Optimisation of a pollen DNA metabarcoding method for diet analysis of flying-foxes (Pteropus spp.)

Author:

Bell Karen L.ORCID,Batchelor Kathryn L.,Bradford Matt,McKeown Adam,Macdonald Stewart L.ORCID,Westcott David

Abstract

Determining the diet of flying-foxes can increase understanding of how they function as pollinators and seed dispersers, as well as managing any negative impacts of large roosts. Traditional methods for diet analysis are time consuming, and not feasible to conduct for hundreds of animals. In this study, we optimised a method for diet analysis, based on DNA metabarcoding of environmental DNA (eDNA) from pollen and other plant parts in the faeces. We found that existing eDNA metabarcoding protocols are suitable, with the most useful results being obtained using a commercial food DNA extraction kit, and sequencing 350–450 base pairs of a DNA barcode from the internally transcribed spacer region (ITS2), with ~550 base pairs of the chloroplast rubisco large subunit (rbcL) as a secondary DNA barcode. A list of forage plants was generated for the little red flying-fox (Pteropus scapulatus), the black flying-fox (Pteropus alecto) and the spectacled flying-fox (Pteropus conspicillatus) from our collection sites across Queensland. The diets were determined to comprise predominantly Myrtaceae species, particularly those in the genera Eucalyptus, Melaleuca and Corymbia. With more plant genomes becoming publicly available in the future, there are likely to be further applications of eDNA methods in understanding the role of flying-foxes as pollinators and seed dispersers.

Publisher

CSIRO Publishing

Subject

Animal Science and Zoology,Ecology, Evolution, Behavior and Systematics

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3