Syntrophic microbiomes associated with methane suppressive irrigation in rice
Data files
May 04, 2026 version files 6.43 MB
-
Differential_Taxa_-_Irrigation.pdf
332.22 KB
-
Differential_Taxa_-_Timepoints.pdf
369.01 KB
-
Faprotax_function.csv
11.42 KB
-
MAGs_Bins.zip
17.43 KB
-
Methane_Taxa_Correlations.zip
1.74 MB
-
README.md
8.33 KB
-
Relative_Abundance_Microbiomes.zip
2.57 MB
-
Taxonomy_Krona.zip
1.39 MB
Abstract
Rice, a staple crop of half of the world’s population, is grown predominantly in flooded paddies which is one of the largest contributors to methane emissions. An effective approach is to minimise the anaerobic flooded conditions that favour the growth of methanogenic archaea. Our findings show that controlled irrigation can reduce methane emissions by up to 90%. In addition, methane levels stayed comparatively low in plots without rice plants. The microbial communities in empty plots were compositional similar to those observed in plots with rice cultivation. Methane is produced by the anaerobic decay of organic matter. Since methane is insoluble in water, it could escape from flooded paddies via the plant aerenchyma roots. The microbial soil dynamics under both aerobic and anaerobic conditions are still not well understood. In this study, both empirical methane measurements and microbiome profiles were presented under flood and drip irrigated conditions in an outdoor field in Singapore.
Dataset DOI: 10.5061/dryad.vt4b8gv67
Study Description
This study aims to profile the methane levels and the soil microbiomes of Temasek rice (TR), Huanghuazhan (HHZ), IR64 rice varieties, and a control plot with no rice plants. The control plot is a negative blank control that provides information on the background soil microbiome and the levels of methane emissions without rice plants. All controlled irrigation trials were conducted in an outdoor rice field in Lim Chu Kang, Singapore. Rhizosphere soil samples were collected at one-month intervals during the early (2 July 2024), mid (13 August 2024), and late (10 September 2024) post-transplantation growth stages of rice for metagenomic sequencing. Any '-' represents data not available/missing.
Files and variables
File: MAGs_Bins.zip
Description:
- Data Type: Phylogenetic/Taxonomic Classification Table
- Source Tool: GTDB-Tk (Genome Taxonomy Database Toolkit)
- Description: This file provides the specific taxonomic assignment for each Metagenome-Assembled Genome (MAG). It determines what kind of organism each "Bin" represents (e.g., Nitrosotenuis) by comparing the genome against the GTDB reference database using both Average Nucleotide Identity (ANI) and phylogenetic marker gene topology.
Variable Descriptions:
- User Genome: The unique identifier for the specific MAG (Bin) being analyzed
- Classification: The final assigned taxonomy string is formatted as Domain; Phylum; Class; Order; Family; Genus; Species.
- FastANI Reference / Radius / Taxonomy:
- Used when the bin has a very high genetic similarity (ANI > 95%) to a known reference genome.
- Closest Placement Reference: The accession number of the known reference genome that is evolutionarily closest to the bin in the phylogenetic tree.
- Closest Placement Taxonomy: The taxonomy of the closest reference genome.
- Classification Method: Average Nucleotide Identity (ANI)
- MSA AA Percent: The percentage of Amino Acids in the Multiple Sequence Alignment. This indicates the quality/completeness of the marker genes found in the bin.
- RED Value: Relative Evolutionary Divergence. A metric used to normalize taxonomic ranks.
File: Faprotax_function.csv
Description: A spreadsheet containing predicted metabolic functions of the microbial community, generated using the FAPROTAX database, which maps taxonomic data to functional traits.
Variables
- #OTU ID: The unique identifier for the Operational Taxonomic Unit (microbe).
- These columns represent the normalized abundance of functional traits in specific samples. The sample IDs follow this naming convention:
- HHZDrip_2July
- HHZDrip_13Aug
- HHZDrip_10Sep
- HHZFlood_2July
- HHZFlood_13Aug
- HHZFlood_10Sep
- IR64Drip_2July
- IR64Drip_13Aug
- IR64Drip_10Sep
- IR64Flood_2July
- IR64Flood_13Aug
- IR64Flood_10Sep
- TRiceDrip_2July
- TRiceDrip_13Aug
- TRiceDrip_10Sep
- TRiceFlood_2July
- TRiceFlood_13Aug
- TRiceFlood_10Sep
- CtrlDrip_2July
- CtrlDrip_13Aug
- CtrlDrip_10Sep
- CtrlFlood_2July
- CtrlFlood_13Aug
- CtrlFlood_10Sep
File: Differential_Taxa_-_Irrigation.pdf
Description: Box plots illustrating the results of a differential abundance analysis. It identifies which specific microbial taxa differ significantly in abundance between the Drip and Flood irrigation treatments. This file highlights microbes that are enriched or depleted specifically due to water management strategies.
