DOI: 10.5061/dryad.76hdr7t8s
title: Data from: Controlled irrigation suppresses methane emissions by reshaping the rhizosphere microbiomes in rice

description: The rhizosphere microbiomes of rice plants under conventional flood
 irrigation consist of highly complex consortia of microorganisms, and in
 particular, methanogens purportedly associated with methane emissions
 therein. Controlled irrigation has been proposed as a cultivation method
 of choice over continuous flooding to reduce water and fertilizer usage in
 an aerobic environment. However, a systemic understanding of the assembly
 and function of microbiota in the rhizosphere under drip and flood
 irrigation remains unclear. Using empirical analyses, we report a
 significant reduction in methane emissions in controlled irrigation
 compared to the flooded environment. Genotypic or varietal differences did
 not influence such methane emissions under conventional flooded
 cultivation of rice. Using metagenomic sequencing and computational
 analyses, we provide a deeper understanding of how drip irrigation or
 continuous flooding affects the root-associated microbiomes in rice.
 Rhizosphere soil from two different rice varieties, Huanghuazhan and
 Temasek rice, grown under drip or flood conditions in a greenhouse was
 collected over 2 months post-transplantation for metagenomic analysis. Our
 results reveal that drip irrigation favours microbes involved in the
 nitrifying-denitrifying processes while continuous flooding enriches for
 methanotrophs and methanogenic archaea. Syntrophic microbiomes associated
 with methanogenesis were significantly reduced in drip irrigation. Several
 keystone taxa were evident in the co-occurrence network model related to
 methanogenic, methanotrophic, nitrifying, sulphur-oxidising and
 sulphur-reducing activities. Lastly, oxygen availability and redox
 potential were identified as key drivers that reshape rhizosphere
 microbiota and the associated metabolic functional differences observed
 between the two irrigation regimes leading up to the microbial mitigation
 of climate impact.
description: # Data from: Controlled irrigation suppresses methane emissions by
 reshaping the rhizosphere microbiomes in rice Dataset DOI:
 [10.5061/dryad.76hdr7t8s](https://doi.org/10.5061/dryad.76hdr7t8s) ##
 Study Description In this study, we assessed and characterized the soil
 microbiomes of two indica rice varieties, Huanghuazhan (HHZ, China) and
 Temasek rice (Singapore) under drip irrigation and continuous flooding
 conditions in a greenhouse. The microbiome composition and structure
 helped provide further insight on the possible microbial activities and
 metabolic functions in the soil. In addition, potential interactions among
 different microbial species/taxa were inferred using microbial
 co-occurrence network analyses. Important keystone members were identified
 to predict microbial clusters and their relation to methane emissions. HHZ
 is an elite indica rice variety from South China that is known for its
 high yield. Temasek rice is a variety bred using marker-assisted breeding
 technique performed in Singapore. Temasek rice also has high yield,
 disease resistance and submergence-tolerance traits that impart adaptation
 to various cultivation regimes and environmental conditions. Using shotgun
 metagenomics analyses, we (i) unravel the taxonomic and functional shifts
 in the root microbiomes under flood- and drip-irrigated conditions and
 (ii) identify syntrophic microbial communities that are involved in
 methane production and tropism (iii) provide insights into nutrient
 metabolism and its influence on methane emissions and/or suppression.
 Lastly, we compared the root morphology under flood and drip-irrigated
 rice systems together with a detailed analysis of the soil parameters such
 as oxidation reduction potential and pH associated with anaerobic and
 aerobic cultivation regimes. ## Files ### File: Bin_Table.csv
 **Description:** Taxonomic bins for contigs assembled from the genomic
 DNA. #### Variables **Bin ID:** The unique identifier assigned to the
 specific genomic bin by CONCOCT. **Method:** DAS Tool. **Tax:** The
 taxonomic classification of the organism found in the bin determined by
 analyzing the entire genome against a database like GTDB. **Tax 16S:** The
 taxonomic classification based specifically on 16S rRNA sequences found
 within the bin. **Length:** The total length of the genome bin in base
 pairs (bp).  **GC perc:** The Guanine-Cytosine content expressed as a
 percentage. **Num contigs**: The total number of contiguous sequences
 (contigs) or fragments that make up the bin. **Disparity:** CheckM metric
 to assess how different the tetra-nucleotide signatures are within the bin
 where a high number suggests the bin might contain DNA from multiple
 different sources. **Completeness:** An estimate percentage of how much of
 the original organism's genome is present in the bin.
