Department of Integrative Marine Ecology, Stazione Zoologica Anton Dohrn, Villa Comunale, 80121, Naples, Italy.
Environ Microbiol. 2020 May;22(5):1917-1929. doi: 10.1111/1462-2920.14984. Epub 2020 Mar 25.
High-throughput sequencing (HTS) metabarcoding is commonly applied to assess phytoplankton diversity. Usually, haplotypes are grouped into operational taxonomic units (OTUs) through clustering, whereby the resulting number of OTUs depends on chosen similarity thresholds. We applied, instead, a phylogenetic approach to infer taxa among 18S rDNA V4-metabarcode haplotypes gathered from 48 time-series samples using the marine planktonic diatoms Chaetoceros and Bacteriastrum as test case. The 73 recovered taxa comprised both solitary haplotypes and polytomies, the latter composed each of a highly abundant, dominant haplotype and one to several minor, peripheral haplotypes. The solitary and dominant haplotypes usually matched reference sequences, enabling species assignation of taxa. We hypothesise that the super-abundance of reads in dominant haplotypes results from the homogenization effect of concerted evolution. Reads of populous peripheral haplotypes and dominant haplotypes show comparable distribution patterns over the sample dates, suggesting that they are part of the same population. Many taxa revealed marked seasonality, with closely related ones generally showing distinct periodicity, whereas others occur year-round. Phylogenies inferred from metabarcode haplotypes enable delineation of biologically meaningful taxa, whereas OTUs resulting from clustering algorithms often deviate markedly from such taxa.
高通量测序 (HTS) 代谢组学通常用于评估浮游植物多样性。通常,通过聚类将单倍型分组为分类操作单元 (OTU),其中 OTU 的数量取决于所选的相似性阈值。我们应用了一种系统发育方法来推断从 48 个时间序列样本中收集的 18S rDNA V4 代谢组单倍型中的分类群,使用海洋浮游硅藻 Chaetoceros 和 Bacteriastrum 作为测试案例。73 个回收的分类群包括单倍型和多态性,后者由一个高度丰富的、优势单倍型和一个到几个次要的、外围的单倍型组成。孤立的和主要的单倍型通常与参考序列匹配,从而能够对分类群进行物种分配。我们假设,在主要单倍型中读取的超丰富是协同进化的均匀化效应的结果。流行的外围单倍型和主要单倍型的读取具有可比的分布模式,表明它们是同一群体的一部分。许多分类群表现出明显的季节性,密切相关的分类群通常具有明显的周期性,而其他分类群则全年存在。从代谢组单倍型推断出的系统发育树能够描绘出具有生物学意义的分类群,而聚类算法产生的 OTU 通常与这些分类群明显不同。