Metagenome-assembled genomes from soil samples in control and warming plots in Blodgett Forest, CA (2014-2021)

The pathways of carbon transport and loss through and from soils—soil organic matter (SOM) depolymerization to dissolved organic carbon and mineralization to carbon dioxide (CO2)—are fundamentally driven by microbial activity, which is strongly regulated by environmental conditions. As part of LBNL (Lawrence Berkeley National Laboratory) TES (Terrestrial Ecosystem Science) Belowground Biogeochemistry Science Focus Area (SFA), we have established a novel whole-soil long-term warming experiment at the University of California (UC) Blodgett Forest Research Station (Sierra Nevada) in 2014, where we study the role of biogeochemical, microbial and geochemical process interactions in SOM decomposition and stabilization. Here, we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community from soil depth profiles collected from 2014 to 2021 from three paired control and warming plots. We collected soil samples across a range of depth profiles (spanning surface to 90 cm deep) from three paired control and warming plots from a temperate mixed forest in Northern California. Each paired plot had been subjected to experimental warming since June 2014 to simulate a predicted climate change scenario for northern California. 101 soil metagenomes were sequenced at JGI (Joint Genome Institute) and UCSF (University of California San Francisco) Center for Advanced Technology and can be found under the JGI (Joint Genome Institute) GOLD (Genomes Online Database) Sequencing project Gs0151586 and NCBI (National Center for Biotechnology Information) Projects PRJNA1225762 and PRJEB39497. Metagenomes were assembled using JGI (Joint Genome Institute) Metagenome Workflow (10.1128/mSystems.00804-20). For each metagenome, the assembled contigs were binned into genomes using 3 binning algorithms (cocacola, metabat, and maxbin) and the resulting bins were consolidated using dastool. The consolidated bins from all metagenomes were pooled, filtered by completeness (>50%) and contamination (<25%), and dereplicated at 99% ANI (average nucleotide identity) using dRep (https://github.com/MrOlm/drep). The dataset includes a zip file of 2321 MAG (Metagenome Assembled Genome) fasta files, the accession numbers for the underlying metagenomes, and a csv file with MAG (Metagenome Assembled Genome) quality metrics and taxonomic classification (GTDB -Genome Taxonomy Database-RS220). This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. A sample metadata file (samples.csv) that contains site information has also been included.

土壤碳运输与流失的路径——土壤有机质（Soil Organic Matter, SOM）解聚为溶解性有机碳、矿化为二氧化碳（Carbon Dioxide, CO₂）——本质上由微生物活动驱动，而微生物活动受环境条件的强烈调控。作为劳伦斯伯克利国家实验室（Lawrence Berkeley National Laboratory, LBNL）陆地生态系统科学（Terrestrial Ecosystem Science, TES）地下生物地球化学科学聚焦区（Science Focus Area, SFA）的研究内容之一，我们于2014年在加利福尼亚大学（University of California, UC）布洛杰特森林研究站（内华达山脉地区）建立了一项全新的全土壤长期增温实验，旨在探究生物地球化学、微生物与地球化学过程的相互作用在土壤有机质分解与稳定中的作用。本研究针对2014年至2021年间从三组配对对照与增温样地的土壤深度剖面中采集的样本，解析其中细菌与古菌群落的宏基因组组装基因组（Metagenome-Assembled Genomes, MAGs）。我们从加利福尼亚北部温带混交林的三组配对对照与增温样地中，采集了覆盖地表至90厘米深度的一系列土壤剖面样本。自2014年6月起，每组配对样地便持续接受实验增温，以模拟加利福尼亚北部预测的气候变化情景。101份土壤宏基因组于联合基因组研究所（Joint Genome Institute, JGI）与加利福尼亚大学旧金山分校（University of California San Francisco, UCSF）先进技术中心完成测序，相关数据可在联合基因组研究所基因组在线数据库（Genomes Online Database, GOLD）测序项目Gs0151586，以及美国国家生物技术信息中心（National Center for Biotechnology Information, NCBI）项目PRJNA1225762和PRJEB39497中获取。宏基因组组装采用联合基因组研究所宏基因组工作流（JGI Metagenome Workflow, 10.1128/mSystems.00804-20）完成。针对每份宏基因组，我们使用三种分箱算法（cocacola、metabat与maxbin）将组装得到的重叠群（contigs）聚类为基因组，随后通过DAStool对所得分箱结果进行整合。将所有宏基因组的整合分箱结果合并后，我们按照完整性（>50%）与污染率（<25%）进行筛选，并通过dRep以99%平均核苷酸一致性（Average Nucleotide Identity, ANI）完成去冗余。本数据集包含2321个宏基因组组装基因组（Metagenome-Assembled Genome, MAG）的FASTA格式压缩包、对应宏基因组的登录号，以及一份包含宏基因组组装基因组质量评估指标与分类学注释（基于基因组分类数据库-RS220版本，Genome Taxonomy Database-RS220, GTDB-RS220）的CSV文件。本数据集还包含一份文件级元数据文件（"flmd.csv"），该文件列出了数据集内所有文件及其关联元数据；此外还有一份数据字典文件（"dd.csv"），其中包含所有文件中使用的列/行表头及其定义、单位与数据类型。一份包含样地信息的样本元数据文件（"samples.csv"）也已纳入本数据集。