Data from: PrimerMiner: an R package for development and in silico validation of DNA metabarcoding primers

1. DNA metabarcoding is a powerful tool to assess biodiversity by amplifying and sequencing a standardized gene marker region. Its success is often limited due to variable binding sites that introduce amplification biases. Thus the development of optimized primers for communities or taxa under study in a certain geographic region and/or ecosystems is of critical importance. However, no tool for obtaining and processing of reference sequence data in bulk that can serve as a backbone for primer design is currently available.

2. We developed the R package PrimerMiner, which batch downloads DNA barcode gene sequences from BOLD and NCBI databases for specified target taxonomic groups and then applies sequence clustering into operational taxonomic units (OTUs) to reduce biases introduced by the different number of available sequences per species. Additionally, PrimerMiner offers functionalities to evaluate primers in silico, which are in our opinion more realistic then the strategy employed in another available software for that purpose, ecoPCR.

3. We used PrimerMiner to download cytochrome c oxidase subunit I (COI) sequences for 15 important freshwater invertebrate groups, relevant for ecosystem assessment. By processing COI markers from both databases, we were able to increase the amount of reference data 249-fold on average, compared to using complete mitochondrial genomes alone. Furthermore, we visualized the generated OTU sequence alignments and describe how to evaluate primers in silico using PrimerMiner.

4. With PrimerMiner we provide a useful tool to obtain relevant sequence data for targeted primer development and evaluation. The OTU based reference alignments generated with PrimerMiner can be used for manual primer design, or processed with bioinformatic tools for primer development.

1. DNA宏条形码技术（DNA metabarcoding）是通过扩增并测序标准化基因标记区域以评估生物多样性的强有力工具。其应用效果常受结合位点变异性引发的扩增偏好性制约。因此，针对特定地理区域和/或生态系统中研究的群落或类群开发优化引物，具有至关重要的意义。然而，目前尚无能够批量获取并处理参考序列数据、可作为引物设计核心支撑的工具。
2. 本研究开发了R语言工具包PrimerMiner，该工具可针对指定目标分类类群，从BOLD与NCBI数据库中批量下载DNA条形码基因序列，随后将序列聚类为操作分类单元（operational taxonomic units, OTUs），以缓解因不同物种可获取序列数量差异引入的偏好性偏差。此外，PrimerMiner还提供了计算机模拟（in silico）引物评估功能，我们认为该策略相较于现有同类工具ecoPCR所采用的方案更为贴合实际应用场景。
3. 本研究利用PrimerMiner，针对15种与生态系统评估相关的重要淡水无脊椎动物类群，下载了细胞色素c氧化酶亚基I（cytochrome c oxidase subunit I, COI）序列。通过整合处理两个数据库中的COI标记序列数据，相较于仅使用完整线粒体基因组的情况，参考数据量平均提升了249倍。此外，本研究还对生成的OTU序列比对结果进行了可视化，并说明了如何利用PrimerMiner开展计算机模拟引物评估。
4. 本研究通过PrimerMiner为靶向引物的开发与评估提供了一款实用工具。利用PrimerMiner生成的基于OTU的参考序列比对结果，既可用于人工引物设计，也可通过生物信息学工具进一步处理以开展引物开发工作。