Genotyping by sequencing for estimating relative abundances of diatom taxa in mock communities.

Ozan Çiftçi, Cornelis A M Wagemaker, Adrienne Mertens, Peter van Bodegom, Walter Pirovano, Barbara Gravendeel
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Abstract

Background: Diatoms are present in all waters and are highly sensitive to pollution gradients. Therefore, they are ideal bioindicators for water quality assessment. Current indices used in these applications are based on identifying diatom species and counting their abundances using traditional light microscopy. Several molecular techniques have been developed to help automate different steps of this process, but obtaining reliable estimates of diatom community composition and species abundance remains challenging.

Results: Here, we evaluated a recently developed quantification method based on Genotyping by Sequencing (GBS) for the first time in diatoms to estimate the relative abundances within a species complex. For this purpose, a reference database comprised of thousands of genomic DNA clusters was generated from cultures of Nitzschia palea. The sequencing reads from calibration and mock samples were mapped against this database for parallel quantification. We sequenced 25 mock diatom communities containing up to five taxa per sample in different abundances. Taxon abundances in these communities were also quantified by a diatom expert using manual counting of cells on light microscopic slides. The relative abundances of strains across mock samples were over- or under-estimated by the manual counting method, and a majority of mock samples had stronger correlations using GBS. Moreover, one previously recognized putative hybrid had the largest number of false positive detections demonstrating the limitation of the manual counting method when morphologically similar and/or phylogenetically close taxa are analyzed.

Conclusions: Our results suggest that GBS is a reliable method to estimate the relative abundances of the N. palea taxa analyzed in this study and outperformed traditional light microscopy in terms of accuracy. GBS provides increased taxonomic resolution compared to currently available quantitative molecular approaches, and it is more scalable in the number of species that can be analyzed in a single run. Hence, this is a significant step forward in developing automated, high-throughput molecular methods specifically designed for the quantification of [diatom] communities for freshwater quality assessments.

Abstract Image

Abstract Image

模拟群落中硅藻类群相对丰度的基因分型分析。
背景:硅藻存在于所有水域,对污染梯度高度敏感。因此,它们是水质评价的理想生物指标。目前在这些应用中使用的指数是基于识别硅藻种类并使用传统光学显微镜计算其丰度。已经开发了几种分子技术来帮助自动化这一过程的不同步骤,但获得可靠的硅藻群落组成和物种丰度估计仍然具有挑战性。结果:在这里,我们首次在硅藻中评估了一种基于基因分型测序(GBS)的定量方法,以估计物种复合体内的相对丰度。为此,从古尼氏菌培养物中生成了由数千个基因组DNA簇组成的参考数据库。校准样品和模拟样品的测序读数被映射到该数据库进行并行定量。我们对25个模拟硅藻群落进行了测序,每个样本最多包含5个不同丰度的分类群。这些群落的分类群丰度也由一位硅藻专家在光显微镜载玻片上手工计数细胞进行了量化。通过人工计数方法,模拟样本中菌株的相对丰度被高估或低估,并且大多数模拟样本使用GBS具有更强的相关性。此外,一种先前公认的假定杂交有最多的假阳性检测,这表明在分析形态相似和/或系统发育接近的分类群时,人工计数方法的局限性。结论:GBS是一种可靠的方法来估计本研究分析的古孢粉分类群的相对丰度,并且在准确性方面优于传统的光学显微镜。与目前可用的定量分子方法相比,GBS提供了更高的分类分辨率,并且在单次运行中可以分析的物种数量方面更具可扩展性。因此,这是在开发自动化、高通量分子方法方面迈出的重要一步,该方法专门设计用于淡水质量评估的[硅藻]群落定量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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