File: Differential_Taxa_-_Timepoints.pdf
Description: PDF document with box plots showing microbial taxa that have statistically significant changes in abundance across the three sampling dates (2 July, 13 August, and 10 September 2024). It helps identify successional patterns in the microbiome over the rice growing season.
File: Methane_Taxa_Correlations.zip
Description:
File: Genus_Taxa.txt
Data Type: Input Data Matrix (Text/Tab-delimited)
Description: This file contains the processed taxonomic abundance data aggregated at the Genus level.
Rows: Specific bacterial/archaeal genera
Columns: Sample identifiers
Values: Relative abundance or normalized counts of that genus in that sample.
File: LinearCorrelation.R
Data Type: Statistical Analysis Script (R Language)
Description: This is the code used to perform the correlation analysis.
Function: It reads the taxonomic data from Genus_Taxa.txt. It then calculates linear Pearson correlation coefficients to determine the relationship between specific microbes and methane levels.
File: Slope.xlsx
Data Type: Statistical Output (Excel)
Description: This file contains the results of the linear regression analysis defined in the R script.
Positive Slope: Indicates the taxon increases as methane increases (potentially a methanogen or an organism thriving in anaerobic conditions).
Negative Slope: Indicates the taxon decreases as methane increases (potentially a methanotroph or an organism sensitive to the anaerobic conditions that produce methane).
File: Taxonomy_Krona.zip
Description: An archive containing Krona charts. These are interactive, hierarchical sunburst diagrams in HTML files that allow users to zoom in and out of the taxonomic classification of the samples. It provides a visual overview of the community composition from the Phylum level down to the Species level for the various samples.
File: Relative_Abundance_Microbiomes.zip
Description: Relative abundance taxa classification from Phylum, Order, Family, Genus, and Species. Files are in txt format.
- Phylum.txt
- Class.txt
- Order.txt
- Family.txt
- Genus.txt
- Species.txt
These files contain count tables. For example, Species.txt lists various bacterial species found in a DNA sample and how many sequencing reads were assigned to each. Phylum.txt would contain the same data aggregated at a higher taxonomic level (e.g., Proteobacteria vs. Firmicutes).
The full taxonomy charts can be viewed in the subfolder 'MEGAN_files'. Each sample has a corresponding metagenomic (.MEGAN) extension file. This allows users to open, interact,t and plot charts across different taxonomic binning and levels in MEGAN6 software.
The filenames follow a naming convention: [Group][Condition]_[Date].megan.
A. The Groups (Rice Genotypes/Treatments)
Four distinct biological groups are being tested:
- Ctrl: Control (standard baseline of soil without rice plant).
- HHZ: Huanghuazhan, a common rice variety used in agricultural research.
- IR64: A widely used high-yielding Indica rice variety developed by the International Rice Research Institute.
- TRice: Temasek Rice bred by Temasek Life Sciences Laboratory.
B. Water Management
Each group is subjected to two different water regimes, which is a common study in rice methane emissions and microbiome dynamics:
- Drip: Drip irrigation
- Flood: Flooding
C. Date (Longitudinal Study)
The samples were taken at three specific time points during the growing season:
- 2 July: Early stage (Vegetative).
- 13 Aug: Mid-stage (Flowering).
- 10 Sep: Late stage (Maturation).
Code/software
Metagenome Analyzer (MEGAN6) software is available for download at: https://uni-tuebingen.de/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/informatik/lehrstuehle/algorithms-in-bioinformatics/software/megan6/
Files with .csv and .txt extensions can be opened in Notepad, and .xlsx files in Microsoft Excel.
Access information
Data was derived from the following sources:
- BioProject ID of PRJNA1377271, accession numbers from SRX31415382 to SRX31415405
- https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA1377271
Other publicly accessible locations of the data:
