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

Annals of Occupational and Environmental Medicine

Wiebke Sickel¹  Markus J Ankenbrand¹  Gudrun Grimmer¹  Andrea Holzschuh¹  Stephan Härtel¹  Jonathan Lanzen¹  Ingolf Steffan-Dewenter¹  Alexander Keller¹ 

[1] Department of Animal Ecology and Tropical Biology, Biocenter, University of Würzburg, Am Hubland, Würzburg, 97074, Germany

关键词: Pollination ecology;    Palynology;    Osmia;    NGS;    Next generation sequencing;    ITS2;    Illumina MiSeq platform;    High throughput sequencing;    DNA barcoding;   

Others  :  1223785
DOI  :  10.1186/s12898-015-0051-y

 received in 2015-04-15, accepted in 2015-06-25,  发布年份 2015

【 摘 要 】

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 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.

【 授权许可】

   
2015 Sickel et al.

【 图 表 】

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