Phylogenetic Relationships in Australian Turf Grass

PHYLOGENETIC RELATIONSHIPS

IN AUSTRALIAN TURF GRASS CULTIVARS

OF THE GENERA STENOTAPHRUM and CYNODON

A thesis submitted for the degree of Master of Science

by Moon Sun Kim

School of Biotechnology and Biomolecular Science University of New South Wales

February, 2005

TABLE OF CONTENTS

ACKNOWLEDGEMENTS i

ABBREVIATION ii

SUMMARY iii CHAPTER ONE: INTRODUCTION

1.1. Turf grass 1 1.1.1 The turf grass family Poeceae 2 1.1.1.1 Stenotaphrum specie 5 1.1.1.1.1 Stenotaphrum secundatum (Walt) Kuntze 6 1.1.1.1.2 Buffalo grass varieties and cultivars 9 1.1.1.2 Cynodon species 10 1.1.1.2.1 Cynodon dactyoln (L.) Pers. 11 1.1.1.2.2 Cynodon dactylon var. dactylon 13 1.1.1.2.3 Cynodon transvaalensis (Burtt-Davy) 13 1.1.1.2.4 Cynodon variants and cultivars 14

1.2. Taxonomic analysis in plant 18 1.2.1 Plant identification and Plant Breeder Rights 18 1.2.1.1 DNA profiling and PBR in Australia 19 1.2.2 Methodologies for plant taxonomic analysis 20 1.2.2.1 Morphological characteristics 20 1.2.2.2 Biochemical characteristics 20 1.2.2.3 Molecular characteristics 21 1.2.2.3.1 Protein-based markers 21 1.2.2.3.2 DNA-based markers 22 1.2.2.3.3 Polymerase Chain Reaction (PCR) 23 1.2.2.3.4 PCR-based genetic markers 25 1.2.2.3.5 Simple sequence repeat (SSR) and inter simple 27 sequence repeat (ISSR) molecular markers 1.2.3 Molecular phylogenic study of turf grass 31

TABLE OF CONTENTS

1.3. Genetic data Analysis 34 1.3.1 Types of data 34 1.3.2 Data Analysis 35 1.3.2.1 Distance matrix method 35 1.3.2.2 Maximum parsimony and Maximum likelihood methods 36 1.3.2.3 Steps in the data analysis based on Distance matrix 37 1.3.2.4 Evaluation of the test 38

1.4. Project objectives 39

CHAPTER TWO: MATERIALS AND METHODS

2.1. Materials 40 2.1.1 Plant materials 40 2.1.2 Primers 40 2.1.3 PCR kit 41 2.1.4 Enzyme and markers 41 2.1.5 General reagents 41

2.2. Methods 42 2.2.1 Extraction of plant genomic DNA 42 2.2.2 Quantitation of genomic DNA 43 2.2.2.1 Dye Binding Fluorescence 43 2.2.2.2 UV absorption 43 2.2.2.3 Electrophoresis for quantitation of genomic DNA 43 2.2.3 Polymerase Chain Reaction (PCR) 44 2.2.3.1 Optimisation of PCR conditions 44 2.2.3.2 ISSR PCR amplification 44 2.2.4 Electrophoresis and visualisation of gels 45 2.2.4.1 Agarose gel electrophoresis and ethidium bromide staining 45 2.2.4.2 Non-denaturing PAGE and silver staining 45 2.2.4.3 Fluorescent labeling detection 46 2.2.5 Statistical Analysis 47 2.2.5.1 Data scoring and Distance matrix 47 2.2.5.2 Clustering analysis and construction of phylogenetic trees 47

TABLE OF CONTENTS

CHAPTER THREE: RESULTS AND DISCUSSION 3.1. Optimization of ISSR-PCR amplification 48 3.2. Preliminary screening 48 3.2.1 Template 48 3.2.1.1 Time of storage of tissue 49 3.2.1.2 RNA inhibition 51 3.2.1.3 Amount of DNA 52 3.2.2 Concentration of ISSR primer 53 3.2.3 Concentration of Taq Polymerase 54

3.2.4 Concentration of MgCl2 55 3.2.5 Number of thermal cycles 57 3.2.6 Annealing temperature 58 3.2.7 Summary of PCR optimal condition 61

3.3. Reproducibility and repeatability in turf grass 62

3.4. Genetic identification of Buffalo grass cultivars using 63 ISSR-PCR analysis 3.4.1 Informative ISSR primers for cultivar identification 63 3.4.2 Polymorphism analysis of Buffalo grass cultivars 66 3.4.2.1 Polymorphism as seen on agarose gel electrophoresis 67 3.4.2.2 Polymorphism as seen on non-denaturing PAGE 70 3.4.2.3 Polymorphism as seen on non-denaturing PAGE with 72 fluorescent labeling detection 3.4.3 Genetic variation of Buffalo grass cultivars 74 3.4.3.1 Specific markers for closely related cultivars 79 3.4.4 Phylogenetic relationship of Buffalo grass cultivars 82 3.4.4.1 Data matrices of Buffalo grass cultivars 82 3.4.4.2 Distance matrices of Buffalo grass cultivars 84 3.4.4.3 Clustering analysis and Phylogenetic construction of Buffalo 86 grass cultivars 3.4.5 Comparison of detection methods 92

TABLE OF CONTENTS

3.5. Genetic identification of Couch grass cultivars using 95 ISSR-PCR analysis 3.5.1 Informative ISSR primers for cultivar identification 95 3.5.2 Polymorphism analysis of Couch grass cultivars 98 3.5.2.1 Polymorphism as seen on agarose gel electrophoresis 98 3.5.2.2 Polymorphism as seen on non-denaturing PAGE 102 3.5.3 Genetic variation of Couch grass cultivars 105 3.5.3.1 Specific markers for closely related cultivars 108 3.5.4 Phylogenetic relationship of Couch grass cultivars 115 3.5.4.1 Data matrices of Couch grass cultivars 115 3.5.4.2 Distance matrices of Couch grass cultivars 120 3.5.4.3 Clustering analysis and Phylogenetic construction of Couch grass 120 cultivars 3.5.5 Comparison of detection methods 127

CHAPTER FOUR: CONCLUSION 4.1. Cultivar identification of turf grass using ISSR-PCR 128 REFERENCES 131

APPENDICES vi

ACKNOWELDGEMENTS

ACKNOWLEDGEMENTS

At first, I would appreciate my supervisor, Dr. Ian McFarlane for experimental recommendation, reviewing of the drafts of my thesis to advance of the thesis’s skill and thanks for encouragement of my study.

I am also grateful to Dr. Wendy Glenn for helping of advice in general molecular biology technique and Dr. Alan Wilton for helping of teaching of computer analysis involved with the phylogenetic analysis.

I would like to thank Dr. Don Loch for providing cultivars for my study and help with cultivar origins and names.

I also thank my laboratory colleagues and Korean friends who are studying in BABS for technical discussions and individual encouragement during the studying.

Finally, I thank my parents for their supporting and my husband, Mickey, for helping emotionally to study very hard all the time.

ABBREVIATIONS

The abbreviation and symbols used throughout this thesis follow the recommendations of the IUPAC-IUB Commission on Biochemical Nomenclature.

AP-PCR Arbitrary Primed PCR

CTAB Hexadecyltrimethylammonuim bromide

DAF DNA Amplification Fingerprinting

dNTP Deoxynucleotide triphosphate

EDTA Ethylendiaminetetra-acetic acid

EtBr Ethidium bromide

FISSR Fluorescent Inter-Simple Sequence Repeat

ISSR Inter Simple Sequence Repeat

NJ Neighbour-Joining algorithm

PAGE Polyacrylamide gel electrophoresis

RAPD Randomly Amplified Polymorphic DNA

PAUP Phylogenetic Analysis Using Parsimony

PBRs Plant Breeder Rights

PCR Polymerase Chain Reaction

RFLP Restriction Fragment Length Polymorphism

SSR Simple Sequence Repeat

TEMED N,N,N',N' - tetramethylenediamine

UV Ultra Violet

SUMMARY

Turf grass has coexisted with human beings for a long time and now has become indispensable for human environment. Many people have been eager to have gorgeous and economical place for their purpose. Therefore, many new turf varieties have been created and turf suppliers have selected and created more appropriate grass cultivars.

The turf grass industry is now a large world-wide market. There is also a large market in

Australia. Many turf grasses that have been developed for Australian circumstances have been used for beautification, recreational facilities and functional facilities. For example, some of the Buffalo grass cultivars (Stenotaphrum species) and Couch grass cultivars (Cynodon species) have been used in many areas and new varieties are still being developed. Moreover, the Australian government has ratified the intellectual property law that offers plant breeder protection in the Plant Breeder Rights Act of 1994.

The granting of Plant Breeder Rights (PBRs) is based on being able to establish the

Distinctness, Uniformity and Stability of the new variety (Smith, 1997).

With developments in the field, cultivar identification and classification of turf grass cultivars is very important. The identification of plants and their variation by using morphological traits has been used for a long time. One obvious reason for this is the ease of observing and recoding external features. However, morphological comparisons may have limitations including subjectivity in the analysis of physical characteristics because of continuous variation. This is particularly so among cultivars with highly similar pedigrees. Therefore, it has been suggested that a more sensitive diagnostic test would benefit the identification of cultivars.

iii

SUMMARY

Inter Simple Sequence Repeats (ISSRs), first developed in 1994, were used to analyse genetic diversity of Buffalo and Couch grass cultivars in this study. ISSRs are semi- arbitrary markers amplified by the Polymerase Chain Reaction (PCR) in the presence of one primer complementary to target microsatellites.

Ten Buffalo and 50 Couch grass cultivars were screened using 100 commercial ISSR primers. Eighteen ISSR primers produced reproducible and informative polymorphic bands from the Buffalo grass cultivars using agarose gel electrophoresis with ethidium bromide staining and non-denaturing polyacylamide gel electrophoresis with silver staining to separate bands. In addition a newer detection method termed Fluorescent labeling detection (FISSR-PCR) was tried. Two of the informative primers were labeled with the fluorescent tag 6-FAM and screened against the 10 Buffalo grass cultivars.

(AG)n and (AC)n repeat sequences produced the most useful polymorphic bands, from agarose gel electrophoresis and non-denaturing PAGE, to differentiate each Buffalo grass cultivar. Phylogenetic trees were created from the data using the Neighbour- joining algorithm. Interestingly the cultivars separated into two main groups. One contained those cultivars granted PBRs in the United States of America, for example

Palmetto. The other group contained a number of cultivars granted PBRs in Australia, for example Sir Walter. Other Australian cultivars, such as Shademaster and ST-15, were found to be closely related to Sir Walter. The phylogenetic tree from FISSR analysis had an almost identical grouping structure compared to the two phylogenetic trees from agarose gel electrophoresis and non-denaturing PAGE, although only two fluorescent primers were used. This technique has excellent potential for cultivar identification and diversity because of its time and cost-effectiveness, and sensitivity.

SUMMARY

The results are the first report related to Buffalo grass cultivar identification using DNA based marker.

Couch grass cultivars were also screened using the ISSR primers selected as informative. Apart from the (AG)n and (AC)n sequences, the (TG)n repeat sequence also produced reproducible bands. The same electrophoresis methods were used for separation of Couch grass PCR amplicons. The analysis showed high intraspecific variation. For example, Wintergreen was differentiated very well from Windsor Green in contrast to previous reports that used RAPD and AP-PCR analysis. Windsor Green is an irradiation derivative of Wintergreen. Greenlees Park Couch was placed in the

Cynodon dactylon group by AP-PCR analysis, but it clustered with C. dactylon and C. transvaalensis hybrids using Internal Transcribe Spacer sequences. In this study, it was found that the cultivar clustered with the C. dactylon group, not the hybrid group. Some intraspecific hybrids, such as Tifdwarf, Tifgreen, and TifEagle could not be distinguished from one another using the ISSR primers. More sensitive techniques, for example, sequencing of the PCR products may be needed to identify the variation in these plants.

In conclusion, ISSR-PCR analysis demonstrated useful variability within the Buffalo and Couch grass cultivars examined. The genetic variation will be based on forensic and accurate result for cultivar identification and will be useful for protection from intellectual property of new plant cultivars.

CHAPTER ONE: INTRODUCTION

1.1. Turf grass

Turf grasses, an integral part of landscape ecological systems worldwide, are one of nature’s many assets. Along with other landscape plants, grass provides humankind with a living form enhancing the environment and improving on natural features. Turf grass has been used in many different ways and under different conditions. As a result, the multi-billion dollar industry is many-faceted, and encompasses diverse facilities and services (Watson et al., 1992).

Turf grass plays an important role in daily life and in the pursuit of happiness. From a beautification standpoint, it provides a canvas for landscaped areas, contributing to aesthetic appeal and adding to economic value and recreational facilities including an array of sports fields, golf courses, parks, and lawns. Turf grass grown primarily for utility turf provides functional value that includes dust control, erosion control, and glare reduction. These can serve as safety factors on airfields and highways (Ho, 1999).

Improvement, selection and creation of new cultivars are major considerations in the modern turf industry. According to Burton (1992), the best turf is realized when genotype, environment, and management are balanced. An ideal turf grass should be wear-resistant when mowed, drought tolerant, and remain green and dense for long periods. It should also withstand both high and low temperature, and would include weed and pest resistance. The balance required for good turf can be most easily and economically achieved by changing the genotype to more nearly fit the existing environment (Burton, 1992). Much variability between genotypes can be found or

CHAPTER ONE: INTRODUCTION created within a species, leading through genetic improvement to the creation of a better turf grass variety.

1.1.1 The turf grass family Poeceae

There are approximately 10,000 known grass species, which constitute about 3.3 % of the total world species of plants (ATRI, 1995). Grasses are believed to have emerged as a distinct group of flowering plants (Angiosperms) during the late Cretaceous period of the Mesozoic era, approximately 70 million years ago (Harlan, 1956).

Around 60 million years ago in all continents except Australia, herbivorous mammals, such as horses, deer and cattle, arose from a group of early mammals. Since then, grasses and these large grazing animals have co-evolved. This co-evolution has resulted in specific structural adaptations of many grasses to withstand defoliation by the animals that graze upon them. The formation of short basal inter-nodes and specialized underground branching have been two important factors in allowing grasses to withstand grazing (ATRI, 1995).

Throughout the world less than 30 grass species are used as turf grass. Whilst these grasses have been classified on the basis of their morphology, they can also be grouped according to their centres of origin and the evolutionary pressures under which they evolved. For example they can be grouped as either a cool season species (temperate) or a warm season species (tropical), depending on their temperature tolerance which is a consequence of their origin. The taxonomic relationships between cultivated turf grass genera are shown in Figure 1.1.

CHAPTER ONE: INTRODUCTION

Family

Subfamily Gramineae syn: Tribe Poeceae Genus

Pooideae Panicoideae Eragrostoideae

Andropogoneae Eragrosteae Poeae Aveneae Triticeae Paniceae Chlorideae Zoysieae Eremochloa (Centipede gra

ss) Agropyron Axonopus Bothriochloa Bouteloua Zoysia (Carpet grass) (Creeing blue Festuca Agrostis (Blue grass) (Zoysia grass, Paspalum grass) (Fescue) (Bent grass) Buchloé Manila grass) (Bahia grass, Lolium Amnophila (Buffalo grass) Dallis grass) (Rye grass) Cynodon Digitaria Poa (Bermuda (Blue couch) (Blue grass) grass) Pennisetum (Kikuyu grass) Stenotaphrum (St. Augustine grass) Warm season turf grass

Fig. 1.1 Taxonomic relationships between commonly cultivated turf grass genera.

Cynodon is in the family Eragrostoideae and Stenotaphrum is in the family Panicoideae (Beard and Krans, 1987).

CHAPTER ONE: INTRODUCTION

Cool season turf grasses, approximately 20 species, originated from various regions adjacent to forests in Europe, Northern Asia and the Mediterranean region of North

Africa. They have a temperature optimum for growth of 15-24ºC. Most of these grass species have a tufted growth habit and generally do not tolerate close mowing because they evolved in the absence of strong grazing pressure from animals. Other factors that have contributed to the Eurasian concentration of these grass species are fertile soils and a well-distributed rainfall. As a group, they can tolerate partial shade (ATRI, 1995).

Cool season turf grass species are organized within the subfamily Pooideae. (Busey,

1989).

There are approximately 14 species of warm season turf grass, which are within the subfamilies Panicoideae and Eragrostoideae (Busey, 1989). The warm season turf grasses have more diverse centres of origin compared to the cool season species. Most have originated from the natural grasslands in tropical East Africa, Southern Asia and subtropical South America. Their temperature optimum for growth is 21-35ºC. Warm season turf grass species are lower growing, tolerant of close and frequent mowing and more drought and heat tolerant than the cool season species. Most of the warm-season turf grasses have a creeping habit, spreading by sending out stolons or rhizomes

(Handreck and Black, 1994).

CHAPTER ONE: INTRODUCTION

1.1.1.1 Stenotaphrum species

The genus Stenotaphrum is one of the warm-season grasses. It is a tropical member of

the tribe Paniceae of the Panicoidea (Busey, 1995). The genus contains seven species.

Life cycles, distribution and habitat are briefly described in Table 1.1.

Table 1.1 Species of Stenotaphrum, their life cycles, distribution, and representative habitats; adapted from Sauer, 1972

Species Life cycle Distribution Representative habitats

Indian Ocean (Aldabra and Dunes and coastal limestone S. clavigerum Annual Assumption Islands)

Beach ridges and inland stream banks; Indian Ocean (East Africa and planted and volunteers in pastures and S. dimidiatum Perennial Malagasy Republic to Sri Lanka) lawns; ground cover under plantation crops

S. helferi Perennial Southern China to Malaysia Forested stream banks and paths

S. micrathum Annual Indian Ocean to South Pacific Open sandy beaches, coralline limestone

Coastal salt marshes, forest borders, S. oostachyum Perennial Malagasy Republic clearings

Sandy beach ridges, stream banks, low World wide, tropics to warm lying disturbed areas; widely cultivated S. secundatum Perennial humid regions for lawns; used as forage and ground cover under plantation crops

S. unilaterale Perennial Malagasy Republic Alluvial uplands

CHAPTER ONE: INTRODUCTION

1.1.1.1.1 Stenotaphrum secundatum (Walt) Kuntze

S. secundatum is widely used as a lawn and pasture grass in warm, subtropical and tropical climate regions (Sauer, 1972). The species is distributed along the Gulf Coast in the United States of America (USA), in southern Mexico, throughout South America,

South Africa, and Australia. It grows naturally on sandy beaches and salty or fresh water marshes.

S. secundatum has different common names depending on the area. It is usually called

‘St. Augustine grass’ in the USA (or ‘Charleston’ in some areas of the South-East),

‘Buffalo grass’ in Australia and the Republic of South Africa and ‘San Augustine’ in

Latin America. In the case of ‘Buffalo grass’, it should not be confused with Buchloe dactyloides, know as Buffalo grass in the USA (Sauer, 1972).

Buffalo grass is a coarse textured, stoloniferous species that roots at the nodes.

Compared to Couch grass (described in the next section), Buffalo grass does not have rhizomes (Duble, 2002). The absence of rhizomes or other protected stems means that it recuperates poorly from defoliation and has poor wear tolerance. The stolons of Buffalo grass are flattened and have a purple colour. Other features of Buffalo grass are the broad, lanceolate leaves of a dark colour, a folded leaf bud and a hair rim ligule.

Internodes may vary from purplish to green (ATRI, 1995). The inflorescences of St.

Augustine grass are modified spike-like panicles, with the branches of the inflorescence contracted and often reduced to single spikelets (Sauer, 1972) (Fig. 1.2). Deliberate propagation of Buffalo grass is usually vegetative by stolon cuttings, plugs, and sod.

CHAPTER ONE: INTRODUCTION

(A) (B)

Fig. 1.2 Typical appearance of Buffalo grass. (A) ST-26 cultivar, (B) ST-15 spikes

Although genetic diversity in Buffalo grass is small, it is divided into clusters of similar genotypes. Morphotype clusters of American St. Augustine grass have been designated variously as “Groups,” “Races” (Busey et al., 1982; Busey, 1986), and “demes” (Sauer,

1972). Cultivars can be keyed to the various races and groups (Table 1.2).

Table 1.2 Morphological classification of St. Augustine grass (Busey et al., 1982)

Spikelets ≤ 5.2 mm long Inflorescence racemes ≤ 15 ------Breviflorus race (2n=18) ≥ 13 ; stigmas usually white ------Gulf Coast group < 13 ; stigmas usually purple ------Dwarf group > 15 Internode attenuation (length/thickness) > 25 ------Longicaudantus race ≤ 25 leaf blades glabrous ------Bitterblue group (2n=27) leaf blades sparsely pubscent ------African polyploid (2n=30) Spikelets > 5.2 mm long ------Floratam group (2n=32)

CHAPTER ONE: INTRODUCTION

Most cultivars are diploids (2n=18) and are subdivided into either the Breviflorus race or the Longicaudantus race. The Breviflorus race is widely represented by weedy and adventive populations (Busey, 1986). The race is composed of a Gulf Coast group and a

Dwarf group depending on the colour of the stigmas. The Gulf Coast group was first described in a 1968 collection from Point Clear along the sandy shores of Mobile Bay,

Alabama, USA. The well known cultivar, Palmetto (‘SS100’ as a registered PBR name and plant patent name) belongs to this group. The Dwarf Group includes genotypes with generally strong anthocyanin pigmentation in the stolons, purple stigmata, and dark green leaf blades (Busey et al., 1982). Longicaudatus race genotypes (2n=18) have elongate stolons (Busey, 1986) and long leaves. This race is probably synonymous with the Natal-Plata deme (Sauer, 1972). Polyploidy has been used in a major way to classify the Buffalo grasses. Polyploid Buffalo grasses were first identified by Long and Bashaw

(1961) who described sterile triploids (2n = 27) with irregular meiosis. In small experimental plots, the polyploids received lower turf grass quality scores than diploids

(Busey, 1986), but were more resistant to the Southern Chinch bug (Busey and Zaenker,

1992) and drought (Busey, 1987). Based on ploidy, several variants of Buffalo grass have been reported. In early records normal strains had a white stigma colour and were fertile diploids with 18 chromosomes. A sterile triploid variant with purple–coloured stigma was first collected from the Cape of Good Hope in 1961 (Duble, 2002). In the case of African polyploids (2n=30), these genotypes act as diploids and they have normal bivalent chromosome pairing at diakinesis and set seed (Busey, 1990). Adaptive and morphological variations in Buffalo grasses are associated with chromosome differences. For example, diploids have narrower, thinner, translucent and brighter green leaf blades than polyploids (Busey, 1986).

CHAPTER ONE: INTRODUCTION

1.1.1.1.2 Buffalo grass varieties and cultivars

Many Buffalo grass cultivars have been commercially released as good and soft grass, especially with good shade tolerance. In the USA, the common Buffalo grass cultivars are Bitterblue, Floratine, Floratam, Raleigh and Seville. Bitterblue, Floratine and

Floratam are less tolerant of the cold and should only be grown in the coastal areas of

South Carolina. Bitterblue has a finer, denser texture and darker blue-green color than

Common Buffalo grass. Floratine is an improved selection from Bitterblue that has a finer leaf texture and lower, denser growth habit that allows closer mowing than with

Common Buffalo grass. Floratam is an improved type of Buffalo grass that has Chinch bug and SADV (St. Augustine Decline Virus) resistance and reddish stolons. It has a very coarse texture and poor cold and shade tolerance. Seville is a semi-dwarf cultivar with a dark green color and low growth habit. It is susceptible to Chinch bug and

Webworm damage and is cold sensitive (Polomski, 2003).

There are also many Buffalo grass cultivars available in Australia. Palmetto (the trademark name) which was also known as SS100 (plant patent name) has a green stem and white stigma. It was originally discovered on a turf farm in Florida, USA. (Seaturn,

1996). ST-85 was the first of the newer ‘soft’ Buffalo grasses to become commercially available. It is small leafed, bright green in colour, very dwarf and dense. Shademaster is not a true soft Buffalo, being large leafed and having considerable silica content in the cells. However, it has excellent shade tolerance, although is very slow growing

(McMaugh, 1997). Sir Walter, developed in the mid- 1990s, is the only PBR protected variety of soft leaf Buffalo grass that is Australian “owned”. B12 has open pollination followed by seedling selection from Sir Walter. The selection took place in Clarendon,

NSW in 2001 (Paananen, 2002). Other leading varieties of PBR or patented soft leaf

CHAPTER ONE: INTRODUCTION

Buffalo grasses, such as Palmetto are American owned with a percentage of every sale going overseas (AGRITURF, 2003). Austine (AusTine) has recently been used by some growers to market ST-26 and Ausdwarf (AusDwarf) to market ST-91.

1.1.1.2 Cynodon species

The genus Cynodon is a perennial, warm-season and sod-forming grass used extensively in the turf industry throughout the world (Anonymous, 1972; Beard, 1973).

The genus as taxonomically revised by Harlan et al., (1970), comprises eight species and ten varieties (Table 1.3).

