Abstract

Simple sequence repeats (SSRs) which is an efficient genetic markers for comparative genome mapping can be helpful in the classification of genotypes, germplasm resource utilization and breeding programmes. Therefore, the present study was conducted to show genetic variation and investigate inter-relationship between ten mango genotypes. Twenty (20) SSR markers were tested with 10 genotypes: Kalepad, Neelum, Swarnarekha, Alphonso Rumani, Sendura, Banganapalli, Himayuddin, Mulgoa and Bangalora. The genomic DNA was extracted from the leaf samples using cetyltrimethyl ammonium bromide (CTAB) method. Polymerase chain reaction (PCR) amplification of the DNA isolated from 10 mango genotypes with 20 SSR primers produced a total of 240 amplified products, of which 184 were polymorphic and 56 monomorphic. The sizes of the alleles detected ranged from 120 to 369 bp. SSR markers were highly polymorphic with an average of 2.70 alleles per primers. SSRs gave moderate values of polymorphic information content (PIC) range of 0.320 to 0.774. The amplified products varied between 2 (LMMA 1, 5, 7, 12, 16, MiSHRS-1 and MiSHRS-37) to 3 and 4 (LMMA 4, 6, 9, 10, 11, 13, 14, 15 MiSHRS-4, 48, 18, 39 and LMMA 8) bands per primer. We obtained moderate degree of genetic diversity, with Jaccard’s similarity co-efficient values ranging from 0.075 between cluster I and II to 0.285 between clusters II and III. The dendrogram generated from the unweighted pair group arithmetic average (UPGMA) cluster analysis broadly placed 10 mango cultivars into three major clusters at co-efficient similarity of 0.65. The cluster size varied from 1 to 6 and cluster III was the largest cluster comprising of six cultivars followed by cluster II possessing three and cluster I possessing one variety. Cluster I had the highest diverse cultivars namely, Kalepad, Neelum and Swarnarekha. Cluster II included cultivar of Alphonso. Cluster III contain the cultivars viz., Rumani, Sendura, Bangnapalli, Himayuddin, Mulgoa and Bangalora. Unique fingerprints were identified in the cultivars. The unique fingerprints size ranged from LMMA-8 (257-270 bp), LMMA-11 (232- 245 bp) to MiSHRS 39 (340-369 bp). The tendency of clustering among mango cultivars revealed that they have strong affinity towards further breeding programme. Key words: Cultivars, genetic diversity, mango, simple sequence repeats (SSR).

Highlights

  • Full Length Research PaperMolecular characterization of ten mango cultivars using simple sequences repeat (SSR) markers

  • Mango (Mangifera indica L.) belonging to the family Anacardiaceae occupies paramount place among the fruit crops grown in India and christened as the “King of fruits” owing to its delicious flavor and taste; there are 1000 varieties found in the country (Singh, 1996)

  • There is a lot of confusion in nomenclature of the mango cultivars, which is attributed to the lack of systematic approach in nomenclature

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Summary

Full Length Research Paper

Molecular characterization of ten mango cultivars using simple sequences repeat (SSR) markers. The most fundamental of these molecular techniques are DNA markers which portray genome sequence composition, enabling the detection of differences in the genetic information carried by the different individuals These markers are powerful tools in genotype identification or fingerprinting and the estimation of relatedness between genotypes. Precise characterization of genetic variation at the molecular level is possible using DNA based markers Different molecular marker, such as randomly amplified polymorphic DNA (RAPDs) (Bajpai et al, 2008), amplified fragments length polymorphism (AFLP) (Eiadthong et al, 2000), inter-simple sequence repeats (Pandit et al, 2007) and simple sequence repeats (Duval et al, 2005; Schnell et al, 2006; Viruel et al, 2005) have been employed for genetic diversity assessment in mango cultivars. Keeping in view these advantages, we analyzed the closely related mango cultivars with micro satellite markers

DNA isolation
PCR procedure
Data analysis
RESULTS AND DISCUSSION
Similarity Coefficient
Cluster Cluster I Cluster II Cluster III
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