Evolution and Spread of Glyphosate Resistant Barnyard Grass (Echinochloa Colona (L.) Link) from Australia

Evolution and Spread of Glyphosate Resistant Barnyard Grass (Echinochloa colona (L.) Link) from Australia

By Thai Hoan Nguyen

This thesis is submitted in fulfilment of the requirements for the degree of Doctor of Philosophy

School of Agriculture, Food and Wine Faculty of Sciences The University of Adelaide Waite Campus

March, 2015

Abbreviations

ACCase: Acetyl-CoA carboxylase

AFLP: Amplified fragment length polymorphism

AGRF: Australian Genome Research Facility

ALS: Acetolactate synthase

EPSP: 5-enolpyruvylshikimate-3-phosphate synthase

HAT: Hour after treatment

LD50: Lethal dosage (dose required to control 50% of individuals in the population)

LSD: Least significant different

NSW: New South Wales

PCR: Polymerase chain reaction

QLD: Queensland

R/S: Resistance/susceptibility

RAPD: Randomly amplified polymorphic DNAs

RFLP: Restriction fragment length polymorphism

SA: South Australia

SE: Standard error

SSR: Simple sequence repeats

VIC: Victoria

WA: Western Australia

Table of Contents

Abbreviations ...... i

Table of contents ...... ii

List of tables ...... viii

List of figures ...... x

Abstract ...... xii

Declaration ...... xiv

Tables Published with Consent from Copyright Holders in this Thesis ...... xv

Figures Published with Consent from Copyright Holders in this Thesis ...... xv

Acknowledgements ...... xvi

Chapter 1: General Introduction ...... 1

Chapter 2: Literature Review ...... 6

2.1 Introduction ...... 6

2.2 Echinochloa spp...... 6

2.2.1 Geographical distribution of Echinochloa spp. in the world ...... 6

2.2.2 Biology ...... 8

2.2.3 Agronomical features ...... 8

2.2.4 Problems caused by Echinochloa spp. in Australia ...... 9

2.2.5 Herbicide resistance in Echinochloa spp ...... 10

2.2.6 Herbicide resistance in weed species in Australia ...... 11

2.3 Causes of resistance evolution ...... 13

2.3.1 Genetic mutations endow resistance ...... 13

2.3.2 Initial frequency of resistant alleles ...... 14

2.3.3 Selection pressure ...... 14

2.3.4 Inheritance of resistance ...... 15

2.3.5 Gene migration ...... 15

2.3.6 Fitness of resistant individuals ...... 16

2.3.7 Characteristics of the seed bank ...... 17

2.4 Glyphosate ...... 17

2.4.1 Properties of glyphosate...... 17

2.4.2 Mode of action ...... 19

2.4.3 Glyphosate resistant weeds ...... 20

2.4.4 Mechanisms of glyphosate resistance ...... 20

2.5 Molecular markers ...... 22

2.5.1 Scientific basis of the use of molecular makers in determining the spread of resistance in Echinochloa spp...... 22

2.5.2 DNA fingerprinting techniques ...... 22

2.5.3 DNA sequencing ...... 24

2.6 Conclusions ...... 25

Literature cited ...... 26

Chapter 3: Genetic Diversity of Glyphosate Resistant Junglerice (Echinochloa colona) in New South Wales and Queensland...... 35

Materials and methods ...... 37

Plant material ...... 37

Glyphosate dose response experiment ...... 40

AFLP analysis ...... 41

Results and discussion ...... 43

Response to glyphosate ...... 43

AFLP analysis ...... 45

Genetic diversity across E. colona populations ...... 45

Genetic diversity within populations ...... 48

Acknowledgements ...... 53

Literature cited ...... 53

iii

Chapter 4: Temperature Influences the Level of Glyphosate Resistance in Barnyard Grass (Echinochloa colona) ...... 58

Abstract ...... 58

1 Introduction ...... 59

2 Materials and methods ...... 60

2.1 Plant material ...... 60

2.2 Temperature response to glyphosate...... 60

2.3 Identifying target-site mutations ...... 61

2.4 EPSPS gene relative copy number ...... 62

2.5 Shikimate assay ...... 64

2.6 Effect of temperature on absorption and translocation of glyphosate ...... 65

3 Results ...... 66

3.1 Temperature response experiments ...... 66

3.2 Target-site mutations...... 69

3.3 EPSPS gene copy number ...... 70

3.4 Effect of temperature on shikimate accumulation ...... 70

3.5 14C-glyphosate absorption and translocation as affected by temperature ...... 71

4 Discussion ...... 73

4.1 Temperature influences glyphosate resistance ...... 73

4.2 Target-site contributes to glyphosate resistance ...... 74

4.3 14C-glyphosate absorption and translocation as affected by temperature ...... 74

5 Conclusions ...... 77

Acknowledgements ...... 78

References ...... 78

Chapter 5: Inheritance of Evolved Glyphosate Resistance in Barnyard Grass (Echinochloa colona) from Australia ...... 83

Abstract ...... 83

5.1 Introduction ...... 84

5.2 Materials and methods ...... 85

5.2.1 Plant material ...... 85

5.2.2 Gene flow between resistant and susceptible individuals ...... 86

5.2.3 Hand crossing of resistant and susceptible individuals ...... 88

5.2.4 Sequencing of F1 and F2 progenies ...... 88

5.2.5 Shikimate accumulation ...... 89

5.2.6 Segregation test ...... 90

5.2.7 Response to glyphosate ...... 91

5.2.8 EPSPS cDNA sequencing ...... 91

5.3 Results and discussion ...... 92

5.3.1 Plant growth of the parental populations ...... 92

5.3.2 Gene flow frequency ...... 94

5.3.3 Detecting EPSPS gene mutation in F1 and F2 progenies ...... 97

5.3.4 Shikimate assay ...... 97

5.3.5 Segregation test ...... 98

5.3.6 Dose response to glyphosate of F2 progenies ...... 100

5.3.7 EPSPS cDNA sequencing ...... 101

5.4 Conclusions ...... 103

Literature cited ...... 104

Chapter 6: General Discussion ...... 110

6.1 Discussion of results ...... 110

6.2 Conclusions ...... 116

6.3 Contributions to knowledge ...... 117

6.4 Future research ...... 117

Literature cited ...... 118

Appendices ...... 124

Appendix 1: Geographical sites of towns where are nearest to origins of 65 E. colona populations used in this research (Chapter 3) ...... 124

Appendix 2: Response of eleven E. colona populations to different glyphosate rates in the dose response experiment (Chapter 3) ...... 125

Appendix 3: Distance matrix from AFLPs based on jaccard’s coefficient in comparison between populations collected across Queensland and New South Wales, Australia (Chapter 3) ...... 126

Appendix 4: Distance matrix from AFLPs based on jaccard’s coefficient in comparison within populations collected in New South Wales, Australia (Chapter 3) ...... 131

Appendix 5: Number and name indexes of E. colona populations in Chapter 3 and Appendices 3 and 4 ...... 144

Appendix 6: Dendrogram of the partial sequence of the predicted amino acid at codon 106 in the EPSPS gene of the susceptible population (Echi S) and the resistant population (A533.1) (Chapter 4) ...... 145

Appendix 7: The sections of the treated leaf, the non-treated leaves, the stem and the roots of E. colona plants were cut at harvest time points of 12, 24, 48 and 72 hours after glyphosate application (Chapter 4) ...... 146

Appendix 8: Response of E. colona populations to glyphosate (240 g a.i. ha-1) at two different temperature levels (20 and 30oC) at three weeks after glyphosate application (Chapter 4) ...... 147

Appendix 9: The pair of resistant (A533.1) and susceptible (Echi S) E. colona individuals at flowering, and two single spikes of each resistant and susceptible individual were bagged with glassine bags as controls before anthesis in gene flow experiments (Chapter 5) ...... 148

Appendix 10: Survivors of E. colona in gene flow frequency experiment at 30 days after spraying glyphosate (Chapter 5) ...... 148

Appendix 11: Growth time, flower-head number, 100-seed weight and germinability of the resistant (A533.1) and the susceptible (Echi S) populations of E. colona in gene flow experiments (Chapter 5) ...... 149

Appendix 12: Number of E. colona plants before and after spraying glyphosate in the gene flow frequency experiment (Chapter 5) ...... 150

Appendix 13: UPGMA dendrogram showing the cDNA sequence groups of the EPSPS gene from five individuals in Table 5 (Chapter 5) ...... 151

vii

List of Tables

Chapter 2

Table 2.1 Documented herbicide resistance in weed species in Australia ...... 12

Chapter 3

Table 1 Geographical sites of towns where are nearest to origins of junglerice populations and resistance phenotype of populations used in this study with resistance that was determined by treating with glyphosate at 270 g a.e. ha-1 ...... 38

Table 2 AFLP adaptors and primers ...... 42

Table 3 The glyphosate resistance levels of ten junglerice populations ...... 44

Table 4 Between-population genetic structure: fragment lengths, total number of fragments, number and percentage of polymorphic fragments produced by each primer set used to analyse the polymorphisms of one individual from each of 62 junglerice populations ...... 46

Table 5 Within-population genetic structure: fragment lengths, total number of fragments, number and percentage of polymorphic fragments produced by each primer set used to analyse the polymorphisms of one individual from each of two glyphosate resistant junglerice populations (63 and 64) and one susceptible population (65) ...... 49

Chapter 4

Table 1 Locations are nearest to origins of E. colona populations used in this study ...... 60

viii

Table 2 The primers and probes used to identify the target-site mutation and determine the genomic copy number of EPSPS and ALS using quantitative real-time PCR ...... 63

Table 3 Glyphosate dose required to control 50% (LD50) (g a.e. ha-1) of susceptible and resistant E. colona populations at 20oC and 30oC was analysed using PriProbit ver. 1.63 with 95% confidence intervals ...... 69

Table 4 Nucleotide and predicted amino acid sequence of EPSPS DNA isolated from a susceptible and five resistant populations of E. colona ...... 70

Chapter 5

Table 1 Growth time (transplanting, flowering and harvest) of the resistant (A533.1) and the susceptible (Echi S) populations of E. colona in the gene flow experiment ...... 92

Table 2 Flower head number, 100-seed weight and germinability of the resistant (A533.1) and the susceptible (Echi S) populations of E. colona in the gene flow experiment ...... 93

Table 3 Survival of F1 progenies from four parental susceptible plants in the gene flow experiment to determine gene flow frequency between resistant (A533.1) and susceptible (Echi S) E. colona plants ...... 94

Table 4 Segregation of the F2 progenies from selfed F1 survivors of E. colona from the gene flow experiment after glyphosate treatment at of 240 g a.e. ha-1 ...... 99

Table 5 Mutations were detected at position 106 of the cDNA from EPSPS gene after cloning of two resistant and one susceptible

plants, and two F2 progenies of E. colona ...... 102

List of Figures

Chapter 2

Figure 2.1 Chemical structure of glyphosate ...... 18

Figure 2.2 Activity of glyphosate on reaction catalysed by enzyme 5-enolpyruvylshikimate-3-phosphate synthase ...... 19

Chapter 3

Figure 1 UPGMA phenogram of the genetic relationship between E. colona populations collected across QLD and NSW, Australia ...... 47

Figure 2 UPGMA phenogram showing the genetic relationship within two resistant populations (63 and 64 in Table 1) and the susceptible population (65) of E. colona collected from three separate fields in NSW, Australia ...... 50

Chapter 4

Figure 1 Response of E. colona populations to glyphosate at 20oC and 30oC ...... 68

Figure 2 Shikimic acid accumulation of leaf discs from two resistant (A533.1 and A818) and one susceptible (Echi S) E. colona populations at different glyphosate concentrations at 20oC and 30oC ...... 71

Figure 3 14C-glyphosate absorbed and translocated to plant sections of two resistant (A533.1 and A818) and one susceptible (Echi S) E. colona populations at 20oC and 30oC at 12, 24, 48 and 72 hours after glyphosate application ...... 72

Chapter 5

Figure 1 Survival percentage at 21 days after glyphosate treatment of the resistant (A533.1) and the susceptible (Echi S) populations of E. colona in the rate test ...... 93

Figure 2 The morphology of E. colona flowers at the opening of the flower and after pollination, with pollen grains adhering to the stigmata ...... 95

Figure 3 Shikimate accumulation of parental plants

(A533.1 and Echi S) and the F1 cross of E. colona ...... 98

Figure 4 Glyphosate dose response of susceptible and resistant

populations of E. colona and the F2 population ...... 101

Abstract

Echinochloa colona is an important summer-growing weed species in northern Australian cropping regions. The intensive use of glyphosate in summer fallow operations has led to the appearance of glyphosate resistant E. colona populations at a large number of sites. Studies of the genetic diversity, resistance mechanisms, inheritance and spread of resistance were undertaken to better understand the evolution of glyphosate resistance in this species. A survey of 65 barnyard grass populations collected from Queensland and New South Wales determined 34 populations were resistant to glyphosate with resistance levels ranging from 2 to 11-fold. High genetic diversity within three populations and between 62 populations was identified by the AFLP technique. A total of 99.2% of alleles identified within populations were polymorphic with a higher percentage of polymorphic alleles within the two resistant populations compared to the susceptible population. The level of glyphosate resistance in populations was dependent on the ambient temperature. Resistant populations showed a noticeably higher level of resistance at 30oC compared to 20oC whereas there was no effect of temperature on the response of the susceptible population. Experiments were carried out on glyphosate absorption and translocation in resistant and susceptible plants to identify the reason for these differences and the results showed a considerable decrease in glyphosate absorption into leaves at 30oC. Differences were also identified in glyphosate translocation between the treated leaves and the other sections of plants at the different temperatures. There were no differences in glyphosate absorption or translocation between the susceptible population and the resistant populations suggesting that differences in absorption and translocation of the herbicide are not the mechanism of resistance in the studied populations.

Studies of EPSPS gene copy number showed gene amplification was not the resistance mechanism either. A mutation was detected at codon 106 (proline substituted by serine) of the

EPSPS gene of the most resistant population, A533.1, indicating the presence of target-site resistance in this population. Gene flow by pollen exchange between the glyphosate resistant

xii population A533.1 and the susceptible population Echi S occurred at a frequency of 1.38% when progeny from the susceptible parent was tested at 240 g a.e. ha-1 of glyphosate. The mutation in the EPSPS gene was detected in 24 F1 progenies of this population pair.

Segregation of resistance in the gene flow experiment between resistant and susceptible individuals occurred at a 3:1 resistance : susceptibility ratio in the F2 generation indicating the trait of glyphosate resistance is a single dominant trait of E. colona. Sequencing the EPSPS cDNA of five parental and F2 filial individuals revealed at least two EPSPS genes present in

E. colona. Shikimate accumulation of the F1 hybrid and the glyphosate response of F2 progenies were intermediate between the two parental populations.

xiii xiv Tables Published with Consent from Copyright Holders in this Thesis

Table 2.1 Documented herbicide resistance in weed species in Australia (Heap, 2014) ...... 12

Figures Published with Consent from Copyright Holders in this Thesis

Figure 2.1 Chemical structure of glyphosate (Franz et al., 1997) ...... 18

Figure 2.2 Activity of glyphosate on reaction catalysed by enzyme 5-enolpyruvylshikimate-3-phosphate synthase (Amrhein et al., 1980) ...... 19

Acknowledgements

I would like to express sincere thanks to my supervisors, Associate Professor Christopher

Preston, Dr Peter Boutsalis and Dr Jenna Malone, for their guidance, help and support through the whole of my research project. Dr Jenna Malone has guided and provided me with valuable advice on technical aspects, especially on molecular biotechnology. The materials and methods section in my thesis and papers was also mostly corrected by Dr Jenna. Dr Peter

Boutsalis gave me technical advice on experiments in shade-house. Particularly, I am greatly indebted to my principal supervisor Associate Professor Christopher Preston, who has given me invaluable guidance, advice, comments and encouragement throughout this research. In addition, he has helped me in improving skills in experimental data analysis and other scientific aspects.

I am extremely grateful to the staff of the weed science group, Sarah Morran, Mahima

Krishnan, Robin St. John-Sweeting, Patrick Krolikowski, Ruwan Lenorage and Geetha

Velappan. Sarah Morran guided me through the glyphosate absorption and translocation experiment. Mahima Krishnan made a valuable contribution to the technique of EPSPS cDNA sequencing. Patrick Krolikowski, Ruwan Lenorage and Geetha Velappan gave me assistance in giving an eye to experiments in shade-house including watering experimental plants. My sincere appreciation is also sent to lab mates, Patricia Adu-Yeboah, Mohammed

Hussein Minati Al-Asklah, Rupinder Haur Saini, Lovreet Singh Shergill and Duc The Ngo, who shared study experience with me, encouraged me in my PhD program and provided me with priceless discussions.

I would like to express my sincerest gratitude to my external advisor, Dr John Heap, who gave me the useful advice on experiments on the temperature response of glyphosate resistant barnyard grass populations. I would like to extend my gratitude to post-graduate coordinators

Associate Professor Gurjeet Gill and Dr Matthew Denton for support and helpful advice. My

xvi special thanks were also sent to Van Lam Lai, Thanh Dzung Phan, Anh Nghia Nguyen and my colleagues at the Rubber Research Institute of Vietnam for support and encouragement.

I gratefully acknowledge the Ministry of Education and Training, Vietnam for scholarship funding, the Rubber Research Institute of Vietnam for permission to leave my duties and study overseas, and the University of Adelaide for access to study facilities.

After all, my deepest gratefulness is dedicated to the spirits of my dearly beloved mother, who had brought up me through the last half of her lifetime and has lately passed away. I am deeply indebted to all members in my big family, my wife and daughters for their constant love and moral support. The patient wait and encouragement of my wife and daughters throughout four years of my PhD program have motivated me to work diligently and accomplish this thesis.

xvii

Chapter 1

General Introduction

High competition for water, sunlight and nutrients with major agricultural crops has made the barnyard grasses (Echinochloa spp.) major weed species; and they were rated among the 18 most troublesome weeds in agriculture worldwide (Holm et al., 1977). These are annual weed species often found in paddy fields throughout the rice-growing regions around the world

(Mooney and Hobbs, 2000). In Australia, Echinochloa spp. were recognised as common weed species in summer fallows (Walker et al., 2004), as well as in crops. Two barnyard grass species (Echinochloa colona and Echinochloa crus-galli) were rated in the top three most harmful weeds in vegetable crops (Holm et al., 1977; Walker et al., 2004).

Many methods of controlling Echinochloa spp. have been used including: hand-weeding, trampling, cultural measures, mechanical weeding and using chemical herbicides (Matsunaka,

1983). Among these methods, herbicides have been the most widely used in recent years in most countries in the world. The intensive use of herbicides over a long period of time has resulted in the evolution of herbicide resistance in these grass species. For example, the herbicide propanil has been repeatedly used for a long time to control E. crus-galli and other grass weeds, and as a result, resistance to propanil in this grass has occurred (Norsworthy et al., 1998).

Since the herbicide glyphosate was introduced to world agriculture in 1974, it has become the world’s most widely used herbicide, especially since the development of genetically modified crops with resistance to glyphosate. However, continued dependence on glyphosate over a large area ranging from field agricultural systems to inner-city landscapes has increased the number of weed species, including E. colona, that have evolved resistance to this herbicide

(Duke and Powles, 2008). Up to now, glyphosate resistance in E. colona has been found in

1 three countries including Australia, USA and Argentina (Heap, 2014). Among these countries, Australia has been discovered to have the largest area of glyphosate resistant E. colona with three states namely New South Wales (NSW), Queensland (QLD) and Western

Australia (WA) (Heap, 2014). Glyphosate resistance has occurred in many plant species

(Lorraine-Colwill et al., 2003; Powles and Preston, 2006; Michitte et al., 2007; Gaines et al.,

2010). However, glyphosate resistance in E. colona, was only recently discovered and is poorly understood (Storrie et al., 2008; Heap, 2014).

With the aim of improving understanding of glyphosate resistance evolution in E. colona, this research was implemented to evaluate the genetic variability, assess the impacts of temperatures on the resistance level, and determine the inheritance and spread of glyphosate resistance in this grass species. Initially, a survey was conducted through QLD and NSW, and the response of E. colona populations to glyphosate doses was examined to establish the real status and herbicide resistance levels of E. colona in these two states. In the following studies, the genetic diversity of E. colona populations collected from different locations in QLD and

NSW was evaluated to understand the potential spread of glyphosate resistant E. Colona

(Chapter 3). The response of glyphosate resistance in E. colona to two different temperatures was also assessed and the reasons causing different responses were elucidated (Chapter 4).

Finally, movement of the glyphosate resistance gene in E. colona over the susceptible population and the pattern of the resistance inheritance were evaluated (Chapter 5). Overall, the components of this thesis are outlined as follows:

 Chapter 1: General introduction.

 Chapter 2: A literature review covered the biological and agronomical characteristics of

Echinochloa spp., geographical distribution and impacts of these grass species, the

properties and action mode of glyphosate, glyphosate resistance evolution and the

mechanisms of resistance, and molecular markers which could be used to research on

genetics of E. colona.

 Chapter 3: Tested populations for glyphosate resistance, evaluated the response of resistant

E. colona populations to different glyphosate rates and investigated the genetic variability

within and between E. colona populations collected through two states QLD and NSW in

Australia with the AFLP technique.

 Chapter 4: Assessed the response of six glyphosate resistant E. colona populations to two

temperature regimes (20oC and 30oC), investigated whether glyphosate resistance

mechanism played a role in the response to temperature and whether absorption and

translocation of glyphosate was different at the two temperatures.

 Chapter 5: Evaluated gene flow due to pollen exchange between the resistant population

A533.1 and the susceptible population Echi S, the inheritance of glyphosate resistance

from a hand-cross between the same populations, the presence of mutations within the

EPSPS gene and whether the mutation was present on one or more homeologs.

 Chapter 6: General discussion of the research. This chapter also includes the principal

conclusions of the research, contributions of the research to knowledge and farming

practice, and the potential studies for the future.

Several results of this research were presented at the 18th Australasian Weeds Conference organised by Council of Australasian Weed Societies Inc. and Weed Society of Victoria at the

Sebel and Citigate Albert Park, Melbourne, Victoria on 8-11 October 2012. Some information from Chapter 3 and 4 have already been also published on the proceedings of this conference as:

Hoan Nguyen, T., Malone, J., Boutsalis, P. and Preston, C. (2012). Glyphosate

resistance in barnyard grass (Echinochloa colona). In Valerie Eldershaw, V. (ed.),

Proceedings of the 18th Australasian Weeds Conference on Developing Solutions to

Evolving Weed Problems, Melbourne, Victoria, Australia, 8-11 October 2012. Weed

Society of Victoria Inc., Batman, Vic 3058, Australia, 237-240.

The results in Chapters 3 and 4 were submitted to the two journals as follows:

Nguyen, T.H., Malone, M.J., Boutsalis, P. and Preston, C. (2015). ‘Genetic diversity of

glyphosate resistant junglerice (Echinochloa colona) in New South Wales and

Queensland’, Weed Science, Manuscript number: WS-D-15-00006.

Nguyen, T.H., Malone, M.J., Boutsalis, P., Shirley, N. and Preston, C. (2015).

‘Temperature influences the level of glyphosate resistance in barnyard grass

(Echinochloa colona)’, Pest Management Science, Manuscript number: PM-15-0127.

As submitted to the journals, these Chapters have been prepared in publication format.

Literature Cited

Duke, S.O. and Powles, S.B. (2008). 'Glyphosate-resistant weeds and crops', Pest Management Science 64 (4), 317-318.

Gaines, T.A., Zhang, W.L., Wang, D.F., Bukun, B., Chisholm, S.T., Shaner, D.L., Nissen, S.J., Patzoldt, W.L., Tranel, P.J., Culpepper, A.S., Grey, T.L., Webster, T.M., Vencill, W.K., Sammons, R.D., Jiang, J.M., Preston, C., Leach, J.E. and Westra, P. (2010). 'Gene amplification confers glyphosate resistance in Amaranthus palmeri', Proceedings of the National Academy of Sciences of the United States of America 107 (3), 1029-1034.

Heap, I. (2014). The international survey of herbicide resistant weeds, viewed 30 July 2014, .

Holm, L.G., Plucknett, D.L., Pancho, J.V. and Herberger, J.P. (1977). The world's worst weeds: Distribution and biology. The University Press of Hawaii, Honolulu, Hawaii.

Lorraine-Colwill, D.F., Powles, S.B., Hawkes, T.R., Hollinshead, P.H., Warner, S.a.J. and Preston, C. (2003). 'Investigations into the mechanism of glyphosate resistance in Lolium rigidum', Pesticide Biochemistry and Physiology 74 (2), 62-72.

Matsunaka, S. (1983). Evolution of rice weed control practices and research: World perspective. In The Conference on Weed Control in Rice, Los Baños, Laguna,

Philippines, 31 August - 4 September 1981. International Rice Research Institute (IRRI), Los Banos, Philippines, 5-17.

Michitte, P., De Prado, R., Espinoza, N., Ruiz-Santaella, J.P. and Gauvrit, C. (2007). 'Mechanisms of resistance to glyphosate in a ryegrass (Lolium multiflorum) biotype from Chile', Weed Science 55 (5), 435-440.

Mooney, H.A. and Hobbs, R.J. (2000). Invasive species in a changing world. Island Press, Washington, D.C., US.

Norsworthy, J.K., Talbert, R.E. and Hoagland, R.E. (1998). 'Chlorophyll fluorescence for rapid detection of propanil-resistant barnyard grass (Echinochloa crus-galli)', Weed Science 46 (2), 163-169.

Powles, S.B. and Preston, C. (2006). 'Evolved glyphosate resistance in plants: Biochemical and genetic basis of resistance', Weed Technology 20 (2), 282-289.

Storrie, A., Cook, T., Boutsalis, P., Penberthy, D. and Moylan, P. (2008). Glyphosate resistance in awnless barnyard grass (Echinochloa colona (L.) Link) and its implications for Australian farming systems. In the 16th Australian Weeds Conference, Cairns Convention Centre, North Queensland, Australia, 18-22 May 2008. Queensland Weed Society, Queensland, Australia, 74-76.

Walker, S., Widderick, M., Storrie, A. and Osten, V. (2004). Preventing glyphosate resistance in weeds of the northern grain region. In the 14th Australian Weeds Conference - Weed management: balancing people, planet and profit, Wagga Wagga, New South Wales, 6-9 September 2004. Weed Society of New South Wales, Sydney, Australia, 428-431.

Chapter 2

Literature Review

2.1 Introduction

Echinochloa spp. cause serious damages to agriculture all over the word and particularly in

Australia owing to inhibiting the growth and losing the yield of crops (Holm et al., 1977;

McGillion and Storrie, 2006). These grass species have been commonly found in paddy fields around the world (Mooney and Hobbs, 2000), in summer fallows and the grain-growing lands in QLD and NSW (Australia) (McGillion and Storrie, 2006). Lands with moist soil and mild weather are suitable for the growth of barnyard grasses (Holm et al., 1977). As a result of using glyphosate, a highly effective and broad spectrum herbicide, over a long period of time to control weeds, the evolution of herbicide resistance has appeared (Norsworthy et al., 1998).

Glyphosate resistance in Echinochloa colona species was first identified in NSW, Australia in

2007 and was later discovered in the United States in 2008, Argentina in 2009, QLD and WA

(Australia) in 2009 and 2010 respectively (Heap, 2014). This review will cover aspects of biological and agronomical characteristics of Echinochloa spp., properties and action mode of glyphosate, glyphosate resistance and causes, mechanisms of resistance in plant species, and molecular markers involving the studies of resistance evolution. Relevant methodologies of the studies will also be reviewed.

2.2 Echinochloa spp.

2.2.1 Geographical distribution of Echinochloa spp. in the world

Echinochloa spp. are widely distributed throughout the world. E. colona is distributed mainly in equatorial regions of the world, whereas E. crus-galli is more widely distributed in both the

6 northern and southern hemispheres (Smith, 1983). According to Holm et al. (1977), E. colona is distributed through the agricultural areas from 23o N to 23o S, especially in Asia, Australia,

Pacific Islands, South America and the Caribbean. However, this grass species is less severe in North Africa and Europe; and its distribution is not yet recorded in temperate regions of the world. E. crus-galli is distributed over a larger area from 50o N to 40o S. It is indigenous to

India and Europe. Similar to E. colona, the presence of E. crus-galli is negligible in Africa

(Holm et al., 1977). Gonzalez et al. (1983) reported that E. colona was a common grass weed in wetland rice, as well as dryland rice in almost all countries of Latin America. This is an extremely serious grass weed species and it is widespread throughout rice fields in Central

America, the Caribbean and tropical South America (Gonzalez et al., 1983). As affirmed by

Michael (1983), E. colona is an important grass weed in the subtropical and tropical rice- growing regions. It also occurs on paddy fields in NSW, Australia and in the southern United

States at times.

In Australia, Echinochloa spp. occur commonly in the grain-growing areas in the north of the country (Walker et al., 2004). In a survey in 1989, Felton et al. (1994) found that Echinochloa spp. were the most important and common grass weeds in northern NSW while McGillion and Storrie (2006) stated E. colona is a troublesome grass for many crops in central and southern QLD, and in southern, central and northern NSW. Friend (1983) also confirmed that, with the exception of the arid west and Tasmania, this grass species is widely distributed in all other States of Australia including inland areas and coastal QLD. It has been generally supposed that wild ducks may have introduced Echinochloa spp. to Australia; subsequently, weed seeds were spread over paddy fields by means of the canal system which connects fields with one another (Holm et al., 1977).

The above information indicates that Echinochloa spp. inhabit many large areas worldwide with a diverse living environment. Consequently, due to the problems caused by these grass

7 species there is a need to develop appropriate control methods in order to minimize damage to crops and the environment.

2.2.2 Biology

Echinochloa spp. are summer-growing annual grasses that grow best where there is plenty of available water (Holm et al., 1977). Yabuno (1983) suggested that E. colona can also grow in comparatively arid regions; however, in flooded conditions with 10 cm of water the growth of seedlings would be halted. In the United States, studies by McGillion and Storrie (2006) showed E. crus-galli can survive and grow in areas with temperatures ranging from 6 - 28oC, an average annual rainfall of 310 - 2500 mm and soil pH of 4.8 - 8.2. Fertile, damp and nitrogen rich soils are the best conditions for the growth of this grass species. However, E. crus-galli can also flourish on sandy and humus soils, and even submerged soil. As stated by

Holm et al. (1977), light is essential for the germination of E. crus-galli seeds and flooding inhibits seeds from germination. For seedlings, the best growth is at 30oC, growth is sluggish at 10oC and stopped at 5oC.

In terms of propagation, Echinochloa spp. reproduce sexually; however, stem nodes can root when stems lie prostrate on the ground allowing asexual reproduction under some circumstances (Holm et al., 1977). The number of seeds produced by mature plants is large and one mature plant can bear more than a thousand seeds (Holm et al., 1977).

2.2.3 Agronomical features

Morphologically, Echinochloa spp. resemble rice. Barrett (1983) suggested that rice mimicry in Echinochloa spp. evolved over a long period of time as a result of hand-weeding rice in

Asian countries, because other weeds that are morphologically different from rice were

8 preferentially removed from paddies by hand weeding, hence Echinochloa spp. would increase in numbers.

High densities of Echinochloa spp. have dramatic impacts on crop yield. Smith (1983) concluded that on dryland and wetland paddy fields that are direct seeded or transplanted, these grasses cause a considerable decrease in yield and quality of rice. Therefore, their presence would have a major impact on profitability of farmers (Smith, 1983). In addition to rice, a wide variety of agricultural crops worldwide were impacted by Echinochloa spp. including vegetables, corn, sugarcane, sugar beets, sorghum, millet, potatoes, peanuts, jute, citrus, orchards, vineyards, soybeans, bananas, cassava, taro, cowpeas, abaca, pineapples, sweet potatoes, cotton, tea, tobacco, coffee and coconuts (Holm et al., 1977). According to

McGillion and Storrie (2006), E. crus-galli not only caused a significant decrease in the yield of agricultural crops, but also reduced production of forage crops by removing up to 80% of available nitrogen in the soil. At the same time, the accumulation of nitrates at high levels in

Echinochloa spp. could harm cattle that graze the foliage (McGillion and Storrie, 2006).

During the early growth stages of rice, competition from Echinochloa spp. is particularly severe compared to later growth stages, because these grasses cause serious effects on the height, panicle number, grain yield, fertility and straw weight of rice. For example, in Taiwan,

E. crus-galli caused a decrease of 85% in rice yield (Datta, 1981).

2.2.4 Problems caused by Echinochloa spp. in Australia

In Australia, rice was directly sown in both dryland and irrigated systems (Swain, 1973), and the existence of E. crus-galli in large numbers has resulted in a reduction in rice yield of two to four tons per hectare (McGillion and Storrie, 2006). In sugarcane fields, this grass was rated as one of three most damaging grass species (Holm et al., 1977). Apart from rice and sugarcane, E. crus-galli decreased yield of a wide range of other crops in Australia, such as cotton, corn, sorghum and vegetables. Similarly, in northern Australia, E. colona is a

9 troublesome grass in rice, cotton, sorghum, sugarcane, corn, linseed, safflower and vegetables. As a result of prostrate growth habit, it is easy for this weed to obtain space below the shade of other plants so that it can compete with surrounding crops (Holm et al., 1977).

According to results of a survey conducted by Walker et al. (2005) in summer fallows of subtropical Australia, 82% of growers rated Echinochloa spp. as their most common weeds and the most difficult to control.

2.2.5 Herbicide resistance in Echinochloa spp.

As a result of the herbicide use in agriculture with an increasing intensity, herbicide resistance of weeds is becoming more and more serious. WSSA (1998) defined herbicide resistance as

“the inherited ability of a plant to survive and reproduce following exposure to a dose of herbicide normally lethal to the wild type”. According to McGillion and Storrie (2006), herbicide resistance of weed individuals within a population occurs in three main ways: (1) pre-existing resistance, (2) importation of genes from resistant populations through crop seed sources contaminated with weed seeds, animals or machinery, and (3) natural dispersal via water and wind. As a whole, once herbicides of the same group are intensively applied to a weed population, susceptible individuals will be killed while resistant ones will set seeds leading to an increase in the number of resistant individuals in the population (McGillion and

Storrie, 2006).

Similar to other weed species, prolonged use of herbicides for the control of Echinochloa species readily results in the evolution of herbicide resistance. An example of this occurred with the propanil herbicide, an acylanilide herbicide that was introduced into the United

States in the 1960s to control Echinochloa spp. and some other weeds in rice. Propanil was widely used on rice paddies in the United States and in some other countries (Hoagland et al.,

2004). As a consequence of the over-reliance on this herbicide, Hirase and Hoagland (2006) discovered resistance in Echinochloa spp. populations to herbicide at recommended doses of

3.6 to 5.6 kg a.i. per hectare. In addition, among eleven samples of Echnochloa spp. collected in Texas in 1992, seven samples were found resistance to propanil (Hoagland et al., 2004).

Subsequently, resistance of these grasses to propanil was also discovered at 160 sites through

38 rice-growing counties in Arkansas (Norsworthy et al., 1998). Hoagland et al. (2004) showed that propanil resistance in Echinochloa spp. has occurred in a large number of rice- growing areas in the world including Italy, Sri Lanka, Mexico, Central America nations,

Columbia, Texas, Thailand, Greece, Venezuela and Costa Rica. The weeds were resistant to propanil as a result of increased detoxification by aryl acylamidase (Hoagland et al., 2004). In another study in California, two Echinochloa species, namely early watergrass (E. oryzoides) and late watergrass (E. phyllopogon), were determined to be resistant to a variety of herbicides including bispyribacsodium, thiobencarb, fenoxaprop-ethyl and molinate although these herbicides belong to different mode-of-action groups (Fischer et al., 2000). Especially,

E. colona has been so far found resistance to a series of herbicides including glyphosate, atrazine, azimsulfuron, bispyribac-sodium, cyhalofop-butyl, fenoxaprop-P-ethyl, fluazifop-P- butyl, haloxyfop-P-methyl, imazapic, imazapyr, metribuzin, propanil and quinclorac (Heap,

2014).

2.2.6 Herbicide resistance in weed species in Australia

In Australia, from 1982 to 2014 there have been reports of at least 40 weed species found resistance to many different herbicides (Heap, 2014). Out of species, Lolium rigidum was determined as resistant to the most numerous herbicides (10 herbicides) and resistance in

Sisymbrium orientale was found in five states of Australia. In E. colona, resistance to both atrazine and glyphosate has been found in NSW, while resistance to glyphosate only has been reported in three states QLD, NSW and WA (Table 2.1) (Heap, 2014).

Table 2.1 Documented herbicide resistance in weed species in Australia (Heap, 2014).

States with Herbicide confirmed No. Species Common name group resistant populations 1 Arctotheca calendula Capeweed D VIC 2 Avena fatua Wild oat A NSW, SA, WA 3 Avena sterilis Sterile oat A NSW, SA 4 Avena sterilis ssp. Ludoviciana Sterile oat B, Z NSW, SA 5 Brassica tournefortii African mustard B SA, WA 6 Bromus diandrus Ripgut brome A, B, G VIC, SA 7 Bromus diandrus ssp. Rigidus Rigid brome A, B SA, WA 8 Chloris truncate Windmill grass G NSW 9 Conyza bonariensis Hairy fleabane G NSW, QLD, SA 10 Cyperus difformis Smallflower umbrella sedge B NSW 11 Damasonium minus Starfruit B NSW 12 Digitaria sanguinalis Large crabgrass A, B SA 13 Diplotaxis tenuifolia Perennial wallrocket B SA 14 Echinochloa colona Junglerice C1, G NSW, QLD, WA 15 Echium plantagineum Salvation jane B SA, WA 16 Ehrharta longiflora Longflowered veldtgrass A WA 17 Fumaria densiflora Dense-flowered fumitory K1 NSW 18 Galium tricornutum Threehorn bedstraw B SA 19 Hordeum murinum ssp. Glaucum Smooth barley A, B, D VIC, SA, WA 20 Hordeum murinum ssp. leporinum Hare barley A, D NSW, VIC, SA 21 Lactuca serriola Prickly lettuce B VIC, SA A, B, C1, D, NSW, VIC, SA, 22 Lolium rigidum Rigid ryegrass F3, G, K1, WA K2, K3, N 23 Mesembryanthemum crystallinum Crystalline iceplant B SA 24 Mitracarpus hirtus Tropical girdlepod D QLD 25 Nassella trichotoma Serrated tussock N VIC 26 Pentzia suffruticosa Calomba daisy B SA 27 Phalaris minor Little seed canary grass A VIC 28 Phalaris paradoxa Hood canarygrass A, B NSW 29 Poa annua Annual bluegrass Z VIC 30 Polygonum convolvulus Wild buckwheat B QLD B, C1, F1, NSW, VIC, SA, 31 Raphanus raphanistrum Wild radish G, O WA 32 Rapistrum rugosum Turnipweed B QLD 33 Sagittaria montevidensis California arrowhead B NSW 34 Sinapis arvensis Wild mustard B NSW B, C1, NSW, QLD, 35 Sisymbrium orientale Oriental mustard F1, O VIC, SA, WA 36 Sisymbrium thellungii African turnipweed B QLD 37 Sonchus oleraceus Annual sowthistle B, G NSW, QLD, VIC 38 Urochloa panicoides Liverseedgrass C1, G NSW, QLD 39 Urtica urens Burning nettle C1 VIC 40 Vulpia bromoides Squirreltail fescue C1, D VIC

NSW: New South Wales, QLD: Queensland, VIC: Victoria, SA: South Australia, WA: Western Australia.