C. dactylon is the most widely distributed and cosmopolitan species and is derived from

South Africa (Anonymous, 1972). Like Stenotaphrum, Cynodon also has different common names in different countries of the world. It is called Bermuda grass in the continental United States of America, Couch grass in Australia, Manienie grass in

Hawaii, Chiendent grass in Mauritius, Wire grass in India, Kweek grass in South Africa and Kabuta in Fiji (Rochecouste, 1962; Skerman and Riveros, 1990; Duble, 1996)

C. transvaalensis is generally called African-type Bermuda grass or Florida grass. It was originally collected near Johannesburg, South Africa about 1907 (Juska and Hanson,

1964). It was introduced into the USA and later exported back to South Africa.

(Taliaferro, 1995).

C. dactylon and C. transvaalensis are the two principal Cynodon grass species used for turf (Caetano-Anollés et al., 1995). Interspecific crosses between these two grasses also have been widely used for intensively maintained turf situations such as golf courses,

CHAPTER ONE: INTRODUCTION athletic fields, tennis courts and bowling greens.

Table 1.3 Taxonomic classification of the genus Cynodon (Harlan et al., 1970)

Chromosome Epithet Distribution number C. aethiopicus Clayton 18, 36 East Africa Rift valleys et Harlan C. arcuatus J.S. Presl. ex C.B. Malagasy, and southern India to northern 36 Presl. Australia C. barberi Rang. et Tad. 18 Southern India C. dactylon (L.) Pers. 36 Cosmopolitan var. dactylon var. afghanicus Harlan et 18, 36 Afghanistan steppes de Wet var. aridus Harlan et Southern Africa northward to Palestine; east to 18 deWet south India var. coursii (A. Camus) 36 Madagascar Harlan et de Wet var. elegans Rendle 36 Southern Africa, south of latitude13º S var. polevansii (Stent) 36 Near Barberspan, South Africa C. incompletus Nees 18 South Africa; Transvaal to the Cape var. incompletus var. hirsutus (Stent) 18, 36 South Africa; Transvaal to the Cape deWet et Harlan C. nlemfuensis Vanderyst 18, 36 East Africa var. nlemfuensis var. robustus Clayton et 18, 36 East Tropical Africa Harlan C. plectostachyus (K.Schum.) 18 East Tropical Africa Pilger C. transvaalensis Burtt-Davy 18 South Africa C. x magennisii Hurcombe 27 South Africa x: natural hybrid between C. dactylon and C. transvaalensis

1.1.1.2.1 Cynodon dactyoln (L.) Pers.

Common couch grass is a long lived perennial that has adapted from warm and humid to warm semi-arid regions of the world (Beard, 1973). This species has a folded leaf bud, a ligule with a membranous rim of short hairs and typically having stolons above the ground and rhizomes below the ground (ATRI, 1995). The leaves are fine textured.

CHAPTER ONE: INTRODUCTION

Propagation is either vegetative by means of sprigs, plugs and sod, or in the case of

Common couch by seed as well (Beard, 1973) (Fig. 1.3).

(A) (B) Fig. 1.3 Typical appearance of C. dactylon. (A) Wintergreen cultivar, (B) Wintergreen Spikes

Its heat and drought hardiness are excellent, but its low temperature tolerance is poor.

Discoloration usually occurs at soil temperatures below 16ºC and persists until the soil temperature rises in the spring. It generally has a poor shade tolerance (Beard, 1973).

Studies on clones of C. dactylon have revealed the existence of four biotypes,

(Beauchamp, Belambre, Constance and Reduit), that differ in their chromosome number, and their morphological and physiological characteristics (Rochecouste, 1962). Somatic chromosome numbers of 18, 27, 30, 36 and 40 have been reported (Rochecouste, 1962;

Fedorov, 1974). C. dactylon has both diploids and tetraploids with broad genetic variability (Juska and Hanson, 1964). Hexaploid, Tifton 10, with 54 chromosomes has been also reported and F1 hybrid (Patriot, tetraploid) has been produced by interspecific cross between Tifton and C. transvaalensis (Taliaferro et al., 2004).

CHAPTER ONE: INTRODUCTION

1.1.1.2.2 Cynodon dactylon var. dactylon

C. dactylon var. dactylon (2n = 4x = 36) is a tetraploid and one of the most widely distributed plants in the world, occurring almost continuously across all continents and islands between 45°N and 45°S latitudes (Harlan and de Wet, 1969). It can be subdivided into three races (Table 1.4) based on their appearance, adoption and geographical distribution (Harlan and de Wet, 1969).

Table 1.4 Races of C. dactylon var. dactylon (Harlan and de Wet, 1969)

Race Appearance/Characteristic Adaptation/Distribution

Tropical Short in stature Wet, infertile, acid soil of the tropics

Cold hardy (−12°C ± 3°C), short in stature and Soil higher in pH and fertility than Temperate forms denser turf than tropical types. tropical types

Tall, very coarse, robust plants bearing stout Seleucid Empire Seleucidus stolons and rhizomes with short internodes, (Turkey to Pakistan)

1.1.1.2.3 Cynodon transvaalensis (Burtt-Davy)

C. transvaalensis, a diploid (2n = 2x = 18), is morphologically distinct from other

Cynodon spp. with narrow, fine, soft and hairy leaves, a dense and fine texture, and having a yellowish-green colour (Taliaferro, 1995) (Fig. 1.4). It rarely produces viable seed (Duble, 1996), and has a low-growing and non-aggressive growth habit (Hanson et al. 1969). While it is used extensively for lawns, putting and bowling greens, its role in the breeding of improved cultivars is of greater value.

CHAPTER ONE: INTRODUCTION

Fig. 1.4 Appearance of C. transvaalensis.

1.1.1.2.4 Cynodon variants and cultivars

Before 1956, common Bermuda grass predominated on putting greens in warm, humid regions (Beard and Sifers, 1997). However, it did not make good turf. Since then various hybrids and cultivars have been made by introducing and recombining valuable characteristics. Now there are many cultivars of C. dactylon var. dactylon, although many are sterile hybrids.

In C. dactylon cultivars, many varieties have been widely adopted for golf putting greens and lawn bowls greens. Spontaneous and induced genetic variation has generated improved selections. For example, FLoraTexTM is thought to have been introduced into the USA under the name ‘Franklin’ in 1954 by African Explosives and Chemical

Industries, Ltd., Johannesburg, South Africa (Juska and Hanson, 1964). Hatfield was selected from a population growing in soil excavated from a building footing in 1983 at

Gympie, QLD and is a creeping type, spreading laterally by stolons and rhizomes (Loch and Roche, 2003a). JT1, a spontaneous mutation was discovered in the mid-1990s as a superior plant growing in a commercial field of common C. dactylon on Jimboomba

Turf Company’s farm at Jimboomba in south-east Queensland. The cultivar has

CHAPTER ONE: INTRODUCTION vigorous lateral spread, high shoot density and turf quality, low inflorescence numbers, and darker green colour (Loch and Roche, 2003b). Riley’s Evergreen is a spontaneous mutant of common Couch grass (C. dactylon) found growing in a bowling green at

Homebush Bowling Club, Homebush, NSW in 1991. The parent plant was characterized by poor low temperature tolerance. The mutant variety differs by showing good low temperature leaf colour retention and a broad leaf width. Vegetative propagation of the mutant stolons was commenced in 1993 (Kaapro, 1999c). Plateau is also a spontaneous mutant of common Couch grass found growing on the property of a breeder at Collaroy Plateau, NSW in 1975. The cultivar was charactrised by low growing height, prostrate shoot growth, short internode length and medium seed head frequency (Kaapro, 1999b). Other new useful variants and cultivars selected naturally or artificially include Legend Couch, CT-2 and Windsor Green.

In hybrid cultivars, intraspecific hybridization of C. dactylon parental plants and interspecific hybridization of C. dactylon var. dactylon (2n=4x=36) and C. transvaalensis (2n=2x=18) parental plants have been useful for breeding improvement.

For example, Tiflawn is an intraspecific hybrid of C. dactylon parental plants and the first of the turf cultivars from the breeding program of Burton (1991). Tiffine and

Tifgreen are interspecific hybrids developed by crossing tetraploid (C. dactylon var. dactylon) and diploid (C. transvaalensis) plants to produce sterile triploid (2n=3x=27) hybrids (Burton, 1991) (Fig. 1.5). During 1946, W.G. Thomas, Chairman of the Green

Committee, and Walter Harkey, Superintendent of the Charlotte Country Club, North

Carolina, USA observed a fine textured Bermuda grass growing in their 4 green. The

Bermuda was planted in the turf plots at the United States Department of Agriculture

Georgia Coastal Plains Experimental Station at Tifton, Georgia, USA for further

CHAPTER ONE: INTRODUCTION observation. Eight selections of common Bermuda grass (C. dactylon), including the

Charlotte Country Club strain, were hybridized with the South African Bermuda grass

(C. transvaalensis) in the spring of 1951 (Robinson et al., 1956). Furthermore, Tifgreen

(Tifton-328) released in 1956, is the hybrid of cross pollination between ‘Common

Couch’ on ‘South African Couch’ at Tifton Georgia USA. It was released for commercial use in America in April 1965 for use on golf club greens. It was brought to

Australia in 1996 by Grass Research in Sydney and trialed at Pennant Hills golf course

(Dalton, 2002). It is triploid (2n=27) and propagated vegetatively. Tifway (Tifton 419) which was officially released in 1960 is the foundation of the “Tif” series of Couch grass hybrids developed at Tifton and traces to a lot of C. transvaalensis seed sent to the

USA from South Africa in 1954 (Hanson, 1972) (Fig. 1.5).

(A) (B)

Fig. 1.5 Examples of hybrid Cynodon grass cultivars. (A) Tifgreen, (B) Tifway

Since 1977, natural and induced mutations from hybrid cultivars have also been a source of new variation and new cultivars. For example, Tifdwarf is a presumed natural mutation of Tifgreen (Burton, 1977). It has a darker green color than Tifgreen and requires less fertilizer to make a comparable degree of greenness (Burton and Elsner,

CHAPTER ONE: INTRODUCTION

1965). Tifway II and Tifgreen II are mutants induced with gamma irradiation (Burton,

1977). Champion Dwarf was selected from a spontaneous mutation of Tifdwarf from a golf green in Walker County, Texas, USA (Kaapro, 1999a). TifEagle was selected from dormant stolons of TifwayII treated with Cobalt 60 gamma radiation (Loch and Hanna,

2001). It was developed at Tifton exclusively for golf greens (Suszkiw, 1998).

FloraDwarf was released by the Florida Agricultural Experiment Station in 1995

(Dudeck and Murdoch, 1997). It is thought to be a mutant from Tifgreen hybrid Couch grass. It is sterile, inconspicuous flowering, triploid perennial having a chromosome complement of 2n = 3x = 27. MS-Supreme is a spontaneous cultivar discovered in a

Tifgreen hybrid putting green at the Gulf Shores Country Club, Gulf Shores, Alabama,

USA, where it maintained a darker green colour and higher shoot density than the surrounding Tifgreen during extended periods of wet, overcast weather (Loch and

Roche, 2003c). TL2 is spontaneous mutant and disease resistant mutant taken at

Novotel Palm Cove resort course in 1996 (Loch and Roche, 2003d). It is similar to

‘Tifdwarf’, ‘TifEagle’, ‘MS-Supreme’, ‘Champion Dwarf’ and FloraDwarfTM in common knowledge.

CHAPTER ONE: INTRODUCTION

1.2. Taxonomic analysis in plants

Taxonomy is concerned with grouping organisms with the same or very similar characteristics and is one of the most challenging fields of the biological sciences. (Weir,

1990). This ordering of organisms into groups or taxa based on similarities and differences was called classification. However the term classification has a dual meaning in taxonomy (Stuessy, 1994). It refers to both a process and a product. Process refers to the act of grouping and ranking organisms based on the criteria of the taxonomic relationships, and product refers to the resultant hierarchy of taxa. The latter sometimes includes the characteristics used to group the ranked units. Classification of plants in systematic botany is largely based on assumptions of phylogeny (Cronquist,

1981). Phylogenetic analysis also investigates the genetic relationships between plant- based taxonomic information (Henry, 1997). Knowledge of such information can provide clues to potential genetic resources for use in plant genetic improvement.

1.2.1 Plant identification and Plant Breeder Rights

Identification refers to an individual specimen that has been classified and named.

Identification of plant cultivars at the present time considers Plant Breeder’s Rights

(PBR) based on Distinctiveness, Uniformity, and Stability (DUS) for each new cultivar

(Mailer et al, 1994). PBR schemes and DUS testing are involved with registration and protection of intellectual property rights by the International Conventions of the Union for the Protection of New Varieties of Plant (UPOV) (Fowler and Kijas, 1994).

In addition, determination of sample identity that has been unknown is also significant in avoiding mislabeling of breeding lines and contamination from accidental mixing of commercial seed and seedling samples.

CHAPTER ONE: INTRODUCTION

1.2.1.1 DNA profiling and PBR in Australia

The Plant Breeder's Rights scheme in Australia is administered under the Plant

Breeder's Rights Act 1994. The Australian PBR system is unique compared to the PBR schemes of other participating countries in that the applicant provides information to support an application, using established techniques and that are supported by adequate documentation. Australia's PBR scheme uses breeder testing to establish the distinctness, uniformity and stability of new varieties. The breeder or their agent carries out comparative trials, using UPOV technical guidelines, to establish that each new variety satisfies DUS criteria. Especially The basis of Distinctness is an objective comparison of the variety with the most similar variety of common knowledge. Quantitative and qualitative differences between the new and existing varieties must be established and recorded. Morphological characteristics, especially those least affected by environmental factors are preferred. However, tests such as comparative DNA or protein profiles are acceptable as supporting evidence. Clear repeatable varietals differences must be demonstrated According to the IP Australia, Australian Government. However,

Morell et al., (1995) have suggested that genetic markers derived from DNA or Protein- based techniques also could be used to establish properties for either obtaining or protecting PBR. A phenetic trait is often difficult to measure because of continuous variation from environmental effects, whereas DNA profiling of new cultivars will not be affected by environmental factors. DNA profiling can be mainly used to identify varieties of a particular plant species and to estimate genetic distances between varieties.

CHAPTER ONE: INTRODUCTION

1.2.2 Methodologies for plant taxonomic analysis

Reliable methods for estimating genetic diversity within and between species are crucial for studying populations, classifying germplasm, or breeding. This means that accurate, fast, and cost-effective identification of plant populations and varieties is essential. Most modern methodologies of plant identification use either morphological, chemical or molecular characteristics or some combination of them.

1.2.2.1 Morphological characteristics

The identification and characterisation of genetic variation of plants using morphological traits has been used for a long time. One obvious reason for this is the ease of observing and recording external features. The study of small morphological features or micro-morphology has also become important in the past several decades with the development of techniques such as scanning electron microscopy (Claugher,

1990). However, morphological comparisons have limitations including subjectivity in the analysis of the characteristics, continuous variation of the characteristic or the limited diversity among cultivars with highly similar pedigrees. Therefore, it has been suggested that a more sensitive diagnostic test would benefit the identification of cultivars.

1.2.2.2 Biochemical characteristics

Biochemical traits, such as the presence of a metabolite, have been used for plant identification and chemotaxonomic studies. The usefulness of chemotaxonomy was suspected in the early part of the 20th century, but no sustained interest developed until the late 1950s. By then, technical advances had made it easier to extract, separate, and identify organic compounds. Many types of compounds from any part of the plant can

CHAPTER ONE: INTRODUCTION be used for taxonomic comparisons. Perhaps the most widely used are secondary metabolites. Some examples are nitro-toxins (Williams and Barneby, 1977), flavonoids

(Bhalla and Dakwale, 1978) and glucosinolates (Kliebenstein et al., 2001). Although some chemical components are relatively easy to handle and identify, many others require more sophisticated techniques (Stuessy, 1994). The resulting cost and complexity of analysis has limited routine adoption of these techniques.

1.2.2.3 Molecular characteristics

Compared with morphological and biochemical traits, molecular markers are discrete traits and are less subject to the influence of physiological and environmental factors.

Molecular techniques can also provide useful tools to study the effect of plant genetic diversity on the sustainability of ecosystems. There are two types of molecular markers

— protein-based markers and DNA-based markers.

1.2.2.3.1 Protein-based markers

Individual proteins can be useful molecular markers in plant taxonomic analysis. For example, the presence of the copper/zinc form of superoxide dismutase in green algae has strengthened the argument that this class of algae is phylogenetically closest to the progenitors of land plants (De Jesus et al., 1989). Isoenzymes have proven useful for identification of plants (Ashari et al., 1989; Zhabg et al., 1993). For example, the isoenzyme patterns of peroxidase and esterase have been used to distinguish some banana cultivars (Mandal et al., 2001). Isoenzyme markers provide a convenient and inexpensive tool. Nevertheless, the relative lack of polymorphisms makes isoenzyme markers unsuitable for resolving closely related cultivars or breeding lines. In addition isoenzymes are restricted in their utility by the number of enzyme systems that can be

CHAPTER ONE: INTRODUCTION visualized and by the possibility that isoenzyme expression can be influenced by environmental conditions or management practices (Fowler and Kijas, 1994).

1.2.2.3.2 DNA-based markers

DNA-based molecular markers have become important tools for studying phylogenetic relationships because genetic polymorphisms revealed by DNA analyses show variations in the genetic material, which is more informative than protein-based markers.

Some advantages of DNA-based markers are that the DNA sequence of an organism is independent of environmental conditions or management practices. Furthermore the presence of the same DNA in every living cell of the plant allows tests on any tissue at any stage of growth. The advent of the polymerase chain reaction (PCR) has enabled the development of new DNA profiling techniques that are simply and quickly performed

(Morell et al., 1995). DNA–based molecular marker techniques are based upon either nucleic acid hybridization, PCR or a combination of the two (Table 1.5).

Table 1.5 DNA-based molecular marker methods for plant identification (Henry, 1997)

Hybridisation-based RFLP Restriction fragment length polymorphism VNTR Variable number of tandem repeats PCR-based RAPD Random Amplified Polymorphic DNA AP-PCR Arbitrary Primed PCR DAF DNA Amplification Fingerprinting SSR Simple Sequence Repeat STR Simple Tandem Repeat micro satellites ISSR Inter Simple Sequence Repeat

Combination AFLP Amplified Fragment Length Polymorphism

CHAPTER ONE: INTRODUCTION

RFLP is one of the most common DNA techniques and is based upon hybridisation of a probe to fragments of genomic DNA following digestion with a restriction enzyme

(Gardner et al., 1991). That is, differences in the sequence at putative restriction sites may result in differences (polymorphisms) in the length of the fragments detected by the probe. Genomic DNA from the sample being tested is digested with a restriction endonuclease. These enzymes cleave DNA at specific sequences recognized by the enzyme. The resulting DNA fragments are separated by electrophoresis on an agarose gel and transferred by Southern blotting onto a nylon membrane to allow hybridization with a probe. Detection of hybridization can be achieved using a variety of methods, the most common being radioisotope-labelling (Henry, 1997).

Examples of RFLP analyses of DNA sequence diversity are sorghum (Chittenden et al.,

1994), photoperiodic genes in cotton (Creech, 1996), and maize populations (Dubreuil et al., 1999). However, RFLP has its limitations. It requires the availability of a suitable

DNA probe. Mutational events that result in novel phenotypic characteristics of the derived cultivar may affect a very small proportion of the genome, perhaps only a single nucleotide in some cases. It is unlikely that such events can be detected efficiently by

RFLP analysis using DNA probes randomly selected from the genome (Fang and Roose,

1997). In addition, RFLP requires complex steps and a large amount of DNA compared to PCR-based markers.

1.2.2.3.3 Polymerase Chain Reaction (PCR)

The invention of PCR by Kary Mullis in 1985 has revolutionized molecular biology.

PCR copies DNA using the basic elements of the natural DNA replication process. The principle is shown in Figure 1.6.

CHAPTER ONE: INTRODUCTION

1 minute 94ºC Double stranded DNA unfolds and separates

45 seconds 54ºC forward and reverse primers anneal to their respective DNA strands

2 minutes 72 ºC Taq polymerase forms Double stranded DNA

Fig. 1.6 The different steps in PCR. (Vierstracte, 1999)

PCR is based on three simple steps. Firstly, the template DNA is denatured to separate the complementary strands. Secondly, the reaction is cooled to an annealing temperature compatible with the primers. The oligonucleotide primers hybridize to the single strand templates. During this step, the thermostable DNA polymerase is active and begins to extend the primers as soon as they anneal. Thirdly, the temperature is raised to 72ºC, the optimum temperature of Taq polymerase. Daughter DNA strands are produced by extension of the oligonucleotide primers by reaction of the appropriate deoxynucleoside triphosphates.

CHAPTER ONE: INTRODUCTION

These steps are repeated by the PCR machine giving rise to greater than a billion fold increase in the target DNA (Fig. 1.7). The PCR products can be separated and visualized using an electrophoresis system.

Fig. 1.7 The exponential amplification of DNA in PCR. (Vierstracte, 2001)

PCR technology generally has the advantage of speed and sensitivity. Amplification can be achieved in a few hours and can be adjusted to produce results indicating family, genus, species, or individual genotype by the choice of primer. Another advantage of

PCR compared to RFLP is that it does not require radioactivity to visualize polymorphisms.

1.2.2.3.4 PCR-based genetic markers

To-day more sensitive and better characterized PCR-based markers have been created.

These markers are generally used for genome linkage mapping, identity testing, determination of genetic relationships and population and pedigree analysis (Caetano-

CHAPTER ONE: INTRODUCTION

Anollés et al., 1991a). At present, Arbitrary Primed PCR (AP-PCR) (Welsh and

McClelland, 1990), Random Amplification of Polymorphic DNA (RAPD) (Williams et al., 1990), DNA Amplification Fingerprinting (DAF) (Caetano-Anollés et al., 1991 b) and microsatellite repeats are some of the new techniques available (Cregan and

Quigley, 1997). AP-PCR, RAPD and DAF refer to the use of arbitrary primers as a convenient and simple process for detecting polymorphisms in the absence of specific nucleotide sequence information. The primers are generally about 10bp long, but because of this short length, the annealing temperature must be low (35ºC-40ºC). The methods make use of agarose gel electrophoresis or PAGE to separate the PCR products.

Differences between AP-PCR, RAPD and DAF are based on primer length, electrophorestic separation and visualisation of products. For example, DAF uses short random primers of 5-8 bp, PAGE for separation and silver staining for visualisation. AP-

PCR uses slightly longer primers and amplification products are radiolabeled and resolved by PAGE (Hadry et al., 1992).

The analyses are able to distinguish among closely related varieties. For example,

Hypericum perforatum L. progenies were characterised by RAPD analyses using six primers (Arnholdt-Schmitt, 2000) and a patented strawberry variety also was characterised by RAPD analysis (Graham et al., 1996). Moreover, the RAPD technique is suitable for identification of asexually reproduced plant varieties for forensic or agricultural purposes (Congiu et al., 2000). The relationships revealed by this type of analysis were generally consistent with other types of evidence such as alloenzyme or protein markers, affirming the value of the RAPD technique (Williams et al., 1990).

However, these techniques have their limitations. A larger number of primers need to be screened to find differences among very closely related varieties (Morell et al., 1995).

CHAPTER ONE: INTRODUCTION

Another disadvantage is that products that arise from weak interaction between the primer and template often result in poor reproducibility. The low annealing temperature can cause primer binding to sequences that are not fully complementary (Anderson,

2000). Therefore, more sensitive DNA-based markers which can overcome these disadvantages should be considered.

1.2.2.3.5 Simple Sequence Repeat (SSR) and Inter Simple Sequence

Repeat (ISSR) molecular markers

There is another application of PCR-based markers that is associated with simple sequence repeats. Simple sequence repeats, also known as microsatellites or simple tandem repeats (STRs), are DNA sequences that consist of two to five nucleotides that are tandemly repeated (Cregan and Quigley, 1997). SSRs are ubiquitous in eukaryotic genomes and the regions flanking the microsatellite are generally conserved within the same species (Cregan and Quigley, 1997). In plant genes, SSR sequences are found mostly in introns and the 5’ flanking region (Henry, 1997).

The microsatellite protocol is simple, once primers have been designed. The first stage is PCR followed by separation on a high resolution polyacrylamide gel. Bands are detected with a variety of techniques including fluorescence or radiolabelling (Robinson and Harris, 1999). Microsatellite markers have been used for the construction of linkage maps in Arabidopsis thaliana (Bell and Ecker, 1994), soybean (Akkaya et al., 1992), barley (Gu et al., 1996) and maize (Senior et al., 1996). Unlike RAPD, AP-PCR or DAF, the method can detect co-dominant polymorphisms, and therefore distinguish between heterozygotes and homozygotes. Simple sequence repeats offer good reproducibility

CHAPTER ONE: INTRODUCTION and generate large numbers of detectable alleles. Moreover, the level of polymorphism is considerably higher than that found with RFLP markers in most plant species (Diwan and Cregan, 1997). However, a major bottleneck in developing SSR markers requires prior knowledge of sequence. Moreover, microsatellites from plants are less abundant in databases than those from mammals. On average they are found once in every 50 kb throughout the genome (Lagercrantz et al., 1993). This technique is more useful in mammals than in plants.

