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Increased efficiency in identifying mixed pollen samples by meta-barcoding with a dual-indexing approach

Please always quote using this URN: urn:nbn:de:bvb:20-opus-125730
  • Background Meta-barcoding of mixed pollen samples constitutes a suitable alternative to conventional pollen identification via light microscopy. Current approaches however have limitations in practicability due to low sample throughput and/or inefficient processing methods, e.g. separate steps for amplification and sample indexing. Results We thus developed a new primer-adapter design for high throughput sequencing with the Illumina technology that remedies these issues. It uses a dual-indexing strategy, where sample-specific combinationsBackground Meta-barcoding of mixed pollen samples constitutes a suitable alternative to conventional pollen identification via light microscopy. Current approaches however have limitations in practicability due to low sample throughput and/or inefficient processing methods, e.g. separate steps for amplification and sample indexing. Results We thus developed a new primer-adapter design for high throughput sequencing with the Illumina technology that remedies these issues. It uses a dual-indexing strategy, where sample-specific combinations of forward and reverse identifiers attached to the barcode marker allow high sample throughput with a single sequencing run. It does not require further adapter ligation steps after amplification. We applied this protocol to 384 pollen samples collected by solitary bees and sequenced all samples together on a single Illumina MiSeq v2 flow cell. According to rarefaction curves, 2,000–3,000 high quality reads per sample were sufficient to assess the complete diversity of 95% of the samples. We were able to detect 650 different plant taxa in total, of which 95% were classified at the species level. Together with the laboratory protocol, we also present an update of the reference database used by the classifier software, which increases the total number of covered global plant species included in the database from 37,403 to 72,325 (93% increase). Conclusions This study thus offers improvements for the laboratory and bioinformatical workflow to existing approaches regarding data quantity and quality as well as processing effort and cost-effectiveness. Although only tested for pollen samples, it is furthermore applicable to other research questions requiring plant identification in mixed and challenging samples.show moreshow less

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Metadaten
Author: Wiebke Sickel, Markus J. Ankenbrand, Gudrun Grimmer, Andrea Holzschuh, Stephan Härtel, Jonathan Lanzen, Ingolf Steffan-Dewenter, Alexander KellerORCiD
URN:urn:nbn:de:bvb:20-opus-125730
Document Type:Journal article
Faculties:Fakultät für Biologie / Theodor-Boveri-Institut für Biowissenschaften
Language:English
Parent Title (English):BMC Ecology
Year of Completion:2015
Volume:15
Issue:20
Source:BMC Ecology (2015) 15:20 DOI 10.1186/s12898-015-0051-y
DOI:https://doi.org/10.1186/s12898-015-0051-y
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Tag:DNA barcoding; ITS2; NGS; high throughput sequencing; illumina MiSeq platform; next generation sequencing; osmia; palynolog; pollination ecology
Release Date:2016/02/04
Collections:Open-Access-Publikationsfonds / Förderzeitraum 2015
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung