1700’s (Hymowitz and
Harlan, 1983), and most of the US. soybean germplasm came from China, South Korea,
and Japan (Morse et al., 1949). It was introduced for forage usage, but now soybean is
mainly used for soybean meal and oil production in the US. Approximately 80% of
edible fats and oils in the US. are derived from soybean.

Soybean is considered an oilseed crop and contributes over 50% of world oilseed
production. Currently, soybean is grown in approximately 50 countries worldwide. The
US. has been a leading soybean producer during the past half century with over 45% of
world production prior to 2001 (FAO 2002). Today, the US, Brazil, China and Argentina
are the four major soybean producers, accounting for more than 90% of the world
production. In 2004, the US. production accounted for 40% of world production, while
Brazil, Argentina, and China contributed 24%, 18%, and 8%, respectively (Soy Stats.

2005)

In the US, soybean is frequently rotated with corn (Zea mays L.) because the
rotation can improve soil fertility and reduce diseases. The five major soybean production ‘
regions in the US. are the Western Corn Belt, Eastern Corn Belt, Southeast, Delta, and
Atlantic states. In 2004, 30.4 million hectares were planted with soybean in the US. and

the US. soybean production was 85.5 million metric tons (Soy Stats. 2005).

SCLEROTINIA STEM ROT

Sclerotinia stem rot, also called white mold, is one of the most serious soybean
diseases in the US, especially in the north central region (Wrather et al., 1997). The
disease was ranked second in the US. and sixth around the world among the most serious
diseases reducing soybean yield (Wrather et al., 1997). In addition to yield loss, white mold
has been reported to cause significant reduction in seed size, seed germination, and seed
quality (Hoffman et al., 1998). White mold was first reported in the US. in 1924 (Grau and
Hartman, 1999). In 1990 it became widespread in the Great Lakes States, and by 1992 it
was prevalent in the North Central States.

White mold is caused by the fungal pathogen Sclerotinia sclerotiorum (Lib.) De Bary,
a long-lived soil-home fungus with a broad host range. It can be found in most regions
where environments are cool and moist. S. sclerotiorum infects about 400 species and 220
genera in 60 plant families (Purdy, 1979). A number of plants such as soybean, dry beans,
cabbage, canola, and sunflower are potential hosts. Non-host crops are com, small grains,

and all forage grasses (Boland and R.Hall, 1994).

Sclerotia, overwinter survival structure, produce apothecia in which ascospores start
infection. Sclerotia are formed and matured from mycelium on the stem surface, and inside
stems and pods. They fall to the soil surface and overwinter in the soil, and survival
sclerotia germinate the following year or remain in the soil for a few years and still are
viable (Grau, 1988).

Disease occurrence depends on germination of sclerotia, formation of apothecia,
release of ascospores, a flowering host, and a favorable canopy microclimate. The canopy
microclimate plays an important role in disease incidence. Canopy temperatures of <28°C
and high relative humidity and soil moistureare needed for disease development (Boland
and Hall, 1988). The disease cycle begins when apothecia form from sclerotia and
ascospores are ejected from asci. The ascospores land on senescing flower petals to
germinate (Sutton and Deverall, 1983), and hyphae colonize senescent tissues, then
infection progresses into pod and node tissues. Cool and moist weather conditions during
flowering favor S. sclerotium infection of soybean flower petals (Grau, 1988). Symptoms
at the canopy level can be observed a few weeks after flowering. White fluffy mycelium
ofien covers the lesions during high humidity periods and the lesioned part of the stem
becomes bleached. The dark- colored sclerotia are formed inside and outside of the stems
or pods.

Several practices have been recommended for the control of white mold on soybean
(Grau et al., 1994). They include using resistant soybean varieties, widening rows,

reducing plant populations, changing tillage practices, and using fungicides. Among these,

using resistant varieties is the most effective approach for the control of the disease (Kurle
et al., 1998). Rotation with non-host crops such as corn or wheat can be beneficial because
sclerotia germinate in non-host crop fields will reduce the infection load of a suitable host
in the following year. Sclerotia germination is enhanced if the canopy moisture is increased
by rapid and complete canopy closure, narrow row width, high population density, early
planting, and high soil fertility (Grau and Radke, 1984). Integrating resistant varieties and
adjusting cultural practices can minimize the effects of environmental factors.
Understanding the genetics of resistance to white mold is essential for the
development of soybean varieties resistant to the disease. Resistance genes fi'om known
sources must be placed on a genetic linkage map before breeders can use molecular

markers to speed the transfer of resistance genes into new high-yielding varieties.

SOURCES AND GENETICS OF RESISTANCE

No sources of complete soybean white mold resistance have been identified according
to Kim and Diers (2000). Only partial resistance to S. sclerotiorum was found in some
soybean genotypes in field tests (Boland and Hall, 1987; Grau et al., 1982; Kim et al., 1999;
Nelson et al., 1991). The cultivar NKSl9-90 is currently the major source for the
development of resistant soybean varieties. Identification of better sources of resistance to
white mold in soybean plant introductions (PI) has received major attention in the past few
years in the North Central Soybean Research Program - White Mold Coalition. Over 5,500

PIs have been tested for resistance to white mold, but only a few PIs were found more

resistant than NKSl9-9O (Hoffman et al., 2002). Of the five resistant PIs brought to
Michigan State University in 2001, PI 391589B appeared to be best adapted to Michigan
growing conditions. PI 391589B has been successfully crossed with IA 2053 which is
susceptible to white mold, but are desirable for other agronomic traits.

Kim and Diers (2000) pointed out that the inheritance of partial resistance to white
mold was under multiple loci control with a broad sense heritability estimate of 0.59. They
studied the inheritance of partial resistance to white mold in NKS 19-90 and identified three
QTLS conferring this resistance. Two QTLs from linkage groups C2 and M were correlated
with an escape mechanism. The resistance allele on linkage group C2 was significantly
associated with shorter plant height and a smaller lodging index. The resistance allele on
linkage group M was significantly associated with early flowering. However, the third
QTL from linkage group K might be related to a physiological mechanism. The three QTLS
from linkage group C2, M and K explained 7.8%, 9.2%, and 9.6% of variation in the
disease severity index, respectively.

Arahana et a1. (2001) identified 28 putative QTLS using single marker analysis (SMA)
for white mold resistance on 15 different linkage groups from five populations, in which
the resistance sources were Corsoy79, Dassel, DSR173, Vinton81, and NKS 19-90, and
found that individual QTLS explained the disease variation range from 4 to 10%. Seven
QTLS on seven different linkage groups (A2, Dla, le, F, G L, and 0) were identified in
more than one population. The five populations shared the same white mold susceptible

parent Williams 82, in which the authors identified a few additional QTLs on different

linkage groups. The seven QTLs were in different linkage groups fi'om those identified by

Kim and Diers (2000).

MECHANISMS OF SOYBEAN RESISTANCE

The soybean white mold resistance mechanisms include disease escape and
physiological resistance. Most factors which affect the canopy environment are escape
mechanisms, such as plant architecture, lodging, and maturity (Kim and Diers, 2000).
However, there are some physiological mechanisms which result in disease resistance,
including glyceolin, a phytoalexin, which is induced when soybean is infected with
ascospores or mycelium (Sutton and Deverall, 1984). White mold secretes oxalic acid, and
cell-wall-degrading enzymes such as polygalacturonase, cellulase, and xylanase, which are
required for S. sclerotiorum infection (Cessna et al., 2000; Marciano et al., 1983). Godoy et
al. (1990) used mutants to demonstrate that oxalic acid is a pathogenecity determinant.
Oxalic acid also lowers extracellular pH, allowing optimum activity of cell-wall-degrading
enzymes (Marciano et al., 1983).

Donaldson et a1. (2001) transformed the oxalate oxidase gf-2.8 (germin) gene from
wheat and found that the transgenic soybean showed greatly reduced disease progress. This
enzyme oxidizes oxalic acid to carbon dioxide and hydrogen peroxide. Partially resistant

soybean genotypes may be tolerant to or metabolize oxalic acid and polygalacturonase.

SOYBEAN GENETIC LINKAGE MAP

The cultivated soybean is considered a diploidized allotetraploid (Shoemaker et al.,
1996) with chromosome number 2n=2x=40. The first 20 consensus linkage groups
(Cregan et al. 1999a; Cregan et al. 1999b) developed from over 1300 markers including
606 SSR markers were assumed to represent the 20 pairs of soybean chromosomes. The 20
linkage groups were named A1, A2, Bl, BZ, C1, C2, Dla, le, D2, E, F, G, H, I, J, K, L, M,
N, and 0. Song et al. (2004) added another 391 SSR markers to the integrated linkage map.

The current soybean genetic linkage map contains over 2,000 molecular markers, of
which about 1,000 are simple sequence repeat (SSR) DNA markers. The soybean
composite map (Song et al., 2004) can be used to help identify where the white mold
resistance genes are located in the genome. In our study all the SSR markers from the 20
linkage groups were tested for polymorphism and all polymorphic markers were used for

identification of QTL conferring white mold resistance.

MARKER ASSISTED SELECTION
Pathogens easily overcome plant resistance that is due to a single gene and produce a
new pathogenic strain. Pyramiding of multiple resistance genes can enhance the resistance
and also make the resistance more durable. Marker assisted selection (MAS) will assist
breeding by identifying individuals with different resistance alleles at differrent loci,
allowing development of new varieties with multiple resistance genes. It provides
consistent results that do not rely on a pest-plant interaction under certain environmental

conditions.

By identifying QTLS associated with desirable traits, DNA markers closely associated
with the QTLS will be available to help identify progenies with genes of interest. MAS
makes selection more efficient by testing for the presence or absence of certain alleles of
markers linked with QTLS associated with desirable traits and providing faster and more
reliable identification of valuable plants. MAS can be helpful under the following
conditions: 1) if space available to select phenotypical traits in the breeding nursery is

limited; 2) if no disease pressure is present during the breeding process; 3) if only one or

 

two years phenotypic data are available; and 5) if breeders have to wait for several
generations for the selection in traditional breeding. For MAS, only a small piece of tissue
is needed to isolate DNA and use selected markers to test if the plant carries genes of
interest.

Graef et al. (National Sclerotinia Initiative abstract, 2005) developed F4-derived
soybean lines homozygous for the desired marker alleles for the 8 QTL on 7 different
linkage groups (Arahana et al., 2001). However, no significant resistance improved lines

were identified until now.

OBJECTIVES
The partially resistant soybean variety NKS 19-90 was the major resistance source for
the development of resistant soybean varieties. Variety Asgrow 2506 also showed partial
resistance and a population was developed by crossing NKS 19-90 and Asgrow 2506. A

new white mold resistance source, PI 391589B, appeared to be the best adapted to

Michigan growing conditions. A few populations were developed from P1 391589B.
The objectives of my research were:
1) Locate the genes conferring white mold resistance in the new resistance

source PI 3915893 in the current soybean genetic linkage map.