Unlike SSR, Inter-simple sequence repeat analysis (ISSR) (Zietkiewicz et al., 1994) is a

PCR-based detection of DNA sequence between microsatellites without prior knowledge of the actual sequences flanking each repeat. That is, ISSRs are semi- arbitrary markers amplified by PCR in the presence of a primer complementary to a target microsatellite. The technique is considered more specific than RAPD reactions since the longer SSR-based primer (usually 15-20 mers) enables higher stringency amplification (Gupta et al., 1994). The technique is based on three assumptions (Julie and Hanson, 1998). Firstly, that any particular repeat is widely represented and is interspersed in a genome. Secondly, that a detectable polymorphism will result from insertions or deletions between conserved repeats or sequence variation at a priming site.

Thirdly, that at some measurable frequency copies of a particular repeat will be in an inverse orientation within a PCR-amplifiable distance from one another in the genome.

There are two types of microsatellite-primed PCR using ISSR. The first uses non- anchored primers in which arbitrary multiloci markers are produced by PCR amplification (Fig. 1.8).

CHAPTER ONE: INTRODUCTION

(CCA)n Primer

T emplate ……NNNGGTGGTGGTGGTNNNNNACCACCACCACCNNNN…… DNA ……NNNCCACCACCACCANNNNNTGGTGGTGGTGGNNNN……

(CCA)n

Daughter DNA

Fig. 1.8 The use of non-anchored primers in ISSR-PCR.

Amplificaton in the presence of non-anchored primers has been called microsatellite- primed PCR, or MP-PCR, (Meyer et al., 1993). It is similar to RAPDs, but the non- anchored primed PCR reaction is presumed to be more specific since the longer SSR- based primers enable higher stringency amplification (Gupta et al., 1994). The level of polymorphism observed in the amplified products relates to the genomic diversity within a species, and also reflects both dominant and co-dominant polymorphisms.

Non-anchored SSR primers have been used successfully for a variety of applications, including species identification in whitefly (Perring et al., 1993), chickpea and tomato germplasm analysis (Sharma et al., 1995), and a polymorphism survey of diverse plant and animal genomes (Gupta et al., 1994). However, non-anchored primed PCR also has disadvantages. A general problem of the technique is that it requires optimal PCR condition to give reproducibility and minimize artifacts. Furthermore, non-anchored di- nucleotides and AT-rich tri-nucleotide primers generally do not produce distinct, resolvable products (Sharma et al., 1995; Weising et al., 1995).

CHAPTER ONE: INTRODUCTION

The second type of ISSR uses primers modified by the addition of either a 3’- or 5’- anchored sequence composed of one or more non repeating bases (Fig. 1.9).

Primer NNN(CA)n (CA)nNN Template …NNNNCACACACACACANNNNNNNTGTGTGTGTGTG NNNN… DNA …NNNNGTGTGTGTGTGTNNNNNNNACACACACACACNNNN…

(CA)nNN

NNN(CA)n

3’ anchored Daughter DNA 5’anchored

Fig. 1.9 The use of anchored primers in ISSR-PCR.

This method, known as either anchored MP-PCR, inter-microsatellite PCR or inter-SSR amplification (ISA), was first reported by Zietkiewicz et al. (1994). Unlike non- anchored primers, the anchor serves to fix the annealing of the primer to a single position at each target site on the template, so that every new polymerization event starts at the same target site. As a result it stops primer slippage on the template, and problems with priming out of register are minimized. In addition, 3’-anchored primers usually begin priming from the downstream flank of the SSR, while 5’-anchored primers begin priming at the upstream boundary of the target SSR (Fig. 1.9). Therefore, the products generated from 5’-anchored primers should exhibit more co-dominant polymorphisms. Although the method still has limitations such as nonspecific annealing of the primer, this approach has been shown to be useful for both inter- and intraspecific germplasm discrimination in a variety of applications.

CHAPTER ONE: INTRODUCTION

Recently a new technique, Fluorescent Inter Simple Sequence Repeats (FISSR-PCR) has been developed. This uses a fluorescent dye labeled primer combined with separation and visualisation using a DNA sequencer with laser scanning to detect fluorescent amplicons (Morell et al., 1995). FISSR-PCR is simple and sensitive with superior resolution (Nagarju et al., 2002), although it requires access to sequencer equipment. The technique is more useful for detecting polymorphism markers in closely related varieties or populations, which can difficult to discriminate using other marker systems. The technique has been used in Chilli (Capsicum annum) (Kumar et al., 2001).

1.2.3 Molecular phylogenic study of turf grass

Morphological assessment has been traditionally used for phylogenic study and identification of plants. Molecular techniques have now shown that the genetic variation in plants and plant populations are of considerable practical interest. Turf grass research is now focused on molecular analysis for demonstrating diversity.

Eleven of 15 Kentucky bluegrass (Poa pratensis L.) cultivars have been identified by peroxidase isoenzymes (Wehner et al., 1976). Wilkinson and Beard (1972) distinguished all six cultivars of creeping Bent grass (Agrostis palustris Huds.) used in their study by a total protein stain. Six cultivars of annual ryegrass (Lolium multiflorum

Lam.) have been distinguished by glutamate oxaloacetate-transminase isoenzymes

(Hayward and McAdam, 1977). Electrophoretic analysis of peroxidase isoenzymes from leaf extracts has been employed for distinguishing turf grass cultivars (McMaugh,

1993). North American Buffalo grass (Stenotaphrum secundatum) cultivars were investigated using isoenzyme variability. ADP glucose pyrophosphorylase, UDP glucose pyrophosporylase, alchol dehydrogenase (ADH) and acid phosphatase isoenzymes

CHAPTER ONE: INTRODUCTION extracted from leaf tissue of 28 clones and separated by polyacrylamide disc electrophoresis (Green et al., 1981). However, Buffalo grass cultivars that are popular in

Australia, such as Palmetto and Sir Walter, have not been subject to isoenzyme analysis.

DNA-based techniques also have been applied to grass species. CpDNAs of five species of cool season turf grasses and six species of warm season turf grasses were characterised using RFLP analysis with digestion by PstI, XhoI and BamHI (Yaneshita et al., 1993). Genetic relationships in Bent grass and Ryegrass have been studied by

RAPD analysis (Golembiewski et al., 1997; Sweeney et al., 1997). The technique also has been used to study relationships in Buffalo grass (Buchloe dactyloides (Nutt.)

Engelm) cultivars (Huff et al., 1993). DAF was used to study inter- genetic relationships in Centipede grass (Eremochloa ophiuroides (Munro) Hack.) (Weaver et al., 1995).

Genetic relationships of Couch grass cultivars have been studied using various DNA- based markers. Using DAF, a high level of polymorphism was detected in Couch grass species by digesting the DNA template with restriction enzymes prior to amplification.

Thirteen American Cynodon cultivars, including a few hybrids, were characterised using

11 arbitrary octamer primers. Tifgreen and its natural somatic mutant Tifdwarf were differentiated by five polymorphisms generated with three primers (Caetano-Anollés et al., 1995). RAPD analysis also was applied to seven commercial cultivars, including

Bayview and Royal Cape, and ten potential new cultivars. The cultivars Silverton Blue and Bayview exhibited the greatest genetic variation (Roodt et al., 2002).

CHAPTER ONE: INTRODUCTION

Eighteen Australian Couch grass cultivars were characterised by AP-PCR (Ho et al.,

1997). Thirteen from 20 arbitrary primers screened gave reproducible and different banding profiles for the Cynodon cultivars. What was well marked was the separation between the C. dactylon cultivars and the hybrids in the phylogenetic tree. The results showed that AP-PCR can be a useful tool in identifying genetic relationships within the

Couch grass group. Ho (1999) also found that Internal Transcribed Spacer (ITS) sequences of rDNA genes also differentiated the same Cynodon cultivars. The sequences of the amplified DNA, which encompassed the ITS 1 and ITS 2 spacers and the 5.8S ribosomal gene, matched published ITS sequences of C. dactylon and other grasses in the GenBank databases. A number of unique restriction sites were found in the ITS sequences (Ho, 1999). Interestingly the ITS sequences showed excellent variability at the interspecific and intraspecific level within Cynodon. The phylogenetic tree from ITS sequences gave three distributed groups, ie. C. transvaalensis, the common Bermuda grasses (C. dactylon) and the interspecific hybrids. However, relationships within the major groups were not strongly supported by bootstrap cultivars.

Most of the cultivars tested were very closely related and hence only low variability was detected in the ITS sequence of the cultivars.

At the beginning of this project, the identification of Buffalo grasses (Stenotaphrum secundatum) had not been investigated using DNA-based marker, although these markers have been useful in other turf grasses.

CHAPTER ONE: INTRODUCTION

1.3. Genetic data analysis

Genetic data resulting from visualisation of polymorphic bands can be analysed using statistical methods. A suitable statistical analysis is therefore, a major consideration in taxonomic studies or the construction of phylogenies. It will require consideration of the type of data to score the profile and the steps to calculating genetic distance and summarizing the genetic relationships as a dendogram.

There are two major ways to examine phylogenetic relationships (Weir, 1990). One is a phenetic relationship composed of similarities of a set of phenotypic characters without regard to evolutionary history (Sneath and Sokal, 1973). The other is a clasdistic relationship containing information about ancestry that can be used to study evolutionary pathways. The taxonomic distance between two taxa is calculated by comparing the presence or absence of each of several characteristics (Funk and Brooks,

1981). Both relationships are represented as phylogenetic trees or dendograms – the terms phenogram and cladogram are based on phenetic and cladistic relationships, respectively (Weir, 1990).

1.3.1 Types of data

There are two types of data that need to be stored to calculate genetic distance – discrete data that describes an individual sample or sequence, and distance or similarity data that are a quantitative comparison of two samples or sequences. Discrete character data can be divided into quantitative data and qualitative data. Quantitative data can involve two states (binary), or more than two states, namely multistate. An example of the binary state is the presence or absence of a character, while nucleotide sequence data would be an example of multistate data. Similarity and distance data is an estimation of the

CHAPTER ONE: INTRODUCTION distance between two individual taxa. Similarity can be calculated using appropriate formulas (Henry, 1997). An example for two samples A and B using RAPD data and the formula of Nei and Li (1979) is shown below.

Similarity (F) = 2(nxy) / nx + ny where

nxy is the number of bands in common between two individual samples (A and B)

nx is the number of bands unique to sample A and

ny is the number of bands unique to sample B.

Dissimilarity (F′) is calculated using the relationship, F′=1-similarity.

1.3.2 Data Analysis

As has been mentioned in the previous section, the analysis is based on two types of measurement – phenetic measure or caldistic (phylogenetic) measure. The principal methods used to construct a phylogenetic tree are Distance Matrix, Maximum

Parsimony and Maximum Likelihood.

1.3.2.1 Distance matrix method

The archetypical phenetic approach uses distance methods. These methods take the input data and derive from them some measure of similarity/difference between species and from this construct a tree that tries to match this data.

It is based on the calculated set of distances between each pair of taxonomic unit, operational taxonomic units (OTUs) that are connected by the same parental node in the

CHAPTER ONE: INTRODUCTION phylogenetic tree (Saitou and Nei, 1987). OTUs can be cultivars, species, groups of species, sequences or anything that can be represented by a node in a tree. Distances are generally based on genetic models, and usually refer to the number of changes between the units. The quality of the resulting phylogenetic tree depends on the quality of the distance estimate.

Two kinds of clustering analysis with the distance matrix are widely used. One is

UPGMA (Unweighted Pair-Group Method using an Arithmetic Average) (Sneath and

Sokal, 1973). It defines the intercluster distance as the average of all the pairwise distances for members of two clusters. The other is the Neighbour-joining method also described by Saitou and Nei (1987). This method identifies closest pairs or neighbors by minimising the total length of a tree. A pair of neighbours is defined as two units connected through a single node in an unrooted, bifurcating tree (two branches joining at each interior node). In general, it is possible to define the topology of a tree by successively joining pairs of neighbours to form new neighbour pairs. Distance matrix methods offer simplicity and time effectiveness in taxonomic analysis. The analyses are performed and the trees constructed using computer software such as PAUP

(Phylogenetic Analysis Using Parsimony) or PHYLIP (the PHYLogeny Inference

Package).

1.3.2.2 Maximum parsimony and Maximum likelihood methods

Maximum parsimony methods take explicit notice of the character values observed for each species, rather than working with the distances between sequences that summarize differences between character values. The method was introduced by Edwards and

Cavalli-Sforza (1963) and attempts to derive the phylogenetic tree which requires the

CHAPTER ONE: INTRODUCTION fewest number of changes to account for the observed data. The method originally developed for morphological characters and was later adapted for sequence data (Eck and Dayhoff, 1966). The principle of the maximum parsimony method is to infer the number of evolutionary events implied by a particular topology and to choose a tree that requires the minimum number of these evolutionary events.

The maximum likelihood method of constructing a tree attempts to avoid the limitations of other methods, although it may require a prohibitive amount of computing. A maximum likelihood method for inferring trees from DNA or RNA sequences was developed by Felsenstein (1981). It differs from parsimony methods by employing standard statistical methods for a probabilistic model of evolution. Like maximum parsimony, maximum likelihood reconstructs ancestors at all nodes of each tree considered, but it also assigns branch lengths based on the probabilities of mutations

(Felsenstein, 1981).

1.3.2.3 Steps in data analysis based on Distance matrix

Firstly the banding pattern from electrophoresis of the PCR products needs to be scored to create a data matrix from the input data. If there are a small number of samples this is often done manually from gel photographs with the aid of a measuring device. However, for larger data sets, it is better to use appropriate computer software in conjunction with digital images. Generally scoring transforms the profile for a sample into a series of present (1) and absent (0) bands.

After producing a data matrix, it is necessary to calculate distance from the data matrix, again using appropriate computer software. It is worth remembering that PBR is

CHAPTER ONE: INTRODUCTION primarily interested in distinctness and genetic distance rather than genetic similarity.

Finally the collected and evaluated data can be visualized by a dendogram. The dendogram illustrates the relationship of each sample such as cultivar or species. The dendogram is produced using an appropriate clustering algorithm.

1.3.2.4 Evaluation of the test

The tree created by a given data set may not always be the best representaton. Some useful tests are now available for evaluation of the results. For example, Bootstrap resampling, suggested by Felsentein (1985), involves random resampling from the original data set. The data are usually re-analysed from 100 to 1000 times to establish the robustness of the resulting tree. Another evaluation method, called Jacknifing, tests the tree by dropping out different samples and reanalyzing.

CHAPTER ONE: INTRODUCTION

1.4. Project objectives

Many new turf grass cultivars have been generated in the last few decades to meet market needs. It now seems reasonable to develop new methods that can accurately and reliably distinguish from one another cultivars that have similar morphological characters for commercial and legal purposes.

The aim of this project was to investigate the usefulness of ISSR-PCR fingerprinting in the identification and classification of Buffalo and Couch grass cultivars available in

Australia. In Buffalo grass, DNA-based methods have not been tested for either identification or taxonomic classification of the available cultivars. This was first DNA- based marker system to classify the Buffalo grass cultivars, and should be especially useful in comparing imported and Australian cultivars. In Couch grass, the variation detected by the ISSR-PCR technique can be compared with that reported by other workers using AP-PACR or DAF.

Apart from the phylogenetic relationships of the two genera, some appropriate visualisation techniques were compared to select the best method for ISSR-PCR analysis. Agarose gel electrophoresis with ethidium bromide staining and non- denaturing PAGE with silver staining will be used and the results compared. In addition, a limited trial using fluorescently labeled ISSR primers will be used with the Buffalo grass cultivars. This has the potential for speed, sensitivity and accuracy particularly with a robotic system for electrophoresis, visualisation and recording of results.

In this study, bootstrapping was used for evaluation of the phylogenetic trees produced from the two turf grass genera.

CHAPTER TWO: MATERIALS AND METHODS

2.1. Materials 2.1.1 Plant materials

Ten Buffalo grass samples (Stenotaphrum secundatum) and fifty Couch grass samples

(Cynodon spp.) were analysed. Samples and their abbreviations are shown in

Appendices A and B.

The Couch grass samples included C. dactylon, C. transvaalensis and various hybrids and were supplied by Dr. Don Loch from the Redlands Research Station, Department of

Primary Industries and Fisheries, Cleveland, QLD. The cultivars Windsor Green and

Riley’s Super Sport were donated also by Windsor Turf Suppliers, Richmond, NSW.

The Buffalo grass samples were kindly donated by Richmond Turf Suppliers, Richmond,

NSW and Dr. Don Loch. All grasses were grown on in large pots in a glasshouse with a temperature range of 20 to 25ºC and about 80 % relative humidity.

2.1.2 Primers

An ISSR primer set (#9) containing 21 non-anchored, 60 3’-anchored, 10 5’-anchored and 9 random sequence primers was purchased from the University of British Columbia,

Vancouver, Canada. Two fluorescent ISSR primers (based on UBC#9 (811) and UBC #9

(826)) containing the dye 6-FAM, were synthesised by Proligo Primers, Lismore, NSW.

λ primer1 and 2 were synthesized by GIBCO BRL, Life Technologies Inc., Australia.

The sequences of all primers are shown in Appendix C.

CHAPTER TWO: MATERIALS AND METHODS

2.1.3 PCR kit

Hotstar Taq Master Mix from QIAGEN, Clifton hill, VIC., Australia was used for PCR amplification of Buffalo and Couch grass genomic DNA. The Hotstar Taq Master Mix

(x 2 concentrated) contains PCR buffer, MgCl2 (3 mM), Hotstar Taq DNA polymerase

(2.5 units) and 400 µM of each dNTP.

2.1.4 Enzyme and markers

DNAase free Pancreatic ribonuclease (RNase A) was purchased from Boehringer

Mannheim, NSW. Lambda DNA for a mass marker and PCR controls was purchased from MBS Fermentas, Australia and the 1 kb plus DNA ladder for a size marker was purchased from Invitrogen, Life Technologies, VIC, Australia.

2.1.5 General reagents

Molecular biology grade agarose powder was purchased from PROGEN Industries

Limited, QLD and Ameresco 40% Acrylamide/bis solution (37.5:1, Acrylamide:N,N'- methylene-bis-acrylamide) was purchased from Astral Scientific, NSW. Ammonium persulfate was purchased from KODAK, NSW. N,N,N’,N’- tetramethylethylenediamine

(TEMED) was purchased from Bio-Rad, NSW. Hexadecyltrimethylammonuim bromide

(CTAB), 2-mercaptoethanol, silver nitrate, calf thymus DNA, iso-amyl alcohol, bromphenol blue and xylene cyanol FF were purchased from Sigma Chemical Co.,

NSW. Formaldehyde, chloroform, urea and isopropanol were purchased from APS Ajax

Finechem, NSW.

Milli-Q water was used throughout. All other chemicals were AR grade or the purest commercially available.

CHAPTER TWO: MATERIALS AND METHODS

2.2. Methods 2.2.1 Extraction of plant genomic DNA

DNA was isolated from freshly harvested young grass leaves using a modification of the

CTAB method of Doyle and Doyle (1991). Approximately 0.2 g of leaf tissue was powdered in a chilled mortar in the presence of liquid nitrogen. The sample was dispersed in 3 ml preheated (60ºC) extraction buffer containing 2 % (w/v) CTAB, 1.4 M

NaCl, 0.2 % (v/v) 2-mercaptoethanol (freshly added), 20mM Na2-EDTA and 100mM

Tris-HCl, pH 8.0. After incubation at 60ºC for 2-3 hours, the sample was extracted with an equal volume of chloroform:isoamyl alcohol (24:1, v/v) and the phases separated by centrifugation (8000 xg, 5 min). The upper aqueous phase was re-extracted with a half volume of chloroform:isoamyl alcohol and after centrifugation the aqueous phase transferred to a fresh tube. Cold isopropanol (2/3 volume) was added and the solution kept at 4ºC overnight. Any precipitate was sedimented by centrifugation (3000 xg, 1 min) and the bulk solution decanted. The pellet in 1ml residual solution was transferred to an Eppendorf tube and the pellet recovered by centrifugation (15,000 xg, 30 s). It was washed with 1ml 76 % aqueous ethanol/10 mM ammonium acetate for 20 min by gentle mixing. After centrifugation (10,000 xg, 1 min) and removal of the wash buffer, the pellet was dissolved in 200 µl of Tris-EDTA (TE) buffer (10 mM Tris-HCl, 1 mM Na2-

EDTA, pH 8.0) and incubated with 2 µl RNase (10 mg/ml) at 37°C for 30 minutes. The

DNA was precipitated by adding 1/10 volume of 3M Na-acetate, pH 5.2 and 2.5 volumes of aqueous 95% (v/v) ethanol and cooling for approximately 20-30 minutes at

-20°C. After centrifugation (10,000 xg, 10 min) and removal of the supernatant, the pellet was washed with 250 µl aqueous 75 % (v/v) ethanol. After centrifugation (10,000 xg, 10 min), the supernatant was removed and the pellet air-dried and dissolved in 100

µl TE buffer.

CHAPTER TWO: MATERIALS AND METHODS

2.2.2 Quantitation of genomic DNA

Three methods were used for quantitation of genomic DNA: Dye Binding Fluorescence,

UV absorption, and agarose gel electrophoresis.

2.2.2.1 Dye Binding Fluorescence

Genomic DNA was quantified by dye binding fluorescence using a Hoefer DyNA

Quant™ 200 fluoremeter (Amersham Pharmacia Biotech, USA) and following the manufacturer’s protocol. Calf thymus DNA was used as a standard.

2.2.2.2 UV absorption

Genomic DNA was quantified from the absorbance at 260 nm and the relationship that an absorbance of 1.00 is equal to 50 µg/ml of DNA. The purity of genomic DNA samples was assessed using the A260/A280 ratio. A value greater than 1.8 was deemed satisfactory.

2.2.2.3 Electrophoresis for quantitation of genomic DNA

Genomic DNA was electrophoresed on a 1 % (w/v) agarose submarine gel (8 cm x 15 cm) containing 0.5 µg/ml ethidium bromide with 50 ng, 100 ng and 200 ng of lambda

DNA mass marker standards and a 1 kb plus DNA ladder as a size marker. The gel electrophoresed in TAE buffer [40 mM Tris-acetate, pH 8.0, 1 mM EDTA] at 5-6 v/cm for 30 minutes. The gels were visualized by UV transillumination, digitally photographed and the DNA quantified using Quantity one 1-D analysis software (Bio-

Rad, USA) using a Windows TM PC.

CHAPTER TWO: MATERIALS AND METHODS

2.2.3 Polymerase Chain Reaction (PCR)

2.2.3.1 Optimisation of PCR conditions

Selected components of the PCR were tested at a number of different concentrations to optimize the reaction. These included MgCl2 (2.0, 2.5, 3.0 and 3.5 mM), primer (0.1,

0.2 and 0.3 µM), amount of template (5, 25, 50 and 75 ng), Taq polymerase (0.5, 1.0,

1.25 and 2 unit) and the number of cycles (25, 35 and 45 cycles).

In addition each primer was tested over a range of annealing temperatures. This was normally 6ºC either side of the Tm calculated from the relationship Tm = 2x (A+T content) + 4x (G+C content) ºC.

2.2.3.2 ISSR PCR amplification

After determining the optimal PCR conditions, a typical PCR contained 1×Hotstar Taq

Master mix [PCR buffer, 1.25 units Taq polymerase, 200 µM of each dNTP and MgCl2 to 3.0 mM], 0.3 µM ISSR primer and 25 ng genomic DNA in a total volume of 25 µl.

Amplification was as follows: an initial enzyme activation at 95ºC for 15 minutes followed by 35 cycles consisting of 94ºC for 60 sec, the optimal annealing temperature for each ISSR primer for 60 sec, and 72ºC for 90 sec, followed by a single cycle at 72ºC for 10 min. The PCR products were stored at 4ºC before electrophoresis.

CHAPTER TWO: MATERIALS AND METHODS

2.2.4 Electrophoresis and visualisation of gels

2.2.4.1 Agarose gel electrophoresis and ethidium bromide staining

After PCR amplification, the products were separated on a 1.8 % (w/v) agarose submarine gel (8 cm x 15 cm or 12 cm x 17 cm) in 1×TAE buffer [40 mM Tris-acetate, pH 8.0, 1 mM EDTA] containing 0.5 µg/ml ethidium bromide. Typically 8 µl of the

PCR solution was loaded with 2 µl of 6x gel loading buffer [0.25 % (w/v) bromophenol blue and 40 % (w/v) sucrose in water] and the gel electrophoresed at 4-5 v/cm for

60min. A 1 kb plus DNA ladder marker was used as size markers. Gels were visualized under UV transillumination, digitally photographed and analysed using Quantity one 1-

D analysis software (Bio-Rad, USA) using a Windows TM PC.

2.2.4.2 Non-denaturing PAGE and silver staining

A vertical electrophoresis system (EI9001-XCell II™ Mini Cell, NOVEX, USA) was employed to separate PCR products on 6 % (w/v) non-denaturing polyacrylamide gels

(PAGE) (10 cm x 10 cm) based on the protocol of Bassam et al. (1991). The gels contained acrylamide:N,N′-methylen-bis-acrylamide (37.5: 1) solution and Tris-borate-

EDTA (1xTBE) buffer [89 mM Tris, 89 mM boric acid and 2 mM Na2-EDTA, pH 8.0].

Polymerisation was achieved by adding ammonium persulphate (0.175 % (w/v)) and

TEMED (0.05 % (v/v) final concentration). Gels were kept at 4ºC before electrophoresis. Typically 5 µl of PCR sample and 1µl of loading buffer [0.25 % (w/v) xylene cyanol FF, 0.25 % (w/v) bromophenol blue and 40 % (w/v) sucrose in water] were loaded in each well. Electrophoresis was carried out in 1×TBE buffer at 7-8 v/cm for 80 min.

CHAPTER TWO: MATERIALS AND METHODS

After PAGE, PCR products were visualised by silver staining as described by Bassam et al. (1991) and Ho et al. (1997). Gels were fixed in 10 % (v/v) acetic acid for 45 minutes with gentle agitation. Following washing with aqueous 10 % (v/v) ethanol for 5 min, the gels were pretreated with 1 % (v/v) nitric acid for 3 min and washed three times with

Milli-Q water. Gels were soaked in 0.2 % (w/v) silver nitrate for 30 min and quickly rinsed with Milli-Q water for 20-30 seconds. The gels were developed in freshly prepared 0.3 M Na2CO3, 0.005 % (v/v) formaldehyde and 0.0001 % (w/v) sodium thiosulfate for 10-20 min in subdued light. 10 % (v/v) acetic acid was employed as a stop solution for 5 min. Gels were archived by clamping between two sheets of moist transparent cellophane paper and air-dried. Dry gels were digitally photographed on a light box and analysed using Quantity one 1-D analysis software (Bio-Rad, USA) using a Windows TM PC.

2.2.4.4 Fluorescent labeling detection

PCR amplification containing the fluorescent primers was carried out as previously described (Section 2.2.3.2). The PCR products were purified using a commercial kit

(Dye Ex™ spin kit, QIAGEN) and following the manufacturer’s protocol. 1 µl of the purified and denatured mixture was analysed on a PAGE sequencing gel using an ABI

PRISM 377 DNA sequencer, Automated DNA Analysis Facility, Biotechnology and

Bioscience, the University of New South Wales, NSW. Band size was estimated by comparing the mobility of the ISSR-PCR products to that of the internal size standard as determined by the ABI PRISM™ Genscan 2.1 analysis software (Applied Biosystem) in conjunction with ABI PRISM™ Genotyper 2.0 software (Applied Biosystem).

CHAPTER TWO: MATERIALS AND METHODS

2.2.5 Statistical Analysis 2.2.5.1 Data scoring and Distance Matrix

Patterns on electrophoresis gels were scored based on the presence or absence of a particular band with all cultivars and all informative primers using the Quantity one 1-D analysis software (Bio-Rad, USA). This software can determine the size of each band in each lane by comparison to the size markers. A manual check of the scoring was carried out for all gels and corrections to the software alignments made if appropriate.

The data from PCR products produced by the fluorescent ISSR primers were compiled in ExcelTM files. For each isolate, a data matrix of characters was compiled by scoring the presence or absence of each allele at each locus.

A Distance matrix was constructed based on the dissimilarity of both the total character and mean character difference matrix. The profiling was created by the biodiversity software, PAUP* (Phylogenetic Analysis Using Parsimony) v4.010b (School of

Computational Science and Information Technology, Florida State University,

Tallahassee, Florida) using an Apple Macintosh computer.

2.2.5.2 Clustering analysis and construction of phylogenetic tree

Clustering analysis was applied using Neighbour-Joining with pairwise distance matrix.

The PAUP software was also used for clustering analysis and construction of phylogenetic trees. The phylogenetic relationships were evaluated using the Bootstrap algorithms within the PAUP software.

CHAPTER THREE: RESULTS AND DISCUSSION

3.1. Optimization of ISSR-PCR amplification

Today PCR is technically a simple operation in which reagents are mixed and incubated in a thermal cycler that automatically controls the parameters of the reaction cycles according to a preprogrammed set of instructions. According to Weising et al. (1995) all the PCR conditions for ISSR amplification can affect the quality of banding patterns.

Therefore, a number of parameters were investigated and optimized to maximize band clarity, reproducibility and to minimize artifacts.

3.2. Preliminary screening

Before selection of the informative primers, the 100 commercial ISSR primers were screened using the PCR conditions of Lim (2002) at the annealing temperature calculated for each primer (Section 2.2.3.1). Only a few Buffalo grass cultivars

(Palmetto, Shademaster and Sir Walter) and Couch grass cultivars (Conquest and Riley’

Super Sport) were used. If 1 or 2 bands were produced by a primer, the primer was determined to be ‘weak’, if 3 or 4 bands were produced, it was determined to be

‘normal’ and if more than 4 bands were produced, it was determined to be ‘strong’. The primers which produced more 4 bands regarded as a pre-informative primer. About 40 primers for Buffalo grass cultivars and 50 primers for Couch grass cultivars were selected as being pre-informative.

3.2.1 Template

Quality and quantity of the DNA template are important in PCR analysis and aspects of

DNA isolation should be considered depending on the purpose of the research.

CHAPTER THREE: RESULTS AND DISCUSSION

3.2.1.1 Time of storage of tissue

The effect of different periods of storage on the quality of extracted DNA was investigated. Typical results are shown in Figure 3.1. Genomic DNA extracted from fresh, green leaves was of good quality with little degradation (lanes 5 and 6, Fig. 3.1).

Tissue stored at -20ºC for 2 months also gave good quality genomic DNA, although some degradation was evident, as judged by some smearing (lanes 7 and 8, Fig. 3.1).

No DNA was detected from tissue stored at -20ºC for 8 months (lanes 9 and 10, Fig.

3.1) nor from in situ senescent tissue extracted immediately after harvesting (lanes 11 and 12, Fig. 3.1). The effect of storing tissue at -80ºC was not investigated because of limited storage capacity.

Fig. 3.1 Quality of genomic DNA extracted from Couch grass tissue stored under different conditions. DNA was extracted from Conquest couch grass and analysed by agarose gel electrophoresis. 1-3: λ-DNA mass marker (25 ng, 50 ng, and 100 2000 bp ng), 4: size marker (1 kb plus DNA ladder), 5: 1650 bp fresh tissue untreated RNase, 6: fresh tissue treated 1000 bp 850 bp RNase, 7: tissue stored at -20°C for 2 months and 650 bp 500 bp untreated RNase, 8: tissue stored at -20°C for 2 400 bp 300 bp months and treated RNase, 9: tissue stored at 200 bp -20°C for 8 months and untreated RNase, 10: 100 bp tissue stored at -20°C for 8 months and treated RNase, 11: in situ senescent tissue untreated RNase, 12: in situ senescent treated RNase.

CHAPTER THREE: RESULTS AND DISCUSSION

Despite the differing quality of DNA all samples were used as a template for PCR amplification (Section 3.2.7). The results are shown in Figure 3.2. They show that tissue stored for up to 2 months after harvesting gave an identical pattern to tissue extracted immediately after harvesting (compare lanes 1 and 2 with lanes 3 and 4, Fig. 3.2).

Although tissue stored at -20ºC for 8 months gave no visible high molecular weight genomic DNA (Fig. 3.1), PCR amplicons were produced (lanes 5 and 6, Fig. 3.2), although the banding pattern was different to the other samples. The results show that grass samples stored at -20ºC for up to 2 months are suitable for DNA extraction and

PCR amplification. The presence of bands with small differences in size is consistent with the loss of annealing sites due to DNA degradation.

Fig. 3.2 PCR fragments amplified from Conquest couch genomic DNA. DNA was extracted from Conquest couch grass and analysed by agarose gel electrophoresis. Primer: UBC #9 (857), 1-2: Fresh tissue, 3-4: 2000 bp 1650 bp tissue stored at –20℃ for 2 months, 5-6: tissue

1000 bp stored at -20℃ over 8 months, 7-8: in situ 850 bp 650 bp senescent. Odd numbers: untreated RNased, 500 bp 400 bp Even numbers: treated RNase. Size marker: 300 bp 200 bp 1kb plus DNA ladder, c: control (λ DNA

100 bp template using λ forward and reverse primers). Optimal PCR conditions were used (Section 3.2.7).

CHAPTER THREE: RESULTS AND DISCUSSION

3.2.1.2 RNA inhibition

On electrophoresis, genomic DNA samples showed the presence of a diffuse band at about 100bp, assumed to be RNA (Fig. 3.1). It has been suggested that contaminating

RNA may interfere with PCR amplification (Pikaart, 1993). Therefore, genomic DNA samples, untreated or treated with RNase, were compared as PCR templates. The results of representative samples are shown in Figure 3.3 and show that there was no apparent effect of RNA on the number and intensity of PCR bands. Nevertheless genomic DNA samples were routinely treated with RNase during isolation (Section 2.2.1).

SW GlP 1 2 3 4 1 2 3 4

2000 bp 1650 bp 2000 bp 1650 bp

1000 bp 1000 bp 850 bp 850 bp 650 bp 650 bp 500 bp 500 bp 400 bp 400 bp 300 bp 300 bp 811 885 859 885 (A) (B)

Fig. 3.3 PCR fragments amplified from genomic DNA before and after RNase treatment. (A) Buffalo grass [SW]; 1, 3: untreated RNase, 2, 4: treated RNase, primers UBC#9 (811, 885). (B) Couch grass [Glp]; 1, 3: untreated RNase, 2, 4: treated RNase, primers UBC#9 (859, 885). Size marker: 1kb plus DNA ladder, Agarose gel electrophoresis, Optimal PCR conditions were used (Section 3.2.7), Cultivar abbreviations are shown in Appendices A and B.

CHAPTER THREE: RESULTS AND DISCUSSION

3.2.1.3 Amount of DNA

The effect of different amounts of DNA template on PCR amplification was tested. The results are shown in Figure 3.4. Qualitatively no difference in band pattern was observed. However, the 50 ng and 75 ng of template gave thicker bands although there was more smearing in the background. The 5 ng of template produced distinctly less intense bands. Polyacrylamide gel electrophoresis gave similar results to agarose gel electrophoresis (results not shown). Therefore, 25 ng was determined to be a suitable amount of template for PCR amplification from Buffalo grass and Couch grass DNA and was routinely used in this study.

2000 bp Fig. 3.4 The effect of template amount 1650 bp 1000 bp on PCR amplification of Wintergreen 850 bp 650 bp couch genomic DNA. 500 bp 400 bp Primer: UBC#9 (825), 1: 5ng, 2: 25ng, 300 bp 200 bp 3: 50ng, 4: 75ng. Size marker: 1kb plus DNA 100 bp ladder, Agarose gel electrophoresis. Optimal PCR conditions were used (Section 3.2.7).

CHAPTER THREE: RESULTS AND DISCUSSION

3.2.2 Concentration of ISSR primer

The concentration of primer is also known to have an effect on PCR result. Previous studies with Couch grass cultivars used 0.2-0.48 µM for RAPD analysis (Roodt et al.,

2002), 0.2 µM for AP-PCR analysis (Ho et al., 1997) and 0.3 µM for DAF analysis

(Caetano-Anollés et al., 1991a). However, there is no reported information on the use of microsatellite primers for identification of Couch grass cultivars. Furthermore no molecular studies have been reported for the identification Buffalo grass cultivars.

Therefore, different concentrations of primer on PCR amplification were tested in this study. Typical results are shown in Figure 3.5. They show that in both Couch grass and

Buffalo grass, a primer concentration of 0.3 µM produced more bands and higher intensity bands when compared to 0.1 or 0.2 µM primer. Therefore, this concentration was routinely used for both the Buffalo and Couch grass cultivars.

Couch (Wt) Buffalo(SM) Couch (Wt) Buffalo(SM) 0.1 0. 2 0. 3 0.1 0. 2 0. 3 0.1 0. 2 0. 3 0.1 0. 2 0. 3

2000 bp 1650 bp

1000 bp 850 bp 650 bp 500 bp 400 bp 300 bp (A) (B) 200 bp

100 bp

(A) (B)

Fig. 3.5 The effect of primer concentration on PCR amplification of Buffalo and Couch grass genomic DNA. Primer: UBC#9 (809), Size marker: 1kb plus DNA ladder. (A): Agarose gel electrophoresis, (B): Non-denaturing PAGE. Primer concentration in µM above each lane. Optimal PCR conditions were used (Section 3.2.7), Cultivar abbreviations are shown in Appendices A and B.

CHAPTER THREE: RESULTS AND DISCUSSION

3.2.3 Concentration of Taq Polymerase

If it is difficult to produce sufficient bands, the concentration of Taq DNA polymerase and the extension time of PCR can be checked. The effect of different concentrations of

Taq polymerase on PCR amplification was tested. Typical results are shown in Figure

3.6. From the results, 1.25 units and 2.0 units of Taq Polymerase produced more bands with greater clarity than 0.5 units and 1.0 unit of Taq Polymerase in both genera of grass.

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

2000 bp 1650 bp

1000 bp 850 bp 650 bp 500 bp 400 bp 300 bp

(A) (B) 1 2 3 4 5 6 2 1 3 4 5 6

2000 bp 1650 bp

1000 bp 850 bp

650 bp

500 bp 400 bp (C) 300 bp (D)

Fig. 3.6 The effect of different concentrations of Taq polymerase on PCR amplification of Buffalo and Couch grass gnomic DNA. (A): 0.5 units, (B): 1.0 unit, (C): 1.25 units, (D): 2.0 units, 1-3: Buffalo grass cultivars (1: PA, 2: SM, 3: SW), 4-6: Couch grass cultivars (4: Co, 5: Rss, 6: Sa), Size Marker: 1kb plus DNA ladder, Primer: UBC#9 (830), Optimal PCR conditions were used (Section 3.2.7), Agarose gel electrophoresis, Cultivar abbreviations are shown in Appendices A and B. NB. Note order change in lanes 1 and 2 in gel (D).

CHAPTER THREE: RESULTS AND DISCUSSION

Overall the band pattern with 1.25 units of enzyme appears better than the others and therefore was selected as the optimal concentration for PCR amplification. Previously,

0.3 units of a Taq DNA polymerase were used in DAF (Caetano-Anollés et al., 1995) and 0.5 units of a Taq DNA polymerase were used as the optimal concentration in AP-

PCR (Ho et al., 1997) and RAPD analysis (Roodt et al., 2002) for Couch grass cultivars.

1 unit of Taq DNA polymerase was used with ISSR primer in trifoliate orange (Poncirus trifoliate (L.) Raf.) (Fang and Roose, 1997).

3.2.4 Concentration of MgCl2

Magnesium is an important component of the PCR reaction mixture. It exists as dNTP-

Mg2+ complexes that interact with the sugar-phosphate backbone of the template and influences the activity of Taq DNA polymerase (McPherson and Moller, 2000). For

Couch grass cultivars, 2.5 mM was the optimal Mg2+ concentration using AP-PCR (Ho et al., 1997) and 1.5 mM using DAF (Caetano-Anollés et al., 1995) and RAPD analysis

(Roodt et al., 2002). The effect of different MgCl2 concentrations on PCR amplification was tested in this study. Typical results are shown in Figure 3.7. Baumforth et al. (1999) suggests that the ideal Mg2+ concentration is 1 to 3 mM. The optimal concentration was found to be 3.0 mM for both Buffalo grass and Couch grass.

CHAPTER THREE: RESULTS AND DISCUSSION

Co ST 15 2.0 2.5 3.0 3.5 2.0 2.5 3.0 3.5

2000 bp 1650 bp

1000 bp 850 bp 650 bp 500 bp 400 bp 300 bp 200 bp 100 bp

Fig. 3.7 The effect of different concentrations of MgCl2 on PCR amplification of Buffalo and Couch grass genomic DNA. Co: Couch grass cultivar, ST15: Buffalo grass cultivar,

MgCl2 concentration in mM above each lane, Primer: UBC#9 (857), Size marker: 1kb plus DNA ladder, Agarose gel electrophoresis, Optimal PCR conditions were used (Section 3.2.7), Cultivar abbreviations are shown in Appendices A and B.

Using the same commercial ISSR primer set with citrus, Fang and Roose (1997) found

2.0 mM to be the optimal Mg2+ concentration. It may be expected that a different optimal MgCl2 concentration will be required depending on the plant, primer and source of Taq enzyme. 1.5 mM MgCl2 was used in cultivar identification of the strawberry

(Fragaria ananajsa L.) in ISSR amplification (Arnau et al., 2002). The QAIGEN

Master Mix contains 1.5 mM of Mg2+ and therefore additional Mg2+ was required for optimal results. It is worth noting that care should be taken in optimising the Mg2+ concentration. If the Mg2+ concentration is too low, then yields of specific products can be poor, while excess Mg2+ can reduce the fidelity of Taq DNA polymerase leading to the amplification of non-specific products. Therefore, it is always desirable to optimize the concentration of Mg2+ to obtain the best results (Cao et al., 2004).

CHAPTER THREE: RESULTS AND DISCUSSION

3.2.5 Number of thermal cycles

Adjusting the number of PCR cycles can be helpful in maximising the yield of PCR products at a given DNA template concentration. Previous Couch grass studies used 40 cycles in RAPD analysis (Roodt et al., 2002), 30 cycles in AP-PCR analysis (Ho et al.,

1997) and 35 cycles in DAF (Caetano-Anollés et al., 1995). The effect of the number of thermal cycles on PCR amplification was tested for both Buffalo and Couch grass cultivars. Typical results are shown in Figure 3.8. No products were produced with 25 cycles although λ DNA used as a control was successfully amplified. Only a few bands were produced with 30 cycles. Both 35 and 45 cycles produced many bands. However,

45 cycles produced so many that it was difficult to distinguish one band from another.

Furthermore 45 cycles produced a more stained background reducing contrast between discrete bands and the background (Fig. 3.8). A greater number of PCR cycles do not necessarily lead to a higher yield of PCR products. Instead it may increase the background smear and decrease the yield of specific PCR products (QIAGEN, 2002).

Since 35 cycles were found to be optimal for PCR of Couch grass genomic DNA,

35cycles was also used for PCR of Buffalo grass genomic DNA.

25 30 35 45 C Fig. 3.8 The effect of the number of thermal cycles on PCR amplification 2000 bp 1650 bp of Wintergreen Couch genomic DNA.

1000 bp 850 bp Number of cycles shown above each lane,

650 bp Size marker: 1 kb plus DNA ladder, primer:

500 bp UBC#9(825), C: λ-DNA control (25 cycles, λ 400 bp forward and reverse primers), Non-denaturing 300 bp PAGE. Optimal PCR conditions were used 200 bp (Section 3.2.7).

CHAPTER THREE: RESULTS AND DISCUSSION

3.2.6 Annealing temperature

The annealing temperature is also a significant parameter in giving the best PCR products. Since annealing temperature is affected by the length and the G+C content of each primer it will vary with the different primers used. Therefore the effect of different annealing temperatures for the informative primers was tested. Typically annealing temperatures were tested in 2ºC increments, 6ºC either side of the calculated Tm

(melting temperature). The Tm was calculated using the relationship [Tm = 2 x (A+T content) + 4 x (G+C content)ºC]. The calculated and experimentally determined optimal annealing temperatures are shown in Table 3.1. The optimal annealing temperature of most of the informative primers was found to be either at or 2ºC below the calculated

Tm. In general it correlated well with the relative GC content in that the higher the GC content, the higher the annealing temperature. An interesting exception was UBC#9

(807) (Table 3.1).

CHAPTER THREE: RESULTS AND DISCUSSION

Table 3.1 Calculated melting temperature and experimental optimal annealing temperature of informative primers for PCR with Buffalo grass and Couch grass genomic DNA Primer Sequence GC content Calc. Tm. Optimal annealing temp. (ºC) (%) (ºC) Buffalo Couch 3'- anchored primers

807 (AG)8T 47 50 52 52

808 (AG)8C 53 52 52 52

809 (AG)8G 53 52 50 50

811 (GA)8C 53 50 50 50

825 (AC)8T 47 50 48 48

826 (AC)8C 53 52 52 52

827 (AC)8G 53 52 50 50

828 (TG)8A 47 50 - 48

830 (TG)8G 53 52 50 50

836 (AG)8YA 44-50 52-54 48 -

840 (GA)8YT 44-50 52-54 - 52

842 (GA)8YG 50-55 54-56 52 52

850 (GT)8YC 50-55 54-56 52 -

855 (AC)8YT 44-50 52-54 48 -

856 (AC)8YA 44-50 52-54 - 50

857 (AC)8YG 50-56 54-56 50 50

859 (TG)8RC 50-56 54-56 52 52 Non-anchored primers

861 (ACC)6 67 60 58 58

862 (AGC)6 67 60 - 58 5'- anchored primers

884 HBH(AG)7 41-59 48-54 48 -

885 BHB(GA)7 41-59 48-54 50 -

889 DBD(AC)7 41-59 48-54 48 -

890 VHV(GT)7 41-59 48-54 - 50

891 HVH(TG)7 41-59 48-54 - 50

Y= (C, T), R= (A, G), H= (A, C, T), B= (C, G, T)(ie. not A), D= (A, G, T)(ie. not C) -: No PCR products, ie non informative primer.

CHAPTER THREE: RESULTS AND DISCUSSION

The previous Couch grass studies used short arvitary primers (10bp) and therefore annealing temperatures were lower (36ºC for AP-PCR, Ho et al., 1997; 30ºC for DAF,

Caetano-Anollés et al., 1991a; 34ºC for RAPD analysis, Roodt et al., 2002) than ISSR primers (17-18bp).

As an example of the results obtained Figure 3.9 shows the effect of different annealing temperatures using primer UBC#9 (859) on PCR amplification of a Couch and Buffalo

DNA sample. Based on these results, 52ºC gives the highest intensity of bands taken across all bands.

Fig. 3.9 The effect of annealing temperature using primer 48 50 52 54 56 48 50 52 54 56 C UBC#9 (859) on PCR amplification of a Couch and 2000 bp 1650 bp Buffalo DNA sample.

1000 bp Column heading is annealing 850 bp Temperature (ºC). Size marker: 1kb 650 bp 500 bp plus DNA ladder. C: λ DNA control 400 bp with λ forward and reverse primers. 300 bp

200 bp Agarose gel electrophoresis. Optimal PCR conditions were used (Section 100 bp Co PA 3.2.7). Cultivar abbreviations are (Couch) (Buffalo) shown in Appendices A and B.

Since Taq DNA polymerase will have some activity at the annealing temperature, the holding time of the reaction at this temperature needs to be kept between 30s and 60s to minimize the amplification of nonspecific products (Nielson et al., 1994).

CHAPTER THREE: RESULTS AND DISCUSSION

3.2.7 Summary of optimal PCR condition

ISSR-PCR amplification was optimized around the use of a commercial HotStar Taq

Master Mix Product (QIAGEN). A number of parameters were systematically varied to improve the qualitative and quantitative results. These included the amount of template

DNA, MgCl2 concentration, primer concentration and the amount of enzyme (Taq polymerase). In addition the number of amplification cycles was investigated. The final composition of each amplification reaction contained proprietary 1X PCR buffer, 25 ng

DNA template, 200 µM of each dNTP, 3.0 mM MgCl2, 0.3 µM primer and 1.25 units of

Taq Polymerase in a total volume of 25 µl.

Thermocycler conditions involved an initial denaturation at 95ºC for 15 minutes to activate the Taq polymerase. Amplification was achieved using 35 cycles at 94ºC for 1 minute, primer annealing at the optimal annealing temperature for 1 minute and extension at 72ºC for 1.5 minutes with a final extension at 72ºC for 10 minutes. These conditions were routinely used for the analysis of the turf grass cultivars.

CHAPTER THREE: RESULTS AND DISCUSSION

3.3. Reproducibility of ISSR-PCR amplification

Reproducibility and repeatability should be a hallmark of any technique used for

cultivar identification. A limited set of identical cultivars were collected from different

sources and processed at the same time. Some sample results are shown in Figure 3.10.

From these and other unshown results it was found that within the limits of detection

excellent reproducibility was obtained between grass samples that had been separated in

parentage for a considerable, although unknown time.

SW ST26 Rss 1 2 1 2 1 2 1 2 2000 bp 2000 bp 1650 bp 1650 bp 1000 bp 1000 bp 850 bp 850 bp 650 bp 650 bp 500 bp 500 bp 400 bp 300 bp 400 bp 200 bp 300 bp 100 bp 200 bp 885 100 bp 859 885 (A) (B)

Fig. 3.10 The Reproducibility of PCR amplification of Buffalo grass and Couch grass genomic DNA. Buffalo grass: SW; 1 was from the Department of Primary Industries, QLD and 2 was from the Royal Botanic Garden, Sydney. ST26; 1 was from the Department of Primary Industries, QLD and 2 was from Richmond Turf Supplies, NSW, Primer: UBC#9 (885), Size marker: 1 kb plus DNA ladder. (B) Couch grass: RSS; 1 was from Windsor Turf Supplies, NSW and 2 was from the Department of Primary Industries, QLD, Primer: UBC#9 (859, 885). Agarose gel electrophoresis, Optimal PCR conditions were used (Section 3.2.7). Cultivar abbreviations are shown in Appendices A and B.

