Indian Journal of Biotechnology Vol. 17, January 2018, pp 91-100

Morphological and microsatellite marker based polymorphic assessment of genetic diversity and relationship of ( indica L.) Lokesh Bora1*, Ashok Kumar Singh2, Anil Kumar3 and Mamta Metwal4

1,College of Agriculture, C/O Shri Bhim Singh Bora, H No 327, Awas Vikas Colony, P O Bhtiaparao, Haldwani, Uttarakhand, Distt, Nainital 263139 2Department of Horticulture, G. B. Pant University of Agriculture & Technology, Pantnagar, Uttarakhand 263145, Distt U S Nagar 3,4College of Basic Science & Humanities, Department of Molecular Biology & Genetic Engineering G. B. Pant University of Agriculture & Technology, Pantnagar, Uttarakhand 263145, India

Received 29 October 2015; revised 27 November 2015; accepted 7 December 2015

Genetic diversity of 19 genotypes of mango was characterized both by morphological and 20 simple sequence repeat (SSR) markers. Characterization of mango genotypes based on morphological and molecular basis is a better approach for designing breeding projects. On the basis of the present findings it was observed that “Sabri” and “” showed dwarf stature, while “Swarna Jahangir” was found to be vigorous in its growth. The unweighted pair group method of arithematic- average (UPGMA) dendrogram based on genetic distance segregated the 19 mango genotypes into two main clusters. The polymorphic information content (PIC) values ranged from 0.38 to 0.81. Jaccard’s similarity coefficient values ranged from 0.15 to 0.79 with polymorphism of 77.5 per cent. Three unique fingerprints were identified in three genotypes which can help in varietal identification. A total of 49 loci (42 polymorphic and 7 monomorphic) were detected with amplified size range of 110 to 359 bp. The maximum numbers of loci (i.e. 5) were detected by the primer MiSHRS-48. Out of 20 SSR primers, 18 were polymorphic. Pusa Surya was found to be the most diverse genotype both morphologically and genetically. The similarity for Pusa Surya was 15 per cent with remaining Indian genotypes. The significant variation exists among the genotypes based on morphological and biochemical characters but with the use of SSR markers, assessment of the genetic diversity can help us to plan a future breeding programme using the diverse parent.

Keywords: Microsatellite, morphological, genetic diversity, relatedness, hybrids, selections, mango

Introduction natural populations and among breeding lines is Mango has been reported to have extensive genetic crucial for effective conservation and exploitation of diversity due to allopolyploid, out breeding nature. those genetic resources for crop improvement Continuous grafting and phenotypic differences arises programmes. This helps in eliminating duplicate due to its cultivation under different growing regions accessions and in maintaining purity of the with varied agro-climatic conditions1. The cause for germplasm. Complex plant characters such as yield these problems is genetically related and to solve are quantitatively inherited and are influenced by them, genetic diversity is needed to be assessed2. genetic effect as well as genotype or environmental Genetic diversity amongst mango cultivars offers interaction. Open pollination, continuous grafting and various opportunities to utilize genomic resources and use of seeds for propagation, mutations and changing technologies in an effort to manipulate desirable environmental conditions may all contribute to the traits. India has been bestowed with the richest development of new traits in mango germplasm6. germplasm centre for cultivating mango. Mango Morphological study is an essential component for the originated in the Indo-Myanmar region3-4. The wild as assessment of diversity and classification. This is the well as cultivated forms of mango in India exhibit a simplest of the formal, standardized and repeatable wide diversity for bearing habits, fruit forms, flavours methods of evaluating crop genetic diversity. and tastes5, and of course the biochemical parameters Morphological characters have great role for the as a whole. Assessment of genetic variation within identification of different cultivars. It is the pre- —————— requisite step that should be done before more *Author for correspondence: profound biochemical or molecular studies are carried [email protected] 92 INDIAN J BIOTECHNOL, JANUARY 2018

out7. It also helps to study the plant variation using hybrids and 5 superior selections of mango. The visual attributes. Hence, systematic characterization, selected trees were 6 years old and were almost documentation and conservation of the varied gene uniform in growth and vigor and maintained under pool are highly essential for future exploitation. similar cultural operations. During the course of study, Morphological characterization is traditionally the the observations related to morphological characters most common method used and many different crops8 like tree height, spread and leaf characteristics were such as mango9-12, banana13 and citrus14 etc. But recorded in September after harvesting mango fruits. A morphological markers are tough to assess, correlate random sample of ten fully developed leaves from the and are always much prone to high degrees of error. middle of the tagged shoots from all the sides of the Markers put forward an efficient tool for cultivars tree was selected for the purpose of recording the data. finger printing, assessment of genetic resemblance The tree canopy volume was calculated as per formula 33 and relationships15 and provide the best estimation of devised by Westwood (1963) . genetic diversity as they are independent of the 3 16 Tree volume (m ) 4/3 h confusing effects of the environmental factors . We can detect them in all tissues and at all stages of Where, π = 3.14 development. Molecular markers are exercised in r = radius from average canopy diameter (m) different fields of genetics such as genetic mapping, h = distance from point of first branch on trunk to the genome organization, characterization and top of tree (m) identification of plant cultivars. They are very Total number of fruits tree-1 in each cultivar was appropriate means for the characterization of counted at the time of harvest. The observation on genotypes in the gene banks17. Use of molecular yield of individual cultivars was recorded and the markers is even more important for the perennial and yield was expressed in terms of kg tree-1. Yield recalcitrant crops, where progress in crop efficiency was calculated by dividing yield with tree improvement is frequently hindered by its long volume and expressed as kg m-3. 18-19 generation time . The term microsatellite was DNA Extraction and PCR Amplification 20 coined by Litt & Luty (1989) and it is also known as The method described by Porebeski et al (1997)34 simple sequence repeats (SSRs). These are sections of with slight modification was followed for extraction DNA, consisting of randomly repeating units of of genomic DNA and subsequently quantified and mono-, di-, tri-, tetra- or penta-nucleotide that are analysed via agarose gel electrophoresis. The task was arranged throughout the genomes of most eukaryotic performed in Biosafety and Molecular Diagnostics species. Microsatellite markers are developed from Laboratory of Department of Molecular Biology and genomic libraries, which belong to either the Genetic Engineering (MBGE), CBSH, GBPU A & T, transcribed region or the non-transcribed region of the Pantnagar. genome. In mango various authors have utilized the SSRs markers in order to study the genetic diversity Data Analysis in the genotypes21-32,55. Keeping the above facts in Morphological Data Analysis mind, the present investigation was conducted in Data were subjected to analysis of variance order to assess the variability among the promising (ANOVA) by using STPR3 GBPUAT, Pantnagar, hybrids and selections of mango genotypes based on India. Analysis of quantitative data (morphological) phenotypic traits complemented by molecular studies. for construction of phylogenetic tree was done using DARwin5 software; version 5.0.158 developed by Materials and Methods CIRAD, Research Unit Genetic Improvement of Vegetatively Propagated Crop35. Plant Material, Vegetative Parameters and Experimental Design The present investigation was carried out at Molecular Data Horticulture Research Centre (HRC), Pattharchatta, A total of 20 SSR primers pairs were used for the G. B. Pant University of Agriculture and Technology, polymorphism survey. The primers used in the study Pantnagar District, Udham Singh Nagar, Uttarakhand were obtained from IDT (Integrated DNA at an altitude of 29ºN latitude & 79.3º E longitude and Technologies, India) based on those reported by at 243.84 metres above mean sea level during the year Ravishankar et al (2011)32. PCR amplification was 2013-14. The experiment was carried out on 14 performed as per the standard protocol using 50–100 ng BORA et al: POLYMORPHIC ASSESSMENT OF GENETIC DIVERSITY AND RELATIONSHIP OF MANGO 93

of template DNA, 30 ng of primer (Life Tech, Delhi, for each SSR primers according to the formula given 2 2 India), 0.1 mM dNTPs, 1.5 U Taq DNA polymerase by Smith et al (1997): PIC = 1- ΣPi , Where Pi is the (Bangalore Genei, Bangalore, India), 1X PCR buffer frequency of the ith allele. Molecular data was (10 mM Tris pH 8.0, 50 mM KCl and interpreted using NTSYS, for generating UPGMA 1.8 mM MgCl2) in a volume of 25 μL. Amplification dendrogram. was performed with thermal cycler (Eppendorf, Hamburg, Germany). The standardized amplification Results and Discussion º was: initial denaturation 95 C for 5 min followed by Morphological Analysis º 40 cycles of denaturation 94 C for 1 min; primer The data pertaining to plant height and spread annealing based on melting temperature (Tm) value revealed significant differences among different for 1 min; primer extension at 72ºC for 2 min; and º cultivars of mango (Table 1). The plant height varied final primer extension at 72 C for 7 min. The from 1.32 to 3.42 m in of different cultivars of mango. annealing temperatures of the cycling parameter were The variation in growth characters amongst the mango readjusted for each microsatellite primer according to cultivars could be due to the variation in genetic make- its calculated T based on the sequence composition m up under the present set of environmental conditions (Table 4): and edaphic eco-geographical conditions37-39. º º º Tm = 4 (G + C) + 2 (A + T) − 3 C Trunk girth was found maximum in case of PCR amplified products were subjected to gel (36.67 cm) followed by Swarna Jahangir (30.33 cm) electrophoresis using 3% SFR Tm (Metaphor) in 0.5 X and Pant Sinduri (26.17 cm). The minimum trunk TBE buffer at 100 V. The fragment sizes, with a girth was recorded in Sabri (17.0 cm). Perusal of the 100 bp DNA ladder (Bangalore Genei, Bangalore, data regarding vegetative growth characteristics like India) and ethidium bromide stained gels were trunk girth and tree volume showed that cultivar documented using Alpha Imager 1200TM (Alpha (Langra, Swarna Jahangir, Pant Sinduri, Pusa Surya, Innotech, San Leandro, USA). Pusa Arunima, Mahmood Bahar and Dashehari appeared to be as vigorous and Sabri, Amrapali, Scoring of Gel and Analysis of Data Ratna, Arka Neelkiran, Arunika, Ambika and Boolean symbols were used for each genotype for Neeluddin seems to be dwarfer). Almost similar scoring as presence (1) or absence (0) for respective findings were also observed by several authors that allele against each primer. Unweighted pair group the cultivar Langra, Samar Bashist , , method with arithmetic average (UPGMA) based Dashehari and Neelum are vigorous40. The panicle dendrogram was generated to determine marker based length ranged from 15.94 to 34.50 cm and width genetic relationship amongst the 19 mango genotypes. varied from 9.71 to 17.12 cm in different genotypes of The data were analyzed using the NTSYS-pc software version 2.11W36. Data analysed were subjected to mango (Table 2). The cultivar Pant Sinduri and Pusa analysis of Jaccard coefficients among the isolates by Surya produced longer and shorter panicle, using NTSYS-pc version 2.11W. The SIMQUAL respectively. The variation in panicle size might be program was used to calculate the Jaccard’s due to genetic makeup of the particular cultivar. Environmental conditions may also contribute for coefficients. A common estimator of genetic identity 41-42 and was calculated as follows: difference in panicle size . The higher number of fruits per plant (81.30) was observed in Langra which Jaccard’s coefficient = NAB / (NAB + NA + NB) was statistically at par with Amrapali (75.7). The

variation in number of fruits per tree might be due to Where, NAB is the number of bands shared by samples, NA represents amplified fragments in sample the fruit size, leaf area and absorption and 43-44 A, and NB represents fragments in sample B. translocation of photosynthates . Maximum fruit -1 Similarity matrices based on these indices were yield was recorded in Langra (25.15 kg tree ) -1 calculated. Polymorphic information content (PIC) followed by Pusa Surya (13.64 kg tree ) and Mallika that provides an estimate of the discriminatory power (11.70 kg tree-1). The minimum yield per tree was of a locus or loci, by taking into account, not only the observed in cultivar Arka Neelkiran (3.03 kgtree-1) number of alleles that expressed, but also relative which was statistically at par with rest of the frequencies of those alleles, values were calculated remaining cultivars. The variation in fruit yield

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Table 1 — Vegetative growth characters of different genotypes of Mango ( L.) S. No. Name of Plant height Plant spread (m) Trunk girth Tree Leaf length Leaf Leaf area Petiole cultivars (m) E-W* N-S** (cm) volume (cm) breadth (cm2) length (m3) (cm) (cm) 1 Neeluddin 1.97 1.84 1.68 21.5 6.20 19.13 4.30 58.81 2.22 2 Neeleshan 2.04 1.76 1.72 19.83 6.34 22.68 4.82 77.75 2.68 3 Amrapali 1.45 1.65 1.65 20.17 4.56 18.03 5.02 64.58 2.40 4 Vanraj 1.9 2.08 2.07 22.83 6.37 19.94 4.86 68.74 2.39 5 Mallika 2.58 2.33 2.27 24.33 9.24 18.08 4.82 61.80 2.93 6 Pant Sinduri 3.16 2.36 2.82 26.17 11.50 19.61 5.76 80.55 3.05 7 Sabri 1.32 1.27 1.25 17.00 3.80 15.57 4.13 45.67 2.37 8 Mahmood 2.78 2.19 2.12 25.17 9.93 18.00 5.79 74.14 2.94 Bahar 9 Ratna 1.53 1.64 1.9 21.50 4.90 20.20 5.42 78.25 3.38 10 Dashehari 1.97 1.75 1.76 20.67 6.36 19.53 4.57 63.26 2.87 clone 11 Swarna 3.42 1.87 2.04 30.33 12.15 18.58 6.24 83.54 3.33 Jahangir 12 Neelgoa 1.98 1.54 1.88 20.83 6.83 19.83 4.70 66.44 2.35 13 Dashehari 1.93 2.28 2.57 23.17 6.68 18.84 4.82 64.72 2.74 14 Langra 3.41 3.28 3.63 36.67 12.91 19.62 5.46 77.33 3.33 15 Pusa 2.39 2.00 1.78 23.00 7.83 21.08 4.82 72.20 3.4 Arunima 1 Pusa Surya 2.19 2.15 2.23 22.17 7.59 16.65 4.60 54.64 2.55 17 Arka 1.67 1.62 1.62 21.33 5.23 18.43 4.59 60.69 3.32 Neelkiran 18 Ambika 2.04 1.95 1.93 21.17 7.18 18.93 6.07 82.03 2.55 19 Arunika 1.84 1.65 1.60 20.33 5.88 20.23 4.69 67.39 3.21 S.Em.± 0.19 0.20 0.23 2.04 0.87 0.20 0.09 1.80 - CD at 0.05% 0.56 0.59 0 .67 5.85 2.52 0.59 0.27 5.15 -

Table 2 — Inflorescence and reproductive characteristics of different genotypes of Mango (Mangifera indica L.) S. No. Name of cultivars Panicle size Total number of fruits tree-1 Yield Yield efficiency -1 -3 Panicle length Panicle width (at harvest) (kg tree ) (kg m ) (cm) (cm) 1 Neeluddin 27.02 16.21 20.7 3.85 0.68 2 Neeleshan 24.31 13.75 20.2 4.34 0.71 3 Amrapali 22.04 15.34 75.7 9.29 2.13 4 Vanraj 21.08 13.69 16.7 5.08 0.83 5 Mallika 25.85 12.65 34.8 11.7 1.24 6 Pant Sinduri 34.5 16.19 41.7 7.04 0.6 7 Sabri 15.94 11.46 26 4.76 1.37 8 Mahmood Bahar 20.94 11.6 40.2 7.47 0.73 9 Ratna 25.75 14.21 20.3 4.55 0.93 10 Dashehari clone 24.6 11.25 34 3.2 0.54 11 Swarna Jahangir 23.17 10.92 21.2 3.57 0.33 12 Neelgoa 22.4 10.25 26.2 8.77 1.34 13 Dashehari 23.56 11.48 21 3.67 0.57 14 Langra 28.63 11.12 81.3 25.15 1.95 15 Pusa Arunima 22.02 12.71 16.5 4.87 0.63 16 Pusa Surya 21.46 9.71 39.5 13.64 1.74 17 Arka Neelkiran 21.6 10.88 11.3 3.03 0.57 18 Ambika 25.27 15.16 13.2 3.83 0.54 19 Arunika 22.52 17.12 29.5 5.1 0.88 S.Em ± 0.49 0.54 7.98 2.03 0.27 CD at 0.05 % 1.41 1.55 22.9 5.84 0.78 ranged from 3.03 to 25.15 kg tree-1. The variation in translocation of photosynthates and plant hormones, the yield of fruits in different cultivars might be due fruit set, fruit retention, tree size and leaf area of an to the inherent variation in the absorption and individual cultivar45-46. BORA et al: POLYMORPHIC ASSESSMENT OF GENETIC DIVERSITY AND RELATIONSHIP OF MANGO 95

