Jordan Journal of Agricultural Sciences, Volume 12, No.3 2016

Morphological Variability and Microsatellite Diversity of Cultivated Mango (Mangifera indica L.) from Andhra Pradesh, India

Hameedunnisa Begum1, Medagam Thirupathi Reddy1, Surapaneni Malathi1, Boreddy Purushotham Reddy1, Gonela

Narshimulu1, Javaregowda Nagaraju2 and Ebrahimali Abubaker Siddiq3

ABSTRACT

An eco-geographic survey covering three eco-geographical regions (Coastal Andhra, Telangana and Rayalaseema) of Andhra Pradesh State, India was undertaken during May-June 2009 to locate, analyse and as- sess the current status of mango genetic resources. Morphological analysis following descriptive statistics revealed considerable variability among 90 mango cultivars which was confirmed by molecular analysis with 109 mango-specific SSRs. Jaccard’s similarity co-efficient ranged between 0.35 and 0.85 signifying a wide range (15-65%) of intraspecific diversity at molecular level in mango. A dendrogram based on application of unweighted pair group method using arithmetic average cluster analysis demonstrated four genotypic groups among the varieties studied.

Keywords: Genetic relationship, intervarietal diversity, mango cultivars, microsatellite markers, molecular characterisation, morpho-physiological characterisation.

INTRODUCTION period of the Cretaceous era (Yonemori et al., 2002). It gradually spread and become naturalized and adapted Mango belongs to the genus Mangifera, family throughout the tropics and subtropics and has been Anacardiaceae and order Sapindales. The edible species grown commercially for centuries. Much of the spread Mangifera indica L. bears good quality fruits and is and naturalization has occurred in conjunction with the commonly referred to as cultivated mango. The other spread of human populations. Today, mangos are edible Mangifera species generally have lower quality recognized and eaten throughout the world and are fruits and are commonly referred to as wild mangos. It regarded as one of the most popular and esteemed originated in the Indo-Burma region during the earlier tropical fruits. It is well adapted to cultivation and has

1 been cultivated for thousands of years in India Vegetable Research Station, Dr.Y.S.R. Horticultural University (Dr.YSRHU), Rajendranagar, Hyderabad, (Kostermans and Bompard, 1993). Its popularity and Andhra Pradesh, 500030, India 2Centre for DNA Fingerprinting and Diagnostics, Nampally, importance can easily be realized by the fact that it is Hyderabad, Andhra Pradesh, 500001, India often referred as ‘the King of fruits’ in the tropical world 3Institute of Biotechnology (Formerly Biotechnology Unit), Acharya N.G. Ranga Agricultural University (ANGRAU), (Singh, 1996). Rajendranagar, Hyderabad, Andhra Pradesh, 500030, India Mango is diploid with 2n=40 (10) having a genome [email protected] 8 Received on 16/7/2013 and Accepted for Publication on of 8.8 × 10 bp, which is about two and a half times that 29/12/2015. of Arabidopsis thaliana (Bennett, 2004). The

© 2016 DAR Publishers/The University of Jordan. All Rights Reserved. -815- Morphological Variability and… Hameedunnisa Begum et al phenomenon of allopolyploidy, out breeding, and the Morphological characterisation is traditionally the different agro-climatic conditions in mango growing most common method used and many different crops areas, has resulted in a high level of genetic diversity in have been studied (Gonzalez et al., 2002) including mangos (Krishna and Singh, 2007). Mango has rich mango (Subedi et al., 2009). Morphological intra-specific diversity and there are about 1600 cultivars characterisation can be used as an important tool since in the world (Pandey, 1998), of which some 350 published descriptors lists are readily available for most cultivars are in commercial production and the rest are major crop species (Hoogendijk and Williams, 2001) limited to mixed orchards or home gardens. India is including mango (IPGRI, 2006). Morphological thought to be the primary centre of diversity for mango characteristics are still extremely useful for identification (NBPGR, 2007). Wide ecological variation and diverse and or differentiation of cultivars. However, they are needs of multi-ethnic communities have enriched the often faced with the problems of being influenced by country with a genetic wealth of diverse mango environmental parameters, heritability and low varieties. India represents the biggest mango germplasm penetrance. Usually, description of mango germplasm in the world and currently, India harbors more than 1000 was based largely on morphology (Ram and Rajan, mango cultivars (Karihaloo et al., 2003). The farming 2003) and in India, mango varieties have been identified communities in India maintain a rich mango genetic and or differentiated based particularly on fruit diversity resource, both commercial and local cultivars. characteristics like size, shape and color. Several studies Farmers with access to the research system have been have been made on morphological characterization of systematically maintaining commercial mango cultivars many different cultivars of mango all over the world for fresh consumption and income generation. In India, (Ascenso et al., 1981; Mukherjee et al., 1983; where such a high diversity of mango cultivars Subramanyam and Iyer, 1989; Jintanawong et al., 1992; originated and exists, ambiguities in cultivar recognition Illoh and Olorode, 1999; Subedi et al., 2009). Some of and classification are also common especially in case of the mango cultivars in India had been identified based the cultivars that exhibit outstanding similarities in their on morphological characters (Mukherjee et al., 1983; morphological traits. It is indispensable to validate the Subramanyam and Iyer, 1989). Morphological identities of such cultivars as well as analyze the description cannot be seen as an older method that was diversity among the existing cultivars. The management replaced by molecular markers, but as a useful tool that of mangos would be effective and efficient if the complements the new techniques (Campos et al., 2005). characterization is accurate, so that it results in clear Molecular characterisation encompasses modern grouping which can be used as reference for the methods that complement morphological descriptors and breeders, orchardists, traders, stakeholders, certification has become quite popular, each with its own advantages agencies, and in intellectual property rights and trade and disadvantages (Lavi et al., 1993). Molecular markers agreements. In addition, it is imperative to safeguard the are recognized as one technique that increased the Indian mango cultivars from defraud and guaranty the advance in mango improvement as well as the other originality. Characterisation and evaluation of classifiable methods such as harmonized open germplasm is thus important for better use of genetic pollination and clonal selection (Iyer and Dinesh, 1997). resources of mango (Ravishankar et al., 2004). There are numerous examples of the application of

-816- Jordan Journal of Agricultural Sciences, Volume 12, No.3 2016 different types of molecular markers in the analysis of marker for plant analysis. the genetic diversity of mango (Viruel et al., 2005; The main objectives of this research work were to Pandit et al., 2007; Santos et al., 2008; Galvez-Lopez et morpho-physiologically characterize and evaluate the al., 2009; Singh and Bhat, 2009; Singh et al., 2010). fruit characteristics and to identify the genetic diversity Techniques used include random amplified polymorphic at molecular level using SSRs among 90 local and DNA - RAPDs (Kumar et al., 2001; Karihaloo et al., popular cultivars of mango in Andhra Pradesh, India, as 2003; de Sousa and Costa Lima 2004; Ravishankar et an essential requirement for crop improvement al., 2004; Schnell et al., 2004; Damodaran et al., 2007; programs, preservation, and selection of elite materials Anju et al., 2008; Rajwana et al., 2008; Faleiro et al., for the mango industry at the state level. This paper 2009; Bhargava and Khorwal, 2011; Majumder et al., presents results of this genetic diversity study and of 2011; Srivastava et al., 2012), variable number of efforts to locate potential sites for in-situ conservation of tandem repeats - VNTRs (Adato et al., 1995), restriction mango genetic resources for future use in research and fragment length polymorphism - RFLPs (Ravishankar et development. al., 2004; Chunwongse et al., 2006), amplified fragment length polymorphism - AFLPs (Eiadthong et al., 2000; MATERIALS AND METHODS Phumichai et al., 2000; Hautea et al., 2001; Kashkush et Eco-geographical survey al., 2001; Teo et al., 2002; Yamanaka et al., 2006; Shi Eco-geographical survey was undertaken during Sheng-you et al., 2011), microsatellites or simple summer 2008 covering three different eco-geographical sequence repeats - SSRs (Eiadthong et al., 2000; regions of Andhra Pradesh, India. A total of 90 different Ravishankar et al., 2000; Kumar et al., 2001; Karihaloo local and commercial cultivars of mango were sampled et al., 2003; Viruel et al., 2005; Honsho et al., 2004; from 12 districts surveyed covering home gardens, Duval et al., 2005; Schnell et al., 2005; Hirano et al., village gardens, roads and highways and scattered 2010; Wahdan et al., 2011; Begum et al., 2012; Vasugi populations of mango in villages (Table 1). Single tree et al., 2012, inter-simple sequence repeats - ISSRs of each of the 90 mango cultivars was selected for fruit (Gonzalez et al., 2002; Pandit et al., 2007; Anju et al., and leaf sampling for in-situ morpho-physiological fruit 2008; Samant et al., 2010; Tomar et al., 2011; characterization and molecular characterization in Srivastava et al., 2012) and directed amplified mini laboratory, respectively. satellite DNA (DAMD) (Srivastava et al., 2012). These Fruit sampling and their characterization and researchers confirmed that the techniques were very evaluation effective in detecting the differential traits targeted in Ten tree-ripe fruits of each of the selected tree of the each study. SSR analysis shows great potential for 90 cultivars were sampled using mango harvesters. Fruit mango improvement and can be performed for variety samples were collected for morpho-physiological identification, validation of parentages and estimation of characterization and evaluation following descriptors of genetic variation in existing populations and mango (IPGRI, 2006) to assess variation in fruit characterisation of rootstocks (Brettell et al., 2002). morpho-physiology. The fruit samples were evaluated Microsatellites, being reproducible, multi-allelic, co- for 10 quantitative traits like fruit length (cm), fruit dominant and relatively abundant, have become the ideal width (cm), fruit thickness (cm), fruit weight (g) fiber

-817- Morphological Variability and… Hameedunnisa Begum et al length (mm), peel (%), pulp (%), stone (%), total soluble Bands on gels were scored as present (1) and absent (0) solids (TSS) (°Brix) and shelf life (Days). Percent peel, for each marker and data were entered in a binary matrix pulp and stone were calculated by the weight of the peel, as discrete variables. The genetic relatedness of local pulp and stone, respectively divided by total weight of and popular cultivars of mango was calculated using the fruit multiplied with 100. TSS was recorded with Jaccard’s similarity coefficient and a dendrogram hand refractometer. The fruit samples were also showing the genetic relatedness of the 90 cultivars of characterized for 16 qualitative traits like fruit shape, mango was constructed using the unweighed pair group color of skin of mature fruit, skin thickness, skin texture, method with arithmetic mean (UPGMA) feature of the quantity of fiber, pulp colour, adherence of skin to pulp, NTSYS PC Software (Version 2.1) statistical analysis stalk insertion, basal cavity, beak type, sinus type, package (Rohlf, 2000). The polymorphic information shoulders, slope of shoulders, apex, eating quality and content (PIC) of microsatellite markers was calculated utility. The mean data of each of the random fruit sample according to the standard formula (Powell et al., 1996). of 90 cultivars was analysed for 9 quantitative traits following 'Descriptive Statistics' for mean, standard RESULTS AND DISCUSSION error, standard deviation, sample variance and Morphological variability coefficient of variation. Historically mango genotypes have been Leaf sampling characterized using morphological markers (Singh, Fresh, young and healthy leaves from each of the 1969). Commercial cultivars have been identified on the sampled tree of the selected cultivars were collected into basis of leaf, panicle, fruit and stone characteristics; moist tissue paper, which were hermetically sealed and however, these characters may change with packed in ice for transport to the laboratory. Samples environmental conditions (Lakshminarayana, 1980). were subsequently stored in the freezer at -50°C until Local varieties of mango in India, in general, are mainly required for analysis. distinguished by fruit morphology (size, shape and DNA extraction colour) and qualitative traits (fruiting time, fiber content The genomic DNA from leaf samples was extracted in flesh, aroma and taste). Based on these, farmers have by a modified CTAB method (Porebski et al., 1997). precise names for mango varieties in their own language. PCR Reaction From the results of mean, standard error, standard Polymerase chain reaction (PCR) amplification was deviation, sample variance and coefficient of variation performed in a Perkin Elmer Thermocycler (PCR-Gene (Table 2), it is evident that there was significant Amp PCR System 9700) as per the standard protocol variation in 9 quantitative fruit traits among 90 cultivars (Williams et al., 1990) using 109 mango-specific of mango under study. In the present study, fruits of microsatellite markers. various cultivars of mango were found variable in size, Data analysis weight, fiber length, peel, pulp and stone content and The number of polymorphic bands generated by each total soluble solids (Table 2). The fruit length, width and primer was determined by an initial visual examination thickness ranged from 5.40-16.80, 3.70-9.70 and 3.00- of the gel photographs. The bands of medium to strong 9.00 cm, respectively. The fruit weight ranged from intensity were included in the subsequent investigation. 50.00 to 844.00 g. ‘Sora’ had biggest and heaviest fruits,