CHAPTER THREE: RESULTS AND DISCUSSION

3.4. Genetic Identification of Buffalo grass cultivars using ISSR-PCR analysis

Genetic variation in plant populations may be caused and maintained by a variety of mechanisms including mutation, sexual recombination, migration and gene flow, genetic drift and genetic selection (Henry, 1997). Many Buffalo grass cultivars also have been discovered and selected by genetic variation, but the similarity of morphological traits makes it difficult to identify cultivars. It is to be hoped that accurate and sensitive genetic characterisation will assist in demonstrating genetic diversity and avoiding incorrect genotypes.

3.4.1 Informative ISSR primers for cultivar identification

Commercial ISSR primers were used for cultivar identification because of the absence of any specific microsatellite information from Buffalo grass. The cost per primer purchasing the commercial kit was less than AUD 10. Using the optimized PCR conditions previously determined (Section 3.2.7), 40 pre-informative UBC#9 ISSR primers (Section 3.1) were screened against 10 available Buffalo grass cultivars. From the results, 18 of the 40 primers were selected as being informative based on the presence of strong and reproducible polymorphic bands. A list of the 18 informative primers is shown in Table 3.2.

CHAPTER THREE: RESULTS AND DISCUSSION

Table 3.2 ISSR PCR primers generating strong and reproducible polymorphic bans from Buffalo grass genomic DNA

Primer Sequence Primer Sequence 3'-Anchored primers 3’-Anchored primers

807 (AG)8T 850 (GT)8YC

808 (AG)8C 855 (AC)8YT

809 (AG)8G 857 (AC)8YG

811 (GA)8C 859 (TG)8RC

825 (AC)8T 5’-Anchored primers

826 (AC)8C 884 HBH(AG)7

827 (AC)8G 885 BHB(GA)7

830 (TG)8G 889 DBD(AC)7

836 (AG)8YA Non-anchored primers

842 (GA)8YG 861 (ACC)6

Y= (C, T), R= (A, G), H= (A, C, T), B= (C, G, T)(ie. not A), D= (A, G, T)(ie. not C)

Fourteen 3’-anchored primers gave reproducible bands with the Buffalo grass cultivars with the (AG)8, (GA)8, and (AC)8 primers giving the best results. This indicates that polymorphisms among Buffalo grass cultivars can be identified easily by these 3’ anchored primers. The use of 3’-anchors avoids priming from within a repeat nucleotide element and provides the specificity that reduces the number of targeted genomic loci to those matching the 3’-terminal residues (Zietiewicz et al., 1994).

The GenBank database indicates that (CA)n repeats are less abundant in the genomes of plants than in mammals (Lagercrantz et al., 1993). Zietiewicz et al., (1994) has examined the distribution among species of the (CA)n microsatellite. (CA)8RG and

(CA)8RY were used to look for genetic distance in some animal, plant, fish and bacteria genomic samples. No amplification products were seen in bacterial DNA. In contrast, too many PCR products were produced in fish DNA and other animal DNA. There were fewer bands in soya, maize, tomato and Arabidopsis. Hamada et al., (1982) reported

CHAPTER THREE: RESULTS AND DISCUSSION

that (CA)n repeats are the most frequent dinucleotide repeats in the human genome. A number of (CA) repeat 3’anchored primers, such as (CA)8T and (CA)8RG, were part of commercial kit. A small number of the bands were produced, but they were not regarded as informative primers when compared with the other ISSR primers (data not shown).

Furthermore, (TC)8, (CT)8 and (AT)8 sequences did not produce any suitable bands. The latter result was interesting because (AT)n sequences are thought to be amongst the most abundant motifs in plant species (Depeiges et al., 1995; Morgante and Olivier, 1993).

According to some reports, an ISSR primer based on these motifs may produce dimers during PCR amplification (Blair et al., 1999). Ossewarde et al. (1992) suggested that this problem might be alleviated with the inclusion of teramethylammonium chloride in the amplification reaction which would serves to negate the weak hydrogen bonding effects of A:T base pairing. This experiment was not tried because enough informative primers were available.

The anchor serves to fix the annealing of the primer to a single position at each target site on the template, such that every new polymerization event initiates at the same target position. Thus, there is little or no chance for primer slippage on the template and problems with priming out of register are minimized (Vogel, and Scolnik, 1998).

Furthermore, the 5’-anchored primers generate products that capture within the amplified product any allelic length variation that may exist within on SSR target site.

Three [HBH(AG)7, BHB(GA)7 and DBD (AC)7] of the ten 5’-anchored primers gave a suitable banding pattern with the Buffalo grass cultivars. These sequences were coincident with the repeat sequences of the informative 3’-anchored primers.

CHAPTER THREE: RESULTS AND DISCUSSION

Of the 21 non-anchored primers, only one [(ACC)6] produced PCR products. No products were observed using tetra- and penta- non-anchored primers. Moreover, the non-anchored primers tended to give fuzzy bands and a smeared background on the gels.

This suggests slippage of the primer on the template, not unexpected with non-anchored primers compared to anchored primers. Although Bornet and Branchard (2001) concluded that the use of non-anchored ISSRs was advantageous, they were not useful for studying genetic diversity of Buffalo grass cultivars in this work. it seems that the anchored primers are more useful for cultivar identification of Buffalo grass than non- anchored primers.

3.4.2 Polymorphism analysis of Buffalo grass cultivars

The level of polymorphism observed in the amplification products can be related to genomic diversity within the species. After the preliminary screening, the 18 informative primers (Table 3.2) were re-tested and the results rigorously quantified for polymorphisms using two different separation and visualisation procedures; agarose gel electrophoresis with ethidium bromide staining and non-denaturing PAGE with silver staining. Representative gels for each of the 18 primers are included in Appendix H (CD

ROM as JPEG images in the Microsoft PowerPoint file).

CHAPTER THREE: RESULTS AND DISCUSSION

3.4.2.1 Polymorphism as seen on agarose gel electrophoresis

Agarose gel electrophoresis and ethidium bromide staining produced a total of 157

bands from the 18 primers. The results are shown in Table 3.3. The size of the bands

ranged from 254 bp to 1936 bp. Of the total bands, 111 (71 %) were selected as being

polymorphic in that the band was absent from at least one cultivar sample. The average

number of bands generated by each primer was nine with a range from six to eleven.

Table 3.3 Polymorphism analysis of Buffalo grass cultivars from agarose gel electrophoresis

Primer Sequence Total Mono. Poly. % of poly. Size range bands bands bands bands (bp) 3’-Anchored primers

807 (AG)8T 6 2 4 67 440-1650

808 (AG)8C 11 6 5 46 353-1021

809 (AG)8G 9 1 8 89 337-1433

811 (GA)8C 11 2 9 82 425-1650

825 (AC)8T 7 2 5 71 505-1652

826 (AC)8C 11 4 7 64 490-1660

827 (AC)8G 9 3 6 67 380-1590

830 (TG)8G 7 3 4 57 450-1343

836 (AG)8YA 9 1 8 89 254-1396

842 (GA)8YG 9 2 7 78 284-937

850 (GT)8YC 9 4 5 56 270-1936

855 (AC)8YT 10 5 5 50 459-1883

857 (AC)8YG 7 3 4 57 676-1602

859 (TG)8RC 7 2 5 71 443-1210 Non-Anchored primers

861 (ACC)6 8 1 7 88 838-1362 5’-Anchored primers

884 HBH(AG)7 10 0 10 100 379-869

885 BHB(GA)7 11 3 8 73 486-1389

889 DBD(AC)7 6 2 4 67 594-1358 Total number: 157 46 111 71 Mono.: monomorphic, Poly.: polymorphic. Y= (C, T), R= (A, G), H= (A, C, T), B= (C, G, T)(ie. not A), D= (A, G, T)(ie. not C)

CHAPTER THREE: RESULTS AND DISCUSSION

No clear pattern was apparent in the results, for example single base anchors producing a higher percentage of polymorphism than two-base anchors.

Figure 3.11 shows some examples of the different banding profiles with an example of each class of ISSR primer used. Primer 811 [(GA)8C] produced more polymorphic band

1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10

2000 bp 1650 bp

1000 bp 850 bp 650 bp 500 bp 400 bp 300 bp 200 bp

100 bp

(A) (B) (C)

Fig. 3.11 Example of banding pattern visualised from agarose gel electrophoresis in Buffalo grass cultivars. Primers: (A) UBC#9 (811), (B) UBC#9 (885), (C) UBC#9 (861), Size marker: 1 kb plus DNA ladder. 1: GGR 2: PA, 3: SM 4: SW, 5: ST15, 6: ST26, 7: ST85, 8: ST91, 9: B12, 10: VET. Optimal PCR conditions were used (Section 3.2.7). Cultivar abbreviations are shown in Appendix A.

in each cultivar compared with the other two examples (Fig. 3.11 (A) ). Nevertheless primer 885 (BHB(GA)7) also produced clear and robust polymorphic bands (Fig. 3.11

(B)).

CHAPTER THREE: RESULTS AND DISCUSSION

In rice Blain et al. (1999) reported that the bands produced by 3’-anchored ISSR primers were easier to score than those produced by 5’-anchored primers because they were of sharper intensity with less stuttering. Citrus cultivars, (Fang and Roose, 1997) reported that 5’-anchored primer amplification produced fewer bands than 3’-anchored primers. However in the Buffalo grass cultivars, both types of anchored primers produced clear banding patterns. It is debatable whether 3’-anchored primers were easier to score and produced more bands in the Buffalo grass cultivars. HBH(AG)7 and

BHB(GA)7 have been utilised for Oryza nivara cultivar identification and HBH(AG)7

(primer 884) amplified the maximum number of bands and also had the highest resolving power (Sarla et al., 2003). However, to say that 3’-anchored primers are more useful than 5’-anchored primers is premature because relatively few were tested in this study. In deed 30 % of the 5’-anchored primers (3 from 10) were considered informative whereas only 23% (14 from 60) of the 3’-anchored primers were informative. In addition, the plant genus and species is likely to alter the relative merits of 3’- and 5’- anchored primers.

In contrast, even the best non-anchored primer with Buffalo grass DNA produced

“fuzzy” bands and a more smeared background, whereby some bands were not considered reproducible (Fig. 3.11 (C)). This may be caused by annealing in several possible registers at each target site, resulting in multiple heterogeneous products from each locus visualized as a smear on the gel (Vogel and Scolnik, 1998).

CHAPTER THREE: RESULTS AND DISCUSSION

3.4.2.2 Polymorphism as seen on non-denaturing PAGE

Non-denaturing PAGE with silver staining produced a total of 224 bands with 182

bands being polymorphic (81 %). The results are shown in Table 3.4. The average

Table 3.4 Polymorphism analysis of Buffalo grass cultivars from non-denaturing PAGE

Primer Sequence Total Mono. Poly. % of poly. Size range bands bands bands bands (bp) 3’-Anchored primers

807 (AG)8T 11 1 10 91 450-4650

808 (AG)8C 14 3 11 79 336-1814

809 (AG)8G 13 4 9 69 335-1650

811 (GA)8C 15 1 14 93 469-1778

825 (AC)8T 11 2 9 82 500-1948

826 (AC)8C 14 3 11 79 401-2068

827 (AC)8G 15 4 11 73 400-1760

830 (TG)8G 9 2 7 78 456-1328

836 (AG)8YA 11 1 10 91 278-1787

842 (GA)8YG 9 3 6 68 296-893

850 (GT)8YC 13 2 11 85 295-1875

855 (AC)8YT 16 4 12 75 484-1753

857 (AC)8YG 9 2 7 78 675-1666

859 (TG)8RC 12 2 10 83 280-1659 Non-Anchored primers

861 (ACC)6 11 1 10 91 818-2250 5’-Anchored primers

884 HBH(AG)7 13 0 13 100 315-882

885 BHB(GA)7 15 4 11 73 500-1600

889 DBD(AC)7 13 3 10 77 661-1679 Total number 224 42 182 81 Mono.: monomorphic, Poly.: polymorphic. Y= (C, T), R= (A, G), H= (A, C, T), B= (C, G, T)(ie. not A), D= (A, G, T)(ie. not C)

number of bands from each primer was twelve and the size of the bands ranged from

218 bp to 2250 bp. The total number of bands detected was higher than that from

agarose gel electrophoresis. This probably reflects the higher resolution of PAGE and sensitivity of silver staining.

CHAPTER THREE: RESULTS AND DISCUSSION

Although the 5’-anchored primers produced many polymorphic bands, most of the differentiation was between GGR02/101 and the other cultivars.

Figure 3.12 shows some examples of the different banding profiles obtained. Primer 811

[(GA)8C] produced many polymorphic bands in each cultivar compared with the other primers (Table 3.4 and Fig. 3.12 (A) ). Primer 885 (BHB(GA)7) also produced clear and robust polymorphic bands. However, the polymorphism was not as good as that achieved for the 3’-anchored primers across the 10 cultivars (Fig. 3.12 (B)). The non- anchored primer still produced a “fuzzy” and smeared band pattern similar to agarose gel electrophoresis (Fig. 3.12 (C)). In general, at least by eye, PAGE produced sharper bands than did the agarose electrophoresis.

1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10

2000 bp 1650 bp

1000 bp 850 bp 650 bp

500 bp 400 bp

300 bp

200 bp

100 bp

(A) (B) (C)

Fig 3.12 Example of banding patterns visualised from non-denaturing PAGE in Buffalo grass cultivars. Primers: (A) UBC#9 (811), (B) UBC#9 (885), (C) UBC#9 (861), Size Marker: 1 kb plus DNA ladder, 1: GGR, 2: PA, 3: SM, 4: SW, 5: ST15, 6: ST26, 7: ST85, 8: ST91, 9: B12, 10: VET, Optimal PCR conditions were used (Section 3.2.7). Cultivar abbreviations are shown in Appendix A.

CHAPTER THREE: RESULTS AND DISCUSSION

3.4.2.3 Polymorphism as seen on non-denaturing PAGE with fluorescent labeling detection

Polymorphism analysis for Buffalo grass cultivars was also trialed using two primers

(UBC#9 (811) and UBC#9 (826)) that were labeled at the 5’-end with the fluorescent dye, 6-FAM. After non-denaturing PAGE separation using an ABI PRISMTM 377 sequencer, the PCR products were visualised and analysed using GeneScan 2.0 software

(Fig. 3.13).

1 2 3 4 5 6 x 7 8 9x 10 1 2 3 4 5 6 x 7 8 9 x 10

Primer 811 Primer 826

Fig 3.13 Banding pattern visualised by FISSR analysis in Buffalo grass cultivars. The bands were visualised using ABI PRISM™ GeneScan 2.0 analysis software. Primer 811 (6-FAM) and primer 826 (6-FAM). 1: GGR, 2: PA, 3: SM, 4: SW, 5: ST15, 6: ST26, 7: ST85, 8: ST91, 9: B12, 10: VET, (x: not used). Optimal PCR conditions were used (Section 3.2.7). Cultivar abbreviations are shown in Appendix A

CHAPTER THREE: RESULTS AND DISCUSSION

The fluorescent primers produced sharper bands than the other methods employed.

Bands were scored from the plot created by the ABI PRISM™ Genotyper 2.0 software in conjunction with ABI PRISM™ GeneScan 2.0 software (Fig. 3.14).

Monomorphic

Polymorphic

Fig 3.14 An example of part of the Genotyper plot produced by fluorescent primer 826 in the Buffalo grass cultivars. Blue box: polymorphic band, Red box: monomorphic band. Cultivar abbreviations are shown in Appendix A.

CHAPTER THREE: RESULTS AND DISCUSSION

A total of 57 bands were produced by the two fluorescent primers with 53 bands being polymorphic (93 %) (Table 3.5). The size of bands ranged from 287 bp to 1630 bp using the same two primers. This was about twice that obtained from non-denaturing PAGE.

Table 3.5 Polymorphism analysis of Buffalo grass cultivars using non-denaturing PAGE and fluorescent detection

Primer Sequence Total Mono. Poly. % of Poly. Size bands bands bands bands range (bp)

811 (AG)8T+6FAM 23 1 22 96 287-1630

826 (AG)8C+6FAM 34 3 31 91 451-1400

Total number : 57 4 53 93

Mono.: monomorphic, Poly.: polymorphic.

3.4.3 Genetic variation of Buffalo grass cultivars

Analysis of variation is important for plant breeding. Improvement of plant varieties is performed by selecting desirable genotypes from the genetic variation available and manipulating them to produce an elite individual (Henry, 1997). Buffalo grass cultivars are being constantly improved. Therefore, turf suppliers who generate new Buffalo grass cultivars want to protect their new varieties. Documentation for these new varieties for PBR is required which includes morphological and developmental traits.

As many Buffalo grass cultivars are closely related to each other, morphological characteristics can be similar. Unless the distance is qualitative (eg. Stigma colour white

[ST-15 and Palmetto] versus purple [other cultivars]), it is necessary to repeat a DUS growing trial to access actually the quantitative differences. DNA profiling provides quick supporting evidence, particularly for legal purposes in defining possible PBR infringements and improved protection is now possible through genetic profiling being accepted as supplement evidence in Australia.

CHAPTER THREE: RESULTS AND DISCUSSION

All specific diagnostic markers for individual cultivars were identified for each of the separation and detection methodologies used and are listed in Tables 3.6, 3.7 and 3.8.

Table 3.6 Diagnostic markers for Buffalo grass cultivars from agarose gel electrophoresis

Band size Cultivars Band size Cultivars Primer Primer (bp) having the band (bp) having the band

807 1650 PA, ST26, ST85, VET 842 765 PA, ST26, ST85, VET 650 GGR 850 843 GGR 809 500 B12 855 1390 VET 811 855 B12 692 GGR 825 1216 GGR 564 PA, ST26, VET 826 510 PA, ST26, ST85, VET 857 1500 SW, ST15, B12 827 1042 PA, ST26, ST85, ST91, VET 676 GGR 1408 GGR 859 650, 505 GGR 771 GGR 861 1362 GGR 830 432 PA, VET 884 797 PA, ST26, VET 836 1396, 616 GGR 404 PA, VET 475 SM, SW, ST15, B12 885 1066, 590 GGR 1349 SM, SW, ST15, B12 889 1358 SM, SW, ST15, B12 969 PA, ST26, ST85, ST91, VET 650 VET

Cultivar abbreviations are shown in Appendix A.

For example, from non-denaturing PAGE (Table 3.7), the polymorphic band at 892 bp could be a diagnostic marker to discriminate ST-26 with the other Buffalo grass cultivars using primer 807. Similarly the polymorphic band at 905 bp could be a diagnostic marker for Palmetto using primer 885. Another example is the polymorphic band at 660 bp from primer 884 which could be a specific marker for the Velvet cultivar

(Table 3.7). Velvet is derived from Californian Common material, but is only available

CHAPTER THREE: RESULTS AND DISCUSSION in Western Australia. It has large soft leaves and is moderately shade tolerant. It is susceptible to Brown Patch disease in Sydney (McMaugh, 1997).

Table 3.7 Diagnostic markers for Buffalo grass cultivars from non-denaturing PAGE

Band size Cultivars Band size Cultivars Primer Primer (bp) having the band (bp) having the band

807 1650 PA, ST26, ST85, VET 842 861 PA, VET

892 ST26 549 SW

632 GGR 850 850 GGR

808 1814, 1771 SW 560 SM, SW, ST15, B12

432 SM 855 1227 GGR

809 592 SM 999 SM, SW, ST15

811 1700 VET 649 PA, ST26, VET

1130 GGR 857 1666 SW

1000, 852 SM 1291 SW, ST15, B12

825 1948, 1804 GGR 675 GGR

1546, 1350 GGR 859 886 SM, SW, ST15, B12

826 1361, 715 GGR 500 GGR

545 PA, ST26, ST85, ST91, VET 861 1838, 947 SM, SW, ST15, B12

401 SM, SW, ST15, B12 884 660 VET

827 1321 SW, ST15, B12 636 GGR

758 GGR 315 PA, ST26, ST85, ST91,

830 1328 GGR 885 905 PA

1306 ST15 688, 659 GGR

456 PA, VET 889 1455 SM

836 1787 PA, ST26, VET 1385 SM, SW, ST15, B12

1366, 479 SM, SW, ST15, B12 1198, 1014 SM

940 ST26, ST85, ST91, VET 955 PA, ST26, ST85, ST91

Cultivar abbreviations are shown in Appendix A.

CHAPTER THREE: RESULTS AND DISCUSSION

Table 3.8 Diagnostic markers for Buffalo grass cultivars from FISSR analysis

Band size Cultivars Band size Cultivars Primer Primer (bp) having the band (bp) having the band

811 1200 GGR 826 627, 611 GGR

766 GGR 622 ST-85

760, 686 GGR 607 B12

515 VET 464 PA, ST26, ST91

509 PA, ST26, ST85 451 GGR

287 PA, ST26, ST91, VET 398 PA

826 940 PA, ST26, VET 394, 391 SM, SW, ST15, B12

819, 812 SW, ST15,B12 388 SM, SW, ST15, B12

Cultivar abbreviations are shown in Appendix A

Interestingly, GGR02/101, which was collected in Tasmania had a very different band pattern compared to the other cultivars (Figs 3.15 and 3.16). These other cultivars have either originated in the USA, such as Palmetto, or are derived from germplasm collected in the lower Hunter Valley, NSW, such as Sir Walter

Fig. 3.15 Some genetic markers

2000bp to distinguish GGR02/101 from 1650bp 1119bp the other Buffalo grass cultivars. 1000bp 850bp Primer: UBC#9 (807), 1: GGR, 2: PA, 3:

650bp 650bp SM, 4: SW, 5: ST15, 6: ST26, 7: ST85, 500bp 8: ST91, 9: B12, 10: VET. Size marker: 400bp 300bp 1 kb plus DNA ladder, Agarose gel 200bp electrophoresis, Optimal PCR conditions

100bp were used (Section 3.2.7). Cultivar abbreviations are shown in Appendix A

CHAPTER THREE: RESULTS AND DISCUSSION

GGR

ST15

ST26

Fig. 3.16 Part of the Genotyper plot produced by fluorescent primer 811 in six Buffalo grass cultivars. The band (683 bp) outlined in the red box was present only in GGR02/101. Cultivar abbreviations are shown in Appendix A

CHAPTER THREE: RESULTS AND DISCUSSION

3.4.3.1 Specific markers for closely related cultivars

Some bands appear useful as diagnostic markers to differentiate Shademaster or Sir

Walter from each other and from the other cultivars (Fig 3.17). Sir Walter produced bands at 1814 bp and 1771 bp on non-denaturing PAGE from primer 808 (Fig 3.17 (A)).

A band at 432 bp differentiates Shademaster from the other cultivars (Fig 3.17 (A)).

Primer UBC#9 (857) produced a band at 1666 bp for identification of Sir Walter only

(Fig 3.17 (B)).

1 2 3 4 5 6 7

1814 bp 1771 bp 2000bp 1650bp 1666 bp 1000bp 850bp

650bp 500bp 432 bp 400bp

300bp 200bp

100bp

(A) (B)

Fig 3.17 Specific markers to differentiate Shademaster and Sir Walter from the other Buffalo grass cultivars. (A) UBC#9 808, 1: GGR, 2: PA, 3: SM, 4: SW, 5: ST15, 6: ST26, 7: ST91, (B) UBC#9 857, 1: GGR, 2: PA, 3: SM, 4: SW, 5: ST15, 6: ST26, 7: ST85, 8: ST91, 9: B12, 10: VET. Size marker: 1 kb plus DNA ladder, Non-denaturing PAGE, Optimal PCR conditions were used (Section 3.2.7). Cultivar abbreviations are shown in Appendix A.

CHAPTER THREE: RESULTS AND DISCUSSION

These polymorphic bands, being unique, can be used as diagnostic markers, especially

Shademaster and Sir Walter, the latter of which has been granted Australian PBR

(McMaugh, 1997). Brent Redman developed the early variety known as Shademaster in the late 1980s and Sir Walter in the mid-1990s. These two cultivars can be morphologically distinguished by the altered colour of their leaves in winter.

Shademaster has purple tinged colour leaves in winter, while Sir Water maintains its green colour (McMaugh, 1997). It is interesting to speculate that one or more of the polymorphic bands may be specific markers involved with the characteristics of colour maintenance. Maintenance of colour is significant for beautification and cost- effectiveness. Therefore, the discovery of the specific gene should be investigated for economic value.

Although only two 6FAM labeled primers were trialed, a number of polymorphic bands were produced that could differentiate between the various cultivars. For example, primer 811-6FAM produced a polymorphic band that clearly distinguishes Sir Walter and ST-15 from the other cultivars (Fig. 3.18).

CHAPTER THREE: RESULTS AND DISCUSSION

GGR

ST15

Fig. 3.18 Part of the Genotyper plot produced by fluorescent primer 811 in five Buffalo grass cultivars. The band (427 bp) outlined in the red box was present only in Sir Walter and ST 15. Cultivar abbreviations are shown in Appendix A.

CHAPTER THREE: RESULTS AND DISCUSSION

3.4.4 Phylogenetic relationships of the Buffalo grass cultivars

Phylogenetic construction for genetic diversity of Buffalo grass can be established with some statistical analysis.

3.4.4.1 Data matrices of Buffalo grass cultivars

After the identification of polymorphic and monomorphic bands for all primers, the presence (1) or absence (0) of a band was scored to create a data matrix. Tables 3.9, 3.10 and 3.11 are an example of the data matrices produced from primer 811 for the three detection methods. All data matrices are shown in Appendix F.