Factors that influence the resistance evolution of weeds include the initial frequency of resistance gene(s), herbicide group used, the effectiveness of herbicide, the weed population size that is treated with herbicides and the biological characteristics of weed (McGillion and

Storrie, 2006).

2.3 Causes of resistance evolution

2.3.1 Genetic mutations endow resistance

Genetic mutations that result in herbicide resistance are unlikely to be caused by herbicides, but occur naturally in susceptible populations at very low initial frequencies (Gressel and

Segel, 1978; Jasieniuk et al., 1996; Letouze and Gasquez, 2001). According to Merrell

(1981), the frequency of natural mutations in living organisms ranges from 1x10-6 to 1x10-5 gametes/locus/generation. However, normally due to the higher rates of gene flow compared to the mutation rates, the initial frequency of herbicide resistant individuals would be high

(Crow, 1983; Jasieniuk et al., 1996). Jasieniuk et al. (1996) suggested that in practice the frequency of mutations to herbicide resistant weeds has not yet been determined, and although the mutation rate of plants might be actually low, the likelihood of detecting at least one mutant weed plant that is resistant to a herbicide in fields of dense mono-species weeds is high. Therefore, the formula for determining the probability of appearance of at least one herbicide resistant plant in a population with various weed density and total weed numbers was suggested by Jasieniuk et al. (1996) as follows:

P = 1 – (1 – p)n

Where, P = probability of occurrence of at least one resistant plant, p = expected frequency of resistant plants in the population, and n = total number of plants in a population.

In general, in a dense weed population, the occurrence likelihood of a herbicide resistant plant is higher than that in a sparse weed population (Preston and Powles, 2002).

2.3.2 Initial frequency of resistant alleles

The initial frequency of resistant alleles plays a significant role in how fast resistance evolves.

When herbicides are applied to a weed population, resistance will occur quickly if the initial gene frequency of resistant plants is high (Preston and Powles, 2002). Normally, the initial frequency of resistant alleles in a population is very low. For this reason, a large number of seeds or plants need to be sampled and screened in order that estimates of the frequency of resistance alleles can obtain high precision (Jasieniuk et al., 1996). The initial frequency of mutant individuals resistant to a specific herbicide before it was applied to a weed population has been estimated in several weed species. For example, Matthews and Powles (1992) estimated the frequency of diclofop-methyl resistant rigid ryegrass (Lolium ridigum) plants at

0.02 ± 0.0092 in formerly unsprayed farm populations and at <0.002 in non-farm populations through southern Australia. Before that, Darmency and Gasquez (1990) estimated the frequencies of triazine resistant individuals within seven common lambsquarters

(Chenopodium album) populations at gardens in France at 1 x 10-4 to 3 x 10-3.

2.3.3 Selection pressure

The application of herbicides is a key factor that promotes the rapid evolution of herbicide resistant weed populations. Herbicides eliminate susceptible weed individuals and increase the proportion of resistant individuals. Therefore, the repeated use of herbicides provides a selective pressure to weed populations (Jasieniuk et al., 1996). However, the number of herbicide applications for a resistant population to occur varies depending on herbicide group applied. For example, for weed individuals with one resistant gene, herbicide groups that

14 inhibit photosynthesis at photosystem II (e.g. triazines) (Group C) and microtubule assembly

(e.g. dinitroanilines) (Group K1) require more herbicide applications than herbicide groups that inhibit acetyl-CoA carboxylase (Group A) and acetolactate synthase (Group B)

(McGillion and Storrie, 2006).

2.3.4 Inheritance of resistance

Herbicide resistance in weed species can be inherited on the nuclear or cytoplasmic genome.

For the majority of modes of action of herbicide, resistance is transmitted to the progeny through ovules and pollen. However, for target-site resistance to the triazine herbicides, most weed species transmit their resistance via the cytoplasm (Jasieniuk et al., 1996), because the gene for the target-site resistance to triazine herbicides was found on the chloroplast genome

(Hirschberg et al., 1984). This is a significant distinction that needs to be noted. As confirmed by Powles and Preston (2006), the mechanisms of glyphosate resistance in weed species are inherited as a single trait and occur on the nuclear genome. In most weed species, when the resistance allele occurs on the nuclear genome, herbicide resistance is controlled by an allele(s) that is at least partially dominant. An allele that is at least partially dominant will spread far faster within a population compared to a recessive allele, because heterozygotes will express at least part of the phenotype of the homozygote under selection pressure

(Darmency and Gasquez, 1990; Matthews and Powles, 1992). After herbicide application, a rare dominant resistance allele will be established more easily in a weed population than a recessive resistance allele (Merrell, 1981).

2.3.5 Gene migration

While mutation plays a role as an initial origin of herbicide resistant alleles, gene migration together with the use of herbicides can enhance the spread and expansion of herbicide

15 resistant weed populations. Resistance alleles can be dispersed over adjacent susceptible weed populations from an original resistant population through seed or pollen. If the level of gene migration is higher than that of mutation, a rapid rise in the number of individuals resistant to a certain herbicide can occur before the herbicide is used. Consequently, gene migration may shorten the time period of establishing a large herbicide resistant population after application of the herbicide (Jasieniuk et al., 1996).

Previous studies have shown that gene migration between weed populations was severely restricted; and the gene flow rates vary from 0.5 to 5.5 individuals per generation (Slatkin,

1985a, 1985b, 1987). Maxwell (1992) and Stallings et al. (1995) recorded the spread of pollen containing resistance alleles within populations for two weed species with two herbicides: namely resistance to sulfonylurea in kochia (Kochia scoparia) and resistance to diclofop- methyl in Italian ryegrass (Lolium multiflorum). In kochia, 1.4% of seeds set on susceptible individuals at a 28.9 m distance were resistant, while in Italian ryegrass 1% of seeds set on susceptible individuals were resistant at 6.84 m (Maxwell, 1992; Stallings et al., 1995). These data demonstrate that herbicide resistant genes can be rapidly spread over short distances in some species.

2.3.6 Fitness of resistant individuals

According to McGillion and Storrie (2006), within the same species, herbicide resistant weeds are often less robust than susceptible weeds. Therefore, in the absence of herbicides, resistant weeds will produce fewer seeds than susceptible individuals. Triazine resistant canola

(Brassica napus) can be considered as a typical example for this case. Because triazine resistance mechanism occurs in chloroplast, the yield of triazine resistant B. napus varieties is lower than that of other varieties and due to a reduction in electron flow between photosystems II and I (Beversdorf et al., 1988). However, for chlorotoluron resistant blackgrass (Alopecurus myosuroides), fitness depends on density and frequency of susceptible and

16 resistant plants once the herbicide is applied, and resistant individuals produce more seed than susceptible individuals (Mortimer et al., 1992).

2.3.7 Characteristics of the seed bank

Apart from the factors mentioned above, resistance evolution also depends partly on the available seed bank. In practice, weed species that have a greater number of dormant seeds will slow down the progress of resistance. At the same time, a large number of susceptible seeds from seed bank will dilute resistance in the population (McGillion and Storrie, 2006).

For Echinochloa spp., photoperiod and several other natural factors affect the production of dormant seeds and the duration of dormancy. For example, the dormancy period of this seeds is 4 to 8 months in Japan and 4 to 48 months in the United States (Holm et al., 1977).

2.4 Glyphosate

2.4.1 Properties of glyphosate

Glyphosate is common name given to the herbicide N - (phosphonomethyl) glycine. Its most well-known trade name is Roundup™; however, it has many other different trade names.

Currently, there are a variety of formulations of glyphosate including trimethylsulfonium, isopropylamine, potassium or ammonium salts. Glyphosate is formulated as a salt because it is a simple zwitterionic amino acid (Figure 2.1). Its molecular weight varies depending on formulations. For example, isopropylamine salt: 228.19 and trimethylsulfonium salt: 245.23.

The trimethylsulfonium salt is a clear amber to yellow solid, mild sulfur odour and 1.23 - 1.25 g/mL in density at 20oC. It is stable for 32 days at 25oC and pH 5, 7, or 9 with melting point at

200oC (Franz et al., 1997; Vencill, 2002).

Figure 2.1 Chemical structure of glyphosate (Franz et al., 1997).

The herbicidal function of glyphosate was discovered by Monsanto Agricultural Products

Company in 1970. Since this chemical came onto the market in 1974, it has become the most widely used herbicide in the world. Since glyphosate-resistant agricultural crops have been introduced and its functionality has been extended, glyphosate has even become a more important herbicide (Duke et al., 2003). The use of this herbicide has continued to grow in almost all countries around the world as its price has been decreasing and its patent has expired. In terms of toxicology and environment, glyphosate is comparatively safe. On account of its properties, glyphosate has become a unique global herbicide with no other herbicide having similar chemical structure or molecular target-site (Franz et al., 1997; Duke et al., 2003).

As a non-selective herbicide with wide activity spectrum and high efficacy, glyphosate has been considered as an ideal herbicide (Duke and Powles, 2008). Although it kills weeds slowly after application, it is translocated to metabolic sites quickly. This makes it highly effective on intractable weeds, particularly monocotyledon grass species such as blady grass

(Imperata cylindrical), quack grass (Agropyron repens), Johnson grass (Sorghum halepense) and Cyperus species (Duke et al., 2003). Owing to its anionic nature, glyphosate is tightly bound by soil components and subsequently inactivated by soil microorganisms once it is in contact with soil (Duke et al., 2003). However, the fertilisation of soil with phosphate together with the presence of mycorrhiza resulted in the remobilisation of glyphosate residues into plants and caused the plant’s mortality. This occurred because mycorrhiza increase phosphate absorption of plants while phosphate causes a competitive desorption of glyphosate

18 from cations in the soil (Beltrano et al., 2013). Normally, glyphosate is only applied to weed foliage, and due to high stability, it can be mixed with other additives, adjuvants and pesticides (Duke et al., 2003).

2.4.2 Mode of action

Glyphosate targets and binds to the enzyme EPSP (5-enolpyruvylshikimate-3-phosphate) synthase, that catalyses the condensation of shikimate-3-phospate and phosphoenolpyruvate to form 5-enolpyruvylshikimate-3-phosphate (Figure 2.2) (Amrhein et al., 1980). EPSP synthase is an important enzyme in the shikimate pathway, facilitating the biosynthesis of aromatic compounds in plants (Marques et al., 2007). Therefore, when glyphosate is applied to plants, the shikimate pathway is blocked resulting in inhibition in carbon flow through the shikimate pathway to aromatic amino acids, flavonoids, anthocyanins and lignins (Harring et al., 1998). Additionally, glyphosate also inhibits the photosynthesis of several species, such as sugar beet (Beta vulgaris) owing to a decline in stomatal conductance as a secondary effect

(Servaites et al., 1987). Because of its slow activity, glyphosate symptoms in the majority of weeds usually occur some days after application and consist of epinasty, loss of terminal domination and anthocyanins, growth delay, wilting and chlorosis (Harring et al., 1998).

Shikimate-3-phosphate Phosphoenolpyruvate 5-enolpyruvylshikimate- Phosphate 3-phosphate

Figure 2.2 Activity of glyphosate on reaction catalysed by enzyme 5-enolpyruvylshikimate-

3-phosphate synthase (Amrhein et al., 1980).

2.4.3 Glyphosate resistant weeds

Similar to other herbicides, the continuous application of glyphosate on a large scale in many countries around the world has led to a noticeable increase in the number of glyphosate resistant weed species (Powles and Preston, 2006). There are currently 29 weed species worldwide that have been reported as glyphosate resistant (Heap, 2014), such as L. ridigum in

Australia (Powles et al., 1998; Pratley et al., 1999; Lorraine-Colwill et al., 2003) and

California (Simarmata et al., 2003), Italian ryegrass (Lolium multiflorum) in Chile (Perez and

Kogan, 2003), goosegrass (Eleusine indica) in Malaysia (Lee and Ngim, 2000; Ng et al.,

2004), horseweed (Conyza canadensis) in Delaware and Mississippi (VanGessel, 2001; Koger et al., 2004) and palmer amaranth (Amaranthus palmeri) in Georgia (Culpepper et al., 2006).

E. colona has been reported as a glyphosate resistant grass species in several countries of the world including Australia (NSW, QLD and WA), the United States (California) and

Argentina (Santa Fe) (Heap, 2014). The number of glyphosate resistant E. colona populations in Australia was assessed as part of this project.

2.4.4 Mechanisms of glyphosate resistance

According to Devine and Shukla (2000), mechanisms leading to the phenomenon of herbicide resistance in weeds include: lowered sensitivity to herbicides due to target site mutations, increase in the number of target sites, increased herbicide detoxification, reduced herbicide activation, decreased herbicide translocation or herbicide sequestration away from target sites.

For glyphosate, there are four main mechanisms of resistance in plants that have been determined to-date. (1) Target-site resistance: A mutation within the target-site prevents the herbicide from binding as effectively; therefore, the plants will be less affected by the herbicide. As specified by Powles and Preston (2006), a mutation that causes changes in the

DNA sequence at the codon 106 in EPSPS gene from proline to either serine or threonine

20 results in glyphosate resistance in weeds; and Funke et al. (2009) found that a double mutation (causing changes from threonine97 to isoleucine and from proline101 to serine) in the

EPSPS gene provided glyphosate resistance in Escherichia coli. (2) Non-target-site resistance is comprised of a decrease in translocation of the herbicide (Powles and Preston, 2006). (3)

Reduced foliar uptake from the abaxial leaf surface leads to the lower volume of herbicide reaching the target-sites (Michitte et al., 2007). (4) Amplification of target-site gene: the genome of glyphosate resistant plants contained many more copies of the EPSPS gene than that of susceptible plants (Gaines et al., 2010). To date, five weed species have evolved resistance to glyphosate by amplification of the EPSPS gene including A. palmeri, tall waterhemp (Amaranthus tuberculatus), L. multiflorum, K. scoparia and spiny amaranth

(Amaranthus spinosus) (Sammons and Gaines, 2014) and the first case of this resistance mechanism was discovered in A. palmeri in Georgia, USA (Gaines et al., 2010).

In a study on glyphosate resistance mechanism in L. ridigum, Lorraine-Colwill et al. (2003) concluded that differential glyphosate translocation within the plant caused a significant difference between resistant and susceptible populations. According to these authors, after application, glyphosate was accumulated in the roots of susceptible individuals and in the leaf tips of resistant ones. At the same time, as suggested by these authors, it was likely that a cellular glyphosate pump was responsible for active transport of glyphosate out of plant cells.

Moreover, glyphosate exclusion in resistant plants was more active than that in susceptible ones. As a result, glyphosate within resistant plants was transferred to the leaf tips through transpiration (Lorraine-Colwill et al., 2003). The absorption of glyphosate into plant cells also depends on a phosphate transporter of the plasma membrane. When this phosphate transporter is inhibited due to mutation, the uptake of glyphosate would be considerably reduced (Denis and Delrot, 1993; Morin et al., 1997; Hetherington et al., 1998; Versaw and Harrison, 2002).

Additionally, several other resistance mechanisms have been proposed such as arresting glyphosate (sequestration) in laticifers (Foley, 1987) or in the vacuole (Ge et al., 2010), cellular uptake and discharge (Hetherington et al., 1998), plant metabolism of glyphosate

(Komoβa et al., 1992), accelerated EPSPS transcription and prolonged half-life (Holländer-

Czytko et al., 1992).

2.5 Molecular markers

2.5.1 Scientific basis of the use of molecular makers in determining the spread of resistance in

Echinochloa spp.

As mentioned above, once a genetic mutation causing herbicide resistance in a weed population occurs, resistant genes will be transmitted to the progeny and can be dispersed to susceptible populations through seeds, pollen or vegetative portions (Levin, 1981;

Christoffers, 1999). By means of molecular makers, the level and range of resistance spread could be determined through studying genetic structure and diversity of populations. Initially, resistant populations are probably very small, but they quickly increase in size with continued herbicide application. Modern genetic techniques have been becoming a useful means of identifying precise genetic modifications in individual weeds and the spread of these mutations within and between populations. With these techniques, understanding of genetic diversity, herbicide resistance evolution and spread of this resistance in weed species is becoming clearer.

2.5.2 DNA Fingerprinting techniques

Molecular markers are indispensable in DNA fingerprinting techniques. At present, several different markers are popularly used in genetics including RFLPs (Restriction fragment length polymorphism), RAPD (Randomly amplified polymorphic DNAs), SSRs (simple sequence repeats) and AFLPs (amplified fragment length polymorphism). With the exception of

RFLPs, the remaining markers are the most commonly used due to their quickness, simplicity and usefulness (McGregor et al., 2000).

For RFLP, variations in length of restriction fragments cut from genomic DNA by a restriction endonuclease are identified between individuals (Williams, 1989). RFLP markers were first used in the 1980s. They are the first generation of DNA markers and considered as one of the best for plant genome mapping (Acquaah, 2007). RFLP is used as a helpful tool in determining the genetic variation of plant species. An advantage of RFLPs is that it is not necessary to know the sequence used as a probe. However, this marker system is fairly expensive and it has low throughput (Acquaah, 2007).

RAPD is a PCR (polymerase chain reaction) based marker system that was introduced in

1990 (Williams et al., 1990). In this technique, only a short (around 10 bases), single and random primer is used to amplify the genomic DNA (Acquaah, 2007). RAPD markers are appropriate for DNA fingerprinting, gene mapping, and applications of animal and plant breeding, especially for population genetics (Williams et al., 1990). So far, RAPD markers have been used in assessing the genetic diversity of Echinochloa millets (Hilu, 1994) as well as in examining herbicide resistance evolution in E. crus-galli (Rutledge et al., 2000).

Currently, RAPDs are considered as an effective assay for polymorphisms, because they produce high levels of polymorphism that can be rapidly and simply identified. The disadvantage of this marker system is that the information content obtained from an individual RAPD marker is negligible (Williams et al., 1990).

SSRs (or microsatellites) are also PCR-based markers. They are random tandem repeats of 2 -

5 nucleotides such as GT or GACA which appear in microsatellites. The copy number of repeats is a polymorphism source in plants and it is different among individuals. Although this technique is more dependable than the RAPD technique, it is more expensive to implement. Furthermore, to use SSRs technology, it is required to know the sequence of nucleotides in order to design primers for PCR. This technique also requires complicated

23 electrophoresis systems and computer software for exact separation and count of DNA bands

(Acquaah, 2007).

AFLP was introduced by Vos et al. (1995). The procedure for AFLP involves three steps: (1) restriction of the DNA and ligation of oligonucleotide adapters to the cut ends, (2) selective

PCR amplification of DNA restriction fragments and (3) electrophoretic product analysis of the amplified fragments. In this technique, 17 - 21 nucleotide primers are used to selectively amplify restriction fragments using PCR and these primers have the capability to anneal completely to target sequences including the adapter and restriction sites along with the nucleotides flanking on the restriction sites. As a whole, AFLP technology is reliable and sturdy, and not influenced by fluctuation in PCR amplification parameters, such as thermal cycles and template concentration. In addition, this technique also produces a great number of restriction fragments that are able to be simultaneously analysed. Another advantage of

AFLPs is that they are visualised by PCR without need for sequence information prior to generating the fingerprints; this is especially helpful in case of DNA marker scarcity (Vos et al., 1995; Acquaah, 2007). Due to the advantages of the AFLP technique, it was used to determine genetic diversity of E. colona in this study.

2.5.3 DNA sequencing

DNA sequencing plays a significant role in providing essential knowledge about biological processes of organisms. This technique was initiated in 1977 by Maxam and Gilbert with the chemical method of breaking a terminally labelled DNA molecule (Maxam and Gilbert,

1977), followed by Sanger et al. with the enzymatic method of using specific chain terminating inhibitors (Maxam and Gilbert, 1977; Sanger et al., 1977). Both these methods are based on agarose gel electrophoretic technology with high resolution to separate the labelled DNA fragments and visualize the base sequence. However, because the application of Sanger technique is easier and quicker, it has been preferred by many people and has

24 become the principal DNA sequencing method for a variety of applications (Graham and Hill,

2001). In studies of herbicide resistant weeds, from the results of DNA sequencing SNPs could be detected and grouped, hence the spread of resistance alleles over crop fields would be grasped as the case of ACCase resistance in A. myosuroides (Menchari et al., 2006).

For Echinochloa spp., DNA sequencing technique was used by Roy et al. (2000) to determine the native status of the cold-adapted E. crus-galli populations in eastern North America. Two sequence types were applied namely chloroplast intron [trnL (UAA)] and rDNA nuclear space

ITS 1 (ITS1-rDNA) with grass samples collected from three various regions including

Quebec (eastern Canada), the east coast of the United States and western Europe. The results indicated that there were genetically significant differences between European populations and all other populations. In contrast, there was no difference among North American populations. At the same time, there were eight haplotypes identified by the combined sequences. Eventually, the authors concluded that the cold-adapted E. crus-galli populations in Quebec are likely indigenous to North America rather than Europe (Roy et al., 2000). In E. colona, EPSPS was used for identifying glyphosate resistance mutation; and in 2012 the mutation was first detected in a resistant E. colona population in California (Alarcon-Reverte et al., 2013). However, in order to detect mutations in Australian E. colona populations, the technique of DNA sequencing was used in this research.

2.6 Conclusions

Echinochloa spp. are annual tropical grass species that have a significant impact on world agriculture. As they possess very adaptable characteristics, Echinochloa spp. can grow well in a diverse range of environments from wetland to dryland as well as on many different soil types; and they have been found commonly in summer fallows in northern Australia.

Glyphosate is a wide spectrum and systemic herbicide that has been utilised as a highly effective herbicide in controlling Echinochloa spp. through inhibiting activity of the EPSP enzyme in the shikimate pathway. The intensive use of glyphosate to control Echinochloa spp. has led to the evolution of resistance to this herbicide. In addition to glyphosate, E. colona has been also found resistance to twelve other herbicides. At the same time, 29 weed species worldwide, including E. colona, have been found resistance to glyphosate. Factors contributing to the evolution of herbicide resistance in plants include the presence of specific genetic mutations, the initial frequency of resistant alleles, selection pressure, gene flow, resistance inheritance, fitness of resistant individuals and characteristics of the seed bank.

Four main mechanisms of glyphosate resistance in plants have been identified consisting of target-site resistance, non-target-site resistance, decreased foliar uptake from the abaxial leaf surface and amplification of target-site gene.

Molecular markers are very helpful tools for DNA fingerprinting techniques. Among markers,

AFLPs is an effective marker in investigating genetic diversity of weed species. In this study,

AFLPs was used to determine genetic variation of E. colona.

Literature Cited

Acquaah, G. (2007). Principles of plant genetics and breeding. Blackwell Publishing, Carlton, Victoria, Australia.

Alarcon-Reverte, R., Garcia, A., Urzua, J. and Fischer, A.J. (2013). 'Resistance to glyphosate in Junglerice (Echinochloa colona) from California', Weed Science 61 (1), 48-54.

Amrhein, N., Schab, J. and Steinrucken, H.C. (1980). 'The mode of action of the herbicide glyphosate', Naturwissenschaften 67 (7), 356-357.

Barrett, S.C.H. (1983). 'Crop mimicry in weeds', Economic Botany 37 (3), 255-282.

Beltrano, J., Ruscitti, M., Arango, C. and Ronco, M. (2013). 'Changes in the accumulation of shikimic acid in mycorrhized Capsicum annuum L. grown with application of

glyphosate and phosphorus', Theoretical and Experimental Plant Physiology 25 (2), 125-136.

Beversdorf, W.D., Hume, D.J. and Donnellyvanderloo, M.J. (1988). 'Agronomic performance of triazine resistant and susceptible reciprocal spring canola hybrids', Crop Science 28 (6), 932-934.

Christoffers, M.J. (1999). 'Genetic aspects of herbicide-resistant weed management', Weed Technology 13 (3), 647-652.

Crow, J.F. (1983). Genetics notes: An introduction to genetics (8th edition). Burgess Publishing Co., Minneapolis, MN, USA.

Culpepper, A.S., Grey, T.L., Vencill, W.K., Kichler, J.M., Webster, T.M., Brown, S.M., York, A.C., Davis, J.W. and Hanna, W.W. (2006). 'Glyphosate-resistant palmer amaranth (Amaranthus palmeri) confirmed in Georgia', Weed Science 54 (4), 620-626.

Darmency, H. and Gasquez, J. (1990). 'Appearance and spread of triazine resistance in common lambsquarters (Chenopodium album)', Weed Technology 4 (1), 173-177.

Datta, S.K.D. (1981). Principles and practices of rice production. John Wiley and Sons, Chichester, UK.

Denis, M.H. and Delrot, S. (1993). 'Carrier-mediated uptake of glyphosate in broad bean (Vicia faba) via a phosphate transporter', Physiologia Plantarum 87 (4), 569-575.

Devine, M.D. and Shukla, A. (2000). 'Altered target sites as a mechanism of herbicide resistance', Crop Protection 19 (8-10), 881-889.

Duke, S.O., Baerson, S.R. and Rimando, A.M. (2003). Glyphosate. In: Encyclopedia of Agrochemicals. John Wiley & Sons, Inc., New York, USA.

Duke, S.O. and Powles, S.B. (2008). 'Glyphosate: a once-in-a-century herbicide', Pest Management Science 64 (4), 319-325.

Felton, W.L., Wicks, G.A. and Welsby, S.M. (1994). 'A Survey of fallow practices and weed floras in wheat stubble and grain-sorghum in northern New South Wales', Australian Journal of Experimental Agriculture 34 (2), 229-236.

Fischer, A.J., Ateh, C.M., Bayer, D.E. and Hill, J.E. (2000). 'Herbicide-resistant Echinochloa oryzoides and E. phyllopogon in California Oryza sativa fields', Weed Science 48 (2), 225-230.

Foley, M.E. (1987). 'Glyphosate accumulation in leafy spurge laticifers', Canadian Journal of Plant Science 67 (2), 509-510.

Franz, J.E., Mao, M.K. and Sikorski, J.A. (1997). Glyphosate: A unique global herbicide. American Chemical Society, Washington.

Friend, E. (1983). Queensland weed seeds. Queensland Department of Primary Industries, Brisbane, Australia.

Funke, T., Yang, Y., Han, H., Healy-Fried, M., Olesen, S., Becker, A. and Schonbrunn, E. (2009). 'Structural Basis of Glyphosate Resistance Resulting from the Double Mutation Thr(97)  Ile and Pro(101)  Ser in 5-Enolpyruvylshikimate-3-phosphate Synthase from Escherichia coli', Journal of Biological Chemistry 284 (15), 9854- 9860.

Ge, X., D'avignon, D.A., Ackerman, J.J.H. and Sammons, R.D. (2010). 'Rapid vacuolar sequestration: the horseweed glyphosate resistance mechanism', Pest Management Science 66 (4), 345-348.

Gonzalez, J., Garcia, E. and Perdomo, M. (1983). Important rice weeds in Latin America. In The Conference on Weed Control in Rice, Los Baños, Laguna, Philippines, 31 August - 4 September 1981. International Rice Research Institute (IRRI), Los Banos, Philippines, 119-132.

Graham, C.A. and Hill, A.J.M. (2001). Introduction to DNA sequencing. In: Graham, C.A. and Hill, A.J.M. (eds.), Methods in Molecular Biology, vol. 167: DNA sequencing protocols, 2nd ed. Humana Press Inc., Totowa, New Jersey, US, 1-12.

Gressel, J. and Segel, L.A. (1978). 'Paucity of plants evolving genetic resistance to herbicides: possible reasons and implications', Journal of Theoretical Biology 75 (3), 349-371.

Harring, T., Streibig, J.C. and Husted, S. (1998). 'Accumulation of shikimic acid: A technique for screening glyphosate efficacy', Journal of Agricultural and Food Chemistry 46 (10), 4406-4412.

Heap, I. (2014). The international survey of herbicide resistant weeds, viewed 30 July 2014, .

Hetherington, P.R., Marshall, G., Kirkwood, R.C. and Warner, J.M. (1998). 'Absorption and efflux of glyphosate by cell suspensions', Journal of Experimental Botany 49 (320), 527-533.

Hilu, K.W. (1994). 'Evidence from RAPD markers in the evolution of Echinochloa millets (Poaceae)', Plant Systematics and Evolution 189 (3), 247-257.

Hirase, K. and Hoagland, R.E. (2006). 'Characterization of aryl acylamidase activity from propanil-resistant barnyard grass (Echinochloa crus-galli [L.] Beauv.)', Weed Biology and Management 6 (4), 197-203.

Hirschberg, J., Bleecker, A., Kyle, D.J., Mcintosh, L. and Arntzen, C.J. (1984). 'The molecular basic of triazine herbicide resistance in higher plant chloroplasts', Zeitschrift Fur Naturforschung C-a Journal of Biosciences 39 (5), 412-420.

Hoagland, R.E., Norsworthy, J.K., Carey, F. and Talbert, R.E. (2004). 'Metabolically based resistance to the herbicide propanil in Echinochloa species', Weed Science 52 (3), 475- 486.

Holländer-Czytko, H., Sommer, I. and Amrhein, N. (1992). 'Glyphosate tolerance of cultured Corydalis sempervirens cells is acquired by an increased rate of transcription of 5- enolpyruvylshikimate-3-phosphate synthase as well as by a reduced turnover of the enzyme', Plant Molecular Biology 20 (6), 1029-1036.

Holm, L.G., Plucknett, D.L., Pancho, J.V. and Herberger, J.P. (1977). The world's worst weeds: Distribution and biology. The University Press of Hawaii, Honolulu, Hawaii.

Jasieniuk, M., Brûlé-Babel, A.L. and Morrison, I.N. (1996). 'The evolution and genetics of herbicide resistance in weeds', Weed Science 44 (1), 176-193.

Koger, C.H., Poston, D.H., Hayes, R.M. and Montgomery, R.E. (2004). 'Glyphosate-resistant horseweed (Conyza canadensis) in Mississippi', Weed Technology 18 (3), 820-825.

Komoβa, D., Gennity, I. and Sandermann, H. (1992). 'Plant metabolism of herbicides with C- P bonds: glyphosate', Pesticide Biochemistry and Physiology 43 (2), 85-94.

Lee, L.J. and Ngim, J. (2000). 'A first report of glyphosate-resistant goosegrass (Eleusine indica (L) Gaertn) in Malaysia', Pest Management Science 56 (4), 336-339.

Letouze, A. and Gasquez, J. (2001). 'Inheritance of fenoxaprop-P-ethyl resistance in a blackgrass (Alopecurus myosuroides Huds.) population', Theoretical and Applied Genetics 103 (2-3), 288-296.

Levin, D.A. (1981). 'Dispersal versus gene flow in plants', Annals of the Missouri Botanical Garden 68 (2), 233-253.

Marques, M.R., Pereira, J.H., Oliveira, J.S., Basso, L.A., De Azevedo, W.F., Santos, D.S. and Palma, M.S. (2007). 'The inhibition of 5-enolpyruvylshikimate-3-phosphate synthase as a model for development of novel antimicrobials', Current Drug Targets 8 (3), 445- 457.

Matthews, J.M. and Powles, S.B. (1992). Aspects of the population dynamics of selection for herbicide resistance in Lolium rigidum (Gaud). In The 1st International Weed Control Congress, 1992. Weed Science Society of Victoria, Melbourne Australia, 318-320.

Maxam, A.M. and Gilbert, W. (1977). A new method for sequencing DNA. In Proceedings of the National Academy of Sciences of the United States of America, February 1977. USA, 560-564.

Maxwell, B.D. (1992). 'Predicting gene flow from herbicide resistant weeds in annual agriculture systems', Bulletin of the Ecological Society of America 73 (2 Suppl), 264.

Mcgillion, T. and Storrie, A. (2006). Integrated weed management in Australian cropping systems - A training resource for farm advisors. CRC (The Cooperative Research Centre) for Australian Weed Management, Adelaide, South Australia.

Mcgregor, C.E., Lambert, C.A., Greyling, M.M., Louw, J.H. and Warnich, L. (2000). 'A comparative assessment of DNA fingerprinting techniques (RAPD, ISSR, AFLP and SSR) in tetraploid potato (Solanum tuberosum L.) germplasm', Euphytica 113 (2), 135-144.

Menchari, Y., Camilleri, C., Michel, S., Brunel, D., Dessaint, F., Le Corre, V. and Delye, C. (2006). 'Weed response to herbicides: regional-scale distribution of herbicide resistance alleles in the grass weed Alopecurus myosuroides', New Phytologist 171 (4), 861-874.

Merrell, D.J. (1981). Ecological genetics. Longman., London, UK.

Michael, P.W. (1983). Taxonomy and distribution of Echinochloa species with special reference to their occurrence as weeds of rice. In the Conference on Weed Control in Rice, Los Baños, Laguna, Philippines, 31 August - 4 September 1981. International Rice Research Institute (IRRI), Los Banos, Philippines, 291-306.

Mooney, H.A. and Hobbs, R.J. (2000). Invasive species in a changing world. Island Press, Washington, D.C., US.

Morin, F., Vera, V., Nurit, F., Tissut, M. and Marigo, G. (1997). 'Glyphosate uptake in Catharanthus roseus cells: Role of a phosphate transporter', Pesticide Biochemistry and Physiology 58 (1), 13-22.

Mortimer, A.M., Ulfhansen, P.F. and Putwain, P.D. (1992). Modeling herbicide resistance - a study of ecological fitness. In Denholm, I., Devonshire, A.L. and Hollomon, D.W., (eds.), Resistance 91: Achievements and Developments in Combating Pesticide Resistance, Rothamsted Experimental Station, Harpenden, England, July 1991. Elsevier Science Publishers, Essex, UK, 148-164.

Ng, C.H., Ratnam, W., Surif, S. and Ismail, B.S. (2004). 'Inheritance of glyphosate resistance in goosegrass (Eleusine indica)', Weed Science 52 (4), 564-570.

Norsworthy, J.K., Talbert, R.E. and Hoagland, R.E. (1998). 'Chlorophyll fluorescence for rapid detection of propanil-resistant barnyard grass (Echinochloa crus-galli)', Weed Science 46 (2), 163-169.

Perez, A. and Kogan, M. (2003). 'Glyphosate-resistant Lolium multiflorum in Chilean orchards', Weed Research 43 (1), 12-19.

Powles, S.B., Lorraine-Colwill, D.F., Dellow, J.J. and Preston, C. (1998). 'Evolved resistance to glyphosate in rigid ryegrass (Lolium rigidum) in Australia', Weed Science 46 (5), 604-607.

Powles, S.B. and Preston, C. (2006). 'Evolved glyphosate resistance in plants: Biochemical and genetic basis of resistance', Weed Technology 20 (2), 282-289.

Pratley, J., Urwin, N., Stanton, R., Baines, P., Broster, J., Cullis, K., Schafer, D., Bohn, J. and Krueger, R. (1999). 'Resistance to glyphosate in Lolium rigidum. I. Bioevaluation', Weed Science 47 (4), 405-411.

Preston, C. and Powles, S.B. (2002). 'Evolution of herbicide resistance in weeds: initial frequency of target site-based resistance to acetolactate synthase-inhibiting herbicides in Lolium rigidum', Heredity 88 (1), 8-13.

Roy, S., Simon, J.P. and Lapointe, F.J. (2000). 'Determination of the origin of the cold- adapted populations of barnyard grass (Echinochloa crusgalli) in eastern North America: a total-evidence approach using RAPD DNA and DNA sequences', Canadian Journal of Botany 78 (12), 1505-1513.

Rutledge, J., Talbert, R.E. and Sneller, C.H. (2000). 'RAPD analysis of genetic variation among propanil-resistant and -susceptible Echinochloa crusgalli populations in Arkansas', Weed Science 48 (6), 669-674.

Sammons, R.D. and Gaines, T.A. (2014). 'Glyphosate resistance: state of knowledge', Pest Management Science, DOI: 10.1002/ps.3743.

Sanger, F., Nicklen, S. and Coulson, A.R. (1977). 'DNA sequencing with chain terminating inhibitors', Proceedings of the National Academy of Sciences of the United States of America 74 (12), 5463-5467.

Servaites, J.C., Tucci, M.A. and Geiger, D.R. (1987). 'Glyphosate effects on carbon assimilation, ribulose bisphosphate carboxylase activity, and metabolite levels in sugar beet leaves', Plant Physiology 85 (2), 370-374.

Simarmata, M., Kaufmann, J.E. and Penner, D. (2003). 'Potential basis of glyphosate resistance in California rigid ryegrass (Lolium rigidum)', Weed Science 51 (5), 678- 682.

Slatkin, M. (1985a). 'Gene flow in natural populations', Annual Review of Ecology and Systematics 16, 393-430.

Slatkin, M. (1985b). 'Rare alleles as indicators of gene flow', Evolution 39 (1), 53-65.

Slatkin, M. (1987). 'Gene flow and the geographic structure of natural populations', Science 236 (4803), 787-792.

Smith, R.J. (1983). Weeds of major economic importance in rice and yield losses due to weed competition. In The Conference on Weed Control in Rice, Los Baños, Laguna, Philippines, 31 August - 4 September 1981. International Rice Research Institute (IRRI), Los Banos, Philippines, 19-36.

Stallings, G.P., Thill, D.C., Mallorysmith, C.A. and Shafii, B. (1995). 'Pollen-mediated gene flow of sulfonylurea-restant kochia (Kochia scoparia)', Weed Science 43 (1), 95-102.

Swain, D.J. (1973). Weeds and weed control in rice in New South Wales, Australia. In The 4th Asian-Pacific Weed Science Society Conference, Yanco, Australia, 1973. Asian- Pacific Weed Science Society, Rotorua, 134-139.

Vangessel, M.J. (2001). 'Glyphosate-resistant horseweed from Delaware', Weed Science 49 (6), 703-705.

Vencill, W.K. (2002). Herbicide handbook. Weed Science Society of America, Lawrence.

Versaw, W.K. and Harrison, M.J. (2002). 'A chloroplast phosphate transporter, PHT2;1, influences allocation of phosphate within the plant and phosphate-starvation responses', Plant Cell 14 (8), 1751-1766.

Vos, P., Hogers, R., Bleeker, M., Reijans, M., Vandelee, T., Hornes, M., Frijters, A., Pot, J., Peleman, J., Kuiper, M. and Zabeau, M. (1995). 'AFLP: a new technique for DNA fingerprinting', Nucleic Acids Research 23 (21), 4407-4414.

Walker, S.R., Taylor, I.N., Milne, G., Osten, V.A., Hoque, Z. and Farquharson, R.J. (2005). 'A survey of management and economic impact of weeds in dryland cotton cropping

systems of subtropical Australia', Australian Journal of Experimental Agriculture 45 (1), 79-91.

Weed Science Society of America (WSSA) (1998). 'Herbicide Resistance and Herbicide Tolerance Definitions', Weed Technology 12 (4), 789

Williams, J.G.K., Kubelik, A.R., Livak, K.J., Rafalski, J.A. and Tingey, S.V. (1990). 'DNA Polymorphisms amplified by arbitrary primers are useful as genetic markers', Nucleic Acids Research 18 (22), 6531-6535.

Williams, R.C. (1989). 'Restriction fragment length polymorphism (RFLP)', Yearbook of Physical Anthropology 32, 159-184.

Yabuno, T. (1983). Biology of Echinochloa species. In the Conference on Weed Control in Rice, Los Baños, Laguna, Philippines, 31 August - 4 September 1981. International Rice Research Institute (IRRI), Los Banos, Philippines, 307-318.

Chapter 3

Genetic Diversity of Glyphosate Resistant Junglerice (Echinochloa colona)

in New South Wales and Queensland*

Junglerice is an important annual grass species in summer fallows in northern Australian cropping regions where repeated use of glyphosate in summer fallows has resulted in the evolution of glyphosate resistance in this species. Pot trials conducted on E. colona populations collected from northern Australia identified 34 glyphosate resistant populations out of 65 populations surveyed, with resistance level varying among the populations from 2 to

11-fold. The AFLP technique was used to investigate genetic diversity across the samples collected and within two resistant and one susceptible population. Within three populations, one susceptible and two resistant a total of 354 alleles were identified with 99.2% being polymorphic. The frequency of polymorphic alleles within 30 individuals of each of the two resistant populations (81.0 and 83.9%) was not lower than for the susceptible population

(80.8%), suggesting no apparent selection bottleneck. The large genetic diversity present within populations suggests a significant level of outcrossing between individuals. In addition, a single individual from each of 62 populations was compared and high levels of genetic diversity across the individuals identified. These individuals clustered into four main groups with three isolated accessions. Individuals did not cluster geographically, suggesting frequent movement of alleles across the landscape. Additionally, individuals did not cluster by resistance or susceptibility to glyphosate. The results of this study indicate glyphosate resistance evolved at numerous locations across the geographical distribution of the species in northern Australia and that the high genetic diversity within populations likely contributed to rapid resistance evolution.

Nomenclature: Glyphosate; junglerice, Echinochloa colona (L.) Link.

Keywords: herbicide resistance, resistance spread, outcrossing. * This chapter was submitted to the Weed Science journal as: Nguyen TH, Malone MJ, Boutsalis P, Preston C (2015) Genetic diversity of glyphosate resistant junglerice (Echinochloa colona) in New South Wales and Queensland. Weed Sci., Manuscript number: WS-D-15-00006. 35

Echinochloa colona (L.) Link (barnyard grass or jungle rice) is an annual weed often found in paddy fields throughout rice-growing regions around the world (Mooney and Hobbs

2000), as well as being an important grass weed in agriculture worldwide, due to its high competition with many major agricultural crops (Holm et al. 1977). E. colona is distributed throughout agricultural areas in the tropics, especially in Asia, Australia, Pacific Islands,

South America and the Caribbean, and is native to India (Holm et al. 1977).

E. colona is widely distributed across Australia, with the exception of the arid west and

Tasmania (Friend 1983). However, it is most common in the grain-growing areas and in summer fallows in northern Australia (Rew et al. 2005; Osten et al. 2007). In addition, Osten et al. (2007) stated that E. colona is the most troublesome grass weed for many crops in central and southern Queensland, as well as in central and northern New South Wales.

A major tool for managing E. colona in fallows in northern Australia has been repeated applications of the herbicide glyphosate. Glyphosate was introduced to world agriculture in

1974 (Duke et al. 2003) and has become the world’s most widely used herbicide. However, the intensive use of herbicides, including glyphosate, has resulted in the evolution of herbicide resistance in weed species (Norsworthy et al. 1998). At present, 28 weed species worldwide have been reported as glyphosate resistant. In addition to glyphosate, E. colona populations resistant to 12 other herbicides belonging to different mode of action groups have been reported (Heap 2014).

Herbicide resistance can be spread between sites and populations through dispersal of pollen, seed or other propagules (Thill and Mallory-Smith 1997; Christoffers 1999; Delye et al. 2010). Factors contributing to the dispersal include wind, water, animals or machinery

(Benvenuti 2007). The spread of herbicide resistant weeds will lead to an increase in the costs involved in herbicides, labour and fuel in addition to the reduction in crop productivity (Orson

1999; Binimelis et al. 2009; Beltran et al. 2012). For E. colona, a hexaploid grass species (2n

= 6x = 54) (Yabuno 1983) with very low morphologic variability (Asins et al. 1999), the

36 evolution and spread of herbicide resistance has made weed management more complicated and difficult (Danquah et al. 2002). Understanding the role that spread of herbicide resistant pollen or propagules has on the extent and seriousness of the resistance problem can allow better decisions to be made with respect to managing resistance (Thill and Mallory-Smith

1997; Llewellyn and Allen 2006). For example, Legleiter and Bradley (2008) determined that glyphosate resistant genotypes of common waterhemp in Missouri had spread rapidly over an area of 503 ha, possibly as a result of pollen movement.

The genetic variability in weeds is caused by differences in individual genotypes within a weed population and a trend towards changes in genetic characteristics when weed populations are subjected to a selection pressure such as the repeated use of herbicides. The study of genetic variability would be helpful for a better understanding of evolvement and adaptation of weed populations, and hence a proper weed management strategy may be considered. Ruiz-Santaella et al. (2006) used the RAPD marker to analyse the genetic variability of six Echinochloa species and observed that genotypes of the same species were similar. As discussed by these authors, E. colona is more closely related to Echinochloa crus- galli and Echinochloa utilis than other Echinochloa species (Ruiz-Santaella et al. 2006).

The objectives of the present study were to assess the response to glyphosate of purported resistant E. colona populations from New South Wales (NSW) and Queensland

(QLD) in Australia, and evaluate the genetic variability, using AFLP technique, of populations collected from different locations in these two states to understand the potential for spread of glyphosate resistance in this weed species.

Materials and Methods

Plant Material. Seeds of E. colona were obtained from different locations in QLD and NSW

(Appendix 1) during 2008 to 2011 due to suspected resistance to glyphosate. All 65

37 populations (Table 1) were confirmed as E. colona through floristic characteristics described as taxonomic keys by Michael (1983). The seeds were treated with 95% H2SO4 for 30 minutes, rinsed under running water for 60 minutes and germinated on 0.6% (w/v) agar in an environmentally controlled cabinet with 12h light/dark periods at 22oC with 30 µmol m-2s-1 during the light period. After eight days, seedlings at the one leaf stage were transplanted into

8.5 by 9.5 by 9.5 cm pots (Masrac Plastics Pty Ltd., South Australia) containing standard potting mix, with a density of nine seedlings per pot and transferred to a growth room under the 25/23oC day/night temperature regime and a 12-h photoperiod at 553 µmol m-2s-1. At the three to four leaf stage, seedlings were sprayed with glyphosate herbicide at various rates depending on the experiment (for details, see below).

Table 1. Geographical sites of towns where are nearest to origins of junglerice populations and resistance phenotype of populations used in this study with resistance that was determined by treating with glyphosate at 270 g a.e. ha-1.

Population Latitude Longitude Location Phenotype number (S) (E) 1 Bellata, NSW 29.91806 149.79111 Resistant 2 Bellata, NSW 29.91806 149.79111 Resistant 3 Bellata, NSW 29.91806 149.79111 Resistant 4 Bellata, NSW 29.91806 149.79111 Resistant 5 Bellata, NSW 29.91806 149.79111 Resistant 6 Bellata, NSW 29.91806 149.79111 Resistant 7 Boggabilla, NWS 28.60250 150.36000 Susceptible 8 Coonamble, NSW 30.95222 148.38861 Resistant 9 Croppa Creek, NSW 29.12472 150.30556 Susceptible 10 Croppa Creek, NSW 29.12472 150.30556 Susceptible 11 Croppa Creek, NSW 29.12472 150.30556 Susceptible 12 Croppa Creek, NSW 29.12472 150.30556 Resistant 13 Croppa Creek, NSW 29.12472 150.30556 Susceptible 14 Dubbo, NSW 32.24944 148.60472 Susceptible 15 Garah, NSW 29.07722 149.63639 Resistant

Table 1 (continued). Geographical sites of towns where are nearest to origins of junglerice populations and resistance phenotype of populations used in this study with resistance that was determined by treating with glyphosate at 270 g a.e. ha-1.

Population Latitude Longitude Location Phenotype number (S) (E) 16 Gilgandra, NSW 31.71083 148.66944 Susceptible 17 Gurley, NSW 29.73639 149.79972 Susceptible 18 Moree, NSW 29.46417 149.84139 Susceptible 19 Moree, NSW 29.46417 149.84139 Resistant 20 Moree, NSW 29.46417 149.84139 Susceptible 21 Moree, NSW 29.46417 149.84139 Susceptible 22 Moree, NSW 29.46417 149.84139 Susceptible 23 Moree, NSW 29.46417 149.84139 Resistant 24 Moree, NSW 29.46417 149.84139 Resistant 25 Moree, NSW 29.46417 149.84139 Susceptible 26 Moree, NSW 29.46417 149.84139 Resistant 27 Moree, NSW 29.46417 149.84139 Susceptible 28 Moree, NSW 29.46417 149.84139 Susceptible 29 Moree, NSW 29.46417 149.84139 Susceptible 30 Moree, NSW 29.46417 149.84139 Resistant 31 North Star, NSW 28.93222 150.39111 Resistant 32 North Star, NSW 28.93222 150.39111 Susceptible 33 North Star, NSW 28.93222 150.39111 Resistant 34 North Star, NSW 28.93222 150.39111 Resistant 35 North Star, NSW 28.93222 150.39111 Resistant 36 North Star, NSW 28.93222 150.39111 Susceptible 37 North Star, NSW 28.93222 150.39111 Susceptible 38 North Star, NSW 28.93222 150.39111 Resistant 39 North Star, NSW 28.93222 150.39111 Susceptible 40 North Star, NSW 28.93222 150.39111 Susceptible 41 Tamworth, NSW 31.09083 150.93028 Susceptible 42 Yallaroi, NSW 29.15500 150.53833 Susceptible 43 Dalby, QLD 27.18306 151.26361 Susceptible 44 Glenmorgan, QLD 27.24861 149.67639 Resistant 45 Glenmorgan, QLD 27.24861 149.67639 Resistant 46 Goondiwindi, QLD 28.54694 150.30750 Susceptible

Population Latitude Longitude Location Phenotype number (S) (E) 47 Goondiwindi, QLD 28.54694 150.30750 Resistant 48 Goondiwindi, QLD 28.54694 150.30750 Susceptible 49 Goondiwindi, QLD 28.54694 150.30750 Susceptible 50 Goondiwindi, QLD 28.54694 150.30750 Resistant 51 Goondiwindi, QLD 28.54694 150.30750 Resistant 52 Goondiwindi, QLD 28.54694 150.30750 Resistant 53 Goondiwindi, QLD 28.54694 150.30750 Resistant 54 Goondiwindi, QLD 28.54694 150.30750 Susceptible 55 Goondiwindi, QLD 28.54694 150.30750 Resistant 56 Meandarra, QLD 27.32139 149.88111 Susceptible 57 Meandarra, QLD 27.32139 149.88111 Susceptible 58 Meandarra, QLD 27.32139 149.88111 Resistant 59 Millmerran, QLD 27.87306 151.27111 Resistant 60 Moonie, QLD 27.71694 150.36972 Resistant 61 Pittsworth, QLD 27.71611 151.63306 Resistant 62 Pittsworth, QLD 27.71611 151.63306 Resistant 63 Coonamble, NSW 30.95222 148.38861 Resistant 64 Croppa Creek, NSW 29.12472 150.30556 Resistant 65 Moree, NSW 29.46417 149.84139 Susceptible

All populations were used in screening for glyphosate resistance. After screening, eleven populations were chosen for the dose response experiment: 12, 15, 23, 31, 33, 38, 41, 45, 51, 52 and 53. For AFLP experiments, 62 populations (from 1 to 62) were used to investigate the genetic diversity between populations, the remaining three populations (63, 64 and 65) were used in comparing within populations (30 individuals for each population). NSW: New South Wales, QLD: Queensland.

Glyphosate Dose Response Experiment. Seedlings from all populations were tested for resistance to glyphosate (Roundup PowerMax®, Nufarm Australia Limted) at the rate of 270 g a.e. ha-1 with three replicates and herbicide application as described below. Following this, a dose response experiment was conducted on ten resistant and one susceptible population chosen from those initially tested. These were populations 12, 15, 23, 31, 33, 38, 41, 45, 51,

52, 53 (Table 1) that exhibited marked differences in resistance to glyphosate among populations at the initial test. Glyphosate was applied at rates of 0, 270, 540, 1080 and 2160 g a.e. ha-1 with three replicates for each rate. Non-ionic surfactant (alcohol alkoxylate, BS 1000,

Crop Care) at 0.2% (v/v) was added to the glyphosate solution. The glyphosate application was carried out using a moving-boom laboratory twin nozzle sprayer (Hardi ISO F-110-01 standard flat fan, Hardi, Adelaide) placed 40 cm above the seedlings with a water volume of

109.6 L ha-1, a pressure of 250 kPa and a boom speed of one m s-1. Control plants were not treated with herbicide. Survival was assessed at three weeks after glyphosate application, with plants having new green leaf tissue considered survivors.

Mortality data were analysed using PriProbit ver. 1.63 (Sakuma 1998) to determine the relationship of glyphosate dose to number of survivors. LD50 (dose required to control 50% of individuals in the population) estimates generated from the Probit analysis were used to calculate the resistance index (resistance/susceptibility - R/S) to compare the resistance level of populations.

AFLP Analysis. To examine the overall variation across populations of E. colona, DNA was extracted from young green leaf tissue of one individual from each of the 62 E. colona populations (populations 1 to 62 in Table 1) using the DNeasy Plant Mini Kit (Qiagen,

Australia) in accordance with the manufacturer’s instructions. These tissues were sampled prior to applying glyphosate at 270 g a.e. ha-1 and the survival of sampled individuals was not determined after herbicide treatment. In addition, genetic diversity was examined within 3 populations: two resistant populations (63 and 64) and one susceptible population (65) by extracting DNA from 30 individuals of each population. These 30 individuals were grown from seed collected in the field and were not selected with glyphosate prior to DNA extraction.

The AFLP technique described by Vos et al. (1995) with minor modifications was used to investigate the genetic diversity within and between populations of E. colona. Adaptors were first prepared by adding 50 µM of each MseI adaptor and 5 µM each PstI adaptor (Table

2) and heating for 3 minutes at 90oC followed by cooling at room temperature for 30 minutes.

Genomic DNA (120 ng) was then digested and adaptors ligated in a single reaction as follows: PstI (10 units) and MseI (2.5 units) restriction enzymes, adaptors (0.08 µM PstI and

0.83 µM MseI), 1× RL Buffer (50 mM Tris-HCl at pH 7.5, 50 mM Mg-acetate, 250 mM K- acetate and 25 mM DTT), 0.2 mM ATP Cofactor and 1 unit of T4 DNA ligase enzyme were combined in a final volume of 60 µl. This reaction was incubated at 37oC for three hours. Pre- amplification PCR was conducted in a volume of 25 µl including 5.5 µl digested DNA, 0.4

µM each of PstI + A and MseI + C primers (A and C were selective nucleotides joined to the

3’-end of adaptors) (Table 2), 1× ImmoBuffer [160 mM (NH4)2SO4, 1M Tris-HCl pH 8.3,

TM 0.1% Tween-20], 2 mM MgCl2, 1.6 mM dNTPs and 1 unit of Taq Immolase . The amplification was performed by an automated DNA thermal cycler (Eppendorf Mastercycler®

Gradient, Germany) with cycle parameters as follows: an initial denaturing step of 95oC for

10 minutes, followed by 21 cycles of denaturation at 94oC for 30 seconds, annealing at 60oC for 1 minute and extension at 72oC for 1 minute.

Table 2. AFLP adaptors and primers.

Adaptor and primer name Sequence 5’-3’ DNA Digestion MseI adaptor 1 GAC GAT GAG TCC TGA G MseI adaptor 2 TAC TCA GGA CTC AT PstI adaptor 1 CTC GTA GAC TGC GTA CAT GCA PstI adaptor 2 TGT ACG CAG TCT AC Pre-amplification PCR MseI pre-selective primer+C GAT GAG TCC TGA GTA AC PstI pre-selective primer+A GAC TGC GTA CAT GCA GA Selective PCR amplification MseI selective primer+CAA Fluro (VIC) GAT GAG TCC TGA GTA ACA A MseI selective primer+CAT Fluro (FAM) GAT GAG TCC TGA GTA ACA T PstI selective primer+AGC GAC TGC GTA CAT GCA GAG C

The pre-amplification reaction was subsequently diluted with nanopure water at a ratio of

1:6.4. Selective PCR amplification was then carried out using 5.5 µl of the diluted pre- amplification PCR reaction as template. Duplicate reactions were performed, both using PstI

+ AGC primer (0.4 µM) but differing in the MseI selective primers (0.4 µM): either MseI +

CAA or MseI + CAT (Table 2). The MseI primers at this step were fluorescently labelled. The other components of the reaction were the same as that in the pre-amplification. The following thermal cycles were applied: an initial denaturation for 10 minutes at 95oC, followed by cycling of denaturation at 94oC for 30 s, annealing at 65oC for 30 s and extension at 72oC for 90 s, with a decrease in the annealing temperature by 1oC each cycle until 56oC was reached. This was then followed by 24 cycles with denaturation at 94oC for 30 s, annealing at 56oC for 30 s and extension at 72oC for 90 s. PCR products were analysed basing on capillary electrophoresis using an Applied Biosystems 3730, fluorescence-based DNA analyser by the Australian Genome Research Facility (AGRF), Australia.

AFLP data were viewed and edited using GeneMapper® software ver. 4.0 (Applied

Biosystems, USA) and informative peaks were recorded as a binary data set with 0 for absence and 1 for presence at each locus. The binary data were used to analyse the genetic relationships, and similarity and distance matrices were computed with Jaccard’s coefficient using DendroUPGMA, a dendrogram construction utility (Garcia-Vallve et al. 1999). The phenograms were displayed using TreeView software ver. 1.6.6 (Page 1996).

Results and Discussion

Response to Glyphosate. Amongst the 65 E. colona populations collected from northern

Australia that were treated with glyphosate at 270 g ha-1, 34 populations had greater than 20% survival and were classified as resistant to glyphosate (Boutsalis et al. 2012) including 13 populations collected from QLD and 21 from NSW (Table 1).

The results of the dose-response experiment showed a range of responses to glyphosate.

The susceptible population (41) was easily controlled with glyphosate and had an LD50

(concentration of glyphosate required to kill 50% of the population) of 110 g ha-1, well below the normal use rate of this herbicide (Table 3). The LD50 of the other populations tested ranged from 234 to 1289 g ha-1 making them 2 to 11-fold resistant to glyphosate compared with the susceptible population. The most resistant population (23) was from Moree in NSW, whereas the next most resistant population (45) was from Glenmorgan in QLD. This data demonstrates that the level of resistance in E. colona varies across the area of collection.

Table 3. The glyphosate resistance levels of ten junglerice populations. The data in the table exhibits the glyphosate dose required to control 50% of susceptible and resistant junglerice populations (LD50) and the resistance index (R/S) for the resistant populations compared with the susceptible population (41).

-1 Population LD50 (g a.e. ha ) R/S

23 (R) 1289 11.6 45 (R) 1069 9.7 33 (R) 867 7.8 31 (R) 635 5.7 51 (R) 595 5.4 53 (R) 508 4.6 52 (R) 392 3.5 15 (R) 279 2.5 12 (R) 263 2.4 38 (R) 234 2.1 41 (S) 110 -

This research has determined that glyphosate resistance in E. colona is widespread in the grain-growing regions of NSW and QLD in Australia. Populations that had strong resistance

44 to glyphosate occurred in both states. These two states of Australia are where E. colona is a common weed species infesting summer fallows (Osten et al. 2007). In this region, summer fallows are typically treated with herbicides several times a season to remove weed growth and conserve summer moisture. Glyphosate is the most commonly used herbicide for this purpose (Osten et al. 2007). Resistance to glyphosate was reported in E. colona in NSW in

2008 (Storrie et al. 2008) and the present study has demonstrated that resistance is now present in at least 34 populations in NSW and QLD. Recently, glyphosate resistance was also reported in a population of E. colona from Western Australia (Gaines et al. 2012), more than

2000 km from the locations in NSW and QLD, demonstrating how widespread the problem has become.

The ten glyphosate resistant populations chosen for full dose response experiments showed varying levels of resistance to glyphosate (Table 3). There are a number of mechanisms known to endow resistance to glyphosate (Shaner et al. 2012), and different mechanisms result in different levels of resistance (Preston et al. 2009). The resistance mechanisms present within the populations of E. colona are not known; however, the different responses to glyphosate suggest the populations do not all carry the same resistance allele.

AFLP Analysis. The AFLP technique was used to investigate the genetic diversity of E. colona populations. The amount of genetic variation across the range of populations was assessed using a single individual from each of 62 populations. The amount of genetic variation within populations was investigated in three populations: two resistant and one susceptible.

Genetic Diversity across E. colona Populations. To assess genetic diversity across the E. colona populations, AFLPs arising from two primer combinations were used to analyse polymorphisms in a single individual from 62 populations of E. colona (Table 1). A total of

70 alleles ranging in length from 45 to 300 bp were reliably detected by the two primer combinations (Table 4). The primer combination of PstI with MseI + CAT produced 49 alleles and all alleles were polymorphic among the populations. The primer pair MseI + CAA produced 21 alleles and again all alleles were polymorphic among the 62 samples.

Table 4. Between-population genetic structure: fragment lengths, total number of fragments, number and percentage of polymorphic fragments produced by each primer set used to analyse the polymorphisms of one individual from each of 62 junglerice populations.

Fragment Total number Number of Polymorphic Primer lengths of fragments polymorphic fragments percentage

MseI + CAT 45-300 49 49 100

MseI + CAA 45-300 21 21 100

Total 70 70

Average 100

The phenogram produced by the UPGMA algorithm using Jaccard’s coefficient grouped the 62 populations into four distinct clusters, with three populations ungrouped (25, 33 and

45) (Figure 1). The largest cluster contained 44 individuals with the other three clusters containing between two and nine individuals. Only one cluster (cluster II) contained individuals from a single location (Goondiwindi); all other clusters contained individuals from many different locations. The phenogram also showed that individuals did not cluster according to herbicide resistance. For example, individuals from six resistant populations (1 to 6) sampled from near Bellata in NSW were split between two clusters (I and IV).

The fact that the glyphosate resistant populations of E. colona are widespread in distribution and have different levels of resistance to glyphosate, suggests that glyphosate resistance has appeared in this species multiple times. This was confirmed by the AFLP analysis, which demonstrated considerable genetic variation within E. colona in Australia

Figure 1. UPGMA phenogram of the genetic relationship between E. colona populations collected across QLD and NSW, Australia. The numbers on the phenogram correspond to the number given to each population in Table 1. The susceptible populations are bold and underlined. 47 with the presence of many different genotypes. While a single large cluster contained 44 of the samples, even within this cluster there was considerable genetic diversity (Figure 1). High genetic diversity within species will increase the likelihood of herbicide resistance evolving

(Powles and Yu 2010).

This study also demonstrated no genetic grouping of glyphosate resistant individuals from across NSW and QLD. This suggests glyphosate resistant populations have evolved from local susceptible populations, rather than resistance arising a few times and then spreading across the region. The fact that six resistant individuals from different sites near

Bellata in NSW were spread across two clusters (I and IV) supports the conclusion that resistance to glyphosate has occurred independently even within a small area. At the same time, the grouping of individuals from different geographical regions suggests gene exchange between E. colona populations in northern Australia. This may be through seed movement in farm machinery, in farm produce or by flood events. Other studies comparing the genetic relatedness of resistant and susceptible weed populations have come to similar conclusions for

Lactuca serriola L. in South Australia (Lu et al. 2007), Chenopodium album L. in Europe

(Aper et al. 2010), Echinochloa oryzoides (Ard.) Fritsch in California (Osuna et al. 2011) and

Amaranthus palmeri S. Wats. in the USA (Chandi et al. 2013). However, in several studies there was evidence of spread of resistance between sites as well as independent selection

(Baker et al. 2007; Lu et al. 2007; Osuna et al. 2011; Okada et al. 2013).

Genetic Diversity within Populations. To assess genetic variability within populations, a study of 30 E. colona individuals from each of three different populations was undertaken using the same two primer pairs as described before. The primers produced a total of 354 AFLP fragments ranging in length from 15 to 615 bp. Of the 354 alleles, 351 were polymorphic, giving an average polymorphism percentage of 99.2% (Table 5). The frequency of polymorphic alleles was similar; between 80.8% and 83.9% across the three populations. For all three populations, the primer combination of PstI + AGC and MseI + CAA produced fewer alleles. The data suggests that the diversity in genotypes of the resistant populations used was

48 as high as that of the susceptible population. Hence there is no evidence in this data of a founder effect resulting from selection for glyphosate resistance.

Table 5. Within-population genetic structure: fragment lengths, total number of fragments, number and percentage of polymorphic fragments produced by each primer set used to analyse the polymorphisms of one individual from each of two glyphosate resistant junglerice populations (63 and 64) and one susceptible population (65) (30 individuals for each population).

Fragment Total number Number of Polymorphic Population Primer lengths of fragments polymorphic fragments percentage

63 (R) MseI + CAT 15-615 203 174 85.7

MseI + CAA 15-615 151 124 82.1

Total 354 298

Average 83.9

64 (R) MseI + CAT 15-615 203 162 79.8

MseI + CAA 15-615 151 124 82.1

Total 354 286

Average 81.0

65 (S) MseI + CAT 15-615 203 160 78.8

MseI + CAA 15-615 151 125 82.8

Total 354 285

Average 80.8

Primers and populations 354 351 99.2 combined

The genetic relationship among individuals within three populations generated by the

UPGMA is shown in Figure 2. In the dendrogram, all but five individuals grouped into five major clusters. All these five ungrouped samples were derived from the two resistant

Figure 2. UPGMA phenogram showing the genetic relationship within two resistant populations (63 and 64 in Table 1) and the susceptible population (65) of E. colona collected from three separate fields in NSW, Australia. The number before the dash is the number assigned to these populations in Table 1 and the number after the dash is an individual plant from that population. The susceptible individuals are bold and underlined.

50 populations 63 (63-19) and 64 (64-17, 64-18, 64-21 and 64-30). All clusters, except cluster

IV, were composed of individuals from more than one population. The data suggests that there is considerable genetic diversity within populations of E. colona in northern Australia.

The examination of 30 individuals each from three populations was to better understand the genetic variation in E. colona. These populations were collected from three different fields at different locations in NSW. High levels of genetic diversity were identified within all three populations. Echinochloa spp. are generally considered to be largely self-pollinating (Maun and Barrett 1986; Honek and Martinkova 1996; Osuna et al. 2011). Therefore, the high genetic diversity obtained within E. colona populations was unexpected. A high level of variation suggests either frequent movement of seed material between sites or significant outcrossing occurs in E. colona. In addition, no evidence of a genetic bottleneck was evident in the two resistant populations, as these populations had similar genetic variation to the susceptible population (Table 5). Founder effects are expected to occur with selection for herbicide resistance where only a small number of individuals in the original population carry the resistance allele (Jasieniuk et al. 1996). Founder effects have previously been identified in herbicide resistant weed populations of Poa annua L. (Mengistu et al. 2000) and C. album

(Aper et al. 2010). Several factors may mediate against the identification of founder effects in populations. For example, if there is cross-pollination and possession of a dominant herbicide resistant trait, the trait will be readily shared among individuals of the population. Low genetic diversity within populations will also make it difficult to identify founder effects; although that would not have been the case in this study.

The UPGMA phenogram of the 90 individuals across three populations showed no clustering by population (Figure 2). The lack of clustering suggests considerable gene flow between populations across the region and this might be due to movement of weed seeds or pollen. Glyphosate resistant A. palmeri populations from Georgia and North Carolina demonstrated some clustering with four populations clustering together and separately from four other populations (Chandi et al. 2013). However, this clustering was neither geographic,

51 nor related to glyphosate resistance status. Okada et al. (2013) showed that glyphosate resistant Conyza canadensis (L.) Cronq. populations in California showed clustering based on geographical areas. They further concluded that glyphosate resistance occurred and spread well before it was detected in California. Echinochloa colona seed has no specific modifications for long-distance seed movement; therefore, movement has most likely occurred as a contaminant on farm machinery, seed for sowing or by flood waters. The genetic diversity among 90 individuals within the three populations examined could have arisen through movement of seed between populations, but is more likely the result of cross- pollination because evidence of outcrossing in this grass species was detected as presented in

Chapter 5. Our results are unable to determine whether seed movement occurred prior to the evolution of glyphosate resistance or afterwards, as was the case for C. canadensis in

California (Okada et al. 2013). However, it is important that good hygiene practices are adopted to limit the movement of glyphosate resistant E. colona seed.

This study has identified 34 glyphosate resistant E. colona populations from northern

New South Wales and Queensland demonstrating glyphosate resistance is widespread in this region. The levels of glyphosate resistance compared to a known susceptible population ranged from 2- to almost 12-fold. There was high genetic diversity across the region sampled and within glyphosate resistant E. colona populations, indicating glyphosate resistance has evolved numerous times in this species. Therefore, over-reliance on glyphosate for weed control has been the most important factor in the current extent of resistance in this weed species. The high levels of glyphosate resistance identified in some of the populations will make them impossible to control with glyphosate and other weed management practices will have to be used. Additionally, farmers should adopt effective methods to limit the movement of glyphosate resistant E. colona seeds.

Acknowledgements

This study was supported by the Grains Research and Development Corporation. Hoan T.

Nguyen was the recipient of a postgraduate scholarship from the Ministry of Education and

Training, Vietnam.

Literature Cited

Aper J, De Riek J, Mechant E, De Cauwer B, Bulcke R, Reheul D (2010) The origin of

herbicide-resistant Chenopodium album: analysis of genetic variation and population

structure. Weed Res. 50: 235-244.

Asins MJ, Carretero JL, Del Busto A, Carbonell EA, De Barreda DG (1999) Morphologic and

isozyme variation in barnyardgrass (Echinochloa) weed species. Weed Technol. 13:

209-215.

Baker J, Hidayat I, Preston C (2007) Molecular tools for understanding distribution and

spread of weed genotypes. Crop Prot. 26: 198-205.

Beltran JC, Pannell DJ, Doole GJ (2012) Economic implications of herbicide resistance and

high labour costs for management of annual barnyardgrass (Echinochloa crus-galli) in

Philippine rice farming systems. Crop Prot. 31: 31-39.

Benvenuti S (2007) Weed seed movement and dispersal strategies in the agricultural

environment. Weed Biol. Manag. 7: 141-157.

Binimelis R, Pengue W, Monterroso I (2009) "Transgenic treadmill": Responses to the

emergence and spread of glyphosate-resistant johnsongrass in Argentina. Geoforum 40:

623-633.

Boutsalis P, Gill GS, Preston C (2012) Incidence of herbicide resistance in rigid ryegrass

(Lolium rigidum) across southeastern Australia. Weed Technol. 26: 391-398.

Chandi A, Milla-Lewis SR, Jordan DL, York AC, Burton JD, Zuleta MC, Whitaker JR,

Culpepper AS (2013) Use of AFLP markers to assess genetic diversity in palmer

amaranth (Amaranthus palmeri) populations from North Carolina and Georgia. Weed

Sci. 61: 136-145.

Christoffers MJ (1999) Genetic aspects of herbicide-resistant weed management. Weed

Technol. 13: 647-652.

Danquah EY, Johnson DE, Riches C, Arnold GM, Karp A (2002) Genetic diversity in

Echinochloa spp. collected from different geographic origins and within rice fields in

Côte d'Ivoire. Weed Res. 42: 394-405.

Delye C, Michel S, Berard A, Chauvel B, Brunel D, Guillemin J-P, Dessaint F, Le Corre V

(2010) Geographical variation in resistance to acetyl-coenzyme A carboxylase-

inhibiting herbicides across the range of the arable weed Alopecurus myosuroides

(black-grass). New Phytol. 186: 1005-1017.

Duke SO, Baerson SR, Rimando AM (2003). Glyphosate. In Encyclopedia of Agrochemicals.

John Wiley & Sons, Inc., New York, USA.

Friend E (1983) Queensland Weed Seeds. Queensland Department of Primary Industries. 206

Gaines TA, Cripps A, Powles SB (2012) Evolved resistance to glyphosate in junglerice

(Echinochloa colona) from the tropical Ord River region in Australia. Weed Technol.

26: 480-484.

Garcia-Vallve S, Palau J, Romeu A (1999) Horizontal gene transfer in glycosyl hydrolases

inferred from codon usage in Escherichia coli and Bacillus subtilis. Mol. Biol. Evol. 16:

1125-1134 (http://genomes.urv.es/UPGMA/).

Heap I (2014) The International Survey of Herbicide Resistant Weeds.

http://www.weedscience.org. Accessed: July 30, 2014.

Holm LG, Plucknett DL, Pancho JV, Herberger JP (1977) The World's Worst Weeds:

Distribution and Biology. The University Press of Hawaii. 610 p.

Honek A, Martinkova Z (1996) Geographic variation in seed dormancy among populations of

Echinochloa crus-galli. Oecologia 108: 419-423.

Jasieniuk M, Brûlé-Babel AL, Morrison IN (1996) The evolution and genetics of herbicide

resistance in weeds. Weed Sci. 44: 176-193.

Legleiter TR, Bradley KW (2008) Glyphosate and multiple herbicide resistance in common

waterhemp (Amaranthus rudis) populations from Missouri. Weed Sci. 56: 582-587.

Llewellyn RS, Allen DM (2006) Expected mobility of herbicide resistance via weed seeds

and pollen in a Western Australian cropping region. Crop Prot. 25: 520-526.

Lu YQ, Baker J, Preston C (2007) The spread of resistance to acetolactate synthase inhibiting

herbicides in a wind borne, self-pollinated weed species, Lactuca serriola L. Theor.

Appl. Genet. 115: 443-450.

Maun MA, Barrett SCH (1986) The biology of Canadian weeds. 77. Echinochloa crus-galli

(L) Beauv. Can. J. Plant Sci. 66: 739-759.

Mengistu LW, Mueller-Warrant GW, Liston A, Barker RE (2000) psbA mutation (valine219 to

isoleucine) in Poa annua resistant to metribuzin and diuron. Pest Manag. Sci. 56: 209-

217.

Michael PW (1983) Taxonomy and distribution of Echinochloa species with special reference

to their occurrence as weeds of rice. Pp 291-306 in Proceedings of the Conference on

Weed Control in Rice. International Rice Research Institute (IRRI).

Mooney HA, Hobbs RJ (2000) Invasive Species in A Changing World. Island Press. i + 457

Norsworthy JK, Talbert RE, Hoagland RE (1998) Chlorophyll fluorescence for rapid

detection of propanil-resistant barnyard grass (Echinochloa crus-galli). Weed Sci. 46:

163-169.

Okada M, Hanson BD, Hembree KJ, Peng Y, Shrestha A, Stewart CN, Jr., Wright SD,

Jasieniuk M (2013) Evolution and spread of glyphosate resistance in Conyza canadensis

in California. Evol. Appl. 6: 761-777.

Orson JH (1999) The cost to the farmer of herbicide resistance. Weed Technol. 13: 607-611.

Osten VA, Walker SR, Storrie A, Widderick M, Moylan P, Robinson GR, Galea K (2007)

Survey of weed flora and management relative to cropping practices in the north-eastern

grain region of Australia. Aust. J. Exp. Agr. 47: 57-70.

Osuna MD, Okada M, Ahmad R, Fischer AJ, Jasieniuk M (2011) Genetic diversity and spread

of thiobencarb resistant early watergrass (Echinochloa oryzoides) in California. Weed

Sci. 59: 195-201.

Page RDM (1996) TreeView: An application to display phylogenetic trees on personal

computers. Comput. Appl. Biosci. 12: 357-358.

Powles SB, Yu Q (2010) Evolution in action: Plants resistant to herbicides. Annu. Rev. Plant

Biol. 61: 317-347.

Preston C, Wakelin AM, Dolman FC, Bostamam Y, Boutsalis P (2009) A decade of

glyphosate-resistant Lolium around the world: Mechanisms, genes, fitness, and

agronomic management. Weed Sci. 57: 435-441.

Rew LJ, Medd RW, Van De Ven R, Gavin JJ, Robinson GR, Tuitee M, Barnes J, Walker S

(2005) Weed species richness, density and relative abundance on farms in the

subtropical grain region of Australia. Aust. J. Exp. Agr. 45: 711-723.

Ruiz-Santaella JP, Bastida F, Franco AR, De Prado R (2006) Morphological and molecular

characterization of different Echinochloa spp. and Oryza sativa populations. J. Agric.

Food Chem. 54: 1166-1172.

Sakuma M (1998) Probit analysis of preference data. Appl. Entomol. Zool. 33: 339-347.

Shaner DL, Lindenmeyer RB, Ostlie MH (2012) What have the mechanisms of resistance to

glyphosate taught us?. Pest Manag. Sci. 68: 3-9.

Storrie A, Cook T, Boutsalis P, Penberthy D, Moylan P (2008) Glyphosate resistance in

awnless barnyard grass (Echinochloa colona (L.) Link) and its implications for

Australian farming systems. Pp 74-76 in Proceedings of the 16th Australian Weeds

Conference. Queensland Weed Society.

Thill DC, Mallory-Smith CA (1997) The nature and consequence of weed spread in cropping

systems. Weed Sci. 45: 337-342.

Vos P, Hogers R, Bleeker M, Reijans M, Vandelee T, Hornes M, Frijters A, Pot J, Peleman J,

Kuiper M, Zabeau M (1995) AFLP: a new technique for DNA fingerprinting. Nuc.

Acids Res. 23: 4407-4414.

Yabuno T (1983) Biology of Echinochloa species. Pp 307-318 in Proceedings of the

Conference on Weed Control in Rice. International Rice Research Institute (IRRI).

Chapter 4

Temperature Influences the Level of Glyphosate Resistance

in Barnyard Grass (Echinochloa colona)

Abstract

BACKGROUND: Echinochloa colona is an important summer-growing weed species in cropping regions of northern Australia that has evolved resistance to glyphosate due to intensive use of this herbicide in summer fallow.

RESULTS: Pot trials conducted at 20oC and 30oC on six E. colona populations showed a significant increase in the level of glyphosate resistance in resistant populations at 30oC compared with 20oC. However, there was no influence of growth temperature on glyphosate susceptibility of the sensitive population. Sequencing of the target-site gene (EPSPS) of the six populations identified a mutation leading to a change from proline to serine at position

106 of EPSPS enzyme in the most resistant population A533.1 only. EPSPS gene amplification was not detected in any resistant populations examined. More glyphosate was absorbed by plants of two resistant and one susceptible population at 20oC than at 30oC.

However, few differences in glyphosate translocation occurred from the treated leaf to other plant parts between populations or temperatures. Therefore, the amount of glyphosate present in each plant part would be about half at 30oC compared with 20oC.

CONCLUSION: There is reduced efficacy of glyphosate at high temperatures on resistant E. colona populations, making these populations harder to control in summer.

Keywords: Barnyard grass; Echinochloa colona; glyphosate resistance; resistance mechanism; EPSPS; shikimate; absorption; translocation.

* This chapter was submitted to the Pest Management Science journal as: Nguyen TH, Malone MJ, Boutsalis P, Shirley N and Preston C, Temperature influences the level of glyphosate resistance in barnyard grass (Echinochloa colona). Pest Manag Sci, Manuscript number: PM-15-0127 (2015). 58

1 INTRODUCTION

Echinochloa colona (L.) Link (barnyard grass) was rated as one of the top three worst weeds in vegetable crops throughout the world1,2 owing to its difficulty of control. Herbicides have become a highly effective way of managing E. colona and are commonly used in most countries where this grass species occurs. Consequently, E. colona has evolved resistance to several different herbicides3.

Since the introduction of glyphosate to agriculture in 19744, it has become the world’s most widely used herbicide. The introduction of genetically modified crops with resistance to glyphosate has increased dependence on glyphosate in cropping systems where these crops are grown5. However, continued dependence on glyphosate over a large area ranging from field agricultural systems to inner-city landscapes has increased the number of weed species, including E. colona, that have evolved resistance to this herbicide5. Glyphosate resistant E. colona has been found in several regions in the world including New South Wales (NSW),

Queensland (QLD), Western Australia (WA) (Australia), California (USA) and Santa Fe

(Argentina)6.

Environmental factors have an impact on glyphosate activity and may affect the expression of glyphosate resistance in plants7. Of these various factors, temperature has been demonstrated to noticeably affect the absorption and translocation of glyphosate to vegetative organs of plants in a number of studies8-15. In addition, a reduction in herbicide translocation in plants has been identified as one of the mechanisms of glyphosate resistance; and these plants have included annual ryegrass (Lolium rigidum)16, Italian ryegrass (Lolium multiflorum)17,18, and horseweed (Conyza canadensis)19. Temperature has an effect not only on mortality of plants, but also on the accumulation of shikimic acid in leaves following glyphosate treatment. In Australia, glyphosate resistance in E. colona has occurred in summer fallows in QLD and NSW, where conditions at the time of application of glyphosate are typically very hot (30 - 40oC). Therefore, this study investigated whether temperature has an

59 influence on the expression of glyphosate resistance in E. colona and if so, whether differences in glyphosate absorption and translocation are involved.

2 MATERIALS AND METHODS

2.1 Plant material

E. colona seeds of five resistant and one susceptible population were collected from fallow fields in NSW and QLD. The locations of the nearest towns are given in Table 1. Seeds were treated with 95% H2SO4 for 30 min, rinsed under running water for 1 h and germinated on

0.6% (w/v) agar in an environmentally controlled cabinet at 12 h light and 12 h dark periods at 22oC with 30 µmol m-2s-1 during the light period.

Table 1. Locations are nearest to origins of E. colona populations used in this study

Population Location (nearest town) Primary phenotype

A533.1 Moree, NSW Resistant

A818 Moree, NSW Resistant

RL11 North Star, NSW Resistant

1307.3 Goondiwindi, QLD Resistant

RL21 Croppa Creek, NSW Resistant

Echi S Tamworth, NSW Susceptible

2.2 Temperature response to glyphosate

In order to evaluate the impact of different temperatures on glyphosate resistance, eight days after germination the one-leaf seedlings were transplanted into 8.5 x 9.5 x 9.5 cm pots

(Masrac Plastic Pty Ltd., South Australia) containing standard potting mix at a density of nine seedlings per pot. Plants were grown in controlled environment chambers under two different

60 temperatures; the low temperature experiment was conducted under 20/18oC day/night and a

12-h photoperiod at 553 µmol m-2s-1 while the high temperature experiment was conducted under 30/28oC day/night with the same light intensity and photoperiod. Relative humidity was the same in each growth chamber. At the 3 to 4 leaf stage, seedlings were treated with glyphosate herbicide (Roundup PowerMax®, Nufarm Australia Limited) at rates from 0 to

1920 g a.e. ha-1, plus 0.2% (v/v) of non-ionic surfactant (alcohol alkoxylate, BS 100, Crop

Care), with four replicates for each rate. Herbicide application was carried out using a moving-boom laboratory twin nozzle sprayer (Hardi ISO F-110-01 standard flat fan, Hardi,

Adelaide) placed 40 cm above the seedlings with a water volume of 109.6 L ha-1 at a pressure of 250 kPa and a boom speed of 1 ms-1. Control plants were treated with non-ionic surfactant only. At three weeks after glyphosate application the number of surviving plants was recorded as plants with new green leaf tissue since treatment.

The dose response experiments were repeated in time. The survival data were analysed using PriProbit ver. 1.6320.

2.3 Identifying target-site mutations

Young green leaf tissue was sampled from one individual plant from each of the six populations (Table 1) and DNA extracted using the DNeasy Plant Mini Kit (Qiagen,

Australia) in accordance with the manufacturer’s instructions.

PCR reactions were conducted in 25 μl volumes containing 80 - 100 ng DNA, 1 × High

Fidelity PCR Buffer [600 mM Tris-SO4 (pH 8.9), 180 mM (NH4)2SO4], 0.4 mM dNTP

® mixture, 4 mM MgSO4, 0.4 μM of each specific primer and 1 unit of Platinum Taq DNA

Polymerase High Fidelity (Invitrogen, Australia). Forward and reverse primers (Table 2) were used for amplification of an approximately 500 bp fragment of the EPSPS (5- enolpyruvylshikimate-3-phosphate synthase) gene. An automated DNA thermal cycler

(Eppendorf Mastercycler® Gradient, Germany) was used for amplification with the cycle parameters as follows: 3 min denaturing at 94°C; 40 cycles of 30 s denaturation at 94°C, 30 s annealing at 56°C and 1 min elongation at 68°C, and a final extension for 7 min at 68°C.

PCR products were examined on 1.5% agarose gels stained with 1 × SYBR® Safe DNA gel stain. Samples were electrophoresed in 1× TAE Buffer [40 mM Trizma base, 1 mM

Na2EDTA (pH to 8) with glacial acetic acid] at 90 volts and photographed under UV light

(λ302nm). DNA fragment sizes were estimated via comparison to a DNA ladder with known size bands (Easy Ladder, Bioline, Australia). PCR products were sequenced at the Australian

Genome Research Facility (AGRF) Ltd., Australia, using the same primers used for amplification.

DNA sequence data were assembled, compared and analysed using ContiExpress from the

Vector-NTi Advance 11.5 programs (Invitrogen, USA).

2.4 EPSPS gene relative copy number

The genomic DNA of two resistant populations (A533.1 and 1307.3) and a susceptible population (Echi S) were used to investigate whether amplification of the EPSPS gene was contributing to resistance. Quantitative real-time PCR (qPCR) was used to analyse the EPSPS genomic copy number relative to a control gene, ALS (acetolactate synthase). Primers and probes sequences are presented in Table 2.

Table 2. The primers and probes used to identify the target-site mutation and determine the genomic copy number of EPSPS and ALS using quantitative real-time PCR

Primer name Primer sequence 5’-3’

Target-site mutation AW F AACAGTGAGGAYGTYCACTACATGCT AW R CGAACA GGAGGGCAMTCAGTGCCAAG EPSPS gene copy number EPSPS-qF GGTGGAAATGCAACGTAAGG EPSPS-qR TGCCAAGGAAACAATCAACA EPSPSProbe TGGTGACTTAGTTGTCGGTTTGAAGCA+FAM ALS-qF GACTCCATCCCCATGGTC ALS-qR CGAGGTAGTTGTGCTTGGTG ALSProbe CCAATCGTCGAGGTCACCCGCT+TET

A template for the standard curve was prepared as described in Burton et al.21. A dilution series of 107, 106, 105 and 104 copies/µl of qPCR templates was used to produce primer efficiency curves. A composite standard set was prepared for the two genes and combined to give a four point standard curve for both genes but were assembled in opposite order, one gene from high copy number to low, the other from low to high, to ensure the linearity of the two gene assay standard curves could be assessed. The linearity was found to be satisfactory

(R2>.98) for both standards. A Taqman based assay using Dual-Labeled BHQ FRET probes

(Bioresearch Technologies, Petaluma, California) (Table 2) was used. The probes were designed with different flourophores so the genes could be assayed independently in one qPCR reaction. QPCR reactions of 10 µl contained 5 µl of SsoFast Probe Supermix

(Gladesville, New South Wales, Australia), 1µM EPSPS and ALS forward and reverse primers, 0.3 µM EPSPS and ALS probes, 2 µl of DNA. QPCR experiments were assembled by hand, in duplicate and run on a RG3000 Rotor-Gene real-time thermal cycler with the

63 following parameters: 3 min at 95°C followed by 45 cycles of 15 s at 95°C, 16 s at 60°C acquiring at 510 nm (EPSPSProbe) and at 555 nm (ALSProbe).

Standard curves were used to calculate the amount of EPSPS and ALS in the samples. The ratio of EPSPS to ALS was calculated for each. The average and the standard deviation of the duplicate reactions were recorded. The results were presented as the increased levels of

EPSPS copy number relative to ALS.

2.5 Shikimate assay

After germination, seedlings at the one leaf stage were grown in 25 cm diameter x 24 cm height pots (Masrac Plastics Pty Ltd., South Australia) containing standard potting mix and placed under the two temperature regimes as described previously, until the plants were well tillered.

The shikimate assay described by Shaner et al.22 was used. From a single completely expanded young leaf of each plant of two resistant (A533.1 and A818) and one susceptible

(Echi S) population, five 5-mm diameter leaf discs were excised using a cork borer and each disc placed into a single well of a 96-well flat-bottomed microtiter plate containing 0, 50, 200,

500 or 1000 µM glyphosate (Roundup PowerMax®, Nufarm Australia Limited) and 10 mM phosphate buffer (pH 7) with one disc from each leaf at each concentration. The plates were incubated under fluorescent lights at 553 µmol m-2s-1 in the growth room for 16 h. The incubating temperature was maintained at 20oC for the temperature regime 20/18oC and at

30oC for the temperature regime 30/28oC. Each sample was then treated with 0.05 M HCl and the samples freeze thawed through two cycles of -20oC for 90 minutes followed by 60oC for

20 minutes until leaf tissue was no longer green. From each well, 25 µl of the solution was transferred to fresh microtiter plates for determining shikimate levels. Shikimic acid at concentrations of 1, 2.5, 5, 10, 25 and 50 µM was added to empty wells as standards. A

64 mixture of 0.25% (w/v) periodic acid and 0.25% (w/v) sodium m-periodate was added to wells of both extract and standard shikimic acid at a volume of 100 µl per well. The samples were incubated at room temperature for 60 minutes and afterwards added with 100 µl of freshly made quench buffer (mixture of 0.6 M NaOH and 0.22 M Na2SO3) to cease the reaction. Absorbance at 380 nm was determined using a double beam GBC Model Cintra 10

UV-Visible Spectrometer (Australia). The optical density measured from the glyphosate treatments was subtracted by the optical density of the control samples as background. A shikimate standard curve was developed and shikimate levels were expressed as nM of shikimic acid accumulated cm-2. The experiments were repeated 5 times for each temperature with five leaves from five separate plants per population as replicates.

USA).

2.6 Effect of temperature on absorption and translocation of glyphosate

Twenty seedlings from each of two resistant (A533.1, A818) and one susceptible (Echi S) population at the one-leaf stage were transplanted into a black plastic container (26 x 19 x 9 cm) containing 2 L of modified Hoagland’s nutrient solution and 1 kg of black polypropylene beads23. The experiments were conducted under two temperature regimes as described earlier.

Losses of nutrient solution due to evaporation were replaced every day.

When the plants had reached the 3-leaf stage they were sprayed with glyphosate at 67.5 g a.e. ha-1. Immediately after the glyphosate application, each plant was treated with 1 µl radio- labeled 14C-glyphosate (mixture of 0.42 kBq of radioactivity and 0.0136 µM glyphosate) to the lower half of the second leaf. The plants were returned to the growth chamber.

At 12, 24, 48 and 72 h after treatment (HAT), five plants from each population were harvested. Plants were sectioned into the treated leaf, the non-treated leaves, the stem and the roots (Appendix 7). Treated leaves were washed in 5 ml of 0.1% Triton X-100 (Sigma-

Aldrich) solution in 20 ml glass vial to remove unabsorbed radioactivity. Plant sections were dried separately in paper envelopes.

The dried plant sections were individually combusted in a biological oxidizer (R.J. Harvey

14 Instrument Corp., USA). The emitted CO2 was trapped in 14 ml of scintillation mixture [1:1

(v/v) ratio of Carbo-Sorb E and Permafluor E+ (Canberra Packard, Groningen, The

Netherlands)]. The radioactivity was quantified by liquid scintillation spectroscopy (Tri-card

2100TR, Packard Bioscience Company, USA). A volume of 8 ml Ultima Gold XR (Canberra

Packard, Groningen, The Netherlands) was added to the leaf wash solutions and the radioactivity level was also quantified by liquid scintillation spectroscopy. The percentage of glyphosate absorbed was calculated as the sum of radiolabel in the plant parts as a proportion of the radiolabel recovered. The percentage of glyphosate in individual plant sections was calculated as the amount of radiolabel in that section as a proportion of the amount of glyphosate absorbed.

USA) comparing absorption and translocation among populations by temperature for each harvest time.

3 RESULTS

3.1 Temperature response experiments

In both experiments, survival percentage and LD50 (glyphosate dose required to kill 50% of the population) were higher at 30oC than at 20oC in glyphosate resistant E. colona

66 populations. However, there was no difference in the response of the susceptible population

Echi S to glyphosate between the two temperatures (Fig. 1 and Table 3). Among populations,

A818 showed the largest difference in response to glyphosate between high and low

o o temperatures. The LD50 for this population was 2.4-fold higher at 30 C than at 20 C in the first experiment and 3.2-fold higher in the second experiment (Table 3). Population A533.1 was the most resistant population in both experiments (Fig. 1, Table 3 and Appendix 8). At the higher temperature regime (30/28oC) there was a large difference in the level of resistance to glyphosate between all the resistant populations and the susceptible population. At the lower temperature (20/18oC) there was less difference between the resistant and susceptible populations (Table 3), especially there was a very similar response to glyphosate between

A818 and the susceptible population at this temperature regime.

Experiment 1

30oC 100 20oC A533.1 (R) 100 A533.1 (R) RL11 (R) 1307.3 (R) 90 1307.3 (R) 90 A818 (R) RL21 (R) RL11 (R) 80 80 RL21 (R) A818 (R) Echi S (S) 70 Echi S (S) 70

60 60

50 50 Survival Survival (%) Survival(%) 40 40

30 30

20 20

10 10

0 0 1.0 1.5 2.0 2.5 3.0 3.5 1.0 1.5 2.0 2.5 3.0 3.5 Glyphosate [log(g a.e. ha-1)] Glyphosate [log(g a.e. ha-1)]

Experiment 2

20oC 30oC 100 A533.1 (R) 100 A533.1 (R) 1307.3 (R) A818 (R) 90 90 RL11 (R) 1307.3 (R) RL21 (R) 80 80 RL11 (R) A818 (R) 70 Echi S (S) 70 RL21 (R) Echi S (S) 60 60

50 50 Survival Survival (%) Survival Survival (%) 40 40

30 30

20 20

10 10

0 0 1.0 1.5 2.0 2.5 3.0 3.5 1.0 1.5 2.0 2.5 3.0 3.5 Glyphosate [log(g a.e. ha-1)] Glyphosate [log(g a.e. ha-1)]

Figure 1. Response of E. colona populations to glyphosate at 20oC and 30oC. Lines are survival data back-transformed from the probit equations. Each data point represents the mean percentage survival from four replicates ± SE.

-1 Table 3. Glyphosate dose required to control 50% (LD50) (g a.e. ha ) of susceptible and resistant E. colona populations at 20oC and 30oC was analysed using PriProbit ver. 1.63 with

95% confidence intervals (in parentheses)

Experiment 1 Experiment 2 Population 20oC 30oC 20oC 30oC

A5331 (R) 333 (230, 466) 466 (333, 647) 233 (187, 284) 271 (226, 322)

1307.3 (R) 148 (101, 206) 250 (179, 347) 140 (114, 168) 237 (203, 277)

RL11 (R) 206 (127, 302) 223 (144, 330) 108 (85.9, 132) 227 (182, 284)

RL21 (R) 117 (74.9, 169) 189 (132, 265) 89.0 (68.5, 112) 178 (151, 210)

A818 (R) 103 (63.7, 150) 242 (173, 334) 81.6 (61.7, 104) 258 (221, 301)

Echi S (S) 70.6 (47.8, 98.8) 68.3 (46.2, 97.6) 58.2 (46.8, 70.8) 60.7 (50.4, 72.4)

3.2 Target-site mutations

The predicted amino acid sequence for the part of the EPSPS enzyme sequence around Pro

106 is shown in Table 4. The predicted amino acid sequence of the susceptible population

Echi S was the same as the consensus sequence of other plant species in the conserved region sequenced. The resistant populations, with the exception of A533.1, showed no differences to the susceptible sequence within the nucleotide sequence in this region. In population A553.1 a single nucleotide substitution of T for C at codon 106 was identified predicting a substitution of serine for proline at position 106. Therefore, a target-site mutation for glyphosate resistance was present in this population, but not in the other resistant populations.

Table 4. Nucleotide and predicted amino acid sequence of EPSPS DNA isolated from a susceptible and five resistant populations of E. colona

Amino acid number 104 105 106 107 108

Amino acid Met Arg Pro Leu Thr

Consensus sequence ATG CGG CCA TTG ACA

Echi S (S) - - - - -

Ser A533.1 (R) - - - - TCA

1307.3 (R) - - - - -

A818 (R) - - - - -

RL11 (R) - - - - -

RL21 (R) - - - - -

3.3 EPSPS gene copy number

In this study, the relative genomic copy numbers of the EPSPS gene relative to ALS in the two resistant (A533.1 and 1307.3) and one susceptible population (Echi S) were determined with quantitative PCR. The result showed that there was no EPSPS amplification detected in the two resistant populations (data not shown).

3.4 Effect of temperature on shikimate accumulation

Considerably more shikimate was accumulated at 30oC than 20oC in all populations (Fig. 2).

At both temperatures, more shikimate accumulated at lower concentrations of glyphosate in the susceptible population Echi S than in the two resistant populations A533.1 and A818. At

30oC shikimate accumulated at low glyphosate concentrations in the susceptible population, reaching a maximum level at 200 μM glyphosate and plateaued. In both resistant populations, shikimate did not accumulate to the same level as the susceptible one until 1000 μM

70 glyphosate was applied. At 20oC, a different pattern was observed. Once again, glyphosate accumulated in leaf discs of the susceptible population at low glyphosate concentrations this time reaching a plateau at less than 200 μM glyphosate. The resistant population A818 accumulated shikimate at lower concentrations of glyphosate reaching a plateau at 200 μM.

This is consistent with this population being less resistant at 20oC than it is at 30oC. In contrast, the resistant population A533.1 accumulated less shikimate at every glyphosate concentration at 20oC than the susceptible population.

Figure 2. Shikimic acid accumulation of leaf discs from two resistant (A533.1 and A818) and one susceptible (Echi S) E. colona populations at different glyphosate concentrations at 20oC and 30oC. Each data point represents the mean amount of shikimate accumulation from five experiments with 5 replicates per each glyphosate rate for each experiment ± SE.

3.5 14C-glyphosate absorption and translocation as affected by temperature

There were significant differences in glyphosate absorption between the two temperature regimes and among time points after glyphosate application (P<0.0001), but there was no difference between populations in absorption at each temperature regime (Fig. 3). There was an increase in absorption of glyphosate with time; and significant differences were found between 12 h and 48 - 72 h after glyphosate treatment at 20oC and between 12 - 24 h and 72 h

71 at 30oC over all populations. In general, the absorption of glyphosate in E. colona populations was higher at 20oC (48 - 66%) than at 30oC (21 - 42%) over all the sample harvesting times.

Figure 3. 14C-glyphosate absorbed and translocated to plant sections of two resistant (A533.1 and A818) and one susceptible (Echi S) E. colona populations at 20oC and 30oC at 12, 24, 48 and 72 hours after glyphosate application. Each data point represents the mean percentage of the recovery and the absorption from 5 replicates multiplied by 2 experiments ± SE.

After glyphosate was absorbed into plants, it mostly remained in the treated leaf with between 74 and 87% of the absorbed glyphosate at 12 HAT, decreasing to 50 to 73% at 72

HAT (Fig. 3). There were no significant differences in the proportion of absorbed glyphosate in the treated leaves between the two temperature regimes. In non-treated leaves, the amount of glyphosate ranged from 5% to 16% of that absorbed and was not different between the times and temperatures. In contrast to the treated leaf, the proportion of glyphosate in the shoot base rose significantly with time, from 2% to 10% at 12 h to up to 18% at 72 h after glyphosate treatment (P = 0.0002). Similarly, glyphosate accumulation in roots also increased from 1-7% at 12 h to 8-23% at 72 h. The only significant differences in translocation between populations and temperatures were to the roots. At 72 HAT, populations A818 and Echi S had less translocation to the roots at 30oC than did A533.1 (P = 0.0437).

4 DISCUSSION

4.1 Temperature influences glyphosate resistance

According to Tanpipat et al.24, under field conditions, increased temperature reduced the efficiency of glyphosate in controlling E. colona. These authors concluded high temperature likely boosted evapotranspiration and stressed the plants leading to lower glyphosate translocation and less herbicide efficacy. Under the well-watered conditions of the present study, there was no difference in response to glyphosate of the susceptible population between two temperatures. Therefore, the effect on the resistant plants is unlikely to be due to water stress and is likely an interaction between the effects of temperature and the glyphosate resistance mechanism(s) present.

4.2 Target-site contributes to glyphosate resistance

To identify possible target-site mutations in E. colona populations, a fragment of the EPSPS gene of glyphosate resistant individuals was sequenced and a target-site mutation was detected in the population A533.1. As showed in Table 3, A553.1 was the most resistant population and had one of the smaller differences in LD50 between high and low temperatures. To date, four mechanisms of glyphosate resistance in plants have been identified and include: (1) a mutation within the target-site that reduces the herbicide binding;

(2) a decrease in translocation of the herbicide25; (3) reduced foliar uptake from the abaxial leaf surface18 and (4) amplification of the target-site gene26. In this study, the glyphosate resistance mechanism by target-site mutation was identified in one E. colona population.

While in some weed species, amplification of the EPSPS gene has been observed as a mechanism for glyphosate resistance, for example glyphosate resistance by EPSPS amplification was observed in tall waterhemp (Amaranthus tuberculatus)27, L. multiflorum28,

Kochia (Kochia scoparia)29 and spiny amaranth (Amaranthus spinosus)30, this mechanism was not identified here in two resistant populations of E. colona examined.

4.3 14C-glyphosate absorption and translocation as affected by temperature

Absorption and translocation of glyphosate to the meristem of plants play an important role in the efficacy of this herbicide16,31,32. A decrease in translocation has been considered as a glyphosate resistant mechanism in plants25,33, although this mechanism does not occur in all resistant populations33. The fact that the glyphosate absorption in E. colona populations in this study was higher at 20oC than at 30oC did not result in lower efficacy of glyphosate on the susceptible population, suggesting sufficient glyphosate was being absorbed to control this population. Nevertheless, the situation must be different in the resistant populations as these became more resistant to glyphosate at higher temperatures. There were no significant differences in translocation of glyphosate from the treated leaf between the two resistant

74 populations and the susceptible population, indicating reduced translocation is not the mechanism of resistance in the two resistant populations tested.

Similar results have been also found in other weed species with different mechanisms. In soyabean (Glycine max), glyphosate absorption and translocation were reduced when air temperature was increased9. In a study on glyphosate resistant C. canadensis, Ge et al.34 acknowledged that the level of glyphosate sequestration in vacuole was noticeably increased in high growth temperatures and this activity was inhibited at low growth temperatures leading to a reduction in glyphosate resistance in this weed species under low temperatures.

Two grass species L. rigidum and johnsongrass (Sorghum halepense) likewise had higher levels of glyphosate resistance at high temperatures but the reason for this was not studied35, and these results were in contrast to the results reported by McWhorter et al.9 on the same grass species S. halepense.

In contrast to E. colona, the results from several studies on other plant species showed a decrease in glyphosate resistance when temperature increased. Pline et al.12 demonstrated that, high temperatures at 35oC decreased resistance in transgenic glyphosate resistant G. max through an increase in translocation of glyphosate to meristematic regions. In hemp dogbane

(Apocynum cannabinum), high temperature of 30oC led to an increase in glyphosate translocation compared to 25oC10, and tolerance decreased accordingly. Similarly, in potato

(Solanum tuberosum), Masiunas and Weller11 showed that under high temperatures phytotoxicity of glyphosate was greater than that under low temperatures, and the reason for this was that at high temperatures more glyphosate was absorbed. McWhorter et al.9 also stated that 14C-glyphosate absorbed by S. halepense was approximately twice as high at 30oC as at 24oC and translocation increased at the higher temperature as well. To explain the effect of temperature on efficacy of glyphosate in controlling redvine (Brunnichia ovata), Reddy13 maintained that at higher temperatures plants are probably more physiologically active and consequently absorb and translocate more glyphosate. Jordan8 showed that at 40% relative humidity, glyphosate was more effective on bermudagrass (Cynodon dactylon) at 32oC than

75 that at 22oC due to an increase in herbicide toxicity at high temperatures. In addition, the activity of glyphosate in common wild oat (Avena fatua) and liverseed grass (Urochloa panicoides) also varied under different temperature regimes. Under well-watered conditions, efficacy of glyphosate in controlling these two grass species was greater at high temperatures

(30 - 35oC) than at low temperature (20oC)36. A different pattern was observed in resistant populations of E. colona in this study, where glyphosate absorption was reduced by high temperature, but translocation was not affected. Under these circumstances, a lower concentration of glyphosate would be expected at the crucial meristematic zones.

When glyphosate is applied to plants, inhibition of the enzyme EPSP synthase leads to a massive accumulation of shikimate37,38. In this study, accumulation of shikimate was measured at two different temperatures on two resistant populations (A533.1 and A818) and one susceptible population (Echi S) of E. colona. As shikimate accumulation is a marker of glyphosate inhibition of EPSPS, these results suggest that it is the ability of glyphosate to get into leaf chloroplasts from outside the leaf cells that is the crucial factor. At high temperatures, a much greater glyphosate concentration outside the leaf cell is required for glyphosate to exert the same effect on the resistant populations compared to the susceptible population.

Sammons and Gaines39 proposed that it is the delivery of a lethal dose of glyphosate within a specified period of time that is important in lethality of this herbicide. High temperatures appear to interfere with this in resistant populations of E. colona. The lower efficacy of glyphosate activity in resistant populations of this species at high temperatures is complex.

There is lower absorption of glyphosate across all species at 30oC compared with 20oC, which would tend to reduce glyphosate activity. However, glyphosate impact, as measured by shikimate accumulation, is higher at 30oC. The lack of change in the susceptible population may result from these two factors cancelling each other out. Population A818 is not resistant to glyphosate at 20oC, but is resistant at 30oC. This population does not contain an amino acid substitution in EPSPS, nor reduced absorption or translocation of glyphosate. Whatever the

76 resistance mechanism in this population is, it is manifested by reduced ability of glyphosate to reach the target site at high temperatures. In this population, at low temperatures, shikimate accumulation in leaf discs is little different to the susceptible population. This population is similar in response to glyphosate-resistant populations of C. canadensis34, but the mechanism must be different as no reduction in translocation occurs. Population A553.1 responds identically with respect to shikimate accumulation to population A818 at high temperatures, but accumulates less shikimate at low temperatures. The amino acid modification identified in

EPSPS likely plays an important role in resistance at low temperatures and perhaps less of a role at high temperatures.

5 CONCLUSIONS

Glyphosate resistant E. colona populations are more resistant to glyphosate at high temperatures than they are at low temperatures. In part this is due to reduced glyphosate absorption at high temperatures that will reduce the internal glyphosate concentration in the leaf and also to reduced ability of glyphosate to enter the chloroplast. The consequences of this are significant, as glyphosate is typically applied to this species in Australia during summer when temperatures are high (30 - 40oC). It is also apparent that testing for resistance in this species needs to be done under similar temperature regimes to the application of the herbicide in the field otherwise there is a significant risk of false negatives. While target-site mutations are present in some E colona populations, other mechanisms that are not differential absorption or translocation of glyphosate, or EPSPS amplification, must also be present.

ACKNOWLEDGMENTS

This study was supported by the Grains Research and Development Corporation. Thai Hoan

Nguyen was the recipient of a postgraduate scholarship from the Ministry of Education and

Training, Vietnam.

REFERENCES

1 Holm LG, Plucknett DL, Pancho JV and Herberger JP, The world's worst weeds:

Distribution and biology. The University Press of Hawaii, Honolulu, Hawaii, 610 pp.

(1977).

2 Walker S, Widderick M, Storrie A and Osten V, Preventing glyphosate resistance in

weeds of the northern grain region. In the 14th Australian Weeds Conference - Weed

management: balancing people, planet and profit. Wagga Wagga, New South Wales,

6-9 September 2004. Weed Society of New South Wales, Sydney, Australia, pp. 428-

431 (2004).

3 Norsworthy JK, Talbert RE and Hoagland RE, Chlorophyll fluorescence for rapid

detection of propanil-resistant barnyard grass (Echinochloa crus-galli). Weed Sci 46:

163-169 (1998).

4 Duke SO, Baerson SR and Rimando AM, Glyphosate. In: Encyclopedia of

Agrochemicals. John Wiley & Sons, Inc., New York, USA (2003).

5 Duke SO and Powles SB, Glyphosate-resistant weeds and crops. Pest Manag Sci 64: 317-

318 (2008).

6 Heap I, The international survey of herbicide resistant weeds. www.weedscience.org

[accessed 30 July 2014].

7 Cerdeira AL, Gazziero DLP, Duke SO, Matallo MB and Spadotto CA, Review of

potential environmental impacts of transgenic glyphosate-resistant soybean in Brazil. J

Environ Sci Health, Part B 42: 539-549 (2007).

8 Jordan TN, Effect of temperature and relative humidity on toxicity of glyphosate to

bermudagrass (Cynodon dactylon). Weed Sci 25: 448-451 (1977).

9 McWhorter CG, Jordan TN and Wills GD, Translocation of 14C-glyphosate in soybeans

(Glycine max) and Johnsongrass (Sorghum halepense). Weed Sci 28: 113-118 (1980).

10 Schultz ME and Burnside OC, Absorption, translocation and metabolism of 2,4-D and

glyphosate in hemp dogbane (Apocynum cannabinum). Weed Sci 28: 13-20 (1980).

11 Masiunas JB and Weller SC, Glyphosate activity in potato (Solanum tuberosum) under

different temperature regimes and light levels. Weed Sci 36: 137-140 (1988).

12 Pline WA, Wu JR and Hatzios KK, Effects of temperature and chemical additives on the

response of transgenic herbicide-resistant soybeans to glufosinate and glyphosate

applications. Pest Biochem Physiol 65: 119-131 (1999).

13 Reddy KN, Factors affecting toxicity, absorption, and translocation of glyphosate in

redvine (Brunnichia ovata). Weed Technol 14: 457-462 (2000).

14 Sharma SD and Singh M, Environmental factors affecting absorption and bio-efficacy of

glyphosate in Florida beggarweed (Desmodium tortuosum). Crop Prot 20: 511-516

(2001).

15 Pline-Srnic W, Technical performance of some commercial glyphosate-resistant crops.

Pest Manag Sci 61: 225-234 (2005).

16 Lorraine-Colwill DF, Powles SB, Hawkes TR, Hollinshead PH, Warner SAJ and Preston

C, Investigations into the mechanism of glyphosate resistance in Lolium rigidum. Pest

Biochem Physiol 74: 62-72 (2003).

17 Perez A, Alister C and Kogan M, Absorption, translocation and allocation of glyphosate

in resistant and susceptible Chilean biotypes of Lolium multiflorum. Weed Biol

Manage 4: 56-58 (2004).

18 Michitte P, De Prado R, Espinoza N, Ruiz-Santaella JP and Gauvrit C, Mechanisms of

resistance to glyphosate in a ryegrass (Lolium multiflorum) biotype from Chile. Weed

Sci 55: 435-440 (2007).

19 Koger CH and Reddy KN, Role of absorption and translocation in the mechanism of

glyphosate resistance in horseweed (Conyza canadensis). Weed Sci 53: 84-89 (2005).

20 Sakuma M, Probit analysis of preference data. Appl Entomol Zool 33: 339-347 (1998).

21 Burton RA, Jobling SA, Harvey AJ, Shirley NJ, Mather DE, Bacic A and Fincher GB,

The genetics and transcriptional profiles of the cellulose synthase-like HvCslF gene

family in barley. Plant Physiol 146: 1821-1833 (2008).

22 Shaner DL, Nadler-Hassar T, Henry WB and Koger CH, A rapid in vivo shikimate

accumulation assay with excised leaf discs. Weed Sci 53: 769-774 (2005).

23 Wakelin AM, Lorraine-Colwill DF and Preston C, Glyphosate resistance in four different

populations of Lolium rigidum is associated with reduced translocation of glyphosate

to meristematic zones. Weed Res 44: 453-459 (2004).

24 Tanpipat S, Adkins SW, Swarbrick JT and Boersma M, Influence of selected

environmental factors on glyphosate efficacy when applied to awnless barnyard grass

(Echinochloa colona (L.) Link). Aust J Agric Res 48: 695-702 (1997).

25 Powles SB and Preston C, Evolved glyphosate resistance in plants: Biochemical and

genetic basis of resistance. Weed Techno 20: 282-289 (2006).

26 Gaines TA, Zhang WL, Wang DF, Bukun B, Chisholm ST, Shaner DL, Nissen SJ,

Patzoldt WL, Tranel PJ, Culpepper AS, Grey TL, Webster TM, Vencill WK, Sammons

RD, Jiang JM, Preston C, Leach JE and Westra P, Gene amplification confers

glyphosate resistance in Amaranthus palmeri. Proc Natl Acad Sci USA 107: 1029-1034

(2010).

27 Tranel PJ, Riggins CW, Bell MS and Hager AG, Herbicide resistances in Amaranthus

tuberculatus: A call for new options. J Agric Food Chem 59: 5808-5812 (2011).

28 Salas RA, Dayan FE, Pan Z, Watson SB, Dickson JW, Scott RC and Burgos NR, EPSPS

gene amplification in glyphosate-resistant Italian ryegrass (Lolium perenne ssp.

multiflorum) from Arkansas. Pest Manag Sci 68: 1223-1230 (2012).

29 Wiersma A, Regional whole plant and molecular response of Kochia scoparia to

glyphosate. MS Thesis, Department of Bioagricultural Sciences and Pest Management,

Colorado State University, Fort Collins, Colorado, USA (2012).

30 Nandula VK, Wright AA, Bond JA, Ray JD, Eubank TW and Molin WT, EPSPS

amplification in glyphosate-resistant spiny amaranth (Amaranthus spinosus): A case of

gene transfer via interspecific hybridization from glyphosate-resistant palmer amaranth

(Amaranthus palmeri). Pest Manag Sci DOI: 10.1002/ps.3754 (2014).

31 Hoss NE, Al-Khatib K, Peterson DE and Loughin TM, Efficacy of glyphosate,

glufosinate, and imazethapyr on selected weed species. Weed Sci 51: 110-117 (2003).

32 Kirkwood RC, Hetherington R, Reynolds TL and Marshall G, Absorption, localisation,

translocation and activity of glyphosate in barnyardgrass (Echinochloa crus-galli (L)

Beauv): influence of herbicide and surfactant concentration. Pest Manag Sci 56: 359-

367 (2000).

33 Shaner DL, Role of translocation as a mechanism of resistance to glyphosate. Weed Sci

57: 118-123 (2009).

34 Ge X, d'Avignon DA, Ackerman JJH, Duncan B, Spaur MB and Sammons RD,

Glyphosate-resistant horseweed made sensitive to glyphosate: low-temperature

suppression of glyphosate vacuolar sequestration revealed by 31P NMR. Pest Manag

Sci 67: 1215-1221 (2011).

35 Vila-Aiub MM, Gundel PE, Yu Q and Powles SB, Glyphosate resistance in Sorghum

halepense and Lolium rigidum is reduced at suboptimal growing temperatures. Pest

Manag Sci 69: 228-232 (2013).

36 Adkins SW, Tanpipat S, Swarbrick JT and Boersma M, Influence of environmental

factors on glyphosate efficacy when applied to Avena fatua or Urochloa panicoides.

Weed Res 38: 129-138 (1998).

37 Steinrucken HC and Amrhein N, The herbicide glyphosate is a potent inhibitor of 5-

enolpyruvyl-shikimic acid-3-phosphate synthase. Biochem Biophys Res Commun 94:

1207-1212 (1980).

38 Rubin JL, Gaines CG and Jensen RA, Enzymological basis for herbicidal action of

glyphosate. Plant Physiol 70: 833-839 (1982).

39 Sammons RD and Gaines TA, Glyphosate resistance: state of knowledge. Pest Manag Sci

DOI: 10.1002/ps.3743 (2014).

Chapter 5

Inheritance of Evolved Glyphosate Resistance in Barnyard Grass

(Echinochloa colona) from Australia

Abstract

Glyphosate resistance has occurred widely in Echinochloa colona in fallow systems of the northern Australian cropping region. Gene flow and the inheritance pattern of resistance alleles can impact on resistance evolution. This research investigated pollen movement between glyphosate resistant (A533.1) and susceptible (Echi S) populations of E. colona collected from the north-east of New South Wales and the inheritance of resistance.

Population A533.1 contains a mutation in the EPSPS gene. For gene flow, plants were grown in adjacent pairs and glyphosate at the rate of 240 g a.e. ha-1 was used to assess potential hybrids in the seed on the susceptible population in each pair and segregation in the F2 generation. In the gene flow experiment, 1.38% of the progeny of the susceptible parents was determined to carry glyphosate resistance and the target-site mutation. A single F1 seed resulted from a hand cross between the resistant population A533.1 and the susceptible population Echi S. The mutation in the EPSPS gene was detected in this F1 hybrid. In the F2 generation, 28 F1 families segregated in a 3:1 survival : mortality ratio suggesting that F1 progenies were heterozygous individuals and glyphosate resistance in E. colona was inherited as a single dominant gene. Sequencing the EPSPS cDNA detected mutation in a F2 progeny and in an individual belonging to another glyphosate resistant population (1307.3), and detected at least two genomes in E. colona. The glyphosate dose response of the F2 filial generation from the hand cross was intermediate between the two parents and tended to follow the pattern expected for a single largely dominant gene with an additional gene or genes contributing to resistance.

5.1 Introduction

Gene movement, either via pollen or seed, plays an important role in the spread of genotypes of a plant species. Slatkin (1987), stated that gene movement can inhibit evolution due to restraining populations from adaptation to local environmental conditions, but can also boost evolution by means of dispersing new genotypes and aggregating genes; and to some extent, gene migration can result in forming new species. A serious problem in herbicide resistance is the movement of resistant genes through a long distance between crop fields, although the gene flow frequencies are low as studied on canola (Brassica napus) by Rieger et al. (2002).

According to Darmency et al. (1998), the movement of herbicide resistant genes could make the problems of weed management in crop fields more difficult. Ellstrand (1992a) affirmed that the gene migration impacts decidedly on evolution and population genetic structure.

Previous studies have shown the extent of gene flow can be highly variable depending on population size, distance between populations, biology of species and the presence of pathways for seed and pollen dispersal (Ellstrand, 1992a). For example, the majority of pollen movement in rice occurs mainly over short distances (Messeguer et al., 2001), but gene flow can occur over much longer distances in forest trees (Kremer et al., 2012). Gene flow rates were high in most gymnosperms, but varied widely in angiosperms (Govindaraju, 1989). In addition, allogamous species had significantly higher gene flow levels than autogamous species (Govindaraju, 1988).

For weed populations, gene flow via pollen movement between herbicide resistant and susceptible plants was demonstrated by Stallings et al. (1995), Christoffers (1999), Marshall et al. (2001), Murray et al. (2002), and Volenberg and Stoltenberg (2002). Gene flow can play an important role in increasing the frequency of herbicide resistant genes within populations.

An increased frequency of resistant genes within a population will speed up the evolution of resistance once the herbicide is used. Gene flow can also result in the spread of herbicide resistance within a location (Jasieniuk et al., 1994; Diggle and Neve, 2001).

The inheritance patterns of herbicide resistance can also influence the evolution of resistance.

Resistance traits inherited as a single dominant allele will quickly be selected in populations, whereas those that are inherited as recessive alleles or are multi-genic will take longer to be selected (Jasieniuk et al., 1994; Kern et al., 2002). Glyphosate resistance is typically inherited as a single partially-dominant allele (Lorraine-Colwill et al., 2001; Davis et al., 2010), but can be multi-genic or have non-Mendelian inheritance (Ng et al., 2004; Simarmata et al., 2005;

Wakelin and Preston, 2006; Chandi et al., 2012). The mode of inheritance of glyphosate resistance in E. colona is currently unknown.

The aims of this study were to evaluate gene flow due to pollen exchange between resistant and susceptible E. colona individuals and to determine the mode of inheritance of glyphosate resistance in this species. The information produced could help farmers to better manage spread of glyphosate resistant E. colona.

5.2 Materials and methods

5.2.1 Plant material

Seeds of three E. colona populations 1307.3, A533.1 and Echi S were collected from near

Goondiwindi (Queensland), Moree and Tamworth (New South Wales) respectively. The populations were confirmed as E. colona through floristic characteristics (Jessop et al., 2006), and determined as resistant (1307.3 and A533.1) and susceptible (Echi S) via a dose response experiment in 2011 (data not shown). In other experiments conducted at the same time,

A533.1 was the most glyphosate resistant population and contained a mutation in EPSPS (5- enolpyruvylshikimate-3-phosphate synthase) gene at codon 106 with a substitution of serine for proline (data not shown). Seeds from the three populations were treated with 95% H2SO4 for 30 minutes, rinsed under running water for 60 minutes and germinated on 0.6% (w/v) agar

85 in an environmentally controlled cabinet with 12h light/dark periods at 22oC with 30 µmol m-

2s-1 during the light period.

5.2.2 Gene flow between resistant and susceptible individuals

A single resistant (A533.1) and susceptible (Echi S) population were used in this experiment.

At the one-leaf stage (8 days after germination), ten seedlings of each population were transplanted into individual 25 cm diameter x 24 cm height pots (Masrac Plastics Pty Ltd.,

South Australia) containing standard potting soil. The pots were arranged into 10 pairs containing one resistant or one susceptible plant, with plants within the pair placed 30 cm

(Appendix 9, left) apart and each pair placed at least 10 m apart. The plants were maintained outdoors, with all other Echinochloa spp. plants removed from the vicinity of the experiment to avoid pollen contamination. Before anthesis, two single spikes from each resistant and susceptible individual were bagged with glassine bags to self-pollinate (Appendix 9, right).

Growth (flowering and seed maturity) and flower-head number of individuals were observed throughout the growing time of the plants. After flowering, all seeds from each individual were harvested separately, air dried and stored at room temperature for three to four months to break dormancy. Seeds from the bagged spikes were also harvested and stored in isolated envelopes. The 100-seed weight from each individual plant was determined and these 100 seeds were tested for germinability when dormancy had waned. The germination of seeds was as described above and the germination percentage was recorded at 10 days. The data were statistically analysed using SAS (Statistic Analysis System) software ver. 6.03 for MS-DOS

(SAS Institute, USA). LSD (least significant different) at the 5% level was used to separate means.

Gene flow frequency was determined by the response of the F1 seed from the susceptible parent of each crossing pair to glyphosate application. This experiment was conducted outdoors during the summer of 2013. Before the gene flow frequency experiment was started,

86 a dose response experiment was conducted outdoors on the two populations A533.1 and Echi

S. The purpose of this experiment was to test the appropriate rate for the gene flow frequency experiment. The seed of these two populations were germinated as described above. After 8 days, seedlings at the one leaf stage were transplanted into 8.5 x 9.5 x 9.5 cm pots (Masrac

Plastics Pty Ltd., South Australia) containing standard potting mix, with a density of nine seedlings per pot. At the 3 to 4 leaf stage, seedlings were sprayed with glyphosate (Roundup

PowerMax®, Nufarm Australia Limted) at rates of 0, 240, 480, 960 and 1920 g a.e. ha-1 with three replicates for each rate. Non-ionic surfactant (alcohol alkoxylate, BS 1000, Crop Care) at 0.2% (v/v) was added to glyphosate. The glyphosate application was carried out using a moving-boom laboratory twin nozzle sprayer (Hardi ISO F-110-01 standard flat fan, Hardi,

Adelaide) placed 40 cm above the seedlings with a water volume of 109.6 L ha-1, a pressure of 250 kPa and a boom speed of 1 m s-1. Control plants were not treated with glyphosate. At

21 days after application of glyphosate, the number of survivors was determined.

The seed set on four susceptible Echi S plants that had been planted adjacent to four resistant plants from population A533.1 were germinated. The seeds from bagged spikes of the resistant and susceptible plants that had been selfed were also germinated at the same time.

Seedlings at the one-leaf stage were transplanted into 35 cm x 29 cm x 6 cm trays (Masrac

Plastics Pty Ltd., South Australia) at a density of 50 plants per tray. Seedlings of resistant and susceptible selfs were planted at a density of 25 plants per tray. At the 3 to 4-leaf stage, these seedlings were treated with glyphosate at a dose of 240 g a.e. ha-1 [plus 0.2% (v/v) non-ionic surfactant] to identify resistant individuals in the F1 generation. Herbicide was applied as described above. At 30 days after treatment, the number of survivors was recorded. These survivors were transplanted into 20 cm diameter pots, placed separately in a glass house and allowed to produce seed by self-pollination. Leaf material was taken from each surviving plant for sequencing the EPSPS gene in the F1 progenies.

5.2.3 Hand crossing of resistant and susceptible individuals

Seedlings of the resistant population A533.1 and susceptible population Echi S were grown outdoors in 25 cm in diameter and 24 cm in height pots (Masrac Plastics Pty Ltd., South

Australia) in the summer of 2012 - 2013. Prior to anthesis, the anthers of 300 susceptible flowers were removed using a tweezers under a stereomicroscope. After that, these flowers were covered with glassine bags to prevent pollen from other susceptible flowers. When the stigmas of the emasculated flowers were exposed, pollen from resistant plants was applied on these susceptible stigmas. When any fertilised seeds that resulted were mature, they were harvested, air dried and stored in an envelope at room temperature. After dormancy was broken (three to four months), the F1 filial seed was germinated and planted in a 25 cm in diameter and 24 cm in height pot and allowed to set seed, and the resultant F2 seeds were collected.

In this experiment, although 300 susceptible flowers were used for hand-pollination, almost none of the flowers produced seed. The majority of flowers died within a couple of days after emasculation, probably due to injury during emasculation. Seeds were set on only two flowers, but only one of these germinated and was used for the subsequent experiments. As showed in Fig. 2, the anthers dehisce and pollen grains are released only if the flowers open.

Therefore, it is likely the seed produced came from hand-pollination.

5.2.4 Sequencing of F1 and F2 progenies

Young green leaf tissue was sampled from each survivor in the gene flow experiment, and the single F1 plant and 30 F2 individuals of the hand cross. DNA was extracted using the DNeasy

Plant Mini Kit (Qiagen, Australia) in accordance with the manufacturer’s instructions.

PCR reactions were conducted in 25 μl volumes containing 80 -100 ng DNA, 1 × High

Fidelity PCR Buffer [600 mM Tris-SO4 (pH 8.9), 180 mM (NH4)2SO4], 0.4 mM dNTP

® mixture, 4 mM MgSO4, 0.4 μM of each specific primer and 1 unit of Platinum Taq DNA

Polymerase High Fidelity (Invitrogen, Australia). A forward (AW F: 5’-

AACAGTGAGGAYGTYCACTACATGCT-3’) and reverse (AW R: 5’-CGAACA

GGAGGGCAMTCAGTGCCAAG-3’) primer were used for amplification of an approximately 500 bp fragment of the EPSPS (5-enolpyruvylshikimate-3-phosphate synthase). An automated DNA thermal cycler (Eppendorf Mastercycler® Gradient, Germany) was used for amplification with the cycle parameters as follows: 3 min denaturing at 94°C; 39 cycles of 30 s denaturation at 94°C, 30 s annealing at 56°C and 1 min elongation at 68°C, and a final extension for 7 min at 68°C.

PCR products were examined on 1.5% agarose gels stained with 1 × of SYBR® Safe DNA gel stain. Samples were electrophoresed in 1× TAE Buffer [40 mM Trizma base, 1 mM

Na2EDTA (pH to 8) with glacial acetic acid] at 90 volts and photographed under UV light

(λ302nm). DNA fragment sizes were estimated via comparison to a DNA ladder with known size bands (EasyLadder I, Bioline, Australia). PCR products were sequenced at the Australian

Genome Research Facility (AGRF) Ltd., Australia using the same primers used for amplification

DNA sequence data was assembled, compared and analysed using ContiExpress from the

Vector-NTi Advance 11.5 programs (Invitrogen, USA).

5.2.5 Shikimate accumulation

Shikimate accumulation was measured as described by Shaner et al. (2005) with minor modifications. Five leaf discs (5 mm diameter) were excised from the youngest fully mature leaf of the F1 plant in hand cross and of the two parental plants (A533.1 and Echi S) using a cork borer and put into 5 wells of a 96-well flat-bottomed microtiter plate containing the mixture of 0, 50, 200, 500 and 1000 µM glyphosate (Roundup PowerMax®, Nufarm Australia

Limited) and 10 mM phosphate buffer at pH 7. The control wells (0 µM glyphosate) contained nanopure water and 10 mM phosphate buffer. Plates were covered with lid and incubated under fluorescent lights (553 µmol m-2s-1) at 25oC for 16 h. At the end of the incubation period, 50 mM HCl was added to each well to stop skikimate accumulation and the plates were wrapped up in cling film to minimise evaporation. At this time, the samples were frozen at -20oC for 90 minutes to freeze and then thawed at 60oC for 20 minutes for 2 cycles until the whole green leaf tissue had turned grey-green signifying that acid had fully penetrated into leaf tissue. Then, 25 µl of extract from each sample was transferred to clean microtiter plates to measure shikimate concentrations. Six concentrations of shikimic acid including 1, 2.5, 5, 10, 25 and 50 µM were also included for a standard curve. A mixture (100

µl) of 0.25% (w/v) periodic acid and 0.25% (w/v) sodium m-periodate was added to each well and the samples were incubated at room temperature for 60 minutes. To stop the reaction, 100

µl of newly made quench buffer (mixture of 0.6 M NaOH and 0.22 M Na2SO3) was added. A double beam GBC Model Cintra 10 UV-Visible Spectrometer (Australia) was used to measure the spectrum absorbance at 380 nm. Background optical density of the 0 glyphosate samples was subtracted from all other samples. Skimikate accumulation was calculated from a standard curve and presented as nmol of shikimate cm-2.

GraphPad Software, Inc., USA) to compare the differences between parental plants and the F1 plant.

5.2.6 Segregation test

The F2 seeds from 28 putative F1 individuals in the gene flow experiment were germinated and transplanted into 8.5 x 9.5 x 9.5 cm pots at a density of nine seedlings per pot. The number of F2 plants from each F1 individual ranged from 13 to 27. At the 3-4 leaf stage, these

90 plants were treated with glyphosate at 240 g a.e. ha-1, a rate sufficient to control the susceptible population. At four weeks after glyphosate treatment, survival and mortality rates

2 were scored and Chi-square (χ ) analysis was used to determine the segregation ratio of F2 progenies.

5.2.7 Response to glyphosate

Dose response experiments were conducted on the F2 progeny from the hand cross and the two parental populations A533.1 and Echi S. The seeds were germinated and seedlings were transplanted into 8.5 x 9.5 x 9.5 cm pots with a density of nine seedlings per pot as described above. Glyphosate was applied at 10 rates of 0, 40, 80, 120, 240, 360, 480, 600, 800 and 1000 g a.e. ha-1 with three replicates for each rate and non-ionic surfactant at 0.2% (v/v) was added to the glyphosate solution. Survival was assessed at 21 days after glyphosate treatment.

5.2.8 EPSPS cDNA sequencing

EPSPS was sequenced from cDNA of one individual from populations A533.1, 1307.3 and

Echi S as well as two F2 individuals from the gene flow experiment. Total RNA was extracted using the Isolate II RNA Plant Kit (Bioline, Australia) and cDNA was synthesized using the

Tetro cDNA Synthesis Kit (Bioline, Australia) in accordance with manufacturer’s instructions. EPSPS was amplified from the cDNA as described above and cloned using the pGEM-T Easy Vector system (Promega, USA). PCR followed by gel electrophoresis was performed on DNA isolated from resultant colonies to confirm the presence of the EPSPS fragment. The PCR reaction conditions were the same as described above, except template cDNA was replaced with a single clone colony and the initial denaturing step increased to 10 min to aid cell lysis. Before addition into the PCR reaction, colonies were streaked onto standard LB/Amp plates and plasmid DNA of positive colonies isolated using the Isolate II

Plasmid Mini Kit (Bioline, Australia) from the re-grown streaked colonies. Plasmids were sequenced at the AGRF (Australia) using the T7 primer (5’-

TAATACGACTCACTATAGGG-3’).

Sequences were aligned using Clustal X software ver. 1.83 (Thompson et al., 1997). From the resultant alignment, SNPs were identified and DendroUPGMA (Garcia-Vallve et al., 1999) was used to produce the dendrogram from these SNPs data. The dendrogram was subsequently displayed using TreeView software ver. 1.6.6 (Page, 1996).

5.3 Results and discussion

5.3.1 Plant growth of the parental populations

There were no differences in the growth patterns of the two populations (A533.1 and Echi S), probably because both populations originated from the same geographical region (the north- east of New South Wales) with similar climatic conditions. However, within populations there was variation in maturity: a two day difference in flowering and six day difference in seed maturity. The flowering time of resistant and susceptible plants was similar, which increased the chances of pollen exchange between flowers of the two individuals (Table 1).

Table 1. Growth time (transplanting, flowering and seed maturity) of the resistant (A533.1) and the susceptible (Echi S) populations of E. colona in the gene flow experiment

Date Condition Days after transplanting

12 December 2011 Transplanting 0

16 - 18 January 2012 Start flowering 35 - 37

12 - 18 February 2012 Seed maturity 62 - 68

There were significant differences in flower-head number (P = 0.0001), 100-seed weight (P =

0.0001) and seed germination (P = 0.0439) between the two resistant and susceptible populations. The resistant population A533.1 produced a smaller number of panicles than the susceptible population Echi S. The 100-seed weight of Echi S was 0.12 g while that of

A533.1 was 0.10 g. The germination of seed from the Echi S population was higher than that of A533.1 (80.9% compared with 62.7% respectively) (Table 2). In general, the growth of the susceptible population Echi S was significantly more robust than that of the resistant population A533.1.

Table 2. Flower head number, 100-seed weight and germinability of the resistant (A533.1) and the susceptible (Echi S) populations of E. colona in the gene flow experiment

Population Flower-head number 100-seed weight (gam) Germinability (%) A533.1 (R) 203.0 a 0.10 a 62.70 a Echi S (S) 286.4 b 0.12 b 80.90 b LSD (5%) 35.95 0.0047 17.65

A dose response experiment was conducted to determine the rate of glyphosate that completely controlled the susceptible population. All individuals of the susceptible population

Echi S were killed at the glyphosate rate of 240 g a.e. ha-1 while no mortality of A533.1 was observed (Fig. 1). Therefore, this rate was used to identify resistant individuals from crosses in later experiments.

100 Figure 1. Survival percentage at 21 A533.1 (R) Echi S (S) days after glyphosate treatment of the 80 resistant (A533.1) and the susceptible 60

(Echi S) populations of E. colona in Survival (%) the rate test. Each number is the 20

0 mean of three replicates. 0 240 480 960 1920 Glyphosate (g a.e. ha-1) 93

5.3.2 Gene flow frequency

The gene flow frequency was determined as the survival rate of seed from the susceptible plant (Echi S) in each pair at 240 g a.e ha-1 of glyphosate. At 30 days after glyphosate application, 28 survivors were recorded out of 2024 plants grown, accounting for a gene flow frequency of 1.38%. Meanwhile, all resistant control plants (80 plants) survived and all susceptible control plants (96 plants) were killed (Table 3, Appendix 10). The gene flow frequency among four different parental pairs was similar, ranging from 1.35% to 1.47%

(Table 3). This suggests that a homogeneous cross-pollination occurred in the crossing pairs.

Table 3. Survival of F1 progenies from four parental susceptible plants in the gene flow experiment to determine gene flow frequency between resistant (A533.1) and susceptible

(Echi S) E. colona plants

Parental pair Number of plants tested Survivor Gene flow frequency (%)

1 68 1 1.47

2 554 8 1.44

3 511 7 1.37

4 891 12 1.35

Total 2024 28 1.38

A533.1 (control) 80 80

Echi S (control) 96 0

Cross-pollination is considered an essential prerequisite for gene flow for grass weed species.

According to Motten and Antonovics (1992), and Nunez-Farfan et al. (1996), self-pollination happens if anthers dehisce inside the flower before the flowers opened. However, in E. colona no dehiscence had occurred in the anthers at the opening of the flowers, and plenty of pollen

94 grains had adhered to the stigmas outside the flowers after anthesis, demonstrating that cross- pollination and subsequent gene flow is possible (Fig. 2).

Figure 2. The morphology of E. colona flowers at the opening of the flower (left) and after pollination, with pollen grains adhering to the stigmata (right).

Gene flow occurs as a result of spread of pollen and seed (Levin, 1981), and herbicide resistant genes can be a helpful marker for determining the frequency of gene flow through pollen (Messeguer et al., 2001). The frequency of gene flow via pollen between plant populations has been reported to vary. Levin (1984) considered gene flow to be limited and likely far lower than 1%, while Ellstrand (1992b) argued that this rate was normally over 1%.

In a study of cultivated rice, Messeguer et al. (2001) determined gene flow from genetically modified rice to conventional rice with a percentage from 0.01% (at 5 m distance) to 0.53%

(at 1 m distance). Volenberg and Stoltenberg (2002) used the acetyl-CoA carboxylase

(ACCase) herbicide resistant trait of giant foxtail (Setaria faberi) as a marker in identifying

95 the gene flow from resistant to susceptible individuals, and showed an outcrossing rate ranging from 0.24 to 0.73% (at 36 cm distance). The ACCase resistance trait was likewise used by Murray et al. (2002) in wild oat (Avena fatua) with an outcrossing rate ranging from

0 to 12.3% (at 25 cm distance). A study of glyphosate resistance in horseweed (Conyza canadensis) also determined that the resistant gene flow frequency reached 1.1 to 3.8% (at 13 to 18 cm distance) (Davis et al., 2010). In this study where resistant and susceptible plants were 25 cm apart, the level of gene flow (1.38%) found for E. colona is not dissimilar to that found in other weed species.

The effect of distance on gene flow between pollen donor and acceptor plants has also been studied by many authors and gene flow reduces greatly with distance (Ellstrand, 1992b). The impact of distance and wind on gene flow was studied by Messeguer et al. (2001) in rice, who found the gene flow rate was higher with plants in close proximity and in a favourable wind direction. A distance of 75 m between pollen donor and acceptor fields produced a remarkable drop in gene flow of meadow fescue (Festuca pratensis) (Rognli et al., 2000). For common sunflower (Helianthus annuus), gene movement from imazethapyr resistant plants to susceptible plants occurred at a distance of 15.5 m (Marshall et al., 2001). In addition,

Ellstrand (1992b) suggested that within a small population, gene flow levels were likely to be higher compared to populations of larger size. In the present study, resistant and susceptible plants were grown as adjacent pairs with only one plant for each biotype in the pair and the distance between two individuals was <1 m in order to maximise cross-pollination. Therefore, the probability of identifying gene flow would be high and the frequency of gene flow by pollen identified in this experiment is likely to be much higher than that between isolated populations.

5.3.3 Detecting EPSPS gene mutation in F1 and F2 progenies

EPSPS gene sequencing was carried out on genomic DNA from the 28 glyphosate resistant F1 progeny from the gene flow experiment. It was found that 23 of the 28 individuals contained a mutation in the target-site gene at codon 106, with a replacement of T for C leading to the replacement of serine for proline. However, this mutation was not detected in genomic DNA of the remaining five resistant F1 individuals.

From the hand cross a mutation was detected in the F1 seedling that germinated. The mutation was the same as in the paternal biotype A533.1: a single nucleotide substitution of T for C resulted in substitution of serine for proline at position 106 of the EPSPS enzyme. Similarly, a mutation was also detected at the codon 106 of the EPSPS gene in all 30 F2 individuals from hand-cross.

5.3.4 Shikimate assay

The application of glyphosate to plants results in inhibition of the EPSPS enzyme

(Steinrucken and Amrhein, 1980; Rubin et al., 1982) leading to a massive accumulation of shikimic acid (Amrhein et al., 1980; Duke et al., 2003). However, as shown in several weed species such as C. canadensis (Mueller et al., 2003; Koger et al., 2005), Italian ryegrass

(Lolium multiflorum) (Perez-Jones et al., 2005) and rigid ryegrass (Lolium rigidum) (Preston et al., 2006), the accumulation of shikimate is lower in glyphosate resistant plants than in susceptible plants after glyphosate treatment. Shikimate accumulation also increases with glyphosate dose. The present study examined shikimate accumulation in the susceptible, resistant and putative F1 plants of E. colona from the hand cross. Shikimate accumulated to higher concentrations in leaf discs from the susceptible plants than the resistant plants (Fig.

3). Shikimate accumulation in the F1 cross was intermediate between that of the two parents.

This is consistent with the F1 cross being a heterozygous individual. Zelaya et al. (2004) also

97 showed with C. canadensis that heterozygotes accumulated less shikimate after exposure to glyphosate than susceptible plants. In addition, Preston et al. (2006) showed that in L. rigidum, shikimate accumulation in heterozygous F1 plants was higher than that in resistant plants, but lower than in susceptible plants. However, shikimate accumulation in F1 progenies is sometimes very variable depending on weed species. On studying eight F1 crosses of palmer amaranth (Amaranthus palmeri), Gaines et al. (2011) showed that two crosses accumulated a higher shikimic acid content than the parental susceptible plants after glyphosate treatment, while the shikimate accumulation of the remaining six crosses was intermediate between that of the parental susceptible and resistant plants.

Figure 3. Shikimate accumulation of parental plants (A533.1 and Echi S) and the F1 cross of E. colona. Each data point represents the mean amount of shikimate from five experiment times with 5 replicates per each glyphosate rate for each experiment ± SE.

5.3.5 Segregation test

In this study, the F2 E. colona hybrids from the selfed survivors of the gene flow experiment segregated at a 3:1 survival : mortality ratio when treated with 240 g ha-1 glyphosate with χ2 ranging from 0 to 3.23 for progeny from different F1 individuals (Table 4). This suggested that the glyphosate resistant trait in E. colona is a dominant trait and this resistance is inherited as a single gene trait. The segregation results also show that although in five out of twenty-eight F1 families (from no. 24 to no. 28) the mutation in the EPSPS gene was not detected by PCR on genomic DNA, their F2 progenies segregated in a 3:1 survival : mortality ratio.

Table 4. Segregation of the F2 progenies from selfed F1 survivors of E. colona from the gene flow experiment after glyphosate treatment at of 240 g a.e. ha-1

Number of F Plant no. 2 Survivor Death χ2 (3:1) P progeny tested 1 25 22 3 2.578 0.108 2 18 15 3 0.708 0.400 3 26 20 6 0.051 0.821 4 21 15 6 0.135 0.713 5 24 19 5 0.227 0.634 6 23 18 5 0.132 0.717 7 24 19 5 0.227 0.634 8 27 22 5 0.634 0.426 9 24 19 5 0.227 0.634 10 27 23 4 1.641 0.200 11 26 21 5 0.480 0.489 12 25 19 6 0.013 0.909 13 24 18 6 0.000 1.000 14 13 9 4 0.212 0.645 15 27 21 6 0.112 0.738 16 25 20 5 0.343 0.558 17 27 21 6 0.112 0.738 18 27 21 6 0.112 0.738 19 26 19 7 0.049 0.824 20 27 19 8 0.292 0.589 21 25 22 3 2.578 0.108 22 26 19 7 0.049 0.824 23 26 23 3 2.899 0.089 24 24 18 6 0.000 1.000 25 26 19 7 0.049 0.824 26 27 19 8 0.292 0.589 27 27 20 7 0.012 0.913 28 27 24 3 3.230 0.072

The plants from no. 1 to no. 23 contain mutation in EPSPS gene at codon 106.

In most previous studies, the inheritance of glyphosate resistance was determined as single gene inheritance and the inherited trait was a nuclear, partially dominant and monogenic trait.

This was demonstrated by Ng et al. (2004) in goosegrass (Eleusine indica) from Malaysia,

Lorraine-Colwill et al. (2001) and Wakelin and Preston (2006) in L. rigidum from Australia,

Chandi et al. (2012) in A. palmeri from North Carolina. However, in L. rigidum from

California (US), Simarmata et al. (2005) suggested that the inheritance of glyphosate resistance was polygenic. Similarly, the inheritance of glyphosate resistance in A. palmeri from New Mexico was not monogenic (Mohseni-Moghadam et al., 2013).

5.3.6 Dose response to glyphosate of F2 progenies

To confirm the segregation pattern in the F2 generation, a dose response experiment was conducted. In other weed species such as C. canadensis (Zelaya et al., 2004), A. palmeri

(Gaines et al., 2011) and L. rigidum (Lorraine-Colwill et al., 2001; Wakelin and Preston,

2006), the response to glyphosate of F1, F2 or backcross populations was intermediate between that of their parental resistant and susceptible populations. Similar results were found in this study on E. colona. After glyphosate treatment, the F2 population had higher survival percentage than the susceptible population, but less than the resistant population (Fig. 4).

When the predicted response of an F2 population showing segregation of 3:1 for resistance

(assuming complete dominance of the resistance trait) was plotted, the survival data followed the response at intermediate rates of glyphosate, but failed to do so at the two lowest and the highest rates (Fig. 4). This suggests that while a single gene was contributing substantially to glyphosate resistance, additional genes may also contribute to resistance in this population.

On the other hand, the mutation detected in the EPSPS gene of all 30 F2 individuals suggests that the mutation was not segregating as a single gene. Furthermore, this glyphosate resistance mechanism is a weak resistance mechanism as suggested by previous studies (Powles and

Preston, 2006; Jasieniuk et al., 2008), therefore this mechanism may only contribute to

100 resistance at the lower rates. As indicated by Powles and Preston (2006), a mutation that occurs by changes in amino acid 106 of EPSPS gene from proline to either serine or threonine results in a weak resistance to glyphosate in a variety of weed species. Jasieniuk et al. (2008) also demonstrated a weak resistance to glyphosate in L. multiflorum in California when amino acid at position 106 changes from proline to serine.

Figure 4. Glyphosate dose response 100 of susceptible and resistant

80 populations of E. colona and the F2 60 population. Each data point represents

Survival Survival (%) 40 the mean amount of survival

20 A533.1 (R) percentages from 3 replicates per each F2 progeny Echi S (S) 0 glyphosate rate ± SE. 100 1000 Glyphosate (g a.e. ha-1)

5.3.7 EPSPS cDNA sequencing

After cloning, a total of 57 clones from five individuals were gained and the EPSPS gene from each clone was sequenced. A dendrogram produced from eight SNPs in the EPSPS sequences by UPGMA grouped all 57 sequences into two main clusters (Appendix 13). One cluster included 39 sequences and another cluster contained 18 sequences. Both clusters contained sequences from all five individuals and all the sequences containing mutations were grouped into the larger cluster only. This indicates that there were at least two EPSPS genes in E. colona being expressed and one gene in resistant plants did not contain the mutation. At the same time, the fact that one cluster contained 39 sequences, a much larger sequence number compared with the other cluster, suggests that this large cluster may comprised the

101 sequences from two similar EPSPS genes, or that this gene was expressed to a greater extent than the gene in the smaller cluster.

The results of sequencing EPSPS cDNA also showed that none of 17 Echi S sequences obtained contained a mutation at position 106 of this gene. However, a mutation was detected in 13 out of 19 sequences of A533.1 and in three of eleven sequences from two F2 individuals

(Table 5). An additional resistant population (1307.3) was sequenced for comparison and a mutation was detected in two of ten sequences of this population. Meanwhile, the mutations were not detected in the genomic DNA of individual 1307.3 and in the F2 individual from non-mutation F1 parent. This suggests that sequencing cDNA in glyphosate resistant E. colona populations is necessary to draw accurate conclusions about the presence of mutations in the EPSPS gene. The reason for this is that E. colona contains multiple EPSPS alleles, but the alleles containing mutation might be not sequenced when sequencing was conducted on genomic DNA. As the resistant population A533.1 was more resistant to glyphosate compared with population 1307.3, it is possible that the A533.1 population may contain the mutation in more than one of the EPSPS genes, whereas population 1307.3 only contains the mutation in one gene, particularly if the large cluster of sequences identified comes from two very similar

EPSPS genes. This requires further investigation.

Table 5. Mutations were detected at position 106 of cDNA from EPSPS gene after cloning of two resistant and one susceptible plants, and two F2 progenies of E. colona.

No. Plant Number of sequences Sequences with mutation

1 A533.1 (R) 19 13 2 1307.3 (R) 10 2 3 Echi S (S) 17 0

4 F2 from mutant-F1 (R) 7 2

5 F2 from non-mutant F1 (R) 4 1 Total 57

102

According to Yabuno (1983), E. colona is a hexaploid grass species with 54 chromosomes

(2n = 6x = 54). This suggests that 9 is the base chromosome number of this grass species. The case of this study is relatively similar to that of ACCase resistance in A. fatua, an allohexaploid species (2n = 6x = 42) (Yang et al., 1999). In A. fatua, there are three homoeologous ACCase genes in which each single gene contains a mutation offering herbicide resistance although the resistance was not strong (Yu et al., 2013). In addition, the existence of more than one EPSPS gene was also found by Goldsbrough et al. (1990) in tobacco (Nicotiana tabacum L.) with presence of at least two EPSPS genes, however, the glyphosate resistance mechanism of this species was gene amplification. The chromosome of

N. tabacum was determined as an allotetraploid (2n = 4x = 48) (Lim et al., 2000). In several other glyphosate resistant weed species, mutations were detected in EPSPS cDNA such as in

E. indica (Baerson et al., 2002) with diploid chromosome (2n = 2x = 18) (Hiremath and

Chennaveeraiah, 1982) and in L. multiflorum (Jasieniuk et al., 2008) with diploid chromosome (2n = 2x = 14) (Thomas et al., 1994). In these two weed species, substitution of serine for proline at codon 106 has been identified. Yu et al. (2013) supposed that the herbicide resistance in hexaploid grass species is more complicated compared to that in diploid species.

5.4 Conclusions

While E colona is generally considered self-pollinated, this study demonstrated a natural outcrossing frequency of 1.38%, as measured by the transfer of glyphosate resistance from resistant plants to susceptible plants. This amount of outcrossing could spread resistance locally within populations, but is unlikely to contribute to spread of resistance between populations. The identification of a mutation in the EPSPS gene of the F1 progenies proved the glyphosate resistance trait came from the resistant parent via pollen. Segregation of the F2 progenies occurred at a 3:1 resistance : susceptibility ratio, demonstrating the F1 individuals

103 were heterozygotes and the glyphosate resistance inheritance in E. colona was likely due to a single, dominant gene. In a hand cross between the resistant and susceptible populations, the dose response of the F2 progeny suggested the existence of additional resistance genes in this population. There was greater than expected survival at low rates in the progeny, suggesting a trait giving low levels of resistance (such as a target site mutation) was present, as well as a trait providing higher levels of resistance. Analysing the cDNA sequence indicated the presence of at least two EPSPS genes in this grass species and only one gene carried a mutation in the resistant individuals. This research demonstrated glyphosate resistance in E. colona may be complex.

Literature Cited

Amrhein, N., Schab, J. and Steinrucken, H.C. (1980). 'The mode of action of the herbicide glyphosate', Naturwissenschaften 67 (7), 356-357.

Baerson, S.R., Rodriguez, D.J., Tran, M., Feng, Y.M., Biest, N.A. and Dill, G.M. (2002). 'Glyphosate-resistant goosegrass. Identification of a mutation in the target enzyme 5- enolpyruvylshikimate-3-phosphate synthase', Plant Physiology 129 (3), 1265-1275.

Chandi, A., Milla-Lewis, S.R., Giacomini, D., Westra, P., Preston, C., Jordan, D.L., York, A.C., Burton, J.D. and Whitaker, J.R. (2012). 'Inheritance of evolved glyphosate resistance in a North Carolina palmer amaranth (Amaranthus palmeri) biotype', International Journal of Agronomy, DOI: 10.1155/2012/176108.

Christoffers, M.J. (1999). 'Genetic aspects of herbicide-resistant weed management', Weed Technology 13 (3), 647-652.

Darmency, H., Lefol, E. and Fleury, A. (1998). 'Spontaneous hybridizations between oilseed rape and wild radish', Molecular Ecology 7 (11), 1467-1473.

Davis, V.M., Kruger, G.R., Hallett, S.G., Tranel, P.J. and Johnson, W.G. (2010). 'Heritability of glyphosate resistance in Indiana horseweed (Conyza canadensis) populations', Weed Science 58 (1), 30-38.

104

Diggle, A.J. and Neve, P. (2001). The population dynamics and genetics of herbicide resistance - A modeling approach. In: Powles, S.B. and Shaner, D.L. (eds.), Herbicide Resistance and World Grains. CRC Press-Taylor & Francis Group, 6000 Broken Sound Parkway NW, Ste 300, Boca Raton, FL 33487-2742 USA, Agr Western Australia, Bentley, WA 6983, Australia, 61-99.

Duke, S.O., Baerson, S.R. and Rimando, A.M. (2003). Glyphosate. In: Encyclopedia of Agrochemicals. John Wiley & Sons, Inc., New York, USA.

