Phenotypic Diversity in the Wheat Wild Relative Aegilops Longissima

PHENOTYPIC DIVERSITY IN THE WHEAT WILD RELATIVE AEGILOPS LONGISSIMA

A THESIS SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL OF THE UNIVERSITY OF MINNESOTA BY

SHUYI HUANG

IN PARTIAL FULFILLMENT OF REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE

Adviser: Brian J. Steffenson

November 2016

Acknowledgements

I would like to express my sincere gratitude and appreciation to my mentor and major advisor, Dr. Brian Steffenson, for all his guidance, support, patience, and encouragement throughout my study at University of Minnesota. I am grateful to Dr. Steffenson for sharing his knowledge of plant pathology, providing insight into this thesis, and leading me to the fascinating and meaningful world of crop improvement and research. My grateful appreciation also goes to Dr. James Kolmer and Dr. James Anderson, who served on my thesis committee. Dr. Kolmer and Dr. Anderson provided their helpful advice and guidance during my graduate work and a critical review of my thesis. From all of these individuals, I have gained the knowledge and experience to be a good and independent scientist.

I extend my gratitude to Dr. Xianming Chen (USDA-ARS) at Pullman, Washington for providing the materials and guidance for working with the stripe rust pathogen. Dr. Hanan Sela and Dr. Eitan Millet of the Institute for Cereal Crops Improvement at Tel Aviv University (ICCI-TAU) generously shared their extensive knowledge about Aegilops longissima with me.

I thank the ICCI-TAU in Tel Aviv, Israel and Leibniz-Institute für Pflanzengenetik und Kulturpflanzenforschung (IPK) in Gatersleben Germany for providing the Ae. longissima germplasm that made this project possible.

I also extend my sincere appreciation to the entire Steffenson project for providing me with a friendly and enjoyable environment in which to conduct my studies. I thank Matthew Martin and Tamas Szinyei for their help and support in the laboratory and greenhouse, and to the students Kathleen Ring, Angela Tomlinson, George Saparashvili, Giorgi Beruashvili, Nathalia Salgado Silva, and Evandro Henrique Figueiredo Moura Da Silva who assisted me in my work. My appreciation also goes to Austin Case, Jeness Scott, Pablo Olivera Firpo, Jamie Simmons, Matthew Haas, and Cole

Welchlin for their inspiring and helpful suggestions. Finally, I would like to thank all of the faculty, staff, and graduate students in the Department of Plant Pathology who provided help, encouragement, and friendship during my time at the University of Minnesota.

I express my deep love and gratitude to my family for walking with me through this journey. I greatly appreciate my father Zili Zhou and my mother Qunying Wang for their financial support, encouragement, and understanding during my studies far from home. I am also grateful to my sister Minyi Huang, my brother Zexian Huang, and all of my friends for their support.

A debt of gratitude is owed to Yu Wang and Kathryn Stinebaugh from the Department of Statistics and U-Spatial, who provided help and guidance on data analysis.

Dedication

This thesis is dedicated to my father (Zili Zhou) and mother (Qunying Wang) for their love and encouragement.

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Abstract

Aegilops longissima is an annual grass species that is native to the eastern Mediterranean Basin and is recognized as a potential source of genetic diversity for cultivated wheat improvement. The primary objectives of this research were to assemble a diverse collection of Ae. longissima and characterize it for agro-morphological traits and resistance to the diseases of stem rust (caused by P. graminis f. sp . tritici ), leaf rust (P. triticina ) and stripe rust ( P. striiformis f. sp. tritici ). A collection of 433 accessions of the species, mostly from Israel, was assembled for this study. Evaluation results indicate that Ae. longissima is very diverse for many agro-morphological traits, especially leaf area. With respect to stem rust resistance, 18% and 80% of accessions were resistant to P. graminis f. sp . tritici pathotypes TTTTF and TTKSK, respectively. The percentage of accessions exhibiting resistance to pathotypes of the leaf rust and stripe rust pathogens ranged from 50 to 62%. Ten accessions were resistant to all races of the three pathogens investigated in this study. The great advances made recently in genomics opens up the possibility for exploiting the allelic diversity of Ae. longissima for cultivated wheat improvement.

Table of Contents

Acknowledgements………………...……………………..………..…..…………………i

Dedication…………………………………………………………………….………….iii

Abstract………………...……………………..…………..………………………..…….iv

Table of Contents………………...………………..…………..……………………..….v

List of Tables………………...……………………..…………..……………………….vii

List of Figures……………………………………..……………..………………………ix

Chapter 1: Genetics, Taxonomy, and Ecology of Aegilops longissima and Establishment of a Diversity Collection for the Species……………………………….1 1. Introduction……………………………………………………………………………..2 2. Name and taxonomy……………………………...…………………………..………...6 3. Morphology and life cycle……………………………………………………………...7 4. Ecology and geographic distribution…………………………………………………...9 5. Establishment of a diversity collection of Aegilops longissima ………………………11

Chapter 2: Phenotypic Diversity for Agro-morphological Traits in the Wheat Wild Relative Aegilops longissima ……………………………………………………………32 1. Introduction……………………………………………………………………………33 2. Materials and methods………………………………………………………………...35 2.1. Plant materials…………………………………………………....………………….35 2.2. Plant growth conditions…...………………………………………………………...36 2.3. Agro-morphological traits assessment………………………………….…………...37 2.4. Data analysis………………………………………………………………………...38

3. Results…………………………………………………………………………………41 4 Discussion……………………………………………………………………………...44

Chapter 3: Diversity of Aegilops longissima for Resistance to Wheat Rust Pathogens………………………………………………………………………………..60 1. Introduction……………………………………………….…………………………...61 2. Materials and methods………………………………………………………………...67 2.1. Plant materials…………………………………………………………………….....67 2.2. Plant growth conditions……………………………………………………………..68 2.3. Pathogen isolates…………………………………………………………………….69 2.3.1. Puccinia graminis f. sp . tritici …………………………………………………….69 2.3.2. Puccinia triticina ………………………………………………………………….70 2.3.3. Puccinia striiformis f. sp . tritici …………………………....……………………...70 2.4. Inoculation protocols and infection/incubation period……………………………...71 2.5. Disease assessment………………………………………………………...………..72 2.6. Data analysis………………………………………………………………………...73 3. Results………………………………………………………………………………....76 3.1. Resistance to Puccinia graminis f. sp. tritici ……………………………………...... 76 3.2. Resistance to Puccinia triticina ………………………………………………...…...77 3.3. Resistance to Puccinia striiformis f. sp. tritici ………………………………….…...77 3.4. Spatial autocorrelation analysis based on Global Moran’s I……………...………...79 3.5. Simple linear regression analysis of rust phenotypes and climate data…………...... 79 4. Discussion……………………………………………………………………………..80

Bibliography…………………………………………………………………………...106 Appendix…………………………………..…………………………………………...114

List of Tables Chapter 1 Table 1.1. List of section Sitopsis species of the genus Aegilops and their common names and genome designations………………………………………………………………...15 Table 1.2. Summary of agronomic traits identified in section Sitopsis species of the genus Aegilops …………………………………………………………………………...16 Table 1.3. List of major disease resistance and pest resistance genes transferred from section Sitopsis species of the genus Aegilops into wheat……………………………….18 Table 1.4. Summary of the taxonomic classifications of Aegilops longissima ………….19 Table 1.5. Summary of the ex situ genetic resources of Aegilops longissima in genebanks worldwide………………………………………………………………………………..20 Table 1.6. Collection sites, corresponding longitude/latitude data and number of Aegilops longissima accessions used in this study………………………………………………...23

Chapter 2 Table 2.1. Collection sites and number of Aegilops longissima accessions used in the evaluation of agro-morphological traits. ………………………………………………...50 Table 2.2. Mean, minimum, maximum, standard deviation (SD) and coefficient of variation (CV) values for 11 agro-morphological traits scored on 337 and 362 accessions of Aegilops longissima in Experiment 1 and Experiment 2 in the greenhouse, respectively. ……………………………………………………...……………………...53 Table 2.3. Correlation coefficients among 11 agro-morphological traits evaluated on Aegilops longissima in the greenhouse. ………………………………………………....55 Table 2.4. Spatial autocorrelation of agro-morphological trait values among Aegilops longissima accessions collected at neighboring sites in Israel as assessed by Global Moran’s I. ………………………………………………………………………………..57 Table 2.5. Ordinary Least Square analysis between agro-morphological traits of Aegilops longissima and 16 bioclimatic variables. ………………………………………………..58

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Chapter 3 Table 3.1. Collection sites, corresponding longitude and latitude coordinates and number of Aegilops longissima accessions used in this study. ………………………...………...89 Table 3.2. Race, isolate, virulence phenotype and source of wheat rust pathogens used to evaluate resistance in Aegilops longissima . ………………………………………...…...92 Table 3.3. Number and percentage of Aegilops longissima accessions exhibiting resistant, susceptible and heterogeneous reactions to three wheat rust pathogens and corresponding values for Shannon’s diversity and equitability indices. ………………...93 Table 3.4. Spatial autocorrelation (Global Moran’s I) of the autocorrelation between collection sites of Aegilops longissima . ………………………………………….……...94 Table 3.5. Ordinary Least Squares analysis between rust phenotypes of Aegilops longissima and 16 bioclimatic variables. …………………………………………...…...95

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List of Figures

Chapter 1 Figure 1.1. Spike morphology of Aegilops longissima ………………………………….26 Figure 1.2. Spike morphology of Aegilops longissima : (A) spikelet attached to rachis (4x); (B) caryopses (4x); (C) lemmas (4x); and (D) glumes (4x)………………………..27 Figure 1.3. Spike morphology traits of Aegilops longissima : (A) apical spikelet (2x) and (B) lemma with awn attached (2x)……………………………………………………….28 Figure 1.4. Range of Aegilops longissima based on verified collections and herbarium samples…………………………………………………………………………………...29 Figure 1.5. Aegilops longissima can sometimes be found in cultivated wheat fields such as this one in Gilat, Israel………………………………………………………………...30 Figure 1.6. Map of Israel showing the geographic distribution of Aegilops longissima accessions collected and used in this study………………………………………………31

Chapter 3 Figure 3.1. Map of Israel showing the geographic distribution of Aegilops longissima accessions collected and used in this study. …………………………………...………...96 Figure 3.2. Examples of different stem rust infection types observed on Aegilops longissima in response to Puccinia graminis f. sp. tritici race TTTTF at the seedling stage. ………………………………………………………………………………….....97 Figure 3.3. Examples of different stem rust infection types observed on Aegilops longissima in response to Puccinia graminis f. sp. tritici race TTKSK at the seedling stage. ………………………………………………………………………………….....98 Figure 3.4. Examples of different leaf rust infection types observed on Aegilops longissima in response to Puccinia triticina race THBJ at the seedling stage…………………………………………………………………………………...... 99 Figure 3.5. Examples of different leaf rust infection types observed on Aegilops longissima in response to Puccinia triticina race BBBD at the seedling stage………………………………………………………………………………..…...100

Figure 3.6. Examples of different stripe rust infection types observed on Aegilops longissima in response to Puccinia striiformis f. sp. tritici race PSTv-37 at the seedling stage. …………………………………………………………………………………...101 Figure 3.7. Map of Israel showing the geographic distribution of Aegilops longissima accessions resistant and susceptible to Puccinia graminis f. sp. tritici race TTKSK……………………………………………………………………………….....102 Figure 3.8. Map of Israel showing the geographic distribution of Aegilops longissima accessions resistant and susceptible to Puccinia striiformis f. sp. tritici race PSTv- 37...... 103 Figure 3.9. Map of Israel showing the Local Indicator of Spatial Association (LISA) clusters of Aegilops longissima accessions in response to infection by Puccinia graminis f. sp. tritici race TTKSK……………………………………………………………...... 104 Figure 3.10. Map of Israel showing the Local Indicator of Spatial Association (LISA) clusters of Aegilops longissima accessions in response to infection by Puccinia striiformis f. sp. tritici race PSTv-37…………………………………………………...105

Appendices Appendix Table 1. Collection sites, corresponding longitude and latitude coordinates, donating genebank and number of selfed generations of Aegilops longissima accessions used in this study. ……………………………………………………….……………...114 Appendix Table 2. Raw data for 11 agro-morphological traits scored on 337 and 362 accessions of Aegilops longissima in Experiment 1 and Experiment 2 in the greenhouse, respectively. …………………………………………………………………………....125 Appendix Table 3. Seedling infection types and general reactions of Aegilops longissima accessions to the stem rust ( Puccinia graminis f. sp. tritici ), leaf rust (Puccinia triticina ) and stripe rust (Puccinia striiformis f. sp. tritici ) pathogens. ………..………………...157 Appendix Figure 1. Map of Israel showing the geographic distribution of Aegilops longissima accessions resistant and susceptible to Puccinia graminis f. sp. tritici race TTTTF……...…………………………………………………………………………...215

Appendix Figure 2. Map of Israel showing the geographic distribution of Aegilops longissima accessions resistant and susceptible to Puccinia triticina race THBJ……………………………………………………………………………….…...216 Appendix Figure 3. Map of Israel showing the geographic distribution of Aegilops longissima accessions resistant and susceptible to Puccinia triticina race BBBD…………………………………………………………………………………...217 Appendix Figure 4. Map of Israel showing the Local Indicator of Spatial Association (LISA) clusters of Aegilops longissima accessions in response to infection by Puccinia graminis f. sp. tritici race TTTTF……………………………………………………....218 Appendix Figure 5. Map of Israel showing the Local Indicator of Spatial Association (LISA) clusters of Aegilops longissima accessions in response to infection by Puccinia triticina race THBJ…………………………………………………………………...... 219 Appendix Figure 6. Map of Israel showing the Local Indicator of Spatial Association (LISA) clusters of Aegilops longissima accessions in response to infection by Puccinia triticina race BBBD………………………………………………………………….....220

Chapter 1

Genetics, Taxonomy, and Ecology of Aegilops longissima and Establishment of a Diversity Collection for the Species

1. Introduction To keep pace with the burgeoning world population estimated to be ~9 billion by 2050, food production must be increased by about 40% above current levels (FAO 2009). Due to severe limitations for additional land and water resources globally, this increased food production will have to be met, in part, through greater productivity of new crop cultivars through breeding. Bread wheat ( Triticum aestivum L.) is one of the most important food crops in the world, supplying nearly one third of the calories consumed by humans (USDA ERA, 2015). It is also the most widely grown cereal in the world with a planted area of 225 million Ha and production of more than 735 million metric tonnes (Awika 2011; USDA 2016). In the United States, wheat ranks third behind corn and soybeans in both planted acreage and gross farm receipts (USDA, 2016). Unfortunately, the crop is vulnerable to many diseases due, in part, to the narrowing of genetic diversity through polyploidization, domestication and years of intensive breeding. Among the diseases attacking wheat, those caused by various fungi can be particularly devastating to production, leading to food security problems worldwide. One means of combating such diseases is through the development of disease resistant cultivars. Key to this effort is sourcing sufficient genetic variation to counter changes in the pathogen populations. Therefore, crop improvement through breeding is predicated on exploiting genetic diversity. However, genetic diversity in many wheat improvement programs is limited due to intensive selection and loss of alleles. To counter this loss of diversity, breeding programs must utilize the tremendous diversity present in the different gene pools of wheat. This thesis is focused on one species in the secondary gene pool of wheat: Aegilops longissima Schweinf. & Muschl. The primary objectives of this chapter are to: 1) review the literature on the genetics, taxonomy, morphology, and ecology of Aegilops longissima , 2) assess the ex situ genetic resources of Ae. longissima in genebanks across the world, and 3) assemble a diverse collection of Ae . longissima accessions for various trait evaluations and genetic studies.

The hexaploid bread wheat genome constitution is BBAADD, and the tetraploid durum (pasta) wheat genome constitution is BBAA. The A genome originated from Triticum uratu Thum. ex Gand. (Dvorák et al. 1993), and the D genome originated from Ae. tauschii Coss. (Rayburn and Gill 1987). The origin of the B genome has not been unequivocally determined. The genome of Aegilops speltoides Tausch is most closely related to B, but it is possible that an extinct or yet undiscovered species contributed this genome to wheat (Kilian et al. 2007).

Genetic diversity for disease resistance and other traits in the genomes of wheat can be augmented by exploiting the primary, secondary and tertiary gene pools. According to Feuillet et al. (2007), Friebe et al. (1996) and Mclntosh (1991), the primary gene pool includes species that can be readily hybridized with cultivated wheat to yield fertile or semi-fertile offspring, including all Triticum species (i.e. wild wheats with different ploidy levels as well as primitive wheats and landraces) and Ae . tauschii. The secondary gene pool includes members from which gene transfer is possible, but requires induction of recombination. Members of this gene pool include species of Aegilops , Secale , Elymus and others that have no genome in common with bread wheat. Finally, the tertiary gene pool includes more distantly related species whose chromosomes will not recombine with those of wheat. Gene transfer from these species requires use of ionizing radiation.

The genus Aegilops contains 23 species of which ten are diploid, nine are tetraploid, three are hexaploid, and one is tetraploid-hexaploid (van Slageren 1994). These species carry one or more of the six diverse genomes of C, D, M, N, S, and U (van Slageren 1994). According to the botanical classification of van Slageren (1994), these species are divided into five sections, three of which contain both diploid and polyploid species. Species in section Aegilops L. contain the U genome or combinations of other genomes with U, those in section Cylindropyrum (Jaub. & Spach) Zhuk. contain the C or CD genomes, and those in section Vertebrata Zhuk. emend. Kihara contain the D genome or a combination of other genomes with D. Two 3

sections have only diploid members: species in section Comopyrum (Jaub. & Spach) Zhuk. carry the M or N genomes, whereas those in section Sitopsis possess only the S or modified S genomes.

Within the secondary gene pool of wheat, the five species of Ae. bicornis (Forssk.) Jaub. & Spach (common name: Spach goatgrass), Ae. longissima (proposed common name: Elongated goatgrass), Ae. searsii Feldman & Kislev ex. Hammer (Sears’ goatgrass), Ae. sharonensis Eig (Sharon goatgrass), and Ae. speltoides (Truncate goatgrass) (Table 1.1) in section Sitopsis of Aegilops (van Slageren 1994) comprise a valuable reservoir of genetic diversity for resistance to many pathogens and pests (Millet 2007) (Table 1.2). For example, members of section Sitopsis have been reported to carry disease resistance to stem rust (caused by Puccinia graminis Pers.:Pers f. sp. tritici Eriks. & E. Henn.), leaf rust ( Puccinia triticina Eriks.), stripe rust ( Puccinia striiformis f. sp. tritici Westend.), powdery mildew ( Blumeria graminis DC E. O. Speer f. sp. tritici Em. Marchal), Septoria tritici blotch ( Zymoseptoria tritici (Desm.) Quaedvlieg & Crous), tan spot ( Pyrenophora tritici-repentis (Died.) Drechs.), spot blotch ( Cochliobolus sativus (S. Ito & Kurib.) Drechsler ex Dastur), Fusarium head blight ( Gibberella zeae (Schwein.) Petch), and eyespot ( Oculimacula acuformis (Boerema, R. Pieters & Hamers) Crous & W. Gams and Oculimacula yallundae (Wallwork & Spooner) Crous & W. Gams) (Millet 2007; Gill et al. 1985; Schneider et al. 2007; Anikster et al. 1997). Additionally, several species carry pest resistance to the greenbug ( Schizaphis graminum Rond.) and Hessian fly ( Mayetiola destructor Say.) (Gill et al. 1985; Millet 2007; Schneider et al. 2007). Many important resistance genes from the Sitopsis species have been transferred into bread wheat, including the stem rust resistance genes Sr32 , Sr39 , Sr47 (all from Ae. speltoides ) and Sr51 (Ae. searsii ); the leaf rust resistance genes Lr28, Lr35, Lr36, Lr47, Lr51 (all from Ae. speltoides ) and Lr56 (Ae. sharonensis ); the stripe rust resistance gene Yr38 (Ae. sharonensis ); and the powdery mildew resistance genes Pm12 , Pm32 (both from Ae. speltoides ) and Pm13 (Ae. longissima ) (Millet 2007; Schneider et al. 2007; Liu et al. 2011; Klindworth et al. 2012) (Table 1.3). In addition, the greenbug resistance 4

genes of Gbx and Gb5 were transferred from Ae. speltoides into wheat (Millet 2007; Schneider et al. 2007) (Table 1.3).

Among the five Sitopsis species, Ae. longissima has not been fully exploited for wheat improvement even though it possesses many valuable genes for resistance to biotic stresses, tolerance to abiotic stresses, yield components, and end-use quality. Accessions of Ae. longissima are reported to carry resistance to stem rust (Anikster et al. 1997; Scott et al. 2014), leaf rust (Y. Anikster et al. 2005), stripe rust (Y. Anikster et al. 2005), powdery mildew (Ceoloni et al. 1988; Donini et al. 1995; Alberto et al. 2003), Septoria glume blotch (Ecker et al. 1990), and eyespot (Sheng et al. 2014). Additionally, the species also carries resistance to the pests of greenbug and Hessian fly. With respect to abiotic stresses, Ae . longissima carries some tolerance to drought (Millet 2007; Rekika et al. 1998). The addition of chromosome 5Sl of Ae . longissima to wheat indicated that it carries gene(s) for increasing grain weight (Millet et al. 1988). End-use quality is another trait for which Ae . longissima may contribute valuable genetic diversity for wheat improvement. In comparison to wheat, this species carries enhanced levels of grain protein and kernel hardness (Millet 2007). Huang et al. (2010) isolated and characterized eight novel low-molecular–weight glutenin subunits (LMW-GS) genes from Ae. longissima . The allelic variation at these loci was associated with significant differences in the dough quality of bread (Gupta et al. 1994; Huang et al. 2010).

The genetic diversity found for traits in Ae. longissima is of little practical use in breeding unless the underlying genes can be transferred into adapted wheat germplasm. In this regard, several cases have been described. As mentioned above, a dominant powdery mildew resistance gene designated Pm13 was identified from Ae. longissima and transferred to chromosome arms 3BS and 3DS in wheat cultivar Chinese Spring (Ceoloni et al. 1988; Cenci et al. 1999; Donini et al. 1995). Another Ae. longissima introgression project aims to transfer eyespot resistance into wheat. To first elucidate the genetics of resistance in the diploid wild species, a segregating 5

population was developed between a resistant and susceptible accession (Sheng et al. 2012). Four quantitative trait loci (QTL) were identified for O. yallundae eyespot resistance on Ae. longissima chromosomes 1S l, 3S l, 5S l, and 7S l, and three other QTL for O. acuformis eyespot resistance were identified on chromosomes 1S l, 3S l, and 5S l. Millet et al. (1988) reported the successful substitution of Ae. longissima chromosome 5S l for its wheat homoeologues, contributing a moderate effect on reducing plant height, promoting earliness, and increasing grain weight in the derived substitution lines. However, these derived lines were not able to compensate for the absence of a pair of any of its homoeologues (Millet et al. 1988). Garg et al. (2014) produced a chromosome 1S l disomic addition line of Ae. longissima (DAL1S l) that had significantly higher dough strength, grain hardness, mixograph peak height, band width and unextractable polymeric protein content compared with wheat. In the same study, grain quality analysis of substitution line DAL1S l(1A) revealed significantly higher dough strength, farinograph development time, stability time, gluten index, bread loaf volume and bread quality score than wheat.

2. Name and taxonomy Aegilops longissima Schweinf. & Muschl. (Table 1.4) Proposed common name: Elongated goatgrass

Etymology: The genus name Aegilops is mentioned for the first time in the ancient Greek works of Dioscorides, Theophrastus and Galenus, where it was written that the plant has healing properties for eye diseases of goats (van Slageren 1994; Quattrocchi 2000). Aegilops is derived from the Greek word αιγιλωΨ, which refers to goat (van Slageren 1994). Through time, different authorities translated the word to mean “a herb liked by goats” or “resembling the eye of a goat”, the latter comparison being made in reference to the long awns that surround spikelets (van Slageren 1994). The species name of longissima is derived from the Latin word “ longissimus ” which means “very long”--a reference to the tall stature of the plant (van Slageren 1994) and especially the exceptionally long spike. 6

Aegilops longissima was first described in 1928 by Zhukovsky (1928). Since that time there have been several taxonomic treatments of the species (Eig 1929; Hammer 1980; Kihara 1954; Kimber et Sears 1987; van Slageren 1994; Whitcombe 1983). The current taxonomic classification of Ae. longissima within the order Poales is given below.

Order Poales Small Family Poaceae Barnh. Subfamily Pooideae Macfarl. & Watts. Supertribe Triticanae Macfarl. & Watts. Tribe Triticeae Dumort. Subtribe Triticinae Griseb. Section Sitopsis (Jaub. & Spach) Zhuk. Genus Aegilops L. Species Ae . longissima Schweinf. & Muschl.

3. Morphology and life cycle Descriptions about the morphology and life cycle of Ae. longissima are based on the publications of Eig (1929), Kimber and Feldman (1987), van Slageren (1994), Witcombe (1983), and my own observations. Aegilops longissima is an annual grass plant with tall, erect and slender stems, usually five to eight in number, but reaching as many as 15 in some accessions. It initially grows in a leafy prostrate habit during the cooler winter season that is typical in the Mediterranean Basin. Then at jointing, the stems extend upright, reaching a height of 40-100 cm, excluding the spikes. Leaves on the stem are sparse and occur mostly toward the base. The stems have a variable number of nodes that range from three to five. Leaf blades are linear- acuminate in shape and 6-12 cm long x 0.3-0.5 cm wide. The margin of the leaf sheath is hyaline and ciliate. Aegilops longissima has a narrowly cylindrical single- rowed spike (Fig. 1.1), approximately 10-20 cm long (excluding awns) x 0.2-0.3 cm wide with 8-17 spikelets. The spikes are slightly tapered at the basal and apical ends 7

due to the lateral compression of the spikelets. Spikelets appress closely to the rachis segment and disarticulate at only one or two points along the lower part of the spike. Thus, the dispersal unit for the species is a long section of multiple spikelets. Oftentimes, a few of the lower fertile spikelets remain attached to the culm at maturity. This is in contrast to the closely related species of Ae . sharonensis , which disarticulates into individual spikelets (van Slageren 1994). In Ae. longissima , rudimentary spikelets are usually absent, but in rare cases one or two may develop at the base of the spike. Spikelets (Fig. 1.2A) are narrowly ellipsoid and sessile and 0.9- 1.5 cm long. Each spikelet consists of three to five florets, but the upper florets are usually sterile. The caryopsis (Fig. 1.2B) is 0.5-0.6 cm long and adheres to the lemma and palea when mature. The palea is narrowly elliptical with two sharp, setose keels, each ending in a sharply acute apex. Lemmas (Fig. 1.2C) of fertile florets are narrowly elliptical and canoe-shaped (0.9-1.2 cm long), exserting the glumes for more than one-third of their length. The lemma of the apical spikelet’s floret (Fig. 1.3A) is sharply acute, extending into a long, setulose, convex awn of 0.8-7.5 cm in length (Fig. 1.3B). Glumes (Fig. 1.2D) are 6-8 mm long and narrowly ovate-elliptical and leathery in texture with a scabrous to setose surface. Glumes have hyaline lateral margins and an apex with two sharp teeth with a membranous depression in between.

Aegilops longissima is very similar to the sympatric species of Ae. sharonensis and the allopatric species of Ae . searsii with respect to morphological traits. The defining traits are described below and based on the studies by Ankori and Zohary (1962) and van Slageren (1994). Aegilops sharonensis was once considered a subspecies of Ae. longissima because it occupied sympatric habitats, and natural hybridizations occurred between them (Ankori and Zohary 1962). Several key morphological similarities between Ae. longissima and Ae. sharonensis include a single-row spike; a comparable culm height of 30-70 cm, excluding the spike; and a fully developed awn in the apical spikelets (van Slageren 1994). However, several key differences exist between the two species: 1) the spikes of Ae. longissima (10-20 cm) are generally longer than Ae. sharonensis (7-10 cm); 2) Ae. longissima has fully 8

developed awns only on the apical spikelets, whereas with Ae. sharonensis awns develop on most of the lateral spikelets; and 3) Ae. longissima disarticulates at only one or two points along the lower part of the spike making the dispersal unit a long section of multiple spikelets, whereas Ae. sharonensis disarticulates at every spikelet base, rendering each spikelet as a dispersal unit (van Slageren 1994). Aegilops longissima and Ae. searsii are similar in two key traits: 1) fully developed awns only in the apical spikelets and 2) disarticulation of the spike at just one or two points along the rachis (van Slageren 1994). With respect to key differences, Ae. longissima has taller stems (40-100 cm vs. 10-35 cm, excluding the spikes) and longer spikes (10-20 cm vs. 6-13 cm) than Ae. searsii (van Slageren 1994). Additionally, with Ae. longissima , the lemma adheres to the grain, whereas with Ae. searsii the grain is naked. The habitat ecology of the two species is also different. Aegilops longissima can often be found growing in light sandy soils and sandstones with an annual rainfall of 250-400mm, while Ae. searsii grows on terra rossa soil (e.g. in dry open grasslands, steppes, ruderal fields and roadsides) with annual rainfall of only 150-300 mm.

In its native habitat in the eastern Mediteranean Basin, Ae. longissima flowers and completes caryopsis development from March to June, depending on the soil type and water availability (van Slageren 1994). The flowering time for other species in the Sitopsis section depends on their ecogeographical habitat. In this regard, Ae. bicornis has the earliest flowering time, followed by Ae. sharonensis , Ae. longissima , Ae. searsii, and finally Ae. speltoides (Brody 1983; van Slageren 1994). In comparison to the closely related species of Ae. sharonensis , Ae. longissima flowers about two to three weeks later and ripens about one month later (Ankori and Zohary 1962).

4. Ecology and geographic distribution Information about the ecology and geographic distribution of Ae. longissima is based on the publications of Witcombe (1983), Kimber & Feldman (1987), van Slageren (1994), Millet (2007) and the Flora of Israel website 9

(http://flora.org.il/en/plants/AEGLON/). Aegilops longissima has a large geographic distribution with respect to the other four species in the Sitopsis section, the exception being Ae. speltoides whose habitat range is the most extensive. It is found around the eastern Mediterranean Basin in lower, coastal and Sinai Egypt, across the north-south axis of western and interior Israel, southern coastal plain of Lebanon, northwestern Jordan, and southern Syria (van Slageren 1994). The range of the species based on verified collections and herbarium samples is given in Fig. 1.4. The species is adapted to light, siliceous sandy soil and sandstones, and rarely on calcareous sandstones or silty, poorly drained soil types. In general, it is common and grows luxuriously in the coastal Mediterranean plains and in several grassland habitats bordering Israel and Jordan. Aegilops longissima has a relatively wide ecological preference, which includes the coastal plains of Egypt, Israel and Lebanon; the sand-derived Nubian sandstone of Jordan; the limestone soils of Mediterranean terra rossa in the undergrowth of Pinus forests in Jordan; and open dwarf shrub or herbaceous steppe- like or desert-like formations in Israel (van Slageren 1994). In addition, Ae. longissima can also found in dry grasslands, abandoned fields, as well as the edges of crop cultivation (Fig. 1.5) and roadsides. Similar to Ae. bicornis and Ae. searsii , Ae. longissima has tolerance to drought, surviving in regions where the annual rainfall is as low as 75 mm (H. Sela, personal communication ). With respect to elevation, Ae. longissima is found from -200 meters below sea level (near the Dead Sea) in Israel to 400-600 meters above sea level in Jordan.

With its relatively wide geographic distribution, Ae. longissima is sympatric with most of the species in the Sitopsis section, excluding Ae. speltoides . This is especially true for Ae. sharonensis as the two species are often found growing side by side in the Sharon Plain between Tel Aviv and Haifa where intermediates and recombinants are occasionally found (Ankori and Zohary 1962). Because Ae. longissima and Ae. sharonensis have very similar genomes, hybridizations between the two species can occur in nature. Such hybridizations can increase the frequency of fertile progeny whose spike morphologies are distinguishably intermediate between 10

the two species (Ankori and Zohary 1962; Millet et al. 2006). Ankori & Zohary (1961) found several fully developed hybrid swarms with intermediate morphology along roadsides and edges of crop cultivation in the Sharon Plain. However, the hybrids and hybrid progenies were not stable and could not adapt well to the natural habitats (Ankori and Zohary 1962). Millet et al. (2006) also found morphologically intermediate types between Ae. longissima and Ae. sharonensis at the Kefar Ganim site in the central coast region of Israel.

5. Establishment of a diversity collection of Aegilops longissima Germplasm is the source material for many types of investigations of a given species, but is particularly critical as the foundation for crop breeding. Without the allelic diversity present in germplasm collections, whether cultivars, breeding lines, landraces or wild relatives, genetic gains could not be made in crops--though there is some evidence for de novo genetic variation in closed breeding populations (Day et al. 1991; Rasmusson & Phillips, 1991). For this reason, it is essential to have large repositories of ex situ germplasm in gene banks for ready use by breeders and other plant scientists. Crop wild relatives are an important component of this germplasm because they often possess the highest level of allelic diversity within the gene pools of a crop species (Day et al. 1991). However, many populations of crop wild relatives are threatened due to urbanization, and ironically, by agriculture itself. Thus, for some crop wild relatives, there is an urgent need to survey likely habitats and make collections for future evaluations and utilization (Day et al. 1991).

The ex situ genetic resources available for some crops are massive. For example, there are over 811,708 accessions of the primary and secondary gene pools of wheat deposited in gene banks across the world (Tadesse et al. 2016; Knüpffer 2009). The large size of such a germplasm collection makes it prohibitively expensive to maintain and to conduct many phenotype and genotype assays. Moreover, many of these collections contain duplicates or redundant samples at some sites, rendering germplasm evaluation efforts inefficient (Escribano et al. 2008). To overcome the 11

problems associated with the evaluation of large germplasm collections, Frankel (1984) proposed the concept of core collections, and Brown (1999) refined the operational definition and demonstrated the advantages and disadvantages of such collections in practical use. A core collection is a limited subset of accessions that captures as much genetic diversity as possible within a crop species without unnecessary repetitiveness or duplication (Escribano et al. 2008; van Hintum et al. 2000). Core collections provide the benefits of increasing the efficiency of evaluations, while at the same time reducing management and evaluation expenses (Diwan et al. 1995; Escribano et al. 2008). According to Diwan et al. (1995), a good core collection should: 1) represent the whole collection of a particular species across its geographical range, 2) be small enough to manage easily with respect to various intensive evaluations, and 3) minimize redundant entries. Diwan et al. (1995) indicated that core collections assembled with evaluation data and cluster analysis better represent the germplasm collection than core collections assembled based solely on passport data and random selection of accessions.

Comprehensive studies on the genetic diversity and population structure of endangered and threatened species are urgently needed to promote effective conservation and management activities (Wu et al. 2014). As discussed above, Aegilops longissima is an important species in the secondary gene pool of wheat and is known to carry many valuable alleles for crop improvement. Across its range in the eastern Mediterranean Basin, there are populations of Ae. longissima that are threatened due to continued habitat disturbance. With the ultimate goal of establishing a core collection of Ae. longissima , I surveyed the ex situ genetic resources and found 2,485 accessions deposited in gene banks across the world (Table 1.5). Data on the country of origin is lacking for some of these accessions. In cases where this information is known, the vast majority (2,389 accessions or 96.0% of total) of Ae. longissima accessions housed in gene banks were collected from Israel, with considerably fewer accessions from Jordan (25 or 1.0% of total) or from unknown provenance (71 or 3%). Most of the available ex situ accessions of Ae. longissima 12

reside in the Harold and Adele Lieberman Germplasm Bank in the Institute for Cereal Crops Improvement (ICCI) at Tel Aviv University (Tel Aviv, Israel) with a subset of the collection deposited in the United States Department of Agriculture-Agricultural Research Service (USDA-ARS) National Small Grains Collection in Aberdeen Idaho. As mentioned previously, populations of Ae. longissima are known to exist in a number of other countries (Egypt, Lebanon, Jordan, Syria) in the eastern Mediterranean Basin (Kimber and Feldman 1987; van Slageren 1994), but searches uncovered very few accessions available for study. Due to the difficulties in sourcing accessions from these other countries and gene banks, my primary focus was on characterizing a diverse collection of Ae. longissima accessions chiefly from Israel, where many populations of the species still exist and ex situ accessions are freely available for evaluation.

Scientists at the ICCI have extensively surveyed Israel and adjacent territories for populations of Ae. longissima and have made many collections. Currently, the ICCI holds 1,786 accessions of Ae. longissima collected from 109 sites in Israel. For my investigation on the genetic diversity of Ae. longissima , Dr. Hanan Sela, Curator of the ICCI, selected 411 accessions from Israel (Fig. 1.6). These accessions were collected from 76 ecogeographically diverse populations within the country where no more than 16 accessions were included from a single site. In addition to these 411 Israeli accessions, two Jordanian accessions also were donated by the ICCI for this investigation. To enhance the germplasm collection further, I received 22 accessions of Ae. longissima from the Leibniz-Institut für Pflanzengenetik und Kulturpflanzenforschung (IPK) in Gatersleben, Germany and five from the National BioResource Project (NBRP) in Kyoto, Japan. Seventeen of the IPK accessions were originally collected from Israel, two from Jordan, and three from an unknown location. Passport data were not available for any of the IPK accessions. All of the accessions from the NBRP were collected in Israel; however, none of them germinated and were therefore dropped from consideration. Thus, for my investigation on the diversity of Ae. longissima , a total of 433 accessions were 13

available for study: 424 from Israel, four from Jordan and five from unknown sites (Table 1.6; Appendix Table 1). This germplasm comprises the Ae. longissima Diversity Collection (ALDIVCO), which was utilized in the research described in Chapter 2 and Chapter 3.

The long-term goal of this research is to exploit economically useful genes from Ae. longissima for cultivated wheat improvement. The primary objectives of this thesis are to: 1) characterize a diverse collection of Ae. longissima for agro- morphological traits (Chapter 2) and 2) assess the resistance of this collection to stem rust, leaf rust, and stripe rust (Chapter 3).

Table 1.1. List of section Sitopsis species of the genus Aegilops and their common names and genome designations a. Species Common name Genome designation Ae. bicornis (Forssk.) Jaub. & Spach Spach goatgrass Sb Ae. longissima Schweinf. & Muschl. Elongated goatgrass (pending) Sl Ae. searsii Feldm. & Kisl. ex Hamm. Sears’ goatgrass Ss Ae. sharonensis Eig Sharon goatgrass Ssh Ae. speltoides Tausch Truncate goatgrass S aBased on Millet (2007).

Table 1.2. Summary of agronomic traits identified in section Sitopsis species of the genus Aegilops . Traits Species Reference Ae. bicornis Anikster et al. (2005) Ae. longissima Anikster et al. (2005) Stem rust Ae. sharonensis Anikster et al. (2005), Olivera et al. (2007) Ae. speltoides Anikster et al. (2005), Dyck (1990), Friebe et al. (1996), Marais et al. (2003), Valxou et al. (1985) Ae. longissima Anikster et al. (2005) , Gill et al. (1985) Ae. searsii Anikster et al. (2005) , Gill et al. (1985) Anikster et al. (2005), Dyck (1990), Friebe et al. (1996), Marais et al. (2003), Olivera et al. (2007), Leaf rust Ae. sharonensis Valxou et al. (1985) Anikster et al. (2005), Dvořák and Knott (1990), Dyck (1990), Friebe et al. (1996), Gill et al. (1985), Ae. speltoides Marais et al. (2003), Valxou et al. (1985) Disease Ae. longissima Anikster et al. (2005) resistance Ae. searsii Anikster et al. (2005) Stripe rust Ae. sharonensis Anikster et al. (2005), Marais et al. (2003), Olivera et al. (2007), Valxou et al. (1985) Ae. speltoides Anikster et al. (2005), Marais et al. (2003), Valxou et al. (1985) Ae. bicornis Gill et al. (1985) Ae. longissima Ceoloni et al. (1992), Friebe et al. (1996), Gill et al. (1985) Powdery mildew Ae. sharonensis Gill et al. (1985), Olivera et al. (20 07) Ae. speltoides Gill et al. (1985), Valxou et al. (1985) Eyespot Ae. longissima Sheng et al. (2012), Sheng et al. (2014) Septoria tritici blotch Ae. speltoides McKendry and Henke (1994) Spot blotch Ae. sharonensis Olivera et al. (2007)

Tan spot Ae. sharonensis Olivera et al. (2007) Ae. longissima Gill et al. (1985) Greenbug Ae. sharonensis Gill et al. (1985) Ae. speltoides Gill et al. (1985), Tyler et al. (1987) Pest resistance Ae. bicornis Gill et al. (1985) Ae. longissima Gill et al. (1985) Hessian fly Ae. sharonensis Gill et al. (1985) Ae. speltoides Gill et al. (1985) Heat tolerance Ae. speltoides Waines (1994) Abiotic Ae. longissima Rekika et al. (1998), Waines et al. (1993) Drought tolerance resistance Ae. sharonensis Rekika et al. (1998), Waines et al. (1993) Manganese toxicity Ae. speltoides Dinev and Netcheva (1995) Grain protein percentage All Sitopsis species Levy and Feldman (1989), Rafi et al. (1992) Grain quality Grain hardness All Sitopsis species Lillemo et al. (2002) Grain weight Ae. longissima Millet et al. (19 88)

Table 1.3. List of major disease resistance and pest resistance genes transferred from section Sitopsis species of the genus Aegilops into wheat. Trait Donor species Gene Reference Sr32 Friebe et al. (1996) , McIntosh (1991) Ae. speltoides Sr39 Kerber and Dyck (1990) Stem rust resistance Sr47 Klindworth et al. (2012) Ae. searsii Sr51 Liu et al. (2011) Lr28 McIntosh et al. (1982), Naik et al. (1998) Lr35 Kerber and Dyck (1990) Lr36 Dvořák (1977), Dvořák and Knott (1990) Ae. speltoides Leaf rust resistance Lr47 Wells et al. (1982) Lr51 Dvořák (1977), Dvořák and Knott (1990), Helguera et al. (2005) Lr66 Marais et al. (2003); Marais et al. (2009) Ae. sharonensis Lr56 Marais et al. (2006) Stripe rust resistance Ae. sharonensis Yr38 Marais et al. (2006) Pm12 Miller et al. (1987) Ae. speltoides Powdery mildew resistance Pm32 Hsam et al. (2003) Ae. longissima Pm13 Ceoloni et al. (1988), Donini et al. (1995) Gb5 Dubcovsky et al. (1998), Lukaszewski (1995), Wells et al. (1982) Greenbug resistance Ae. speltoides Gbx Weng and Lazar (2002)

Table 1.4. Summary of the taxonomic classifications of Aegilops longissima a. Year Author Classification 1928 Zhukovsky Ae. longissima (Schweinf. & Muschl.) Eig 1929 Eig Ae. longissima Schweinf. & Muschl. 1954 Kihara Ae. longissima Schweinf. & Muschl. 1980 Hammer Ae. longissima Schweinf. & Muschl. emend. Eig s.l. 1983 Whitcombe Ae. longissima Schweinf. & Muschl. 1983 Kimber et Sears Triticum longissimum (Schweinf. & Muschl.) Bowd. 1994 van Slageren Ae. longissima Schweinf. & Muschl. aBased on Schneider et al. (2008).

