Jain, A., Chaudhary, S. orcid.org/0000-0003-2360-3325 and Sharma, P.C. (2014) Mining of microsatellites using next generation sequencing of seabuckthorn (Hippophae rhamnoides L.) transcriptome. Physiology and Molecular Biology of Plants, 20 (1). pp. 115-123. ISSN: 0971-5894
Abstract
Gene based microsatellite markers are becoming more popular as compared to traditional random genomic microsatellite markers due to rapid and inexpensive method of isolation and their cross species portability. The present study documents occurrence of microsatellites in the transcriptome of seabuckthorn, a plant with immense medicinal, nutritional and ecological value. De novo assembly of over 80 million high quality short reads generated by high throughput next generation sequencing yielded 88297 putative unigenes. Of these, 7.69 % unigenes harbored microsatellite repeats with an average of one microsatellite per 6.704 Kb transcriptome. Dinucleotide repeats were most abundant followed by trinucleotide repeats. Microsatellites were densely populated in coding regions followed by 3′ and 5′ untranslated regions. AG and AAG type repeats were most frequently represented. Of the microsatellite positive unigenes, 48.81 % could be assigned gene ontology (GO) terms in order to assess associations between microsatellite containing unigenes and biological role of known genes. Utility of unigene specific microsatellites was assessed on the basis of polymorphism(s) detected in 18 seabuckthorn collections from Leh (India) using a set of randomly selected 25 unigene specific microsatellites. The findings presented here are likely to find immense use in future breeding and molecular biology research projects in seabuckthorn aiming at its overall development as a crop.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2013 Prof. H.S. Srivastava Foundation for Science and Society. |
Keywords: | Seabuckthorn; Transcriptome sequencing; Microsatellites markers; Gene ontology; Codon usage |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > School of Biosciences (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 25 Sep 2025 11:11 |
Last Modified: | 25 Sep 2025 11:11 |
Status: | Published |
Publisher: | Springer Science and Business Media LLC |
Refereed: | Yes |
Identification Number: | 10.1007/s12298-013-0210-6 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:232218 |