Following the recent publication of our plant DNA barcode library from Mpala Research Centre, Kenya, led by Brian Gill, we are happy to provide a set of files to serve as our local trnL-P6 reference library (version 2.0). These files were carefully prepared by Courtney Reed, to whom we are most grateful.
The reference library is provided below. We will post occasional updates as new data become incorporated. (To be sure you are working with the most current version, please check the link to "Data" under Categories in the panel to the right to see if there are more recent updates).
Version 2.0 corresponds exactly to the trnL dataset and taxonomic identifications included in the Gill et al. 2019 Molecular Ecology Resources paper. This replaces Version 1.0 of the library, from the publication of our first Mpala DNA metabarcoding study (Kartzinel et al. 2015, PNAS), which is archived on here on Dryad (together with other datasets presented in that study).
The Mpala plant DNA barcoding project is a collaboration between Mpala Research Centre, The East African Herbarium, National Museums of Kenya, the Smithsonian Institution, Princeton University, and Brown University. Links to the current set of publicly available data associated with this project can be found on the Barcode of Life Datasystems (www.boldsystems.org) under the project name UHURU.
We are grateful to the Government of Kenya for permission to conduct this research. We are especially grateful to Sam Kurukura, Ali Hassan, Peter Lokeny, and Dr. Mutuku Musili for the painstaking efforts required to archive and identify these invaluable research specimens.
The data files follow this brief description: These data files were kindly provided by Courtney Reed in February 2019. The reference library was extracted from the trnL sequence set provided in the Gill et al. publication and formatted to serve as a the trnL-P6 reference database using the program Obitools. If you have a relevant metabarcoding dataset in fasta format, these files should include everything necessary to identify each sequence using the ecoTag function in Obitools
Computational resources kindly contributed and explained by members of our community.