基于DNA宏条形码技术的中国马铃薯农业生态系统昆虫生物多样性数据。

Data on insect biodiversity in a Chinese potato agroecosystem from DNA metabarcoding.

作者信息

Lin Changjin, Liu Chenxi, Chen Lilin, Cheng Hongmei, Ashfaq Muhammad, Hebert Paul D N, Gao Yulin

机构信息

Sino-American Biological Control Laboratory, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, 100193, PR China.

College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, Fujian, 350002, PR China.

出版信息

Sci Data. 2025 Jan 22;12(1):131. doi: 10.1038/s41597-025-04452-8.

DOI:10.1038/s41597-025-04452-8

PMID:39843438

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11754625/

Abstract

Potato (Solanum tuberosum) is a staple crop important in global food security. As a leading potato producer, China faces significant challenges from insect pest infestations that compromise yield and quality. However, insect communities within Chinese potato fields remain poorly characterized. This study aimed to explore insect diversity in potato fields in Yunnan Province. From autumn 2021 to summer 2022, five Malaise traps were strategically deployed to capture insect samples. In total, 245 samples were collected over 49 weeks, and DNA metabarcoding was performed on bulk samples. The generated sequences were curated and analyzed using the Barcode of Life Data System and the Multiplex Barcode Research and Visualization Environment. The analysis assigned sequences to 1,688 Barcode Index Numbers (BINs) as species proxies derived from the Global Insecta Library, along with 166 BINs from the China Insecta dataset. This research provides valuable insights for barcoding local biodiversity and developing regional reference libraries and presents a comprehensive dataset of insect biodiversity within potato agroecosystems, encompassing 1,707 BINs linked to known insect taxa.

摘要

马铃薯（Solanum tuberosum）是全球粮食安全中重要的主粮作物。作为马铃薯主要生产国，中国面临着因虫害导致产量和品质受损的重大挑战。然而，中国马铃薯田中的昆虫群落特征仍鲜为人知。本研究旨在探索云南省马铃薯田中的昆虫多样性。从2021年秋季至2022年夏季，在多处战略位置部署了5个马氏网诱捕器来采集昆虫样本。在49周内共收集了245个样本，并对混合样本进行了DNA宏条形码分析。使用生命条形码数据系统和多重条形码研究与可视化环境对生成的序列进行整理和分析。分析将序列归类为1688个来自全球昆虫库的作为物种代理的条形码索引号（BIN），以及来自中国昆虫数据集的166个BIN。本研究为当地生物多样性条形码编目和区域参考文库的开发提供了有价值的见解，并呈现了马铃薯农业生态系统内昆虫生物多样性的综合数据集，其中包括与已知昆虫分类群相关的1707个BIN。