-818- Jordan Journal of Agricultural Sciences, Volume 12, No.3 2016 while ‘Amrigola’ had smallest and lightest fruits. The of the 84 primers differed significantly in their ability to peel, pulp and stone contents ranged from 8.90 to determine variability among the varieties. A total of 250 46.80%, 46.80 to 75.50% and 7.10 to 32.00%, alleles were generated using 84 primers, with a mean of respectively. The TSS ranged from 8.00 (‘Amrigola’) to 2.98 alleles per SSR (Table 3). Of these, 43 23.00 °Brix (‘Pandurivarimamidi’), while shelf life amplification fragments were polymorphic, yielding a ranged from 3 days (‘Mukkurasalu’) to 9 days polymorphism rate of 17.20%. The highest level of (‘Kumkum’). Perusal of quantitative data (Table S1) polymorphism was detected in SSR-44 followed by revealed high variability in fruit morphology. There SSR-19 and SSR-84. Complex banding patterns were were some differences among 90 varieties of mango encountered in mango with the number of amplified with respect to certain qualitative traits like fruit shape, fragments (Table 3) ranging from 1 (MngSSR-27) to 6 color of skin of mature fruit, skin thickness, pulp color, (SS6-84). The level of polymorphism in the present quantity of fibre and eating quality (Table S1). Fruit study is in line with that of the findings of earlier shape varied from round to oblong-reniform, colour of research groups (Bally et al., 1996; Viruel et al., 2005; the skin from green, yellow to red colour. Thickness of Duval et al., 2009; Wahdan et al., 2011). A total of 88 peel of fruit ranged from thin to very thick. The bands ranging from 3 to 9 with an average of 5.5 organoleptic evaluation divided the fruits in to poor to bands/microsatellite primer validated with 16 SSRs in 28 excellent quality. The study highlights the diversity of mango genotypes was reported (Viruel et al., 2005). mango fruit forms that exists in Andhra Pradesh, which with 10 oligonucleotide primers allowed the scoring of was also observed in wild and cultivated Indian mangos 107 alleles (Bally et al., 1996). High diversity within the (Karihaloo et al., 2003). sample with a total number of 140 alleles displayed wherein 19 SSRs were utilized to analyze a total of 307 Microsatellite polymorphism accessions from India, South-East Asia, Florida, Africa In this study, high levels of polymorphism were and the Caribbean (Duval et al., 2009). A total of 92 observed for the SSR markers. Of the 109 SSRs scorable bands ranging from 2 to 4 with an average of validated, only 88 were amplified. Among the amplified 2.55 bands/SSR using 36 SSRs in the two strains primers, only 84 SSRs which showed clear and ("Hania" and "Aml") of mango was reported (Wahdan et consistent banding patterns and were found to be al., 2011). Following RAPD analysis of 30 Kensington polymorphic (Table S3). This is in line with the findings mangos comprising of 27 'Kensington Pride' accessions, of another researcher group (Wahdan et al., 2011) who 2 'R2E2' and 1 seedling found that 36 out of 42 SSR primers gave reproducible In the present study, fragment size ranged from 100 polymorphic DNA amplification patterns among two (SSR-2, SSR-17, SSR-21, SSR-52, SSR-81and SSR-94) to Egyptian mango strains ‘Hania’ and ‘Aml’ and other 375 bp (SSR-13) in length. Polymorphic information research group (Hirano et al., 2010) who observed that content (PIC), the reflection of allele diversity and 11 out of 24 SSRs were found to be highly variable frequency among the accessions, varied greatly for all the among 113 mango accessions. Amplification profile SSRs validated. The PIC values varied widely among loci revealed by one of the highly polymorphic marker (SSR- and ranged from 0.47 (SSR-37) to 0.97 (SSR-44) with an 82) across 90 mango varieties is depicted in Fig. 1. Each average of 0.72 per SSR (Table 3). This is higher than that

-819- Morphological Variability and… Hameedunnisa Begum et al reported by a research group (Wahdan et al., 2011) in their relationships among accessions and their corresponding work with 42 SSR primer pairs ranging from 0.25 to 0.75, collecting-site environments (Steiner and Greene, 1996). with a mean value 0.51 for all loci among two Egyptian Understanding the genetic diversity among the varieties mango strains ‘Hania’ and ‘Aml’ and by another research is important in mango production, improvement and group (58) in their work with 15 microsatellite loci isolated breeding; knowledge on this field can supply useful from mango ranged from 0.21 to 0.63 for the polymorphic information for further scientific progress in developing loci among 59 Florida cultivars and four related species new genotypes (Rajwana et al., 2008). Cluster analysis from the USDA germplasm collection for mango. PIC demonstrating genetic relationships of mango varieties value of 0.346 to 0.857 was recorded with 11 SSRs over was generated using UPGMA and Jaccard’s similarity common cultivars from Florida, India and Southeast Asia coefficient (Fig. 2). The dendrogram revealed four major (Hirano et al., 2010). This may probably be due to the clusters (cluster-I-IV). Cluster I could be further divided higher number of analyzed samples, as well as due to the into two subclusters (cluster-IA and IB). Of these two more diverse genotypes analyzed. The microsatellites with subclusters, cluster-IA consisted of 54 varieties while high PIC values (SSR-44, SSR-19, SSR-84, and SSR-15) subcluster-IB consisted of 33 varieties. Cluster II, III and were found to be more useful in differentiating the mango IV were solitary; consisting of only one genotype each. varieties. The relatively higher number of polymorphic This dendrogram can be used to select the most bands per SSR and the high level of PIC value of SSR data appropriate parental material to improve horticultural suggested that a small number of primers would be traits. The selection and hybridization programmes in adequate to distinguish between mango accessions. Our mango can be affected based on the clustering. From the results clearly demonstrated that PCR based SSR markers dendrogram, it is evident that ‘Natupalli’, ‘Natlu’ and targeting 250 polymorphic bands, is a good tool for the ‘Palli’ clearly formed separate solitary clusters, which genetic analysis of mango varieties. The high level of SSR occupied the extreme position in the tree. The varieties polymorphism observed in the present material is consistent could not be grouped based on usage viz., table or juicy with the extensive morphological diversity reported in or pickle type. These findings are in agreement with Indian mango cultivars (Mukherjee, 1948; Naik and those of earlier researcher (Eiadthong et al., 1999), Gangolly, 1950; Mukherjee, 1953; Rajwana et al., 2008). where in SSR-anchored primers could not separate the However, it is obvious that from the variation in band cultivars according to the types eaten as ripened fruit or frequencies of all the SSR primers validated, the results unripe fruits. The cultivars ‘Erraarati’ and indicate that mango too represents very rich reserves of ‘Kobbarimamidi’ were highly similar (85% similarity). genetic variability which in turn will provide a wide Jaccard’s similarity coefficient ranged between 0.35 spectrum for the selection of desirable types from the and 0.85 signifying wide amplitude (15-65%) of germplasm. intraspecific diversity, which could be the probable reason for heterogeneity in production and quality of Cluster analysis and genetic relationships mangoes across the state. In Indian mangos, genetic To identify genetic materials that may contain useful diversity had been studied by various workers using traits for germplasm enhancement, a systematic RAPD, ISSR, SSR and AFLP (Ravishankar et al., 2000; evaluation of genetic diversity is required to understand Kumar et al., 2001; Karihaloo et al., 2003; Pandit et al.,

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2007; Srivastava et al., 2007; Bajpai et al., 2008), which banding patterns (alleles) to discriminate and identify the indicated presence of wide genetic diversity in mango. mango cultivars. Some markers produced more variety- Here, high genetic diversity indicates fixation of new specific alleles enabling better differentiation ofvarieties, alleles in specific population along with recombination implying that some genomic regions were more variable and segregation of alleles by open-pollination of between varieties. A unique allele of 130 bp was produced by genetically different mangos in varied agro-climates. It SSR-18 and SSR-82 for ‘Alphonso’ and ‘Panakalu’, has been mentioned earlier that the development of respectively. SSR-46, SSR-59, SSR-81, SSR-83, SSR-84 mango in the country is result of selections from the SSR-85, SSR-88, and MngSSR-27 generated solitary unique amateur gardeners. A high diversity within regions in alleles of 210, 165, 100, 200, 245, 205, 250bp for ‘Neelum’, India was reported (Karihaloo et al., 2003) and is not ‘Himayat’, ‘Bangalora’, ‘Dashehari’, ‘Imampasand’, surprising given that mango is a cross-pollinated plant ‘Pulihora’, ‘Shakkaragola’ and Neelum, respectively. and selecting superior strains according to taste among Further, we suggest that this discrimination of cultivars can naturally produced seedlings has given birth to the be carried out with just these selected microsatellites. commercial cultivars and the observed appreciable range of variation. Most varieties of mango have arisen CONCLUSIONS through a selection of desirable types among naturally The current study adds to the previous one in providing produced seedlings (Karihaloo et al., 2003). more insight into the morphology and genetic diversity that exists among the mango varieties in the face of growing Identification of cultivars interest in the potential of the mango production sector. The Many molecular markers are nowadays utilized for study highlights the diversity of mango fruit forms that varietal identification and clonal fidelity testing (Hoogendijk exists in Andhra Pradesh, India. Both molecular and and Williams, 2001). Identification of genotype using morphological methods were effective at portraying the molecular markers can help in identification of trees for sale, variation. A rich diversity of both commercial and local minimizing the risk of mix-ups in orchards (Struss et al., cultivars was found. Local mango cultivars possess unique 2001). Microsatellite marker technique will help in characteristics, having both economic and cultural value. identifying superior genotypes for cultivar upgrading or for High genetic variability of Andhra Pradesh mangos can be generating new cultivars. Here, 25 promising varieties were exploited by breeding programs to produce high quality selected for assigning the molecular IDs. For each primer, the mangos. As genetic erosion of local cultivar diversity is amplification profiles were carefully noted down and the increasing, evaluation has become a necessity for on-farm specific bands appeared were critically observed and and ex-situ conservation, at least for most of the important compared with the other varieties and the unique banding types. pattern obtained was assigned as molecular ID (Table 4). An allele found in only one accession is termed a variety-specific ACKNOWLEDGEMENTS allele. Here, comparison of the 250 alleles which were The authors wish to acknowledge the financial detected using 84 polymorphic SSRs revealed distinct support of Department of Biotechnology, New Delhi.

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Table 1: Collection sites of 90 cultivars of mango in Andhra Pradesh. Collection site Cultivar LatitudeLongitude Village District Eco-geographic region Peddarasam 13º58' N 79º20' E Anantharajupeta Kadapa Rayalaseema Cherukurasam 13º58' N 79º20' E Anantharajupeta Kadapa Rayalaseema Chinnarasam 16º46' N 80º51' E Nuzividu Krishna Coastal Andhra Panchadarakalasa 13º58' N 79º20' E Anantharajupeta Kadapa Rayalaseema Tellarasam 16º52' N 80º44' E Reddygudem Krishna Coastal Andhra Sinduri 16º86' N 80º73' E Rangapuram Krishna Coastal Andhra Amrutham 15º30' N 78º20' E Panyam Kurnool Rayalaseema Delhipasand 15º30' N 78º20' E Panyam Kurnool Rayalaseema Reddipasand 15º30' N 78º20' E Panyam Kurnool Rayalaseema Doodpeda 15º18' N 78º13' E Banganapalle Kurnool Rayalaseema Shakargola 15º18' N 78º12' E Yagantipalle Kurnool Rayalaseema Natupalli 15º18' N 78º12' E Yagantipalle Kurnool Rayalaseema Nadusalai 13º58' N 79º20' E Anantharajupeta Kadapa Rayalaseema Moolky 13º58' N 79º20' E Anantharajupeta Kadapa Rayalaseema Panakalu 13º58' N 79º20' E Anantharajupeta Kadapa Rayalaseema Nagulpalli Irsala 13º58' N 79º20' E Anantharajupeta Kadapa Rayalaseema Peter 13º58' N 79º20' E Anantharajupeta Kadapa Rayalaseema Pulihora 13º58' N 79º20' E Anantharajupeta Kadapa Rayalaseema Dashehari 13º58' N 79º20' E Anantharajupeta Kadapa Rayalaseema Vikarabad 13º58' N 79º20' E Anantharajupeta Kadapa Rayalaseema Laddupasand 14º50' N 78º15' E Veerareddigaripalle Kadapa Rayalaseema Lalbahar 14º50' N 78º15' E Veerareddigaripalle Kadapa Rayalaseema Kesar 17º43' N 78º39' E Tandarapulli Medak Telangana Dondakayalamamidi 17º43' N 78º39' E Tandarapulli Medak Telangana Panukulamamidi 17º43' N 78º39' E Tandarapulli Medak Telangana Goa 17º43' N 78º39' E Tandarapulli Medak Telangana Pandurivarimamidi 17º43' N 78º39' E Tandarapulli Medak Telangana Nawabpasand 15º30' N 78º20' E Panyam Kurnool Rayalaseema Rumani 15º30' N 78º20' E Panyam Kurnool Rayalaseema Khader 13º58' N 79º20' E Anantharajupeta Kadapa Rayalaseema Kumkum 15º18' N 78º12' E Yagantipalle Kurnool Rayalaseema Phirangiladwa 13º58' N 79º20' E Anantharajupeta Kadapa Rayalaseema Beneshan 15º18' N 78º12' E Kausurbagh Kurnool Rayalaseema Bangalora 17º37' N 78º05' E Sangareddy Medak Telangana Tiyyamamidi 13º58' N 79º20' E Anantharajupeta Kadapa Rayalaseema Imampasand 15º15' N 79º57' E Sanampudi Prakasam Coastal Andhra Sora 17º37' N 78º05' E Sangareddy Medak Telangana Alphonso 16º45' N 80º38' E Mylavaram Krishna Coastal Andhra Neelum 15º19' N 78º07' E Hyderbagh Kurnool Rayalaseema Abbasi 15º18' N 78º12' E Yagantipalle Kurnool Rayalaseema Safeddamini 15º18' N 78º12' E Yagantipalle Kurnool Rayalaseema Govander 15º18' N 78º12' E Yagantipalle Kurnool Rayalaseema Chukla 15º18' N 78º12' E Yagantipalle Kurnool Rayalaseema Hublee 15º18' N 78º12' E Yagantipalle Kurnool Rayalaseema Jahangir 13º58' N 79º20' E Anantharajupeta Kadapa Rayalaseema Amrigola 13º58' N 79º20' E Anantharajupeta Kadapa Rayalaseema Janardhanpasand 13º58' N 79º20' E Anantharajupeta Kadapa Rayalaseema Zardalu 14º10' N 78º48' E Veeraballi Kadapa Rayalaseema Jalalu 16º46' N 80º18' E Raghavapuram Krishna Coastal Andhra Tellagulabi 16º52' N 80º44' E Reddygudem Krishna Coastal Andhra Chinnaachaar 15º30' N 78º20' E Panyam Kurnool Rayalaseema Peddaachaar 15º30' N 78º20' E Panyam Kurnool Rayalaseema Punasabaramasi 13º58' N 79º20' E Anantharajupeta Kadapa Rayalaseema Royalspecial 13º58' N 79º20' E Anantharajupeta Kadapa Rayalaseema

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Himayat 16º45' N 80º38' E Mylavaram Krishna Coastal Andhra Suvarnarekha 17º19' N 78º23' E Rajendranagar Rangareddy Telangana Chinnasuvarnarekha 13º58' N 79º20' E Anantharajupeta Kadapa Rayalaseema Mylapurpunasa 17º37' N 78º05' E Sangareddy Medak Telangana Aryavarth Irasala 17º37' N 78º05' E Sangareddy Medak Telangana Panchavarnam 17º37' N 78º05' E Sangareddy Medak Telangana Lazzat Bux 17º37' N 78º05' E Sangareddy Medak Telangana Kothapallikobbari 17º37' N 78º05' E Sangareddy Medak Telangana Kanthavarapadu 17º37' N 78º05' E Sangareddy Medak Telangana Nuzivedurasalu 16º46' N 80º51' E Nuziveedu Krishna Coastal Andhra Desavali 17º07' N 82º15' E Pithapuram East Godavari Coastal Andhra Paparaoguava 17º15' N 82º20' E Kathipudi East Godavari Coastal Andhra Kolankagova 17º15' N 82º20' E Kathipudi East Godavari Coastal Andhra kobbariantu 18º32' N 83º44' E Palakinda sankili Srikakulam Coastal Andhra Kalamamidi 17º15' N 82º20' E Kathipudi East Godavari Coastal Andhra Patikarasalu 18º41' N 83º91' E Akkulapet Srikakulam Coastal Andhra Nallayendrasulu 18º41' N 83º91' E Akkulapet Srikakulam Coastal Andhra Mukkurasalu 18º41' N 83º91' E Akkulapet Srikakulam Coastal Andhra Mettavalasapeechumanu 18º34' N 83º22' E Bobbili Vizainagaram Coastal Andhra Chotaamrutham 18º34' N 83º22' E Bobbili Vizainagaram Coastal Andhra Bobbilipeechumanu 18º34' N 83º22' E Bobbili Vizainagaram Coastal Andhra Kinthalooripeta 18º34' N 83º22' E Bobbili Vizainagaram Coastal Andhra Sannarasalu 17º21' N 82º32' E Tuni East Godavari Coastal Andhra Erraarati 18º34' N 83º22' E Bobbili Vizainagaram Coastal Andhra Kobbarimamidi 17º15' N 82º20' E Kathipudi East Godavari Coastal Andhra Punasa 17º15' N 82º20' E Kathipudi East Godavari Coastal Andhra Navaneetham 17º19' N 78º23' E Rajendranagar Rangareddy Telangana Chitoor Rasalu 13º37' N 79º20' E Narasingapuram Chittor Rayalaseema Mallepalli Beneshan 16º42' N 78º58' E Mallepalli Nalgonda Telangana Alampur Beneshan 17º37' N 78º05' E Sangareddy Medak Telangana Veeraballi Beneshan 14º10' N 78º48' E Veeraballi Kadapa Rayalaseema Rati Banginapalli 17º37' N 78º05' E Sangareddy Medak Telangana Hydersahib 17º15' N 82º20' E Kathipudi East Godavari Coastal Andhra Mulgoa 13º58' N 79º20' E Anantharajupeta Kadapa Rayalaseema Natlu 16º45' N 80º38' E Mylavaram Krishna Coastal Andhra Palli 15º18' N 78º12' E Yagantipalle Kurnool Rayalaseema

Table 2: Descriptive statistics of quantitative fruit traits of 90 cultivars of mango in Andhra Pradesh. Fruit Fruit Fruit Fruit Length Peel Pulp Stone TSS Shelf life Statistic parameter length width thickness weight of fiber (%) (%) (%) (°Brix) (Days) (cm) (cm) (cm) (g) (mm) (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) Mean 9.66 6.61 6.22278.23 17.63 21.16 62.00 16.45 16.38 5.92 Range 11.40 6.00 6.00794.00 56.00 28.60 28.70 24.90 15.00 6.00 Standard Error 0.25 0.13 0.13 14.72 1.15 0.60 0.72 0.52 0.33 0.11 Standard Deviation 2.36 1.21 1.19 139.62 10.87 5.67 6.81 4.97 3.13 1.06 Sample Variance 5.57 1.47 1.42 19494.52 118.21 32.18 46.32 24.66 9.77 1.13 CV(%) 24.43 18.37 19.2050.18 61.68 26.80 10.98 30.18 19.08 17.94

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Table 3: Observed variation in the number of alleles and polymorphic information content of the highly polymorphic microsatellites in mango. Number PIC Number PIC Number PIC SSR SSR SSR of alleles values of alleles values of alleles values SSR-1 3 0.7 SSR-33 2 0.51 SSR-67 3 0.82 SSR-2 2 0.8 SSR-34 3 0.75 SSR-68 2 0.69 SSR-3 3 0.71 SSR-36 4 0.82 SSR-71 4 0.70 SSR-4 2 0.71 SSR-37 3 0.47 SSR-72 3 0.70 SSR-5 2 0.61 SSR-38 2 0.66 SSR-76 3 0.90 SSR-6 3 0.76 SSR-39 3 0.81 SSR-77 3 0.60 SSR-7 2 0.51 SSR-41 3 0.76 SSR-78 2 0.70 SSR-8 3 0.51 SSR-42 2 0.53 SSR-79 2 0.62 SSR-11 2 0.74 SSR-43 2 0.66 SSR-80 2 0.74 SSR-12 2 0.63 SSR-44 2 0.97 SSR-81 3 0.70 SSR-13 3 0.70 SSR-46 5 0.80 SSR-82 5 0.72 SSR-15 4 0.86 SSR-48 2 0.58 SSR-83 3 0.79 SSR-16 4 0.84 SSR-49 3 0.75 SSR-84 6 0.87 SSR-17 2 0.69 SSR-50 2 0.51 SSR-85 5 0.77 SSR-18 3 0.67 SSR-51 2 0.73 SSR-87 5 0.80 SSR-19 5 0.88 SSR-52 4 0.85 SSR-88 3 0.80 SSR-20 5 0.69 SSR-53 3 0.79 SSR-89 4 0.81 SSR-21 3 0.81 SSR-54 2 0.69 SSR-90 3 0.71 SSR-22 3 0.82 SSR-55 3 0.78 SSR-91 3 0.71 SSR-24 3 0.56 SSR-56 3 0.82 SSR-92 3 0.79 SSR-25 2 0.73 SSR-57 3 0.73 SSR-93 4 0.81 SSR-26 4 0.74 SSR-58 2 0.74 SSR-94 5 0.78 SSR-27 2 0.63 SSR-59 4 0.82 SSR-95 3 0.66 SSR-28 3 0.79 SSR-60 3 0.77 SSR-96 2 0.49 SSR-29 3 0.76 SSR-61 2 0.55 MngSSR-14 3 0.73 SSR-30 2 0.56 SSR-62 3 0.85 MngSSR-24 3 0.74 SSR-31 3 0.72 SSR-64 3 0.76 MngSSR-26 3 0.60 SSR-32 2 0.52 SSR-65 4 0.81 MngSSR-27 1 0.65 PIC= Polymorphic information content

Table 4: Variety-specific microsatellite markers of mango. Primer producing Size of the specific Primer producing Size of the specific Cultivar Cultivar specific band(s) band (bp) specific band(s) band (bp) Juicy type Juicy type Suvarnarekha SSR-15 205, 215 Nagulapalli SSR-57 285, 300 Irasalu SSR-65 235, 250 Khader SSR-88 225, 240 SSR-89 130, 140 Kesar SSR-89 120, 140 Peter SSR-16 150, 170 Laddu Pasand SSR-85 250, 265, 310 SSR-84 225, 230, 245 Pulihora SSR-85 265 Alphonso SSR-18 130 SSR-87 160, 170, 195 SSR-19 150, 200 Table type MngSSR-24 110, 130, 150, 180 Himayat SSR-15 215, 245 SSR-64 300, 310 SSR-46 185, 200 Delhipasand SSR-19 135, 150 SSR-59 165 SSR-46 150, 200 Imampasand SSR-84 245 SSR-82 110, 130, 150, 180 SSR-86 190, 215 SSR-85 300, 310 Bangalora SSR-46 210 Pandurivarimamidi SSR-20 270, 300, 310 SSR-57 275, 285 SSR-82 150, 180 SSR-81 100 Shakkaragola SSR-46 185, 210 Neelum SSR-20 290, 300 SSR-52 100, 200 SSR-46 150, 200 SSR-88 250 MngSSR-27 195

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Panakalu SSR-46 165, 200, 210 SSR-59 165, 185 SSR-82 130 SSR-82 110, 130, 160, 180 SSR-84 230, 245, 265 SSR-85 275, 300 SSR-46 165,185,200 Pickle type Dashehari SSR-81 100, 120 Kumkum SSR-19 140, 150 SSR-83 200 SSR-46 150, 185, 210 SSR-89 110, 120, 130 SSR-81 100, 125 Amrutham MngSSR-26 130, 140 SSR-82 110, 130, 150, 160 SSR-84 215, 255, 265 SSR-88 215, 240, 250 SSR-85 250, 265, 275 SSR-88 225, 250

1a: Lane 1-42

1b: Lane 43-90

Fig.1. Amplification gel profiles of 90 mango cultivars using SSR-82 primer. M: Molecular weight marker (50 base pair DNA ladder in left, centre and right)

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Fig. 2. UPGMA dendrogram of 90 cultivars of mango constructed by cluster anallysis of SSR markers.

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Table S1. Quantitative fruit traits of 90 cultivars of mango in Andhra Pradesh. Fruit Fruit Fruit Fruit Length Peel Pulp Stone TSS Shelf life Cultivar length width thickness weight of fiber (%) (%) (%) (°Brix) (Days) (cm) (cm) (cm) (g) (mm) (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) Peddarasam 14.00 8.00 7.00 430.00 40.00 14.00 65.00 21.00 18.50 5 Cherukurasam 11.50 8.00 6.00 280.00 25.00 21.40 60.70 17.90 17.00 6 Chinnarasam 12.00 6.20 6.80 380.00 30.00 18.40 60.50 15.80 17.40 6 Panchadarakalasa 8.30 5.80 5.50 190.00 10.00 21.10 63.10 15.80 18.00 6 Tellarasam 12.00 8.00 7.00 380.00 41.00 10.00 75.50 14.50 16.30 6 Sinduri 11.00 6.50 7.00 284.00 15.00 17.60 68.60 13.80 13.40 6 Amrutham 8.20 5.10 5.80 220.00 17.00 18.20 70.90 10.90 15.00 5 Delhipasand 12.00 7.00 7.00 360.00 10.00 25.00 61.10 13.90 17.00 6 Reddipasand 10.70 7.00 8.50 420.00 20.00 21.40 66.20 12.40 14.20 5 Doodpeda 7.00 5.00 5.00 170.00 45.00 23.50 54.10 22.40 16.00 6 Shakargola 6.00 5.20 4.70 110.00 5.00 32.70 47.30 20.00 19.00 5 Natupalli 12.50 6.50 5.80 246.00 60.00 32.50 47.20 20.30 17.00 6 Nadusalai 9.70 5.20 5.30 188.00 35.00 31.90 46.80 21.30 12.00 6 Moolky 7.50 5.80 6.00 212.00 45.00 23.60 60.40 16.00 18.50 6 Panakalu 8.50 7.00 6.50 186.00 20.00 26.90 54.30 18.80 16.00 7 Nagulpalli Irsala 11.50 6.20 6.00 300.00 15.00 28.70 54.70 16.60 14.50 5 Peter 7.20 6.00 5.50 260.00 7.00 19.20 70.00 11.00 15.00 7 Pulihora 6.20 5.50 5.00 140.00 10.00 28.60 50.00 21.40 18.00 6 Dashehari 8.50 4.20 4.00 130.00 35.00 15.40 66.90 17.70 18.00 6 Vikarabad 7.30 6.80 7.00 344.00 10.00 10.00 75.50 14.50 11.20 6 Laddupasand 10.30 7.50 6.50 300.00 10.00 21.30 58.70 20.00 14.80 7 Lalbahar 8.00 7.00 5.70 142.00 17.00 21.10 56.40 22.50 18.00 6 Kesar 9.20 5.30 5.00 168.00 20.00 17.80 64.30 17.90 20.60 8 Dondakayalamamidi 11.20 4.40 4.60 156.00 13.00 25.50 48.80 25.70 19.60 7 Panukulamamidi 8.20 5.60 6.00 250.00 30.00 14.40 64.00 21.60 20.40 6 Goa 8.20 6.00 6.30 244.00 8.00 24.60 67.20 8.00 20.00 7 Pandurivarimamidi 7.20 5.70 5.50 146.00 35.00 16.60 54.70 28.70 23.00 7 Nawabpasand 9.50 6.20 6.80 308.00 15.00 26.00 61.00 13.00 13.60 5 Rumani 7.00 7.00 7.50 300.00 25.00 25.00 65.00 10.00 15.00 4 Khader 8.50 6.50 6.50 280.00 15.00 17.80 75.00 7.10 21.00 5 Kumkum 9.20 6.00 5.00 168.00 25.00 26.70 51.70 21.60 15.00 9 Phirangiladwa 10.50 7.80 7.30 420.00 18.00 23.80 61.90 14.30 15.00 6 Beneshan 11.00 7.50 8.00 460.00 10.00 21.70 67.50 10.80 19.00 7 Bangalora 16.80 7.80 7.00 572.00 12.00 21.00 66.00 13.00 18.00 6 Tiyyamamidi 7.80 8.00 6.70 212.00 8.00 13.20 75.50 11.30 14.00 7 Imampasand 13.20 8.30 8.80 761.00 9.00 19.70 71.10 9.20 18.50 7 Sora 16.50 9.70 9.00 844.00 20.00 21.40 66.80 11.80 10.40 6 Alphonso 9.00 7.00 6.50 220.00 7.00 16.30 70.10 13.60 16.00 6 Neelum 10.00 7.00 6.50 320.00 15.00 37.50 50.00 12.50 19.00 6 Abbasi 12.70 8.50 8.00 510.00 20.00 25.50 62.70 11.80 18.00 4 Safeddamini 14.00 8.50 8.20 615.00 15.00 32.60 59.30 8.10 17.60 7 Govander 8.00 6.50 7.00 270.00 10.00 10.00 72.00 11.10 18.00 5

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Chukla 10.20 5.50 5.20 200.00 5.00 30.00 53.00 17.00 21.60 7 Hublee 10.50 8.00 7.50 390.00 10.00 25.70 66.10 8.20 16.20 8 Jahangir 12.50 7.50 8.00 526.00 10.00 32.40 56.20 11.40 18.00 7 Amrigola 5.40 3.70 3.00 50.00 4.00 20.00 48.00 32.00 8.00 7 Janardhanpasand 9.20 6.00 6.00 216.00 8.00 23.20 58.30 18.50 11.00 6 Zardalu 13.20 7.60 8.20 496.00 15.00 18.00 62.00 10.10 20.00 8 Jalalu 14.20 8.20 6.40 428.00 10.00 16.50 74.20 9.30 13.00 7 Tellagulabi 7.70 7.00 7.00 270.00 15.00 25.90 66.70 7.40 15.00 6 Chinnaachaar 8.50 5.00 5.80 180.00 40.00 18.30 65.00 16.70 13.00 6 Peddaachaar 11.80 6.50 6.40 294.00 10.00 17.10 68.00 14.90 12.60 6 Punasabaramasi 11.80 6.50 6.00 280.00 15.00 21.50 57.10 21.40 11.20 7 Royalspecial 6.50 7.00 7.00 185.00 22.00 32.40 56.80 10.80 13.80 6 Himayat 13.00 8.00 7.00 460.00 12.00 20.00 61.00 10.90 19.00 7 Suvarnarekha 10.00 7.00 6.50 330.00 17.00 15.20 72.70 18.00 16.00 7 ChinnaS.rekha 10.20 6.50 5.50 250.00 25.00 20.00 64.00 16.00 14.00 7 Mylapurpunasa 7.20 4.20 4.00 94.00 11.00 21.40 62.70 15.90 11.00 4 Aryavarth Irasala 10.50 8.00 7.50 305.00 13.00 16.30 66.60 17.10 20.00 5 Panchavarnam 7.80 6.50 5.50 318.00 11.00 15.70 65.40 18.90 18.50 5 LazzatBux 6.20 4.10 3.10 120.00 13.00 17.50 65.00 17.50 13.60 8 Kothapallikobbari 10.00 5.50 6.00 306.00 30.00 14.70 65.70 19.60 18.00 6 Kanthavarapadu 8.80 5.10 4.50 150.00 25.00 23.30 56.70 20.00 10.00 6 Nuzivedurasalu 9.50 6.50 6.00 230.00 35.00 15.30 63.00 21.70 18.00 5 Desavali 7.00 6.50 5.00 130.00 20.00 15.50 69.20 15.30 13.40 3 Paparaoguava 10.40 8.80 6.80 320.00 9.00 21.90 58.30 19.80 19.00 6 Kolankagova 9.30 6.80 5.80 306.00 9.00 20.90 69.30 9.80 18.60 6 kobbariantu 8.30 6.10 6.60 180.00 10.00 22.20 55.60 22.20 17.20 6 Kalamamidi 7.10 4.00 4.00 120.00 10.00 16.70 66.60 16.70 13.00 6 Patikarasalu 10.50 7.00 5.50 318.00 20.00 22.00 60.70 17.30 17.80 5 Nallayendrasulu 9.10 7.00 5.00 207.00 21.00 20.30 62.80 16.90 10.00 5 Mukkurasalu 9.50 7.50 7.00 270.00 17.00 19.30 62.20 18.50 15.00 3 Mettavalasapeechumanu 6.50 5.00 5.00 102.00 15.50 19.70 62.70 17.60 14.50 6 Chotaamrutham 7.00 6.00 5.00 130.00 13.00 19.40 57.60 23.00 16.00 5 Bobbilipeechumanu 7.40 5.50 4.90 110.00 10.00 18.20 63.60 18.20 21.20 5 Kinthalooripeta 8.00 7.00 6.50 180.00 12.00 16.70 61.10 22.20 14.00 5 Sannarasalu 10.00 6.20 5.80 192.00 20.00 18.30 60.90 20.80 15.00 5 Erraarati 12.00 6.00 5.00 232.00 30.00 21.60 57.80 20.60 17.30 5 Kobbarimamidi 9.40 5.90 5.50 198.00 14.00 20.30 54.50 25.20 19.20 6 Punasa 6.80 7.10 7.30 200.00 23.00 30.00 57.50 12.50 15.60 5 Navaneetham 8.50 7.00 6.50 190.00 9.00 26.30 60.50 13.20 20.60 5 Chitoor Rasalu 6.00 7.00 6.00 180.00 18.00 19.60 63.80 16.60 14.60 6 Mallepalli Beneshan 11.80 6.90 5.80 288.00 5.00 14.00 67.30 18.70 18.00 6 Alampur Beneshan 10.80 8.60 8.00 342.00 7.00 20.00 68.40 11.60 18.00 6 Veeraballi Beneshan 12.00 8.50 7.50 470.00 5.00 8.90 60.30 20.80 16.00 6 Rati Banginapalli 8.00 6.80 7.00 214.00 5.00 18.80 57.00 24.20 12.00 5 Hydersahib 9.00 6.80 6.70 230.00 35.00 29.50 54.80 15.70 18.40 5 Mulgoa 9.40 8.60 7.80 360.00 13.00 24.50 61.70 13.80 22.80 5

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Natlu 10.50 7.50 6.20 340.00 20.00 20.70 58.80 20.50 18.10 7 Palli 12.70 5.80 5.50 258.00 8.00 19.50 64.30 16.20 21.20 4

Table S2. Qualitative fruit traits of 90 cultivars of mango in Andhra Pradesh Adheren Color of skin Skin Skin Quantity ce of Stalk Fruit shape Pulp color Cultivar of mature fruit thickness texture of fiber skin to insertion pulp (1) (2) (3) (4) (5) (6) (7) (8) Peddarasam Oblong Yellowish Green Thin Smooth Abundant Dark Yellow Present Vertical Cherukurasam Oblong Yellowish Green Medium Smooth Abundant Dark Yellow Present Oblique Oblong Chinnarasam Yellowish Green Thin Smooth Abundant Yellow Present Vertical reniform Panchadarakalasa Ovate Greenish Yellow Thin Smooth Abundant Yellow Absent Oblique Tellarasam Oblong Yellow Thin Smooth Abundant Light Yellow Present Vertical Red blush over Sinduri Oblong Medium Smooth Abundant Dark Yellow Present Vertical shoulders Orange Amrutham Oblong oval Light Yellow Thin Smooth Abundant Present Vertical Yellow Oblong Delhipasand Yellowish Green Medium Smooth Abundant Light Yellow Present Vertical reniform Ovate Reddipasand Green Thick Smooth Abundant Dark Yellow Present Oblique reniform Red blush over Doodpeda Round oblique Medium Smooth Abundant Light Yellow Present Vertical shoulders Shakargola Ovate Greenish Yellow Thick Smooth Abundant Yellow Present Vertical Natupalli Oblong Greenish Yellow Medium Smooth Abundant Yellow Present Vertical Nadusalai Oblong Green Thin Smooth Abundant Yellow Present Vertical Orange Moolky Ovate oblong Yellowish Green Thick Smooth Abundant Present Vertical Yellow Panakalu Ovate oblique Greenish Yellow Medium Smooth Abundant Dark Yellow Present Vertical Nagulpalli Irsala Oblong Green Thick Smooth Abundant Yellow Present Vertical Peter Ovate Greenish Yellow Medium Smooth Abundant Orange Present Vertical Golden Pulihora Ovate Red blemish green Medium Smooth Abundant Present Vertical Yellow Dashehari Oblong Green Thin Smooth Abundant Yellow Present Oblique Vikarabad oval round Greenish Yellow Thick Smooth Abundant Light Yellow Present Vertical Laddupasand Oblong oval Green Thin Smooth Abundant Dark Yellow Present Oblique Orange Lalbahar Ovate Red Thin Smooth Scarce Present Vertical Yellow Golden Kesar Oblong Greenish Yellow Thin Smooth Abundant Present Vertical Yellow Dondakayalamami Oblong Green Thin Smooth Abundant Yellow Present Vertical di Panukulamamidi Ovate oblong Yellow with dots Medium Smooth Abundant Yellow Present Vertical Goa Ovate oblong Greenish Yellow Medium Smooth Abundant Yellow Present Oblique Pandurivarimamid Ovate oblong Green with white dots Thin Smooth Abundant Light Yellow Present Oblique i Nawabpasand Ovate oblong Yellow Medium Smooth Scarce Yellow Present Vertical Rumani Round Yellowish Green Medium Smooth Scarce Light Yellow Present Vertical Golden Khader Oblong ovateYellow Thin Smooth Scarce Present Oblique Yellow Kumkum Oblong oval Red blush over yellow Medium Smooth Abundant Yellow Present Vertical Phirangiladwa Oblong oval Green with dots Medium Smooth Abundant Yellow Present Vertical Beneshan Ovate oblong Golden yellow Medium Smooth Scarce Yellow Present Oblique Bangalora Oblong ellicticYellow Thick Smooth Scarce Yellow Present Vertical

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Tiyyamamidi Round Yellowish Green Thin Smooth Abundant Yellow Present Vertical Ovate Imampasand Yellowish Green Thin Smooth Scarce Yellow Present Vertical Reniform Oblong Sora Yellowish Green Thick Smooth Scarce Light Yellow Absent Vertical oblique Alphonso Ovate Yellow Medium Smooth Scarce Yellow Absent Oblique Neelum Oblong oval Greenish Yellow Thick Smooth Scarce Yellow Absent Oblique Ovate Red blush over Abbasi Thick Smooth Scarce Yellow Present Vertical reniform yellowish green Golden Safeddamini Oblong oval Golden yellow Thick Smooth Scarce Present Vertical Yellow Ovate Red blush over Govander Thick Smooth Abundant Dark Yellow Present Vertical roundish yellowish green Chukla Oblong Greenish Yellow Thick Rough Abundant Yellow Present Oblique Hublee Oblong oval Greenish Yellow Thin Smooth Abundant Yellow Absent Vertical Jahangir Ovate oblong Yellowish Green Thick Smooth Abundant Light Yellow Present Vertical Amrigola Round Greenish Yellow Medium Smooth Abundant Yellow Present Vertical Janardhanpasand Oblong Red blush with yellow Medium Smooth Scarce Light Yellow Present Vertical Zardalu Oblong oval Yellow Thin Smooth Abundant Yellow Absent Vertical Oblong Jalalu Greenish Yellow Thick Smooth Abundant Light Yellow Present Oblique reniform Golden Tellagulabi Round Yellow Thick Smooth Abundant Present Vertical Yellow Chinnaachaar Oblong oval Yellow Thin Smooth Abundant Yellow Present Oblique Peddaachaar Oblong Green Medium Smooth Scarce Light Yellow Present Oblique Punasabaramasi Oblong Green Medium Smooth Abundant Yellow Present Vertical Royalspecial Round Yellowish Green Thick Smooth Abundant Light Yellow Present Vertical Oblong Himayat Yellow Thick Smooth Scarce Light Yellow Present Oblique oblique Suvarnarekha Oblique oval Yellow Thin Smooth Abundant Yellow Absent Vertical ChinnaS.rekha Oblong oval Red blush over green Thin Smooth Abundant Yellow Present Vertical Golden Mylapurpunasa Round Green Thick Smooth Scarce Present Vertical Yellow Aryavarth Irasala Oblong Greenish Yellow Very thick Rough Abundant Light Yellow Present Oblique Panchavarnam Round Yellow Medium Smooth Scarce Light Yellow Present Vertical LazzatBux Elliptic Greenish Yellow Medium Smooth Scarce Yellow Present Oblique Kothapallikobbari Oblique oval Yellow Medium Smooth Abundant Yellow Present Vertical Kanthavarapadu Round Lemon Yellow Medium Smooth Abundant Light Yellow Present Oblique Nuzivedurasalu Oblong Yellow Thin Smooth Abundant Yellow Present Oblique Desavali Round Yellow Thin Smooth Scarce Light Yellow Present Oblique Paparaoguava Oblong Yellow Medium Smooth Abundant Yellow Present Vertical Kolankagova Oblong Greenish Yellow Medium Smooth Abundant Yellow Present Vertical Golden kobbariantu Round Golden Yellow Medium Smooth Scarce Present Vertical Yellow Kalamamidi Elliptic Golden Yellow Medium Smooth Abundant Yellow Present Vertical Patikarasalu Oblong Golden Yellow Medium Smooth Abundant Light Yellow Absent Vertical Nallayendrasulu Round Yellowish Green Thin Smooth Abundant Dark Yellow Present Oblique Oblique Mukkurasalu Yellow Medium Smooth Abundant Yellow Present Vertical oblong Mettavalasapeech Round Green Medium Smooth Abundant Yellow Present Vertical umanu Chotaamrutham Round Yellow Thin Smooth Scarce Light Yellow Present Vertical Bobbilipeechuman Round Deep Yellow Medium Smooth Abundant Yellow Present Vertical u Kinthalooripeta Round Greenish Yellow Thin Smooth Abundant Yellow Present Vertical Sannarasalu Oblong Yellow Thin Smooth Abundant Yellow Present Vertical Erraarati Oblong Golden Yellow Medium Smooth Abundant Light Yellow Present Vertical

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Kobbarimamidi Elliptic Yellowish Green Thin Smooth Abundant Yellow Present Vertical Punasa Round Yellowish Green Thick Smooth Abundant Yellow Present Vertical Navaneetham Oblong Yellowish Green Thin Smooth Abundant Dark Yellow Present Oblique Chitoor Rasalu Oblong Yellow Medium Smooth Abundant Yellow Present Vertical Mallepalli Oblique oval Golden Yellow Thin Smooth Abundant Yellow Present Oblique Beneshan Alampur Elliptic Yellowish Green Thin Smooth Scarce Yellow Present Oblique Beneshan Veeraballi Oblong oval Yellowish Green Thin Smooth Abundant Yellow Absent Oblique Beneshan Rati Banginapalli Oblong Yellow Thin Smooth Scarce Yellow Present Oblique Hydersahib Oblong Greenish Yellow Thin Smooth Abundant Yellow Absent Oblique Mulgoa Round Greenish Yellow Very thick Smooth Abundant Yellow Present Vertical Natlu Ovate oblique Reddish Yellow Thick Smooth Abundant Light Yellow Present Vertical Palli Oblong Golden Yellow Medium Smooth Abundant Dark Yellow Present Oblique Ventral higher Ending in a Peddarasam Absent Pointed shallow Round Excellent Juicy than dorsal long curve Ventral higher Rising and Cherukurasam Absent Pointed shallow Round Excellent Juicy than dorsal then rounded Dorsal higher Ending in a Chinnarasam Absent prominent Absent Round Excellent Juicy than ventral long curve ventral higher Rising and Panchadarakalasa Absent Absent Absent Round Good Juicy than dorsal then rounded Dorsal higher Rising and Tellarasam Present Pointed Absent Round Excellent Juicy than ventral then rounded Dorsal higher Ending in a Sinduri Absent Absent shallow Round Good Juicy than ventral long curve Ventral higher Rising and Amrutham Present prominent shallow Acute Excellent Juicy than dorsal then rounded Ending in a Delhipasand Absent Pointed deep Level Round Excellent Juicy long curve Ventral higher Rising and Reddipasand Absent Pointed deep Round Good Juicy than dorsal then rounded Ventral higher Rising and Doodpeda Present Absent shallow Round Good Juicy than dorsal then rounded Ventral higher Rising and Shakargola Present Pointed Absent Round Average Juicy than dorsal then rounded Ventral higher Ending in a Juicy/Pic Natupalli Absent Pointed Absent Round Good than dorsal long curve kle Ventral higher Rising and Nadusalai Absent Pointed Absent Round Poor Juicy than dorsal then rounded Ventral higher Ending in a Moolky Absent Absent Absent Round Good Juicy than dorsal long curve Ventral higher Rising and Panakalu Present Pointed Absent Round Excellent Juicy than dorsal then rounded Ventral higher Ending in a Nagulpalli Irsala Absent Absent Absent Round Good Juicy than dorsal long curve Ventral higher Rising and Peter Absent Pointed shallow Round Good Juicy than dorsal then rounded Ventral higher Ending in a Pulihora Absent Pointed Absent Round Good Juicy than dorsal long curve Ventral higher Rising and Dashehari Absent Pointed Absent Round Good Juicy than dorsal then rounded Ventral higher Rising and Vikarabad Present Absent Absent Round Good Juicy than dorsal then rounded Ventral higher Ending in a Laddupasand Absent Pointed shallow Round Excellent Juicy than dorsal long curve

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Ventral higher Rising and Lalbahar Absent Pointed Absent Round Excellent Juicy than dorsal then rounded Ventral higher Ending in a Kesar Absent Pointed Absent Round Excellent Juicy than dorsal long curve Dondakayalamami Ventral higher Ending in a Absent Pointed deep Round Good Juicy di than dorsal long curve Ventral higher Rising and Panukulamamidi Present Absent shallow Round Good Juicy than dorsal then rounded Ventral higher Rising and Goa Present Pointed shallow Round Good Juicy than dorsal then rounded Pandurivarimamid Ventral higher Ending in a Absent Absent Absent Round Excellent Juicy i than dorsal long curve Ventral higher Rising and Juicy/Ta Nawabpasand Present Absent Absent Round Excellent than dorsal then rounded ble Rising and Juicy/Ta Rumani Present Pointed Absent level Round Good then rounded ble Ventral higher Rising and Juicy/Ta Khader Present Absent Absent Round Excellent than dorsal then rounded ble Ending in a Kumkum Absent Absent Absent Level Round Good Pickle long curve Ventral higher Rising and Intermed Phirangiladwa Present Absent Shallow Round Juicy than dorsal then rounded iate Ventral higher Rising and Beneshan Present Absent Shallow Round Excellent Table than dorsal then rounded Ventral higher Rising and Bangalora Absent Pointed Shallow Round Good Table than dorsal then rounded Rising and Tiyyamamidi Present Absent Absent Level Round Good Table then rounded Ventral higher Ending in a Imampasand Present Prominent Absent Round Good Table than dorsal long curve Ventral higher Ending in a Sora Absent Absent Shallow Round Poor Table than dorsal long curve Ventral higher Rising and Juicy/Ta Alphonso Absent Absent Shallow Round Good than dorsal then rounded ble Ventral higher Rising and Neelum Absent Absent Absent Round Excellent Table than dorsal then rounded Ventral higher Ending in a Abbasi Present Pointed Shallow Acute Good Table than dorsal long curve Dorsal higher Rising and Safeddamini Absent Pointed Absent Acute Good Table than ventral then rounded Ventral higher Rising and Govander Present Pointed Shallow Round Good Table than dorsal then rounded Dorsal higher Ending in a Chukla Absent Pointed Shallow Round Excellent Table than ventral long curve Rising and Hublee Present Prominent Deep Level Round Excellent Table then rounded Ventral higher Ending in a Intermed Jahangir Absent Pointed Absent Round Table than dorsal long curve iate Ventral higher Sloping and Amrigola Absent Absent Absent Round Poor Juicy than dorsal abrupting Ventral higher Ending in a Janardhanpasand Absent Pointed Absent Round Poor Table than dorsal long curve Ventral higher Ending in a Zardalu Absent Absent Shallow Round Good Table than dorsal long curve Ventral higher Rising and Jalalu Present Absent Shallow Round Poor Pickle than dorsal then rounded Tellagulabi Present Pointed Absent Level Rising and Round IntermedPickle

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then rounded iate Ventral higher Ending in a Chinnaachaar Absent Pointed Shallow Round Good Pickle than dorsal long curve Ventral higher Ending in a Intermed Peddaachaar Absent Absent Shallow Round Pickle than dorsal long curve iate Ventral higher Rising and Intermed Punasabaramasi Absent Pointed Shallow Round Pickle than dorsal then rounded iate Ventral higher Ending in a Royalspecial Absent Absent Absent Acute Poor Pickle than dorsal long curve Ventral higher Rising and Table/Jui Himayat Present Absent Absent Acute Excellent than dorsal then rounded cy Dorsal higher Table/Pic Suvarnarekha Absent Pointed Absent Absent Round Excellent than ventral kle Chinna Ventral higher Ending in a Absent Pointed Shallow Round Good Table Suvarnarekha than dorsal long curve Dorsal higher Ending in a Juicy/Pic Mylapurpunasa Absent Absent Absent Round Poor than ventral long curve kle Ending in a Aryavarth Irasala Absent Absent Shallow Level Abtuse Inter Juicy long curve Dorsal higher Ending in a Juicy/Ta Panchavarnam Absent Absent Absent Round Inter than ventral long curve ble Dorsal higher Rising and Intermed LazzatBux Absent Absent Shallow Rounded Juicy than ventral then rounded iate Dorsal higher Ending in a Kothapallikobbari Present Pointed Absent Rounded Good Juicy than ventral long curve Dorsal higher Ending in a Intermed Kanthavarapadu Absent Perceptible Shallow Rounded Juicy than ventral long curve iate Rising and Nuzivedurasalu Present Absent Shallow Level Rounded Good Juicy then rounded Slopping Desavali Absent Absent Absent Level Rounded Poor Table abruptly Rising and Paparaoguava Present Perceptible Absent Level Rounded Good Juicy then rounded Ending in a Intermed Kolankagova Absent Perceptible Shallow Level Rounded Juicy long curve iate Dorsal higher Ending in a Intermed kobbariantu Absent Absent Absent Rounded Juicy than ventral long curve iate Ending in a Kalamamidi Absent Absent Absent Level Rounded Poor Juicy long curve Ending in a Intermed Patikarasalu Absent Absent Shallow Level Rounded Juicy long curve iate Dorsal higher Ending in a Intermed Nallayendrasulu Absent Perceptible Shallow Acute Juicy than ventral long curve iate Slopping Mukkurasalu Absent Perceptible Absent Level Rounded Poor Juicy abruptly Mettavalasapeech Ending in a Absent Absent Shallow Level Rounded Poor Juicy umanu long curve Rising and Intermed Chotaamrutham Present Pointed Shallow Level Acute Juicy then rounded iate Bobbilipeechuman Rising and Intermed Present Perceptible Absent Level Rounded Juicy u then rounded iate Dorsal higher Ending in a Kinthalooripeta Absent Absent Absent Rounded Poor Juicy than ventral long curve Rising and Sannarasalu Absent Absent Shallow Level Rounded Poor Juicy then rounded Dorsal higher Ending in a Erraarati Absent Perceptible Deep Rounded Good Juicy than ventral long curve

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Dorsal higher Rising and Kobbarimamidi Absent Absent Absent Rounded Good Table than ventral then rounded Dorsal higher Ending in a Pickle/Ta Punasa Absent Perceptible Shallow Acute Poor than ventral long curve ble Ending in a Navaneetham Absent Absent Absent Level Rounded Good Juicy long curve Dorsal higher Rising and Intermed Chitoor Rasalu Absent Perceptible Shallow Rounded Juicy than ventral then rounded iate Mallepalli Dorsal higher Rising and Present Absent Absent Rounded Good Table Beneshan than ventral then rounded Alampur Dorsal higher Slopping Absent Perceptible Shallow Rounded Good Table Beneshan than ventral abruptly Veeraballi Dorsal higher Slopping Absent Absent Shallow Rounded Good Table Beneshan than ventral abruptly Ending in a Intermed Rati Banginapalli Absent Absent Absent Level Rounded Table long curve iate Ending in a Intermed Hydersahib Absent Perceptible Shallow Level Acute Juicy long curve iate Dorsal higher Rising and Mulgoa Absent Prominent Deep Rounded Good Table than ventral then rounded Rising and Juicy/Ta Natlu Absent Absent Shallow Level Rounded Excellent then rounded ble Rising and Palli Absent Absent Shallow Level Rounded Excellent Juicy then rounded

Table S3. List of microsatellite primers used in this study. Annealing Allele size Primer Sequence 5' to 3' temperature (°C) range (bp) SSR-1 F: TAACAGCTTTGCTTGCCTCC 57 191-207 R: TCCGCCGATAAACATCAGAC SSR-2 F: CCACGAATATCAACTGCTGCC 57 121-131 R: TCTGACACTGCTCTTCCACC SSR-3 F: AAACGAGGAAACAGAGCAC 50 90-111 R: CAAGTACCTGCTGCAACTAG SSR-4 F: AGGTCTTTTATCTTCGGCCC 55 199-203 R: AAACGAAAAAGCAGCCCA SSR-5 F: TGTAGTCTCTGTTTGCTTC 55 260-275 R:TTCTGTGTCGTCAAACTC SSR-6 F: CAACTTGGCAACATAGAC 51 174-182 R: ATACAGGAATCCAGCTTC SSR-7 F: AGAATAAAGGGGACACCAGAC 52 222 R: CCATCATCGCCCACTCAG SSR-8 F: TTGATGCAACTTTCTGCC 53 200-224 R: ATGTGATTGTTAGAATGAACTT SSR-9 F: CGAGGAAGAGGAAGATTATGAC 56 236-248 R:CGAATACCATCCAGCAAAATAC SSR-10 F: TGTGAAATGGAAGGTTGAG 52 220-235 R: ACAGCAATCGTTGCATTC SSR-11 F: GTTTTCATTCTCAAAATGTGTG 52 174-190 R: CTTTCATGTTCATAGATGCAA SSR-12 F: CTCGCATTTCTCGCAGTC 56 127-132 R: TCCCTCCATTTAACCCTCC SSR-13 F: GAACGAGAAATCGGGAAC 53 348-370 R: GCAGCCATTGAATACAGAG SSR-14 F: AACCCATCTAGCCAACCC 55 253-260 R: TTGACAGTTACCAAACCAGAC SSR-15 F: TTTACCAAGCTAGGGTCA 52 201-226

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R: CACTCTTAAACTATTCAACCA SSR-16 F: GCTTTATCCACATCAATATCC 54 160-170 R: TCCTACAATAACTTGCC SSR-17 F: TAAGCTAAAAAGGTTATAG 52 190 R: CCATAGGTGAATGTAGAGAG SSR-18 F: CGTCATCCTTTACAGCGAACT 56 100-115 R: CATCTTTGATCATCCGAAAC SSR-19 F: AATTATCCTATCCCTCGTATC 54 135-145 R: AGAAACATGATGTGAACC SSR-20 F: CGCTCTGTGAGAATCAAATGGT 58 295-310 R: GGACTCTTATTAGCCAATGGGATG SSR-21 F: GTGCGAGGAGATATCTGT 56 110 R: CTGGTTCTTCATTGTTGAGATG SSR-22 F: TGAGTTGTTGTCCTGCT 52 190-196 R: GGTGCTTGTTTCTCGT SSR-23 F: AAACAAAGAATGGAGCA 50 240-270 R: TGGACTGAATGTGGATAG SSR-24 F: GATGAAACCAAAGAAGTCA 53 310-318 R: CCAATAAGAACTCCAACC SSR-25 F: CTTGAAAGAGATTGAGATTG 53 200-212 R: AGAAGGCAGAAGGTTTAG SSR-26 F: GCCCTTGCATAAGTTG 52 170-182 R: TAAGTGATGCTGCTGGT SSR-27 F: TCTAAGGAGTTCTAAAATGC 52 158-180 R: CTCAAGTCCAACATACAATAC SSR-28 F: GACCCAACAAATCCAA 52 160 R: ACTGTGCAAACCAAAAG SSR-29 F: AAAGATAAGATTGGGAAGAG 52 156-170 R: CGTAAGAAGAGCAAAGGT SSR-30 F: TAGGGATATAGCTGGAGG 54 270-290 R: ACGCAGTAGAACCTGTG SSR-31 F: CAGCCTTATGTGTTGAAG 55 188-194 R: AAACTAAACAAGCTGAACC SSR-32 F: CTTCATTTCTCCACTTTTG 54 230-234 R: ATGAAATACTGGCTGGTT SSR-33 F: GCGTAAAGCTGTTGACTA 52 148-168 R: TCATCTCCCTCAGAACA SSR-34 F: GAGGAACATAAAGATGGTG 53 144-164 R: GACAAGATAAACAACTGGAA SSR-35 F: TAGCTGTTTTGGCCTT 53 230-240 R: ATGTGGTTTGTTGCTTC SSR-36 F: CCTCAATCTCACTCAACA 55 215-245 R: ACCCCACAATCAAACTAC SSR-37 F: GACTTGCAGTTTCCTTTT 50 148-176 R: TCAAGAACCCCATTTG SSR-38 F: CCATTCTCCATCCAAA 52 164-196 R: TGCATAGCAGAAAGAAGA SSR-39 F: TGTCTACCATCAAGTTCG 53 150-190 R: GCTGTTGTTGCTTTACTG SSR-40 F: ATTTTGATTCCCGTTCT 52 226-242 R: ATTCGATCATGGTTTTG SSR-41 F: ATCCCCAGTAGCTTTGT 53 210–244 R: TGAGAGTTGGCAGTGTT SSR-42 F: ACGGTTTGAAGGTTTTAC 50 165-170 R: ATCCAAGTTTCCTACTCCT SSR-43 F: AAGAGGGAATCTTAATCAAC 53 184–194 R: GTCGTTTTGCGTTAGTG

