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Pollen identification using sequencing techniques
University of Skövde, School of Bioscience.
2022 (English)Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Palynology or the study of pollen, is essential understand the relationship between plants and their pollinators. Traditionally, pollen grains are identified by microscopy. The method has several shortcomings, such as being time-consuming and having low taxonomic resolution. DNA-barcoding-based sequencing can identify pollen at the genus and species levels without specialized paleontological expertise. Aim of this study is to assess which molecular approach can be the most effective tool and is the most cost-effective for the identification of pollen from mixed pollen samples. A DNA metabarcoding study was conducted using the rbcL barcode gene for pollen identification using two sequencing techniques: Sanger and MinION. DNA metabarcoding produced taxonomic data easily. For the analysis of Sanger and MinION sequencing data, BLAST and KRAKEN2 were used respectively. Pavian and KRONA were later used to visualize the MinION sequencing data. Various plant species native to Sweden were identified with this metabarcoding approach. However, the reference database failed to identify a few of them, thus indicating the need to expand the reference database. 

Place, publisher, year, edition, pages
2022. , p. 44
Keywords [en]
pollen, rbcL gene, barcoding, metabarcoding, Sanger sequencing, MinION sequencing
National Category
Other Environmental Biotechnology
Identifiers
URN: urn:nbn:se:his:diva-21890OAI: oai:DiVA.org:his-21890DiVA, id: diva2:1700423
Subject / course
Bioscience
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Examiners
Available from: 2022-09-30 Created: 2022-09-30 Last updated: 2022-09-30Bibliographically approved

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • apa-cv
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
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  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf