Phylogeny‐based assignment of functional traits to DNA barcodes outperforms distance‐based, in a comparison of approaches

Author:

Xie Tingting12ORCID,Orr Michael C.13,Zhang Dan1,Ferrari Rafael R.1,Li Yi14,Liu Xiuwei5,Niu Zeqing1,Wang Mingqiang1,Zhou Qingsong1,Hao Jiasheng2,Zhu Chaodong16ORCID,Chesters Douglas16ORCID

Affiliation:

1. Key Laboratory of Zoological Systematics and Evolution Institute of Zoology, Chinese Academy of Sciences Beijing China

2. College of Life Sciences Anhui Normal University Wuhu China

3. Entomologie Staatliches Museum für Naturkunde Stuttgart Stuttgart Germany

4. Institute of Botany Chinese Academy of Sciences Beijing China

5. Institute of Agro‐Products Processing Kunming China

6. International College University of Chinese Academy of Sciences Beijing China

Abstract

AbstractThe full potential for using DNA barcodes for profiling functional trait diversity has yet to be determined in plants and animals; thus, we outline a general framework for quantifying functional trait diversity of insect community DNA and propose and assess the accuracy of three methods for achieving this. We built a novel dataset of traits and DNA barcodes for wild bees in China. An informatics framework was developed for phylogeny‐based integration of these data and prediction of traits for any subject barcodes, which was compared with two distance‐based methods. For Phylogenetic Assignment, we additionally conducted a species‐level analysis of publically available bee trait data. Under the specimen‐level dataset, the rate of trait assignment was negatively correlated with distance between the query and the nearest trait‐known reference, for all methods. Phylogenetic Assignment was found to perform best under several criteria; particularly, it had the lowest false‐positive rate (rarely returning a state prediction where success was unlikely; where the distance from query to the nearest reference was high). For a wider range of compiled traits, conservative life‐history traits showed the highest rates of assignment; for example, sociality was predicted with confidence at 53%, parasitism at 44% and nest location at 33%. As outlined herein, automated trait assignment might be applied at scale to either barcodes or metabarcodes. With further compilation and databasing of DNA barcode and trait data, the rate and accuracy of trait assignment is expected to increase to the point of being a widely viable and informative approach.

Funder

National Natural Science Foundation of China

National Science Fund for Distinguished Young Scholars

Publisher

Wiley

Subject

Genetics,Ecology, Evolution, Behavior and Systematics,Biotechnology

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