Table 3.9 Data matrix of Buffalo grass cultivars from primer UBC#9(811) and agarose gel electrophoresis Name Band size (bp) (Abbr.) 1650 1162 1057 983 855 850 659 630 515 475 425 GGR 1 1 0 0 0 1 1 1 1 0 0 PA 1 0 0 1 0 1 1 1 1 1 0 SM 1 0 0 1 0 1 1 1 1 1 0 SW 1 0 1 1 0 1 1 1 1 1 1 ST15 1 0 1 1 0 0 1 1 1 1 1 ST26 1 0 0 1 0 1 1 1 1 0 1 ST85 1 1 0 1 0 1 1 1 1 1 1 ST91 1 1 0 1 0 1 1 1 1 0 0 B12 1 0 1 1 1 1 0 1 1 1 1 VET 1 0 0 1 0 1 1 0 1 0 0 Cultivar abbreviations are shown in Appendix A, 0= absent, 1=present

CHAPTER THREE: RESULTS AND DISCUSSION

Table 3.10 Data matrix of Buffalo grass cultivars from primer UBC#9(811) and non- denaturing PAGE

Name Band size (bp)

(Abbr.) 1778 1700 1650 1590 1139 1130 1000 990 912 852 764 664 540 505 469

GGR 0 0 100100101 1 0 00 PA 1 0 010001101 1 1 10 SM 1 0 110011111 1 1 10 SW 1 0 111001101 1 1 11 ST15 1 0 111001001 1 1 11 ST26 1 0 010001101 1 1 01 ST85 1 0 111001101 1 1 11 ST91 1 0 111001101 1 1 00 B12 1 0 001001101 1 1 11 VET 1 1 011001100 1 1 00 Cultivar abbreviations are is shown in Appendix A, 0= absent, 1=present

Table 3.11 Data matrix of Buffalo grass cultivars from primer UBC#9(811) and fluorescent detection

Name Band size (bp)

(Abbr.) 686 664 657 648 642 622 542 516 515 509 488 427 376 347 302 287 360 766 978 1090 1200 1540 1680

GGR 1 11 1 1 110000001101 1 1 0 1 0 0 PA 0 11 1 1 111011011110 0 1 0 0 1 1 SM 0 11 0 0 111001001100 0 1 0 0 1 1 SW 0 11 1 1 111001101100 0 1 1 0 1 1 ST15 0 11 1 1 111001101100 0 1 1 0 1 1 ST26 0 11 1 1 111010101110 0 1 0 0 1 1 ST85 0 01 0 1 101011110000 0 0 0 0 1 1 ST91 0 01 1 1 111001101110 0 1 0 0 1 1 B12 0 11 1 0 111001000000 0 1 1 0 1 1 VET 0 11 1 0 010100111110 0 0 0 0 1 1 Cultivar abbreviations are shown in Appendix A, 0= absent, 1=present

CHAPTER THREE: RESULTS AND DISCUSSION

The size of bands was determined using the Quantity One 1-D analysis software (Bio-

Rad, USA) and comparison to the size marker. However, because the software does not always accurately line up the bands with the marker, all size assignments were visually and manually double checked.

3.4.4.2 Distance matrices of Buffalo grass cultivars

Distance matrices were constructed based on the number of differentiated bands between individuals using the phylogenetic software package PAUP* v4.010b

(Swofford, 1998). Three distance matrices for the Buffalo grass cultivars were produced

– one for each of the analysis methodologies. They are tabulated in Tables 3.12, 3.13 and 3.14. These distance matrices consist of two characteristics – total character differences and mean character differences.

Table 3.12 Distance matrix of Buffalo grass cultivars produced from agarose gel electrophoresis

GGR PA SM SW ST15 ST26 ST85 ST91 B12 VET GGR - 0.522 0.401 0.433 0.446 0.446 0.440 0.376 0.440 0.490 PA 82 - 0.185 0.217 0.229 0.115 0.134 0.185 0.312 0.147 SM 63 29 - 0.070 0.108 0.210 0.127 0.102 0.166 0.255 SW 68 34 11 - 0.038 0.204 0.121 0.121 0.108 0.299 ST15 70 36 17 6 - 0.217 0.121 0.134 0.121 0.312 ST26 70 18 33 32 34 - 0.121 0.147 0.287 0.185 ST85 69 21 20 19 19 19 - 0.076 0.217 0.217 ST91 59 29 16 19 21 23 12 - 0.217 0.255 B12 69 49 26 17 19 45 34 34 - 0.369 VET 77 23 40 47 49 29 34 40 58 - Below diagonal: Total character differences, Above diagonal: Mean character differences Cultivar abbreviations are shown in Appendix A

CHAPTER THREE: RESULTS AND DISCUSSION

Table 3.13 Distance matrix of Buffalo grass cultivars produced from non-denaturing PAGE

GGR PM SM SW ST15 ST26 ST85 ST91 B12 VET

GGR - 0.505 0.469 0.482 0.482 0.469 0.482 0.446 0.460 0.482

PA 113 - 0.304 0.317 0.299 0.143 0.192 0.201 0.321 0.201

SM 105 68 - 0.147 0.165 0.268 0.219 0.192 0.170 0.317

SW 108 71 33 - 0.080 0.272 0.241 0.205 0.112 0.366

ST15 108 67 37 18 - 0.263 0.214 0.196 0.103 0.321

ST26 105 32 60 61 59 - 0.138 0.156 0.277 0.192

ST85 108 43 49 54 48 31 - 0.107 0.228 0.232

ST91 100 45 43 46 44 35 24 - 0.237 0.241

B12 103 72 38 25 23 62 51 53 - 0.326

VET 108 45 71 82 72 43 52 54 73 -

Below diagonal: Total character differences, Above diagonal: Mean character differences Cultivar abbreviations are shown in Appendix A.

Table 3.14 Distance matrix of Buffalo grass cultivars produced from FISSR analysis

GGR PA SM SW ST15 ST26 ST85 ST91 B12 VET

GGR - 0.500 0.482 0.568 0.568 0.448 0.655 0.448 0.603 0.517

PA 29 - 0.224 0.275 0.344 0.086 0.293 0.120 0.379 0.224

SM 28 13 - 0.155 0.224 0.241 0.344 0.206 0.258 0.275

SW 33 16 9 - 0.068 0.258 0.362 0.224 0.172 0.362

ST15 33 20 13 4 - 0.327 0.362 0.293 0.103 0.431

ST26 26 5 14 15 19 - 0.310 0.068 0.396 0.206

ST85 38 17 20 21 21 18 - 0.275 0.362 0.310

ST91 26 7 12 13 17 4 16 - 0.362 0.241

B12 35 22 15 10 6 23 21 21 - 0.465

VET 30 13 16 21 25 12 18 14 27 -

Below diagonal: Total character differences, Above diagonal: Mean character differences Cultivar abbreviations are shown in Appendix A.

CHAPTER THREE: RESULTS AND DISCUSSION

The Total Character Difference between two cultivars was calculated by summing the number of different bands between the two cultivars. For example, the number of different bands between Sir Walter and ST-15 was 6 from agarose gel electrophoresis

(Table 3.12). The Mean Character Difference is the ratio of the number of different bands to the total band number. For example, the Mean Character Difference between

Sir Walter and ST-15 was 0.038 [6/157] from agarose gel electrophoresis (Table 3.12).

The largest total character difference was between GGR 02/101 and Palmetto based on the data from agarose gel electrophoresis and non-denaturing PAGE (Tables 3.12 and

3.13 respectively). FISSR analysis created the largest difference between GGR 02/101 and ST-85 (Table 3.14). The smallest Total Character Difference was between Sir Walter and ST-15 (Tables 3.12, 3.13 and 3.14).

The differences between individuals by non-denaturing PAGE and FISSR analysis were higher than by agarose gel electrophoresis. Therefore, it may be concluded that non- denaturing PAGE and FISSR are a more sensitive and useful tool to study the relatedness of the cultivars.

3.4.4.3 Clustering analysis and phylogenetic construction for Buffalo grass

Clustering analysis is an important step in the construction of a phylogenetic tree and many algorithms have been used for this purpose. The Neighbour-joining algorithm of

Saitou and Nei (1987) was used for clustering analysis and generation of phylogenetic trees in this study. The algorithm was part of the PAUP software package. A separate

CHAPTER THREE: RESULTS AND DISCUSSION tree was created for each of the three electrophoresis and detection methods. Evaluation of the robustness in each branch was performed using Bootstrap value with 1000 re- samplings. The resulting dendograms are shown in Figs. 3.19, 3.20 and 3.21.

GGR02/101

Palmetto

Velvet

ST-26

ST-85

ST-91

Shademaster

Sir Walter

ST-15

B12

Fig. 3.19 Neighbour-joining dendogram (unrooted, phylogram) of Buffalo grass cultivars generated from agarose gel electrophoresis data. Software: PAUP v4.010b, Bootstrap values are shown above each internode. Genetic change is matched to the length of the internodes.

CHAPTER THREE: RESULTS AND DISCUSSION

GGR02/101

Palmetto

Velvet

ST-26

ST-85

ST-91

Shademaster

Sir Walter

ST-15

B12

Fig. 3.20 The Neighbour-joining dendogram (unrooted, phylogram) of Buffalo grass cultivars generated from non-denaturing PAGE data. Software: PAUP v4.010b, Bootstrap values are shown above each internode. Genetic change is matched to the length of the internodes.

CHAPTER THREE: RESULTS AND DISCUSSION

GGR02/101

Palmetto

ST-26

ST-91

ST-85

Velvet

Shademaster

Sir Walter

ST-15

B12

Fig. 3.21 The Neighbour-joining dendogram (unrooted, phylogram) of Buffalo grass cultivars generated from FISSR analysis data. Software: PAUP v4.010b, Bootstrap values are shown above each internode. Genetic change is matched to the length of the internodes.

CHAPTER THREE: RESULTS AND DISCUSSION

From the dendograms, two major groups of cultivars were found. One group contained

Palmetto, Velvet, ST-26, ST-91 and ST-85. ST-26, ST-91 and ST-85 are all derived from

Seville (a dwarf US variety) x ST series and have Australia plant patent according to IP

Australia, Australia Government, although the genetic material came from the USA.

Palmetto (SS100) was developed on a sod farm near Daytona Beach, Florida, USA

(Scattini, 1998) and very closely related to Velvet which was from Californian Common

Buffalo grass (McMaugh. Pers. Commend, 2004).

The other group contained ST-15, Shademaster, Sir Walter, and B12. Sir Walter has been granted by Australia PBR. Three cultivars, Shademaster, Sir Walter and B12 are from

Lower Hunter Valley, NSW. B12 was created by open pollination followed by seedling selection from Sir Walter. Therefore, the dendograms could be helpful to identify for the original of Buffalo grass.

GGR02/101 appeared as an out-group with respect to the other cultivars, although it is morphologically similar to the other cultivars although it has darker green leaves and large inflorescences. Collected in Tasmamia, its origin and natural history are unknown.

The two dendograms created by the agarose gel electrophoresis and non-denaturing

PAGE data were identical except for the branch between ST-85 and ST-91 (Fig. 3.19 and Fig. 3.20). ST-85 was bifurcated from ST-91 in the dendogram created from the agarose gel electrophoresis data, but they were assembled in the same inter-node from the non-denaturing PAGE data. Palmetto was closely related to Velvet and Sir Walter to

ST-15 in both data sets. For the FISSR data set, the main structure of the tree was quite coincident with the other twp dendograms (Fig 3.21). Although the dendogram different

CHAPTER THREE: RESULTS AND DISCUSSION in detail, it needs to be remembered that only two primers have been used to generate the initial data.

The Bootstrap values pleasing, most values being well above 50 %. Based on the

Bootstrap values of the branches the structure of the phylogenetic tree from the non- denaturing PAGE data set is probably the most robust (Fig.3.20).

In summary, all the Buffalo grass cultivars tested could be differentiated by ISSR-PCR analysis. Although the genetic markers identified can only be used as supplementary evidence for the protection of current and new varieties at present, it is to be hoped that

ISSR-PCR could be a major forensic method to protect mislabeling or misidentification in the future.

CHAPTER THREE: RESULTS AND DISCUSSION

3.4.5 Comparison of detection methods

An appropriate experimental method is important to resolve and visualize the ISSR-

PCR products into a reproducible fingerprint pattern. A suitable gel matrix and gel concentration must be chosen to suit the size range of the molecules to be separated.

Polymorphisms are detected based on size differences and the visualization needs to combine simplicity with sensitivity.

The three detection methodologies used in this study were directly compared using a few specific examples that appeared to give anomalous results. For example, primer 808 gave a “doublet” at 1814 bp and 1771 bp and a band at 432 bp on non-denaturing PAGE, but these bands were not visible on agarose gel electrophoresis (Fig. 3.22).

1 2 3 4 5 6 7 1 2 3 4 5 6 7 1814 bp 1771 bp 2000 bp 1650 bp

2000 bp (lane 4) 1650 bp 1000 bp 850 bp 1000 bp 650 bp 850 bp 650 bp 500 bp 500 bp 432 bp 400 bp 400 bp (lane 3) 300 bp 300 bp

200 bp 100 bp 200 bp

100 bp

(A) (B)

Fig. 3.22 Comparison of band patterns between agarose gel electrophoresis and non- denaturing PAGE using primer 808. Size marker: 1 kb plus DNA ladder, (A) agarose gel electrophoresis (B) non-denaturing PAGE, 1: GGR, 2: PA, 3: SM, 4: SW 5: ST-15, 6: ST-26, 7: ST-91. Optimal PCR conditions were used (Section 3.2.7). Cultivar abbreviations are shown in Appendix A.

CHAPTER THREE: RESULTS AND DISCUSSION

Independent DNA isolation and PCR amplification gave identical results. In agarose gels, pore formation is a physical process, resulting from a shift in conformation of the molecules composing it. In contrast, pore formation in polyacrylamide gels is a chemical process, resulting from chemical cross-linking. The result is a very regular matrix with a much more uniform pore size. It is not clear how the different gel matrices may be affecting migration of the DNA through the gel.

Using primer 826 as an example, the total number of bands generated by FISSR analysis (34) was greater than agarose electrophoresis (11) or non-denaturing PAGE

(14). If only the total number of polymorphic bands is considered, florescent labeling detection will give the best result for banding pattern. Likewise the Bootstrap score was higher in the dendogram from non-denaturing PAGE than for agarose gel electrophoresis. Although only two fluorescent ISSR primers were used in this study, the structure of phylogenetic tree produced was similar to the polygenetic trees created by the other visualisation methodologies. This suggests that the Bootstrap score of the phylogenetic tree from FISSR analysis will be increased if a few more primers are tested.

However, it is difficult to conclude whether non-denaturing PAGE or fluorescent labeling is better than agarose gel electrophoresis for cultivar identification. From the distance matrix tables, dissimilarities of some cultivars were higher from agarose gel electrophoresis than non-denaturing PAGE or distances between some cultivars were higher from non-denaturing PAGE than agarose gel electrophoresis. For example, the distance between Shademaster and Sir Walter generated by non-denaturing PAGE was higher than by agarose gel electrophoresis, but distance between Palmetto and ST 26

CHAPTER THREE: RESULTS AND DISCUSSION from agarose gel electrophoresis was greater than from non-denaturing PAGE (Table

3.12 and 3.13). Therefore, it could be debated to the comparison of visualization methodologies for genetic identification.

CHAPTER THREE: RESULTS

3.5. Genetic Identification of Couch grass cultivars using ISSR-PCR analysis

According to Shakesby (1998), there are about forty named forms of Cynodon grasses used in Australia. Therefore, the genetic variation of Couch grasses should be established for plant population. Normally morphological inspection is used to identify individuals or varieties in the turf market area. However, many Couch grass cultivars are so similar that it is difficult to distinguish them using morphological traits alone.

Therefore, the availability of asensitive, reproducible and robust technique based on genetic characterization would be of great benefit.

3.5.1 Informative ISSR primers for cultivar identification

Commercial ISSR primers were used for cultivar identification because of the absence of any specific microsatellite information from Couch grass. Using the optimized PCR conditions previously determined (Section 3.2.7), 50 pre-informative UBC#9 ISSR primers (Section 3.2) were screened against 50 Couch grass cultivars. 18 primers were selected as being informative based on the presence of strong and reproducible polymorphic bands.. A list of the imformative primers is shown in Table 3.15.

CHAPTER THREE: RESULTS

Table 3.15 ISSR PCR primers generating strong and reproducible polymorphic bands from Couch grass genomic DNA

Primer Sequence Primer Sequence 3’-Anchored primers 3’-Anchored primers

807 (AG)8T 842 (GA)8YG

808 (AG)8C 856 (AC)8YA

809 (AG)8G 857 (AC)8YG

811 (GA)8C 859 (TG)8RC

825 (AC)8T 5’-Anchored primers

826 (AC)8C 890 VHV(GT)7

827 (AC)8G 891 HVH(TG)7

828 (TG)8A Non-anchored primers

830 (TG)8G 861 (ACC)6

840 (GA)8YT 862 (AGC)6 Y= (C, T), R= (A, G), H= (A, C, T), B= (C, G, T)(ie. not A), D= (A, G, T)(ie. not C)

From of the 60 3’- anchored primers, 14 (23%) gave reproducible bands. Like Buffalo grass, the 3’-anchored (AG)8 and (AC)8 produced many bands. The 3’- and 5’-anchored primers with the (TG)8 repeated sequence worked better Couch grass than Buffalo grass.

This suggests that (TG) repeat microsatellite regions are more abundant in Couch grass than Buffalo grass. The lower number of bands from (CA) repeats with the Couch grass cultivars was similar to that in Buffalo grass. (AT)8, (TA)8, (TC)8 and (CT)8 primers did not produce useful or reproducible bands. As has already been mentioned, (AT)8 and

(TA)8 anchored primers may perform poorly becaused of self-annealing of the primers

(Blair et al., 1999).

Two [VHV(GT)7 and HVH(TG)7] of the 10 5’-anchored primers gave a useful banding pattern with the Couch grass cultivars. The repeat sequences of the informative 5’- anchored primers with the Couch grass cultivars were different to these that were informative with the Buffalo grass cultivars. As was mentioned in the Section 3.4., Fang

CHAPTER THREE: RESULTS and Roose (1997) reported that 5’-anchored primers produced fewer bands than 3’- anchored primers in citrus cultivars. In this study, only 10 5’-anchored primers were tested compared to 60 3’-anchored primers. It is difficult to support the result, reported by Fang and Roose (1997). It could be useful to test using further 5’-anchored primers.

Only two [(ACC)6 and (AGC)6] of the 21 non-achored primers produced many bands.

Like Buffalo grass cultivars, the two primers produced a fuzzy and smeared pattern with no clear bands. As with Buffalo grass, this may be caused by primer annealing to several possible target sites (Vogel and Scolinik, 1998). No PCR products were produced when tetra- and penta- primers were tested. According to Toth et al., (2000), tri- and hexa-nucleotide repeats are prevalent in protein-coding exons of all taxa tested in their study. Therefore, tri-nucleotide repeats may be of further interest, although the banding pattern for these tased was not strong. Other tri-microsatellite primers and hexa-non-anchored primers could be tried for more functional and robust cultivar identification.

Unfortunately, no primers produced polymorphic bands that could differentiate some hybrids such as FloraDwarf TM and Tifgreen. Their differences could be the result of a single point mutation within the flanking sequence that does not result in detectable change in fragment length (Burgess et al., 2001) or there are differences in the random sequence regions not the repeated sequence regions. Therefore, sequencing of the PCR- products or using of another genetic method could find differences between these hybrids. Zietkiewicz et al. (1994) suggested that ISSR-PCR products can be easily excised from dried gels and cloned or re-amplified to be used as probes. This could provide an alternative strategy for identifying microsatelites in genomic libraries.

CHAPTER THREE: RESULTS

3.5.2 Polymorphism analysis of Couch grass cultivars

Couch grass was introduced to other parts of the world in the 18th century or earlier

(Hanson et al., 1969). It grows throughout warmer regions and has adapted to both tropical and subtropical climates. Selection of the improved cultivars has been done for various purposes and identification of genetic variation is important in this process.

Polymorphisms could be detected as the presence and absence of a band. This may be caused by the primer’s failure to anneal at a site in some individuals because of nucleotide sequence differences or by insertions or deletions in the fragment between two conserved primer sites (Clark and Lanigan, 1993).

After the preliminary screening, the 18 informative primers (Table 3.15) were re-tested and the results rigorously quantified for polymorphisms using two different separation and visualisation procedures; agarose gel electrophoresis with ethidium bromide staining and non-denaturing PAGE with silver staining. Representative gels for each of the 18 primers are included in Appendix I (CD ROM as JPEG images in the Microsoft

PowerPoint file).

3.5.2.1 Polymorphism as seen on agarose gel electrophoresis

Agarose gel electrophoresis and ethidium bromide staining produced a total of 335 bands from the 18 primers. The results are shown in Table 3.16. The size of the bands ranged from 314 bp to 2340 bp. Of the total bands, 327 (98 %) were selected as being polymorphic in that the band was absent from at least one cultivar sample. The average number of bands generated by each primer was 20 with a range from 11 to 29.

CHAPTER THREE: RESULTS

Table 3.16 Polymorphism analysis of Couch grass cultivars from agarose gel electrophoresis

Primer Sequence Total Mono. Poly. % of Poly. Size range bands bands bands bands (bp) 3’- Anchored primers

807 (AG)8T 16 0 16 100 400-2008

808 (AG)8C 18 0 18 100 400-1532

809 (AG)8G 21 0 21 100 421-1792

811 (GA)8C 17 0 17 100 469-2000

825 (AC)8T 13 1 12 92 552-1778

826 (AC)8C 20 0 20 100 566-2000

827 (AC)8G 18 0 18 100 464-2000

828 (TG)8A 19 0 19 100 400-2000

830 (TG)8G 15 0 15 100 500-1455

840 (GA)8YT 16 0 16 100. 503-2057

842 (GA)8YG 23 1 22 96 314-1969

856 (AC)8YA 20 0 20 100.0 473-2340

857 (AC)8YG 23 2 21 91 344-2324

859 (TG)8RC 21 0 21 100.0 390-1784 Non-anchored primers

861 (ACC)6 17 1 16 94 515-2083

862 (AGC)6 11 2 9 82 529-1650 5’- Anchored primers

890 VHV(GT)7 18 0 18 100.0 627-1636

891 HVH(TG)7 29 1 28 97 441-1724 Total number : 335 8 327 98

Mono.: monomorphic, Poly.: polymorphic Y=(C, T), R=(A, G), H=(A, C, T), B=(C, G, T)(ie. not A), D=(A, G, T)(ie. not C)

CHAPTER THREE: RESULTS

Figure 3.23 shows some examples of the banding profiles produced frim the Couch grass cultivars. Primers 811 (3’-anchored) and 891 (5’-anchored) produced polymorphic bands with clear profiles (Fig. 3.23 (A) and (B)). Band pattern for Couch grass cultivar identification also was not able to support the report of Fang and Roose (1997) like

Buffalo grass cultivar results. For example, UBC#9 (891) (5’-anchored) primer produced better separated bands variously compared to UBC#9 (811) (3’-anchored).

Moreover, only 10 commercial 5’-anchored ISSR primers were tested compared to 60

3’-anchored primers as well as Buffalo grass. It is premature to conclude the result. In addition, the plant genus and species is likely to alter the relative merits of 3’- and 5’- anchored primers.

Although primer UBC#9 (861) (non-anchored) produced polymorphic bands, they were fuzzy and smeared as was found for the Buffalo grass cultivars (Fig. 3.23(C)). As was mentioned in Section 3.4.2, this may be caused by annealing in several possible registers at each target site, resulting in multiple heterogeneous products from each locus visualized as a smear on the gel (Vogel and Scolnik, 1998).

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CHAPTER THREE: RESULTS

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 4 4 45 46 47 48 49 50

2000 bp 1 650 bp 1000 bp 850 bp 650 bp 500 bp 400 bp 300 bp 200 bp 100 bp

(A) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 4 4 45 46 47 48 49 50

2000 bp 1650 bp 1 000 bp 850 bp 650 bp 500 bp 400 bp 300 bp 200 bp 100 bp

(B) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 4 4 45 46 47 48 49 50

2000 bp 1 650 bp 1000 bp 850 bp 650 bp 500 bp 400 bp 300 bp 200 bp 100 bp (C)

Fig 3.23 Example of banding pattern visualised from agarose gel electrophoresis in Couch grass cultivars. Primers: (A): UBC#9 (811), (B): UBC#9 (891), (C): UBC#9 (861). Size marker: 1kb plus DNA ladder. Optimal PCR conditions were used (Section 3.2.7). Lane numbers are coincident with the list of Couch grass cultivars shown in Appendix B.

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CHAPTER THREE: RESULTS

3.5.2.2 Polymorphism as seen on non-denaturing PAGE

Non-denaturing PAGE with silver staining produced a total of 664 bands from the 18 informative primers and 658 bands (99 %) as being polymorphic. This was nearly twice the number found by agarose gel electrophoresis. The average number of bands per primer was 36 and the size of bands ranged from 174 bp to 2350 bp (Table 3.17).

