STRESS-INDUCED GERMINATION VIGOR AND ITS TRANSLATION TO SEEDLING
VIGOR IN BETA VULGARIS L.
By
Rachel P. Naegele

A THESIS
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
MASTERS OF SCIENCE
Plant Breeding, Genetics and Biotechnology- Crop and Soil
2010

ABSTRACT
STRESS-INDUCED GERMINATION VIGOR AND ITS TRANSLATION TO SEEDLING
VIGOR IN BETA VULGARIS L.
By
Rachel P. Naegele
Beta vulgaris L., sugarbeet, is an important plant for sucrose production in the U.S. and
worldwide. One limitation for sugarbeet production is poor germination. Breeding for improved
germination and seedling vigor has been unsuccessful due to low heritability of traits controlling
germination vigor, few molecular markers and high environmental variability. Germination and
seedling responses to stress in two beet varieties with differing vigor were studied in hydrogen
peroxide and water. Differences in water absorption and internal hydrogen peroxide
concentrations were observed between varieties. Gene expression changes were identified
qualitatively (343 genes) and quantitatively (48 genes) during germination. In both varieties,
germination was characterized by a rapid uptake of water and rapid gene activation within the
first 24 h of imbibition. Upregulation of putative LTP4 (lipid transfer protein), MPK4 (MAP
Kinase 4), BRI1 (Brassinosteroid 1), and MKK9 (MAPK Kinase 9) was associated with response
to H2O2. The 48 genes, tested for expression in germination vigor, were evaluated for their
ability to predict vigor in 3-week old seedlings of the same two varieties. Gene expression of
seedlings treated with H2O, Aphanomyces sp., or Rhizopus sp. had different quantitative and
temporal expression patterns depending on the variety and treatment. BRI1 and CAF1 (CCR4NOT Associated Factor) were upregulated in both varieties in response to pathogen treatments.
Of the 48 genes quantitatively tested between seeds and seedlings, varieties and the stress
treatments, only BRI1, LTP4 and MKK9 were consistently upregulated. These genes may be
useful as molecular markers for breeding efforts to enhance seedling vigor.

ACKNOWLEDGEMENTS

I am very grateful to Dr. J. Mitchell McGrath, my major professor and advisor, for his
tireless support, constructive criticism, and the many opportunities he has created for me to grow
and develop as a scientist.
I sincerely thank the many people in the USDA-ARS Sugarbeet and Bean Research Unit who
have helped me throughout my work. Particularly I extend my thanks to Dr. Linda E. Hanson for
her guidance, critical feedback, and patience. Special thanks also to Tim Duckert for field help,
Leah Granke and Lina Quesada for manuscript review, Ray Lindsey, Jillian Waxmonsky and
Azeza Bughrara for laboratory assistance and R. Scott Shaw for keeping the lab organized.
Thank you to the members of my committee: Drs. Sheng Yang He and Janet M. Lewis for
their critical analysis of my work, inspirational ideas, and encouragement.

iii

TABLE OF CONTENTS
LIST OF TABLES ........................................................................................................................ v
LIST OF FIGURES .................................................................................................................... vii
LITERATURE REVIEW ............................................................................................................ 1
LITERATURE CITED .......................................................................................................... 12
CHAPTER I: INDUCTION AND IDENTIFICATION OF STRESS-INDUCED GENES
ASSOCIATED WITH GERMINATION VIGOR IN BETA VULGARIS ............................. 19
ABSTRACT ............................................................................................................................. 19
INTRODUCTION................................................................................................................... 20
MATERIALS AND METHODS ........................................................................................... 23
RESULTS ................................................................................................................................ 27
DISCUSSION .......................................................................................................................... 49
LITERATURE CITED .......................................................................................................... 58
CHAPTER 2: EARLY SEEDLING RESPONSE TO WATER AND PATHOGEN STRESS
AND THE IDENTIFICATION OF VIGOR RESPONSE GENES IN BETA VULGARIS . 64
ABSTRACT ............................................................................................................................. 64
INTRODUCTION................................................................................................................... 65
MATERIALS AND METHODS ........................................................................................... 68
RESULTS ................................................................................................................................ 70
DISCUSSION .......................................................................................................................... 84
LITERATURE CITED .......................................................................................................... 94
APPENDIX A: SUPPLEMENTARY TABLES ..................................................................... 101

iv

LIST OF TABLES
Table 1.1 Water absorption over time in fruited seeds and embryos of ACH185 and SP7622
in hydrogen peroxide and water ............................................................................................ 29
Table 1.2 The proportion of internal fungi present after surface disinfesting seeds of
ACH185 and SP7622 ............................................................................................................ 30
Table 1.3 Number of ACH185 and SP7622 seeds germinated (out of 50) in water and
hydrogen peroxide over time ................................................................................................ 30
Table 1.4 Internal hydrogen peroxide concentrations for embryos of ACH185 and SP7622
over time in water ................................................................................................................. 32
Table 1.5 Germination genes, shared at a specific time between the treatments that resulted
in germination, SP7622 H2O2 and H2O treatments and ACH185 H2O2 treatment. Genes
highlighted in green were shared with the imbibition list at a different time. Genes not
highlighted were specific to germination using RT-PCR ..................................................... 35
Table 1.6 Imbibition genes, present in both varieties and treatments at a specific time using
RT-PCR. Genes in green were also present in the germination list at an earlier time point.
Genes in pink were present in the hydrogen peroxide vigor gene list at an earlier time point.
Genes not highlighted were specific to imbibition ............................................................... 36
Table 1.7 Genes shared between treatments and varieties at a specific time using RT-PCR.
Hydrogen peroxide induced vigor genes, genes shared between both varieties in the
hydrogen peroxide treatment at a specific time. Genes highlighted in pink were also present
at one time point in the imbibition list. ................................................................................. 39
Table 1.8 Quantitative gene expression (relative fold change) over time in ACH185 and
SP7622 in H2O and H2O2 treatments during the first 24 hours of germination. Light pink
denotes a fold change <3. Blue indicates a fold change >3 and <10. Purple indicates a fold
change >10. Gray squares indicate the relative expression was not calculated because of a
lack of expression in the control treatment and nd indicates the gene was not detected ...... 44
Table 1.9 Genes in ACH185 associated with hydrogen peroxide-induced vigor over time
using qPCR ........................................................................................................................... 50
Table 1.10 Genes associated with hydrogen peroxide-induced vigor in SP7622 over time
using qPCR ........................................................................................................................... 50

v

Table 2.1 Quantitative gene expression (fold change) over time of 3 wk seedlings of
ACH185 and SP7622 and the Aphanomyces cochlioides, Rhizopus sp. and H2O treatments.
Light pink denotes a fold change <3. Blue indicates a fold change >3 and <10. Purple
indicates a fold change >10. Gray squares indicate the relative expression was not
calculated because of a lack of expression in the control treatment and nd indicates the gene
was not detected .................................................................................................................... 71
Table 2.2 Genes upregulated and associated with response to Aphanomyces cochlioides and
Rhizopus sp. treatment over time in ACH185 using qPCR .................................................. 76
Table 2.3 Genes upregulated and associated with response to Aphanomyces cochlioides and
Rhizopus sp. treatment over time in SP7622 using qPCR .................................................... 78
Appendix Table 1.1 Sugarbeet ESTs with sequence similarity to Arabidopsis proteins
involved in stress response, hormone biosynthesis, and growth used for primer design.
Sequences and primers in bold were used for qPCR analyses............................................ 102
Appendix Table 1.2 Genes detected in both SP7622 and ACH185 in mature untreated
seeds (0 hours) prior to H2O or H2O2 treatment ............................................................... 115
Appendix Table 1.3 Genes present in SP7622 and not ACH185 in mature seeds (0 h) prior
to treatment using RT-PCR................................................................................................. 117
Appendix Table 1.4 Genes present in ACH185 and not SP7622 in mature seeds (0 h) prior
to treatment using RT-PCR................................................................................................. 120
Appendix Table 1.5 K-means grouping of 343 putative stress, growth and hormone related
genes in ACH185 cDNA over the first 24 hours of germination time points in H2O and
H2O2 ................................................................................................................................... 121
Appendix Table 1.6 K-means grouping of 343 putative stress, growth and hormone related
genes in SP7622 cDNA over the first 24 hours of germination time points in H2O and H2O2
............................................................................................................................................. 130

vi

LIST OF FIGURES

Figure 1.1 Single seeds of ACH185 A) fruited, unpolished seed and B) fruited seed with
the seed cap removed showing the embryo inside. Single seeds of SP7622 C) fruited,
semi polished seed and B) fruited seed with the seed cap removed showing the embryo
inside. (Orange scale bar is in mm). [For interpretation of the references to color in this
and all other figures, the reader is referred to the electronic version of this thesis.] ........ 30
Figure 1.2 K-means groupings of A) ACH185 and B) SP7622 in H2O and H2O2 using
RT-PCR over the first 24 hours of germination. Purple indicates presence of a particular
transcript and green indicates absence ............................................................................. 44
Figure 2.1 Roots of ACH185 (A-C) and SP7622 (D-F) prior (0 h) (A, D) and post (1 wk)
treatment with Aphanomyces cochlioides (B, E) or Rhizopus sp. (C, F) .......................... 85

vii

LITERATURE REVIEW
Beta vulgaris L. belongs to the plant family Amarantheaceae, sub family Chenopodiaceae, in
the order Caryophyllales (Kadereit et al. 2003). Amaranthaceae is a large (2,500 species) and
diverse (180 genera) family with nutritionally important crops such as amaranth (Amaranthus
cruentus), a high-protein grain and a calcium-rich leaf grown in the Americas, spinach (Spinacia
oleracea), a well-known leafy vegetable used as an iron source, and quinoa (Chenopodium
quinoa), a protein-rich staple crop of the indigenous people of southern South America (Bewley
1997). Some well-known noxious weed species including Lambsquarter (Chenopodium album),
Redroot Pigweed (Amaranthus retroflexus), Tumbleweed (Amaranthus albus) and Kochia
(Kochia sp.) are also members of this family (Muller 2005).
The Amarantheaceae is known for its diversity of plant species, its ability to tolerate stress,
and the production of unique substances. Members produce the pigment betalain in place of
anthocyanin, some produce squalene oil, an oil traditionally found in shark livers used for cancer
treatment, and some members are halophytic and tolerant of suboptimal conditions when adults
(Cai et al. 2005; Dini et al. 1992; Flowers 1972; Ryan et al. 2007; Strack et al. 2003). These
scientifically interesting and economically useful characteristics have renewed interest in
Amaranthaceae, in particular the Chenopodiaceae, for medicines, biofuels, land reclamation, and
dyes, in addition to their current uses. In the Chenopodiaceae, the genus Beta is economically
important. One of the species within the genus Beta, B. vulgaris L., can be divided into the four
crop groups, sugarbeet, table beet (or red beet), swiss chard and fodder beet, and the wild and
weedy relatives (B. vulgaris spp. maritima and B. vulgaris spp. macrocarpa) (Arnaud et al.
2010; Driessen et al. 2001; Fenart et al. 2008; Panella and Lewellen 2007).
1

Annual weedy and wild members of Beta vulgaris are found along coastlines throughout
Italy and Greece, the Middle East and Northern Africa (Draycott 2006). Beta vulgaris is thought
to have originated along the Mediterranean coast, and fossil records of beet roots, flowers and
leaves suggest that some part of beets have been consumed since the Neolithic age. The earliest
written records of consumption and possible cultivation of Beta vulgaris stem from Babylon (8th
century) (Zohary 2000). Present day, cultivated Beta vulgaris L. spp. vulgaris is divided into
three separate market classes based on their morphology: vegetable, ornamental and row crops.
Chards, also known as leaf beets, are grown for their nutrient-rich leaves and fleshy petioles.
Chards have small, fleshy roots and contributed the extra alleles to give the sugarbeet its high
sucrose levels (Draycott 2006; Fischer 1989). Chards are grown as both a vegetable and an
ornamental crop. Table beets are harvested early during development and have small, round
roots with lower sucrose content (Draycott 2006). Table beet’s roots are mostly red or yellow in
color; though specialty beets, e.g. Chioggia, have red roots with white rings. Table beets are
primarily grown as a vegetable crop. Root shape, color and size are the main morphological
differences between table, fodder, and sugar beets. Fodder beets, grown for animal feed, have a
long, conical, yellow or orange root that contains low quantities of sucrose. Sugarbeet has a long,
white, conical taproot that contains, on average, 18% sucrose (Lohaus 1994). Sugarbeet and
fodder beets are grown as a field crops unlike red beets and chards. Seeds are planted in early
spring and roots are machine-harvested late in the season to maximize sucrose accumulation
(Scott et al. 1973).
Originating in Eastern Europe in the 1700s, the sugarbeet was likely the progeny of a cross
between a table beet (or fodder beet) and a chard (Fischer 1989). The chemical composition of
the sweetener and its identification as sucrose occurred in the 1740s, but it wasn’t until the 1800s
2

that sugarbeets were marketed and grown as an alternative source of cane sugar in Europe (Ali
2004). Sugarbeet, a temperate annual crop, provided a local alternative to the importation of
sugarcane from tropical and subtropical regions of South America and Asia. Modern sugarbeet is
grown throughout the Great Lakes region and the western United States, Italy, France, Germany,
Russia, Turkey, and the Ukraine as a sucrose source (FAO 2005). Beet sugar accounted for
approximately 50% of the sucrose consumed in the United States in 2008 and 25% worldwide
(Khan 2010). In Michigan, the sugarbeet industry harvested 149,000 acres of sugarbeets worth
$140 million dollars in 2008 (National Agricultural Statistics Service).
Low germination, weeds, and an array of diseases work together to reduce the profitability of
this crop. Many of the chemical inputs required to control weed species can also damage the beet
crop, since many of the common weeds, e.g. Lambsquarter and pigweed, are in the same family
(Chenopodiaceae) as sugarbeet (Wille and Morishita 1999). Preemergence herbicides are used to
reduce weed pressure prior to germination and postemergence control requires timely micro-rate
treatments. In 2008, Monsanto (St. Louis, MO, USA) released RoundUp Ready sugarbeets,
which contain glyphosphate resistance. This allowed growers to control weeds by using the
herbicide RoundUp, a broad-spectrum glyphosate herbicide. 80% of the sugarbeets grown in the
U.S. in 2008 were RoundUp Ready, decreasing costs associated with herbicide sprays for weed
control, while increasing fees associated with seed technology (Kemp et al. 2009; Khan 2008).
RoundUp Ready varieties do not necessarily have the same level of seedling and adult disease
resistance to abiotic and biotic stresses as the non-genetically modified varieties.
Disease resistance is important at both the seedling and adult stage. Rhizoctonia solani,
Cercospera beticola and Rhizopus spp. are examples of pathogens that cause adult and post
harvest diseases that can cause major economic losses if left untreated. In adult sugarbeets,
3

diseases are controlled through carefully timed fungicide sprays and selective breeding, though
losses still occur (Campbell and Klotz 2006; Draycott 2006; Kiewnick et al. 2001; McGrann et
al. 2009; Stevens 2007). Aphanomyces cochlioides, Pythium spp. and Rhizoctonia solani. are
examples of pathogens that can cause sugarbeet seedling death, resulting in devastating stand
losses if left untreated, and at times even when treated. Resistant germplasm and fungicidetreated seeds are used as preventative methods to reduce seedling damping-off disease incidence.
For the past two centuries, breeding efforts have focused on bringing disease resistance,
sucrose accumulation, biennialism, and storage longevity into cultivated beet from its weedy,
wild, and un-adapted relatives, but germination vigor has been neglected due to its low
heritability (Sedlmayr 1960). Industry members have overcome much of the variability in
germination vigor by using “primed” or “pre-germinated” fungicide-treated seeds, and other
management practices (Bene and Eori 1992; Orzeszko-Rywka and Podlaski 2003). Yet, primed
and treated seeds are only a small proportion of the total seed harvested. Much of the seed
harvested is discarded because seeds are underdeveloped or internal disease concentrations are
too high for a given seedlot (Kadereit et al. 2003). Sugarbeet seed and seedling mortality are two
of the costliest, and possibly unrealized, limitations in sugar beet production (Ali 2004). Even
today, germination in the field ranges from 0 to 100%, with an average of 60% depending upon
field location, weather, and biotic pressures (McGrath et al. 2000). In order to improve
profitability of this crop, methods to enhance germination vigor through mechanical or breeding
means are necessary.
Cytogenetically, the chromosomes in sugarbeet, red beet, and chard are almost
indistinguishable (Nakamura et al. 1991; Biancardi 2005). Most members of this species are
diploid (though some triploid lines have been developed through crosses with artificial
4

tetraploids) and have a base chromosome number of 2n=2x=18. Despite morphological
differences in root size, shape, and color, they are freely inter-crossable (Arnaud et al. 2010;
Schondelmaier and Jung 1997). Beta vulgaris is an outcrossing species with high levels of selfincompatibility. Breakdown of self-incompatibility has been identified, but few inbred lines have
been developed. Breeding efforts rely primarily on population improvement for incorporating
advantageous traits (Biancardi 2005). Most cultivated sugarbeets are hybrids with high genetic
heterogeneity within each population. Sucrose accumulation and disease resistance have been
positively selected using conventional breeding techniques within the species. Breeding efforts to
enhance the germination vigor of seeds have been limited and mostly unsuccessful to date,
possibly due to the high population variance, low heritability, and physical germination
impediments (Sadeghian and Khodaii 1998; Taylor et al. 2003, McGrath et al. 2008).
Wild beets, those found along the Mediterranean coast, are annuals, producing copious
amounts of seeds, which they disperse via ocean currents (Fievet et al. 2007). The true seed of
Beta vulgaris is an oil-based seed, similar to some members of the Brassicaceae. A maternally
derived, carbohydrate-based tissue called the perisperm surrounds the beet embryo and provides
a nutrition source for the emerging seedling. The perisperm takes the place of the endosperm,
present in most other species’ seeds. The true beet seed, consisting of the embryo, perisperm and
a thin, seed coat, is encapsulated in a corky, maternally derived tissue, called the pericarp, which
aids in seed dispersal via water and protects the embryo (Ware 1898, Guja et al. 2010). The
presence of the pericarp makes working with beet seeds difficult, as it is a mechanical
impediment for the germinating seed and a physical barrier for studying germination of the true
seed. Beet propagules, or fruits, are typically multi-germ (multiple embryos or seeds per fruit),
and as few as zero or as many as four or five embryos can germinate from the same propagule.
5

The multi-germ seed characteristic is retained for both chards and table beets. Sugarbeet
production requires a level of uniformity in beet size and shape for machine harvesting that is
unattainable using multi-germ propagules, without extensive thinning. Modern sugarbeet
varieties have been bred to be monogerm (one seed per fruit), a single gene controlled trait
discovered in the late 1940s (Savitsky 1952; Tekrony 1968). With the advent of monogerm seed,
the sugarbeet industry had solved the problem of multiple beets per fruit, but was accosted by the
unforeseen problem of low germination rates.
Certain varieties of sugarbeets exhibit higher levels of germination uniformity and vigor than
others, indicating a genetic basis and control for differences in germination vigor. Increasing
fitness by selecting and propagating vigorous seedlings has been attempted, but due to low
heritability and a presumed multi-component system, the results were not effective. Genetic
variance accounts for less than 30% of the total variation in germination with the remaining 70%
being attributed to the environment (Sadeghian and Khodaii, 1998). Recently, several studies on
the proteomics of dry and germinating seeds, transcript profiles at the same time points, and
molecular assessments of varietal vigor differences have emerged (Catusse et al. 2008a; Catusse
et al. 2008b; de los Reyes and McGrath 2003; de los Reyes et al. 2003; Elamrani et al. 1994;
Elamrani et al. 1992; Hermann et al. 2007; McGrath et al. 2000; McGrath et al. 2008; Sadeghian
and Khodaii 1998; Taylor et al. 2003; Pestsova et al. 2008). In several of these studies H2O2
concentrations and Reactive Oxygen Species (ROS) activated genes were found to be present at
higher levels in germinating seeds than in quiescent seeds or seedlings, and others demonstrated
an increased lipid mobilization and hormone activity associated with the germinating seeds.
Hydrogen peroxide has been known to enhance germination vigor in sugarbeets since the 1960s,
and in other non related species, but few studies have looked at the genetic changes hydrogen
6

peroxide induces to cause vigor (Ishibashi et al. 2010; Sedlmayr 1960; Kim et al. 2010; Sunkar et
al. 2006; Wahid et al. 2007; Wang et al. 2009; Xing et al. 2009; Xing et al. 2008).
de los Reyes and McGrath (2003) demonstrated differences in gene expression between
USH20 (a legacy commercial hybrid that consistently showed good emergence) and ACH185 (a
legacy commercial hybrid with less vigor under similar field conditions). These two varieties had
a difference in germination that could be negated with the application of dilute concentrations of
hydrogen peroxide. Seedling vigor differences were attributed, in part, to differences in the
expression of a putative oxalate oxidase (i.e. BvGLP165, germin-like protein 165) expressed in
the vigorous germinator in H2O. In USH20, the GLP (germin-like protein) was expressed in
water conditions, but was not expressed in ACH185 under the same conditions (H2O) after 96
hours of treatment. In conjunction with the induced GLP expression, an increase in transcripts of
key enzymes in lipid metabolism and the glyoxylate cycle was also observed. This initial
seedling vigor study suggested a genetic basis for germination vigor when seeds were treated
with hydrogen peroxide visible by increased stored lipid reserve mobilization and radical
emergence. This group theorized that the germin-like protein in USH20 might function under
non-stress conditions to produce hydrogen peroxide (plus carbon dioxide) and release calcium
stored in seeds (as calcium oxalate), activating metabolic activity and enhancing vigor. However,
the mechanism by which hydrogen peroxide activated metabolic activity and enhanced vigor was
not addressed in this study.
In 2008, Catusse et al. used a proteomics approach to profile the complement and tissue
specificity of proteins in mature sugar beet seeds (96 hours into germination). This study found a
full complement of proteins involved in the glyoxylate cycle present in the germinating seed,
7

confirming previous work by de los Reyes et al. 2003. Another result of this study was the
prevalence of stress-associated genes, with over 60 chaperones and heat shock proteins (HSPs)
being identified, in addition to ROS induced enzymes. The authors suggested that the prevalence
of ROS defense mechanisms was due to the enhanced oxidative stress during metabolic activity
resumption associated with lipid catabolism in the peroxisomes. This study suggested that
internal H2O2 might be more a byproduct of vigor and not its catalyst.
In other species it has been shown that H2O2 is produced in chloroplasts, mitochondria, and
peroxisomes (Apel and Hirt 2004). H2O2 can regulate ABA catabolism and GA biosynthesis
during germination, act as a signaling molecule, and play multiple other roles in plant
development and stress response (Liu et al. 2010; Van Breusegem et al. 2001). It is both a
byproduct and an instigator of lipid metabolism (Apel and Hirt 2004; Van Breusegem et al.
2001; Vranova et al. 2002). H2O2 is produced upon infection by pathogens and during abiotic
stress, as a signaling molecule, to affect changes in gene expression in the nucleus (Van
Breusegem et al. 2001; Vranova et al. 2002). H2O2 reportedly cross talks with a number of other
signaling molecules and pathways including various hormones that can contribute to the stress
response (Barba-Espin et al. 2010; Brock et al. 2010; Finkelstein et al. 2002; Kucera et al. 2005;
Lu et al. 2002; Shinozaki and Yamaguchi-Shinozaki 2007; Xue et al. 2009). H2O2 can regulate
mitogen-activated protein kinases (MAPKs) and other kinase activity, or can have a more direct
role in regulating stress response genes (Pitzschke and Hirt 2006).
While the role of MAPKs in plant-pathogen and stress interactions are well studied, their role
in activating lipid metabolism, though documented, is still unclear. Multiple studies have shown
8

that the induction or constitutive expression of MAPKs results in higher levels of stress-activated
metabolism and resistance, but the process and pathways are still being unraveled (Brader et al.
2007; Cheong and Kim 2010; Shi et al. 2010; Zhang et al. 2007). While useful for understanding
the genetic control of stress, this information has not been applied as a breeding tool for many
crop species, including Beta vulgaris.
In Beta vulgaris, studies have demonstrated that germination is controlled through dynamic
changes in gene expression and metabolism (Catusse et al. 2008b; de los Reyes et al. 2003;
Pestsova et al. 2008). Many stress-related and metabolism transcripts are present in beets
suggesting the importance of these processes for successful germination under both stress and
non-stress conditions. ROS and stress related transcripts including heat shock proteins, MAP
kinases, and germin-like proteins are all shown to be present during vigorous germination, yet
the number, compilation and function of these genes is still unknown. The morphological and
genetic process of germination, dry seeds to emerged radical, and the differences under stress
and non-stress conditions is yet to be defined. Linking both morphological and genetic
components of germination under multiple conditions is necessary to create an accurate view of
germination and vigor that can be effectively modified and improved.
In summary, despite advances in breeding and chemical controls to enhance germination,
disease control, and sucrose accumulation more work remains to be done. Information on the
genetics behind germination and germination vigor is needed to successfully improve sugarbeet
germination, either through improved breeding lines, marker assisted evaluation, or priming. The
recent protein and transcript information on germinating seeds provides a possible window into
the genetics behind germination vigor. Previous studies have mainly focused on 4 day-old
seedlings, because of the ease of working with seedlings instead of seeds. However, germination
9

tests have shown that members within sugarbeet populations can germinate as early as twentyfour hours into imbibition. To effectively breed and screen for germination vigor, future research
will need to focus on energy mobilization, water absorption, gene expression, and protein
synthesis prior to radical emergence.
The research objective of this thesis was to identify and characterize morphological and
molecular factors associated with vigorous germination and stress during early seedling growth.

10

LITERATURE CITED

11

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Ali MR (2004) Characteristics and production costs of U.S. sugarbeet farms. USDA: Economic
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18

CHAPTER I: INDUCTION AND IDENTIFICATION OF STRESS-INDUCED
GERMINATION VIGOR GENES IN BETA VULGARIS

ABSTRACT
The initial environmental conditions a germinating seed encounters affects the speed and success
of germination, the availability of stored energy reserves to withstand future adverse
environments, and the overall ability of the seedling to flourish. Beta vulgaris seedling and
germination molecular markers to predict vigor are not currently available and little information
exists on the genetics of germination and seedling vigor. Germination is a stressful period of
development, and low dosages of stress can boost metabolism and increase vigor. To understand
differences in seedling vigor under stress and identify markers useful for breeding, typical
germination in water was compared to physiological and gene expression changes in hydrogen
peroxide. Two former commercial varieties with known differences in vigor were germinated in
water and hydrogen peroxide. Physical differences in the total number of seeds germinated and
internal hydrogen peroxide for each variety were observed over 96 h. Rapid imbibition occurred,
and gene expression was measured, between 0 and 24 h for both varieties. Expression patterns of
343 genes related to development and stress were qualified between varieties and treatments. A
subset of forty-eight genes was tested using qPCR to quantify changes in gene expression
between varieties and treatments over time. Lower internal hydrogen peroxide, increased water
absorption, and an upregulation of the stress genes Deadbox and MBF1C were associated with
reduced germination. Higher internal hydrogen peroxide concentrations and upregulation of
putative genes involved in pathogen defense, hormone biosynthesis and lipid transfer were
associated with radical emergence and a response to hydrogen peroxide during germination.
19

INTRODUCTION
Sugarbeet, Beta vulgaris L., is an economically important crop accounting for 50% of the
sucrose consumed in the U.S. and 30% worldwide. Low germination, a production limitation
since the 1940s, is a continuous source of revenue loss. In the field, emergence is highly variable
and can range from 0 to 100% depending upon the variety and environmental conditions. Seed
size, weight and the proportion of corky dried maternal fruit surrounding the seed are highly
variable between and within populations and can contribute to varying levels of vigor and
germination. In addition, processing of the fruit can have an effect on germination and vigor
(Orzeszko-Rywka and Podlaski 2003). The corky fruit surrounding the embryo restricts
germination by acting as a physical barrier, preventing radical emergence and water uptake, and
as a chemical barrier, leaching solutes and inhibitors (Draycott 2006; Hermann et al. 2007;
Taylor et al. 2003).
For sugarbeets, germination vigor is a measurable differential trait between varieties that
ultimately impacts yield, sucrose accumulation, and profitability. From dry seeds, germination is
broken into three physically distinct phases: Phase I is characterized by a rapid uptake in water,
Phase II is a resting stage or plateau, and Phase III is an increase in weight followed by radical
emergence and completion of germination (Bewley 1997). Physiologically, the three phases of
germination include protein synthesis, biochemical activation, and germination. However, these
are not well-defined phases. Germination vigor, or the ability to rapidly complete all three phases
and successfully overcome less than ideal environmental conditions, is a complex heritable stress
response. It has been shown for several plant species that H2O2 can enhance germination vigor
(Barba-Espin et al. 2010; Liu et al. 2010; McGrath et al. 2000; Tekrony and Hardin 1969; Wahid
et al. 2007). The mechanism is unclear, but one possibility is that H2O2 is acting as a signaling
20

molecule to activate energy mobilization and germination (Apel 2004; de los Reyes and
McGrath 2003a).
In adult plants, abiotic and biotic stress results in the induction of a number of defense
responses, including cell wall strengthening and energy mobilization (Beckers et al. 2009;
Desikan et al. 2001; Hajheidari et al. 2005; Hu et al. 2006; Hyun et al. 2009; Kim et al. 2007;
Kreps et al. 2002b; Mane et al. 2007; Shinozaki and Yamaguchi-Shinozaki 2007). The treatment
of adult Arabidopsis plants with H2O2 resulted in the activation of a number of pathogen and
drought defense mechanisms, ROS scavenging genes and lipid mobilization units, suggesting the
role of this signaling molecule in stress recognition during the adult phase of development
(Faurie et al. 2009; Hu et al. 2003; Kovtun et al. 2000; Orozco-Cardenas et al. 2001; Ramanjulu
and Bartels 2002; Van Breusegem et al. 2001; Vranova et al. 2002; Yu et al. 2008). During
germination, the exposure to low doses of H2O2 may result in similar responses in the seed.
Defense mechanisms and the additional mobilization of reserves in response to stress would
improve access to heterotrophic resources for the germinating seed, resulting in more rapid
germination. Previous work in sugarbeet demonstrated the importance of H2O2 during
germination, its role on lipid catabolism, and the mobilization of seedling reserves resulting in
seedling vigor (de los Reyes and McGrath 2003; Pestsova et al. 2008). These mobilization events
appear to be instigated by the activation of a germin-like protein gene (BvGLP165), shown to be
activated in a variety with high germination vigor (referred to hereafter as a vigorous variety) but
absent in the a variety with poor germination (non-vigorous variety) measured at 96 hours
(Catusse et al. 2008; de los Reyes and McGrath 2003a). Germination could be induced in the
non-vigorous variety with the addition of a dilute hydrogen peroxide solution, which resulted in
21

increased radical emergence and lipid mobilization similar to the vigorous variety (de los Reyes
and McGrath 2003).
Germin Like Proteins (GLPs) are a large gene family with diverse roles in stress response
and germination (Bernier and Berna 1999; Knecht et al. 2010; Manosalva et al. 2009). Many are
oxalate oxidases, and one functional role is to produce the signaling molecule H2O2. Hydrogen
peroxide accumulation and signaling is also essential for breaking seed dormancy by
upregulating ABA catabolism and GA biosynthesis and inducing lipid metabolism (Liu et al.
2010; Puntarulo et al. 1988; Wahid et al. 2007).
ABA and GA have well documented roles in germination. ABA is essential for maintaining
seed dormancy, is a negative regulator of germination and is also produced in response to
moisture and pathogen stress (Atia et al. 2009; Finkelstein et al. 2002; Kucera et al. 2005).
Components of the ABA-instigated mitogen-activated protein kinase (MAPK) cascade result in
changes in gene expression leading to stomatal closure and pathogen defense. During
germination, ABA-induced MAPK activation can result in decreased germination (through
AtMPK3 and AtMPK6) (Adie et al. 2007; Atia et al. 2009; Liu et al. 2010; Xing et al. 2009).
Other pathogenesis-related hormones, e.g. jasmonic acid and salicylic acid, have been shown to
have a role in germination vigor by activating pathogenesis-related proteins (PR) proteins (Rajiv
and Stanisaw 1992; Seo et al. 2008).
The objectives of this study were to characterize germination through physical changes over
the first 96 h of imbibition (water absorption) and gene expression changes over the first 24 h
(Phase I of germination) under typical conditions (H2O), and atypical germination (H2O2)
conditions.