Ellstrand, N.C. (1992a). 'Gene flow among seed plant populations', New Forests 6 (1-4), 241- 256.

Ellstrand, N.C. (1992b). 'Gene flow by pollen: implications for plant conservation genetics', Oikos 63 (1), 77-86.

Gaines, T.A., Shaner, D.L., Ward, S.M., Leach, J.E., Preston, C. and Westra, P. (2011). 'Mechanism of resistance of evolved glyphosate-resistant palmer amaranth (Amaranthus palmeri)', Journal of Agricultural and Food Chemistry 59 (11), 5886- 5889.

Garcia-Vallve, S., Palau, J. and Romeu, A. (1999). 'Horizontal gene transfer in glycosyl hydrolases inferred from codon usage in Escherichia coli and Bacillus subtilis', Molecular Biology and Evolution 16 (9), 1125-1134 (http://genomes.urv.es/UPGMA/).

Goldsbrough, P.B., Hatch, E.M., Huang, B., Kosinski, W.G., Dyer, W.E., Herrmann, K.M. and Weller, S.C. (1990). 'Gene amplification in glyphosate tolerant tobacco cells', Plant Science 72 (1), 53-62.

Govindaraju, D.R. (1988). 'Relationship between dispersal ability and levels of gene flow in plants', Oikos 52 (1), 31-35.

Govindaraju, D.R. (1989). ' Estimates of gene flow in forest trees', Biological Journal of the Linnean Society 37 (4), 345-357.

Hiremath, S.C. and Chennaveeraiah, M.S. (1982). 'Cytogenetical studies in wild and cultivated species of Eleusine (Gramineae)', Caryologia 35 (1), 57-69.

Jasieniuk, M., Ahmad, R., Sherwood, A.M., Firestone, J.L., Perez-Jones, A., Lanini, W.T., Mallory-Smith, C. and Stednick, Z. (2008). 'Glyphosate-resistant Italian ryegrass

105

(Lolium multiflorum) in California: Distribution, response to glyphosate, and molecular evidence for an altered target enzyme', Weed Science 56 (4), 496-502.

Jasieniuk, M., Brulebabel, A.L. and Morrison, I.N. (1994). 'Inheritance of trifluralin resistance in green foxtail (Setaria viridis)', Weed Science 42 (1), 123-127.

Jessop, J., Dashorst, G.R.M. and James, F.M. (2006). Grasses of South Australia : An illustrated guide to the native and naturalised species. Wakefield Press, Kent Town, Australia.

Kern, A.J., Myers, T.M., Jasieniuk, M., Murray, B.G., Maxwell, B.D. and Dyer, W.E. (2002). 'Two recessive gene inheritance for triallate resistance in Avena fatua L.', Journal of Heredity 93 (1), 48-50.

Koger, C.H., Shaner, D.L., Henry, W.B., Nadler-Hassar, T., Thomas, W.E. and Wilcut, J.W. (2005). 'Assessment of two nondestructive assays for detecting glyphosate resistance in horseweed (Conyza canadensis)', Weed Science 53 (5), 559-566.

Kremer, A., Ronce, O., Robledo-Arnuncio, J.J., Guillaume, F., Bohrer, G., Nathan, R., Bridle, J.R., Gomulkiewicz, R., Klein, E.K., Ritland, K., Kuparinen, A., Gerber, S. and Schueler, S. (2012). 'Long-distance gene flow and adaptation of forest trees to rapid climate change', Ecology Letters 15 (4), 378-392.

Levin, D.A. (1981). 'Dispersal versus gene flow in plants', Annals of the Missouri Botanical Garden 68 (2), 233-253.

Levin, D.A. (1984). Immigration in plants: An exercise in the subjunctive. In: Dirzo, R. and Sarukhan, J. (eds.), Perspectives on Plant Population Ecology. Sinauer Associates Inc., Sunderland. Mass, USA, 242-260.

Lim, K.Y., Kovarik, A., Matýăsek, R., Bezdĕk, M., Lichtenstein, C.P. and Leitch, A.R. (2000). 'Gene conversion of ribosomal DNA in Nicotiana tabacum is associated with undermethylated, decondensed and probably active gene units', Chromosoma 109 (3), 161-172.

Lorraine-Colwill, D.F., Powles, S.B., Hawkes, T.R. and Preston, C. (2001). 'Inheritance of evolved glyphosate resistance in Lolium rigidum (Gaud.)', Theoretical and Applied Genetics 102 (4), 545-550.

106

Marshall, M.W., Al-Khatib, K. and Loughin, T. (2001). 'Gene flow, growth, and competitiveness of imazethapyr-resistant common sunflower', Weed Science 49 (1), 14-21.

Messeguer, J., Fogher, C., Guiderdoni, E., Marfa, V., Catala, M.M., Baldi, G. and Mele, E. (2001). 'Field assessments of gene flow from transgenic to cultivated rice (Oryza sativa L.) using a herbicide resistance gene as tracer marker', Theoretical and Applied Genetics 103 (8), 1151-1159.

Mohseni-Moghadam, M., Schroeder, J. and Ashigh, J. (2013). 'Mechanism of resistance and inheritance in glyphosate resistant palmer amaranth (Amaranthus palmeri) populations from New Mexico, USA', Weed Science 61 (4), 517-525.

Motten, A.F. and Antonovics, J. (1992). 'Determinants of outcrossing rate in a predominantly self-fertilizing weed, Datura stramonium (Solanaceae)', American Journal of Botany 79 (4), 419-427.

Mueller, T.C., Massey, J.H., Hayes, R.M., Main, C.L. and Stewart, C.N. (2003). 'Shikimate accumulates in both glyphosate-sensitive and glyphosate-resistant horseweed (Conyza canadensis L. Cronq.)', Journal of Agricultural and Food Chemistry 51 (3), 680-684.

Murray, B.G., Morrison, I.N. and Friesen, L.F. (2002). 'Pollen-mediated gene flow in wild oat', Weed Science 50 (3), 321-325.

Ng, C.H., Ratnam, W., Surif, S. and Ismail, B.S. (2004). 'Inheritance of glyphosate resistance in goosegrass (Eleusine indica)', Weed Science 52 (4), 564-570.

Nunez-Farfan, J., Cabralesvargas, R.A. and Dirzo, R. (1996). 'Mating system consequences on resistance to herbivory and life history traits in Datura stramonium', American Journal of Botany 83 (8), 1041-1049.

Page, R.D.M. (1996). 'TreeView: An application to display phylogenetic trees on personal computers', Computer Applications in the Biosciences 12 (4), 357-358.

Perez-Jones, A., Park, K.W., Colquhoun, J., Mallory-Smith, C. and Shaner, D. (2005). 'Identification of glyphosate-resistant Italian ryegrass (Lolium multiflorum) in Oregon', Weed Science 53 (6), 775-779.

Powles, S.B. and Preston, C. (2006). 'Evolved glyphosate resistance in plants: Biochemical and genetic basis of resistance', Weed Technology 20 (2), 282-289.

107

Preston, C., Shaner, D.L., Westra, P., Culpepper, A.S., Grey, T., Vencill, W.K. and Wakelin, A. (2006). Can a shikimate assay be used to determine the genotype of glyphosate resistant plants for population genetic studies? In Preston, C., Watts, J.H. and Crossman, N.D., (eds.),The 15th Australian Weeds Conference on Managing Weeds in A Changing Climate, Adelaide, South Australia, 24-28 September 2006. Weed Management Society of South Australia, Australia, 511-514.

Rieger, M.A., Lamond, M., Preston, C., Powles, S.B. and Roush, R.T. (2002). 'Pollen- mediated movement of herbicide resistance between commercial canola fields', Science 296 (5577), 2386-2388.

Rognli, O.A., Nilsson, N.O. and Nurminiemi, M. (2000). 'Effects of distance and pollen competition on gene flow in the wind-pollinated grass Festuca pratensis Huds', Heredity 85 (6), 550-560.

Rubin, J.L., Gaines, C.G. and Jensen, R.A. (1982). 'Enzymological basis for herbicidal action of glyphosate', Plant Physiology 70 (3), 833-839.

Shaner, D.L., Nadler-Hassar, T., Henry, W.B. and Koger, C.H. (2005). 'A rapid in vivo shikimate accumulation assay with excised leaf discs', Weed Science 53 (6), 769-774.

Simarmata, M., Bughrara, S. and Penner, D. (2005). 'Inheritance of glyphosate resistance in rigid ryegrass (Lolium rigidum) from California', Weed Science 53 (5), 615-619.

Slatkin, M. (1987). 'Gene flow and the geographic structure of natural populations', Science 236 (4803), 787-792.

Stallings, G.P., Thill, D.C., Mallorysmith, C.A. and Shafii, B. (1995). 'Pollen-mediated gene flow of sulfonylurea-restant kochia (Kochia scoparia)', Weed Science 43 (1), 95-102.

Steinrucken, H.C. and Amrhein, N. (1980). 'The herbicide glyphosate is a potent inhibitor of 5-enolpyruvyl-shikimic acid-3-phosphate synthase', Biochemical and Biophysical Research Communications 94 (4), 1207-1212.

Thomas, H.M., Morgan, W.G., Meredith, M.R., Humphreys, M.W., Thomas, H. and Leggett, J.M. (1994). 'Identification of parental and recombined chromosomes in hybrid derivatives of Lolium multiflorum x Festuca pratensis by genomic in situ hybridization', Theoretical and Applied Genetics 88 (8), 909-913.

108

Thompson, J.D., Gibson, T.J., Plewniak, F., Jeanmougin, F. and Higgins, D.G. (1997). 'The CLUSTAL_X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools', Nucleic Acids Research 25 (24), 4876-4882.

Volenberg, D.S. and Stoltenberg, D.E. (2002). 'Giant foxtail (Setaria faberi) outcrossing and inheritance of resistance to acetyl-coenzyme A carboxylase inhibitors', Weed Science 50 (5), 622-627.

Wakelin, A.M. and Preston, C. (2006). 'Inheritance of glyphosate resistance in several populations of rigid ryegrass (Lolium rigidum) from Australia', Weed Science 54 (2), 212-219.

Yang, Q., Hanson, L., Bennett, M.D. and Leitch, I.J. (1999). 'Genome structure and evolution in the allohexaploid weed Avena fatua L. (Poaceae)', Genome 42 (3), 512-518.

Yu, Q., Ahmad-Hamdani, M.S., Han, H., Christoffers, M.J. and Powles, S.B. (2013). 'Herbicide resistance-endowing ACCase gene mutations in hexaploid wild oat (Avena fatua): insights into resistance evolution in a hexaploid species', Heredity 110 (3), 220- 231.

Zelaya, I.A., Owen, M.D.K. and Vangessel, M.J. (2004). 'Inheritance of evolved glyphosate resistance in Conyza canadensis (L.) Cronq.', Theoretical and Applied Genetics 110 (1), 58-70.

109

Chapter 6

General Discussion

6.1 Discussion of results

Weeds have always been considered a formidable obstacle to farming systems because of their impacts, such as reducing crop yield, obstructing harvest operations and contaminating produce. Herbicides have become the most common tool used by farmers in weed control

(Powles et al., 1997). Since herbicides were first used widely for controlling weeds in 1946, there has been a considerable increase in the amount and the variety of herbicides used due to their efficacy, ease of use and low cost (Heap, 1997). However, along with development of herbicides there has been an increase in herbicide resistant weed biotypes (Heap, 1997;

Powles et al., 1997). The first herbicide resistant weed was reported in 1968 as triazine resistance in common groundsel (Senecio vulgaris) (Ryan, 1970). At present, there are 236 weed species with resistance to 155 different herbicides in 65 countries of the world including

98 monocotyledon and 138 dicotyledon species (Heap, 2014). This has made weed control with herbicides more difficult, resulting in a need for new weed control tactics. One of these has been the development of genetically engineered crops resistant to multiple herbicides

(Powles et al., 1997).

As mentioned earlier, the main factors that impact on the evolution of herbicide resistance in weeds include genetic mutations, initial frequency of resistant alleles, selection pressure by using herbicide, fitness of resistant plants, gene migration, inheritance of resistance and features of the weed seed bank (Section 2.3). Glyphosate, a post-emergence systemic herbicide, has become a favourite herbicide of farmers all over the world since its introduction in 1974 (Franz et al., 1997; Duke et al., 2003; Duke and Powles, 2008a; Duke and Powles,

2008b) because of its pre-eminent properties such as high efficacy, wide-spectrum, non-

110 selection, safety for environment and mammals; and as a result has been applied on a large scale of in minimum- and no-tillage agriculture (Baylis, 2000; Woodburn, 2000; Dill et al.,

2008; Duke and Powles, 2008b). The massive adoption of glyphosate resistant crops has been another reason for widespread use of glyphosate. As for other herbicides, over-reliance on glyphosate has resulted in the evolution of resistance to this herbicide (Sammons et al., 2007).

Glyphosate resistance was first reported in 1996 in Lolium rigidum in Australia (Pratley et al.,

1996), and to date 29 weed species have been identified with populations resistant to glyphosate around the world (Heap, 2014). Control of herbicide-resistant weeds could be obtained by the rotational use of herbicides with different modes of action; however, control becomes more complicated for multiple-herbicide resistant weeds. For example, a L. rigidum population in South Australia was resistant to nine different herbicide families (Burnet et al.,

1994).

The recent rapid evolution of the glyphosate resistant E. colona populations in northern

Australia was one of reasons for this study. A survey showed that the number of glyphosate resistant E. colona populations (34 populations) was higher than that of susceptible populations (31 populations) tested (Chapter 3). The number of resistant populations has increased rapidly in a short time period and now occurs over a large area of southern

Queensland and northern NSW. This suggests that resistance has evolved at numerous sites due to similar farming practices. This was confirmed by the AFLP studies. These studies showed that populations of E. colona were highly variable and resistant individuals did not cluster genetically (Chapter 3). Therefore, it is unlikely that resistance had evolved in one location and been spread by seed across the landscape.

Resistant E. colona populations contained as much genetic diversity as a susceptible population (Chapter 3). This result indicates that a selection bottleneck was not evident in this species; because selection bottlenecks lead to reduced genetic diversity (Iqbal et al., 2001) and therefore adaptive evolution would be more limited (Dlugosch and Parker, 2008). In addition, it suggests that considerable gene flow is occurring within populations. This was

111 confirmed by the finding of a relatively high natural cross-pollination (1.38%) in this grass species (Chapter 5). This level of gene flow between resistant and susceptible individuals would contribute to localised expansion in resistant populations. As suggested by Jasieniuk et al. (1996), a high gene flow frequency would lead to a more accelerated dissemination of resistant individuals in a population. Letouze and Gasquez (2001) suggested that allogamy in plants resulted in greater spread of resistance than autogamy. In addition to enlarging herbicide resistant populations, allogamy would allow the ready accumulation of low level glyphosate resistance genes in sensitive weed populations (Busi and Powles, 2009).

Glyphosate resistance in E. colona was inherited as a single dominant gene trait (Chapter 5).

This characteristic would also aid the spread of glyphosate resistance within populations, as heterozygous individuals would be resistant to the herbicide. However, there was some evidence of weaker growth of resistant E. colona individuals compared to susceptible individuals, which might retard the evolution of resistance. According to Jasieniuk et al.

(1994) and Diggle and Neve (2001), the pattern of inheritance plays an important role in resistance evolution. The number of genes controlling resistance can impact on the speed of resistance evolution in weeds (Roush et al., 1990; Maxwell, 1992). Maxwell and Mortimer

(1994) concluded that dominant single gene inheritance can cause more rapid spread of resistance alleles within populations than where resistance has multigenic inheritance. In a large majority of studies to-date, resistance to herbicides in general and to glyphosate in particular in plants has been controlled by a single gene and there has been less evidence for herbicide resistance due to multiple genes (Darmency, 1994; Gasquez, 1997; Mohseni-

Moghadam et al., 2013). In addition, glyphosate resistance is inherited as a nuclear gene mutation (Souza-Machado, 1982; Jasieniuk et al., 1996) rather than as a maternally inherited trait as for triazine resistance (Souza-Machado et al., 1978; Darmency and Gasquez, 1981;

Scott and Putwain, 1981; Gasquez and Darmency, 1983; Darmency and Pernes, 1985).

The target-site resistance mechanism of E. colona in population A533.1 was used to identify the movement of the resistant gene to the susceptible population (Echi S) and the inheritance

112 of resistance (Chapter 5). This mutation proved to be an ideal marker in tracking the gene movement.

In addition to spread within populations, there is some evidence that resistance may have spread between populations of E. colona (Figure 1, Chapter 3). The different genetic clusters identified in the AFLP assessment contained accessions from numerous different sites in QLD and NSW and a high genetic diversity was present within each cluster. The evolution of glyphosate resistance in E. colona in Australia has most likely been a combination of two processes of independent evolution and gene flow (Chapter 3). Ultimately, the spread of glyphosate resistance in weed species can make management of that weed species difficult for many farmers over a large area. For example, in Argentina, glyphosate resistance in johnsongrass (Sorghum halepense) first occurred in 2002 but seven years later (2009) the land area with resistance was more 10,000 ha (Binimelis et al., 2009). Australia is the country having the largest reported area of glyphosate resistant E. colona in the world (Heap, 2014).

The ability of glyphosate resistance to spread within and between E. colona populations might be one of reasons for this.

This study indicated that some of the E. colona populations have evolved high levels of resistance to glyphosate. Population A533.1 was more than ten-fold resistant to glyphosate

(Chapter 3) meaning glyphosate would be unlikely to be economic as a weed control tactic and other measures should be applied, such as using alternate herbicides (Smith, 2010), a combination of herbicide and non-herbicidal tactics (Beckie, 2006) or integrated weed management (Llewellyn et al., 2007). In E colona, glyphosate resistance increased at high temperatures (Chapter 4) that occur frequently in summer in QLD and NSW. This is a significant difference between E. colona and other weed species. The reason for increasing resistance in E. colona at the high temperature was likely a result of decreased absorption of glyphosate into leaves and a lower amount of glyphosate entering leaf chloroplasts (Chapter

4). This finding has important considerations for the detection of glyphosate resistance in populations of E. colona. Testing for resistance under cool conditions may generate false

113 negatives where the population is assumed to be susceptible to the herbicide when it is really resistant in the field. Reduced movement of glyphosate into the leaf chloroplasts of L. rigidum was proposed by Lorraine-Colwill et al. (1999) and this was suggested to be due to reduced activity of the chloroplast phosphate carrier (Versaw and Harrison, 2002). It is not known whether a similar effect may occur in E.colona. Apart from glyphosate, the activity of some other herbicides can be affected by differences in temperature (Sheets, 1961; Dudek et al.,

1973; McWhorter and Jordan, 1976). According to Hatzios and Penner (1982), the influence of variation in temperature on the effectiveness of some herbicides happens via influencing the absorption, translocation or metabolism of these herbicides in plants. In addition to temperature, other environmental factors such as humidity, light likewise influence the efficacy of glyphosate in controlling weeds (Jordan, 1977; Cerdeira et al., 2007). Thus, in order to maximise the effectiveness of glyphosate on E. colona, environmental conditions should to be considered before applying this herbicide.

Although at least four glyphosate resistant mechanisms have been discovered in various plant species by previous studies (Section 2.4.4), mutation of the target-site gene was the only mechanism of glyphosate resistance identified in this study (Chapter 4). However, the fact that resistance mechanisms were not identified in several populations of E. colona in this research (Chapter 4) and the strongest resistance occurred in a population containing target- site mutation (A533.1) (Chapters 3 and 4), suggests the possible presence of additional glyphosate resistance mechanisms in E. colona. According to earlier studies of numerous weed species, mutations of the target-site gene EPSPS do not confer a strong glyphosate resistance level (Comai et al., 1983; Padgette et al., 1991; Powles and Preston, 2006;

Jasieniuk et al., 2008; Kaundun et al., 2011). This suggests the existence of multiple glyphosate resistance mechanisms may occur in population A533.1. Yu et al. (2007) discovered that the resistance mechanisms by mutation in EPSPS gene and by decline in translocation controlled simultaneously the glyphosate resistance in a L. rigidum population.

Within an Italian ryegrass (Lolium multiflorum) population from Chile, Michitte et al. (2007)

114 also found the concomitant action of three glyphosate resistance mechanisms: namely a decrease in glyphosate translocation, reduced foliar uptake and reduced spray retention. To date, mutations in the target-site gene have been detected in only six out of 29 glyphosate resistant weed species (Gains and Heap, 2014).

Blockage of the shikimate pathway in plants due to the inhibition of EPSP synthase causes a decrease in synthesis of aromatic amino acid and protein, hence results in the death of juvenile cells (Duke et al., 2003). At the same time, there is massive accumulation of shikimate in plants (Amrhein et al., 1980; Duke et al., 2003). In this research, population

A533.1 was used to compare the shikimate accumulation with the susceptible population Echi

S (Chapter 4); because accumulation of shikimate in plant tissues could be utilised as a marker in assessing the amount of inhibition of EPSPS by glyphosate (Lydon and Duke,

1988); and the shikimate accumulation in the resistant population A533.1 was found lower than that in the susceptible population Echi S. In addition, the shikimate assay can be used to identify glyphosate resistant weeds early (Nol et al., 2012).

To protect crops from invasion of E. colona and slow down the evolution of glyphosate resistance in this grass, effective management strategies need to be adopted. The use of alternative herbicides is an effective control method. Previously, when propanil resistance in

E. colona was identified in rice fields in Arkansas, quinclorac was used as an alternate herbicide, and after quinclorac resistance occurred, clomazone (a pre-emergence herbicide) was recommended for controlling this grass (Smith, 2010). According to Diggle and Neve

(2001), using glyphosate at high rates could restrict heterozygous weed populations through reducing the potential dispersal of the resistant weed populations; however, this measure is expensive and will simply result in the evolution of weeds with higher levels of resistance.

The concurrent combination of different herbicides is also recommended. For example, the combination of glyphosate and 2,4-D herbicides can be used as an effective control for cutleaf evening primrose (Oenothera laciniata) and henbit (Lamium amplexicaule) (Smith, 2010). In

C. canadensis management in the US, the combination of glyphosate and pre-emergence

115 herbicides (Vangessel et al., 2001) provided effective weed control. Apart from chemical control, other weed management tactics should be considered. Before the introduction of glyphosate resistant transgenic cotton into Australia, a system of integrated weed control had been used with a combination of different herbicides and alternate control measures consisting of manual weeding, crop rotations and cultivation (Roberts, 1998). This method of weed management restricted the evolution of herbicide resistance including glyphosate resistance in weeds in cotton fields of Australia. Mechanical measures likewise showed high efficacy in controlling C. canadensis in the US (Brown and Whitwell, 1988). For E. colona control in fallows in northern Australia, it is important for new weed management practices to be identified and adopted as the continual use of glyphosate will only result in more cases of glyphosate resistance.

6.2 Conclusions

In conclusion, this research identified glyphosate resistant E. colona present over a wide area of the cropping regions in northern Australia with high resistance levels. The high levels of genetic diversity between and within glyphosate resistant populations demonstrated the evolution of glyphosate resistance occurring repeatedly in many different locations. High temperatures increased the level of glyphosate resistance in E. colona, probably due to decreases in glyphosate absorption and in penetration of glyphosate into the chloroplast. A target-site mutation within EPSPS was the only glyphosate resistance mechanism detected in

E. colona in this research, but at least one other glyphosate resistance mechanism may be present in E. colona. E. colona is a mainly autogamous grass species with the low allogamy rate. However, glyphosate resistance can move from resistant plants to susceptible plants within populations through pollen movement. Glyphosate resistance in one resistant population of E. colona was inherited in a dominant monogenic inheritance pattern. More than one EPSPS gene within E. colona were shown to be expressed.

116

6.3 Contributions to knowledge

This research has contributet to knowledge about glyphosate resistance evolution in

E. colona through the evaluation of genetic diversity amongst grass populations, the identification of resistance mechanisms; the mode of inheritance of glyphosate resistance and demonstration of resistance spread within populations by pollen movements. As glyphosate resistant E. colona with high resistance levels is widespread over the cropping regions in

QLD and NSW, other tactics to control this weed need to be adopted. The control of E. colona with glyphosate is normally conducted in summer with high temperatures (over 30oC) in northern Australia and this is a considerable hindrance to controlling resistant grass populations. The high genetic diversity identified in E. colona populations suggests seed movement of glyphosate resistance may be playing an important role in spread. Accordingly, preventing the spread of seed could slow resistance evolution in this species.

6.4 Future research

Some issues related to the evolution of glyphosate resistance in E. colona have not been elucidated. Only one mechanism, namely a mutation of the target-site gene was found in population A533.1. Other populations clearly contain mechanisms of glyphosate resistance that are not target site mutations within the EPSPS gene. These mechanisms remain to be elucidated. There also appears to be differences among resistant populations between the levels of expression of genes carrying a mutation within EPSPS. This could be investigated by a more thorough sequencing the EPSPS cDNA across resistant populations. In addition, the exact number of EPSPS genes in E. colona that are expressed has not been fully determined.

117

Literature Cited

Amrhein, N., Schab, J. and Steinrucken, H.C. (1980). 'The mode of action of the herbicide glyphosate', Naturwissenschaften 67 (7), 356-357.

Baylis, A.D. (2000). 'Why glyphosate is a global herbicide: strengths, weaknesses and prospects', Pest Management Science 56 (4), 299-308.

Beckie, H.J. (2006). 'Herbicide-resistant weeds: Management tactics and practices', Weed Technology 20 (3), 793-814.

Binimelis, R., Pengue, W. and Monterroso, I. (2009). '"Transgenic treadmill": Responses to the emergence and spread of glyphosate-resistant johnsongrass in Argentina', Geoforum 40 (4), 623-633.

Brown, S.M. and Whitwell, T. (1988). 'Influence of tillage on horseweed, Conyza- canadensis', Weed Technology 2 (3), 269-270.

Burnet, M.W.M., Hart, Q., Holtum, J.a.M. and Powles, S.B. (1994). 'Resistance to nine herbicide classes in a population of rigid ryegrass (Lolium rigidum)', Weed Science 42 (3), 369-377.

Busi, R. and Powles, S.B. (2009). 'Evolution of glyphosate resistance in a Lolium rigidum population by glyphosate selection at sublethal doses', Heredity 103 (4), 318-325.

Cerdeira, A.L., Gazziero, D.L.P., Duke, S.O., Matallo, M.B. and Spadotto, C.A. (2007). 'Review of potential environmental impacts of transgenic glyphosate-resistant soybean in Brazil', Journal of Environmental Science and Health, Part B: Pesticides, Food Contaminants, and Agricultural Wastes 42 (5), 539-549.

Comai, L., Sen, L.C. and Stalker, D.M. (1983). 'An altered aroA gene product confers resistance to the herbicide glyphosate', Science 221 (4608), 370-371.

Darmency, H. (1994). Genetics of herbicide resistance in weeds and crops. In: Powles, S.B. and Holtum, J.A.M. (eds.), Herbicide resistance in plants: Biology and biochemistry. 263-297.

Darmency, H. and Gasquez, J. (1981). 'Inheritance of triazine resistance in Poa annua: Consequences for population dynamics', New Phytologist 89 (3), 487-493.

118

Darmency, H. and Pernes, J. (1985). 'Use of wild Setaria-viridis (L.) Beauv. to improve triazine resistance in cultivated S. italica (L.) by hybridization', Weed Research 25 (3), 175-179.

Dill, G.M., Cajacob, C.A. and Padgette, S.R. (2008). 'Glyphosate-resistant crops: adoption, use and future considerations', Pest Management Science 64 (4), 326-331.

Dlugosch, K.M. and Parker, I.M. (2008). 'Founding events in species invasions: genetic variation, adaptive evolution, and the role of multiple introductions', Molecular Ecology 17 (1), 431-449.

Dudek, C., Basler, E. and Santelma.Pw (1973). 'Absorption and translocation of terbutryn and propazine', Weed Science 21 (5), 440-443.

Duke, S.O., Baerson, S.R. and Rimando, A.M. (2003). Glyphosate. In: Encyclopedia of Agrochemicals. John Wiley & Sons, Inc., New York, USA.

Duke, S.O. and Powles, S.B. (2008a). 'Glyphosate-resistant weeds and crops', Pest Management Science 64 (4), 317-318.

Duke, S.O. and Powles, S.B. (2008b). 'Glyphosate: a once-in-a-century herbicide', Pest Management Science 64 (4), 319-325.

Franz, J.E., Mao, M.K. and Sikorski, J.A. (1997). Glyphosate: A unique global herbicide. American Chemical Society, Washington.

Gains, T.A. and Heap, I.M. (2014). Mutations in herbicide-resistant weeds to EPSP synthase inhibitors, viewed 16 July 2014, .

Gasquez, J. (1997). Genetics of herbicide resistance within weeds. Factors of evolution, inheritance and fitness. In De-Prado, R., Jorrin, J. and Garcia-Torres, L., (eds.),Weed and Crop Resistance to Herbicides, Cordoba, Spain, April 1995. Kluwer Academic Publ, Dordrecht, The Netherlands, 181-189.

119

Gasquez, J. and Darmency, H. (1983). 'Variation of chloroplast properties between two triazine resistant biotypes of Poa annua L.', Plant Science Letters 30 (1), 99-106.

Hatzios, K.K. and Penner, D. (1982). Metabolism of herbicides in higher plants. Burgess Publishing Company, Minneapolis, USA.

Heap, I. (2014). The international survey of herbicide resistant weeds, viewed 30 July 2014, .

Heap, I.M. (1997). 'The occurrence of herbicide-resistant weeds worldwide', Pesticide Science 51 (3), 235-243.

Iqbal, M.J., Reddy, O.U.K., El-Zik, K.M. and Pepper, A.E. (2001). 'A genetic bottleneck in the 'evolution under domestication' of upland cotton Gossypium hirsutum L. examined using DNA fingerprinting', Theoretical and Applied Genetics 103 (4), 547-554.

Jasieniuk, M., Ahmad, R., Sherwood, A.M., Firestone, J.L., Perez-Jones, A., Lanini, W.T., Mallory-Smith, C. and Stednick, Z. (2008). 'Glyphosate-resistant Italian ryegrass (Lolium multiflorum) in California: Distribution, response to glyphosate, and molecular evidence for an altered target enzyme', Weed Science 56 (4), 496-502.

Jasieniuk, M., Brûlé-Babel, A.L. and Morrison, I.N. (1996). 'The evolution and genetics of herbicide resistance in weeds', Weed Science 44 (1), 176-193.

Jasieniuk, M., Brulebabel, A.L. and Morrison, I.N. (1994). 'Inheritance of trifluralin resistance in green foxtail (Setaria viridis)', Weed Science 42 (1), 123-127.

Jordan, T.N. (1977). 'Effect of temperature and relative humidity on toxicity of glyphosate to bermudagrass (Cynodon dactylon)', Weed Science 25 (5), 448-451.

Kaundun, S.S., Dale, R.P., Zelaya, I.A., Dinelli, G., Marotti, I., Mcindoe, E. and Cairns, A. (2011). 'A novel P106L mutation in EPSPS and an unknown mechanism(s) act additively to confer resistance to glyphosate in a South African Lolium rigidum population', Journal of Agricultural and Food Chemistry 59 (7), 3227-3233.

Letouze, A. and Gasquez, J. (2001). 'Inheritance of fenoxaprop-P-ethyl resistance in a blackgrass (Alopecurus myosuroides Huds.) population', Theoretical and Applied Genetics 103 (2-3), 288-296.

120

Llewellyn, R.S., Lindner, R.K., Pannell, D.J. and Powles, S.B. (2007). 'Herbicide resistance and the adoption of integrated weed management by Western Australian grain growers', Agricultural Economics 36 (1), 123-130.

Lorraine-Colwill, D.F., Hawkes, T.R., Williams, P.H., Warner, S.a.J., Sutton, P.B., Powles, S.B. and Preston, C. (1999). 'Resistance to glyphosate in Lolium rigidum', Pesticide Science 55 (4), 486-503.

Lydon, J. and Duke, S.O. (1988). 'Glyphosate induction of elevated levels of hydroxybenzoic acid in higher plants', Journal of Agricultural and Food Chemistry 36 (4), 813-818.

Maxwell, B.D. (1992). 'Predicting gene flow from herbicide resistant weeds in annual agriculture systems', Bulletin of the Ecological Society of America 73 (2 Suppl), 264.

Maxwell, B.D. and Mortimer, A.M. (1994). Selection for herbicide resistance. In: Powles, S.B. and Holtum, J.A.M. (eds.), Herbicide resistance in plants: Biology and biochemistry. CRC Press, Inc., Boca Raton, Florida, USA; CRC Press, London, England, UK, 1-25.

Mcwhorter, C.G. and Jordan, T.N. (1976). 'Effects of adjuvants and environment on tocicity of dalapon to johnsongrass', Weed Science 24 (3), 257-260.

Nol, N., Tsikou, D., Eid, M., Livieratos, I.C. and Giannopolitis, C.N. (2012). 'Shikimate leaf disc assay for early detection of glyphosate resistance in Conyza canadensis and relative transcript levels of EPSPS and ABC transporter genes', Weed Research 52 (3), 233-241.

Padgette, S.R., Re, D.B., Gasser, C.S., Eichholtz, D.A., Frazier, R.B., Hironaka, C.M., Levine, E.B., Shah, D.M., Fraley, R.T. and Kishore, G.M. (1991). 'Site-directed mutagenesis of a conserved region of the 5-enolpyruvyl shikimate-3-phosphate synthase active site', Journal of Biological Chemistry 266 (33), 22364-22369.

121

Powles, S.B. and Preston, C. (2006). 'Evolved glyphosate resistance in plants: Biochemical and genetic basis of resistance', Weed Technology 20 (2), 282-289.

Powles, S.B., Preston, C., Bryan, I.B. and Jutsum, A.R. (1997). Herbicide resistance: Impact and management. In: Sparks, D.L. (ed.), Advances in Agronomy, vol. 58. Elsevier Academic Press Inc., 525 B Street, Suite 1900, San Diego, CA 92101-4495 USA, 57- 93.

Pratley, J., Baines, P., Eberbach, P., Incerti, M. and Broster, J. (1996). Glyphosate resistance in annual ryegrass. In Virgona, J. and Michalk, D., (eds.),The 11th Annual Conference of Grassland Society of New South Wales, Wagga Wagga, NSW, Australia, 10-11 July 1996. New South Wales, Australia, 122.

Roberts, G.N. (1998). Developing integrated weed management systems for cotton. In Proceedings of the 2nd World Cotton Conference, Athens, Greece, 6–12 September 1998.

Roush, M.L., Radosevich, S.R. and Maxwell, B.D. (1990). 'Future outlook for herbicide- resistance research', Weed Technology 4 (1), 208-214.

Ryan, G.F. (1970). 'Resistance of common groundsel to simazine and atrazine', Weed Science 18 (5), 614-616.

Sammons, R.D., Heering, D.C., Dinicola, N., Glick, H. and Elmore, G.A. (2007). 'Sustainability and stewardship of glyphosate and glyphosate-resistant crops', Weed Technology 21 (2), 347-354.

Scott, K.R. and Putwain, P.D. (1981). 'Maternal inheritance of simazine resistance in a population of Senecio vulgaris', Weed Research 21 (3-4), 137-140.

Sheets, T.J. (1961). 'Uptake and distribution of simazine by oat and cotton seedlings', Weeds 9 (1), 1-13.

Smith, K. (2010). Strategies for managing glyphosate resistance - an extension perspective. In: Nandula, V.K. (ed.), Glyphosate Resistance in Crops and Weeds: History, Development, and Management. John Wiley & Sons, Inc., Hoboken, New Jersey, USA, 281-295.

Souza-Machado, V. (1982). Inheritance and breeding potential of triazine tolerance and resistance in plants. In: LeBaron, H.M. and Gressel, J. (eds.), Herbicide resistance in plants. John Wiley & Sons, Inc., New York, USA, 257-273.

122

Souza-Machado, V., Bandeen, J.D., Stephenson, G.R. and Lavigne, P. (1978). 'Uniparental inheritance of chloroplast atrazine tolerance in Brassica campestris', Canadian Journal of Plant Science 58 (4), 977-981.

Vangessel, M.J., Ayeni, A.O. and Majek, B.A. (2001). 'Glyphosate in full-season no-till glyphosate-resistant soybean: Role of preplant applications and residual herbicides', Weed Technology 15 (4), 714-724.

Woodburn, A.T. (2000). 'Glyphosate: production, pricing and use worldwide', Pest Management Science 56 (4), 309-312.

Yu, Q., Cairns, A. and Powles, S. (2007). 'Glyphosate, paraquat and ACCase multiple herbicide resistance evolved in a Lolium rigidum biotype', Planta 225 (2), 499-513.

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Appendices

Appendix 1: Geographical sites of towns where are nearest to origins of 65 E. colona populations used in this research (Chapter 3).

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Appendix 2: Response of eleven E. colona populations to different glyphosate rates in the dose response experiment. Lines are survival data back-transformed using the probit equations. Each data point represents the mean percentage survival from three replicates ± SE

(Chapter 3).

A533.1 (R) L594 (R) 100 RL11 (R) 1352.1 (R)

90 1307.3 (R) A516 (R) A491 (R) RL17 (R) 80 RL21 (R) RL4 (R) Echi S (S) 70

50 Survival (%) Survival 40

0 0 500 1000 1500 2000 2500

Glyphosate (g air. ha-1)

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Appendix 3: Distance matrix from AFLPs based on jaccard’s coefficient in comparison between populations collected across Queensland and New South Wales, Australia (Chapter 3).

Population Echi S 1307.3 Echi R 1264.1 A516 RL15 RL11 1264.2 1265.1 A533.1

Echi S 0.000 0.644 0.226 0.674 0.472 0.258 0.821 0.541 0.457 0.528 1307.3 0.000 0.634 0.188 0.600 0.659 0.907 0.553 0.590 0.650 Echi R 0.000 0.632 0.529 0.115 0.829 0.515 0.469 0.500 1264.1 0.000 0.667 0.622 0.897 0.622 0.543 0.571 A516 0.000 0.559 0.892 0.469 0.515 0.545 RL15 0.000 0.824 0.545 0.452 0.484

RL11 0.000 0.947 0.857 0.886 1264.2 0.000 0.588 0.576 1265.1 0.000 0.192 A533.1 0.000

(Appendix 3 continued)

Population RL17 L594 A491 967.1 RL8 182-12 1352.1 1352.3 RL2 RL19 Echi S 0.375 0.730 0.643 0.619 0.281 0.605 0.485 0.564 0.675 0.281 1307.3 0.738 0.737 0.294 0.156 0.634 0.206 0.622 0.575 0.312 0.667 Echi R 0.379 0.765 0.667 0.605 0.276 0.625 0.594 0.543 0.667 0.276 1264.1 0.744 0.778 0.312 0.226 0.667 0.273 0.618 0.528 0.276 0.632 A516 0.618 0.727 0.667 0.605 0.571 0.590 0.548 0.622 0.667 0.611 RL15 0.357 0.758 0.658 0.632 0.310 0.683 0.581 0.529 0.657 0.250 RL11 0.812 0.900 0.897 0.900 0.794 0.930 0.909 0.895 0.886 0.794 1264.2 0.647 0.719 0.622 0.514 0.600 0.579 0.533 0.485 0.618 0.639 1265.1 0.647 0.758 0.583 0.556 0.600 0.615 0.483 0.333 0.618 0.559 A533.1 0.636 0.750 0.611 0.622 0.629 0.641 0.464 0.310 0.647 0.588 RL17 0.000 0.700 0.744 0.718 0.259 0.732 0.600 0.629 0.714 0.259 L594 0.000 0.778 0.750 0.688 0.730 0.577 0.697 0.750 0.727 A491 0.000 0.333 0.732 0.371 0.618 0.641 0.214 0.667 967.1 0.000 0.605 0.294 0.629 0.541 0.241 0.675 RL8 0.000 0.659 0.594 0.622 0.667 0.214 182-12 0.000 0.611 0.600 0.394 0.690 1352.1 0.000 0.562 0.613 0.548 1352.3 0.000 0.639 0.622 RL2 0.000 0.629 RL19 0.000

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(Appendix 3 continued)

Population RL4 BYG5 A533.3 RL21 QBG4 RL6 1352.4 L593 RL3 A533.2

Echi S 0.634 0.258 0.686 0.630 0.630 0.667 0.625 0.622 0.714 0.682

1307.3 0.219 0.659 0.795 0.316 0.222 0.206 0.250 0.147 0.281 0.212

Echi R 0.622 0.250 0.719 0.682 0.619 0.659 0.611 0.643 0.711 0.641

1264.1 0.172 0.658 0.771 0.333 0.235 0.324 0.267 0.212 0.355 0.167

A516 0.622 0.515 0.719 0.651 0.619 0.659 0.571 0.575 0.639 0.641

RL15 0.611 0.286 0.710 0.674 0.643 0.683 0.639 0.667 0.703 0.632

RL11 0.895 0.824 0.897 0.935 0.911 0.905 0.921 0.909 0.889 0.927

1264.2 0.571 0.588 0.710 0.575 0.575 0.541 0.515 0.564 0.629 0.556

1265.1 0.571 0.545 0.710 0.610 0.575 0.650 0.600 0.526 0.667 0.556

A533.1 0.600 0.576 0.700 0.564 0.600 0.675 0.588 0.625 0.694 0.583

RL17 0.667 0.357 0.774 0.750 0.778 0.732 0.694 0.773 0.686 0.750

L594 0.735 0.719 0.862 0.750 0.780 0.763 0.727 0.775 0.719 0.784

A491 0.290 0.756 0.806 0.333 0.286 0.324 0.375 0.265 0.355 0.281

967.1 0.258 0.667 0.811 0.351 0.257 0.188 0.233 0.235 0.267 0.194

RL8 0.658 0.310 0.794 0.682 0.651 0.590 0.611 0.674 0.676 0.675

182-12 0.250 0.650 0.722 0.342 0.250 0.333 0.226 0.229 0.412 0.294

1352.1 0.562 0.581 0.714 0.568 0.675 0.684 0.548 0.632 0.667 0.629

1352.3 0.556 0.571 0.765 0.487 0.561 0.600 0.543 0.585 0.649 0.541

RL2 0.250 0.730 0.818 0.400 0.353 0.290 0.286 0.333 0.192 0.300

RL19 0.622 0.310 0.758 0.682 0.682 0.690 0.684 0.674 0.676 0.675

RL4 0.000 0.684 0.765 0.361 0.314 0.303 0.179 0.294 0.214 0.258

BYG5 0.000 0.667 0.733 0.705 0.744 0.639 0.667 0.737 0.667

A533.3 0.000 0.805 0.775 0.850 0.758 0.769 0.824 0.778

RL21 0.000 0.263 0.297 0.294 0.333 0.417 0.306

QBG4 0.000 0.250 0.294 0.194 0.417 0.206

RL6 0.000 0.281 0.278 0.258 0.242

1352.4 0.000 0.324 0.310 0.233

L593 0.000 0.400 0.235

RL3 0.000 0.375

A533.2 0.000

127

(Appendix 3 continued)

Population 1352.5 RL1 A475 967.2 RL9 1352.8 1301 RL10 BYG4 RL13 Echi S 0.682 0.636 0.674 0.636 0.643 0.711 0.575 0.650 0.674 0.698 1307.3 0.212 0.206 0.278 0.152 0.242 0.265 0.188 0.281 0.242 0.219 Echi R 0.707 0.625 0.634 0.625 0.667 0.675 0.595 0.639 0.667 0.692 1264.1 0.281 0.161 0.389 0.273 0.258 0.281 0.258 0.179 0.312 0.290 A516 0.605 0.625 0.667 0.625 0.595 0.675 0.514 0.639 0.632 0.622 RL15 0.700 0.615 0.690 0.615 0.658 0.667 0.622 0.629 0.658 0.684 RL11 0.927 0.905 0.932 0.905 0.925 0.900 0.897 0.919 0.925 0.923 1264.2 0.595 0.579 0.553 0.541 0.583 0.595 0.500 0.588 0.583 0.571 1265.1 0.595 0.500 0.659 0.541 0.543 0.632 0.543 0.588 0.622 0.649 A533.1 0.622 0.568 0.650 0.605 0.611 0.658 0.611 0.576 0.611 0.639 RL17 0.718 0.762 0.767 0.732 0.744 0.780 0.711 0.722 0.744 0.703 L594 0.784 0.763 0.800 0.730 0.706 0.784 0.743 0.758 0.743 0.735 A491 0.281 0.273 0.242 0.273 0.312 0.226 0.312 0.241 0.258 0.233 967.1 0.303 0.188 0.361 0.188 0.281 0.303 0.167 0.323 0.333 0.312 RL8 0.707 0.690 0.756 0.690 0.732 0.707 0.632 0.711 0.700 0.692 182-12 0.343 0.286 0.306 0.333 0.219 0.343 0.219 0.258 0.324 0.250 1352.1 0.588 0.649 0.658 0.611 0.618 0.703 0.576 0.533 0.576 0.606 1352.3 0.579 0.526 0.575 0.486 0.528 0.615 0.568 0.571 0.605 0.595 RL2 0.355 0.290 0.364 0.290 0.387 0.355 0.214 0.192 0.214 0.310 RL19 0.738 0.659 0.727 0.690 0.732 0.707 0.667 0.639 0.667 0.725 RL4 0.258 0.303 0.371 0.250 0.233 0.312 0.172 0.148 0.290 0.207 BYG5 0.700 0.683 0.721 0.683 0.658 0.732 0.658 0.667 0.692 0.718 A533.3 0.778 0.757 0.795 0.789 0.735 0.778 0.735 0.750 0.771 0.765 RL21 0.306 0.297 0.270 0.250 0.333 0.306 0.378 0.324 0.235 0.314 QBG4 0.351 0.147 0.270 0.250 0.286 0.206 0.235 0.324 0.286 0.265 RL6 0.294 0.333 0.306 0.286 0.371 0.242 0.273 0.364 0.324 0.303 1352.4 0.233 0.333 0.353 0.281 0.267 0.344 0.143 0.185 0.207 0.179 L593 0.286 0.176 0.297 0.278 0.265 0.235 0.212 0.303 0.314 0.294 RL3 0.323 0.364 0.429 0.258 0.355 0.375 0.241 0.345 0.300 0.333 A533.2 0.194 0.188 0.314 0.242 0.226 0.194 0.281 0.207 0.226 0.200 1352.5 0.000 0.343 0.314 0.242 0.281 0.303 0.281 0.267 0.226 0.138 RL1 0.000 0.351 0.182 0.219 0.242 0.219 0.312 0.273 0.303 A475 0.000 0.257 0.343 0.265 0.343 0.281 0.242 0.273 967.2 0.000 0.219 0.294 0.219 0.312 0.219 0.250 RL9 0.000 0.281 0.258 0.241 0.312 0.233 1352.8 0.000 0.333 0.323 0.281 0.200 1301 0.000 0.241 0.258 0.233 RL10 0.000 0.179 0.214 BYG4 0.000 0.172 RL13 0.000

128

(Appendix 3 continued)

Population A508 A1076.1 1307.1 163-12 A818 RL14 A498.1 A671.1 1307.2 140.1-12 RL16 Echi S 0.634 0.614 0.161 0.659 0.628 0.610 0.682 0.643 0.651 0.636 0.738 1307.3 0.219 0.176 0.651 0.303 0.182 0.294 0.265 0.188 0.265 0.206 0.364 Echi R 0.622 0.634 0.267 0.649 0.650 0.632 0.641 0.595 0.605 0.590 0.703 1264.1 0.233 0.294 0.683 0.267 0.353 0.364 0.281 0.258 0.333 0.219 0.276 A516 0.583 0.564 0.514 0.649 0.541 0.556 0.641 0.595 0.568 0.625 0.667 RL15 0.611 0.659 0.241 0.639 0.675 0.658 0.632 0.622 0.667 0.615 0.694 RL11 0.923 0.907 0.838 0.921 0.902 0.925 0.927 0.925 0.927 0.905 0.946 1264.2 0.485 0.514 0.543 0.600 0.568 0.500 0.514 0.500 0.471 0.541 0.618 1265.1 0.571 0.590 0.500 0.559 0.605 0.622 0.595 0.583 0.632 0.579 0.657 A533.1 0.559 0.650 0.529 0.588 0.667 0.649 0.583 0.571 0.622 0.568 0.606 RL17 0.703 0.738 0.310 0.730 0.756 0.744 0.718 0.744 0.718 0.762 0.676 L594 0.735 0.737 0.706 0.765 0.722 0.706 0.750 0.743 0.750 0.763 0.750 A491 0.290 0.294 0.714 0.207 0.400 0.364 0.281 0.258 0.382 0.219 0.333 967.1 0.138 0.265 0.659 0.344 0.273 0.333 0.250 0.167 0.133 0.242 0.355 RL8 0.658 0.667 0.323 0.750 0.683 0.700 0.707 0.667 0.641 0.659 0.703 182-12 0.250 0.206 0.610 0.226 0.314 0.219 0.294 0.219 0.242 0.286 0.394 1352.1 0.562 0.622 0.531 0.636 0.639 0.618 0.629 0.618 0.629 0.649 0.656 1352.3 0.514 0.538 0.528 0.583 0.625 0.568 0.541 0.568 0.579 0.564 0.600 RL2 0.250 0.312 0.718 0.345 0.375 0.438 0.300 0.276 0.300 0.290 0.231 RL19 0.658 0.698 0.323 0.718 0.714 0.732 0.641 0.667 0.707 0.690 0.703 RL4 0.207 0.219 0.641 0.241 0.333 0.290 0.258 0.290 0.312 0.250 0.310 BYG5 0.684 0.690 0.241 0.711 0.641 0.658 0.700 0.658 0.700 0.683 0.730 A533.3 0.765 0.763 0.656 0.719 0.714 0.735 0.778 0.771 0.778 0.789 0.818 RL21 0.265 0.316 0.636 0.343 0.410 0.333 0.257 0.286 0.351 0.297 0.444 QBG4 0.265 0.171 0.667 0.242 0.324 0.286 0.257 0.182 0.306 0.091 0.353 RL6 0.250 0.257 0.674 0.382 0.361 0.324 0.294 0.273 0.242 0.235 0.344 1352.4 0.179 0.250 0.632 0.276 0.312 0.267 0.290 0.207 0.233 0.226 0.345 L593 0.294 0.147 0.689 0.273 0.257 0.265 0.235 0.212 0.333 0.229 0.382 RL3 0.276 0.333 0.692 0.419 0.290 0.406 0.323 0.355 0.323 0.364 0.321 A533.2 0.138 0.314 0.659 0.233 0.371 0.333 0.194 0.167 0.250 0.188 0.300 1352.5 0.258 0.314 0.659 0.290 0.324 0.382 0.353 0.333 0.353 0.294 0.355 RL1 0.194 0.257 0.643 0.226 0.265 0.324 0.188 0.161 0.294 0.182 0.344 A475 0.324 0.229 0.682 0.250 0.378 0.294 0.265 0.242 0.314 0.257 0.412 967.2 0.194 0.206 0.610 0.281 0.212 0.324 0.242 0.219 0.294 0.235 0.394 RL9 0.233 0.242 0.615 0.143 0.250 0.138 0.281 0.258 0.333 0.273 0.387 1352.8 0.258 0.265 0.721 0.233 0.371 0.281 0.194 0.226 0.353 0.188 0.406 1301 0.172 0.129 0.615 0.267 0.194 0.258 0.281 0.200 0.226 0.219 0.333 RL10 0.214 0.281 0.658 0.185 0.394 0.300 0.267 0.241 0.323 0.258 0.259 BYG4 0.233 0.294 0.650 0.267 0.303 0.364 0.226 0.200 0.333 0.219 0.333 RL13 0.207 0.219 0.675 0.179 0.333 0.290 0.258 0.233 0.312 0.194 0.310 A508 0.000 0.273 0.605 0.241 0.333 0.290 0.138 0.107 0.138 0.250 0.310 A1076.1 0.000 0.651 0.250 0.235 0.188 0.265 0.242 0.314 0.206 0.364 1307.1 0.000 0.632 0.634 0.615 0.659 0.650 0.659 0.674 0.718 163-12 0.000 0.364 0.207 0.233 0.207 0.344 0.226 0.345 A818 0.000 0.250 0.371 0.303 0.371 0.314 0.471 RL14 0.000 0.281 0.258 0.333 0.273 0.438 A498.1 0.000 0.103 0.250 0.242 0.355 A671.1 0.000 0.167 0.161 0.333 1307.2 0.000 0.294 0.355 140.1-12 0.000 0.290 RL16 0.000

129

(Appendix 3 continued)

Population 1352.2 RL18 RL20 1313.1 RL24 RL22 BYG2 1352.7 BYG3 A492.2 BYG6 Echi S 0.267 0.674 0.634 0.717 0.643 0.698 0.696 0.667 0.636 0.614 0.689 1307.3 0.675 0.242 0.219 0.235 0.129 0.324 0.152 0.161 0.152 0.229 0.235 Echi R 0.259 0.595 0.583 0.683 0.632 0.658 0.690 0.658 0.625 0.600 0.650 1264.1 0.676 0.138 0.233 0.303 0.138 0.290 0.273 0.290 0.219 0.242 0.250 A516 0.531 0.667 0.622 0.683 0.595 0.622 0.625 0.622 0.625 0.600 0.683 RL15 0.231 0.622 0.611 0.675 0.622 0.649 0.683 0.684 0.650 0.625 0.641 RL11 0.812 0.925 0.923 0.902 0.897 0.923 0.930 0.923 0.905 0.907 0.902 1264.2 0.562 0.583 0.529 0.641 0.543 0.571 0.541 0.571 0.579 0.514 0.605 1265.1 0.562 0.543 0.571 0.641 0.583 0.611 0.615 0.611 0.579 0.553 0.568 A533.1 0.548 0.571 0.559 0.667 0.611 0.559 0.641 0.639 0.641 0.579 0.632 RL17 0.167 0.744 0.737 0.692 0.711 0.769 0.732 0.703 0.700 0.738 0.725 L594 0.700 0.778 0.735 0.789 0.743 0.735 0.730 0.735 0.730 0.769 0.757 A491 0.711 0.312 0.233 0.250 0.258 0.290 0.371 0.344 0.324 0.242 0.250 967.1 0.684 0.226 0.258 0.371 0.167 0.312 0.242 0.258 0.242 0.212 0.219 RL8 0.259 0.700 0.692 0.714 0.632 0.725 0.659 0.692 0.625 0.667 0.683 182-12 0.667 0.219 0.194 0.361 0.219 0.353 0.286 0.250 0.235 0.257 0.361 1352.1 0.500 0.618 0.606 0.676 0.576 0.647 0.611 0.606 0.611 0.583 0.676 1352.3 0.545 0.528 0.556 0.659 0.568 0.556 0.526 0.556 0.564 0.538 0.590 RL2 0.714 0.333 0.310 0.323 0.214 0.310 0.344 0.367 0.344 0.312 0.267 RL19 0.259 0.667 0.692 0.683 0.632 0.725 0.690 0.725 0.659 0.667 0.683 RL4 0.629 0.233 0.207 0.226 0.107 0.323 0.303 0.267 0.133 0.219 0.226 BYG5 0.231 0.658 0.649 0.738 0.692 0.684 0.683 0.649 0.650 0.721 0.707 A533.3 0.690 0.771 0.765 0.784 0.771 0.765 0.789 0.765 0.789 0.795 0.816 RL21 0.690 0.333 0.314 0.368 0.333 0.265 0.200 0.314 0.342 0.270 0.368 QBG4 0.721 0.286 0.212 0.278 0.235 0.212 0.297 0.361 0.250 0.270 0.229 RL6 0.732 0.324 0.303 0.314 0.219 0.353 0.235 0.353 0.286 0.206 0.265 1352.4 0.618 0.267 0.179 0.312 0.207 0.241 0.226 0.179 0.167 0.303 0.312 L593 0.714 0.265 0.242 0.306 0.212 0.343 0.229 0.294 0.229 0.200 0.257 RL3 0.722 0.406 0.387 0.290 0.241 0.333 0.312 0.333 0.312 0.333 0.290 A533.2 0.684 0.103 0.200 0.273 0.167 0.200 0.188 0.312 0.242 0.212 0.161 1352.5 0.649 0.281 0.312 0.219 0.226 0.312 0.188 0.200 0.242 0.265 0.273 RL1 0.700 0.219 0.250 0.314 0.219 0.194 0.235 0.303 0.286 0.257 0.212 A475 0.707 0.294 0.219 0.286 0.343 0.324 0.306 0.273 0.351 0.278 0.333 967.2 0.667 0.273 0.250 0.265 0.219 0.250 0.182 0.194 0.235 0.257 0.212 RL9 0.676 0.200 0.172 0.353 0.258 0.233 0.273 0.233 0.219 0.294 0.250 1352.8 0.718 0.281 0.258 0.219 0.226 0.200 0.242 0.364 0.294 0.212 0.219 1301 0.639 0.312 0.233 0.303 0.138 0.290 0.273 0.233 0.219 0.242 0.303 RL10 0.647 0.179 0.148 0.290 0.179 0.276 0.312 0.276 0.258 0.281 0.290 BYG4 0.676 0.312 0.233 0.194 0.258 0.172 0.161 0.233 0.273 0.343 0.250 RL13 0.629 0.290 0.207 0.167 0.172 0.207 0.194 0.207 0.194 0.273 0.226 A508 0.629 0.172 0.207 0.333 0.107 0.207 0.194 0.267 0.303 0.161 0.281 A1076.1 0.675 0.343 0.219 0.286 0.188 0.324 0.257 0.273 0.206 0.229 0.286 1307.1 0.185 0.650 0.641 0.698 0.650 0.675 0.643 0.641 0.674 0.651 0.698 163-12 0.657 0.207 0.111 0.258 0.267 0.241 0.333 0.241 0.281 0.303 0.258 A818 0.692 0.400 0.333 0.343 0.303 0.333 0.265 0.226 0.265 0.378 0.343 RL14 0.676 0.312 0.172 0.400 0.312 0.290 0.324 0.290 0.273 0.294 0.353 A498.1 0.684 0.226 0.200 0.273 0.226 0.200 0.188 0.312 0.294 0.212 0.219 A671.1 0.676 0.200 0.107 0.303 0.200 0.172 0.219 0.233 0.273 0.242 0.250 1307.2 0.684 0.226 0.258 0.417 0.226 0.312 0.294 0.312 0.343 0.212 0.324 140.1-12 0.700 0.273 0.133 0.212 0.219 0.133 0.286 0.303 0.182 0.257 0.156 RL16 0.714 0.333 0.310 0.323 0.276 0.310 0.394 0.419 0.394 0.364 0.323 1352.2 0.000 0.676 0.667 0.692 0.639 0.703 0.667 0.629 0.667 0.675 0.725 RL18 0.000 0.172 0.353 0.200 0.290 0.273 0.290 0.273 0.188 0.250 RL20 0.000 0.281 0.233 0.207 0.303 0.207 0.194 0.273 0.226 1313.1 0.000 0.250 0.281 0.265 0.281 0.212 0.333 0.188 RL24 0.000 0.290 0.219 0.290 0.219 0.129 0.250 RL22 0.000 0.250 0.323 0.303 0.324 0.226 BYG2 0.000 0.194 0.235 0.257 0.265 1352.7 0.000 0.194 0.371 0.333 BYG3 0.000 0.306 0.156 A492.2 0.000 0.286 BYG6 0.000

130

Appendix 4: Distance matrix from AFLPs based on jaccard’s coefficient in comparison within populations collected in New South Wales, Australia (Chapter 3).

78- 185- 158- 78- 185- 78- 78- 158- 158- 185- Individual 12.1 12.1 12.1 12.18 12.21 12.5 12.21 12.25 12.6 12.10

78-12.1 0.000 0.451 0.347 0.773 0.625 0.522 0.700 0.685 0.611 0.510 185-12.1 0.000 0.325 0.758 0.613 0.520 0.718 0.718 0.526 0.354

158-12.1 0.000 0.763 0.596 0.511 0.681 0.681 0.517 0.454

78-12.18 0.000 0.815 0.827 0.772 0.785 0.778 0.791

185-12.21 0.000 0.609 0.695 0.708 0.670 0.642

78-12.5 0.000 0.722 0.745 0.583 0.561

78-12.21 0.000 0.702 0.796 0.724

158-12.25 0.000 0.687 0.679

158-12.6 0.000 0.556

185-12.10 0.000

(Appendix 4 continued)

185- 185- 185- 185- 185- 185- 185- 78- 158- 158- Individual 12.18 12.22 12.29 12.3 12.4 12.5 12.7 12.14 12.5 12.10

78-12.1 0.614 0.562 0.553 0.489 0.471 0.494 0.534 0.522 0.736 0.450 185-12.1 0.617 0.557 0.562 0.442 0.457 0.432 0.484 0.427 0.673 0.345 158-12.1 0.581 0.564 0.571 0.409 0.407 0.398 0.522 0.479 0.688 0.402 78-12.18 0.780 0.771 0.822 0.783 0.765 0.796 0.750 0.755 0.767 0.763 185-12.21 0.594 0.661 0.651 0.596 0.636 0.574 0.567 0.643 0.714 0.629 78-12.5 0.680 0.653 0.545 0.547 0.615 0.578 0.598 0.573 0.752 0.535 78-12.21 0.737 0.746 0.733 0.710 0.702 0.713 0.699 0.752 0.776 0.723 158-12.25 0.750 0.746 0.745 0.710 0.726 0.725 0.724 0.706 0.636 0.697 158-12.6 0.694 0.652 0.598 0.569 0.625 0.600 0.635 0.581 0.707 0.511 185-12.10 0.661 0.592 0.613 0.467 0.509 0.514 0.519 0.560 0.741 0.450 185-12.18 0.000 0.682 0.630 0.598 0.629 0.644 0.625 0.624 0.731 0.604 185-12.22 0.000 0.594 0.541 0.569 0.596 0.591 0.591 0.706 0.571

185-12.29 0.000 0.545 0.590 0.592 0.586 0.651 0.777 0.548

185-12.3 0.000 0.490 0.510 0.529 0.560 0.680 0.474

185-12.4 0.000 0.510 0.515 0.561 0.721 0.505

185-12.5 0.000 0.562 0.523 0.766 0.479

185-12.7 0.000 0.596 0.706 0.531

78-12.14 0.000 0.725 0.520

158-12.5 0.000 0.730

158-12.10 0.000

131

(Appendix 4 continued)

158- 158- 158- 158- 158- 158- 158- 158- 158- 158- Individual 12.11 12.12 12.13 12.14 12.15 12.16 12.17 12.18 12.19 12.20

78-12.1 0.471 0.535 0.546 0.438 0.529 0.570 0.556 0.566 0.576 0.524 185-12.1 0.409 0.447 0.514 0.462 0.600 0.516 0.535 0.604 0.583 0.505 158-12.1 0.444 0.480 0.520 0.410 0.517 0.506 0.511 0.584 0.532 0.476 78-12.18 0.794 0.784 0.809 0.802 0.790 0.760 0.800 0.827 0.767 0.755 185-12.21 0.681 0.669 0.624 0.606 0.645 0.612 0.611 0.637 0.640 0.590 78-12.5 0.519 0.544 0.615 0.569 0.648 0.629 0.490 0.654 0.593 0.608 78-12.21 0.745 0.750 0.730 0.725 0.750 0.720 0.676 0.722 0.705 0.740 158-12.25 0.734 0.750 0.708 0.725 0.723 0.667 0.726 0.722 0.717 0.630 158-12.6 0.540 0.577 0.637 0.577 0.673 0.568 0.625 0.667 0.560 0.559 185-12.10 0.509 0.496 0.542 0.528 0.667 0.547 0.562 0.649 0.627 0.579 185-12.18 0.667 0.630 0.667 0.624 0.624 0.615 0.615 0.614 0.646 0.652 185-12.22 0.528 0.551 0.620 0.615 0.675 0.670 0.619 0.682 0.623 0.613 185-12.29 0.588 0.632 0.655 0.612 0.626 0.646 0.561 0.632 0.621 0.581 185-12.3 0.547 0.581 0.579 0.525 0.610 0.531 0.562 0.614 0.566 0.580 185-12.4 0.505 0.545 0.568 0.526 0.584 0.561 0.535 0.602 0.607 0.567 185-12.5 0.565 0.585 0.595 0.545 0.613 0.578 0.566 0.618 0.583 0.541 185-12.7 0.585 0.591 0.577 0.608 0.594 0.586 0.515 0.553 0.642 0.592 78-12.14 0.490 0.543 0.553 0.553 0.645 0.600 0.574 0.651 0.591 0.578 158-12.5 0.752 0.746 0.748 0.745 0.755 0.688 0.745 0.780 0.736 0.681 158-12.10 0.441 0.490 0.529 0.511 0.573 0.548 0.536 0.621 0.584 0.522 158-12.11 0.000 0.434 0.527 0.510 0.610 0.588 0.562 0.654 0.606 0.566 158-12.12 0.000 0.500 0.523 0.661 0.632 0.630 0.643 0.610 0.613

158-12.13 0.000 0.519 0.637 0.643 0.555 0.679 0.596 0.529

158-12.14 0.000 0.620 0.568 0.598 0.653 0.574 0.574

158-12.15 0.000 0.612 0.612 0.653 0.654 0.589

158-12.16 0.000 0.631 0.617 0.536 0.549

158-12.17 0.000 0.616 0.539 0.582

158-12.18 0.000 0.634 0.624

158-12.19 0.000 0.511

158-12.20 0.000

132

(Appendix 4 continued)

158- 158- 158- 158- 158- 158- 158- 158- 158- 158- Individual 12.21 12.22 12.23 12.24 12.26 12.27 12.28 12.29 12.2 12.30

78-12.1 0.518 0.525 0.537 0.562 0.567 0.624 0.565 0.614 0.517 0.563 185-12.1 0.451 0.570 0.564 0.632 0.500 0.570 0.630 0.602 0.485 0.557 158-12.1 0.489 0.529 0.540 0.598 0.505 0.533 0.567 0.598 0.438 0.533 78-12.18 0.792 0.825 0.779 0.780 0.798 0.784 0.843 0.717 0.745 0.753 185-12.21 0.636 0.606 0.654 0.636 0.620 0.617 0.621 0.608 0.606 0.632 78-12.5 0.639 0.637 0.576 0.626 0.611 0.658 0.638 0.676 0.570 0.623 78-12.21 0.728 0.719 0.711 0.723 0.736 0.683 0.730 0.743 0.708 0.700 158-12.25 0.690 0.745 0.670 0.723 0.724 0.696 0.743 0.704 0.644 0.738 158-12.6 0.537 0.649 0.629 0.624 0.608 0.644 0.702 0.676 0.520 0.673 185-12.10 0.505 0.645 0.627 0.685 0.571 0.641 0.670 0.646 0.518 0.619 185-12.18 0.656 0.640 0.691 0.644 0.581 0.621 0.580 0.626 0.650 0.578 185-12.22 0.579 0.654 0.661 0.682 0.628 0.672 0.655 0.679 0.614 0.627 185-12.29 0.616 0.642 0.621 0.615 0.586 0.650 0.657 0.643 0.612 0.598 185-12.3 0.545 0.637 0.618 0.653 0.585 0.633 0.612 0.651 0.543 0.540 185-12.4 0.545 0.598 0.592 0.657 0.587 0.583 0.614 0.614 0.469 0.598 185-12.5 0.520 0.614 0.621 0.644 0.562 0.598 0.642 0.654 0.533 0.587 185-12.7 0.541 0.622 0.670 0.639 0.554 0.592 0.610 0.624 0.567 0.566 78-12.14 0.558 0.608 0.615 0.663 0.583 0.631 0.636 0.610 0.556 0.607 158-12.5 0.735 0.778 0.758 0.796 0.755 0.776 0.775 0.775 0.714 0.745 158-12.10 0.500 0.602 0.565 0.604 0.546 0.571 0.633 0.619 0.452 0.558 158-12.11 0.545 0.637 0.590 0.667 0.558 0.620 0.651 0.638 0.515 0.596 158-12.12 0.528 0.664 0.596 0.667 0.627 0.658 0.652 0.640 0.540 0.650 158-12.13 0.591 0.639 0.633 0.667 0.577 0.611 0.652 0.640 0.523 0.547 158-12.14 0.552 0.591 0.585 0.653 0.608 0.618 0.650 0.622 0.520 0.577 158-12.15 0.596 0.649 0.600 0.593 0.521 0.546 0.608 0.533 0.606 0.484 158-12.16 0.573 0.628 0.591 0.584 0.571 0.582 0.629 0.629 0.570 0.583 158-12.17 0.615 0.568 0.620 0.554 0.545 0.583 0.627 0.641 0.515 0.541 158-12.18 0.600 0.656 0.589 0.614 0.626 0.594 0.534 0.613 0.650 0.653 158-12.19 0.564 0.573 0.610 0.574 0.590 0.587 0.644 0.644 0.602 0.615 158-12.20 0.516 0.573 0.598 0.607 0.516 0.543 0.591 0.606 0.561 0.589 158-12.21 0.000 0.565 0.559 0.613 0.584 0.635 0.640 0.626 0.525 0.610 158-12.22 0.000 0.584 0.609 0.650 0.604 0.624 0.667 0.592 0.606

158-12.23 0.000 0.602 0.644 0.680 0.632 0.617 0.586 0.643

158-12.24 0.000 0.639 0.591 0.670 0.641 0.622 0.578

158-12.26 0.000 0.564 0.624 0.663 0.581 0.521

158-12.27 0.000 0.592 0.592 0.604 0.576

158-12.28 0.000 0.625 0.660 0.579

158-12.29 0.000 0.594 0.608

158-12.2 0.000 0.606

158-12.30 0.000

133

(Appendix 4 continued)

158- 158- 158- 158- 158- 185- 185- 185- 185- 185- Individual 12.3 12.4 12.7 12.8 12.9 12.11 12.12 12.13 12.14 12.15 78-12.1 0.526 0.511 0.716 0.425 0.477 0.584 0.529 0.554 0.630 0.494 185-12.1 0.434 0.417 0.720 0.480 0.447 0.495 0.495 0.490 0.558 0.432 158-12.1 0.419 0.452 0.684 0.418 0.395 0.558 0.483 0.495 0.565 0.467 78-12.18 0.741 0.745 0.820 0.757 0.767 0.781 0.819 0.794 0.829 0.796 185-12.21 0.667 0.635 0.621 0.647 0.534 0.595 0.617 0.646 0.656 0.649 78-12.5 0.550 0.602 0.676 0.564 0.495 0.549 0.510 0.637 0.518 0.551 78-12.21 0.705 0.743 0.704 0.697 0.680 0.724 0.745 0.745 0.746 0.748 158-12.25 0.739 0.697 0.717 0.685 0.705 0.777 0.757 0.745 0.776 0.689 158-12.6 0.609 0.544 0.676 0.585 0.602 0.632 0.590 0.636 0.647 0.600 185-12.10 0.538 0.526 0.746 0.526 0.486 0.550 0.568 0.536 0.533 0.443 185-12.18 0.638 0.654 0.711 0.627 0.589 0.623 0.606 0.626 0.664 0.670 185-12.22 0.617 0.558 0.724 0.545 0.573 0.580 0.637 0.541 0.672 0.609 185-12.29 0.562 0.630 0.709 0.549 0.489 0.613 0.552 0.602 0.617 0.578 185-12.3 0.523 0.509 0.676 0.451 0.495 0.536 0.539 0.574 0.603 0.524 185-12.4 0.509 0.480 0.692 0.524 0.539 0.562 0.596 0.575 0.581 0.495 185-12.5 0.527 0.514 0.737 0.514 0.515 0.540 0.571 0.551 0.640 0.500 185-12.7 0.573 0.505 0.689 0.533 0.535 0.545 0.578 0.598 0.565 0.534 78-12.14 0.561 0.509 0.719 0.550 0.565 0.585 0.618 0.533 0.613 0.523 158-12.5 0.746 0.692 0.711 0.704 0.736 0.752 0.752 0.752 0.782 0.743 158-12.10 0.510 0.495 0.699 0.495 0.462 0.524 0.478 0.490 0.584 0.495 158-12.11 0.481 0.436 0.712 0.550 0.495 0.523 0.525 0.547 0.530 0.480 158-12.12 0.546 0.496 0.740 0.547 0.495 0.545 0.562 0.518 0.516 0.522 158-12.13 0.592 0.518 0.720 0.569 0.532 0.613 0.598 0.591 0.573 0.532 158-12.14 0.557 0.515 0.663 0.544 0.515 0.607 0.546 0.596 0.636 0.515 158-12.15 0.515 0.611 0.689 0.624 0.531 0.595 0.604 0.636 0.647 0.639 158-12.16 0.575 0.563 0.683 0.577 0.594 0.574 0.610 0.602 0.653 0.606 158-12.17 0.550 0.551 0.654 0.551 0.539 0.612 0.583 0.589 0.569 0.552 158-12.18 0.613 0.615 0.642 0.588 0.620 0.636 0.650 0.654 0.675 0.631 158-12.19 0.593 0.556 0.604 0.542 0.571 0.615 0.639 0.655 0.675 0.634 158-12.20 0.581 0.463 0.663 0.540 0.526 0.593 0.558 0.635 0.647 0.598 158-12.21 0.587 0.490 0.680 0.534 0.535 0.611 0.608 0.573 0.627 0.563 158-12.22 0.610 0.556 0.638 0.556 0.527 0.670 0.646 0.637 0.672 0.557 158-12.23 0.590 0.564 0.632 0.564 0.596 0.627 0.667 0.631 0.667 0.608 158-12.24 0.625 0.627 0.656 0.600 0.604 0.661 0.635 0.653 0.675 0.695 158-12.26 0.586 0.519 0.713 0.561 0.535 0.609 0.592 0.611 0.625 0.602 158-12.27 0.569 0.596 0.698 0.596 0.573 0.629 0.629 0.620 0.656 0.636 158-12.28 0.624 0.639 0.625 0.639 0.561 0.596 0.620 0.638 0.638 0.642 158-12.29 0.598 0.600 0.611 0.676 0.576 0.634 0.620 0.638 0.672 0.615 158-12.2 0.532 0.490 0.685 0.533 0.475 0.619 0.590 0.622 0.623 0.533 158-12.30 0.583 0.544 0.676 0.598 0.500 0.542 0.576 0.623 0.600 0.600 158-12.3 0.000 0.540 0.661 0.553 0.486 0.526 0.542 0.600 0.557 0.514 158-12.4 0.000 0.664 0.500 0.528 0.552 0.557 0.550 0.570 0.500

158-12.7 0.000 0.664 0.718 0.692 0.710 0.735 0.726 0.703

158-12.8 0.000 0.500 0.576 0.646 0.550 0.669 0.514

158-12.9 0.000 0.472 0.515 0.524 0.509 0.470

185-12.11 0.000 0.555 0.536 0.508 0.553

185-12.12 0.000 0.594 0.549 0.598

185-12.13 0.000 0.603 0.578

185-12.14 0.000 0.547

185-12.15 0.000

134

(Appendix 4 continued)

185- 185- 185- 185- 185- 185- 185- 185- 185- 185- Individual 12.16 12.17 12.19 12.20 12.23 12.24 12.25 12.26 12.27 12.28

