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Extrapolative microRNA precursor based SSR mining from tea EST database in respect to agronomic traits

Tea (Camellia sinensis, (L.) Kuntze) is considered as most popular drink across the world and it is widely consumed beverage for its several health-benefit characteristics. These positive traits primarily rely on its regulatory networks of different metabolic pathways. Development of microsatellite...

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Autores principales: Hazra, Anjan, Dasgupta, Nirjhar, Sengupta, Chandan, Das, Sauren
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5501407/
https://www.ncbi.nlm.nih.gov/pubmed/28683768
http://dx.doi.org/10.1186/s13104-017-2577-x
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author Hazra, Anjan
Dasgupta, Nirjhar
Sengupta, Chandan
Das, Sauren
author_facet Hazra, Anjan
Dasgupta, Nirjhar
Sengupta, Chandan
Das, Sauren
author_sort Hazra, Anjan
collection PubMed
description Tea (Camellia sinensis, (L.) Kuntze) is considered as most popular drink across the world and it is widely consumed beverage for its several health-benefit characteristics. These positive traits primarily rely on its regulatory networks of different metabolic pathways. Development of microsatellite markers from the conserved genomic regions are being worthwhile for reviewing the genetic diversity of closely related species or self-pollinated species. Although several SSR markers have been reported, in tea, the trait-specific Simple Sequence Repeat (SSR) markers, leading to be useful in marker assisted breeding technique, are yet to be identified. Micro RNAs are short, non-coding RNA molecules, involved in post transcriptional mode of gene regulation and thus effects on related phenotype. Present study deals with identification of the microsatellite motifs within the reported and predicted miRNA precursors that are effectively followed by designing of primers from SSR flanking regions in order to PCR validation. In addition to the earlier reports, two new miRNAs are predicting here from tea expressed tag sequence database. Furthermore, 18 SSR motifs are found to be in 13 of all 33 predicted miRNAs. Trinucleotide motifs are most abundant among all followed by dinucleotides. Since, miRNA based SSR markers are evidenced to have significant role on genetic fingerprinting study, these outcomes would pave the way in developing novel markers for tagging tea specific agronomic traits as well as substantiating non-conventional breeding program.
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spelling pubmed-55014072017-07-10 Extrapolative microRNA precursor based SSR mining from tea EST database in respect to agronomic traits Hazra, Anjan Dasgupta, Nirjhar Sengupta, Chandan Das, Sauren BMC Res Notes Short Report Tea (Camellia sinensis, (L.) Kuntze) is considered as most popular drink across the world and it is widely consumed beverage for its several health-benefit characteristics. These positive traits primarily rely on its regulatory networks of different metabolic pathways. Development of microsatellite markers from the conserved genomic regions are being worthwhile for reviewing the genetic diversity of closely related species or self-pollinated species. Although several SSR markers have been reported, in tea, the trait-specific Simple Sequence Repeat (SSR) markers, leading to be useful in marker assisted breeding technique, are yet to be identified. Micro RNAs are short, non-coding RNA molecules, involved in post transcriptional mode of gene regulation and thus effects on related phenotype. Present study deals with identification of the microsatellite motifs within the reported and predicted miRNA precursors that are effectively followed by designing of primers from SSR flanking regions in order to PCR validation. In addition to the earlier reports, two new miRNAs are predicting here from tea expressed tag sequence database. Furthermore, 18 SSR motifs are found to be in 13 of all 33 predicted miRNAs. Trinucleotide motifs are most abundant among all followed by dinucleotides. Since, miRNA based SSR markers are evidenced to have significant role on genetic fingerprinting study, these outcomes would pave the way in developing novel markers for tagging tea specific agronomic traits as well as substantiating non-conventional breeding program. BioMed Central 2017-07-06 /pmc/articles/PMC5501407/ /pubmed/28683768 http://dx.doi.org/10.1186/s13104-017-2577-x Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Short Report
Hazra, Anjan
Dasgupta, Nirjhar
Sengupta, Chandan
Das, Sauren
Extrapolative microRNA precursor based SSR mining from tea EST database in respect to agronomic traits
title Extrapolative microRNA precursor based SSR mining from tea EST database in respect to agronomic traits
title_full Extrapolative microRNA precursor based SSR mining from tea EST database in respect to agronomic traits
title_fullStr Extrapolative microRNA precursor based SSR mining from tea EST database in respect to agronomic traits
title_full_unstemmed Extrapolative microRNA precursor based SSR mining from tea EST database in respect to agronomic traits
title_short Extrapolative microRNA precursor based SSR mining from tea EST database in respect to agronomic traits
title_sort extrapolative microrna precursor based ssr mining from tea est database in respect to agronomic traits
topic Short Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5501407/
https://www.ncbi.nlm.nih.gov/pubmed/28683768
http://dx.doi.org/10.1186/s13104-017-2577-x
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