Sample Preservation, DNA or RNA Extraction and Data Analysis for High-Throughput Phytoplankton Community Sequencing.
Sample Preservation, DNA or RNA Extraction and Data Analysis for High-Throughput Phytoplankton Community Sequencing.
复制标题
高通量浮游植物群落序列测定中的样品保存、DNA或RNA提取和数据分析
DOI：
10.3389/fmicb.2017.01848
复制
发表时间：
2017
影响因子：
5.2
通讯作者：
Tiirola M
中科院分区：
文献类型：
--
作者：
Mäki A;Salmi P;Mikkonen A;Kremp A;Tiirola M
浮游植物是水生食物网的基础，反映了水质。传统上，浮游植物分析已经完成了耗时和部分主观的显微镜观察，但下一代测序（NGS）技术提供了有前途的潜力，快速自动化检测环境样品。由于许多浮游植物物种具有坚韧的细胞壁，因此细胞裂解和DNA或RNA分离的方法需要是有效的，以允许无偏见的核酸检索。在这里，我们分析了两种浮游植物保存方法，三种商业DNA提取试剂盒及其改进，三种RNA提取方法，以及两种数据分析程序如何影响NGS分析的结果。一个模拟社区汇集从浮游植物种类的变化，细胞核大小和细胞壁硬度。虽然这项研究显示了研究卢戈保存的样本收集的潜力，但它表明了基于DNA的浮游植物分析总体上面临的关键挑战。18S rRNA基因测序输出受到每个细胞rRNA基因拷贝数变化的高度影响，而样品保存和核酸提取方法形成了另一个变异来源。在顶部，当滑动窗口方法用于Ion Torrent数据的质量修整时，数据质量中的序列特异性变化引入了意外的生物信息学偏倚。虽然基于DNA的分析与模拟群落的生物量或细胞数量没有相关性，但基于rRNA的分析受不同RNA提取程序的影响较小，并且与生物量，干重和碳含量更好地匹配，因此推荐用于浮游植物定量分析。
Phytoplankton is the basis for aquatic food webs and mirrors the water quality. Conventionally, phytoplankton analysis has been done using time consuming and partly subjective microscopic observations, but next generation sequencing (NGS) technologies provide promising potential for rapid automated examination of environmental samples. Because many phytoplankton species have tough cell walls, methods for cell lysis and DNA or RNA isolation need to be efficient to allow unbiased nucleic acid retrieval. Here, we analyzed how two phytoplankton preservation methods, three commercial DNA extraction kits and their improvements, three RNA extraction methods, and two data analysis procedures affected the results of the NGS analysis. A mock community was pooled from phytoplankton species with variation in nucleus size and cell wall hardness. Although the study showed potential for studying Lugol-preserved sample collections, it demonstrated critical challenges in the DNA-based phytoplankton analysis in overall. The 18S rRNA gene sequencing output was highly affected by the variation in the rRNA gene copy numbers per cell, while sample preservation and nucleic acid extraction methods formed another source of variation. At the top, sequence-specific variation in the data quality introduced unexpected bioinformatics bias when the sliding-window method was used for the quality trimming of the Ion Torrent data. While DNA-based analyses did not correlate with biomasses or cell numbers of the mock community, rRNA-based analyses were less affected by different RNA extraction procedures and had better match with the biomasses, dry weight and carbon contents, and are therefore recommended for quantitative phytoplankton analyses.
登录
查看更多内容
影响因子：
7.7
作者：
Decelle, Johan;Romac, Sarah;Christen, Richard
通讯作者：
Christen, Richard
影响因子：
12.8
作者：
Eland, Lucy E.;Davenport, Russell;Mota, Cesar R.
通讯作者：
Mota, Cesar R.
影响因子：
4.4
作者：
Schloss, Patrick D.;Westcott, Sarah L.;Weber, Carolyn F.
通讯作者：
Weber, Carolyn F.
影响因子：
3.7
作者：
Macmanes MD
通讯作者：
Macmanes MD
DOI：
10.1111/jeu.12425
发表时间：
2017-11
期刊：
The Journal of eukaryotic microbiology
影响因子：
--
作者：
Fu R;Gong J
通讯作者：
Gong J