22

MATERIALS AND METHODS
Germination vigor testing. Two former commercial varieties, ACH185 (EL-A012206) and
USH20 (EL-A012230), and a breeding germplasm, SP7622 (EL-A015030), were chosen for
analyses based from results on previous studies that indicated genetic and visible differences in
vigor (de los Reyes and McGrath 2003a; de Los Reyes et al. 2003b; McGrath et al. 2000).
ACH185 is a triploid, multigerm, CMS (cytoplasmic male sterile) variety with low germination
vigor (<60%) under stress conditions and low field emergence. SP7622 is a diploid, multigerm
variety with high germination vigor (>60%) and high field emergence. Three replicates of fifty
seeds each from ACH185 and SP7622 were placed into 125 mL flasks, and 25 mL of 18 MOhm
H2O or 88 mM H2O2 solution was added. Seeds were shaken continuously at 25 °C under
constant fluorescent light. Seeds with radicals protruding from the fruit were counted as
germinated. Germinated seeds were counted at 24, 48, 72 and 96 h after hydrogen peroxide or
water was added. Germination percentages were calculated from the number of seeds germinated
out of the total.

Water uptake (Imbibition) of B. vulgaris varieties during germination. Seeds from
ACH185 and SP7622 were surface disinfested for 20 min in 0.015% hypochlorate, with Triton
X-100 added as a surfactant, on a shaker at 150 rpm. Seeds were rinsed in 18 MOhm H2O and
allowed to air dry. Dry seeds (35 seeds) for fruited imbibition were placed onto filter paper in
germination boxes with 10 mL of either 0.3% H2O2 or H2O and weighed at 0, 6, 22.5, 30.5, 45.5
52, 70 and 99 h during imbibition grown at 25 °C. Average weight was calculated for each
variety and treatment. Water uptake was measured by the amount of weight gain over time.
23

Individual germination boxes were treated as replicates and seed imbibition and weight was
calculated as the average of the total number of individuals within each box. Embryos were
manually extracted from the dry, fruited seeds by soaking them in H2O for 3 hours, loosening the
seed cap by applying pressure with the cap end of a 15 mL Falcon tube, and lifting out the
embryos using a classic dental pick. Embryos (15 seeds) were treated with 10 mL of H2O and
weighed at 0, 6, 22.5, 30.5, 45.5 52, 70 and 99 h after the start of imbibition. Embryos were
weighed to measure water absorption. Each treatment was replicated three times and the
experiment was repeated twice. Data was analyzed between treatments and varieties using the
NMLE ANOVA function of the R statistical software package (v 2.11.1) and the JMP statistical
software package (v.7) using alpha = 0.05 (SAS Institute Inc 2007; R Development Core Team
2008; Hornik 2010; Pinheiro 2010).
An additional 30 surface disinfested seeds of each accession were plated onto cornmeal agar
to determine the presence of internal fungi and fungal colonies were identified to genus after 5
days (replicated twice).

RNA extraction and cDNA synthesis. Seeds from ACH185 and SP7622 were surface
disinfested as described. Seeds were rinsed in 18 MOhm H2O and allowed to air dry. Fifty seeds
of each accession were transferred to flasks and 25 mL of 18 MOhm H2O or 88 mM H2O2 were
added. Seeds were shaken constantly at 25 °C under constant fluorescent light. Samples were
collected at 0, 1, 3, 6, 12, 18, and 24 h of imbibition (replicated 3 times). Total RNA was
collected using the Macherey-Nagel NucleoSpin RNA Plant kit according to manufacturer’s
protocols (Duren, Germany). cDNA was synthesized using 1 µg of total RNA per reaction and
24

Superscript III reverse transcriptase according to the manufacturer’s protocol (Invitrogen,
Carlsbad, CA). cDNA was diluted to 50 ng/µl for downstream applications.

RT-PCR. Beet Expressed Sequence Tags (ESTs) with a sequence similarity (<e-20 with the
exception of 6 genes with a value > e-20 and < e-3) to Arabidopsis genes with a documented role
in hydrogen peroxide response, growth or hormone biosynthesis were used for oligo synthesis
(Appendix 1.A). Primers were developed using LaserGene PrimerSelect software (DNA Star,
Madison, WI) and synthesized by IDT (Integrated DNA Technologies Coralville, IA). PCR was
performed using the Promega Green GoTaq mastermix according to the manufacturer’s protocol
(Madison, WI). The PCR program had an initial denaturation at 94 °C for 90 s, followed by a
cycle of 94 °C for 30 s, 58 °C for 30 s with a -0.8 °C per cycle, and 72 °C 60 s, repeated 12
times, and an additional program of 94 °C for 30 s, 47 °C for 30 s and 72 °C for 60 s, repeated 30
times and a final 72 °C for 10 m. PCR products were visualized on 2% agarose gels using .002%
ethidium bromide. All 343 genes were clustered into clusters of similar expression patterns using
k-means clustering. Gene expression patterns were grouped into 7 clusters for three variety and
treatment combinations (ACH185 H2O2 and SP7622 H2O and H2O2) and 6 clusters for one
variety and treatment combination (ACH185 H2O) (Cluster 3.0 Stanford University Palo Alto,
CA). K-means clustering was performed using the Euclidean distance and 300,000 iterations.
Clustering was visualized as a modified heat map using Java TreeView (Alok Saldanha, Stanford
University Palo Alto, CA).

qPCR. Quantitative analysis of transcriptional changes in individual gene products were
tested on a subset of 48 genes chosen from qualitative PCR analyses based their predicted roles
25

in abiotic and biotic stress response, hormone biosynthesis, and lipid mobilization in Arabidopsis
seedlings and adult plants. Analyses were performed using quantitative PCR (qPCR) of the
selected genes using the KapaSybr HotStart master mix (Kapabiosystems, Woburn, MA)
according to the manufacturer’s protocol on the Applied Biosystems StepOne Plus thermocycler
(Carlsbad, CA). Relative expression was calculated using the delta delta Ct method (Livak and
Schmittgen 2001). 18s rRNA (BQ589671) was used as the reference gene for analyses, and the
experiment was replicated twice.

Direct peroxide assay of seeds. H2O2 extraction procedures were performed according to
Warm and Laties (1982). 350 seeds of USH20 (EL-A012230) and 350 seeds of ACH185 (ELA012205) were soaked in 100 mL of 18 MOhm H2O at room temperature shaken constantly.
Seeds were started at staggering times to acquire samples at 3, 6, 12, 24, 48, 72, and 96 h
simultaneously. Water was changed daily for seeds soaking for more than 24 h. The seed cap
was manually removed from the seeds and individual embryos were placed in micro-titer plate
wells. Sixty microliters of sterile 18 MOhm water was added into the micro-titer plate wells
containing embryos, and embryos were crushed. After centrifuging (20 m at 12,000 g at 4 °C),
50 µl of the supernatant was transferred to a Victor plate (Perkin Elmer, Waltham, MA). 50 µl of
an H2O2 concentration gradient prepared according to the Amplex Red (10-acetyl-3,7dihydrophenoxazine) Hydrogen Peroxide/Peroxidase Assay Kit (A-22188 Molecular Probes Inc
Eugene, OR) was loaded into the Victor plate. Fifty microliters of the reaction mix (Amplex Red
reagent/HRP working solution) were added to each well. Plates were incubated at 25 °C for 30 m
in the dark. Fluorescence was measured (using a 560 nm excitation filter) at 590 nm and
26

standard curve and hydrogen peroxide concentrations were calculated for each sample. The
experiment was conducted three times.

RESULTS
Phenotypic evaluation of vigor and physical characterization of seed. Differences in the
physical and genetic characteristics of vigor induced by hydrogen peroxide were observed
between the two lines over time. The two varieties chosen for analyses (ACH185 and SP7622)
showed differences in fruit size and weight (Figure 1.1, Table 1.1). True (embryo) dry seed
weights were not statistically different between the two varieties in both experiments. ACH185
had more internal fungal contamination compared to SP7622 after surface disinfestation and
performed poorly, in comparison to SP7622, under the water germination treatment (0 vs. 33
germinated, respectively) (Table 1.2, Table 1.3). These lines performed similarly (31 vs. 40) in
hydrogen peroxide at 96 h, but not at earlier time points. Seeds within each population
germinated as soon as 24 h for SP7622 and 48 h for ACH185 in hydrogen peroxide (13 and 9)
and 24 h for USH20 in H2O. ACH185 had no germination in water at 0 h.
During imbibition of fruited seeds, ACH185 had a greater weight gain on average than
SP7622 (Table 1.1). Imbibition did not consistently significantly differ between treatments for
SP7622 across all time points. ACH185 showed a slight decrease in water-uptake (p = 0.06) in
H2O2 in comparison to the H2O treatment. For both varieties, Phase I, the period of most rapid
water uptake, of germination was completed prior to the first 30 hours measured. Phase II
spanned from 30 to 80 h depending on the variety and treatment and Phase III and secondary

27

Figure 1.1 Single seeds of ACH185 A) fruited, unpolished seed and B) fruited seed with the
seed cap removed showing the embryo inside. Single seeds of SP7622 C) fruited, semi
polished seed and B) fruited seed with the seed cap removed showing the embryo inside.
(Orange scale bar is in mm.)

28

Table 1.1 Water absorption over time in fruited seeds and embryos of ACH185 and SP7622 in hydrogen peroxide and water

Imbibition Experiment 1 Individual Seed wt (mg)
0.0 h
6.5 h
22.5 h
30.5 h
45.5 h
52.0 h
1
2
3
4
4
4
4
4
4
V
Frt
Trt
Avg SD Avg
SD Avg
SD Avg SD Avg SD Avg SD
a
a
a
ab
ab
ab
22
27
28
AC Pre H2O2 12
1
2
1 28
2 29
1
1
b
a
a
b
ab
ab
19
21
20
22
SP Pre H2O2 16
2
4
3
3 23
3
2
a
a
a
a
a
a
12
26
30
32
33
3
AC Pre H2O
1
2
2
2
4
4
b
a
a
ab
b
b
24
27
25
26
26
SP Pre H2O 16
4
7
7
7
7
6
AC Abs
SP

1

5

Abs5

2

V

Frt

AC

Pre

SP
AC
SP

Pre
Pre
Pre

AC Abs

5

SP

5

1

Abs

c

H2O

4

H2O

3

Trt

3

0

c

0

0.0 h
4
Avg SD
b

H2O2

13

H2O2

16

H2O

a

ab

14

b

H2O

14

H2O

2

H2O

2

c
c

0
1
2
2
0
0

6
5

c

0

d

0

7
5

b

0

c

0

c

7

0

d

5

0

c

7

c

7

0

d

5

5

0

ab

31

ab

24

a

36
27

3
7

c

0

d

5

0

1
3

b

7

0

d

70.5 h
4
Avg SD

0

Imbibition Experiment 2 Individual Seed wt (mg)
6.5 h
22.5 h
30.5 h
45.5 h
52.0 h
70.5 h
4
4
4
4
4
4
Avg SD Avg
SD Avg SD Avg SD Avg SD Avg SD
b

24

0

c

21

2

a

30

3

c

21

2

d

4

1

d

4

0

b

27

c

23

a

36

c

22

d

4
4

d

0
2
3
2
1
1

b

28

0.0

bc

25

1.9

a

39

4.0

c

22

1.7

d

4

0.7

d

4

0.6

2

b

31

c

27

a

42

d

23

e

5
5

e

b

31

1

b

27

2

a

42

3

c

23

2

d

5

1

d

5

1
3

0
2
4
2
1
1

b

36

c

28

a

44

c

24

d

5
6

d

1
2
4
2
0
1

99.0 h
4
Avg
SD
a

35

2

a

32

14

a

38

3

a

28

9

b

7

0

b

13

11

99.0 h
4
Avg
SD
b

38

c

28

a

43

c

24

1
2
4
1

d

5

d

6

4

2

Variety AC=ACH185 and SP=SP7622 Fruit is Pre=Fruit present Abs=Fruit absent Treatment Average numbers within a
5

column followed by the same letter are not different at p = 0.05 embryos were analyzed separately. SD is the standard
deviation between replications
29

Table 1.2 The proportion of internal fungi present after surface disinfesting seeds of ACH185 and SP7622
*

Variety
ACH185

Aspergillus
0.02
+
-

SP7622
*

Proportion of fungal contamination
(plated on cornmeal agar after 5 days)
Alternaria
Penicillium
Fusarium
Rhizopus
0.10
0.43
0.15
0.02
-

0.48

-

Trichoderma
0.02

-

-

+

proportion of seeds out of the 30 possible with the fungal contamination indicates that the fungus was not detectable

Table 1.3 Number of ACH185 and SP7622 seeds germinated (out of 50) in water and hydrogen peroxide over time

Variety
ACH185
SP7622
ACH185
SP7622
*

Treatment
H2O

24 h
*
Mean
b

0.00

a

H2O

10.00

H2O2

0.00

H2O2

13.33

b
a

Sugarbeet Germination (Number germinated out of 50)
48 h
72 h
*
*
Mean
Mean
SE
SE
SE
0.00
2.89
0.00
0.88

d

0.00

b

24.33

c

9.00

a

36.33

0.00
4.67
0.58
2.60

c

0.00

ab

31.00

b

27.00

a

39.00

0.00
3.21
5.03
3.06

96 h
*
Mean
b

0.00

a

32.67

a

31.00
40.00

a

SE
0.00
2.91
6.11
3.00

Numbers within a column followed by the same letter are not significantly different at p = 0.05. SE is the standard error between
replications

30

weight gain, due to water absorption or growth, was detected at 72 through 96 h. The time of
most rapid imbibition was 0 to 24 h.
Imbibition differences were compared between seeds of ACH185 and SP7622 that had the
fruit removed in H2O. ACH185 embryos did not complete imbibition significantly faster than
SP7622 (p=0.06). However, there was a significant (p=0.01) increase in the total amount of H2O
absorbed over time by ACH185 embryos compared to SP7622 (7mg vs. 5mg respectively at 22
to 70.5 h). Embryos of both varieties completed Phase I of imbibition after approximately 6 h.
The internal hydrogen accumulation assay revealed differences in H2O2 accumulation
between the two varieties in H2O over time. Individual seeds within each population showed a
range of H2O2 concentrations over time (Table 1.4). Concentrations of H2O2 were
indistinguishable between the two varieties at 3 and 12 h post treatment. Visible differences were
detected at 6, 24, 48, 72 and 96 h; however they were not statistically significant, except at 72 h.
USH20 (the vigorous variety) seed had higher average concentrations of internal H2O2 than
ACH185 (non vigorous variety) seed over the 96 hours monitored.
Genetic evaluation of vigor. For large scale, qualitative gene expression profiling, RT-PCR
was performed on 343 primer combinations developed from sugarbeet ESTs showing sequence
similarity to Arabidopsis stress response, hormone biosynthesis, developmentally regulated and
MAP Kinase genes (Swarbreck et al. 2008) (Table A.1). Genes were scored as present or absent,
and expression fingerprints were created for each variety and treatment. Large genetic
differences were visible between the vigorous (SP7622) and non-vigorous (ACH185) variety and
between treatments (H2O and H2O2) during the first 24 h of imbibition. Out of the possible 343
31

Table 1.4 Internal hydrogen peroxide concentrations for embryos of ACH185 and SP7622 over time in water

V

Frt

AC

Abs

Hydrogen peroxide concentration (µM)
3h
6h
12 h
24 h
48 h
3
4
4
4
4
4
Trt Avg
SD Avg
SD Avg
SD Avg
SD Avg
SD
a
a
a
a
a
H2O 1.32 0.22 1.19 0.12 1.22 0.25 1.10 0.16 0.90 0.00

SP

Abs

H2O

1

1

2

a

1.18

a

1.73

0.10

0.36

a

1.41

0.09

2

a

1.81

0.19
3

a

1.50

0.12
4

72 h
4
Avg
SD
b
0.59 0.15
1.48

a

0.45

96 h
4
Avg
SD
a
0.63 0.24
a

1.25

0.33

Variety AC=ACH185 and SP=SP7622 Fruit is Pre=Fruit present Abs=Fruit absent Treatment Average numbers within a column
followed by the same letter are not different at p = 0.05

32

genes tested in dry seeds, only 39 were shared between the two varieties. Many of the 39-shared
genes had sequence similarity to Arabidopsis genes involved in growth and response to
pathogens (Table A.2). Eighteen of the genes shared at 0 h were still detectable at 1 h in at least
one variety and treatment. Most of these genes were present in ACH185 and not SP7622 at 1 h
(data not shown). Putative BvGSTF8 and GSTF7, similar to Arabidopsis genes expressed during
seedling growth and in response to fungi, were two examples of genes expressed in both varieties
at 0 h, but only detectable in the ACH185 at 1 h. Only ROF and M3Ka were detectable in both
varieties at 0 h but only in SP7622 at 1 h.
One hundred twenty transcripts were uniquely present in SP7622 dry seeds, and 21 were
uniquely present in ACH185 dry seeds (Table A.3 and Table A.4). Out of the 120 unique
transcripts present in SP7622 at 0 h, only eight were also detected at 1 h. Only 7 of the 21 genes
uniquely present in ACH185 at 0 h were also detectable at 1 h. SP7622 had a greater number of
putative hormone, growth, metabolism and signaling transcripts present in dry seeds compared to
ACH185.
Post 0 h, SP7622 had fewer genes expressed in growth and stress-related than ACH185 in
H2O (data not shown). In the H2O2 treatment, SP7622 had a similar number of stress, growth
and signaling genes detectable to ACH185, for the first 6 h followed by a rapid increase in
growth and stress-related transcripts at 24 h. Between treatments, the total number of genes
detectable at any one time for each variety was very similar, with the exception of SP7622 at 24
h (H2O vs. H2O2). However, the functional composition of those genes differed between
treatments. In SP7622, there were increased stress transcripts present at 3 (30 vs. 8), 6 (51 vs.
28), 18 (44 vs. 26) and 24 (94 vs. 34) h in H2O2 as compared to H2O. Growth transcripts were
33

also more prevalent in the H2O2 treatment of SP7622 as compared to H2O at 3 (14 vs. 2), 6 (27
vs. 17) and 24 (69 vs. 22) h. In contrast, ACH185 had a greater number of stress related
transcripts detectable at 1 (26 vs. 6) and 18 (46 vs. 26) h for the H2O treatment compared to the
H2O2. Growth-related transcripts were also more prevalent in the ACH185 H2O treatment
compared to the H2O2 at 3 (17 vs. 7), 18 (26 vs. 17) and 24 (19 vs. 10) h.
Stress genes detected during the first 24 hours were grouped by whether they were abiotic,
biotic, or undetermined stress genes. Similarities in the varietal and treatment specific expression
patterns of genes over time were no longer visible when stress-associated genes were looked at
more closely (data not shown). In SP7622, increases in the total proportion of stress genes
(abiotic, biotic, undetermined and both) occurred at 6 and 24 h in the H2O2 treatment. In
ACH185 an increase in biotic stress genes was seen at 18 h in the H2O treatment, and not the
H2O2.
Both SP7622 treatments and the ACH185 H2O2 treatment resulted in germination, but the
ACH185 H2O treatment did not. Genes common between these three variety and treatment
combinations at a given time point, and not present in ACH185 H2O, were termed germination
genes (Table 1.5). Imbibition genes were those genes expressed in both treatments and varieties
at a given point as the seeds were imbibing water, but not necessarily involved in the actual
process of germination. When the germination genes were compared across time to the
imbibition genes, few genes were unique (Table 1.6). The most notable difference between the

34

Table 1.5 Germination genes, shared at a specific time between the treatments that resulted
in germination, SP7622 H2O2 and H2O treatments and ACH185 H2O22 treatment. Genes
highlighted in green were shared with the imbibition list at a different time. Genes not
highlighted were specific to germination using RT-PCR.
Germination genes
*

Bv Accession
BQ060614
BQ488461
BQ586400
CK136793
ED032901
BE590397
BQ584876
BU089558
ED032901
BQ489189
BQ582409
BQ588055
CK136793
CX779686
BF011227
BI096237
BQ583369
BQ588646
BQ594997
BQ595152
BU089558
CK136793
*

Beta vulgaris

**

***

At gene/function
MPK16
AOX1A
JAZ1
HSP18.2
retrotransposon
XTR7
kinase
HSL1
retrotransposon
MPK4
kinase
kinase
HSP18.2

At Protein
NP_197402.1
NP_188876.1
NP_973862.1
NP_200780.1
NP_193149.2
NP_197362.1
NP_174166.1
NP_192046.1
NP_567574.1
NP_567072.1
NP_200780.1
NP_200414.1
NP_182029.1
NP_188194.1
NP_194648.1
NP_568946.1
NP_172220.1
NP_174166.1
NP_200780.1

HSP81-2
EF
PLDA
AT1G03790
AML1
HSP17.8-CI
HSL1
HSP18.2
**

Arabidopsis thaliana gene

35

***

Time (h)

Arabidopsis thaliana NCBI protein

1
6
6
6
6
12
12
12
12
18
18
18
18
18
24
24
24
24
24
24
24
24

Table 1.6 Imbibition genes, present in both varieties and treatments at a specific time using
RT-PCR. Genes in green were also present in the germination list at an earlier time point.
Genes in pink were present in the hydrogen peroxide vigor gene list at an earlier time
point. Genes not highlighted were specific to imbibition.
Imbibition genes
*

Bv Accession
BI096176
BQ587887
CF543001
BE590444
BF011227
BI096176
BQ060614
BQ587622
BQ589141
BQ589734
BQ594558
BQ595152
BU089558
CF543001
CK136658
CK136793
CK136863
AW063023
AW697779
BE590444
BF010998
BF011036
BF011227
BI073235
BI096111
BI543285
BI543685
BI543772
BQ488119
BQ584136
BQ592168
BQ593588
BQ595152
BU089563
AW697779
BE590444

**

***

At gene/function
GER1

At Protein
NP_177405.1
NP_567072.1
NP_179361.1
NP_172220.1
NP_200414.1
NP_177405.1
NP_197402.1
NP_172358.1
NP_172358.1
NP_200780.1
NP_189093.1
NP_172220.1
NP_174166.1
NP_179361.1
NP_172220.1
NP_200780.1
NP_200780.1
NP_196543.1
NP_190397.1
NP_172220.1
NP_187818.1
NP_190397.1
NP_200414.1
NP_200412.1
NP_190397.1
NP_190397.1
NP_187864.1
NP_195870.1
NP_849745.1
NP_193456.4
NP_849377.1
NP_200412.1
NP_172220.1
NP_174166.1
NP_190397.1
NP_172220.1

HSP17.8
HSP81-2
GER1
MPK16
MYB60
MYB60
HSP18.2
MBFC1
HSP17.8-CI
HSL1
HSP17.8-CI
HSP18.2
HSP18.2
ACT7
AT3G29970
HSP17.8
ACT11
AT3G29970
HSP81-2
HSP81-3
AT3G29970
AT3G29970
HSP70
HSC70-1
IP5PII/BME3
SCL13
GRP2/GR-RBP4
HSP81-3
HSP17.8-CI
HSL1
AT3G29970
HSP17.8
36

Time (h)
1
1
1
3
3
3
3
3
3
3
3
3
3
3
3
3
3
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
12
12

Table 1.6 continued
BF010998
BF011036
BF011227
BI073235
BI096111
BI543285
BI543685
BI543772
BQ488461
BQ489189
BQ582382
BQ586930
BQ593588
CX779686
ED032482
AW697779
BE590397
BE590444
BF011036
BI073235
BI543685
BQ595152
BG577441
BI073128
BI096176
BI543685
BI543772
BQ060614
BQ489189
BQ584082
BQ593209
BQ594412
CX779686
*

Beta vulgaris

ACT11
AT3G29970
HSP81-2
HSP81-3
AT3G29970
AT3G29970
HSP70
HSC70-1
AOX1A
MPK4

NP_187818.1
NP_190397.1
NP_200414.1
NP_200412.1
NP_190397.1
NP_190397.1
NP_187864.1
NP_195870.1
NP_188876.1
NP_192046.1
NP_194839.2
NP_195235.1
NP_200412.1
NP_190397.1
NP_193149.2
NP_172220.1
NP_190397.1
NP_200412.1
NP_187864.1
NP_172220.1
NP_194311.1
NP_197563.1
NP_177405.1
NP_187864.1
NP_195870.1
NP_197402.1
NP_192046.1
NP_194839.2
NP_973684.1
NP_198860.1
-

CAT2
HSP81-3

AT3G29970
XTR7
HSP17.8
AT3G29970
HSP81-3
HSP70
HSP17.8-CI
XTR6
GER3
GER1
HSP70
HSC70-1
MPK16
MPK4
OEP37
MKK3
**

Arabidopsis thaliana gene

37

***

Arabidopsis thaliana NCBI protein

12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
18
18
18
18
18
18
18
24
24
24
24
24
24
24
24
24
24
24

germination and the imbibition genes was a lag in expression at one or more time points for
many of the genes observed. This indicated that many of the genes termed “germination” were
actually a combination of imbibition and germination genes. Both varieties and treatments
resulted in the activation of transcripts involved in the process of germination; however, the
timing of activation was differential.
The few germination genes not present in the imbibition genes were a putative jasmonate
biosynthesis (JAZ1), phospholipase D alpha (PLDA1), two retrotransposons, a protein kinase, an
elongation factor, a negative regulator of light-dependent seed germination and a gene involved
in meristem development and growth (AML1). Contrastingly, genes found to be specific to the
H2O2 treatments in ACH185 and SP7622 had no overlap with the germination genes and little
overlap with the imbibition genes (Table 1.7). Hydrogen peroxide transcripts included genes
involved in metabolism, brassinosteroid signaling, heat shock proteins, stress transcription
factors, and defense.
K-means clustering of gene expression revealed expression patterns common between
varieties and treatments (e.g. Clusters 0, 1, 2, 3, and 6) (Figure 1.2). It should be noted that
individual genes within a specific expression cluster were not typically shared between varieties
and treatments and the total number of genes within each cluster varied greatly (Table A.2). In
Cluster 6, a large cluster representing genes with little to no expression, only 18 genes were
detected in both ACH185 and SP7622 in both the H2O and the H2O2 treatments. At least one
cluster was unique to the specific profile for each variety and treatment. Cluster 9 was only
present in SP7622 and Cluster 10 was only present in the hydrogen peroxide treatment of
SP7622 (Figure 1.2). No expression clusters were shared solely between in the two hydrogen
peroxide treatments or the two water treatments. Treatment and variety specific clusters did not
38

Table 1.7 Genes shared between treatments and varieties at a specific time using RTPCR. Hydrogen peroxide induced vigor genes, genes shared between both varieties in the
hydrogen peroxide treatment at a specific time. Genes highlighted in pink were also present
at one time point in the imbibition list.

*

Bv Accession
BI096011
BI096145
BQ583306
BQ584422
BQ584988
BQ586920
BQ591929
BQ592393
BQ594715
CK136649
BQ487747
BQ589734
BQ592254
BQ594875
BQ595355
BQ654409
CK136263
BF011089
BI096232
BI543460
BQ589734
CK136863
BI543265
BI543360
BQ586930
BQ587848
BQ587874
BQ587887
BQ589925
BQ592254
BQ595856
*

Hydrogen peroxide specific sugarbeet gene expression
**
***
Gene Name
At protein
GER3
NP_197563.1
LOX1
NP_175900.1
LOX2
NP_566875.1
LOX3
NP_564021.1
LOX2
NP_566875.1
BRH1
NP_191705.1
NP_564717.1
UCC2
NP_182006.1
NP_568046.1
OSM34
NP_192902.1
XTR6
NP_194311.1
HSP18.2
NP_200780.1
DREB2C
NP_565929.1
RGA1
NP_178266.1
SSI2
NP_181899.1
XTR6
NP_194311.1
NIC1
NP_565539.1
DTC
NP_197477.1
PLDALPHA1
NP_188194.1
MTHSC70-2
NP_196521.1
HSP18.2
NP_200780.1
HSP18.2
NP_200780.1
NP_194648.1
CAT2
NP_001031791.1
CAT2
NP_195235.1
MKK9
NP_177492.1
NP_567072.1
NP_567072.1
RPN10
NP_195575.1
DREB2A
NP_001031837.1
ATTPC1
NP_567258.1

Beta vulgaris

**

Arabidopsis thaliana gene

39

***

Time (h)

Arabidopsis thaliana NCBI protein

1
3
3
3
3
3
3
3
3
3
6
6
6
6
6
6
6
12
18
18
18
18
24
24
24
24
24
24
24
24
24

Figure 1.2 K-means groupings of A) ACH185 and B) SP7622 in H2O and H2O2 using RT-PCR over the first 24 hours of
germination. Purple indicates presence of a particular transcript and green indicates absence.

40

Figure 1.2 continued

41

typically translate into genes uniquely expressed in a variety or treatment. Cluster 7, an ACH185
H2O specific expression cluster with 48 genes, had only five genes that were not expressed in
ACH185 H2O2, SP7622 H2O and H2O2. The five genes were glutathione ROS reductase,
glutathione S transferase, MPK20, LOX2 and PAL1.
Cluster 9, a SP7622 specific cluster, did not have many genes common between the H2O and
H2O2 treatments. In H2O, 28 genes were placed into Cluster 9. Out of the 28 possible, two genes
were also in Cluster 9 for the H2O2 treatment, while seven were in Cluster 10, and five were not
expressed at all in the H2O2 treatment. Of the 27 total in the H2O2 treatment, two were shared
and 14 were not expressed in H2O.
Of the 343 genes tested, only 36 were not detectable at any time, in any treatment or variety
during the first 24 hours of germination, and 27 were detected at only one time or treatment. It is
unlikely that a lack of amplification was due to failed primers, as the primers were able to
amplified in other sugarbeet cDNAs (data not shown.) However, many of the genes had little
expression over the first 24 hours, including genes with known roles in hydrogen peroxide
response in Arabidopsis. Non-detectable genes using RT-PCR did not segregate with a particular
set of processes, such as pathogen defense, metabolism or growth. For ACH185 in H2O and
H2O2, 156 and 167 genes were in Cluster 6, respectively and for SP7622 H2O and H2O2, 215
and 124 genes, respectively were in Cluster 6 (Table A.5 and Table A.6).
Quantitative PCR was used to evaluate the robustness of RT-PCR for detecting transcript
presence from sugarbeet seeds and to evaluate quantitative differences in transcripts between the
42

varieties and treatments. Differences in the 48 genes, selected based on their roles in abiotic and
biotic stress, growth, and hormone biosynthesis, were detectable between varieties and
treatments throughout the first 24 h of germination. Varietal specific responses to hydrogen
peroxide were evident (Table 1.8). Out of the 21 genes quantitatively detectable in SP7622 at 1 h
H2O2 only four were expressed at a basal level (level similar to expression at 0 h or 1 h H2O). Of
the 25 genes detectable in ACH185 at 1 h in H2O2 only 10 were expressed at a basal level. By 1
h, kinase activity, calmodulin signaling, and peroxidases were all upregulated (>10 fold increase)
in the H2O2 treatment of ACH185 (Table 1.9). In the H2O treatment of ACH185, only a single
kinase (M3Ka) and a respiratory burst oxidase gene were upregulated. In SP7622, none of the
stress-related genes were upregulated at 1 h in the H2O treatment. In H2O2, SP7622 had an array
of gene upregulation involving ABA biosynthesis, lipoxygenase activity, kinase signaling, and
histone deacetylation (>10 fold). A putative GRAS1 (BQ584136), CAF1 (BQ586375), and
CML41 (BQ587396) showed an increase (>4 fold) in expression in ACH185 in response to
H2O2. In SP7622, a putative PDC (BQ490338), BRI1 (BQ583692), LOX3 (BQ584422), Br6OX2
(BQ585998), MKK3 (BQ594412), NSP5 (BQ594578) were all upregulated (>5 fold increase) in
response to H2O2 (Table 1.10).
Both RT-PCR and qPCR results showed activation of genes as soon as 1 h of treatment and
an increase in expression (qPCR) or preferential detection (RT-PCR) of growth, abiotic and
biotic stress genes including brassinosteroid responsive, lipoxygenases and MAPKs. A more
pronounced up-regulation of stress-regulated genes in response to H2O2 was observed in both
varieties. The highest level of gene expression (both number of genes and expression quantity) in
43

Table 1.8 Quantitative gene expression (relative fold change) over time in ACH185 and SP7622 in H2O and H2O2 treatments
during the first 24 h of germination. Lt. pink denotes a fold change <3. Blue indicates a fold change >3 and <10. Purple
indicates a fold change >10. Gray squares indicate the relative expression was not calculated (NC) because of a lack of
expression in the control treatment and nd indicates the gene was not detected.

