Meta-barcoding in combination with palynological inference is a potent diagnostic marker for honey floral composition

Abstract Identification of floral samples present in honey is important in order to determine the medicinal value, enhance the production of honey as well as to conserve the honey bees. Traditional approaches for studying pollen samples are based on microscopic observation which is laborious, time i...

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Main Authors: Rama Chandra Laha, Surajit De Mandal, Lalhmanghai Ralte, Laldinfeli Ralte, Nachimuthu Senthil Kumar, Guruswami Gurusubramanian, Ramalingam Satishkumar, Raja Mugasimangalam, Nagesh Aswathnarayana Kuravadi
Format: Article
Language:English
Published: SpringerOpen 2017-06-01
Series:AMB Express
Subjects:
Online Access:http://link.springer.com/article/10.1186/s13568-017-0429-7
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author Rama Chandra Laha
Surajit De Mandal
Lalhmanghai Ralte
Laldinfeli Ralte
Nachimuthu Senthil Kumar
Guruswami Gurusubramanian
Ramalingam Satishkumar
Raja Mugasimangalam
Nagesh Aswathnarayana Kuravadi
author_facet Rama Chandra Laha
Surajit De Mandal
Lalhmanghai Ralte
Laldinfeli Ralte
Nachimuthu Senthil Kumar
Guruswami Gurusubramanian
Ramalingam Satishkumar
Raja Mugasimangalam
Nagesh Aswathnarayana Kuravadi
author_sort Rama Chandra Laha
collection DOAJ
description Abstract Identification of floral samples present in honey is important in order to determine the medicinal value, enhance the production of honey as well as to conserve the honey bees. Traditional approaches for studying pollen samples are based on microscopic observation which is laborious, time intensive and requires specialized palynological knowledge. Present study compares two composite honey metagenome collected from 20 samples in Mizoram, Northeast India using three gene loci- rbcL, matK and ITS2 that was sequenced using a next-generation sequencing (NGS) platform (Illumina Miseq). Furthermore, a classical palynology study for all 20 samples was carried out to evaluate the NGS approach. NGS based approach and pollen microscopic studies were able to detect the most abundant floral components of honey. We investigated the plants that were frequently used by honey bees by examining the results obtained from both the techniques. Microscopic examination of pollens detected plants with a broad taxonomic range covering 26 families. NGS based multigene approach revealed diverse plant species, which was higher than in any other previously reported techniques using a single locus. Frequently found herbaceous species were from the family Poaceae, Myrtaceae, Fabaceae and Asteraceae. The future NGS based approach using multi-loci target, with the help of an improved and robust plant database, can be a potential replacement technique for tedious microscopic studies to identify the polleniferous plants.
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spelling doaj.art-90b29ce26c1b4013b63c22a9936daf4b2022-12-21T19:34:40ZengSpringerOpenAMB Express2191-08552017-06-01711810.1186/s13568-017-0429-7Meta-barcoding in combination with palynological inference is a potent diagnostic marker for honey floral compositionRama Chandra Laha0Surajit De Mandal1Lalhmanghai Ralte2Laldinfeli Ralte3Nachimuthu Senthil Kumar4Guruswami Gurusubramanian5Ramalingam Satishkumar6Raja Mugasimangalam7Nagesh Aswathnarayana Kuravadi8Departments of Botany, Biotechnology and Zoology, School of Life Sciences, Mizoram UniversityDepartments of Botany, Biotechnology and Zoology, School of Life Sciences, Mizoram UniversityDepartments of Botany, Biotechnology and Zoology, School of Life Sciences, Mizoram UniversityDepartments of Botany, Biotechnology and Zoology, School of Life Sciences, Mizoram UniversityDepartments of Botany, Biotechnology and Zoology, School of Life Sciences, Mizoram UniversityDepartments of Botany, Biotechnology and Zoology, School of Life Sciences, Mizoram UniversityDepartment of Biotechnology, Bharathiar UniversityGenotypic TechnologiesQTLomics TechnologiesAbstract Identification of floral samples present in honey is important in order to determine the medicinal value, enhance the production of honey as well as to conserve the honey bees. Traditional approaches for studying pollen samples are based on microscopic observation which is laborious, time intensive and requires specialized palynological knowledge. Present study compares two composite honey metagenome collected from 20 samples in Mizoram, Northeast India using three gene loci- rbcL, matK and ITS2 that was sequenced using a next-generation sequencing (NGS) platform (Illumina Miseq). Furthermore, a classical palynology study for all 20 samples was carried out to evaluate the NGS approach. NGS based approach and pollen microscopic studies were able to detect the most abundant floral components of honey. We investigated the plants that were frequently used by honey bees by examining the results obtained from both the techniques. Microscopic examination of pollens detected plants with a broad taxonomic range covering 26 families. NGS based multigene approach revealed diverse plant species, which was higher than in any other previously reported techniques using a single locus. Frequently found herbaceous species were from the family Poaceae, Myrtaceae, Fabaceae and Asteraceae. The future NGS based approach using multi-loci target, with the help of an improved and robust plant database, can be a potential replacement technique for tedious microscopic studies to identify the polleniferous plants.http://link.springer.com/article/10.1186/s13568-017-0429-7HoneyMultilocus targetDNA barcodingPalynology
spellingShingle Rama Chandra Laha
Surajit De Mandal
Lalhmanghai Ralte
Laldinfeli Ralte
Nachimuthu Senthil Kumar
Guruswami Gurusubramanian
Ramalingam Satishkumar
Raja Mugasimangalam
Nagesh Aswathnarayana Kuravadi
Meta-barcoding in combination with palynological inference is a potent diagnostic marker for honey floral composition
AMB Express
Honey
Multilocus target
DNA barcoding
Palynology
title Meta-barcoding in combination with palynological inference is a potent diagnostic marker for honey floral composition
title_full Meta-barcoding in combination with palynological inference is a potent diagnostic marker for honey floral composition
title_fullStr Meta-barcoding in combination with palynological inference is a potent diagnostic marker for honey floral composition
title_full_unstemmed Meta-barcoding in combination with palynological inference is a potent diagnostic marker for honey floral composition
title_short Meta-barcoding in combination with palynological inference is a potent diagnostic marker for honey floral composition
title_sort meta barcoding in combination with palynological inference is a potent diagnostic marker for honey floral composition
topic Honey
Multilocus target
DNA barcoding
Palynology
url http://link.springer.com/article/10.1186/s13568-017-0429-7
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