Optimal sequence similarity thresholds for clustering of molecular operational taxonomic units in DNA metabarcoding studies

Clustering approaches are pivotal to handle the many sequence variants obtained in DNA metabarcoding data sets, and therefore they have become a key step of metabarcoding analysis pipelines. Clustering often relies on a sequence similarity threshold to gather sequences into molecular operational taxonomic units (MOTUs), each of which ideally represents a homogeneous taxonomic entity (e.g., a species or a genus). However, the choice of the clustering threshold is rarely justified, and its impact on MOTU over-splitting or over-merging even less tested. Here, we evaluated clustering threshold values for several metabarcoding markers under different criteria: limitation of MOTU over-merging, limitation of MOTU over-splitting, and trade-off between over-merging and over-splitting. We extracted sequences from a public database for nine markers, ranging from generalist markers targeting Bacteria or Eukaryota, to more specific markers targeting a class or a subclass (e.g., Insecta, Oligochaeta). Based on the distributions of pairwise sequence similarities within species and within genera, and on the rates of over-splitting and over-merging across different clustering thresholds, we were able to propose threshold values minimizing the risk of over-splitting, that of over-merging, or offering a trade-off between the two risks. For generalist markers, high similarity thresholds (0.96–0.99) are generally appropriate, while more specific markers require lower values (0.85–0.96). These results do not support the use of a fixed clustering threshold. Instead, we advocate careful examination of the most appropriate threshold based on the research objectives, the potential costs of over-splitting and over-merging, and the features of the studied markers.     

DNA barcoding reveals taxonomic uncertainty in Salminus (Characiformes)

Salminus is a genus composed of four species of migratory fishes and top predators. Although this group has great economic and ecological importance, the species level diversity of Salminus is not yet completely clarified. Our goal was to detect if this taxonomic problem is the consequence of lineage divergence within species, and, if so, whether these divergences are sufficient to flag potentially undescribed taxa. We employed the standard DNA barcoding analyses and a generalized mixed Yule-coalescent model (GMYC) using one mitochondrial (COI) marker and Bayesian Inference (BI) reconstruction for one nuclear (RAG2) marker for all currently recognized species of Salminus, sampled across different hydrographic basins. Eight MOTUs (Molecular Operational Taxonomic Units) were determined by distance and model-based analyses, and recovered with BI analyses for COI. Only Salminus affinis and Salminus franciscanus formed monophyletic haplogroups. Salminus brasiliensis and Salminus hilarii had two and four distinct mitochondrial lineages, respectively, and higher intraspecific K2P distances than the adopted optimum threshold. The RAG2 gene tree supported two lineages of S. hilarii (S. hilarii Amazon and S. hilarii Araguaia), while the other mitochondrial lineages of S. hilarii and S. brasiliensis were not supported. All lineages of both species, corresponded to morphological variation described in previous studies. We suggest, based on the DNA barcoding analysis, a new taxonomic scenario and conservation polices for Salminus in the Brazilian territory.     

DNA条形码技术在北京百花山地区夜蛾科物种鉴定中的应用

为了探讨DNA条形码技术在夜蛾物种鉴定中的可行性, 本研究利用条形码通用引物扩增了北京百花山地区43种夜蛾75个样本的线粒体细胞色素C氧化酶亚基I （mitochondrial cytochrome c oxidase subunit I, COI）基因序列, 以Kimura双参数模型进行种内种间遗传距离分析、 使用邻接法（neighbor-joining, NJ）和最大简约法（maximum parsimony, MP）分别构建系统发育树, 并利用分子序列差异阈值对样本进行分子可操作分类单元（molecular defined operational taxonomic units, MOTU）划分。结果表明： 所有夜蛾种类通过系统发育树可以成功区分; 种内平均遗传距离(0.03%)远远小于种间平均遗传距离(11.29%); 采用较为保守的1%的序列差异阈值将75个夜蛾样本分为42个MOTU, 正确率为95%, 除了MOTU04包含2个物种外, 剩余41个MOTU与形态种呈现一一对应的关系。结果显示, 基于COI基因的DNA条形码对于本研究中所涉及的夜蛾具有较好的区分, 可以作为一种有效的工具在夜蛾科昆虫物种鉴定中进行应用。     

How many replicates to accurately estimate fish biodiversity using environmental DNA on coral reefs?

Quantifying fish species diversity in rich tropical marine environments remains challenging. Environmental DNA (eDNA) metabarcoding is a promising tool to face this challenge through the filtering, amplification, and sequencing of DNA traces from water samples. However, because eDNA concentration is low in marine environments, the reliability of eDNA to detect species diversity can be limited. Using an eDNA metabarcoding approach to identify fish Molecular Taxonomic Units (MOTUs) with a single 12S marker, we aimed to assess how the number of sampling replicates and filtered water volume affect biodiversity estimates. We used a paired sampling design of 30 L per replicate on 68 reef transects from 8 sites in 3 tropical regions. We quantified local and regional sampling variability by comparing MOTU richness, compositional turnover, and compositional nestedness. We found strong turnover of MOTUs between replicated pairs of samples undertaken in the same location, time, and conditions. Paired samples contained non‐overlapping assemblages rather than subsets of one another. As a result, non‐saturated localized diversity accumulation curves suggest that even 6 replicates (180 L) in the same location can underestimate local diversity (for an area <1 km). However, sampling regional diversity using ~25 replicates in variable locations (often covering 10 s of km) often saturated biodiversity accumulation curves. Our results demonstrate variability of diversity estimates possibly arising from heterogeneous distribution of eDNA in seawater, highly skewed frequencies of eDNA traces per MOTU, in addition to variability in eDNA processing. This high compositional variability has consequences for using eDNA to monitor temporal and spatial biodiversity changes in local assemblages. Avoiding false‐negative detections in future biomonitoring efforts requires increasing replicates or sampled water volume to better inform management of marine biodiversity using eDNA.     

SPdel: A pipeline to compare and visualize species delimitation methods for single-locus datasets

An accurate species delimitation is critical for biological studies. In this context, the use of molecular techniques along with species delimitation methods would help to a rapid and accurate biodiversity assessment. The species delimitation methods cluster data sets of orthologous sequences in molecular operational taxonomic units (MOTU). In particular, the methods based on a single gene are easily integrated with the widely used DNA barcoding approach. We developed SPdel a user-friendly pipeline to integrate different single-gene species delimitation methods. SPdel is designed to calculate and compare MOTUs obtained by different species delimitation approaches. SPdel also outputs diverse ready-to-publish quality figures, that facilitate the interpretation of results. SPdel aims to help researchers use species delimitation methods that would improve biodiversity studies.