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能否根据序列数据推断原生生物的丰度:以有孔虫为例的一项研究。

Can abundance of protists be inferred from sequence data: a case study of foraminifera.

机构信息

Department of Genetic and Evolution, University of Geneva, Sciences III, Genève, Switzerland.

出版信息

PLoS One. 2013;8(2):e56739. doi: 10.1371/journal.pone.0056739. Epub 2013 Feb 19.

Abstract

Protists are key players in microbial communities, yet our understanding of their role in ecosystem functioning is seriously impeded by difficulties in identification of protistan species and their quantification. Current microscopy-based methods used for determining the abundance of protists are tedious and often show a low taxonomic resolution. Recent development of next-generation sequencing technologies offered a very powerful tool for studying the richness of protistan communities. Still, the relationship between abundance of species and number of sequences remains subjected to various technical and biological biases. Here, we test the impact of some of these biological biases on sequence abundance of SSU rRNA gene in foraminifera. First, we quantified the rDNA copy number and rRNA expression level of three species of foraminifera by qPCR. Then, we prepared five mock communities with these species, two in equal proportions and three with one species ten times more abundant. The libraries of rDNA and cDNA of the mock communities were constructed, Sanger sequenced and the sequence abundance was calculated. The initial species proportions were compared to the raw sequence proportions as well as to the sequence abundance normalized by rDNA copy number and rRNA expression level per species. Our results showed that without normalization, all sequence data differed significantly from the initial proportions. After normalization, the congruence between the number of sequences and number of specimens was much better. We conclude that without normalization, species abundance determination based on sequence data was not possible because of the effect of biological biases. Nevertheless, by taking into account the variation of rDNA copy number and rRNA expression level we were able to infer species abundance, suggesting that our approach can be successful in controlled conditions.

摘要

原生动物是微生物群落中的关键成员,但由于鉴定原生动物物种及其数量的困难,我们对它们在生态系统功能中的作用的理解受到严重阻碍。目前用于确定原生动物丰度的基于显微镜的方法繁琐,并且通常显示出低分类分辨率。新一代测序技术的最新发展为研究原生动物群落的丰富度提供了非常强大的工具。尽管如此,物种丰度与序列数量之间的关系仍然受到各种技术和生物偏差的影响。在这里,我们测试了其中一些生物偏差对有孔虫的 SSU rRNA 基因序列丰度的影响。首先,我们通过 qPCR 定量测定了三种有孔虫的 rDNA 拷贝数和 rRNA 表达水平。然后,我们用这三种物种制备了五个模拟群落,其中两种以相等的比例,三种以一种物种的十倍丰度。构建了 rDNA 和 cDNA 的模拟群落文库,进行 Sanger 测序并计算了序列丰度。将初始物种比例与原始序列比例以及按 rDNA 拷贝数和每个物种的 rRNA 表达水平归一化的序列丰度进行了比较。我们的结果表明,在没有归一化的情况下,所有序列数据与初始比例差异显著。归一化后,序列数量与标本数量之间的一致性要好得多。我们得出的结论是,由于生物偏差的影响,在没有归一化的情况下,基于序列数据确定物种丰度是不可能的。然而,通过考虑 rDNA 拷贝数和 rRNA 表达水平的变化,我们能够推断出物种的丰度,这表明我们的方法在受控条件下可以取得成功。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9809/3576339/14e320d96bc8/pone.0056739.g001.jpg

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