The maximum yield efficiency was recorded in statured, while “Swarna Jehangir” was found to be Amrapali (2.13 kg m-3) which was statistically at par vigorous in growth. with Langra (1.95 kg m-3) and Pusa Surya (1.74 kg m-3). The minimum yield efficiency was recorded in Molecular Analysis Swarna Jahangir (0.33 kg m-3). Fruit yield is the major Relationship Among Mango Genotypes Based on SSR Markers determinant variable for selecting a particular cultivar On the basis of SSR marker data the Jaccard’s for its commercialization and income generation. similarity coefficients were estimated between pair of Many folds increase in fruit yield of a particular genotypes. The values of Jaccard’s similarity variety might be due to differences in genetic makeup coefficient ranged from 0.043 to 0.79 with the of varieties, growing conditions and age of the plants. average value of 0.41. The association among 19 genotypes revealed by UPGMA cluster analysis based Construction of Similarity Tree Based on Morphological on amplification profile after gel electrophoresis is Characters presented in Figure 2. The cluster analysis based on The dendrogram based on morphological UPGMA categorized 19 mango genotypes into two characters was obtained by drawing similarity tree major clusters. Subgroup B1 consisting Neeleshan considering both of these qualitative and quantitative and Arka Neelkiran were found 79%, contrary to morphological characters using DARwin5 software this Mallika and Ratna were 73% similar. Jaccard’s (Fig. 1). The dendrogram was constructed based on similarity coefficient values clearly depicted rich UPGMA. At each bifurcation, the pair of elements genetic diversity within the hybrid and superior with the smallest dissimilarity is grouped to form a selection selected for investigation. The reason for new node. If this minimal value is shared by several rich genetic variation found could be attributed tothe pairs, they are grouped at the same iteration. The cross pollinated nature and high degree of cluster was divided into two parts. The bigger cluster heterozygosity. The Jaccard’s similarity values among (‘Cluster A’) comprises of 18 genotypes namely, Indian mangoes was observed ranged from 0.31 and Arka Neelkiran, Neelgoa, Dashehari clone, Vanraj, 0.75 with a mean of 0.5647. Jaccard’s similarity values Neeluddin, Arunika, Ratna, Pusa Arunima, in the range from 0.51 to 0.99, with a mean value 0.66 Neeleshan, Pusa Surya, Swarna Jahangir, Mehmood for ISSR analysis of 79mango accessions48. The Bahar, Ambika, Pant Sinduri, Sabri and Amrapali. genetic similarity between different mango genotypes The genotype Langra in Cluster B was most diverse in based on Jaccard’s similarity coefficient ranged from terms of its quantitative morphological characters 0.79 (between Chausa and Dashehari, and between from the remaining genotypes under consideration. Langra and Mallika) and 0.41 (between our and On the basis of findings, it can be concluded that the ) among different genotypes49. significant variation exists within the genotypes based on morphological characteristics. “Sabri” and “Amrapali” were not very vigorous being dwarf

Fig 1 — Dendrogram based on morphological characters Fig 2 — Dendrogram illustrating the genetic relationship among (quantitative data) of Mango genotypes constructed using mango genotypes based on SSR markers using UPGMA cluster DARwin5 software. analysis.