 **Contamination:** An estimate percentage of foreign DNA present in the
 bin. Values over 100 could indicate contamination where the bin may
 contain multiple distinct genomes lumped together. **Strain het:** Index
 (0-100) indicating if the "Contamination" is likely due to the
 presence of closely related strains. Transcript per million (TPM) counts
 for Samples * HHZ-Drip1: Huanghuazhan Drip 1 * HHZ-Drip2: Huanghuazhan
 Drip 2 * HHZ-Flood1: Huanghuazhan Flood 1 * HHZ-Flood2: Huanghuazhan Flood
 2 * TR-Drip1: Temasek Rice Drip 1 * TR-Drip2: Temasek Rice Drip 2 *
 TR-Flood1: Temasek Rice Flood 1 * TR-Flood2: Temasek Rice Flood 2 ###
 File: Differential_taxa_list.csv **Description:** Differential taxa list
 with 513 taxa classified at the genus level and their corresponding
 *p*-value were found to be differentially enriched in flood and
 drip-irrigated soil. #### Variables **feature:** The specific microbe or
 taxonomic group being analyzed. **metadata:** "Irrigation"
 metadata used for analysis. **value:** Irrigation factor levels:
 "Flood" or "Drip". **coef:** The Coefficient (Effect
 Size). **stderr:** The Standard Error of the coefficient. **N:** The total
 number of samples included in the analysis. **N.not.0:** The number of
 samples where this microbe was actually detected. **pval:** The p-value
 (nominal significance). **qval:** The *q*-value (False Discovery Rate
 adjusted *p*-value). ### File: Faprotax_function.csv
 **Description:** Putative metabolic functions were predicted using
 Functional Annotation of Prokaryotic Taxa (FAPROTAX). Functional
 activities relating to methanogenesis, methanotrophy, methylotrophy,
 methanol oxidation, hydrocarbon and aromatic compound degradation were
 identified and were higher in continuously flooded soil. #### Variables
 **faprotax:** Functional Groups or Metabolic Pathways. Normalized read
 counts for Samples * HHZ-Drip1: Huanghuazhan Drip 1 *
 HHZ-Drip2: Huanghuazhan Drip 2 * HHZ-Flood1: Huanghuazhan Flood 1 *
 HHZ-Flood2: Huanghuazhan Flood 2 * TR-Drip1: Temasek Rice Drip 1 *
 TR-Drip2: Temasek Rice Drip 2 * TR-Flood1: Temasek Rice Flood 1 *
 TR-Flood2: Temasek Rice Flood 2 ### File: Relative_Abundance_Matrix.zip
 **Description:** Relative abundance taxa classification from Kingdom,
 Phylum, Order, Family, Genus and Species. Files are in csv format.
 **taxa:** taxon names collapsed at the following levels: *
 Kingdom_Abundance.csv * Phylum_Abundance.csv * Class_Abundance.csv *
 Order_Abundance.csv * Family_Abundance.csv * Genus_Abundance.csv *
 Species_Abundance.csv ### File: Concoct_Fasta_Files.zip
 **Description:** Concoct119 and Concoct137 are metagenome assembled
 contigs that closely match ** Methanogenic Archaea* *species. ####
 Variables * Concoct.119.fa: Assembled contig sequence for 119 taxonomic
 bin * Concoct.119.fa.tax: Taxonomic assignment for contig119. *
 Concoct.137.fa: Assembled contig 137 sequence *
 Concoct.137.fa.tax: Taxonomic assignment for contig137. ### File:
 KEGG_RPKM.csv **Description:** Metabolic functions of microbes that are
 present in drip and flood-irrigated soil were predicted by mapping the
 metagenomes to putative functions in the Kyoto Encyclopedia of Genes and
 Genomes (KEGG) database. Reads were expressed as RPKM (Reads Per Kilobase
 per Million mapped reads). #### Variables * HHZ-Drip1: Huanghuazhan Drip 1
 * HHZ-Drip2: Huanghuazhan Drip 2 * HHZ-Flood1: Huanghuazhan Flood 1 *
 HHZ-Flood2: Huanghuazhan Flood 2 * TR-Drip1: Temasek Rice Drip 1 *
 TR-Drip2: Temasek Rice Drip 2 * TR-Flood1: Temasek Rice Flood 1 *
 TR-Flood2: Temasek Rice Flood 2 ### File: Contig_Table.tsv
 **Description:**  **1. Gene Identification and Characteristics:** * **ORF
 ID and Contig ID:** These columns identify specific genetic sequences.  *
 **Method:** Prodigal tool. * **Length NT and Length AA:** These indicate
 the length of the genetic sequence in nucleotides (NT) and the
 corresponding protein in amino acids (AA). * **GC percentage:** This is
 the percentage of Guanine (G) and Cytosine. **2. Functional and Taxonomic
 Annotation:** * **Gene name:** This column provides the common name of the
 identified gene, if known. * **Tax:** This indicates the taxonomic
 classification of the organism from which the gene is thought to
 originate. * **KEGG ID, KEGGFUN, and KEGGPATH:** The Kyoto Encyclopedia of
 Genes and Genomes (KEGG) pathways. * KEGG ID is a specific identifier for
 a particular gene or protein function. * KEGGFUN describes the function of
 that gene. * KEGGPATH shows the metabolic or signaling pathways in which
 the gene product is involved. * **COG ID, COGFUN, and COGPATH:** The
 Clusters of Orthologous Groups (COG) database is another tool for
 functional annotation of proteins based on their evolutionary
 relationships. * COG ID is the identifier for a cluster of related
 proteins. * COGFUN provides a general functional category. * COGPATH
 indicates the broader functional pathway. * **PFAM:** To infer the
 function of a protein even if it has not been experimentally
 characterized. * **ARG-OAP and BACMET:** To indicate potential resistance
 mechanisms in the sampled microbial community. ## Access information Data
 was derived from the following sources: * BioProject ID of PRJNA1193822
 and accession numbers SRX26959100 to SRX26959107 - **ID:**
 **[SRX26959100](https://www.ncbi.nlm.nih.gov/sra/SRX26959100)** HHZ Rice
 Metagenome Drip Irrigation - **ID:**
 **[SRX26959101](https://www.ncbi.nlm.nih.gov/sra/SRX26959101)** HHZ Rice
 Metagenome Drip Irrigation - **ID:**
 **[SRX26959102](https://www.ncbi.nlm.nih.gov/sra/SRX26959102)** HHZ Rice
 Metagenome Flood Irrigation - **ID:**
 **[SRX26959103](https://www.ncbi.nlm.nih.gov/sra/SRX26959103)** HHZ Rice
 Metagenome Flood Irrigation - **ID:**
 **[SRX26959104](https://www.ncbi.nlm.nih.gov/sra/SRX26959104)** Temasek
 Rice Metagenome Drip Irrigation - **ID:**
 **[SRX26959105](https://www.ncbi.nlm.nih.gov/sra/SRX26959105)** Temasek
 Rice Metagenome Drip Irrigation - **ID:**
 **[SRX26959106](https://www.ncbi.nlm.nih.gov/sra/SRX26959106)** Temasek
 Rice Metagenome Flood Irrigation - **ID:**
 **[SRX26959107](https://www.ncbi.nlm.nih.gov/sra/SRX26959107)** Temasek
 Rice Metagenome Flood Irrigation * Other publicly accessible locations of
 the data: *
 [https://narrative.kbase.us/narrative/232903](https://narrative.kbase.us/narrative/232903)