2) Determine whether Asgrow 2506 contains genes conferring partial white
mold resistance.
3) If genes conferring partial white mold resistance were identified determine if

 

the white mold resistance can be increased by combining resistance genes

from Asgrow 2506 and NKS 19-90.

REFERENCES

Arahana, V.S., GL. Graef, J .E. Specht, J.R. Steadman, and K.M. Eskridge. 2001.
Identification of QTLS for resistance to Sclerotinia sclerotiorum in soybean. Crop
Sci. 41:180-188.

Boerrna, HR, and J .E. Specht. 2004. Soybeans: Improvement, Production, and Uses.
ASA, CSSA, and SSSA Publishers.

Boland, (1]., and R. Hall. 1988. Epidemiology of Sclerotinia stem rot of soybean in
Ontario. Phytopathology 78: 1241-1245.

Boland, (1]., and R.Hall. 1994. Index of plant hosts of Sclerotinia Sclerotiorum. Can. J.
Plant Pathol. 16:93-100.

Cessna, SG, V.E. Sears, M.B. Dickrnan, and PS. Low. 2000. Oxalic acid, a pathogenicity
factor for Sclerotinia sclerotiorum, suppresses the oxidative burst of the host plant.
Plant Cell 12:2191-2199.

Concibido, V.C., D.A. Lange, R.L. Denny, J.H. Orf, and ND. Young. 1997. Genome
mapping of soybean cyst nematode resistance genes in 'Peking', PI 90763, and PI
88788 using DNA markers. Crop Sci. 37:258-264.

Cregan, P.B., T. Jarvik, A.L. Bush, R.C. Shoemaker, KG Lark, A.L. Kahler, N. Kaya, T.T.
VanToai, D.G Lohnes, J. Chung, and J.E. Specht. 1999a. An integrated genetic
linkage map of the soybean genome. Crop Sci. 39: 1464-1490.

Cregan, P.B., J. Mudge, E.W. Fickus, D. Danesh, R. Denny, and ND. Young. 1999b. Two
simple sequence repeat markers to select for soybean cyst nematode resistance
conditioned by the rth locus. Theor. Appl. Genet. 99:811-818.

FAO (Food and Agricultural Organization of the United Nations) statistic 2002.

Grau, CR. 1988. T. D. Wyllie and D. H. Scott, eds. Soybean diseaes of the north central
region. Am. Phytopath 800., St. Paul, MN. p. 56-66.

Grau, CR, and V.L. Radke. 1984. Effects of cultivars and cultural practices on
Sclerotinia stem rot of soybean. Plant Dis. 68:56-558.

10

 

Grau, CR, and GL. Hartman. 1999. Compendium of soybean diseases. 4th ed. APS
Press, St. Paul.

Hofi‘man, D.D., GL. Hartman, D.S. Mueller, R.A. Leitz, C.D. Nickell, and W.L. Pedersen.
1998. Yield and seed quality of soybean cultivars infected with Sclerotinia
sclerotiorum. Plant Dis. 82:826-829.

Hofl‘man, D.D., B.W. Diers, GL. Hartman, C.D. Nickell, R.L. Nelson, W.L. Pedersen,
E.R. Cober, GL. Graef, J .R. Steadman, C.R. Grau, B.D. Nelson, L.E.d. Rio, T.
Helms, T. Anderson, V. Poysa, I. Rajcan, and WC. Stienstra. 2002. Selected

soybean plant introductions with partial resistance to Sclerotinia sclerotiorum.
Plant Dis. 86:971-980.

Hymowitz, T., and J .R. Harlan. 1983. Introduction of Soybean to North America by
Samuel Bowen in 1765. Econ. Bot. 37:371-379.

Kim, H.S., and B.W. Diers. 2000. Inheritance of partial Sclerotinia stem rot resistance in
soybean. Crop Sci. 40:55-61.

B. D. Nelson and T. J. Gulya (ed.) 1998. Proc. 1998 Int. Sclerotinia Workshop, Fargo, ND.
9-12 September, 1998.

Kurle, J .E., C.R. Grau, E.S. Oplinger, and A. Mengistu. 2001. Tillage, crop sequence, and
cultivar effects on Sclerotinia stem rot incidence and yield in soybean. Agron. J.
93:973-982.

Marciano, P., P.d. Lenna, and P. Magro. 1983. Oxalic acid, cell wall-degrading enzymes
and pH in pathogenesis and their significance in the virulence of two Sclerotinia
sclerotiorum isolates on sunflower. Physiol. Plant Pathol. 22:339-345.

Morse, W.J., J .L. Cartter, and LP. Williams. 1949. Soybeans: culture and varieties. No.
1520: 1-38.

National Sclerotinia Initiative abstract, 2005 [online] Available at:
http://www.whitemoldresearch.com/html/abstractdetailsZ.cfm?Research_ID= 106

SAS Institute. SAS/STAT Software Version 8. 2000. SAS Institute Inc., Cary, NC.
Shoemaker, R.C., K Polzin, J. Labate, S. J ., E.C. Brummer, T. Olson, N. Young, V.

Concibido, J. Vlrrlcox, J .P. Tamulonis, G. Kochert, and HR. Boerrna. 1996.
Genome duplication in soybean (Glycine soja). Genetics 144:329-338.

11

 

Song, Q.J., L.F. Marek, R.C. Shoemaker, KG Lark, V.C. Concibido, X. Delannay, J.E.
Specht, and RB. Cregan. 2004. A new integrated genetic linkage map of the
soybean. Theor. Appl. Genet. 109:122-128.

Soy Stats. 2005 [online] Available at: httn://www.soy_atats.coWZOOS/DefLMt-fiame.htm.

Sutton, DC, and 8.]. Deverall. 1983. Studies on infection of bean (Phaseolus vulgaris)
and soybean (Glycine max) by ascospores of Sclerotinia sclerotiorum. Plant
Pathol. 32:251-261.

Sutton, DC, and BI. Deverall. 1984. Phytoalexin accumulation during infection of bean
and soybean by ascospores and mycelium of Sclerotinia sclerotiorum. Plant
Pathol. 33:377-383.

Wang, D., P.R. Arelli, R.C. Shoemaker, and B.W. Diers. 2001. Loci underlying resistance
to Race 3 of soybean cyst nematode in Glycine soja plant introduction 468916.
Thero. and Appl. Genet. 103 (4):561-566.

Wrather, J .A., T.R. Anderson, D.M. Arsyad, J. Gai., L.D. Ploper, A. Porta-Puglia, H.H.

Ram, and J.T. Yorinori. 1997. Soybean disease loss estimates for the top 10
soybean producing countries in 1994. Plant Dis. 81:107-110.

12

 

CHAPTER 2

GENETIC MAPPING OF QTLS UNDERLYING PARTIAL SCLEROTINIA

STEM ROT RESISTANCE IN SOYBEAN PI 391589B

 

ABSTRACT L

Sclerotinia stem rot is an important yield reducing disease in soybean in the
Midwestern states of the US. Soybean plant introduction (PI) 391589B has partial
resistance to the disease. The objective of this study was to identify quantitative trait loci
(QTLs) associated with partial Sclerotinia stem rot resistance in P1 391589B. PI 391589B
was crossed with susceptible cultivar IA 2053 to develop a mapping population of 94 F2
derived lines. The population was evaluated for Sclerotinia stem rot resistance in the field
in 2003 and 2004 and in the greenhouse in 2005. The population was also evaluated for
genotypes with 109 polymorphic simple sequence repeat (SSR) markers. Single marker
analysis (SMA) revealed several markers from linkage group B significantly (P<0.05)
associated with soybean Sclerotinia stem rot resistance. Composite interval mapping (CIM)
method identified a QTL in the 2005 greenhouse experiments located near marker Satt185
on the lower part of linkage group E, which explained about 15.5% of the total phenotypic

variance in greenhouse experiment. The resistance allele near the marker Satt185 was from

13

IA 2053. The second QTL located near marker Satt651 on the upper part of linkage group B
was identified in the 2004 field experiment and explained 53.1% of the total phenotypic

variance. The resistance allele near marker Satt651 was from P1 391589B.

INTRODUCTION
Sclerotinia stem rot, also called white mold, is caused by the fungal pathogen

Sclerotinia sclerotiorum (Lib.) De Bary. S. sclerotiorum is a soil borne fungus which

 

infects a large number of crops including soybean. The severity of Sclerotinia stem rot is
related to environmental conditions, with cool temperatures (below 25°C) and moist
canopy conditions favoring S. sclerotiorurn growth (Grau, 1988). The infection process
begins by colonization of the soybean flower petals by S. sclerotiorum ascospores.
Infection then spreads to pods, nodes, and stems, and finally may result in premature plant
death (Grau, 1988). Sclerotinia stem rot has been prevalent in the north central United
States since 1992 (Wrather et al., 1997), causing yield loss, and reduction in seed size and
quality (Hoffman et al., 1998).

The most effective approach to control Sclerotinia stem rot is to use resistant varieties
(Kurle et al., 1998). No sources of complete resistance to the disease has been identified,
and only sources of partial resistance, which show less disease severity with less yield
loss and better seed quality compared with susceptible ones, have been identified (Kurle
et al., 2001). Partial Sclerotinia stern rot resistance in soybean is a quantitative trait (Kim

and Diers, 2000). Kim and Diers (2000) identified three quantitative trait loci (QTLS)

l4

associated with Sclerotinia stem rot resistance in the soybean variety NKS 19-90. Arahana
et a1. (2001) identified twenty-eight putative QTLs from five recombinant inbred line (RIL)
populations. However, correlations of these putative QTLS with Sclerotinia stem rot
resistance have not yet been confirmed in other populations.

QTLs conferring disease resistance could vary among different sources of resistance.
Identification of QTLS from other resistant sources could help understand relationship

among resistance genes and evolution of resistance. DNA markers closely linked to QTLS

 

could be used in marker assisted selection in soybean breeding for Sclerotinia stem rot
resistance, which would accelerate the breeding process and facilitate combining different
resistance genes into one variety. The objective of the study was to identify QTL conferring

partial Sclerotinia stem rot resistance in soybean PI 391589B.

MATERIALS AND METHODS
Mapping population
A mapping population of 94 F2 derived lines was developed from a cross of soybean

PI 391589B x IA 2053. P13915898 was a germplasm collected from China (USDA-ARS),
National Genetic Resources Program) with partial Sclerotinia stem rot resistance (Hoffman
et al., 2002). IA 2053 is a food-grade variety developed by Dr. Walter Fehr at Iowa State
University and is susceptible to Sclerotinia stem rot. F2 plants were individually harvested
to create F23 lines. Each F23 line was advanced to the F24 generation by harvesting a single

seed from each plant and bulking the single seed of all plants of the F23 line. F25 lines were

15

produced in the same way.
Population genotyping

Genotyping were carried out at the F2 generation of the population. Unopened
trifoliolate leaves were collected from each F2 plant in the field and kept on ice before the
samples were transported to the laboratory. The leaf samples were kept at -80°C for at least
48 hours and then lyophilized for approximately 72 hours. DNA was extracted from the
dried leaf tissues using a modified CTAB method (Kisha et al., 1997).