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Table 3 — Number of alleles and allele size obtained by using SSR markers in promising hybrids and selections of mango. S. No Locus Sequence (5’-3’) Number of Allele size Annealing temperature alleles (bp) Tm (◦C)

1 MiSHRS-23 F: AGGTCTTTTATCTTCGGCCC 3 181-252 53.0 R: AAACGAAAAAGCAGCCCA 2 MiSHRS-32 F: TTGATGCAACTTTCTGCC 3 179-233 50.8 R: TGTGATTGTTAGAATGAACTT 3 MiSHRS-37 F: CTCGCATTTCTCGCAGTC 3 128-143 55.0 R: TCCCTCCATTTAACCCTCC 4 MiSHRS-48 F: TTTACCAAGCTAGGGTCA 5 215-262 50.3 R: CACTCTTAAACTATTCAACCA 5 LMMA2 F: AAATAAGATGAAGCAACTAAAG 3 178-216 48.0 R: TTAGTGATTTTGTATGTTCTTG 6 LMMA4 F: AAAAACCTTACATAAGTGAATC 3 113-212 55.5 R: CAGTTAACCTGTTACCTTTTT 7 LMMA10 F: CATGGAGTTGTGATACCTAC 3 156-218 50.8 R: CAGAGTTAGCCATATAGAGTG 8 MiIIHR03a F: GTCGATGCCTGGAATGAAGT 2 213-236 57.8 R: AAGCATCGAACAGCTCCAAT 9 MiIIHR07a F: GCCACTCAGCTAAATAGCCTCT 2 168-192 55.5 R: TGCAGTCGGTAAAGTGATGG 10 MiIIHR08 b F: TGCTCTCTACTGCCCCGTAT 1 257-271 55.8 R: GTCACACCAATCGGGAATCT 11 MiIIHR09c F: GTTGTGACCGAGGCCTTAAA 2 274-301 55.5 R: CTTTGACATCGCTGATCTGG 12 MiIIHR10c F: CGATTCAAGACGGAAAGGAA 2 179-187 55.5 R: TTCAAGCACAGACGACCAAC 13. MiIIHR11a F: CAGTGAAACCACCAGGTCAA 2 114-142 53.0 R: TGGCCAGCTGATACCTTCTT 14 MiIIHR12a F: GCCCCATCAATACGATTGTC 2 147-195 55.5 R: ATTTCCCACCATTGTCGTTG 15 MiIIHR14 b F: CCGAAACAACTCTTCCTCCA 2 327-359 53.8 R: TGCTCTCTGGCCTCTTCTTC 16 MiIIHR20a F: CCTAACGCGCAAGAAACATA 2 179-198 55.0 R: ACCCACCTTCCCAATCTTTT 17 MiIIHR27c F: TGGGGATTCATCGGAGATAG 3 187-217 54.5 R: TGGAAGACCCATTCTCATGC 18 MiIIHR33a F: GAAGCACTTGTCTCCCTTGC 3 154-208 55.5 R: CCTCACACTCCTCCACCTGT 19 MiIIHR21 b F: TTTGGCTGGGTGATTTTAGC 1 233-269 55.0 R: TTAATTGCAGGACTGGAGCA 20 MiIIHR25a F: TGTGAGTCTCCGTTTGTGCT 2 125-179 55.0 R: CCCTCTCATTTTCCCAGTCA Characterization and Genotypes Identification maximum numbers of loci five (5) were detected, Characterization of 19 genotypes of mango with 20 by the primer MiSHRS-48. However, this primer SSR primer pairs identified a total of 49 alleles failed to identify any unique fingerprint. The primer (Table 3). Out of 20 primer pair’s 18 produced pair MiSHRS-23 showed a unique band of 252 bp polymorphic bands while two produced monomorphic. with the genotype Mahmood Bahar, MiSHRS-32 of The amplification profile of MiIIHR12a with different genotypes of mango is shown in Figure 3. Unique 232 bp with Vanraj and LMMA4 with Pant Sinduri band was amplified by primers namely MiSHRS- 189 bp. Unique bands are generated and marker 23, LMMA4 and MiSHRS-32. A total of 42 specific alleles. The occurrence of unique alleles amplified loci exhibited 77.5 % polymorphism. The specific to different mango genotypes has been BORA et al: POLYMORPHIC ASSESSMENT OF GENETIC DIVERSITY AND RELATIONSHIP OF MANGO 97

