Evaluation of Genetic Diversity and Stability of Colocasia Cultivars Using ISSR Seukmin Hong [email protected]
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This thesis is available at SFA ScholarWorks: https://scholarworks.sfasu.edu/etds/129 Evaluation of Genetic Diversity and Stability of Colocasia Cultivars Using ISSR
By
Seukmin Hong, B.S. Biotechnology
Presented to the faculty of the graduate school of Stephen F. Austin State University In Partial Fulfillment Of the Requirements
For the degree of Masters of science in General Agriculture
STEPHEN F. AUSTIN STATE UNIVERSITY December 2017 Evaluation of Genetic Diversity and Stability of Colocasia Cultivars Using ISSR
By
Seukmin Hong, Biotechnology BS
APPROVED: ______Jared Barnes, Ph. D., Thesis Director ______Bea Clack, Ph. D., Committee Member ______Yuhui Weng, Ph. D., Committee Member
______Richard Berry, D.M.A Dean of the Graduate School
ABSTRACT
Using 44 ornamental Colocasia cultivars planted at Stephen F. Austin
State University (Nacogdoches, TX), cultivar assessment, genetic diversity, stability, and relationship were examined with banding patterns produced from
Inter-simple sequence repeat (ISSR) markers. Comparing banding patterns of vegetatively propagated clones of each cultivar, genetic stability was examined. Unweighted pair group method with arithmetic mean (UPGMA) and principal coordinate analysis (PCO) were performed to examine genetic relationship that can explain a need for the new classification Colocasia gigantea and recent movement of re-classifying Colocasia antiquorum.
Average Shannon’s diversity index for all loci was found to quantify genetic diversity. The genetic stability analysis confirmed all 44 cultivars commonly found in market have identical genetic characteristics. The genetic relationship analysis supports the new classification of Colocasia antiquorum but does not strongly support the need for re-classification of Colocasia gigantea based on our results. Shannon’s diversity index suggested that 44 ornamental Colocasia cultivars have high gene pool.
i
TABLE OF CONTENTS
ABSTRACT ...... i TABLE OF CONTENTS ...... ii LIST OF FIGURES ...... iv LIST OF TABLES ...... v CHAPTER ONE ...... 1 Plant Breeding and Cultivar Assessment Using Biotechnology ...... 1 General Description of Colocasia ...... 3 Colocasia Breeding ...... 4 Genetic Diversity of Colocasia ...... 7 Project Introduction ...... 10 CHAPTER 2 ...... 14 Introduction ...... 14 DNA isolation from Colocasia leaf tissue ...... 14 Marker Choices ...... 16 Genetic Stability Analysis ...... 18 Genetic Diversity Analysis ...... 18 Materials and Methods ...... 23 Sample collection and preparation ...... 23 DNA Isolation ...... 25 Quantification of DNA ...... 26 Polymerase Chain Reaction Based Inter Simple Sequence ...... 26 Agarose Gel Electrophoresis ...... 28 Banding Patter Scoring ...... 28 Statistical Analysis and Genetic Quantification ...... 29 Results and Discussion ...... 29 DNA Isolation and Quantification ...... 29 Banding Pattern Scoring ...... 30 Genetic Stability Analysis ...... 34 UPGMA ...... 35 ii Principal Coordinates Analysis...... 40 Genetic Diversity Quantification ...... 44 Conclusion ...... 49 Literature Cited ...... 50 Appendix A ...... 59 Appendix B ...... 61 Appendix C ...... 64 Appendix D ...... 69 Appendix E ...... 73 Appendix F ...... 83 VITA ...... 99
iii LIST OF FIGURES
Figure 1. Representation of Colocasia trial garden five beds (Bed A to E)...... 24
Figure 2. Dendrogram of 44 Colocasia cultivars produced using UPGMA with Jaccard’s coefficient...... 39
Figure 3. PCO scatter graph of 44 Colocasia cultivars using PC1 as X- axis and PC2 as Y-axis...... 43
iv LIST OF TABLES
Table 1. List of Colocasia cultivars with breeder information and number of clones sampled...... 13
Table 2. List of primers with sequence and annealing temperature...... 27
Table 3. Thermocycler setting for PCR-ISSR...... 27
Table 4. Observed bands produced from each primer...... 32
Table 5. Number of bands produced after PCR-ISSR...... 33
Table 6. Percent of bands shared by all cultivars and unique bands for each cultivar in all 44 cultivars ...... 34
Table 7. Seven most similar Colocasia cultivars where the similarity index value was higher than overall similarity index average...... 40
Table 8. Comparable Shannon’s diversity index of other Colocasia cultivars and ornamental genera...... 44
v
CHAPTER ONE
Plant Breeding and Cultivar Assessment Using Biotechnology
People have exploited plant genetics to benefit humankind for more than ten thousand years (Ross-Ibarra et al., 2007). A tremendous diversity of plant cultivars have been created, found, and selected by man, and the discovery of new traits that can benefit horticulture continues today. Breeding began with domestication as plants with desirable characteristics such as bigger fruit, higher yield, reduced branching, taller height, the loss or reduction of seed dispersal, the loss of seed dormancy, changes in photoperiod sensitivity, and the loss or reduction of toxic compounds were selected (Gepts,
2004; Hammer, 1984). Many benefits that arose from selection such as obtaining food from a farm, minimized travel to find a food source. However, society now faces new obstacles like the need for feeding a dramatically increasing population in a changing climate with unexpected pests and diseases. In addition, non-edible uses of plants are increasing as the need for biofuels, feed crops, fibers for clothes, ornamental and environmental crops, and even biodegradable plastics is rising (Birren et al., 2010). To meet the increasing need of plants, they must be grown efficiently. Since all cultivars don’t perform well everywhere on earth, new cultivars need to be assessed to ensure that superior cultivars are used.
The advent of biotechnology has changed the paradigm of plant 1 breeding. Breeding plants has become more systematic and faster compared to traditional breeding. Due to genetic engineering techniques, tissue culture, and molecular markers, transgenic cultivars have been introduced to farmers
(Borem et al., 2014). Herbicide-tolerant cultivars survive application of herbicide while weeds are killed, and using machines for planting crops and application of herbicides minimizes human labor. Bacillus thuringiensis produce cry proteins, also known as delta endotoxins that kills Lepidoptera,
Diptera, and Cleopetera by creating pores in digestive tracts (Schünemann et al., 2014). For other crops like BT corn, incorporated genes express insecticide proteins so that there is no need to apply pesticides regularly.
Ultimately introduction of transgenic plants enable efficient and environment friendly farming.
Traditional breeding methods use selection to produce plants with desired genotypes and rely on visual inspection of characteristics; however, these visual assessments may not always be accurate because morphological characterization can be influenced by environmental effect.
Biotechnology enables us to obtain genetic information about plants with molecular markers. Genetic information is useful when examining crop domestication, plant evolution, and genetic mechanisms of agronomical traits
(Borem et al., 2014). Molecular characterization can provide crucial information for cultivar assessment by detecting polymorphism in DNA.
Molecular marker data can be used for DNA finger printing to efficiently manage and conserve germplasms. This data also can be analyzed with statistical methods to find genetic diversity and relationship information. 2 General Description of Colocasia
Colocasia, commonly known as taro or elephant ear, is a mostly tropical genus in the Araceae family that is composed of 10 species, the most popular of which are Colocasia esculenta, Colocasia antiquorum, and
Colocasia gigantea. Each species has its own characteristics. Three species have different shape and size of tuber. Colocasia esculenta produce a larger central tuber and smaller side suckers. Colocasia antiquorum produce a small central corm and big side suckers (Ivancic et al., 2000). Colocasia gigantea produce large and long tuber (Hather, 2013). Colocasia is one of the traditional crops that has been produced and selected for a long time
(Whitney et al., n.d.). Historical records in China reported Colocasia in 100
B.C. (Whitney et al., n.d.). Papua New Guinea has a record of cultivation in
9,000 B.C. (Golson, 1977). There are many hypotheses about the center of origin of Colocasia, but the widely accepted theory is that the species arose from New Guinea and Melanesian areas since most of the domesticated
Colocasia from the wild originated from New Guinea and the Malaysian area
(Lebot et al., 1991). Recent genetic diversity investigated by Chaïr et al. (2016) used cultivars that represented each country from Africa, America, Asia, and
Polynesian to trace dispersal of Colocasia. Using microsatellite markers and diversity indices, genetic diversity was found. Chaïr et al. (2016) suggested that Asia could be the origin since the largest genetic diversity was found there, and many cultivars from Africa and America also originated from Asia.
Colocasia esculenta, Colocasia antiquorum, and Colocasia gigantea
3 are important food source in southeast Asia, Polynesian countries, and some
African countries (Singh et al, 1992). It is the 14th most consumed vegetable in the world (Cho et al., 2007); high starch, minerals, and vitamins in taro are source of nourishment for people (Rao et el, 2010).
Colocasia Breeding
Because of high genetic diversity and ability to propagate sexually and vegetatively, thousands of Colocasia cultivars have been developed and released to farmers and horticulturists (Clay et al., 1987). Breeding efforts of
Colocasia began in earnest when taro leaf blight (TLB) disease caused by
Phytophthora colocasiae was discovered. Outbreaks of TLB significantly reduced yield all over the world. For example, 97% of taro yield of Colocasia was reduced in islands of Samoa, 80% of taro yield was reduced in the
Dominican Republic in 2004, and Puerto Rico’s taro crop yield was totally lost in 2004 (CTAHR, 2009). Phytophthora colocasiae exists as oomycetes. Once plants are infected, circular lesions on leaf tissue are observed and they lead to huge losses of leaf tissue and significant loss in tuber yield (Hunter et al.,
2012). The biggest problem is TLB is a highly infectious organism and hard to cure once plants are infected (CTAHR, 2009). Developing TLB tolerant plants is sustainable way to manage diseases since chemical fungicide is proven to be ineffective against pests damaging Colocasia (Singh et al., 2012). Due to breeders’ efforts worldwide, resistant cultivars that are not heavily affected by
Phytophthora colocasiae have been developed and diseases have been cost effectively managed (Singh et al., 2010). Moreover, effort to develop cultivars
4 with high yield, aphid tolerance, eating quality, and abiotic stress tolerance has led to various cultivars that are profitable to grow (Cho, 2004; Rao, n.d.).
Other pathogens such as taro beetle and the alomae-bobone virus complexes
(ABVC) continue to present problems for taro production (Sar et al., 1998).
Ornamental Colocasia cultivars are produced from breeders or collected from wild. Breeding programs take advantage of the wide genetic diversity and phenotypic polymorphism to produce superior cultivars (Cho,
2004). High genetic diversity of Colocasia is suspected to be derived from sexual recombination and somatic mutations (Okpul et al., 2005). In addition, protogyny and self-incompatibility has contributed to genetic variation (Okpul et al., 1996; Shaw, 1975). Genetic polymorphism of taro causes plants to have multiple colors and patterns on the leaves (Karuri et al., 2009). There are several characters that make Colocasia ornamental plants such as leaf and petiole color, leaf shape, growth habit, and various levels of waxiness.
According to international plant genetic resources institute (IPGRI)’s taro descriptor, the most common leaf sheath color of Colocasia is green however, there are red, purple, brownish, yellow, and white variants. Not only the leaves but also petiole and veins can have different color like white, yellow, orange, light green, green, red, brown, or purple. For mid-veins, there are colors like whitish, yellow, orange, green, pink, red, brownish, and purple. Variegated cultivars have high ornamental value for having mosaics of multiple colors leaves. The surface of the leaves can be either matte or glossy which is purposely selected for ornamental use. The amount of wax determines whether the leaf is glossy, or matte. Shape of the leaf is also important in 5 ornamental use. Leaves are peltate, and shapes can be sagittate or hastate.
Margin of the leaf blade can be entire, undulate, or sinuate. Size of the whole plant is also important. Plant span and height are important characteristics.
Plant width can be narrow (<50 cm), medium (50–100 cm), and wide (>100).
Plant width can be dwarf (<50 cm), medium (50–100cm), and tall (>100 cm)
(IPGRI, 1999).
According to CTAHR (2009), Dr. John Cho’s breeding programs in
Hawaii initially aimed for producing new agricultural cultivars that are resistant to TLB and have high tuber and leaf yield. Ornamental value of his cultivars was once recognized by enthusiasts, and those cultivars were released to market after the cultivars were assessed for their ornamental value (University of Hawaii, n.d.). Many of his are patented in the U.S. For example, Colocasia esculenta ‘White Lava’, Colocasia esculenta ‘Hawaiian Punch’, and Colocasia esculenta 'Morning Dew' are patented in the U.S. According to U.S. patent
PP26152 (Williams, 2015), and PP28001 (Williams, 2015), Brian Williams, produced Colocasia cultivars from a controlled breeding program in his nursery. He selected plants for specific characters like size of the leaf, colors of the leaf, and growing condition. For example, Colocasia ‘Maximus Gigante’ was the result of crossing Colocasia esculenta × Colocasia gaoligongensis as the female parent and an unnamed plant of Leucocasia gigantea plant as the male parent. The new hybrid cultivar was made for colorful characteristics, suitability for landscape or container growth, clump-forming habitat, and large leaves.
6 Genetic Diversity of Colocasia
Diminishing genetic diversity in Colocasia cultivars have been reported especially in leading taro producing regions such as Africa and Pacific islands
(Akwee et al., 2015; Banjaw, 2017; Singh et al., 2004). Pests, disease and continuous clonal propagation are major factors decreasing the genetic diversity of Colocasia (Okpul et al., 2004; Wagih et al.,1994). Average seed production of Colocasia has been decreasing since 1971, and yield of taro has been decreasing since 2007 (Food and Agriculture Organization, 2017).
This indicates that the outcome of cross pollination in Colocasia is reducing since Colocasia is self-incompatible plants and vegetatively propagated in farms and gardens (Lebot, 1991).
Major genes that contribute to agronomical value have been exploited for efficiency of agricultural crop production. Taking advantage of a superior genome, high yielding varieties exhibit outstanding performance compared to traditional varieties (Hedden, 2003). However, selecting a few desirable traits for the long term is one of the main factors causing genetic erosion (Brian, et al., 2006). Once genetic diversity narrows, plants could be susceptible for diseases and pests. When Musa acuminata 'Gros Michel' banana was attacked by panama disease (Fusarium oxysporum), there was nothing that could stop the spread of disease since ‘Gros Michel’ banana is a vegetatively propagated cultivar. Farmers and distributers experienced staggering losses due to a lack of genetic diversity in the banana market. Damage in trade losses caused by panama disease was estimated at approximately
7 $400,000,000 (Ploetz, 2005). As referred to earlier, Colocasia has been severely affected by TLB disease, especially in places where genetic diversity is low. Lack of genetic diversity in the Samoa Island caused extinction of their own cultivars from July 1993 to June 1994 when TBL was introduced from outside of the island (Food and Agriculture Organization of the United Nations,
2000).
Early genetic diversity analysis of Colocasia began with simple cytological techniques (Matthews, 2004). Colocasia can be both diploid 2n=28 and triploid 3n=42 (Matthews, 2004). Triploid Colocasia cultivars are rare.
Approximately 1 in 170 plants is triploid (Isshiki et al., 1999). Only diploid
Colocasia cultivars are fertile and they only bloom in favorable environments.
Infertile triploid Colocasia cultivars are vegetatively propagated (Isshiki et al.,
1999). Many researchers tried to find the pattern of ploidy based on location.
Kreike et al. (2004) conducted genetic analysis on 255 Colocasia esculenta collected diploid and triploid Colocasia from mainland in Asia while diploid
Colocasia were found in the Pacific islands. Zhang et al., (1990) found triploid cultivars in northern parts of China, central and eastern China, and southern parts of China. Diploid cultivars were only found in southern parts of China.
They observed the frequency of diploidy from the south to north decreased while triploidy increased suggesting that an additional chromosome increased their physiological advantage to endure cold temperatures.
