Assembly-free reads accurate identification (AFRAID) approach outperforms other methods of DNA barcoding in the walnut family (Juglandaceae)

Abstract

DNA barcoding has been extensively used for species identification. However, species identification of mixed samples or degraded DNA is limited by current DNA barcoding methods. In this study, we use plant species in Juglandaceae to evaluate an assembly-free accurate reads identification (AFRAID) method of species identification, a novel approach for precise species identification in plants. Specifically, we determined (1) the accuracy of DNA barcoding approaches in delimiting species in Juglandaceae, (2) the minimum size of chloroplast dataset for species discrimination, and (3) minimum amount of next generation sequencing (NGS) data required for species identification. We found that species identification rates were highest when whole chloroplast genomes were used, followed by taxon-specific DNA barcodes, and then universal DNA barcodes. Species identification of 100% was achieved when chloroplast genome sequence coverage reached 20% and the original sequencing data reached 500,000 reads. AFRAID accurately identified species for all samples tested after 500,000 clean reads, with far less computing time than common approaches. These results provide a new approach to accurately identify species, overcoming limitations of traditional DNA barcodes. Our method, which uses next generation sequencing to generate partial chloroplast genomes, reveals that DNA barcode regions are not necessarily fixed, accelerating the process of species identification.