Table 3.17 Polymorphism analysis of Couch grass cultivars from non-denaturing PAGE

Primer Sequence Total Mono. Poly. % of Poly. Size range bands bands bands bands (bp) 3’- Anchored primers

807 (AG)8T 36 2 34 94 308-2053

808 (AG)8C 37 0 37 100 459-2003

809 (AG)8G 31 0 31 100 374-1716

811 (GA)8C 47 0 47 100 174-2129

825 (AC)8T 30 1 29 97 523-2350

826 (AC)8C 41 0 41 100 469-1904

827 (AC)8G 43 0 43 100 440-1684

828 (TG)8A 30 0 30 100 353-2025

830 (TG)8G 32 0 32 100 477-1396

840 (GA)8YT 32 0 32 100 363-2012

842 (GA)8YG 48 0 48 100 320-1845

856 (AC)8YA 34 0 34 100 469-2099

857 (AC)8YG 39 0 39 100 365-2136

859 (TG)8RC 34 0 34 100 405-2109 Non- anchored primers

861 (ACC)6 30 1 29 97 565-1981

862 (AGC)6 31 1 30 97 467-2008 5’- Anchored primers

890 VHV(GT)7 49 0 49 100 319-1872

891 HVH(TG)7 40 1 39 98 483-1722 Total numbers : 664 6 658 99

Mono.: monomorphic, Poly.: polymorphic Y= (C, T), R= (A, G), H= (A, C, T), B= (C, G, T)(ie. not A), D= (A, G, T)(ie. not C)

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CHAPTER THREE: RESULTS

Figure 3.24 shows some examples of the banding profiles produced from the Couch grass cultivars. In general, at least by eye, PAGE produced sharper bands than did the agarose electrophoresis. This probably reflects the higher resolution of PAGE and sensitivity of silver staining.

Primers 857 (3’-anchored) and 890 (5’-anchored) produced polymorphic bands with clear profiles (Fig. 3.23 (A) and (B)). These banding profiles also demonstrated that it was premature to conclde the usefulness for clear and separated banding pattern between 3’-anchored and 5’-anchored primers. The non-anchored primers, UBC#9

(861) also created many polymorphic bands, but again the pattern was fuzzy and of low intensity (Fig. 3.24 (C)).

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CHAPTER THREE: RESULTS

1 2 3 4 5 6 7 8 9 10 11 12 13 14 151617 18 19 20 21 22 23 24 25 26 27 28 29 30 3132 33 34 35 36 37 38 39 40 4142 43 4 4 45 4647484950

2000 bp 1650 bp 1000 bp 850 bp 650 bp 500 bp 400 bp 300 bp 200 bp 100 bp (A)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 151617 18 19 20 21 22 23 24 25 26 27 28 29 30 3132 33 34 35 36 38 39 40 4142 43 4 4 45 4647484950

2000 bp 1650 bp 1000 bp 850 bp 650 bp 500 bp 400 bp 300 bp 200 bp 100 bp (B)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 151617 18 19 20 21 22 23 24 25 26 27 28 29 30 3132 33 34 35 36 37 38 39 40 4142 43 4 4 45 4647484950

2000 bp 1650 bp 1000 bp 850 bp 650 bp 500 bp 400 bp 300 bp 200 bp 100 bp (C)

Fig. 3.24 Example of banding pattern visualised from non-denaturing PAGE in Couch grass cultivars. Primers: (A): UBC#9 (857), (B): UBC#9 (890), (C): UBC#9 (861), Size marker: 1kb plus DNA ladder. Optimal PCR conditions were used (Section 3.2.7). Lane numbers are coincident with the list of Couch grass cultivars shown in Appendix B.

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CHAPTER THREE: RESULTS

3.5.3 Genetic variation of Couch grass cultivars

New turf varieties are being continually developed for sporting, commercial and domestic applications. Analysis of variation is important for plant breeding.

Improvement of plant varieties is performed by selecting desirable genotypes from the genetic variation available and manipulating them to produce an elite individual (Henry,

1997). The specific diagnostic markers for the individual Couch grass cultivars tested were identified for both separation and detection methodologies and are listed in Tables

3.18 and 3.19.

Table 3.18 Diagnostic markers for Couch grass cultivars from agarose gel electrophoresis

Band size Cultivars Band size Cultivars Primer Primer (bp) having the band (bp) having the band

807 1281 Fr 830 1206, 790 Gp 808 1532 Ct2 840 1258 Com 1223 038, Sa 997 Tw, Sa 633 Con, Tw, 200, Sa 842 960 Ts 400 Gp 856 1645 Ts 809 1290 Rss 863 Lg 421 Ct2 857 695 TL1 825 1660 Gp 859 1084 Tv 552 Tv 1014 TL1 826 1295, 1284 Ts, 200 657 Kgs 795 Gp 533 Wt 827 2000 Ts 861 2083 Tv 894 Tw, Ts, 200 862 737 Tv 1517 Tv 890 956 Tw, 001, Ts, 200, Sa 828 1344 Rc, Ts, 200, Tv 837 Rc 1014 Kgs 891 1343 Com, Tw, Ts, 200, Sa 830 1097 195 738 Wt 910 Kgs 514 Tv 596 195 Cultivar abbreviations are shown in Appendix B

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CHAPTER THREE: RESULTS

Table 3.19 Diagnostic markers for Couch grass cultivars from non-denaturing PAGE

Band size Cultivars Band size Cultivars Primer Primer (bp) having the band (bp) having the band 807 535 Fr 840 1545 Fr 808 1840 Kgs 697 Con 1801 Rc 394 Rss 868 Ts, 200, Sa 842 1572, 1428 195 809 929 Sa 1400 Lg 823 Tv 806, 631 Tl 1 540 Fr 504 Kgs 811 1813 133 856 965 Ws 1800 Kgs 899 001 1440, 634 Tv 679 Fr 534 Tv 857 1769 Ct2, Fr 1187 Ts, 200, Sa 1404 Com 1119 Com 605 Jt1 930 Fr 859 1538 Ct2 825 1715 Ws, 038 652 Wt 1319 Gp 861 1691, 1100 Np 1093 Pl 927 Np 826 1787 Ts, 200, Sa 763 195 933, 683 Tv 862 1894 Glp, Ha, Ss2 827 1678, 1501 Com 1787 Rc 1409 Tw 1305 195 784 Np 890 1329 Glp, Ha, Ss2 487 Tl 1 940 195 828 737 Tv 939 tv 784 Rc 688 Kgs 972, 876 Np 891 1641 Ts, 200, Sa 830 873 Pl 1243 Jt1 477 Tv 628, 482 195 840 1733 Tv 498 Tv 1706 195 Cultivar abbreviations are shown in Appendix B.

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An example of a diagnostic marker the 960 bp band of the TifSport cultivar, using primer 842 on agarose gel electrophoresis (Fig. 3. 25).

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

2000 bp 1650 bp

1000 bp 850 bp

650 bp 500 bp 400 bp 300 bp 200 bp

100 bp

Fig. 3.25 The genetic marker to differentiate between TifSport and other couch grass cultivars using primer UBC#9 (842) 1: Con, 2: TW, 3: Tl1, 4: Tl2, 5: Td(t), 6: Td(j), 7: 001, 8: Fd, 9: Tg, 10: Ts, 11: Te, 12: Ms, 13: Ch, 14: 200, 15: Sa, 16: Tv, : The specific marker for TifSport at 960bp. Size marker: 1kb plus DNA ladder, Agarose gel electrophoresis. Optimal PCR conditions were used (Section 3.2.7). Cultivar abbreviations are shown in Appendix B.

Tifsport is a vigorous triploid (2n=3x=27 chromosomes) which has use on golf course fairways and tees, athletic fields, lawns, commercial landscape sites, and other turf areas where a fine-textured, low growing turf is desired. It is a finer-textured mutant induced with radiation in the Midiron cultivar of bermudagrass (Hanna, 1997). TifSport was similar to Tifway and Tifway II in morphological and developmental characteristics.

The banding pattern is useful to distinguish between TifSport and Tifway cultivars.

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Figure 3.26 shows that by using primer 842, the bands at 1572 and 1428 bp can be used to distinguish WS195 from the other cultivars.

1 2 3 4 5 6 7 8 9 10 11 12 13 Fig. 3.26 The genetic marker to 2000bp 1650bp differentiate between WS195 and other Couch grass cultivars using 1000bp 850bp primer UBC#9 (842).

650bp 1: Rc, 2: Ws, 3: Wt, 4: Ss2, 5: 038, 6: 133,

500bp 7: 195, 8: Con, 9: Tw, 10: Tl1, 11: Tl2, 400bp 12: Td(t), 13: Td(j). : The specific

300bp markers for WS195 at 1572 bp and 1428 bp. Size marker: 1 kb plus DNA ladder, 200bp Non-denaturing PAGE. Optimal PCR

100bp Conditions were used (Section 3.2.7). Cultivar abbreviations are shown in Appendix B.

3.5.3.1 Specific markers for closely related cultivars

The 18 informative ISSR primers produced enough diagnostic markers to discriminate between all C. dactylon, but only some of the hybrids.

There were only a few band differences to differentiate some cultivars. For example, It may be appeared that Greenlees Park, Hatfield, and SS2 appear to be closely related to each other. In this study, only one primer 825 could differentiate between Greenlees

Park and Hatfield (Fig 3. 27).

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Glp Ha

2000bp 1650bp

1000bp 850bp 822 bp 802 bp 650bp 500bp Fig. 3.27 Diagnostic markers that differentiate 400bp between Greenlees Park (Glp) and Hatfield 300bp (Ha) cultivars. Primer: UBC#9 (825), Size Marker: 200bp 1kb plus DNA ladder, Non-denaturing PAGE. Optimal

PCR conditions were used (Section 3.2.7). 100bp

Figure 3.28 shows the band at 997 bp that can distinguish cultivar SS2 cultivar from Greenlees Park and Hatfield cultivars.

Glp Ha Ss2

2000bp 1650bp

1000bp 997 bp 850bp

650bp 500bp Fig. 3.28 Diagnostic marker that differentiate 400bp between SS2 and the other two Couch grass 300bp cultivars. 200bp Primer: UBC#9 (859), Glp: Greenlees Park,

100bp Ha: Hatfield, Ss2: SS2. Size Marker: 1kb plus DNA ladder, Non-denaturing PAGE. Optimal PCR conditions were used (Section 3.2.7).

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Hatfield from Gympie, QLD is similar to Riley’s Super Sport in low growing and more prostrate with common knowledge (Loch and Roche, 2003a) and the Riley’s Super

Sport is a spontaneous mutant of Greenlees Park cultivar (Kaapro, 1996).

Windsor Green was created by McMaugh (1993) using γ-irradiation of Wintergreen.

Therefore, it is expected that the two C. dactylon cultivars will be closely related to each other. Pleasingly the informative ISSR primers gave many polymorphic bands differentiating between the two cultivars in this study. An example of a differential gel band pattern can be seen in Figure 3.29.

Ws Wt

2324 bp 2000bp 1650bp

1000bp Fig. 3.29 Diagnostic markers that differentiate 850bp between Windsor Green (Ws) and cultivars 650bp 500bp Wintergreen (Wt) from agarose gel 400bp 375 bp electrophoresis. 300bp Primer: UBC#9 (857), Size marker: 1kb plus DNA 200bp ladder, Agarose gel electrophoresis. Optimal PCR 100bp conditions were used (Section 3.2.7).

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ISSR-PCR differentiated two identical cultivars, but collected from different locations

(Fig. 3.30). Conquest™ (Co) is the trademark name and Riley’s Evergreen (Re) is the marketing name. They should have an identical banding pattern. However, some polymorphic bands differentiated between the two cultivars. It is suggested that the difference is due to genetic variation consisitent with both temporal and geographic separation. sod contamination is another possibility but it is probably premature to define as an ‘off-type’ sample that only displayed distinctive patches of variant morphology.

Co Re Co Re

2000bp 1977 bp 1650bp 1820 bp 1000bp 2000bp 1650bp 850bp 650bp 1000bp 500bp 850bp 400bp 650bp 552 bp 500bp 300bp 400bp 200bp 300bp

200bp 100bp 100bp (A) (B)

Fig.3.30 Diagnostic markers to distinguish between Conquest™ and Riley’s Evergreen. (A) primer: UBC#9 (826), agarose gel electrophoresis. (B) primer: UBC#9 (890), non-denaturing PAGE. Co was collected from Windsor, NSW and Re was collected from DPI, QLD. Size marker: 1kb plus DNA ladder, Optimal PCR conditions were used (Section 3.2.7). Cultivar abbreviations are shown in Appendix B.

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Figure 3.31 shows that the Contaminant (Con), Tifway (Tw) and TL1 (Tl1) banding patterns were quite different to other hybrids. TifSport (Ts), WS200 (200) and Santa

Ana (Sa) banding patterns were similar to each other. The remaining cultivars show a strong similarity to one another.

Con Tw Tl 1 Tl 2 Td(t) Td(j) 001 Fd Tg Ts Te Ms Ch 200 Sa

2000bp 1650bp 1000bp 850bp 650bp 500bp 400bp

300bp 200bp

100bp

Fig. 3.31 Band patterns differentiating various Couch hybrids. Primer: UBC#9 (842), Size marker: 1kb plus DNA ladder, Non-denaturing PAGE. Optimal PCR conditions were used (Section 3.2.7). Cultivar abbreviations are shown in appendix B.

There was only one polymorphic band that could distinguish between Tifdwarf

(Toowoomba form) and Tifdwarf (Jindalee form). This was at 1290 bp generated using primer 811 (Fig 3.32). Therefore, the polymorphic band could be forensic evidence to distinguish between origin cultivar and off type cultivar.

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1 2 1 2

2000bp 1650bp 2000bp 1000bp 1650bp 1290 bp 850bp 650bp 1000bp 500bp 850bp 400bp 650bp 500bp 300bp 400bp 200bp 300bp 200bp 100bp 100bp (A) (B)

Fig. 3.32 Diagnostic marker that differentiates Tifdwarf (Toowoonba form) (Td (t)) and Tifdwarf (Jindalee from) (Td (j)). Primer: UBC#9 (811), 1: Td (t), 2: Td (j), Size Marker: 1kb plus DNA ladder, (A): Agarose gel electrophoresis, (B): Non-denaturing PAGE. Optimal PCR conditions were used (Section 3.2.7). Cultivar abbreviations are shown in in Appendix B.

C. transvaalensis easily appeared, differentiated from the other cultivars (Fig. 3.33).

2000bp 1650bp

1000bp 850bp 650bp 500bp 400bp 652bp 300bp 200bp 100bp

Fig. 3.33 The polymorphic band unique to C. transvaalensis (Tv). Primer: UBC#9 (857), Size marker: 1kb plus DNA ladder, Agarose gel electrophoresis. Optimal PCR conditions were used (Section 3.2.7). Cultivar abbreviations are shown in Appendix B.

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None of the 13 unknown cultivars matched to the named C. dactylon cultivars or hybrids. DN009 and DN010 are from Frankston, Victoria. PBR1, PBR2, PBR3, PBR5,

PBR9 and PBR13 are all contaminant plants from commercially grown Windsor farm.

P2, P3, and P9, expected to C. dactylon, were similar to one another and P5 and P13 , presuposed to hybrid, also appeared to be closely related (Fig. 3.34). SA 80210A, SA

80211B, SA 80212C, SA 80213D and SA 80214E are breeding from StrathAyr Turf

Systems, Seymour, Victoria.

009 010 A B C D E P1 P2 P3 P5 P9 P13

2000bp 1650bp 1000bp 850bp 650bp 500bp 400bp

300bp

200bp 100bp

Fig. 3.34 Band patterns from some of the unknown Couch grass samples. Primer: UBC#9 (842), Size marker: 1 kb plus DNA ladder. Non-denaturing PAGE, Optimal PCR conditions were used (Section 3.2.7). Cultivar abbreviations are shown in Appendix B.

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3.5.4 Phylogenetic relationships of Couch grass cultivars

Phylogenetic construction for genetic diversity of Couch grass cultivars can be established with some statistical analysis.

3.5.4.1 Data matrices of Couch grass cultivars

After the identification of polymorphic and monomorphic bands for all informative primers, the presence (1) or absence (0) of a band was scored to create a data matrix.

The size of bands was determined using Quantity one 1-D analysis software (Bio-Rad,

USA) and comparison to the size marker. However, because the software does not always accurately line up the bands with the marker, all size assignments were visually and manually double checked. Tables 3.20 and 3.21 are examples of the data matrices produced from primer 811 for the two detection methods. All data matrices are shown in

Appendix G.

Table 3.20 Data matrix of Couch grass from primer UBC#9 (811) from agarose gel electrophoresis

Name Band size (bp) (Abbr.) 1998 1670 1637 1533 1418 1415 1259 1150 1100 936 846 789 769 653 585 537 469 Com 1 01 0 1 00101000 1 0 01 Co 1 01 0 0 00101001 1 1 01 Ct2 1 01 0 1 00101010 1 0 00 Fr 1 00 1 1 01101010 0 1 11 Glp 1 01 0 1 01101101 1 1 11 Ha 1 01 0 0 01101101 1 1 11 Jt 1 1 01 1 1 01101110 1 1 01 Lg 1 01 1 1 01101000 0 1 01 Np 1 01 1 0 00101010 1 1 01 Pl 1 01 0 1 00100110 1 1 01 Re 1 01 0 0 00101101 1 1 01

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Table 3.20 countinued

Name Band size (bp) (Abbr.) 1998 1670 1637 1533 1418 1415 1259 1150 1100 936 846 789 769 653 585 537 469 Rss 1 01 0 0 01100101 1 1 11 Rc 1 01 1 0 11101111 0 1 00 Ws 1 01 1 0 11101111 1 1 01 Wt 1 01 1 0 11101111 1 1 01 Ss2 1 01 0 0 01101001 1 1 11 038 1 01 1 0 10100000 1 0 00 133 1 01 1 0 01100101 1 1 00 195 1 01 1 0 01100101 1 1 01 Con 0 01 1 0 01000000 0 1 00 Tw 1 01 1 0 01000000 0 1 00 Tl 1 0 00 0 0 01100000 1 1 00 Tl 2 0 01 1 0 01101000 1 0 00 Td(t) 0 01 1 0 01101000 1 0 00 Td(j) 0 01 1 0 00101000 1 0 00 001 0 01 1 0 01101000 1 0 00 Fd 0 01 1 0 01101000 1 0 00 Tg 0 01 1 0 01101000 1 0 00 Ts 0 01 1 0 01000100 0 1 00 Te 0 01 1 0 01101000 1 0 00 Ms 0 01 1 0 01101000 1 0 00 Ch 0 01 1 0 01101000 1 0 00 200 1 01 1 0 01000000 0 1 00 Sa 0 01 1 0 01000000 0 1 00 Tv 0 01 1 0 01000000 0 1 00 Gp 0 00 0 0 01100010 1 1 00 Kgs 1 01 1 0 11100010 1 1 00 009 0 01 1 0 11010000 1 0 00 010 0 01 1 0 11010100 1 1 00 210a 0 10 0 0 11101000 0 0 00 211b 0 00 0 0 11101000 0 1 00 212c 0 10 1 0 01100000 1 1 00 213d 0 10 1 0 01000000 0 0 00 214e 0 10 0 0 01100000 1 0 00 P1 1 00 0 0 01100000 0 0 00 P2 0 01 1 0 11000100 1 1 00 P3 0 01 1 0 11000100 1 1 00 P5 0 00 0 0 11011000 1 1 00 P9 0 01 1 0 11000100 1 1 00 P13 0 00 0 0 11011000 1 1 00 Cultivar abbreviations are shown in Appendix B

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Table 3.21 Data matrix of Couch grass from primer UBC#9 (811) and non-denaturing PAGE

Name Band size (bp) (Abbr.) 2129 1925 1837 1813 1800 1794 1768 1707 1620 1598 1519 1517 1437 1440 1393 1328 1356 1242 1187 1169 1110 990 970 930 954 900

Com 0 0 10 0 0 000010000001 0 0 1 1 1010

Co 0 0 10 0 1 000010100000 0 1 0 1 1010

Ct2 0 0 00 0 1 100000100001 0 1 0 1 1010

Fr 0 0 00 0 0 100001000001 0 1 0 1 1100

Glp 0 0 10 0 0 100000000001 0 1 0 1 1010

Ha 0 0 10 0 0 100000000001 0 1 0 1 1010

Jt 1 0 0 10 0 0 100000000001 0 1 0 1 1000

Lg 0 0 10 0 1 000010100001 0 1 0 1 1010

Np 0 0 00 0 0 000011000001 0 1 0 1 1000

Pl 0 0 10 0 1 000010100001 0 1 0 1 1000

Re 0 0 10 0 1 000010100000 0 1 0 1 1010

Rss 0 0 10 0 1 000000100001 0 0 0 1 1010

Rc 0 0 10 0 0 100010000001 0 1 0 0 1000

Ws 0 0 10 0 0 100010000101 0 1 0 0 0000

Wt 0 0 10 0 0 100010000001 0 1 0 0 0000

Ss2 0 0 10 0 0 100010000001 0 1 0 1 1010

038 0 0 10 0 0 000010000000 0 1 0 0 0000 133 0 0 11 0 0 000010000001 0 1 0 0 0010

195 0 0 10 0 0 000010000100 0 1 0 0 0010

Con 1 0 10 0 0 100010000001 0 1 0 0 1010

Tw 1 0 10 0 0 100010000001 0 0 0 0 0000

Tl 1 0 0 00 0 0 000000000001 0 1 0 1 0010

Tl 2 0 0 10 0 0 100000000001 0 1 0 1 0010

Td(t) 0 0 10 0 0 100000000001 0 1 0 1 0010

Td(j) 0 0 10 0 0 100000000001 0 1 0 1 0010

001 0 0 10 0 0 000100000001 0 1 0 1 0010

Fd 0 0 10 0 0 100000000001 0 1 0 1 0010

Tg 0 0 10 0 0 100000000001 0 1 0 1 0010

Ts 0 1 10 0 0 100100000000 1 0 0 0 0000

Te 0 0 10 0 0 100000000001 0 1 0 1 0010

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Table 3.21 continued

Name Band size (bp) (Abbr.) 2129 1925 1837 1813 1800 1794 1768 1707 1620 1598 1519 1517 1437 1440 1393 1328 1356 1242 1187 1169 1110 990 970 930 954 900

Ms 0 0 10 0 0 100000000001 0 1 0 1 0010 Ch 0 0 10 0 0 100000000001 0 1 0 1 0010 200 0 1 10 0 0 100100000000 1 0 0 1 1000 Sa 0 1 10 0 0 100100000000 1 0 0 1 1000 Tv 1 0 10 0 0 100000010000 0 1 0 0 1000 Gp 0 0 10 0 0 000000000001 0 1 0 0 0000 Kgs 0 0 00 1 0 000100000001 0 1 0 0 0000 009 0 0 00 0 0 100010000000 0 1 0 1 0000 010 0 0 00 0 0 100010000000 0 1 0 1 0000 210a 0 0 00 0 0 101000001000 0 1 0 0 0001 211b 0 0 00 0 0 000000001000 0 1 0 0 0001 212c 0 0 10 0 0 010010000000 0 1 0 0 0000 213d 0 1 10 0 0 001010000000 0 1 0 0 0001 214e 0 0 00 0 0 010010000100 0 1 0 0 0001 P1 0 1 10 0 0 010000000000 0 0 0 0 0000 P2 0 0 10 0 0 010010001000 0 1 0 1 0001 P3 0 0 10 0 0 010010001000 0 1 0 1 0001 P5 0 0 10 0 0 010010000000 0 0 0 0 1000 P9 0 0 10 0 0 010010001000 0 1 0 1 0001 P13 0 0 10 0 0 010010000000 0 0 0 0 1000

Table 3.21 continued

Name Band size (bp) (Abbr.) 884 871 855 800 757 717 651 627 644 634 614 598 570 550 541 537 534 486 480 404 175 Com 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0 0 0 0 1 0 1 Co 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 Ct2 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 Fr 1 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 1 0 0 1 Glp 0 0 1 0 0 0 1 0 1 0 0 1 0 0 0 0 0 0 1 0 1 Ha 0 0 1 0 0 0 1 0 1 0 0 1 0 0 0 0 0 0 1 0 1 Jt1 1 0 0 0 1 0 1 1 0 0 0 1 0 0 0 0 0 0 1 0 1 Lg 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 1 Np 0 0 0 1 1 0 1 1 0 0 0 1 0 0 0 0 0 1 0 0 0 Pl 1 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 1 0 Re 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1

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Table 3.21 countinued

Name Band size (bp)

(Abbr.) 884 871 855 800 757 717 651 627 644 634 614 598 570 550 541 537 534 486 480 404 175 Rss 0 0 1 0 0 0 1 0 1 0 0 1 0 0 0 0 0 0 1 1 1 Rc 0 1 0 0 1 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 Ws 1 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0 0 0 1 1 1 Wt 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1 0 Ss2 0 0 1 0 0 0 1 0 1 0 0 1 0 0 0 0 0 0 1 1 1 038 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1 1 133 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1 0 195 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Con 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 Tw 0 1 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 Tl1 0 1 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 1 1 0 Tl2 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 Td(t) 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 Td(j) 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 001 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 Fd 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 Tg 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 Ts 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 Te 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 Ms 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 200 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 Sa 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 Tv 0 1 0 0 0 0 1 0 0 1 0 0 0 0 0 0 1 0 0 0 0 Gp 0 1 0 0 0 0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 Kgs 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 009 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1 0 010 0 1 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 1 1 1 210a 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 211b 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 212c 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 213d 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 214e 0 0 0 0 1 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 P1 0 0 1 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 P2 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 1 0 P3 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 1 0 P5 0 1 0 0 1 0 1 0 0 0 0 1 0 0 0 0 0 0 0 1 0 P9 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 1 0 P13 0 1 0 0 1 0 1 0 0 0 0 1 0 0 0 0 0 0 0 1 0 Cultivar abbreviations are shown in Appendix B

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3.5.4.2 Distance matrices of Couch grass cultivars

Distance matrices were constructed based on the data matrices using the phylogenetic software package PAUP v4.010b (Swoffond, 1998). C. transvaalensis was transferred to an outgroup leaving the number of ingroup taxa as 49. Like the distance matrices of

Buffalo grass cultivars, the distance matrices of the Couch grass cultivars contained the

Total Character Differences and Mean Character Differences. The distance matrices from agarose gel electrophoresis and non-denaturing PAGE are shown in Appendix E because of their large size. The distance matrices were used for clustering analysis.