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SSR-44 F: GCGTGTCAATCTAGTGG 52 176-204 R: GCTTTGGTAAAAGGATAAG SSR-45 F: GCTCTTTCCTTGACCCT 52 174-194 R: TCAAAATCGTGTCATTTC SSR-46 F: TCATTGCTGTCCCTTTTC 54 154–210 R: ATCGCTCAAACAATCC SSR-47 F: GTATAAATCGCGTGCAT 50 232-234 R: AGTTTCCCTCCTTGTATCT SSR-48 F: TCGGTCATTTACACCCTCT 53 192-212 R: TTATTGAGCTTCTTTGTGTT SSR-49 F: ACCACGAAAAGACAACTC 53 252–268 R: TCATCTTTGTTAAATAGGTTAAT SSR-50 F: ATGGAGACTAGAATGTACAGAG 52 202 R: ATTAAATCTCGTCCACAAGT SSR-51 F: AAATAAGATGAAGCAACTAAAG 52 287 R: TTAGTGATTTTGTATGTTCTTG SSR-52 F: AAAAACCTTACATAAGTGAATC 52 207 R: CAGTTAACCTGTTACCTTTTT SSR-53 F: AGATTTAAAGCTCAAGAAAAA 52 241 R: AAAGACTAATGTGTTTCCTTC SSR-54 F: AGAATAAGCTGATACTCACAC 52 283 R: TAACAAATATCTAATTGACAGG SSR-55 F: ATATCTCAGGCTTCGAATGA 54 118 R: TATTAATTTTCACAGACTATGTTCA SSR-56 F: ATTTAACTCTTCAACTTTCAAC 51 212 R: AGATTTAGTTTTGATTATGGAG SSR-57 F: CATGGAGTTGTGATACCTAC 56 271 R: CAGAGTTAGCCATATAGAGTG SSR-58 F: TTGCAACTGATAACAAATATAG 52 185 R: TTCACATGACAGATATACACTT SSR-59 F: TTCTTTAGACTAAGAGCACATT 56 191 R: AGTTACAGATCTTCTCCAATT SSR-60 F: ATTATTTACCCTACAGAGTGC 52 244 R: GTATTATCGGTAATGTCTTCAT SSR-61 F: AAAGATAGCATTTAATTAAGGA 52 206 R: GTAAGTATCGCTGTTTGTTATT SSR-62 F: CACAGCTCAATAAACTCTATG 53 172 R: CATTATCCCTAATCTAATCATC SSR-63 F: ATTTTCCCTATAATGCCCTAT 54 170 R: CTCGGTTAACCTTTGACTAC SSR-64 F: AACTACTGTGGCTGACATAT 52 215 R: CTGATTAACATAATGACCATCT SSR-65 F: ATAGATTCATATCTTCTTGCAT 53 233 R: TATAAATTATCATCTTCACTGC SSR-66 F: TGCGTCTTGTGTGTGTGTGT 55 175 R: GGAATGCTGTGTGTGTGTG SSR-67 F: AGAAATGGTTGGTGGTGGTC 55 167 R: ACCGTGTGTGTGTGTGTGC SSR-68 F: GGTCAGCTGTGTGTGTGTG 56 158 R: CAATTCAATGCTTTGGATGCT SSR-69 F: TGTTCGATTTGCAAACTTTTT 55 299 R: GGCCTAATGTGTGTGTGTG SSR-70 F: TGGAAGGACCATGCTTGAAT 55 161 R: GGTCACACACACACACACA SSR-71 F: CGGCACACACACACACA 55 150 R: AAGGTCATTGGGTTCATTCC SSR-72 F: TGTCACACACACACACACA 56 163

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R: AATGGAAGGACCATGCTTGA SSR-73 F: CCTGAGAGAGAGAGAGAGA 55 176 R: GAGAGAGAGAGAGAGGTGG SSR-74 F: TGAAGGATAGGTGTGGTG 55 158 R: CATGAGAGAGAGAGAGAGA SSR-75 F: CACGAGAGAGAGAGAGAGA 55 187 R: GGGTCTCAGAGGGAGGATTT SSR-76 F: CATGAGAGAGAGAGAGAGAGA 55 153 R: AAAGG AJAAGGCAGGGAAATG SSR-77 F: GACAGACAAAGCCAGCAGAA 60 297 R: CCCGAGAGACAGAGAGAGAGA SSR-78 F: CCTTGGGTTCATTCGCTAAA 55 165 R: GGACGCCACACACACACAC SSR-79 F: TGGCGCTACACACACACAC 55 299 R: CACACACACACACACACACG SSR-80 F: TGGTATTCAAGCATGGTCCTC 57 244 R: TCCCATCACACACACACAC SSR-81 F: TCTCCCTTCATCGATTGTCC 55 122 R: GGAGCGTCTCTCTCTCTCCA SSR-82 F: TCTGACCCAACAAAGAACCA 57 108-155 R: TCCTCCTCGTCCTCATCATC SSR-83 F: AGCTATCGCCACAGCAAATC 57 190-213 R: GTCTTCTTCTGGCTGCCAAC SSR-84 F: TCTATAAGTGCCCCCTCACG 58 210-250 R: ACTGCCACCGTGGAAAGTAG SSR-85 F: GCTTGCTTCCAACTGAGACC 58 229-269 R: GCAAAATGCTCGGAGAAGAC SSR-86 F: CCCAGTTCCAACATCATCAG 55 156-193 R: TTCCTCTGGAAGAGGGAAGA SSR-87 F: GCCCCATCAATACGATTGTC 55 153-187 R: ATTTCCCACCATTGTCGTTG SSR-88 F: CTGAGTTTGGCAAGGGAGAG 55 222-244 R: TTGATCCTTCACCACCATCA SSR-89 F: CGCCGAGCCTATAACCTCTA 55 92-122 R: ATCATGCCCTAAACGACGAC SSR-90 F: TGATATTCAGGGCCCAAG 54 167-209 R: AAATGGCACAAGTGGGAAAG SSR-91 F: GCTCAACGAACCCAACTGAT 60 237-260 R: TCCAGCATTGAATGAAGAAGTT SSR-92 F: TCTGACGTCACCTCCTTTCA 55 148-193 R: ATACTCGTGCCTCGTCCTGT SSR-93 F: GCGAAAGAGGAGAGTGCAAG 55 130-165 R: TCTATAAGTGCCCCCTCACG SSR-94 F: CTAACCATTCGGCATCCTCT 55 111-194 R: TCTGTGATAGAATGGCAAAAGAA SSR-95 F: TTCTGTTAGTGGCGGTGTTG 57 207-230 R: CACCTCCTCCTCCTCCTCTT SSR-96 F: TGGTGGTGTTTGTTTGCAGT 55 175-196 R: ACCACCCGCAGTATTGAAAG MngSSR-2 F: AACAAATGACTGCGTGGTTG 58 190 R: CCATCATTAGGTGCTGTGCTT MngSSR-7 F: GAGTTTTCTGACTCACCTGCA 58 148 R: AGGCTTGAAGTGCTTTTGCT MngSSR-9 F: CTTCCCGAACCAAACATGAA 59 155 R: ATCACGACATTTTGGAATATG MngSSR-10 F: GTTGAACTTGTGAGCCTATC 58 164 R: GCAGGTTCAAACGAGAAC

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MngSSR-12 F: ACAATGAAATTGAACACCA 46 290-300 R: GATCAGACAGATAAGCTT MngSSR-14 F: TCATTAAGCTGTGGCAACCA 59 160-192 R: CATTGCATAGATGTGGTCATT MngSSR-18 F: ACCCAGGAATTGTCCAT 54 140-155 R: GGGATAAACCCAAGCTGA MngSSR-22 F: TTTCAGGATTGGAAGTTGCAG 62 140-158 R: ACCACACATCATGAGCAACC MngSSR-23 F: CGAACTGTTCTTGATGGTATCT 55 194 R: TGCAGTGGTTTGGTGAGTGT MngSSR-24 F: CGATGGACTTCATAAGAAGAG 58 150 R: GCTAGCAGAATCACCTTGGTC MngSSR-26 F: ACCTTGGTCAGGACAAAATCC 60 135-150 R: GACTTCATAAGAAGAGGCGTC MngSSR-27 F: CGAAACCGACTGCCTATTTT 57 158-172 R: CCATTAATAAAGTTGTGGCCA MngSSR-28 F: AGTTCTTCCTCTTCTTC 46 158 R: CTCTTGAAATGTCTGTC Source: eurofins mwg/operon (www.Eurofinsdna.com)

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Adato, A., Sharon, D., Lavi, U., Hillel, I., and Gazit, S. 1995. indica L.) in Andhra Pradesh, India. The Asian and Application of DNA fingerprints for identification and Australian Journal of Plant Science and Biotechnology, 6 genetic analysis of mango Mangifera indica genotypes. (1): 24-37. Journal of American Society of Horticultural Science, Bennett, M.D., and Leitch, I.J. 2004. Angiosperm DNA C- 120: 259-264. values Database (Release 4.0, Jan. 2003), (2003) http, Anju, B., Srivastava, R.S., and Chandra, R. 2008. Genetic //www.rbgkew.org.uk/cval/homepage.html (accessed July diversity and discrimination of mango accessions using 2004). RAPD and ISSR markers. Indian Journal of Horticulture, Bhargava, R., and Khorwal, R. 2011. Molecular 65: 377-382. Characterization of Mangifera indica by using RAPD Ascenso, J.C., Milheiro, A., Mota, M.I., and Cabral, M. 1981. marker. Indian Journal of Fundamental and Applied Life Selecao preliminar da Sciences, 1 (1): 47-49. mangueira. Pesquisa Agropecuaria Brasileira, 16: 417-429. Brettell, R., Coulson, M., and Gonzalez, A. 2002. Development Bajpai, A., Srivastava, N., Rajan, S., and Chandra, R. 2008. of DNA markers (ISSRs) in mango. Acta Horticulture, Genetic diversity and discrimination of mango accessions 575: 39-143. using RAPD and ISSR markers. Indian Journal of Campos, E.I., Espinosa, M.A.G., Warburton, M.L., Varela, Horticulture, 65: 377-82. A.S., and Villegas, A.M. 2005. Charaterisation of mandarin Bally, I.S.E., Graham, and Henery, R.J. 1996. Genetic diversity (Citrus spp.) using morphological and AFLP markers. of Kensington mango in Australia. Australian Journal of Intersciencia, 30: 687-693. Experimental Agriculture, 36 (2): 243-247. Chunwongse, J., Phumichai, C., Barbrasert, C., Chunwongse, Begum, H., Reddy, M.T., Malathi, S., Reddy, B.P., Arcahk, S., C., Sukonsawan, S., and Boonreungrawd, R. 2006. Nagaraju, J., and Siddiq, E.A. 2012. Molecular analysis for Molecular mapping of mango cultivars ‘Alphonso’ and genetic distinctiveness and relationships of indigenous ‘Palmar’. Acta Horticulture, 509: 193-206. landraces with popular cultivars of mango (Mangifera Damodaran, T., Medhi, R.P., Kapil, Dev, G., Damodaran, V.,

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Rai, R.B., and Kavino, M. 2007. Identification of molecular Hautea, D.M., Padlan, C.P., Rabara, R.P., and Coronel, R.F. markers linked with differential flowering behavior of 2001. Molecular characterization of Philippine ‘Carabao’ mangoes in Andaman and Nicobar Islands. Current mango using RAPD and AFLP markers. Asian Agriculture Science, 92: 1054-1056. Congress. Manilla (Philippines), 24-27 April. (2001). de Sousa, V.A., and Costa Lima, P. 2004. Genetic variability in Society for the Advancement of Breeding Researchers in mango genotypes detected by RAPD markers. Acta Asia and Oceania, Tokyo (Japan); Asian Crop Sci Horticulture, 645: 303-310. Association (Australia); Federation of Crop Sci Societies of Duval, M.E., Risterucci, A.M., Calabre, C., Le Bellec, F., the Philippines, College, Laguna (Philippines); Food Bunel, J,. and Sitbon, C. 2009. Genetic diversity of Security and Environment Protection in the New Caribbean mangoes (Mangifera indica L.) using Millenium. Manila (Philippines). microsatellite markers. Acta Horticulture, 820: 183-188. Hirano, R., Htun-Oo, T., and Watanabe, K.N. 2010. Myanmar Duval, M.F., Bunel, J., Sitbon, C., and Risterucci, A.M. 2005. mango landraces reveal genetic uniqueness over common Development of microsatellite markers for mango (Mangifera cultivars from Florida, India, and Southeast Asia. Genome, indica L.). Molecular Ecology Notes, 4: 824-826. 53: 321-330. Eiadthong, W., Yonemoni, K., Kanzaki, S., Sugiura, A., Honsho, C., Nishiyama, K., Eiadthong, S., and Yonemori, K. Utsunomiya, N., and Subhadrabandhu, S. 1999. 2004. Isolation and characterization of new microsatellites Identification of mango cultivars of Thailand and markers in mango (Mangifera indica). Molecular Ecology evaluation of their genetic variation using the amplified Notes, 5: 152-154. fragments by simple sequence repeat (SSR) anchored Hoogendijk, M., and Williams, D. 2001. Characterizing the primers. Scientia Horticulturae, 82: 57-66. genetic diversity of home garden crops, Some examples Eiadthong, W., Yonemori, K., Kanzai, S., Sugiura, A.S., from Americas. In Proceedings of the 2nd International Utsunomiya, N., and Subhadrabandhu, S. 2000. Amplified Home Gardens Workshop, 17-19 July 2001, fragment length polymorphism analysis for studying Witzenhausen, Federal Republic of Germany, 34-40. genetic relationships among Mangifera species in Thailand. Illoh, H.C., and Olorode, O. 1991. Numerical taxonomic Journal of American Society of Horticultural Science, studies of Nigerian mango varieties (Mangifera indica L.). 125: 160-164. Euphytica, 40: 197-205. Faleiro, F.G., Pinto, A.C.Q., Cordeiro, M.C.R., Andrade, IPGRI, 2006. Descriptors of Mango, International Plant S.R.M., Ramos, V.H.V., Bellon, G., and Dias, J.N. 2009. Genetic Resources Institute, Rome, Italy. Genetic variability of mango cultivars developed by Iyer, C.P.A., and Dinesh, M.R. 1997. Advances in classical Embrapa Cerrados breeding program using RAPD markers. breeding and genetics in mango. Acta Horticulture, 455: Acta Horticulture, 820: 177-182. 252-267. Galvez-Lopez, D., Hernandez-Delgado, S., Gonzalez-Paz, M., Jintanawong, S., Hiranpradit, H., Polprasid, P., and Becerra-Leor, E.N., Salvador-Figueroa, M. and Mayek- Duangpikul, P. 1992. Group characterization of Thai Perez, N. 2009. Genetic analysis of mango landraces from mango, Mangifera indica L. Acta Horticulture, 321: 254- Mexico based on molecular markers. Plant Genetic 261. Resources Characterization and Utilization, 7: 244-251. Karihaloo, J.L., Dwivedi, Y.K., Archak, S., and Gaikwad, A.B. Gonzalez, A., Coulson, M., and Brettel, R. 2002. Development 2003. Analysis of genetic diversity of Indian mango of DNA markers (ISSRs) in mango. Acta Horticulture, cultivars using RAPD markers. Journal of Horticultural 575: 139-143. Science and Biotechnology, 78: 285-289.