Table 1.5. Summary of the ex situ genetic resources of Aegilops longissima in genebanks worldwide.

Genebank Acronym Number of Accessions Countries of Origin a Lieberman Germplasm Bank, Institute for Cereal Crops Improvement, Tel Aviv ICCI 1,786 Israel (1781), Jordan (2), Unknown (3) University, Tel Aviv, Israel

USDA-ARS National Small Grains Germplasm Research Facility, Aberdeen, United NSGC 509 Israel (503), Jordan (3), Turkey (1), States of American Soviet Union (1), Unknown (1)

Plant Genetic Resources Documentation in the Czech Republic, Prague, Czech CRI 36 Israel (23), Turkey (1), Unknown (12) Republic

National BioResource Project, KOMUGI Wheat Genetic Resources Database, Kyoto, NBRP 35 Israel (30), Jordan (2), Unknown (3) Japan

Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben, Germany IPK 25 Israel (19), Jordan (2), Unknown (4)

International Centre for Agricultural Research in Dry Areas, Aleppo, Syrian Arab ICARDA 24 Israel (8), Jordan (8), Unknown (8) Republic

Germplasm Resources Unit at the John Innes Centre, Norwich, United Kingdom GRU 16 Israel (5), Jordan (2), Unknown (9)

Wheat Genetics Resource Center, Manhattan, United States of American WGRC 12 Israel (7), Jordan (2), Canada (1),

Turkey (1), Palestine (1)

N.I. Vavilov Research Institute of Plant Industry, St. Petersburg, Russia VIR 10 Israel (3), Jordan (1), Unknown (6)

Centro Internacional de Mejoramiento de Maíz y Trigo, Texcoco, Mexico CIMMYT 8 Israel (4), Turkey (2), Japan (1), United States (1)

Millennium Seed Bank Project, Seed Conservation Department, Royal Botanic RBG 6 Israel (5), Jordan (1) Gardens, Kew, Wakehurst Place, Ardingly, United Kingdom

Dobrudja Agricultural Institute, National Centre of Agricultural Science, General DAI 4 Unknown (4) Toshevo, Bulgaria

Institute for Plant Genetic Resources “K. Malkov”, Sadovo, Bulgaria IPGR 3 Israel (1), Jordan (2)

Centro Nacional de Recursos Fitogenéticos, Madrid, Spain INIA-CRF 2 Unknown (2)

Plant Breeding and Acclimatization Institute, Radzików-Wieś, Poland IHAR 2 Unknown (2)

Research Institute for Cereals and Technical Plants Fundulea, Calarasi, Romania ICCPT Fundul 2 United Kingdom (2)

Suceava Genebank, Suceava, Romania BRGV Suceava 2 United Kingdom (2)

Azerbaijan Genetic Resources Institute, Baku, Azerbaijan AGRI 1 Unknown (1)

Institute for Agrobotany, Tápiószele, Hungary RCA 1 Unknown (1)

Institute of Plant Production nd. a. V. Ya. Yuryev of NAAS, Kharkov, Ukraine IR 1 Unknown (1)

Total 2,485 aAegilops longissima is only known to occur naturally in the countries of Egypt, Lebanon, Israel, Jordan, and Syria. The other listed countries of origin represent the location of the donating genebank.

Table 1.6. Collection sites, corresponding longitude/latitude data and number of Aegilops longissima accessions used in this study. Collection Site Longitude Latitude Number of Accessions Akko 35.08450 32.92989 11 Ashalim 34.67443 30.95645 11 Ashdod 34.70007 31.83610 4 Be'er Sheva 34.79576 31.25067 8 Be'er Sheva -Arad 34.97110 31.26642 1 Beit Lid 34.92786 32.33349 6 Ben Zakkay 34.72830 31.85664 11 Benaya 34.75259 31.84373 11 Berekhya 34.64611 31.66749 1 Dimona 35.02579 31.06940 3 Dorot 34.64667 31.50744 4 En Gev 35.64119 32.78367 7 Ge'alya Kubeiba 34.76632 31.88609 11 Gevar'am 34.61328 31.59199 10 Gilat 34.66168 31.33539 13 Giv'at Arnon 34.67285 31.66040 4 Giv'at Brenner 34.80263 31.86713 10 HaBesor 34.50523 31.23739 1 Hadera 34.92245 32.44402 11 HaNegev Junction 34.83688 31.06699 6 Herzliyya 34.84554 32.15992 1 Hevron -- -- 1 Horbat Allon 34.96300 32.45040 3 Ilanot 34.89945 32.28830 1 Kefar Menahem 34.83516 31.73211 12 Kefar Mordechay 34.75688 31.83148 4 Kefar Yona 34.93412 32.31760 14 Liman 35.11188 33.05918 6 Mamshit 35.06349 31.02720 12 Mash'abbe Sade 34.75162 31.03082 6 Mash'abbe Sade -Retamim 34.70427 31.04970 1 Mefalsim 34.56179 31.50268 1 Megdar Farm 34.64875 31.35340 1 Nahal Hatzatz 34.84066 30.89407 2 Nahal Liman 35.10566 33.05052 12 Nahal Oz 34.49776 31.47274 1

Nahal Solelim -Beersheba 34.74890 31.26755 7 Nahal Zin 35.03710 30.83100 1 Nahariyya-Rosh HaNikra 35.10486 33.01839 1 Nir'am 34.58058 31.51892 8 Nizzanim 34.63440 31.71838 8 Or-Haner 34.60823 31.55348 3 Pardes Hanna 34.93411 32.48272 2 Petah Tiqwa 34.88880 32.08345 5 Qiryat Ono 34.85893 32.05537 15 Qiryat Ono -Petah Tiqwa 34.87340 32.07012 4 Raffiah Yam 34.24458 31.32220 1 Ramat Aviv 34.80613 32.11242 5 Rehovot 34.81087 31.89447 10 Re'im 34.45913 31.38640 9 Revivim 34.81523 31.05056 1 Rishon LeZiyyon 34.81121 31.96003 3 Ruhama 34.70530 31.49821 1 Ruhama -Badlands 34.71153 31.49777 2 Sde Boker 34.79345 30.87372 15 Shedema 34.74031 31.83360 16 Shedema-Benaya 34.74003 31.83927 9 Shefayyim 34.82245 32.21665 4 Shemuel Hospital 34.82426 31.93166 1 Shirat HaYam 34.27177 31.36698 2 Shivta -Haluza 34.62270 31.01853 1 Shomerat 35.09515 32.95197 4 Tel Katifa 34.30480 31.36420 1 Tel Mond 34.91816 32.25665 10 Tlalim 34.77135 30.99031 10 Tel-Nof 34.78353 31.83983 1 Tifrah 34.68758 31.31092 6 Tifrah2 34.68670 31.31678 4 Yad Mordekhay 34.55750 31.58702 1 Yaqum 34.84211 32.24932 2 Yaziz-Gibton 34.86490 31.85339 4 Yeroham 34.87481 31.03196 7 Yeroham-Be'er Sheva 34.87800 31.02850 1 Dead Sea a -- -- 1 Jordan River a -- -- 1 Unknown Israel b -- -- 17

Unknown Jordan c -- -- 2 Unknown d -- -- 5 Total 433 aCollection sites of accessions are from Jordan. bSpecific collection sites are not known for 17 accessions from Israel. cSpecific collection sites are not known for 2 accessions from Jordan. dThe country of origin is not known for 5 accessions.

Figure 1.1. Spike morphology of Aegilops longissima .

Figure 1.2. Spike morphology traits of Aegilops longissima : (A) spikelet attached to rachis (4x); (B) caryopses (4x); (C) lemmas (4x); and (D) glumes (4x).

Figure 1.3. Spike morphology traits of Aegilops longissima :

(A) apical spikelet (2x) and (B) lemma with awn attached (2x).

Figure 1.4. General habitat r ange of Aegilops longissima based on verified collections and herbarium samples.

aAdapted from Kimber & Feldman (1987), Millet (2007), van Slageren (1994) and Witcombe

(1983).

Figure 1.5. Aegilops longissima can sometimes be found in cultivated wheat fields such as this one in Gilat, Israel a.

aPicture courtesy of Brian Steffenson

Figure 1.6. Map of Israel showing the geographic distribution of Aegilops longissima accessions collected and used in this study a.

aTwenty-two accessions from donated by the Leibniz-Institut für Pflanzengenetik und Kulturpflanzenforschung (IPK) and four accessions of unknown origin were not included in the map but were evaluated in the study.

Chapter 2

Phenotypic Diversity for Agro-morphological Traits in the Wheat Wild Relative Aegilops longissima

Diversification of traits is the essential basis for successful crop breeding, especially when markedly different production regions are targeted (Sabaghnia et al. 2013). Genetic diversity in plants can be estimated based on either agro- morphological traits or molecular markers (Amini, Saeidi, and Arzani 2007). Although molecular markers reflect variation in the entire genome, agro- morphological traits represent variation in the expressed regions of genome (Barakat et al. 2013). For many genetic studies of plants, agro-morphological traits are often the first phenotypes taken due to their ease of observation and scoring (Levy and Feldman 1989). Additionally, analyzing differences in agro-morphological traits between wild relatives and cultivated crops may reveal new genes that can be utilized to enhance the latter or as markers in genetic analyses (Levy and Feldman 1989). Measurement of agro-morphological traits in under-utilized species has diverse applications, including the analysis of genetic variability, conservation of germplasm and identification of accessions with valuable traits for introgression programs of cultivated crops (Sabaghnia et al. 2013; Zafar et al. 2004).

The genus Aegilops contains 23 species classified into five sections. Section Sitopsis comprises five diploid species, carrying the S genome, which is closely related to the B genome of wheat (van Slageren 1994). These five species include Ae. bicornis (Forssk.) Jaub. & Spach (Spach goatgrass), Ae. longissima (proposed common name: Elongated goatgrass), Ae. searsii Feldman & Kislev ex. Hammer (Sears’ goatgrass), Ae. sharonensis Eig (Sharon goatgrass), and Ae. speltoides (Truncate goatgrass). Species in the section Sitopsis (van Slageren 1994) are part of the secondary gene pool of wheat and represent a valuable reservoir of genetic diversity for many agronomic traits and disease resistance (Millet 2007).

Within the Sitopsis section, Ae. longissima possesses many useful traits, but has not been fully exploited for enhancing wheat. It is recognized as a rich source of disease resistance. For example, accessions of Ae. longissima are reported to carry resistance to stem rust (Y. Anikster et al. 2005; Scott et al. 2014), leaf rust (Y. Anikster et al. 2005), stripe rust (Y. Anikster et al. 2005), powdery mildew (Ceoloni et al. 1988), Septoria glume blotch (Ecker, Cahaner, and Dinoor 1990), and eyespot (Sheng, See, and Murray 2012). With respect to abiotic stresses, Ae . longissima carries tolerance to drought (Millet 2007). Grain quality is another trait for which Aegilops species may contribute valuable genetic diversity for wheat improvement. All of the Sitopsis species were reported to carry enhanced levels of grain protein and kernel hardness in comparison to wheat. The addition of chromosome 5Sl of Ae . longissima to wheat indicated that it carries gene(s) for increased grain weight (Millet et al. 1988). Huang et al. (2010) isolated and characterized eight novel low- molecular–weight glutenin subunit (LMW-GS) genes from Ae. longissima . The allelic variation at these loci was associated with significant differences in the dough quality of bread (Gupta et al. 1994; Huang et al. 2010). Moreover, a chromosome 1S l disomic addition line of Ae. longissima (DAL1S l) had significantly higher dough strength, grain hardness, mixograph peak height, band width, and unextractable polymeric protein content compared with wheat (Garg et al. 2014). In the same study, grain quality analysis of a substitution line DAL1S l(1A) revealed significantly higher dough 34

strength, farinograph development time, stability time, gluten index, bread loaf volume and bread quality score than the wheat cultivar Chinese Spring (CS).

Few investigations have been advanced on the diversity of agro-morphological traits in Ae. longisssima . If such variation is cataloged, the underlying genes could be introgressed into wheat to enhance its genetic diversity, productivity and adaptation (Gupta and Sharma 2005). The long-term objective of this research is the enhancement of wheat with genes derived from wild relatives. The specific objective of this research is to evaluate a diverse collection of Ae. longissima for agro- morphological traits.

2. Materials and Methods 2.1 Plant materials The Ae. longissima Diversity Collection (ALDIVCO) (Chapter 1) was used for all evaluations of agro-morphological traits in this study. It consists of 433 accessions: 424 from Israel, four from Jordan and five from unknown sites (Table 2.1). Accessions from other countries (Egypt, Lebanon, and Syria) where the species is found (Kimber & Feldman 1987; Millet 2007; van Salgeren 1994; Witcombe 1983) were not available for study. Israel encompasses the largest and most diverse populations of Ae. longissima across its entire habitat range. The 424 ALDIVCO accessions from Israel were collected from 76 ecogeographically diverse populations within the country where no more than 16 accessions were included from a single site. The four accessions from Jordan were collected near the Dead Sea and the Jordan River. Finally, five other Ae. longissima accessions of unknown provenance were also included in the collection. Most (411 of 433) of the ALDIVCO accessions were donated by the Harold and Adele Lieberman Germplasm Bank in the Institute for Cereal Crops Improvement (ICCI) at Tel Aviv University (Tel Aviv, Israel) with the remaining ones donated by the Leibniz-Institut für Pflanzengenetik und Kulturpflanzenforschung (IPK) in Gatersleben, Germany. Passport data are available

for all of the Israeli accessions provided by the ICCI, but not those from Jordan nor those donated by the IPK (Appendix Table 1).

In order to increase homozygosity in the ALDIVCO accessions and generate sufficient seed stocks for the phenotyping evaluations, all of the received Ae. longissima accessions were selfed from one to four generations. The first one or two generation increases for most accessions from the ICCI were made within a net-house where spikes were not bagged. Subsequent increases of the germplasm were made inside a greenhouse at the University of Minnesota Plant Growth Facility in St. Paul. For each of these later increase generations, the spikes were bagged to prevent cross- pollination and then a single seed was advanced. Although every effort was made to increase all 433 ALDIVCO accessions, some problems (e.g. poor plant growth, failure to flower, partial sterility, etc.) were encountered during their cultivation, resulting in low seed stocks. Therefore, the total number of accessions assessed for agro-morphological traits was 337 and 362 for Experiments 1 and 2, respectively. Passport information (where available) and raw agro-morphological data for each accession are given in Appendix Tables 1 and 2, respectively.

Not all of the Ae. longissima accessions were available at the start of this investigation. For Experiment 1, starting in November 2013, 337 accessions were evaluated for agro-morphological traits in the greenhouse. These accessions were all donated by the ICCI, and the harvested seed was used for Experiment 2. For Experiment 2, starting in December 2014, 362 accessions were evaluated. This set included all of the ICCI accessions from Experiment 1 for which harvested seed was available, plus additional accessions received from IPK and the ICCI in a second shipment of germplasm.

2.2 Plant growth conditions Since Ae. longissima is a wild species, its seeds can carry undesirable dormancy. To break this dormancy and achieve uniform germination and emergence, 36

five seeds of each accession were first germinated on filter paper moistened with distilled water in 9-cm Petri dishes and incubated at 4°C for four (Experiment 1) or six (Experiment 2) weeks and then at room temperature (22-25°C) for one day. Germinated seeds were sown on December 12, 2013 and February 4, 2015 for Experiment 1 and Experiment 2, respectively. The three most robust germinating seeds of each accession were sown in plastic pots (10.5 x 10.5 x 8.9 cm; l x w x h) containing a 50:50 mixture of steam-sterilized native soil and plant growth medium (Sunshine MVP mix; Sungro Horticulture Distributors Inc., Agawam, MA). Plants were then grown in a greenhouse at the University of Minnesota Plant Growth Facility on the St. Paul campus at a day/night temperature of 25/17°C with supplemental lighting provided by 400-W high pressure sodium lamps, emitting between 300-400 μmol photons s -1 m-2 for 16 hours/day. After two weeks of growth, two of the plants were rogued out, leaving just one plant per pot for subsequent phenotypic evaluations. Optimal fertility was maintained for plants throughout the experiments. At planting, two fertilization treatments were applied: 0.3 g/pot of Osmocote 14-14-14 and approximately 40g/liter at 1/16 dilution of Peter’s Dark Weather 15-0-15 (Scott’s Company, Marysville, OH). Thereafter, approximately 40g/liter at 1/16 dilution of Peter’s 20-10-20 (Scott’s Company) was applied at weekly intervals until the plants were mature.

2.3 Agro-morphological trait assessment During the greenhouse increases of Ae. longissima , phenotypic assessments were made for eleven agro-morphological traits in two separate experiments. Experiment 1 was conducted from November 2013 to April 2014 and included 337 accessions. Experiment 2 was conducted from December 2014 to May of 2015 and included 362 accessions. The agro-morphological traits assessed included days to heading (DH), area of first seedling leaf (LA1), area of second seedling leaf (LA2), area of flag leaf (LAF), length of peduncle (LP), length of spike (LS), length of awn (LA), number of nodes (NN), number of spikelets (NS), plant height (PH), and 30

kernel weight (30KW). All assessments were made on the first (primary) tiller of one plant from each accession.

Days to heading were recorded as the number of days from planting to halfway emergence of the first spike from the flag leaf sheath. To calculate the areas of the first and second seedling leaves and flag leaves of maturing primary tillers, measurements were taken on the length (from base to very tip) and width (at widest part) of the respective leaf blades. The leaves of Ae . longissima roughly approximate a triangle; thus, the leaf areas were calculated by the following equation: Leaf Area (cm 2) = 0.5 x (Length (cm) x Width (cm)). Leaf area assessments of the first and second seedling leaves were taken after the latter was fully extended and the third leaf was beginning to emerge. Assessments of the flag leaves were taken after the spikes were fully emerged from the leaf sheaths. The length of the peduncle was measured from where it begins just above the flag leaf sheath up to the bottom of the basal spikelet in the spike. Spike length was measured from the bottom of the basal spikelet to the very top of the apical spikelet on the spike. In Ae. longissima , fully developed awns occur only on the apical spikelet and are mostly even in length. Awn length was measured on the longer of the two awns from the top of the apical spikelet to the very tip of the awn. The number of nodes was assessed from the base of the plant at the soil level to the flag leaf sheath on the primary tiller. Spikelet number was enumerated from the base to the top of the spike on the first tiller. Plant height was derived by summing the lengths of the following plant parts: a) primary tiller from soil level to flag leaf, b) peduncle, c) spike, and d) awn. Kernel weight was assessed on 30 arbitrarily selected seeds harvested from each accession.

2.4 Data analysis Data for the 11 agro-morphological traits were collated and analyzed separately for Experiment 1 and Experiment 2. This was done for three reasons: 1) not all of the same accessions were included in each test, 2) the accessions in the two experiments were vernalized for different durations: four vs. six weeks, respectively 38

and 3) the experiments were sown on different dates during the greenhouse season. To provide a general summary of the agro-morphological data, the mean, minimum, maximum, standard deviation (SD) and coefficient of variation (CV) were calculated (Table 2.2). Additionally, Pearson product-moment correlation coefficients were calculated among pairs of the 11 traits to assess the degree of relationship between them. To assess the proportion of variation for agro-morphological traits due to

2 genetic factors, heritability was estimated using the equation: H = V G/V P.

Spatial autocorrelation (SA) refers to the correlation of a variable with itself in space (GeoDa Center, GeoDa 1.6.7). To assess the degree of spatial autocorrelation for agro-morphological traits among Ae . longissima accessions at neighboring collection sites, global spatial autocorrelation was measured using Global Moran’s I in GeoDa. Values of Global Moran’s I provide an overall assessment of whether a measured variable follows a clustered, dispersed, or random pattern in space (ArcGIS 10.3.1; ArcGIS Resource Center, 2012). Spatial weights matrices were constructed and used to impose a neighborhood structure on the data to assess the extent of similarity between location sites and values. Neighbors were defined by a binary (0,1) and row-standardized spatial weights matrix in GeoDa (GeoDa Center). The indices of Global Moran’s I range from -1 to 1. When the index is positive and closer to 1, it indicates there is an overall pattern of similar phenotypic values being close together in space, i.e. high values at one site correlate with high values at neighboring sites (high-high relationship) or low values at one site correlate with low values at neighboring sites (low-low relationship). An index near 0 indicates a pattern of randomness for the measured phenotypic value. When the index is negative, it means there is an overall pattern of different phenotypic values being close together in space, i.e. high values at one site correlate with low values at a neighboring site (high-low relationship) and visa versa (low-high relationship) (GeoDa Center). Global Moran’s I is calculated from Moran’s I Index value, and then a pseudo p-value was derived for each Global Moran’s I using 999 permutations (GeoDa Center). To prepare data for this analysis, the raw agro-morphological trait values of accessions at each collection 39

site (ranging from 61 to 73 sites) within Israel were averaged to derive a single mean value that was calculated for each site. In ArcGIS (ArcGIS Resource Center, 2012), the accessions were geocoded to the coordinates provided in the World Geodetic System (WGS 1984). Then, the dataset was reduced to include only one mean value per pair of identical coordinates. The resulting shapefile of each variable was projected into the Israel Transverse Mercator (meters) for spatial analysis.

In addition to an overall assessment of clustering for phenotypic values in Ae . longissima as given by Global Moran’s I, we also investigated whether local clusters occurred in the dataset. Local Indicator of Spatial Association (LISA) (Anselin 1995) indicates the presence or absence of significant spatial clusters or outliers for each location. LISA maps are useful for assessing the hypothesis of spatial randomness and to identify local clusters. In the LISA analysis, a spatial weights matrix was generated for each variable using GeoDa, comparing each site to its nearest four neighbors. For each point in space, LISA gives an indication of significant spatial clustering of similar values.

To determine whether a particular climate parameter might be associated with individual agro-morphological traits of Ae . longissima accessions collected from different sites in Israel, linear regression was conducted with 16 BIOCLIM variables (Bio1-13, Bio15, Bio16, and Bio19 in Bioclim; http://www. worldclim.org/bioclim). BIOCLIM variables are derived from monthly temperature and rainfall data compiled using values from 1950 to 2000 to generate more biologically meaningful variables. Ordinary Least Squares (OLS) analysis was run between the agro-morphological traits and 16 climate variables. For this analysis, a spatial weights matrix was generated considering all points within 65 km as neighbors, thereby ensuring that every point had at least four neighbors. Models were first assessed for spatial dependence and then goodness of fit using the log-likelihood (LL), Akaike Information Criterion (AIC), and Schwarz Criterion model diagnostics (Akaike 1974; Edwards 1972; Schwarz 1978). These model diagnostics are used to compare standard OLS, spatially 40

lagged OLS, and spatial error OLS with each other. With respect to standard OLS, two sets of spatial diagnostics were examined to determine whether the model should be spatially lagged with respect to the dependent variable or if a spatial error term is needed. Spatial lag and spatial error models are two different ways to reduce the effect of the dependent values’ reliance on space, thereby showing the actual relationships between the dependent and independent variables. The spatial diagnostics (Lagrange Multipliers-the lag set and the error set) are used to assess an individual model's spatial dependence. A significant p-value for a Lagrange Multiplier set (non-robust and robust) indicates a poor fit for the standard OLS model; thus, the spatial lag or spatial error model is more appropriate. For selecting the best model for each of the dependent variables, the model with the p-value (alpha<0.05) for the independent variable was examined first and then compared with the aspatial diagnostics for LL, AIC, and Schwarz Criterion.

3. Results The raw data recorded for all of the agro-morphological traits of Ae. longissima from Experiments 1 and 2 are given in Appendix Table 2. Data summaries that include the mean, minimum and maximum values as well as corresponding standard deviations (SD) and coefficients of variation (CV) are presented in Table 2.2. A moderate to high level of variation was observed for all 11 agro-morphological traits based on the CV. Variation was greatest for leaf area (LA1, LA2 and LAF; CV range of 28.9-56.2%) and LP (CV range of 57.1-62.4%) and lowest for LS (CV range of 13.0-14.5%) and NS (CV range of 12.-13.2%)(Table 2.2). The largest magnitude difference between the minimum and maximum value for any of the individual traits was 136.2x for LP, 59.7x for LAF and 56.0x for LA1. In contrast, the smallest magnitude difference found was 2.1x for NS, 3.0x for NN and 2.9x for DH. The difference between the minimum and maximum values for all other traits was between 4.0x and 32.3x.

To assess the degree of association between pairs of the agro-morphological traits, Pearson product-moment correlations were applied to the data in Experiment 1 and in Experiment 2. Among the 55 pairs of comparisons made in Experiment 1, seven were significant (P = 0.05) and 13 were highly significant (P = 0.01) (Table 2.3). In Experiment 1, the largest coefficient found among pairs of traits was with LA1-LA2 (r 2 = 0.70), followed by NS-DH (r 2 =0.32), PH-NN (r 2 = 0.31), PH-NS (r 2 = 0.30) and PH-LA (r 2 = 0.29). In Experiment 2, 26 of 55 total pairs of comparisons were significant at either P = 0.05 or P = 0.01. As in Experiment 1, the largest coefficient found among pairs of traits was with LA1-LA2 (r 2 = 0.58). Many of the strongest associations (r 2 > 0.30) found among pairs of traits were with plant height: PH-LP with r 2 = 0.57, PH-NN with r 2 = 0.43, PH-LS with r 2 = 0.38, PH-DH with r 2 = 0.34 and PH-LA with r 2 = 0.33 (Table 2.3). However, strong associations (r 2 > 0.30) were also observed for LAF-DH (r 2 = -0.46), NN-DH (r 2 = 0.34), NN-LAF (r 2 = - 0.39), NS-DH (r 2 = 0.35), NS-LS (r 2 = 0.34), and 30KW-LA (r 2 = 0.38).

With respect to heritability, traits with the lowest values included LAF (0.037), LA (0.129), LS (0.145), LP (0.169), and 30KW (0.181), whereas those with the highest values include DH (0.871), NN (0.995), and NS (0.999). Heritabilities for the other traits were intermediate to these values ranging from 0.204 (LA2) to 0.553 (HP).

The null hypothesis for spatial autocorrelation as assessed by Global Moran’s I statistic is that values for agro-morphological traits of Ae. longissima are randomly distributed among collection sites in Israel (ArcGIS Resource Center, 2012). In Experiment 1, the null hypothesis was rejected in only three of the 11 cases involving these different traits: DH at P = 0.001 and NN and PH at P = 0.01 (Table 2.4). The highest level of spatial autocorrelation (i.e. clustering of accessions with similar values) found was with DH and NN, having Global Moran’s I values of 0.39 and 0.33, respectively. Values for PH (Global Moran’s I value = 0.29) also were significantly clustered. The results for Experiment 2 were markedly different than 42

those found in Experiment 1 as the null hypothesis was rejected (P = 0.05 to P = 0.001) in all but two cases: LS and 30KW (Table 2.4). Thus, for the other nine agro- morphological traits studied, significant clustering of accessions with similar phenotypic values was present. The highest level of spatial autocorrelation found was with PH, DH and NN, which had Global Moran’s I values of 0.56, 0.48 and 0.32, respectively. LA2, LP, and LA exhibited a moderate level of spatial autocorrelation, having Global Moran’s I values of 0.22, 0.21, and 0.20, respectively.

Ordinary Least Squares (OLS) analysis was used to assess the relationship between the agro-morphological traits of Ae. longissima and 16 climate parameters from BIOCLIM. From this analysis, the number of significant correlations (P < 0.05) found ranged from 0 (LA1 and PH in Experiment 1 and LAF in Experiment 2) to 15 (NS in Experiment 2) for the individual agro-morphological traits (Table 2.5). In Experiment 1, the agro-morphological traits of DH, NS, and NN were highly significantly (P = 0.01) correlated with 12, 11, and 10 BIOCLIM parameters, respectively. Other traits with many significant correlations included LAF (7 at P = 0.01 and 2 at P = 0.05) and LP (9 at P = 0.01 and 2 at P = 0.05). The results in Experiment 2 were similar to those in Experiment 1 in that DH and NS were again highly significantly (P = 0.01) correlated with most (12) of 16 BIOCLIM parameters. However, PH and LP also had many highly significant correlations (12 and 8, respectively) with the BIOCLIM variables. Other traits with four or more highly significant correlations with BIOCLIM variables included LA2, LS, LA, and NN.

For cases where highly significant correlations were found, the agro- morphological traits of DH, LP, NN, and NS were positively correlated with the precipitation variables of BIO13, BIO15, BIO16, and BIO19 in both experiments. The same trend was also observed for LA and PH in Experiment 2. Highly significant negative correlations were observed for LAF with BIO13, BIO15, and BIO16 in Experiment 1. Highly significant negative correlations were also found between many of the agro-morphological traits and temperature parameters in Experiment 2. In many 43

of these cases, DH, LS, NN and NS were negatively correlated with various temperature parameters. Other agro-morphological traits, while not always statistically significant, trended the same way with negative correlations.

4. Discussion

Aegilops longissima is recognized as a valuable reservoir of useful traits, but has not been utilized to any great extent for wheat improvement. In this study, I evaluated from 337 to 362 accessions of Ae. longissima for 11 agro-morphological traits in the greenhouse in two separate experiments. These traits included those related to yield (number of spikelets and 30 kernel weight), photosynthetic surface of plants (area of first, second and flag leaves), agronomy (plant height and heading date) and various morphological features (length of peduncle, spike, and awns as well as number of nodes). Most of these traits could enhance the productivity of wheat if the underlying genes could be mapped, tagged and successfully transferred. As an initial step toward cataloging such genes, the ALDIVCO will be subject to a genome- wide association study (GWAS). Genotype by sequencing will be used to generate single nucleotide polymorphic (SNP) markers across the genome, and then assessments will be made for statistical associations between the markers and agro- morphological traits. Although whole genome sequencing has not been done for Ae. longissima , a genome sequence does exist for the closely related species of Ae. sharonensis (Marcussen et al. 2014). Sequence data of significantly associated SNP markers will be BLASTED against Ae. sharonensis , whose sequence assembly has already been analyzed for proteins of gene models from annotated grass genomes.

Improvement of grain yield is the one of the primary objectives of crop breeding programs (Amini, Saeidi, and Arzani 2007). Kernel weight and number of spikelets per spike are two of many important traits contributing to overall grain yield (Sabaghnia et al. 2013; Zafar et al. 2004). Aegilops longissima may be particularly useful for enhancing wheat yields because Brody (1983) found it has the longest spikes and highest number of spikelets per spike among Aegilops species in section 44

Sitopsis. In this study, we identified several accessions (AEG-1263-9, AEG-1265-11, and AEG-1512-4) with high 30 kernel weights (>~0.6g) or spikelet numbers (>17) (AEG-1264-10, AEG-4161-2, AEG-5646-1, AEG-9614-2, and AEG-9615-3) that could be candidates for a wide crossing program with wheat (Appendix Table 2). Success in such an endeavor was achieved by Millet (2007), who described a gene in Ae. longissima that contributes to a higher grain weight than that found in wheat.

Increased leaf area (LA1, LA2, and LAF), and sometimes even awn length (LA) (Ba, Fu, and Bai 2010), can increase the photosynthetic capacity of a cereal plant, possibly leading to increased grain fill. While Ae. longissima has very narrow and short leaves in comparison to wheat, positive alleles for increased leaf area may be revealed when small chromosomal segments are introgressed into the genetic background of a cultivated wheat. In a classical study by Tanksley and McCouch (1997), positive alleles for increased fruit size, quality and red pigment color were successful transferred from wild tomato species with inferior phenotypes (i.e. small- fruited, poor yielding green and red fruited species) into adapted tomato breeding lines by the advanced backcross quantitative trait locus method. While this technique would be intrinsically more difficult to perform with Ae. longissima and wheat due to all of the barriers to hybridization and reduced chromosome pairing and recombination, it is a possible option for enhancing wheat.

Long peduncles were reported to be an important disease escape trait in wheat against leaf rust and Fusarium head blight (Borner et al. 2002; Sabaghnia et al. 2013). In this study, we identified three (AEG-1510-2, AEG-1512-4, and AEG-1879-7) accessions with exceptionally long peduncles (> 21cm). Although the genetic basis of peduncle length is not known nor how effective it might be in ameliorating disease, the cataloging of variation for the trait in Ae. longissima may be useful in the future.

Plant height can be a significant factor in the lodging of cereal crops. Shorter plants will generally lodge less than tall plants (Zafar et al. 2004). The development of 45

semi-dwarf wheat cultivars that are nitrogen responsive was a major breakthrough in plant breeding and contributed to the success of the Green Revolution (Zafar et al. 2004). Although Ae . longissima is one of the tallest species in Aegilops at ~50-120 cm (excluding awns), eight very short-statured (< 40 cm) accessions (AEG-20-9, AEG- 2893-30, AEG-2897-34, AEG-3507-30, AEG-8710-15, AEG-9573-0, AEG-122, and AEG-9647-1) were identified (Appendix Table 2) and could be sources of new semi- dwarfing genes for wheat.

Early maturing wheat cultivars have, in some environments, the advantage of escaping abiotic and biotic stresses and also facilitating a crop rotation system (Zafar et al. 2004; Amini et al. 2007). Yet many of the highest yielding cultivars are those with longer grain filling periods contributed by delayed heading times. In this study, an extremely wide range of heading times was observed in the ALDIVCO: from as few as 19 days after planting for accession AEG-2052-9 in Experiment 1 to as many as 92 days after planting for accessions AEG-1212-8 and AEG-1334-30 in Experiment 1 (Appendix Table 2). Depending on the goal of a wheat breeding program, the heading time could be pushed in either direction with the extreme diversity found for this trait in Ae . longissima . In general, accessions with the earliest heading times were from Negev desert of southern Israel, whereas those with the longest heading times were from the central and northern part of the country where temperatures are more moderate and rainfall higher. It follows that accessions from the desert area of the south might be early in their heading time due to the stress of higher temperatures and lack of rainfall.

The relationship between pairs of the agro-morphological traits were assessed using Pearson product-moment correlations in the two separate experiments. The highest correlation found for any pair of traits was between LA1 and LA2 in both experiments (r 2 = 0.70 and 0.58, respectively) (Table 2.3). This result is not surprising given that LA1 and LA2 represent the areas of two successive leaves forming on seedling plants. Many significant correlations were found with plant height in both 46

experiments and some had among the highest r 2 values recorded. The traits significantly correlated with height included days to heading (DH), area of first leaf (LA1), length of peduncle (LP), length of spike (LS) (Experiment 2 only), length of awn (LA), number of nodes (NN), and number of spikelets (NS). The lengths of the peduncle, spikes, and awns are all components of overall plant height as calculated in this study. Thus, it follows that these traits would be correlated with plant height (Table 2.3). In addition, the number of spikelets (NS) is a reflection, to some degree, of the length of spike and was also found significantly correlated with plant height in both experiments. The minimum and maximum number of nodes only ranged from 2 to 6 in Ae. longissima , yet the trait was significantly correlated with plant height in both experiments. It follows that a taller plant would have more nodes than a shorter one. Kernel weight is one trait that is used to assess potential yield in plants. Due to the low seed production of single Ae. longissima plants, assessments for kernel weight were done on only 30 seeds (30KW). No consistent correlations were found for 30KW across the two experiments. This may be due to the extremely low numbers of kernels assessed for this character.

Heritability estimates are useful for assessing the amount of genetic variation contributing to phenotypic traits (Wray & Visscher, 2008). In this study, extremely high heritabilities were found for the number of spikelets (NS) (0.999) and number of nodes (NN) (0.995). These two traits did not vary widely in their range of values and probably are not strongly influenced by environment. Days to heading (DH) (0.871) also had a high heritability despite having a wide range of phenotypic values. This was somewhat surprising given that the germplasm was subjected to different durations of cold treatment (four vs. six weeks for Experiment 1 and 2, respectively) and planting dates (December 12 vs. February 4 for Experiment 1 and 2, respectively). All of the remaining eight traits exhibited heritabilities less than 0.170, indicating the marked influence of the environment on phenotypes.

Global Moran’s I is a useful statistic for assessing the overall clustering of agro-morphological trait values in a dataset. In this study, significant clustering was observed in both experiments for the traits of days to heading (DH), number of nodes (NN) and plant height (PH) (Table 2.4). In Experiment 2, all other traits except for the length of spike (LS) and 30 kernel weight (30KW) were also significantly clustered. The clustering of these traits may be partly explained by the dispersal unit of Ae. longissima . In this species, the dispersal unit is the entire spike--minus the few bottom spikelets that remain attached to the culm. Given this dispersal unit and the large size of the Ae. longissima spike, one would expect spread over a short distance, thereby leading to clusters of plants with similar agro-morphological traits.

Correlation analyses between BIOCLIM data and those collected on the 11 agro-morphological traits may provide insights as to the important climatic factors contributing to the evolution of certain traits in Ae. longissima at its center of origin (Podger et al. 1990). The most highly significant and consistent negative correlations to the agro-morphological traits were with temperature seasonality (BIO4), maximum temperature of warmest month (BIO5), and temperature annual range (BIO7) (Table 2.5). The agro-morphological traits most correlated to the climate parameters were days to heading, numbers of nodes, number of spikelets, and plant height. In contrast, the most highly significant and consistent positive correlations of the traits were heading date, length of peduncle, length of awn, numbers of nodes, and plant height. The growth of grasses like Aegilops is favored by cool and moist weather conditions. Thus, one would expect negative correlations between these dependent variables (excluding heading date) and increasing temperature and positive correlations between the dependent variables and increasing moisture. With respect to days to heading, early heading is correlated with higher temperatures. This again is likely due to the stress of higher temperatures inducing earlier influorescence emergence. In contrast, increased precipitation would extend the vegetative period of plants thereby delaying heading date.

In summary, Ae. longissima is an exceptionally diverse species for many traits of value for wheat improvement. Unfortunately, it has rarely been used for such a purpose. The great advances in genomics over the past few years should open up the possibility for exploiting the allelic diversity of this important wheat wild relative.

Table 2.1. Collection sites and number of Aegilops longissima accessions used in the evaluation of agro-morphological traits. Collection Site Longitude Latitude Experiment 1 Experiment 2 Akko 35.08450 32.92989 8 10 Ashalim 34.67443 30.95645 10 8 Ashdod 34.70007 31.83610 4 4 Be'er Sheva 34.79576 31.25067 4 8 Be'er Sheva-Arad 31.26642 34.97110 1 1 Beit Lid 34.92786 32.33349 6 5 Ben Zakkay 34.72830 31.85664 9 7 Benaya 34.75259 31.84373 10 8 Berekhya 34.64611 31.66749 1 -- a Dimona 35.02579 31.06940 3 3 Dorot 34.64667 31.50744 -- 3 En Gev 35.64119 32.78367 6 5 Ge'alya Kubeiba 34.76632 31.88609 10 7 Gevar'am 34.61328 31.59199 10 9 Gilat 34.66168 31.33539 9 11 Giv'at Arnon 34.67285 31.6604 3 4 Giv'at Brenner 34.80263 31.86713 8 8 HaBesor 34.50523 31.23739 1 1 Hadera 34.92245 32.44402 11 11 HaNegev Junction 34.83688 31.06699 5 5 Herzliyya 34.84554 32.15992 1 -- Hevron -- -- 1 1 Horbat Allon 34.96300 32.45040 3 3 Ilanot 34.89945 32.28830 1 1 Kefar Menahem 34.83516 31.73211 8 9 Kefar Mordekhay 34.75688 31.83148 4 3 Kefar Yona 34.93412 32.31760 11 10 Liman 35.11188 33.05918 6 6 Mamshit 35.06349 31.02720 12 10 Mash'abbe Sade 34.75162 31.03082 6 6 Mash'abbe Sade -Retamim 34.70427 31.04970 1 1 Mefalsim 34.56179 31.50268 1 1 Megdar Farm 34.64875 31.35340 -- 1 Nahal Hatzatz 34.84066 30.89407 2 2 Nahal Liman 35.10566 33.05052 11 10

Nahal Oz 34.49776 31.47274 1 1 Nahal Solelim -Beersheba 34.74890 31.26755 -- 7 Nahal Zin 35.03710 30.83100 1 1 Nahariyya -Rosh HaNiqra 31.01853 34.62270 1 1 Nir'am 34.58058 31.51892 7 7 Nizzanim 34.63440 31.71838 8 8 Or -Haner 34.60631 31.55461 1 2 Pardes Hanna 34.93411 32.48272 2 2 Petah Tiqwa 34.88880 32.08345 5 5 Qiryat Ono 34.85893 32.05537 14 14 Qiryat Ono-Petah Tiqwa 34.87340 32.07012 3 3 Raffiah Yam 34.24458 31.32220 1 1 Ramat Aviv 34.80613 32.11241 5 2 Rehovot 34.81087 31.89447 10 9 Re'im 34.45913 31.38640 7 6 Revivim 34.81523 31.05056 1 1 Rishon LeZiyyon 34.81121 31.96003 2 1 Ruhama 34.70530 31.49821 1 -- Ruhama-Badlands 34.71153 31.49777 -- 2 Sde Boker 34.79345 30.87372 13 14 Shedema 34.74031 31.83360 14 13 Shedema-Benaya 34.74003 31.83927 9 8 Shefayyim 34.82245 32.21665 3 3 Shemuel Hospital 34.82426 31.93166 -- 1 Shirat HaYam 34.27177 31.36698 1 1 Shivta -Haluza 31.01853 34.62270 1 1 Shomrat 35.09515 32.95197 4 4 Tel Katifa 34.30480 31.36420 1 1 Tel Mond 34.91816 32.25665 8 7 Tel-Nof 34.78353 31.83983 1 1 Tifrah 34.68758 31.31092 -- 6 Tifrah2 34.68670 31.31678 -- 4 Tlalim 34.77135 30.99031 10 10 Yad Mordekhay 34.55750 31.58702 1 1 Yaqum 34.84211 32.24932 2 1 Yaziz -Gibton 34.86490 31.85339 3 2 Yeroham 34.87481 31.03196 4 7 Yeroham-Be'er Sheva 34.87794 31.02847 1 1 Dead Sea b -- -- 1 1 Jordan River b -- -- 1 1

Unknown Israel c ------13 Unknown Jordan d ------2 Unknown e -- -- 2 4 Total 337 362 aAccessions not included in the experiment. bCollection sites of accessions are from Jordan. cSpecific collection sites are not known for 13 accessions from Israel. dSpecific collection sites are not known for 2 accessions from Jordan. eThe country of origin is not known for 4 accessions.