3.5.4.3 Clustering analysis and phylogenetic construction of Couch grass cultivars

The Neighbour-joining algorithm of Saitou and Nei (1987) was used for clustering analysis and generation of phylogenetic trees in this study. The algorithm was part of the PAUP software package. A separate tree was created for each of the two electrophoresis and detection methods. Evaluation of the robustness in each branch was performed using Bootstrap value with 1000 re-samplings. The resulting dendograms are shown in Figures 3.35 and 3.36. They show a clear bifurcation between the C. dactylon cultivars and the hybrids.

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Com Jt1 77 Co 52 Re Pl 94 Glp 58 Ha 99 Ss2 Rss Lg Np 58 Ct2

71 Fr 92 133 195 67 Rc Wt Ws 038 Tl1 P1 210a 211b 212c 214e Tl2 Ch Td(t) 100 Fd Tg 100 Te Ms Td(j) 001 100 P5 P13 89 Gp Kgs 75 009

98 010 P2 53 100 P3 P9 213d Con 70 76 Tw 54 Sa 53 Ts 200 Tv

Fig 3.35 Neighbour-Joining dendogram (unrooted, cladogram) of Couch grass cultivars generated from agarose gel electrophoresis data. Software: PAUP v4.010b, Bootstrap values are shown above each internode. Green line: C. transvaalensis, Red line: hybrids, Blue line: unknown samples, Black line: C. dactylon group. Cultivar abbreviations are shown in Appendix B.

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Com Jt1 Co Re Glp Ha Ss2 Rss Pl Lg Np Ct2 Fr Rc Con Tw Ws 038 Wt 133 195 009 010 P2 P3 P9 213d 210a 211b 212c 214e P1 P5 P13 Tl1 Tl2 Td(t) Td(j) Fd Tg Te Ms Ch 001 Gp Kgs Ts 200 Sa Tv

Fig 3.36 Neighbour-joining dendogram (unrooted, cladogram) of Couch grass cultivars generated from non-denaturing PAGE data. Software: PAUP v4.010b, Bootstrap value are shown above each internode. Green line: C. transvaalensis, Red line: hybrids, Blue line: unknown samples, Black line: C. dactylon group. Cultivar abbreviations are shown in Appendix B.

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Although superficially similar the two dendograms localized differences, interestingly,

Contaminant (Co) and Tifway (Tw) were grouped with Royal Cape (Rc) and closely related to Wintergreen (Wt) and Windsor Green (Ws) which are C.dactylon from non- denaturing PAGE data. The two samples were clustered one of the hybrid groups from the dendogram from agarose gel electrophoresis data. TifSport, WS200, Santa Ana were appeared as outgroup like C. transvaalensis.

According to the Neighbour-Joining (NJ) dendograms, TifsPort, Santa Ana, and WS200 are more closely related to C. transvaalensis than the other hybrids. For example, Santa

Ana had bright green colour leaf texture. It is supposed to be inherited from C. transvaalensis. Interestingly, Tifway was close to C. transvaalensis using DAF

(Caetano-Anollés et al., 1995), but Tifway was placed within the C. dactylon group using AP-PCR (Ho, 1999). ISSR-PCR gave both results. The Tifway hybrid belonged to the group that was closely related to C. transvaalensis on the agarose gel electrophoresis, but was placed in one of the C. dactylon groups with Wintergreen and

Windsor Green by non-denaturing PAGE. It was hard to determine which relationship was correct. The Couch grass samples PCR-products were separated on mini agarose gels with only 20 wells and mini polyacrylamide gels with 15 wells. The Tifway result may have been more definitive on a larger gel.

Within C. dactylon cultivars, ISSR-PCR analysis demonstrated good genetic variation, with many polymorphic bands confirming the genetic differences within C. dactylon cultivars. Legend Couch was discovered during a late 1980s trial project by Turfgrass

Technology funded through the Melbourne Cricket Club. Legend Couch was closely related to the ‘National Park’ cultivar in this study.

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Wintergreen and its irradiation derivative, Windsor Green, were difficult to differentiate using isoenzyme analysis (McMaugh, 1993a). McMaugh (1993b) found that a RAPD primer produced an additional band at 950 bp in Wintergreen, but not Windsor Green.

Likewise, some polymorphic bands were also shown by AP-PCR analysis (Ho, 1999).

ISSR-PCR analysis produced a lot of polymorphic bands which differentiated between

Wintergreen and Windsor Green couch cultivars. Probably the result is caused by a mutation of repeat sequences. Genomic regions containing microsatellites are evolving and mutation occurs more rapidly than in other areas (Levinson and Gutman, 1987).

Windsor Green is an irradiated mutant with possible mutations in the microsatellite regions. ISSR primers seem to produce more specific markers to distinguish between the two cultivars than the other genetic analyses.

Greenlees Park couch was one on the first of the new breed of finer leaf couch and was originally selected from Greenlees Park Bowling Club in Concord, Sydney in 1996

(Jimboombaturf, 2002). Ho (1999) mentioned that the cultivar was a hybrid which clustered in the hybrid group of the phylogenetic tree using AP-PCR analysis, but found that the cultivar was clustered with the C. dactylon group using ITS sequence variation.

The two phylogenetic trees produced in this study showed it to be very closely related to

Hatfield and SS2 that are found in the C. dactylon group. It could be considered that

Greenlees Park Couch is suitable using ISSR-PCR analysis and ITS sequence analysis rather than using AP-PCR for its identification. In conclusion more tests may be needed to confirm its standing and other Couch grass cultivars.

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Within the hybrid grasses, five hybrids, Santa Ana, TifSport, WS200, Contaminant and

Tifway, were grouped as seen on agarose gel electrophoresis. However, the hybrids were divided into two groups on non-denaturing PAGE. One group contained Santa Ana,

TifSport and WS200 as an out group and the other group contained Contaminant and

Tifway clustered in the C. dactylon group.

Interestingly, TL1 cultivar was not found in the hybrid groups on either dendogram.

Although TL1 was selected from a sward of the hybrid Bermuda grass ‘Tifgreen’, its inflorescence structure (4, not 3, racemes per inflorescence) and agronomic attributes

(e.g. its tolerance to certain herbicides) are consistent with a chance seedling of

Cynodon dactylon rather than a mutant plant of hybrid (C. dactylon x C. transvaalensis) origin (Loch and Roche, 2003e). The DNA profile results also support this suggestion.It will be accurate worth more testing for identification of the cultiar.

Tifway solved many of the weed problems associated with common couch grass and saved millions of dollars required for weed control (Burton, 1992). ISSR primers discriminated the Tifway cultivar from other hybrids, especially primer 827 which produced a unique specific marker at 1409 bp (Table 3.19). Tifdwarf is a presumed spontaneous mutation of Tifgreen (Burton, 1991). Ho (1999) reported that AP-PCR diagnostic markers that could distinguish between Tifgreen and Tifdwarf. Unfortunately, in this study no specific markers could differentiate between Tifdwarf and Tifgreen.

FloraDwarf is one of the new “ultra-dwarf’ selections developed for putting greens. It is dense and low growing (Burton, 1991). The four ‘ultra-dwarf’ cultivars (Champion

Dwarf, MS-Supreme, FlorDwarf and TifEagle) have been differentiated by

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CHAPTER THREE: RESULTS morphological and developmental characters (Roche and Loch, 2005). They showed slower vertical tension and produced fewer inflorescences than Tifdwarf, Tifgreen and

TL2 (Novotek). In unmown swards, the four ultra-dwarfs produced shorter leaves than

Tifgreen and Tifdwarf. However, undermown condition the comparison was failed. It has been reported that FloraDwarf differed from Tifdwar and Tifgreen based on DNA analyses conducted at the Universities of Florida and Tennessee (Dudeck and Murdoch,

1997). However, there was no specific marker to differentiate between Tifgreen,

FloraDwarf, TifEagle, MS-Supreme, and Champion Dwarf was found. Other untested primers may be better or sequencing of the PCR fragments could yield the necessary result.

PBR2, PBR3 and PBR9 were expected to Windsor Green type (Loch, pers. Common,

2002). However, the group was far from the Windsor Green group, although the cultivars clustered in C. dactylon. PBR5 and PBR 13 were supposed to hybrid. From the dendogram, the two cultivars were slightly clusterd to hybrid group. It could be re- tested for further accurate result.

The Bootstrap values were significant results. Most of values were quite great (>50%).

The Bootstrap values of the branches were greater from non-denaturing PAGE than the other dendograms. Therefore, the structure of the phylogenetic tree from the non- denaturing PAGE is probably the most robust. Using these phylogenetic relationships of the Couch grass cultivars, it should be relatively easy to fingerprint unidentified individuals or cultivars.

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3.5.5 Comparison of detection methods

The two detection methodologies used in this study were directly compared using a few specific examples that appeared to give anomalous results. An example can be seen in

Figure 3.37. Primer 808 gave a “doublet” at 1560 and 1483 bp on non-denaturing PAGE in Greenlees Park and Hatfield cultivars. Independent DNA isolation and PCR amplification gave identical results.

Glp Ha Glp Ha

2000 bp 1650 bp 1560bp 1483bp 1000 bp Fig. 3.37 Comparison of band patterns 850 bp between agarose gel electrophoresis and 650 bp 500 bp non-denaturing PAGE. Primer: UBC#9 (808). 400 bp Size marker: 1kb plus DNA ladder. (A): Agarose gel 300 bp electrophoresis, (B): Non-denaturing PAGE. 200 bp Optimal PCR conditions were used (Section 3.2.7). 100 bp Cultivar abbreviations are shown in Appendix B.

(A) (B)

As was mentioned in Section 3.4.5, polymorphisms are detected based on size differences. Therefore, it is important how these bands better appear and how theses bands size are accurate for cultivar identification. However, when distances between each cultivar were checked, some distances were numerically higher from agarose gel electrophoresis thab non-denaturing PAGE. Moreover, the Bootstrapping values of the non-denaturing PAGE data were consistently better than the agarose gel electrophoresis data. Therefore, it could be debated to the comparison of visualization methodologies for genetic identification.

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CHAPTER FOUR : CONCLUSION

4.1. Cultivar identification of turf grasses using ISSR-PCR

Turf grass has offered improved and beautiful environment for human beings. The values of turf varieties are based on the different environments. Although many turf grass varieties have been commercially released and development of improved varieties continues to-day. During improvement of turf grasses, misidentification and mislabeling of the genotype will result in lost time and money. Therefore, correct and appropriate identification of cultivars is required to ensure authenticity of genotypes.

Two turf grasses – Buffalo (Stenotaphrum secundatum) and Couch (Cynodon dactylon) grasses – both popular in Australia were used for this study. These two species are warm-season turf grass and have now adapted to the Australia environment. Many

Buffalo and Couch grass varieties need to be protected for their economic value to the breeder. Plant Breeder Rights (PBRs) legislation protects new plant cultivars in

Australia. The PBR scheme requires careful and thorough descriptions of morphological and other characteristics. However, it has become more difficult to differentiate cultivars because of their similar phenotypes. Therefore techniques that differentiate on the bases of genotype have great potential in PBR criteria.

ISSR-PCR analysis is one fingerprinting technology and is based on polymorphisms related to simple sequence repeats. This was investigated as to its suitability for Buffalo and Couch grass cultivar identification and genetic diversity. ISSR marker could offer great potential for differentiating closely related turf grass cultivars.

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All Buffalo grass cultivars in this study were differentiated and new insights into their genetic relationships identified using ISSR-PCR analysis. Further analysis of the genetic relationships should give valuable management to the development of better varieties.

FISSR analysis also produced a pleasing number of polymorphic bands using only two fluorescent primers. It is expected to be vary cost and time-effective. Moreover, the cultivars from the US genetic varieties and Lower Hunter Valley, NSW were clearly separated by the ISSR primers. So far as known, the ISSR-PCR analysis is the first marker system that differentiates Buffalo grass cultivars from another.

Couch grass cultivars have been genetically selected and improved all over the world.

ISSR-PCR analysis also allowed data for a large number of Couch grass cultivars in this study. C. dactylon, C. transvaalensis, and their hybrids were clearly separated from one another. This is the first report to use ISSR–PCR for the Couch grass identification.

Disappointingly, there was not a large number of polymorphic bands to differentiate within the hybrids. This group may require the used of a different type of molecular analysis. Alternatively further ISSR-type primers could be investigated. There was not sufficient time to trial the two 6-FAM labelled primers with the Couch grass samples.

This would be a high priority for future work as would 6-FAM labeling of other selected informative primers.

The ISSR-PCR analysis described here gave informative genetic relationships whithin

Buffalo and Couch grass cultivars. The banding patterns generated by ISSR-PCR analysis will be valuable for the identification and certification of mislabeled plant materials and contaminated sod field. In conclusion, ISSR-PCR analysis offers powerful and potential possibilities as a simple method like RAPD analysis, that is time and cost

129

CHAPTER FOUR: CONCLUSION effective. The analysis should provide better forensic evidence for plant protection and trading relationships among countries.

130

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147

APPENDICES

APPENDIX A Buffalo grass cultivars used in this study NO SPECIES NAME Abbre. CULTIVAR NAME SOURCE

1 Stenotaphrum secundatum GGR GGR 02/101 DPI

2 Stenotaphrum secundatum PA Palmetto™ DPI

3 Stenotaphrum secundatum SM Shadmaster DPI

4 Stenotaphrum secundatum SW Sir Walter DPI

5 Stenotaphrum secundatum ST15 ST-15 DPI

6 Stenotaphrum secundatum ST26 ST-26 DPI

7 Stenotaphrum secundatum ST85 ST-85 DPI

8 Stenotaphrum secundatum ST91 ST-91 DPI

9 Stenotaphrum secundatum B12 B12 DPI

10 Stenotaphrum secundatum VET Velvet DPI

DPI : Queensland Department of Primary Industries (Redlands Research Station)

Appendix B List of couch grass cultivars used in this study

NO SPECIES NAME Abbre. CULTIVAR NAME SOURCE

1 Cynodon dactylon Com Common (ex. Jimboomba Turf) DPI 2 Cynodon dactylon Co Conquest™ Windsor 3 Cynodon dactylon Ct2 CT-2 DPI 4 Cynodon dactylon Fr FLoraTex TM DPI 5 Cynodon dactylon Glp Greenlees Park DPI 6 Cynodon dactylon Ha Hatfield DPI 7 Cynodon dactylon Jt1 JT-1 DPI 8 Cynodon dactylon Lg Legend TM (=c1) DPI 9 Cynodon dactylon Np National Park DPI 10 Cynodon dactylon Pl Plateau DPI 11 Cynodon dactylon Re Riley's Evergreen (=Conquest™) DPI 12 Cynodon dactylon Rss Riley's Super Sport DPI 13 Cynodon dactylon Rc Royal Cape DPI 14 Cynodon dactylon Ws Windsor Green DPI 15 Cynodon dactylon Wt Wintergreen DPI 16 Cynodon dactylon Ss2 SS2 DPI 17 Cynodon dactylon 038 WS 038 DPI

APPENDICES

Appendix Continued NO SPECIES NAME Abbre. CULTIVAR NAME SOURCE 18 Cynodon dactylon 133 WS 133 DPI 19 Cynodon dactylon 195 WS 195 DPI 20 Cynodon dactylon x transvaalensis Con Contaminant (C3 plot) DPI 21 Cynodon dactylon x transvaalensis Tw Tifway (=Tifton 419) DPI 22 Cynodon dactylon x transvaalensis Tl 1 TL 1 DPI 23 Cynodon dactylon x transvaalensis Tl 2 TL 2 DPI 24 Cynodon dactylon x transvaalensis Td(t) Tifdwarf (=Toowoomba form) DPI 25 Cynodon dactylon x transvaalensis Td(j) Tifdwarf (=Jindalee form) DPI 26 Cynodon dactylon x transvaalensis 001 Ws 001 DPI 27 Cynodon dactylon x transvaalensis Fd FloraDwarf TM DPI 28 Cynodon dactylon x transvaalensis Tg Tifgreen (= tifton 328) DPI 29 Cynodon dactylon x transvaalensis Ts TifSport™ (= Tift 94) DPI 30 Cynodon dactylon x transvaalensis Te TifEagle DPI 31 Cynodon dactylon x transvaalensis Ms MS-Supreme DPI 32 Cynodon dactylon x transvaalensis Ch Champion Dwarf DPI 33 Cynodon dactylon x transvaalensis 200 WS 200 DPI 34 Cynodon dactylon x transvaalensis Sa Santa Ana DPI 35 Cynodon transvaalensis Tv (ex Kew Golf Club, Melbourne) DPI 36 Cynodon dactylon Gp Gabba Pitch Couch DPI 37 Cynodon dactylon Kgs Gabba Special Couch DPI 38 Cynodon dactylon 009 DN 009 D. Nickson 39 Cynodon dactylon 010 DN 010 D. Nickson 40 Cynodon dactylon 210a SA 80210A StrathAyr 41 Cynodon dactylon 211b SA 80211B StrathAyr 42 Cynodon dactylon 212c SA 80212C StrathAyr 43 Cynodon dactylon 213d SA 80213D, StrathAyr 44 Cynodon dactylon 214e SA 80214E, StrathAyr 45 Cynodon dactylon (?) P1 PBR1 (Greenlees Park type) DPI 46 Cynodon dactylon (?) P2 PBR2 (Windsor Green type) DPI 47 Cynodon dactylon (?) P3 PBR3 (Windsor Green type) DPI 48 Cynodon dactylon x transvaalensis (?) P5 PBR5 (hybrid type) DPI 49 Cynodon dactylon (?) P9 PBR9 (Windsor Green type) DPI 50 Cynodon dactylon x transvaalensis (?) P13 PBR13 (hybrid type) DPI DPI : Queensland Department of Primary Industries (Redlands Research Station) Windsor: Windsor Turf (Windsor, NSW) StrathAyr: StrathAyr Turf Systems (Seymour, Victoria) D. Nickson (Frankston, Victoria)

vii

APPENDICES

Appendix C

UBC#9 ISSR primers used in this study

Primer Primer Sequence Sequence Number Number

801 ATATATATATATATATT 851 GTGTGTGTGTGTGTGTYG 802 ATATATATATATATATG 852 TCTCTCTCTCTCTCTCRA 803 ATATATATATATATATC 853 TCTCTCTCTCTCTCTCRT 804 TATATATATATATATAA 854 TCTCTCTCTCTCTCTCRG

805 TATATATATATATATAC 855 ACACACACACACACACYT

806 TATATATATATATATAG 856 ACACACACACACACACYA 807 AGAGAGAGAGAGAGAGT 857 ACACACACACACACACYG 808 AGAGAGAGAGAGAGAGC 858 TGTGTGTGTGTGTGTGRT 809 AGAGAGAGAGAGAGAGG 859 TGTGTGTGTGTGTGTGRC 810 GAGAGAGAGAGAGAGAT 860 TGTGTGTGTGTGTGTGRA 811 GAGAGAGAGAGAGAGAC 861 ACCACCACCACCACCACC 812 GAGAGAGAGAGAAGAA 862 AGCAGCAGCAGCAGCAGC 813 CTCTCTCTCTCTCTCTT 863 AGTAGTAGTAGTAGTAGT 814 CTCTCTCTCTCTCTCTA 864 ATGATGATGATGATGATG 815 CTCTCTCTCTCTCTCTG 865 CCGCCGCCGCCGCCGCCG 816 CACACACACACACACAT 866 CTCCTCCTCCTCCTCCTC 817 CACACACACACACACAA 867 GGCGGCGGCGGCGGCGGC 818 CACACACACACACACAG 868 GAAGAAGAAGAAGAAGAA 819 GTGTGTGTGTGTGTGTA 869 GTTGTTGTTGTTGTTGTT 820 GTGTGTGTGTGTGTGTC 870 TGCTGCTGCTGCTGCTGC 821 GTGTGTGTGTGTGTGTT 871 TATTATTATTATTATTAT 822 TCTCTCTCTCTCTCTCA 872 GATAGATAGATAGATA 823 TCTCTCTCTCTCTCTCC 873 GACAGACAGACAGACA

824 TCTCTCTCTCTCTCTCG 874 CCCTCCCTCCCTCCCT 825 ACACACCACACACACT 875 CTAGCTAGCTAGCTAG 826 ACACACACACACACACC 876 GATAGATAGACAGACA 827 ACACACACACACACACG 877 TGCATGCATGCATGCA 828 TGTGTGTGTGTGTGTGA 878 GGATGGATGGATGGAT 829 TGTGTGTGTGTGTGTGC 879 CTTCACTTCACTTCA 830 TGTGTGTGTGTGTGTGG 880 GGAGAGGAGAGGAGA

viii

APPENDICES

Continued

Primer Primer Sequence Sequence Number Number

831 ATATATATATATATATYA 881 GGGTGGGGTGGGGTG 832 ATATATATATATATATYC 882 VBVATATATATATATAT 833 ATATATATATATATATYG 883 BVBTATATATATATATA 834 AGAGAGAGAGAGAGAGYT 884 HBHAGAGAGAGAGAGAG 835 AGAGAGAGAGAGAGAGYC 885 BHBGAGAGAGAGAGAGA 836 AGAGAGAGAGAGAGAGYA 886 VDVCTCTCTCTCTCTCT 837 TATATATATATATATART 887 DVDTCTCTCTCTCTCTC 838 TATATATATATATATARC 888 BDBCACACACACACACA 839 TATATATATATATATARG 889 DBDACACACACACACAC 840 GAGAGAGAGAGAGAGAYT 890 VHVGTGTGTGTGTGTGT 841 GAGAGAGAGAGAGAGAYC 891 HVHTGTGTGTGTGTGTG 842 GAGAGAGAGAGAGAGAYG 892 TAGATCTGATATCTGAATTCCC 843 CTCTCTCTCTCTCTCTRA 893 NNNNNNNNNNNNNNN 844 CTCTCTCTCTCTCTCTRC 894 TGGTAGCTCTTGATCANNNNN 845 CTCTCTCTCTCTCTCTRG 895 AGAGTTGGTAGCTCTTGATC 846 CACACACACACACACART 896 AGGTCGCGGCCGCNNNNNNATG 847 CACACACACACACACARC 897 CCGACTCGAGNNNNNNATGTGG 848 CACACACACACACACARG 898 GATCAAGCTTNNNNNNATGTGG 849 GTGTGTGTGTGTGTGTYA 899 CATGGTGTTGGTCATTGTTCCA 850 GTGTGTGTGTGTGTGTYC 900 ACTTCCCCACAGGTTAACACA

FISSR Primers

811 GAGAGAGAGAGAGAGAC-6FAM 826 ACACACACACACACACC-6FAM

λ Primers

Primer1 GACATGGCTCGATTGGCGCG Primer2 ACGGCGTAATTCCGCATCAG N=(A,G,C,T), R=(A,G), Y=(C,T), B=(C,G,T)(i.e.not A), D=(A,G,T)(i.e.not C) H=(A,C,T), V=(A,C,G)

APPENDICES

Appendix D

Distance matrix of Couch grass cultivars generated from agarose gel electrophoresis

On CD-ROM (File name: Appendix D.xls)

Appendix E

Distance matrix of Couch grass generated by non-denaturing PAGE

On CD-ROM (File name: Appendix E.xls)

Appendix F

Data matrices of Buffalo grass cultivars by three detection methods

(Agarose gel electrophoresis, non-denaturing PAGE, FISSR analysis)

On CD-ROM (File name: Appendix F (DATA matrix).xls)

Appendix G

Data matrices of Couch grass cultivars by two detection methods

(Agarose gel electrophoresis and non-denaturing PAGE)

On CD-ROM (File name: Appendix G (DATA matrix).xls)

Appendix H

The banding profiles of Buffalo grass cultivars

On CD-ROM (File name: Appendix H (Buffalo grass).ppt)

Appendix I

The banding profiles of Couch grass cultivars

On CD-ROM (File name: Appendix I (Couch grass).ppt)