ACH185
Putative
*
Function

ABA1

MKK2
ERF9

a
a

MPK4
a

PDC

b

WAK

PHS2

g

CYP76C7
XLG1

a

FC

nd

3

nd

272

nd

nd

nd

0

0

4

nd

nd

nd

nd

nd

32

nd

nd

nd

3

nd

171

nd
nd

nd
nd

4
1

nd
nd

nd
nd

0
nd

0
nd

0
nd

nd

2

32

nd

nd

nd

3

nd

nd

nd

0

2

nd

10

2

0

3

0

147

4.5+09

nd

nd

0

444

4

nd

nd

nd

nd

61

nd

nd

nd

nd

2

32

nd

nd

nd

325

1833

nd

nd

nd

nd

nd

nd

742

nd

nd

nd

9

8

nd

1

0

100

151

5

221

12

1

nd

8

3

1149

1

2

1

1

2

11319

7

26

0

7

30

66

1

8

nd

0

nd

215

24

nd

nd

nd

nd

nd

BQ582629

a

FC

BQ582382

b

FC

BQ490338

RBOHD

24

BQ489189

a

18

BQ488935

ATL2
ABA2
a
RH26

FC

FC

FC

FC

FC

FC

0

0

nd

138

nd

nd

nd

nd

nd

nd

nd

0

1

nd

2

nd

2

56

1

nd

11

nd

nd

1
nd

nd
nd

nd
nd

nd
nd

1

4

nd

13

80

1

BQ488850

b

3

BQ488795

NCED4

1

BQ488466

b

24

BQ488337

MKK9

18

BQ488179
BQ488279

a

3

nd

nd

1

H2O2
6
12

BQ487982

GLP165

FC

BQ487860

b

FC

BI073128

M3Ke1

Accession

1
**
FC

BF011062

a

Genbank

H2O
6
12

nd

nd

nd

nd

nd

1

nd

nd

1

nd

nd

nd

BQ582634
BQ583062

5
nd

nd
nd

8
nd

4
nd

4
nd

899
nd

0
nd

6
nd

0
nd

0
nd

37
1

1106
1

44

Table 1.8 continued
b
PLDa
BQ583369
BRI1

LTP4

RD26

b

MKK9

b

RPN10
Kinase

b

a

Myb

a

GRP2

c

DREB2C
a

MPK4

e

CDKC

b

MKK3

a

MBF1C
a

NSP5

a

MPK6

111

2527

nd

nd

nd

nd

nd

1

6

8

nd

nd

nd

19

0

0

8

11

189

1

nd

2

nd

2

nd

nd

nd

nd

5

nd

nd

nd

nd

1

1

1

1

nd

nd

1

nd

nd

nd

53

4

2

nd

7

16

2

5

nd

nd

83

nd

BQ585998

1

nd

nd

nd

nd

nd

nd

nd

nd

nd

nd

nd

1

nd

0

0

nd

nd

nd

2

nd

21

nd

130

1

nd

0

0

nd

9

1

nd

nd

1

nd

nd

1

nd

nd

0

nd

2

nd

nd

nd

nd

nd

nd

2

nd

nd

nd

nd

nd

nd

0

nd

4

nd

nd

1

0

2

nd

2

nd

24

nd

nd

nd

nd

nd

1

0

2

nd

nd

50

nd

2

nd

nd

nd

nd

1

4

0

0

2

25

9

2

nd

5

14

125

nd

1

nd

nd

nd

nd

nd

nd

1

nd

nd

nd

nd

0

nd

nd

nd

nd

nd

nd

nd

nd

nd

nd

5

18

10

8

18

3983

98

5

0

1

29

2246

BQ592254

nd

1

1

1

nd

nd

nd

nd

nd

nd

nd

nd

nd

nd

0

nd

nd

nd

5

1

nd

2

3

1601

nd

nd

nd

1

nd

nd

1

1

nd

nd

1

nd

BQ594412

CML41

4

BQ592936

a

nd

BQ592267

a

nd

BQ592168

PP2C

nd

BQ590125

b

1

BQ591669

Kinase

b

54

BQ589925

CAF1

0

BQ587848

a

5

BQ587396

BR6OX2

0

BQ586991

a

0

BQ586635

M3KA

2

BQ586464

a

11

BQ586375

LOX3

0

BQ585699

d

0

BQ584422

GRAS1

0

BQ584136

b

nd

BQ584083

b

1

BQ583692

b

1

nd

nd

0

nd

51

nd

nd

nd

38

nd

884

BQ594558

5

0

0

2

2

74

2

nd

nd

nd

nd

nd

BQ594578

nd

nd

nd

nd

0

0

nd

nd

nd

nd

0

nd

BQ594736

0

nd

2

0

2

nd

nd

nd

2

nd

nd

nd

45

Table 1.8 continued
a
ATLP
BQ594810
PXA1

BAM1
HDA1

PER50
Total

a
*

0

nd

0

0

0

0

0

0

1

16

4

nd

nd

44

nd

nd

16

nd

nd

nd

1

7

nd

nd

3

46

15

nd

nd

4

nd

229

1

8

1

nd

19

nd

nd

2

nd

48

61

nd

1

nd

4

0

nd

50

0

2

0

2

15

6375

CK136719

b

nd

CF543165

a

0

BU089560

MKK9

0

BQ595738

b

nd

BQ595543

b

nd
31

23
21

8
25

0
20

4
22

219
27

11
24

15
18

0
14

42
25

20
20

0
20

a

b

c

d

e

f

g

h

Fold change normalized to 0 h 1 h H2O 3 h H2O 6 h H2O 12 h H2O 18 h H2O 24 H2O

**

FC is fold change

SP7622
H2O
Putative

Genbank

MKK9

a

NCED4
a

ATL2
ABA2
c
RH26
c

RBOHD
ABA1

d

MKK2
ERF9

b
a

MPK4

6

12

18

24

1

3

Accession
BF011062

FC
nd

FC
nd

FC
nd

FC
NC

FC
NC

FC
nd

FC
nd

FC
nd

FC
nd

BI073128

0

2

4

0

2

210

5

0

nd

17

nd

42

nd

53

nd

BQ487982

nd

17

nd

nd

nd

17

1
nd

3
nd

nd
nd

0
nd

1
nd

BQ488337

a

3

BQ488179
BQ488279

Function
M3Ke1
a
GLP165

1

BQ487860

+

a

H2O2
6
12

18

24

FC
nd

FC
NC

FC
NC

8

46

1

nd

nd

nd

nd

nd

nd

10

2

nd

nd

nd

2

6
nd

5
nd

8
nd

8
nd

nd
nd

nd
nd

nd
nd

nd

1

0

nd

nd

nd

nd

nd

nd

nd

nd

0

BQ488466

nd

1

0

0

0

0

nd

nd

0

nd

nd

4

BQ488795

nd

15

nd

0

nd

2

42903

9

nd

nd

nd

nd

BQ488850

nd

nd

1

0

0

1

1

nd

nd

5

nd

nd

BQ488935

1

8

8

nd

nd

nd

nd

1

nd

39

39833

2

BQ489189

1

1

nd

1

265

3

18

2

1

nd

881

0

46

Table 1.8 continued
b
PDC
BQ490338
BQ582382
WAK
e
PHS2
BQ582629

BRI1

LTP4

Kinase

c

a

PP2C
RD26

a
a

CML41

d

MKK9

a

RPN10
Kinase
a
Myb
c

GRP2

c

DREB2C
c

MPK4

b

CDKC

nd

1

0

498

nd

0

nd

658

nd

4

BQ582634
BQ583062

nd
nd

8
nd

nd
nd

2
nd

5
nd

24
NC

21
nd

1
nd

26
nd

85
nd

10486
nd

3
nd

BQ583369

nd

2

nd

0

nd

3

nd

0

nd

nd

nd

1

nd

1

2

0

nd

nd

9

0

3

nd

2.7E+09

7

nd

46

0

19

8

3

nd

8

32

81

35440

2

nd

nd

nd

1

nd

1

nd

1

nd

nd

nd

nd

nd

nd

nd

2

nd

1

30

0

6

12

18790

nd

1

11

16

0

nd

nd

14

2

nd

nd

nd

nd

BQ585998

nd

nd

nd

0

1

nd

nd

0

8

21

nd

1

1

0

0

0

0

nd

nd

nd

nd

nd

nd

nd

nd

1

3864

1

nd

1

nd

0

nd

nd

nd

nd

1

8

nd

1

15

nd

nd

nd

nd

nd

nd

2

nd

2

2

0

1

1

5

1

19

nd

nd

nd

nd

1

nd

1

12

0

nd

nd

nd

5

nd

0

nd

nd

1

1

1

nd

nd

nd

1

nd

nd

nd

1
nd

nd
nd

nd
nd

nd
nd

nd
nd

0
nd

nd
NC

0
nd

nd
nd

nd
NC

nd
nd

0
NC

nd

nd

nd

0

nd

nd

8

1

nd

nd

nd

nd

BQ592168

CAF1

nd

BQ591669

a

nd

BQ589925
BQ590125

BR6OX2

7
NC

BQ587848

a

2426
nd

BQ587396

M3KA

703
NC

BQ586991

a

4
nd

BQ586635

LOX3

0
NC

BQ586464

a

nd
nd

BQ586375

GRAS1

4
nd

BQ585699

a

nd
NC

BQ584422

a

0
NC

BQ584136

a

nd
nd

BQ584083

CYP76C7
XLG1
a
PLDa

2
nd

BQ583692

a

1
nd

nd

1

0

0

0

0

2

0

6

16

198

18

BQ592254

nd

1

nd

nd

nd

0

nd

nd

nd

nd

nd

0

BQ592267

nd

1

nd

0

0

0

1

0

nd

nd

984

0

BQ592936

1

nd

9

578

2

23

380

1

16

nd

nd

1

47

Table 1.8 continued
a
MKK3
BQ594412
NSP5

a

MPK6

b

ATLP
PXA1

a
a

MKK9
BAM1

a

a

HDA1

PER50
Total

a

nd

1

nd

nd

11

nd

8

82

nd

2

BQ594558

nd

1

nd

0

1

1

nd

0

1

2

233

0

nd

nd

nd

nd

nd

nd

4

nd

nd

nd

1647

0

BQ594736

nd

nd

nd

0

nd

nd

nd

nd

nd

nd

nd

nd

1

372

nd

nd

2

4

nd

nd

15

nd

nd

16

BQ595543

a

nd

BQ594810

MBF1C

nd

BQ594578

c

nd

nd

nd

nd

nd

nd

nd

6

nd

nd

nd

2

BQ595738

1

nd

nd

2

nd

nd

nd

0

nd

20

4612

1

BU089560

nd

0

nd

0

0

nd

2

nd

nd

nd

1115

0

CF543165

1

nd

nd

0

23

nd

10

1

nd

nd

nd

42

CK136719

nd
14

nd
26

75
15

0
35

3
25

2
26

12
21

29
29

10
18

31
17

5538
16

6
31

+

a

b

c

d

Fold change normalized to 0 h 1 h H2O 3 h H2O 6 h H2O

48

both varieties was seen at 24 h for most genes tested. In response to H2O2, both varieties
upregulated a putative MKK9, BRI1 and MPK4. In addition, a LTP4 and RD26 were upregulated
in both treatments of SP7622 and the H2O2 treatment of ACH185 indicating a possible role in
germination vigor. Several genes putatively functioning in drought and salt response as well as
hydrogen peroxide signaling (BQ488279 (ABA2), BQ586464 (kinase), BQ591669 (Myb),
BQ594736 (MPK6)) showed little (< 2 fold) change in expression between the two varieties and
treatments during the first 24 h.

DISCUSSION

Germination is a multigenic, dynamic process, easily modified by external stresses. In sugarbeet
seeds, germination was characterized by rapid water absorption during the first 24 h of
imbibition and, in the vigorous variety, higher levels of internal hydrogen peroxide. Genetic
characteristics of germination were a rapid degradation of endogenous mRNA over the first 3 h
of imbibition and a slow concurrent activation of seed-based genes in growth, stress and
signaling. Sugarbeet germination was a very dynamic process with gene expression changes,
likely involved in vigor induction, occurring rapidly upon treatment.
RT-PCR analyses of the vigor-inducing hydrogen peroxide treatment revealed a number of
putative metabolic, drought, and pathogen related genes between 3 and 24 h. A number of
hydrogen peroxide specific genes were shared between 3 and 6 hours and again at 24 h. Shared
genes at these particular times suggest a common mode of early stress response, which may lead
to a common response later, e.g. growth, and may prove useful for early screening of sugarbeet
germplasm. The upregulation of abiotic, water response in particular, genes was expected due to
49

Table 1.9 Genes in ACH185 associated with hydrogen peroxide-induced vigor over time
using qPCR
ACH185
H2O2
Only
Only
Only
Only
Pred
Pred
Pred
Pred
Pred
Pred
Pred
Pred

Gene name
CML41
MPK4
CAF1
LTP4
HDA1
BRI1
MKK3
MKK9
MPK4
PLDa
BAM1
MKK2
*

Putative Role
Stress regulated (Undetermined)
Stress signaling (Biotic)
Stress regulated (Biotic)
Stress regulated (Abiotic)
Stress regulated (Abiotic)
Stress and growth
Stress signaling (Biotic)
Stress signaling (Both)
Stress signaling (Biotic)
Growth
Growth
Stress signaling (Abiotic)

Only indicates gene was only upregulated in H2O2. Pred indicates gene was
predominantly upregulated in H2O2

Table 1.10 Genes associated with hydrogen peroxide-induced vigor in SP7622 over time
using qPCR.
SP7622
H2O2*
Only
Only
Only
Only
Only
Only
Only
Only
Only
Pred
Pred
Pred
Pred
Pred
Pred
Pred
Pred
*

Gene name
Myb
RD26
LOX3
GRP2
BRI1
MKK3
BAM1
KELCH
MBF1C
ABA1
PDC
PER50
CYP76C7
ERF9
MKK9
MPK4
LTP4

Putative Role
Stress regulated (Both)
Stress regulated (Abiotic)
Stress regulated (Biotic)
Stress regulated (Abiotic)
Stress and growth
stress signaling (Biotic)
Growth
Growth
Stress regulated (Abiotic)
Stress regulated (Abiotic)
Growth
Stress regulated (Abiotic)
Undetermined
Stress regulated (Biotic)
Stress signaling (Both)
Stress signaling (Biotic)
Stress regulated (Abiotic)

Only indicates gene was only upregulated in H2O2. Pred indicates gene was
predominantly upregulated in H2O2
50

the abiotic nature of the stress, but upregulation of biotic-related stress genes was not.
Quantitative transcript changes of a putative lipid transfer protein (LTP4) showed a large
increase in expression in the H2O2 treatment in ACH185 and SP7622 in comparison to the H2O
treatment. Expression was quantitatively high (>10 fold increase at any given time point
compared to the 0 h expression) in the SP7622 H2O treatment, though significantly less than in
H2O2. Upregulation of this specific lipid transfer protein was positively correlated with
hydrogen peroxide vigor in the two varieties tested. Lipid transfer proteins in general have been
implicated largely in pathogen response, and are upregulated by ABA (Gonorazky et al. 2005;
Mane et al. 2007). LTP4, in particular, has been associated with pathogen response in
barley(Molina 1996).
BRI1, another gene found to be associated with vigor and hydrogen peroxide response in
germinating seedlings, has no known role in germination in Arabidopsis. Arabidopsis bri1
mutants are insensitive to Br (Brassinosteroids) and show a range of phenotypes including
dwarfing, sensitivity to ethylene, ABA, GA and auxins, male sterility, reduced cell and leaf
expansion, and a misregulation of genes regulated by GA (Swarbreck 2008). A lack of BRI1
expression during germination could result in enhanced sensitivity to ABA and would hinder
germination. Conversely it is also possible that upregulating BRI1 expression could be
instigating growth and working through GA dependent pathways. It has been shown that Br
signaling provided tolerance to a range of stresses and was activated as soon as 1 h (Che et al.
2010). These two genes (LTP4 and BRI1), which are associated with germination vigor in both
varieties, could be potential molecular markers for screening sugarbeets.

51

Of the MAPKs tested, a putative beet MPK4 showed an induction in both varieties in
response to H2O2, but not in the H2O treatment. A putative BvMKK2, had an increase in
expression (quantity and duration) in the ACH185 H2O2 treatment compared to the H2O
treatment. MKK2 expression levels in SP7622 were not determined, because of a lack of a
suitable treatment and time for normalization. However, expression was present in both H2O and
H2O2 treatments and showed differential timing. Another putative MKK9 showed a >900 fold
increase of expression in the H2O2 treatment for both varieties in comparison to the H2O
treatment. H2O2 has numerous roles as a signaling molecule in abiotic and biotic stress response
(Liu 2010; Orozco-Cardenas 2003). BQ594736 (a putative beet MPK6) showed minimal changes
in expression (<2.5 fold change) in both varieties and treatments over the first 24 h measured.
ANP1 and MPK3 were not tested quantitatively for expression changes, but were not detectable
in the RT-PCR assay. Our results imply that the H2O2 activated ANP1/MPK3/6 pathway does
not play a role in germination vigor. MKK2/MPK4 and MKK9 pathways may have a positive role
on improved emergence and the hydrogen peroxide response in the two beet varieties tested.
This research suggests that H2O2 accumulation instigates vigor prior to lipid catabolism and
that this vigor induction is through the activation of signaling molecules and abiotic and
pathogen-defense related genes. Differences in gene expression between the two varieties prior
to treatment revealed that ACH185 had a number of stress-related transcripts present that were
not detectable in SP7622, but no metabolic-related transcripts. These additional stress-related
transcripts at 0 h and over time may have been present as a result of the fungal contamination of
the seed, as the incidence of fungal contamination was higher for the ACH185 seed. SP7622 had
52

a diverse array of signaling molecules, metabolic transcripts, and transcription factors that were
not present in the ACH185 seed. This suggests that natural priming, for germination and defense,
may occur during seed development and maturation to dictate germination vigor (Beckers 2009;
Masoudi 2010). Transcripts shared between the two varieties prior to treatment, likely to be
essential for seed development and germination, included a number of MAPKs, a jasmonate
inducible, and fatty acid biosynthesis genes. The array of pre-germination metabolic and
signaling transcripts present in SP7622, but not in ACH185, may be important for germination
vigor. RT-PCR was able to show that 1 h in H2O2 was sufficient to induce a genetic response to
hydrogen peroxide during germination for both varieties. Germination-vigor specific RT-PCR
genes, genes shared by SP7622 (H2O and H2O2) and ACH185 (H2O2), included a large number
of genes involved in cell signaling and defense (protein kinases, MAP kinases, etc). Shared
genes were mainly detected between 6 and 24 hours of treatment, which indicates that different
initial responses may converge to common pathways over time. The large proportion of genes
that were shared between the germination and imbibition list indicated that within each variety,
despite their vigor differences, steps were being taken for imbibition and successful germination.
For ACH185 in the H2O treatment, germination, though delayed, was being instigated.
BI073121, one of the five genes upregulated only in ACH185 H2O treatment according to RTPCR, was similar to an Arabidopsis gene putatively involved in the glutathione cycle to degrade
toxic hydrogen peroxide (Swarbreck 2008). Another gene, BI543980, is a glutathione S
transferase (Sappl 2004). While response may be mediated through the activation and repression
of genes, clustering of the RT-PCR results showed that differential timing might also play a large
role in moderating the hydrogen peroxide induced germination response. Many of the clusters,
53

even those specific to a variety or treatment, did not have genes uniquely expressed across all the
time points tested. The addition of exogenous H2O2 activated, repressed and changed the timing
of expression for many of the genes observed. qPCR further confirmed that gene expression
changes were occurring in response to H2O2, and revealed qualitative and quantitative changes
in stress, growth, and signaling genes. H2O2 elicited a response as soon as 1 h in the seed and
continued throughout the first 24 h of germination. Whether the hydrogen peroxide signals that
induce seedling vigor are activated that early is unclear, but it is certain that seeds are able to
perceive and respond rapidly to this stress treatment. While a proportion of the genes found to
respond to H2O2 in adult Arabidopsis plants did have altered gene expression in response to
hydrogen peroxide during germination for sugarbeets, many of the stress-related transcripts
showed little response to H2O2. Under H2O2 exposure, microarray data has revealed hundreds of
genes activated by more than 1.5 fold increase in adult Arabidopsis plants (Desikan et al. 2001).
Our work suggests that many of these genes (shown to be induced under H2O2 stress during
adult stress in Arabidopsis) do not play a role in hydrogen peroxide induced germination vigor,
at the time points examined in Beta vulgaris.
Internal hydrogen peroxide concentrations were inversely related to the differences in water
absorption between the two varieties. ACH185, which absorbs more water than SP7622 over
time, had a more rapid decrease in internal hydrogen peroxide than SP7622. This decrease in
internal hydrogen peroxide was correlated with an increase in water absorption and a decrease in
germination by ACH185. This possibly results in the dilution of internal H2O2 during
imbibition, which can be restored with the exogenous application of H2O2. Differences in
54

internal hydrogen peroxide concentration were observed in the two varieties at 6 h and 24 h.
Since physical differences were clear in the first 24 h of imbibition between good and poor
emerging treatments (H2O2 and H2O) it is likely that Phase I, or the first 24 hours of imbibition
for fruits and 6 h for embryos, are when germination speed and vigor are defined. Phase I of
germination and internal hydrogen peroxide concentrations may be good initial physical
indicators of a variety and seedlot’s germination vigor.
The complexity of the varietal gene expression response to a vigor inducing stress was
clearly demonstrated in this study. ACH185 and SP7622, which both show increased vigor in
H2O2, had very different genetic reactions during Phase I (first 24 h) of germination. Despite the
very divergent profiles observed, several key genes were identified as possible components of a
shared response. Within the varieties and conditions tested, it appeared that low levels of
oxidative stress during sugarbeet germination activated a complex series of signaling cascades
and defense responses involving the MAPK cascades (MPK4 and MKK9), lipid mobilization
(LTP4) and catabolism, jasmonate biosynthesis, and brassinosteroid signaling (BRI1) that
resulted in enhanced germination in H2O2 (both varieties) and in H2O (for the vigorous variety).
In germinating sugarbeets, hydrogen peroxide results in a large-scale activation and
repression of many growth and development, hormone biosynthesis, and stress-related genes as
soon as 1 h after treatment and continues through at least 24 h. MPK4, MKK9, LTP4 and BRI1
were genes found to be associated with hydrogen peroxide induced vigor that were shared
between the two (highly genetically different) varieties. These genes, upon confirmation in other
varieties, may be useful as molecular markers for screening germplasm and selective breeding to
improve germination in sugarbeets. While further studies will need to be completed, this study
55

provides the first look at large-scale transcriptional and physical changes in sugarbeet seeds
during the first 24 h of germination, and describes the possible role of stress-related transcripts in
sugarbeet germination vigor.

56

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63

CHAPTER 2: EARLY SEEDLING RESPONSE TO WATER AND PATHOGEN STRESS
AND THE IDENTIFICATION OF VIGOR RESPONSE GENES IN BETA VΜLGARIS

ABSTRACT
Sugarbeet seedlings are extremely susceptible to environmental stress during the first few weeks
of growth. Abiotic stresses, such as changes in water availability, are difficult to control and limit
crop productivity. Soilborne pathogens such as Aphanomyces cochlioides, Rhizopus sp., Pythium
spp. and Rhizoctonia can also significantly impact the quantity and quality of beet seedlings in
the field. Extensive breeding, expensive chemical control, and cultural practices are essential to
combat losses due to seedling stress. Currently, molecular markers for early screening of
quantitative disease and stress resistance traits are unavailable for sugarbeet breeders. Forty-eight
genes, previously tested for their role in germination vigor, were quantitatively evaluated in 3week old seedlings of two sugarbeet varieties under an oomycete, a fungal, and a water stress
condition. Differences were observed between two varieties in the type of genes activated in
response to each stress. The pathogen treatments, Rhizopus sp. and A. cochlioides, showed
greater similarity in their gene expression to each other than with the water treatment for both
varieties. Putative PP2C (Protein phosphatase 2C) and GRP2 (Glycine-rich binding protein)
were upregulated in both sugarbeet varieties in the water treatment suggesting a possible role in
flooding stress. Genes involved in basal pathogen response in sugarbeet, specific Rhizopus sp.
and A. cochlioides responses, and varietal specific pathogen responses were identified among
upregulated genes. Gene expression was compared in 3-week old stressed seedlings with
expression during seed germination. Genes common between varieties and developmental stages
revealed overlapping expression patterns between germination and early seedling vigor.
64

INTRODUCTION
The first few weeks of growth are the most critical for Beta vulgaris (sugarbeet) germination,
growth and stand establishment. During this time, the plants are highly susceptible to abiotic and
biotic stress as cells are rapidly dividing and growing (Nevins et al. 1968; Sanchez-Rodriguez et
al. 2010). Cold, heat and drought hinder sugarbeet germination and growth while soilborne
pathogens, such as Rhizopus sp., Pythium spp. and Aphanomyces cochlioides, can infect and
debilitate susceptible seedlings. Breeding efforts and fungicide applications have limited the
prevalence of seedling diseases, but stand losses still occur when conditions are suitable for
disease development. Breeding for tolerance to individual pathogens and abiotic stresses is time
consuming, narrows the genetic base and is often only effective for a few years (Acosta-Leal et
al. 2010; Kuzdowicz 2009; Sadeghian and Khodaii 1998; Taguchi and Ogata 2010). A.
cochlioides, an oomycete, has been listed as a major cause of seedling death since the 1920s
(Dyer et al. 2004; Humphries and French 1969). Partial resistance has been incorporated into
most of the modern sugarbeet varieties grown in the Midwest, but damage and losses still occur
annually. Breeding for improved germination, seedling vigor and durable disease resistance traits
is difficult due to low heritability and significant environmental influence. In many instances,
breeding efforts are limited by inconsistent lab and greenhouse results, few resistant germplasm
and a lack of molecular markers.
Molecular markers, which rely on genetic variation associated with phenotypic traits, can
serve as tags to rapidly evaluate germplasm and incorporate desired traits into alternative genetic
backgrounds. In beets, self-incompatibility has limited the number of available populations
segregating for specific traits, increasing the need for markers associated with traits of interest.
Previous work (Chapter 1) identified expression differences in genes in two sugarbeet lines
65

germinated in hydrogen peroxide and water, with potential roles as molecular markers. High
hydrogen peroxide concentrations and upregulation of specific genes involved in growth,
signaling and defense were associated with increased germination vigor and growth.
Upregulation of abiotic and biotic stress responses in particular were associated with successful
germination and vigor in the two varieties tested. Germination markers have limited usefulness,
due to the rapidity with which germination can be tested. However, germination markers that are
also predictive of early seedling vigor to pathogens or abiotic stress would be invaluable.
Over the last decade, multiple studies in model organisms have shown that cellular responses
to abiotic and biotic stimuli can converge through overlapping signaling cascades, such as
mitogen-activated protein kinases (MAPKs), to induce changes in gene expression that can
activate plant defenses (Beckers et al. 2009; Colcombet and Hirt 2008; Pitzschke and Hirt 2006).
In Arabidopsis thaliana, the constitutive expression of defense related MAPKs results in
enhanced disease and stress resistance to multiple stimuli (Brader et al. 2007; Cheong and Kim
2010; Jeong et al. 2008; Shi et al. 2010; Zhang et al. 2007). Hormone and metabolic components
are also common response elements activated by multiple stresses. Abscisic acid (ABA),
jasmonic acid (JA), salicylic acid (SA) and brassinosteroids (Br) are hormones produced upon
infection, wounding or stress. These hormones can activate plant cell defenses such as stomatal
movement, cell death, systemic acquired resistance (SAR) and reactive oxygen species (ROS)
production (Adie et al. 2007; Beckers et al. 2009; Colcombet and Hirt 2008; Krishna 2003;
Pitzschke and Hirt 2006; Yu et al. 2008; Zhao et al.). Metabolic-related proteins such as
alternative oxidases (AOX), lipoxygenases (LOX) and phospholipase D alpha (PLDA) are also
induced by external stresses and result in the mobilization of stored lipid reserves, similar to the
lipid mobilization seen by de los Reyes et al. (2003). Information on common elements of stress
66

response derived from model organisms may provide potential markers or genetic indicators to
assess germination and seedling vigor in less studied crop species useful for assessing tolerance
to abiotic and biotic stresses.
Identification of genes involved in early stress responses has been primarily achieved by
mapping genetic traits through bulk segregant analyses (BSA) or mapping populations (Bansal et
al. 2008; Bariana et al. 2001; Li et al. 2010; Manangkil et al. 2008; Mano and Takeda 1997;
Shankar et al. 2008; Yu et al. 2009). Expression QTLs (eQTLs) have been used to link QTLs
(quantitative trait loci) with the genes for metabolite changes and certain disease resistances such
as aphid and rust resistance in various plant species (Dai et al. 2009; Druka et al. 2008;
Kliebenstein 2009; Michaelson et al. 2009). While effectively linking the expression of a
particular gene or set of genes of a given locus with a response, an eQTL’s ability to detect
differential timing of gene expression as well as those genes located externally to QTL regions
associated with a response were limited. The ability to combine eQTLs and association mapping
to correlate gene expression changes with a trait of breeding interest (disease or insect resistance,
metabolite changes, etc.) could be a more accurate and useful way to determine resistance when
traits are controlled by more than a single gene and mapping populations are not available.
The ability to run diagnostic tests on sugarbeet seeds and accurately detect germination
potential and early season abiotic and biotic stress resistance would greatly assist sugarbeet
breeders in developing improved varieties. Identifying genetic components associated with plant
stress responses at early stages of growth may also provide resources for breeders and seed
companies to assess the adult vigor in addition to seedling vigor of populations. The objectives
of this study were to identify genes involved in two sugarbeet varieties’ seedling response to two

67

seedling pathogen stresses, and to identify genes associated with vigor in both germinating seeds
and 3-week old seedlings.

