Data from: Genomic evidence for global ocean plankton biogeography shaped by large-scale current systems

Biogeographical studies have traditionally focused on readily visible organisms, but recent technological advances are enabling analyses of the large-scale distribution of microscopic organisms, whose biogeographical patterns have long been debated. Here we assessed the global structure of plankton geography and its relation to the biological, chemical and physical context of the ocean (the 'seascape') by analyzing metagenomes of plankton communities sampled across oceans during the Tara Oceans expedition, in light of environmental data and ocean current transport. Using a consistent approach across organismal sizes that provides unprecedented resolution to measure changes in genomic composition between communities, we report a pan-ocean, size-dependent plankton biogeography overlying regional heterogeneity. We found robust evidence for a basin-scale impact of transport by ocean currents on plankton biogeography, and on a characteristic timescale of community dynamics going beyond simple seasonality or life history transitions of plankton. Supplementary Table 1. List of Tara Oceans samples sequenced with a metabarcoding (18S V9) approach and with a metagenomic approach, including identifiers for sequencing reads deposited in the DDBJ/ENA/GenBank Short Read Archives (SRA). [This Table is identical in version 2.] Supplementary Table 2. Table of environmental parameters for each sample. [This Table is identical in version 2.] Supplementary Table 3. Matrix of metagenomic dissimilarity for the 0-0.22 μm size fraction. [This Table is identical in version 2.] Supplementary Table 4. Matrix of metagenomic dissimilarity for the 0.22-1.6/3 μm size fraction. [This Table is identical in version 2.] Supplementary Table 5. Matrix of metagenomic dissimilarity for the 0.8-5 μm size fraction. [This Table is identical in version 2.] Supplementary Table 6. Matrix of metagenomic dissimilarity for the 5-20 μm size fraction. [This Table is identical in version 2.] Supplementary Table 7. Matrix of metagenomic dissimilarity for the 20-180 μm size fraction. [This Table is identical in version 2.] Supplementary Table 8. Matrix of metagenomic dissimilarity for the 180-2000 μm size fraction. [This Table is identical in version 2.] Supplementary Table 9. Matrix of OTU dissimilarity for the 0-0.22 μm size fraction. [This Table is identical in version 2.] Supplementary Table 10. Matrix of OTU dissimilarity for the 0.22-1.6/3 μm size fraction. [This Table is identical in version 2.] Supplementary Table 11. Matrix of OTU dissimilarity for the 0.8-5 μm size fraction. [This Table is identical in version 2.] Supplementary Table 12. Matrix of OTU dissimilarity for the 5-20 μm size fraction. [This Table is identical in version 2.] Supplementary Table 13. Matrix of OTU dissimilarity for the 20-180 μm size fraction. [This Table is identical in version 2.] Supplementary Table 14. Matrix of OTU dissimilarity for the 180-2000 μm size fraction. [This Table is identical in version 2.] Supplementary Table 15. Matrix of minimum travel time, in years. [This Table is identical in version 2.] Supplementary Table 16. Matrix of minimum geographic distance (without traversing land), in kilometers. [This Table is identical in version 2.] Supplementary Table 17. Matrix of imaging-based dissimilarity. [This Table is identical in version 2.] Supplementary Table 18. Matrix of metagenome-assembled genome (MAG)-based dissimilarity for the 20-180 μm size fraction. [The filename of this Table was modified from version 2. The contents of the Table are identical.] Supplementary Table 19. The cophenetic correlation coefficient for different methods of clustering metagenomic dissimilarity. [This Table is identical in version 2.] Supplementary Table 20. Baker's Gamma index comparing clustering results within size fractions. [This Table is identical in version 2.] Supplementary Table 21. Rand Index for K-means and spectral clustering, and multivariate ANOVA calculated by the adonis function. [This Table is identical in version 2.] Dataset 1. Reference database (in FASTA format) used to perform taxonomic assignment of metabarcodes. The header line of each reference V9 rDNA barcode (with a > sign) contains a unique identifier derived from GenBank accession number, followed by the taxonomic path associated to the reference barcode. [This Dataset is identical in version 2.] Dataset 2. V9 rDNA abundance at the metabarcode level. md5sum = unique identifier; totab = total abundance across all samples; cid = identifier of the OTU to which the barcode belongs (see Dataset 3); pid = best percentage identity to a barcode in Dataset 1; refs = identifier(s) of the best matching barcode(s) in Dataset 1; lineage = taxononmic lineage of the best match in Dataset 1; taxogroup = high-level taxonomic grouping of the best match in Dataset 1; sequence = V9 rDNA sequence; TV9_XXX = barcode abundance by sample (see Supplementary Table 1 for sample identifiers). [This Dataset is identical in version 2.] Dataset 3. V9 rDNA abundance at the OTU (operational taxonomic unit) level. cid = identifier of the OTU; md5sum = unique identifier of the most abundant barcode in the OTU; pid, refs, lineage, taxogroup, sequence = defined as in Dataset 2; rtotab = total abundance of the most abundant barcode in the OTU; ctotab = total abundance of all barcodes in the OTU; TV9_XXX = abundance by sample of all barcodes in the OTU (see Supplementary Table 1 for sample identifiers). [This Dataset is identical in version 2.] Dataset 4. Relative abundances of metagenome-assembled genomes (MAGs) in metagenomic samples from the 20-180 μm size fraction. [This Dataset is new in version 3.]