Using in-vitro propagation and molecular markers, researchers have worked on improving Colocasia genetics. The Pacific islanders have been
8 leading the breeding research. The Universities of the South Pacific (USP),
West Indies (UWI), Florida (UF), Hawaii (UH), the University of Technology in
Papua New Guinea, and organizations such as the National Agricultural
Research Institute (NARI-PNG), the Caribbean Agricultural Research and
Development Institute (CARDI) and the Secretariat of the South Pacific (SPC-
Fiji) have played an important role in breeding Colocasia (INEA, 2015). For example, the International Network for Edible Aroids, which is funded by the
European Union, receives germplasm from farmers and partners to breed taro.
Their main goal in breeding programs is to produce different cultivars of taro with good quality tuber resistance to TLB caused by fungus, and drought resistance. After five years of breeding hybrid propagules, which was an important first step to produce TLB resistant taro (INEA, 2015).
Okpul et al. (2005) from the National Agricultural Research Institute in
Papua New Guinea conducted genetic analysis of 13 accessions from Papua
New Guinea and Thailand using ISSR markers. The goal was to see if physiological variation matches up with genetic polymorphism so that individual growers can select cultivars with desirable cultivars based on appearance. In addition, Okpul et al. (2005) conducted cluster analysis to examine genetic diversity. Three primers were used to observe polymorphism.
For agromorphological variation, they collected 22 descriptors. They could characterize molecular data and make a phylogenetic tree to see how closely or distantly related cultivars are. They obtained two groups and high genetic similarity ranging 64% to 95%. However, they only found little correlation between agro-morphological and molecular data (Okpul et al., 2005). 9 Project Introduction
The ornamental value of Colocasia has been recognized by the horticulture industry because of its color, shape, and size variation (Carey et al., 2012; Cho, 2004). Colocasia is a popular genus for growers in temperate climate zones (CTAHR, 2009) and used in landscape and water gardens
(Collins, 2017). However, to date, there has been no genetic evaluation of ornamental Colocasia cultivars. With DNA finger print of 44 cultivars, genetic diversity, stability, and relationship can be obtained. By analyzing DNA finger print of vegetatively propagated clones within a cultivar, breeders can confirm that their cultivars possess distinct, uniform and stable genetic characteristics after released in the market. Genetic relationship information can be helpful identifying Colocasia species. Genetic relationship and diversity information can be used as a reference for marker assisted selection.
To qualify as a cultivar, the plant germplasm must be distinct, uniform and stable (Plant Variety Protection Act of 1970). In this project, those three factors will be analyzed for cultivar assessment. To spot unique genomic regions that can distinguish cultivars, ISSR was used which amplifies random unique genomic regions between two microsatellites (Ng et al., 2015).
Colocasia cultivars are commonly propagated by cloning method because it is important to have uniform and stable genetic material over generations. In the market, Colocasia cultivars are sold as tubers since they are easy to handle and contain uniform genome since tubers are produced by vegetative propagation. But, genetic mutations occur rarely which can lead to loss of
10 desired characteristics. In this project, we will observe if vegetatively propagated Colocasia cultivars commonly found in the market contain distinct, uniform and stable genetic characteristics by observing banding patterns of clones of 44 cultivars.
Taxonomic confusion in Colocasia antiquorum and Colocasia gigantea has been reported since Colocasia genus was first classified by Schott (1832) based on morphological characteristics. It has been a controversial that
Colocasia antiquorum and Colocasia esculenta are only distinguished by morphological characteristics because Colocasia esculenta is a highly polymorphic species having a wide range of morphological variations
(Velayudhan, 2003). New classification of Colocasia antiquorum was suggested by studies since morphological characteristics of Colocasia antiquorum can be a part of the morphological variation of Colocasia esculenta (Harlan, 1971; Velayudhan, 2003). Nauheimer et al. (2012) suggested that taxonomic realignments are required for Colocasia gigantea since it is genetically and morphologically closer to Alocasia in the south east
Asian mainland compared to Colocasia. Genetic relationships of our ornamental Colocasia cultivars will be analyzed using UPGMA and PCO with
ISSR data. Genetic relationships of cultivars will be illustrated visually as a dendrogram and a scatter plot. Based on similarity of the banding patterns, cultivars will form clusters in a dendrogram and a scatter plot. Relationship of three species will be examined by identifying composition of clusters.
Having information about genetic diversity and relationships of
11 ornamental Colocasia cultivars can be helpful breeding new cultivars.
Shannon’s diversity index in our ornamental Colocasia cultivars will be a part of the genetic diversity data. Shannon’s diversity index examines how bands at loci are evenly produced and total number of loci in 44 cultivars. Genetic diversity information can be a reference for breeders by offering similarity data of our cultivars which can be useful in selection decision in plant breeding
(Lado et al. 2017) and selection of genetically diverse parental lines for recombinants (Salgotra et al., 2015). Genetic diversity assessment represents available building blocks that can be used to construct new cultivars in a long term. Therefore, breeding program can be done effectively with genetic diversity information (Govindaraj et al., 2015).
12 Table 1. List of Colocasia cultivars with breeder informationx and numbe r of clonesy sampled.
Scientific Name Cultivar Breeder or Location Clones Accession Number Colocasia esculenta Big Dipper Indonesia 5 1 Colocasia esculenta Bikini-Tini Brian Williams 5 2 Colocasia antiquorum Black Beauty Brian Williams 5 3 Colocasia esculenta Black Coral Dr.John Cho 5 4 Colocasia esculenta Black Magic Philippines 5 6 Colocasia esculenta Black Ripple Brian Williams 5 8 Colocasia esculenta Black Runner N/A 5 10 Colocasia esculenta Black Sapphire Gecko Brian Williams 4 11 Colocasia esculenta Blue Hawaii Dr.John Cho 5 12 Colocasia esculenta Coal Miner Tony Avent 5 15 Colocasia Coffee Cups N/A 5 16 Colocasia esculenta Dragon Heart Gigante Brian Williams 5 18 Colocasia esculenta Electric Blue Gecko Brian Williams 5 19 Colocasia esculenta Elepaio N/A 5 21 Colocasia gigantea Fierce Gigante Brian Williams 5 22 Colocasia Fontenseii N/A 5 23 Colocasia esculenta Hawaiian Punch Dr.John Cho 5 25 Colocasia antiquorum Illustris N/A 5 27 Colocasia esculenta Imperial Gigante Brian Williams 5 28 Colocasia esculenta Jack’s Giant Costa Rica 5 29 Colocasia esculenta Kona Coffee Dr.John Cho 5 30 Colocasia gigantea Laosy Giant Laos 5 31 Colocasia esculenta Lemonade Alan Galloway 5 32 Colocasia esculenta Lime Aide Philippines 4 34 Colocasia esculenta Madiera N/A 5 35 Colocasia Mammoth N/A 5 36 Colocasia esculenta Mau Gold Dr.John Cho 5 37 Colocasia esculenta Maui Magic Dr.John Cho 5 38 Colocasia Maximus Gigante Brian Williams 5 39 Colocasia esculenta Midori Sour N/A 4 41 Colocasia esculenta Mojito Strode, Ty Richard 5 42 Colocasia esculenta Morning Dew Dr.John Cho 5 43 Colocasia esculenta Nancy’s Revenge Caribbean 5 44 Colocasia esculenta Painted Black Gecko Brian Williams 5 46 Colocasia esculenta Pink China Brian Williams 5 48 Colocasia esculenta Red-Eyed Gecko Brian Williams 5 51 Colocasia esculenta Rhubarb Hawaii 5 52 Colocasia esculenta Ruffles Alabama 5 54 Colocasia esculenta Sangrina N/A 5 55 Colocasia esculenta Tea Cup N/A 5 57 Colocasia gigantea Thailand Giant Thailand 4 58 Colocasia esculenta Tropical Storm Dr.John Cho 5 60 Colocasia esculenta Violet Stem N/A 2 62 Colocasia esculenta White Lava Dr.John Cho 5 63
x Breeder’s names and location of the cultivars were found in Colocasia breeders’ websites such as Plant Delights Nursery, inc. web page (Carey et al. 2012) and Brian’s Botanical web page (Brian's Botanicals, 2011). y Vegetatively propagated tubers commonly sold in nurseries.
13 CHAPTER 2
Introduction
DNA isolation from Colocasia leaf tissue
DNA should be isolated from the plant material and purified if necessary because pure DNA is required for best polymerase chain reaction
(PCR) result. DNA can be found in plant tissues like leaf, stem, flower, seed, and even root. Depending on the part of the plant tissue, the amount of DNA and amount of impurities that inhibit PCR reaction differ (Birren et al., 1996).
Generally, young expanding leaves are preferred because vacuoles are smaller than fully grown leaves, which results in more cells per unit area and lower secondary metabolites (Birren et al., 1996). Plant tissues contain polysaccharides, polyphenols, pectin, and xylan that inhibit PCR reaction (Wei et al. 2008). Amount and types of phenols depends on growing condition and cultivars (Ferreres et al., 2012). Ferreres et al. (2012) found 41 phenolic compounds in Colocasia leaves. To minimize secondary metabolites and to maximize DNA, young leaves were used.
There are methods and kits that can isolate plant DNA. For example, acetyl trimethylammonium bromide and DNA isolation kits from biotechnology companies are available. To obtain an ample amount of pure DNA with a simplified procedure, DNeasy PowerPlant Pro Kit (Qiagen; MD) was used.
DNeasy PowerPlant Pro Kit uses patented technologies like mechanical bead beating technology and inhibitor removal technology. Mechanical bead
14 beating technology was designed to result in an ample amount of DNA collection, and inhibitor removal technology was designed to result in pure
DNA. According U.S. patent 20120288957 A1 (Bruinsma, 2012) mechanical bead beating technology increases the yield by disrupting cells effectively with metal beads in a tube. When the tube is shaken with homogenizer, metal beads disrupt the cells effectively. Inhibitor removal technology uses a two- step method. The first step is to add insoluble polyvinylpyrrolidone to samples.
Insoluble polyvinylpyrrolidone binds to secondary metabolites and forms complexes. Polyvinylpyrrolidone and secondary metabolites complexes can be easily removed with spin columns which consist of polyethylene frit with 20
μm pores. Spin columns hold DNA while filtering unwanted secondary metabolites and elute DNA at the final step. According to Qiagen, an extra purification step can be omitted using PowerPlant Pro Kit since its inhibitor removal technology effectively remove secondary metabolites.
There are many ways to quantify the isolated DNA, and they each have advantages and disadvantages. The spectrophotometery method measures a range of ultraviolet spectrum absorbed by purines and pyrimidines in DNA, and absorption value at 260 nm can be used to find concentration of DNA (Loring et al., 1952). It is an easy and cheap method, but spectrophotometry is not species specific and not specific for double stranded DNA. 260 nm also detects single stranded DNA and RNA
(Nakayama, 2016). PicoGreen and QuantiFluor dsDNA system use DNA binding dye for better sensitivity at 260 nm. It can detect as low as 50 pg/mL
(Promega, 2016; Thermofisher, n.d.). However, PicoGreen and QuantiFluor 15 dsDNA system are expensive. Spectrophotometry method is a cheap and accurate method for this project since samples only contain double stranded
DNA. RNA was degraded by RNAse during the DNA isolation process.
Marker Choices
There are many marker systems that can characterize cultivars.
Morphological, biochemical, and molecular marker system have been used to characterize and assess diversity in cultivars (Devi, 2012). It is important to pick an adequate molecular marker for specific usage because each marker system offers different information. Morphological markers rely on visual descriptors to characterize each sample, and it can be done cheaply. However, morphological data could be influenced by environmental effects and other factors (Okpul, 2005). In addition, inheritable somatic mutations can be shown phenotypically (Kuruvilla et al.,1980). Morphological markers are not reliable but can be good complementary information when used with molecular markers (Okpul, 2005). Isozyme markers utilize isozymes that their alleles are highly variable yet still functioning the same (McClean, 1998). Some isozymes migrate differently in gel electrophoresis. For example, enzymes like malate dehydrogenase, isocitrate dehydrogenase, phosphohexose isomerase, 6- phosphogluconate dehydrogenase, malic enzyme, shikimate 5- dehydrogenase, and alcohol dehydrogenase are known to have variation among different groups of Colocasia (Lebot, 1991). Isozyme marker is co- dominant marker system that can be used to calculate heterozygosity.
However, isozyme markers are rarely studied because they have a limited
16 number of isozyme loci, they are expensive, and variability among tissues in same plant occurs (McClean,1998).
A DNA marker system is highly polymorphic and reliable when measuring genetic diversity. The genetic characterization of Colocasia’s genome with DNA markers has been done by many researchers with promising results. There are some different DNA markers that can evaluate genetic diversity among cultivars or species such as simple sequence repeat
(SSR), ISSR, amplified fragment length polymorphism (AFLP), and random amplified polymorphic DNA (RAPD) (Chaïr et al, 2016; James et al, 2012;
Quero-García et al.,2009). While they exhibit high polymorphism (Irwin et al.
1998; James et al., 2012; Okpul, 2005; Rasco et al., 2016) RAPD has a problem with low reproducibility, high cost for AFLP, and SSR requires prior knowledge for flanking sequence (Reddy, 2002).
ISSR is a multilocus method where each reaction with a primer amplifies different sets of fragments of DNA. With extensive loci assessment in genome, ISSR is used for finger printing, phylogenetic analysis, population structure analysis, varietal/line identification, genetic mapping, and marker- assisted selection (Vijayan, 2005). Each reaction contains a primer that binds on simple sequence repeat microsatellites on template. Primers can either bind close to 3’ end or 5’ end. When two complementary strands bind together, genomic region in between microsatellite repeats are amplified (Ng et al.,
2015). This genomic region between microsatellite regions can be conserved or nonconserved region. Therefore, ISSR is not suitable for distinguishing
17 individuals (Rukam, 2010), but genomic regions are variable enough to distinguish cultivars and species (Reddy et al., 2002).
Genetic Stability Analysis
While wild Colocasia is a normally propagated via seed (CTAHR,
2009), commercial cultivars are propagated vegetatively. Vegetative propagation is preferred for consistent desirable characteristics. Sexual recombination is not preferred for cultivars because of genetic recombination that can cause loss of desired characteristics. To be a cultivar, uniformity of genetic material is crucial to maintain desired characteristics. However, mutations have played an important role in creating new cultivars with desired characteristics like TLB disease resistance and improved yield. Mutations that are crucial for genetic diversity can be problematic for growers who desire uniformity. Clonal mutation in Colocasia happens, and it was reported in
African and American countries (Chaïr, 2016). In this project, banding patterns of clones of each cultivar will be compared. We expect matching bands in a cultivar since mutation rarely occurs.
Genetic Diversity Analysis
Heterozygosity is a major indicator of genetic diversity that measures richness and evenness of allele in the dataset (McDonald, n.d.). However, it is impossible to find heterozygosity and allele frequency with ISSR data especially for Colocasia cultivars. As referred earlier, Colocasia cultivars can be diploid or triploid, and ploidy of our cultivars is unknown. Heterozygosity
18 cannot be found since dominant homozygotes and heterozygotes produce a band in dominant marker. Only co-dominant markers can be used to find heterozygosity. Genetic analysis methods that are free from Hardy-Weinberg equilibrium (HWE) were used in this project to overcome limitations of ISSR. A distance based clustering method UPGMA with Jaccard’s coefficient (Jaccard,
1908) and, PCO using Gower’s general similarity measure (Gower,1966) were used find a relationship among cultivars. Shannon’s diversity index (Shannon et al., 1949) was used to quantify genetic diversity. Genetic relationship and diversity quantification information can be complimentary data to explain genetic diversity within 44 ornamental Colocasia cultivars.
Cluster analysis groups individuals based on characteristics they have
(Hair et al., 1995). Individuals sharing common characteristics gather together while individuals with different characteristics separate when plotted geometrically. In our case, cultivars that have more matching bands were plotted closer than cultivars that have less matching bands. Graphed plots from cluster analysis represent high internal homogeneity within the cluster and high external heterogeneity between clusters (Hair et al., 1995). Cluster analysis can be done with two different ways such as distance-based method that utilize pairwise distance matrix as an input and model-based methods that use observations from distribution of characteristics. Distance-based method has been widely used to measure genetic diversity since graphical results such as trees and dendrograms represent relationship visually
(Mohammadi et al., 2003).
19 ISSR examines multiple loci for each sample. ISSR is a dominant marker which means a band is produced when single dominant allele is present on a locus, and recessive homozygous alleles do not produce a band.
However, absence of the band could be due to many reasons including recessive homozygous alleles. For example, loss of a primer annealing site, insertions or deletions in the fragment between the two primer sites, or experimental error can lead to absence of band (Culley, 2005). Assuming absence of band as homozygous recessive based on HWE can affect the precision of the analysis. For example, there is a chance when absence of band from homozygous recessive is categorized same as absence of band from error, not assuming HWE increase precision. UPGMA (Sokal et al. 1958) with Jaccard’s (1908) coefficient was chosen to minimize the error. Jaccard’s coefficients can be calculated with equation:
. (1)
where A is number of loci that have matching present alleles between two cultivars, and
B and C are number of loci where the band is present in only one cultivar.
Because only present bands are reflected on the coefficient, absent bands are excluded from analysis. UPGMA is designed to minimize the inter- group distance by averaging pairwise distance among all size of the bands of samples. A dendrogram will be made based on UPGMA to identify relationship among cultivars visually.
20 Multivariate statistical algorithms classify and order genetic variability for a large number of samples with multiple characteristics simultaneously
(Mohammadi et al., 2003). Multivariate statistical algorithms compress large amounts of data into a simplified way minimizing loss of data. This way it is easy to capture the similarity among different samples with a lot of variables.
The multivariate statistical techniques such as principal component analysis, principal coordinate analysis, correspondence analysis, and discriminant analysis are commonly done when finding genetic diversity (Jombart et al.,
2009). PCO is useful when there are more variables than samples since similarities between a pair of samples is measured directly (Kovach, 2007).
One advantage of PCO is that the user has a choice of similarity or dissimilarity measures. For mixed binary data, Gower’s general similarity coefficient is a good option because it works same as Jaccard’s coefficient by using only present bands. Eigen value and eigen vectors are calculated in
Eigenanalysis. Eigen values are same as variance of each principal component. Eigen vectors are array of loadings that indicate influence of principal component. By multiplying component loadings with original data, a matrix of component scores are obtained for each principal component.
Scatter graph is made to find relationship among samples using first two principal components as X and Y axis. Gower’s general similarity can be calculated with equation:
(2)
21
where sijk =
sijk is 1 for matches of binary or multistate data
sijk is 0 for all mismatches
wijk is 0 for negative matches of binary data
wijk is 1 in all other situations
Once the relationships among the cultivars are examined, genetic diversity can be quantified by examining richness and evenness of alleles.
Richness of alleles means number of alleles that exist in a population.
Evenness of the alleles means how proportionally alleles are present at loci in a population. Shannon’s diversity index was used since they do not assume
HWE to explain genetic diversity (Culley, 2005). Shannon’s diversity index is one of the diversity indexes often used to find genetic diversity in ecology. It measures diversity in alleles by calculating abundance and evenness of the alleles at loci. When using ISSR binary data, it does not assume HWE but it recognizes bands as a phenotypic characteristic (Shannon et al., 1949).
Shannon’s diversity index is calculated by equation below:
(3)
where i is proportion of allele I and,
pi is proportion of I divided by total number of alleles.
22 Materials and Methods
Sample collection and preparation
44 ornamental Colocasia cultivars were planted and cultivated in the
SFA Horticulture trial garden in Stephen F Austin State University (USDA
Hardiness zone 8b, AHS Plant Heat-Zone 9) from in July 2016. Using a razor blade, leaves were cut from bottom of the petiole. One newly emerged smallest and lightest color leaf was collected from each plant in Nov 2016.
During the growing season, April to November, the average maximum temperature was 29°C, average minimum temperature was 16°C, and average precipitation was 100.5 mm. The trial garden consisted of five beds
(Bed A to E) with each bed containing clones of 44 cultivars in a complete randomized block design, allowing for up to five samples from the trial.
Accession number was given to each cultivar. Figure 1. illustrates how each bed from A to E containing 44 cultivars are positioned. However, due to mortality, six cultivars had less than five clones. Number of clones and information about each cultivar can be seen on (Table. 1). Each leaf sample was enclosed in a zip lock and stored in -80°C fridge.
23 A B C D E 39 29 17 34 57 6 19 44 3 11 60 31 8 25 43 38 63 12 32 44 37 15 44 55 15 42 1 20 51 9 3 22 44 48 15 32 44 8 3 11 40 3 43 29 40 6 39 52 36 18 63 3 31 17 55 21 63 19 19 32 30 31 19 1 57 10 25 34 60 10 16 6 35 21 63 46 51 57 40 22 36 23 15 37 28 38 34 9 54 22 35 40 17 25 42 17 31 32 25 23 37 8 6 28 37 21 54 21 57 12 27 2 41 41 29 25 43 62 27 29 2 58 46 41 1 35 39 31 28 23 30 40 62 34 36 10 19 41 16 52 36 62 60 54 10 9 54 23 58 16 17 34 37 46 60 51 11 20 57 41 12 35 28 9 12 63 2 36 11 31 18 42 18 51 46 11 1 38 48 21 43 6 4 4 20 48 27 38 1 23 8 51 30 39 30 35 52 4 18 52 62 9 32 58 18 12 39 8 4 15 54 48 38 62 55 60 20 27 27 16 42 22 55 42 28 22 43 4 10 16 2 29 20 58 55 52 46 48 2 58
Figure 1. Representation of Colocasia trial garden five bedsxy (Bed A to E).
x Each bed contained a clone of each cultivar in a complete randomized block design. y Open spaces were for additional future cultivars.
24 DNA Isolation
DNA from all samples were extracted with DNAeasy PowerPlant Pro
Kit using the included PD1, PD2, RNase, PD3, PD4, PD5, PD6, PD7, and MB spin column (Qiagen; MD). Every time leaf samples were needed they were taken out from the -80°C fridge and grounded with pestle and mortar until they looked like paste with pestle and mortar. Pestle and mortar were washed with alkonox (Alconox; NY) after grinding each sample. 50 mg of grounded paste- like plant leaf tissue were added into a PowerBead tube with 410 µL of bead solution and 40 µL of phenolic separation solution. 50 µL of solution SL and 3
µL RNAse A solution were added and homogenized with vortex for 10 min.
After taking out of the vortex, PowerBead tube was centrifuged at 13,000 gn for 2 min. Only supernatant was transferred to 2 mL collection tube. 175 µL of solution IR was added and vortexed for 5 seconds and then incubated at 4°C for 5 min. 2 mL l tube was centrifuged at 13,000 x gn for 2 min. 600 µl of supernatant was transferred to other 2 mL tube and mixed with 600 µl of solution PB and 600 µL ethanol and then 2 mL tube was vortexed. In MB spin column, 600 µL of lysate was loaded each time and centrifuged at 10,000 x gn for 30 seconds until 2 mL tube is empty. Then 500 µl of CB was loaded to the
MB spin column and centrifuged at 10,000 x gn for 30 seconds. Flow-through was discarded. 500 µL of ethanol was added to the MB spin column and centrifuged at 10,000 x gn for 30 seconds. Flow-through was discarded. 2 mL collection tube was centrifuged at 16,000 x gn for 2 minutes. 50 µL of EB solution was added on the white filter membrane and incubated for 2 min at
25 room temperature. Collection tube was centrifuged at 10,000 x gn for 30 seconds. MB spin column was discarded, and genomic DNA was stored in
4°C refrigerator.
Quantification of DNA
Purity and quantity of DNA samples were measured with spectrophotometer Cary 15 (Varian, Inc; CA) and semi micro open top quartz spectrophotometer cuvette (Starna Cells; CA). On the quartz cuvette, 4 µL of
DNA sample was placed on the top of the cuvette. Using Varian Cary WinUV program (Varian, Inc; CA), range of the absorbance was set 240 mm to 325 mm. To measure concentration of the DNA, 260 mm value was subtracted from 320 mm to find the concentration of DNA without contaminants in DNA samples. Subtracted value was multiplied by 10, which is pathlength factor, and then 50 was multiplied to make µg/µL (Carlos et al., 2007). Purity of the
DNA sample was obtained by dividing 260 mm from 280 mm. DNA samples considered as pure ranged from 1.7 to 2.1. Only samples in that range were used for ISSR.
Polymerase Chain Reaction Based Inter Simple Sequence
260 nm/280 nm values of all the DNA samples were within the range from 1.6 to 2.1. Amplifications were done using GoTaq® G2 DNA Polymerase
(Promega; WI), Nucleotides mix (Promega; WI), and 8 different primers
(Sigma-Aldrich; MO) which are listed in Table 2. Primers were ordered as dried. Polymorphic primer sequences were obtained from Okpul et al. (2005),
26 James et al. (2012), and Hussain et al. (2006). Number and size of the bands showed variation by researchers. Okpul (2005) obtained 10–16 bands and 6–12 bands for Hussain et al. (2006), Singh et al., (2008) obtained 22–83 bands. Recommended amount of nuclease free water was added to each primer tube to make concentration of 100 μM and diluted to 10 μM for convenience. Each PCR reaction was done total 25 µL volume consisting of
0.5 U gotaq polymerase, 3 mm MgCl2, 5 μL of 5X green GoTaq reaction buffer
(Promega; WI), 0.6 μM of primer, 200 μM of each nucleotide, and 30 ng of
DNA. PCR reaction temperatures and durations were based on recommendation on GoTaq® G2 DNA Polymerase (Promeg; WI). Annealing temperature for each primer was determined by equation Tm (°C) = 81.5 +
0.41(%GC) - (675/N). T100 thermocycler (Bio-Rad;CA) was used for PCR.
Time setting and temperature setting for each process is listed in Table 3.
After final extension, products were stored in 4°C thermocycler overnight.
Table 2. List of primers with sequence and annealing temperature.
Primer Sequence (5’-3’) Annealing Temperature (°C) SINGH 1 GAGAGAGAGAGAGAGAGAAT 50 SINGH 2 GAGAGAGAGAGAGAGAGAAC 52 SINGH 3 ACCACCACCACCACCACCY 56 814 CTCTCTCTCTCTCTCTTG 48 844A CTCTCTCTCTCTCTCTAC 48 17898B CACACACACACAGT 45 17899A CACACACACACAAG 48 HB11 GTGTGTGTGTGTCC 51
Table 3. Thermocycler setting for PCR-ISSR.
27 Stage Duration Temperature (°C) Cycles Initial Denaturation 5 min 94 1 Denaturation 1 min 94 35 Annealing 30 sec 45-56 35 Extension 5 min 72 35 Final Extension 10 min 72 1
Agarose Gel Electrophoresis
108 well owl A1 large gel electrophoresis system (ThermoFisher
Scientific; MA) and 8 well gel electrophoresis system were used for gel electrophoresis. Every gel had 4mm thickness. 1.5 % Agarose gel was made with 0.5 μg/mL ethidium bromide and 1 x TAE. All purpose Hi-Lo DNA marker
(Bionexus; CA) was used for marker. Gel electrophoresis was stopped when
PCR products and All Purpose Hi-Lo DNA Marker were migrated to 2/3 of the gel. Then, the gel was carefully transferred to glass tray in Typhoon FLA 9500
(GE Healthcare Life Sciences;IL).
Banding Patter Scoring
To visualize bands on a gel and determine fragment sizes of each sample, a program called ImageQuant TL (GE Healthcare;IL) was used.
Changing contrast function in ImageQuant TL, bands were visualized clearly.
Band sizes were estimated comparing standard which is all purpose Hi-Lo
DNA marker. All Purpose Hi-Lo DNA Marker showed standard from 50 base pair (bp) to 10,000 bp. The ImageQuant TL enabled the user to detect bands for each sample. Bands produced by Hi-Lo DNA Marker was detected and bp
28 size were assigned to each band. Once bands of the standards are labeled with bp size, fragments of each samples were compared to standard and software estimated fragment sizes of each sample. Bands were scored as presence and absence character. Present bands were scored as 1 and absent band was scored as 0. Samples that did not create bands at all were amplified again.
Statistical Analysis and Genetic Quantification
All the statistical analysis was done using a program called Multi
Variate Statistical Package (MVSP) 3.2.1 (Kovach Computing Service; UK).
Binary score data from ISSR was entered in data editor. UPGMA with
Jaccard’s coefficient, and PCO with Gower’s general similarity coefficient were performed choosing options. Using graph option, scatter graphs were made for PCO. Shannon information index were obtained with Popgen32.
Binary data were treated as dominant diploid data.
Results and Discussion
DNA Isolation and Quantification
Approximately 90% of the isolated DNA samples were considered as pure and had high DNA concentration for PCR. 50–100 µL of EB solution containing DNA was collected for each sample. Two cultivars were hard to collect pure DNA because of high secondary metabolite content. Those samples were isolated again eluting 100 µL instead of 50 µL and extra time 29 was given for vortexing and incubation. Re-isolated samples had good amount of pure DNA for PCR. Results are in Appendix A.
Quality and quantity of isolated DNA using DNeasy PowerPlant Pro Kit
(Qiagen;MD) were suitable for PCR based on quantification using spectrophotometer. Best results were obtained after some modifications on manufacture’s protocol. The most effective modification was grounding plant tissue samples fine with mortar and pestle until they became a paste. When leaf samples were cut into big pieces, low concentration of DNA was obtained occasionally. The reason is because metal beads sometimes fail to disrupt the cells even though plant tissues were soft. Additional steps such as adding more incubating time, re-eluting DNA, more centrifuging time, more vortexing time for bead beating, and larger volume of eluting buffer lead to better result.
Manufacturer recommends 50–100 µL for final elution. Eluting 100 µL resulted in the same concentration of DNA as eluting 50 µL while having purer DNA.
Cultivars like Colocasia esculenta ‘Morning Dew’ and Colocasia esculenta
‘Painted Black Gecko’ had a hard time isolating pure DNA. They have dark purple leaves and dark pigments remained with DNA after final elution. When they were treated with modifications listed above, pigments were no longer present with eluted DNA. All samples had 260 nm/280 nm ratio for 1.6–1.8, and concentrations of DNA were 50–200 µg/mL. No extra purification was necessary as advertised from Qiagen.
Banding Pattern Scoring
The main point of using PCR based ISSR marker is to detect
30 polymorphism in DNA. ISSR data showed a total of 266 loci amplified with 8 primers. 264 loci were polymorphic loci, which makes 99.25% polymorphic loci percentage. 8 primers showed a large number of polymorphic loci as well as polymorphic loci percentage because only primers that were known to be polymorphic were used. 27–43 bands were observed in 8 primers in our result.
Range of band size was different by studies. Okpul et al. (2005) obtained
200–1300 bp, Hussain et al., (2006) obtained 200-2000 bp, and our result showed 360–3975 bp.
Each cultivar produced total 46–72 bands amplified with 8 primers.
Colocasia esculenta ‘Morning Dew’ and Colocasia esculenta ‘Jacks Giant’ produced 72 bands which is the highest number. However, they do not share similar genetic background. Colocasia esculenta ‘Morning Dew’ is from a breeding program conducted by Dr.John Cho and Colocasia esculenta ‘Jacks
Giant’ was found in Costa Rica. The least number of bands produced in our
Colocasia collection was 47 bands produced from Colocasia esculenta
‘Tropical Storm’ introduced by Dr.John Cho.
Colocasia esculenta cultivars showed highest level of banding polymorphism. The highest and lowest number of bands were produced by
Colocasia esculenta cultivars. Colocasia gigantea and Colocasia antiquorum cultivars showed relatively lower banding polymorphism than Colocasia esculenta cultivars. Colocasia gigantea cultivars produced 56–66 bands and
Colocasia antiquorum cultivars produced 52–61 bands which are within the range of bands produced by Colocasia esculenta cultivars. Differences could
31 be due to different number of cultivars per species or Colocasia esculenta cultivars are more polymorphic than Colocasia gigantea cultivars and
Colocasia antiquorum cultivars. Percent of bands shared by all cultivars is zero which support the high genetic diversity.
Primer S3, the trinucleotide repeat primer, produced the highest of bands unique to one cultivar which indicate S3 detects polymorphism of DNA better than rest of the primers. Highest number of bands created at a locus was 36 bands. Percent of bands unique to one cultivar is 4.2%–33.3% and average is 13.9%.
Table 4. Observed bands produced from each primer.
Primer 814 S1 S2 S3 844 17898B 17898A HB11 Number of Bands 27 34 26 29 36 43 36 36 Band size (bp) 500-2665 500-3975 360-2110 240-2665 360-2930 360-3070 450-2750 450-3110
32 Table 5. Number of bands producedx after PCR-ISSR.
Marker C.e 'Big Dipper' C.e 'Bikini-Tini' C. a 'Black Beauty ' C.e 'Black Coral' C.e 'Black Magic' 814 8 7 7 8 5 S1 8 8 6 6 6 S2 6 5 6 4 5 S3 7 5 6 8 9 844 10 10 7 8 10 17898B 9 11 8 8 8 17898A 10 7 7 9 6 HB11 10 8 5 12 8 Total 68 61 52 63 57
Marker C.e 'Black Ripple' C.e 'Black Runner' C.e 'Black Sapphire Gecko' C.e 'Blue Hawaii' C.e 'Coal Miner' 814 4 6 6 5 8 S1 6 6 8 8 9 S2 4 4 6 7 11 S3 6 4 7 4 4 844 6 9 12 8 8 17898B 8 6 9 10 9 17898A 8 6 8 10 9 HB11 8 10 3 9 7 Total 50 51 59 61 65
Marker C. 'Coffee Cups' C. gigantea 'Laosy Giant' C.e 'Lemonade' C.e 'Lime Aide' C.e 'Madiera' 814 7 6 4 4 4 S1 7 9 13 13 13 S2 9 6 7 7 7 S3 3 7 3 4 4 844 11 7 8 8 7 17898B 9 9 8 11 7 17898A 9 7 8 9 9 HB11 8 5 8 8 5 Total 63 56 59 64 56
Marker C. 'Mammoth' C.e 'Maui Gold' C.e 'Maui Magic' C 'Maximus Gigante' C.e 'Midori Sour' 814 6 4 3 7 4 S1 13 9 11 8 8 S2 7 7 8 7 6 S3 4 4 5 5 7 844 7 10 10 7 9 17898B 10 11 9 9 10 17898A 8 8 11 11 7 HB11 7 7 10 6 5 Total 62 60 67 60 56
Marker C.e 'Mojito' C.e 'Morning Dew' C.e 'Dragon Heart Gigante' C.e 'Electric Blue Gecko' C.e 'Elepaio' 814 4 8 5 2 2 S1 6 12 5 12 7 S2 7 8 7 6 11 S3 4 7 5 10 3 844 7 10 10 7 9 17898B 12 10 9 0 4 17898A 9 10 8 8 8 HB11 8 7 10 7 9 Total 57 72 59 52 53
Marker C. g 'Fierce Gigante' C. 'Fontenseii' C.e 'Hawaiian Punch' C. a 'Illustris' C.e 'Imperial Gigante' 814 3 9 5 11 7 S1 9 0 0 7 7 S2 7 7 10 9 7 S3 4 4 4 2 2 844 14 12 10 8 7 17898B 9 10 7 9 8 17898A 10 10 8 8 7 HB11 9 9 10 7 5 Total 65 61 54 61 50
x For each cultivar, bands produced from each primer was counted and total bands produced from 8 primers were summed at below.
33 Table 5 continues with rest of the cultivars.
Marker C.e 'Jack’s Giant' C.e 'Kona Coffee' C.e 'Nancy’s Revenge' C.e 'Painted Black Gecko' C.e 'Pink China' 814 7 7 4 5 5 S1 14 12 8 8 5 S2 10 8 7 8 6 S3 2 4 5 6 4 844 8 7 11 12 11 17898B 12 8 8 10 0 17898A 11 7 7 12 9 HB11 8 7 6 5 6 Total 72 60 56 66 46
Marker C.e 'Red-Eyed Gecko' C.e 'Rhubarb' C.e 'Ruffles' C.e 'Sangria' C.e 'Tea Cup' 814 3 7 8 7 3 S1 7 9 5 7 9 S2 6 5 7 5 6 S3 4 5 4 5 5 844 13 6 7 10 11 17898B 9 8 8 8 12 17898A 11 9 9 7 7 HB11 5 5 3 5 7 Total 58 54 51 54 60
Marker C. gigantea Thailand Giant' C.e 'Tropical Storm' C.e 'Violet Stem' C.e 'White Lava' 814 4 4 4 5 S1 0 6 7 6 S2 8 7 11 10 S3 6 3 3 5 844 10 4 9 10 17898B 10 6 9 7 17898A 12 9 7 2 HB11 10 8 9 8 Total 60 47 59 53 Table 6. Percent of bands shared by all cultivars and unique bands for each cultivar in all 44 cultivars
Marker Percent of Bands Shared by all Cultivars Percent of Bands Unique to One Cultivar 814 0% 22.2% S1 0% 8.8% S2 0% 4.2% S3 0% 33.3% 844 0% 8.3% 17898B 0% 11.9% 17898A 0% 13.9% HB11 0% 8.3% Average 0% 13.9% Genetic Stability Analysis
Within a cultivar, no variation in banding pattern was observed among clones. In some cases, visibility of the bands was not identical among clones.
Some bands were less visible than other bands. However, most of the faint bands were confirmed to exist by changing contrast of the picture. Seven clones produced different banding pattern from other clones in a same cultivar.
34 To verify absence of bands or additional bands were due to a genetic difference, DNA was isolated again from the leaf tissue. After using newly isolated DNA as a template for ISSR, band patterns matched with rest of the clones. Band pattern of original amplification and new amplification with new
DNA results were compared on Appendix D. There is no statistical data for mutation frequency when Colocasia is vegetatively propagated. However, when plants are vegetatively propagated, mutations are more likely happen compared to sexually propagated plants (Fisher, 1930). In vitro clone propagation demonstrated that when a clone contains an organized meristem, the plant is less susceptible to genetic variation via cell division or cell differentiation (Shenoy et al., 1992). Since there was no difference in banding pattern among the cultivars, data has been simplified by having no repetitive samples for each cultivar.
UPGMA
The dendrogram using UPGMA was made using Jaccard’s coefficient.
By taking average distance and grouping two most similar samples or groups, the dendrogram was made. For example, the two cultivars that share the highest similarity index Colocasia esculenta 'Lemonade' and Colocasia esculenta 'Lime Aide' were grouped first. Similarity values between the first group was averaged with rest of the cultivars. Second most similarity index was found between cultivars Colocasia esculenta 'Big Dipper' and Colocasia esculenta 'Bikini-Tini' which were grouped together. By taking average similarity of 4 cultivars between two groups, a distance between two groups
35 were calculated. Next most similar cultivars or groups were grouped together as previously stated, and this process continued until all the samples are branched.
Formation of clusters and distances of branches were considered when interpreting the dendrogram. X-axis indicates Jaccard’s coefficient that can be percentage of similarity when multiplied by 100. Branches that were close to right side share more similarities than branches close to the left.
Branches were concentrated at the left side around 0.3, which indicates low similarity. Similarity indexes were obtained from the Jaccard’s coefficient, and
44 cultivars showed low similarities between cultivars. Overall similarity was
30% between cultivars and groups. The most similar cultivar pair was
Colocasia esculenta 'Lemonade' and Colocasia esculenta 'Lime Aide' with a similarity index of 0.618. They shared a similar genetic background. Colocasia esculenta 'Lime Aide' was first brought from Philippines by Mr. Alan Galloway.
Colocasia esculenta 'Lemonade' is a mutant form of Colocasia esculenta
'Lime Aide'. A pair of the most dissimilar cultivars were Colocasia esculenta
'Electric Blue Gecko' and Colocasia gigantea 'Fierce Gigante' with similarity index of 0.073.
Overall similarity among our ornamental Colocasia cultivars are lower than overall similarity among Colocasia cultivars from the same region done by James et al. (2012). Compared to our result, which is overall 30% similarity, samples collected from the same region showed higher similarities.
Okpul et al., (2005) collected samples from Papua New Guinea and found
36 high similarities (64–95%) among cultivars using UPGMA. James et al. (2012) collected samples from Hawaii and found high overall similarities (80%) among cultivars using UPGMA. In addition, Chaïr et al. (2016) found out similarity index is very low (20%) among international core samples that represent nineteen countries.
UPGMA distinguished most of the Colocasia gigantea cultivars from
Colocasia antiquorum cultivars and Colocasia esculenta cultivars. In the dendrogram, two Colocasia gigantea cultivars and a Colocasia gigantea hybrid cultivar produced a cluster. However, there was an outlier that was not included in the Colocasia gigantea cluster. Colocasia gigantea ‘Thailand
Giant’, Colocasia ‘Maximus Gigante’, and Colocasia gigantea ‘Laosy Giant’ produced a cluster. Since Colocasia ‘Maximus Gigante’ contains Colocasia gigantea genome from the male parent, it was expected that Colocasia
‘Maximus Gigante’ belonged to Colocasia gigantea cluster. One outlier that did not belong to the Colocasia gigantea cluster was Colocasia gigantea
‘Fierce Gigante’.
Studies demonstrated that Colocasia gigantea and Colocasia esculenta are separate species and suggested that Colocasia gigantea may belongs to different genus. Irwin et al. (1998) clearly distinguished Colocasia gigantea from Colocasia esculenta in a dendrogram that they produced by
UPGMA using RAPD data. Ahmed et al. (2012) examined chloroplast genomes using SSR markers and reported that Colocasia gigantea did not seem to belong to Colocasia genus instead, they were close to Alocasia
37 genus based on chloroplast genome. Filtered super networks that showed phylogenetic trees revealed Colocasia gigantea was closer to Alocasia than to other Colocasia species (Ahmed et al., 2012). Matthews et al. (1990) used mitochondrial DNA probe to distinguish plant samples and they clearly distinguished Colocasia esculenta from Colocasia gigantea. However, differences were not observed between Colocasia esculenta cultivars. Results from examining mitochondrial rDNA indicated Colocasia gigantea is less closely related to mitochondria in Colocasia esculenta but closely related to
Alocasia brisbanensis (Matthews et al., 1990). Our UPGMA dendrogram showed similar results by distinguishing majority of the Colocasia gigantea cultivars including Colocasia gigantea hybrid from rest of the Colocasia antiquorum cultivars and Colocasia esculenta cultivars.
Two Colocasia antiquorum cultivars were not distinguished from
Colocasia esculenta cultivars. Two Colocasia antiquorum cultivars did not produce a cluster. Instead, they were clustered with Colocasia esculenta cultivars. As referred earlier in project introduction, it has been a controversial whether Colocasia antiquorum and Colocasia esculenta are two separate species since Colocasia antiquorum can be one of the morphologic variant of
Colocasia esculenta. Previous studies using morphological characterization successfully distinguished between two species (Barrau, 1957; Onyilagha et al., 1986). On the other hand, studies using molecular characterization did not distinguish between Colocasia esculenta cultivars and Colocasia antiquorum cultivars (Brown et al., 2009; Mace et al., 2002). Recently, those two species were reduced to the level of two botanical verities Colocasia esculenta var. 38 esculenta and Colocasia esculenta var. antiquorum based on floral characteristics (Lakhanpaul et al., 2003). United States national plant germplasm system consider Colocasia antiquorum and Colocasia esculenta as a same species (United States National Plant Germplasm System, 2011).
Our UPGMA dendrogram showed same results from Mace et al. (2002) and
Brown et al. (2009) and supports the recent movement in changes in taxonomic position.
Figure 2. Dendrogramxy of 44 Colocasia cultivars produced using UPGMA with Jaccard’s coefficient.
x X-axis represents Jaccard’s coefficient yboxed in red are Colocasia gigantea and blue are Colocasia antiquorum. 39 Table 7. Seven most similar Colocasia cultivars where the similarity index value was higher than overall similarity index average.
Rank Most Closely Related Pair Similarity Index 1 Colocasia esculenta ' Lemonade' Colocasia esculenta 'Lime Aide' 0.618 2 Colocasia esculenta 'Big Dipper' Colocasia esculenta ' Bikini-Tini' 0.593 3 Colocasia 'Coffee Cups' Colocasia esculenta ' Coal Miner' 0.542 4 Colocasia esculenta 'Red-Eyed Gecko' Colocasia esculenta ' Rhubarb' 0.455 5 Colocasia antiquorum 'Illustris' Colocasia esculenta ' Imperial Gigante' 0.442 6 Colocasia esculenta ' Painted Black Gecko' Colocasia esculenta ' Morning Dew' 0.38 7 Colocasia esculenta 'Violet Stem' Colocasia esculenta 'Tropical Storm' 0.338
Principal Coordinates Analysis
There was only 12.2% of variation observed in two principal components. 6.9% variation on first axis, and 6.3 % variation on second axis were observed. Low cumulative variation in first two principle components can be caused by having a lot of variables. Similar studies demonstrated that PCO with low variations in first two PCs can be used as a complimentary data to find genetic relationships among cultivars and species. James et al. (2012) obtained 23.5% variation in first two PCs and formed clusters in PCO plot which are same clusters made from UPGMA. Costa et al. (2016) examined genetic relationships Dactylis glomerata using PCO with RAPD, ISSR and
AFLP markers and obtained 14.2% of variation in first two PCs in PCO. Their
UPGMA and PCO showed a same picture that Dactylis glomerata are genetically closely related. Genotypes are plotted on the center of PCO plot, overlapping significantly with the other genotypes (Costa et al., 2016).
The scatter graph of PCO was made starting from plotting each sample with 267 variables in each dimension. PCO created number of sample
– 1 dimension, which made total of 43 dimensions. A principle component for
40 each dimension represents variation among the cultivars. A dimension that represented the most variation became PC1 and a dimension that contained second most variation became PC2. Each cultivar was plotted based on component scores of PC1 and PC2 on PCO scatter graph. Component scores were calculated from Eigenanalysis and Eigenvector using Gower’s similarity measure. Ultimately cultivars were positioned in reduced dimension while preserving distance relationships. Cultivars that were closely related had shorter distance than cultivars that were distantly related.
Some cultivars were plotted more closely than others, but overall, cultivars were widely dispersed in all four quadrants in the scatter graph.
Colocasia gigantea cultivars did not form a cluster in distinct area. However,
Colocasia gigantea ‘Thailand Giant’, Colocasia gigantea ‘Fierce Gigante’, and
Colocasia gigantea ‘Laosy Giant’ formed a cluster at the second and third quadrant. An outlier, Colocasia ‘Maximus Gigante’ was relatively distantly located from the cluster consists of three Colocasia gigantea cultivars. Two
Colocasia antiquorum cultivars shared a long distance in the scatter graph, and they were plotted on the second and forth quadrant of the scatter graph.
Instead, two Colocasia antiquorum cultivars shared close distances to other
Colocasia esculenta cultivars. The PCO result did not exactly match with the result from UPGMA. However, the PCO result supports the result from
UPGMA by producing a cluster consists of most of the Colocasia gigantea cultivars and not forming a cluster consists of Colocasia antiquorum cultivars.
Pairs of cultivars that were highly similar such as top 7 similar cultivars
41 from UPGMA maintained relatively short distances in PCO scatter graph. The dendrogram made from UPGMA and the scatter graph from PCO showed same big picture by having no groups while cultivars were loosely related overall.
42
Figure 3. PCO scatter graphy of 44 Colocasia cultivars using PC1 as X- axis and PC2 as Y-axisx.
y 6.9% variation on PC1 and 6.3 % variation on PC2 were observed. x Red circles contain Colocasia gigantea cultivars. Blue circles contain Colocasia antiquorum cultivars. 43 Genetic Diversity Quantification
Average Shannon’s diversity index for all loci is 0.44. Our Shannon’s diversity index is relatively high compared to studies using other ornamental plants and Colocasia cultivars planted locally in farm. Contrary to studies using Colocasia cultivars from a specific region, Chaïr et al. (2016) performed genetic diversity analysis of an international core collection. An international core collection is a set of collection that contains cultivars represented from each country. It consists of 321 Colocasia cultivars obtained from farmers in
19 different countries in four continents. Using SSR-PCR as a marker and 11 primers, they obtained 0.11–0.21 in Shannon’s information index for four continents. Highest Shannon’s diversity index value of 0.21 was obtained from
Asian cultivars which they suspected to be origin of the Colocasia. Our
Shannon’s diversity index is higher diversity than Colocasia cultivars obtained from four continents. Macharia et al., (2014) obtained 98 Colocasia cultivars from farmers in Uganda, Tanzania, and Kenya. Using ISSR and seven primers, they obtained Shannon’s diversity index value of 0.2476–0.4871. Our
Shannon’s diversity index 0.44 was slightly lower than their highest Shannon’s diversity index value of 0.4871.
Table 8. Comparable Shannon’s diversity index of other Colocasia cultivars and ornamental genera.
Researchers Number of cultivars Habitat Genera Shannon’s Diversity Index Hong et al., 2017 (Our Result) 44 Various location Colocasia 0.44 Chaïr et al., 2016 321 Various location Colocasia 0.11–0.21 Macharia et al., 2014 98 Uganda, Tanzania, and Kenya Colocasia 0.2476–0.4871 Cui et al.,2014 62 Various location Lilium 0.408 Zhao et al., 2014 20 China Lilium 0.3503 Žukauskienė et al., 2014 35 Kaunas Botanical Garden natural field Lilium 0.26 Duţă-Cornescu et al., 2017 10 Various location Rosa 0.45
44 Relatively high genetic diversity in our ornamental Colocasia cultivars was suspected to result from selection of various sets of phenotypic characteristics using germplasm from many regions. To obtain premium ornamental cultivars, Colocasia breeding programs utilize various germplasm from wild and existing commercial disease resistant high yield cultivars (Cho,
2004; Singh et al., 2010). Our cultivar collection, which are commonly sold and cultivated for ornamental use, consisted of three sources such as from wild plants, ornamental cultivar breeding programs, and crop producing cultivar breeding program.
On the other hand, Colocasia cultivars cultivated for tuber production have agronomic traits that are beneficial in specific region because taro yield is highly influenced by environmental effects (Singh et al., 1991), and people prefer different traits by regions (Wilson, 1990). Agronomic traits considered important in breeding are plant vigor, number of suckers, disease resistance, growing time, yield, tuber characteristic, adaptability, and eating quality
(Wilson, 1990). For example, one of the recent Hawaii’s breeding program conducted by Cho (2004) selected traits resistant to adverse environmental condition such as high salt, low rain, and pest resistance to increase plant vigor and yield. Traditional crop producing cultivars have been selected by farmers using best germplasm that one can obtain. Farmers obtain various germplasm from neighbors, outside of the village, mutation, and wild.
Four genetic diversity analyses studies done using other ornamental species were compared. Those studies used PCR-ISSR as a marker. On
45 Table 6 Shannon’s genetic diversity index and location where samples obtained were listed with cultivar name. Studies with other ornamental species show a wide range of Shannon’s diversity index. Similar indexes were observed in studies with hybrids cultivars from various regions. Duţă-
Cornescu et al., (2017) performed genetic diversity analysis with 10 hybrid
Rosa (rose) cultivars. Rose is an ornamental species that has cultivars with extremely large diversity of colors, growth, shapes, and fragrances.
Shannon’s Diversity Index value of 0.45 was obtained with ISSR data. They suggested 10 hybrid Rosa cultivars have relatively high genetic diversity based on statistical analysis including Shannon’s diversity index (Duţă-
Cornescu et al., 2017). The genus Lilium (lily) has various highly polymorphic species and cultivars (Singh, 2006). Lily has more than 200 years history of selection (Peng, 2002). Cui et al. (2014) performed genetic diversity analysis of 62 hybrid lily cultivars using ISSR. They obtained 0.4080 for Shannon’s
Diversity Index. Our Shannon’s Diversity Index is similar to the diversity indexes using other ornamental species with various phenotypic variation done with ISSR-PCR.
Our genetic diversity results can be useful for breeding new Colocasia cultivars. Having high genetic diversity in Colocasia cultivars is good news because it means there are more options for breeders. Colocasia breeders look for different combinations of characteristics and parental lines (Singh et al., 2004). For example, Iramu et al., (2009) conducted a breeding program to develop new TLB resistant cultivars in Papua New Guinea. The breeding program consisted of three cycles. Each cycle lasted 12–18 months and 46 10,000 seedlings from more than 599 cultivars were used. Each cycle aimed at different selection criteria. The first stage selected 30% of initial cultivars that do not bloom with less than 3 suckers. Second stage selected 40% of initial cultivars that are resistant to TLB. Third stage selected 33% of initial cultivars that fall into superior quality of corm. As referred earlier, lack of genetic diversity of Colocasia was observed in isolated area and TLB caused detrimental damage. Breeders had to find a way to obtain new germplasm that are resistant to TLB. Induced mutations for resistant genotypes are used effectively in places where acquisition of foreign germplasm is impossible
(Nurilmala et al., 2016). Fonoti et al. (n. d.) bred TLB resistant cultivars in
Samoa crossing high commercial value cultivars and TLB resistant cultivars from Philippines and Micronesia due to lack of genetic diversity in Samoa island.
Genetic diversity plays an important role in increasing productive of agrocrops. During the green revolution from 1930s to 1960s, genetic diversity contributed to doubling yields of rice, barley, soybeans, wheat, cotton, and sugarcane; a threefold increase in tomato yields; and a fourfold increase in yields of corn, sorghum and potato (UNEP, 1997).
Breeding programs can be efficiently conducted by having knowledge about genetic diversity and similarity index beforehand. Genetic diversity and similarity index help to predict superior crosses that can induce heterosis and greater segregation during the recombination (Cruz et al., 2001). Morales et al.
(2011) genetically characterized 11 strawberry cultivars using ISSR and RAPD.
47 They obtained genetic relationship and similarity index using UPGMA with
Jaccard’s coefficient and suggested that cultivars with low similarity would be good parental lines because it could induce greatest heterotic effect.
Low genetic variability of parental lines can cause detrimental inbreeding depression because Colocasia is known to be susceptible to inbreeding depression (Palaniswami et al., 2008). On the other hand, manifestation of hybrid vigor was reported when breeding Colocasia (Rai et al., 2006). If one desires to breed new Colocasia cultivars using cultivars from our collection, genetic diversity and similarity index can possibly be the part of information that can be used to prevent inbreeding depression and promote heterosis.
48
Conclusion
Our finding supports the recent movement of new classification of
Colocasia antiquorum to one of the Colocasia esculenta varieties. This study was not able to distinguish Colocasia antiquorum cultivars from Colocasia esculenta cultivars. Colocasia gigantea cultivars demonstrated it to be a separate group from Colocasia antiquorum cultivars and Colocasia antiquorum cultivars. However, it was unclear that Colocasia gigantea needs a new classification based on our finding since an outlier from the cluster was observed in both UPGMA dendrogram and PCO scatter graph, and PCO did not clearly form a cluster in a distinct area consisting of Colocasia gigantea cultivars.
High genetic diversity within 44 ornamental Colocasia cultivars was observed. Genetic diversity of ornamental Colocasia germplasms confirmed to well conserved. Random genetic drift is a possible reason for a high genetic diversity. Ornamental Colocasia has a potential in producing new cultivars exploiting high genetic diversity in a long term. Jaccard’s similarity index between Colocasia cultivars can be a part of the data to pick parental lines to prevent inbreeding depression and promote heterosis. DNA finger print can be used to identify cultivars. Genetic stability analysis demonstrated identical genetic characteristics among clones in each cultivar. All 44 cultivars from wild and breeders have distinct, uniform and stable genetic characteristics.
49
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58 Appendix A
DNA DNA DNA Sample concentration (µ Purity Sample concentration (µ Purity Sample concentration (µ Purity g/ml) g /ml) g /ml) 1A 68.5 1.65 25A 113.5 1.75 A43 54 1.67 1B 56 1.64 25B 105 1.76 43B 84 1.8 1C 62.5 1.8 25C 176 1.97 43C 165 1.7 1D 58 1.74 25D 64.5 1.6 43D 89 1.7 1E 143 1.64 25E 78.5 1.67 43E 200 1.64 2A 144 1.8 27A 54 1.91 44A 222.5 1.811 2B 138 1.6 27B 141 1.69 44B 211 1.75 2C 25 2.33 27C 161 1.73 44C 90 1.68 2D 37 1.81 27D 112 1.87 44D 87.5 1.75 2E 175 1.8 27E 96 1.88 44E 90.5 1.7 3A 83.5 1.67 28A 189 1.86 46A 50 1.77 3B 180 1.79 28B 136 1.68 46B 134 1.7 3C 115 2.24 28C 240 1.755 46C 185 1.74 3D 64 1.74 28D 117.5 1.76 46D 102 1.6 3E 59 1.81 28E 63.5 1.72 46E 230.5 1.6 4A 209.5 1.71 29A 59 1.91 48A 89 1.7 4B 191.6 1.58 29B 165 1.65 48B 250 1.77 4C 217 1.73 29C 147 1.87 48C 91.5 1.86 4D 130 1.6 29D 71 1.96 48D 170.5 1.06 6A 286.5 1.77 29E 145.5 1.73 48E 176.5 1.73 6B 55.5 1.73 30A 72 2.1 51E 1.68 1.88 6C 72.5 1.87 30B 185 1.77 51A 98 1.94 6D 45 1.73 30C 161 1.73 51B 45.5 1.65 6E 68 1.85 30D 246 1.89 51C 56.5 1.7 8A 111.1 1.77 30E 182 1.7 51D 146 1.91 8B 145 1.72 31A 238.5 1.81 52A 93 1.51 8C 40 1.68 31B 88.5 1.67 52B 229.5 1.74 8D 172 1.86 31C 37.5 2.1 52C 224 1.74 8E 35 1.85 31D 135.5 1.38 52D 93.5 1.89 10A 176.5 1.73 31E 406 1.61 52E 140 1.8 10B 326.5 1.8 32A 69 1.88 54A 47 1.74 10C 67 1.65 32B 97 1.82 54B 89 1.89 10D 120.5 1.92 32C 126 1.77 54C 124 1.71 10E 112 1.76 32D 81 1.87 54D 107 1.82 11A 143.5 1.69 32E 116.5 1.65 54E 125 1.76 11B 153 1.74 34A 133.5 1.92 55A 221.5 1.8 11C 145 1.76 34B 110 1.96 55B 284 1.77 11D 147 1.76 34C 110 1.6 55C 287.5 1.7 11E 53 1.88 34D 153 1.91 55D 128 1.77 12A 68.5 1.73 34E 21 1.81 55E 23.7 1.83 12B 36.65 1.68 35A 50 1.75 57A 103 1.76 12C 79 1.78 35B 54 1.8 57B 105 1.7 Appendix12D 198 A1. DNA1.78 isolation35C results89 of each1.7 clone sample57C with143.5 purity1.74 and DNA12E concentration22 1.13 35D 53.5 1.8 57D 47 1.68 15A 123.5 1.6 35E 160 1.82 57E 68.5 1.61 15B 212 1.84 36A 111 1.8 58A 46 1.86 15C 48 2.33 36B 145 1.76 58B 111 1.56 15D 53 1.69 36C 25 2.12 58C 116.5 1.91 15E 250 1.76 36D 59 1.71 58D 75 1.81 16A 51 1.73 36E 63 1.84 58E 55.5 1.7 16B 42 1.82 37A 83.5 1.8 60A 44 1.6 16C 84 1.67 37B 47 1.88 60E 101 1.72 16D 69 1.87 37C 28.5 1.74 62A 212 1.66 16E 54.8 1.75 37D 162 1.81 62B 205 1.61 18A 115 1.8 37E 87 1.89 62C 123 1.66 18B 161 1.77 38A 168 1.6 62D 69 1.82 18C 61 1.87 38B 93 1.77 62E 148 1.72 18D 142 1.7 38C 36 1.64 63A 121.5 1.77 18E 120 1.6 38D 38.5 2.7 63B 186 1.9 19A 54 1.82 38E 68 1.8 63C 190 1.66 19B 139.5 1.66 39A 152.5 1.68 63D 92.5 1.7 19C 189 1.67 39B 195 1.7 63E 56 1.8 19D 162.5 1.71 39C 232 1.74 19E 190.5 1.22 39D 120 1.8 21A 306.5 1.33 39E 102 1.7 21B 53 1.7 41A 238.5 1.8 21C 164 1.9 41B 122.5 1.65 21D 248.5 1.84 41C 83 1.7 21E 100 1.75 B42 50 1.8 22A 48 1.74 42C 35.6 59 1.6 22B 174.5 1.76 42D 206 1.75 22C 320 1.78 42E 127 1.88 22D 140 1.55 22E 176 1.8 23A 65.5 1.67 23B 87 1.51 23C 73 1.75 23D 128 1.85 23E 112 1.75 22A 146 1.81 22B 174.5 1.76 22C 320 1.78 22D 156 1.85 22E 258 1.97
Appendix A2. DNA isolation results of each clone sample with purity and DNA concentration
60 Appendix B
Appendix B1. Image of 1.5% agarose gel. Samples were amplified using primer S1. BioNexus Hi-Lo marker was used as a marker on first lane and seven samples were loaded next to the marker.
Appendix B2. Image of 1.5% agarose gel. Samples were amplified using primer 814 and S1 primer. BioNexus Hi-Lo marker was used as a marker on first lane and seven samples were loaded next to the marker.
61
Appendix B3. Image of 1.5% agarose gel. Samples were amplified using primer 814. BioNexus Hi-Lo marker was used as a marker on first lane and seven samples were loaded next to the marker.
Appendix B4. Image of 1.5% agarose gel. Samples were amplified using primer S2. BioNexus Hi-Lo marker was used as a marker on first lane and seven samples were loaded next to the marker. 62
Appendix B5. Image of 1.5% agarose gel. Samples were amplified using primer S3. BioNexus Hi-Lo marker was used as a marker on first lane and seven samples were loaded next to the marker.