MATERIALS AND METHODS
Inoculation. A Rhizopus sp. (RP08-1) and an Aphanomyces cochlioides isolate collected
from Michigan (provided by Dr. Linda Hanson, USDA-ARS, East Lansing, MI) were
individually grown on potato dextrose agar (PDA) for two weeks. An actively growing plug (7
mm diameter) of each isolate was transferred to cornmeal agar (CMA) and grown for 5 days at
25 °C under constant fluorescent light. Five milliliters of 18 MOhM H2O were added to the
Rhizopus sp. plates and the resulting spore suspension was diluted to 100 spores/ml with 18
MOhm water. Four 10 mm diameter disks from the A. cochlioides plates were transferred to an
empty sterile Petri dish and flooded with sterile pond water (Horticulture Demonstration
Gardens, Michigan State University), and placed in the dark according to Yu (2003). Zoospores
were counted 18 h later and diluted to a suspension of 100 zoospores/ml with 18 MOhm water.

Germination and growth of seedlings. A former commercial variety, ACH185 (ELA012206) and breeding germplasm, SP7622 (EL-A015030), were chosen for analyses. ACH185
is a triploid, cytoplasmic male sterile variety with low average germination (<60%) under stress
conditions, low field emergence, partial resistance to A. cochlioides, and complete resistance to
Rhizopus sp.. SP7622 is a diploid germplasm with high germination (>60%) and field
emergence, partial resistance to A. cochlioides and resistance to Rhizopus sp.. 400 seeds of each
accession were germinated in 88 mM H2O2 for 4 days shaken constantly at 25 °C under constant
68

light. Germinated seeds were transferred onto filter paper in germination boxes with 25 ml of 18
MOhm H2O and grown at 25 °C under constant fluorescent light for 17 days (water levels were
maintained) in a growth chamber. Fifteen seedlings were transferred to each flask containing 25
ml of H2O, 100 spores/ml Rhizopus sp. or a 100 zoospores/ml Aphanomyces cochlioides spore
suspension and shaken constantly at 25 °C. Three replicates of 15 plants were used per time
point for each treatment. Inoculated seedlings were removed at 6, 12, 18 and 24 h.

RNA extraction and cDNA synthesis. Total RNA was extracted using the Plant NucleoSpin
Total RNA (Machery-Nagel) according to the manufacturer’s protocol (Duren, Germany). cDNA
synthesis was performed using 1 µg of the total RNA with Superscript III reverse transcriptase
according to the manufacturers protocol (Invitrogen, Carlsbad, CA). cDNA was diluted to 50
ng/µl and used for qPCR analyses.

qPCR analysis of genes over time. The forty-eight primers developed from putative beet
stress response genes, used previously for germination vigor quantitative PCR studies, were
tested against the three-week old seedling cDNA (Table A.1). qPCR was performed using the
HotStart Kapa Sybr, Sybr Green master mix (Kapabiosystems, Woburn, MA), according to the
manufacturer’s protocol on the ABI StepOne Plus (Applied Biosystems, Carlsbad, CA) with 50
ng/µl of cDNA per reaction and analyzed as described previously (Chapter 1). The experiment
was replicated twice. qPCR results from the study on germinating seeds of ACH185 and SP7622
over time (Chapter 1 (Table 1.5)) were compared with qPCR results from 3-wk old seedlings to
identify conserved modes of vigor between germination and seedling vigor.
69

RESULTS
Three-week old sugarbeet seedlings showed varietal and treatment differences in gene
expression when exposed to two different pathogen treatments and one abiotic treatment.
SP7622 displayed a rapid activation of genes involved in signaling, lipid mobilization, hormone
biosynthesis and DNA transcription in response to the individual treatments (11 in H2O, 35 in
Rhizopus sp., 37 in A. cochlioides) (Table 2.1). In contrast, ACH185 had fewer genes (4 in H2O,
22 in Rhizopus sp., 19 in A. cochlioides) upregulated in response to any given treatment tested
(Table 2.2). Expression between varieties, within each treatment, was different in the total
number of genes expressed, the quantity of expression and the time at which genes were
expressed.
ACH185 showed changes in gene expression as soon as 6 h between the three treatments,
and continued through the 24 h monitored. Of the 48 genes tested in ACH185, only putative
DREB2C (BQ592254) and a protein kinase (BQ590125) were not detectable at any time or
treatment. The remaining 46 were expressed intermittently across the time points tested in one or
more treatment. ACH185 did not show induced expression of 17 of the 44 genes tested (at a fold
change >3 from the 6 h water control), and few (9 genes) overlaps were visible between the
pathogen treatments. Sixteen of the genes tested in ACH185 at 3 wks had an induction (> 3 fold
increase) in either the Rhizopus or Aphanomyces treatments compared to the abiotic flooding
control (H2O) treatment at the times observed. Genes that were upregulated (>3 fold increase) in
response to both Rhizopus and Aphanomyces in ACH185 were a putative GER3 [Germin protein
3] (BI073128), PDC [pyruvate decarboxylase] (BQ490338), CYP76C7 [cytochrome P450 76C7]
(BQ582634), BRI1 [Brassinosteroid insensitive 1] (BQ583692), M3Ka [MAPKK Kinase alpha]
70

Table 2.1 Quantitative gene expression (fold change) over time of 3 wk seedlings of ACH185 and SP7622 and the
Aphanomyces, Rhizopus and H2O treatments. Numbers in bold indicate these genes were associated with hydrogen peroxide
induced vigor during germination. Genes highlighted in purple were upregulated in both pathogen treatments and not the
water treatment.
ACH185
Aphanomyces
a

At gene
M3Ke1
GER3
MKK9
NCED4
ATL2
RBOHD
ABA1
MKK2
ERF9
MPK4
PDC
WAK
PHS2
CYP76C7
PLDa
BRI1
LTP4
GRAS1
LOX3
M3KA
BR6OX2
CAF1
Serine kinase
PP2C

Genbank
BF011062
BI073128
BQ487860
BQ487982
BQ488179
BQ488466
BQ488795
BQ488850
BQ488935
BQ489189
BQ490338
BQ582382
BQ582629
BQ582634
BQ583369
BQ583692
BQ584083
BQ584136
BQ584422
BQ585699
BQ585998
BQ586375
BQ586464
BQ586635

6
0
2
0
0
0
nd
2
nd
nd
0
3
4
nd
3
38
38
1
2
2
3
6
264
nd
3

12
0
3
0
0
nd
0
1
0
nd
0
1
2
NC
1
0
0
0
1
0
0
7
1
1
7

18
20
3
1
0
0
nd
2
nd
nd
0
2
nd
nd
5
2
2
2
2
2
2
2
2
2
3
71

H2O

Rhizopus
24
nd
1
nd
nd
nd
nd
1
nd
nd
0
2
nd
nd
3
2
3
24
nd
1
2
2
nd
nd
nd

6
0
0
nd
nd
nd
nd
2
nd
nd
nd
5
nd
nd
6
nd
2
2
nd
5
4
5
nd
nd
4

12
nd
3
nd
nd
nd
nd
2
nd
nd
0
1
nd
nd
2
nd
27
2
80
3
3
1
28
nd
14

18
0
250
0
0
11
nd
3
nd
nd
0
2
nd
nd
6
3
3
3
1
3
6
5
1
nd
2

24
0
1
0
0
0
0
2
nd
NC
0
3
nd
nd
5
57
58
1
2
3
5
4
1
nd
4

6
1
1
nd
nd
1
1
1
nd
nd
1
1
nd
nd
1
nd
1
1
1
1
1
1
1
nd
1

18
nd
1
1
1
nd
nd
1
nd
nd
0
6
nd
nd
1
1
1
5
2
1
1
1
1
nd
10

24
0
2
0
0
0
nd
2
1
nd
0
7
1
NC
1
4
1
2
1
0
1
1
1
1
1

Table 2.1 continued
RD26
CML41
MKK9
RPN10
Myb
Protein kinase
GRP2
DREB2C
MPK4
CDKC
MKK3
MBF1C
NSP5
MPK6
ATLP
PXA1
MKK9
BAM1
HDA1
PER50

BQ586991
BQ587396
BQ587848
BQ589925
BQ591669
BQ590125
BQ592168
BQ592254
BQ592267
BQ592936
BQ594412
BQ594558
BQ594578
BQ594736
BQ594810
BQ595543
BQ595738
BU089560
CF543165
CK136719

2
52
0
1
nd
nd
nd
nd
nd
nd
1
2
3
1
nd
1
2
4
2
2

1
1
3
2
NC
nd
1
nd
nd
nd
1
0
0
0
nd
0
2
1
1
2
a

2
5
1
2
nd
nd
19
nd
nd
nd
1
2
1
1
nd
1
1
2
2
2

1
0
0
nd
nd
nd
nd
nd
nd
nd
1
nd
nd
nd
nd
nd
5
3
1
nd

2
7
0
nd
nd
nd
nd
nd
nd
nd
1
nd
nd
1
nd
nd
2
4
2
3

1
1
1
3
nd
nd
nd
nd
nd
nd
1
2
1
1
nd
1
1
8
6
4

2
1
0
5
nd
nd
nd
nd
nd
nd
1
6
nd
2
NC
4
3
2
4
2

2
0
0
3
nd
nd
nd
nd
nd
nd
1
2
nd
0
nd
22
4
3
2
3

1
1
1
nd
nd
nd
1
nd
nd
1
1
1
nd
nd
nd
1
1
1
1
1

1
0
0
nd
nd
nd
nd
nd
nd
nd
0
1
1
1
nd
0
2
2
1
1

1
1
0
1
nd
nd
3
nd
NC
nd
0
1
1
0
nd
0
1
2
1
49

Arabidopsis thaliana genes

SP7622
Aphanomyces
a

At gene
M3Ke1
GER3
MKK9
NCED4
ATL2

Genbank
BF011062
BI073128
BQ487860
BQ487982
BQ488179

6
2
1
37
23
4

12
8
0
nd
3
nd

18
68
25
39214
3028
1

H2O

Rhizopus
24
0
0
2
24
0

6
69
10
1505
214
1
72

12
240
85
681
2172
nd

18
1
0
5
27
0

24
0
0
21
13
0

6
1
1
1
1
nd

12
0
0
nd
4
nd

18
1
0
0
23
nd

24
2
0
7
17
nd

Table 2.1 continued
RBOHD
BQ488466
ABA1
BQ488795
MKK2
BQ488850
ERF9
BQ488935
MPK4
BQ489189
PDC
BQ490338
WAK
BQ582382
PHS2
BQ582629
CYP76C7
BQ582634
PLDa
BQ583369
BRI1
BQ583692
LTP4
BQ584083
GRAS1
BQ584136
LOX3
BQ584422
M3KA
BQ585699
BR6OX2
BQ585998
CAF1
BQ586375
kinase
BQ586464
PP2C
BQ586635
RD26
BQ586991
CML41
BQ587396
MKK9
BQ587848
RPN10
BQ589925
Myb
BQ591669
kinase
BQ590125
GRP2
BQ592168
DREB2C
BQ592254
MPK4
BQ592267
CDKC
BQ592936
MKK3
BQ594412
MBF1C
BQ594558
NSP5
BQ594578

15
0
nd
nd
6
0
3
90
2
0
2
nd
84
1
nd
6
2
4
1
1
4
2
4
0
nd
103
4
2
2
129
37
4983

8
0
0
nd
0
nd
0
0
12
0
0
0
nd
0
0
2
0
5
0
0
0
0
1
0
nd
12
nd
0
0
0
3
nd

4157
1
39
nd
0
1
304
49
0
nd
119
47
7731
51
132
104
28
14
284
25
970
24
111
nd
19
991
nd
31
76
48
373
nd

16
0
1
nd
2
0
5
1
0
0
0
5
13
0
1
2
1
2
6
0
nd
0
2
0
nd
27
nd
0
1
1
2
37

4795
0
2
nd
657
0
197
4
0
0
0
35
31
13
5
16
18
0
42
5
26
0
8
2
nd
257
3
7
8
3
2
1079
73

15376
2
101
nd
4
2
770
185
1
nd
159
684
41
64
371
1886
nd
344
955
143
586
185
1020
nd
nd
3801
nd
198
440
447
28
nd

8
0
1
nd
2
0
3
0
0
0
0
1
258
9
1
2
0
3
4
0
1
1
1
0
nd
39
0
0
1
1
5
1083

117
0
0
0
74
0
2
0
0
0
0
0
17
0
0
1
0
1
11
0
1
0
1
0
1
25
nd
0
0
8
4
19

1
1
1
1
1
1
1
1
1
1
1
1
1
1
nd
1
1
1
1
1
1
1
1
1
nd
1
nd
1
1
1
1
1

9
0
nd
nd
1
0
1
0
0
nd
0
0
nd
0
nd
1
nd
2
0
0
0
0
123
nd
nd
14
nd
0
1
0
nd
nd

566
0
0
nd
2
1
7
1
0
nd
1
1
nd
1
1
3
1
1
64
0
6
1
0
0
nd
32
nd
1
1
1
0
nd

55
0
0
nd
1
0
5
0
0
nd
0
1
nd
0
2
2
0
2
127
0
3
0
1
nd
1
4
1
0
1
1
2
nd

Table 2.1 continued
MPK6
BQ594736
ATLP
BQ594810
PXA1
BQ595543
MKK9
BQ595738
BAM1
BU089560
HDA1
CF543165
PER50
CK136719

nd
nd
316
1
1
6
0

0
nd
0
0
0
0
0

44
0
29
39
20
141
1
a

0
nd
1
0
0
2
0

nd
nd
409
12
12
16
0

464
nd
nd
165
19
1039
7

Arabidopsis thaliana genes

74

0
0
0
0
1
2
0

nd
0
0
0
0
1
0

1
nd
1
1
1
1
1

nd
nd
0
0
nd
1
0

0
1
0
1
0
3
0

24
nd
1
0
0
2
0

(BQ585699), Br6OX2 [Brassinosteroid 6 oxidase] (BQ585998), CAF1 [CCR4 Associated Factor
1] (BQ586375), PP2C [Protein Phosphatase 2C] (BQ586635),
CML41 [Calmodulin-like 41](BQ587396), MKK9 [MAPK Kinase 9] (BQ595738), and BAM1
[Barely Any Meristem 1] (BU089560) (Table 2.2). PP2C and PDC were also upregulated in the
water treatment, and therefore not exclusive to the pathogen stimuli. These upregulated genes
included a mixture of putative abiotic and biotic stress responses as well as growth and
development regulated genes. ACH185 specific responses to the individual treatments were also
identifiable. Aphanomyces upregulated genes (>5 fold increase compared to Rhizopus and H2O
treatments at any time) for ACH185 were M3Ke1 [MAP2K Kinase epsilon 1] (BF011062), LTP4
[Lipid transfer protein 4] (BQ584083), CML41, CAF1 and GRP2 [Glycine-rich binding protein
2] (BQ592168). The Rhizopus treatment in ACH185 had a higher number (18) of transcripts than
both the Aphanomyces (11) and H2O (4) treatment with a fold change >3. A putative GER3,
ATL2 [Arabidopsis toxicos en levadura 2] (BQ488179), BRI1, GRAS1 [Scarecrow-like 13]
(BQ584136), and PXA1 [peroxisomal ABC transporter] (BQ595543) were induced when treated
specifically with Rhizopus. The transcripts detected were again a mixture of abiotic, biotic and
growth related responses.
In the water treatment of ACH185, 31 of the genes detected were expressed at basal levels
and 6 were upregulated (≥ 3 fold change). Five of the six genes upregulated in the H2O treatment
were also upregulated in the pathogen treatments, only a putative PER50 [peroxidase]
(CK136719) had significantly higher expression in the H2O treatment compared to the pathogen
treatments in ACH185. One gene, a putative MPK4 (BQ592267) was only detectable in the H2O

75

Table 2.2 Genes upregulated and associated with response to Aphanomyces and Rhizopus
treatment over time in ACH185 using qPCR.

ACH185
Gene name
GER3
PDC
BRI1
Br6OX2
CYP76C7
M3KA
CAF1
CML41
MKK9
BAM1

Putative Role
Stress regulated (Abiotic)
Growth
Stress and Growth
Stress and Growth
Undetermined
Growth
Stress regulated (Biotic)
Stress regulated (Undetermined)
Stress signaling (Both)
Growth

76

treatment, not the pathogen treatments, but quantity of expression was not determined due to the
lack of a reference.
In SP7622, differences were observed in the level and patterns of expression between the
three treatments as soon as 6 h and continued until the last time point measured (24 h). All of the
48 genes tested were detectable in SP7622 in at least one time and treatment. SP7622 showed an
induction of gene expression in response to the Rhizopus treatment at 6 h with maximum
expression detected at 12 h. In response to the Aphanomyces treatment, maximum gene
expression was observed at 18 h. Many of the genes tested were upregulated in response to both
pathogens, but not the control (H2O) treatment (Table 2.3). Of the forty-eight genes tested, only
RBHOD [Respiratory Burst Oxidase D] (BQ488466), PDC, PLDA [Phospholipase D alpha]
(BQ583369), myb (BQ591669), and ATLP [Thaumatin-like protein] (BQ594810) were not
upregulated in either of the pathogen treatments at the times observed in SP7622. Putative
NCED4, RBOHD, WAK [Wall Associated Kinase] (BQ582382), PP2C, RPN10 [Regulatory
particle non-ATPase 10], GRP2, and MPK6 (BQ594736) were also upregulated in H2O with a
fold change >3. The genes also present in the H2O treatment included putative abiotic stress
response genes shown to be involved with water stress, genes involved in growth and
development, and two genes putatively involved in defense responses.
In SP7622, expression differences were also observed between the Rhizopus sp. and A.
cochlioides pathogen treatments. The Rhizopus and Aphanomyces treatments elicited the
induction of similar genes, with 28 genes being upregulated in response to both the pathogen
treatments. Differences in the timing of expression varied between the pathogen treatments in
SP7622. Under Aphanomyces treatment in SP76222, plant responses were detected at 6 h,
77

Table 2.3 Genes upregulated and associated with pathogen response to both Aphanomyces
and Rhizopus treatments in SP7622 over time using qPCR

SP7622
Gene name
M3Ke1
GER3
MKK2
WAK
PHS2
BRI1
LTP4
GRAS1
LOX3
MAP3KA
RD26
Br6OX2
CML41
MKK9
GRP2
MPK4
DREB2C
Kinase
CDKC
MKK3
MBF1C
NSP5
PXA1
BAM1
HDA1
CAF1

Putative Role
Signaling
Stress regulated (Abiotic)
Stress signaling (Abiotic)
Growth
Growth
Stress and Growth
Stress regulated (Abiotic)
Stress regulated (Biotic)
Stress regulated (Biotic)
Growth
Stress regulated (Abiotic)
Stress and Growth
Stress regulated (Undetermined)
Stress signaling (Both)
Stress regulated (Abiotic)
Stress signaling (Biotic)
Stress regulated (Abiotic)
Undetermined
Growth
Stress signaling (Biotic)
Stress regulated (Abiotic)
Growth
Growth
Growth
Stress regulated (Both
Stress regulated (Biotic)

78

downregulated at 12 h, and reactivated at 18 hours. Stress and defense related mechanisms were
evident and upregulated at 6 h and again at 18 h, before returning to basal levels at 24 h in the
Aphanomyces treatment. In the Rhizopus treatment of SP7622, upregulation was seen at 6 h and
12 h followed by a return to basal levels at 18 and 24 h. In the SP7622 Aphanomyces treatment,
8 genes were upregulated with a fold change >3, compared to the Rhizopus and H2O treatments.
CYP76C7 and a putative serine/threonine kinase (BQ590125) were only upregulated in the
Aphanomyces treatment of SP7622.
In the Rhizopus treatment of SP7622 there was a greater number (26) of genes with a >3 fold
increase in expression compared to the Aphanomyces and H2O treatments. Genes solely
expressed in the Rhizopus treatment of SP7622 were a MPK4 (BQ489189) and a peroxidase.
RPN10, a putative serine/threonine kinase, ABA1, PDC, PER50, and MKK9 showed no change in
expression in SP7622 in response to the Rhizopus treatment. Genes classified as growth or
developmental were upregulated during the pathogen stress in both varieties in response to at
least one of the pathogen treatments. Unlike ACH185, none of the genes measured had an
upregulation only in the H2O treatment. Both the varieties tested showed readily identifiable
responses to the treatments tested throughout the 24 h measured.
Expression patterns common and distinct between the two varieties in a particular treatment
were observed over time. In particular, ACH185 had a higher number of genes (7 to 24) not
detectable at any given time compared to SP7622 (2 to 16) regardless of the treatment. An
increase in gene expression in both varieties indicated that both treatments were initiating a
response, in the plant, as soon as 6 h. In response to the pathogen treatments, early recognition of
Aphanomyces cochlioides and Rhizopus sp. and subsequent downregulation was evident for both
79

varieties tested. However, in SP7622 a secondary increase in gene expression was seen in the
Rhizopus (12 h) and Aphanomyces (18 h) treatments, but there was no corresponding increase in
gene expression in ACH185.
Aphanomyces treatment differences between the two varieties showed 5 genes were
upregulated in both varieties. BRI1, LTP4, CAF1, CML41, and GRP2 were upregulated in
common with both varieties under the Aphanomyces treatment. The remaining genes upregulated
in either SP7622 or ACH185 showed no regulation or a decrease in expression over time in the
other variety. LOX3 (BQ584422), PP2C, CDKC, RBOHD, GRP2, GRAS1, HDA1, and RD26
(BQ586991) all showed no activity (or a decrease) in Aphanomyces for ACH185, while all of
these genes were upregulated in SP7622. SP7622 showed little or no activity (or a decrease) in
PDC, PLDA, ABA1, myb, and PER50 under Aphanomyces treatment while these genes were
upregulated in ACH185.
Rhizopus differences between the two varieties also showed a large variation in the number
(16 in ACH185 and 38 for SP7622) and types of genes being upregulated in response to the
pathogen. Genes were considered upregulated if they had >3 fold increase compared to the initial
control levels (6 h H2O). Upregulated genes, in both varieties, in the Rhizopus treatments were
BRI1, GRAS1, CAF1, PP2C, and PXA1. Out of the 35 genes upregulated in SP7622 in response
to Rhizopus, MPK4 (BQ592267), MKK2, WAK, PHS2, serine/threonine kinase, GRP2 and a
CDKC were not detectable in ACH185. The remaining genes upregulated in SP7622 and
detectable in ACH185, at lower levels were M3Ke1, MKK9, NCED4, RBOHD, ABA1, MPK4
(BQ489189), LTP4, LOX3, Br6OX2, RD26, RPN10, MKK3, MBF1C (BQ594558), NSP5, MPK6
and HDA1. Of the 22 genes upregulated in ACH185 in response to Rhizopus only a putative

80

PDC and CYP76C7 were not in SP7622 under the Rhizopus treatment. Many of the genes with
no change in expression in ACH185 in Rhizopus stress were signal cascade components.
An upregulation of stress-related genes was also detected in the control (H2O) treatment.
Certain genes (PER50, LTP4, and PLDA in ACH185 and NCED4, RBOHD, RPN10, Br6Ox2,
CML41, HDA1, and MPK6) were upregulated (3 fold and higher) in the water treatment but not
in both varieties. ACH185 had high levels (10 fold increase or greater) of PER50 and PP2C
transcription in the water treatment over time compared to 6 h. SP7622 also had upregulation of
multiple genes under the water treatment. In the ACH185 H2O treatment, putative ABA1,
CYP76C7, MKK2, GRP2, PDC, PHS2, CAF1, BRI1, RD26, MKK9, MPK4, CDKC, PER50,
MKK3, PLDA, and LTP4 were detectable at low levels and present, though not always
upregulated, in SP7622. ATL2, M3KA, protein kinase, ATLP, Br6OX2, and ERF9 (BQ488935)
were down regulated or not present in SP7622 compared to ACH185. ACH185 and SP7622 had
a basal level of expression of the genes tested in the H2O treatment over time. Of the genes that
overlapped between the two varieties with a fold increase >3, GRP2 is a putative glycine-rich
binding protein, induced by cold and a putative PP2C is a negative regulator of ABA. The
simulated flooding stress experienced by the seedlings in the H2O treatment did not induce the
metabolic, growth and signaling genes that the pathogen treatments did.
Varietal modes of stress response conserved between germinating seeds and developing
seedlings were identifiable using gene expression of the putative varietal molecular markers
previously identified in Chapter 1. In SP7622, the 9 genes upregulated (>10 fold increase) during
germination and correlated specifically with the SP7622 hydrogen peroxide response showed an
upregulation in the pathogen treatments at 3 wks. A putative RD26, MPK4, MKK3, MKK9,
81

BAM1, Br6OX2, LOX3, BRI1, and a putative NSP5 were upregulated in both of the pathogen
treatments tested for SP7622. Those genes, MKK9, the putative serine/threonine kinase, PP2C,
and CML41, specifically upregulated in the H2O treatment of SP7622 during germination were
also upregulated in both of the pathogen treatments. These germination molecular markers were
upregulated in the pathogen treatments, but not the H2O treatment with the exception of PP2C.
Of the genes found to be upregulated (>10 fold) in the H2O2 treatments in ACH185 during
germination, CML41, LTP4, and CAF1 were the only H2O2 germination specific transcripts
upregulated in both pathogen treatments (Table 2.2). MPK4 (BQ592267), also associated with
H2O2 germination, was not detectable in either of the pathogen treatments. Those genes
specifically upregulated in ACH185 in the H2O and not the H2O2 treatment during germination,
MKK9, NSP5, and ERF9 had less than 3 fold changes in expression in 3 wk seedlings. MKK9
(BQ587848) and MBF1C were detectable in the 3 wk seedlings, but had minimal expression.
Between varieties, pathogen and H2O2 treatments and developmental stages (germination
and 3 wk seedlings) only three genes were upregulated in common. During germination, few
genes were conserved between varieties and treatments. MKK9 (BQ487860) was the only gene,
out of the 48 genes tested, upregulated exclusively in the H2O treatments for both varieties
during germination. In 3 wk seedlings, this gene had no visible shared activity. In H2O2, there
were no genes exclusively upregulated in both varieties during germination. However, 10 genes
out of the 48 tested were associated with germination vigor. Genes that were associated with
germination vigor (genes with a high amount of expression over time in treatments with higher
82

germination) were LTP4 (BQ584083), MPK4 (BQ592267 and BQ489189), PER50 (CK136719),
HDA1 (CF543165), BAM1 (BU089560), MKK9 (BQ595738), MKK3 (BQ594412), BRI1
(BQ583692), and CYP76C7 (BQ582634). Of those 10 genes, BAM1 (BU089560), MKK9
(BQ595738), BRI1 (BQ583692), and LTP4 (BQ584083) were also upregulated (>3 fold change)
across both pathogen treatments in both varieties in 3 wk old seedlings. The remaining genes
were either upregulated in all but one treatment of a variety or were varietal specific.

DISCUSSION
In Michigan, continuous Aphanomyces pressure has resulted in a level of resistance being
bred into most varieties grown, including two moderately vigorous varieties, ACH185 and
SP7622, which also show resistance to Rhizopus spp. in the field and lab (Coe 1971; Naegele
unpublished data). At 3 weeks of age, differences in gene expression between the two varieties
under stress, flooding and pathogen treatments were readily detectable, despite no visible
morphological differences in response to the stresses (Figure 2.1). Differences in gene expression
however, displayed the large heterogeneity in gene response possible between sugarbeet varieties
and may provide some insight into the genetic diversity behind pathogen and flood response in
seedlings. Literature has shown that the boundary between biotic and abiotic response genes is
no longer as clear as once thought (Mantri 2010; Jain 2010, Chapter 1). Crosstalk between the
abiotic and biotic response pathways allows diverse signals to converge through signaling
molecules, hormones, and metabolism to elicit a common response. This research showed a
number of biotic, abiotic and growth-related genes being actively transcribed in 3 wk seedlings
during pathogen and flooding treatments. These early seedling response mechanisms to biotic

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Figure 2.1 Roots of ACH185 and SP7622 prior (0 h) and post (1 wk) treatment with
Aphanomyces cochlioides or Rhizopus sp..

84

and abiotic stress may have large overlaps in the genes regulated or the pathway components for
abiotic and biotic stress may not be well partitioned during early development.
Quantitative analyses revealed eight genes, out of the 48 tested, shared between both
varieties and pathogen treatments in 3 wk seedlings. The lack of shared genes between varieties
indicates that the response to Aphanomyces cochlioides is highly varietal specific and may
provide alternative sources of resistance for breeders. Between varieties, the plant’s response to a
fungal and an oomycete stress was associated with the induction of BRI1, CAF1, GER3, MKK9,
Br6OX2, M3Ka, BAM1, and CML41. CAF1 has been associated with biotic response (Sarowar
2007), CML41, has an undetermined stress response function (Denoux et al. 2008), and BRI1, is
part of an abiotic and biotic signaling cascade involved in stress response and growth (Che et al.
2010). GER3 has been implicated in cold and defense response (Swarbreck 2008; Larkindale
2007). MKK9, a MAPK kinase known to be involved in ethylene biosynthesis, activates MPK3/6
under certain stress conditions (Zhou 2009; Yoo 2008). Br6Ox2 is a component of Br
biosynthesis (Nomura 2005), and M3Ka has no defined role, but it thought to be involved in ATP
binding and development (Swarbreck 2008). BAM1 is a receptor kinase implicated in shoot and
floral development in Arabidopsis (Hord 2006). The genes upregulated in both pathogen
treatments had putative functions involved in abiotic and biotic stimulated stress response and
growth. Many of these putative genes belong to gene families and the closest Arabidopsis
homologue may or may not indicate their true function or role. Full-length cDNA and protein
characterization is needed to confirm the functionality and identity of many of these genes.
Putative BRI1, a component of the brassinosteroid receptor, aids in broad-spectrum resistance
to drought, salt, temperature and pathogen attack in Arabidopsis (Che 2010). Additionally, BRI1
may have some role in regulating a response to multiple hormones as Arabidopsis bri1 mutants
85

show sensitivity to ethylene, ABA, GA and auxins (Swarbreck 2008). Some evidence also
suggests that BRI1 may modulate hypocotyl elongation (Krishna 2003; Steber and McCourt
2001). While it is known that high temperatures can induce production of Br, the role of Br in
pathogen response is still unclear (Che 2010). Our data of BRI1 and Br6OX2 suggest that Br is
being produced in response to the pathogen treatments. Upregulation of Br, during sugarbeet
seedling pathogen response, may be involved in increased seedling growth, hormone regulation
or pathogen defense.
CAF1 was another gene shared between the two varieties in response to the pathogens tested.
Overexpression of CAF1 in chili pepper and tomato resulted in higher growth (larger cells) and
thicker cuticles, which may have been responsible for its role in successful defense against a
bacterium, Xanthomonas axonopodis, and an oomycete, Phytophthora infestans (Sarowar et al.
2007). It has also been shown that CAF1 may play a role in pathogen defense response
modulation in Arabidopsis (Liang 2009). Other research on CAF1 in other organisms suggests
that it also has a role in mRNA turnover (in mice and yeast), which may be how it modulates
defense responses (Berthet 2004; Liang 2009). In sugarbeet seedlings, CAF1 may be contributing
to both enhanced growth and cuticle development to prevent infection.
CML41, a gene shared between both varieties in both pathogen treatments, has no known
biological function but is putatively involved in Ca2+ binding and stress response in Arabidopsis
(Baev 2010; McCormack 2005). Recent research however, has suggested CML41 operates in the
chloroplasts and functions in defense response by suppressing or “dampening” the immune
response (Baev 2010). Our data supports this role in ACH185 pathogen response, as CML41 is
the most highly expressed gene at 6 h in both the Aphanomyces and Rhizopus treatments and
subsequently no large gene activation was seen in this variety. In SP7622, CML41 expression is
86

moderate to low in both the pathogen treatments and high levels of expression are seen at 18 h
for the Aphanomyces treatment and 12 h for the Rhizopus treatment, the time points before
expression returned to basal levels. Alternatively, CML41 may be a byproduct of enhanced
growth and energy mobilization in response to pathogens and not necessarily involved in the
response.
During germination, SP7622 had little to no expression of CAF1 under either treatment, but
H2O2 germinated ACH185 seedlings had high levels of CAF1 induction (Chapter 1). This
induction during early germination may have resulted in increased cuticle thickness, which in
part may be aiding in the resistance to pathogens and drought stress during later development.
Since SP7622 did not produce CAF1 during germination, the role of CAF1 as a marker for
seedling stress tolerance during germination and 3 wk stress is limited. Also, CAF1 expression
during germination may be contributing to the later differences in pathogen response seen
between these two varieties if CAF1 was contributing to cuticle thickness. As CAF1 was not
expressed during germination in both varieties, the ability to use putative CAF1 as a stress
resistance marker to screen germinating seedlings may be limited to specific varieties. BRI1 and
CML41, genes found to be upregulated in response to both pathogens in both varieties, were
associated with increased germination vigor in both varieties (Chapter 1). This indicates a
possible conserved role in germination and seedling vigor and a potential use as a molecular
marker for assessing vigor, germination and seedling, across varieties to improve the efficiency
of the breeding process.
Each variety had unique patterns of gene expression in response to a pathogen treatment
when ACH185 and SP7622 were compared. The difference in response could be due, in part, to
the times observed; SP7622 may have a later or earlier recognition of the pathogen, or the
87

differences could be in the mode of pathogen recognition. Pathogens utilize different modes of
infection, and different plant species or varieties can utilize different physical and genetic
mechanisms, e.g. growth habit, trichomes, R genes, etc. to overcome the same stress (TortoAlalibo 2009; Xiao 2004). Many of the genes observed in our study were common between the
pathogen treatments within a variety but not between varieties. The limited number of treatmentspecific genes might be a reflection of the type of genes chosen to analyze, i.e. conserved
elements of stress pathways, and not similarities in the modes of defense.
In response to the Rhizopus treatment, both ACH185 and SP7622 had some level of
upregulation at 6 h. SP7622 had an increase in the number of genes upregulated in stress
response genes and transcription factors involved in reducing and transporting H2O2, increasing
metabolism and growth, and signaling, indicative of recognition and response to a pathogen.
Upregulation in response to the pathogen was visible at 6 h and expression peaked for most
genes upregulated at 12 h before returning to basal levels. ACH185 had less genes expressed in
the Rhizopus treatment, possibly due to an inability of Rhizopus sp. to infect the beet through
physical prevention of infection, e.g. increased cuticle thickness resulting from the increased
expression of CAF1 during germination. The possibility of defense by exclusion is also
consistent with MPK4 and MPK6 expression data, which indicated little or no expression in
ACH185 under the Rhizopus treatment, but an upregulation in SP7622. While the data does not
show an upregulation of MAPK expression in ACH185 under pathogen stress this may also be
caused by a difference in the time of expression and not necessarily the lack of infection by the
pathogens due to physical barriers. In addition there may be an alternative response pathway
utilized by ACH185 in response to Rhizopus sp. and A. cochlioides not tested in this study.

88

In the Aphanomyces treatment, ACH185 had some level of pathogen detection, denoted by
the upregulation of genes at 6 h post treatment, but gene activation was low in general. This
again may be indicative of a lack of initial infection through increase cuticle thickness (CAF1), a
difference in the timing of expression, or an alternative network of genes. In SP7622 the
Aphanomyces response again had upregulation at 6 h, followed by a decrease at 12 h and a
subsequent increase at 18 h before returning to basal levels. The 6 h delay in expression between
the SP7622 Rhizopus and Aphanomyces treatments may be due to the nature and virulence of the
pathogens. In adult beets, Rhizopus is a weak root rot and postharvest pathogen, while
Aphanomyces is a devastating seedling disease and can cause a root rot in adult plants (Harveson
2009). In other species, it has been shown that Rhizopus spp. can cause a preemergence damping
off (Howell 2002; Jackson 2004). Rhizopus may be a weak pathogen of sugarbeet seedlings, and
the activation of most defense genes is not necessary. The differences in expression timing
between the pathogen treatments for SP7622 may also be due to differences in the pathogen’s
mode of infection. Rhizopus sp. may lack the plant defense suppression machinery, present in
Aphanomyces, necessary to cause disease without the aid of additional stress or it may be
germinating and coming to contact with the host tissue more rapidly and in greater quantities.
Disease resistance depends on successful recognition of the invading pathogen and rapid
induction of defense genes (Boller and Felix 2009; Faurie et al. 2009; Jones and Dangl 2006;
Nimchuk et al. 2003; Park and Paek 2007). Pathogenic organisms have evolved mechanisms to
suppress the natural immune system (MAPKs) of the plant and colonize the host tissue causing
disease (Bent and Mackey 2007; Espinosa et al. 2003; Gudesblat et al. 2009; Houterman et al.
2008). Plants in turn have adapted elaborate systems to recognize the suppression of their basal
defense and re-activate them (Lin 2007; Hardham 2010). Rhizopus sp. may be activating plant
89

defenses upon initial contact, and be unable suppress the plants basal immune system, resulting
in resistance. A. cochlioides may be able to suppress the plant’s immune system, suggested by
the repression of gene expression at 12 h, however the resistant plant can overcome the
repression and reactivate defenses, suggested by the upregulation of genes at 18 h in SP7622.
These two pathogen treatments, despite transcript and timing differences, activated many of the
same genes. Large overlaps in the genes expressed during defense can occur in Arabidopsis
between pathogens with differing virulence and modes of infection, but transcript quantities and
timing of those genes can vary dramatically (De Vos 2005). While further studies using
additional times, isolates and genes are necessary to further explore the differences in response to
Aphanomyces cochlioides and Rhizopus sp. between the two varieties tested; these differences in
recognition and response may provide useful information for breeders looking to improve
seedling resistance.
Flooding response in the two varieties tested showed unique and common genes being
upregulated. Both varieties exhibited basal levels of most of the 48 genes tested and an
upregulation of certain abiotic stress genes. Genes, associated with water stress response,
common between the two varieties PP2C and GRP2. These two genes are both abiotic stress
related and may be part of an H2O or motion-related response that is conserved between
varieties. PP2C is a Protein Phosphatase 2 C known to negatively regulated ABA signaling
(Hubbard et al. 2010; Ma et al. 2009). During drought conditions, ABA upregulation can
increase drought tolerance by closing stomata and conserving water (Chak et al. 2000; Fujita et
al. 2005; Kim et al. 2010). However in flooding, ABA is downregulated to enhance growth
(Chen 2010). The upregulation of PP2C would likely result in a downregulation of ABA, which
could enable the seedlings to enhance their growth. GRP2 is a glycine-rich binding protein
90

involved in cold and osmotic stress response in Arabidopsis (Carpenter et al. 1994; Karlson et al.
2002; Kim et al. 2007a). Functional characterization of GRP2 in Arabidopsis showed that it
enhanced seed germination under salt stress, but had no effect on germination or seedling growth
under osmotic stress (Kim et al. 2007b; Lee et al. 2009). The slight increased expression seen in
both beet varieties indicates that this gene may play a role in osmotic stress in beet seedlings.
The lack of H2O induced transcripts was unexpected, since many of the stress genes chosen
had known phenotypes under abiotic stresses. Early seedlings may be more resistant to flooding
stress, or pathogen detection and defense utilizes an array of genes that differ from those utilized
by adult plants. These pathogen treatments also simulated flooding and motion stress since the
seedlings were submerged in water and constantly shaking. The upregulation of abiotic response
genes in the pathogen treatments were likely in response to the pathogen stimuli and not flooding
or motion since most of these genes were not upregulated in the water treatment.
3 wk seedlings exhibited a range of abiotic and biotic, growth and metabolic gene responses
to pathogen and flooding stress. Pathogen treatments showed high similarity within a variety,
and more differences between varieties. The identification of varietal specific defense responses
to a pathogen provides useful information to breeders, improving disease resistance. However,
those small numbers of genes shared between varieties have the potential to become molecular
markers to screen resistance. Molecular markers to predict or assess the ability of a plant to
withstand germination and early seedling stress would be indispensible. Of the genes upregulated
in vigorous germination in both varieties, only, BRI, CML41, LTP4, and MKK9, were also in one
or more of the pathogen treatments tested on the 3 wk seedlings. These particular genes may be
useful as expression molecular markers for germination and early seedling vigor. Increased
expression of these genes in a given variety during the first 24 h of germination under H2O
91

conditions may be indicative of stress tolerance during the first few weeks of growth. More work
to determine the efficacy of these genes in predicting seedling vigor is needed, but this study
serves as a first approximation of the genetics behind predictive seedling vigor in sugarbeet.

92

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100

APPENDIX A
SUPPLEMENTARY TABLES

101

Appendix Table 1.1 Sugarbeet ESTs with sequence similarity to Arabidopsis proteins involved in stress response, hormone
biosynthesis and growth used for primer design. Sequences and primers in bold were used for qPCR analyses
Plant Growth and Development Regulated Genes
*

Bv Accession
CF542917
CF430002
BQ593316
BE590301
BE590301
BF011057
AW697779
BF011036
BI096111
BI543285
BQ588646
BQ595434
CK136263
BQ584431
BQ594284
CF543263
BE590328
BQ591856
BQ586318
BQ588744
BQ594788
BI543526
BI096046
BQ487636
BG577441
BQ487747

Forward Primer
ACAGAGGGACCCGACTTATTG
GGGGCAGCTGTTGGTGAT
GTCCGCTCTTTGTCTTTCTTTT
TAGGAGCAGGCATACATA
TAGGAGCAGGCATACATA
GTTCCGTGTCGAGTTTGGTGA
GTTTGCGGCCGTTGGAGT
TTGCGGCCGTTGGAGTTG
GCGGCCGTTGGAGTTG
TGCGGCCGTTGGAGTTG
AAGATCCAACGACCCCCATTTT
ATGCCAAGACCCACTGATGAA
GTATCCATATCCTCCCCACTGCT
CCGGAAAAGTGAAGGAAAGAAAG
GAGCCCATACATTGTTGCCCACCAC
ACATGGTTTCACTTTTGGGGTAG
TCATTTTTGGGGCTGCTTCT
GTATTGTAAAAGGGGGCAGTCATC
CAGATTTGGCGGTAGTGGTGT
TAAAGTGATGATTGCCGATAGG
GCTTGCCGTTTTGGGTTAC
GCACGAGGGAAAGAGAAAACT
TCAACTATAGTCAAGCAGGAAGGA
CTTCTATGGGTGCTATGCTTC
GACCAACCCATGATGAGATAGACT
GACGCAACACCCATCAGAGA

Reverse Primer
TCCCGCCTGTTGATTGTTAC
CATGATTCCCGATTGTGTCTG
TTTCCACCAATTCCACCAT
ACCGCCCAATCCCCTCAAG
GAGGTGTGACAAGGGAAGT
GGCCCCCTTCCGTAGTATTG
AGCAGGCCTGTGAGTGTAT
GCGAGTTGGATCAGCGAAAAAG
TAGAGCCTTTCAGTTACGAGTTGG
TAGAGCCTTTCAGTTACGAGTTG
ACTACCACGGCGGAACTCAG
TTGCCCCCACTCTAACTG
TTTTGCGGCGAACACATTG
AAAGGGCCAGCACCAACAGT
GATCCCCAACTCGCTCCCTCATT
TGAGGAAGATCGCCGTGTAATA
AGGGCTGTATACCGTTGTTGATTA
CATTCCGAGCATATAGTGTGGTGT
TCCGGCAGTGAACGAGAGG
GCTGCGTGCTTGGTTCC
CGGGTGCAAATTTGTTGATG
TTGCCAAGGGATCACTAAGG
CAGCTAACATATGGGTGACAACA
AATGCGGCCAGGTAAAT
TGAGCTGCAAGATGATTTACCC
AAGCGTTGGCATTAAAGTTCCT
102

**

At Gene
CYP71A25
NAS4
WOX13
SIP1
SIP1
SIP1
AT3G29970
AT3G29970
AT3G29970
AT3G29970
SOM
APY2
NIC1
NIC1
BGLU40
BGLU12
BGLU12
BGLU41
F1N13.150
AT3G51680
AT3G51680
TPS
PUMP1
ECHID
XTR6
XTR6

E value
1.00E-61
9.00E-41
3.00E-21
2.00E-09
2.00E-09
2.00E-09
9.00E-33
1.00E-32
1.00E-32
1.00E-32
3.00E-69
5.00E-57
3.00E-87
5.00E-51
5.00E-70
9.00E-72
4.00E-62
8.00E-79
2.00E-50
2.00E-46
4.00E-46
7.00E-38
5.0E-108
8.00E-78
2.00E-90
5.00E-86

Appendix Table 1.1 continued
BQ654409
GACCAACCCATGATGAGATAGACT
BQ490338
GCCGATCGCGCCACCTGAAT
BQ587173
CAGCGGCATAAGTGAAATAGAGAC
BQ594578
TGCGATAGCCATAGTAGGAAGGA
CK136733
GGCCGGGGAAACCAAGTCAC
BQ595543
CAATTGGGGTGAGGAACTTT
BQ586903
TGTTGCCCTTCTGTGTCATTCT
BQ582685
TTCATCATCCCAAACACAAA
BQ585998
TAGGGTGCCCAACAATAGTG
BQ586518
GGACGCGTGGGGGCAAAAT
BQ586790
CCACCGACTGCGCTAAGAGAA
BQ582763
GGCTTGCCTTTGATTGGTA
BQ583764
GCGTGGGCGTGAGTTGG
BQ586719
AGTTCCACGCTCTTCC
CF543627
GGGAGGCCTGTGAAGAATAC
BQ583692
CTGCAAAGTGGGAGAAGAACGA
BQ595856
AAGCGTTACCGAGCATTTGTTG
AW777170
TCCCAGTGAGATTGAGAGTT
BF011211
TCCCAGTGAGATTGAGAGTT
BQ592312
GGAAGCCCCTACTGGATGG
AW063034
CGATCACCGGGCTGCTTCTTA
BQ585514
GCCTTGCCACGCTAAAT
BQ594919
GCGGACGCGTGGGTTCAT
BQ583416
GTCGCCAAACAATCAAGTA
BI096232
GGGGGCCTACCAACCTC
BQ583369
GGGGGCCTACCAACCTC
BQ587272
GATTATAGCCGAGCACAGGA
BQ588870
TGGCCGTTTGACAGATT
BQ591910
ACTAGGCGTGCCCCAACC
BI543316
GCTGGTGCCATGAATGCTTTGAT
AW063023
CCGCCGCATATGTTGGAG
BQ587329
TCCTTCCGTTGCTTCTGATG

TGAGCTGCAAGATGATTTACCC
CGGCTCGGCTAAAAGATGAT
CATCGCAGAACCAATCAGAACAC
AATAGTATCAAAGGCCCAAAGGTC
GGGGGTCCAAGCAACAGAATAAGT
AACTAATGCAGGACGATGTGAT
ACCATCGCAGCCAAAAGTATC
TGCATACTTCTTCATCTCACATAA
GTGGGGCTGATAAGAGAAAGA
GTAAGGGGGTCGACAAGGAGAT
TAAAAGACCTGCCAAGACCAGAT
CATTGATGGGAGCAGAAGTTAT
TAGGGTTTTAGCATCGGTGTG
TTCTTCGGGTTCAATG
AAGAACAGTTAAGGCACCAGAGTC
GACCCACCCGACAAGATTATTATG
GGCGGCGATCTGTTTTTGTT
CAATCGAGGTATGGGTAGAAG
CAATCGAGGTATGGGTAGAAG
GAGGTCGAGCGGGTGAAAC
CAACCCCGGGCCACTACTG
GGTTCTCGGTCATCCTCA
TCGCCTTGGACAAATCAGA
CAACATCCGCTGCTATCT
GTGTCGGGGAAGAACTCAAA
GTGTCGGGAAGAACTCAAA
TCGCGGTTTGGTTCACTT
CATTTTGAGCTTCCTTTAC
ATCTCTACATCCCCATCATCAGTG
CCACTCTTCCCCTTCTTCCTTGAT
GAGAATGGCGTGGGGAA
ACTCTCCGTCTCCCCTCTAACA
103

XTR6
PDC
FAB1
NSP5
XTH16
PXA1
LPP2
CYP707A2
BR6OX2
BIN2
BIN2
KAO2
SLY1
GA20OX2
GA2OX2
BRI1
TPC1
WNK1
WNK1
YDA
ER
ER
ER
PERK1
PLDALPHA1
PLDALPHA1
PLDALPHA1
DCL1
PHYB
CESA1
ACT7
AT1G56300

2.00E-92
7.00E-70
3.00E-55
4.00E-67
4.00E-91
2.00E-73
8.0E-107
6.00E-63
4.00E-59
8.0E-109
3.0E-104
3.00E-57
1.00E-10
2.00E-44
7.00E-72
3.0E-101
3.00E-69
1.00E-51
6.00E-53
3.00E-65
3.00E-79
2.00E-71
3.00E-88
8.00E-81
2.00E-55
9.00E-76
1.00E-74
7.00E-44
1.00E-81
4.0E-106
7.0E-152
2.00E-46

Appendix Table 1.1 continued
BQ591929
GGGCTTTCCTCCTTTGTCCA
BQ582477
GAGCACGGCGATCAGAGAAAT
BQ589455
CGTGGGGTTGCGGTTTTT
BQ584462
CAATGGCGTGGTGGTGTA
CF543216
GACGCGTGGGCAAAAAC
BQ584474
GTTCTTATGGGCAGCTTTATTCA
BQ488119
AAGGCCGCGCATTTGAT
CF543420
GATTTTGCGAGACTTTCCACA
BQ587458
ACTGATGTTGAGGGGGATGA
BQ595269
CCACTCGGCCTCAAACT
BQ595231
ATAGGCTGAAGCATAAAAAG
BQ588748
CCACCGACTGCGCTAAGAGAA
BI543360
CACGAGGCCTGTTTGGAAT
BQ587384
CTCCGCCACCGAACTCAAGAAC
BQ588709
AGCTAATTTGGCAACCCTCCTT
BQ584898
CCTTCGCGACATTCTTCTTCTCT
BQ594123
ATATGGCATCAAAGGAGGACT
BI073146
CAAGGGGGCCACAAGATA
BI096176
GCTATGCTGCACTTTCAA
BQ582859
TTGCCCTTCAGCTACTCCATC
BQ591613
AAGCCACCTGGGAAAAAGATG
BQ588316
TTCGGCCTCCATTCCCATCTCCT
EG551187
ATGCGGTGAATGTAGGGATAG
EG551187
ATGCGGTGAATGTAGGGATAG
BQ590743
GACGCGTGGGCTTGTTTCTTA
BQ591253
CCATCTTACCCGCCTCAACTCTTT
BI096237
TCACCGCCATTTCCGATTATTTTC
BQ488277
ACATGTGGAAGCAGCAATCAA
BQ588706
ATGATGGGACTGAGTGGAGACAAC
BF010998
CTGGATTTGCCCGGAGATGATG
BQ593076
TCGGTGATCTACTGAAGGTTGTG
BQ582629
CAGCCTAATTTTAACCCAGACC

CAGCCGCCATTGTTTCTCAC
AGGAGTAGAGTAATGGCGAGAACC
CCACTTCATTCCCTTCCTACACTC
CTTTTTGCCTGTTTCTCCTCTCTA
AAAAATGTAGTGACCCCAATAACT
GACCGCTCTTCCACACTACTTC
TACGTCTCCCCACCTT
TTACATCCGGGCTTTTCTGA
CTCGGCTGGCCTCTGTAAAT
GAAACCGCATCCCCACAGAAAC
AATTCGGGCGTACCAACACAAC
TAAAAGACCTGCCAAGACCAGAT
GTTGGGCTTGAGGGAGT
CATCACCATCCGCATCAACAGACT
GATTCCCCCTGCTCCTATGACT
TCACGCCGGACACCCTCTA
GGAACAGCCAAGCCATTAGGT
ATACCCAAGCCATTCAAAG
CCCGCGAGCTGGACGAC
NCCTATACCCCATCCAACATTTT
GTAGACAACGGAACGACAACAAGA
TGCAATTCCGCCTTCTACAAAACC
GAGCAATTTTAACACCAAGTAG
GAGCAATTTTAACACCGAAGTAG
AATATCCCTTGCTCTGTTTCATCC
CTATGCTGGGATTCGGGGTGCTAT
AGGACACGCAAGGCACGCTCTACT
ACCGCCTTCACTCTTTACTGG
TGATTAAAGCACGCAAACAAGAA
GAGAATGGCGTGGGGAAG
CAGCTCGTCGTAATTTTGTGAA
TTTTGCTTCCCTCCATTCAGTT
104

AT1G56300
CDC2
SPT
ABI8
ABI8
GCL1
IP5PII
HSI2
ETT
ARF6
WNK1
CDKB1
CAT2
AT1G73800
POT
POT
AT1G63640
GER1
GER1
PTR2
CHR5
UCP5
BRK1
BRK1
CPK20
AT2G41380
EFG
SEC
SEC
ACT11
PHS2
PHS2

3.00E-23
8.00E-96
2.00E-16
2.00E-82
2.00E-55
6.00E-77
9.00E-50
7.00E-26
4.00E-75
7.00E-97
2.00E-92
2.00E-87
3.0E-100
2.00E-40
1.00E-67
1.00E-63
8.00E-83
3.00E-06
2.00E-03
3.00E-94
5.0E-107
8.00E-33
2.00E-37
2.00E-37
7.00E-79
7.00E-23
3.00E-86
1.00E-92
1.0E-114
2.0E-122
1.00E-98
5.00E-93

Appendix Table 1.1 continued
BQ489620
CGATAAAGATGGCGATGGTT
CF542908
ATGGAAATGTATAGGCCGCACAAA
BI073176
AGCCCTCATTTCTCCCCTCTG
BQ593574
ACGAGCAGCTGCCGGTGTTACT
BQ595049
CATCGTATTGGTGCAGTGTTGTC
BI073121
GAGCGCCTTGTTCCTGATTGGTAT
BI096180
GTATGTCTAGCGCCCTGGTTGT
BE590397
AACCGCTTATTATTTATCTTCA
BE590397
AACCGCTTATTATTTATTTATCTTCA
BQ487982
TGAGCGCAAAGCAGGAT
BQ489959
GGTGTCCTGCCCTCCTGTCTTA
BQ582708
GAGCGCAAAGCAGGGTCTACTATC
BQ590158
GGCCTCCATTCCCATCTCCTTGTT
BQ586930
AATGCCCCCAAGTGCTCTC
BQ582632
TGGGCTACAGGGTCAGTCCAAATC
BQ583301
AGCCCCCTCGCAAGCCCAAGAAC
BQ588784
GCTTCGACATACCAATCTCTTCTA
BQ582799
CCTTGCCCGCTCTTTTTCA
BQ592936
GCGGTTGCAGCTACAGGAC
BQ584025
GATTTCGGTCTTTCTGTCTTTT
BF011089
CTTCGCGATGAGGGTGTTTCTG
BI073250
CTTCGCGATGAGGGTCTTTCTG
BQ585834
CCTCCAGGATCCGGTAAAAGT
BQ585195
CACCCCCATCAGCCCTAACA
BQ586657
CCAACTCGCGACCCAAATAGAC
CF543447
GTTTAGCGAGGGGACAAGTG
BQ490300
TTGTTTATGGGCCTCTTTATTTTC
BI543415
AGATTCGGGCACTTCAGA
BU089560
CAACAAAATCGCCACCTCCAG
BU089560
TGGGGAATTTCTTGCTTGGTC
BU089560
TTGGGGAATTTCTTGCTTGGTC
EG552800
GGGGTTTTATCGGAGCAG

TCCGGGAAGTCAATAGTA
GCATAGTATTCCCCTTCCCTCTCC
TTGGCCCTCCTTGGTAATCTG
ATGGCGAATTCTCCTTGTTAT
CCGAATTGGCGTATCAGC
TGTTCTTTGCGTCAGCTCCTTGTA
TGAGCGGGGAAGAAGATTTTATT
ACGACCGCCTTGTGTAG
ACGACCGCCTTGTGTAG
CCAAAGAAGGCCAGGTTAGT
GCAAATGCCTCCCCTGTGTCTA
GCAAATGCCTCCCCTGTGTCTA
TGGTGGTGGTGGTGGGTTCTCC
CGTCTCGATCCCCAAATAATG
AGAGCGCCGGAAGGAAGCAGTA
GCATGCATTTAAATCCCGTCAGAA
TGCGGTCCATATCCAGTTCA
CTCCCGTAGGCGTCTCTTCAT
GCGAGACCAGCTAAATCAT
AACTTCTGGCCCGTATTTTCTCTT
GGTCCGGCTCCTTTCCATAAT
GGTCCGGCTCCTTTCCATAAT
GGCCAGGAAAATCGAAAAGTAG
GGCGATTCTTTTGGTAACTT
AGGAACATCGGTGGGTGAAAGTAG
GCAATGCCAATAGCGTGAAT
AGCGGGCCCATGACTCGTA
GGCGTCCCCTTGTTTAG
CTCCCCCTACCCTTTTTCATTCTT
TCGCCCGAAAACTTGTTACTACTA
TCGCCCGAAAACTTGTTACTACTA
GGTGGCACATGGAGGAAT
105

CAM7
HDA9
PHS2
CPK13
GTE6
AT3G52880
EP3
XTR7
XTR7
NCED4
NCED4
NCED4
AT4G24570
CAT2
CSLD4
CESA3
AML4
CDKC
CDKC
CPK17
DTC
DTC
QQT1
AT5G27980
AT5G42830
RPT4A
CESA6
BAM1
BAM1
BAM1
BAM1
FKBP

4.00E-73
2.0E-118
1.00E-76
6.00E-77
9.00E-38
1.00E-92
1.00E-41
3.00E-77
3.00E-77
5.00E-62
5.00E-80
1.00E-63
5.00E-17
2.00E-89
6.0E-110
4.00E-99
3.00E-47
1.00E-71
8.00E-82
2.00E-89
4.00E-92
5.00E-88
3.00E-87
4.00E-27
7.00E-59
1.0E-132
4.00E-84
3.0E-113
0.00E+00
0.00E+00
0.00E+00
4.00E-60

Appendix Table 1.1 continued
BQ584125
CATCAGGCCGAGCAACC
BQ586159
TTGTCACCGGAAACCTAACTT
BQ586036
GCTTTTCGAGAGGGGATGAG
EG551101
CCACTATCGGGGACAACTCAC
BQ488890
TGCATCCGCGAATCGTCAGGTT
BQ488901
ATAGCTCCGTCGACCTCAACTTCC
BI543278
GGCCAGCCAAAGCAGACTAT
BQ593732
AGGTGGGTAGATGATGATGATGAA
BQ594997
TGAAGGTAGAAAGTGGGAGAAGTT
BQ593209
GCGACCGAATCATCACCACAA

TGGGAAAATCAAGATCAACAGTC
AAAAACTCCCCCACTGTAAAAT
AAGCTAAGGCCAAACACAAGAA
TAGGATCGGGCGGAATAAAG
CCCATCCCGGCGCTAATCAAT
CCATCTTTCCGGGTCAATCTTCC
CAACCCCCAGACCAGATGT
TTACGCCGGAAAATGAACGAA
ACCAGCATTAGGACCATCAGTGT
GGCTCAGCGATTTCTCCTCTTCC

ARP4
XCP2
SCO1
FKBP15-1
ANL2
HSFA5
SK11
KATC
AML1
OEP37

BI543568
BI543569
BI543889
BI643062
BI643161
BQ589671
CF543368

TGACGGAAGGGCACCACCAGGAGT
CCGCCGGCACCTTATGAGAAATC
CGGAAGGGCACCACCAGGAGT
CACACCGCCCGTCGCTCCTACC
GACGGAAGGGCACCACCAGGAGT
CCGGCGGCGTCCTAAAAGTAAC
CGCGCCTGCTGCCTTCCTT

18SrRNA
18SrRNA
18SrRNA
18SrRNA
18SrRNA
18SrRNA
18SrRNA

GCGCGTGCGGCCCAGAACAT
CTAAGAACGGCCATGCACCACCAC
AGCGTGCGGCCCATAACATCTAA
GCCAGCACCCCCTTCCCACAGAT
CTAAGAACGGCCATGCACCACCAC
GGACAGTCGGGGGCATTCGTATT
GCCGGCGACGCATCATTCAAA

3.00E-87
2.00E-92
3.00E-61
1.00E-50
7.00E-62
2.00E-59
6.0E-126
4.00E-25
2.00E-38
3.00E-31
***
-

Signaling Genes
*

Bv Accession
BQ489058
BQ584059
BU089558
BU089558
BU089563
BU089563
BU089563
BF011062
BF011062
BQ588826

Forward Primer
GTGCGCGAAATTCAGAGACAAA
TTCACCGAGGCTCAGATAAA
GGCGGATTTCGGAGTG
GGCGGATTTCGGAGTGG
GGCGGATTTCGGAGTGG
GGGGTTACCGCATTTATCATTG
GTCATCGCCGGTTCTTGTGG
CCGGGGAGTGCAACATCGTC
CGGGGAGTGCAACATCGTC
TTTGCGGGTCATTTTCTCTAAGT

Reverse Primer
CAGATCCCGGTGCAGAACATT
ACAACCCGCACTCCACAT
CGATGGGCGGTTGATGG
CGATGGGCGGTTGATGG
CGATGGGCGGTTGATGG
TCTCCCGGAAAAACCATTACTT
ATTTACCGTCCCTCTTCCCTGATT
GCTGCTTGCTCTTGCCTTCTCTT
CGCCATTTCGCACAACAGA
GGATGGCATGCAGGCTCTC
106

At Gene
MPK13
IBS1
HSL1
HSL1
HSL1
HSL1
HSL1
M3Ke1
M3Ke1
WAK1

**

E value
5.00E-74
4.00E-63
0.00E+00
0.00E+00
0.00E+00
0.00E+00
0.00E+00
3.0E-102
3.0E-102
4.00E-57

Appendix Table 1.1 continued
BQ592039
GCTTACGCTGTCGCTTGATA
CK136500
GTCCAGGAGGCCAAACACTT
BQ583877
GACGCGTGGGAAAAA
BQ590382
TTATAGAGGGGCGGATTGTTGTGT
BU089551
CGGCACGAGGCTATTCTTCATC
BQ593921
CAAGCCGTTATCAAGTTCAAG
BQ594267
CAAGCCGTTATCAAGTTCAAG
BQ488487
TTATAGAGGGGCGGATTGTTGTGT
CF543170
AAAGTTATCGTTCTCGGGGACAGT
BQ591700
GCAGCCTGTTCCTTTTTCTCA
BQ489848
CGACAGCGGAGTGGGGAAGAC
BU089564
GGTTCCGTCGTTGCTGTGT
CF542879
TGCCGCCTAAAAGACTACGAA
BQ582382
CGATCCCGACCTTCTTCTTG
BQ585091
TTCGTCATGGAGTTCGCTAAAG
BQ060547
TCCGGCTTTTGCGTCAT
BQ060614
TCCGGCTTTTGCGTCAT
BQ583062
GTTGCCACCACTACATCTG
CF543157
TTAGGCTTGTGATATTCTGTG
BQ489063
AGGCCCTTTTCAGAGA
BQ489063
TTTGCGGGTCATTTTTCTCTAAGT

