Phylogenetic relatedness drives protists assembly in marine and terrestrial environments

Aim: Assembly of protists communities is known to be driven mainly by environmental filtering, but the imprint of phylogenetic relatedness is unknown. In this study, we aim to test the degree at which co-occurrences and co-exclusions of protists in different phylogenetic relatedness classes are deviating from random expectation in two ecosystems in order to link them to ecological processes. Location: Global open-oceans and Neotropical rainforest soils Major taxa: Protists Time period: 2009-2013 Methods: Protist metabarcoding data originated from two large scale studies. Co-occurrence and co-exclusion networks were constructed using a recent method combining a null distribution model with Spearman’s rank correlation coefficients among pairs of OTU. Phylogenetic relatedness was estimated using either global pairwise sequence distance or phylogenetic distance inferred from best maximum-likelihood trees derived from multiple alignments of OTU representative sequences. Significance of obser..., Protistan OTUs from the world’s open oceans and seas came from de Vargas et al. (2015). This marine dataset is composed of 355 samples collected at the surface and deep chlorophyll maximum (DCM) in six oceans and two seas, which produced 366,800,845 protist reads of the V9 hyper-variable region of the SSU-rRNA locus that clustered into 302,663 OTUs. To allow for comparison, the version of this marine dataset used here was re-analyzed by Mahé et al. (2017). All filter-size classes libraries of either the surface or DCM at a single station were pooled together, thus the number of samples used here reduced to 47 for surface and 32 for DCM waters. This correspond to the \"Dataset S1\" of this archive which an OTU table provided into the standard JSON BIOM format. Protistan OTUs from three lowland Neotropical rainforests came from Mahé et al. (2017). This terrestrial dataset is composed of 144 samples collected at the soil surface, which produced 46,652,206 protist reads of the V4 hyper-variab..., The two dataset files follow the BIOM format (http://biom-format.org/).Ways to open these datasets are provided in section 2.1 and 2.2 of the \"File S1\".The \"File S1\" is a standard HTML file which can be open with any web browser.The full list of dependencies to run the analyses described in \"File S1\" is provide in the section 8 of this file.All files were produced and analysed using Linux operating systems (Ubuntu 18.04.4 on a personal computer and Debian 4.19.12-1 on an HPC).,研究目的：已知原生生物（Protists）群落构建主要受环境过滤作用驱动，但系统发育亲缘关系的印记效应尚未明确。本研究旨在检测两类生态系统中，不同系统发育亲缘关系类群的原生生物共现与互斥模式偏离随机预期的程度，进而将其与生态过程建立关联。 研究区域：全球开阔大洋与新热带区雨林土壤 主要研究类群：原生生物 研究时段：2009年—2013年 研究方法：原生生物宏条形码数据来自两项大规模研究。本研究采用最新方法构建共现与互斥网络，该方法结合了零分布模型与操作分类单元（Operational Taxonomic Unit，OTU）对间的斯皮尔曼秩相关系数。系统发育亲缘关系通过两种方式估算：一是全局成对序列距离，二是基于操作分类单元代表序列多序列比对构建的最优最大似然树所推导的系统发育距离。观测...的显著性 全球开阔大洋与海域的原生生物OTU数据来自de Vargas等人（2015年）的研究。该海洋数据集包含6个大洋与2个海域的355份表层与深层叶绿素最大值层（DCM）样品，共获得SSU-rRNA基因座V9高变区的原生生物读段366,800,845条，聚类得到302,663个OTU。为便于比较，本研究使用的海洋数据集版本由Mahé等人（2017年）重新分析得到。研究中将单个站位的表层或深层叶绿素最大值层的所有过滤尺寸分级文库合并，因此本研究使用的样品数量缩减为表层水47份、深层叶绿素最大值层水32份。该数据集对应本存档的「数据集S1」，其中提供了标准JSON格式的BIOM格式OTU表格。 三个新热带低地雨林的原生生物OTU数据来自Mahé等人（2017年）的研究。该陆地数据集包含144份土壤表层样品，共获得V4高变...的原生生物读段46,652,206条。 两份数据集文件均采用BIOM格式（http://biom-format.org/）。数据集的打开方法详见「文件S1」的2.1与2.2节。「文件S1」为标准HTML文件，可通过任意网页浏览器打开。运行「文件S1」中所述分析所需的全部依赖软件清单详见该文件的第8节。所有文件均基于Linux操作系统生成与分析（个人计算机使用Ubuntu 18.04.4，高性能计算集群（High Performance Computing，HPC）使用Debian 4.19.12-1）。