Fig. 3 — Amplification profile of MiIIHR12a with different genotypes of mango. M. 100 bp Ladder, 1 Neeluddin, 2 Neeleshan, 3 Amrapali, 4 Vanraj, 5 Mallika, 6 Pant Sinduri, 7 Mahmood Bahar, 8 Sabri, 9 Ratna, 10 Dashehari clone, 11 Swarna Jahangir, 12 Neelgoa, 13 Dashehari, 14 Langra, 15 Pusa Arunima, 16 Pusa Surya, 17 Arka Neelkiran, 18 Ambika, 19 Arunika. reported earlier50-51. Presence of unique alleles may serve as indicator genome specific to a particular Table 4 — Details of different hybrids and selections of mango used as a treatment. region, of a particular trait of horticulture importance. S. No Name of cultivars Parentage The presence of unique band with the specific 1 Neeluddin Neelum × Himayuddin genotype can be helpful in its own identification. 2 Neeleshan Neelum × Baneshan Sequencing of these unique fingerprints and analyzing 3 Amrapali Dashehari× Neelum the sequence obtained using bioinformatics 4 Vanraj Chance seedling selection approaches can help us in exploiting their functional 5 Mallika Neelum × Dashehari traits which can be useful in further fruit breeding 6 Pant Sinduri Selection from Banglore Goa programmes for introducing diversity. Therefore, the 7 Sabri Gulab –Khas × Bombai 8 Mahmood Bahar Bombai × Kalapadi above study reveals that microsatellites markers are 9 Ratna Neelum × useful not only for varietal identification and 10 Dashehari clone Clone from Dashehari detection of duplicate entries, but also to study the 11 Swarna Jahangir China Swarnarekha × Jahangir genetic variability among the mango cultivars. 12 Neelgoa Neelum× Mulgoa 13 Dashehari Chance seedling selection Genetic Diversity Among Mango Genotypes 14 Langra Chance seedling selection The grouping of the genotypes was according to 15 Pusa Arunima Amrapali × Sensation the geographical origin and less or more based on 16 Pusa Surya Selection from their parentage (Table 4). Group A consist of the most 17 Arka Neelkiran Alphonso × Neelum diverse superior selection, Pusa Surya. Cluster B was 18 Ambika Amrapali × JanardhanPasand again bifurcated into two sub clusters namely clusters 19 Arunika Amrapali× Vanraj B1 and B2. Cluster B1 consisted of 17 genotypes first generation of ‘Florida’ mangoes developed by namely, Neeluddin, Neelgoa, Arka Neelkiran, ’ and ‘’, which are seedlings of Amrapali, Mallika, Ratna, Dashehari Clone, ‘’, an accession from India crossed with Dashehari, Pusa Arunima, Vanraj, Arunika, Ambika, Turpentine. Similarly, ‘Eldon’, ‘’, ‘’, Pant Sinduri, Sabri, Swarna Jahangir and Langra ‘’, ‘’ and ‘’ are while B2containing the single hybrid Mahmood second-generation selections, and are seedlings of Bahar. The genotypes which showed similar ‘Haden’58. Pusa Surya is a selection from Eldon. morphological and genetic trends were grouped The different consecutive generations have more or less together in both these cases were a contributed for diverse genetic diversity in sub- few. Pusa Surya and Mahmood Bahar showed generations. Mallika and Ratna being reciprocal deviation from the existing cluster were also crosses of Neelum and Dashehari shared the cluster diverse with respect to their genetic makeup. The morphologically and genetically while they differ