TTGGCTGACTCTTTGGGAATG
AACATAATTCCGCGATCTTCATAA
TTAACATCGGAAAACTCG
TATGAATGGGAATGCCTTGGTATC
CACCCGCGTCCCATTTGTAA
AGCAAGGCCAAAGTCACAT
AGCAAGGCCAAAGTCACAT
TGAATGGGAATGCCTTGGTATCTG
CATGCCAATTATCAAGGGTATCAA
CTCCCCGGTATATCAATTCCCTAAC
GCACCTCGGTAGAAAGCAACAC
TCCCCGTGAGTCATCGTTGTC
TAACAGAACCGGAAGCTATCAAAG
AGTGCGTCGGCTATGTCAGTA
ACCTAAAATCTCCCCTGTGG
TGGCTGTCGGAGTGTCATT
TGGCTGTCGGAGTGTCATT
GGGTCCCCAACATTCA
ATATTTCAAGGCGGCAT
CACCCATTGCCCACATA
GGATGGCATGCAGGCTCTC

MERI5B
MERI5B
MAPKKK21
RABG3A
WAKL2
MPK8
MPK8
RABG3B
RABG3B
MPK19
RAB7B
TMKL1
SRF3
WAK
CIPK14
MPK16
MPK16
XLG1
XLG1
MPK20
MPK20

7.00E-83
5.00E-91
5.00E-29
8.00E-88
9.00E-48
4.0E-102
6.00E-94
2.00E-73
4.00E-95
9.00E-90
1.00E-71
0.00E+00
1.0E-101
9.00E-46
2.00E-72
4.0E-108
1.00E-86
6.00E-66
8.00E-60
2.00E-87
2.00E-87

Abiotic, Biotic and Undetermined Stress Genes
*

Bv Accession
BQ584082
BQ586375
BI073128
BI095934
BI096011
BQ594432
BI096145

Forward Primer
CGGGCCGATTTTTACTACTCA
TGTAATCCACCGTCCTCAAAC
ACCCGGAAATAACGTAACTCTA
AGGGATCCCGCTACTCT
AGGGATCCCGCTACTCT
CGGCTGCCTTTTTCTACTCCA
TGGGGAGTCAGCTTTTAGTATTA

Reverse Primer
CAAGCAAAAGATGGTCACGAATAA
TACCCAAAATCATACGCACTGT
TGCGCCATTCAAACTAACA
GCGCCATTCAAACTAACAA
CGCGGATTCAAACTAACAA
CTCAGCTGCCCCCATTTACATA
TCCCTTCTCCATTCCCTCTCAG
107

**

At Gene
CYP90A
CAF1
GER3
GER3
GER3
GBF1
LOX1

E value
9.00E-56
1.00E-65
5.00E-42
2.00E-40
2.00E-40
2.00E-04
7.00E-74

Appendix Table 1.1 continued
BQ585097
GCGGTTTGACATGAAGGCACTG
BQ488691
ACCGGACGGCCACCCACTGA
BQ594875
TGCTTGCCGTTTTGGGTTAC
BQ587264
AAGCCGTGTAAAGAAAGGAAAAA
BQ589960
ATGCCAATGGGTCCCTTTAGAT
BF011122
AAAAGGCCATGGTGATAAGAAGGA
BQ592313
AATAGAGCCCTTTTGTGATAGCAT
BQ488466
ATTGCGTGATTTTTGGGAACAG
BQ584422
AACCCCGCTAGCATTGAGAGGAT
BQ583249
AACCCTTACTTCCGCTTCAC
BQ583306
CTCCGAAAGACCCGAAGAAAC
BQ584988
TAAGGGGACTAATTTGTATGGAT
BQ594810
GCACCCCAAAACTCGCAACAACAG
BQ586635
GAACCGTCGACGAGAACTGCT
BQ582721
GTGGGTCGCCTGTTGTTTATGA
BQ587840
TTCATTGCCCTTGCCTATTTT
BQ487855
ACGCCCTTCATTCCCTTTACC
BQ487855
CGCCTCCCACTTCCAGAT
BQ487860
ACGCCCTTCATTCCCTTTACC
BQ487902
GCCTCCCACTTCCAGATAAAT
BQ487902
GCCTCCCACTTCCAGATAAAT
BQ587848
AGGATTATGGGGAGAACACTTGA
BQ595738
CCTTCTCACTCCACCACCACTAA
BQ595738
CTTCGACGCCCTTCATTCC
BQ583639
AGGGGCTGATGCGTGTT
BQ586400
CCGGTTGCAGTCCCAGTTT
BQ588862
CCACGCGTCCGGTATTTGA
BQ594725
CGCGTGGGTTTGTCCTC
BQ584433
ATAAGAGAAATGGCGACACAAGT
BQ488279
AACGCGTTTGTCATT
BQ582770
GTAACCGGAGGAGCCAATG
BQ584498
AAATTTGGCACTCTTGATA

CCATCACTAGCATAAGGGTAATCT
AATCCCGAATGTTATCTGCT
GACGGGTCGAAATTTGTTGATG
CTACGCCAAAGCCAACCAG
AGTAGAACCCTTTGCGTGTAT
GCATGGAGGGCAGAAGCAACC
AGCCATTCCCCTCTTGACGA
TGGCACCTCGCTTGATGG
AAGGGTGCCAAGTGAGGTTAGGAA
GTTCGCAAATGGGTAGTCCTC
CAGGTGAATGTCCCGAAAGAAC
TGCTGCAATTATGTATGGTTCTG
CACAAACCCGACCCACCACTTACC
ATCCATGGCCGTCGTAAACAC
GTTTTCCTCCCCAGTTTGTTCC
ATGTCGCCCTGTTTCTTCTTG
TGAGATCATACGTCGGAGAAT
CACGGTGCACAATTTATGAG
TGAGATCATACGTCGGAGAAT
TAAGTGCGTAAATGGTGTTGTT
TAAGTGCGTAAATGGTGTTGTT
AATCGGGTCTTTCTCCAGGTAAC
TCATACGTCGGAGGATTTCTTTC
CTTTGTAGACAGTTCCCCCATTA
TCTGGGGTGATTGTTTAT
AGCCGGTCTTTTCTCTTCT
CCTAGCGCCATGCCAGTTTAT
CGGCGGGTTTGCTTCT
TGGATGGGCAGGCAACA
TGCTTCATCCCATAGA
ATATGTTCGCGTCTTCACCAA
TAGTTCGGCTGCCACATTCTT
108

LOX
LOX
RGA1
MFP2
MFP2
LOX5
LOX5
RBOHD
LOX3
LOX2
LOX2
LOX2
ATLP
PP2CA
NCED3
ETR1
MKK9
MKK9
MKK9
MKK9
MKK9
MKK9
MKK9
MKK9
EIN2
JAZ1
ABI2
LRR PK
MPK1
ABA2
ABA2
ABA2

9.00E-56
1.00E-49
5.00E-30
3.0E-105
3.00E-91
9.00E-73
2.00E-66
4.00E-62
2.00E-62
5.00E-55
4.00E-52
9.00E-70
6.00E-83
1.00E-39
6.00E-81
1.00E-97
8.00E-47
8.00E-47
1.00E-33
6.00E-39
6.00E-39
2.00E-38
3.00E-51
3.00E-51
2.00E-35
3.00E-17
4.00E-45
5.00E-89
3.00E-64
4.00E-46
4.00E-39
9.00E-49

Appendix Table 1.1 continued
BQ593155
TTTGGGCCCGTGTTCA
BQ593157
TTTGGGCCCGTGTTCA
CF542675
CCCCGAGGAGCTTGGAGAGT
BU089562
TGCCCAAACAGTCCCTTCTAATC
BQ488276
GTATTCCGGCGACTCTC
BQ488276
TCCTCTTCCCGATCATTCTCA
BQ588562
GCGGACGCGTGGGTTGC
BQ594736
TCCTCTTCCCGATCATTCTCA
BQ488461
AGGGCCACGCTACTTTTCCACAAC
BQ586418
GAGATGGTTGCGATGAAGAAAGATT
BQ586920
TTCCTCCGCAAGTCCGTCCTCTCC
BQ489189
TTCCTACAAAGTGATAATGCTC
BQ592267
GTGCGCGAAATTCAGAGACAAA
BQ489814
CGGGCTGCAGGTTTCTATCTC
BQ488850
GACGGCGATCTTTTAGTTA
BQ489814
CCGGGCTGCAGGTTTCTATC
BQ593362
CAAGCTCGATGTTCCTCCTGAC
CF543254
TGTGGAGGAAGCTGGGAAGGTGTT
BU089571
TTATAGGGCGATTACACTCACTTC
BQ594412
AATCCGTGTATCTGGCTCTTTC
BU089561
ATTGCCAAGGCGTTCGTAT
BQ488795
CGTGCCTGCAGACATTGATT
BQ587858
TAGTGGGCAGAAGAAGAAAGAGAA
BQ582800
CTGATTAAGGCGGGTGTAGTTC
BU089565
TTATGGGCCCGTTTCCTGTATC
BU089547
AGCAGAAGGCGAGCGTGAAT
BQ593937
TTGCCGGCTGTGAACCA
BQ594117
TTGCCGGCTGTGAACCA
CF543001
AGGGGCAGCTGTTGGTGA
BQ595702
CCACGCGTCCGAAACTT
BQ593603
ATTGGGGAGAAGAGGGTCATC
BU089552
AGCGGCTGCCTTGAAAA

TTGGTTGCCTTAATGTCTCTGT
TTGGTTGCCTTAATGTCTCTGT
TAGGTTATTCGCCGTCAGGTCA
CGCCACCGTCGCTCCAT
TCCCTGATTTGAACGAA
TCCTCTTCGCATCAACTTTATTAT
CACGTGATCTCTGCCTGGAAATAG
TCCTCTTCGCATCAACTTTATTAT
TCCCATCGGCCCCACCACT
GGATGTATTTAAGCCCACGAAGTA
CTCCGCACCTCGTCGTCGCTCTCG
CTGTCAAAGATGGCTGCTC
TCAGATCCCGGTGCAGAACATT
GCTGCACAAGGCCACCACTA
AAGAGACCCACCATCCAT
CTGCACAAGGCCACCACTACC
TTACCTTTGCCAATGACCTTA
GCCAATGCCGGAAGGGATAAGTC
TAACTTTCGGGTATCTGTCTCCA
AGGCAATTCTAACTGTTTTCTGAC
AATCATTCGCGGTGTAGTTAGG
GCACCACCAGCAGATTCCTT
AGGCCATTATCCGATCACCAGTA
CTTGGCGGCATAGGCTGGTAGG
TGGGCGAGCGTCAAGTTTC
GGGGTCGAAGTAGCCAAAAGTG
CATGTAGTCCGAAACCAGAGTAGC
CCATGTAGTCCGAAACCAGAGTAG
CAGATCGCCGTGTGAGC
GTCATCCCAATACCACTGTCAAT
AGGAGCCATATAGCCAAGTGTTC
CAGGAGAACGACACCGAAACTAT
109

LRR protein
LRR protein
LRR protein
LRR PK
MPK6
MPK6
MPK6
MPK6
AOX1A
MPK3
BRH1
MPK4
MPK4
MKK2
MKK2
MKK2
MKK2
LRR protein
RLP52
MKK3
LRR PK
ABA1
ABA2
ABI5
LRR PK
PK
PK
PK
PK
PK
PK
PK

6.00E-90
4.00E-89
2.00E-82
0.00E+00
8.00E-81
8.00E-81
1.0E-110
2.00E-82
3.00E-19
3.00E-90
4.00E-28
2.00E-51
3.0E-108
4.00E-54
1.00E-51
4.00E-54
7.00E-39
8.00E-51
5.00E-79
3.00E-35
0.00E+00
3.00E-49
3.00E-57
3.00E-21
0.00E+00
4.0E-149
2.00E-57
1.00E-51
1.00E-13
1.00E-69
6.00E-97
5.0E-161

Appendix Table 1.1 continued
BQ582873
GTTAGGGGCAAGGTGGTTTT
BI543739
TTCGCCACCGCCATCTG
BI096304
GAGCGATCTATCTTCCTTAT
CF543002
GGGGCAGCTGTTGGTGATA
BQ584876
TCCCCCAGGCAAAGAGC
BQ585999
GGCCGCTAATATCCTCCTC
BQ585841
TAAGTCGCATACACCACAGG
BQ582618
GGGCGCATCAGGGCTACA
BQ593922
TTACACTGCCAATCAAAAACAACC
BQ586464
TGCTTTGCCGGACGACCTT
BU089554
GTTCTGCCCTTATCTTCCTTCA
BQ585434
TGGGCTGTCAAGGATAATG
BQ587874
TGGGCTGTCAAGGATAATG
BQ587887
TGGGCTGTCAAGGATAATG
BQ588055
TGGGCTGTCAAGGATAATG
BQ582409
CAGCCAGAACTCTTTATCCACATC
BQ590125
CCTATCGCTTTTTCACCATCCTA
BQ582687
GCGGAAAGGCAATGAAAG
BQ488935
GCGGCGCGTGCTTATGATGA
BQ591669
CTGGGAAGAAAGTGAGGAAG
BI543377
GGCGGCTGAAGATATGATGAAC
BI543386
GGCGGCTGAAGATATGATGAAC
BI543980
GTTCACGGCAGCAATACCTCAA
CK136876
GTTCACGGCAGCAATACCTCAA
BQ592234
GATTGCTTCGTTAGGGGTTGTGAT
BE590444
ATCCAAAACAACCGACCAACAA
BE590444
CCTCGACATATGGGACTCTTTCA
BQ595152
AACGCACGAATTGACTGGAAAGAA
BQ595152
AATCCAAAACAACCGACCAACA
CK136617
GGCCGGGATCTCAAAC
CK136658
GCCGGGGATCTCAAACA
CK136658
GGCCGGGGATCTCAAACAAT

TGGCCTCATAGTTTTCATCC
CTCGGTAAGCTGTTGTCTCCTGAA
GTTCCCAGCCTTCACA
AAGGCCCGGAGGTTTTGT
GCCCAAGCAACGAGATTAT
CTGGGTCGGTTAAAGTATCAAAAT
CGGGCTTACGTCCAGTTA
CTCAACACGGGCAACACCAA
TGGCAAAGTAGATGGCTCACAA
TCCCACGAACACCACCTGACA
ATTAACCGGCCATTCTCCA
TGAGCCCGGCCAAGAGGTC
AATGAGCCCGGCCAAGAGGT
TGAGCCGGCGGAAGAGGTC
AATGAGCCGGCCAAGAGGT
ACTCCCACACGTACTGCTCATC
AATCCCAAATCAGCAATCTTCA
CAATGATAAAGCACCCCAGTC
TCGGCGCCGGAAAACCAA
TTTTTGGGGGTAAGGATGAG
TAGGCGGGATGGTAGGAGGTG
TAGGCGGGATGGTAGGAGGTG
AGCCTCGACCTCCATCCAAACT
AGCCTCGACCTCCATCCAAACT
ATGGAGGTGGGATGTTTTGGAGT
TGCCAAGTATCATTTTTCTCCTC
GCCCGTTGCCCGCTAATCTTT
TTGCCCGTTGCCGCTAATC
TGCCAAGTATCATTTTTCTCCTC
CTCTCAACACGATGCCAAGTAT
CTCTCAACACGATGCCAAGTAT
CGGAACGAGGAATGGTGGAG
110

PK
PK
PK
PK
PK
PK
PK
PK
PK
PK
PK
PK
PK
PK
PK
PK
PK
AAO4
ERF9
myb
ROF1
ROF1
GSTF7
GSTF7
RCI3
HSP17.8
HSP17.8-CI
HSP17.8-CI
HSP17.8-CI
HSP17.8-CI
HSP17.8-CI
HSP17.8-CI

9.00E-99
2.00E-99
1.0E-108
2.00E-73
2.0E-112
2.00E-90
3.00E-87
4.00E-82
1.00E-81
1.0E-116
3.0E-123
2.00E-52
2.00E-60
2.00E-60
2.00E-60
6.0E-107
7.00E-63
2.00E-57
6.00E-32
1.00E-55
4.00E-70
3.00E-71
2.00E-61
3.00E-61
4.00E-68
4.00E-57
9.00E-48
2.00E-39
2.00E-50
5.00E-58
5.00E-58
6.00E-49

Appendix Table 1.1 continued
BQ587622
AACTTCCAGGGACAACATCAACA
BQ587622
TTATCTTAGGCCTGGAATCAAA
BQ589141
TTATCTTAGGCCTGGAATCA
BQ589141
TTGGACCCCTGAAGAAGAT
BQ589354
ACGATAACATTAGACCAAAACAAA
BQ586261
GTATCTTTTCTGGCCGTGTTATTG
BQ592726
CAATGGCGGCGGTAGTGCTC
CF542723
CGGAAAATCGGTGACTGGA
BQ584180
ACGCCACGGCTGTCACTTTG
BQ585826
TGGGAGGCTCGCATCAAG
BQ488894
GCTCAAAACTCCCACATCATCATT
BQ582278
AAATTGCAATGGCTTCTTACTG
BQ585675
CAGGCCTTGGCTAATGGTGATA
BQ582606
CAGGCCAAGGAATGAGA
BQ582606
CAGGCCAAGGAATGAGAG
BQ582479
CGGCTGCCTCCCCTGCTGACA
BQ587197
AGAAGAGATCGCCCGCTACAT
BQ595355
AAGCCATACATGCCTCCAAAAGAA
BQ595697
TTCCCGTCAAATGCCTGCTCT
BQ592393
CGTCGGTGTTTGCCTTGGAATA
BI543685
CCCGATGAGGCTGTTGCTTAC
BQ488223
TGCGGGTCATCAATTTTCTCTTC
BQ488179
CGTCGGCGCACTCACCTTGTATTC
BQ595328
CCGTCGGCGCACTCACCTTGTATT
BQ594558
ACAAAACCCGCCCAAAATCC
BQ587644
TAGACGCCATATGGTTAGAAGAAA
BQ582634
ACCGGCCCCGTTTTTGATA
BQ582634
ACCGGCCCCGTTTTTGATACC
BQ585612
CCCGGCCCCTATTATGAT
BQ592954
CGGACGCGTGGGCTAAACTC
CK136649
CCGACGGGTGCAAGAATCCT
BQ584136
GTCCCCCACTTGTTCGTATCAC

GTCATCGTCGTGGTGCTTAGG
GTCATCGTCGTGGTGCTTAG
AGTTGCGGTTGTGTTGCTAC
AGTTGCGGTTGTGTTGCTAC
ATCTCTGCAACCCGGTATTAGTAG
CCGGTTACTAGGGATTTCATTGT
CTGGCCCCTTAAGAATCCCTCAT
CTGGGCCCGAACATAAAAGA
ATTGCCAGGTTGTAGCCATCCACT
AAGCAAAACGCCAAAACTGTAAAT
TACTCCGCAACCATCTTCTTCACT
GGACCTTTCTGCACACCTGAC
AGCGCGCTGCAGCCTCATACTTC
GGGCAAGATATCCAACTGT
GGGGCAAGATATCCAACTGT
AATGGCGTAGGGAACACTGACACC
AACTTCCCATCATAATCACCAACA
TCATATCCCCAACCAGAACAACAA
TCATATCCCCAACCAAAACCACAT
GCGGTGCTGGATGGTGTAGTG
GCCTGCCCTTGTCATTTGTG
CGTTCGGGTATTTTCGGTCTCT
ATGCGCCCCTGTTCTTTTTCCTCA
ATGCGCCCCTGTTCTTTTTCCTCA
CTTCTTCTCAATCCTCGCCTTCTG
TGGCCATGTTAGTGTGATAGA
ATGAATGGAGAAGAGTGGCTAATG
GAATGGAGAAGAGTGGCTAATGTC
ATGCGGCAAGTGATTAGAACA
TGGCTGCATTGGTGGGTGTG
TGGGCAGAAAGTAACGGTGTAATC
AGCCGGTCTCTATGGTTTTCTGT
111

MYB60
MYB60
MYB60
MYB60
MYB60
GLP5
HSFA1D
TTL1
TLP
RFO1
PAL1
PAL1
PAL1
RLK
RLK
LTP1
HSPRO2
FAB2
FAB2
UCC2
HSP70
NAC055
ATL2
ATL2
MBF1C
CYP82G1
CYP76C7
CYP76C7
CCD1
OSM34
OSM34
SCL13

3.00E-75
2.00E-75
8.00E-73
5.00E-73
2.00E-68
6.00E-61
1.00E-55
2.00E-77
3.00E-63
9.00E-43
1.00E-50
1.00E-51
2.00E-93
3.00E-86
3.00E-86
3.00E-21
2.00E-40
3.00E-72
3.00E-70
2.00E-16
3.0E-133
6.00E-58
9.00E-40
9.00E-40
1.00E-46
2.00E-46
4.00E-72
7.00E-72
7.00E-67
1.00E-59
6.00E-59
6.00E-72

Appendix Table 1.1 continued
BQ584136
TGTACCAGTTTTGCCCTTATTT
BI543265
CTTGCCGTCTTCTGAGTTTGATGA
BQ593897
GCGGCAGCGAGCAGTAA
BQ584386
TGTACCCTGTTGCTCCCATTGT
CK136719
GCAGAAAAAGATCATCCCGACAAT
BQ589925
AAGCCCCGTTAAATATGAAAAGA
BQ586015
ACCCGCGTCTCAAAATA
BQ588529
GGAATATGCTGCTGGAGGAGAG
BI543772
CAAGGGCAGGCTCTCAAAGGAA
BI643098
GTAACGGAAAAGGAACGAAAACT
BQ594995
GCCGGAAGAGAAGATTAT
BQ490017
CTTGCCCAAATGCTCTTAGTAT
BQ488337
ATTAAGGCCGGAGCAGCATA
BI543460
GGTCCCATTTCGCCTTCTTTA
BQ060494
CCATGGCCGCCGTTCTTC
EG552299
TCCGCCGTCCCTCTTTCTC
BQ583421
AGTGGCCTTCTAATCCTCCTTCAT
BQ586894
GAAAAATCTCCGCCACCGAACTC
BI073235
GTGCCAGACAAGACCAACAA
BI096038
GCACGAGGCTGATGACGA
BQ489704
ATCGTGCCAGACAAGACCAA
BQ584196
CCACGCGTCCGAAACTT
BQ593588
CAAAGCAAATCCCCCTGTTAT
BF011227
CGTGCCAACAAGACCAACAAC
BQ589734
CGAAAACCGACGAAGTAACATCT
CK136793
CGACACCGCAAAAGAAACC
CK136793
TCAACAATCGACGCAACAACATCT
CK136863
CCCGGGTTAAAGAAGGAGGAAGT
BQ490607
TGCAGCTATGGCGTTCTTCAG
CF543165
ATGCGGGGCGGATTCAC
BQ582835
ACTCGCTGCAGCCAAGAAAG
BI543937
GGAGAAAGAATGCCCTATGACTGT

AGCCGGTCTCTATGGTTTTCTGT
GGAGCTGGTCGGGGGAGTG
CCCCGTCGAAGGATTGTC
CGTTTCGCCATATTCTCACCAG
GAGCCCCTGAAAGAGCAACCAT
CAGCAGCAGCAGCAAACC
ATACGCGGACATAATCAGG
AGACGCGGACATAATCAGGAAT
CGGACCGGCACCACTG
CGGCACGAGGTCACAATCAC
GCCCCGCACGACCAC
CGAGCCGAGTTGTTATTAGGAG
GGTGGCGGAGAACAGAAGTG
GTACGGGCACTTTCAGCATTTT
CCTTCTGTGTTTGGGCATCATCA
AGCGGCCATCCTGTAACCTG
CTGGGCTTATCTGCATTCACAACT
ACCTAATTTTGCGACGACGACGAT
CCAAGGGGCTCACCAGT
CAGATGGGCTTTTGCTTGTTA
ACTCCCACACGTACTGCTCATC
GTCATCCCAATACCACTGTCAAT
GGTGCCCGAGTGTTATCAATG
AGACTCCCACACGTACTGCTCATC
CACTTTGCCGTCTTCCACCTCTA
GTAAAAGTAAGCCCATAAAACATT
TGCCAAGTATCATTTTTCTCCTC
TAGACGGTTTAGACACGAGCACAT
ATATCCGCCGCCACCGTA
CTTTGGGCGAGTTCTGGTTTTC
AATAGCGGCAAGCACATCATC
GGTTGCCCGTTTCCACTCTG
112

SCL13
CCH
TAFII15
CYP81D1
PER50
RPN10
SNRK2-3
SNRK2-3
HSC70-1
HSC70-1
GRBP
peroxidase
RH26
MTHSC70-2
MTHSC70-2
chaperonin
DMR6
TCH2
HSP81-3
HSP81-3
HSP81-3
HSP81-3
HSP81-3
HSP81-2
HSP18.2
HSP18.2
HSP18.2
HSP18.2
GR-RBP3
HDA6
SAL1
PER72

6.00E-72
2.00E-72
4.00E-58
2.00E-43
4.0E-101
2.00E-68
2.0E-100
2.0E-107
5.00E-92
5.00E-62
3.00E-40
3.00E-69
9.00E-53
3.00E-65
2.00E-81
9.00E-84
8.00E-95
8.00E-37
2.00E-90
7.0E-106
1.00E-78
2.00E-90
1.00E-77
3.0E-107
2.00E-45
2.00E-58
2.00E-51
1.00E-57
4.00E-58
5.00E-83
1.00E-74
2.00E-98

Appendix Table 1.1 continued
BQ587584
GTACAGGCGGAGAACTTTT
BQ585699
TATCTCCGGTGGGTCTATTCA
CF542797
GCGTGGGAAGGAAGTGAGAA
CF542821
ACGCGTGGGAAGGAAG
BQ585699
TATCTCCGGTGGGTCTATTCA
BQ593448
TATGCCGGGGAAAGGACTCTA
BQ592254
GGGGCCAAAGAAAGGATGTA
BQ592254
TAAGGGGCCAAAGAAAGGATGTA
EG552103
TATACCTGCCCATGTGGATTAGAA
BI543239
AGCCCTTCACTCCATCCACCATA
BQ586991
GAGTAGCCGGGTCTGGGTATTG
BQ594715
GCACCCCAAAACTCGCAACAACAG
CF543190
ACGCGTCCGAACAAGAAGAAAAT
BQ584083
AGGGTGGCGCTAGTCCGTCTCC
BQ592168
AACCCTAGCCGCTCCAAAACC
CK136419
ACGGAAAGCAAAGGGCAGAG
CK136420
GACGGAAAGCAAAGGGCAGAG

AGAACGCCCTTTGTATC
CTCAGGGGCCATCCAGTAA
CAGGGGCCATCCAGTAAGG
CAGCGTTTGGATGTGAA
CAGGGGCCATCCAGTAAGG
GCTTGCGGACATGGATACTGA
AGTGGTGGTGGTTGCAGTAGTAG
TCAAGGGCAGTGGGGAAAGTA
GTTATTGGGGGAGGATTTTAGTGA
ATAAACATACGGCACATTCTA
CCGGATTTGCGAGTTGGTTC
CCCGACCCACCACTTACCTCAACC
CCGGCATCGATCCAAAAGTC
TTTCAGGCATCCGCAAGCAGTTTT
CCGCCACCACCACCGTATC
CAGGGGAGGCAAGTGATGAAG
CAGGGGAGGCAAGTGATGAAGA

CIPK23
M3KA
M3KA
M3KA
MAP3KA
RBOHF
DREB2C
DREB2C
PLDBETA1
ATL6
RD26
TLP
LCL1
LTP4
GRP4
GSTF8
GSTF8

4.00E-88
1.00E-77
1.0E-100
2.00E-20
1.00E-77
1.00E-91
3.00E-37
3.00E-37
7.00E-65
7.00E-26
5.00E-96
5.00E-72
9.00E-43
6.00E-29
3.00E-48
3.00E-69
5.00E-71

Genes with Undetermined Functions
*

Bv Accession
BQ586553
BQ592405
BQ591201
BQ583037
BQ588349
BQ583828
BQ590906
BQ587396
BQ487898
BI096344
BQ499841

Forward Primer
ATGCCCTGTGATATGGTTGAG
TGCGGCAAATAGTACAAAAATCAG
AACATCCCGCTCACTTTCA
CCCCATTCTTTTTCCCACAA
ACTCACCCCCACATCCACA
TTTTCAACCGCATTTAT
CAAACATGGGGCGATCTTACGAA
TTCACTCCCGGGTCCGTTTCTAT
CTACGCTTATTGGCTTGGTCTTG
CACGGTTGCGATGAAGG
CAGCGTCGAAAATTAGATGAT

Reverse Primer
TCCCTGTTGTTGATTGATTGTAG
GCCAGGCAAAATACCCACACT
GGGCCCTTCCTCACGA
GATATAAACATTCTTCGCAACAGC
AATTCTTCTGCTTCTTCCATCAAC
TATTGGGCAACTACAGC
ATTTTGGAACTTGCGATGGTGGAG
AATCACCTCTTGCGCCTCCTCCTG
AGGGCACTGCTTGGGTTCTAC
TGAGACGCGATAACAA
CGAAGTGGCCCGTAGGAG
113

**

At Gene
E value
AT1G30910.1 2.00E-79
AT1G80530
9.00E-56
AT2G26270
1.00E-52
AT2G39980
5.00E-60
9.00E-36
TCP20
1.00E-65
PHB1
AT5G58020
5.00E-20
CML41
4.00E-42
AT5G25170
1.00E-79
Und.
Und.
-

Appendix Table 1.1 continued
CX779686
CCACGGCTCTGATAGGGAATA
GTACGCCGGGGATGACAG
CX779686
CCACGGCTCTGATAGGGAATA
AGGTACGCCGGGGATGACA
DX811261
CCACCTCCTCCTGATGCTGACTCT
ATAATGGCGGGGGCGTTGTTG
ED032482
AGAGAAAAACGGCAAGAAATACA
AGGATGAATAGGCCCACAAAT
ED032901
TATGGCATGACCGATTAGG
ATTCCCCCAGCATTGTCT
*
**
***
Beta vulgaris EST Arabidopsis thaliana gene
No information available

114

Und.
Und.
Und.
Und.
Und.