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cultivars of India using RAPD markers. Journal of Srivastava, A.P., Chandra, R., Saxena, S., Ranjan, S., Ranade, Horticultural Science and Biotechnology, 75 (2): 198-201. S., and Prasad, V. 2007. A PCR based assessment of Rohlf, F.J. 2000. NTSYS-pc Numerical taxonomy and genetic diversity and parentage analysis among commercial multivariate analysis system, version 2.1. Exeter Software, mango cultivars and hybrids. Journal of Horticultural Setauket, New York, USA. Science and Biotechnology, 82: 951-959. Samant, D., Singh, A.K., Srivastav, M., and Singh, N.K. 2010. Srivastava, N., Bajpai, A., Chandra, R., Rajan, S., Assessment of genetic diversity in mango using inter- Muthukumar, M., and Srivastava, M.K. 2012. Comparison simple sequence repeat markers. Indian Journal of of PCR based marker systems for genetic analysis in Horticulture, 67: 1-8. different cultivars of mango. Journal of Environment and Santos, C.A.F., Lima-Neto, F.P., Rodrigues, M.A. and Costa, Biology, 33: 159-166. J.G. 2008. Similaridade genetica de acessos de mangueira Steiner, J.J. and Greene S.L., 1996. Proposed ecological de diferentes origens geograficas avaliadas por marcadores descriptors and their utility for plant germplasm collections. AFLP. Review Brasilia Frutica, 30: 736-740. Crop Science, 36: 439-451. Schnell, R.J., Olano, C.T., Quintanilla, W.E., and Meerow, Struss, D., Boritzki, M., Glozer, K., and Southwick, S. 2001. A.W. 2005. Isolation and characterization of 15 Detection of genetic diversity among populations of sweet microsatellite loci from mango (Mangifera indica L.) and cherry (Prunus avium L.) by AFLPs. Journal of cross-species amplification in closely related taxa. Horticultural Science and Biotechnology, 76: 362-367. Molecular Ecology Notes, 5: 625-627. Subedi, A., Bajracharya, J., Joshi, B.K., Gupta, S.R., Regmi, Schnell, R.J., Ronning, C.M., and Knight, R.J. 2004. H.N., and Sthapit, B. 2009. Locating and managing the Identification of cultivars and validation of genetic mango (Mangifera indica L.) genetic resources in Nepal. relationship in Mangifera indica L. using RAPDs. PGR - News, FAO - Bioversity International, 115, 52-61. Theoretical and Applied Genetics, 90: 269-274. Subramanyam, M.D. and Iyer, C.P.A. 1989. Identification of Shi Sheng-you, Wu Hong-xia, Wang Song-biao, Liu Li-qin, dwarf genotypes for mango improvement. The 3rd Wang Yi-cheng, and Ma Wei-h, 2011. Genetic diversity of International Mango Symposium, Darwin, Australia, 16. mango germplasm based on morphological characters and Teo, L.L., Kiew, R., Set, O., Lee, S.K., and Gan, Y.Y. 2002. AFLP markers. Acta Horticulture Sinica, 38 (3): 449-456. Hybrid status of kuwini, Mangifera odorata Griff. Singh, L.B., 1969. Mango. In, Outlines of perennial crop (Anacardiaceae) verified by amplified fragment length breeding in the tropics, F.P. Ferwerda, and F. Wit (editors), polymorphism. Molecular Ecology, 11: 1465-1469. Veenman and Zonem, Wageningen, Netherlands, 309. Tomar, R.S., Gajera, H.P., Viradiya, R.R., Patel, S.V., and Singh, R.N., 1996. Mango. Indian Council of Agricultural Golakiya, B.A. 2011. Phylogenetic relationship among Research, New Delhi. Mango (Mangifera indica L.) Landraces of Saurashtra Singh, S. and Bhat K.V., 2009. Molecular characterization and based on DNA fingerprinting. Journal of Horticulture and analysis of geographical differentiation of Indian mango Forestry, 3 (13): 379-385. (Mangifera indica L.) germplasm. Acta Horticulture, 839: Vasugi, C., Dinesh, M.R., Sekar, K., Shivashankara, K.S., 599-606. Padmakar, B., and Ravishankar, K.V. 2012. Genetic Singh, S., Gaikwad, A.B., and Karihaloo, J.L. 2010. diversity in unique indigenous mango accessions Morphological and molecular analysis of intracultivar (Appemidi) of the Western Ghats for certain fruit variation in Indian mango (Mangifera indica L.) cultivars. characteristics. Current Science, 103(2): 199-207. Acta Horticulture, 29: 205-212. Viruel, M.A., Escribano, P., Babieri, M., Ferri, M., and

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اﻟﺗﻧوع اﻟوراﺛﻲ و اﻟﺷﻛﻠﻲ ﻷﺻﻧﺎف ﻧﺑﺎﺗﺎت اﻟﻣﺎﻧﺟو (.Mangifera indica L) اﻟﻣزروﻋﺔ ﺑﺎﺳﺗﺧدام اﻟواﺳﻣﺎت اﻟوراﺛﻳﺔ اﻟﺻﻐرﻳﺔ

ھميدونيسا بنجوم1، ميداجام ريدي1، سوراينيني ماالثي1، بوريدي ريدي1، جونيال نارشيمولو1،

جافا ريدوداناجاراجو2، إبراھيمالي ّصديق3

ﻣﻠﺧـص

أ ﺟ ري ﻣﺳﺢ ﻟﻠﺑﻳﺋﺔ اﻟﺟﻐراﻓﻳﺔ اﻟﺗﻲ ﺗﻐطﻲ ﺛﻼث ﻣﻧﺎطق ﺟﻐراﻓﻳﺔ (ﺳﺎﺣﻝ وﻻﻳﺔ اﻧدرا، ﺗﻳﻼﻧﺟﺎﻧﺎ وراﻳﺎﻻﺳﻳﻣﺎ) ﻣن وﻻﻳﺔ ا ﻧ د را ﺑرادﻳش ﻓﻲ اﻟﻬﻧد ﺧﻼﻝ ﺷ ﻬ ري ﻣﺎﻳو وﻳوﻧﻳو 2009 و ذﻟك ﻣن اﺟﻝ ﺗﺣدﻳد وﺗﺣﻠﻳﻝ وﺗﻘﻳﻳم اﻟوﺿﻊ اﻟﺣﺎﻟﻲ ﻟ ﻠ ﻣ وا رد اﻟوراﺛﻳﺔ ﻟﻧﺑﺎت اﻟﻣﺎﻧﺟو. وﻛﺷف اﻟﺗﺣﻠﻳﻝ اﻟﺷﻛﻠﻲ ﻟﻠﻧﺑﺎت و اﻟذي ﺗﺑﻌﻪ اﻟﺗﺣﻠﻳﻝ اﻹﺣﺻﺎﺋﻲ اﻟوﺻﻔﻲ ﺗﻔﺎوﺗﺎ ﻛﺑﻳرا ﺑﻳن 90 ﻣن أﺻﻧﺎف اﻟﻣﺎﻧﺟو وﻫو ﻣﺎ أﻛدﻩ اﻟﺗﺣﻠﻳﻝ اﻟﺟزﻳﺋﻲ ﻣﻊ 109 ﻣن ﻋﻳﻧﺎت اﻟﻣﺎﻧﺟو اﻟﺗﻲ ﺗم ﺗﺣﻠﻳﻠﻬﺎ ﺑﺎﺳﺗﺧدام اﻟواﺳﻣﺎت اﻟوراﺛﻳﺔ اﻟﺻﻐﻳرﻳﺔ SSRs. ﺗراوﺣت ﻗﻳم ﻣﻌﺎﻣﻝ ﺟ ﺎ ﻛ ﺎ رد (Jaccard) ﻟﻠﺗﺷﺎﺑﻪ ﺑﻳن 0.35 و 0.85 ﻣﻣﺎ ﻳدﻝ ﻋﻠﻰ اﺧﺗﻼف ﻣ ﻌ ﻧ وي ﺑﻧطﺎق واﺳﻊ (15-65٪) ﻣن اﻟ ﺗ ﻧ وع ﺿﻣن ا ﻟ ﻧ وع ﻋﻠﻰ ا ﻟ ﻣ ﺳ ﺗ وى اﻟﺟزﻳﺋﻲ ﻓﻲ اﻟﻣﺎﻧﺟو. و ﻗد ﺗم اﻟﺣﺻوﻝ ﻋﻠﻰ ﺷﻛﻝ اﻟدﻧدوﻏرام (dendrogram) ﺑﺎﺳﺗﺧدام ﺗطﺑﻳق طرﻳﻘﺔ ﻣﺟﻣوﻋﺔ ا ﻟ زوج ﻏﻳر اﻟﻣرﺟﺢ ﻣﻊ اﻟﺗﺣﻠﻳﻝ اﻟﺣﺳﺎﺑﻲ اﻟﻌﻧﻘودي ﻟﻣﺗوﺳط أرﺑﻊ ﻣﺟﻣوﻋﺎت ااﺻﻧﺎف وراﺛﻳﺔ ﺑﻳن اﻷﺻﻧﺎف اﻟﻣدروﺳﺔ. اﻟﻛﻠﻣـــﺎت اﻟداﻟـــﺔ: اﻟﻌﻼﻗـــﺔ اﻟوراﺛﻳـــﺔ، اﻟ ﺗ ﻧـ ـ وع ﺿـــﻣن ا ﻟ ﻧـ ـ وع ، أﺻـــﻧﺎف اﻟﻣـــﺎﻧﺟو، اﻟواﺳـــﻣﺎت اﻟوراﺛﻳـــﺔ اﻟﺻـــﻐرﻳﺔ، اﻟﺗوﺻـــﻳف اﻟﺟزﻳﺋـــﻲ، اﻟﺗوﺻﻳف اﻟﻔﺳﻳوﻟوﺟﻲ اﻟﺷﻛﻠﻲ.

1 . ﻣﺣطﺔ ﺑﺣوث اﻟﺧﺻراوات، ﺟﺎﻣﻌﺔ اﻟﺑﺳﺗﻧﺔ، ﺣﻳدر اﺑﺎد، اﻟﻬﻧد.  [email protected] 2 . ﻣرﻛز اﻟﺣﻣض ا ﻟ ﻧ ووي ﻟﻠﺑﻌﺛﺎت واﻟﺗﺣﻠﻳﻝ، ﺣﻳدر اﺑﺎد، اﻟﻬﻧد. 3 . ﻣﻌﻬد اﻟﺗﻛﻧوﻟوﺟﻳﺎ اﻟﺣﻳوﻳﺔ، ﺟﺎﻣﻌﺔ اﻟزراﻋﺔ، ﺣﻳدر اﺑﺎد، اﻟﻬﻧد. ﺗﺎرﻳﺦ اﺳﺗﻼم اﻟﺑﺣث 16/7/2013 وﺗﺎرﻳﺦ ﻗﺑوﻟﻪ 2015/12/29.

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