63 Appendix C
1 2 3 4 6 8 10 11 12 1 1 2 0.593 1 3 0.304 0.314 1 4 0.297 0.305 0.278 1 6 0.263 0.255 0.225 0.29 1 8 0.204 0.22 0.2 0.189 0.244 1 10 0.227 0.231 0.272 0.253 0.227 0.202 1 11 0.27 0.237 0.247 0.22 0.172 0.211 0.196 1 12 0.303 0.271 0.215 0.216 0.242 0.261 0.217 0.237 1 15 0.317 0.26 0.315 0.28 0.312 0.237 0.234 0.253 0.313 16 0.272 0.228 0.264 0.212 0.212 0.202 0.226 0.232 0.192 18 0.233 0.212 0.247 0.184 0.303 0.253 0.222 0.204 0.224 19 0.176 0.119 0.143 0.186 0.147 0.159 0.157 0.194 0.189 21 0.152 0.118 0.193 0.208 0.196 0.272 0.169 0.167 0.213 22 0.188 0.178 0.136 0.219 0.208 0.198 0.149 0.181 0.212 23 0.194 0.14 0.119 0.159 0.135 0.11 0.143 0.143 0.184 25 0.184 0.15 0.128 0.194 0.181 0.156 0.154 0.177 0.211 27 0.206 0.184 0.202 0.228 0.242 0.144 0.179 0.188 0.22 28 0.168 0.144 0.159 0.153 0.202 0.176 0.202 0.16 0.233 29 0.176 0.198 0.159 0.134 0.152 0.196 0.194 0.18 0.198 30 0.219 0.21 0.217 0.171 0.258 0.209 0.207 0.308 0.175 31 0.138 0.125 0.174 0.133 0.153 0.14 0.163 0.198 0.182 32 0.198 0.188 0.194 0.13 0.149 0.172 0.183 0.229 0.212 34 0.211 0.168 0.196 0.155 0.163 0.163 0.162 0.183 0.168 35 0.181 0.17 0.149 0.155 0.119 0.093 0.081 0.186 0.194 36 0.204 0.206 0.107 0.096 0.123 0.131 0.13 0.152 0.16 37 0.231 0.222 0.167 0.206 0.147 0.158 0.156 0.214 0.21 38 0.227 0.185 0.144 0.121 0.107 0.194 0.157 0.223 0.208 39 0.243 0.198 0.179 0.16 0.245 0.196 0.168 0.227 0.222 41 0.159 0.136 0.149 0.144 0.153 0.152 0.151 0.237 0.17 42 0.263 0.216 0.16 0.165 0.163 0.202 0.125 0.234 0.269 43 0.261 0.22 0.216 0.216 0.229 0.173 0.171 0.337 0.198 44 0.192 0.136 0.213 0.112 0.177 0.205 0.163 0.264 0.219 46 0.252 0.233 0.229 0.152 0.194 0.208 0.147 0.33 0.245 48 0.239 0.176 0.167 0.16 0.157 0.185 0.183 0.265 0.189 51 0.212 0.167 0.209 0.163 0.186 0.301 0.185 0.258 0.202 52 0.258 0.173 0.233 0.182 0.22 0.224 0.193 0.228 0.264 54 0.24 0.191 0.256 0.188 0.213 0.232 0.214 0.25 0.217 55 0.151 0.15 0.14 0.136 0.181 0.195 0.154 0.177 0.173 57 0.143 0.131 0.231 0.183 0.182 0.209 0.194 0.266 0.235 58 0.219 0.142 0.179 0.16 0.125 0.196 0.181 0.178 0.175 60 0.198 0.137 0.269 0.17 0.195 0.228 0.21 0.205 0.241 62 0.219 0.175 0.191 0.128 0.17 0.209 0.144 0.24 0.163 63 0.173 0.15 0.152 0.147 0.22 0.106 0.129 0.119 0.198 Appendix C1. Similarity index of pairs of cultivars using Jaccard’s coefficient.
64 15 16 18 19 21 22 23 25 27 28 1 2 3 4 6 8 10 11 12 15 1 16 0.542 1 18 0.425 0.356 1 19 0.206 0.237 0.233 1 21 0.341 0.289 0.302 0.265 1 22 0.204 0.267 0.265 0.073 0.242 1 23 0.189 0.228 0.176 0.119 0.152 0.2 1 25 0.293 0.286 0.284 0.218 0.305 0.227 0.322 1 27 0.34 0.319 0.277 0.202 0.213 0.2 0.196 0.369 1 28 0.223 0.215 0.239 0.159 0.241 0.292 0.156 0.284 0.442 1 29 0.212 0.216 0.202 0.17 0.276 0.212 0.177 0.235 0.255 0.271 30 0.238 0.255 0.24 0.155 0.165 0.238 0.163 0.253 0.287 0.236 31 0.152 0.178 0.139 0.113 0.172 0.186 0.158 0.146 0.194 0.247 32 0.253 0.271 0.216 0.156 0.167 0.216 0.165 0.284 0.319 0.282 34 0.217 0.245 0.206 0.149 0.147 0.24 0.147 0.269 0.276 0.267 35 0.21 0.214 0.211 0.161 0.135 0.222 0.194 0.294 0.272 0.233 36 0.21 0.225 0.142 0.14 0.139 0.176 0.15 0.196 0.206 0.258 37 0.289 0.242 0.253 0.191 0.256 0.214 0.235 0.267 0.247 0.222 38 0.222 0.215 0.235 0.167 0.212 0.189 0.123 0.198 0.174 0.158 39 0.225 0.183 0.178 0.12 0.165 0.214 0.163 0.175 0.21 0.264 41 0.198 0.202 0.186 0.137 0.185 0.21 0.158 0.222 0.206 0.165 42 0.371 0.29 0.261 0.16 0.222 0.208 0.192 0.291 0.229 0.189 43 0.412 0.324 0.248 0.181 0.25 0.191 0.099 0.167 0.255 0.22 44 0.247 0.227 0.223 0.149 0.211 0.186 0.158 0.209 0.206 0.205 46 0.297 0.217 0.168 0.157 0.202 0.202 0.144 0.212 0.27 0.247 48 0.22 0.253 0.141 0.101 0.207 0.194 0.176 0.19 0.151 0.2 51 0.23 0.198 0.245 0.134 0.247 0.194 0.155 0.179 0.167 0.241 52 0.293 0.272 0.284 0.14 0.23 0.253 0.186 0.227 0.278 0.268 54 0.261 0.239 0.294 0.108 0.182 0.247 0.179 0.207 0.258 0.278 55 0.24 0.219 0.215 0.14 0.189 0.19 0.127 0.187 0.264 0.195 57 0.25 0.218 0.214 0.191 0.256 0.19 0.12 0.188 0.287 0.236 58 0.202 0.23 0.214 0.167 0.177 0.157 0.131 0.239 0.198 0.17 60 0.231 0.17 0.218 0.151 0.205 0.155 0.187 0.161 0.187 0.244 62 0.238 0.183 0.19 0.143 0.165 0.179 0.186 0.175 0.163 0.25 63 0.202 0.182 0.177 0.128 0.138 0.202 0.162 0.227 0.173 0.195 Appendix C2. Similarity index of pairs of cultivars using Jaccard’s coefficient.
65 29 30 31 32 34 35 36 37 38 39 41 42 1 2 3 4 6 8 10 11 12 15 16 18 19 21 22 23 25 27 28 29 1 30 0.282 1 31 0.219 0.172 1 32 0.26 0.337 0.162 1 34 0.236 0.265 0.2 0.618 1 35 0.185 0.275 0.231 0.369 0.5 1 36 0.264 0.151 0.216 0.21 0.248 0.269 1 37 0.234 0.224 0.184 0.202 0.204 0.333 0.258 1 38 0.287 0.233 0.206 0.273 0.26 0.255 0.277 0.309 1 39 0.148 0.188 0.275 0.214 0.159 0.137 0.258 0.143 0.187 1 41 0.219 0.234 0.179 0.25 0.29 0.244 0.18 0.247 0.268 0.137 1 42 0.217 0.136 0.153 0.221 0.235 0.256 0.293 0.272 0.265 0.182 0.202 1 43 0.252 0.257 0.208 0.236 0.236 0.231 0.229 0.234 0.241 0.179 0.243 0.372 44 0.231 0.261 0.12 0.278 0.29 0.204 0.146 0.184 0.218 0.196 0.258 0.242 46 0.29 0.212 0.196 0.238 0.215 0.208 0.164 0.248 0.267 0.2 0.208 0.268 48 0.192 0.165 0.186 0.18 0.17 0.186 0.187 0.247 0.228 0.205 0.133 0.226 51 0.204 0.18 0.188 0.232 0.271 0.175 0.143 0.192 0.19 0.242 0.175 0.25 52 0.178 0.175 0.196 0.256 0.326 0.222 0.172 0.213 0.222 0.239 0.222 0.321 54 0.268 0.306 0.202 0.17 0.198 0.202 0.153 0.181 0.18 0.194 0.189 0.213 55 0.189 0.213 0.17 0.189 0.192 0.146 0.149 0.152 0.186 0.213 0.146 0.181 57 0.211 0.237 0.16 0.19 0.204 0.208 0.184 0.277 0.233 0.111 0.221 0.258 58 0.168 0.154 0.234 0.227 0.228 0.149 0.162 0.176 0.296 0.25 0.196 0.258 60 0.214 0.202 0.184 0.233 0.261 0.198 0.124 0.138 0.226 0.189 0.184 0.224 62 0.179 0.224 0.16 0.178 0.204 0.172 0.196 0.143 0.21 0.237 0.16 0.219 63 0.145 0.152 0.134 0.141 0.168 0.17 0.184 0.175 0.163 0.175 0.183 0.247 Appendix C3. Similarity index of pairs of cultivars using Jaccard’s coefficient.
66 43 44 46 48 51 52 54 55 57 58 60 62 63 1 2 3 4 6 8 10 11 12 15 16 18 19 21 22 23 25 27 28 29 30 31 32 34 35 36 37 38 39 41 42 43 1 44 0.267 1 46 0.38 0.232 1 48 0.204 0.159 0.273 1 51 0.25 0.267 0.265 0.3 1 52 0.248 0.279 0.29 0.25 0.455 1 54 0.23 0.216 0.245 0.228 0.346 0.438 1 55 0.248 0.222 0.263 0.149 0.204 0.333 0.235 1 57 0.282 0.221 0.299 0.191 0.216 0.253 0.194 0.213 1 58 0.222 0.221 0.248 0.191 0.216 0.163 0.144 0.163 0.2 1 60 0.214 0.212 0.284 0.208 0.25 0.278 0.195 0.202 0.259 0.274 1 62 0.189 0.196 0.286 0.205 0.269 0.239 0.276 0.14 0.165 0.212 0.338 1 63 0.167 0.158 0.2 0.235 0.155 0.227 0.18 0.137 0.129 0.129 0.174 0.326 1 Appendix C4. Similarity index of pairs of cultivars using Jaccard’s coefficient.
67 Axis 1 Axis 2 Eigenvalues 114.503 87.907 Percentage 6.945 5.332 Cum. Percentage 6.945 12.277
PCO case scores Axis 1 Axis 2 Colocasia esculanta 'Big Dipper' 3.256 0.359 Colocasia esculanta 'Bikini-Tini' 3.298 0.714 Colocasia antiquorum 'Black Beauty ' 2.483 -0.257 Colocasia esculanta 'Black Coral' 3.304 1.734 Colocasia esculanta 'Black Magic' 2.752 0.579 Colocasia esculanta 'Black Ripple' 1.541 -1.352 Colocasia esculanta 'Black Runner' 1.958 -0.033 Colocasia esculanta 'Black Sapphire Gecko' 0.888 -1.373 Colocasia esculanta 'Blue Hawaii' 1.564 -0.071 Colocasia esculanta 'Coal Miner' 1.785 2.275 Colocasia 'Coffee Cups' 0.607 2.622 Colocasia esculanta 'Dragon Heart Gigante' 1.008 1.831 Colocasia esculanta 'Electric Blue Gecko' 0.376 1.495 Colocasia esculanta 'Elepaio' 0.338 1.028 Colocasia gigantea 'Fierce Gigante' -0.485 0.508 Colocasia 'Fontenseii' -0.314 1.229 Colocasia esculanta 'Hawaiian Punch' -1.395 2.407 Colocasia antiquorum 'Illustris' -0.94 2.322 Colocasia esculanta 'Imperial Gigante' -1.229 -0.032 Colocasia esculanta 'Jack¡¯s Giant' -1.806 0.065 Colocasia esculanta 'Kona Coffee' -0.687 0.579 Colocasia gigantea 'Laosy Giant' -1.029 -1.454 Colocasia esculanta 'Lemonade' -2.828 0.669 Colocasia esculanta 'Lime Aide' -3.388 0.33 Colocasia esculanta 'Madiera' -3.121 1.467 Colocasia 'Mammoth' -2.001 0.341 Colocasia esculanta 'Mau Gold' -0.991 1.967 Colocasia esculanta 'Maui Magic' -2.072 -0.753 Colocasia esculanta 'Maximus Gigante' 0.672 -2.018 Colocasia esculanta 'Midori Sour' -1.844 0.182 Colocasia esculanta 'Mojito' -0.445 0.301 Colocasia esculanta 'Morning Dew' 0.158 0.112 Colocasia esculanta 'Nancy¡¯S Revenge' -0.955 -0.887 Colocasia esculanta 'Painted Black Gecho' -0.19 -2.024 Colocasia esculanta 'Pink China' 0.229 -1.444 Colocasia esculanta 'Red-Eyed Gecko' 0.177 -2.873 Colocasia esculanta 'Rhubarb' -0.043 -1.511 Colocasia esculanta 'Ruffles' 0.59 -1.261 Colocasia esculanta 'Sangrina' -0.167 -0.766 Colocasia esculanta 'Tea Cup' -0.542 -0.038 Colocasia gigantea 'Thiland Giant' -0.599 -1.353 Colocasia esculanta 'Tropical Storm' -0.036 -2.061 Colocasia esculanta 'Violet Stem' 0.081 -2.893 Colocasia esculanta 'White Lava' 0.045 -0.659 Appendix C5. PC1 and PC2 scores of each cultivar from PCO
68 Appendix D
Appendix D.1. Images of two 1.5% agarose gel loaded with PCR product amplified with HB11 A- Original gel consists of BioNexus Hi-Lo marker at the left and five clones of accession number 35. A31 and E31 showed different banding patterns from other clones. B- Repeated gel consists of BioNexus Hi- Lo marker at the left and A31 and E31 amplified with new DNA.
Appendix D.2. Images of two 1.5% agarose gel loaded with PCR product amplified with primer 17898A. A- Original gel with BioNexus Hi-Lo marker at the left and two different 60 clones showed different banding patterns. B- Repeated gel consists of sample A60 and E60 amplified with new DNA.
69
Appendix D.3. Images of two 1.5% agarose gel loaded with PCR product amplified with primer 814. A- Original gel consists of BioNexus Hi-Lo marker at the left and five clones of accession number 28. B28 showed a different banding pattern from other clones. B- Repeated gel with BioNexus Hi-Lo marker at the left and B28 amplified with new DNA.
Appendix D4. Images of two 1.5% agarose gel loaded with PCR product amplified with primer 814. A- Original gel loaded with BioNexus Hi-Lo marker at the left and three clones of accession number 51. A51 showed a different banding pattern from two other clones. B- Repeated gel loaded with BioNexus Hi-Lo marker at the left and A51 amplified with new DNA. 70
Appendix D.6. Images of two 1.5% agarose gel loaded with PCR product amplified with primer 17898B. A- Original gel loaded with BioNexus Hi-Lo marker at the left and four clones of accession number 24. C28 showed a different banding pattern from three other clones. B- Repeated gel loaded with BioNexus Hi-Lo marker at the left and C28 amplified original DNA.
71
Appendix D.7. Images of three 1.5% agarose gel loaded with PCR product amplified with primer S3. A- Original gel with BioNexus Hi-Lo marker at the left and five accession number 25 clones. Each clone showed a slightly different banding pattern. B- Repeated gel consists of BioNexus Hi-Lo marker at the left and four clones of accession number 25 amplified with new DNA. C- Repeated gel consists of BioNexus Hi-Lo marker at the left and E25 amplified with new DNA.
72 Appendix E
Appendix E. POPGEN32 source code based on PCR-ISSR binary data of 44 Colocasia cultivars
/*Diploid ISSR data for all Colocasia samples*/ Number of populations = 44 Number of loci = 266 Locus name: 814-2665 814-2480 814-2110 814-2050 814-1965 814-1855 814-1715 814-1650 814-1600 814-1500 814-1440 814-1380 814-1315 814-1230 814-1160 814-1080 814-950 814-900 814-840 814-755 814-690 814-655 814-545 814-500 814-450 814-400 814-360 S1-3975 S1-3678 S1-3350 S1-3110 S1-2900 S1-2750 S1-2665 S1-2570 S1-2480 S1-2110 S1-1965 S1-1910 S1-1855 S1-1800 S1-1715 S1-1650 S1-1600 S1-1550 S1-1500 S1-1440 S1-1380 S1-1315 S1-1230 S1-1160 S1-1140 S1-1080 S1-950 S1-900 S1-840 S1-755 S1-690 S1-655 S1-545 S1-500 S2-1855 S2-1800 S2-1715 S2-1650 S2-1600 S2-1550 S2-1500 S2-1440 S2-1380 S2-1315 S2-1230 S2-1160 S2-1140 S2-1080 S2-950 S2-900 S2-840 S2-755 S2-690 S2-655 S2-545 S2-500 S2-400 S2-360 s3-2665 s3-2220 s3-2110 s3-1600 s3-1550 s3-1500 s3-1440 s3-1380 s3-1315 s3-1230 s3-1160 s3-1080 s3-1030 s3-1000 s3-950 s3-900 s3-840 s3-800 s3-755 s3-690 s3-655 s3-620 s3-545 s3-500 s3-450 s3-400 s3-360 s3-260 s3-240 844-2930 844-2665 844-2480 844-2370 844-2310 844-2110 844-1965 844-1910 844-1855 844-1800 844-1715 844-1650 844-1600 844-1550 844-1500 844-1440 844-1380 844-1315 844-1230 844-1160 844-1080 844-1030 844-1000 844-985 844-950 844-900 844-840 844-800 844-755 844-690 844-655 844-620 844-545 844-500 844-400 844-360 17b-3070 17b-2750 17b-2665 17b-2570 17b-2480 17b-2370 17b-2310 17b-2220 17b-2110 17b-1965 17b-1910 17b-1855 17b-1800 17b-1715 17b-1650 17b-1600 17b-1550 17b-1500 17b-1440 17b-1420 17b-1380 17b-1315 17b-1270 17b-1230 17b-1160 17b-1080 17b-1030 17b-1000 17b-985 17b-950 17b-900 17b-840 17b-800 73 17b-755 17b-690 17b-655 17b-620 17b-545 17b-450 17b-400 17b-360 17b-260 17a-2750 17a-2370 17a-2110 17a-2050 17a-2000 17a-1965 17a-1910 17a-1855 17a-1800 17a-1750 17a-1715 17a-1650 17a-1550 17a-1500 17a-1440 17a-1420 17a-1380 17a-1315 17a-1270 17a-1230 17a-1160 17a-1080 17a-1030 17a-1000 17a-985 17a-950 17a-900 17a-840 17a-800 17a-755 17a-690 17a-655 17a-620 17a-545 17a-500 17a-450 HB11-3110 HB11-2665 HB11-2370 HB11-2310 HB11- 2220 HB11-2110 HB11-1965 HB11-1910 HB11-1855 HB11- 1800 HB11-1750 HB11-1715 HB11-1650 HB11-1600 HB11- 1550 HB11-1500 HB11-1440 HB11-1420 HB11-1380 HB11- 1315 HB11-1270 HB11-1230 HB11-1160 HB11-1080 HB11- 1030 HB11-1000 HB11-985 HB11-950 HB11-900 HB11-840 HB11-800 HB11-755 HB11-690 HB11-655 HB11-620 HB11-545 HB11-500 HB11-450
name = 1 01101010001000100001001000000000000001000010010000110101 00100000000101001010011000000000000101010001010001001000000001 00110010000000001001100011001000000000000011000000010010100000 10010011000000000000101000010000010010101010100100000000010010 010100011010010100000001
name = 2 01101010001000100001000000000000000001000010010000110101 00100000000100001010011000000000000001010000010001001000000001 00110010000000001001100011001000000000001001001100110010010000 10010010000000000000001000100000100100110000000100000000100000 100000011000101100000001
name = 4 01101010001000000101000000000000000001000000000001001101 10000000000100101010101000000000000001010001000101001000000000 01001001000001001000100010000000000000001001000010000011000000 10100100000000000010000010100101000000001000100000000010000000 100100010000000000001000
74
name =6 01101010001001100001000000000000000000000000000001101110 00100000000000010110001000000000101001110000100101000000000000 00010010000010011000100010001000000000000000000011000100110001 00100100000000000100000010000010011000010100100100000001001000 100000110010110110100001
name = 7 00001000001001000001001000000000000001000000001001010000 011000000000000001110110000000000001001100101001010100100001100 01000100000101011000000100100000000000010010000010000101000001 00101000000000000010000001000010110000100000000000100001000010 01000010010010000000010
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name = 44 81 00000000000010000101001000000000000000000100000001101010 10000000000010001010100111000000000000000000001001001000000010 01000001100000000000000000000000000000010000001000000000100000 10010100000000000000100000100001011010001010100000000010000000 101000010100010001000001
name = 45 00000000000010000101001000000000000000100001000000100101 01100000100101010001111011010000000000000000001001001000000010 00001001000000110010000001001001101000010000000100000000101000 10100000110000000000100000100001010010001000010000000100000010 001000010100001001001001
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82 Appendix F
Appendix F. The chart of band scoring based on presence or absence of the 266 loci in 44 ornamental Colocasia cultivars. The top row is accession number of cultivars and the first left column is primer-loci.
1 2 3 4 6 8 10 1 12 15 16 18 19 21 22 23 25 27 28 29 1 814- 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 2665 814- 1 1 1 1 0 1 0 0 1 1 1 0 0 0 0 0 0 0 0 0 2480 814- 1 1 1 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 2110 814- 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 2050 814- 1 1 1 1 1 0 1 0 1 1 1 1 1 0 0 1 0 1 0 0 1965 814- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1855 814- 1 1 1 1 0 0 1 1 0 1 0 0 0 1 0 0 0 0 0 0 1715 814- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1650 814- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1600 814- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1500 814- 1 1 1 1 1 0 0 0 0 1 0 1 0 0 1 0 0 0 0 0 1440 814- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1380 814- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 1 1315 814- 0 0 0 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1230 814- 1 1 0 1 0 1 0 1 0 1 1 1 0 0 1 0 0 1 0 0 1160 814- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 1 1080 814-950 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 814-900 0 0 1 0 0 0 0 0 0 0 1 1 0 0 1 1 0 1 0 0 814-840 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 814-755 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 1 1 1 1 1 814-690 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 814-655 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 1 1 814-545 1 0 0 0 1 0 0 0 1 1 0 0 0 0 0 1 1 1 1 1 814-500 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 814-450 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 814-400 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 814-360 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 S1- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 3975 S1- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3678 S1- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 3350 S1-3110 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 83 S1- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 2900 S1- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2750 S1- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2665 S1- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2570 S1- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 1 2480 S1-2110 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 1 1 S1- 1 1 1 0 1 1 1 0 1 1 1 1 1 0 1 0 0 1 1 0 1965 S1- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1910 S1- 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1855 S1- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1800 S1- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 1715 S1- 1 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 1650 S1- 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 1 1 1600 S1- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1550 S1- 1 1 0 0 0 0 1 0 0 0 1 0 1 0 0 0 0 0 0 1 1500 S1- 0 0 0 0 1 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1440 S1- 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 1 0 1380 S1- 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 1 1315 S1- 0 0 1 1 1 1 1 0 0 1 0 0 0 1 1 0 0 0 0 1 1230 S1-1160 1 1 0 1 0 0 0 0 1 0 1 0 1 0 0 0 0 1 1 0 S1-1140 1 1 0 0 1 1 0 0 0 0 0 1 0 1 0 0 0 0 0 1 S1- 0 0 1 1 0 0 1 1 0 1 1 0 1 0 0 0 0 0 0 0 1080 S1-950 1 1 1 1 0 0 0 1 1 1 0 0 0 1 0 0 0 0 0 0 S1-900 0 0 0 1 0 0 0 0 1 0 0 0 1 1 0 0 0 0 0 0 S1-840 1 1 1 0 0 0 1 1 0 1 1 0 0 0 0 0 0 0 0 0 S1-755 0 0 1 0 0 0 0 1 1 1 0 1 1 1 0 0 0 0 0 0 S1-690 0 0 0 0 1 1 0 0 0 1 1 1 1 0 0 0 0 0 0 0 S1-655 1 1 0 1 1 1 0 1 0 1 1 1 1 1 0 0 0 0 0 1 S1-545 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 S1-500 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 S2- 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 1 1 1 0 1855 S2- 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 0 0 1 1800 S2- 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1715 S2- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1650 S2- 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1600 S2- 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 1 0 1 1550 S2- 1 1 1 0 0 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 84 1500 S2- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1440 S2- 1 0 0 0 0 0 0 0 1 1 1 0 0 1 1 0 0 0 1 1 1380 S2- 0 0 1 0 0 0 0 1 0 0 0 1 1 1 0 0 1 1 0 1 1315 S2- 0 0 0 1 0 0 0 1 0 1 1 0 0 0 1 1 1 1 0 0 1230 S2-1160 1 1 1 0 0 1 1 1 1 0 1 0 0 1 1 1 0 0 1 1 S2-1140 0 0 0 1 1 0 0 0 1 1 0 0 0 1 0 0 1 1 0 0 S2- 1 1 1 1 1 0 1 0 1 1 1 1 1 1 0 0 1 1 1 1 1080 S2-950 0 0 0 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0 1 0 S2-900 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 1 S2-840 1 1 0 0 1 0 1 0 1 1 0 1 0 1 1 0 1 0 1 1 S2-755 1 1 1 1 1 0 0 1 0 1 1 1 0 0 0 1 1 1 0 0 S2-690 0 0 0 0 0 1 0 0 1 1 0 0 1 1 0 0 0 1 0 1 S2-655 0 0 0 0 0 0 1 0 0 1 1 1 0 0 1 1 1 1 1 0 S2-545 0 0 0 0 0 1 0 0 0 0 0 1 1 1 0 0 0 0 0 1 S2-500 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 S2-400 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 S2-360 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 s3-2665 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 s3-2220 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 s3-2110 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 s3-1600 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 s3-1550 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 s3-1500 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 s3-1440 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 s3-1380 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 s3-1315 1 1 1 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 s3-1230 0 0 0 1 1 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 s3-1160 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 s3-1080 0 0 0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 s3-1030 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 s3-1000 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 s3-950 1 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 s3-900 0 0 0 1 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 s3-840 1 1 0 0 0 1 0 1 1 0 0 0 1 0 0 1 0 0 0 0 s3-800 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 s3-755 0 0 1 1 1 1 1 0 0 1 1 1 0 1 1 0 1 1 1 1 s3-690 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 s3-655 1 1 1 1 1 1 0 1 0 0 0 0 0 0 1 0 0 0 0 0 s3-620 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 1 0 0 0 s3-545 0 0 0 0 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0
85 s3-500 1 1 1 0 0 1 1 1 0 1 0 1 0 0 0 1 1 0 0 0 s3-450 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 1 1 1 1 s3-400 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 s3-360 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 s3-260 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 s3-240 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 844- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2930 844- 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2665 844- 0 0 0 0 1 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 2480 844- 1 1 0 0 0 0 1 1 0 0 1 0 0 0 1 1 0 0 0 1 2370 844- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2310 844- 0 0 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 2110 844- 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1965 844- 1 1 0 1 0 0 0 1 1 0 0 0 0 0 0 1 0 1 0 0 1910 844- 0 0 1 0 0 1 1 0 0 0 0 1 1 0 0 0 0 0 1 0 1855 844- 0 0 0 0 0 0 0 0 0 1 1 1 0 1 1 0 0 0 0 0 1800 844- 1 1 0 1 1 0 0 0 1 0 0 0 1 0 1 1 1 1 1 0 1715 844- 0 0 1 0 0 1 1 1 0 0 1 0 0 1 0 0 0 0 0 1 1650 844- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1600 844- 0 0 0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 1550 844- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1500 844- 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1440 844- 0 0 0 1 1 0 1 0 0 1 1 1 0 0 1 1 0 1 0 0 1380 844- 0 0 1 0 0 0 0 1 1 1 1 1 0 1 1 0 1 0 0 0 1315 844- 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 1 0 0 1 0 1230 844- 0 0 0 1 0 0 0 1 0 0 0 0 1 0 1 0 1 1 1 0 1160 844- 1 1 1 1 1 0 0 0 0 1 1 1 0 0 0 1 0 1 0 0 1080 844- 0 0 0 0 1 0 1 1 1 0 0 0 0 0 0 0 0 0 0 1 1030 844- 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1000 844-985 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 844-950 1 1 1 1 0 0 0 0 0 1 1 0 0 1 1 0 0 1 0 1 844-900 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 0 844-840 0 0 0 0 0 0 0 1 0 0 1 0 0 0 1 1 1 0 0 0 844-800 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 844-755 1 1 1 1 1 0 1 0 1 1 1 1 1 1 0 1 1 1 1 0 844-690 1 1 0 0 0 1 0 1 0 0 0 1 0 0 0 0 1 0 0 1 844-655 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
86 844-620 0 0 0 0 1 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 844-545 1 1 0 1 0 1 0 1 1 1 1 0 1 1 1 0 1 1 1 1 844-500 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 844-400 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 844-360 0 0 0 0 0 1 0 0 1 1 1 0 1 1 1 1 1 0 0 0 17b- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3070 17b- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2750 17b- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2665 17b- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2570 17b- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2480 17b- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2370 17b- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2310 17b- 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2220 17b- 0 1 1 0 1 1 0 1 1 1 1 0 0 0 0 0 0 1 0 1 2110 17b- 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 1 0 0 0 1965 17b- 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1910 17b- 1 1 1 0 1 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1855 17b- 0 0 0 0 0 0 0 1 0 1 1 1 0 1 1 0 0 1 1 1 1800 17b- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1715 17b- 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 1650 17b- 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1600 17b- 0 0 1 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1550 17b- 0 0 0 1 1 0 0 1 0 0 0 0 0 0 1 0 0 0 1 0 1500 17b- 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1440 17b- 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1420 17b- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 1 1380 17b- 0 0 0 1 0 1 1 1 1 0 0 1 0 1 1 1 1 0 0 1 1315 17b- 1 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1270 17b- 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 1 1 1 0 1230 17b- 1 0 0 1 1 1 0 0 0 1 0 1 0 1 0 0 0 0 0 0 1160 17b- 0 1 0 1 0 0 0 0 0 0 0 1 0 0 1 0 0 0 1 1 1080 17b- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1030 17b- 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 1000 17b-985 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 17b-950 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 17b-900 1 1 1 0 1 1 1 1 1 1 1 1 0 0 0 0 0 1 1 1
87 17b-840 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 17b-800 0 0 1 1 0 0 0 1 1 0 0 0 0 0 1 0 0 0 0 0 17b-755 1 1 0 0 1 1 0 1 0 0 0 0 0 0 0 0 0 1 0 1 17b-690 0 0 0 0 0 1 0 1 0 1 1 1 0 0 0 1 1 1 0 0 17b-655 0 0 1 1 1 1 1 0 1 0 0 1 0 0 1 0 0 1 1 1 17b-620 1 1 0 0 0 0 0 1 1 1 1 0 0 0 1 1 1 0 0 0 17b-545 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 1 0 17b-450 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 17b-400 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 1 17b-360 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 17b-260 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 17a- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2750 17a- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2370 17a- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2110 17a- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2050 17a- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2000 17a- 0 0 0 1 0 0 1 0 1 0 0 0 0 0 0 1 0 0 0 0 1965 17a- 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1910 17a- 0 0 0 0 1 0 0 1 0 1 1 0 0 1 0 0 0 0 0 1 1855 17a- 1 0 0 0 0 0 0 1 1 0 0 1 1 0 0 0 1 1 1 0 1800 17a- 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1750 17a- 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1715 17a- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1650 17a- 0 0 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1550 17a- 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 1 1 0 1 1500 17a- 0 1 1 0 1 0 0 1 1 1 1 1 0 0 1 0 0 0 1 0 1440 17a- 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1420 17a- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1380 17a- 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1315 17a- 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 1270 17a- 0 0 1 0 1 0 0 0 0 1 1 1 1 1 0 1 1 1 0 1 1230 17a- 0 1 0 0 0 1 1 0 1 0 0 0 0 1 1 0 1 1 1 1 1160 17a- 1 0 0 1 1 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0 1080 17a- 0 0 0 1 1 1 0 1 1 1 1 1 0 1 1 0 1 1 1 0 1030 17a- 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1000 17a-985 1 0 0 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 0 1 17a-950 0 0 0 0 0 1 0 0 0 1 1 1 1 1 0 0 0 0 0 0
88 17a-900 1 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 17a-840 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 17a-800 1 0 1 0 0 0 1 1 0 1 1 1 1 1 0 1 1 1 1 1 17a-755 0 0 0 1 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 17a-690 1 0 0 0 0 1 0 1 1 1 1 1 1 0 0 0 0 0 0 0 17a-655 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 17a-620 1 0 1 1 0 0 0 0 0 1 1 1 0 1 1 1 1 1 1 1 17a-545 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 1 0 0 0 1 17a-500 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 17a-450 1 1 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 HB11- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3110 HB11- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2665 HB11- 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 2370 HB11- 0 0 0 0 1 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 2310 HB11- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2220 HB11- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 2110 HB11- 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1965 HB11- 0 0 0 1 0 1 0 0 0 0 0 0 1 1 1 1 1 0 0 0 1910 HB11- 0 1 0 0 1 0 1 0 0 1 1 1 0 0 0 0 0 1 0 0 1855 HB11- 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1800 HB11- 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1750 HB11- 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 1 1 0 1 1 1715 HB11- 1 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 1650 HB11- 0 0 0 0 1 0 0 0 1 1 0 1 0 0 0 1 1 1 0 0 1600 HB11- 0 1 1 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1550 HB11- 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 1500 HB11- 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 1 1 0 1440 HB11- 1 0 1 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 1420 HB11- 0 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0 0 1 1380 HB11- 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1315 HB11- 0 0 0 1 0 0 0 0 0 0 1 0 1 0 0 1 1 0 0 1 1270 HB11- 1 1 1 1 1 1 1 1 1 1 0 1 0 1 1 1 0 0 1 0 1230 HB11- 1 1 0 0 0 0 1 0 1 0 1 1 0 0 1 0 1 1 0 0 1160 HB11- 0 0 0 0 0 1 0 0 1 0 0 1 0 1 1 1 0 0 1 0 1080 HB11- 1 0 0 1 1 0 1 0 0 1 1 0 1 0 0 0 1 1 0 0 1030 HB11- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1000
89 HB11- 0 1 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 985 HB11- 1 0 0 1 1 0 1 0 1 1 1 1 1 1 0 1 1 0 0 1 950 HB11- 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 900 HB11- 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 840 HB11- 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 800 HB11- 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 1 0 755 HB11- 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 690 HB11- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 655 HB11- 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 620 HB11- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 545 HB11- 0 0 0 0 1 1 0 0 0 0 1 1 1 1 1 0 1 0 0 0 500 HB11- 1 1 0 1 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 450
Appendix F. Continues with rest of the cultivars.
3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 5 5 5 5 5 5 6 6 6 0 1 2 4 5 6 7 8 9 1 2 3 4 6 8 1 2 4 5 7 8 0 2 3 814- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2665 814- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2480 814- 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 0 0 0 2110 814- 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 2050 814- 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1965 814- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1855 814- 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1715 814- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1650 814- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 1600 814- 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1500 814- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1440 814- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1380 814- 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 1 1 1315 814- 1 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 0 0 1 1 0 0 0 0 1230 814- 0 1 0 0 0 0 1 1 0 1 1 1 0 0 0 0 0 0 0 0 1 0 0 0 1160 814- 0 1 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 1080 814- 0 1 0 0 0 1 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 950 814- 1 1 0 0 1 0 0 0 0 1 1 0 0 0 0 0 1 1 1 1 0 1 1 1 900 814- 0 0 0 0 0 0 1 0 1 0 0 0 1 0 0 0 0 0 1 0 1 0 0 0 840
90 814- 1 0 1 1 1 0 0 0 0 1 1 1 1 1 0 0 1 1 1 1 0 1 1 1 755 814- 0 0 0 0 0 1 1 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 690 814- 0 1 0 0 0 1 0 1 1 0 0 0 0 1 0 0 0 1 0 0 1 0 0 0 655 814- 1 0 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 1 0 0 0 1 1 1 545 814- 0 1 1 1 0 1 1 1 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 500 814- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 450 814- 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 400 814- 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 360 S1- 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3975 S1- 0 0 1 1 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3678 S1- 1 0 1 1 1 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 3350 S1- 0 0 1 1 1 1 1 1 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 3110 S1- 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2900 S1- 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2750 S1- 1 1 0 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2665 S1- 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2570 S1- 1 1 1 1 1 1 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 2480 S1- 1 1 1 1 1 1 1 1 1 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 2110 S1- 1 0 1 1 0 0 1 0 0 0 0 0 1 0 0 0 1 0 1 1 0 0 0 0 1965 S1- 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 1 1910 S1- 1 0 0 0 1 0 1 1 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0 1855 S1- 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1800 S1- 0 0 1 1 1 1 0 0 1 0 0 0 0 0 0 0 1 0 1 1 0 1 0 1 1715 S1- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1650 S1- 1 1 0 0 0 0 0 0 0 1 0 1 0 1 0 1 0 1 0 1 0 0 1 0 1600 S1- 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1550 S1- 0 0 1 1 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1500 S1- 0 1 0 1 1 1 0 1 1 0 1 0 0 0 0 1 1 0 0 1 0 0 0 0 1440 S1- 1 0 1 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1380 S1- 0 1 0 0 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1315 S1- 1 1 1 1 0 0 0 1 0 1 0 1 1 1 0 1 1 1 1 1 0 1 0 0 1230 S1- 0 0 0 0 1 1 1 1 0 0 1 1 0 1 1 0 1 0 1 1 0 1 1 1 1160 S1- 1 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1140 S1- 1 0 1 1 1 0 1 0 0 1 0 1 0 1 0 0 0 0 0 1 0 1 0 0 1080 S1- 0 1 0 0 0 0 1 1 1 0 1 1 0 1 1 0 1 0 1 0 0 0 1 1 91 950 S1- 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 1 0 1 900 S1- 0 0 0 0 0 0 0 0 1 0 0 1 0 1 1 1 1 1 0 0 0 0 1 0 840 S1- 0 1 0 0 0 0 0 0 1 0 1 1 0 1 0 1 1 0 1 1 0 1 0 0 755 S1- 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 690 S1- 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 1 1 1 0 0 0 0 1 0 655 S1- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 545 S1- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 500 S2- 0 0 1 1 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1855 S2- 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1800 S2- 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1715 S2- 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 1650 S2- 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1600 S2- 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1550 S2- 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 1 1500 S2- 0 1 0 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 1440 S2- 1 0 0 0 0 1 0 1 1 0 0 0 0 0 1 0 0 1 0 0 0 0 1 1 1380 S2- 1 0 0 0 0 0 1 0 0 0 0 1 1 1 0 0 0 0 0 1 0 0 0 0 1315 S2- 1 1 1 1 1 0 0 0 0 1 1 0 0 0 1 1 1 1 0 0 0 0 1 1 1230 S2- 0 1 0 0 0 1 1 1 1 1 1 0 1 0 1 1 1 1 0 1 1 1 0 0 1160 S2- 1 0 1 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1140 S2- 0 1 1 0 0 0 0 1 1 1 0 1 1 1 0 1 1 0 1 0 1 1 0 0 1080 S2- 0 0 0 0 0 1 0 0 1 0 1 1 0 1 0 1 1 1 1 0 0 0 1 1 950 S2- 0 1 0 1 1 1 0 1 0 0 0 1 1 1 0 0 0 0 0 1 1 1 1 1 900 S2- 1 0 1 0 0 0 1 1 1 1 1 1 0 1 0 0 0 1 0 0 1 0 1 1 840 S2- 1 0 1 1 1 1 1 0 1 1 0 0 1 0 0 1 1 1 0 0 0 0 1 1 755 S2- 0 0 1 0 0 0 0 1 0 0 1 1 0 1 0 0 0 0 1 1 1 1 0 0 690 S2- 0 1 0 0 0 1 0 0 1 1 1 0 0 0 0 0 0 0 0 0 1 1 1 1 655 S2- 0 0 0 0 0 0 0 1 0 0 1 1 0 1 0 0 0 0 0 0 1 1 1 1 545 S2- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 500 S2- 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 400 S2- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 360 s3- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2665 s3- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2220 s3- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2110 92 s3- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1600 s3- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1550 s3- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1500 s3- 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1440 s3- 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1380 s3- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1315 s3- 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1230 s3- 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1160 s3- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1080 s3- 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1030 s3- 0 1 0 0 0 0 0 0 1 0 0 1 1 1 1 1 1 1 1 0 0 0 0 1 1000 s3- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 950 s3- 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 900 s3- 0 0 1 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 840 s3- 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 1 1 1 0 800 s3- 0 0 0 1 1 1 1 0 0 0 1 1 0 1 1 0 1 1 1 1 0 0 0 1 755 s3- 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 690 s3- 1 0 0 0 0 0 0 1 1 0 0 0 0 1 1 0 0 0 0 1 0 1 1 0 655 s3- 0 1 0 1 1 1 1 0 0 1 1 1 1 0 0 1 1 1 1 0 1 0 0 1 620 s3- 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 545 s3- 0 0 1 1 1 1 1 1 1 0 1 0 1 1 1 1 1 0 1 0 0 1 1 0 500 s3- 1 1 0 1 1 1 1 1 0 1 1 1 1 0 0 0 1 1 1 1 0 0 0 0 450 s3- 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 400 s3- 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 360 s3- 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 260 s3- 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 240 844- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2930 844- 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 2665 844- 1 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 1 1 1 1 1 2480 844- 1 0 1 1 0 0 0 0 0 1 0 1 1 1 1 0 0 0 1 0 0 0 0 1 2370 844- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 2310 844- 0 0 1 1 0 0 0 1 0 1 0 0 0 1 1 1 1 0 1 1 1 1 0 0 2110 844- 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1965 844- 0 0 0 0 1 0 1 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1910 844- 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 1 0 0 0 0 1 0 93 1855 844- 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0 0 0 0 1800 844- 0 0 0 1 1 1 1 0 0 1 1 0 0 1 0 0 0 0 0 0 0 0 0 1 1715 844- 1 1 1 0 0 0 0 1 1 0 0 1 1 0 1 1 0 1 0 1 1 1 1 0 1650 844- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1600 844- 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1550 844- 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1500 844- 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1440 844- 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1380 844- 0 0 1 1 1 0 1 1 0 1 1 1 1 1 1 0 0 0 0 1 1 0 0 1 1315 844- 0 1 0 0 0 1 1 0 1 0 0 0 0 0 1 1 1 0 0 0 0 0 1 1 1230 844- 1 0 1 1 1 0 0 0 1 0 0 0 1 1 0 0 0 1 1 1 1 0 1 0 1160 844- 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 1080 844- 0 1 0 0 0 0 1 1 0 1 1 0 0 1 1 0 1 0 0 1 0 0 0 1 1030 844- 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 0 0 0 0 1 0 1 0 1000 844- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 985 844- 0 0 0 0 0 1 1 0 0 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 950 844- 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 900 844- 1 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 840 844- 0 0 0 0 0 0 0 1 0 0 0 0 1 1 0 1 1 0 0 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17a- 1 0 1 1 1 0 0 1 0 0 1 0 1 1 0 0 0 0 0 0 1 1 1 0 1230 17a- 0 1 0 0 0 1 0 0 0 0 0 0 0 1 1 1 1 1 1 1 0 0 0 0 1160 17a- 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 1080 17a- 1 0 0 0 0 0 1 1 0 1 0 1 1 1 1 1 1 1 1 1 1 1 0 0 1030 17a- 1 0 1 1 1 1 0 1 0 1 0 1 0 0 0 0 0 0 1 0 0 0 0 0 1000 17a- 0 0 0 0 0 0 0 0 1 0 1 0 1 1 1 1 1 1 0 0 0 1 1 0 985 17a- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 950 17a- 0 0 1 1 1 1 0 0 0 0 1 1 1 0 0 1 0 0 0 0 0 0 0 0 900 17a- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 840 17a- 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 800 17a- 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 755 17a- 0 1 1 1 1 0 1 1 0 0 1 1 0 1 1 1 1 1 0 0 1 1 0 0 690 17a- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 655 17a- 0 0 1 1 1 0 1 1 1 0 1 1 0 1 1 1 1 1 0 0 1 1 0 0 620 17a- 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 1 0 545 96 17a- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 500 17a- 1 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 1 1 1 0 0 450 HB11- 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3110 HB11- 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2665 HB11- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2370 HB11- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2310 HB11- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2220 HB11- 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 0 0 1 0 1 0 2110 HB11- 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1965 HB11- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1910 HB11- 1 0 1 0 0 0 1 1 1 0 0 0 0 0 1 0 0 0 1 0 0 0 0 1 1855 HB11- 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 1 0 0 0 0 1800 HB11- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1750 HB11- 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1715 HB11- 0 0 0 0 0 1 0 1 0 1 0 1 0 0 0 0 0 0 0 0 0 0 1 0 1650 HB11- 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 1600 HB11- 0 0 1 1 0 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 1 1 0 0 1550 HB11- 1 0 0 0 1 0 1 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 1 1500 HB11- 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1 1 0 1440 HB11- 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1420 HB11- 0 0 0 0 0 0 0 1 0 0 1 1 1 0 0 0 0 1 0 0 0 0 0 0 1380 HB11- 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1315 HB11- 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1270 HB11- 1 1 0 0 1 0 1 0 0 0 0 1 0 1 1 1 0 1 0 1 0 1 1 1 1230 HB11- 0 0 1 1 0 1 0 1 1 0 1 0 1 0 0 0 1 0 0 0 1 0 0 1 1160 HB11- 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1080 HB11- 1 0 0 0 0 0 0 0 0 0 1 1 0 0 1 0 0 0 0 0 1 0 0 1 1030 HB11- 0 0 1 1 1 0 1 1 0 1 0 0 1 1 0 0 1 0 0 1 0 0 0 0 1000 HB11- 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 985 HB11- 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 1 950 HB11- 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 1 0 900 HB11- 0 0 0 0 0 1 0 0 1 0 1 1 0 0 1 0 0 0 0 0 1 0 0 0 840 HB11- 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 800 HB11- 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 755 HB11- 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 97 690 HB11- 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 655 HB11- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 620 HB11- 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 545 HB11- 1 0 1 1 1 0 0 0 1 1 0 0 0 0 0 1 1 0 0 0 1 0 0 0 500 HB11- 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 450
98
VITA
Seukmin Hong graduated Stratford High School in Houston, Texas in fall 2011, and graduated University of Houston with B.S. in Biotechnology in fall 2015. He started his master’s degree in General Agriculture and minor in
Biotechnology in Stephen F. Austin State University in Spring 2016, and finished his degree in spring 2017.
Permanent Address: Apt. 114-401, 74 Toegye-ro 90-Gil, Jung-Gu, Seoul 0458L, South Korea
Style designation of American Society of Horticulture Science
This thesis was typed by Seukmin Hong 99