-

Appendix Table 1.2 Genes present in both SP7622 and ACH185 in mature untreated
seeds (0 h) prior to H2O or H2O2 treatment using RT-PCR
*

Accession
BI073128
BI073235
BI096046
BI096176
BI096232
BI543386
BI543568
BI543569
BI543772
BI543980
BI643062
BI643161
BQ060614
BQ487902
BQ488276
BQ489063
BQ489189
BQ582618
BQ582859
BQ584082
BQ584876
BQ585841
BQ586400
BQ587173
BQ587272
BQ587848
BQ587887
BQ588562
BQ589671
BQ593588
BU089563
CF542821
CF542917
CF543368
CF543447
CK136420
CX779686
ED032482

**

At Gene/Function
GER3
HSP81-3
PUMP1
GER1
PLDALPHA1
ROF1

At protein
NP_197563.1
NP_200412.1
NP_190979.1
NP_177405.1
NP_188194.1
NP_001118695.1

18S rRNA
18S rRNA
HSC70-1
GSTF7
18S rRNA
18S rRNA
MPK16
MKK9
MPK6
MPK20
MPK4
protein kinase
PTR2
CPD
protein kinase
protein kinase
JAZ1
FAB1
PLDALPHA1
MKK9
protein kinase
MPK6
18S rRNA
HSP81-3
HSL1
M3KA
CYP71A25
18S rRNA
RPT4A
GSTF8
Undetermined
Undetermined

-

***

NP_195870.1
NP_171791.1
NP_197402.1
NP_177492.1
NP_181907.1
NP_565989.1
NP_192046.1
NP_199811.1
NP_178313.1
NP_001031838.1
NP_197362.1
NP_198672.1
NP_973862.1
NP_565097.1
NP_188194.1
NP_177492.1
NP_567072.1
NP_181907.1
NP_200412.1
NP_174166.1
NP_564635.1
NP_680107.1
NP_199115.1
NP_850479.1
115

E value
5.00E-42
2.00E-90
5.00E-108
2.00E-03
2.00E-55
3.00E-71
5.00E-92
2.00E-61
1.00E-86
6.00E-39
8.00E-81
2.00E-87
2.00E-51
4.00E-82
3.00E-94
9.00E-56
2.00E-112
3.00E-87
3.00E-17
3.00E-55
1.00E-74
2.00E-38
2.00E-60
1.00E-110
1.00E-77
0.00E+00
2.00E-20
1.00E-61
1.00E-132
5.00E-71
-

Appendix Table 1.2 continued
EG551101
FKBP15-1
*

Arabidopsis thaliana gene

NP_566762.1
**

Arabidopsis thaliana protein

116

***

1.00E-50

no information available

Appendix Table 1.3 Genes present in SP7622 and not ACH185 in mature seeds (0 h) prior
to treatment using RT-PCR
SP7622 (0h)
Bv
*
Accession
AW063023
AW697779
AW777170
BE590444
BF010998
BF011036
BF011057
BF011062
BG577441
BI073176
BI095934
BI096011
BI096180
BI096237

At gene/function
ACT7
AT3G29970
WNK1
HSP17.8
ACT11
AT3G29970
SIP1
MAPKKK7
XTR6
PHS2
GER3
GER3
EP3
mitochondrial elongation factor

BI096344
BI543265
BI543285
BI543360
BI543377
BI543415
BI543460
BI543685
BI543739
BI643098
BQ060494
BQ060547
BQ487636
BQ487747
BQ487855
BQ487860
BQ487982
BQ488119
BQ488279
BQ488487
BQ488795
BQ488894
BQ488935
BQ489620
BQ489814

Undetermined
zinc finger (CCCH-type) protein
AT3G29970
CAT2
ROF1
BAM1
MTHSC70-2
HSP70
Protein kinase
HSC70-1
MTHSC70-2
MPK16
enoyl-CoA hydratase protein
XTR6
MKK9
MKK9
NCED4
IP5PII/BME3
ABA2
RABG3B
ABA1
PAL1
ERF9
CAM7
MKK2

**

117

***

At protein
NP_196543.1
NP_190397.1
NP_001118576.1
NP_172220.1
NP_187818.1
NP_190397.1
NP_175970.1
NP_187962.1
NP_194311.1
NP_190281.1
NP_197563.1
NP_197563.1
NP_191010.1
NP_182029.1
****
NP_194648.1
NP_190397.1
NP_001031791.1
NP_001118695.1
NP_201371.1
NP_196521.1
NP_187864.1
NP_190214.1
NP_195870.1
NP_196521.1
NP_197402.1
NP_191610.3
NP_194311.1
NP_177492.1
NP_177492.1
NP_193652.1
NP_849745.1
NP_175644.1
NP_173688.1
NP_201504.2
NP_181241.1
NP_199234.1
NP_189967.1
NP_194710.1

E value
7.00E-152
9.00E-33
1.00E-51
4.00E-57
2.00E-122
1.00E-32
2.00E-09
3.00E-102
2.00E-90
1.00E-76
2.00E-40
2.00E-40
1.00E-41
3.00E-86
2.00E-72
1.00E-32
3.00E-100
4.00E-70
3.00E-113
3.00E-65
3.00E-133
2.00E-99
5.00E-62
2.00E-81
4.00E-108
8.00E-78
5.00E-86
8.00E-47
1.00E-33
5.00E-62
9.00E-50
4.00E-46
2.00E-73
3.00E-49
1.00E-50
6.00E-32
4.00E-73
4.00E-54

Appendix Table 1.3 continued
BQ489848
RAB7B
BQ490607
GRP3
BQ499841
Undetermined
BQ582382
WAK
BQ582477
CDC2
BQ582479
LP1
BQ582606
RLK
BQ582634
CYP76C7
BQ582708
NCED4
BQ582770
ABA2
BQ582799
CDKC
BQ582800
ABI5
BQ582873
protein kinase
BQ583306
LOX2
BQ583369
PLDALPHA1
BQ583421
DMR6
BQ583639
EIN2
BQ583692
BRI1
BQ584083
LTP4
BQ584136
SCL13
BQ584196
HSP81-3
BQ584386
CYP81D2
BQ584433
MPK1
BQ584498
ABA2
BQ584988
LOX2
BQ585195
seed maturation protein
BQ585514
ER
BQ585675
PAL1
BQ585699
M3KA
BQ585826
RFO1
BQ585998
BR6OX2
BQ585999
protein kinase
BQ586015
SNRK2-3 /SNRK2.2
BQ586635
AtPP2CA
BQ586657
transferase family protein
BQ586719
GA20OX2
BQ586920
BRH1
BQ586930
CAT2
BQ587264
MPF2
BQ587622
MYB60
BQ587840
ETR1
BQ587858
ABA2
BQ588316
UCP5
BQ588349
TCP20
BQ588529
SNRK2-3 /SNRK2.2

NP_188512.1
NP_200911.1
NP_194839.2
NP_566911.1
NP_181388.1
NP_181307.1
NP_191663.1
NP_193652.1
NP_175644.1
NP_196589.1
NP_565840.1
NP_188511.1
NP_566875.1
NP_188194.1
NP_197841.1
NP_195948.1
NP_195650.1
NP_568904.1
NP_193456.4
NP_200412.1
NP_195452.1
NP_172492.1
NP_175644.1
NP_566875.1
NP_198150.1
NP_180201.1
NP_181241.1
NP_564635.1
NP_178085.1
NP_566852.1
NP_197362.1
NP_195711.1
NP_187748.1
NP_199097.1
NP_199994.1
NP_191705.1
NP_195235.1
NP_187342.1
NP_172358.1
NP_176808.3
NP_201504.2
NP_179836.1
NP_189337.1
NP_195711.1
118

1.00E-71
4.00E-58
9.00E-46
8.00E-96
3.00E-21
3.00E-86
4.00E-72
1.00E-63
4.00E-39
1.00E-71
3.00E-21
9.00E-99
4.00E-52
9.00E-76
8.00E-95
2.00E-35
3.00E-101
6.00E-29
6.00E-72
2.00E-90
2.00E-43
3.00E-64
9.00E-49
9.00E-70
4.00E-27
2.00E-71
2.00E-93
1.00E-77
9.00E-43
4.00E-59
2.00E-90
2.00E-100
1.00E-39
7.00E-59
2.00E-44
4.00E-28
2.00E-89
3.00E-105
2.00E-75
1.00E-97
3.00E-57
8.00E-33
9.00E-36
2.00E-107

Appendix Table 1.3 continued
BQ589141
MYB60
BQ589455
SPT
BQ589925
RPN10
BQ590158
mitochondrial substrate carrier
BQ590906
Undetermined
BQ591669
myb transcription factor
BQ592254
DRE2B
BQ593448
RBOH F
BQ593732
KATC
BQ593897
TAFII15
BQ594117
protein kinase
BQ594412
MKK3
BQ594558
MBFC1
BQ594736
MPK6
BQ594788
SDR protein
BQ594875
RGA1
BQ594995
GRBP
BQ595049
GTE6
BQ595152
HSP17.8-CI
BQ595355
SSI2
BQ595434
APY2
BQ595738
MKK9
BQ595856
ATTPC1
BQ654409
XTR6
BU089561
LRR Kinase
CF542675
LRR Kinase
CF542797
M3KA
CF542908
HDA9
CF543165
HDA6
CF543254
LRR protein
CF543420
HSI2
CF543627
2OG-Fe(II) oxygenase protein
CK136419
GSTF8
CK136658
HSP17.8-CI
CK136876
GSTF7
EG551187
BRK1
*

Beta vuglaris EST

**

NP_172358.1
NP_568010.1
NP_195575.1
NP_194188.1
NP_200610.1
NP_001030662.1
NP_565929.1
NP_564821.1
NP_568811.1
NP_194900.1
NP_177507.1
NP_198860.1
NP_189093.1
NP_181907.1
NP_190736.1
NP_178266.1
NP_196048.1
NP_190796.1
NP_172220.1
NP_181899.1
NP_197329.4
NP_177492.1
NP_567258.1
NP_194311.1
NP_199948.1
NP_176918.1
NP_564635.1
NP_190054.2
NP_201116.1
NP_197731.1
NP_850146.1
NP_566623.1
NP_850479.1
NP_172220.1
NP_171791.1
NP_179849.2
***

Arabidopsis thaliana gene
Arabidopsis thaliana protein
information available

119

5.00E-73
2.00E-16
2.00E-68
5.00E-17
5.00E-20
1.00E-55
3.00E-37
1.00E-91
4.00E-25
4.00E-58
1.00E-51
3.00E-35
1.00E-46
2.00E-82
4.00E-46
5.00E-30
3.00E-40
9.00E-38
2.00E-39
3.00E-72
5.00E-57
3.00E-51
3.00E-69
2.00E-92
0.00E+00
2.00E-82
1.00E-100
2.00E-118
5.00E-83
8.00E-51
7.00E-26
7.00E-72
3.00E-69
5.00E-58
3.00E-61
2.00E-37
****

No

Appendix Table 1.4 Genes present in ACH185 and not SP7622 in mature seeds (0 h) prior
to treatment using RT-PCR

ACH185 (0h)
Bv
*
Accession
BF011227
BI073146

**

***

At gene/function
HSP81-2
GER1

At protein
E value
NP_200414.1
3.00E-107
NP_177405.1
3.00E-06
****
BI543889
18S rRNA
BQ488461
NP_188876.1
3.00E-19
AOX1A
BQ489058
NP_172266.2
5.00E-74
MPK13
BQ490017
peroxidase, putative
NP_196153.1
3.00E-69
BQ490300
NP_201279.1
4.00E-84
CESA6
BQ582721
NP_188062.1
6.00E-81
NCED3
BQ584898
NP_175630.1
1.00E-63
POT
BQ586318
steroid 5-alpha-reductase protein
NP_197105.1
2.00E-50
BQ586991
RD26
NP_567773.1
5.00E-96
BQ587584
NP_564353.1
4.00E-88
CIPK23
BQ588055
protein kinase
NP_567072.1
2.00E-60
BQ588646
AT1G03790
NP_194648.1
3.00E-69
BQ588709
NP_173322.1
1.00E-67
POT
BQ588784
NP_196346.1
3.00E-47
AML4
BQ593316
NP_195280.1
3.00E-21
WOX13
BQ595269
NP_001031115.1
7.00E-97
ARF6
BQ595543
NP_568072.1
2.00E-73
PXA1
CF543001
protein kinase
NP_179361.1
1.00E-13
CK136793
NP_200780.1
2.00E-58
HSP18.2
EG552299
chaperonin, putative
NP_197589.1
9.00E-84
*
***
***
****
Beta vuglaris EST
Arabidopsis thaliana gene
Arabidopsis thaliana protein
No
information available

120

Appendix Table 1.5 K-means clustering of 343 putative stress (abiotic, biotic and both
abiotic and biotic), growth and hormone related genes in ACH185 cDNA over the first 24 h
of germination time points in H2O and H2O2. Accessions in bold were also used for qPCR
analyses.

ACH185
H2O
Bv
*
Accession
AW063023
AW063034
AW697779
AW777170
BE590301
BE590301
BE590328
BE590397
BE590397
BE590397
BE590444
BE590444
BF010998
BF011036
BF011057
BF011057
BF011062
BF011062
BF011089
BF011122
BF011211
BF011227
BG577441
BI073121
BI073128
BI073146
BI073146
BI073176
BI073235
BI073250
BI095934
BI096011
BI096038
BI096046

**

Role 1
Growth
Growth
Growth
Growth
Growth
Growth
Growth
Growth
Growth
Growth
Stress
Stress
Growth
Growth
Growth
Growth
Signaling
Signaling
Growth
Stress
Growth
Stress
Growth
Growth
Stress
Growth
Growth
Growth
Stress
Growth
Stress
Stress
Stress
Growth

H2O2
Role
*+
2

Abiotic
Abiotic

Both
Abiotic

Abiotic

Abiotic
Abiotic
Abiotic
Abiotic

Cluster
2
6
2
6
6
6
3
6
1
1
7
2
2
2
6
6
6
6
7
6
6
2
1
7
3
6
6
1
2
7
3
6
0
3

Bv
*
Accession
AW063023
AW063034
AW697779
AW777170
BE590301
BE590301
BE590328
BE590397
BE590397
BE590397
BE590444
BE590444
BF010998
BF011036
BF011057
BF011057
BF011062
BF011062
BF011089
BF011122
BF011211
BF011227
BG577441
BI073121
BI073128
BI073146
BI073146
BI073176
BI073235
BI073250
BI095934
BI096011
BI096038
BI096046

121

Role 2
**

Role 1
Growth
Growth
Growth
Growth
Growth
Growth
Growth
Growth
Growth
Growth
Stress
Stress
Growth
Growth
Growth
Growth
Signaling
Signaling
Growth
Stress
Growth
Stress
Growth
Growth
Stress
Growth
Growth
Growth
Stress
Growth
Stress
Stress
Stress
Growth

*

+

Abiotic
Abiotic

Both
Abiotic

Abiotic

Abiotic
Abiotic
Abiotic
Abiotic

Cluster
5
6
2
6
6
6
6
2
4
6
4
5
2
2
6
6
6
6
3
6
6
2
3
6
2
6
6
5
2
3
6
6
0
6

Appendix Table 1.5 continued
BI096111
Growth
BI096145
Stress
Biotic
BI096176
Growth
BI096176
Growth
BI096180
Growth
BI096232
Growth
BI096237
Growth
BI096304
Stress
Und.
***
Und.
BI096344
BI543239
Stress
Biotic
BI543265
Stress
Abiotic
BI543278
Growth
BI543285
Growth
BI543316
Growth
BI543360
Growth
BI543377
Stress
Biotic
BI543386
Stress
Biotic
BI543415
Growth
BI543460
Stress
Abiotic
BI543526
Growth
***+
BI543568
BI543569
BI543685
Stress
Both
BI543739
Stress
Und.
BI543772
Stress
Abiotic
BI543889
BI543937
Stress
Abiotic
BI543980
Stress
Abiotic
BI643062
BI643098
Stress
Abiotic
BI643161
BQ060494
Stress
Abiotic
BQ060547
Signaling
BQ060547
Signaling
BQ060614
Signaling
BQ060614
Signaling
BQ487636
Growth
BQ487747
Growth
BQ487855
Stress
Both
BQ487855
Stress
Both
Both
BQ487860
Stress
BQ487898
Und.
BQ487902
Stress
Both
BQ487902
Stress
Both
BQ487902
Stress
Both

2
1
1
7
6
1
7
6

BI096111
BI096145
BI096176
BI096176
BI096180
BI096232
BI096237
BI096304

6
1
0
6
2
7
0
3
3
6
1
6

BI096344
BI543239
BI543265
BI543278
BI543285
BI543316
BI543360
BI543377
BI543386
BI543415
BI543460
BI543526

2
2
2
1
2
2
7
7
2
6
2
1
1
6
6
3
0
1
6
6
1
6
6
1
1

BI543568
BI543569
BI543685
BI543739
BI543772
BI543889
BI543937
BI543980
BI643062
BI643098
BI643161
BQ060494
BQ060547
BQ060547
BQ060614
BQ060614
BQ487636
BQ487747
BQ487855
BQ487855
BQ487860
BQ487898
BQ487902
BQ487902
BQ487902

122

Growth
Stress
Growth
Growth
Growth
Growth
Growth
Stress
***
Und.
Stress
Stress
Growth
Growth
Growth
Growth
Stress
Stress
Growth
Stress
Growth
***+
Stress
Stress
Stress
Stress
Stress
Stress
Stress
Signaling
Signaling
Signaling
Signaling
Growth
Growth
Stress
Stress
Stress
Und.
Stress
Stress
Stress

Biotic

Und.
Biotic
Abiotic

Biotic
Biotic
Abiotic

Both
Und.
Abiotic
Abiotic
Abiotic
Abiotic
Abiotic

Both
Both
Both
Both
Both
Both

4
3
5
2
6
2
1
6
6
6
5
6
4
0
1
3
6
6
1
6
2
2
2
4
4
4
6
5
2
6
2
4
6
4
3
1
3
5
6
6
6
6
1
4
6

Appendix Table 1.5 continued
BQ487982
Growth
BQ488119
Growth
Biotic
BQ488179
Stress
BQ488223
Stress
Abiotic
BQ488276
Stress
Both
BQ488276
Stress
Both
BQ488277
Growth
Abiotic
BQ488279
Stress
Both
BQ488337
Stress
BQ488461
Stress
Abiotic
Abiotic
BQ488466
Stress
BQ488487
Signaling
BQ488691
Stress
Biotic
Abiotic
BQ488795
Stress
Abiotic
BQ488850
Stress
BQ488890
Growth
BQ488894
Stress
Both
BQ488901
Growth
Biotic
BQ488935
Stress
BQ489058
Signaling
BQ489063
Signaling
BQ489063
Signaling
Both
BQ489189
Stress
BQ489620
Growth
BQ489704
Stress
Abiotic
BQ489814
Stress
Abiotic
BQ489814
Stress
Abiotic
BQ489848
Signaling
BQ489959
Growth
BQ490017
Stress
Abiotic
BQ490300
Growth
BQ490338
Growth
BQ490607
Stress
Abiotic
BQ499841
Und.
BQ582278
Stress
Both
BQ582382
Signaling
BQ582409
Stress
Und.
BQ582477
Growth
BQ582479
Stress
Biotic
BQ582606
Stress
Biotic
BQ582606
Stress
Biotic
BQ582618
Stress
Und.
BQ582629
Growth
BQ582632
Growth
BQ582634
Und.

6
0
3
6
1
2
0
6
6
1
0
6
6
3
1
6
3
3
7
6
6
7
2
7
7
6
1
7
3
6
7
0
2
6
0
1
1
6
3
0
1
1
6
6
2

BQ487982
BQ488119
BQ488179
BQ488223
BQ488276
BQ488276
BQ488277
BQ488279
BQ488337
BQ488461
BQ488466
BQ488487
BQ488691
BQ488795
BQ488850
BQ488890
BQ488894
BQ488901
BQ488935
BQ489058
BQ489063
BQ489063
BQ489189
BQ489620
BQ489704
BQ489814
BQ489814
BQ489848
BQ489959
BQ490017
BQ490300
BQ490338
BQ490607
BQ499841
BQ582278
BQ582382
BQ582409
BQ582477
BQ582479
BQ582606
BQ582606
BQ582618
BQ582629
BQ582632
BQ582634

123

Growth
Growth
Stress
Stress
Stress
Stress
Growth
Stress
Stress
Stress
Stress
Signaling
Stress
Stress
Stress
Growth
Stress
Growth
Stress
Signaling
Signaling
Signaling
Stress
Growth
Stress
Stress
Stress
Signaling
Growth
Stress
Growth
Growth
Stress
Und.
Stress
Signaling
Stress
Growth
Stress
Stress
Stress
Stress
Growth
Growth
Und.

Biotic
Abiotic
Both
Both
Abiotic
Both
Abiotic
Abiotic
Biotic
Abiotic
Abiotic
Both
Biotic

Both
Abiotic
Abiotic
Abiotic

Abiotic

Abiotic
Both
Und.
Biotic
Biotic
Biotic
Und.

5
0
6
5
6
2
0
6
1
4
4
6
6
3
3
0
0
3
0
6
6
6
2
5
6
6
6
5
6
6
6
3
0
6
5
4
6
0
6
1
6
4
6
4
3

Appendix Table 1.5 continued
BQ582634
Und.
BQ582685
Growth
BQ582687
Stress
Abiotic
BQ582708
Growth
BQ582721
Stress
Abiotic
BQ582763
Growth
BQ582770
Stress
Abiotic
BQ582799
Growth
BQ582800
Stress
Both
BQ582835
Stress
Abiotic
BQ582859
Growth
BQ582873
Stress
Und.
BQ583037
Und.
BQ583062
Signaling
BQ583249
Stress
Both
BQ583301
Growth
BQ583306
Stress
Both
BQ583369
Growth
BQ583421
Stress
Biotic
BQ583639
Stress
Both
BQ583692
Growth
BQ583764
Growth
BQ583828
Und.
BQ583877
Signaling
BQ584025
Growth
BQ584082
Stress
Abiotic
Abiotic
BQ584083
Stress
BQ584125
Growth
BQ584136
Stress
Biotic
Biotic
BQ584136
Stress
BQ584180
Growth
BQ584196
Stress
Abiotic
BQ584386
Stress
Biotic
Biotic
BQ584422
Stress
BQ584431
Growth
BQ584433
Stress
Biotic
BQ584462
Growth
BQ584474
Growth
BQ584498
Stress
Abiotic
BQ584876
Stress
Und.
BQ584898
Growth
BQ584988
Stress
Both
BQ585091
Signaling
BQ585097
Stress
Biotic
BQ585195
Growth

0
6
0
6
6
0
6
6
7
6
3
6
6
1
7
2
6
2
2
2
6
0
0
6
6
1
3
3
0
2
6
1
3
7
3
1
6
0
6
1
6
6
6
6
6

BQ582634
BQ582685
BQ582687
BQ582708
BQ582721
BQ582763
BQ582770
BQ582799
BQ582800
BQ582835
BQ582859
BQ582873
BQ583037
BQ583062
BQ583249
BQ583301
BQ583306
BQ583369
BQ583421
BQ583639
BQ583692
BQ583764
BQ583828
BQ583877
BQ584025
BQ584082
BQ584083
BQ584125
BQ584136
BQ584136
BQ584180
BQ584196
BQ584386
BQ584422
BQ584431
BQ584433
BQ584462
BQ584474
BQ584498
BQ584876
BQ584898
BQ584988
BQ585091
BQ585097
BQ585195

124

Und.
Growth
Stress
Growth
Stress
Growth
Stress
Growth
Stress
Stress
Growth
Stress
Und.
Signaling
Stress
Growth
Stress
Growth
Stress
Stress
Growth
Growth
Und.
Signaling
Growth
Stress
Stress
Growth
Stress
Stress
Growth
Stress
Stress
Stress
Growth
Stress
Growth
Growth
Stress
Stress
Growth
Stress
Signaling
Stress
Growth

Abiotic
Abiotic
Abiotic
Both
Abiotic
Und.

Both
Both
Biotic
Both

Abiotic
Abiotic
Biotic
Biotic
Abiotic
Biotic
Biotic
Biotic

Abiotic
Und.
Both
Biotic

0
6
5
5
6
0
6
6
0
6
1
6
6
1
6
3
3
2
5
5
5
6
1
6
3
5
6
6
5
5
6
6
5
3
6
1
6
0
0
4
6
3
6
6
6

Appendix Table 1.5 continued
BQ585514
Growth
BQ585612
Stress
Abiotic
BQ585675
Stress
Both
BQ585699
Growth
BQ585699
Growth
BQ585826
Stress
Biotic
BQ585834
Growth
BQ585841
Stress
Und.
BQ585998
Growth
BQ585999
Stress
Und.
BQ586015
Stress
Abiotic
BQ586036
Growth
BQ586159
Growth
BQ586261
Stress
Abiotic
BQ586318
Growth
Biotic
BQ586375
Stress
BQ586400
Stress
Biotic
Und.
BQ586464
Stress
BQ586518
Growth
BQ586553
Und.
Abiotic
BQ586635
Stress
BQ586657
Growth
BQ586719
Growth
BQ586790
Growth
BQ586894
Stress
Abiotic
BQ586903
Growth
BQ586920
Stress
Biotic
BQ586930
Growth
Abiotic
BQ586991
Stress
BQ587173
Growth
BQ587197
Stress
Both
BQ587264
Growth
BQ587272
Growth
BQ587329
Growth
BQ587384
Growth
BQ587396
Growth
BQ587458
Growth
BQ587584
Stress
Abiotic
BQ587622
Stress
Both
BQ587622
Stress
Both
BQ587644
Growth
BQ587840
Stress
Both
Both
BQ587848
Stress
BQ587858
Stress
Abiotic
BQ587874
Stress
Und.

1
0
7
1
6
1
3
1
0
1
2
2
6
6
2
3
3
6
6
0
0
6
6
6
0
6
7
2
7
1
6
0
6
3
2
6
6
0
7
3
0
0
6
6
7

BQ585514
BQ585612
BQ585675
BQ585699
BQ585699
BQ585826
BQ585834
BQ585841
BQ585998
BQ585999
BQ586015
BQ586036
BQ586159
BQ586261
BQ586318
BQ586375
BQ586400
BQ586464
BQ586518
BQ586553
BQ586635
BQ586657
BQ586719
BQ586790
BQ586894
BQ586903
BQ586920
BQ586930
BQ586991
BQ587173
BQ587197
BQ587264
BQ587272
BQ587329
BQ587384
BQ587396
BQ587458
BQ587584
BQ587622
BQ587622
BQ587644
BQ587840
BQ587848
BQ587858
BQ587874

125

Growth
Stress
Stress
Growth
Growth
Stress
Growth
Stress
Growth
Stress
Stress
Growth
Growth
Stress
Growth
Stress
Stress
Stress
Growth
Und.
Stress
Growth
Growth
Growth
Stress
Growth
Stress
Growth
Stress
Growth
Stress
Growth
Growth
Growth
Growth
Growth
Growth
Stress
Stress
Stress
Growth
Stress
Stress
Stress
Stress

Abiotic
Both

Biotic
Und.
Und.
Abiotic

Abiotic
Biotic
Biotic
Und.

Abiotic

Abiotic
Biotic
Abiotic
Both

Abiotic
Both
Both
Both
Both
Abiotic
Und.

4
5
6
6
3
1
3
4
5
6
5
5
0
6
5
6
0
6
6
3
0
6
3
6
0
6
3
2
4
1
6
5
6
6
5
6
6
6
0
3
6
5
2
6
1

Appendix Table 1.5 continued
BQ587887
Stress
Und.
BQ588055
Stress
Und.
BQ588316
Growth
BQ588349
Und.
BQ588529
Stress
Abiotic
BQ588562
Stress
Both
BQ588646
Growth
BQ588706
Growth
BQ588709
Growth
BQ588744
Growth
BQ588748
Growth
BQ588784
Growth
BQ588826
Signaling
BQ588862
Stress
Abiotic
BQ588870
Growth
BQ589141
Stress
Both
BQ589141
Stress
Both
BQ589354
Stress
Both
BQ589455
Growth
BQ589671
BQ589734
Stress
Abiotic
Abiotic
BQ589925
Stress
BQ589960
Growth
Und.
BQ590125
Stress
BQ590158
Growth
BQ590382
Signaling
BQ590743
Growth
BQ590906
Und.
BQ591201
Und.
BQ591253
Growth
BQ591613
Growth
BQ591669
Stress
Both
Both
BQ591669
Stress
BQ591700
Signaling
BQ591856
Growth
BQ591910
Growth
BQ591929
Growth
BQ592039
Signaling
Abiotic
BQ592168
Stress
BQ592234
Stress
Abiotic
BQ592254
Stress
Abiotic
Abiotic
BQ592254
Stress
BQ592267
Stress
Both
Both
BQ592267
Stress
BQ592312
Growth

7
6
2
0
7
7
7
0
1
6
6
0
6
6
0
3
7
6
7
2
3
2
0
6
6
6
0
7
0
6
0
6
3
3
6
0
6
6
2
7
3
6
6
6
6

BQ587887
BQ588055
BQ588316
BQ588349
BQ588529
BQ588562
BQ588646
BQ588706
BQ588709
BQ588744
BQ588748
BQ588784
BQ588826
BQ588862
BQ588870
BQ589141
BQ589141
BQ589354
BQ589455
BQ589671
BQ589734
BQ589925
BQ589960
BQ590125
BQ590158
BQ590382
BQ590743
BQ590906
BQ591201
BQ591253
BQ591613
BQ591669
BQ591669
BQ591700
BQ591856
BQ591910
BQ591929
BQ592039
BQ592168
BQ592234
BQ592254
BQ592254
BQ592267
BQ592267
BQ592312

126

Stress
Stress
Growth
Und.
Stress
Stress
Growth
Growth
Growth
Growth
Growth
Growth
Signaling
Stress
Growth
Stress
Stress
Stress
Growth
Stress
Stress
Growth
Stress
Growth
Signaling
Growth
Und.
Und.
Growth
Growth
Stress
Stress
Signaling
Growth
Growth
Growth
Signaling
Stress
Stress
Stress
Stress
Stress
Stress
Growth

Und.
Und.

Abiotic
Both

Abiotic
Both
Both
Both

Abiotic
Abiotic
Und.

Both
Both

Abiotic
Abiotic
Abiotic
Abiotic
Both
Both

1
6
3
0
6
3
1
0
6
6
6
1
6
6
1
3
0
6
6
2
5
4
0
6
5
6
6
0
6
6
0
6
6
3
6
0
3
6
2
6
0
4
6
6
1

Appendix Table 1.5 continued
BQ592313
Stress
Both
BQ592393
Growth
BQ592405
Und.
BQ592726
Stress
Abiotic
BQ592936
Growth
BQ592954
Stress
Both
BQ593076
Growth
BQ593155
Stress
Und.
BQ593157
Stress
Und.
BQ593209
Growth
BQ593316
Growth
BQ593362
Stress
Abiotic
BQ593448
Stress
Both
BQ593574
Growth
BQ593588
Stress
Abiotic
BQ593603
Stress
Und.
BQ593732
Growth
BQ593897
Stress
Abiotic
BQ593921
Signaling
BQ593922
Stress
Und.
BQ593937
Stress
Und.
BQ594117
Stress
Und.
BQ594123
Growth
BQ594267
Signaling
BQ594284
Growth
Biotic
BQ594412
Stress
BQ594432
Stress
Abiotic
Abiotic
BQ594558
Stress
BQ594578
Growth
BQ594715
Stress
Biotic
BQ594725
Stress
Und.
Both
BQ594736
Stress
BQ594788
Growth
Biotic
BQ594810
Stress
BQ594875
Stress
Abiotic
BQ594919
Growth
BQ594995
Und.
BQ594997
Growth
BQ595049
Growth
BQ595152
Stress
Abiotic
BQ595152
Stress
Abiotic
BQ595231
Growth
BQ595269
Growth
BQ595328
Stress
Biotic
BQ595355
Stress
Biotic

6
0
3
6
6
6
6
6
6
1
6
6
6
6
2
6
3
2
6
6
6
6
6
6
6
3
6
7
7
7
7
2
7
6
3
6
2
0
0
2
2
6
1
3
6

BQ592313
BQ592393
BQ592405
BQ592726
BQ592936
BQ592954
BQ593076
BQ593155
BQ593157
BQ593209
BQ593316
BQ593362
BQ593448
BQ593574
BQ593588
BQ593603
BQ593732
BQ593897
BQ593921
BQ593922
BQ593937
BQ594117
BQ594123
BQ594267
BQ594284
BQ594412
BQ594432
BQ594558
BQ594578
BQ594715
BQ594725
BQ594736
BQ594788
BQ594810
BQ594875
BQ594919
BQ594995
BQ594997
BQ595049
BQ595152
BQ595152
BQ595231
BQ595269
BQ595328
BQ595355

127

Stress
Growth
Und.
Stress
Growth
Stress
Growth
Stress
Stress
Growth
Growth
Stress
Stress
Growth
Stress
Stress
Growth
Stress
Signaling
Stress
Stress
Stress
Growth
Signaling
Growth
Stress
Stress
Stress
Growth
Stress
Stress
Stress
Growth
Stress
Stress
Growth
Und.
Growth
Growth
Stress
Stress
Growth
Growth
Stress
Stress

Both

Abiotic
Both
Und.
Und.

Abiotic
Both
Abiotic
Und.
Abiotic
Und.
Und.
Und.