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Table 5 — Genetic parameters estimated for 20 SSR primers in 19 genotypes of mango S. No Primers Gene diversity Heterozygosity PIC values 1 MiSHRS-23 0.57 0.07 0.79 2 MiSHRS-32 0.76 0.11 0.72 3 MiSHRS-37 0.72 0.05 0.79 4 MiSHRS-48 0.80 0.16 0.72 5 LMMA2 0.75 0.31 0.72 6 LMMA4 0.77 0.44 0.81 7 LMMA10 0.79 0.64 0.65 8 MiIIHR03a 0.57 0.00 0.70 9 MiIIHR07a 0.72 0.44 0.72 10 MiIIHR08 b 0.11 0.00 0.00 11 MiIIHR09c 0.47 0.06 0.44 12 MiIIHR10c 0.33 0.00 0.66 13 MiIIHR11a 0.87 0.62 0.56 14 MiIIHR12a 0.75 0.33 0.44 15 MiIIHR14 b 0.78 0.36 0.38 16 MiIIHR20a 0.64 0.00 0.72 17 MiIIHR27c 0.73 0.44 0.76 18 MiIIHR33a 0.82 0.52 0.74 19 MiIIHR21 b 0.81 0.00 0.00 20 MiIIHR25a 0.75 0.31 0.44 Mean 0.68 0.24 0.58

with respect to vegetative growth character. The low values of genetic diversity express the present findings are in consistent with the earlier vulnerability of the genotypes towards disease, reports reported similar values of SSR polymorphism climatic and insect problems. The dendrograms (71 and 81.8%), number of alleles, allele size in generated based on considering morphological and mango. In the present investigation most of the SSR molecular data revealed a huge variation in the primers detected multiple loci, which can be behavior of genotypes. The genotypes clustered in 52 attributed to the allopolyploid nature of mango . group on the basis of degree to which the traits or Very low to moderate PIC values of SSR markers in 50-51 characters was shared. The germplasm of mango from mango . Polymorphic information content (PIC) India has a wide genetic diversity. The results of this values of these primers were also low to moderate in 53 study showed the potential of SSR loci in deciphering Florida mango cultivars . the most the existing genetic diversity among the mango diverse germplasm under study of indigenous genotypes analyzed. In the present study certain SSR genotypes and exotic germplasm conducted at loci have reported high PIC content which can be Pakistan54. The grouping of the hybrids in the taken under consideration for future mango genotype dendrogram was also based on their eco-geographical distribution, north, south and exotic, while more or characterization. The SSR markers are polymorphic, less also based on their parentage. In the present co-dominant, highly abundant, widely distributed study, the PIC of SSRs primer pair was low to throughout the genome, readily transferable and moderate ranged from 0.38 to 0.81, with the average analytically simple in nature. SSRs are found to be value of 0.58 (Table 5). PIC values of these primers in highly variable as compared to RAPD or RFLP and Florida cultivars were also low to moderate varying have been reported to be utilized extensively in 24,56,57 from 0.21 to 0.63 for the polymorphic loci53. Earlier various genomic studies . In comparison to other reports in this regard are in tune with the present markers they may be felt more successfully, when findings. Working on mango with SSR markers, these will be used to trace most anticipated characters similar range of values from 0.45 to 0.88 were on large scale in mango improvement programmes as observed48. The range for genetic diversity was anchored point map based system for cloning observed 0.11 to 0.87 with a mean of 0.68. The strategies of desirable traits. BORA et al: POLYMORPHIC ASSESSMENT OF GENETIC DIVERSITY AND RELATIONSHIP OF MANGO 99

Conclusions 7 Hoogendijk M & Williams D, Characterizing genetic The result of our investigation shows the efficacy of diversity of home garden crop species: some examples from the Americas, in. Proceedings of the Second International SSRs markers for assessment of genetic relationship Home Gardens Workshop held on 17-19 July, 2001 and diversity, which gives an idea to programme a (Witzenhausen, Federal Republic of Germany, Home gardens hybridization using a distant parent in order to and in situ conservation of plant genetic resources in farming introduce the traits of interest in the cultivated systems edited by J W Watson & P B Eyzaguirre) 2001, 34-40. 8 Gonzalez A, Coulson M & Brettell R, Development of DNA genotypes. Also the precise studies can be done at markers (ISSRs) in mango. Acta Hort, 575 (2002) 139-143. genomics by understanding the genes which are 9 Ascenso J C, Milheiro A, Mota M I & Cabral M, expressed in the different stages of growth. 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