<b>Generation of a global freshwater algal taxonomic database by application of PCR-free </b><b><i>rbcL</i></b><b> gene detection and machine-learning-based taxonomic classification to public metagenome datasets</b>

Taxonomic Classifier:All rbcL accessions were collected from the Barcode of Life Database (BOLD) Feb 4, 2023 public release. Bacterial sequences and accessions without species assignments were removed, leaving 91,997 sequences. High-confidence and informative bacterial rbcL sequences were amended to the database. These included all rbcL collected from isolate genomes in the JGI IMG database corresponding to phylum Cyanobacteriota and all American Type Culture Collection (ATCC) strains, 565 in total. The single longest sequence for each species was utilized for classifier training (43,315 sequences) while the remaining 49,247 sequences were utilized for model validation. Training set sequences and their corresponding seven-level taxonomy were used to train a naïve-Bayes classifier operated in a qiime2-amplicon-2023.9 conda environment. To use this classifier simply follow standard operating procedures for classification of imported reads in the qiime2-amplicon-2023.9 conda environment. Note that the classifier may not function in different qiime2 versions due to varying underlying scikit versions that the environment utilizes.rbcL Database:All 4,206 assembled freshwater metagenomes in the IMG database, defined as those with the metadata tag “Ecosystem Type = Freshwater”, were delineated on February 23, 2023 and scanned for genes that had been assigned domain annotation pfam00016 by the IMG metagenome annotation pipeline. Gene nucleotide sequences were downloaded along with source genome metadata and estimated scaffold read depth metrics. Genes were classified using the constructed <i>rbcL</i><i> </i>taxonomic classifier following import into qiime2-amplicon-2023.9 operated with a minimum confidence threshold of 0.7.Table S1 includes all rbcL sequences detected in the course of the analysis, regardless of final taxonomy.Table S2 includes only rbcL sequences classified as one of the eight trained algal phyla.

分类学分类器：所有rbcL序列条目均采集自2023年2月4日公开版本的生命条形码数据库（Barcode of Life Database，BOLD）。移除细菌序列及未完成物种注释的条目后，共保留91997条序列。本数据库增补了高质量且具信息价值的细菌rbcL序列，其中包含从对应蓝细菌门（Cyanobacteriota）的联合基因组研究所综合微生物基因组数据库（Joint Genome Institute Integrated Microbial Genomes，JGI IMG）分离基因组中获取的全部rbcL序列，以及美国典型培养物保藏中心（American Type Culture Collection，ATCC）的全部菌株序列，总计565条。选取每个物种中最长的单条序列用于分类器训练（共43315条序列），剩余的49247条序列则用于模型验证。以训练集序列及其对应的七级分类学注释信息为基础，在qiime2-amplicon-2023.9的Conda环境中训练得到朴素贝叶斯（naïve-Bayes）分类器。使用该分类器时，仅需遵循qiime2-amplicon-2023.9 Conda环境中针对导入测序reads的标准分类操作流程即可。需注意，由于不同版本的qiime2所依赖的scikit库版本存在差异，该分类器在其他版本的qiime2环境中可能无法正常运行。
rbcL数据库：2023年2月23日，我们从JGI IMG数据库中筛选出4206条已组装的淡水宏基因组（元数据标签为"Ecosystem Type = Freshwater"），并通过IMG宏基因组注释流程扫描其中被注释为结构域pfam00016的基因。下载了这些基因的核苷酸序列、其来源基因组的元数据以及预测的支架测序深度指标。将这些基因导入设置了最低置信度阈值0.7的qiime2-amplicon-2023.9环境中，使用本研究构建的rbcL分类学分类器进行物种分类。补充表S1包含本分析中检测到的全部rbcL序列，无论其最终分类学注释结果如何。补充表S2仅包含被分类为8个已训练藻类门之一的rbcL序列。

搜集汇总

背景与挑战

背景概述

该数据集是一个全球淡水藻类分类数据库，通过应用PCR-free rbcL基因检测和基于机器学习的分类方法对公共宏基因组数据进行构建。数据集包含两个核心文件：Table S1记录所有检测到的rbcL序列，Table S2则筛选出分类为八个藻类门类的序列，适用于淡水生态学和宏基因组学分析。