{Reference Type}: Journal Article
{Title}: Algorithms and strategies in short-read shotgun metagenomic reconstruction of plant communities.
{Author}: Harbert RS;
{Journal}: Appl Plant Sci
{Volume}: 6
{Issue}: 3
{Year}: Mar 2018
{Factor}: 2.511
{DOI}: 10.1002/aps3.1034
{Abstract}: <B>OBJECTIVE: </B>DNA may be preserved for thousands of years in very cold or dry environments, and plant tissue fragments and pollen trapped in soils and shallow aquatic sediments are well suited for the molecular characterization of past floras. However, one obstacle in this area of study is the limiting bias in the bioinformatic classification of short fragments of degraded DNA from the large, complex genomes of plants.<BR><B>METHODS: </B>To establish one possible baseline protocol for the rapid classification of short-read shotgun metagenomic data for reconstructing plant communities, the read classification programs Kraken, Centrifuge, and MegaBLAST were tested on simulated and ancient data with classification against a reference database targeting plants.<BR><B>RESULTS: </B>Performance tests on simulated data suggest that Kraken and Centrifuge outperform MegaBLAST. Kraken tends to be the most conservative approach with high precision, whereas Centrifuge has higher sensitivity. Reanalysis of 13,000 years of ancient sedimentary DNA from North America characterizes potential post-glacial vegetation succession.<BR><B>CONCLUSIONS: </B>Classification method choice has an impact on performance and any downstream interpretation of results. The reanalysis of ancient DNA from glacial lake sediments yielded vegetation histories that varied depending on method, potentially changing paleoecological conclusions drawn from molecular evidence.