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Assessment of mangroves from Goa, west coast India using DNA barcode

Mangroves are salt-tolerant forest ecosystems of tropical and subtropical intertidal regions. They are among most productive, diverse, biologically important ecosystem and inclined toward threatened system. Identification of mangrove species is of critical importance in conserving and utilizing biod...

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Autores principales: Saddhe, Ankush Ashok, Jamdade, Rahul Arvind, Kumar, Kundan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5021661/
https://www.ncbi.nlm.nih.gov/pubmed/27652127
http://dx.doi.org/10.1186/s40064-016-3191-4
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author Saddhe, Ankush Ashok
Jamdade, Rahul Arvind
Kumar, Kundan
author_facet Saddhe, Ankush Ashok
Jamdade, Rahul Arvind
Kumar, Kundan
author_sort Saddhe, Ankush Ashok
collection PubMed
description Mangroves are salt-tolerant forest ecosystems of tropical and subtropical intertidal regions. They are among most productive, diverse, biologically important ecosystem and inclined toward threatened system. Identification of mangrove species is of critical importance in conserving and utilizing biodiversity, which apparently hindered by a lack of taxonomic expertise. In recent years, DNA barcoding using plastid markers rbcL and matK has been suggested as an effective method to enrich traditional taxonomic expertise for rapid species identification and biodiversity inventories. In the present study, we performed assessment of available 14 mangrove species of Goa, west coast India based on core DNA barcode markers, rbcL and matK. PCR amplification success rate, intra- and inter-specific genetic distance variation and the correct identification percentage were taken into account to assess candidate barcode regions. PCR and sequence success rate were high in rbcL (97.7 %) and matK (95.5 %) region. The two candidate chloroplast barcoding regions (rbcL, matK) yielded barcode gaps. Our results clearly demonstrated that matK locus assigned highest correct identification rates (72.09 %) based on TaxonDNA Best Match criteria. The concatenated rbcL + matK loci were able to adequately discriminate all mangrove genera and species to some extent except those in Rhizophora, Sonneratia and Avicennia. Our study provides the first endorsement of the species resolution among mangroves using plastid genes with few exceptions. Our future work will be focused on evaluation of other barcode markers to delineate complete resolution of mangrove species and identification of putative hybrids. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40064-016-3191-4) contains supplementary material, which is available to authorized users.
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spelling pubmed-50216612016-09-20 Assessment of mangroves from Goa, west coast India using DNA barcode Saddhe, Ankush Ashok Jamdade, Rahul Arvind Kumar, Kundan Springerplus Research Mangroves are salt-tolerant forest ecosystems of tropical and subtropical intertidal regions. They are among most productive, diverse, biologically important ecosystem and inclined toward threatened system. Identification of mangrove species is of critical importance in conserving and utilizing biodiversity, which apparently hindered by a lack of taxonomic expertise. In recent years, DNA barcoding using plastid markers rbcL and matK has been suggested as an effective method to enrich traditional taxonomic expertise for rapid species identification and biodiversity inventories. In the present study, we performed assessment of available 14 mangrove species of Goa, west coast India based on core DNA barcode markers, rbcL and matK. PCR amplification success rate, intra- and inter-specific genetic distance variation and the correct identification percentage were taken into account to assess candidate barcode regions. PCR and sequence success rate were high in rbcL (97.7 %) and matK (95.5 %) region. The two candidate chloroplast barcoding regions (rbcL, matK) yielded barcode gaps. Our results clearly demonstrated that matK locus assigned highest correct identification rates (72.09 %) based on TaxonDNA Best Match criteria. The concatenated rbcL + matK loci were able to adequately discriminate all mangrove genera and species to some extent except those in Rhizophora, Sonneratia and Avicennia. Our study provides the first endorsement of the species resolution among mangroves using plastid genes with few exceptions. Our future work will be focused on evaluation of other barcode markers to delineate complete resolution of mangrove species and identification of putative hybrids. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40064-016-3191-4) contains supplementary material, which is available to authorized users. Springer International Publishing 2016-09-13 /pmc/articles/PMC5021661/ /pubmed/27652127 http://dx.doi.org/10.1186/s40064-016-3191-4 Text en © The Author(s) 2016 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.
spellingShingle Research
Saddhe, Ankush Ashok
Jamdade, Rahul Arvind
Kumar, Kundan
Assessment of mangroves from Goa, west coast India using DNA barcode
title Assessment of mangroves from Goa, west coast India using DNA barcode
title_full Assessment of mangroves from Goa, west coast India using DNA barcode
title_fullStr Assessment of mangroves from Goa, west coast India using DNA barcode
title_full_unstemmed Assessment of mangroves from Goa, west coast India using DNA barcode
title_short Assessment of mangroves from Goa, west coast India using DNA barcode
title_sort assessment of mangroves from goa, west coast india using dna barcode
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5021661/
https://www.ncbi.nlm.nih.gov/pubmed/27652127
http://dx.doi.org/10.1186/s40064-016-3191-4
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