Data from: DNA metabarcoding multiplexing and validation of data accuracy for diet assessment: application to omnivorous diet

Ecological understanding of the role of consumer-resource interactions in natural food webs is limited by the difficulty of accurately and efficiently determining the complex variety of food types animals have eaten in the field. We developed a method based on DNA metabarcoding multiplexing and next-generation sequencing to uncover different taxonomic groups of organisms from complex diet samples. We validated this approach on 91 faeces of a large omnivorous mammal, the brown bear, using DNA metabarcoding markers targeting the plant, vertebrate, and invertebrate components of the diet. We included internal controls in the experiments and performed PCR replication for accuracy validation in post-sequencing data analysis. Using our multiplexing strategy, we significantly simplified the experimental procedure and accurately and concurrently identified different prey DNA corresponding to the targeted taxonomic groups, with ≥60% of taxa of all diet components identified to genus/species level. The systematic application of internal controls and replication was a useful and simple way to evaluate the performance of our experimental procedure, standardize the selection of sequence filtering parameters for each marker data, and validate the accuracy of the results. Our general approach can be adapted to the analysis of dietary samples of various predator species in different ecosystems, for a number of conservation and ecological applications entailing large-scale population level diet assessment through cost effective screening of multiple DNA metabarcodes, and the detection of fine dietary variation among samples or individuals and of rare food items.当前学界对自然食物网中消费者-资源相互作用的生态功能的认知，受限于难以精准且高效地确定动物在野外实际摄食的复杂多样食物类型。我们开发了一种基于DNA宏条形码（DNA metabarcoding）多重扩增与下一代测序（next-generation sequencing）的方法，可从复杂的饮食样本中识别出不同分类类群的生物。我们以91份大型杂食性哺乳动物棕熊的粪便样本为研究对象，使用针对饮食中植物、脊椎动物与无脊椎动物组分的DNA宏条形码标记，对该方法进行了验证。本实验设置了内参对照（internal controls），并在测序后数据分析阶段通过PCR重复（PCR replication）实验对结果准确性进行验证。通过采用该多重扩增策略，我们大幅简化了实验流程，可精准同时鉴定出对应目标分类类群的不同猎物DNA，所有饮食组分中≥60%的分类单元均可鉴定至属/种水平。系统性应用内参对照与重复实验，可简便有效地评估实验流程的表现，统一各标记数据的序列过滤参数选择标准，并验证结果的准确性。我们的通用方法可适配不同生态系统中各类捕食者物种的饮食样本分析，可应用于多项保护与生态研究场景：包括通过成本高效的多重DNA宏条形码筛选开展大规模种群水平的饮食评估，同时可检测样本或个体间的细微饮食差异以及稀有食物类群。