Related Experiment Video
Updated: Apr 13, 2026

A Noninvasive Hair Sampling Technique to Obtain High Quality DNA from Elusive Small Mammals
Published on: March 13, 2011
Assembling and dietary application of a local trnL metabarcoding database for Cervusnipponkopschi in Taohongling
Yuqin Liu1, Dandan Wang1, Zhiming Cao1
1Jiangxi Provincial Key Laboratory for Conservation Biology, Jiangxi Agricultural University, Nanchang, China Jiangxi Provincial Key Laboratory for Conservation Biology, Jiangxi Agricultural University Nanchang China.
Abstract:
The quality and completeness of the reference database have a direct impact on the accuracy of forage plant identification, thereby influencing the level of conservation and management of wildlife resources. In our research, target amplification was subjected to first-generation sequencing to assemble a local reference database using chloroplast trnL metabarcoding. We found that the primers c-h outperformed g-h as a universal DNA metabarcoding and 162 valid choloroplast trnL sequences were submitted (GenBank ID: PP081756 - PP081917), which exhibited an obvious preference for A and T nucleotides (60.49%). The haplotype diversity (Hd), nucleotide diversity (Pi) and average number of nucleotide differences (K) of these trnL sequences were 0.978, 0.0484 and 4.743, respectively. To assess the availability of the local database in identifying the diet of South China sika deer (Cervusnipponkopschi), high-throughput metabarcoding sequencing and BLAST analysis were performed. Ultimately, 25 forage plant species were identified, belonging to 19 families and 25 genera. Shrubs and herbaceous plants, such as Potentillafreyniana, Persicariaperfoliata, Rosalaevigata and Ardisiajaponica etc, dominated the forage plants. This study established a local trnL reference database that holds immense value for the forage plant identification and nutritional evaluation for sika deer and other sympatric herbivores, as well as the conservation and management of biodiversity.
Related Concept Videos
Modern Molecular Taxonomy
Applications of Molecular Taxonomy

