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

Overview of attention for article published in SpringerPlus, January 2016
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Assessment of mangroves from Goa, west coast India using DNA barcode
Published in
SpringerPlus, January 2016
DOI 10.1186/s40064-016-3191-4
Pubmed ID

Saddhe, Ankush Ashok, Jamdade, Rahul Arvind, Kumar, Kundan


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.

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Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 4 15%
Lecturer 4 15%
Student > Bachelor 3 11%
Researcher 3 11%
Student > Ph. D. Student 3 11%
Other 4 15%
Unknown 6 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 10 37%
Biochemistry, Genetics and Molecular Biology 8 30%
Environmental Science 3 11%
Sports and Recreations 1 4%
Engineering 1 4%
Other 0 0%
Unknown 4 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 September 2016.
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