生物地理学研究传统上多聚焦于肉眼易见的大型生物，但近年来技术进步使得学界得以开展微型生物的全球分布分析——这类生物的生物地理分布格局长期以来存在学术争议。本研究依托塔拉海洋（Tara Oceans）科考项目在全球大洋采集的浮游生物群落宏基因组（metagenome）数据，结合环境观测数据与洋流输运机制，解析了浮游生物地理分布的全球格局及其与海洋生物、化学、物理环境（即"海洋景观"seascape）的关联。本研究采用统一的分析框架覆盖不同粒径级别的浮游生物，实现了前所未有的分辨率以量化群落间基因组组成差异，最终揭示了横跨全球大洋、依粒径大小分化的浮游生物生物地理格局，且该格局叠加了区域异质性特征。本研究获得了确凿可信的证据，证明洋流输运对大洋盆地尺度下的浮游生物生物地理格局存在显著影响，且群落动态的特征时间尺度远超单纯的季节波动或浮游生物的生活史转变过程。

补充表1：采用扩增子条形码测序（metabarcoding，18S V9区域）与宏基因组测序的塔拉海洋样本列表，包含提交至DDBJ/ENA/GenBank短读长档案库（Short Read Archive, SRA）的测序读段标识符。[本表格与第2版完全一致。]
补充表2：各样本的环境参数表。[本表格与第2版完全一致。]
补充表3：0-0.22 μm粒径组分的宏基因组组间差异矩阵。[本表格与第2版完全一致。]
补充表4：0.22-1.6/3 μm粒径组分的宏基因组组间差异矩阵。[本表格与第2版完全一致。]
补充表5：0.8-5 μm粒径组分的宏基因组组间差异矩阵。[本表格与第2版完全一致。]
补充表6：5-20 μm粒径组分的宏基因组组间差异矩阵。[本表格与第2版完全一致。]
补充表7：20-180 μm粒径组分的宏基因组组间差异矩阵。[本表格与第2版完全一致。]
补充表8：180-2000 μm粒径组分的宏基因组组间差异矩阵。[本表格与第2版完全一致。]
补充表9：0-0.22 μm粒径组分的操作分类单元（operational taxonomic unit, OTU）组间差异矩阵。[本表格与第2版完全一致。]
补充表10：0.22-1.6/3 μm粒径组分的OTU组间差异矩阵。[本表格与第2版完全一致。]
补充表11：0.8-5 μm粒径组分的OTU组间差异矩阵。[本表格与第2版完全一致。]
补充表12：5-20 μm粒径组分的OTU组间差异矩阵。[本表格与第2版完全一致。]
补充表13：20-180 μm粒径组分的OTU组间差异矩阵。[本表格与第2版完全一致。]
补充表14：180-2000 μm粒径组分的OTU组间差异矩阵。[本表格与第2版完全一致。]
补充表15：以年为单位的最小旅行时间矩阵。[本表格与第2版完全一致。]
补充表16：不跨越陆地的最小地理距离矩阵（单位：千米）。[本表格与第2版完全一致。]
补充表17：基于成像技术的组间差异矩阵。[本表格与第2版完全一致。]
补充表18：20-180 μm粒径组分的宏基因组组装基因组（metagenome-assembled genome, MAG）组间差异矩阵。[本表格的文件名相较于第2版有所修改，表格内容完全一致。]
补充表19：不同宏基因组组间差异聚类方法的cophenetic相关系数。[本表格与第2版完全一致。]
补充表20：用于比较各粒径组分聚类结果的贝克伽马指数（Baker's Gamma index）。[本表格与第2版完全一致。]
补充表21：K-means与谱聚类的兰德指数（Rand Index），以及通过adonis函数计算的多变量方差分析结果。[本表格与第2版完全一致。]

数据集1：用于对扩增子序列进行分类学注释的参考数据库（FASTA格式）。每条参考V9区核糖体DNA（rDNA）条码的标题行（以>开头）包含一个源自GenBank登录号的唯一标识符，其后跟随该参考条码对应的分类学路径。[本数据集与第2版完全一致。]
数据集2：扩增子条码水平的V9区rDNA丰度信息。包含以下字段：md5sum为唯一标识符；totab为所有样本中的总丰度；cid为该条码所属的OTU标识符（详见数据集3）；pid为与数据集1中条码的最佳匹配百分比相似度；refs为数据集1中最佳匹配条码的标识符；lineage为数据集1中最佳匹配序列的分类学谱系；taxogroup为数据集1中最佳匹配序列的高级分类学分组；sequence为V9区rDNA序列；TV9_XXX为各样本中的条码丰度（样本标识符详见补充表1）。[本数据集与第2版完全一致。]
数据集3：OTU水平的V9区rDNA丰度信息。包含以下字段：cid为OTU标识符；md5sum为该OTU中丰度最高条码的唯一标识符；pid、refs、lineage、taxogroup、sequence的定义与数据集2一致；rtotab为该OTU中丰度最高条码的总丰度；ctotab为该OTU中所有条码的总丰度；TV9_XXX为该OTU中所有条码在各样本中的丰度（样本标识符详见补充表1）。[本数据集与第2版完全一致。]
数据集4：20-180 μm粒径组分的宏基因组样本中，宏基因组组装基因组（MAG）的相对丰度。[本数据集为第3版新增内容。]