Simple sequence repeat (SSR) markers were used to genotype the population. The
SSR primer sequences were obtained according to Song et a1. (2004). SSR primers were
synthesized by the Genomics Technology Support Facility at Michigan State University. A
total of 1132 SSR markers were screened for polymorphism between the two parents. The
bulked F2 population DNA was added to confirm polymorphism in the population. A total
of 109 polymorphic SSR markers were selected to genotype the entire population.

DNA amplification of SSR markers was performed using a 15 pl polymerase chain
reaction (PCR) mix consisting of 1.0x PCR bufl‘er (10 mM Tris-HCl, 5 0 mM KCl, 0.01%
Gelatin, pH = 8.3), 3.0 mM MgCl2, 0.2 mM each of dATP, dCTP, dGTP, and dTTP
(Sigma-Aldrich, St. Louis, M0), 0.3 uM each of forward and reverse primers, 100 ng of
genomic DNA, and 1 unit of Hermus aquaticus (Taq) DNA polymerase. The amplification
consisted of an initial denaturation of 4 min. at 94 ° C followed by 43 cycles of 25 sec.
denaturation at 94 ° C, 25 sec. annealing at 47 ° C, and 25 sec. extension at 68 ° C, and finally

an additional 7 min. extension at 72 ° C before cooling down to 4 ° C in a MJ TetradTM

l6

thermal cycler (MJ Research, Waltham, MA). The PCR products were analyzed in a 6%
non-denaturing polyacrylarnide gel system as described by Wang et al. (2003).
Population phenotyping

The F23 and F 23 populations were tested for Sclerotinia stem rot resistance by field
inoculation in 2003 and 2004. Field experiments were performed at the Agronomy Farm of
the Department of Crop and Soil Sciences at Michigan State University (East Lansing,
Michigan). A randomized complete block design (RCBD) was used with three replications
of the parental genotypes and 94 F 23 lines in 2003 and six replications of the parental
genotypes and 94 F234 lines in 2004. Each plot had one 3 m long row of approximately 30
plants; rows were spaced 38 cm apart. After each inoculation the fields were sprinkler-
irrigated with approximately 2.5 mm of water every evening for three weeks.

The F23 population was planted on May 28th 2003 and was tested for Sclerotinia stem
rot resistance by the cut-petiole inoculation based on the method of of Del Rio et a1. (2001)
using S. sclerotiorum soybean isolate HT 105 (Provided by Dr. Glen Hartman, University
of Illinois). The HT 105 isolate was maintained by subculturing every two weeks onto
potato dextrose agar (PDA) medium. To prepare inocula for field experiments, a plug of
mycelia was transfered to PDA medium in 120 mm x 30 mm Petri dishes maintained on the
lab bench at room temperature (22-25°C ) until mycelia reached the edge of the plate in
approximately three days. A 1 cm diameter, 8 mm deep plug of mycelium was removed
using an inverted 1 ml pipette filter tip (USA Scientific, Ocala, FL) and was used to

inoculate a soybean plant in the field. The mycelium plugs loaded in 1 ml pipette tips were

prepared in the early morning of the inoculation day and kept on ice until placed on the
plants. The second youngest fully opened trifoliolate leaf was removed with a razor blade
approximately 5 cm above the point of attachment to the petiole. The cut petiole was forced
into the wide end of the pipette tip containing the mycelial plug, to assure contact of the cut
petiole surface with the mycelia. Each replication was inoculated on a separate day, August
13'“, August 22“d and August 29‘”, respectively. Plants were observed daily after
inoculation until the fust plant showed apical wilting symptoms. Plants were subsequently
evaluated for wilting twice a week for the first 7 weeks after each inoculation. The wilted
apical parts were removed after data collection to prevent plant death to allow for F23 seed
production. AUDPC (Area Under Disease Progress Curve) was calculated for each line
according to the formula of Shaner and Finney (Shaner and F inney, 1977).

The F23 population was planted on June 8m 2004. In order to expedite field
inoculations a new method (tip drop method) was developed (Chen and Wang, 2005). S.
sclerotiorum HT 105 mycelia were cultured in PDA medium for three days at room
temperature (22-25°C). Twenty, 8 mm diameter plugs of S. sclerotiorum HT 105 mycelia
were put into 2 L of autoclaved liquid potato dextrose broth (PDB), and cultured for five
days at room temperature with shaking at 100 RPM. The mycelial culture was blended for
10 seconds at high speed using a 1350 ml household blender (BlenderMaster, Hamiton
Beach/Proctor-Silex Inc, Mexico) to create a uniform suspension and was then transferred
to 500 ml wash bottles. Approximately 3 m1 of the mycelial suspension (sufficient to allow

runoff) was applied to the apical meristems and the youngest one or two axillary meristems

18

 

of each plant. Inoculation of the six replicate blocks were made on different days, August
10'“, August 13‘“, August 17‘“, August 19‘“, August 23", and August 24'h to avoid the rain
wash off or environmental effect. When the majority of the plants reached physiological
maturity (R7) (F ehr and Caviness, 1977) all inoculated plants in each row were
individually rated for disease severity based on the rating system of Gran et al. (1982),
where 0 = no symptom, l = lesions on lateral branches only, 2 = lesions on the main stem
but little or no effects on pod fill, and 3 = lesions on main stem resulting in poor pod fill or
plant death. A disease severity index (DSI) was calculated for each line using the formula
DSI=100 x (2 r/3n) (r = rating of each plant; n = number of plants rated).

Plant height and lodging scores were collected before harvest in 2003 and 2004 field.
Plant height was determined as the average length of plants in a plot from the ground to the
uppermost node of the plant at maturity. Lodging notes were recorded on a scale of 1 to 5
according to the following criteria: 1.0 - almost all plants erect; 2.0 - either all plants
leaning slightly, or a few plants down; 3.0 - either all plants leaning moderately (45° ), or 25
to 50% down; 4.0 - either all plants leaning considerably, or 50 to 80% down; 5.0 - all
plants down.

The F23 population was tested by greenhouse inoculation in 2005 using a randomized
complete block design with three replications. Each replication consisted of two pots with
approximately ten plants. To facilitate infection, an inoculation chamber was made by
covering a 5 m X 1.5 m X 1.5 m section of bench with plastic. Two misters were placed at

each end of the plastic chamber. The plants were grown in the greenhouse outside the

19

plastic chamber for about three weeks (between V2 and V3 stages) and then transferred to
the inoculation chamber. Inoculation was done using the tip drop method previously
described. Approximately 0.5 ml of the mycelial suspension was applied to the apical
meristems. After each inoculation the plastic chamber was covered and the misters emitted
water mist for one minute every five minutes. The growth chamber held one replication of
the parental genotypes and 94 F 23 lines. Three replications were sequentially done in
March and April of 2005. The plants were scored for mortality on day 5, 8 and 12 after
inoculation. AUDPC (Area Under Disease Progress Curve) was calculated for each line
according to the formula of Shaner and Finney (1977).

The computer program JoinMap 3.0 (Van Ooijen and Voorrips, 2001) and the
Kosambi mapping function (Kosambi, 1944) were used to determine the linkage
relationships among the polymorphic SSR markers. The LCD groupings threshold was set
to 3.0 to divide markers into 23 linkage groups. The best position of each marker was
searched by comparing the goodness-of-fit for each tested position to determine the order
and distance among markers within each linkage group. The linkage map resulted from
J oinMap analysis was used as map input in the QTL analysis using \VrnQTLcart V2.5
(Wang et al., 2005).

The simple linear regression model from VVmQTLcart V2.5 was used to identify
markers significantly (P value=5%) associated with Sclerotinia stem rot resistance in
soybean. The LCD threshold used to declare the putative QTLs associated with Sclerotinia

stem rot resistance in CIM method was 2.5. The estimated QTL position was under the

20

peak of LOD score curve.

RESULTS

Distribution of Phenotypic Data

The AUDPC values of the mapping population obtained in the 2003 field evaluation
were normally distributed with a range from 5 to 30 (Figure 2-1). The DSI of the
population from the 2004 field test was approximately normally distributed with a range
from 0 to 40 (Figure 2-1). For both field evaluations, the resistant and susceptible parents
fell near the extremes of the distribution. The AUDPC values of the population in the 2005
greenhouse evaluation was also approximately normally distributed with a range from 1 to
8 (Figure 2-1). The AUDPC values obtained from the greenhouse evaluation was smaller
than those from the field evaluation because younger plants were inoculated and higher
humidity was maintained in the greenhouse relative to the field. Most susceptible plants
died within 12 days after inoculation in the greenhouse evaluation versus 7 weeks after
inoculation in the field evaluation. In the 2004 field evaluation and the 2005 greenhouse
evaluation, the tip drop inoculation method was used. However, the AUDPC disease rating
system was used in the greenhouse evaluation while DSI was used in the field evaluation

due to slower disease development and limited time available to score disease in the field.

21

Field 2003

11

 

 

No. of lines

2.5 7.5 12.5 17.5 22.5 27.5 32.5

AUDPC
Field 2004

3340 '
féifll" 1i
9— 20 7

O

, 10 '
é o

 

 

2. 5 7. 5 12.5 17.5 22.5
DSI

Greenhouse 2005

No. of lines

 

 

2.5 3.5 4.5 5.5 6.5 7.5
AUDPC

Figure 2-1. Distributions of the AUDPC values in the 2003 field evaluation and the 2005
greenhouse evaluation and the D81 in the 2004 field evaluation of the 94 F2—derived lines
from the cross PI 391589B x IA 2053.

22

Identification of QTL for Sclerotinia stem rot resistance

Of the 1132 SSR markers tested for polymorphism between the two parents, 109 were
polymorphic. The 109 polymorphic markers were placed into 23 linkage groups with a
LCD threshold of 3.0 using Joinmap 3.0. The 23 linkage groups were segments of 18
linkage groups on the integrated soybean linkage map (Song et al., 2004). Fifieen markers
were placed on linkage group E (Figure 2-2). The total map distance of the 23 linkage
groups with 88 SSR markers was 673.6 cM with average interval length 7.7 cM. The total
map distance was 399.9 cM using the map of Song et al. (2004) and represented 16% of the
soybean genome coverage.

Both single marker analysis (SMA) and composite interval mapping (CIM) methods
were used in the QTL analysis. Single marker analysis (Table 2-1) revealed significant
markers on linkage groups F, I, and E significantly (P<0.05) associated with soybean
Sclerotinia stern rot resistance. All the resistance alleles of the significant markers
identified with the 2003 and 2004 field data were from P1 391589B. However, the
resistance alleles of the significant markers identified with the 2005 greenhouse data were
from IA 2053. The CIM method identified one QTLwith the 2003 field data with a LOD
score of 2.6 (Figure 2-2A). The QTL was located near marker Satt483 on linkage group B
and explained 12.2% of the total phenotypic variance. Another QTL was identified with the
2004 field data with a LOD score of 15.1(Figure 228). The QTL was located near marker
Satt651 on linkage group B and explained 53.1% of the total phenotypic variance. The

third QTL was identified with the 2005 greenhouse data with a LOD score of 3.7 (Figure

23

2-2A). This QTL was located near marker Satt185 on linkage group E and explained 15.5%
of the total phenotypic variance.