78-12.1 0.565 0.549 0.586 0.659 0.612 0.550 0.538 0.543 0.562 0.506 185-12.1 0.543 0.559 0.547 0.615 0.600 0.606 0.598 0.538 0.556 0.585 158-12.1 0.534 0.552 0.587 0.641 0.611 0.633 0.593 0.547 0.516 0.563 78-12.18 0.771 0.777 0.786 0.747 0.825 0.809 0.817 0.787 0.747 0.774 185-12.21 0.648 0.552 0.651 0.634 0.592 0.598 0.559 0.606 0.630 0.634 78-12.5 0.638 0.641 0.615 0.676 0.663 0.630 0.622 0.637 0.620 0.582 78-12.21 0.704 0.722 0.745 0.705 0.732 0.685 0.707 0.732 0.696 0.677 158-12.25 0.755 0.681 0.745 0.691 0.732 0.765 0.734 0.719 0.696 0.758 158-12.6 0.676 0.639 0.667 0.690 0.606 0.710 0.691 0.635 0.604 0.677 185-12.10 0.596 0.598 0.613 0.645 0.658 0.651 0.632 0.594 0.593 0.633 185-12.18 0.641 0.614 0.630 0.640 0.625 0.678 0.655 0.640 0.635 0.593 185-12.22 0.604 0.632 0.670 0.642 0.691 0.608 0.679 0.654 0.600 0.642 185-12.29 0.643 0.632 0.712 0.656 0.670 0.506 0.656 0.697 0.596 0.582 185-12.3 0.570 0.586 0.588 0.624 0.567 0.630 0.594 0.582 0.525 0.596 185-12.4 0.627 0.573 0.618 0.653 0.626 0.619 0.596 0.626 0.583 0.598 185-12.5 0.602 0.631 0.606 0.667 0.627 0.647 0.640 0.614 0.624 0.586 185-12.7 0.552 0.612 0.627 0.622 0.676 0.554 0.576 0.622 0.606 0.516 78-12.14 0.636 0.625 0.545 0.660 0.673 0.692 0.647 0.580 0.618 0.648 158-12.5 0.737 0.659 0.740 0.685 0.713 0.760 0.742 0.753 0.728 0.778 158-12.10 0.574 0.544 0.579 0.673 0.602 0.593 0.615 0.571 0.511 0.556 158-12.11 0.584 0.641 0.654 0.663 0.689 0.657 0.622 0.663 0.567 0.596 158-12.12 0.640 0.667 0.678 0.675 0.627 0.681 0.676 0.652 0.600 0.640 158-12.13 0.640 0.617 0.643 0.676 0.711 0.670 0.612 0.613 0.598 0.639 158-12.14 0.636 0.596 0.626 0.635 0.621 0.628 0.604 0.560 0.604 0.591 158-12.15 0.650 0.611 0.692 0.673 0.635 0.656 0.634 0.621 0.631 0.576 158-12.16 0.600 0.602 0.619 0.656 0.628 0.634 0.596 0.598 0.582 0.628 158-12.17 0.614 0.616 0.590 0.667 0.705 0.604 0.625 0.640 0.583 0.568 158-12.18 0.656 0.630 0.646 0.656 0.684 0.633 0.640 0.711 0.689 0.626 158-12.19 0.631 0.634 0.621 0.630 0.670 0.622 0.696 0.657 0.573 0.657 158-12.20 0.606 0.529 0.667 0.634 0.634 0.626 0.618 0.604 0.527 0.620 158-12.21 0.583 0.585 0.630 0.693 0.625 0.660 0.609 0.596 0.536 0.639 158-12.22 0.653 0.547 0.684 0.708 0.652 0.581 0.605 0.622 0.604 0.637 158-12.23 0.700 0.573 0.677 0.701 0.630 0.652 0.702 0.615 0.583 0.674 158-12.24 0.670 0.581 0.660 0.656 0.640 0.648 0.624 0.625 0.621 0.560 158-12.26 0.610 0.583 0.667 0.636 0.676 0.670 0.621 0.608 0.619 0.579 158-12.27 0.634 0.650 0.663 0.660 0.660 0.667 0.646 0.686 0.667 0.604 158-12.28 0.653 0.598 0.643 0.653 0.653 0.645 0.622 0.694 0.647 0.638

135

(Appendix 4 continued)

185- 185- 185- 185- 185- 185- 185- 185- 185- 185- Individual 12.16 12.17 12.19 12.20 12.23 12.24 12.25 12.26 12.27 12.28

158-12.29 0.653 0.642 0.643 0.667 0.707 0.645 0.695 0.667 0.647 0.638 158-12.2 0.594 0.596 0.612 0.686 0.634 0.653 0.619 0.562 0.604 0.592 158-12.30 0.548 0.549 0.626 0.621 0.635 0.642 0.573 0.606 0.576 0.576 158-12.3 0.636 0.600 0.675 0.636 0.673 0.642 0.673 0.673 0.619 0.623 158-12.4 0.600 0.574 0.655 0.625 0.638 0.644 0.637 0.625 0.557 0.598 158-12.7 0.706 0.598 0.721 0.720 0.707 0.701 0.695 0.707 0.686 0.707 158-12.8 0.573 0.588 0.642 0.625 0.651 0.631 0.624 0.598 0.543 0.584 158-12.9 0.531 0.606 0.648 0.573 0.644 0.594 0.600 0.630 0.559 0.543 185-12.11 0.583 0.636 0.649 0.620 0.670 0.639 0.632 0.645 0.605 0.553 185-12.12 0.620 0.622 0.650 0.699 0.633 0.581 0.587 0.604 0.602 0.511 185-12.13 0.625 0.654 0.629 0.676 0.689 0.683 0.663 0.689 0.607 0.624 185-12.14 0.602 0.664 0.686 0.672 0.695 0.655 0.673 0.684 0.633 0.587 185-12.15 0.629 0.618 0.592 0.667 0.667 0.620 0.640 0.667 0.624 0.627 185-12.16 0.000 0.628 0.657 0.667 0.694 0.630 0.607 0.593 0.606 0.578 185-12.17 0.000 0.646 0.698 0.596 0.618 0.593 0.580 0.533 0.641

185-12.19 0.000 0.697 0.670 0.717 0.656 0.613 0.637 0.697

185-12.20 0.000 0.695 0.674 0.696 0.681 0.673 0.695

185-12.23 0.000 0.688 0.696 0.607 0.604 0.681

185-12.24 0.000 0.659 0.659 0.639 0.598

185-12.25 0.000 0.571 0.632 0.571

185-12.26 0.000 0.604 0.622

185-12.27 0.000 0.633

185-12.28 0.000

136

(Appendix 4 continued)

185- 185- 185- 185- 185- 78- 78- 78- 78- 78- Individual 12.2 12.30 12.6 12.8 12.9 12.10 12.11 12.12 12.13 12.15

78-12.1 0.600 0.592 0.581 0.567 0.489 0.451 0.516 0.500 0.571 0.488 185-12.1 0.467 0.570 0.559 0.505 0.409 0.457 0.485 0.416 0.474 0.440 158-12.1 0.489 0.564 0.552 0.525 0.444 0.405 0.441 0.435 0.478 0.405 78-12.18 0.755 0.804 0.781 0.805 0.760 0.770 0.759 0.755 0.765 0.817 185-12.21 0.610 0.602 0.606 0.617 0.634 0.587 0.614 0.623 0.544 0.600 78-12.5 0.600 0.617 0.583 0.571 0.600 0.563 0.528 0.587 0.505 0.577 78-12.21 0.728 0.700 0.720 0.726 0.698 0.755 0.676 0.703 0.650 0.755 158-12.25 0.740 0.700 0.766 0.780 0.734 0.693 0.767 0.728 0.714 0.706 158-12.6 0.567 0.652 0.694 0.655 0.623 0.542 0.627 0.596 0.584 0.557 185-12.10 0.519 0.580 0.630 0.547 0.495 0.509 0.518 0.519 0.562 0.550 185-12.18 0.628 0.631 0.622 0.608 0.626 0.571 0.590 0.613 0.615 0.571 185-12.22 0.579 0.656 0.672 0.565 0.580 0.515 0.610 0.618 0.582 0.570 185-12.29 0.616 0.607 0.584 0.515 0.602 0.562 0.607 0.602 0.546 0.592 185-12.3 0.485 0.568 0.596 0.532 0.547 0.505 0.528 0.500 0.534 0.442 185-12.4 0.515 0.569 0.544 0.546 0.534 0.490 0.542 0.545 0.549 0.550 185-12.5 0.549 0.571 0.547 0.550 0.538 0.495 0.559 0.577 0.566 0.510 185-12.7 0.556 0.578 0.539 0.514 0.571 0.560 0.510 0.510 0.500 0.574 78-12.14 0.515 0.650 0.619 0.558 0.546 0.475 0.554 0.544 0.574 0.490 158-12.5 0.735 0.730 0.784 0.754 0.729 0.713 0.752 0.723 0.670 0.725 158-12.10 0.500 0.598 0.560 0.575 0.505 0.420 0.544 0.500 0.536 0.473 158-12.11 0.545 0.605 0.596 0.559 0.547 0.442 0.541 0.515 0.548 0.505 158-12.12 0.605 0.610 0.669 0.579 0.557 0.519 0.538 0.568 0.583 0.545 158-12.13 0.565 0.631 0.636 0.588 0.603 0.500 0.548 0.538 0.568 0.582 158-12.14 0.567 0.602 0.632 0.593 0.525 0.526 0.548 0.537 0.598 0.542 158-12.15 0.596 0.589 0.606 0.606 0.648 0.542 0.562 0.582 0.584 0.557 158-12.16 0.573 0.594 0.625 0.673 0.629 0.562 0.581 0.602 0.604 0.592 158-12.17 0.515 0.582 0.558 0.546 0.589 0.520 0.514 0.560 0.505 0.550 158-12.18 0.657 0.657 0.624 0.648 0.654 0.619 0.657 0.615 0.588 0.619 158-12.19 0.578 0.611 0.664 0.626 0.631 0.596 0.598 0.578 0.553 0.596 158-12.20 0.533 0.600 0.590 0.577 0.580 0.538 0.559 0.548 0.521 0.553 158-12.21 0.557 0.593 0.636 0.609 0.545 0.561 0.566 0.557 0.574 0.531 158-12.22 0.565 0.642 0.577 0.592 0.582 0.600 0.629 0.625 0.583 0.570 158-12.23 0.633 0.623 0.641 0.676 0.576 0.594 0.648 0.673 0.577 0.579 158-12.24 0.613 0.682 0.636 0.648 0.640 0.617 0.657 0.642 0.629 0.632 158-12.26 0.612 0.591 0.594 0.582 0.624 0.531 0.524 0.510 0.515 0.545 158-12.27 0.551 0.661 0.604 0.616 0.607 0.584 0.600 0.536 0.510 0.584 158-12.28 0.653 0.655 0.608 0.633 0.638 0.616 0.604 0.626 0.557 0.630 158-12.29 0.583 0.617 0.594 0.607 0.598 0.543 0.617 0.612 0.586 0.616

137

(Appendix 4 continued)

185- 185- 185- 185- 185- 78- 78- 78- 78- 78- Individual 12.2 12.30 12.6 12.8 12.9 12.10 12.11 12.12 12.13 12.15

158-12.2 0.540 0.626 0.606 0.617 0.570 0.485 0.550 0.540 0.571 0.559 158-12.30 0.537 0.627 0.564 0.579 0.610 0.526 0.490 0.537 0.556 0.571 158-12.3 0.533 0.581 0.584 0.522 0.509 0.495 0.491 0.519 0.537 0.524 158-12.4 0.505 0.558 0.573 0.561 0.550 0.449 0.518 0.520 0.524 0.495 158-12.7 0.717 0.667 0.709 0.716 0.712 0.695 0.702 0.717 0.627 0.708 158-12.8 0.575 0.607 0.586 0.561 0.550 0.510 0.545 0.520 0.565 0.465 158-12.9 0.505 0.573 0.534 0.495 0.538 0.479 0.476 0.457 0.464 0.510 185-12.11 0.560 0.530 0.607 0.522 0.586 0.550 0.543 0.476 0.495 0.602 185-12.12 0.580 0.533 0.590 0.591 0.553 0.541 0.547 0.566 0.525 0.598 185-12.13 0.587 0.568 0.634 0.609 0.519 0.505 0.629 0.515 0.615 0.535 185-12.14 0.591 0.574 0.612 0.577 0.669 0.595 0.538 0.579 0.569 0.642 185-12.15 0.563 0.596 0.587 0.536 0.524 0.525 0.559 0.549 0.593 0.539 185-12.16 0.598 0.630 0.580 0.594 0.638 0.602 0.577 0.489 0.586 0.616 185-12.17 0.570 0.670 0.610 0.596 0.600 0.589 0.578 0.615 0.602 0.604 185-12.19 0.630 0.658 0.612 0.624 0.615 0.647 0.645 0.644 0.618 0.620 185-12.20 0.667 0.679 0.660 0.619 0.689 0.629 0.654 0.680 0.626 0.670 185-12.23 0.639 0.679 0.673 0.670 0.663 0.629 0.654 0.706 0.640 0.629 185-12.24 0.602 0.648 0.598 0.598 0.630 0.621 0.635 0.632 0.604 0.663 185-12.25 0.667 0.654 0.646 0.657 0.650 0.642 0.600 0.562 0.533 0.613 185-12.26 0.611 0.654 0.686 0.657 0.596 0.615 0.588 0.625 0.583 0.570 185-12.27 0.580 0.625 0.617 0.604 0.581 0.541 0.547 0.621 0.569 0.556 185-12.28 0.639 0.602 0.562 0.606 0.663 0.570 0.602 0.581 0.583 0.585 185-12.2 0.000 0.631 0.583 0.515 0.545 0.500 0.538 0.511 0.560 0.531 185-12.30 0.000 0.626 0.613 0.629 0.557 0.586 0.579 0.542 0.583

185-12.6 0.000 0.555 0.596 0.559 0.537 0.610 0.571 0.587

185-12.8 0.000 0.559 0.561 0.527 0.557 0.505 0.547

185-12.9 0.000 0.505 0.555 0.587 0.562 0.549

78-12.10 0.000 0.529 0.531 0.535 0.422

78-12.11 0.000 0.495 0.500 0.515

78-12.12 0.000 0.452 0.484

78-12.13 0.000 0.490

78-12.15 0.000

138

(Appendix 4 continued)

78- 78- 78- 78- 78- 78- 78- 78- 78- 78- Individual 12.16 12.17 12.19 12.20 12.22 12.23 12.24 12.25 12.26 12.27

78-12.1 0.571 0.573 0.488 0.506 0.536 0.556 0.553 0.539 0.506 0.613 185-12.1 0.641 0.667 0.582 0.538 0.562 0.581 0.562 0.592 0.505 0.615 158-12.1 0.607 0.591 0.544 0.458 0.523 0.541 0.506 0.588 0.477 0.583 78-12.18 0.809 0.835 0.788 0.781 0.773 0.798 0.798 0.800 0.758 0.775 185-12.21 0.617 0.657 0.642 0.657 0.625 0.630 0.570 0.611 0.573 0.620 78-12.5 0.635 0.673 0.606 0.697 0.654 0.686 0.629 0.675 0.604 0.707 78-12.21 0.663 0.755 0.697 0.752 0.745 0.644 0.653 0.702 0.693 0.724 158-12.25 0.722 0.742 0.723 0.714 0.707 0.729 0.733 0.726 0.706 0.724 158-12.6 0.648 0.713 0.657 0.604 0.667 0.673 0.640 0.651 0.586 0.673 185-12.10 0.670 0.713 0.616 0.593 0.587 0.655 0.613 0.647 0.537 0.655 185-12.18 0.605 0.737 0.620 0.622 0.615 0.605 0.600 0.683 0.646 0.653 185-12.22 0.692 0.735 0.649 0.573 0.594 0.676 0.645 0.689 0.609 0.640 185-12.29 0.609 0.720 0.622 0.625 0.646 0.680 0.619 0.670 0.660 0.716 185-12.3 0.635 0.660 0.592 0.551 0.615 0.592 0.574 0.615 0.563 0.585 185-12.4 0.638 0.636 0.551 0.505 0.561 0.622 0.618 0.590 0.505 0.559 185-12.5 0.667 0.689 0.623 0.598 0.606 0.567 0.578 0.631 0.553 0.615 185-12.7 0.620 0.673 0.546 0.592 0.614 0.604 0.614 0.651 0.560 0.648 78-12.14 0.646 0.706 0.590 0.592 0.573 0.618 0.613 0.637 0.602 0.634 158-12.5 0.785 0.776 0.755 0.695 0.727 0.763 0.765 0.769 0.713 0.755 158-12.10 0.629 0.613 0.568 0.506 0.579 0.598 0.579 0.608 0.521 0.590 158-12.11 0.663 0.647 0.592 0.566 0.588 0.647 0.629 0.575 0.549 0.661 158-12.12 0.676 0.684 0.611 0.574 0.632 0.707 0.643 0.675 0.609 0.683 158-12.13 0.650 0.636 0.609 0.611 0.606 0.648 0.643 0.605 0.569 0.661 158-12.14 0.633 0.632 0.511 0.574 0.583 0.617 0.505 0.584 0.557 0.608 158-12.15 0.648 0.687 0.588 0.574 0.583 0.632 0.598 0.598 0.571 0.608 158-12.16 0.593 0.624 0.636 0.565 0.589 0.562 0.604 0.561 0.577 0.600 158-12.17 0.609 0.663 0.566 0.596 0.561 0.622 0.546 0.655 0.550 0.651 158-12.18 0.624 0.681 0.635 0.609 0.632 0.622 0.632 0.683 0.619 0.653 158-12.19 0.628 0.692 0.625 0.586 0.566 0.612 0.648 0.670 0.623 0.655 158-12.20 0.616 0.645 0.570 0.571 0.565 0.568 0.611 0.582 0.553 0.660 158-12.21 0.591 0.677 0.592 0.548 0.588 0.591 0.573 0.629 0.546 0.612 158-12.22 0.619 0.633 0.602 0.589 0.613 0.602 0.567 0.568 0.600 0.636 158-12.23 0.628 0.641 0.611 0.567 0.606 0.656 0.606 0.647 0.636 0.616 158-12.24 0.588 0.696 0.649 0.607 0.630 0.652 0.600 0.643 0.660 0.653 158-12.26 0.649 0.660 0.644 0.606 0.600 0.589 0.600 0.573 0.588 0.673 158-12.27 0.674 0.709 0.627 0.602 0.582 0.585 0.537 0.648 0.625 0.619 158-12.28 0.605 0.663 0.619 0.649 0.629 0.604 0.643 0.654 0.616 0.610 158-12.29 0.636 0.743 0.574 0.635 0.643 0.663 0.643 0.654 0.657 0.610

139

(Appendix 4 continued)

78- 78- 78- 78- 78- 78- 78- 78- 78- 78- Individual 12.16 12.17 12.19 12.20 12.22 12.23 12.24 12.25 12.26 12.27

158-12.2 0.673 0.630 0.588 0.561 0.584 0.630 0.584 0.585 0.545 0.607 158-12.30 0.586 0.673 0.573 0.574 0.583 0.602 0.553 0.598 0.600 0.648 158-12.3 0.647 0.682 0.579 0.539 0.589 0.645 0.602 0.638 0.565 0.647 158-12.4 0.636 0.660 0.581 0.525 0.590 0.608 0.577 0.551 0.538 0.625 158-12.7 0.652 0.730 0.646 0.716 0.709 0.717 0.670 0.704 0.683 0.650 158-12.8 0.650 0.673 0.607 0.569 0.590 0.594 0.590 0.616 0.593 0.625 158-12.9 0.628 0.653 0.584 0.557 0.566 0.612 0.536 0.594 0.569 0.630 185-12.11 0.682 0.702 0.616 0.618 0.600 0.679 0.613 0.658 0.589 0.667 185-12.12 0.615 0.696 0.600 0.588 0.596 0.629 0.610 0.610 0.612 0.682 185-12.13 0.649 0.722 0.657 0.580 0.615 0.660 0.602 0.652 0.590 0.624 185-12.14 0.685 0.681 0.644 0.669 0.641 0.736 0.664 0.693 0.630 0.680 185-12.15 0.667 0.676 0.610 0.570 0.645 0.663 0.632 0.618 0.553 0.664 185-12.16 0.667 0.704 0.589 0.649 0.600 0.634 0.600 0.667 0.602 0.637 185-12.17 0.624 0.637 0.576 0.624 0.646 0.607 0.617 0.588 0.574 0.640 185-12.19 0.670 0.745 0.676 0.667 0.633 0.667 0.673 0.730 0.660 0.667 185-12.20 0.725 0.745 0.673 0.649 0.642 0.691 0.642 0.729 0.670 0.676 185-12.23 0.635 0.648 0.660 0.573 0.670 0.618 0.598 0.640 0.629 0.622 185-12.24 0.610 0.685 0.609 0.626 0.649 0.670 0.663 0.604 0.621 0.683 185-12.25 0.617 0.678 0.630 0.663 0.626 0.648 0.611 0.581 0.567 0.663 185-12.26 0.619 0.663 0.571 0.620 0.582 0.602 0.628 0.626 0.600 0.594 185-12.27 0.584 0.643 0.600 0.588 0.582 0.600 0.650 0.636 0.570 0.645 185-12.28 0.619 0.677 0.617 0.649 0.642 0.602 0.613 0.640 0.629 0.650 185-12.2 0.637 0.677 0.562 0.594 0.511 0.591 0.573 0.602 0.576 0.651 185-12.30 0.626 0.735 0.585 0.639 0.620 0.676 0.620 0.619 0.634 0.664 185-12.6 0.632 0.670 0.602 0.644 0.676 0.644 0.598 0.649 0.613 0.645 185-12.8 0.683 0.703 0.627 0.617 0.611 0.667 0.598 0.669 0.625 0.711 185-12.9 0.635 0.647 0.592 0.580 0.602 0.620 0.574 0.627 0.604 0.661 78-12.10 0.626 0.611 0.552 0.522 0.547 0.611 0.532 0.550 0.521 0.588 78-12.11 0.612 0.688 0.544 0.613 0.607 0.598 0.594 0.632 0.570 0.664 78-12.12 0.622 0.690 0.577 0.608 0.602 0.621 0.558 0.602 0.561 0.638 78-12.13 0.638 0.676 0.536 0.610 0.531 0.594 0.576 0.642 0.550 0.639 78-12.15 0.641 0.667 0.610 0.568 0.592 0.549 0.562 0.619 0.580 0.602 78-12.16 0.000 0.631 0.565 0.600 0.625 0.647 0.625 0.609 0.580 0.634 78-12.17 0.000 0.684 0.615 0.680 0.674 0.667 0.622 0.596 0.673

78-12.19 0.000 0.629 0.579 0.567 0.548 0.621 0.596 0.631

78-12.20 0.000 0.517 0.615 0.596 0.637 0.553 0.606

78-12.22 0.000 0.578 0.589 0.670 0.562 0.627

78-12.23 0.000 0.578 0.608 0.596 0.604

78-12.24 0.000 0.590 0.562 0.641

78-12.25 0.000 0.520 0.626

78-12.26 0.000 0.574

78-12.27 0.000

140

(Appendix 4 continued)

78- 78- 78- 78- 78- 78- 78- 78- 78- 78- Individual 12.29 12.2 12.30 12.3 12.4 12.6 12.7 12.8 12.9 12.28

78-12.1 0.534 0.429 0.630 0.516 0.536 0.535 0.585 0.489 0.511 0.500 185-12.1 0.515 0.436 0.604 0.500 0.446 0.398 0.505 0.474 0.366 0.548 158-12.1 0.522 0.402 0.643 0.473 0.495 0.471 0.542 0.478 0.418 0.506 78-12.18 0.750 0.781 0.849 0.798 0.789 0.804 0.760 0.817 0.802 0.779 185-12.21 0.633 0.667 0.648 0.616 0.661 0.636 0.658 0.609 0.611 0.600 78-12.5 0.544 0.515 0.676 0.542 0.518 0.530 0.561 0.444 0.537 0.618 78-12.21 0.673 0.731 0.752 0.716 0.744 0.677 0.722 0.710 0.732 0.698 158-12.25 0.699 0.720 0.752 0.704 0.744 0.716 0.722 0.734 0.697 0.684 158-12.6 0.621 0.550 0.676 0.617 0.640 0.567 0.583 0.623 0.571 0.683 185-12.10 0.532 0.477 0.669 0.531 0.496 0.461 0.561 0.481 0.444 0.575 185-12.18 0.667 0.650 0.628 0.634 0.657 0.628 0.653 0.667 0.654 0.633 185-12.22 0.604 0.577 0.712 0.600 0.612 0.618 0.629 0.617 0.607 0.661 185-12.29 0.557 0.526 0.683 0.596 0.570 0.602 0.574 0.545 0.590 0.621 185-12.3 0.585 0.515 0.664 0.582 0.545 0.573 0.561 0.547 0.466 0.618 185-12.4 0.587 0.515 0.679 0.500 0.559 0.588 0.575 0.534 0.510 0.532 185-12.5 0.575 0.519 0.667 0.560 0.549 0.520 0.591 0.495 0.514 0.608 185-12.7 0.540 0.594 0.676 0.618 0.568 0.556 0.571 0.571 0.574 0.527 78-12.14 0.596 0.569 0.611 0.568 0.581 0.529 0.598 0.598 0.536 0.629 158-12.5 0.789 0.714 0.806 0.745 0.739 0.771 0.717 0.786 0.716 0.770 158-12.10 0.484 0.500 0.660 0.559 0.547 0.467 0.550 0.520 0.480 0.565 158-12.11 0.571 0.500 0.651 0.514 0.505 0.500 0.587 0.519 0.495 0.604 158-12.12 0.603 0.565 0.686 0.576 0.465 0.514 0.581 0.569 0.496 0.646 158-12.13 0.602 0.588 0.664 0.586 0.563 0.551 0.603 0.579 0.491 0.620 158-12.14 0.551 0.520 0.637 0.563 0.551 0.521 0.596 0.554 0.485 0.585 158-12.15 0.594 0.606 0.624 0.655 0.640 0.637 0.648 0.583 0.636 0.554 158-12.16 0.654 0.584 0.630 0.623 0.622 0.573 0.615 0.602 0.549 0.591 158-12.17 0.530 0.515 0.602 0.570 0.559 0.515 0.548 0.505 0.524 0.547 158-12.18 0.598 0.637 0.683 0.648 0.594 0.585 0.600 0.586 0.654 0.604 158-12.19 0.617 0.548 0.657 0.613 0.600 0.564 0.579 0.606 0.569 0.637 158-12.20 0.577 0.516 0.650 0.588 0.589 0.564 0.551 0.566 0.554 0.582 158-12.21 0.584 0.540 0.654 0.539 0.607 0.495 0.559 0.573 0.534 0.619 158-12.22 0.594 0.532 0.639 0.531 0.642 0.596 0.624 0.637 0.584 0.552 158-12.23 0.602 0.571 0.673 0.612 0.585 0.574 0.576 0.576 0.619 0.593 158-12.24 0.625 0.579 0.613 0.620 0.670 0.628 0.640 0.626 0.654 0.618 158-12.26 0.596 0.539 0.612 0.606 0.580 0.570 0.585 0.571 0.561 0.602 158-12.27 0.564 0.617 0.648 0.640 0.638 0.608 0.633 0.607 0.583 0.538 158-12.28 0.582 0.660 0.640 0.619 0.643 0.626 0.664 0.612 0.664 0.587

141

(Appendix 4 continued)

78- 78- 78- 78- 78- 78- 78- 78- 78- 78- Individual 12.29 12.2 12.30 12.3 12.4 12.6 12.7 12.8 12.9 12.28

158-12.29 0.537 0.648 0.653 0.632 0.631 0.612 0.651 0.612 0.639 0.587 158-12.2 0.510 0.552 0.648 0.524 0.603 0.540 0.570 0.557 0.505 0.600 158-12.30 0.521 0.619 0.610 0.590 0.604 0.582 0.610 0.569 0.558 0.489 158-12.3 0.519 0.476 0.672 0.558 0.482 0.519 0.495 0.523 0.514 0.549 158-12.4 0.519 0.490 0.627 0.559 0.495 0.505 0.550 0.564 0.486 0.564 158-12.7 0.689 0.697 0.705 0.694 0.701 0.680 0.625 0.712 0.722 0.713 158-12.8 0.561 0.519 0.687 0.571 0.522 0.548 0.481 0.577 0.500 0.606 158-12.9 0.490 0.490 0.632 0.475 0.509 0.441 0.538 0.433 0.485 0.505 185-12.11 0.584 0.607 0.658 0.593 0.582 0.546 0.586 0.561 0.576 0.589 185-12.12 0.564 0.549 0.635 0.575 0.589 0.551 0.645 0.553 0.543 0.626 185-12.13 0.624 0.596 0.639 0.569 0.619 0.573 0.613 0.613 0.550 0.644 185-12.14 0.578 0.539 0.661 0.563 0.553 0.591 0.626 0.543 0.534 0.582 185-12.15 0.562 0.547 0.679 0.519 0.509 0.520 0.538 0.495 0.486 0.536 185-12.16 0.610 0.635 0.640 0.606 0.643 0.612 0.612 0.612 0.613 0.587 185-12.17 0.568 0.582 0.670 0.521 0.645 0.585 0.600 0.627 0.629 0.557 185-12.19 0.667 0.664 0.683 0.636 0.692 0.644 0.654 0.642 0.642 0.663 185-12.20 0.663 0.634 0.680 0.682 0.642 0.706 0.637 0.650 0.664 0.660 185-12.23 0.689 0.647 0.667 0.631 0.690 0.667 0.663 0.689 0.651 0.688 185-12.24 0.585 0.626 0.700 0.610 0.636 0.632 0.657 0.602 0.631 0.591 185-12.25 0.621 0.646 0.680 0.657 0.691 0.653 0.676 0.608 0.637 0.614 185-12.26 0.622 0.634 0.625 0.604 0.702 0.625 0.676 0.650 0.570 0.645 185-12.27 0.564 0.563 0.697 0.602 0.661 0.566 0.594 0.607 0.609 0.640 185-12.28 0.594 0.577 0.611 0.604 0.630 0.611 0.650 0.610 0.625 0.600 185-12.2 0.556 0.554 0.614 0.567 0.582 0.511 0.573 0.573 0.520 0.589 185-12.30 0.628 0.602 0.655 0.600 0.588 0.593 0.580 0.568 0.518 0.610 185-12.6 0.539 0.593 0.685 0.578 0.591 0.569 0.609 0.543 0.586 0.571 185-12.8 0.556 0.568 0.670 0.566 0.504 0.583 0.571 0.545 0.586 0.573 185-12.9 0.571 0.570 0.688 0.542 0.595 0.545 0.600 0.533 0.537 0.618 78-12.10 0.531 0.500 0.631 0.544 0.546 0.546 0.535 0.520 0.480 0.564 78-12.11 0.495 0.523 0.643 0.550 0.513 0.524 0.514 0.514 0.477 0.540 78-12.12 0.541 0.525 0.614 0.581 0.556 0.444 0.545 0.559 0.520 0.543 78-12.13 0.485 0.515 0.642 0.557 0.545 0.515 0.575 0.490 0.524 0.516 78-12.15 0.545 0.515 0.618 0.529 0.573 0.531 0.563 0.563 0.495 0.548 78-12.16 0.620 0.660 0.652 0.615 0.704 0.575 0.621 0.635 0.636 0.628 78-12.17 0.686 0.657 0.716 0.692 0.722 0.703 0.722 0.673 0.685 0.656 78-12.19 0.516 0.588 0.634 0.573 0.613 0.562 0.592 0.578 0.594 0.517 78-12.20 0.660 0.531 0.636 0.615 0.589 0.622 0.621 0.608 0.569 0.613

142

(Appendix 4 continued)

78- 78- 78- 78- 78- 78- 78- 78- 78- 78- Individual 12.29 12.2 12.30 12.3 12.4 12.6 12.7 12.8 12.9 12.28

78-12.22 0.614 0.570 0.602 0.610 0.634 0.616 0.642 0.602 0.590 0.591 78-12.23 0.633 0.588 0.635 0.614 0.664 0.591 0.673 0.660 0.608 0.596 78-12.24 0.586 0.526 0.588 0.596 0.609 0.573 0.574 0.602 0.590 0.576 78-12.25 0.626 0.636 0.667 0.583 0.699 0.629 0.675 0.615 0.640 0.606 78-12.26 0.574 0.573 0.670 0.571 0.635 0.604 0.590 0.577 0.552 0.579 78-12.27 0.623 0.658 0.664 0.643 0.675 0.651 0.684 0.684 0.649 0.644 78-12.29 0.000 0.553 0.676 0.538 0.593 0.526 0.571 0.485 0.547 0.461 78-12.2 0.000 0.636 0.480 0.514 0.495 0.543 0.515 0.476 0.557

78-12.30 0.000 0.620 0.678 0.654 0.676 0.676 0.652 0.660

78-12.3 0.000 0.590 0.539 0.595 0.528 0.519 0.526

78-12.4 0.000 0.471 0.491 0.505 0.425 0.585

78-12.6 0.000 0.559 0.453 0.475 0.574

78-12.7 0.000 0.547 0.537 0.590

78-12.8 0.000 0.509 0.561

78-12.9 0.000 0.578

78-12.28 0.000

143

Appendix 5: Number and name indexes of E. colona populations in Chapter 3 and

Appendices 3 and 4.

Population number Population name Population number Population name 1 BYG2 34 RL13 2 BYG3 35 RL14 3 BYG4 36 RL2 4 BYG5 37 RL3 5 BYG6 38 RL4 6 Echi R 39 RL6 7 1301 40 RL8 8 182-12 41 Echi S 9 RL10 42 RL16 10 RL15 43 140.1-12 11 RL19 44 1264.1 12 RL21 45 L594 13 RL22 46 967.1 14 A498.1 47 967.2 15 RL17 48 1264.2 16 1313.1 49 1307.1 17 A475 50 1307.2 18 1265.1 51 1307.3 19 1352.2 52 A491 20 1352.7 53 A516 21 163-12 54 A671.1 22 A1076.1 55 L593 23 A533.1 56 1352.3 24 A533.2 57 1352.4 25 A533.3 58 1352.5 26 A818 59 QBG4 27 RL18 60 1352.8 28 RL20 61 A492.2 29 RL24 62 A508 30 RL9 63 185-12 31 1352.1 64 78-12 32 RL1 65 158-12 33 RL11

144

Appendix 6: Dendrogram of the partial sequence of the predicted amino acid at codon 106 in the EPSPS gene of the susceptible population (Echi S - top) and the resistant population

(A533.1 - bottom) showing the mutation (substitution of T for C leading to substitution of serine for proline) in the resistant population A533.1 (Chapter 4).

145

Appendix 7: The sections of the treated leaf, the non-treated leaves, the stem and the roots of

E. colona plants were cut at harvest time points of 12, 24, 48 and 72 hours after glyphosate application (Chapter 4).

146

Appendix 8: Response of E. colona populations to glyphosate (240 g a.i. ha-1) at two different temperature levels (20oC on the left and 30oC on the right) at three weeks after glyphosate application. The order of photos from the left: Echi S (susceptible), 1307.3

(standard resistant) and A533.1 (most resistant) (Chapter 4).

Experiment 1

Experiment 2

147

Appendix 9: The pair of resistant (A533.1) and susceptible (Echi S) E. colona individuals at flowering (left), and two single spikes of each resistant and susceptible individual were bagged with glassine bags as controls before anthesis (right) in gene flow experiments. Letters inside the photos: S: susceptible plant, R: resistant plant (Chapter 5).

Appendix 10: Survivors of E. colona in gene flow frequency experiment at 30 days after spraying glyphosate (Chapter 5).

Control (Echi S) Control (A533.1) F1 progenies of Echi S plants

148

Appendix 11: Growth time, flower-head number, 100-seed weight and germinability of the resistant (A533.1) and the susceptible (Echi S) populations of E. colona in gene flow experiments (Chapter 5).

Putting seeds on agar: 02/12/2011 Transplanting: 12/12/2011 Finish harvesting: 30/04/2012 Recording 100-seed weight: 06-07/06/2012 Recording germinability: 18-19/03/2013

Flowering Harvesting 100-seed Germination Individual Start *Day FH Start *Day weight (g) (%) A533.1-1 16/01/12 35 183 13/02/12 63 0.11 85 A533.1-2 16/01/12 35 260 12/02/12 62 0.10 71 A533.1-3 16/01/12 35 133 14/02/12 64 0.10 48 A533.1-4 16/01/12 35 221 13/02/12 63 0.11 68 A533.1-5 18/01/12 37 229 18/02/12 68 0.10 75 A533.1-6 16/01/12 35 167 14/02/12 64 0.10 44 A533.1-7 16/01/12 35 238 16/02/12 66 0.10 86 A533.1-8 16/01/12 35 205 18/02/12 68 0.11 71 A533.1-9 17/01/12 36 231 17/02/12 67 0.10 29 A533.1-10 18/01/12 37 163 18/02/12 68 0.10 50 Average 203.0 0.10 62.7 Echi S-1 16/01/12 35 267 13/02/12 63 0.12 96 Echi S-2 16/01/12 35 321 13/02/12 63 0.12 91 Echi S-3 16/01/12 35 193 14/02/12 64 0.11 88 Echi S-4 16/01/12 35 284 13/02/12 63 0.12 82 Echi S-5 16/01/12 35 312 13/02/12 63 0.11 63 Echi S-6 16/01/12 35 304 14/02/12 64 0.12 93 Echi S-7 16/01/12 35 294 16/02/12 66 0.11 86 Echi S-8 16/01/12 35 298 18/02/12 68 0.12 35 Echi S-9 16/01/12 35 307 13/02/12 63 0.12 93 Echi S-10 16/01/12 35 284 17/02/12 67 0.11 82 Average 286.4 0.12 80.9

* Number of days was counted since transplanting. FH: Flower-head number.

149

Appendix 12: Number of E. colona plants before and after spraying glyphosate in the gene flow frequency experiment (Chapter 5).

Time points of experiment: Putting seed on agar: 18/01/2013 Transplanting into trays: 29/01/2013 Spraying glyphosate: 28/02/2013 Recording survival: 30/03/2013

Before spraying (2024 plants) After spraying (28 plants) Tray Echi S 1 Echi S 2 Echi S 3 Echi S 4 Echi S 1 Echi S 2 Echi S 3 Echi S 4 1 17 47 48 49 1 0 1 0 2 10 43 50 49 0 0 1 1 3 24 31 45 45 0 0 1 0 4 13 47 49 45 0 3 1 3 5 4 42 49 46 0 1 1 1 6 49 44 48 1 1 0 7 46 42 50 0 0 0 8 45 40 49 1 0 0 9 42 39 46 1 0 0 10 49 40 48 0 1 1 11 44 47 48 0 0 3 12 29 18 47 1 0 1 13 31 44 0 0 14 9 50 0 0 15 45 0 16 47 0 17 31 0 18 44 1 19 31 1 20 29 0 Total 68 554 511 891 1 8 7 12 Echi S 24 25 24 23 0 0 0 0 (control) A533.1 20 18 23 19 20 18 23 19 (control) Echi S 1, Echi S 2, Echi S 3, Echi S 4: E. colona plants of which seeds were harvested from susceptible plants in Gene Flow experiment. Glyphosate rate was applied: 240 g a.i. ha-1. Survival rate after spraying glyphosate: 1.38%. Echi S (control): 96 plants before spraying, A533.1 (control): 80 plants before and after spraying.

150

Appendix 13: UPGMA dendrogram showing the cDNA sequence groups of the EPSPS gene from five individuals in Table 5 (Chapter 5). The number before the dash is the number assigned to these individuals in Table 5 and the number after the dash is an individual sequence from that population. The sequences containing mutation are in bold italic.

151