High-throughput methods for efficiently building massive phylogenies from natural history collections

从自然历史收藏中高效构建大规模系统发育的高通量方法

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作者:Ryan A Folk, Heather R Kates, Raphael LaFrance, Douglas E Soltis, Pamela S Soltis, Robert P Guralnick

Discussion

The approach we present is appropriate at any taxonomic scale and is extensible to other collection types. The widespread use of large-scale sampling strategies repositions herbaria as accessible but largely untapped resources for broad taxonomic sampling with thousands of species.

Methods

We developed an integrated Specimen-to-Laboratory Information Management System (SLIMS), connecting sampling and wet lab efforts with progress tracking at each stage. Using unique identifiers encoded in QR codes and a taxonomic database, a research team can sample herbarium specimens, efficiently record the sampling event, and capture specimen images. After sampling in herbaria, images are uploaded to a citizen science platform for metadata generation, and tissue samples are moved through a simple, high-throughput, plate-based herbarium DNA extraction and sequencing protocol.

Results

We applied this sampling-to-sequencing workflow to ~15,000 species, producing for the first time a data set with ~50% taxonomic representation of the "nitrogen-fixing clade" of angiosperms.

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