Table 2.2. Mean, minimum, maximum, standard deviation (SD) and coefficient of variation (CV) values for 11 agro-morphological traits scored on 337 and 362 accessions of Aegilops longissima in Experiment 1 and Experiment 2 in the greenhouse, respectively. Trait Experiment Mean Minimum Maximum SD CV 1 60 32 92 9.6 16.1% Days to heading DH 2 45 19 77 8.7 19.5% 1 1.1 0.3 2.3 0.3 32.6% Area of first leaf (cm 2) LA1 2 0.7 0.0 1.7 0.3 35.4% 1 2.6 1.0 6.9 0.8 28.9% Area of second leaf (cm 2) LA2 2 1.3 0.3 2.9 0.4 32.6% 1 2.5 0.1 7.6 1.4 56.2% Area of flag leaf (cm 2) LAF 2 2.4 0.2 5.7 1.1 44.9% 1 9.0 0.3 35.4 5.1 57.1% Length of peduncle (cm) LP 2 7.5 0.0 26.0 4.6 62.4% 1 18.4 2.7 24.3 2.7 14.5% Length of spike (cm) LS 2 15.0 10.3 20.0 2.0 13.0% 1 7.6 2.3 14.3 2.2 28.6% Length of awn (cm) LA 2 7.7 2.0 12.5 1.9 24.4% 1 4 2 6 0.6 16.0% Number of nodes NN 2 4 2 6 0.6 17.0% 1 13 8 17 1.6 12.0% Number of spikelets NS 2 13 8 17 1.7 13.2% 1 74.7 30.7 122.4 15.4 20.6% Plant height (cm) PH 2 63.0 18.8 99.5 12.0 19.0%

1 0.22 0.13 0.42 0.06 28.9% 30 kernel weight (g) 30KW 2 0.27 0.13 0.58 0.07 25.5%

Table 2.3. Correlation coefficients among 11 agro-morphological traits evaluated on Aegilops longissima in the greenhouse. Parameters (Experiment 1) LA1 LA2 LAF LP LS LA NN NS PH 30KW DH 0.09 0.06 -0.09 0.10 0.01 0.14 0.25 0.32 0.24 0.04 LA1 -- 0.70 0.08 -0.08 0.04 0.02 0.12 0.06 0.15 0.05 LA2 -- -- 0.05 -0.09 0.07 0.04 0.05 0.07 0.12 0.03 LAF ------0.08 0.09 -0.14 0.01 -0.02 -0.09 -0.02 LP ------0.03 0.24 0.20 0.07 0.18 0.15 LS ------0.04 -0.12 0.03 -0.03 -0.08 LA ------0.14 0.18 0.29 0.13 NN ------0.16 0.31 0.04 NS ------0.30 -0.03 PH ------0.11

Values in italics are significant at P< 0.05, values underlined are significant at P< 0.01.

Parameters (Experiment 2) LA1 LA2 LAF LP LS LA NN NS PH 30KW DH 0.02 -0.09 -0.46 0.10 0.06 0.1 4 0.3 4 0.35 0.34 0.05 LA1 -- 0.58 0.00 0.05 0.14 0.05 0.06 0.09 0.17 0.22 LA2 -- -- 0.08 0.01 0.20 0.01 0.07 0.04 0.13 0.09 LAF ------0.05 0.13 0.07 -0.39 -0.17 -0.13 -0.01 LP ------0.02 0.18 0.09 0.14 0.57 0.12 LS ------0.01 0.03 0.3 4 0.38 -0.12 LA ------0.11 0.00 0.33 0.38 NN ------0.11 0.43 0.16 NS ------0.24 -0.06 PH ------0.27

Values in italics are significant at P< 0.05, values underlined are significant at P< 0.01.

Table 2.4. Spatial autocorrelation of agro-morphological trait values among Aegilops longissima accessions collected at neighboring sites in Israel as assessed by Global Moran’s I. Variable Number of sites Global Moran's I P-value Experiment 1 DH 67 0.39 <0.001 LA1 67 0 >0.1 LA2 67 0.01 >0.1 LAF 67 0.11 >0.05 LP 65 0.09 >0.05 LS 67 0.02 >0.1 LA 67 -0.02 >0.1 NN 67 0.33 <0.01 NS 65 -0.1 >0.05 PH 67 0.29 <0.01 30KW 52 -0.01 >0.05 Experiment 2 DH 72 0.48 <0.001 LA1 72 0.17 <0.05 LA2 72 0.21 <0.01 LAF 72 -0.05 <0.05 LP 68 0.2 <0.01 LS 70 0.12 >0.05 LA 71 0.22 <0.01 NN 72 0.32 <0.001 NS 70 0.17 <0.05 PH 72 0.56 <0.001 30KW 63 -0.01 >0.05

To prepare data for this analysis, the raw agro-morphological trait values of accessions at each collection site within Israel were averaged to derive a single mean value that was calculated for each site. In ArcGIS (ArcGIS Resource Center, 2012), the accessions were geocoded to the coordinates provided in the World Geodetic System (WGS 1984). Then, the dataset was reduced to include only one mean value per pair of identical coordinates. The resulting shapefile of each variable was projected into the Israel Transverse Mercator (meters) for spatial analysis.

Table 2.5. Ordinary Least Squares analysis between agro-morphological traits of Aegilops longissima and 16 bioclimatic variables. Experiment 1 Bioclimatic variables DH LA1 LA2 LAF LP LS LA NN NS PH 30KW BIO1 Annual Mean Temperature 1.92 0.005 -0.02 -0.002 -0.23 -0.43 0.11 0.07 -0.65 -15.29 0.02 Mean Diurnal Range (Mean of monthly (max -0.29 0.002 -0.005 0.04 -0.11 -0.05 -0.02 -0.01 -0.28 -0.09 0.0002 BIO2 temp - min temp)) BIO3 Isothermality (BIO2/BIO7) (*100) -0.32 0.04 0.02 0.19 -0.16 -0.19 0.05 0.02 0.82 -3.20 0.002 BIO4 Temp Seasonality (standard deviation *100) -0.01 0.00001 -0.0002 0.001 -0.004 -0.002 -0.0005 -0.001 -0.01 -0.01 <0.0001 BIO5 Max Temp of Warmest Month -0.18 0.004 -0.04 0.03 -0.09 -0.04 -0.15 -0.11 -3.54 -4.52 0.01 BIO6 Min Temp of Coldest Month 0.41 0.006 0.05 -0.03 0.09 * 0.10 0.27 0.01 1.02 -7.73 0.008 BIO7 Temp Annual Range (BIO5-BIO6) -0.20 0.0004 -0.04 0.02 -0.07 -0.03 -0.16 -0.01 -0.22 -0.13 0.0005 BIO8 Mean Temp of Wettest Quarter 0.20 0.01 0.05 -0.02 0.49 0.20 0.11 0.01 1.77 -7.91 0.006 BIO9 Mean Temp of Driest Quarter -1.08 0.001 -0.05 0.24 -0.09 -0.06 -0.09 -0.06 -0.54 -9.58 0.02 BIO10 Mean Temp of Warmest Quarter 0.07 0.01 -0.01 0.14 -0.62 -0.05 0.02 -0.01 -0.54 -12.58 0.02 BIO11 Mean Temp of Coldest Quarter 0.28 0.004 0.04 -0.03 0.85 0.05 0.23 0.01 -0.06 -9.72 0.009 BIO12 Annual Precipitation 0.03 0.0002 0.0005 -0.002 0.007 0.001 0.003 0.002 0.17 -0.03 <0.0001 BIO13 Precip of Wettest Month 0.11 0.0006 0.002 -0.007 0.02 0.002 0.01 0.01 0.17 -0.11 0.0001 BIO15 Precip Seasonality (Coefficient of Variation) 1.07 0.012 0.03 -0.08 0.22 0.05 0.09 0.05 1.43 -2.92 0.0001 BIO16 Precip of Wettest Quarter 0.04 0.0002 0.0009 -0.003 0.01 0.001 0.004 0.002 0.07 -0.05 <0.0001 BIO19 Precip of Coldest Quarter 0.05 0.0004 0.001 -0.003 0.01 0.001 0.004 * 0.002 0.07 -0.06 <0.0001

Values in italics are significant at P< 0.05, values underlined are significant at P< 0.01.

Experiment 2 Bioclimatic variables DH LA1 LA2 LAF LP LS LA NN NS PH 30KW BIO1 Annual Mean Temperature -1.22 0.002 -0.08 0.68 0.10 -0.39 -0.05 -0.05 -0.25 -0.35 0.02 Mean Diurnal Range (Mean of monthly -0.23 -0.00001 0.01 0.01 -0.07 -0.04 -0.02 -0.008 -0.44 -0.05 0.0002 BIO2 (max temp - min temp)) BIO3 Isothermality (BIO2/BIO7) (* 100) -0.64 0.04 0.09 1.68 -0.04 -0.07 0.012 0.05 -1.70 0.03 0.002 Temperature Seasonality (standard -0.007 -0.005 0.0001 -0.002 -0.002 -0.002 -0.0002 -0.0004 -0.01 -0.002 <0.0001 BIO4 deviation *100) BIO5 Max Temperature of Warmest Month -0.20 -0.01 0.01 -0.39 -0.55 -0.04 -0.09 -0.01 -0.33 -0.40 0.01 BIO6 Min Temperature of Coldest Month 0.20 0.002 -0.01 1.07 0.10 0.08 0.21 0.06 0.23 0.04 0.008 BIO7 Temperature Annual Range (BIO5 -BIO6) -0.15 -0.002 0.03 -0.54 -0.06 -0.02 -0.12 -0.007 -0.27 -0.03 0.0005 BIO8 Mean Temperature of Wettest Quarter 0.09 - -0.008 0.99 0.39 0.06 0.08 0.03 0.17 0.16 0.006 BIO9 Mean Temperature of Driest Quarter -0.23 -0.02 -0.03 -0.31 -0.27 -0.05 -0.35 -0.01 -0.43 -0.05 0.02 BIO10 Mean Temperature of Warmest Quarter -0.22 -0.02 -0.03 0.27 -0.16 -0.05 -0.14 -0.12 -0.40 -0.04 0.02 BIO11 Mean Temperature of Coldest Quarter 1.05 -0.02 -0.01 1.21 0.11 0.10 0.11 0.08 1.71 0.04 0.009 BIO12 Annual Precipitation 0.03 0.0001 0.0002 0.02 0.01 0.002 0.003 0.002 0.08 0.004 <0.0001 BIO13 Precipitation of Wettest Month 0.10 0.001 0.001 0.07 0.04 0.005 0.01 0.007 0.16 0.01 0.0001 Precipitation Seasonality (Coefficient of 0.90 0.01 0.005 0.72 0.30 0.06 0.08 0.05 1.49 0.14 0.0001 BIO15 Variation) BIO16 Precipitation of Wettest Quarter 0.04 - 0.0004 0.03 0.01 0.002 0.005 0.003 0.11 0.006 <0.0001 BIO19 Precipitation of Coldest Quarter 0.03 - 0.0004 0.02 0.02 0.003 0.005 0.003 0.07 0.006 <0.0001

Values in italics are significant at P< 0.05, values underlined are significant at P< 0.01.

Chapter 3

Diversity of Aegilops longissima for Resistance to Wheat Rust Pathogens

1. Introduction To keep pace with the burgeoning world population estimated to be ~9 billion by 2050, food production must be increased by about 40% above current levels (FAO 2009). Due to severe limitations for additional land and water resources globally, this increased food production will have to be met, in part, through greater productivity of new crop cultivars through breeding. Bread wheat ( Triticum aestivum L.) is one of the most important food crops in the world, supplying nearly one third of the calories consumed by humans (USDA ERA, 2015). Unfortunately, the crop is vulnerable to many diseases due, in part, to the narrowing of genetic diversity through polyploidization, domestication and years of intensive breeding. Of the major biotic threats to wheat production, the rust diseases rank among the most widely distributed and devastating. These rust diseases include: stem rust caused by Puccinia graminis Pers.:Pers. f. sp. tritici Eriks. & E. Henn., leaf rust caused by Puccinia triticina Eriks., and stripe rust caused by Puccinia striiformis Westend. f. sp. tritici Eriks. (Roelfs et al. 1992). In many wheat growing regions of the world, these rust diseases continue to be an important production constraint (Vikas et al. 2014). The average annual losses on a global scale are estimated at 6.20 million metric tonnes (value of $1.12 billion) for stem rust, 5.76 million metric tonnes ($1.03 billion) for leaf rust and 5.47 million metric tonnes ($979 million) for stripe rust (Y. Chai, personal communication; Pardey et al. 2013; Beddow et al. 2015).

Stem rust has historically been the most damaging rust disease of wheat in many parts of the world (Roelfs and Bushnell 1987). It is capable of completely destroying crops during severe epidemics, but yield losses ranging from 50 to 70% are more common (Roelfs et al. 1992). In the northern Great Plains of North America, deployment of resistant cultivars is the primary means of control. Early efforts at breeding stem rust resistant wheat cultivars were met with failure when virulent races of the pathogen emerged, causing spectacular epidemics in the mid-1930s and again in the mid-1950s (Ellis et al. 2014). Since these “boom and bust” cycles, stable stem rust resistance has been achieved in wheat cultivars for more than five decades (Singh 61

et al. 2011). This success is attributed to the incorporation of multiple effective genes in cultivars, eradication of the pathogen’s alternate host ( Berberis species), and diligent monitoring of new virulence types in the pathogen population (McIntosh et al. 1995).

Unfortunately, there is a new stem rust threat on the horizon in the form of widely virulent P. graminis f. sp. tritici races from Africa. The first described race of this unique virulence group was TTKSK (isolate synonym Ug99), discovered in Uganda in 1998 (Singh et al. 2011). Race TTKSK is a threat to food security because it is virulent on over 80% of the world’s wheat cultivars, including those carrying the widely deployed resistance gene Sr31 (Singh et al. 2011). The wide virulence of TTKSK for most of the deployed resistance genes in wheat is a great concern to breeders and pathologists, as is the potential for new virulence types to emerge within the “Ug99 lineage” of races. Indeed, thirteen variants are now recognized in the Ug99 lineage, including TTKSK, TTKSF, TTKST, TTTSK, TTKSP, PTKSK, PTKST, TTKSF+, TTKTT, TTKTK, TTHSK, PTKTK, and TTHST (Fetch et al. 2016; Patpour et al. 2015; Singh et al. 2015). This degree of pathogen variation makes breeding for stable stem rust resistance more complicated and difficult. Since its first discovery in Uganda, race TTKSK and variants in the Ug99 lineage have spread across eastern Africa, South Africa, Yemen, Egypt, and Iran (Singh et al. 2015). It may be only a matter of time before these virulent races reach other major wheat production areas.

More than 60 different genes for stem rust resistance have been described in wheat and its wild relatives (McIntosh et al. 1995; BGRI 2015). Most of them are classified as race-specific genes and confer a hypersensitive reaction in the host. Although a number of new genes have been described for resistance against TTKSK and its variants (Visser et al. 2011; Jin et al. 2008; Wanyera et al. 2006; Singh 2006; Njau et al. 2010), they will have to be strategically deployed in combination to attain the long-lasting resistance achieved in the past. 62

Leaf rust is the most common rust disease of wheat worldwide, causing more frequent epidemics than either stem or stripe rust (Bolton et al. 2008). The disease frequently causes yield losses ranging from 5 to 20%, but in severe epidemics losses up to 50% can occur (USDA-ARS, 2014). Yield losses result from a reduction in both the number of kernels per spike and also kernel weight, leading to overall lower test weights. Grain quality can also be affected, most notably the lowering of protein content by rust infection (Bolton et al. 2008). In the United States, P. triticina is variable with respect to its virulence on wheat, even without a functioning sexual cycle on the alternative hosts of Thalictrum speciosissimum (meadow rue) and Isopyrum fumaroides (a false rue anemone). Over 70 races of P. triticina are detected each year in surveys throughout the country (Kolmer et al. 2007). Most of the important P. triticina races in North America have either evolved through mutations in existing populations or migrated from other unknown areas (Huerta-Espino et al. 2011).

As with stem rust, the best means of controlling leaf rust is through the use of resistant cultivars. To date, over 75 leaf rust resistance genes have been described from bread wheat, durum wheat, and diploid wild wheat relatives (Bolton et al. 2008, USDA-ARS 2015). Combinations of the race-nonspecific adult plant resistance genes Lr34 and Lr46 confer durable resistance to leaf rust in wheat (Bolton et al. 2008). Lr34 was cloned and shown to be the same gene as Yr18 (for resistance to stripe rust), Sr57 (resistance to stem rust), Pm38 (resistance to powdery mildew) and Ltn1 (causing leaf tip necrosis) (Kolmer et al. 2008). Lr67 has similar characteristics to Lr34 in that it confers resistance to both leaf rust and stripe rust and controls the leaf tip necrosis phenotype (Spielmeyer et al. 2013).

Over the past two decades, stripe rust has increased in importance on wheat in the United States. The most stripe rust prone area of the country was historically in the Pacific Northwest where losses of 5 to 40% were common. In the large production 63

area of the southern and central Great Plains region, the disease was seldom reported (Chen 2007). This situation changed in the early 2000s when stripe rust became more frequent and started causing losses in Texas, Louisiana, Arkansas, and 28 other states (Wan and Chen 2014). These epidemics were due to a new strain of P. striiformis f. sp. tritici with additional virulence (on resistance genes Yr8 and Yr9 ), increased aggressiveness and a wider adaptation to warmer temperatures (Markell & Milus 2008; Milus et al. 2015). Since the emergence of this strain, estimated yield losses of 1.1 to 2.6 million metric tonnes occurred from 2001-2005 in the United States with a significant portion being from the Great Plains production area (Wan & Chen, 2014). The stripe rust pathogen is also variable with respect to virulence as more than 80 races have been identified since 2000 (Wan and Chen 2014). The five most predominant races in the United States are PSTv-37, PSTv-11, PSTv-14, PSTv-36, and PSTv-34 (Wan & Chen, 2014). Race PSTv-37 is distributed throughout the United States, while PSTv-11 and PSTv-14 are mostly restricted to states west of the Rocky Mountains, including California, Idaho, Montana, Oregon and Washington (Wan & Chen, 2014). PSTv-36 and PSTv-34 were detected in ten and seven states, respectively (Wan & Chen, 2014). The virulence spectrum of P. striiformis f. sp. tritici is extremely wide: race PSTv-18 is avirulent for all 18 Yr genes in the differential set, whereas PSTv-41 is virulent for 13 of the 18 (Wan & Chen, 2014). In 2010, barberry was identified as the alternate host of P. striiformis f. sp. tritici by Jin et al. (2010). Even though the sexual cycle on barberry may contribute to diverse virulence combinations in P. striiformis f. sp. tritici , the infection rate is very low on this alternate host under natural conditions (Zhao et al. 2016).

More than 70 stripe rust resistance genes have been described or provisionally described in wheat, the majority of which confer race-specific resistance (Li et al. 2011). Unfortunately, virulence for almost all of the race-specific resistance genes is known in P. striiformis f. sp. tritici . Only Yr5 and Yr15 are effective against all races identified in the United States (Li et al. 2011). For decades, successful control of stripe rust has been achieved in wheat cultivars carrying the additive genes of 64

Lr34 /Yr18 , Lr46 /Yr29 , and Yr30 as well as genes conferring race non-specific partial resistance in the Pacific Northwest region of United States (Milus et al. 2015).

The development of disease resistant cultivars is the preferred method of controlling rust diseases because it is environmentally benign, cost-effective, and also sustainable--if the resistance genes can be strategically combined (Dakouri et al. 2013). Efficient utilization of genetic resistance relies on an accurate and deep understanding of the rust resistance genes, their durability, and effectiveness in different environments (Dakouri et al. 2013). Therefore, the identification and characterization of new diverse sources of resistance is key to providing long-lasting disease control against the evolving rust populations (Vikas et al. 2014). Genetic diversity for disease resistance and other traits in the genomes of wheat can be augmented by exploiting the primary, secondary and tertiary genepools. The reservoir of rust resistance genes in the primary genepool has been extensively mined and utilized; thus, the secondary and tertiary genepools offer a potentially rich source of untapped resistance genes for wheat (Vikas et al. 2014).

The secondary genepool includes members of the genus Aegilops (except for Ae. tauschii ) that possess one genome in common with cultivated wheat, including the diploid Aegilops species of the section Sitopsis (Feuillet et al. 2007; Friebe et al. 1996; and Mclntosh 1991). This section of Aegilops includes the five species of Ae. bicornis (Forssk.) Jaub. & Spach (Spach goatgrass), Ae. longissima (proposed common name: Elongated goatgrass), Ae. searsii Feldman & Kislev ex. Hammer (Sears’ goatgrass), Ae. sharonensis Eig (Sharon goatgrass) and Ae. speltoides (Truncate goatgrass) carrying the S genome, which is closely related to the B genome of wheat (Kilian et al. 2007; van Slageren 1994). Species in section Sitopsis comprise a valuable reservoir of genetic diversity for many agronomic traits and disease resistance (Millet 2007). Indeed, a number of important resistance genes from the Sitopsis species have been transferred into cultivated wheat, including the stem rust resistance genes Sr32 , Sr39 , Sr47 (all from Ae. speltoides ) and Sr51 (Ae. searsii ); the 65

leaf rust resistance genes Lr28, Lr35, Lr36, Lr47, Lr51 (all from Ae. speltoides ) and Lr56 (Ae. sharonensis ); the stripe rust resistance gene Yr38 (Ae. sharonensis ); and the powdery mildew resistance genes Pm12 , Pm32 (both from Ae. speltoides ) and Pm13 (Ae. longissima ) (Millet 2007; Schneider et al. 2007; Liu et al. 2011; Klindworth et al. 2012).

Among the five Sitopsis species, Ae. longissima possesses resistance to many diseases, but has not been fully exploited for enhancing the resistance of wheat. For example, accessions of Ae. longissima are reported to carry resistance to stem rust (Anikster et al. 2005; Scott et al. 2014), leaf rust (Anikster et al. 2005), stripe rust (Anikster et al. 2005), powdery mildew (Ceoloni et al. 1988), Septoria glume blotch (Ecker et al. 1990), and eyespot (Sheng et al. 2012). The resistances described in Ae. longissima are of little practical use in breeding unless the underlying genes can be transferred into adapted wheat germplasm. In this regard, only the dominant powdery mildew resistance gene Pm13 has been successfully transferred into wheat (Ceoloni et al. 1988; Cenci et al. 1999; Donini, Koebner, and Ceoloni 1995). Another Ae. longissima introgression project aims to transfer eyespot resistance into wheat. To first elucidate the genetics of resistance in the diploid wild species, a segregating population was developed between a resistant and susceptible accession (Sheng, See, and Murray 2012). Four quantitative trait loci (QTL) were identified for O. yallundae eyespot resistance on Ae. longissima chromosomes 1S l, 3S l, 5S l, and 7S l and designated as Q.Pch.wsu-1S l, Q.Pch.wsu-3S l, Q.Pch.wsu-5S l, and Q.Pch.wsu-7S l, respectively (Sheng, See, and Murray 2012). Additionally, Sheng et al. (2014) identified three other QTL for O. acuformis eyespot resistance on chromosomes 1S l, 3S l, and 5S l designated as Q.Pch-oa.wsu-1S l, Q.Pch-oa.wsu-3S l, and Q.Pch-oa.wsu- 5S l, respectively.

As described above, Ae. longissima possesses great potential as a valuable source of resistance to the three rust diseases of wheat. Thus, the objective of this

study was to evaluate a diverse collection of Ae. longissima germplasm for resistance to stem rust, leaf rust and stripe rust at the seedling stage.

2. Materials and Methods 2.1 Plant materials The Ae. longissima Diversity Collection (ALDIVCO) was used for all rust evaluations in this study (Chapter 1). It consists of 433 accessions: 424 from Israel, four from Jordan and five from unknown sites (Table 3.1). Accessions from other countries (Egypt, Lebanon, and Syria) where the species is reported (Kimber & Feldman 1987; Millet 2007; van Salgeren 1994; Witcombe 1983) were not available for study. Israel encompasses the largest and most diverse populations of Ae. longissima across its entire habitat range. The 424 ALDIVCO accessions from Israel were collected from 76 ecogeographically diverse populations within the country where no more than 16 accessions were included from a single site (Fig. 3.1). The four accessions from Jordan were collected near the Dead Sea and the Jordan River. Finally, five other Ae. longissima accessions of unknown provenance were also included in the collection. Most (411 of 433) of the ALDIVCO accessions were donated by the Harold and Adele Lieberman Germplasm Bank in the Institute for Cereal Crops Improvement (ICCI) at Tel Aviv University (Tel Aviv, Israel) with the remaining ones donated by the Leibniz-Institut für Pflanzengenetik und Kulturpflanzenforschung (IPK) in Gatersleben, Germany. Passport data are available for all of the Israeli accessions provided by the ICCI, but not those from Jordan nor those donated by the IPK (Appendix Table 1).

For each of these later increase generations, the spikes were bagged to prevent cross- pollination and then a single seed was advanced. Although every effort was made to increase all 433 ALDIVCO accessions, some problems (e.g. poor plant growth, abnormal morphology, failure to flower, partial sterility, etc.) were encountered during their cultivation, resulting in low seed stocks. Thus, the total number of accessions included in any one rust evaluation ranged from 308 to 379 accessions (Appendix Table 3).

Susceptible controls were included in each experiment to monitor the infection level (density of uredinia on leaves) and virulence (maximum uredinial size) of the pathogen races. Wheat cultivars McNair 701 (Cltr 15288), Thatcher (Cltr 10003) and Morocco (PI 431591) were the susceptible controls for the stem rust, leaf rust and stripe rust evaluations, respectively. Additionally, the respective wheat differential lines also were included in the experiments to confirm the identity and purity of races of P. graminis f. sp. tritici , P. triticina , and P. striiformis f. sp. tritici (Roelfs and Martens 1988; Long and Kolmer 1989; Wan and Chen 2014). Resistant lines within the respective differential wheat sets served as the resistant controls.

2.2 Plant growth conditions Since Ae. longissima is a wild species, its seeds can carry undesirable dormancy. To break this dormancy and achieve uniform germination and emergence, five seeds of each accession were first germinated on filter paper moistened with distilled water in 9-cm Petri dishes and incubated at 4°C for five days and then at room temperature (22-25°C) for one day. After this treatment, three seeds of each accession were sown in plastic cones (3.8 cm in diameter by 21 cm in depth) or peat pots (7 x 7 x 9 cm, l x w x h) containing a 50:50 mixture of steam-sterilized native soil and plant growth medium (Sunshine MVP mix; Sungro Horticulture Distributors Inc., Agawam, MA). For convenience in handling, the cones and peat pots were set into trays holding 98 and 16 units, respectively. Plants sown in cones and slated for evaluation with stem rust race TTTTF, both leaf rust races and the stripe rust race 68

were grown in a greenhouse on the St. Paul campus at the University of Minnesota. Plants sown in peat pots were grown in a Biosafety Level-3 (BSL-3) containment greenhouse on the St. Paul campus and evaluated to the widely virulent P. graminis f. sp. tritici race TTKSK. The greenhouse was maintained at a day/night temperature of 25/17°C with supplemental lighting provided by 400W high pressure sodium lamps, emitting between 300-400 μmol photons s -1 m-2 for 16 hours/day. In the BSL-3 containment greenhouse, a day/night temperature of 22/19°C was maintained with a 14-h photoperiod provided by 400W high pressure sodium lamps emitting a minimum of 300 μmol photons s -1 m-2.

Four fertilization treatments were applied to plants during the course of the rust phenotyping experiments: two at planting (0.3 g/pot of slow-release Osmocote 14-14-14 and approximately 40g/liter at 1/16 dilution of Peter’s Dark Weather 15-0- 15; Scott’s Company, Marysville, OH) and two additional ones (approximately 40g/liter at 1/16 dilution of Peter’s 20-10-20; Scott’s Company, Marysville, OH) at weekly intervals until the plants were scored.

2.3 Pathogen isolates 2.3.1 Puccinia graminis f. sp. tritici Two races of P. graminis f. sp. tritici were used in the evaluation of the Ae . longissima panel (Table 3.2). Race TTTTF (isolate 02MN84A-1-2) was selected because it is the most widely virulent race reported in the United States, producing high infection types on all but Sr24 and Sr31 in the 20 line wheat stem rust differential set (Zhang et al. 2014). Isolate 04KEN156/04 of race TTKSK was also included in the experiment because it possesses the same virulence spectrum as the original P. graminis f. sp. tritici isolate Ug99 first found in Uganda (Jin et al. 2008; Njau et al. 2010). Use of races TTTTF and TTKSK facilitated the identification of resistance that is effective against widely virulent domestic and foreign stem rust races.

2.3.2 Puccinia triticina Two races of Puccinia triticina were used to assess the reaction of the Ae . longissima panel to leaf rust (Table 3.2). Race BBBD (isolate JAK) has the narrowest virulence spectrum of races held in the USDA-ARS Cereal Disease Laboratory collection and therefore has the potential to detect the presence of many resistance genes in Ae. longissima . In contrast, race THBJ (isolate 99ND588DLL) has a much wider virulence spectrum than BBBD and is one of the most common races found in the Great Plains region of the United States. The contrasting virulence spectra of these races will facilitate the identification of different resistances in the Ae. longissima germplasm.

2.3.3 Puccinia striiformis f. sp. tritici Race PSTv-37 of P. striiformis f. sp. tritici was selected for the stripe rust evaluation because it is the most predominant virulence type found in the United States (Table 3.2). It possesses virulence on 10 of the 18 lines in the stripe rust differential set (Wan & Chen 2014) and will identify Ae. longissima accessions with effective resistance against the most common P. striiformis f. sp. tritici race in the country.

Virulence phenotypes of races of all three rust pathogens were verified on the respective differential sets (Long & Kolmer 1989; Roelfs & Martens 1988; Wan & Chen 2014) and then increased in isolation to produce sufficient inoculum for all experiments. Races of P. graminis f. sp. tritici were increased on the susceptible cultivar McNair 701, those of P. triticina on Thatcher, and the one of P. striiformis f. sp. tritici on Morocco. Mass collections of urediniospores from the susceptible hosts were made using a specialized cyclone collector (Roelfs, et al. 1992) attached to a small shop vacuum (1,103 kW). After collection, urediniospores of the respective rusts were desiccated inside a 20% relative humidity chamber for seven days at 21 to 23°C (stem and leaf rust) or at 4°C (stripe rust). Desiccated urediniospores were then

placed in size 00 gelatin capsules (Gallipot, Inc., St. Paul, MN) set inside cryovials (Corning Inc., Corning, NY) and stored at -80°C in a freezer under needed.

2.4 Inoculation protocol and infection/incubation period Rust inoculations were made according to the standard protocols used at the USDA-ARS Cereal Disease Laboratory and the University of Minnesota. On the day before inoculation, urediniospores of the rust pathogens were removed from the -80°C freezer, heat-shocked in a 45°C water bath for 15 min, and then rehydrated in an 80% relative humidity chamber overnight. To assess the viability of infective propagules, the urediniospore suspension (~1 mg of urediniospores in 700 μl of lightweight mineral oil carrier Soltrol 170; Phillips Petroleum, Bartlesville, OK) was sprayed onto a Petri plate containing 2% water agar and incubated for 16 hours in the dark at 22- 25°C. Germination rate was assessed by observing 100 urediniospores from random fields under a compound microscope. Urediniospores were considered viable if they produced a germ tube extending more than half the length of its long axis.

After the germination rate assessment, 10 mg of urediniospores were placed into individual gelatin capsules (size 00) to which 700 μl of the oil carrier was added. The inoculum suspension was applied to 12-day-old plants (second leaf fully expanded) using special atomizers (Tallgrass Solutions, Inc., Manhattan, KS) pressured by a pump set at 25-30 kPa. Approximately 0.15 mg of urediniospores were applied per plant. Immediately after inoculation, the plants were placed in front of a small electric fan for 3–5 minutes to hasten evaporation of the oil carrier from leaf surfaces. Plants were held for an additional 90 minutes to allow the oil carrier to completely evaporate before placing them inside mist chambers. Inside the mist chambers, ultrasonic humidifiers (Vick’s model V5100NSJUV; Proctor & Gamble Co., Cincinnati, OH) were run continuously for 30 minutes to provide sufficient initial moisture for the germination of urediniospores. For the next 16-20 hours, plants were kept in the dark and the humidifiers run for 2 minutes every 15 minutes to maintain moisture on the plants. For experiments with the stem rust pathogen, light (490W 71

emitting 300 μmol photon s -1 m-2) was provided for 2 to 4 hours after the dark period to induce the final stages of the infection process, i.e. formation of penetration pegs. Then, the chamber doors were opened half-way to allow the leaf surfaces to dry completely before returning the plants to the greenhouse under the same conditions described above.

The inoculation/incubation protocols used for leaf rust were the same as described for stem rust with two modifications: (i) the concentration of inoculum applied to plants was approximately 0.033 mg urediniospores per plant and (ii) no light was provided during the final stages of infection by P. triticina . Protocols for stripe rust were the same as described for leaf rust, except that for the infection period, plants were placed inside a dew chamber at 10°C and 100% RH for 24 h. Thereafter, for the incubation period, plants were moved into a growth chamber with a diurnal temperature cycle gradually changing from 10°C at 0200 hours to 15°C at 1400 hours with a 16-h photoperiod of 300 μmol photon s -1 m-2.

2.5 Disease assessment All rust phenotyping experiments were conducted in a completely randomized design and repeated at least once over time. Accessions exhibiting variable reactions across experiments were repeated in an additional experiment, if sufficient seeds were available. The disease evaluation tests were performed between the months of August to November in 2015.

Stem and leaf rust infection types (ITs) on the ALDIVCO accessions were scored 12 days after inoculation using a 0 to 4 scale (Stakman et al. 1962). In this scale, IT 0 is assigned when no uredinia or other macroscopic signs of infection are present; IT ; is assigned when hypersensitive necrotic or chlorotic flecks of varying size are present, but not uredinia; IT 1 is assigned when small uredinia often surrounded by chlorosis or necrosis are present; IT 2 is assigned when small to medium uredinia often surrounded by chlorosis or necrosis are present; IT 3 is 72

assigned when medium-sized uredinia without chlorosis or necrosis are present; and IT 4 is assigned when large uredinia without chlorosis or necrosis are present. If more than one IT was observed on the leaves of an individual accession, the final IT score was recorded with the most common IT listed first followed by the next most common IT. When uredinia were larger or smaller than those classically described for the ITs, a “+” or “-” sign was added, respectively. When distinct necrotic or chlorotic areas surrounded uredinia, a notation of “n” or “c”, respectively, was included after the IT.

Due to the slower development of the stripe rust pathogen in wheat, ITs were scored 19 days after inoculation. ITs were scored based on the 0 to 9 scale developed by Wan and Chen (2014). IT 0 is assigned to plants with no visible rust infection; IT 1 is assigned to plants with necrotic or chlorotic flecks; IT 2 is assigned to plants with necrotic or chlorotic blotches or stripes without sporulation; and ITs 3 to 6 are assigned to plants with necrotic or chlorotic blotches or stripes with uredinial sporulation ranging from a trace to moderate. IT 7 is assigned to plants with necrotic or chlorotic blotches or stripes with abundant uredinial sporulation; IT 8 is assigned to plants having abundant uredinial sporulation associated with underlying chlorosis; and IT 9 is assigned to plants having abundant uredinial sporulation with no necrosis or chlorosis.

2.6 Data analysis For the summary of stem rust and leaf rust phenotype data, raw ITs were divided into two general reaction classes: resistant (ITs ranging from 0 to 2+) and susceptible (ITs ranging from 3- to 4). Similarly, stripe rust ITs ranging from 0 to 6 were classified as resistant and those from 7 to 9 as susceptible. Accessions were classified as heterogeneous if they included both resistant and susceptible plants. The percentage of accessions giving resistant, susceptible, and heterogeneous reactions to each rust race was calculated and presented in Table 3.3.

Phenotypic diversity for rust reaction in Ae. longissima was estimated using the Shannon information index hs = -Σp i ln(p i) with maximum hs = 1.099 (Fetch et al.

2003). Shannon’s diversity index ( hs) was determined based on the frequency (p i) of the three general reaction classes of resistant, heterogeneous, and susceptible (Fetch et al. 2003; Shannon 1948). The diversity of disease phenotypes was classified by values of Shannon’s equitability Eh = hs/hmax (Olivera et al. 2007). Lower values of the Shannon equitability statistic indicate less diversity, while higher values indicate more diversity. Values of Shannon’s equitability Eh higher than 0.85 were considered indicative of high diversity, 0.85 to 0.50 of intermediate diversity, and less than 0.50 of low diversity (Olivera et al. 2007).

Spatial autocorrelation (SA) refers to the correlation of a variable with itself in space (GeoDa Center, GeoDa 1.6.7). To assess the degree of spatial autocorrelation for rust phenotypes among Ae . longissima accessions at neighboring collection sites, global spatial autocorrelation was measured using Global Moran’s I in GeoDa. Values of Global Moran’s I provide an overall assessment of whether a measured variable follows a clustered, dispersed, or random pattern in space (ArcGIS 10.3.1; ArcGIS Resource Center, 2012). Spatial weights matrices were constructed and used to impose a neighborhood structure on the data to assess the extent of similarity between location sites and values. Neighbors were defined by a binary (0,1) and row- standardized spatial weights matrix in GeoDa (GeoDa Center). The indices of Global Moran’s I range from -1 to 1. When the index is positive and closer to 1, it indicates there is an overall pattern of similar phenotypic values being close together in space, i.e. high values at one site correlate with high values at neighboring sites (high-high relationship) or low values at one site correlate with low values at neighboring sites (low-low relationship). An index near 0 indicates a pattern of randomness for the measured phenotypic value. When the index is negative, it means there is an overall pattern of different phenotypic values being close together in space, i.e. high values at one site correlate with low values at a neighboring site (high-low relationship) and visa versa (low-high relationship) (GeoDa Center). Global Moran’s I is calculated 74

from Moran’s I Index value, and then a pseudo p-value was derived for each Global Moran’s I using 999 permutations (GeoDa Center). To prepare data for this analysis, the raw rust IT values of accessions at each collection site (ranging from 61 to 73 sites) within Israel were averaged to derive a single mean value that was calculated for each site. In ArcGIS (ArcGIS Resource Center, 2012), the accessions were geocoded to the coordinates provided in the World Geodetic System (WGS 1984). Then, the dataset was reduced to include only one mean value per pair of identical coordinates. The resulting shapefile of each variable was projected into the Israel Transverse Mercator (meters) for spatial analysis.

To determine whether a particular climate parameter might be associated with individual rust phenotypes of Ae . longissima accessions collected from different sites in Israel, linear regression was conducted with 16 BIOCLIM variables (Bio1-13, Bio15, Bio16, and Bio19 in Bioclim; http://www. worldclim.org/bioclim). BIOCLIM variables are derived from monthly temperature and rainfall data compiled using values from 1950 to 2000 to generate more biologically meaningful variables. Ordinary Least Squares (OLS) analysis was run between the rust phenotype data and 16 climate variables. For this analysis, a spatial weights matrix was generated considering all points within 65 km as neighbors, thereby ensuring that every point had at least four neighbors. Models were first assessed for spatial dependence and 75

then goodness of fit using the log-likelihood (LL), Akaike Information Criterion (AIC), and Schwarz Criterion model diagnostics (Akaike 1974; Edwards 1972; Schwarz 1978). These model diagnostics are used to compare standard OLS, spatially lagged OLS, and spatial error OLS with each other. With respect to standard OLS, two sets of spatial diagnostics were examined to determine whether the model should be spatially lagged with respect to the dependent variable or if a spatial error term is needed. Spatial lag and spatial error models are two different ways to reduce the effect of the dependent values’ reliance on space, thereby showing the actual relationships between the dependent and independent variables. The spatial diagnostics (Lagrange Multipliers-the lag set and the error set) are used to assess an individual model's spatial dependence. A significant p-value for a Lagrange Multiplier set (non-robust and robust) indicates a poor fit for the standard OLS model; thus, the spatial lag or spatial error model is more appropriate. For selecting the best model for each of the dependent variables, the model with the p-value (alpha<0.05) for the independent variable was examined first and then compared with the aspatial diagnostics for LL, AIC, and Schwarz Criterion.

3. Results Uniform infection was obtained on all of the susceptible controls and Ae. longissima accessions to each of the rust pathogens. Additionally, the ITs exhibited by each accession to the respective pathogen races were, in most cases, similar between the two experiments conducted sequentially over time. In the few cases where the ITs were divergent, a third experiment was conducted to yield a consensus phenotype. The complete set of raw IT data for the Ae. longissima accessions are given in Appendix Table 3.

3.1 Resistance to Puccinia graminis f. sp . tritici A wide range of ITs (from 00; to 4) was observed in the Ae. longissima collection to stem rust (Figs. 3.2 & 3.3; Appendix Table 3). The percentage of resistant accessions varied greatly to the two races of P. graminis f. sp . tritici : over 76

80% were resistant to race TTKSK compared to only 18.2% to race TTTTF (Table 3.3). Among the accessions classified into the general category of resistance, 30.3% and 5.8% exhibited highly resistant ITs (0 to 0;) in response to races TTKSK and TTTTF, respectively (Appendix Table 3). The percentage of heterogeneous accessions (i.e. those with both resistant and susceptible plants) ranged from 4.2% to race TTKSK to 17.7% to race TTTTF (Table 3.3). Fifty-five accessions (22.4%) exhibited resistance to both races of P. graminis f. sp . tritici (Appendix Table 3).

The level of diversity for stem rust phenotypes as given by Shannon equitability values differed markedly to races TTKSK (0.54) and TTTTF (0.82) (Table 3.3).

3.2 Resistance to Puccinia triticina As in the stem rust evaluations, accessions in the ALDIVCO exhibited a wide range of ITs to P. triticina : from 0; to 3+4 to race THBJ and from 00; to 3+4 to race BBBD (Figs. 3.4 & 3.5; Appendix Table 3). The percentage of resistant accessions to the two races of P. triticina was comparable at 65.9% for THBJ and 52.2% for BBBD (Table 3.3). Among the accessions classified as resistant, 5.6% and 10.1% exhibited the highly resistant ITs of 0 to 0; to the respective races (Appendix Table 3). The percentage of accessions exhibiting heterogeneous reactions was 13.9% to race THBJ and 18.5% to race BBBD (Table 3.3). One hundred and forty-nine accessions (45.8%) exhibited resistance to both races of P. triticina (Appendix Table 3).

The level of diversity for leaf rust phenotypes as given by Shannon equitability values were 0.79 for race THBJ and 0.92 for race BBBD (Table 3.3).

3.3 Resistance to Puccinia striiformis f. sp . tritici ALDIVCO accessions exhibited the full range of ITs (1 to 9) to P. striiformis f. sp. tritici race PSTv-37 (Fig. 3.6; Appendix Table 3). Half (50.1%) of the Ae. longissima collection was resistant to race PSTv-37 (Table 3.3), and of this group 77

42.5% exhibited highly resistant ITs of 0 to 2 (Appendix Table 3). The percentage of accessions showing heterogeneous reactions to P. striiformis f. sp. tritici was low at 6.6%.

The Shannon equitability value was 0.81 for ALDIVCO accessions infected with P. striiformis f. sp. tritici (Table 3.3).

The Ae. longissima accessions displayed different combinations of resistance to the three rust pathogens. Ten (3.9%) accessions (AEG-683-23, AEG-725-15, AEG- 803-49, AEG-1274-20, AEG-1276-22, AEG-1471-15, AEG-1475-19, AEG-2974-0, AEG-4005-20, and AEG-8705-10) were resistant to all races of the three rust pathogens tested in this study; 21 (8.2%) were resistant to both races of P. graminis f. sp . tritici and both races of P. triticina ; 18 (6.3%) were resistant to both races of P. graminis f. sp. tritici and P. striiformis f. sp. tritici ; and 86 (26.7%) were resistant to both races of P. triticina and P. striiformis f. sp. tritici . In contrast, only three (1.2%) accessions (AEG-5002-5, AEG-8770-25, and AEG-9654-8) were susceptible to all of the three pathogens (Appendix Table 3).

Although the number of Ae. longissima accessions collected from different sites within Israel was quite variable, distinct differences in the geographic distribution of resistance and susceptibility were noted for some rust races. For example, to P. graminis f. sp. tritici race TTKSK, there was a clear concentration of resistance in central and northern Israel and a concentration of susceptibility in the south (Fig. 3.7). The concentration of susceptible accessions in the south generally coincided with lower rainfall (<600 mm). The reverse trend was observed with respect to P. striiformis f. sp. tritici race PSTv-37 where resistance was clearly concentrated in southern Israel and susceptibility in central Israel and to some extent in the northern part of the country (Fig. 3.8). No clear geographical trends were observed in response to the other rust pathogens (Appendix Figs. 1, 2 and 3).

3.4 Spatial autocorrelation analysis based on Global Moran’s I The null hypothesis for spatial autocorrelation as assessed by Global Moran’s I statistic is that the rust phenotypes of Ae. longissima accessions are randomly distributed among the collection sites in Israel. In four of the five cases involving the different rust races (all except race BBBD), the null hypothesis was rejected as the p- values were statistically significant at P < 0.05 or P < 0.01 (Table 3.4). The highest level of spatial autocorrelation (i.e. clustering of accessions with similar rust phenotypes) found was with the two races of P. graminis f. sp. tritici , both with a Global Moran’s I value of 0.42. The next highest value of Global Moran’s I (0.34) was observed for P. striiformis f. sp. tritici , again indicating a high degree of clustering of accessions with similar rust phenotypes. Finally, a moderate degree of clustering was observed for P. triticina rust phenotypes with races THBJ and BBBD having Global Moran’s I values of 0.19 and 0.12, respectively. However, as mentioned above, the null hypothesis was not rejected with respect to the data for race BBBD.

3.5 Simple linear regression analysis of rust phenotypes and climate data Ordinary Least Squares (OLS) analysis was used to assess the relationship between the rust phenotypes of Ae. longissima and 16 climate parameters from BIOCLIM. From this analysis, the number of significant correlations (P < 0.05 or P < 0.01) found ranged from 1 ( P. triticina race BBBD) to 12 ( P. graminis f. sp. tritici race TTTTF) for the individual rust races (Table 3.5). Positive correlations indicate that higher rust ITs (i.e. more susceptible reactions) are correlated with higher values for the climatic variables and negative correlations indicate that higher rust ITs are correlated with lower values for the climatic variables. Twelve of 16 BIOCLIM parameters were highly significantly (P < 0.01) or significantly correlated (P < 0.05) with the rust phenotypes to P. graminis f. sp. tritici race TTTTF. All of the climatic variables related to precipitation (BIO12, BIO13, BIO15, BIO16, and BIO19) were negatively correlated with the higher rust ITs. In contrast, most of those related to temperature (BIO2, BIO4, BIO7 and BIO10) were positively correlated with higher 79

rust ITs, the exceptions being BIO6 and BIO8. For P. graminis f. sp. tritici race TTKSK, the results were very similar to those found for race TTTTF with respect to the number and direction of significant correlations. The only exceptions were that BIO5 and BIO9 were significant with race TTKSK and not TTTTF and that BIO8, BIO10 and BIO11 were significant with race TTTTF and not TTKSK (Table 3.5). The number of BIOCLIM parameters significantly (P<0.05) associated with the P. triticina rust phenotypes differed markedly to the two tested races. To race THBJ, rust phenotypes were significantly or highly significantly correlated (P < 0.05 or P < 0.01) with 11 of the 16 BIOCLIM parameters. Highly significant positive (P<0.01) correlations were found for the four temperature (BIO4, BIO5, BIO9, and BIO10) variables and highly significant negative correlations were found for the two precipitation (BIO12 and BIO19) variables. Other temperature and precipitation variables followed these same trends but were only significant at P < 0.05. In contrast, the rust phenotypes to race BBBD were only significantly correlated (P < 0.05) with one BIOCLIM variable: BIO6 (Table 3.5). To P. striiformis f. sp. tritici race PSTv- 37, rust phenotypes were significantly (P < 0.05) or highly significantly (P < 0.01) correlated with 10 of the 16 BIOCLIM parameters. In contrast to the negative correlations found between higher stem/leaf rust ITs and precipitation variables, the direction of the correlation for stripe rust was positive (Table 3.5). Similar contrasting correlation directions were observed for many of the temperature variables with respect to stripe rust vs. stem and leaf rust ITs.

4. Discussion Virulence changes in P. graminis f. sp. tritici , P. triticina , and P. striiformis f. sp. tritici present one of the greatest challenges for achieving durable control of rust diseases in wheat. When single resistance genes are deployed in widely grown cultivars, rust pathogens can easily overcome these resistances through single mutations, leading to widespread epidemics. The repeated practice of this gene deployment scheme has been unnecessarily wasteful of the finite number of resistance genes available in the primary genepool of wheat. As the reservoir of these readily 80

accessible resistance genes becomes depleted, the secondary and tertiary genepools have gained increasing importance as sources of new resistance. Aegilops longissima is a member of the secondary genepool of wheat and is vastly under utilized as a source of disease resistance genes. In this study, a diverse collection of Ae. longissima accessions, mostly from Israel, was evaluated for resistance to the three rust diseases of wheat at the seedling stage. The results clearly demonstrated that Ae. longissima is a rich and diverse source of resistance to the stem, leaf and stripe rust diseases. With respect to TTKSK, the original virulence type of the Ug99 lineage of African P. graminis f. sp. tritici races, over 80% of the Ae. longissima accessions were resistant (Table 3.3) with nearly one third of these resistant accessions exhibiting very low ITs of 0 or 0; (Appendix Table 3). As expected, the high frequency of resistance found for Ae. longissima to race TTKSK in this study (80.2%) was very similar to that found by Scott et al. (2014) (84%), who screened many of the same accessions of the ALDIVCO in their stem rust evaluations of ten Aegilops species. They also reported a high frequency of resistance (97%) in these same Ae. longissima accessions to two other races in the Ug99 lineage: TTKST and TTTSK. These combined results demonstrate the great potential of Ae. longissima as a source of new resistance genes against the Ug99 lineage of P. graminis f. sp. tritici races. A comparable high frequency of resistance (~70%) to race TTKSK was also reported for the closely related species of Ae . sharonensis by Olivera et al. (2007). In contrast to the race TTKSK results, the frequency of resistance to the widely virulent domestic race of TTTTF found in this study was markedly lower at just 18.2% (Table 3.3), indicating strong race-specificity of stem rust resistance genes in Ae. longissima . On the 20 wheat lines used for differentiating virulence types of P. graminis f. sp. tritici , race TTTTF carries virulence for two additional resistance genes ( Sr36 and SrTmp ) than TTKSK, while the latter carries just one unique virulence ( Sr31 ) not present in the former race (Table 3.2). It is apparent that many accessions of Ae. longissima with resistance to race TTKSK lack the ability to detect the avirulence effectors present in the American race TTTTF and are susceptible.

From the leaf rust evaluations, moderately high frequencies of resistance were found in Ae. longissima after challenge with races THBJ (65.9%) and BBBD (52.2%) (Table 3.3). Additionally, accessions exhibiting highly resistant ITs were nearly twice as common with the former race (10.1%) than the latter race (5.6%). Race THBJ possesses virulence for eight additional leaf rust resistance genes ( Lr1 , Lr2a , Lr2c , Lr3a , Lr16 , Lr26 , Lr10 , Lr14a , and Lr18 ) than race BBBD ( Lr14a ) based on the Thatcher wheat line series (Long & Kolmer 1989) (Table 3.2), yet the frequency of resistance in Ae. longissima was >13% higher to the former than the latter race. This suggests that in spite of having these eight extra virulences, race THBJ must carry a set of avirulence effectors that are recognized by receptors in more accessions of Ae. longissima , thereby initiating an effective resistant response. The frequency of leaf rust resistance found in this study was higher than that found previously for Ae. longissima accessions from Israel by Anikster et al. (2005). In that study, 379 accessions were tested against the American races SBDB and TBBL and 39% were found resistant. In another test with a composite of 12 domestic races of P. triticina , Anikster et al. (2005) found 37% of these accessions resistant. Olivera et al. (2005) investigated the resistance of Ae . sharonensis to the same P. triticina races of THBJ and BBBD (mistakenly labeled BBBB in their study) used in this study and found very similar resistance frequencies of 62.6% and 59.8%, respectively.

The ALDIVCO accessions were also evaluated to the most widely distributed P. striiformis f. sp. tritici race in the United States (PSTv-37), and over half (50.1%) were found resistant (Table 3.3). Moreover, a substantially high percentage (42.5%) of these resistant accessions exhibited very low ITs (0 to 2) (Appendix Table 3). Anikster et al. (2005) assessed the resistance of 512 Ae. longissima accessions to stripe rust in the field in Israel and found 91% were resistant. In that study, most accessions showed low rust severities of 1-2%, yet few exhibited highly resistant ITs (ITs=0 to 2), indicative of a hypersensitive response. Thus, many of these accessions likely carry partial resistance, which reduces the rate of disease development in the

field. In a study done with Ae . sharonensis , Olivera et al. (2007) found 44 of 107 (44.9%) accessions resistant to P. striiformis f. sp. tritici race PST-78.

Since Ae. longissima is a wild species that can occasionally outcross in nature, one would expect it to segregate at a number of genetic loci. For this investigation, we made single plant selections for each Ae. longissima accession and then selfed them from one to four generations to increase homozygosity and also generate sufficient seed stocks for the experiments. The percentage of Ae. longissima accessions showing heterogeneous reactions to the rusts ranged from 4.2% to race TTKSK of P. graminis f. sp. tritici to 18.5% to race BBBD of P. triticina (Table 3.3). When the rust phenotype data across different increase generations was analyzed, the percentage of heterogeneous reactions was slightly higher in accessions selfed only once (15.7%) compared to those selfed four times (10.3%). This indicates that repeated selfing can increase homozygosity at rust resistance loci.

The Shannon equitability ( Eh = hs/hmax ) value was used to assess diversity for rust phenotypes in Ae. longissima . Lower values of this statistic indicate less diversity, while higher values indicate more diversity. A high level of diversity was found in response to P. triticina races BBBD ( Eh = 0.92) (Table 3.3). An intermediate level of diversity was found in response to P. graminis f. sp. tritici race TTTTF (0.82), P. striiformis f. sp. tritici race PST-37 (0.81), P. triticina races THBJ (0.79), and P. graminis f. sp. tritici race TTKSK (0.54).

Analysis of the geographic distribution of disease phenotypes in Ae. longissima can help inform future studies on where to collect additional resistant accessions. In this study, only two of the five different rust pathogen races showed distinct geographic patterns of resistance and susceptibility (Figs. 3.7 & 3.8; Appendix Figs. 1, 2 and 3). With respect to P. graminis f. sp. tritici race TTKSK, resistance was concentrated in the central and northern part of Israel where the rainfall is higher, and susceptibility in the southern part of the country (including the Negev 83

Desert) where rainfall is low (Fig. 3.7). The distribution pattern of resistance found to race TTKSK in this study was similar to that observed by Scott et al. (2014) to the domestic Israeli race of TTTTC. This result provides some confirmation of the distinct geographic pattern found in the current study. However, it is interesting to note that this clear distribution pattern of resistance was not found for race TTTTF in this study (Appendix Fig. 1) nor for the other races analyzed by Scott et al. (2014). Assuming that different stem rust races infect under similar climatic conditions, it is difficult to attribute the observed concentration of TTKSK or TTTTF resistance in central/northern Israel solely to more intense co-evolutionary disease selection pressure mediated by increased levels of precipitation. Another distinct geographic pattern of resistance in Ae. longissima was found for P. striiformis f. sp. tritici race PSTv-37. However, in this case, the trend was opposite to that observed for stem rust race TTKSK: resistance was concentrated in the southern part of Israel and susceptibility in the central and northern part of the country (Fig. 3.8). It is again difficult to attribute the higher concentration of resistance to the “cool season” stripe rust disease in the warmer and dryer areas of southern Israel. Anikster et al. (2005) stated that the stand density of Aegilops populations is a significant determinant in the evolution of resistance and level of diversity.

Spatial autocorrelation of rust phenotypes among Ae. longissima accessions at neighboring collection sites was measured using Global Moran’s I. In four of the five cases involving the different rust races (all except race BBBD), statistically significant spatial autocorrelation was found (Table 3.4). The highest level of spatial autocorrelation found was with the two races of P. graminis f. sp. tritici (both with a Global Moran’s I value of 0.42) followed by P. striiformis f. sp. tritici (Global Moran’s I=0.34). These high positive values for Global Moran’s I indicate clustering of accessions with similar rust phenotypes. A moderate degree of clustering was observed for P. triticina rust phenotypes with races THBJ and BBBD having Global Moran’s I values of 0.19 and 0.12, respectively. However, as mentioned previously, the null hypothesis that rust phenotypes for race BBBD are randomly distributed 84

among the collection sites in Israel was not rejected. LISA maps are useful for visualizing patterns of significant spatial clustering of similar values. In this study, spatial clustering of low and high rust infection phenotypes was observed in Ae. longissima to four of the five rust pathogen races (Figs. 3.9 and 3.10; Appendix Figs. 4 and 5), with the exception of P. triticina race BBBD (Appendix Fig. 6). However, the most striking patterns of spatial clustering were with P. graminis f. sp. tritici race TTKSK (Fig. 3.9) and P. striiformis f. sp. tritici race PSTv-37 (Fig. 3.10). With the former, significant spatial clustering of resistance (i.e. low ITs) was observed in a ~356km 2 area along the cities between Ashdod and Hadera, and significant clustering of susceptibility (i.e. high ITs) was observed in a ~378km 2 area northwest of Be’er Sheva and ~496km 2 area between Be’er Sheva and Sde Boker (Fig. 3.9). For P. striiformis f. sp. tritici race PSTv-37, the pattern of spatial clustering was reversed: significant spatial clustering of susceptibility (i.e. high ITs) was observed in a ~758km 2 area along the cities between Ashdod and Hadera, whereas clustering of resistance (i.e. low ITs) was found in a ~409km 2 area northwest of Be’er Sheva and ~523km 2 area between Be’er Sheva and Sde Boker (Fig. 3.10). The LISA maps shown in Figs. 3.9, 3.10 and Appendix Figs. 4, 5 and 6 are similar to the basic geographic distribution maps presented in Figs. 3.7, 3.8 and Appendix Figs. 1, 2 and 3. The primary difference is that the former provides both statistical assessment and visualization of spatial clustering.

OLS analyses between BIOCLIM data and rust phenotype data may provide insights as to the important climatic factors contributing to the evolution of disease resistance in a host species at its center of origin (Podger et al. 1990). Although many significant and highly significant correlations were found between the rust phenotypic data and climatic variables, the coefficients were generally low, indicating a weak linear relationship between the variables. However, some general trends in the data are worth noting. For the stem rust (both races TTTTF and TTKSK) and leaf rust (race THBJ) phenotypes, consistent negative correlations were found between increasing rust ITs (susceptibility) and various precipitation variables (BIO12, BIO13, 85

BIO15, BIO16, and BIO19). With respect to the temperature variables (BIO1 through BIO11), both positive and negative correlations were observed for these same stem rust and leaf rust phenotypes, and in all but one case (race TTTTF with BIO1), the correlations were in the same direction. The correlation results found for the stripe rust phenotypes were completely opposite to those found for the stem rust and leaf rust phenotypes. Consistent positive correlations were found between increasing stripe rust ITs and the precipitation variables. Additionally, with respect to the temperature variables (BIO1 through BIO11), the direction of the coefficients for stripe rust ITs was opposite that found for stem and leaf rust in all cases except BIO9. These results suggest possible differences in the climatic conditions favoring the development of stripe rust vs. stem and leaf rust and ultimately the frequency and distribution of the respective resistances in the wild host. It is curious to note that of all the significant correlations (positive or negative) found between rust ITs and various BIOCLIM parameters, only one was with race BBBD of P. triticina. The reason for this result is not known, but could be related to the poorer fit of the models used in this analysis. Recently, Scott et al. (2014) investigated the resistance of ten Aegilops species, including Ae. longissima , for their resistance to African and Israeli races of P. graminis f. sp. tritici . Few significant correlations were found between climatic variables and stem rust resistance in the Aegilops species. A notable exception was with Ae . longissima infected with the domestic Israeli race TTTTC, where a very strong positive correlation of r 2 = 0.85 was found for precipitation. Most previous disease evaluations of Aegilops species were to pathogen collections outside their native range. It is interesting to note that in the study by Scott et al. (2014), the only strong and significant correlation found between a climatic variable and resistance in Ae . longissima was to a domestic Israeli race, where the possibility for a long period of co-evolution between host and pathogen may have occurred.

To efficiently exploit the most widely effective rust resistance genes from Ae. longissima for wheat improvement, additional rust evaluations and genetic studies should be completed. On the short list for such studies are the ten accessions (AEG- 86

683-23, AEG-725-15, AEG-803-49, AEG-1274-20, AEG-1276-22, AEG-1471-15, AEG-1475-19, AEG-2974-0, AEG-4005-20, and AEG-8705-10) that were resistant to all races of the three pathogens investigated in this study (Appendix Table 3). Studies are underway to investigate the resistance spectrum of these ten accessions to a large and diverse panel of rust virulence types at both the seedling and adult plant stages. Coupled with this work, we are also making crosses between these ten resistant accessions and select susceptible accessions of Ae. longissima to elucidate the number of genes conferring resistance, determine their chromosomal position and provide a possible platform for gene cloning. Aside from these 10 select accessions, there are other ALDIVCO accessions with valuable resistance to multiple rust pathogens worthy of further investigation. For example, 21 accessions were resistant to both races of P. graminis f. sp . tritici and both races of P. triticina ; 18 were resistant to both races of P. graminis f. sp. tritici and P. striiformis f. sp. tritici ; and 86 were resistant to both races of P. triticina and P. striiformis f. sp. tritici (Appendix Table 3). Finally, other accessions resistant to the two races of P. graminis f. sp. tritici , the two races of P. triticina, or the single race of P. striiformis f. sp. tritici also merit further rust evaluations to assess their spectrum of resistance to the individual rust pathogens.

Our long-term goal is to transfer rust resistance genes from Ae. longissima into wheat. This process is difficult and time-consuming using standard wide- hybridization techniques because of inherent low crossibility between the species, low homoeologous pairing, the “hitch-hiking” of deleterious genes along with target genes in the introgressed segments (i.e. linkage drag) and gametocidal genes (Endo 1985; Millet 2007). Nevertheless, a number of disease resistance genes have been transferred from Ae. longissima and its closely related sympatric species Ae . sharonensis into wheat via this technique. A dominant gene for resistance to powdery mildew ( Pm13 ) was transferred from Ae. longissima into wheat cv. ‘Chinese Spring’ using the ph1 mutant wheat to induce homoeologous recombination (Ceoloni et al. 1988). With respect to Ae. sharonensis , Lr56 for leaf rust resistance and Yr38 for 87

stripe rust resistance have been successfully transferred into wheat using wide- hybridization techniques (Millet et al. 2014).

The direct cloning of resistance genes from Aegilops species, coupled with their transfer into wheat via various transformation vectors, represents a promising alternative to wide-hybridization techniques that can eliminate the problem of linkage drag and also facilitate the strategy of resistance gene stacking or pyramiding. Recently, Steuernagel et al. (2016) described a three-step protocol called mutagenesis resistance gene enrichment sequencing (MutRenSeq) for rapidly isolating resistance genes from plants. This protocol is based on chemical (i.e. EMS) mutagenesis of the resistance sources and subsequent screening for susceptibility mutants; exome capture and sequencing of resistance gene family members; and sequence comparisons of wild type and susceptibility mutants. As a proof of concept, Steuernagel et al. (2016) used MutRenSeq to clone the stem rust resistance genes Sr22 and Sr45 from wheat. Preliminary data from our laboratory suggests that susceptibility mutants for MutRenSeq can be readily recovered from the raw wild species of Ae . sharonensis (B. Steffenson and B. Wulff, unpublished). It is certain that MutRenSeq will lead to the isolation of many new rust resistance genes from Aegilops species in the near future. This, coupled with new biotechnology protocols that can transfer three to four genes at a time into wheat, hold great promise for the gene pyramiding strategy and more durable disease control.

Table 3.1. Collection sites, corresponding longitude and latitude coordinates and number of Aegilops longissima accessions used in this study. Collection Site Longitude Latitude Number of Accessions Akko 35.08450 32.92989 10 Ashalim 34.67443 30.95645 11 Ashdod 34.70007 31.83610 4 Be'er Sheva 34.79576 31.25067 8 Be'er Sheva -Arad 31.26642 34.97110 1 Beit Lid 34.92786 32.33349 6 Ben Zakkay 34.72830 31.85664 8 Benaya 34.75259 31.84373 10 Berekhya 34.64611 31.66749 1 Dimona 35.02579 31.06940 3 Dorot 34.64667 31.50744 4 En Gev 35.64119 32.78367 5 Ge'alya Kubeiba 34.76632 31.88609 9 Gevar'am 34.61328 31.59199 9 Gilat 34.66168 31.33539 11 Giv'at Arnon 34.67285 31.66040 4 Giv'at Brenner 34.80263 31.86713 8 HaBesor 34.50523 31.23739 1 Hadera 34.92245 32.44402 11 HaNegev Junction 34.83688 31.06699 6 Hevron -- -- 1 Horbat Allon 34.96300 32.45040 3 Ilanot 34.89945 32.28830 1 Kefar Menahem 34.83516 31.73211 11 Kefar Mordechay 34.75688 31.83148 3 Kefar Yona 34.93412 32.31760 11 Liman 35.11188 33.05918 5 Mamshit 35.06349 31.02720 10 Mash'abbe Sade 34.75162 31.03082 6 Mash'abbe Sade-Retamim 34.70427 31.04970 1 Meffalsim 34.56179 31.50268 1 Megdar Farm 34.64875 31.35340 1 Nahal Hatzatz 34.84066 30.89407 2 Nahal Liman 35.10566 33.05052 11 Nahal Oz 34.49776 31.47274 1 Nahal Solelim-Beersheba 34.74890 31.26755 7

Nahal Zin 35.03710 30.83100 1 Nahariyya -Rosh HaNikra 33.01839 35.10486 1 Nir'am 34.58058 31.51892 8 Nizzanim 34.63440 31.71838 8 Or-Haner 34.60823 31.55348 2 Pardes Hanna 34.93411 32.48272 2 Petah Tiqwa 34.88880 32.08345 5 Qiryat Ono 34.85893 32.05537 15 Qiryat Ono -Petah Tiqwa 34.87340 32.07012 4 Raffiah Yam 34.24458 31.32220 1 Ramat Aviv 34.80549 32.11208 4 Rehovot 34.81087 31.89447 10 Re'im 34.45913 31.38640 8 Revivim 34.81523 31.05056 1 Rishon LeZiyyon 34.81121 31.96003 2 Ruhama-badlands 34.71153 31.49777 2 Sede Boqer 34.79345 30.87372 14 Shedema 34.74031 31.83360 15 Shedema-Benaya 34.74003 31.83927 9 Shefayyim 34.82245 32.21665 4 Shemuel Hospital 34.82426 31.93166 1 Shirat HaYam 34.27177 31.36698 1 Shivta -Haluza 31.01853 34.62270 1 Shomerat 35.09515 32.95197 4 Tel Katifa 34.30480 31.36420 1 Tel Mond 34.91816 32.25665 7 Telalim 34.77135 30.99031 10 Tel -Nof 34.78353 31.83983 1 Tifrah 34.68758 31.31092 6 Tifrah2 34.68670 31.31678 4 Yad Mordekhay 34.55750 31.58702 1 Yaqum 34.84211 32.24932 1 Yaziz -Gibton 34.86490 31.85339 2 Yeroham 34.87481 31.03196 7 Yeroham-Be'er Sheva 34.87800 31.02850 1 Dead Sea a -- -- 1 Jordan River a -- -- 1 Unknown site within Israel b -- -- 16 Unknown site within Jordan c -- -- 2 Unknown site d -- -- 5

Total 394 aCollection sites of accessions are from Jordan. bThe specific collection sites in Israel are not known. cThe specific collection sites in Jordan are not known. dThe country of origin is not known for five accessions.

Table 3.2. Race, isolate, virulence phenotype and source of wheat rust pathogens used to evaluate resistance in Aegilops longissima . Pathogen Race a Isolate Virulence / avirulence formula b Source Puccinia graminis f. sp. 5, 6, 7b, 8a, 9a, 9b, 9d, 9e, 9g, 10, 11, Y. Jin (USDA-ARS Cereal Disease Laboratory. St. Paul, TTTTF 02MN84A-1-2 tritici 17, 21, 30, 36, 38, McN, Tmp / 24, 31 MN)

Puccinia graminis f. sp. 5, 6, 7b, 8a, 9a, 9b, 9d, 9e, 9g, 10, 11, Y. Jin (USDA-ARS Cereal Disease Laboratory. St. Paul, TTKSK 04KEN156/04 tritici 17, 21, 30, 31, 38, McN / 24, 36, Tmp MN)

1, 2a, 2c, 3a, 16, 26, 10, 14a, 18 / 9, J. Kolmer (USDA-ARS Cereal Disease Laboratory. St. Puccinia triticina THBJ 99ND588DLL 24, 3ka, 11, 17, 30, B Paul, MN)

14a / 1, 2a, 2c, 3a, 9, 16, 24, 26, 3ka, J. Kolmer (USDA-ARS Cereal Disease Laboratory. St. Puccinia triticina BBBD JAK 11, 17, 30, B, 10, 18 Paul, MN)

Puccinia striiformis f. sp. PSTv-37 10-106 6, 7, 8, 9, 17, 27, 43, 44, Tr1, Exp2 / X. Chen (USDA-ARS Wheat Genetics, Physiology, tritici 1, 5, 10, 15, 24, 32, SP, Tye Quality, and Disease Research Unit and Department of Plant Pathology, Washington State University, Pullman, WA) aRaces of the pathogens were characterized on the respective wheat differential host sets for stem rust (Pretorius et al. 2000; Jin 2005), leaf rust (Kolmer et al. 2004; Long et al. 2002) and stripe rust (Wan & Chen 2014). bThe virulence / avirulence formulae represent the resistance genes of the differential wheat genotypes for which the pathogen races possess virulence or avirulence.

Table 3.3. Number and percentage of Aegilops longissima accessions exhibiting resistant, susceptible and heterogeneous reactions to three wheat rust pathogens and corresponding values for Shannon’s diversity and equitability indices.

a b c Pathogen Race Resistant Susceptible Heterogeneous Total hs hs/ hmax P. graminis f. sp. tritici TTTTF 64 (18.2%) 225 (64.1%) 62 (17.7%) 351 (100%) 0.90 0.82 P. graminis f. sp. tritici TTKSK 249 (80.8%) 46 (14.9%) 13 (4.2%) 308 (100%) 0.59 0.54 P. triticina THBJ 247 (65.9%) 76 (20.3%) 52 (13.9%) 375 (100%) 0.87 0.79 P. triticina BBBD 178 (52.2%) 100 (29.3%) 63 (18.5%) 341 (100%) 1.01 0.92 P. striiformis f. sp. tritici PSTv-37 190 (50.1%) 164 (43.3%) 25 (6.6%) 379 (100%) 0.89 0.81 aNumber of resistant (those exhibiting infection types [ITs] of 0 to 2+ for stem rust and leaf rust and 0 to 6 for stripe rust) accessions observed to each pathogen race. The frequency of resistance is given in parentheses. bNumber of susceptible (those exhibiting ITs of 3– to 4 for stem rust and leaf rust and 7 to 9 for stripe rust) accessions observed to each pathogen race. The frequency of susceptibility is given in parentheses. cHeterogeneous indicates that individual accessions exhibited a mixture of distinctly resistant or susceptible plants.

Table 3.4. Spatial autocorrelation (Global Moran’s I) of the autocorrelation between collection sites of Aegilops longissima. Pathogen Race Number of sites Analyzed Global Moran's I P-value P. graminis f. sp. tritici TTTTF 73 0.42 < 0.001 P. graminis f. sp. tritici TTKSK 61 0.42 < 0.001 P. triticina THBJ 73 0.19 < 0.05 P. triticina BBBD 70 0.12 > 0.05 P. striiformis f. sp. tritici PSTv-37 72 0.34 < 0.001

Table 3.5. Ordinary Least Squares analysis between rust phenotypes of Aegilops longissima and16 bioclimatic variables. P. graminis f. sp. tritici P. triticina P. striiformis f. sp. tritici Bioclimatic variables TTTTF TTKSK THBJ BBBD PSTv37 BIO1 Annual Mean Temperature -0.04 0.05 0.32 0.31 -0.23 BIO2 Mean Diurnal Range (Mean of monthly (max temp - min temp)) 0.02 0.03 0.02 -0.02 -0.05 BIO3 Isothermality (BIO2/BIO7) (* 100) 0.003 -0.02 -0.02 -0.15 -0.03 BIO4 Temperature Seasonality (standard deviation *100) 0.0004 0.001 0.0007 0 -0.002 BIO5 Max Temperature of Warmest Month 0.07 0.36 0.22 0.02 -0.40 BIO6 Min Temperature of Coldest Month -0.26 -0.22 -0.06 0.2 0.35 BIO7 Temperature Annual Range (BIO5-BIO6) 0.12 0.21 0.12 -0.06 -0.32 BIO8 Mean Temperature of Wettest Quarter -0.17 -0.08 -0.02 0.12 0.24 BIO9 Mean Temperature of Driest Quarter 0.06 0.55 0.30 0.19 0.84 BIO10 Mean Temperature of Warmest Quarter 0.03 0.22 0.31 0.22 -0.26 BIO11 Mean Temperature of Coldest Quarter -0.14 -0.23 -0.07 0.20 0.30 BIO12 Annual Precipitation -0.002 -0.004 -0.001 0.0003 0.008 BIO13 Precipitation of Wettest Month -0.007 -0.01 -0.005 0.001 0.03 BIO15 Precipitation Seasonality (Coefficient of Variation) -0.06 -0.12 -0.05 0.009 0.25 BIO16 Precipitation of Wettest Quarter -0.003 -0.009 -0.002 0.0004 0.01 BIO19 Precipitation of Coldest Quarter -0.003 -0.006 -0.002 0.0004 0.01 P-value at significance level <0.05. ** P-value at significance level <0.01.

Figure 3.1. Map of Israel showing the geographic distribution of Aegilops longissima accessions collected and used in this study a.

aTwenty-two accessions donated by the Leibniz-Institut für Pflanzengenetik und Kulturpflanzenforschung (IPK) are not included in the map but were evaluated in the study.

Figure 3.2. Examples of different stem rust infection types observed on Aegilops longissima in response to Puccinia graminis f. sp. tritici race TTTTF at the seedling stage.

Figure 3.3. Examples of different stem rust infection types observed on Aegilops longissima in response to

Puccinia graminis f. sp. tritici race TTKSK at the seedling stage.

Figure 3.4. Examples of different leaf rust infection types observed on Aegilops longissima in response to

Puccinia triticina race THBJ at the seedling stage.

Figure 3.5. Examples of different leaf rust infection types observed on Aegilops longissima in response to Puccinia triticina race BBBD at the seedling stage.

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Figure 3.6. Examples of different stripe rust infection types observed on Aegilops longissima in response to

Puccinia striiformis f. sp. tritici race PSTv-37 at the seedling stage.

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Figure 3.7. Map of Israel showing the geographic distribution of Aegilops longissima accessions resistant and susceptible to Puccinia graminis f. sp. tritici race TTKSK.

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Figure 3.8. Map of Israel showing the geographic distribution of Aegilops longissima accessions resistant and susceptible to Puccinia striiformis f. sp. tritici race PSTv-37.

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Figure 3.9. Map of Israel showing the Local Indicator of Spatial Association (LISA) a clusters of Aegilops longissima accessions in response to infection by Puccinia graminis f. sp. tritici race TTKSK.

aFor the LISA analysis, a spatial weights matrix was generated for each variable using GeoDa, comparing each site to its nearest four neighbors. High-High indicates significant clusters of neighboring accessions exhibiting susceptible reactions; Low-Low indicates significant clusters of accessions exhibiting resistant reactions; Low-High indicates significant clusters of neighboring accessions exhibiting resistant and also susceptible reactions; and High-Low indicates significant clusters of neighboring accessions exhibiting susceptible and also resistant reactions.

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Figure 3.10. Map of Israel showing the Local Indicator of Spatial Association (LISA) a clusters of Aegilops longissima accessions in response to infection by Puccinia striiformis f. sp. tritici race PSTv-37.

105

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Appendix Table 1. Collection sites, corresponding longitude and latitude coordinates, donating genebank and number of selfed generations of Aegilops longissima accessions used in this study. Accessions Donating Collection site Longitude Latitude Current selfed genebank generation AEG -13 -1 ICCI Revivim 34.81523 31.05056 3 AEG-14-2 ICCI Hevron -- -- 4 AEG-16-4 ICCI Gilat 34.66168 31.33539 2 AEG -17 -5 ICCI Nahariyya -Rosh HaNikra 33.01839 35.10486 4 AEG-19-7 ICCI Hadera 34.92245 32.44402 2 AEG-20-9 ICCI Dead Sea -- -- 3 AEG -21 -10 ICCI Jordan River -- -- 4 AEG-22-11 ICCI Dimona 35.02579 31.06940 4 AEG -23 -12 ICCI Yad Mordekhay 34.55750 31.58702 4 AEG-24-13 ICCI Be'er Sheva-Arad 31.26642 34.97110 4 AEG-25-14 ICCI Shivta-Haluza 31.01853 34.62270 4 AEG -26 -15 ICCI Dimona 35.02579 31.06940 2 AEG-27-16 ICCI Nahal Oz 34.49776 31.47274 4 AEG-28-17 ICCI Dimona 35.02579 31.06940 2 AEG -29 -18 ICCI Yeroham -Be'er Sheva 34.87800 31.02850 2 AEG-30-19 ICCI Nahal Zin 35.03710 30.83100 4 AEG -249 -1 ICCI Shedema 34.74031 31.83360 2 AEG-250-2 ICCI Shedema 34.74031 31.83360 2 AEG-251-3 ICCI Shedema 34.74031 31.83360 2 AEG -264 -19 ICCI Shedema 34.74031 31.83360 2 AEG-265-21 ICCI Shedema 34.74031 31.83360 0 AEG -267 -23 ICCI Shedema 34.74031 31.83360 2 AEG -268 -24 ICCI Shedema 34.74031 31.83360 2 AEG-271-27 ICCI Shedema 34.74031 31.83360 2 AEG -274 -30 ICCI Shedema 34.74031 31.83360 2 AEG-280-37 ICCI Shedema 34.74031 31.83360 2 AEG-281-40 ICCI Shedema 34.74031 31.83360 2 AEG -282 -41 ICCI Shedema 34.74031 31.83360 2 AEG-284-44 ICCI Shedema 34.74031 31.83360 2 AEG -289 -49 ICCI Shedema 34.74031 31.83360 2 AEG -290 -50 ICCI Shedema 34.74031 31.83360 0 AEG-293-54 ICCI Shedema 34.74031 31.83360 0 AEG -297 -4 ICCI Beit Lid 34.92786 32.33349 3 AEG-298-5 ICCI Beit Lid 34.92786 32.33349 2 AEG-299-6 ICCI Beit Lid 34.92786 32.33349 3

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AEG -300 -7 ICCI Beit Lid 34.92786 32.33349 4 AEG -302 -9 ICCI Beit Lid 34.92786 32.33349 2 AEG-303-10 ICCI Beit Lid 34.92786 32.33349 4 AEG -479 -23 ICCI Mash'abbe Sade -Retamim 34.70427 31.04970 4 AEG-480-24 ICCI Kefar Yona 34.93412 32.31760 2 AEG-622-4 ICCI Rehovot 34.81087 31.89447 4 AEG -623 -5 ICCI Rehovot 34.81087 31.89447 2 AEG-624-6 ICCI Rehovot 34.81087 31.89447 3 AEG -625 -7 ICCI Rehovot 34.81087 31.89447 4 AEG -627 -9 ICCI Rehovot 34.81087 31.89447 2 AEG-628-10 ICCI Rehovot 34.81087 31.89447 3 AEG -629 -11 ICCI Rehovot 34.81087 31.89447 2 AEG-631-13 ICCI Rehovot 34.81087 31.89447 4 AEG-637-19 ICCI Rehovot 34.81087 31.89447 2 AEG -657 -39 ICCI Rehovot 34.81087 31.89447 2 AEG-661-1 ICCI Ge'alya Kubeiba 34.76632 31.88609 0 AEG -664 -4 ICCI Ge'alya Kubeiba 34.76632 31.88609 3 AEG -667 -7 ICCI Ge'alya Kubeiba 34.76632 31.88609 4 AEG-668-8 ICCI Ge'alya Kubeiba 34.76632 31.88609 4 AEG -669 -9 ICCI Ge'alya Kubeiba 34.76632 31.88609 0 AEG-670-10 ICCI Ge'alya Kubeiba 34.76632 31.88609 4 AEG-671-11 ICCI Ge'alya Kubeiba 34.76632 31.88609 2 AEG -682 -22 ICCI Ge'alya Kubeiba 34.76632 31.88609 2 AEG-683-23 ICCI Ge'alya Kubeiba 34.76632 31.88609 2 AEG -692 -32 ICCI Ge'alya Kubeiba 34.76632 31.88609 1 AEG -710 -50 ICCI Ge'alya Kubeiba 34.76632 31.88609 2 AEG-711-1 ICCI Ben Zakkay 34.72830 31.85664 4 AEG -712 -2 ICCI Ben Zakkay 34.72830 31.85664 4 AEG-713-3 ICCI Ben Zakkay 34.72830 31.85664 1 AEG-715-5 ICCI Ben Zakkay 34.72830 31.85664 0 AEG -716 -6 ICCI Ben Zakkay 34.72830 31.85664 1 AEG-718-8 ICCI Ben Zakkay 34.72830 31.85664 3 AEG -719 -9 ICCI Ben Zakkay 34.72830 31.85664 2 AEG -725 -15 ICCI Ben Zakkay 34.72830 31.85664 2 AEG-738-28 ICCI Ben Zakkay 34.72830 31.85664 2 AEG -745 -35 ICCI Ben Zakkay 34.72830 31.85664 0 AEG-746-36 ICCI Ben Zakkay 34.72830 31.85664 2 AEG-757-3 ICCI Benaya 34.75259 31.84373 4 AEG -759 -5 ICCI Benaya 34.75259 31.84373 3 AEG-760-6 ICCI Benaya 34.75259 31.84373 4

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AEG -761 -7 ICCI Benaya 34.75259 31.84373 4 AEG -762 -8 ICCI Benaya 34.75259 31.84373 4 AEG-763-9 ICCI Benaya 34.75259 31.84373 2 AEG -766 -12 ICCI Benaya 34.75259 31.84373 2 AEG-791-37 ICCI Benaya 34.75259 31.84373 2 AEG-792-38 ICCI Benaya 34.75259 31.84373 0 AEG -803 -49 ICCI Benaya 34.75259 31.84373 2 AEG-809-55 ICCI Benaya 34.75259 31.84373 2 AEG -1003 -1 ICCI Gilat 34.66168 31.33539 4 AEG -1005 -3 ICCI Gilat 34.66168 31.33539 4 AEG-1006-4 ICCI Gilat 34.66168 31.33539 2 AEG -1008 -6 ICCI Gilat 34.66168 31.33539 2 AEG-1011-9 ICCI Gilat 34.66168 31.33539 0 AEG-1013-11 ICCI Gilat 34.66168 31.33539 4 AEG -1015 -13 ICCI Gilat 34.66168 31.33539 2 AEG-1018-16 ICCI Gilat 34.66168 31.33539 4 AEG -1032 -30 ICCI Gilat 34.66168 31.33539 1 AEG -1033 -31 ICCI Gilat 34.66168 31.33539 1 AEG-1040-38 ICCI Gilat 34.66168 31.33539 0 AEG -1049 -47 ICCI Gilat 34.66168 31.33539 2 AEG-1057-4 ICCI Shedema-Benaya 34.74003 31.83927 2 AEG-1059-6 ICCI Shedema-Benaya 34.74003 31.83927 4 AEG -1078 -25 ICCI Shedema -Benaya 34.74003 31.83927 2 AEG-1084-31 ICCI Shedema-Benaya 34.74003 31.83927 4 AEG -1086 -33 ICCI Shedema -Benaya 34.74003 31.83927 4 AEG -1087 -34 ICCI Shedema -Benaya 34.74003 31.83927 4 AEG-1088-35 ICCI Shedema-Benaya 34.74003 31.83927 2 AEG -1090 -37 ICCI Shedema -Benaya 34.74003 31.83927 2 AEG-1094-41 ICCI Shedema-Benaya 34.74003 31.83927 2 AEG-1182-3 ICCI Mash'abbe Sade 34.75162 31.03082 2 AEG -1184 -5 ICCI Mash'abbe Sade 34.75162 31.03082 1 AEG-1185-6 ICCI Mash'abbe Sade 34.75162 31.03082 2 AEG -1187 -8 ICCI Mash'abbe Sade 34.75162 31.03082 2 AEG -1188 -9 ICCI Mash'abbe Sade 34.75162 31.03082 2 AEG-1189-10 ICCI Mash'abbe Sade 34.75162 31.03082 2 AEG -1205 -1 ICCI Tel Mond 34.91816 32.25665 4 AEG-1206-2 ICCI Tel Mond 34.91816 32.25665 3 AEG-1207-3 ICCI Tel Mond 34.91816 32.25665 2 AEG -1208 -4 ICCI Tel Mond 34.91816 32.25665 4 AEG-1209-5 ICCI Tel Mond 34.91816 32.25665 4

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AEG -1211 -7 ICCI Tel Mond 34.91816 32.25665 4 AEG -1212 -8 ICCI Tel Mond 34.91816 32.25665 2 AEG-1220-16 ICCI Tel Mond 34.91816 32.25665 2 AEG -1236 -32 ICCI Tel Mond 34.91816 32.25665 0 AEG-1241-37 ICCI Tel Mond 34.91816 32.25665 0 AEG-1255-1 ICCI Qiryat Ono 34.85893 32.05537 2 AEG -1263 -9 ICCI Qiryat Ono 34.85893 32.05537 2 AEG-1264-10 ICCI Qiryat Ono 34.85893 32.05537 4 AEG -1265 -11 ICCI Qiryat Ono 34.85893 32.05537 2 AEG -1266 -12 ICCI Qiryat Ono 34.85893 32.05537 2 AEG-1268-14 ICCI Qiryat Ono 34.85893 32.05537 4 AEG -1269 -15 ICCI Qiryat Ono 34.85893 32.05537 1 AEG-1270-16 ICCI Qiryat Ono 34.85893 32.05537 2 AEG-1271-17 ICCI Qiryat Ono 34.85893 32.05537 2 AEG -1272 -18 ICCI Qiryat Ono 34.85893 32.05537 3 AEG-1274-20 ICCI Qiryat Ono 34.85893 32.05537 3 AEG -1276 -22 ICCI Qiryat Ono 34.85893 32.05537 4 AEG -1285 -31 ICCI Qiryat Ono 34.85893 32.05537 2 AEG-1296-42 ICCI Qiryat Ono 34.85893 32.05537 1 AEG -1303 -49 ICCI Qiryat Ono 34.85893 32.05537 1 AEG-1306-2 ICCI Hadera 34.92245 32.44402 4 AEG-1308-4 ICCI Hadera 34.92245 32.44402 4 AEG -1310 -6 ICCI Hadera 34.92245 32.44402 2 AEG-1312-8 ICCI Hadera 34.92245 32.44402 2 AEG -1314 -10 ICCI Hadera 34.92245 32.44402 4 AEG -1316 -12 ICCI Hadera 34.92245 32.44402 3 AEG-1318-14 ICCI Hadera 34.92245 32.44402 2 AEG -1319 -15 ICCI Hadera 34.92245 32.44402 2 AEG-1334-30 ICCI Hadera 34.92245 32.44402 2 AEG-1348-44 ICCI Hadera 34.92245 32.44402 2 AEG -1355 -1 ICCI Giv'at Brenner 34.80263 31.86713 4 AEG-1356-2 ICCI Giv'at Brenner 34.80263 31.86713 2 AEG -1357 -3 ICCI Giv'at Brenner 34.80263 31.86713 4 AEG -1358 -4 ICCI Giv'at Brenner 34.80263 31.86713 4 AEG-1359-5 ICCI Giv'at Brenner 34.80263 31.86713 0 AEG -1360 -6 ICCI Giv'at Brenner 34.80263 31.86713 4 AEG-1361-7 ICCI Giv'at Brenner 34.80263 31.86713 2 AEG-1382-28 ICCI Giv'at Brenner 34.80263 31.86713 0 AEG -1392 -38 ICCI Giv'at Brenner 34.80263 31.86713 2 AEG-1397-43 ICCI Giv'at Brenner 34.80263 31.86713 2

117

AEG -1406 -1 ICCI Re'im 34.45913 31.38640 2 AEG -1407 -2 ICCI Re'im 34.45913 31.38640 4 AEG-1409-4 ICCI Re'im 34.45913 31.38640 4 AEG -1410 -5 ICCI Re'im 34.45913 31.38640 0 AEG-1411-6 ICCI Re'im 34.45913 31.38640 4 AEG-1425-20 ICCI Re'im 34.45913 31.38640 0 AEG -1445 -40 ICCI Re'im 34.45913 31.38640 1 AEG-1449-44 ICCI Re'im 34.45913 31.38640 2 AEG -1451 -46 ICCI Re'im 34.45913 31.38640 2 AEG -1471 -15 ICCI Nir'am 34.58058 31.51892 4 AEG-1475-19 ICCI Nir'am 34.58058 31.51892 1 AEG -1478 -22 ICCI Nir'am 34.58058 31.51892 2 AEG-1479-23 ICCI Nir'am 34.58058 31.51892 2 AEG-1480-24 ICCI Nir'am 34.58058 31.51892 2 AEG -1495 -39 ICCI Nir'am 34.58058 31.51892 4 AEG-1509-1 ICCI Kefar Yona 34.93412 32.31760 3 AEG -1510 -2 ICCI Kefar Yona 34.93412 32.31760 2 AEG -1512 -4 ICCI Kefar Yona 34.93412 32.31760 4 AEG-1513-5 ICCI Kefar Yona 34.93412 32.31760 4 AEG -1514 -6 ICCI Kefar Yona 34.93412 32.31760 4 AEG-1515-7 ICCI Kefar Yona 34.93412 32.31760 1 AEG-1519-11 ICCI Kefar Yona 34.93412 32.31760 2 AEG -1528 -20 ICCI Kefar Yona 34.93412 32.31760 2 AEG-1533-25 ICCI Kefar Yona 34.93412 32.31760 0 AEG -1538 -30 ICCI Kefar Yona 34.93412 32.31760 0 AEG -1545 -37 ICCI Kefar Yona 34.93412 32.31760 0 AEG-1667-2 ICCI Sde Boker 34.79345 30.87372 4 AEG -1668 -3 ICCI Sde Boker 34.79345 30.87372 4 AEG-1669-4 ICCI Sde Boker 34.79345 30.87372 2 AEG-1670-5 ICCI Sde Boker 34.79345 30.87372 4 AEG -1671 -6 ICCI Sde Boker 34.79345 30.87372 2 AEG-1672-7 ICCI Sde Boker 34.79345 30.87372 4 AEG -1673 -8 ICCI Sde Boker 34.79345 30.87372 4 AEG -1675 -10 ICCI Sde Boker 34.79345 30.87372 2 AEG-1676-11 ICCI Sde Boker 34.79345 30.87372 0 AEG -1685 -20 ICCI Sde Boker 34.79345 30.87372 2 AEG-1695-30 ICCI Sde Boker 34.79345 30.87372 1 AEG-1702-37 ICCI Sde Boker 34.79345 30.87372 2 AEG -1708 -43 ICCI Sde Boker 34.79345 30.87372 2 AEG-1750-85 ICCI Sde Boker 34.79345 30.87372 2

118

AEG -1754 -89 ICCI Sde Boker 34.79345 30.87372 2 AEG -1757 -2 ICCI Tlalim 34.77135 30.99031 4 AEG-1760-5 ICCI Tlalim 34.77135 30.99031 4 AEG -1762 -7 ICCI Tlalim 34.77135 30.99031 2 AEG-1763-8 ICCI Tlalim 34.77135 30.99031 4 AEG-1764-9 ICCI Tlalim 34.77135 30.99031 3 AEG -1765 -10 ICCI Tlalim 34.77135 30.99031 3 AEG-1773-18 ICCI Tlalim 34.77135 30.99031 2 AEG -1793 -38 ICCI Tlalim 34.77135 30.99031 2 AEG -1796 -41 ICCI Tlalim 34.77135 30.99031 2 AEG-1805-50 ICCI Tlalim 34.77135 30.99031 2 AEG -1860 -1 ICCI HaNegev Junction 34.83688 31.06699 3 AEG-1861-2 ICCI HaNegev Junction 34.83688 31.06699 3 AEG-1862-3 ICCI HaNegev Junction 34.83688 31.06699 2 AEG -1864 -5 ICCI HaNegev Junction 34.83688 31.06699 4 AEG-1865-6 ICCI HaNegev Junction 34.83688 31.06699 4 AEG -1866 -7 ICCI HaNegev Junction 34.83688 31.06699 4 AEG -1873 -1 ICCI Gevar'am 34.61328 31.59199 4 AEG-1874-2 ICCI Gevar'am 34.61328 31.59199 4 AEG -1875 -3 ICCI Gevar'am 34.61328 31.59199 2 AEG-1877-5 ICCI Gevar'am 34.61328 31.59199 2 AEG-1878-6 ICCI Gevar'am 34.61328 31.59199 3 AEG -1879 -7 ICCI Gevar'am 34.61328 31.59199 3 AEG-1880-8 ICCI Gevar'am 34.61328 31.59199 4 AEG -1882 -10 ICCI Gevar'am 34.61328 31.59199 2 AEG -1912 -40 ICCI Gevar'am 34.61328 31.59199 2 AEG-1913-41 ICCI Gevar'am 34.61328 31.59199 2 AEG -2052 -9 ICCI Petah Tiqwa 34.88880 32.08345 4 AEG-2055-12 ICCI Petah Tiqwa 34.88880 32.08345 2 AEG-2058-15 ICCI Petah Tiqwa 34.88880 32.08345 3 AEG -2062 -19 ICCI Petah Tiqwa 34.88880 32.08345 4 AEG-2065-22 ICCI Petah Tiqwa 34.88880 32.08345 3 AEG -2244 -1 ICCI Nahal Liman 35.10566 33.05052 2 AEG -2247 -4 ICCI Nahal Liman 35.10566 33.05052 2 AEG-2248-5 ICCI Nahal Liman 35.10566 33.05052 4 AEG -2250 -7 ICCI Nahal Liman 35.10566 33.05052 0 AEG-2251-8 ICCI Nahal Liman 35.10566 33.05052 3 AEG-2252-9 ICCI Nahal Liman 35.10566 33.05052 2 AEG -2253 -10 ICCI Nahal Liman 35.10566 33.05052 4 AEG-2265-22 ICCI Nahal Liman 35.10566 33.05052 2

119

AEG -2269 -26 ICCI Nahal Liman 35.10566 33.05052 1 AEG -2275 -32 ICCI Nahal Liman 35.10566 33.05052 2 AEG-2277-34 ICCI Nahal Liman 35.10566 33.05052 1 AEG -2284 -41 ICCI Nahal Liman 35.10566 33.05052 1 AEG-2340-3 ICCI Shomerat 35.09515 32.95197 2 AEG-2341-4 ICCI Shomerat 35.09515 32.95197 3 AEG -2342 -5 ICCI Shomerat 35.09515 32.95197 4 AEG-2343-6 ICCI Shomerat 35.09515 32.95197 3 AEG -2893 -30 ICCI Yeroham 34.87481 31.03196 4 AEG -2894 -31 ICCI Yeroham 34.87481 31.03196 4 AEG-2895-32 ICCI Yeroham 34.87481 31.03196 4 AEG -2897 -34 ICCI Yeroham 34.87481 31.03196 4 AEG-2898-1 ICCI Nahal Hatzatz 34.84066 30.89407 4 AEG-2899-2 ICCI Nahal Hatzatz 34.84066 30.89407 4 AEG -2947 -0 ICCI Tel -Nof 34.78353 31.83983 4 AEG-2949-0 ICCI Herzliyya 34.84554 32.15992 2 AEG -2972 -0 ICCI -- a -- -- 3 AEG -2974 -0 ICCI ------4 AEG-2993-0 ICCI Ilanot 34.89945 32.28830 3 AEG -3036 -0 ICCI Mefalsim 34.56179 31.50268 3 AEG-3039-0 ICCI Yaqum 34.84211 32.24932 4 AEG-3040-0 ICCI Yaqum 34.84211 32.24932 1 AEG -3141 -1 ICCI Ruhama 34.70530 31.49821 3 AEG-3336-1 ICCI Ashalim 34.67443 30.95645 4 AEG -3337 -2 ICCI Ashalim 34.67443 30.95645 4 AEG -3338 -3 ICCI Ashalim 34.67443 30.95645 4 AEG-3339-4 ICCI Ashalim 34.67443 30.95645 3 AEG -3345 -10 ICCI Ashalim 34.67443 30.95645 2 AEG-3346-11 ICCI Ashalim 34.67443 30.95645 1 AEG-3355-20 ICCI Ashalim 34.67443 30.95645 2 AEG -3365 -30 ICCI Ashalim 34.67443 30.95645 0 AEG-3375-40 ICCI Ashalim 34.67443 30.95645 1 AEG -3376 -41 ICCI Ashalim 34.67443 30.95645 1 AEG -3380 -45 ICCI Ashalim 34.67443 30.95645 2 AEG-3403-1 ICCI Liman 35.11188 33.05918 2 AEG -3407 -5 ICCI Liman 35.11188 33.05918 2 AEG-3412-10 ICCI Liman 35.11188 33.05918 2 AEG-3422-20 ICCI Liman 35.11188 33.05918 2 AEG -3432 -30 ICCI Liman 35.11188 33.05918 2 AEG-3439-37 ICCI Liman 35.11188 33.05918 2

120

AEG -3463 -1 ICCI Mamshit 35.06349 31.02720 4 AEG -3464 -2 ICCI Mamshit 35.06349 31.02720 3 AEG-3465-3 ICCI Mamshit 35.06349 31.02720 4 AEG -3466 -4 ICCI Mamshit 35.06349 31.02720 4 AEG-3474-12 ICCI Mamshit 35.06349 31.02720 2 AEG-3478-1 ICCI Mamshit 35.06349 31.02720 1 AEG -3484 -7 ICCI Mamshit 35.06349 31.02720 2 AEG-3486-9 ICCI Mamshit 35.06349 31.02720 2 AEG -3491 -14 ICCI Mamshit 35.06349 31.02720 2 AEG -3498 -21 ICCI Mamshit 35.06349 31.02720 2 AEG-3505-28 ICCI Mamshit 35.06349 31.02720 2 AEG -3507 -30 ICCI Mamshit 35.06349 31.02720 1 AEG-3731-6 ICCI Yaziz-Gibton 34.86490 31.85339 1 AEG-3759-34 ICCI Yaziz-Gibton 34.86490 31.85339 0 AEG -3765 -40 ICCI Yaziz -Gibton 34.86490 31.85339 2 AEG-3771-46 ICCI Yaziz-Gibton 34.86490 31.85339 2 AEG -3931 -6 ICCI Nir'am 34.58058 31.51892 2 AEG -3932 -7 ICCI Nir'am 34.58058 31.51892 2 AEG-3986-1 ICCI Akko 35.08450 32.92989 2 AEG -3988 -3 ICCI Akko 35.08450 32.92989 2 AEG-3995-10 ICCI Akko 35.08450 32.92989 2 AEG-4001-16 ICCI Akko 35.08450 32.92989 2 AEG -4005 -20 ICCI Akko 35.08450 32.92989 2 AEG-4015-30 ICCI Akko 35.08450 32.92989 2 AEG -4025 -40 ICCI Akko 35.08450 32.92989 2 AEG -4026 -41 ICCI Akko 35.08450 32.92989 2 AEG-4075-16 ICCI Kefar Yona 34.93412 32.31760 2 AEG -4099 -40 ICCI Kefar Yona 34.93412 32.31760 2 AEG-4160-1 ICCI Nizzanim 34.63440 31.71838 3 AEG-4161-2 ICCI Nizzanim 34.63440 31.71838 4 AEG -4162 -3 ICCI Nizzanim 34.63440 31.71838 4 AEG-4163-4 ICCI Nizzanim 34.63440 31.71838 4 AEG -4166 -7 ICCI Nizzanim 34.63440 31.71838 2 AEG -4185 -26 ICCI Nizzanim 34.63440 31.71838 2 AEG-4191-32 ICCI Nizzanim 34.63440 31.71838 1 AEG -4194 -35 ICCI Nizzanim 34.63440 31.71838 2 AEG-4542-2 ICCI Pardes Hanna 34.93411 32.48272 3 AEG-4543-3 ICCI Pardes Hanna 34.93411 32.48272 4 AEG -4998 -1 ICCI Dorot 34.64667 31.50744 0 AEG-5000-3 ICCI Dorot 34.64667 31.50744 1

121

AEG -5002 -5 ICCI Dorot 34.64667 31.50744 1 AEG -5004 -7 ICCI Dorot 34.64667 31.50744 1 AEG-5016-1 ICCI Shemuel Hospital 34.82426 31.93166 1 AEG -5646 -1 ICCI Akko 35.08450 32.92989 1 AEG-5647-2 ICCI Akko 35.08450 32.92989 1 AEG-5648-3 ICCI Akko 35.08450 32.92989 1 AEG -6327 -1 ICCI En Gev 35.64119 32.78367 3 AEG-6328-2 ICCI En Gev 35.64119 32.78367 3 AEG -6329 -3 ICCI En Gev 35.64119 32.78367 4 AEG -6330 -4 ICCI En Gev 35.64119 32.78367 4 AEG-6371-0 ICCI HaBesor 34.50523 31.23739 4 AEG -6763 -1 ICCI Ramat Aviv 34.79593 32.10701 0 AEG-6764-2 ICCI Ramat Aviv 34.80868 32.11377 3 AEG-6765-3 ICCI Ramat Aviv 34.80868 32.11377 3 AEG -6766 -4 ICCI Ramat Aviv 34.80868 32.11377 4 AEG-6767-5 ICCI Ramat Aviv 34.80868 32.11377 4 AEG -6781 -1 ICCI Ashdod 34.70007 31.83610 4 AEG -6782 -2 ICCI Ashdod 34.70007 31.83610 4 AEG-6783-3 ICCI Ashdod 34.70007 31.83610 3 AEG -6784 -4 ICCI Ashdod 34.70007 31.83610 4 AEG-8696-1 ICCI Kefar Menahem 34.83516 31.73211 1 AEG-8698-3 ICCI Kefar Menahem 34.83516 31.73211 2 AEG -8699 -4 ICCI Kefar Menahem 34.83516 31.73211 1 AEG-8705-10 ICCI Kefar Menahem 34.83516 31.73211 2 AEG -8708 -13 ICCI Kefar Menahem 34.83516 31.73211 1 AEG -8710 -15 ICCI Kefar Menahem 34.83516 31.73211 1 AEG-8715-20 ICCI Kefar Menahem 34.83516 31.73211 0 AEG -8718 -23 ICCI Kefar Menahem 34.83516 31.73211 1 AEG-8719-24 ICCI Kefar Menahem 34.83516 31.73211 1 AEG-8724-29 ICCI Kefar Menahem 34.83516 31.73211 2 AEG -8725 -30 ICCI Kefar Menahem 34.83516 31.73211 2 AEG-8735-40 ICCI Kefar Menahem 34.83516 31.73211 1 AEG -8760 -15 ICCI En Gev 35.64119 32.78367 2 AEG -8769 -24 ICCI En Gev 35.64119 32.78367 2 AEG-8770-25 ICCI En Gev 35.64119 32.78367 1 AEG -8771 -1 ICCI Qiryat Ono -Petah Tiqwa 34.87340 32.07012 4 AEG-8772-2 ICCI Qiryat Ono-Petah Tiqwa 34.87340 32.07012 3 AEG-8773-3 ICCI Qiryat Ono-Petah Tiqwa 34.87340 32.07012 4 AEG -8774 -4 ICCI Qiryat Ono -Petah Tiqwa 34.87340 32.07012 2 AEG-8779-1 ICCI Rishon LeZiyyon 34.81121 31.96003 3

122

AEG -8780 -2 ICCI Rishon LeZiyyon 34.81121 31.96003 2 AEG -8781 -3 ICCI Rishon LeZiyyon 34.81121 31.96003 1 AEG-8794-1 ICCI Shefayyim 34.82245 32.21665 1 AEG -8795 -2 ICCI Shefayyim 34.82245 32.21665 1 AEG-8796-3 ICCI Shefayyim 34.82245 32.21665 4 AEG-8797-4 ICCI Shefayyim 34.82245 32.21665 2 AEG -9521 -0 ICCI Berekhya 34.64611 31.66749 1 AEG-9522-1 ICCI Kefar Mordechay 34.75688 31.83148 4 AEG -9523 -2 ICCI Kefar Mordechay 34.75688 31.83148 4 AEG -9524 -3 ICCI Kefar Mordechay 34.75688 31.83148 3 AEG-9525-4 ICCI Kefar Mordechay 34.75688 31.83148 4 AEG -9527 -1 ICCI Giv'at Arnon 34.67285 31.66040 3 AEG-9528-2 ICCI Giv'at Arnon 34.67285 31.66040 4 AEG-9529-3 ICCI Giv'at Arnon 34.67285 31.66040 4 AEG -9530 -4 ICCI Giv'at Arnon 34.67285 31.66040 4 AEG-9545-1 ICCI Shirat HaYam 34.27177 31.36698 2 AEG -9546 -2 ICCI Shirat HaYam 34.27177 31.36698 4 AEG -9547 -1 ICCI Tel Katifa 34.30480 31.36420 4 AEG-9548-1 ICCI Raffiah Yam 34.24458 31.32220 3 AEG -9573 -0 ICCI Be'er Sheva 34.79576 31.25067 4 AEG-9574-0 ICCI Be'er Sheva 34.79576 31.25067 3 AEG-9575-0 ICCI Be'er Sheva 34.79576 31.25067 3 AEG -9576 -0 ICCI Be'er Sheva 34.79576 31.25067 4 AEG-9577-1 ICCI Be'er Sheva 34.79576 31.25067 1 AEG -9579 -3 ICCI Be'er Sheva 34.79576 31.25067 1 AEG -9581 -5 ICCI Be'er Sheva 34.79576 31.25067 1 AEG-9583-0 ICCI Be'er Sheva 34.79576 31.25067 1 AEG -9584 -1 ICCI Yeroham 34.87481 31.03196 1 AEG-9586-3 ICCI Yeroham 34.87481 31.03196 1 AEG-9588-5 ICCI Yeroham 34.87481 31.03196 1 AEG -9591 -0 ICCI Or -Haner 34.60823 31.55348 3 AEG-9614-2 ICCI Horbat Allon 34.96300 32.45040 4 AEG -9615 -3 ICCI Horbat Allon 34.96300 32.45040 4 AEG -9616 -4 ICCI Horbat Allon 34.96300 32.45040 4 AEG-9647-1 ICCI Tifrah 34.68758 31.31092 1 AEG -9650 -4 ICCI Tifrah 34.68758 31.31092 1 AEG-9654-8 ICCI Tifrah 34.68758 31.31092 1 AEG-9657-11 ICCI Tifrah 34.68758 31.31092 1 AEG -9660 -14 ICCI Tifrah 34.68758 31.31092 1 AEG-9662-16 ICCI Tifrah 34.68758 31.31092 1

123

AEG -9736 -1 ICCI Nahal Solelim -Beersheba 34.74890 31.26755 1 AEG -9738 -3 ICCI Nahal Solelim -Beersheba 34.74890 31.26755 1 AEG-9740-5 ICCI Nahal Solelim-Beersheba 34.74890 31.26755 1 AEG -9742 -7 ICCI Nahal Solelim -Beersheba 34.74890 31.26755 1 AEG-9744-9 ICCI Nahal Solelim-Beersheba 34.74890 31.26755 1 AEG-9746-11 ICCI Nahal Solelim-Beersheba 34.74890 31.26755 1 AEG -9748 -13 ICCI Nahal Solelim -Beersheba 34.74890 31.26755 1 AEG-9750-1 ICCI Tifrah2 34.68670 31.31678 1 AEG -9751 -2 ICCI Tifrah2 34.68670 31.31678 1 AEG -9752 -3 ICCI Tifrah2 34.68670 31.31678 1 AEG-9753-4 ICCI Tifrah2 34.68670 31.31678 1 AEG -9754 -1 ICCI Megdar Farm 34.64875 31.35340 1 AEG-9755-1 ICCI Or-Haner 34.60823 31.55348 1 AEG-9757-1 ICCI Ruhama-badlands 34.71153 31.49777 1 AEG -9758 -2 ICCI Ruhama -badlands 34.71153 31.49777 1 AEG-9838-3 ICCI Or-Haner 34.60823 31.55348 1 AE -121 IPK ------0 AE -122 IPK ------1 AE-123 IPK Israel -- -- 0 AE -124 IPK ------1 AE-125 IPK Israel -- -- 1 AE-320 IPK Israel -- -- 1 AE -321 IPK Israel -- -- 1 AE-334 IPK Israel -- -- 0 AE -335 IPK Israel -- -- 0 AE -337 IPK Israel -- -- 1 AE-339 IPK Israel -- -- 1 AE -340 IPK Israel -- -- 1 AE-341 IPK Israel -- -- 1 AE-342 IPK Israel -- -- 1 AE -412 IPK Israel -- -- 1 AE-416 IPK Israel -- -- 1 AE -417 IPK Israel -- -- 0 AE -904 IPK Israel -- -- 1 AE-905 IPK Israel -- -- 1 AE -906 IPK Israel -- -- 1 AE-1077 IPK Jordan -- -- 1 AE-1078 IPK Jordan -- -- 1 aSpecific collection sites are not known.

124

Appendix Table 2. Raw data for 11 agro-morphological traits scored on 337 and 362 accessions of Aegilops longissima in Experiment 1 and Experiment 2 in the greenhouse, respectively. Experiment 1 Accessions DH LA1 LA2 LAF LP LS LA NN NS HP 30KW AEG -13 -1 45 1.1 2.1 4.3 6.9 16.3 7.6 3 11 58.6 0.2 AEG-14-2 50 1.4 3.0 2.8 -- a 17.9 12.6 3 -- 94.6 0.2 AEG-16-4 57 1.1 2.7 3.3 10.5 22.3 9.2 3 14 81.2 0.3 AEG -17 -5 51 0.5 1.5 1.7 14.5 17.2 7.9 4 11 86.9 0.2 AEG-19-7 49 1.4 -- 2.3 18.4 18.3 6.5 4 13 66.5 0.3 AEG-20-9 49 0.8 2.0 3.6 5.5 15.6 8.6 3 10 34.6 -- AEG -21 -10 46 1.0 2.2 3.6 2.9 16.7 7.2 3 10 59.2 -- AEG-22-11 47 1.4 2.2 2.1 8.0 17.6 4.9 3 10 69.9 0.1 AEG -23 -12 57 1.4 3.2 1.9 6.3 22.8 8.9 3 13 78.9 0.2 AEG-24-13 49 0.8 1.5 3.8 10.5 17.2 4.7 4 10 68.8 0.2 AEG-25-14 45 1.2 4.0 5.2 8.9 17.8 9.1 3 12 74.1 0.2 AEG -26 -15 48 0.8 2.3 3.0 5.1 19.9 4.8 3 11 73.8 0.2 AEG-27-16 64 1.1 3.3 1.9 7.5 19.3 8.1 4 13 63.1 0.1 AEG-28-17 47 1.0 2.8 4.3 12.0 19.0 6.5 3 14 47.5 0.1 AEG -29 -18 42 1.3 2.7 1.2 1.6 15.5 7.3 3 10 49.3 -- AEG-30-19 51 1.6 3.2 4.3 7.8 17.6 6.9 3 13 61.9 0.3 AEG -249 -1 67 0.8 1.2 1.7 12.6 18.2 7.4 3 13 70.4 -- AEG-250-2 55 1.3 5.4 1.9 -- 19.6 8.2 4 -- 82.2 0.2 AEG-251-3 51 0.7 1.0 2.1 17.4 19.8 7.5 4 14 74.5 0.3

125

AEG -264 -19 53 0.7 1.8 4.1 17.5 19.3 9.2 4 11 64.2 -- AEG -267 -23 48 0.8 2.2 2.4 9.1 16.2 6.6 3 15 75.6 0.2 AEG-268-24 58 0.4 1.1 1.1 8.4 18.7 8.6 3 15 98.6 -- AEG -271 -27 64 0.8 2.3 1.5 9.1 16.3 7.3 3 8 62.3 0.1 AEG-274-30 57 1.0 3.0 3.8 15.2 17.5 9.2 4 12 79.2 0.3 AEG-280-37 52 1.1 2.6 2.4 6.8 16.6 7.3 4 11 81.3 0.1 AEG -281 -40 55 1.3 3.4 4.7 10.7 20.8 7.1 4 13 79.1 0.2 AEG-282-41 58 0.7 1.9 1.2 16.6 19.3 9.3 4 13 73.3 -- AEG -284 -44 62 0.7 1.5 1.6 8.6 17.8 7.5 4 11 71.5 -- AEG -289 -49 59 1.1 1.9 5.7 17.4 18.8 7.9 4 12 63.4 0.3 AEG-293-54 53 1.0 2.2 1.0 5.9 13.6 4.2 3 12 62.2 0.1 AEG -297 -4 64 1.0 2.1 1.0 8.1 18.1 14.3 4 13 104.3 -- AEG-298-5 64 1.2 2.2 1.6 17.7 17.2 8.6 3 12 92.6 -- AEG-299-6 58 0.4 1.3 1.5 15.1 18.4 13.5 3 14 114.5 -- AEG -300 -7 67 0.6 1.5 0.9 15.1 18.6 7.6 4 12 63.6 0.3 AEG-302-9 72 1.7 3.5 2.0 18.0 18.5 10.5 4 10 68.5 0.1 AEG -303 -10 61 1.0 2.1 1.9 15.6 17.0 10.7 4 13 74.7 0.3 AEG -479 -23 55 0.9 2.3 2.0 -- 17.7 7.8 3 -- 77.8 -- AEG-480-24 73 1.4 2.8 2.1 10.1 17.6 12.7 3 14 80.7 0.2 AEG -622 -4 70 0.8 1.6 1.5 9.7 19.5 6.2 4 15 88.2 0.2 AEG-623-5 63 1.1 3.4 1.0 5.5 18.6 6.9 4 12 75.9 0.3 AEG-624-6 60 1.3 3.1 -- 13.1 20.9 6.6 4 13 69.6 -- AEG -625 -7 52 0.8 1.8 2.0 12.2 18.4 5.7 3 12 71.6 --

126

AEG -627 -9 59 0.6 2.8 2.9 9.2 21.3 6.7 3 13 76.2 0.1 AEG -628 -10 61 0.9 2.2 1.0 6.7 19.6 7.9 3 15 106.9 0.2 AEG-629-11 50 0.9 2.2 0.8 11.9 17.4 9.4 4 14 64.4 -- AEG -631 -13 53 1.1 2.4 1.1 0.3 15.8 4.9 4 14 80.9 -- AEG-637-19 64 1.0 2.7 2.2 18.4 18.9 5.9 4 14 69.9 0.2 AEG-657-39 62 1.3 3.1 2.6 8.1 23.9 7.6 4 14 62.6 0.2 AEG -664 -4 62 1.4 5.7 1.9 8.6 15.6 7.1 4 14 92.1 -- AEG-667-7 67 0.9 3.2 3.1 9.6 22.0 5.8 4 15 81.3 0.2 AEG -668 -8 68 0.9 1.9 3.1 13.7 16.5 11.2 4 15 85.2 -- AEG -669 -9 67 1.0 2.6 2.3 12.5 16.8 5.7 4 13 76.7 -- AEG-670-10 64 1.4 3.2 2.3 ------4 13 -- 0.2 AEG -671 -11 67 1.6 2.7 1.4 ------3 14 -- 0.3 AEG-682-22 57 0.7 1.4 0.9 ------3 12 -- 0.2 AEG-683-23 51 0.7 2.1 1.8 ------4 12 -- 0.2 AEG -692 -32 61 0.5 1.6 1.5 1.6 11.8 7.8 4 12 80.3 -- AEG-710-50 53 1.4 3.5 1.9 7.3 14.1 5.3 4 12 70.3 0.3 AEG -711 -1 68 1.8 3.3 2.2 10.3 17.5 7.1 4 12 90.1 0.2 AEG -712 -2 63 1.3 1.8 5.3 5.9 19.5 6.0 4 14 91.0 -- AEG-713-3 68 1.2 2.0 7.0 5.4 21.4 7.3 4 12 76.8 -- AEG -716 -6 61 0.9 2.5 1.2 1.5 17.6 10.0 3 13 84.5 -- AEG-718-8 42 1.4 2.8 0.8 2.4 18.0 9.7 3 13 90.7 -- AEG-719-9 59 2.0 4.9 2.3 2.3 20.2 9.1 4 12 69.1 0.2 AEG -725 -15 64 1.1 2.6 1.5 7.9 17.7 3.8 4 15 95.8 --

127

AEG -738 -28 55 1.1 2.3 2.4 6.1 17.8 10.9 4 13 86.9 0.2 AEG -746 -36 63 1.1 2.5 2.3 9.0 17.3 3.3 4 12 100.3 0.1 AEG-757-3 53 1.4 3.4 1.0 -- 16.5 6.3 4 -- 86.3 -- AEG -759 -5 59 1.0 2.6 5.1 2.3 20.5 6.2 4 14 90.7 -- AEG-760-6 55 1.1 1.8 3.0 13.3 19.7 8.5 3 11 84.5 -- AEG-761-7 57 1.1 2.6 1.6 11.3 19.3 10.1 4 13 88.6 -- AEG -762 -8 53 1.3 2.7 1.8 12.1 15.1 9.9 5 12 71.9 -- AEG-763-9 50 0.9 2.7 2.0 11.4 18.6 9.6 4 12 93.6 -- AEG -766 -12 69 0.9 2.3 0.7 14.0 18.8 7.1 4 10 95.1 -- AEG -791 -37 42 0.4 2.1 2.5 19.0 18.0 10.9 4 12 73.9 -- AEG-803-49 64 1.1 2.8 4.5 21.6 15.9 11.1 4 13 84.1 -- AEG -809 -55 61 0.9 2.4 2.4 12.6 21.7 7.5 4 13 82.5 -- AEG-1003-1 47 0.9 2.4 5.0 5.8 20.8 4.3 3 12 80.3 0.2 AEG-1005-3 52 1.1 2.5 2.0 9.9 20.5 9.1 4 12 73.1 0.2 AEG -1006 -4 53 0.8 1.5 2.8 -- 14.8 5.8 4 -- 58.8 -- AEG-1008-6 48 0.8 1.6 5.4 8.8 23.7 7.7 3 14 72.7 0.3 AEG -1013 -11 64 0.7 2.6 3.0 5.6 17.7 8.3 3 12 73.3 0.2 AEG -1015 -13 53 1.1 2.6 2.1 8.2 20.2 5.6 3 11 71.6 0.2 AEG-1018-16 57 0.6 1.7 5.1 4.5 17.2 4.4 3 10 63.4 0.2 AEG -1049 -47 53 0.3 1.0 2.2 7.0 16.3 7.2 3 12 65.2 -- AEG-1057-4 59 1.0 2.8 3.0 15.7 14.5 11.9 4 15 88.9 0.2 AEG-1059-6 63 1.3 2.3 4.9 5.4 21.6 4.5 4 14 75.5 0.2 AEG -1078 -25 61 1.3 3.4 0.6 12.6 18.2 7.4 4 12 92.4 0.2

128

AEG -1084 -31 52 1.2 2.6 3.5 11.8 17.8 6.4 3 12 67.4 0.3 AEG -1086 -33 62 0.9 2.1 1.6 17.5 19.3 9.2 4 13 76.2 0.3 AEG-1087-34 64 1.3 2.9 1.6 9.5 16.2 5.9 3 13 69.9 0.3 AEG -1088 -35 49 1.1 2.5 3.1 13.2 13.8 8.3 4 13 116.3 -- AEG-1090-37 53 0.8 2.0 2.6 8.2 23.4 8.2 3 12 68.2 0.2 AEG-1094-41 48 1.3 3.3 3.2 7.4 15.6 6.3 4 14 69.2 0.3 AEG -1182 -3 53 1.1 2.4 1.4 9.1 16.3 7.3 3 10 70.8 0.3 AEG-1184-5 73 0.3 1.4 1.1 3.5 6.1 4.8 4 13 77.3 -- AEG -1185 -6 64 1.0 2.5 1.2 6.8 18.1 7.4 4 15 80.9 -- AEG -1187 -8 62 1.5 3.3 3.0 15.3 21.9 8.2 3 13 85.2 0.3 AEG-1188-9 55 0.8 2.2 4.4 6.8 16.6 7.3 4 11 76.3 -- AEG -1189 -10 53 1.2 2.4 3.2 16.6 19.3 9.3 4 11 80.3 -- AEG-1205-1 61 1.6 3.3 3.7 6.5 17.4 4.1 4 12 91.1 0.3 AEG-1206-2 60 1.6 3.7 1.6 5.6 17.6 5.8 4 13 80.3 0.3 AEG -1207 -3 62 0.9 2.5 3.7 ------4 13 -- 0.3 AEG-1208-4 59 1.2 2.2 3.4 ------4 12 -- -- AEG -1209 -5 59 1.1 1.9 1.8 ------3 13 -- 0.3 AEG -1211 -7 71 1.4 3.1 1.0 ------4 14 -- 0.2 AEG-1212-8 92 1.2 3.0 2.6 ------4 16 -- -- AEG -1220 -16 64 1.3 2.7 4.7 ------4 11 -- 0.3 AEG-1255-1 51 0.8 3.0 4.7 ------3 15 -- 0.2 AEG-1263-9 58 0.7 1.5 2.3 ------3 13 -- 0.3 AEG -1264 -10 81 1.4 3.0 2.3 18.0 18.5 10.5 4 17 99.5 --

129

AEG -1265 -11 50 1.5 3.1 1.6 -- 12.5 10.4 4 -- 85.4 -- AEG -1266 -12 81 1.7 4.0 1.2 7.1 17.5 6.4 3 14 89.4 -- AEG-1268-14 59 1.2 2.8 2.8 5.1 17.1 8.8 4 12 84.8 0.3 AEG -1270 -16 63 1.7 3.2 2.3 8.1 20.3 11.8 4 16 81.8 0.3 AEG-1271-17 57 0.9 5.1 1.5 6.9 21.1 5.9 3 13 86.9 0.3 AEG-1272-18 64 1.0 2.3 2.8 9.8 19.8 7.6 3 13 84.6 0.3 AEG -1274 -20 54 1.7 2.8 2.1 8.2 20.8 9.2 3 14 82.2 -- AEG-1276-22 67 1.2 3.0 4.4 15.6 15.9 11.0 4 12 87.0 0.2 AEG -1285 -31 62 1.3 3.0 1.1 21.5 18.2 10.8 4 12 116.8 -- AEG -1296 -42 58 1.5 3.6 3.0 8.9 19.8 7.8 3 12 108.8 -- AEG-1303-49 67 1.6 3.2 2.2 5.4 19.0 9.5 4 13 119.5 0.3 AEG -1306 -2 63 1.6 2.7 1.7 13.3 18.4 13.1 4 13 59.1 0.3 AEG-1308-4 65 1.3 2.3 1.3 8.8 17.3 8.1 3 15 83.1 0.3 AEG-1310-6 57 1.4 2.8 3.2 1.2 17.4 4.8 4 14 85.8 0.4 AEG -1312 -8 82 0.3 1.8 1.7 11.2 20.9 9.8 5 13 120.8 -- AEG-1314-10 85 1.2 2.9 2.4 15.3 14.4 13.3 4 13 61.3 0.2 AEG -1316 -12 78 1.8 3.6 5.8 1.2 17.4 4.8 5 15 92.8 -- AEG -1318 -14 67 0.8 2.5 2.5 4.0 21.2 9.6 4 15 109.6 0.2 AEG-1319-15 83 1.1 2.4 2.3 8.0 19.6 9.4 3 15 92.4 -- AEG -1334 -30 92 1.4 3.2 4.0 4.1 17.1 4.3 3 12 78.3 -- AEG-1348-44 55 1.4 2.7 0.9 4.0 21.2 9.6 4 12 90.6 -- AEG-1355-1 56 1.2 2.6 1.1 4.3 20.7 7.6 3 12 66.6 0.2 AEG -1356 -2 67 1.2 3.0 3.4 4.8 17.1 7.5 4 13 86.5 0.2

130

AEG -1357 -3 55 2.0 3.4 0.6 8.0 19.6 9.4 4 13 107.4 0.2 AEG -1358 -4 59 1.8 3.9 2.6 -- 15.2 7.1 4 -- 81.1 -- AEG-1360-6 51 1.5 3.3 1.0 3.7 15.4 5.4 4 13 122.4 0.2 AEG -1361 -7 61 1.3 2.5 2.9 16.7 16.6 7.1 5 11 92.1 -- AEG-1392-38 58 0.7 2.4 3.0 15.6 16.9 11.1 4 15 84.1 0.2 AEG-1397-43 57 1.3 3.4 2.3 4.0 15.9 8.4 4 15 93.4 0.3 AEG -1407 -2 62 0.9 2.4 1.6 -- 19.1 8.9 2 -- 81.9 -- AEG-1409-4 62 0.6 1.5 3.1 3.6 22.4 9.3 3 13 77.3 0.2 AEG -1411 -6 64 0.8 2.5 1.7 6.1 17.8 10.9 3 12 68.9 -- AEG -1425 -20 57 0.6 2.2 3.3 13.2 13.8 8.3 4 13 83.3 -- AEG-1445-40 47 0.6 1.7 4.9 8.2 23.4 8.2 3 10 73.2 -- AEG -1449 -44 63 0.6 2.0 3.7 16.5 18.9 6.6 3 14 64.6 0.3 AEG-1451-46 62 1.1 3.0 1.9 6.8 18.6 9.7 3 13 72.7 0.3 AEG-1471-15 55 0.9 1.9 2.1 1.5 17.6 10.0 4 10 81.0 0.3 AEG -1478 -22 53 0.4 1.4 3.8 7.4 15.6 6.3 4 11 62.3 0.2 AEG-1479-23 48 0.7 1.8 1.0 3.9 20.1 6.8 4 12 63.8 -- AEG -1480 -24 59 1.0 3.0 0.8 13.4 23.2 7.5 4 11 76.5 0.3 AEG -1495 -39 51 0.8 2.3 1.1 5.0 22.1 7.3 4 10 75.3 0.2 AEG-1509-1 54 1.1 3.4 1.5 19.0 18.0 10.9 4 12 77.9 0.3 AEG -1510 -2 61 0.6 1.6 1.3 21.6 15.9 11.1 4 12 99.1 0.4 AEG-1512-4 61 1.4 2.4 -- 26.8 15.4 4.8 4 13 97.8 -- AEG-1513-5 63 1.3 2.8 6.8 4.0 17.5 6.9 4 14 83.9 0.1 AEG -1514 -6 49 1.4 2.9 5.4 2.3 22.1 8.4 4 14 69.4 --

131

AEG -1515 -7 72 1.4 3.1 2.2 3.5 21.3 7.7 4 12 82.7 0.2 AEG -1519 -11 58 0.7 2.2 2.0 6.8 22.3 9.8 5 10 75.8 0.2 AEG-1528-20 65 0.7 2.7 1.3 15.7 14.5 11.9 3 10 80.9 0.4 AEG -1667 -2 46 1.2 3.2 2.1 5.4 21.6 4.5 3 13 49.5 0.3 AEG-1668-3 57 1.4 2.8 3.3 5.7 21.2 6.8 3 14 55.8 0.2 AEG-1669-4 59 0.7 2.3 1.4 10.3 17.5 7.1 3 12 85.1 0.1 AEG -1670 -5 56 1.4 2.4 5.2 7.0 17.3 5.6 3 13 64.6 0.2 AEG-1671-6 52 1.1 2.8 3.4 5.6 16.9 4.8 3 13 79.8 0.1 AEG -1672 -7 51 0.5 2.3 5.4 7.9 19.2 5.1 4 12 73.1 0.2 AEG -1673 -8 59 0.7 2.3 3.4 7.4 15.6 6.3 3 13 77.3 0.3 AEG-1675-10 47 1.4 3.2 3.3 3.9 20.1 6.8 3 13 79.8 0.2 AEG -1685 -20 58 0.6 3.3 2.5 10.5 17.0 6.7 4 12 74.7 0.2 AEG-1702-37 42 1.0 2.6 1.2 -- 21.8 6.1 3 -- 69.1 0.1 AEG-1708-43 54 0.6 2.7 2.1 7.5 24.3 6.5 3 11 75.5 0.2 AEG -1750 -85 54 0.9 2.4 1.2 9.0 18.1 5.7 4 12 70.7 0.2 AEG-1754-89 52 1.1 2.1 1.4 2.8 21.5 5.4 3 13 75.4 0.2 AEG -1757 -2 53 1.3 3.0 1.2 5.8 19.6 6.5 3 12 70.5 0.3 AEG -1760 -5 52 0.9 2.8 0.1 3.5 21.3 7.7 3 12 67.7 0.2 AEG-1762-7 51 1.1 2.5 2.7 6.8 22.3 9.8 3 12 78.8 0.2 AEG -1763 -8 57 1.1 3.1 3.8 5.2 23.4 5.3 4 10 60.3 0.3 AEG-1764-9 47 1.4 3.5 5.5 4.0 17.5 6.9 3 11 59.9 0.2 AEG-1765-10 45 1.4 3.4 2.2 2.3 22.1 8.4 3 12 58.4 0.2 AEG -1773 -18 54 1.0 2.5 1.0 6.1 2.7 8.0 3 12 46.0 0.2

132

AEG -1793 -38 54 1.2 2.4 0.9 4.0 17.5 6.7 3 11 64.7 -- AEG -1796 -41 59 0.9 2.1 1.7 6.9 21.1 5.9 3 12 63.8 0.2 AEG-1805-50 54 1.3 3.1 1.5 7.6 20.4 9.0 3 10 61.0 0.2 AEG -1860 -1 53 0.9 2.1 1.9 6.5 19.0 7.1 3 13 51.1 0.2 AEG-1861-2 56 1.5 3.3 1.9 9.1 18.4 9.3 3 11 58.3 0.2 AEG-1864-5 47 0.6 1.5 4.7 8.1 17.6 4.4 3 13 61.4 0.2 AEG -1865 -6 47 1.0 2.8 6.6 8.9 19.8 7.8 3 12 65.8 0.3 AEG-1866-7 55 1.6 3.5 2.0 5.4 19.0 9.5 3 13 55.5 0.2 AEG -1873 -1 57 1.0 2.5 3.3 9.0 18.1 6.8 4 13 76.8 -- AEG -1874 -2 53 0.8 2.3 0.9 5.3 18.5 7.2 3 11 64.2 0.3 AEG-1875-3 55 0.4 1.3 1.3 7.1 17.5 6.4 4 12 48.4 0.2 AEG -1877 -5 61 0.7 1.4 2.2 15.2 21.0 7.1 4 12 64.1 0.3 AEG-1878-6 85 1.4 2.4 4.8 3.9 16.2 6.1 6 15 74.1 -- AEG-1879-7 87 0.7 1.7 0.7 35.4 17.5 4.0 4 12 81.0 -- AEG -1880 -8 59 0.5 1.8 0.8 12.8 18.5 9.1 4 13 78.1 0.3 AEG-1882-10 61 0.8 2.4 1.0 7.3 22.1 9.2 3 15 82.7 -- AEG -1912 -40 62 0.4 2.0 1.0 2.7 11.4 7.6 4 13 76.1 -- AEG -1913 -41 63 0.6 2.3 2.3 8.2 20.8 9.2 4 11 72.2 0.2 AEG-2052-9 32 1.3 2.9 2.0 5.8 19.6 6.5 4 15 91.0 0.2 AEG -2055 -12 66 1.0 2.3 2.1 3.5 21.3 7.7 3 16 88.7 0.2 AEG-2058-15 63 1.5 3.7 1.4 16.8 16.5 2.3 4 10 77.3 0.3 AEG-2062-19 60 1.6 3.3 0.7 5.6 15.9 4.9 4 12 67.4 0.2 AEG -2065 -22 54 1.1 2.5 2.2 12.8 17.4 10.6 3 13 83.6 0.2

133

AEG -2244 -1 51 1.1 2.2 1.7 ------3 13 -- -- AEG -2247 -4 61 0.8 1.8 2.9 ------4 12 -- 0.2 AEG-2248-5 70 1.2 3.0 4.7 ------4 15 -- 0.2 AEG -2250 -7 81 0.4 1.8 6.1 ------4 15 -- -- AEG-2251-8 61 1.1 2.3 2.0 ------4 15 -- 0.2 AEG-2252-9 60 0.9 2.3 1.6 ------5 14 -- -- AEG -2253 -10 63 1.2 2.3 2.2 ------4 14 -- -- AEG-2265-22 52 1.0 3.1 4.1 ------4 11 -- 0.3 AEG -2275 -32 63 1.3 2.1 2.4 ------4 11 -- 0.2 AEG -2277 -34 87 0.5 1.4 0.6 -- 17.1 8.2 4 -- 81.2 0.2 AEG-2284-41 61 0.4 1.7 3.7 6.5 19.0 7.1 4 12 78.1 -- AEG -2340 -3 69 1.0 3.1 0.7 9.1 18.4 9.3 4 14 98.3 -- AEG-2341-4 62 0.9 2.6 1.4 8.1 17.6 4.4 3 14 78.9 -- AEG-2342-5 63 1.2 2.7 3.3 8.9 19.8 7.8 4 13 86.8 0.2 AEG -2343 -6 67 1.2 6.9 3.1 5.4 19.0 9.5 3 12 79.5 0.3 AEG-2893-30 60 0.8 2.3 2.0 1.2 17.4 4.8 3 14 37.8 -- AEG -2894 -31 52 1.0 3.5 2.7 4.0 21.2 9.6 3 14 44.6 0.2 AEG -2895 -32 48 1.0 2.6 2.6 8.0 19.6 9.4 4 13 49.4 0.1 AEG-2897-34 57 0.8 2.7 4.8 4.1 17.1 4.3 3 14 38.3 0.2 AEG -2898 -1 49 1.1 2.7 5.2 6.5 17.4 4.1 3 12 66.1 0.2 AEG-2899-2 49 1.2 2.8 3.5 5.6 17.6 5.8 3 11 65.3 0.2 AEG-2947-0 52 1.0 2.2 1.0 4.0 15.9 8.4 4 11 59.4 -- AEG -2949 -0 52 0.7 1.7 0.7 -- 10.1 4.4 4 -- 80.9 --

134

AEG -2972 -0 52 0.5 1.1 1.6 -- 12.1 3.9 3 -- 48.9 -- AEG -2974 -0 44 1.3 2.5 5.5 9.5 16.2 5.9 3 10 68.9 -- AEG-2993-0 53 1.2 3.4 1.1 13.2 13.8 8.3 3 13 68.3 -- AEG -3036 -0 58 0.3 1.4 1.5 8.2 23.4 8.2 4 12 47.2 -- AEG-3039-0 58 1.4 3.8 1.6 8.8 23.7 7.7 4 14 65.7 -- AEG-3040-0 67 1.3 3.0 1.9 5.6 17.7 8.3 4 13 63.3 -- AEG -3141 -1 71 1.3 2.1 1.4 1.5 17.6 10.0 4 13 44.0 -- AEG-3336-1 48 0.9 2.5 2.6 2.4 18.0 9.7 3 12 69.7 -- AEG -3337 -2 66 1.2 2.8 3.3 2.3 20.2 9.1 4 12 70.1 0.3 AEG -3338 -3 53 1.4 2.8 1.8 7.9 17.7 3.8 3 12 64.8 0.1 AEG-3339-4 57 1.1 3.0 4.4 9.0 17.3 3.3 3 12 63.3 -- AEG -3345 -10 47 1.2 3.9 1.7 -- 16.5 6.3 3 -- 63.3 -- AEG-3346-11 84 1.4 4.0 1.6 2.3 20.5 6.2 3 14 42.2 0.2 AEG-3355-20 47 -- -- 2.7 7.2 17.5 6.6 3 13 54.6 0.3 AEG -3375 -40 53 -- -- 1.1 12.6 21.7 7.5 3 12 59.5 -- AEG-3376-41 52 0.7 2.2 6.7 5.8 20.8 4.3 3 12 63.3 -- AEG -3380 -45 62 1.0 2.1 3.5 2.1 21.4 6.9 3 11 66.9 0.2 AEG -3403 -1 83 1.2 2.7 3.2 11.3 19.3 10.1 4 13 77.1 -- AEG-3407-5 63 0.7 2.0 3.0 12.1 15.1 9.9 4 16 88.9 -- AEG -3412 -10 63 1.2 2.3 2.2 3.9 16.2 6.1 4 15 76.1 0.2 AEG-3422-20 64 0.9 2.4 4.6 6.1 17.8 10.9 4 15 65.9 0.2 AEG-3432-30 54 0.5 1.9 2.1 16.5 18.9 6.6 4 12 66.6 0.2 AEG -3439 -37 63 0.9 2.7 5.5 6.8 18.6 9.7 4 13 80.7 --

135

AEG -3463 -1 56 0.9 2.8 5.9 9.5 16.1 6.5 2 13 61.5 0.2 AEG -3464 -2 66 0.8 2.1 2.6 8.2 20.9 5.7 3 14 44.7 0.2 AEG-3465-3 76 0.8 2.4 1.6 9.0 18.1 6.8 3 11 47.8 0.2 AEG -3466 -4 52 1.0 2.7 1.9 7.3 22.1 9.2 3 12 70.2 0.2 AEG-3474-12 47 0.6 1.8 4.1 11.4 18.6 9.6 3 12 68.6 0.1 AEG-3478-1 69 1.5 3.5 1.7 10.3 17.5 7.1 3 12 49.1 0.2 AEG -3484 -7 52 0.5 1.9 1.0 5.9 19.5 6.0 3 12 62.0 0.2 AEG-3486-9 53 1.0 2.5 1.7 5.4 21.4 7.3 3 13 57.3 0.2 AEG -3491 -14 57 0.8 2.3 3.4 9.6 22.0 5.8 3 12 56.8 0.2 AEG -3498 -21 48 0.9 2.8 0.9 13.7 16.5 11.2 3 13 90.2 0.4 AEG-3505-28 50 1.1 2.5 1.2 12.5 16.8 5.7 4 12 68.7 0.2 AEG -3507 -30 53 1.2 3.5 2.4 9.2 21.3 6.7 4 11 30.7 -- AEG-3731-6 87 1.3 3.0 1.6 6.7 19.6 7.9 3 11 77.9 -- AEG-3765-40 63 0.8 2.3 3.9 15.6 17.0 10.7 4 13 69.7 0.2 AEG -3771 -46 61 0.9 2.7 1.3 5.6 21.4 7.0 3 13 72.0 0.3 AEG-3931-6 47 0.7 1.9 1.5 9.7 20.2 6.4 3 13 50.4 0.2 AEG -3932 -7 58 0.5 1.9 2.5 5.0 22.1 7.3 3 10 78.3 -- AEG -3986 -1 63 1.1 2.7 2.4 19.0 18.0 10.9 4 16 85.9 0.2 AEG-3988-3 57 1.1 2.8 4.0 21.6 15.9 11.1 4 16 82.6 0.2 AEG -3995 -10 64 0.6 2.3 1.6 12.6 21.7 7.5 4 16 69.5 0.1 AEG-4001-16 67 0.6 2.3 2.7 5.8 20.8 4.3 3 14 62.3 0.1 AEG-4005-20 63 1.1 3.0 2.2 9.9 20.5 9.1 4 15 63.1 0.3 AEG -4015 -30 68 0.6 2.5 2.0 13.3 19.7 8.5 3 16 82.5 --

136

AEG -4025 -40 62 1.0 2.6 0.9 11.9 15.8 8.2 4 12 69.2 0.2 AEG -4026 -41 73 1.1 2.4 1.4 4.5 17.7 7.8 3 14 76.8 0.2 AEG-4075-16 91 1.0 1.9 1.7 10.1 17.6 12.7 4 16 94.7 0.2 AEG -4099 -40 61 0.8 2.9 1.0 6.6 17.0 9.8 3 13 71.8 0.2 AEG-4160-1 72 1.5 3.5 2.0 7.2 17.9 8.0 5 9 81.0 0.2 AEG-4161-2 63 1.7 4.0 1.5 12.5 19.3 9.1 4 17 97.1 0.1 AEG -4162 -3 72 0.6 1.8 1.1 19.2 20.4 10.1 4 15 84.6 -- AEG-4163-4 63 1.3 3.6 0.7 7.4 18.9 5.8 4 13 82.8 -- AEG -4166 -7 62 1.2 2.8 1.2 5.5 18.6 6.9 3 12 89.9 -- AEG -4185 -26 66 1.3 3.3 1.9 13.1 20.9 6.6 4 13 76.6 0.2 AEG-4191-32 61 1.1 2.5 1.9 12.2 18.4 5.7 4 12 40.7 -- AEG -4194 -35 66 1.0 2.2 2.6 4.9 17.7 9.4 4 13 91.4 -- AEG-4542-2 64 1.5 3.9 1.5 15.1 18.4 13.5 4 15 85.5 0.2 AEG-4543-3 83 1.2 2.5 2.1 15.1 18.6 7.6 3 14 88.6 0.3 AEG -6327 -1 71 0.9 1.7 0.4 3.9 17.5 3.8 4 12 55.8 -- AEG-6328-2 69 0.7 2.0 1.1 5.3 17.8 9.6 4 15 54.6 -- AEG -6329 -3 53 1.1 3.1 1.4 1.1 18.0 7.3 3 10 72.3 0.2 AEG -6330 -4 57 1.4 2.4 2.0 1.6 11.8 7.8 4 12 79.8 0.3 AEG-6371-0 52 0.9 2.1 2.2 7.3 14.1 5.3 3 13 75.3 -- AEG -6763 -1 67 1.3 3.3 1.4 8.8 23.7 7.7 3 12 82.2 -- AEG-6764-2 83 1.4 2.8 1.6 5.6 17.7 8.3 4 15 81.8 0.3 AEG-6765-3 59 1.5 2.9 5.2 8.2 20.2 5.6 4 15 81.6 -- AEG -6766 -4 63 1.9 4.2 4.5 4.5 17.2 4.4 4 12 79.9 0.2

137

AEG -6767 -5 68 1.4 3.1 2.5 7.0 16.3 7.2 4 15 85.7 -- AEG -6781 -1 58 0.9 2.6 0.9 15.7 16.3 6.2 4 13 71.7 0.2 AEG-6782-2 64 0.5 2.2 0.7 3.3 19.5 9.4 3 14 109.4 0.2 AEG -6783 -3 64 0.4 1.4 2.1 18.4 18.3 6.5 4 14 82.5 -- AEG-6784-4 59 1.2 2.7 2.9 2.2 17.9 7.0 4 13 86.5 0.2 AEG-8696-1 57 1.1 2.7 1.0 17.4 19.8 7.5 3 13 52.5 -- AEG -8698 -3 63 1.5 3.1 1.9 -- 20.6 8.5 3 -- 73.0 -- AEG-8705-10 57 0.7 1.9 2.0 7.4 17.7 5.7 3 13 77.7 -- AEG -8710 -15 49 0.6 1.9 2.5 3.4 13.5 7.5 3 13 37.5 -- AEG -8718 -23 63 1.0 2.3 6.6 2.9 16.7 7.2 3 12 81.7 -- AEG-8724-29 58 1.0 2.6 2.3 1.8 16.4 6.6 3 15 71.1 -- AEG -8725 -30 64 0.6 1.9 1.1 7.5 19.3 8.1 3 12 52.1 -- AEG-8735-40 85 1.1 1.1 2.0 5.2 22.8 8.2 3 11 81.2 0.2 AEG-8760-15 61 1.4 3.6 7.6 8.6 17.8 7.5 3 8 57.5 -- AEG -8769 -24 59 0.9 1.9 1.7 5.9 13.6 4.2 3 13 66.2 -- AEG-8771-1 62 1.2 2.9 1.2 8.1 18.1 14.3 3 12 75.8 0.2 AEG -8772 -2 63 0.7 1.7 1.7 17.7 17.2 8.6 3 11 68.6 0.3 AEG -8773 -3 52 0.9 2.2 0.8 12.2 15.1 5.6 3 12 62.6 0.2 AEG-8779-1 62 1.4 2.9 2.5 6.3 22.8 8.9 4 14 78.9 0.1 AEG -8781 -3 74 1.4 2.9 3.5 8.9 17.8 9.1 3 12 70.1 -- AEG-8794-1 72 1.5 3.4 4.8 1.6 15.5 7.3 4 12 81.8 -- AEG-8796-3 63 1.6 4.6 2.7 11.9 17.4 9.4 4 15 111.9 -- AEG -8797 -4 72 1.4 3.1 2.0 2.9 16.7 7.2 4 12 79.2 --

138

AEG -9521 -0 81 0.8 2.8 1.6 4.6 15.8 2.4 3 14 59.4 -- AEG -9522 -1 62 0.8 2.9 1.4 0.3 15.8 4.9 3 12 53.9 -- AEG-9523-2 62 0.9 2.9 3.3 18.4 18.9 5.9 3 13 84.4 0.2 AEG -9524 -3 86 0.6 2.5 2.1 8.1 23.9 7.6 3 12 66.6 -- AEG-9525-4 61 1.3 2.7 2.1 21.0 19.3 6.3 4 12 74.8 0.2 AEG-9527-1 56 2.3 5.0 3.6 16.7 18.6 7.5 3 12 67.5 0.2 AEG -9528 -2 59 0.9 2.4 2.4 9.5 16.9 5.2 3 12 70.2 -- AEG-9529-3 69 0.7 1.9 2.1 15.1 18.4 13.5 3 16 89.0 -- AEG -9546 -2 59 1.3 2.5 1.2 7.9 19.4 6.0 3 11 66.0 -- AEG -9547 -1 61 1.2 2.7 1.5 17.7 18.5 5.4 3 13 69.4 -- AEG-9548-1 55 1.2 2.7 1.2 6.5 19.4 8.8 3 11 45.8 -- AEG -9573 -0 55 1.4 2.7 4.1 7.5 22.2 3.5 3 13 37.5 -- AEG-9574-0 47 1.0 2.5 3.0 12.5 22.9 3.3 3 12 64.8 -- AEG-9575-0 51 1.2 2.2 4.2 9.0 20.9 4.7 3 12 53.2 -- AEG -9576 -0 51 1.1 2.2 1.7 2.5 22.3 6.1 2 12 59.6 -- AEG-9591-0 57 2.1 3.6 3.7 13.3 19.7 8.5 4 12 83.0 -- AEG -9614 -2 71 -- 2.0 2.5 11.3 19.3 10.1 4 17 89.6 0.2 AEG -9615 -3 88 1.7 3.4 2.9 9.2 21.3 6.7 4 17 80.2 -- AEG-9616-4 79 1.6 4.0 1.6 11.4 18.6 9.6 4 15 97.6 -- aData are not available.

139

Experiment 2 Accessions HD LA1 LA2 LAF LP LS LA NN NS HP 30KW AEG-13-1 37 0.8 1.7 2.5 4.5 13.5 5.2 3 11 46.0 0.2 AEG-14-2 46 0.7 1.8 2.6 5.0 15.7 12.5 3 13 65.8 0.3 AEG -16 -4 44 0.6 1.2 2.7 2.6 16.7 6.5 3 14 57.5 0.3 AEG-17-5 46 0.6 1.7 1.2 1.5 13.4 10.1 4 11 57.5 0.4 AEG -19 -7 42 0.6 1.6 0.8 5.6 10.9 2.5 4 13 55.8 0.3 AEG -20 -9 35 0.5 1.3 1.7 2.7 12.5 7.0 3 10 40.2 -- AEG-21-10 36 0.6 1.0 2.2 4.8 11.5 6.8 3 10 43.7 -- AEG -22 -11 37 1.0 1.9 3.3 3.3 13.3 7.9 3 10 50.8 0.2 AEG-23-12 41 0.9 1.0 2.7 3.5 14.8 6.6 3 13 55.2 -- AEG-24-13 42 1.2 1.4 1.7 3.2 12.6 8.0 4 10 53.3 0.3 AEG -25 -14 38 1.1 1.3 3.6 1.4 16.4 6.0 3 12 47.1 0.3 AEG-26-15 38 0.2 1.1 2.2 4.1 14.2 6.5 3 11 50.2 -- AEG -27 -16 46 0.8 1.4 1.9 0.0 16.1 7.6 4 13 65.8 0.2 AEG -28 -17 36 1.0 1.9 2.7 5.0 14.2 6.3 3 14 50.6 0.2 AEG-29-18 36 0.6 1.1 1.9 0.0 10.8 6.9 3 10 41.2 -- AEG -30 -19 36 0.9 1.7 2.9 7.0 14.2 -- 3 13 49.5 -- AEG-249-1 47 0.7 0.7 3.3 2.9 16.6 8.0 3 13 58.3 -- AEG-250-2 44 0.9 1.7 2.0 5.5 16.8 6.4 4 14 60.1 0.4 AEG -251 -3 45 0.7 1.5 1.3 2.2 16.5 4.5 4 14 65.0 -- AEG-264-19 45 0.5 0.6 2.2 3.2 11.6 6.8 4 11 49.7 0.3 AEG -267 -23 46 1.3 1.1 2.7 6.5 16.8 6.9 3 15 60.2 0.3

140

AEG -268 -24 47 0.6 0.9 3.4 12.5 14.5 8.3 3 15 55.3 0.3 AEG -271 -27 51 0.6 1.1 1.7 14.2 10.5 8.9 3 8 41.9 -- AEG-274-30 43 1.1 2.7 1.5 7.3 14.3 7.2 4 12 63.7 0.3 AEG -280 -37 44 0.7 1.1 2.3 8.0 16.2 9.3 4 11 70.9 0.3 AEG-281-40 43 0.7 1.2 0.9 10.9 15.4 11.3 4 13 81.6 0.4 AEG-282-41 48 0.6 0.7 2.2 12.8 16.0 7.0 4 13 79.2 - - AEG -284 -44 47 0.5 0.7 2.1 5.0 12.3 7.2 4 11 62.7 -- AEG-289-49 45 1.1 1.6 0.8 1.8 13.6 6.1 4 12 54.6 -- AEG -298 -5 51 0.9 1.9 1.7 5.8 14.5 11.5 3 12 77.2 0.4 AEG -299 -6 48 0.8 1.9 2.1 -- 17.5 10.3 3 14 64.0 0.4 AEG-300-7 48 0.6 1.1 1.4 1.0 13.7 -- 4 12 66.0 0.3 AEG -302 -9 51 0.6 1.5 3.8 3.6 10.4 10.8 4 10 56.1 0.4 AEG-303-10 43 1.1 1.6 1.9 11.6 13.2 7.9 4 13 75.3 0.4 AEG-479-23 38 0.6 0.9 2.4 -- -- 5.9 3 -- 41.6 -- AEG -480 -24 46 1.2 1.5 1.1 1.8 16.2 12.5 3 14 62.8 -- AEG-622-4 45 0.7 1.7 2.7 12.5 17.6 7.1 4 15 78.2 0. 3 AEG -623 -5 46 0.6 0.8 2.5 0.3 15.6 8.6 4 12 63.9 0.3 AEG -624 -6 45 0.7 2.0 4.2 9.0 16.4 7.6 4 13 74.3 0.3 AEG-625-7 43 0.6 0.8 3.3 11.4 12.9 5.5 3 12 64.1 0.2 AEG -627 -9 42 0.6 1.8 3.1 12.1 17.2 6.4 3 13 64.6 -- AEG-628-10 43 0.6 1.1 1.5 18.2 15.8 4.8 3 15 76.5 -- AEG-631-13 47 0.5 1.3 2.4 -- 17.8 10.7 4 14 69.6 0. 3 AEG -637 -19 42 0.8 1.6 3.4 4.4 17.8 5.9 4 14 68.6 0.2

141

AEG -657 -39 45 1.0 2.5 2.6 5.8 17.8 10.0 4 14 86.0 0.3 AEG -664 -4 51 0.9 2.2 1.8 11.2 15.3 8.6 4 14 78.4 0.3 AEG-667-7 -- 1.0 1.2 ------0.2 AEG -668 -8 51 0.5 1.0 1.8 4.5 16.5 6.5 4 15 63.2 -- AEG-670-10 44 0.6 1.7 0.9 4.5 17.0 7.0 4 13 70.2 -- AEG-671-11 48 0.7 1.5 1.4 6.2 14.0 9.6 3 14 64.5 0.4 AEG -682 -22 47 0.6 1.0 4.3 3.4 16.4 7.5 3 12 60.3 -- AEG-683-23 45 0.5 1.0 4.8 11.8 15.6 9.2 4 12 68.4 0.3 AEG -710 -50 38 0.6 1.5 1.2 13.5 15.0 7.2 4 12 66.3 0.2 AEG -711 -1 45 0.5 1.4 1.0 5.9 17.3 7.2 4 12 80.7 0.2 AEG-712-2 47 0.4 2.0 2.2 12.7 19.4 7.8 4 14 86.8 -- AEG -718 -8 46 1.5 1.6 2.7 4.2 19.5 8.3 3 13 79.3 0.4 AEG-719-9 38 0.9 1.9 3.6 5.0 17.9 8.0 4 12 66.4 0.2 AEG-725-15 46 0.7 1.8 2.0 2.9 19.2 8.2 4 15 71.3 0.2 AEG -738 -28 38 0.8 1.4 2.0 7.2 15.2 7.3 4 13 67.2 -- AEG-746-36 47 0.8 1.7 2.3 5.7 18.0 9.5 4 12 83.0 0.3 AEG -757 -3 47 0.9 1.4 2.6 15.3 18.0 3.8 4 15 87.9 0.2 AEG -760 -6 38 1.0 1.6 2.9 8.8 14.5 7.5 3 11 63.8 0.2 AEG-761-7 44 0.6 2.0 2.9 14.0 16.1 9.6 4 13 78.5 0. 2 AEG -762 -8 43 1.0 1.1 1.6 6.0 12.6 9.4 5 12 71.4 0.3 AEG-763-9 37 1.1 1.5 3.0 11.2 15.9 5.5 4 12 72.6 0. 3 AEG-766-12 47 1.6 2.6 1.8 -- 13.0 6.2 4 10 55.1 0.2 AEG -791 -37 -- 1.7 1.7 ------0.2

142

AEG -803 -49 47 0.8 1.5 2.1 6.1 17.0 7.4 4 13 68.7 0.3 AEG -809 -55 43 0.8 1.8 2.6 17.5 16.8 8.3 4 13 84.3 -- AEG-1003-1 36 0.8 2.0 -- 10.6 17.2 7.2 3 12 62.2 -- AEG -1005 -3 38 0.6 1.4 2.9 6.2 12.7 7.5 4 12 55.8 -- AEG-1006-4 43 0.0 0.3 1.1 -- -- 3.0 4 -- 44.8 -- AEG-1008-6 36 0.6 1.3 4.4 5.6 16.7 11.5 3 14 57.7 0.3 AEG -1013 -11 43 0.5 0.8 2.4 -- -- 6.9 3 -- 53.7 0.2 AEG-1015-13 37 0.9 1.4 1.9 2.8 15.0 9.3 3 11 47.9 - - AEG -1018 -16 37 0.5 1.4 3.0 3.8 12.7 6.4 3 10 43.1 -- AEG -1032 -30 38 0.5 0.8 3.9 -- -- 7.1 3 -- 49.2 0.2 AEG-1033-31 36 0.7 1.6 4.5 6.0 15.5 8.2 3 12 58.8 0.3 AEG -1049 -47 36 0.6 1.0 2.8 6.7 16.2 6.8 3 12 49.2 -- AEG-1057-4 -- 0.9 1.5 0.5 4.3 14.2 8.3 4 15 62.8 -- AEG-1059-6 46 0.8 1.4 1.1 7.7 18.2 8.2 4 14 76.8 0. 3 AEG -1078 -25 44 0.8 1.7 0.6 15.8 13.2 7.6 4 12 82.8 0.4 AEG-1084-31 44 0.4 0.9 3.3 12.2 18.1 9.2 3 12 78.9 -- AEG -1086 -33 43 0.8 1.8 1.0 7.5 15.7 6.2 4 13 63.1 0.3 AEG -1087 -34 44 0.8 1.5 2.0 9.0 15.9 7.5 3 13 63.3 -- AEG-1090-37 42 0.6 1.1 -- 15.5 -- -- 3 -- -- 0.3 AEG -1094 -41 43 0.9 1.6 2.1 17.2 15.5 8.5 4 14 64.9 -- AEG-1182-3 43 0.7 1.1 2.5 1.3 12.0 8.6 3 10 51.4 0.3 AEG-1184-5 42 0.5 1.2 1.3 3.8 14.8 7.2 3 12 59.2 -- AEG -1185 -6 46 0.6 1.4 2.3 5.7 18.0 5.8 4 15 74.6 0.4

143

AEG -1187 -8 42 0.8 1.4 4.9 10.0 15.5 7.6 3 13 68.3 -- AEG -1188 -9 43 0.5 0.9 1.9 3.4 12.7 7.1 4 11 61.7 -- AEG-1189-10 38 0.6 1.1 1.6 -- 13.3 7.7 4 11 57.8 -- AEG -1205 -1 46 0.4 0.6 -- 8.5 12.1 10.1 4 12 69.0 -- AEG-1206-2 -- 1.0 1.5 ------AEG-1207-3 51 1.1 1.5 1.2 8.9 17.0 10.0 4 13 76.5 -- AEG -1208 -4 45 0.7 1.5 2.7 17.5 12.6 11.0 4 12 80.1 -- AEG-1209-5 44 0.7 1.2 2.3 16.3 11.2 8.6 3 13 71.4 -- AEG -1211 -7 75 0.6 1.4 0.7 17.0 13.0 9.1 4 14 84.9 -- AEG -1212 -8 75 0.8 1.3 0.8 8.0 17.2 10.0 4 16 83.0 0.2 AEG-1220-16 53 1.0 1.4 2.6 17.3 11.6 10.3 4 11 74.5 -- AEG -1255 -1 43 1.2 1.6 -- 1.2 19.0 8.5 3 15 63.4 0.3 AEG-1263-9 46 1.6 1.6 2.7 7.7 15.8 9.7 3 13 69.0 0. 6 AEG-1264-10 75 1.4 2.0 0.8 13.0 19.0 8.0 4 17 93.8 0.3 AEG -1265 -11 43 0.5 1.3 3.2 6.5 13.4 11.3 4 11 70.1 0.5 AEG-1266-12 76 1.1 2.0 1.5 10.0 14.6 11.8 3 14 81.2 -- AEG -1268 -14 42 0.7 1.5 0.7 7.5 11.5 7.5 4 12 65.3 0.3 AEG -1269 -15 43 0.8 2.0 3.1 16.9 14.7 9.4 4 13 82.9 0.3 AEG-1270-16 51 0.9 0.8 2.5 7.2 15.6 9.3 4 16 73.4 0.3 AEG -1271 -17 46 0.9 1.2 5.7 13.0 16.2 10.6 3 13 75.1 0.4 AEG-1272-18 45 0.5 1.5 4.0 6.5 14.0 10.4 3 13 66.5 0.4 AEG-1274-20 43 1.0 1.2 3.8 6.7 14.8 9.3 3 14 69.4 0.4 AEG -1276 -22 48 0.4 0.9 2.4 15.5 13.0 5.0 4 12 58.5 --

144

AEG -1285 -31 43 1.1 1.3 2.0 17.8 14.4 8.5 4 12 87.9 0.3 AEG -1296 -42 44 1.0 1.3 3.3 17.5 14.0 9.2 3 12 78.9 0.4 AEG-1306-2 46 1.4 1.6 3.0 7.6 13.5 9.8 4 13 69.5 -- AEG -1308 -4 51 1.1 1.3 0.5 5.5 15.3 6.0 3 15 66.6 -- AEG-1310-6 43 1.3 1.8 1.8 15.5 16.8 8.0 4 14 90.3 0.3 AEG-1312-8 75 0.4 1.1 0.4 6.4 14.2 6.6 5 13 73.7 0. 2 AEG -1314 -10 76 0.7 0.9 1.9 1.8 13.7 -- 4 13 62.0 -- AEG-1316-12 76 0.6 1.8 0.2 4.5 16.4 6.8 5 15 75.2 0.2 AEG -1318 -14 51 0.7 1.3 4.2 9.1 16.1 12.5 4 15 75.3 0.4 AEG -1319 -15 76 0.7 0.8 0.5 15.7 18.6 5.5 3 15 72.6 0.3 AEG-1334-30 77 0.8 1.6 0.7 10.5 13.2 11.9 3 12 68.2 0.3 AEG -1348 -44 43 0.4 1.5 3.4 10.2 14.3 6.5 4 12 74.2 0.2 AEG-1355-1 44 0.6 1.3 2.2 2.0 14.2 8.4 3 12 62.8 0.3 AEG-1356-2 45 0.8 1.2 2.6 0.7 15.5 8.0 4 13 67.3 0. 2 AEG -1357 -3 43 1.2 1.9 2.0 14.4 14.5 11.0 4 13 86.6 0.3 AEG-1358-4 38 0.7 1.6 3.1 -- 12.8 6.6 4 12 46.7 -- AEG -1360 -6 44 0.8 1.7 3.0 2.8 16.0 5.9 4 13 68.6 0.3 AEG -1361 -7 47 0.5 0.8 1.1 10.6 14.0 9.6 5 11 80.5 0.3 AEG-1392-38 47 1.1 2.0 2.5 6.4 15.7 7.9 4 15 71.3 0.3 AEG -1397 -43 43 0.9 1.4 2.7 15.0 15.7 6.5 4 15 79.7 -- AEG-1407-2 44 0.5 1.2 ------5.5 2 -- 59.6 0.3 AEG-1409-4 45 0.6 1.1 2.1 -- -- 9.2 3 -- 58.4 0.2 AEG -1411 -6 45 0.6 0.7 1.9 0.8 13.7 9.2 3 12 41.4 0.2

145

AEG -1445 -40 45 0.5 0.8 2.8 4.5 10.7 7.3 3 10 38.7 0.3 AEG -1449 -44 43 0.6 1.2 2.2 8.3 16.9 8.0 3 14 65.3 0.3 AEG-1451-46 46 0.5 0.6 2.9 10.5 16.5 8.6 3 13 67.4 0.4 AEG -1471 -15 43 0.4 0.9 1.0 7.2 12.6 5.6 4 10 65.1 0.2 AEG-1475-19 44 0.6 1.5 2.8 13.6 14.5 8.6 4 11 67.9 0.3 AEG-1478-22 38 0.5 1.4 2.5 1.3 14.5 7.4 4 11 63.7 0.2 AEG -1480 -24 44 0.7 1.1 0.7 6.0 13.7 8.6 4 11 63.4 0.3 AEG-1495-39 37 0.4 0.7 -- 3.1 14.5 7.7 4 10 63.8 0.4 AEG -1509 -1 38 0.9 1.6 2.9 6.6 14.0 6.2 4 12 69.1 -- AEG -1510 -2 43 0.6 1.0 3.2 26.0 13.0 11.3 4 12 90.6 0.3 AEG-1512-4 47 0.4 0.8 2.4 18.1 15.0 10.2 4 13 99.5 0.5 AEG -1513 -5 53 0.5 0.9 3.3 9.2 13.5 7.2 4 14 68.2 0.3 AEG-1514-6 43 1.3 1.9 1.2 12.3 12.8 8.1 4 14 68.8 0.3 AEG-1519-11 43 0.6 1.0 -- -- 10.6 10.5 5 10 61.6 -- AEG -1528 -20 45 1.1 1.2 4.1 5.0 12.3 10.9 3 10 60.1 -- AEG-1667-2 36 1.1 1.9 4.9 12.7 16.8 7.1 3 13 65.7 0.3 AEG -1668 -3 38 0.9 1.9 4.3 4.0 18.4 5.8 3 14 59.6 0.3 AEG -1669 -4 42 0.8 1.7 4.3 8.5 16.3 6.7 3 12 62.7 0.3 AEG-1670-5 42 0.8 1.9 ------8.1 3 -- 62.8 0.3 AEG -1671 -6 37 0.4 1.5 3.5 -- -- 6.2 3 -- 61.1 0.2 AEG-1672-7 37 0.8 2.0 2.9 8.4 15.5 8.9 4 12 62.9 0. 3 AEG-1673-8 44 0.5 0.9 3.7 6.2 16.3 8.5 3 13 63.4 -- AEG -1675 -10 38 0.7 1.4 4.8 -- -- 5.0 3 -- 62.5 --

146

AEG -1685 -20 42 0.7 1.7 2.2 -- -- 9.7 4 -- 62.0 0.3 AEG -1695 -30 38 0.7 1.9 4.5 10.2 15.9 8.6 3 13 64.4 0.2 AEG-1702-37 37 0.9 2.2 5.2 10.4 15.7 9.5 3 13 60.5 0.3 AEG -1708 -43 42 0.5 1.7 1.5 8.0 10.3 7.3 3 11 55.7 0.3 AEG-1750-85 38 0.7 1.8 2.5 3.4 15.9 8.3 4 12 59.3 -- AEG-1754-89 37 0.7 1.4 2.1 2.0 17.5 7.0 3 13 58.2 - - AEG -1757 -2 36 0.8 1.5 3.2 8.7 15.4 6.0 3 12 56.6 0.2 AEG-1760-5 36 0.9 1.5 3.4 6.4 16.6 6.7 3 12 62.7 0. 4 AEG -1762 -7 37 0.9 1.9 4.3 7.7 15.7 6.8 3 12 64.2 0.3 AEG -1763 -8 42 0.5 1.1 1.2 0.6 13.6 5.4 4 10 51.5 0.3 AEG-1764-9 36 0.7 1.7 2.5 6.5 14.0 6.3 3 11 50.1 0.3 AEG -1765 -10 36 0.7 1.9 3.9 6.2 16.5 6.8 3 12 56.7 0.3 AEG-1773-18 42 0.6 1.0 ------6.2 3 -- 56.1 -- AEG-1793-38 42 0.5 1.4 1.8 2.0 14.0 5.7 3 11 49.6 0.3 AEG -1796 -41 42 0.7 1.0 3.9 13.6 14.7 6.5 3 12 59.2 0.2 AEG-1805-50 37 0.6 1.2 2.1 10.0 14.3 7.2 3 10 60.2 0.2 AEG -1860 -1 36 0.5 1.5 4.0 4.8 14.5 4.8 3 13 50.0 -- AEG -1861 -2 36 0.8 1.5 4.2 7.4 12.2 6.4 3 11 50.6 0.2 AEG-1864-5 36 0.8 1.5 2.1 -- -- 9.0 3 -- 55.9 0.2 AEG -1865 -6 35 0.9 1.5 2.5 7.9 15.5 5.7 3 12 57.1 0.3 AEG-1866-7 37 0.8 1.9 2.2 3.3 15.8 8.5 3 13 60.4 0.2 AEG-1873-1 44 0.6 1.1 2.4 3.8 15.3 7.3 4 13 66.2 0. 3 AEG -1874 -2 43 0.8 1.5 2.0 8.7 14.7 7.5 3 11 59.3 0.3

147

AEG -1875 -3 42 0.6 1.5 ------4 -- 62.0 0.3 AEG -1877 -5 45 0.5 0.9 1.7 6.0 15.4 9.3 4 12 68.4 0.3 AEG-1878-6 75 0.7 0.8 ------4.1 6 -- 61.4 0.3 AEG -1880 -8 42 0.5 1.4 2.4 10.5 14.2 8.3 4 13 71.3 0.3 AEG-1882-10 46 0.4 0.7 2.1 10.5 10.5 10.5 3 15 69.6 0.2 AEG-1912-40 46 0.4 1.1 0.9 -- -- 3.9 4 -- 62.4 0.2 AEG -1913 -41 44 0.5 0.8 3.0 4.0 14.2 7.4 4 11 63.2 0.2 AEG-2052-9 19 0.8 1.4 5.0 9.6 18.5 9.3 4 15 81.4 0.3 AEG -2055 -12 52 0.9 1.9 0.7 3.4 19.5 10.1 3 16 76.5 -- AEG -2058 -15 51 0.9 2.1 2.8 6.3 12.6 10.2 4 10 64.0 0.4 AEG-2062-19 46 0.3 1.0 2.4 -- 14.6 9.0 4 12 62.4 0. 2 AEG -2065 -22 38 0.8 1.0 3.5 11.2 15.3 11.1 3 13 76.1 0.4 AEG-2247-4 47 0.7 1.0 1.3 3.2 12.0 8.7 4 12 54.4 0. 3 AEG-2248-5 55 0.2 0.7 1.4 9.8 16.7 7.7 4 15 68.3 -- AEG -2251 -8 47 0.7 1.6 2.9 17.3 17.5 9.2 4 15 81.9 -- AEG-2252-9 55 0.6 1.1 2.9 4.2 16.4 10.5 5 14 74.1 -- AEG -2253 -10 55 0.9 1.5 1.3 -- -- 6.8 4 -- 61.7 -- AEG -2265 -22 38 0.7 2.1 2.3 9.0 13.2 5.6 4 11 48.1 0.3 AEG-2269-26 47 0.5 1.1 2.0 4.8 14.1 11.0 4 12 62.1 0.3 AEG -2275 -32 47 0.9 2.0 1.0 -- -- 10.2 4 -- 56.5 -- AEG-2277-34 77 0.7 1.7 1.9 2.2 16.6 9.0 4 15 63.9 - - AEG-2284-41 46 0.4 0.7 2.2 8.6 14.3 10.2 4 12 66.0 -- AEG -2340 -3 53 0.3 1.2 2.9 3.8 16.1 5.2 4 14 75.0 0.3

148

AEG -2341 -4 44 0.6 1.6 2.3 15.1 16.3 9.2 3 14 79.4 -- AEG -2342 -5 46 0.4 1.4 2.5 13.2 16.5 11.3 4 13 83.1 0.3 AEG-2343-6 48 0.4 1.0 3.8 16.1 15.5 9.8 3 12 75.5 0.3 AEG -2893 -30 42 0.5 1.1 4.0 5.6 17.0 8.8 3 14 52.9 0.3 AEG-2894-31 37 0.5 1.5 4.9 5.2 15.6 8.9 3 14 52.9 -- AEG-2895-32 37 0.6 1.3 1.1 3.1 14.7 8.6 4 13 53.4 - - AEG -2897 -34 38 0.5 1.1 4.2 5.2 15.7 8.5 3 14 46.4 -- AEG-2898-1 36 0.8 1.7 4.1 3.3 14.5 8.8 3 12 47.9 0. 3 AEG -2899 -2 38 0.6 1.4 3.8 8.2 14.5 9.3 3 11 51.4 -- AEG -2947 -0 42 0.6 0.8 1.8 -- 12.8 6.5 4 11 56.2 -- AEG-2972-0 42 0.7 1.0 2.4 2.9 11.3 8.1 3 8 33.8 -- AEG -2974 -0 35 1.0 1.1 4.1 6.0 13.3 7.1 3 10 60.2 -- AEG-2993-0 42 0.5 0.5 3.1 12.2 12.2 9.3 3 13 66.9 -- AEG-3036-0 44 0.7 1.2 1.7 6.8 16.3 5.6 4 12 66.1 -- AEG -3039 -0 43 0.9 1.4 2.2 3.7 15.2 6.7 4 14 64.2 -- AEG-3336-1 38 0.5 1.3 2.9 6.0 15.2 5.4 3 12 56.5 0. 3 AEG -3337 -2 53 0.5 0.7 1.1 -- 14.5 7.3 4 12 61.2 -- AEG -3338 -3 36 0.4 1.7 3.8 10.0 14.6 9.0 3 12 56.9 0.3 AEG-3345-10 38 0.7 1.8 3.1 8.2 14.8 6.6 3 12 56.7 0.3 AEG -3355 -20 37 1.2 2.0 2.9 2.3 18.8 7.7 3 13 47.3 0.2 AEG-3375-40 37 0.5 1.3 3.4 8.0 14.1 6.8 3 12 44.7 0.3 AEG-3376-41 36 0.8 1.8 4.7 0.0 14.8 9.0 3 12 51.4 - - AEG -3380 -45 42 1.0 1.5 2.6 4.0 14.6 7.7 3 11 51.8 0.4

149

AEG -3403 -1 77 0.6 1.2 0.3 2.7 12.3 8.2 4 13 61.3 -- AEG -3407 -5 52 0.4 1.4 1.1 3.3 18.6 7.3 4 16 73.2 0.2 AEG-3412-10 47 0.6 0.5 1.2 -- -- 7.5 4 -- 62.8 -- AEG -3422 -20 46 0.8 1.6 2.8 16.7 17.4 7.0 4 15 77.2 0.2 AEG-3432-30 38 0.5 0.9 1.5 10.8 14.1 9.4 4 12 66.4 0.4 AEG-3439-37 52 0.4 1.1 1.1 12.3 14.2 8.7 4 13 65.9 -- AEG -3463 -1 35 0.5 1.3 3.3 5.1 15.0 6.3 2 13 45.1 0.3 AEG-3465-3 69 0.5 1.0 2.7 2.9 12.8 6.8 3 11 44.2 0.2 AEG -3466 -4 38 0.8 2.3 3.9 4.8 16.5 6.1 3 12 53.6 -- AEG -3474 -12 35 0.5 0.9 2.7 6.7 15.2 5.8 3 12 52.1 -- AEG-3484-7 38 0.2 0.3 1.9 10.0 13.3 8.2 3 -- 55.3 0.2 AEG -3486 -9 38 0.5 1.1 3.3 4.0 13.7 3.9 3 13 45.9 0.3 AEG-3491-14 38 0.6 1.4 3.6 11.2 16.2 8.5 3 12 58.9 0.2 AEG-3498-21 38 0.7 1.8 2.6 1.6 16.1 8.1 3 13 54.8 0.3 AEG -3505 -28 37 0.5 0.8 0.8 0.9 14.0 4.2 4 12 56.4 -- AEG-3507-30 36 0.6 2.0 2.3 1.7 15.3 9.0 4 11 52.4 -- AEG -3765 -40 47 0.6 1.1 2.6 -- 16.1 8.2 4 13 65.8 0.2 AEG -3771 -46 46 0.6 1.5 ------8.8 3 -- 62.9 0.2 AEG-3931-6 35 0.9 2.1 4.7 9.0 17.0 8.0 3 13 96.7 0. 2 AEG -3932 -7 42 0.3 0.3 2.5 13.6 13.8 10.1 3 10 65.0 -- AEG-3986-1 47 0.8 1.5 1.4 12.8 18.7 7.5 4 16 78.8 0.2 AEG-3995-10 53 0.6 1.6 0.6 -- 16.6 6.4 4 16 54.1 -- AEG -4001 -16 53 0.7 1.3 4.5 2.8 17.6 9.1 3 14 54.9 0.2

150

AEG -4005 -20 52 0.8 0.7 1.8 5.8 17.6 7.5 4 15 64.3 -- AEG -4015 -30 54 0.4 1.0 2.1 5.6 19.8 7.9 3 16 79.3 -- AEG-4025-40 43 0.6 0.8 2.9 5.1 15.2 11.0 4 12 68.1 -- AEG -4026 -41 55 0.9 1.0 0.6 4.9 15.0 6.3 3 14 67.1 0.3 AEG-4075-16 77 0.5 0.7 0.9 5.5 14.4 11.3 4 16 74.1 -- AEG-4099-40 42 1.3 1.6 3.7 11.1 12.7 10.1 3 13 74.0 -- AEG -4160 -1 53 1.2 1.2 -- 11.1 15.0 9.2 5 9 66.4 0.3 AEG-4161-2 47 0.7 1.1 2.3 6.7 20.0 5.5 4 17 69.1 0. 2 AEG -4162 -3 54 0.4 0.6 -- 2.0 16.8 7.9 4 15 71.3 0.3 AEG -4163 -4 43 0.5 1.2 1.5 2.7 14.2 6.5 4 13 56.7 -- AEG-4166-7 42 0.4 1.0 1.9 10.0 14.2 6.5 3 12 56.7 0.2 AEG -4185 -26 46 0.5 0.9 4.2 3.3 16.5 -- 4 13 62.0 0.2 AEG-4191-32 44 0.6 1.1 2.9 4.8 13.7 6.4 4 12 70.6 -- AEG-4194-35 53 0.2 0.8 2.7 13.5 16.3 9.4 4 13 80.9 0.2 AEG -4542 -2 53 0.6 1.1 1.7 -- 13.6 7.8 4 15 66.3 -- AEG-4543-3 72 0.7 1.2 0.6 12.1 15.2 3.6 3 14 73.9 0.2 AEG -5000 -3 44 1.2 1.6 2.2 5.0 15.5 5.7 4 13 58.6 0.2 AEG -5002 -5 37 0.4 0.6 1.2 -- -- 5.9 3 -- 62.6 0.2 AEG-5004-7 38 0.8 1.3 3.1 -- 14.0 4.9 3 12 50.5 0.3 AEG -5016 -1 38 1.0 2.1 2.6 7.9 16.2 7.3 6 12 61.7 0.4 AEG-5646-1 63 0.6 1.2 1.0 6.2 16.3 8.2 3 17 66.3 0.3 AEG-5647-2 56 0.6 1.1 1.4 11.3 12.6 11.3 4 10 70.6 0.2 AEG -5648 -3 70 0.5 1.0 1.4 -- -- 8.0 4 -- 60.8 0.3

151

AEG -6329 -3 37 0.9 1.9 2.2 -- 13.8 8.2 3 10 43.3 -- AEG -6330 -4 43 0.8 1.7 1.4 10.5 15.5 7.8 4 12 65.8 0.3 AEG-6371-0 43 0.5 0.7 2.9 4.5 13.2 6.2 3 13 55.1 -- AEG -6764 -2 72 1.2 1.4 0.9 5.6 13.5 4.1 4 15 59.4 -- AEG-6766-4 -- 0.7 1.3 ------AEG-6767-5 48 1.0 1.8 2.4 0.0 18.5 9.0 4 15 76.4 0.2 AEG -6781 -1 42 0.9 1.8 2.2 5.2 17.0 7.3 4 13 75.2 0.2 AEG-6782-2 44 0.5 1.2 3.6 8.8 17.6 8.5 3 14 67.4 -- AEG -6783 -3 48 0.7 1.2 1.9 6.8 17.5 6.8 4 14 69.7 0.2 AEG -6784 -4 46 0.7 1.2 1.4 2.8 17.4 8.8 4 13 72.4 0.2 AEG-8696-1 44 0.6 1.2 3.0 8.2 16.2 7.7 3 13 64.8 0. 3 AEG -8698 -3 46 0.6 1.1 1.1 -- 14.5 9.1 3 12 57.9 -- AEG-8699-4 42 0.5 0.7 1.9 2.5 15.5 7.2 4 13 49.7 0. 1 AEG-8705-10 44 0.7 1.5 2.2 6.8 16.2 7.2 3 13 65.2 -- AEG -8708 -13 47 1.0 2.7 1.5 11.7 14.2 9.5 4 13 76.5 0.4 AEG-8718-23 46 0.5 0.8 2.0 6.0 16.8 8.6 3 12 63.9 -- AEG -8719 -24 43 0.6 1.3 3.3 3.2 16.5 8.2 4 13 65.8 0.2 AEG -8724 -29 46 0.5 1.5 3.1 5.0 16.5 4.8 3 15 56.5 0.2 AEG-8725-30 48 0.6 1.2 2.0 7.7 13.1 6.6 3 12 48.7 0.2 AEG -8760 -15 42 0.7 1.5 1.7 5.5 10.4 7.0 3 8 44.2 -- AEG-8769-24 44 0.7 1.4 4.0 2.5 16.2 8.3 3 13 54.8 0.2 AEG-8770-25 38 0.4 0.9 3.6 8.7 13.3 7.8 3 11 53.8 0.2 AEG -8771 -1 47 1.1 2.0 -- 6.5 15.2 6.9 3 12 56.2 --

152

AEG -8772 -2 44 0.4 0.9 1.9 7.2 14.0 6.7 3 11 65.7 0.3 AEG -8773 -3 37 0.8 1.4 2.2 12.4 13.5 7.5 3 12 61.8 0.3 AEG-8779-1 47 0.8 2.2 0.5 7.4 15.0 6.5 4 14 66.7 0.3 AEG -8794 -1 44 0.9 1.4 4.2 2.7 12.0 8.4 3 12 54.3 0.4 AEG-8795-2 55 1.4 1.7 0.9 7.6 15.4 10.6 4 13 67.6 0.3 AEG-8796-3 47 0.9 1.5 4.0 16.3 17.5 11.0 4 15 85.6 0.2 AEG -9522 -1 43 0.6 1.1 2.1 13.6 13.2 7.2 3 12 73.7 -- AEG-9523-2 44 0.5 0.6 2.7 17.5 14.5 8.0 3 13 74.3 0.2 AEG -9525 -4 46 0.6 1.1 1.1 8.6 13.3 4.8 4 12 62.0 0.2 AEG -9527 -1 44 0.8 1.0 2.8 17.5 14.5 6.5 3 12 69.7 0.3 AEG-9528-2 44 0.5 0.7 1.6 15.0 14.5 7.5 3 12 63.3 0.3 AEG -9529 -3 56 0.4 0.9 2.8 9.1 17.3 5.8 3 16 71.6 0.2 AEG-9530-4 42 0.6 1.4 2.3 -- -- 6.0 3 -- 62.6 0.2 AEG-9546-2 44 0.6 0.6 2.7 10.8 13.8 8.6 3 11 62.9 0.2 AEG -9547 -1 44 0.6 1.0 2.1 10.3 16.5 6.6 3 13 67.7 0.2 AEG-9548-1 37 0.6 1.2 3.5 5.8 14.0 5.2 3 11 57.5 -- AEG -9573 -0 42 0.7 1.3 3.8 5.5 15.4 4.0 3 13 47.9 -- AEG -9574 -0 37 0.8 0.9 1.6 8.0 15.3 3.5 3 12 54.4 -- AEG-9575-0 36 0.7 1.8 2.8 4.8 15.2 7.0 3 12 47.2 -- AEG -9576 -0 36 0.7 1.0 2.6 8.7 15.3 6.0 2 12 49.6 -- AEG-9577-1 38 0.6 1.0 3.8 6.0 17.5 10.0 3 12 41.0 0.2 AEG-9579-3 37 1.0 1.7 -- -- 14.5 5.9 3 13 39.6 0.2 AEG -9581 -5 38 0.9 1.3 3.3 7.8 16.0 6.6 3 11 59.2 --

153

AEG -9583 -0 46 0.8 1.3 2.7 9.5 14.6 8.2 3 13 56.3 -- AEG -9584 -1 38 0.7 1.3 1.6 -- 13.0 5.7 4 9 44.1 0.3 AEG-9586-3 42 0.9 1.9 3.8 -- 16.0 3.9 3 12 49.4 0.2 AEG -9588 -5 36 0.9 2.0 2.6 0.0 17.0 5.3 4 12 52.5 0.3 AEG-9614-2 56 0.3 0.9 1.0 11.0 17.5 7.0 4 17 84.7 - - AEG-9615-3 72 1.0 1.9 0.6 9.8 13.8 6.2 4 17 68.6 0.2 AEG -9616 -4 69 1.1 2.1 0.5 4.0 13.8 4.1 4 15 57.9 -- AEG-9647-1 37 0.4 0.8 2.9 0.0 12.1 7.3 2 10 22.2 -- AEG -9650 -4 36 0.5 0.7 1.8 1.5 14.2 4.7 3 11 45.0 0.2 AEG -9654 -8 36 0.3 0.8 2.3 0.0 11.4 9.2 3 9 34.9 0.2 AEG-9657-11 36 0.7 2.1 2.0 3.0 15.0 2.0 3 10 48.2 0.2 AEG -9660 -14 42 0.4 0.7 1.7 -- 12.4 7.3 4 11 44.7 0.2 AEG-9662-16 36 0.6 0.9 2.3 0.0 14.0 6.8 3 13 47.2 0.2 AEG-9736-1 37 0.9 1.8 2.7 0.0 16.5 6.0 3 14 47.1 0.2 AEG -9738 -3 38 0.3 1.0 3.4 3.5 14.7 8.9 3 12 51.4 0.2 AEG-9740-5 38 0.7 1.4 2.0 -- -- 7.3 3 -- 62.7 0.2 AEG -9742 -7 37 0.7 1.3 3.6 4.4 14.5 5.2 3 12 52.5 0.2 AEG -9744 -9 38 0.6 1.3 3.2 8.0 13.4 8.0 3 11 50.8 0.2 AEG-9746-11 42 0.8 2.3 4.7 -- -- 5.1 3 -- 45.0 0.2 AEG -9748 -13 38 0.6 1.2 5.1 9.6 16.5 5.5 3 15 60.6 0.3 AEG-9750-1 42 0.6 1.1 1.7 4.3 13.3 8.4 3 9 40.3 0.2 AEG-9751-2 41 0.9 1.4 4.3 2.3 14.7 3.8 3 12 53.9 0.2 AEG -9752 -3 38 0.5 1.2 3.7 10.2 15.6 8.3 4 12 64.3 0.3

154

AEG -9753 -4 45 0.4 0.7 0.5 2.2 15.3 6.6 3 13 43.2 -- AEG -9754 -1 36 0.6 1.2 2.9 2.9 17.8 5.8 3 12 50.1 0.2 AEG-9755-1 37 0.8 1.3 2.1 5.8 18.3 7.1 3 15 72.2 0.3 AEG -9757 -1 42 0.9 1.8 ------7.9 4 -- 62.8 0.2 AEG-9758-2 42 0.8 1.4 1.9 -- -- 9.8 4 -- 62.5 0.2 AEG-9838-3 47 1.0 1.5 2.2 -- -- 7.0 4 -- 62.7 -- AE -122 47 0.8 1.1 2.8 11.8 17.6 7.7 3 14 18.8 -- AE-123 ------AE -124 47 0.9 1.1 2.4 1.5 13.5 6.2 3 12 58.1 -- AE -125 36 0.6 1.1 3.0 4.3 16.5 6.8 3 13 52.2 -- AE-320 42 1.6 2.9 1.6 -- 16.2 6.8 4 13 70.7 -- AE -321 56 0.8 1.8 1.9 8.3 16.5 5.7 4 15 71.6 -- AE-337 47 1.0 1.1 2.0 18.3 19.0 5.7 4 16 90.6 -- AE-339 42 1.0 1.3 0.5 0.0 14.1 11.5 4 11 62.2 -- AE -340 44 1.1 1.9 2.1 15.4 16.5 8.5 4 14 90.9 -- AE-341 47 0.5 0.8 2.3 13.2 15.3 11.5 4 12 81.7 -- AE -342 56 0.7 0.9 0.5 1.0 15.6 7.8 4 14 60.8 -- AE -412 43 0.9 2.4 1.5 9.5 11.3 4.5 4 14 66.5 -- AE-416 44 0.9 1.3 1.5 15.8 11.8 8.1 3 9 60.8 -- AE -904 43 0.5 1.1 2.5 8.0 10.7 7.5 4 9 60.8 -- AE-905 43 0.7 0.4 2.0 7.5 14.8 6.4 4 14 73.1 -- AE-906 44 0.7 1.2 1.7 10.0 15.2 4.5 4 15 73.5 -- AE -1077 36 0.8 0.9 1.8 5.3 12.2 6.0 3 11 50.1 --

155

AE -1078 37 0.7 1.7 2.7 -- -- 6.6 4 -- 68.1 -- aData is not available.

156

Appendix Table 3. Seedling infection types and general reactions of Aegilops longissima accessions to the stem rust ( Puccinia graminis f. sp. tritici ), leaf rust (Puccinia triticina ) and stripe rust (Puccinia striiformis f. sp. tritici ) pathogens. Puccinia graminis f. sp. tritici

Accessions TTTTF TTKSK IT1 IT2 GenRxn IT1 IT2 GenRxn AEG-13-1 3+4 3 S 1 21 R AEG-14-2 2pl=1/1pl=2 2pl=2/1pl=3-2 R 0;1- 0; R AEG -16 -4 3+ 3 S 23 - 1 R AEG-17-5 2pl=21cn/1pl=34 1pl=1/1pl=3+ H 0; 0; R AEG-19-7 4 3 S 2- 0; R AEG -20 -9 3+4 3 S -- a -- -- AEG-21-10 3 3 S ------AEG -22 -11 3+4 3 S 2 2- R AEG-23-12 2pl=3/1pl=3+4 3- S ------AEG-24-13 3 3 S ------AEG -25 -14 3+4 3 S ------AEG-26-15 3C 3 S 1 1+ R AEG-27-16 3+4 3+4 S 3- 3 S AEG -28 -17 3 3 S 1pl=2/1pl=3 - 1pl=2/1pl=3 H AEG-29-18 3-C 3- S ------AEG -30 -19 0; 3+ H ------AEG-249-1 213 21 R 0; 0; R AEG-250-2 4 3+ S 0;1 1 R

157

AEG -251 -3 2pl=1n/1pl=3 23 - H 0; 0;1 R AEG -264 -19 3- 3-1 S 1 0; R AEG-265-21 ------AEG -267 -23 12 0;1 R 0; 0;1 R AEG-268-24 2pl=3/1pl=21 3 H 0; 0; R AEG-271-27 3+4 4 S 0; 1+ R AEG -274 -30 3+ 3+4 S 3 3-2 S AEG-280-37 2pl=3+/1pl=2 4 H ------AEG -281 -40 33+ 1pl=10;/1pl=3 H 0; 0; R AEG -282 -41 3+ 3 S ------AEG-284-44 3+4 4 S 0; 1- R AEG -289 -49 2pl=2c/1pl=3 1pl=10;/1pl=21 H 0; 0; R AEG-290-50 ------AEG-293-54 ------AEG -297 -4 ------AEG-298-5 1pl=3-3/1pl=3N 10; H 0; 0;1- R AEG -299 -6 2pl=0;/1pl=3 00; H ------AEG -300 -7 2pl=3/1pl=2 1pl=3/1pl=0;/1pl=23 -1 H ;1 -- 1 R AEG-302-9 3- 3 S 0; 0; R AEG -303 -10 3+4 3-2 S 0;1 - 0; R AEG-479-23 33+ 3 S 3 3- S AEG-480-24 0;1 0;1- R 1 0;1 R AEG -622 -4 3+4 3+ S 21 2 R

158

AEG -623 -5 33+ 3 S 0;1 -- 0; R AEG -624 -6 3+4 31 S 10; 1 R AEG-625-7 3 3 S 0; 0; R AEG -627 -9 3+4 3+ S 21 1 R AEG-628-10 23 2 R ------AEG-629-11 ------AEG -631 -13 23 - 1pl=10;/1pl=23 - R 0; 0; R AEG-637-19 3+4 3+4 S 0 0; R AEG -657 -39 4 3+4 S 0;1 - 0; R AEG -661 -1 ------AEG-664-4 2pl=3-2/1pl=3+ 2pl=2/1pl=3+ H 0;1- 0; R AEG -667 -7 21 2+ R 0; 0; R AEG-668-8 21 1-0; R ------AEG-669-9 ------AEG -670 -10 2pl=3n/1pl=3+4 3 S 0; 0; R AEG-671-11 33- 33+ S 1- 0;1 R AEG -682 -22 33+ 3 S 0;1 0;1 - R AEG -683 -23 0;1 10; R 0; 0; R AEG-692-32 ------AEG -710 -50 3 3 S 0; 0; R AEG-711-1 3+4 3+4 S 1pl=3/1pl=0; 1 H AEG-712-2 23- 1pl=1/1pl=3 H 0; 0; R AEG -713 -3 ------0; 0; R

159

AEG -715 -5 ------AEG -716 -6 ------AEG-718-8 2pl=3/1pl=21 21 H 0; 0; R AEG -719 -9 3N 3N S 0; 0;1 R AEG-725-15 21 1 R 0; 0; R AEG-738-28 3 3-2 S 23- 2 R AEG -745 -35 ------AEG-746-36 2pl=0;/1pl=3+ 3+4 H 0; 0; R AEG -757 -3 2pl=21/1pl=3 1N H 0; 0; R AEG -759 -5 ------AEG-760-6 3+ 3+ S ------AEG -761 -7 3-cn 3-C S 0; 0; R AEG-762-8 3CN 3- S 0; 0; R AEG-763-9 3+ 3+ S 0;1- 0; R AEG -766 -12 3-2 3 S 3-2 3- S AEG-791-37 12 0;1- R ------AEG -792 -38 ------AEG -803 -49 23 -c 1 R 0;2 - 0; R AEG-809-55 1pl=23-/1pl=3/1pl=3+4 1pl=21/1pl=3-2 H ------AEG -1003 -1 3 3 S ------AEG-1005-3 33+ 33+ S ------AEG-1006-4 33+ 3 S 1 12- R AEG -1008 -6 3 3+4 S 10; 21 R

160

AEG -1011 -9 ------AEG -1013 -11 3 3+4 S 23 - 2+ R AEG-1015-13 3+4 3+4 S 2 2 R AEG -1018 -16 3+4 3+ S ------AEG-1032-30 33+ 3 S 2-3 2- R AEG-1033-31 3+4 3+ S 3- 3 S AEG -1040 -38 ------AEG-1049-47 3+4 3+ S ------AEG -1057 -4 23 - 1+ R 0 0; R AEG -1059 -6 10 ； 1- R 0; 0; R AEG-1078-25 3 3-2 S 0; 0; R AEG -1084 -31 33+ 3 S 2 0; R AEG-1086-33 10 ； 10; R 0;? 0;1 R AEG-1087-34 33+ 1pl=0;1/1pl=3-2 H ------AEG -1088 -35 ------AEG-1090-37 3- 3- S 0;1-- 1- R AEG -1094 -41 3- 3-c S 0; 0; R AEG -1182 -3 30; 3 S ------AEG-1184-5 3 3 S ------AEG -1185 -6 3 3+4 S 0;1 0; R AEG-1187-8 3+4 3+ S 1 1 R AEG-1188-9 3 3 S 0; 0;1- R AEG -1189 -10 3+4 3+ S ------

161

AEG -1205 -1 1 1 R 0;1 - 1 R AEG -1206 -2 ------AEG-1207-3 2pl=3+4/1pl=escape 3+ S 0; 0; R AEG -1208 -4 3+4 3+4 S 23 - 2 R AEG-1209-5 3+ 0; H ------AEG-1211-7 33+ 33- S 0; 0; R AEG -1212 -8 00; 0;1 - R 1pl=2/1pl=0; 0; R AEG-1220-16 3+ 0; H ------AEG -1236 -32 ------AEG -1241 -37 ------AEG-1255-1 2pl=2c/1pl=3 2pl=2/1pl=3 H 1 1- R AEG -1263 -9 00; 10;N R 0; 0; R AEG-1264-10 10; 0;1- R 0; 0; R AEG-1265-11 2pl=0;/1pl=3+ 0; H 10; 1 R AEG -1266 -12 3+ 2pl=3+/1pl=21 H 2- 0;1 R AEG-1268-14 1+ 3 H 0; 0; R AEG -1269 -15 3-c 33 - S 1pl=21/1pl=3 - 2 H AEG -1270 -16 ------0;1 0; R AEG-1271-17 3- 3-2n S 10; 1 R AEG -1272 -18 33+ 4 S 23 - 1 R AEG-1274-20 00; 00; R 23- 1 R AEG-1276-22 0; 10; R 0; 0;1 R AEG -1285 -31 3+ 3+ S 0; 0;1 - R

162

AEG -1296 -42 0;1 10; R 0; 0; R AEG -1303 -49 ------0; 0;1 R AEG-1306-2 0; 0; R ------AEG -1308 -4 0;1 0;1 R 0;1 -- 0; R AEG-1310-6 0;1 0; R 0 1 R AEG-1312-8 21 2 R 1- 0;1 R AEG -1314 -10 21 2 R 1-0; 1- R AEG-1316-12 0; 0; R 0; 0; R AEG -1318 -14 310; 12 H 0;1 0;1 R AEG -1319 -15 3+4 3+ S 0; 0;1 - R AEG-1334-30 23-cn 2 R 0;1 0;1- R AEG -1348 -44 3+ 3 S 0;? 0; R AEG-1355-1 21 2pl=3-2/1pl=1 H 0; 0; R AEG-1356-2 3+4 3+ S 0;1- 0; R AEG -1357 -3 1pl=23/1pl=21/1pl=0;1 2pl=1/1pl=3 H 2pl=0;1/1pl=2 0; R AEG-1358-4 3+4 3+ S 0;1-- 0;1 R AEG -1359 -5 ------AEG -1360 -6 3+ 3- S 21 0;1 R AEG-1361-7 3- 3 S 0; 0; R AEG -1382 -28 ------AEG-1392-38 3 1pl=3+/2pl=10;N H 0; 0; R AEG-1397-43 3+ 3+ S ------AEG -1406 -1 ------2 1pl=3/1pl=1 H

163

AEG -1407 -2 3-2 3 S 2pl=21/1pl=0; 1 R AEG -1409 -4 3- 3-2c S 1pl=21/1pl=2 1 R AEG-1410-5 ------AEG -1411 -6 ------1pl=3 -/1pl=0; 21 H AEG-1425-20 ------AEG-1445-40 2c 21 R 0; 0; R AEG -1449 -44 3-c 2pl=21/1pl=3 at tip H 0; 1 R AEG-1451-46 3-c 3 S ------AEG -1471 -15 0;1 0; R 1 10; R AEG -1475 -19 10; 1 R 0? 1 R AEG-1478-22 3+ 4 S 1pl=3-/1pl=2 1 R AEG -1479 -23 ------1+N 0; R AEG-1480-24 2pl=0;/1pl=3 0;1 H 213- 2 R AEG-1495-39 3 33+ S 2? 21 R AEG -1509 -1 3+ 3+4 S 1- 0;1 - R AEG-1510-2 3+ 1pl=0;/1pl=2c/1pl=3 H 0;? 0; R AEG -1512 -4 2pl=23 -/1pl=21 21 R 0; 1 R AEG -1513 -5 3+ 3+4 S 2 23 - R AEG-1514-6 10; 10; R 1pl=1/1pl=0; 1-0; R AEG -1515 -7 ------0;1 - 0; R AEG-1519-11 10; 10; R 23- 21 R AEG-1528-20 2- 2- R 1pl=2/1pl=23- 21 R AEG -1533 -25 ------

164

AEG -1538 -30 ------AEG -1545 -37 ------AEG-1667-2 3 3+ S 3- 3- S AEG -1668 -3 33+ 3 S 2+ 2 R AEG-1669-4 3+ 33+ S 3- 3 S AEG-1670-5 ------2- 2 R AEG -1671 -6 3+4 3+ S 2c 1 R AEG-1672-7 3+4 3+4 S 3 3- S AEG -1673 -8 3-2 CN 3- S 3+3 3 S AEG -1675 -10 3+4 33+ S 3- 33 - S AEG-1676-11 ------AEG -1685 -20 3+4 3 S 3 3 S AEG-1695-30 3+ 3 S 3 3 S AEG-1702-37 3+4 3 S 3- 3 S AEG -1708 -43 3 3 S 2 2 R AEG-1750-85 33+ 33+ S 3 3-2 S AEG -1754 -89 33+ 33+ S 23 - 2 R AEG -1757 -2 3 3 S 2 21 R AEG-1760-5 33- 3 S 2c 0;? R AEG -1762 -7 3- 1pl=3 -2/1pl=3/1pl=0;1 H 2 2 R AEG-1763-8 3 2pl=3-/1pl=0;1N H 23? 2 R AEG-1764-9 3- 3 S 3 3- S AEG -1765 -10 30; 33+ S 2c 2 R

165

AEG -1773 -18 ------AEG -1793 -38 ------AEG-1796-41 2pl=21/1pl=3 2 H 3- 3- S AEG -1805 -50 30; 3 S 12 1 R AEG-1860-1 3+4 3 S 1 1pl=0;/1pl=2 R AEG-1861-2 3- 3- S 3- 3- S AEG -1862 -3 ------3 0; H AEG-1864-5 33+ 3 S 1 21 R AEG -1865 -6 3 3- S 21 23 - R AEG -1866 -7 33+ 3 S 21 2 R AEG-1873-1 23-c 21 R 2c 2? R AEG -1874 -2 2pl=3 -2/1pl=1 3-2 H 1 23 - R AEG-1875-3 3+ 3+ S 3- 3- S AEG-1877-5 3- 33- S 1+ 21 R AEG -1878 -6 2 2pl=1/1pl=0;1 R 1 12 R AEG-1879-7 ------AEG -1880 -8 21 0; R 0; 0;? R AEG -1882 -10 3+4 3+4 S 3 3- S AEG-1912-40 3 3+ S 2 2 R AEG -1913 -41 33+ 3+ S ------AEG-2052-9 33-c 3 S 1 ;1-- R AEG-2055-12 33+ 3+ S 0; 0; R AEG -2058 -15 3- 3 S 12 23 -? R

166

AEG -2062 -19 3+4 3 S 0; 0; R AEG -2065 -22 3+4 3 S 12 10; R AEG-2244-1 ------0; 0; R AEG -2247 -4 3+4 3 S 10; 1-- R AEG-2248-5 2pl=2/1pl=3 0; H 0; 0; R AEG-2250-7 ------AEG -2251 -8 3 3+4 S 0; 0;1 - R AEG-2252-9 0; 10; R 0; 0;? R AEG -2253 -10 3+4 3 S ------AEG -2265 -22 3+4 4 S 3- 3-2 S AEG-2269-26 10; 12 R 0; 0; R AEG -2275 -32 2pl=23/1pl=2n 23 R 0; 0; R AEG-2277-34 1n 3+ H 0; 0;1 R AEG-2284-41 21 21 R 0? 0; R AEG -2340 -3 3 3+4 S 0? 0;? R AEG-2341-4 21 3+4 H 0;1 0;1- R AEG -2342 -5 0; 3 H 0;1 0; R AEG -2343 -6 3- 3+ S 10; 0; R AEG-2893-30 33+ 3+4 S 2pl=2/1pl=3 3 S AEG -2894 -31 33+ 3+4 S 3 3- S AEG-2895-32 3 3 S ------AEG-2897-34 33+ 3+ S 3- 3 S AEG -2898 -1 3 3+4 S 3 3 S

167

AEG -2899 -2 33+ 3+4 S 2- 2 R AEG -2947 -0 3+ 3+ S ------AEG-2949-0 ------AEG -2972 -0 3- 3 S ------AEG-2974-0 2c 2 R 0;1 0; R AEG-2993-0 1 0;1- R 0; 0; R AEG -3036 -0 3-3 1n H ------AEG-3039-0 0; 0; R 10; 2 R AEG -3040 -0 ------21 1 R AEG -3141 -1 ------AEG-3336-1 0;2 3 H 2c 2 R AEG -3337 -2 1pl=3/2pl=0;? 2pl=3 -2/1pl=3 - H 1pl=1/1pl=2 1 R AEG-3338-3 2pl=3/1pl=12 33+ H 3- 3-2 S AEG-3339-4 ------AEG -3345 -10 3 3 S 10; 1- R AEG-3346-11 ------AEG -3355 -20 3 3 S 1 21 R AEG -3365 -30 ------1 1- R AEG-3375-40 33+ 33+ S 21 2 R AEG -3376 -41 3 3- S 21 1 R AEG-3380-45 33+ 3+ S 21 23- R AEG-3403-1 ------AEG -3407 -5 0; 1N R ------

168

AEG -3412 -10 2pl=1n/1pl=3 - 23 - H 0;? 0; R AEG -3422 -20 21 21 R 0; 0; R AEG-3432-30 33+ 3+ S 1+ 2 R AEG -3439 -37 23 -c 2c R 0? 0; R AEG-3463-1 33+ 3+ S 3 3- S AEG-3464-2 ------AEG -3465 -3 33+ 33+ S 3- 3 S AEG-3466-4 3 33+ S 3 3- S AEG -3474 -12 33+ 3 S 10; 1pl=1/1pl=3 - H AEG -3478 -1 ------3- 3-2 S AEG-3484-7 33+ 3- S 3 3 S AEG -3486 -9 3+4 3+4 S ------AEG-3491-14 33+ 3- S 23-? 2 R AEG-3498-21 3 3 S 11+ 3 H AEG -3505 -28 3+4 3+4 S 3- 3-2 S AEG-3507-30 ------AEG -3731 -6 ------AEG -3759 -34 ------AEG-3765-40 0; 3+ H 0; 0; R AEG -3771 -46 ------0; 0; R AEG-3931-6 3-2 3- S 21 2 R AEG-3932-7 33+ 33+ S ------AEG -3986 -1 3 2pl=2/1pl=3 H 0; 0;? R

169

AEG -3988 -3 ------AEG -3995 -10 33+ 3+4 S 0;1 - 1- R AEG-4001-16 2 22-c R 1 10; R AEG -4005 -20 0; 0;1 R 0;1? 0;1 R AEG-4015-30 10; 1 R 0; 0;1 R AEG-4025-40 3 33+ S 10; 10; R AEG -4026 -41 ------12 1? R AEG-4075-16 3 3-2 S 0;1- 0;1 R AEG -4099 -40 4 4 S ------AEG -4160 -1 2pl=10;/1pl=3 2pl=3/1pl=1 H 1- 1 R AEG-4161-2 3c 3+4 S 33- 1pl=1/1pl=2 H AEG -4162 -3 2pl=1/1pl=2 3+4 H 0; 0; R AEG-4163-4 33+ 3+4 S 1- 1 R AEG-4166-7 0; 0;12 R 0; 0;? R AEG -4185 -26 3 33+ S ------AEG-4191-32 0;1-- 0;1 R 0;? 0; R AEG -4194 -35 33+ 3+ S 0; 0; R AEG -4542 -2 1+0; 1 R ------AEG-4543-3 3-2 3- S ------AEG -4998 -1 ------21 10; R AEG-5000-3 3+ 3 S 1 1 R AEG-5002-5 3 33- S 3 3 S AEG -5004 -7 3 33+ S 2 1-? R

170

AEG -5016 -1 3- 33 - S 0;1 0;? R AEG -5646 -1 3-c 3- S 0 0 R AEG-5647-2 3 3 S 21 2- R AEG -5648 -3 10; 0;1 -- R 0? 0 R AEG-6327-1 ------AEG-6328-2 ------AEG -6329 -3 33+ 33+ S ------AEG-6330-4 33+ 33+ S ------AEG -6371 -0 33+ 3+ S 0; 0; R AEG -6763 -1 3 3+ S ------AEG-6764-2 2pl=21/1pl=3 2 H ------AEG -6765 -3 ------AEG-6766-4 ------AEG-6767-5 33+ 3-2cn S 0;1-- 0; R AEG -6781 -1 33+ 33+ S 10; 1 R AEG-6782-2 12- 10; R ------AEG -6783 -3 1-- 0; 10; R 0; 0; R AEG -6784 -4 3- 3- S 0; ; R AEG-8696-1 3+ 3 S 1 3 H AEG -8698 -3 3+ 3 S 0? 0; R AEG-8699-4 3+4 3+ S 12 1- R AEG-8705-10 2 2+c R 12 0; R AEG -8708 -13 1 10; R 1 0; R

171

AEG -8710 -15 ------AEG -8715 -20 ------0;1 -- 21 R AEG-8718-23 33+ 3+ S ------AEG -8719 -24 3-2 3+ S 0 0; R AEG-8724-29 ------1pl=0;1-/1pl=0; 0; R AEG-8725-30 2pl=3-/1pl=no infection 3n S 0; 0; R AEG -8735 -40 ------AEG-8760-15 3 2pl=0;1/1pl=3 H ------AEG -8769 -24 3-2 3- S 1pl=3+/1pl=0; 3 H AEG -8770 -25 33+ 3 S 3 3 S AEG-8771-1 ------AEG -8772 -2 33+ 3 S ------AEG-8773-3 3 2pl=3/1pl=10; H ------AEG-8774-4 ------AEG -8779 -1 3+4 3+ S 1-0; 1-0; R AEG-8780-2 ------AEG -8781 -3 33+ 3+ S ------AEG -8794 -1 2pl=2/1pl=3+ 2pl=3/1pl=0; H 0; 10; R AEG-8795-2 3 2pl=3/1pl=10; H 0;1 0; R AEG -8796 -3 21n 2pl=3 -/1pl=10; H ------AEG-8797-4 ------AEG-9521-0 ------AEG -9522 -1 3+ 3 S ------

172

AEG -9523 -2 33+ 3+ S 21 23 - R AEG -9524 -3 ------AEG-9525-4 3+ 3+4 S ------AEG -9527 -1 2pl=0;dark n/1pl=3 -c 2cn H 0;? 0; R AEG-9528-2 3c 3-c S 0; 0; R AEG-9529-3 2cn 1pl=3/1pl=1 H ------AEG -9530 -4 3-2c 3 S 0;1 - 2c R AEG-9545-1 ------AEG -9546 -2 3+ 3- S 0;? 0; R AEG -9547 -1 3+ 3+4 S 10; 1- R AEG-9548-1 3+ 33+ S ------AEG -9573 -0 3-c 3+ S 23 - 23 - R AEG-9574-0 3 3 S 21 1- R AEG-9575-0 3 3 S 3 3- S AEG -9576 -0 3 3- S 3-2? 3- S AEG-9577-1 33+ 3 S 2c 2? R AEG -9579 -3 33+ 3+ S 3-2 3- S AEG -9581 -5 33+ 3+ S ------AEG-9583-0 3+ 3 S 1 0;? R AEG -9584 -1 3 3-3 S ------AEG-9586-3 ------AEG-9588-5 33+ 3 S 0 0 R AEG -9591 -0 ------3-2 3- S

173

AEG -9614 -2 21 12 R ------AEG -9615 -3 0;1 2pl=3 -/1pl=0; H 0;1 -- 0;1 -- R AEG-9616-4 3- 3-c S ------AEG -9647 -1 33+ 3 S ------AEG-9650-4 33+ 33+ S ------AEG-9654-8 3 33+ S 3 3- S AEG -9657 -11 3 3 S 2c 2 R AEG-9660-14 33- 3 S 12 2 R AEG -9662 -16 33+ 3+ S 3 3- S AEG -9736 -1 3 3+4 S 3 3- S AEG-9738-3 3+ 3 S 3- 3 S AEG -9740 -5 3 1pl=3/1pl=2 H 0 21 R AEG-9742-7 33+ 3 S 0 23- R AEG-9744-9 33+ 3 S 0 0; R AEG -9746 -11 3 3+ S 3- 3-2 S AEG-9748-13 3 3 S ------AEG -9750 -1 ------3 3 S AEG -9751 -2 3- 3 S 21 0;1 R AEG-9752-3 3 3-2 S 2 2 R AEG -9753 -4 ------AEG-9754-1 3 3+4 S 3 3 S AEG-9755-1 33+ 3+4 S 0;1 2 R AEG -9757 -1 33+ 3+4 S 21 2 R

174

AEG -9758 -2 3 3+ S 1 2 R AEG -9838 -3 ------AE-121 ------AE -122 12 21 R 0; 0; R AE-123 ------AE-124 3+4 3+4 S 10; 12 R AE -125 3-2c 3- S 1 12 R AE-320 3+4 33+ S 10; 1- R AE -321 2pl=2/1pl=3 1pl=2/1pl=1 -- H 1 1-- 0; R AE -334 4 3+ S 2pl=1/1pl=3 -2 10; H AE-335 ------3 3 S AE -337 3+ 3+ S 3- 1 H AE-339 2pl=0;/1pl=3 0;1 H 0? 0;1-- R AE-340 33+ 3+ S 1- 0;1- R AE -341 2? 1 R 0; 0; R AE-342 33+ 3+4 S 0;1 0; R AE -412 33+ 1pl=10;/1pl=2c/1pl=3 H 0; 0; R AE -416 33+ 33+ S 2 0; R AE-417 ------21 2 R AE -904 2pl=21/1pl=3 1-0; H 0; 0; R AE-905 2pl=3/1pl=10; 3 H 0; 0; R AE-906 1-0; 0;1- R ------AE -1077 3+ 3 S 3-2 3- S

175

AE -1078 2c 2+c R ------aSeeds are not available for testing.

Appendix Table 3. continued Puccinia triticina Accessions THBJ BBBD IT1 IT2 GR IT1 IT2 GR AEG-13-1 33+ 3-c S 3+4 3 S AEG -14 -2 1N 0;1 - R -- a -- -- AEG-16-4 0;1-- 0;1- R 0;1- 1 R AEG -17 -5 2c 2 R 3 3+ S AEG -19 -7 0; 10; R 2 2+ R AEG-20-9 ------AEG -21 -10 3 3 S 1pl=0;/1pl=3 4 H AEG-22-11 3+4 3-2 S ------AEG-23-12 1n 1 R ------AEG -24 -13 3+4 3- S 2c? 2c R AEG-25-14 0;1- 0; R 0;1- 0;1- R AEG -26 -15 1pl=10;/1pl=2/1pl=3 2pl=3 -2/1pl=10; H ------AEG -27 -16 1 1 R 12 2 R AEG-28-17 3 3- S 3 3+ S AEG -29 -18 22+ 2- R 3+ 3+ S AEG-30-19 2n 2 R ------AEG-249-1 2 2- R 2 2 R

176

AEG -250 -2 1 0;1 R 1 0;1 R AEG -251 -3 3 3- S 3- 3+ S AEG-264-19 2pl=0;/1pl=2- 0; R 1pl=1--0;/1pl=1 12 R AEG -265 -21 ------AEG-267-23 1 0;1- R 3 3+ S AEG-268-24 3 3 S 3+ 3+ S AEG -271 -27 0; 0;1 R ------AEG-274-30 1pl=2/1pl=3- 2 H 3+ 3+ S AEG -280 -37 0; 0; R 0;1 - 0;1 - R AEG -281 -40 0;1 - 1-0; R 0;1 - 1pl=0;1/1pl=2/1pl=3+ H AEG-282-41 2+ 1 R 3+ 3+ S AEG -284 -44 1- 1-0; R 0;1 - 0;1 - R AEG-289-49 3 3 S 1pl=3/1pl=1-0;/1pl=2-n 1pl=2n/1pl=3 H AEG-290-50 ------0; 1 R AEG -293 -54 10; 1-0; R 1 0;1 - R AEG-297-4 12 2 R ------AEG -298 -5 3+ 3+ S 3 3+ S AEG -299 -6 2 2 R 0; 0 R AEG-300-7 2 2 R 3+ 3+ S AEG -302 -9 3+ 1-0; H ------AEG-303-10 0;1- 0;1- R 0; 0; R AEG-479-23 1+ 2 R 1 1 R AEG -480 -24 1pl=0;/1pl=1/1pl=1 - 1pl=10;/1pl=3 H ------

177

AEG -622 -4 0;1 -- 0; R 0; 0; R AEG -623 -5 2- 12? R 11 - 2+ R AEG-624-6 0; 0;1- R 0;1- 0;1- R AEG -625 -7 0;1 -- 0;1 - R 10; 2pl=1/1pl=2 R AEG-627-9 0;1-- 0;1- R 0; 0;1- R AEG-628-10 2pl=1/1pl=3+ 1pl=1/1pl=3- H 1pl=2/1pl=3 10; H AEG -629 -11 0;1 -- 0; R ------AEG-631-13 3 3 S 1- 0;1-- R AEG -637 -19 2pl=1/1pl=3 1pl=1 -0;/1pl=1/1pl=3 - H 3 3+3 S AEG -657 -39 2- 2 R 3 3+ S AEG-661-1 ------AEG -664 -4 0;1 0;1 - R 1pl=0;/1pl=3+ 3 H AEG-667-7 1 2pl=2/1pl=1-0; R 2pl=3+/1pl=1- 3 H AEG-668-8 2pl=0;/1pl=1 2 R ------AEG -669 -9 ------AEG-670-10 2pl=1/1pl=4 1pl=1/1pl=3+ H 3 3+ S AEG -671 -11 1 2pl=1/1pl=2 R 2+ 0;1 - R AEG -682 -22 2pl=10;/1pl=2 1 R ------AEG-683-23 2pl=2/1pl=1 1 R 0;1- 0;1- R AEG -692 -32 1 2 R 0;1 1pl=2 -/2pl=3 H AEG-710-50 2pl=1/1pl=2 0;1- R 3 3 S AEG-711-1 2pl=1/1pl=0; 2pl=1/1pl=2 R 0;1 2? R AEG -712 -2 2-2 1 R 3? 3 S

178

AEG -713 -3 ------3 2pl=2/1pl=3+ H AEG -715 -5 ------AEG-716-6 ------AEG -718 -8 0; 0; R 1 1pl=3+/1pl=0; H AEG-719-9 2pl=12/1pl=0; 10; R 1 1 R AEG-725-15 0; 0; R 00; 0;1- R AEG -738 -28 0;1 00; R 0; 0; R AEG-745-35 ------AEG -746 -36 0; 2pl=0;/1pl=2 R 2 21 R AEG -757 -3 0;1 -N 1 R 1 12 R AEG-759-5 1 0;1- R 1? 1 R AEG -760 -6 10; 10; R 0; 2pl=2/1pl=0; R AEG-761-7 1 1-0; R 3 33+ S AEG-762-8 0; 0; R 0; 10; R AEG -763 -9 2c 10; R 1pl=3/1pl=2 3+4 H AEG-766-12 21 10; R 2pl=2/1pl=10; 0;1 R AEG -791 -37 0;n 0; R 0; 21 R AEG -792 -38 ------AEG-803-49 0; 1-0; R 0; 0;1-- R AEG -809 -55 0;1 -- 1pl=2/1pl=3 H 2+ 2pl=3+/1pl=1 H AEG-1003-1 21 1pl=3/1pl=2 H ------AEG-1005-3 2-c 1-0; R ------AEG -1006 -4 2 1pl=1/1pl=3 -/1pl=3 H ------

179

AEG -1008 -6 23 - 21 R ------AEG -1011 -9 ------AEG-1013-11 2 1 R 2+ 2pl=3+/1pl=23- H AEG -1015 -13 3 3+4 S 3 3+ S AEG-1018-16 3- 3 S ------AEG-1032-30 1- 1-0; R 0; 10; R AEG -1033 -31 2 10; R ------AEG-1040-38 ------AEG -1049 -47 1-0; 0;1 - R 1pl=2/1pl=3 3- H AEG -1057 -4 2pl=0;1 -- /1pl=1n 1- R 1pl=3/2pl=2n 2n H AEG-1059-6 0;1 0;1- R 0; 1-- R AEG -1078 -25 2pl=2/1pl=0;1 1-0; R 2+ 1pl=0;1 -/1pl=3/1pl=2 H AEG-1084-31 2 2 R 3 3+ S AEG-1086-33 1 0;1- R 1 2 R AEG -1087 -34 2pl=3/1pl=0; 3 H 3 33 - S AEG-1088-35 ------0;1 10; R AEG -1090 -37 21 1-0; R 1 10; R AEG -1094 -41 1n 0;1 - R 1 0;1 - R AEG-1182-3 12- 1-0; R 1 1 R AEG -1184 -5 3 3- S 22+ 22+ R AEG-1185-6 2c 10; R 1 21 R AEG-1187-8 0;1- 10; R 0;1 0;1 R AEG -1188 -9 2- 1pl=1/1pl=3 - H 10; 2 R

180

AEG -1189 -10 2 2- R ------AEG -1205 -1 0; 0;1 - R 1pl=0;1/1pl=1 0;1 - R AEG-1206-2 ------AEG -1207 -3 0;1 - 0; R ------AEG-1208-4 0; 0; R 0; 0;1 R AEG-1209-5 31 1pl=2/1pl=3 H 12 1pl=10;/1pl=2/1pl=3 H AEG -1211 -7 1 12 R 1pl=1 -/1pl=2+ 12 R AEG-1212-8 33+ 3 S 3 3+ S AEG -1220 -16 3 3 S 1pl=3/1pl=2 3+ H AEG -1236 -32 ------AEG-1241-37 ------AEG -1255 -1 0;1 -- 1 R 10; 0;1 -- R AEG-1263-9 2pl=2/1pl=1 1 R 33+ 1pl=12/1pl=2/1pl=3 H AEG-1264-10 0; 0; R 0; 00; R AEG -1265 -11 0; 0; R 0; 00; R AEG-1266-12 2-1 10; R 2- 1pl=0;1--/1pl=2+ R AEG -1268 -14 ------0;1 1 R AEG -1269 -15 1-0; 1- R 3- 3 S AEG-1270-16 1 0; R 0;1- 1 R AEG -1271 -17 10; 0; R 3- 3+ S AEG-1272-18 3- 3 S 2pl=3/1pl=2 2pl=3/1pl=2 H AEG-1274-20 10; 0;1 R 1 10; R AEG -1276 -22 0;1 0;1 - R 0;1 - 10; R

181

AEG -1285 -31 1N 1+ R 3 3+ S AEG -1296 -42 0;1 - 12c R 2+ 1pl=1/1pl=3 H AEG-1303-49 3 3 S ------AEG -1306 -2 10; 10; R 2+ 10; R AEG-1308-4 0;1 21 R ------AEG-1310-6 1-0; 0;1- R 12 0; R AEG -1312 -8 3- 3- S 2pl=3/1pl=2 3 H AEG-1314-10 33+ 33+ S ------AEG -1316 -12 1 0;1 - R 1-0; 1- R AEG -1318 -14 33+ 3 S 3+ 3+ S AEG-1319-15 3+ 3+4 S 2+ 2pl=3/1pl=0;1-- H AEG -1334 -30 1 1-0; R 1 2+ R AEG-1348-44 3+4 33+ S 3? 3- S AEG-1355-1 1n 0;2N R 0; 2pl=0;/1pl=1 R AEG -1356 -2 0;1 - 1-0; R 1 10; R AEG-1357-3 0; 0;1- R 0; 2pl=0;1/1pl=2 R AEG -1358 -4 0;n 0; R 0; 0; R AEG -1359 -5 ------AEG-1360-6 1n 1- R 2+ 2pl=3+/1pl=1 H AEG -1361 -7 0; 1 R ------AEG-1382-28 ------AEG-1392-38 3 3 S 3 33+ S AEG -1397 -43 3- 3-2 S ------

182

AEG -1406 -1 0;n 0; R 0; 2 R AEG -1407 -2 3- 3 S 3-? 3+ S AEG-1409-4 1-0; 1-0; R 0;1- 1-0; R AEG -1410 -5 ------AEG-1411-6 ------2 2 R AEG-1425-20 10; 0;1- R 0; 10; R AEG -1445 -40 10; 10; R 0;1 - 0; R AEG-1449-44 10; 1? R 1 10; R AEG -1451 -46 0; 0; R 1 21 R AEG -1471 -15 2 2- R 2c 0 R AEG-1475-19 23- 2+ R 2 2- R AEG -1478 -22 3 3- S 2+ 2+ R AEG-1479-23 ------2 1 R AEG-1480-24 2pl=23-/1pl=3 23- H 1 1 R AEG -1495 -39 3 3- S 3 3+ S AEG-1509-1 10; 2 R 10; 1+ R AEG -1510 -2 2 2 R 2 2+ R AEG -1512 -4 10; 1-0; R 2+ 2pl=3+/1pl=0;1 - H AEG-1513-5 3- 3 S 0;1 21 R AEG -1514 -6 1- 10; R 10; 2pl=1/1pl=3 H AEG-1515-7 ------2 1 R AEG-1519-11 3-2 3 S ------AEG -1528 -20 1n 1pl=3/1pl=2 H 2+ 2 R

183

AEG -1533 -25 ------AEG -1538 -30 ------AEG-1545-37 ------AEG -1667 -2 1 1 R 2c 2 R AEG-1668-3 0; 0;1- R 0; 0; R AEG-1669-4 10; 1-0; R 1 22+ R AEG -1670 -5 10; 1-0; R 1 0;1 - R AEG-1671-6 1n 10; R 1pl=1/1pl=2 10; R AEG -1672 -7 10; 1-0; R 0;1 10; R AEG -1673 -8 3 3- S 3 3+ S AEG-1675-10 1pl=3/1pl=2 2 H ------AEG -1676 -11 ------AEG-1685-20 10; 0;1 R 0;1- 0; R AEG-1695-30 10; 1-0; R 10; 1 R AEG -1702 -37 10; 0;1 - R 0;1 - 1+ R AEG-1708-43 21 23- R 1 1 R AEG -1750 -85 1-0; 0;1 - R ------AEG -1754 -89 10; 1-0; R 10; 1 R AEG-1757-2 2 10; R 2 2 R AEG -1760 -5 2 10; R 1 1 R AEG-1762-7 1- 1 R 1 1 R AEG-1763-8 1 10; R 2 1 R AEG -1764 -9 1 1-0; R 2 1 R

184

AEG -1765 -10 2 10; R 2 2 R AEG -1773 -18 ------AEG-1793-38 1 1 R 2+ 2+ R AEG -1796 -41 3 3 S 2+ 1pl=3/2pl=2+ H AEG-1805-50 23- 21 R 1 12 R AEG-1860-1 3 3 S 3+ 3+ S AEG -1861 -2 3 3 S 3+ 3+4 S AEG-1862-3 12 1 R 1 1+ R AEG -1864 -5 2pl=1n?/1pl=3 - 3- H 2+ 2c R AEG -1865 -6 3 33+ S 3 3+4 S AEG-1866-7 3+4 3-2 S 3 3+ S AEG -1873 -1 1-0; 0;1 - R 2 1pl=1/1pl=2+/1pl=3+ H AEG-1874-2 2pl0;/1pl=3 0; H ------AEG-1875-3 2 1pl=2/1pl=3- H 2pl=3+/1pl=2 3+4 H AEG -1877 -5 1-0; 0;1 - R 12 2+ R AEG-1878-6 ------3+ 3+ S AEG -1879 -7 ------AEG -1880 -8 1-0; 10; R 1pl=1 -- 0;/1pl=3 - 3+ H AEG-1882-10 0;1- 10; R 2+ 1pl=10;/1pl=3 H AEG -1912 -40 ------2+ 2 R AEG-1913-41 3 3+ S 3- 3+ S AEG-2052-9 10; 12 R 2 2+3 R AEG -2055 -12 10; 1pl=0;1 -/1pl=2 R 2 22+ R

185

AEG -2058 -15 2 2 R 2 2n R AEG -2062 -19 23 - 0;1 - R 3+ 2pl=1 -- 0;/1pl=3+ H AEG-2065-22 10; 0;1- R 0;1 0;1- R AEG -2244 -1 ------3+ 2pl=3/1pl=0;1 - H AEG-2247-4 0; 0;1- R 22+ 22+ R AEG-2248-5 2 1N R 3 33+ S AEG -2250 -7 ------AEG-2251-8 3 3 S 3+ 3+ S AEG -2252 -9 3 3 S 3? 3-2 S AEG -2253 -10 4 3 S 3? 3- S AEG-2265-22 2 23-c R 3+ 3+ S AEG -2269 -26 1pl=0;/1pl=1/1pl=2 2 R 3 3- S AEG-2275-32 3-2c 1 H 10; 1 R AEG-2277-34 1 10; R 1N 1 R AEG -2284 -41 10; 0; R 3+ 3+ S AEG-2340-3 10; 1-0; R 2+ 0;1 R AEG -2341 -4 0;1 - 0;1 - R 3+ 2pl=0;1 -- /1pl=3 H AEG -2342 -5 1 0;1 - R 1 2pl=3+/1pl=1 -0; H AEG-2343-6 2pl=12/1pl=3 1 H 2 10; R AEG -2893 -30 10; 10; R 0; 0 R AEG-2894-31 0; 0;1- R 0; 23- R AEG-2895-32 10; 10; R 0; 23- R AEG -2897 -34 1-0; 0;1 R 0;1 0;1 R

186

AEG -2898 -1 2- 0;1 - R 0;1 0;1 -- R AEG -2899 -2 10; 0; R ------AEG-2947-0 0; 0; R 0; 1 R AEG -2949 -0 ------AEG-2972-0 2 10; R 2c 2 R AEG-2974-0 10; 10; R 0;1- 0;1-- R AEG -2993 -0 1N 2c? R 3+ 3 S AEG-3036-0 1 1-0; R 3- 3 S AEG -3039 -0 3 3 S 3- 3+ S AEG -3040 -0 ------3+ 3+ S AEG-3141-1 ------AEG -3336 -1 1+ 2 R 22+ 2+ R AEG-3337-2 2 2 R 0; 0 R AEG-3338-3 0;1 1-0; R 0; 0;1-- R AEG -3339 -4 23 - 21c R 1 1 R AEG-3345-10 1- 1-0; R 2 2 R AEG -3346 -11 ------0; 2 R AEG -3355 -20 10; 0; R 0; 0; R AEG-3365-30 1-0; 10; R ------AEG -3375 -40 3 3-2 S 3+ 3+ S AEG-3376-41 2 2 R 2 2 R AEG-3380-45 10; 0;1 R 0; 0; R AEG -3403 -1 ------

187

AEG -3407 -5 10; 2pl=0;/1pl=1 R 0; 1 R AEG -3412 -10 2 2- R 2pl=2+/1pl=0; 2pl=0;/1pl=3+ H AEG-3422-20 21 12n R 2pl=3/1pl=2 3+ H AEG -3432 -30 3 1pl=1/1pl=2 H 3 3 S AEG-3439-37 1-0; 1pl=1/1pl=3 H 3 3- S AEG-3463-1 2 1 R 2 2+ R AEG -3464 -2 ------AEG-3465-3 2-1 1 R 0;1- 0;1- R AEG -3466 -4 33+ 3 S 2 0 R AEG -3474 -12 3-3 3-2 S 3? 3- S AEG-3478-1 3 3 S 3+ 3+ S AEG -3484 -7 3 3 S 3+ 3+ S AEG-3486-9 3 43+ S 3+ 3+ S AEG-3491-14 3 3+4 S 3 3+ S AEG -3498 -21 3 3 S 3 3+ S AEG-3505-28 3- 3-2 S ------AEG -3507 -30 ------AEG -3731 -6 ------AEG-3759-34 ------AEG -3765 -40 0; 0; R 0; 00; R AEG-3771-46 3-2 3- S 3 3+ S AEG-3931-6 2n 2pl=21/1pl=3- H 33+ 3+ S AEG -3932 -7 1pl=10;/1pl=3 - 2 H ------

188

AEG -3986 -1 0;1 -- 0; R 2+ 0; R AEG -3988 -3 ------AEG-3995-10 10; 1pl=0;1-/1pl=3 H 1pl=1/1pl=23- 0;? R AEG -4001 -16 10; 10; R 0; 0; R AEG-4005-20 0; 1-0; R 0; 1 R AEG-4015-30 10; 0;1- R 2pl=2/1pl=3 2 H AEG -4025 -40 1 1 R 0;1 2 R AEG-4026-41 1-0; 10; R 3 33+ S AEG -4075 -16 1 0;1 - R 2pl=3/1pl=2 33+ H AEG -4099 -40 1 1pl=0;1 -/1pl=3 H ------AEG-4160-1 1 10; R 33+ 33+ S AEG -4161 -2 3 10; H 3+ 2pl=3+/1pl=1 H AEG-4162-3 2pl=0;/1pl=10; 0; R 0; 00; R AEG-4163-4 0;1 0;1- R ------AEG -4166 -7 1 1pl=0;/1pl=1 R 3+ 3+ S AEG-4185-26 3 3 S 2pl=3/1pl=3+ 2pl=3/1pl=3+ S AEG -4191 -32 1 33+ H 3+ 3+4 S AEG -4194 -35 10; 0;1 - R 3 3 S AEG-4542-2 0;1 0;1- R ------AEG -4543 -3 1 1 R 3 3 S AEG-4998-1 1pl=10;/1pl=2 3- H 3 33- S AEG-5000-3 2pl=12/1pl=3 23- H 33- 3 S AEG -5002 -5 3 3 S 3+ 33+ S

189

AEG -5004 -7 10; 10; R 1pl=1/2pl=3 1-0; H AEG -5016 -1 0; 0;1 - R 0; 00; R AEG-5646-1 0;1-- 0;1- R 1pl=0;/2pl=10; 0; R AEG -5647 -2 1-0; 0;1 - R 3 33+ S AEG-5648-3 3+4 3 S 33+ 3+ S AEG-6327-1 ------AEG -6328 -2 ------AEG-6329-3 3+4 1pl=10;/1pl=3 H ------AEG -6330 -4 10; 10; R 3 3 S AEG -6371 -0 3 3 S 3+ 3+ S AEG-6763-1 2c 0;1 R 2pl=3-/1pl=2 2+ H AEG -6764 -2 ------0; 1 R AEG-6765-3 ------AEG-6766-4 10; 10; R ------AEG -6767 -5 3-2 10; H 3 33+ S AEG-6781-1 1-0; 2pl=10;/1pl=2+ R 3 33+ S AEG -6782 -2 1-0; 0;1 - R 0; 0; R AEG -6783 -3 21n 2 R 2 1pl=3/1pl=2 H AEG-6784-4 3- 3 S 3+ 1pl=3+/1pl=3- S AEG -8696 -1 2pl=10;/1pl=3 3- H 3 3+ S AEG-8698-3 1-0; 10; R 3+ 3 S AEG-8699-4 3 3-? S 33+ 1pl=3/1pl=2 H AEG -8705 -10 21 10; R 0; 1 R

190

AEG -8708 -13 2- 1-0; R 33+ 3 S AEG -8710 -15 ------AEG-8715-20 ------3 3 S AEG -8718 -23 1n 1N R 3 1pl=1/1pl=2/1pl=3 H AEG-8719-24 10; 10; R 3pl=0;1-/1pl=2 1 R AEG-8724-29 ------3+ 3+ S AEG -8725 -30 3- 3 S 33+ 3+ S AEG-8735-40 10; 1 R ------AEG -8760 -15 3- 3-2 S 0;1 12 R AEG -8769 -24 2 23 - R 2 2+ R AEG-8770-25 3 3 S 3 33+ S AEG -8771 -1 0; 0; R 0;1 - 00; R AEG-8772-2 10; 0; R 2 2pl=3/1pl=2 H AEG-8773-3 1pl=1/1pl=2 3-2 H 3+ 3+4 S AEG -8774 -4 1- 1pl=1 R ------AEG-8779-1 3 3- S 3+ 3+4 S AEG -8780 -2 ------AEG -8781 -3 10; 0;1 - R 10; 0;1 - R AEG-8794-1 2pl=0;1/1pl=2 0;1- R 2pl=1/1pl=1--0; 0; R AEG -8795 -2 2pl=2/1pl=3 1pl=0;1 -/1pl=23 - H 33+ 3+ S AEG-8796-3 3+4 1pl=10;/1pl=2/1pl=3 H 3+ 3+ S AEG-8797-4 3 3 S ------AEG -9521 -0 ------10; 1-0; R

191

AEG -9522 -1 3 3- S ------AEG -9523 -2 23 - 2 R 3+4 3+ S AEG-9524-3 ------AEG -9525 -4 23 - 2 R 3+4 3+4 S AEG-9527-1 2pl=0;/1pl=3 10; H ------AEG-9528-2 2 1 R 1 22+ R AEG -9529 -3 10; 1-0; R 0;1 - 0;1 - R AEG-9530-4 2c 2c R 2 2 R AEG -9545 -1 ------AEG -9546 -2 2-1 2+c R 3+ 3 S AEG-9547-1 2 10; R 3 3- S AEG -9548 -1 3 3 S ------AEG-9573-0 3 3- S ------AEG-9574-0 2pl=3/1pl=1 3- H ------AEG -9575 -0 2c 2c R ------AEG-9576-0 3 3- S ------AEG -9577 -1 10; 10; R 0; 0;1 - R AEG -9579 -3 0;1 -- 0;1 - R 0;1 -- 0;1 -- R AEG-9581-5 3+ 3- S ------AEG -9583 -0 10; 1-0; R 0; 0;1 -- R AEG-9584-1 2 10; R 3 3 S AEG-9586-3 1pl=2/1pl=3 10; H 22+ 21 R AEG -9588 -5 2pl=3/1pl=2 2 H 22+ 2+ R

192

AEG -9591 -0 10; 0;1 - R 1 2pl=00;/1pl=2 R AEG -9614 -2 1pl=3+/1pl=1 3 H 3+ 3+ S AEG-9615-3 10; 10; R 1 1 R AEG -9616 -4 10; 0;1 - R ------AEG-9647-1 3 0; H 3+ 33- S AEG-9650-4 3 3 S 3 2pl=3/1pl=0; H AEG -9654 -8 3 3-2 S 3 3 S AEG-9657-11 3- 3 S 3 3+ S AEG -9660 -14 3- 1 H 33+ 33+ S AEG -9662 -16 2 2c R 2pl=2/1pl=3 33+ H AEG-9736-1 3- 3 S 2 2pl=0;1--/11pl=3 H AEG -9738 -3 1+ 1-0; R 2pl=0;/1pl=0;1 - 0;1 -- R AEG-9740-5 1pl=0;/2pl=3 1 H 1pl=10;/1pl=2/1pl=3 2+ H AEG-9742-7 10; 0;1 R 0; 0;1-- R AEG -9744 -9 2 2 R 2 1 R AEG-9746-11 3 3-? S 33+ 3 S AEG -9748 -13 1 1 R 2pl=3/1pl=2 33 - H AEG -9750 -1 3 2pl=2c/1pl=3 - H 3 2pl=2/1pl=3 H AEG-9751-2 1 10; R 0; 0; R AEG -9752 -3 10; 1 R 0;1 - 0;1 -- R AEG-9753-4 10; 2c? R 0;1- 0;1- R AEG-9754-1 3 3-? S 33+ 3 S AEG -9755 -1 10; 1N R 10; 2pl=3/1pl=2 H

193

AEG -9757 -1 23 - 23 - R 3+ 3+ S AEG -9758 -2 3 3- S 3+ 3+ S AEG-9838-3 ------AE -121 1 12 R 2pl=21/1pl=3 - 1pl=3 -/2pl=21 H AE-122 12-0; 2 R 0; 10; R AE-123 ------AE -124 0; 0; R 3+4 3+ S AE-125 10; 1-0; R 2pl=0;/1pl=1 0; R AE -320 2pl=0;1 -/1pl=21 10; R 2pl=0;/1pl=3 0;1 -- H AE -321 2pl=3+4/1pl=10; 33+ H 0;1 - 0; R AE-334 10; 0;1- R 0; 0;1- R AE -335 2- 1 R 0;1 - 0; R AE-337 3+ 1pl=3/1pl=2 H 3+4 3+ S AE-339 10; 0;1 R 0; ;2 R AE -340 3-2 1 H 2pl=3/1pl=1 3+ H AE-341 0;1N 1pl=0;/1pl=3 H 0; 2pl=0;/1pl=3+ H AE -342 ------1pl=2/2pl=3 3+ H AE -412 3+4 3 S 2pl=3+/1pl=1 3+ H AE-416 10; 3 H 22+ 0;1 R AE -417 2pl=0;/1pl=3 -c 3 H 2pl=3+/1pl=1 3 H AE-904 33+ 3 S 3+4 2pl=3+/1pl=0;1-- H AE-905 33+ 3 S 2 22+ R AE -906 1 1 R 1 2pl=21/1pl=3 H

194

AE -1077 2c 23 - R 2pl=33+/1pl=1 -- 33+ H AE -1078 33+ 3+ S 1pl=0;/2pl=2 10; R aSeeds are not available for testing.

Appendix Table 3. continued Accessions Puccinia striiformis f. sp. tritici PSTv-37 IT1 IT2 GenRxn AEG -13 -1 5 5 R AEG-14-2 7 8 S AEG -16 -4 2 2 R AEG -17 -5 8 8 S AEG-19-7 8 8 S AEG -20 -9 -- a -- -- AEG-21-10 2 2 R AEG-22-11 2 3 R AEG -23 -12 2 2 R AEG-24-13 2 2 R AEG -25 -14 2 2 R AEG -26 -15 2 2 R AEG-27-16 2 2 R AEG -28 -17 7 7 S AEG-29-18 2 3 R AEG-30-19 1 2 R

195

AEG -249 -1 8 8 S AEG -250 -2 8 7 S AEG-251-3 7 7 S AEG -264 -19 7 7 S AEG-265-21 ------AEG-267-23 8 1pl=4/1pl=7 H AEG -268 -24 8 8 S AEG-271-27 ------AEG -274 -30 8 7 S AEG -280 -37 5 4 R AEG-281-40 5 3 R AEG -282 -41 7 8 S AEG-284-44 5 5 R AEG-289-49 2 5 R AEG -290 -50 ------AEG-293-54 8 8 S AEG -297 -4 2 3 R AEG -298 -5 5 5 R AEG-299-6 2 1 R AEG -300 -7 2 3 R AEG-302-9 7 8 S AEG-303-10 2 2 R AEG -479 -23 3 4 R

196

AEG -480 -24 2 2 R AEG -622 -4 8 8 S AEG-623-5 9 9 S AEG -624 -6 8 8 S AEG-625-7 2 2 R AEG-627-9 8 7 S AEG -628 -10 5 3 R AEG-629-11 2 3 R AEG -631 -13 7 8 S AEG -637 -19 8 7 S AEG-657-39 9 8 S AEG -661 -1 ------AEG-664-4 8 8 S AEG-667-7 8 8 S AEG -668 -8 2 2 R AEG-669-9 ------AEG -670 -10 5 2 R AEG -671 -11 5 2 R AEG-682-22 5 2pl=7/1pl=4 H AEG -683 -23 6 6 R AEG-692-32 2 2 R AEG-710-50 7 8 S AEG -711 -1 8 8 S

197

AEG -712 -2 8 1pl=9/1pl=3 H AEG -713 -3 8 8 S AEG-715-5 ------AEG -716 -6 ------AEG-718-8 9 8 S AEG-719-9 8 8 S AEG -725 -15 5 2 R AEG-738-28 5 5 R AEG -745 -35 ------AEG -746 -36 9 8 S AEG-757-3 7 7 S AEG -759 -5 5 2 R AEG-760-6 2 3 R AEG-761-7 5 3 R AEG -762 -8 7 9 S AEG-763-9 2 2 R AEG -766 -12 7 7 S AEG -791 -37 3 5 R AEG-792-38 ------AEG -803 -49 4 5 R AEG-809-55 2 1 R AEG-1003-1 2 2 R AEG -1005 -3 2 2 R

198

AEG -1006 -4 ------AEG -1008 -6 2 1 R AEG-1011-9 ------AEG -1013 -11 7 8 S AEG-1015-13 3 4 R AEG-1018-16 5 5 R AEG -1032 -30 5 5 R AEG-1033-31 3 4 R AEG -1040 -38 ------AEG -1049 -47 2 2 R AEG-1057-4 8 9 S AEG -1059 -6 8 8 S AEG-1078-25 9 8 S AEG-1084-31 8 8 S AEG -1086 -33 8 8 S AEG-1087-34 8 7 S AEG -1088 -35 ------AEG -1090 -37 9 9 S AEG-1094-41 4 2 R AEG -1182 -3 2 2 R AEG-1184-5 2 2 R AEG-1185-6 2 2 R AEG -1187 -8 5 5 R

199

AEG -1188 -9 2 2 R AEG -1189 -10 ------AEG-1205-1 8 8 S AEG -1206 -2 ------AEG-1207-3 2 2 R AEG-1208-4 8 7 S AEG -1209 -5 8 8 S AEG-1211-7 5 2 R AEG -1212 -8 5 1pl=7/1pl=4 H AEG -1220 -16 8 8 S AEG-1236-32 ------AEG -1241 -37 ------AEG-1255-1 8 8 S AEG-1263-9 7 8 S AEG -1264 -10 8 9 S AEG-1265-11 5 6 R AEG -1266 -12 8 8 S AEG -1268 -14 8 8 S AEG-1269-15 8 8 S AEG -1270 -16 7 7 S AEG-1271-17 8 8 S AEG-1272-18 8 8 S AEG -1274 -20 5 3 R

200

AEG -1276 -22 5 5 R AEG -1285 -31 8 8 S AEG-1296-42 8 8 S AEG -1303 -49 8 8 S AEG-1306-2 5 5 R AEG-1308-4 5 5 R AEG -1310 -6 8 8 S AEG-1312-8 8 8 S AEG -1314 -10 8 7 S AEG -1316 -12 8 8 S AEG-1318-14 5 5 R AEG -1319 -15 8 8 S AEG-1334-30 7 9 S AEG-1348-44 8 8 S AEG -1355 -1 8 8 S AEG-1356-2 8 8 S AEG -1357 -3 5 6 R AEG -1358 -4 9 8 S AEG-1359-5 ------AEG -1360 -6 8 7 S AEG-1361-7 5 2 R AEG-1382-28 ------AEG -1392 -38 8 9 S

201

AEG -1397 -43 8 8 S AEG -1406 -1 5 6 R AEG-1407-2 2 5 R AEG -1409 -4 3 4 R AEG-1410-5 ------AEG-1411-6 5 1 R AEG -1425 -20 5 2 R AEG-1445-40 8 9 S AEG -1449 -44 2 5 R AEG -1451 -46 2 5 R AEG-1471-15 5 4 R AEG -1475 -19 5 6 R AEG-1478-22 3 4 R AEG-1479-23 2 5 R AEG -1480 -24 2 2 R AEG-1495-39 5 2 R AEG -1509 -1 8 8 S AEG -1510 -2 5 5 R AEG-1512-4 8 7 S AEG -1513 -5 8 8 S AEG-1514-6 5 6 R AEG-1515-7 5 4 R AEG -1519 -11 8 8 S

202

AEG -1528 -20 8 8 S AEG -1533 -25 ------AEG-1538-30 ------AEG -1545 -37 ------AEG-1667-2 2 2 R AEG-1668-3 2 3 R AEG -1669 -4 2 2 R AEG-1670-5 5 4 R AEG -1671 -6 2 3 R AEG -1672 -7 2 5 R AEG-1673-8 2 2 R AEG -1675 -10 2 5 R AEG-1676-11 ------AEG-1685-20 5 4 R AEG -1695 -30 7 7 S AEG-1702-37 4 3 R AEG -1708 -43 5 5 R AEG -1750 -85 7 7 S AEG-1754-89 1 5 R AEG -1757 -2 2 2 R AEG-1760-5 3 2pl=7/1pl=4 H AEG-1762-7 7 1pl=8/1pl=5 H AEG -1763 -8 2 2 R

203

AEG -1764 -9 2 3 R AEG -1765 -10 7 7 S AEG-1773-18 2 2 R AEG -1793 -38 2 2 R AEG-1796-41 4 3 R AEG-1805-50 3 2 R AEG -1860 -1 2 2 R AEG-1861-2 4 6 R AEG -1862 -3 2 1pl=8/1pl=4 H AEG -1864 -5 2 5 R AEG-1865-6 2 5 R AEG -1866 -7 5 5 R AEG-1873-1 3 4 R AEG-1874-2 9 9 S AEG -1875 -3 3 3 R AEG-1877-5 8 9 S AEG -1878 -6 3 4 R AEG -1879 -7 ------AEG-1880-8 5 3 R AEG -1882 -10 7 1pl=5/1pl=7 H AEG-1912-40 3 2pl=5/1pl=8 H AEG-1913-41 ------AEG -2052 -9 8 8 S

204

AEG -2055 -12 7 7 S AEG -2058 -15 8 7 S AEG-2062-19 8 8 S AEG -2065 -22 7 7 S AEG-2244-1 7 7 S AEG-2247-4 8 8 S AEG -2248 -5 7 7 S AEG-2250-7 ------AEG -2251 -8 8 7 S AEG -2252 -9 8 8 S AEG-2253-10 2 5 R AEG -2265 -22 3 2 R AEG-2269-26 8 9 S AEG-2275-32 8 8 S AEG -2277 -34 7 1pl=2/1pl=4/1pl=7 H AEG-2284-41 7 8 S AEG -2340 -3 8 1pl=4/1pl=8 H AEG -2341 -4 5 1 R AEG-2342-5 8 1pl=8/1pl=5 H AEG -2343 -6 8 8 S AEG-2893-30 3 5 R AEG-2894-31 8 7 S AEG -2895 -32 5 2 R

205

AEG -2897 -34 2 6 R AEG -2898 -1 1pl=2/1pl=7 1pl=2/1pl=6 H AEG-2899-2 1pl=2/1pl=5 5 R AEG -2947 -0 2 0 R AEG-2949-0 ------AEG-2972-0 2 1 R AEG -2974 -0 2 4 R AEG-2993-0 7 8 S AEG -3036 -0 2 2 R AEG -3039 -0 8 8 S AEG-3040-0 9 8 S AEG -3141 -1 ------AEG-3336-1 2 4 R AEG-3337-2 2 4 R AEG -3338 -3 2 4 R AEG-3339-4 2 3 R AEG -3345 -10 2 2 R AEG -3346 -11 ------AEG-3355-20 3 3 R AEG -3365 -30 2 3 R AEG-3375-40 2 3 R AEG-3376-41 2 4 R AEG -3380 -45 5 1pl=3/1pl=4/1pl=5 R

206

AEG -3403 -1 ------AEG -3407 -5 2 5 R AEG-3412-10 8 1pl=7/1pl=5 H AEG -3422 -20 8 8 S AEG-3432-30 7 7 S AEG-3439-37 5 2pl=5/1pl=7 H AEG -3463 -1 2 5 R AEG-3464-2 ------AEG -3465 -3 5 5 R AEG -3466 -4 5 1pl=5/1pl=6 R AEG-3474-12 5 6 R AEG -3478 -1 8 7 S AEG-3484-7 3 2pl=7/1pl=5 H AEG-3486-9 5 5 R AEG -3491 -14 8 7 S AEG-3498-21 8 8 S AEG -3505 -28 2 2 R AEG -3507 -30 ------AEG-3731-6 ------AEG -3759 -34 ------AEG-3765-40 4 6 R AEG-3771-46 9 8 S AEG -3931 -6 8 4 H

207

AEG -3932 -7 5 4 R AEG -3986 -1 7 7 S AEG-3988-3 ------AEG -3995 -10 6 6 R AEG-4001-16 7 7 S AEG-4005-20 4 5 R AEG -4015 -30 5 5 R AEG-4025-40 8 7 S AEG -4026 -41 1pl=8/1pl=6 8 H AEG -4075 -16 9 7 S AEG-4099-40 2 2 R AEG -4160 -1 8 8 S AEG-4161-2 8 8 S AEG-4162-3 4 5 R AEG -4163 -4 8 8 S AEG-4166-7 1pl=5/1pl=8 3 H AEG -4185 -26 2 5 R AEG -4191 -32 9 8 S AEG-4194-35 7 7 S AEG -4542 -2 2 2 R AEG-4543-3 9 1pl=2/1pl=8 H AEG-4998-1 8 8 S AEG -5000 -3 5 5 R

208

AEG -5002 -5 9 8 S AEG -5004 -7 2pl=4/1pl=8 7 H AEG-5016-1 8 8 S AEG -5646 -1 2 2 R AEG-5647-2 8 8 S AEG-5648-3 8 7 S AEG -6327 -1 ------AEG-6328-2 ------AEG -6329 -3 5 4 R AEG -6330 -4 8 8 S AEG-6371-0 8 8 S AEG -6763 -1 5 5 R AEG-6764-2 8 8 S AEG-6765-3 ------AEG -6766 -4 8 9 S AEG-6767-5 9 8 S AEG -6781 -1 8 8 S AEG -6782 -2 2 3 R AEG-6783-3 8 8 S AEG -6784 -4 8 7 S AEG-8696-1 4 3 R AEG-8698-3 2 2 R AEG -8699 -4 8 8 S

209

AEG -8705 -10 4 4 R AEG -8708 -13 8 8 S AEG-8710-15 ------AEG -8715 -20 9 9 S AEG-8718-23 8 8 S AEG-8719-24 2 2 R AEG -8724 -29 8 8 S AEG-8725-30 1pl=4/2pl=8 4 H AEG -8735 -40 8 8 S AEG -8760 -15 2 6 R AEG-8769-24 5 5 R AEG -8770 -25 8 9 S AEG-8771-1 8 8 S AEG-8772-2 8 8 S AEG -8773 -3 8 8 S AEG-8774-4 ------AEG -8779 -1 8 8 S AEG -8780 -2 ------AEG-8781-3 5 3 R AEG -8794 -1 9 7 S AEG-8795-2 7 7 S AEG-8796-3 7 7 S AEG -8797 -4 7 8 S

210

AEG -9521 -0 ------AEG -9522 -1 2 5 R AEG-9523-2 9 8 S AEG -9524 -3 ------AEG-9525-4 ------AEG-9527-1 9 9 S AEG -9528 -2 9 9 S AEG-9529-3 2pl=6/1pl=8 7 H AEG -9530 -4 3 2 R AEG -9545 -1 ------AEG-9546-2 8 7 S AEG -9547 -1 6 6 R AEG-9548-1 ------AEG-9573-0 4 5 R AEG -9574 -0 5 2 R AEG-9575-0 5 4 R AEG -9576 -0 5 4 R AEG -9577 -1 2 2 R AEG-9579-3 3 1 R AEG -9581 -5 ------AEG-9583-0 2 1pl=4/1pl=1 R AEG-9584-1 3 5 R AEG -9586 -3 2 2 R

211

AEG -9588 -5 2 2 R AEG -9591 -0 8 9 S AEG-9614-2 7 7 S AEG -9615 -3 8 8 S AEG-9616-4 2 5 R AEG-9647-1 2 3 R AEG -9650 -4 8 7 S AEG-9654-8 8 7 S AEG -9657 -11 5 5 R AEG -9660 -14 3 2 R AEG-9662-16 8 7 S AEG -9736 -1 2 2 R AEG-9738-3 3 3 R AEG-9740-5 3 2 R AEG -9742 -7 8 7 S AEG-9744-9 5 4 R AEG -9746 -11 5 3 R AEG -9748 -13 5 R AEG-9750-1 2 2 R AEG -9751 -2 2 2 R AEG-9752-3 5 2 R AEG-9753-4 ------AEG -9754 -1 4 2 R

212

AEG -9755 -1 8 7 S AEG -9757 -1 8 8 S AEG-9758-2 2 1 R AEG -9838 -3 ------AE-121 5 5 R AE-122 7 7 S AE -123 ------AE-124 8 9 S AE -125 2 2 R AE -320 7 8 S AE-321 8 8 S AE -334 7 8 S AE-335 7 8 S AE-337 8 9 S AE -339 9 8 S AE-340 9 8 S AE -341 3 5 R AE -342 2 2 R AE-412 3 1pl=8/1pl=4/1pl=5 R AE -416 9 8 S AE-417 3 2pl=8/1pl=2 H AE-904 1pl=2/1pl=4 4 R AE -905 7 9 S

213

AE -906 9 8 S AE -1077 8 2pl=8/1pl=3 H AE-1078 5 5 R aSeeds are not available for testing.

214

Appendix Figure 1. Map of Israel showing the geographic distribution of Aegilops longissima accessions resistant and susceptible to Puccinia graminis f. sp. tritici race TTTTF.

215

Appendix Figure 2. Map of Israel showing the geographic distribution of Aegilops longissima accessions resistant and susceptible to Puccinia triticina race THBJ.

216

Appendix Figure 3. Map of Israel showing the geographic distribution of Aegilops longissima accessions resistant and susceptible to Puccinia triticina race BBBD.

217

Appendix Figure 4. Map of Israel showing the Local Indicator of Spatial Association (LISA) a clusters of Aegilops longissima accessions in response to infection by Puccinia graminis f. sp. tritici race TTTTF.

218

Appendix Figure 5. Map of Israel showing the Local Indicator of Spatial Association (LISA) a clusters of Aegilops longissima accessions in response to infection by Puccinia triticina race THBJ.

219

Appendix Figure 6. Map of Israel showing the Local Indicator of Spatial Association (LISA) a clusters of Aegilops longissima accessions in response to infection by Puccinia triticina race BBBD.

aFor the LISA analysis, a spatial weights matrix was generated for each variable using GeoDa, comparing each site to its nearest four neighbors. High- High indicates significant clusters of neighboring accessions exhibiting susceptible reactions; Low-Low indicates significant clusters of accessions exhibiting resistant reactions; Low-High indicates significant clusters of neighboring accessions exhibiting resistant and also susceptible reactions; and High-Low indicates significant clusters of neighboring accessions exhibiting susceptible and also resistant reactions.

220