Biotic
Abiotic
Abiotic
Biotic
Und.
Both
Biotic
Abiotic

Abiotic
Abiotic

Biotic
Biotic

6
3
6
6
6
6
0
6
6
1
1
6
0
6
2
6
0
5
6
6
6
1
6
6
6
1
6
3
6
3
0
5
3
6
5
6
0
1
0
1
2
6
1
4
5

Appendix Table 1.5 continued
BQ595434
Growth
BQ595543
Growth
BQ595697
Stress
Biotic
BQ595702
Stress
Und.
BQ595738
Stress
Both
Both
BQ595738
Stress
BQ595856
Growth
BQ654409
Growth
BU089547
Stress
Und.
BU089551
Signaling
BU089552
Stress
Und.
BU089554
Stress
Und.
BU089558
Signaling
BU089558
Signaling
BU089558
Signaling
BU089560
Growth
BU089560
Growth
BU089560
Growth
BU089560
Growth
BU089561
Stress
Und.
BU089561
Stress
Und.
BU089562
Stress
Und.
BU089563
Signaling
BU089563
Signaling
BU089563
Signaling
BU089563
Signaling
BU089564
Signaling
BU089565
Stress
Und.
BU089571
Stress
Biotic
CF430002
Growth
CF542675
Stress
Und.
CF542723
Growth
CF542797
Growth
CF542821
Growth
CF542879
Signaling
CF542908
Growth
CF542917
Und.
CF543001
Stress
Und.
CF543002
Stress
Und.
CF543157
Signaling
Abiotic
CF543165
Stress
CF543170
Signaling
CF543190
Stress
Both
CF543216
Growth
CF543254
Stress
Und.

0
0
3
6
6
6
3
1
0
6
6
7
3
0
6
2
6
6
0
6
6
6
6
0
6
0
6
6
6
3
6
3
6
6
6
6
0
3
6
0
7
3
6
7
6

BQ595434
BQ595543
BQ595697
BQ595702
BQ595738
BQ595738
BQ595856
BQ654409
BU089547
BU089551
BU089552
BU089554
BU089558
BU089558
BU089558
BU089560
BU089560
BU089560
BU089560
BU089561
BU089561
BU089562
BU089563
BU089563
BU089563
BU089563
BU089564
BU089565
BU089571
CF430002
CF542675
CF542723
CF542797
CF542821
CF542879
CF542908
CF542917
CF543001
CF543002
CF543157
CF543165
CF543170
CF543190
CF543216
CF543254

128

Growth
Growth
Stress
Stress
Stress
Stress
Growth
Growth
Stress
Signaling
Stress
Stress
Signaling
Signaling
Signaling
Growth
Growth
Growth
Growth
Stress
Stress
Stress
Signaling
Signaling
Signaling
Signaling
Signaling
Stress
Stress
Growth
Stress
Growth
Growth
Growth
Signaling
Growth
Und.
Stress
Stress
Signaling
Stress
Signaling
Stress
Growth
Stress

Biotic
Und.
Both
Both

Und.
Und.
Und.

Und.
Und.
Und.

Und.
Biotic
Und.

Und.
Und.
Abiotic
Both
Und.

5
0
6
6
6
6
1
5
5
6
6
1
1
5
5
6
4
5
6
6
6
6
0
6
0
4
6
6
6
6
4
1
6
3
6
6
5
3
6
1
1
6
6
3
6

Appendix Table 1.5 continued
CF543263
Growth
CF543368
CF543420
Growth
CF543447
Growth
CF543627
Growth
CK136263
Growth
CK136419
Stress
Abiotic
CK136420
Stress
Abiotic
CK136500
Signaling
CK136617
Stress
Abiotic
CK136649
Stress
Both
CK136658
Stress
Abiotic
CK136658
Stress
Abiotic
Abiotic
CK136719
Stress
CK136733
Growth
CK136793
Stress
Abiotic
CK136793
Stress
Abiotic
CK136863
Stress
Abiotic
CK136876
Stress
Abiotic
CX779686
Und.
CX779686
Und.
DX811261
Und.
ED032482
Und.
ED032901
Und.
EG551101
Growth
EG551187
Growth
EG551187
Growth
EG552103
Stress
Biotic
EG552299
Stress
Und.
EG552299
Stress
Und.
EG552800
Growth
*

Beta vulgaris accession

**

6
2
6
1
7
6
7
7
6
6
7
6
3
6
6
7
6
3
3
7
1
6
7
7
7
3
6
6
6
1
1

Putative function
function

CF543263
CF543368
CF543420
CF543447
CF543627
CK136263
CK136419
CK136420
CK136500
CK136617
CK136649
CK136658
CK136658
CK136719
CK136733
CK136793
CK136793
CK136863
CK136876
CX779686
CX779686
DX811261
ED032482
ED032901
EG551101
EG551187
EG551187
EG552103
EG552299
EG552299
EG552800

*+

Growth
Growth
Growth
Growth
Growth
Stress
Stress
Signaling
Stress
Stress
Stress
Stress
Stress
Growth
Stress
Stress
Stress
Stress
Und.
Und.
Und.
Und.
Und.
Growth
Growth
Growth
Stress
Stress
Stress
Growth

Putative secondary function

***+

18s rRNA

129

Abiotic
Abiotic
Abiotic
Both
Abiotic
Abiotic
Abiotic
Abiotic
Abiotic
Abiotic
Abiotic

Biotic
Und.
Und.
***

Undetermined

6
2
6
5
5
0
5
3
6
1
3
6
5
1
6
1
2
3
3
1
4
6
4
4
6
4
6
6
1
6
6

Appendix Table 1.6 K-means clustering of 343 putative stress (abiotic, biotic and both
abiotic and biotic), growth and hormone related genes in SP7622 cDNA over the first 24 h
of germination time points in H2O and H2O2. Accessions in bold were also used for qPCR
analyses.
SP7622
H2O
Bv
*
Accession
AW063023
AW063034
AW697779
AW777170
BE590301
BE590301
BE590328
BE590397
BE590397
BE590397
BE590444
BE590444
BF010998
BF011036
BF011057
BF011057
BF011062
BF011062
BF011089
BF011122
BF011211
BF011227
BG577441
BI073121
BI073128
BI073146
BI073146
BI073176
BI073235
BI073250
BI095934
BI096011
BI096038
BI096046
BI096111
BI096145

**

Role 1
Growth
Growth
Growth
Growth
Growth
Growth
Growth
Growth
Growth
Growth
Stress
Stress
Growth
Growth
Growth
Growth
Signaling
Signaling
Growth
Stress
Growth
Stress
Growth
Growth
Stress
Growth
Growth
Growth
Stress
Growth
Stress
Stress
Stress
Growth
Growth
Stress

H2O2
*+

Role 2

Abiotic
Abiotic

Both
Abiotic

Abiotic

Abiotic
Abiotic
Abiotic
Abiotic

Biotic

Cluster
2
1
2
6
6
6
3
6
6
9
2
8
0
2
6
6
6
9
0
0
6
2
2
6
1
6
6
6
2
0
6
6
6
6
0
6

Bv
*
Accession
AW063023
AW063034
AW697779
AW777170
BE590301
BE590301
BE590328
BE590397
BE590397
BE590397
BE590444
BE590444
BF010998
BF011036
BF011057
BF011057
BF011062
BF011062
BF011089
BF011122
BF011211
BF011227
BG577441
BI073121
BI073128
BI073146
BI073146
BI073176
BI073235
BI073250
BI095934
BI096011
BI096038
BI096046
BI096111
BI096145

130

**

Role 1
Growth
Growth
Growth
Growth
Growth
Growth
Growth
Growth
Growth
Growth
Stress
Stress
Growth
Growth
Growth
Growth
Signaling
Signaling
Growth
Stress
Growth
Stress
Growth
Growth
Stress
Growth
Growth
Growth
Stress
Growth
Stress
Stress
Stress
Growth
Growth
Stress

*+

Role 2

Abiotic
Abiotic

Both
Abiotic

Abiotic

Abiotic
Abiotic
Abiotic
Abiotic

Biotic

Cluster
10
6
10
1
6
6
6
0
10
10
2
10
10
10
6
9
0
6
3
10
6
2
0
6
9
1
6
1
10
1
1
1
1
3
2
3

Appendix Table 1.6 continued
BI096176
Growth
BI096176
Growth
BI096180
Growth
BI096232
Growth
BI096237
Growth
***
Und.
BI096304
Stress
BI096344
BI543239
BI543265
BI543278
BI543285
BI543316
BI543360
BI543377
BI543386
BI543415
BI543460
BI543526
BI543568
BI543569
BI543685
BI543739
BI543772
BI543889
BI543937
BI543980
BI643062
BI643098
BI643161
BQ060494
BQ060547
BQ060547
BQ060614
BQ060614
BQ487636
BQ487747
BQ487855
BQ487855
BQ487860
BQ487898
BQ487902
BQ487902
BQ487902
BQ487982

***

Und.
Stress
Stress
Growth
Growth
Growth
Growth
Stress
Stress
Growth
Stress
Growth
***+
Stress
Stress
Stress
Stress
Stress
Stress
Stress
Signaling
Signaling
Signaling
Signaling
Growth
Growth
Stress
Stress
Stress
Und.
Stress
Stress
Stress
Growth

Biotic
Abiotic

Biotic
Biotic
Abiotic

Both
Und.
Abiotic
Abiotic
Abiotic
Abiotic
Abiotic

Both
Both
Both
Both
Both
Both

8
1
6
0
3

BI096176
BI096176
BI096180
BI096232
BI096237

0 BI096304
6
6
6
6
2
1
6
6
0
6
0
3

BI096344
BI543239
BI543265
BI543278
BI543285
BI543316
BI543360
BI543377
BI543386
BI543415
BI543460
BI543526

2
2
2
6
2
2
6
0
2
6
2
9
9
6
8
1
6
9
3
6
1
6
6
0
6
0

BI543568
BI543569
BI543685
BI543739
BI543772
BI543889
BI543937
BI543980
BI643062
BI643098
BI643161
BQ060494
BQ060547
BQ060547
BQ060614
BQ060614
BQ487636
BQ487747
BQ487855
BQ487855
BQ487860
BQ487898
BQ487902
BQ487902
BQ487902
BQ487982

131

Growth
Growth
Growth
Growth
Growth
Stress
***
Und.
Stress
Stress
Growth
Growth
Growth
Growth
Stress
Stress
Growth
Stress
Growth
***+
Stress
Stress
Stress
Stress
Stress
Stress
Stress
Signaling
Signaling
Signaling
Signaling
Growth
Growth
Stress
Stress
Stress
Und.
Stress
Stress
Stress
Growth

1
3
1
9
1
Und.

***

Biotic
Abiotic

Biotic
Biotic
Abiotic

Both
Und.
Abiotic
Abiotic
Abiotic
Abiotic
Abiotic

Both
Both
Both
Both
Both
Both

6
1
6
1
6
2
6
1
1
0
0
9
6
2
2
10
0
10
10
6
1
2
6
2
10
1
6
3
6
1
10
1
0
1
6
0
1
9
1

Appendix Table 1.6 continued
BQ488119 Growth
Biotic
BQ488179 Stress
BQ488223 Stress
Abiotic
BQ488276 Stress
Both
BQ488276 Stress
Both
BQ488277 Growth
Abiotic
BQ488279 Stress
Both
BQ488337 Stress
BQ488461 Stress
Abiotic
Abiotic
BQ488466 Stress
BQ488487 Signaling
BQ488691 Stress
Biotic
Abiotic
BQ488795 Stress
Abiotic
BQ488850 Stress
BQ488890 Growth
BQ488894 Stress
Both
BQ488901 Growth
Biotic
BQ488935 Stress
BQ489058 Signaling
BQ489063 Signaling
BQ489063 Signaling
Both
BQ489189 Stress
BQ489620 Growth
BQ489704 Stress
Abiotic
BQ489814 Stress
Abiotic
BQ489814 Stress
Abiotic
BQ489848 Signaling
BQ489959 Growth
BQ490017 Stress
Abiotic
BQ490300 Growth
BQ490338 Growth
BQ490607 Stress
Abiotic
BQ499841 Und.
BQ582278 Stress
Both
BQ582382 Signaling
BQ582409 Stress
Und.
BQ582477 Growth
BQ582479 Stress
Biotic
BQ582606 Stress
Biotic
BQ582606 Stress
Biotic
BQ582618 Stress
Und.
BQ582629 Growth
BQ582632 Growth
BQ582634 Und.
BQ582634 Und.

8
3
6
6
8
6
6
6
2
9
6
6
6
6
6
9
3
6
6
0
6
2
0
1
6
1
2
6
6
1
2
6
6
9
9
9
6
9
6
6
1
6
6
0
6

BQ488119
BQ488179
BQ488223
BQ488276
BQ488276
BQ488277
BQ488279
BQ488337
BQ488461
BQ488466
BQ488487
BQ488691
BQ488795
BQ488850
BQ488890
BQ488894
BQ488901
BQ488935
BQ489058
BQ489063
BQ489063
BQ489189
BQ489620
BQ489704
BQ489814
BQ489814
BQ489848
BQ489959
BQ490017
BQ490300
BQ490338
BQ490607
BQ499841
BQ582278
BQ582382
BQ582409
BQ582477
BQ582479
BQ582606
BQ582606
BQ582618
BQ582629
BQ582632
BQ582634
BQ582634

132

Growth
Stress
Stress
Stress
Stress
Growth
Stress
Stress
Stress
Stress
Signaling
Stress
Stress
Stress
Growth
Stress
Growth
Stress
Signaling
Signaling
Signaling
Stress
Growth
Stress
Stress
Stress
Signaling
Growth
Stress
Growth
Growth
Stress
Und.
Stress
Signaling
Stress
Growth
Stress
Stress
Stress
Stress
Growth
Growth
Und.
Und.

Biotic
Abiotic
Both
Both
Abiotic
Both
Abiotic
Abiotic
Biotic
Abiotic
Abiotic
Both
Biotic

Both
Abiotic
Abiotic
Abiotic

Abiotic

Abiotic
Both
Und.
Biotic
Biotic
Biotic
Und.

0
10
6
1
1
1
1
6
2
6
6
6
1
1
1
1
6
1
0
1
6
10
3
6
1
1
1
3
6
3
9
3
1
1
9
10
6
10
6
9
6
1
6
1
1

Appendix Table 1.6 continued
BQ582685 Growth
BQ582687 Stress
Abiotic
BQ582708 Growth
BQ582721 Stress
Abiotic
BQ582763 Growth
BQ582770 Stress
Abiotic
BQ582799 Growth
BQ582800 Stress
Both
BQ582835 Stress
Abiotic
BQ582859 Growth
BQ582873 Stress
Und.
BQ583037 Und.
BQ583062 Signaling
BQ583249 Stress
Both
BQ583301 Growth
BQ583306 Stress
Both
BQ583369 Growth
BQ583421 Stress
Biotic
BQ583639 Stress
Both
BQ583692 Growth
BQ583764 Growth
BQ583828 Und.
BQ583877 Signaling
BQ584025 Growth
BQ584082 Stress
Abiotic
Abiotic
BQ584083 Stress
BQ584125 Growth
Biotic
BQ584136 Stress
BQ584136 Stress
Biotic
BQ584180 Growth
BQ584196 Stress
Abiotic
BQ584386 Stress
Biotic
Biotic
BQ584422 Stress
BQ584431 Growth
BQ584433 Stress
Biotic
BQ584462 Growth
BQ584474 Growth
BQ584498 Stress
Abiotic
BQ584876 Stress
Und.
BQ584898 Growth
BQ584988 Stress
Both
BQ585091 Signaling
BQ585097 Stress
Biotic
BQ585195 Growth
BQ585514 Growth

6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
1
9
0
6
3
6
6
6
1
6
1
2
9
6
6
9
1
6
6
6
6
6
6
6
6
6
6
6
6

BQ582685
BQ582687
BQ582708
BQ582721
BQ582763
BQ582770
BQ582799
BQ582800
BQ582835
BQ582859
BQ582873
BQ583037
BQ583062
BQ583249
BQ583301
BQ583306
BQ583369
BQ583421
BQ583639
BQ583692
BQ583764
BQ583828
BQ583877
BQ584025
BQ584082
BQ584083
BQ584125
BQ584136
BQ584136
BQ584180
BQ584196
BQ584386
BQ584422
BQ584431
BQ584433
BQ584462
BQ584474
BQ584498
BQ584876
BQ584898
BQ584988
BQ585091
BQ585097
BQ585195
BQ585514

133

Growth
Stress
Growth
Stress
Growth
Stress
Growth
Stress
Stress
Growth
Stress
Und.
Signaling
Stress
Growth
Stress
Growth
Stress
Stress
Growth
Growth
Und.
Signaling
Growth
Stress
Stress
Growth
Stress
Stress
Growth
Stress
Stress
Stress
Growth
Stress
Growth
Growth
Stress
Stress
Growth
Stress
Signaling
Stress
Growth
Growth

Abiotic
Abiotic
Abiotic
Both
Abiotic
Und.

Both
Both
Biotic
Both

Abiotic
Abiotic
Biotic
Biotic
Abiotic
Biotic
Biotic
Biotic

Abiotic
Und.
Both
Biotic

1
1
1
0
6
1
6
0
6
6
6
6
6
6
6
0
10
1
3
1
6
6
1
6
1
0
1
0
0
0
9
1
2
0
9
1
0
1
10
1
3
9
6
1
0

Appendix Table 1.6 continued
BQ585612 Stress
Abiotic
BQ585675 Stress
Both
BQ585699 Growth
BQ585699 Growth
BQ585826 Stress
Biotic
BQ585834 Growth
BQ585841 Stress
Und.
BQ585998 Growth
BQ585999 Stress
Und.
BQ586015 Stress
Abiotic
BQ586036 Growth
BQ586159 Growth
BQ586261 Stress
Abiotic
BQ586318 Growth
Biotic
BQ586375 Stress
BQ586400 Stress
Biotic
Und.
BQ586464 Stress
BQ586518 Growth
BQ586553 Und.
Abiotic
BQ586635 Stress
BQ586657 Growth
BQ586719 Growth
BQ586790 Growth
BQ586894 Stress
Abiotic
BQ586903 Growth
BQ586920 Stress
Biotic
BQ586930 Growth
Abiotic
BQ586991 Stress
BQ587173 Growth
BQ587197 Stress
Both
BQ587264 Growth
BQ587272 Growth
BQ587329 Growth
BQ587384 Growth
BQ587396 Growth
BQ587458 Growth
BQ587584 Stress
Abiotic
BQ587622 Stress
Both
BQ587622 Stress
Both
BQ587644 Growth
BQ587840 Stress
Both
Both
BQ587848 Stress
BQ587858 Stress
Abiotic
BQ587874 Stress
Und.
BQ587887 Stress
Und.

6
6
6
6
6
6
9
1
6
1
1
6
6
3
3
2
6
6
6
6
6
6
6
0
6
0
9
3
0
6
1
6
3
0
6
6
6
1
3
6
6
6
8
9
3

BQ585612
BQ585675
BQ585699
BQ585699
BQ585826
BQ585834
BQ585841
BQ585998
BQ585999
BQ586015
BQ586036
BQ586159
BQ586261
BQ586318
BQ586375
BQ586400
BQ586464
BQ586518
BQ586553
BQ586635
BQ586657
BQ586719
BQ586790
BQ586894
BQ586903
BQ586920
BQ586930
BQ586991
BQ587173
BQ587197
BQ587264
BQ587272
BQ587329
BQ587384
BQ587396
BQ587458
BQ587584
BQ587622
BQ587622
BQ587644
BQ587840
BQ587848
BQ587858
BQ587874
BQ587887

134

Stress
Stress
Growth
Growth
Stress
Growth
Stress
Growth
Stress
Stress
Growth
Growth
Stress
Growth
Stress
Stress
Stress
Growth
Und.
Stress
Growth
Growth
Growth
Stress
Growth
Stress
Growth
Stress
Growth
Stress
Growth
Growth
Growth
Growth
Growth
Growth
Stress
Stress
Stress
Growth
Stress
Stress
Stress
Stress
Stress

Abiotic
Both

Biotic
Und.
Und.
Abiotic

Abiotic
Biotic
Biotic
Und.

Abiotic

Abiotic
Biotic
Abiotic
Both

Abiotic
Both
Both
Both
Both
Abiotic
Und.
Und.

1
6
1
6
6
1
6
0
9
6
10
6
6
0
1
2
6
6
6
6
3
1
6
1
1
0
10
3
0
6
1
6
6
6
6
6
1
0
1
6
6
9
1
10
2

Appendix Table 1.6 continued
BQ588055 Stress
Und.
BQ588316 Growth
BQ588349 Und.
BQ588529 Stress
Abiotic
BQ588562 Stress
Both
BQ588646 Growth
BQ588706 Growth
BQ588709 Growth
BQ588744 Growth
BQ588748 Growth
BQ588784 Growth
BQ588826 Signaling
BQ588862 Stress
Abiotic
BQ588870 Growth
BQ589141 Stress
Both
BQ589141 Stress
Both
BQ589354 Stress
Both
BQ589455 Growth
BQ589671 BQ589734 Stress
Abiotic
Abiotic
BQ589925 Stress
BQ589960 Growth
Und.
BQ590125 Stress
BQ590158 Growth
BQ590382 Signaling
BQ590743 Growth
BQ590906 Und.
BQ591201 Und.
BQ591253 Growth
BQ591613 Growth
BQ591669 Stress
Both
Both
BQ591669 Stress
BQ591700 Signaling
BQ591856 Growth
BQ591910 Growth
BQ591929 Growth
BQ592039 Signaling
Abiotic
BQ592168 Stress
BQ592234 Stress
Abiotic
BQ592254 Stress
Abiotic
Abiotic
BQ592254 Stress
BQ592267 Stress
Both
Both
BQ592267 Stress
BQ592312 Growth
BQ592313 Stress
Both

1
9
6
1
3
1
6
6
6
1
6
6
6
6
3
1
6
3
2
3
6
0
1
6
6
6
2
6
9
6
6
6
6
9
6
6
6
0
0
6
3
6
6
6
6

BQ588055
BQ588316
BQ588349
BQ588529
BQ588562
BQ588646
BQ588706
BQ588709
BQ588744
BQ588748
BQ588784
BQ588826
BQ588862
BQ588870
BQ589141
BQ589141
BQ589354
BQ589455
BQ589671
BQ589734
BQ589925
BQ589960
BQ590125
BQ590158
BQ590382
BQ590743
BQ590906
BQ591201
BQ591253
BQ591613
BQ591669
BQ591669
BQ591700
BQ591856
BQ591910
BQ591929
BQ592039
BQ592168
BQ592234
BQ592254
BQ592254
BQ592267
BQ592267
BQ592312
BQ592313

135

Stress
Growth
Und.
Stress
Stress
Growth
Growth
Growth
Growth
Growth
Growth
Signaling
Stress
Growth
Stress
Stress
Stress
Growth
Stress
Stress
Growth
Stress
Growth
Signaling
Growth
Und.
Und.
Growth
Growth
Stress
Stress
Signaling
Growth
Growth
Growth
Signaling
Stress
Stress
Stress
Stress
Stress
Stress
Growth
Stress

Und.

Abiotic
Both

Abiotic
Both
Both
Both

Abiotic
Abiotic
Und.

Both
Both

Abiotic
Abiotic
Abiotic
Abiotic
Both
Both
Both

10
1
1
6
1
1
1
1
6
1
1
6
6
1
3
6
6
9
2
2
9
1
1
1
6
6
1
1
1
6
1
6
6
6
1
2
6
2
6
0
6
1
6
6
6

Appendix Table 1.6 continued
BQ592393 Growth
BQ592405 Und.
BQ592726 Stress
Abiotic
BQ592936 Growth
BQ592954 Stress
Both
BQ593076 Growth
BQ593155 Stress
Und.
BQ593157 Stress
Und.
BQ593209 Growth
BQ593316 Growth
BQ593362 Stress
Abiotic
BQ593448 Stress
Both
BQ593574 Growth
BQ593588 Stress
Abiotic
BQ593603 Stress
Und.
BQ593732 Growth
BQ593897 Stress
Abiotic
BQ593921 Signaling
BQ593922 Stress
Und.
BQ593937 Stress
Und.
BQ594117 Stress
Und.
BQ594123 Growth
BQ594267 Signaling
BQ594284 Growth
Biotic
BQ594412 Stress
BQ594432 Stress
Abiotic
Abiotic
BQ594558 Stress
BQ594578 Growth
BQ594715 Stress
Biotic
BQ594725 Stress
Und.
Both
BQ594736 Stress
BQ594788 Growth
Biotic
BQ594810 Stress
BQ594875 Stress
Abiotic
BQ594919 Growth
BQ594995 Und.
BQ594997 Growth
BQ595049 Growth
BQ595152 Stress
Abiotic
BQ595152 Stress
Abiotic
BQ595231 Growth
BQ595269 Growth
BQ595328 Stress
Biotic
BQ595355 Stress
Biotic
BQ595434 Growth

2
9
6
6
6
6
6
6
1
6
6
6
6
2
0
8
6
6
6
9
3
6
1
6
8
6
8
3
6
6
8
8
1
3
6
0
1
6
8
9
6
6
3
6
9

BQ592393
BQ592405
BQ592726
BQ592936
BQ592954
BQ593076
BQ593155
BQ593157
BQ593209
BQ593316
BQ593362
BQ593448
BQ593574
BQ593588
BQ593603
BQ593732
BQ593897
BQ593921
BQ593922
BQ593937
BQ594117
BQ594123
BQ594267
BQ594284
BQ594412
BQ594432
BQ594558
BQ594578
BQ594715
BQ594725
BQ594736
BQ594788
BQ594810
BQ594875
BQ594919
BQ594995
BQ594997
BQ595049
BQ595152
BQ595152
BQ595231
BQ595269
BQ595328
BQ595355
BQ595434

136

Growth
Und.
Stress
Growth
Stress
Growth
Stress
Stress
Growth
Growth
Stress
Stress
Growth
Stress
Stress
Growth
Stress
Signaling
Stress
Stress
Stress
Growth
Signaling
Growth
Stress
Stress
Stress
Growth
Stress
Stress
Stress
Growth
Stress
Stress
Growth
Und.
Growth
Growth
Stress
Stress
Growth
Growth
Stress
Stress
Growth

Abiotic
Both
Und.
Und.

Abiotic
Both
Abiotic
Und.
Abiotic
Und.
Und.
Und.

Biotic
Abiotic
Abiotic
Biotic
Und.
Both
Biotic
Abiotic

Abiotic
Abiotic

Biotic
Biotic

3
1
6
6
0
6
6
0
9
6
6
1
1
10
9
9
3
0
6
6
6
6
6
6
0
6
2
6
3
6
1
1
1
10
6
6
1
1
0
2
6
6
6
0
9

Appendix Table 1.6 continued
BQ595543 Growth
BQ595697 Stress
Biotic
BQ595702 Stress
Und.
BQ595738 Stress
Both
Both
BQ595738 Stress
BQ595856 Growth
BQ654409 Growth
BU089547 Stress
Und.
BU089551 Signaling
BU089552 Stress
Und.
BU089554 Stress
Und.
BU089558 Signaling
BU089558 Signaling
BU089558 Signaling
BU089560 Growth
BU089560 Growth
BU089560 Growth
BU089560 Growth
BU089561 Stress
Und.
BU089561 Stress
Und.
BU089562 Stress
Und.
BU089563 Signaling
BU089563 Signaling
BU089563 Signaling
BU089563 Signaling
BU089564 Signaling
BU089565 Stress
Und.
BU089571 Stress
Biotic
CF430002 Growth
CF542675 Stress
Und.
CF542723 Growth
CF542797 Growth
CF542821 Growth
CF542879 Signaling
CF542908 Growth
CF542917 Und.
CF543001 Stress
Und.
CF543002 Stress
Und.
CF543157 Signaling
Abiotic
CF543165 Stress
CF543170 Signaling
CF543190 Stress
Both
CF543216 Growth
CF543254 Stress
Und.
CF543263 Growth

3
6
6
6
6
6
9
6
6
6
6
3
9
3
0
6
6
6
6
6
6
6
3
0
0
6
6
6
6
6
1
6
6
6
6
6
8
6
6
1
6
6
0
6
6

BQ595543
BQ595697
BQ595702
BQ595738
BQ595738
BQ595856
BQ654409
BU089547
BU089551
BU089552
BU089554
BU089558
BU089558
BU089558
BU089560
BU089560
BU089560
BU089560
BU089561
BU089561
BU089562
BU089563
BU089563
BU089563
BU089563
BU089564
BU089565
BU089571
CF430002
CF542675
CF542723
CF542797
CF542821
CF542879
CF542908
CF542917
CF543001
CF543002
CF543157
CF543165
CF543170
CF543190
CF543216
CF543254
CF543263

137

Growth
Stress
Stress
Stress
Stress
Growth
Growth
Stress
Signaling
Stress
Stress
Signaling
Signaling
Signaling
Growth
Growth
Growth
Growth
Stress
Stress
Stress
Signaling
Signaling
Signaling
Signaling
Signaling
Stress
Stress
Growth
Stress
Growth
Growth
Growth
Signaling
Growth
Und.
Stress
Stress
Signaling
Stress
Signaling
Stress
Growth
Stress
Growth

Biotic
Und.
Both
Both

Und.
Und.
Und.

Und.
Und.
Und.

Und.
Biotic
Und.

Und.
Und.
Abiotic
Both
Und.

3
1
9
0
1
1
0
6
6
6
0
0
1
3
1
6
6
9
1
6
6
0
1
6
9
6
1
0
1
6
6
1
1
6
1
1
3
6
1
9
6
1
6
6
6

Appendix Table 1.6 continued
***+
CF543368 CF543420 Growth
CF543447 Growth
CF543627 Growth
CK136263 Growth
CK136419 Stress
Abiotic
CK136420 Stress
Abiotic
CK136500 Signaling
CK136617 Stress
Abiotic
CK136649 Stress
Both
CK136658 Stress
Abiotic
CK136658 Stress
Abiotic
Abiotic
CK136719 Stress
CK136733 Growth
CK136793 Stress
Abiotic
CK136793 Stress
Abiotic
CK136863 Stress
Abiotic
CK136876 Stress
Abiotic
CX779686 Und.
CX779686 Und.
DX811261 Und.
ED032482 Und.
ED032901 Und.
EG551101 Growth
EG551187 Growth
EG551187 Growth
EG552103 Stress
Biotic
EG552299 Stress
Und.
EG552299 Stress
Und.
EG552800 Growth
*

Beta vulgaris accession

**

2
6
6
6
6
2
2
6
6
6
3
6
6
3
2
8
8
9
2
8
6
8
0
6
6
0
6
6
9
6

Putative function
function

CF543368
CF543420
CF543447
CF543627
CK136263
CK136419
CK136420
CK136500
CK136617
CK136649
CK136658
CK136658
CK136719
CK136733
CK136793
CK136793
CK136863
CK136876
CX779686
CX779686
DX811261
ED032482
ED032901
EG551101
EG551187
EG551187
EG552103
EG552299
EG552299
EG552800
*+

Growth
Growth
Growth
Growth
Stress
Stress
Signaling
Stress
Stress
Stress
Stress
Stress
Growth
Stress
Stress
Stress
Stress
Und.
Und.
Und.
Und.
Und.
Growth
Growth
Growth
Stress
Stress
Stress
Growth

Abiotic
Abiotic
Abiotic
Both
Abiotic
Abiotic
Abiotic
Abiotic
Abiotic
Abiotic
Abiotic

Biotic
Und.
Und.

Putative secondary function

***+

18s rRNA

138

***

2
1
0
9
0
10
10
3
6
3
1
3
6
6
2
2
2
1
2
9
6
3
10
3
9
10
0
0
3
9

Undetermined