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

Area of Science:

• Molecular biology
• Bioinformatics
• Ecology

Background:

• Pollen meta-barcoding offers an alternative to traditional light microscopy for identifying mixed pollen samples.
• Current meta-barcoding methods face limitations in sample throughput and processing efficiency, often requiring separate amplification and indexing steps.

Purpose of the Study:

• To develop an improved primer-adapter design for high-throughput sequencing of pollen samples.
• To enhance sample throughput, reduce processing steps, and improve the cost-effectiveness of pollen identification.

Main Methods:

• Developed a novel primer-adapter design with a dual-indexing strategy for Illumina sequencing.
• Implemented a single sequencing run for 384 pollen samples without additional adapter ligation steps.
• Updated the reference database for classifier software, significantly increasing the number of identifiable plant species.

Main Results:

• The new protocol enables high sample throughput with a single sequencing run.
• 2,000-3,000 high-quality reads per sample were sufficient for accurate diversity assessment in 95% of samples.
• Detected 650 plant taxa, with 95% identified at the species level, and expanded the reference database by 93%.

Conclusions:

• The study presents a significantly improved laboratory and bioinformatical workflow for pollen meta-barcoding.
• The enhanced method offers improvements in data quantity, quality, processing efficiency, and cost-effectiveness.
• The protocol is applicable to other research requiring plant identification in mixed and challenging samples.