The correlations between D81 and plant height were not significant at 0.05 probability
level in 2003 and 2004 field. The correlations between D81 and lodging scores in 2003 and
2004 were 0.33 (p<0.004) and 0.30 (p<0.003), respectively. However, no significant
association was identified between Sclerotinia stem rot resistance and lodging in SMA and

QTL analysis.

24

 

.. . . mammary

Table 2-1. Markers significantly associated with Sclerotinia stem rot resistance in single
marker analysis. Markers significant at the 5%, 1%, 0.1% and 0.01% levels were indicated

by *, **, ***, and **** respectively. Linkage group names and relative position for the

markers were assigned according to the Soybean Composite Map (Song et al., 2004).

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

.Marker Linkage Position'l P-value Resistance
Gm" 2003 2004 2005 SW”:
AUDPC D31 AUDPC

Satt512 E ? 0.064 0.835 0.688 NRS
31847343 E ? 0.288 0.9 0.405 NRS
Satt4ll E 12.92 0.014 * 0.011 " 0.277 PI 391589B
Satt384 E 19.3 0.11 0.066 0.23 NRS
Satt720 E 20.8 0.095 0.019 "' 0.314 Pl 391589B
Satt651 E 32.1 0.005 " 0.000 *"* 0.931 PI 391589B
Satt212 E 32.27 0.019 "‘ 0.006 " 0.769 Pl 391589B
Satt606 E 39.77 0.276 0.594 0.022 "' IA 2053
Satt699 E 41.24 0.239 0.432 0.001 *" IA 2053
Satt706 E 43.36 0.243 0.381 0.002 *"‘ IA 2053
Satt491 E 43.64 0.305 0.693 0.003 " IA 2053
Sattl85 E 44.76 0.066 0.262 0.000 ”"' IA 2053
Satt483 E 44.98 0.894 0.185 0.011 "‘ IA 2053
Satt263 E 45.4 0.333 0.838 0.001 “" IA 2053
Satt685 E 56.7 0.198 0.948 0.584 NRS
AW186493 F ? 0.034 “ 0.015 " 0.147 PI 391589B
Satt149 F 18.13 0.025 " 0.035 "' 0.859 PI 391589B
Satt4l9 I 21.9 0.037 "' 0.035 * 0.477 PI 391589B

 

T “?” means no position available on the soybean composite map.
I NRS = no resistance source available at 0.05 probability level.

25

 

 

Figure 2-2A

Satt$84

 

0.0

 

12.1

18.1 ~-—-
20.7 "

$311411

/ SattS51
~ Satt720

SattZlZ

 

31.2

55.4 «-
58.1 ’-

,- Satt512
~ Satt685

 

76.2

 

86.5

92.7 \
95.8 \-
98.2 /
101.3 /‘
105.6 /

1111

l

 

Satt606

/ Sa11699
«- Satt706
N Satt491
\ Satt263
\ Satt185

 

 

116.2

Satt483

BR347343

l

 

Odd/1V M91580

Odd/1V 8990

 

 

 

 

 

26

 

 

+ 03Field_A UDPC
....-. O5GR_AUDPC

 

 

Figure 2-23

 

 

 

 

 

 

 

 

 

 

E
0.0 Satt384
12.1 Satt411
18.1 N—iw Sa11651
20.7 Satt720
31.2 Satt212
55.4 ~—-» Satt512
58.1 Saueas
76.2 BR347343
86.5 SattSOG
92.7 \LV Sa11699
95.8 Satt706
98.2 /:N Satt491
101.3 / \ Satt263
105.6 /_\ $311185
116.2 Satt483

 

Figure 2-2. Putative QTLS associated with Sclerotinia stem rot resistance on linkage group
B from 2003 and 2004 field and 2005 greenhouse experiments. The map distances between
the markers are given in cM (centiMorgans). The linkage groups are named according to
Song et al. (2004). One QTL was identified around SSR marker SattZ63 and Sattl85 on
linkage group B in 2003 field and 2005 greenhouse experiments (A) and a second QTL was
identified around SSR marker Satt651 on linkage group B in 2004 field experiment (B).
The LCD threshold after 1000 permutation was 2.6 in 2003 field and 2005 greenhouse but

_ I
ISO plea-no

l-Z
9
L9
L9
.01
Let
n

 

 

 

 

 

 

it was 10.4 in 2004 field data.

27

 

 

+ 04FieId_DSI

 

 

 

DISCUSSION

The results obtained in this study indicate two putative QTLS on linkage group B
contributed to soybean Sclerotinia stem rot resistance. The resistance allele of one putative
QTL near marker Satt651 on linkage group E was from P1 391589B. This QTL was
identified by SMA in both 2003 and 2004 field experiments and also by CIM in the 2004
field experiment. The resistance allele of the other putative QTL near marker Sattl 85 on
linkage group E was from IA 2053. This QTL was identified by both SMA and CIM in the
2005 greenhouse experiment and also suggested by the CIM in the 2003 field experiment.
The QTLS identified in the field and greenhouse environments belong to two different
regions of linkage group B. The QTL with resistance allele from P1 391589B was observed
under field conditions, and the QTL with resistance allele from IA 2053 was observed
primarily under greenhouse conditions.

Previous studies by Arahana et al. (2001) identified one marker OP_m12 on linkage
group B significantly associated with soybean Sclerotinia stem rot resistance. The putative
QTL close to marker Satt651 on linkage group E was approximately 10 cM from their
significant marker Op_m12, based on the integrated soybean linkage map (Song et al.,
2004). The resistance allele at the marker OP_m12 identified by Arahana et al. (2001) was
from a susceptible variety, Williams 82, while the resistance allele we identified was from a
partially resistant germplasm, PI 391589B. Since these two markers are only 10 cM away
from each other on the same linkage group, the putative QTLs might be the same locus

carrying the same or different resistance alleles.

28

The QTL located near marker Satt185 on linkage group B has not been identified in
any other studies and the resistance allele was from the susceptible parent, IA 2053. This
QTL was identified in both the 2003 field evaluation and the 2005 greenhouse evaluation,
suggesting the QTL may confer resistance consistently expressed across different
environments.

The cut-petiole inoculation method used in the 2003 field experiment allowed easier
pathogen infection due to the lack of an epidermal barrier from the host plant. Tip drop
inoculation used in the 2004 field and 2005 greenhouse experiments is more similar to
natural infection because the pathogen was allowed to infect the plants without wounding
the plants. Different disease rating systems were used for the tip drop method in the
greenhouse versus the field because of differences in the speed of disease development and
in labor intensity in disease rating. The differences in the speed of disease development in
the greenhouse and in the field were likely due to the differences in the environmental
conditions during disease development.

The Sclerotinia stem rot resistance QTL near Satt651 from P1 391589B was identified
in two years’ field evaluations. The other Sclerotinia stem rot resistance QTL near Sattl85
from IA 2053 was identified in one year’s field evaluation and the greenhouse evaluation.
None of the resistance QTL was identified in all evaluations, indicating the expression of
the resistance was affected by the environment.

It is important to have a sufficient number of polymorphic markers and reproducible

phenotypic data to identify useful QTLs. The 109 polymorphic markers used in the study

29

were not enough to cover the twenty linkage groups of soybean. However, the new markers
identified on linkage group B will provide information for future breeding for soybean
Sclerotinia stem rot resistance. Breeding process will be accelerated if breeders test the
markers identified in this study to be associated with soybean Sclerotinia stem rot

resistance to start the primary screening.

30

REFERENCES

Arahana, V.S., G.L. Graef, J.E. Specht, J.R. Steadman, and K.M. Eskridge. 2001.
Identification of QTLs for resistance to Sclerotinia sclerotiorum in soybean. Crop Sci.
41:180-188.

Chen, Y., and D. Wang. 2005. Two convenient methods to evaluate soybean for resistance
to Sclerotinia sclerotiomm. Plant Dis. (in press).

Del Rio, L.E., N.C. Kurtzweil, and CR. Grau. 2001. Petiole inoculation as a tool to screen
soybean germplasm for resistance to Sclerotinia sclerotiorum. Phytopathology
(supplement) 91:S176.

F ehr, W.R., and CE. Caviness. 1977. Stages of soybean development. Special Report,
Agriculture and Home Economics Experiment Station, Iowa State University No. 80

llpp.

Grau, CR. 1988. p. 56—66, In T. D. Wyllie and D. H. Scott, eds. Soybean diseaes of the
north central region. Am. Phytopath Soc., St. Paul, MN.

Grau, C.R., V.L. Radke, and FL. Gillespie. 1982. Resistance of soybean cultivars to
Sclerotinia sclerotiorum. Plant Dis. 66:506-508.

Hoffman, D.D., G.L. Hartman, D.S. Mueller, R.A. Leitz, C.D. Nickell, and W.L. Pedersen.
1998. Yield and seed quality of soybean cultivars infected with Sclerotinia
sclerotiorum. Plant Dis. 82:826-829.

Hoffman, D.D., B.W. Diers, G.L. Hartman, C.D. Nickell, R.L. Nelson, W.L. Pedersen,
E.R. Cober, G.L. Graef, J .R. Steadman, C.R. Grau, B.D. Nelson, L.E.d. Rio, T.
Helms, T. Anderson, V. Poysa, I. Rajcan, and WC. Stienstra. 2002. Selected soybean
plant introductions with partial resistance to Sclerotinia sclerotiorum. Plant Dis.
86:971-980.

Kim, H.S., and B.W. Diers. 2000. Inheritance of partial resistance to Sclerotinia stem rot in
soybean. Crop Sci. 40:55-61.

Kisha, T.J., C.H. Sneller, and B.W. Diers. 1997. Relationship between genetic distance

among parents and genetic variance in populations of soybean. Crop Sci
37:1317—1325.

31

Kosambi, DD. 1944. The estimation of map distance from recombination values. Ann.
Eugen. 12: 172-175.

Kurle, J .E., C.R. Grau, and ES. Oplinger. 1998. Management practice effects on soybean
yield in the presence of Sclerotinia stem rot, pp. 62-63, In B. D. Nelson and T. J.
Gulya, (eds.) Proc. 1998 Int. Sclerotinia Workshop, Fargo, ND.

Kurle, J.E., C.R. Grau, E.S. Oplinger, and A. Mengistu. 2001. Tillage, crop sequence, and
cultivar effects on Sclerotinia stem rot incidence and yield in soybean. Agron. J.
93:973-982.

SAS Institute. SAS/STAT Software Version 8. 2000. SAS Institute Inc., Cary, NC.

Shaner, G., and RE. Finney. 1977. The effect of nitrogen fertilization on the expression of
slow-mildewing resistance in knox wheat. Phytopathology 67: 1051-1056.

Song, Q.J., L.F. Marek, R.C. Shoemaker, K.G. Lark, V.C. Concibido, X. Delannay, J .E.
Specht, and RB. Cregan. 2004. A new integrated genetic linkage map of the soybean.
Theor. Appl. Genet. 109:122-128.

USDA-ARS, N.G.R.P. Germplasm Resources Information Network - (GRIN) [Online].
Available by National Germplasm Resources Laboratory, Beltsville, Maryland
http://www.ars-grin.gov2/cgi-bin/npgs/html/acchtml.pl?1486332 (verified 05 May
2005).

Van Ooijen, J .W., and RE. Voorrips. 2001. JoinMap® Version 3.0, Software for the
calculation of genetic linkage maps. Plant Research International, Wageningen, the
Netherlands.

Wang, D., J. Shi, S.R. Carlson, P.B. Cregan, R.W. Ward, and B.W. Diers. 2003. A
low-cost, high-throughput polyacrylamide gel electrophoresis system for genotyping
with microsatellite DNA'markers. Crop Sci. 43:1828-1832.

Wang, S., C]. Basten, and Z.-B. Zeng. 2005. Windows QTL Cartographer 2.5.
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(hm;://statgen.ncsu.edu/gtlcart/WOTLC§rt.htm).

Wrather, J .A., T.R. Anderson, D.M. Arsyad, J. Gai., L.D. Ploper, A. Porta-Puglia, H.H.
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producing countries in 1994. Plant Dis. 81:107-110.

 

32

CHAPTER3

GENETIC MAPPING OF QTLS UNDERLYING PARTIAL SCLEROTINIA

STEM ROT RESISTANCE IN SOYBEAN VARIETY ASGROW 2506

ABSTRACT

Sclerotinia stem rot is an important yield reducing disease in soybean in the
Midwestern states of the U.S..The objective of this study was to identify quantitative trait
loci (QTLS) associated with partial Sclerotinia stem rot resistance in soybean variety
Asgrow 2506. The Asgrow 2506 with partial Sclerotinia stem rot resistance was crossed
with another partially resistant variety NKS 19-90 to develop a mapping population of
140 F4 derived lines. The population was evaluated for Sclerotinia stem rot resistance in
the field in 1998, 1999, and 2002, and also in the greenhouse in 2002 and 2003. The
population was tested with 53 polymorphic simple sequence repeat (SSR) markers.
Single marker analysis (SMA) revealed marker Sat_327 fi'om linkage group C 1
significantly (P<0.05) associated with soybean Sclerotinia stem rot resistance. Composite
interval mapping (CIM) method also identified a QTL located near marker Sat_327. The
QTL explained about 12.2% of the total phenotypic variance in 2003 greenhouse

experiment. The resistance allele near the marker Sat_327 was from NKS 19-90.

33

INTRODUCTION

Sclerotinia stem rot (white mold) of soybean is caused by the fungal pathogen
Sclerotinia sclerotiorum (Lib.) De Bary. S. sclerotiorum can be found in most areas where
environments are cool and moist with a host range of about 400 species, 220 genera, and 60
plant families (Purdy, 1979). The infection process begins by colonization of the soybean
flower petals by S. sclerotiorum ascospores. Infection then spreads to pods, nodes, and
stems, and finally may result in premature plant death (Grau, 1988). Sclerotinia stem rot
has been prevalent in the north central United States since 1992 (Wrather et al., 1997),
causing yield loss and seed size and quality reduction (Hoffman et al., 1998).

Several practices have been recommended for the control of white mold on
soybean (Grau et al., 1994). The recommended practices include using resistant soybean
varieties, widening rows, reducing plant populations, changing tillage practices, and using
fungicides. Among these, using resistant varieties is the most effective approach to control
the disease (Kurle et al., 1998).

Although no sources of complete resistance to the disease are available, sources of
partial resistance have been identified (Kim et al. 1999; Hoffman et al. 2002). Kim et al.
(1999) evaluated 18 soybean genotypes for Sclerotinia stem rot resistance in six Michigan
environments over 3 years and found that NKS 19-90, Asgrow 2506, Colfax, and Corsoy
79 had the greatest resistance. Hofirnan et al. (2002) evaluated 6,520 soybean plant
introductions (Pls) for Sclerotinia stem rot resistance and found 68 Pls with partial

resistance to the disease.

34

 

Partial Sclerotinia stem rot resistance in soybean is a quantitative trait (Kim and Diers,
2000). Kim and Diers (2000) studied the inheritance of partial resistance to white mold in
NKS 19-90 and identified three QTLs conferring partial resistance to the disease in NKS
19-90. Arahana et al. (2001) identified twenty-eight putative QTLs fi'om five recombinant
inbred line (RIL) populations. However, correlation between these putative QTLs and
Sclerotinia stem rot resistance has not yet been confirmed. QTLS conferring disease
resistance could vary among different sources of resistance. Identification of QTLs from
other resistant sources could help understand genetic variation associated with disease
resistance. The objective of this study was to identify QTLS conferring partial Sclerotinia
stem rot resistance in soybean variety Asgrow 2506 and to determine if the resistance to
white mold can be increased by combining resistance genes fi'om Asgrow 2506 and NKS

19-90.

MATERIALS AND METHODS
Mapping population
The mapping population consisted of 140 F4-derived lines developed from a cross of
NKS 19-90 and Asgrow 2506 at Michigan State University by Dr. Brian Diers. NKS 19-90
was developed by Northrup King Company with a high level of partial Sclerotinia stem rot
resistance. Asgrow 2506 was developed by Asgrow Seed Company with partial Sclerotinia
stem rot resistance. Single-seed descent was used to advance the population to the F4

generation. F4 -derived lines were tested for partial Sclerotinia stem rot resistance.

35

Population genotyping

Unopened trifoliolate leaves from two weeks old plants were collected from 10 plants
of each F4 derived line in the greenhouse and kept on ice until transported to the laboratory.
The leaf samples were kept at -80°C for at least 48 hours and then lyophilized for
approximately 72 hours. DNA was extracted from the dried leaf tissues using a modified
CTAB method (Kisha et al., 1997).

Simple sequence repeat (SSR) markers were used to genotype the population. The
SSR primer sequences were obtained according to Song et al. (2004). SSR primers were
synthesized by the Genomics Technology Support Facility at Michigan State University. A
total of 1132 SSR markers were screened for polymorphism between the two parents. The
bulked F4 population DNA was also used to confirm polymorphism in the population. Fifiy
three polymorphic SSR markers were selected to genotype the entire population.

DNA amplification of SSR markers was performed using a 15 pl polymerase chain
reaction (PCR) mix consisting of 1.0x PCR buffer (10 mM Tris-HCl, 50 mM KCl, 0.01%
Gelatin, pH = 8.3), 3.0 mM MgCl2, 0.2 mM each of dATP, dCTP, dGTP, and dTTP
(Sigma-Aldrich, St.Louis, M0), 0.3 pM each of forward and reverse primers, 100 ng of
genomic DNA, and 1 unit of Thermus aquaticus (Taq) DNA polymerase. The amplification
consisted of an initial denaturation of 4 min at 94 ° C followed by 43 cycles of 25 sec
denaturation at 94° C, 25 sec. annealing at 47 ° C, and 25 sec extension at 68 ° C, and finally
an additional 7 min extension at 72 ° C before cooling down to 4° C in a MJ Tetr'adTM

thermal cycler (MJ Research, Waltham, MA). The PCR products were analyzed in a 6%

36

non-denaturing polyacrylamide gel system as described by Wang et al. (2003).
Population phenotyping

In 1998 and 1999 field phenotypical data in Michigan and Illinois were collected by
Dr. Brian Dier’s group. The F4-derived lines and parents were evaluated on the Agronomy
Farm at Michigan State University in East lansing, Michigan and at the Crop Sciences
Research and Education Center in Urbana, Illinois. Both enviroments were planted with a
randomized complete block design (RCBD) with two replications. The plots in East
Lansing were three, 6 m rows spaced 38 cm apart and the plots in Urbana were six, 3.7 m
rows spaced 19 cm apart. The plots were inoculated with sclerotia collected from harvested
common bean (Phaseolus vulgaris L.) by evenly spreading over the field from one week
prior to the earlist soybean line having 50% of its plants reaching the R1 growth stage (F ehr
and Caviness, 1977).

In 2002 the population was evaluated for white mold resistance on the Agronomy
Farm at Michigan State University in East Lansing, Michigan. The field was artificially
inoculated with sclerotia of S. sclemtiorum using the same method fi'om last description.
Both parents and the population of F4-derived lines were planted in a RCBD with 2
replications. The lines were planted in 6-row plots with 38 cm row spacing and a length of
4.2 m. The fields were sprinkler-irrigated (approximately 2.5 mm) every evening from
approximately one week prior to the first line onset of blooming (R1) (Fehr and Caviness,
1977) until completion of flowering of all lines.

The plots were rated for disease severity based on the rating system of Grau et al.

37

(1982) at approximately the beginning of physiological maturity (R7) (Fehr and Caviness,
1977). Thirty plants in the center rows of plots were individually rated on a scale of 0 to 3,
where 0 = no symptoms, 1 = lesions on lateral branches only, 2 = lesions on the main stem
but little or no effects on pod fill, and 3 = lesions on main stem resulting in plant death or
poor pod fill. A disease severity index (DSI) was calculated for each plot using the formula:
DSI=100 x (2 r/3n) (r = rating of each plant; n = number of plants rated). The DSI ranges
from 0 for absence of disease to 100 for severe infection. Before harvesting, plant height
and lodging scores were collected. Plant height was determined as the average length of
plants in a plot from the ground to the uppermost node of the plant at maturity. Lodging
notes were recorded on a scale of 1 to 5 according to the following criteria: 1.0 - almost all
plants erect; 2.0 - either all plants leaning slightly, or a few plants down; 3.0 - either all
plants leaning moderately (45° ), or 25 to 50% down; 4.0 - either all plants leaning
considerably, or 50 to 80% down; 5.0 - all plants down.

In addition to field evaluation, the mapping population was tested for Sclerotinia stem
rot resistance in greenhouse using a petiole inoculation method described by Del Rio et al.
(2001). The S. sclerotiorum isolate Montcalm collected from local common beans field
was used for the inoculation. The culture was maintained by sub-culturing every three
weeks at room temperature on potato dextrose agar (PDA, Sigma® P-2182) medium. A
single mycelia plug cut from the culture with 6-mm diameter cork-borer was placed in the
center of a new plate with roughly 4 mm thick layer of PDA (39.0 g PDA/L) to produce

inocula for the inoculation. Each seede‘d Petri plate was sealed and incubated for three days

38

at 22 °C with 10 hours light daily. A mycelia plug on the growing edge of the 3-day old S.
sclerotiorum colonies was loaded at the wide end of a 1 ml pipette tip (USA Scientific,
Ocala, FL) by pushing the wide end of the tip through the media. The first fully Open
trifoliate leaf was removed with a razor blade approximately 2.5 cm above the point of
attachment to the petiole. The cut petiole was forced into the wide end of the pipette tip
containing the mycelial plug to ensure contact of the cut petiole surface with the mycelia.
Ten plants of each F4-derived line were inoculated. The number of plants wilted during
each day in the 10 days following inoculation was recorded. AUDPC (Area Under Disease
Progress Curve) was calculated for each line according to the formula of Shaner and
Finney (1977).
Linkage and QTL analysis

The computer program JoinMap 3.0 (Van Ooijen and Voorrips, 2001) and the
Kosambi mapping function (Kosambi, 1944) were used to determine the linkage
relationships among the polymorphic SSR markers. The likelihood of odds (LOD)
groupings threshold was set to 3.0 to divide markers into linkage groups. The best position
of each marker was searched by comparing the goodness-of-fit for each tested position to
determine the order and distance among markers within each linkage group. The linkage
map resulting from JoinMap analysis was used as map input in the QTL analysis using
\VrnQTLcart V2.5 (Wang et al., 2005).

A simple linear regression model from MnQTLcart V2.5 was used to identify

markers significantly (P value = 5%) associated with Sclerotinia stem rot resistance. Model

39

6 was used with window size 10 cM and 5 background markers. The LCD threshold used
to declare the putative QTLs significant in composite interval mapping (CIM) method was
determined by 1000 permutations (Churchill and Doerge, 1994). The estimated QTL

position was at the peak position of LOD score curve.

RESULTS
Phenotypic Data

Field DSI from Illinois in 1998 and 1999 were approximately normally distributed
with a range from 0 to 65 (Figure 3-1). The distributions of field DSI from Michigan in
1998 and 1999 were skewed to the right with a range from 0 to 70. The 2002 field DSI was
only collected from Michigan and D81 distribution was severe skewed to the right with a
range from 0 to 35 (Figure 3-1). For the parents, the D81 for Asgrow 2506 was 16 and for
NKS 19-90 was 0. In 2002, the field condition was hot and dry which was not suitable for
Sclerotinia stem rot development.

Greenhouse average AUDPC in 2002 (Figure 3-2) was approximately normally
distributed with a range from 0 to 16. For the parents, the AUDPC for Asgrow 2506 was 14
and for NKS 19-90 was 0. However, the distribution of the average AUDPC in 2003
(Figure 3-2) was slightly left skewed with a range from 2 to 7. For the parents, the AUDPC
for Asgrow 2506 was 5 and for NKS 19-90 was 2. In the 2003 greenhouse experiments the
inoculated plants were younger than those in the 2002 experiments in which plants in 2003

were early V2 stage but plants in 2002 were late V2 stage so the disease progressed faster

40

in 2003. Over 80% of the inoculated plants were dead on the 10‘h day after inoculation in

2003, while only 40% of the inoculated plants were dead on the 10th day after inoculation

in 2002.

41

Figure 3-1.

IL 1998

1W1 aflines
a:
c>

 

 

DSI

IL 1999

cfi’lines

No.

 

 

DSI

MI 1998

No. of lines

 

 

D81

42

 

Figure 3-1. (cont’d)

MI 1999

No. of lines
N
0

D81

AVE IL & MI

60
50
4O
30
20

Na oflhrs

051

M1 2002

80
7O
60
50
4O
30
20

No. of lines

o 5 15 25 35
D51

43

Figure 3-1. The DSI distributions of 140 F4—derived lines from a cross between Asgrow
2506 and NKS 19-90 in 1998, 1999, and 2002 field experiments. The DSI was the average

of the two replications with 30 plants in each replication.

Greenhouse 2002

No.<fi'lines

 

 

0 2 6 10 14

Greenhouse 2003
60 - g
50 i
40 ll
30

:2 20

10

  

of lines

 

 

Figure 3-2. Distributions of the average AUDPC of 140 F4—derived lines from a cross between
Asgrow 2506 and NKS 19-90 in the 2002 and 2003 greenhouse experiments. The plants at late and early
V2 stages in 2002 and 2003, respectively, were inoculated with the cut-petiole method. The AUDPC
depends on the percentage of wilted plants and the observation days afler inoculation. The observation
period was 20 and 10 days after inoculation in 2002 and 2003, respectively. The AUDPC was calculated

based on 10 plants in each replication with four replications.

45

 

The broad-sense heritability estimates were obtained by proc glm in SAS analysis.
The heritability was 0.41 in 1998 and 1999 in Michigan and Illinois field data and it was
0.24 and 0.16 in 2002 and 2003 greenhouse environment in Michigan, respectively.
Identification of QTL for Sclerotinia stem rot resistance

Of the 1132 SSR markers tested for polymorphism between the two parents, only 53
were polymorphic. The 53 polymorphic markers were placed into 9 linkage groups with a
LOD threshold of 3.0 using Joinmap 3.0. The 9 linkage groups corresponded with soybean
composite map (Song et al., 2004) linkage groups A1, B2, C1, le, D2, Dla and G, H, N,
and O. The total map distance of the 9 linkage groups with 25 SSR markers was 116.2 cM
with average interval length 4.6 cM. However, the total map distance was only 49.6 cM
using Song et al. (2004) map and it was only 2% of the soybean genome coverage.

Both single marker analysis (SMA) and composite interval mapping (CIM) methods
were used in the QTL analysis. Markers from different linkage groups were significantly
associated with soybean Sclerotinia stem rot resistance but only the marker Sat_327 from
linkage group C1 was relatively consistent among the tests in different years. Single
marker analysis (Table 3-1) identified marker Sat_327 on linkage group C1 significantly
(P<0.001) associated with soybean Sclerotinia stem rot resistance in field test in Michigan
in 1999 and in greenhouse test in 2003. The resistance allele was from NKS 19-90.
Marker-wise P=0.001 is equivalent to experiment-wise P=0.001*53 (polymorphic markers)
=0.05 in my study. The CIM method also identified a QTL (Figure 3-3) around marker

Sat_327 with LOD scores of 9.2 and 3.7 comparing to 3.4 and 3.5 of the LOD thresholds

46

for P5005 determined by 1000 permutations for the 2002 Michigan field tests and the
AUDPC of the 2003 greenhouse test, respectively (Figure 3-3). The QTL explained 62.1%
and 12.2% of the total phenotypic variances of the 2002 Michigan field tests and the

AUDPC of the 2003 greenhouse test, respectively.

47

Table 3-1. Markers significantly associated with Sclerotinia stem rot resistance at the 0.01
probability level at least in one environment in single marker analysis. Markers significant
at the 5%, 1%, 0.1% and 0.01% levels were indicated by *, **, ***, and **** respectively.
Linkage group names and relative position for the markers were assigned according to the

Soybean Composite Map (Song et al., 2004).

 

 

 

 

 

 

 

 

 

 

Marker LG Position p-value Source
Name 1 I of R
“.1 MI AVE W G... 6..
Field Field 98 & Field 2002 2003 Allele
1998 1999 99 2002
Sat_327 C1 ? 0.003 0.001 0.002 0.019 0.016 0.000 NKS
it ##t it t * **** 19_90
Satt37l C2 145.5 0.008 NS NS NS NS NS A2506
it
Satt463 M 50.1 NS NS NS NS 0.009 NS NKS
** 19-90
Satt445 O 20.4 NS NS NS NS 0.001 NS NKS
** 19-90
Satt526 A1 28.0 NS NS NS NS 0.006 NS NKS
** 19-90
Sctt008 D2 3.2 NS NS NS NS NS 0.006 NKS
** 19-90
Satt373 L 107.2 NS NS NS NS NS 0.005 NKS
** 19-90

 

 

 

 

 

 

 

 

 

 

1‘ LG = Linkage Group
I “2” means no position available on the soybean composite map.
§ GH = Greenhouse; NS = not significant at 0.05 probability level.

48

 

Figure 3-3. Putative QTL associated with Sclerotinia stem rot resistance on linkage group
Cl and the map distances between the markers are given in cM (centiMorgans). The

linkage group was named according to Song et al. (2004). A QTL was identified around

SSR marker Sat_327 in 2002 field and 2003 greenhouse environments. The LOD§

threshold after 1000 permuatation was 3.4 and 3.5, respectively.

C1

0.0

 

O
Sat1294

 

 

 

K + 02FieId_DSI

“ '0 r ' O3GR_A UDPC

 

 

 

adanv‘aoeo

 

ISO-019.1330

 

 

16.3

 

I37

Sat_327

 

 

 

 

§ The LOD threshold in the figure was 3.5.

49

The correlation between D81 and plant height was 0.26 (p<0.01) and the correlation
between D81 and lodging score was 0.31 (p<0.001) in 1998 and 1999. However, no
significant association was identified between Sclerotinia stem rot resistance with height

and lodging in SMA and QTL analysis.

50

DISCUSSION

The results obtained indicate that the allele from linkage group C1 contribute to
soybean Sclerotinia stem rot resistance in NKS 19-90. A QTL region near Sat_327 was
identified by SMA and CIM in both field and greenhouse experiments. Previous studies
(Arahanna et al., 2001; Kim and Diers, 2000) did not identify any markers from linkage
group C] significantly associated with soybean Sclerotinia stem rot resistance. The
resistance allele at the marker Sat_327 was from soybean variety NKS 19-90. The reason
that no resistance allele from Asgrow 2506 was idientified might be that the resistance
alleles in Asgrow 2506 are also present in NKS 19-90 so there was no segregation for these
alleles in the mapping populations. Another reason could be that there were no
polymorphic markers near the resistance allele in Asgrow 2506. A third possible reason
could be that the phenotypic data were collected under conditions not favouring the
expression of the resistance allele in Asgrow 2506.

Most significant markers were not identified by other studies. Arahana et al. (2001)
identified some markers using SMA from the same linkage groups such as Al, D2, L, and
0 but they are over 50 CM away from the significant markers in my study except that
marker ScttO08 on linkage group D2 is about 20 cM fi'om Satt458 in their study.

The correlation between disease index, plant height and lodging were observed and
some significant markers from disease score were associated with plant height and lodging

(Kim and Diers, 2000). However, there was no significant association between marker

51

Sat_327 with plant height and lodging at 0.05 probability level.

During the QTL mapping of soybean Sclerotinia stem rot resistance in this population,
two big challenges were encountered. One was that not enough polymorphic markers were
identified between the two parents and the other was the difficulty in obtaining consistent
phenotypic data. It is important to have a sufficient number of polymorphic markers and
reproducible phenotypic data to identify useful QTL. The disease. development depends on
the environmental conditions and this make it difficult to obtain consistent phenotypic data.
Nevertheless, the new marker found to be associated with Sclerotinia stem rot resistance in
this study can be used in marker assisted selection for resistance to the disease in a soybean
breeding program.

Some lines showed better resistance than both parents but they were not significantly
better at the 0.05 probability level. So it is hard to say that the resistance was increased by
combining resistance genes from Asgrow 2506 and NKS 19-90. One reason might be that
both parents share some major resistance genes. Another reason might be the population
size was not big enough to have some lines with good combination of all the resistance

genes from both parents.

52

 

REFERENCES

Arahana, V.S., G.L. Graef, J.E. Specht, J.R. Steadman, and K.M. Eskridge. 2001.
Identification of QTLS for resistance to Sclerotinia sclerotiorum in soybean. Crop Sci.
41 : 180-1 88.

Churchill, GA, and RW. Doerge. 1994. Empirical threshold values for quantitative trait
mapping. Genetics 138:963-971.

Del Rio, L.E., N.C. Kurtzweil, and CR. Grau. 2001. Petiole inoculation as a tool to screen
soybean germplasm for resistance to Sclerotinia sclerotiorum. Phytopathology
(supplement) 91 :Sl76.

Fehr, W.R., and CE. Caviness. 1977. Stages of soybean development. Special Report,
Agriculture and Home Economics Experiment Station, Iowa State University No. 80

llpp.

Grau, CR. 1988. p. 56-66, In T. D. Wyllie and D. H. Scott, eds. Soybean diseaes of the
north central region. Am. Phytopath Soc., St. Paul, MN.

Hoffman, D.D., G.L. Hartman, D.S. Mueller, R.A. Leitz, C.D. Nickell, and W.L. Pedersen.
1998. Yield and seed quality of soybean cultivars infected with Sclerotinia
sclerotiorum. Plant Dis. 82:826—829.

Hoffman, D.D., B.W. Diers, G.L. Hartman, C.D. Nickell, R.L. Nelson, W.L. Pedersen,
E.R. Cober, G.L. Graef, J .R. Steadman, C.R. Grau, B.D. Nelson, L.E.d. Rio, T.
Helms, T. Anderson, V. Poysa, I. Rajcan, and WC. Stienstra. 2002. Selected soybean
plant introductions with partial resistance to Sclerotinia sclerotiorum. Plant Dis.
86:971-980.

Kim, H.S., and B.W. Diers. 2000. Inheritance of partial resistance to Sclerotinia stem rot in
soybean. Crop Sci. 40:55-61.

Kim, H.S., C.H. Sneller, and B.W. Diers. 1999. Evaluation of soybean cultivars for
Sclerotinia stem rot resistance in field environments. Crop Sci. 39:64-68.

Kisha, T.J., C.H. Sneller, and B.W. Diers. 1997. Relationship between genetic distance
among parents and genetic variance in populations of soybean. Crop Sci.
37:1317—1325.

53

Kosambi, DD. 1944. The estimation of map distance from recombination values. Ann.
Eugen. 12:172-175.

SAS Institute. SAS/STAT Software Version 8. 2000. SAS Institute Inc., Cary, NC.

Shaner, G., and RE. Finney. 1977. The effect of nitrogen fertilization on the expression of
slow-mildewing resistance in knox wheat. Phytopathology 67: 1051-1056.

Song, Q.J., L.F. Marek, R.C. Shoemaker, K.G. Lark, V.C. Concibido, X. Delannay, J .E.
Specht, and RB. Cregan. 2004. A new integrated genetic linkage map of the soybean.
Theor. Appl. Genet. 109:122-128.

Van Ooijen, J .W., and RE. Voon'ips. 2001. JoinMap® Version 3.0, Software for the
calculation of genetic linkage maps. Plant Research International, Wageningen, the
Netherlands.

Wang, D., J. Shi, S.R. Carlson, P.B. Cregan, R.W. Ward, and B.W. Diers. 2003. A
low-cost, high-throughput polyacrylamide gel electrophoresis system for genotyping
with microsatellite DNA markers. Crop Sci. 43:1828-1832.

Wang, 8., OJ. Basten, and Z.-B. Zeng. 2005. Windows QTL Cartographer 2.5.
Department of Statistics, North Carolina State University, Raleigh, NC.
(http://staLtgen.ncsu.edu/qtlgrt/WOTLCaLrthtm).

Wrather, J .A., T.R. Anderson, D.M. Arsyad, J. Gai., L.D. Ploper, A. Porta-Puglia, H.H.

Ram, and J .T. Yorinori. 1997. Soybean disease loss estimates for the top 10 soybean
producing countries in 1994. Plant Dis. 81:107-1 10.

54

APPENDIX

55

0.0

6.2

30.2

A1

 

$811471

 

$311300

 

 

 

$311648

0.0

8.2

 

 

 

 

$811187 0.0

$311424

11.7

14.4

39.0

 

 

 

 

 

 

Sa11233 0.0
$811327
$311329

21 .2
8811209

32

3311467

 

 

 

$811168

 

0.0

20.2

 

 

 

 

SattZ72

AW620774

Figure 1. Linkage maps of 94 F2-derived lines from cross P1391589 B and IA 2053

constructed using JoinMap 3.0 with a LOD grouping threshold 3.0. The linkage groups
were named according to Song et al. (2004) and the map distances between the markers
are given in cM (centiMorgans).

56

Figure 1. (cont’d)

 

 

 

 

 

 

 

C1 D1a
no anus on emwz
an smcwna
m5 same
351% sums
24.2 / \ SattO77

0.0

12.8

 

 

 

 

85021153

8311698

57

DZ

$311669

 

0.0

3811166

 

35.0

82111672

 

“A

55.7 N
57.3 /

 

/ $311256
\ $811386

 

 

63.4

Scl_1 37

ima/
1%5/

Satt384

 

0.0

 

12.1

18.1~—
20.7““

8811411

r' $811651
N $811720

$811212

 

312

MA~~

’- $811512

 

76.2

 

86.5

92.7 \
95.8 ~
98 2 ’

llll

 

8811606

/ $811699
- Satt706
\ Satt491
\ $311263
\ $311185

 

Satt483

 

116.2

BR347343

Figure 1. (cont’d)

F+l

 

0.0

 

11.1

 

 

 

16.6

$311149

$811419

AW186493

0.0

28.6

 

 

 

 

$811423

$811239

0.0

41.8

 

 

 

 

 

$811330

$811292

GMLPSIZ

58

0.0

10.0

13.7
17.0

39.7
42.9

 

 

 

 

 

 

 

 

$811533

$811427

Satt704
$511594

$811288
$811612

0.0

10.2
13.7

19.6

35.7

78.6

 

 

 

 

 

 

 

 

$811380

$811621
$811620

Sat_366

$811547

Sat_396

Figure 1. (cont’d)

0.0

1 3.5

18.1

23.7

 

 

 

 

 

 

Satt1 67

$811264

$811326

$811628

0.0

6.5

16.5

 

 

 

 

 

SattZBO

$811475

Sat_243

 

0.0

 

6.3

 

14.4

 

20.4

 

30.0

 

 

 

43.3

59

 

$311652 0.0 Sact_D1 O

Satt398

Satt143

 

 

 

1 6.6 3811561

881161 3

Satt238

AW508274

Figure 1. (cont’d)

 

 

 

M+02
o.o Satt201
37.8 Sanzae

 

(10

833

1315

 

 

 

 

 

Sau245

Saneze

838536

01)

215
119

 

 

 

 

60

 

San576 (to

Safi188
Sauces

161!

3215

 

 

 

 

 

Slfi592

San581

Slfl153

A1 82 C1 D1 b D2

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

0.0 Sa11526 0.0 Satto70 0.0 Sa11294 0.0 Satt266 0.0 Satt669
2.8 838449
5.1 85111364
6.7 Satt438
11.0 $811556
16.3 Sat_327
17.2 Sa11574
20.3 SattZQO 20.4 $311662
24.3 Satt'579
26.6 $811514
29.2 Satta11

 

 

 

Figure 2. Linkage maps of 140 F4-derived lines from cross Asgrow 2506 and NKS 19-90
constructed using JoinMap 3.0 with a LOD grouping threshold 3.0. The linkage groups
were named according to Song et al. (2004) and the map distances between the markers
are given in cM (centiMorgans).

61

Figure 2. (cont’d)

 

 

 

 

G+D1a
0.0 51111275 60
1 .3
8.9
1 1.1 Satt468

 

 

 

 

 

 

 

 

 

N
Satt142 0.0 $811152 0.0
838293
37
6.6 8311530
538317

62

 

 

 

 

3811479

85111550

Table 1. Information about all polymorphic simple sequence repeat (SSR) markers from
F2-derived population of PI 391589B X IA 2053

 

 

 

 

 

 

 

Marker Own ma Inte ted . . . . 2 Significant
name (cM) P map $221M” a.h.b Mrssrng X levelzl:
Linkage Group Al

Satt471 0.0 28.0 27:47:17 0 2.3 -
Satt300 6.2 30.9 30:42: 19 0 3.2 -
Satt648 30.2 59.2 26:46:17 2 2.0 -
Linkage Group A2

Sattl87 0.0 54.9 19:54:18 0 3.2 -
Satt424 8.2 60.6 18:54: 19 0 3.2 -
Linkage Group A2

Satt233 0.0 100.1 20:47:24 0 0.5 -
Satt327 11.7 109.9 17:49:25 0 2.0 -
Satt329 14.4 1 10.9 20:44:26 1 0.9 -
SattZ09 39.0 128.4 18:42:31 0 4.2 -
Linkage Group B2

Satt467 0.0 17.8 24:51:16 0 2.7 -
Sattl68 21.2 55.2 19:57:15 0 6.1 *
Linkage Group BZ

SattZ72 0.0 71.7 20:50: 19 2 1.4 -
AW620774 20.2 90.3 18:50:19 4 2.0 -
Linkage Group C1

Sct_186 0.0 9.0 37:29:16 9 17.3 1'"
SOYGPATR 8.4 10.3 26:39:25 1 1.7 -
Linkage Group D1a

Satt402 0.0 57.8 16:42:32 1 6.0 -
Sattl98 21.3 68.6 16:52:23 0 2.9 -
Satt468 23.5 69.9 16:50:25 0 2.7 -
SattO77 24.2 77.5 16:47:24 4 2.1 -
Linkage Group le

BE021153 0.0 30.2 19:44:27 1 1.5 -

Satt698 12.8 38.0 29:36:25 1 3.9 -

63

Table l. (cont’d)

 

 

 

 

 

 

Marker Own map Integrated . _ . . 2 Significant
name (cM) map (cM) a.h.b Mrssrng X level
Linkage Group D2

Satt669 0.0 67.7 51:1 1:25 4 62.1 ***
Sattl86 35.0 105.5 22:45:24 0 0.2 -
Satt672 49.4 1 15.0 20:45:22 4 0.3 -
Sat1256 55.7 124.3 22:49: 19 1 1.0 -
Satt386 57.3 125.0 ‘ 22:51:18 0 1.7 -
Sct_137 63.4 129.0 19:56:14 2 6.4 *
Linkage Group E

Satt384 0.0 19.3 48: 19:23 1 42.6 “*
Satt411 12.1 12.9 27:39:24 1 1.8 -
Satt651 18.1 32.1 14(a):60(c) 17 1.5 -
Satt720 20.7 20.8 22:42:26 1 0.8 -
Satt212 31.2 32.3 28:43:20 0 1.7 -
Satt512 55.4 ? 23:39:28 1 2.2 -
Satt685 58.1 56.7 24:21 :24 22 10.3 **
BR347343 76.2 ? 25:44:21 1 0.5 -
Satt606 86.5 39.8 29:34: 14 14 6.8 *
Satt699 92.7 41.2 29:45:17 0 3.2 -
Satt706 95.8 43.4 28:38:25 0 2.7 -
Satt491 98.2 43.6 30:37:19 5 4.4 -
Satt263 101.3 45.4 36:36:19 0 10.1 **
SattlSS 105.6 44.8 30:36:24 1 4.4 -
Satt483 116.2 45.0 20:40:29 2 2.7 -
Linkage Group F+I

Satt149 0.0 18.1(F) 26:33:32 0 7.5 *
Satt419 11.1 21.9(1) 29:38:23 1 3.0 -
AW186493 16.6 21.0(F) 32:34:22 3 6.7 *
Linkage Group F+I

Satt423 0.0 20.6(F) 27:46:17 1 2.3 -
Satt239 28.6 36.9(I) 24:48:16 3 2.2 -
Linkage Group I

Satt330 0.0 77.8 21:9:61 0 68.1 "*
Satt292 26.8 82.8 22:48:20 1 0.6 -
GMLPSI2 41.8 97.0 22:45:21 3 0.2 -

 

Table l. (cont’d)

 

 

 

 

 

 

 

 

Marker Own map Integrated . . . . 2 Si gnificant
name (cM) map (cM) a.h.b Mrssrng X level
Linkage Group G

SattS33 0.0 56.5 23:37:28 3 2.8 -
Satt427 10.0 51.7 26:39:25 1 1.7 -
Satt704 13.7 ? 28:39:23 1 2.2 -
SattS94 17.0 52.9 25:40:23 3 0.9 -
Satt288 39.7 76.8 18:44:21 8 0.6 -
Satt612 42.9 80.4 18:50:21 2 1.6 -
Linkage Group J

SattB80 0.0 43.1 19:52:20 0 1.9 -
Satt621 10.2 ? 19:41 :26 5 1.4 -
Satt620 13.7 ? 21:47:23 0 0.3 -
Sat_366 19.6 52.7 21:42:27 1 1.3 -
Satt547 35.7 67.7 22:45:23 1 0.1 -
Sat_396 78.6 69.0 4: 17:70 0 127.3 "*
Linkage Group K

Sattl67 0.0 45.7 34:23:19 15 17.2 1”"
SattZ64 13.5 46.2 24:42:25 0 0.6 -
Satt326 18.1 49.5 24:46:21 0 0.3 -
Satt628 23.7 49.6 18:46:21 6 0.9 -
Linkage Group K

Satt260 0.0 80.1 14:51 :23 3 4.0 -
Satt475 6.5 78.7 16:46:27 2 2.8 -
Sat_243 16.5 86.8 ' 23(b):57(d) 1 1 0.7 -
Linkage Group L

Satt652 0.0 30.9 23:20: 13 35 7.9 *
Satt398 6.3 30.6 19:47:25 0 1.0 -
Satt143 14.4 30.2 31:38:17 5 5.6 -
Satt613 20.4 36.1 26:36:21 8 2.1 -
SattZ38 30.0 19.9 24:48:19 0 0.9 -
AW508274 43.3 38.8 30:42:16 3 4.6 -
Linkage Group L

Sct_010 0.0 59.5 31:40: 19 l 4.3 -
Satt561 16.6 71.4 28:36:17 10 4.0 -
Linkage Group M+C2

Satt201 0.0 13.6(M) 26:47:17 1 2.0 -

Satt286 37.8 101.8(C2) 20:52:19 0 1.9 -

65

Table l. (cont’d)

 

 

 

Marker

Own map Integrated map . . . . 2 Significant
name (cM) (cM) a.h.b Mrssrng X level
Linkage Group M
Satt245 0.0 53.5 24:36:27 4 2.8 -
Satt626 8.3 58.6 19:44:17 11 0.9 -
Satt536 13.5 62.1 21:43:25 2 0.5 -
Linkage Group 0
SattS76 0.0 55.8 22:47:21 1 0.2 -
Sattl88 2.5 55.6 22:45: 19 5 0.4 -
Satt633 3.9 56.9 25:45:20 1 0.6 -
Linkage Group 0
SattS92 0.0 100.4 26:46: 18 1 1.5 -
Satt581 16.8 106.0 27:36:23 5 2.7 -
SattlSB 32.5 128.4 24:46:20 1 0.4 -
Unlinked Group
Sat_217 101.6(A1) 20:46:21 4 0.3 -
Satt359 102.6(B1) 24:39:28 0 2.2 -
Satt294 _ 78.6 (C1) 19:49:23 0 0.9 -
Satt476 80.6 (C1) 17:45:15 14 2.3 -
Satt338 123.8 (C1) 26:50:15 0 3.6 -
Satt227 26.6 (C2) 15:53:23 0 3.9 -
Satt422 44.7 (C2) 24:42:25 0 0.6 -
Satt322 82.2 (C2) 15:53:23 0 3.9 -
Satt433 128.2 (C2) 27:46:18 0 1.8 -
Satt408 . 14.2(Dla) 24:48:19 0 0.8 -
Satt353 8.5 (H) 32:32:27 0 8.6 *“
SattS4l 53.4 (H) 22:47:22 0 0.1 -
Satt674 16 (J) 18:34:12 27 1.4 -
Satt715 0.9 (K) 21:50:20 0 0.9 -
Satt513 106.4 (L) 65:0:25 1 125.6 ***
Sct_195 2.4 (N) 26:35:17 13 2.9 -
Satt358 5.4 (0) 20:49:21 1 0.7 -
Satt445 20.4 (0) 3:29:58 1 78.6 ”*
SattOS4 ? 16:42:27 6 2.9 -
SattO59 ? 17:45:29 0 3.2 -
Satt108 ? 23:42:26 0 0.7 -

 

1' “2” means no position available on the soybean composite map.
It “-” means not significant at 0.05 probability level; *, ", and *" means Significant at
the 0.05, 0.01, and 0.001 probability levels, respectively.

66

Table 2. Information about all polymorphic simple sequence repeat (SSR) markers from
F4-derived population of Asgrow 2506 X NKS 19-90

 

 

 

 

 

 

 

 

 

 

 

Marker Own map Integrated . . . . 2 Significant
name (cM) map (cM)1' a.h.b Mrssrng X levelil:
Linkage Group A]

SattSZ6 0.0 28.0 68:5:63 4 9.9 **
Satt449 2.8 27.8 64: 17:56 3 0.5 -
Satt364 5.1 29.0 64:11:61 4 2.5 -
Linkage Group B2

Satt070 0.0 72.8 61 :8:64 7 5.2 -
Satt438 6.7 ? 67:21:50 2 3.3 -
SattSS6 11.0 73.2 76:7:53 4 11.2 **
Linkage Group C1

Satt294 0.0 78.6 44:35:58 3 23.0 ***
Sat_327 16.3 ? 66:0:60 14 18.3 "*
Linkage Group le

Satt266 0.0 59.6 81 :6:53 0 15.0 1'"
SattZ90 20.3 73.3 67:5:57 11 9.7 **
Satt579 24.3 75.9 72: 16:50 2 4.1 -
Linkage Group D2

Satt669 0.0 67.7 66:9:63 2 4.6 -
Satt574 17.2 87.7 59:9:70 2 5.5 -
Satt662 20.4 87.9 61:12:61 6 1.5 -
Satt514 26.6 85.7 56:35:49 0 20.4 **"'
Satt311 29.2 84.6 50:33:56 1 16.4 ***
Linkage Group G+Dla

Satt275 0.0 2.2 (G) 53:15:72 0 3.4 -
Satt468 11.1 69.9(D1a) 55: 12:73 0 4.6 -
Linkage Group H

Sattl42 0.0 86.5 65:4:71 0 12.2 **
Satt293 1.3 89.1 65:4:68 3 11.6 **
Satt317 8.9 89.5 64:9:63 4 4.3 -
Linkage Group N

Satt152 0.0 22.7 58:2:65 15 14.0 "'*"'
SattS30 6.6 32.8 66:8:63 3 5.6 -
Linkage Group 0

Satt479 0.0 54.2 56:2:80 2 20.2 ***

SattSSO 3.7 55.1 50:10:77 3 9.5 *"‘

67

Table 2. (cont’d)

 

 

Marker Own map Integrated a:h:b Missing X2 Srgmficant
name map (cM) level
Unlinked Group
Satt545 71.4 (A1) 66:15:58 1 0.9 -
GMENODZB 58.4 (A2) 68:0:55 17 19.1 1'"
Satt409 145.6(A2) 68:1 :49 22 18.1 ***
SattS60 97.9 (B2) 76:5:59 0 12.6 ‘1'
Sattl80 127.8(C1) 55:3:69 13 13.7 **
Satt316 127.7(C2) 63:23:54 0 2.6 -
Satt371 145.5(C2) 54:26:56 4 5.5 -
Sattl98 52.3(Dla) 65:20:55 0 1.2 -
Sctt008 3.2 (D2) 56:17:67 0 1.0 -
Satt002 47.7 (D2) 62:5:50 23 8.6 *
Satt464 89.8 (D2) 67:19:49 5 3.0 -
Satt252 16.1 (F) 60:14:65 1 1.0 -
Satt114 63.7 (F) 63:11:65 1 2.7 -
Sat1570 12.7 (G) 52:2:51 35 10.8 **
Satt115 43.8 (G) 58:8:65 9 5.3 -
SattZBS 76.8 (G) 64:11:57 8 2.5 -
Satt451 20.3 (I) 55:8:73 4 8.2 *
Satt475 78.7 (K) 56:11:73 0 5.1 -
Satt523 27.9 (L) 70:16:54 0 2.2 -
Satt448 64.7 (L) 66:10:61 3 3.6 -
Satt373 107.2 (L) 60:24:49 7 4.8 -
Satt463 50.1 (M) 61:14:60 5 0.6 -
Satt308 130.8 (M) 77:9:46 8 12.2 **
Satt257 92.6 (N) 67:8:59 6 5.8 -
Satt445 20.4 (0) 69: 13:57 1 2.4 -
Satt120 ? 58(b):77(c) 5 0.0 -
SattS 12 ? 71:10:59 0 4.8 -
i146 ? 73:4:56 7 13.4 **

 

1' “?” means no position available on the soybean composite map.

:1: “-” means not significant at 0.05 probability level; *, **, and 1‘" means Significant at

the 0.05, 0.01, and 0.001 probability levels, respectively.

68

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