ArticleData in brief2024
High-throughput amplicon sequencing datasets of microbial community in soils irrigated by quicklime and fly ash-treated acid mine drainage water.
Article in Data in brief, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 1 citations in OpenAlex.
- Metagenomic Tools as Predictive Approaches to Decipher Soil and Rhizosphere Microbial Communities and Their Functions for Sustainable Agriculture.International journal of genomics · 2026Review
- Article
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Authors and funding
3 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In water-stressed regions, the use of treated acid mine drainage (AMD) water for irrigated agriculture has been suggested as an alternative to address the shortage of fresh water sources. However, the short and long-term impact of using such (un)treated AMD water on soil health, particularly the microbiome structure and functional capacity, is not known. We present high-throughput amplicon sequence (HTS) datasets of purified microbial metacommunity DNA of soils under Irish potato production irrigated by quicklime and fly ash treated AMD water. The irrigation treatments included quicklime treated AMD water (A1Q and A2Q; n = 16), and quicklime and fly ash-treated AMD water (AFQ; n = 5), untreated AMD water (uAMD; n = 7) and control group using tap water (n = 5). The V1-V3 hypervariable region of the 16S rRNA gene from each sample were sequenced on an Illumina MiSeq to generate these HTS datasets. The raw sequences underwent quality-checking, demultiplexing into FASTQ files, and processing using MOTHUR pipeline (v1.40.0). Th quality reads classified into taxonomic ids (phylum, class, order, family, and genus) using the Naïve Bayesian classifier algorithm against the SILVA database (v132) and were assigned to operational taxonomic units (OTUs) based on the pairwise distance matrix (Euclidean distance matrix). The applicability of the HTS datasets was confirmed by microbial taxa at the phylum level. All HTS datasets are available through the BioSample Submission Portal under the BioProject ID PRJNA974836 (https://www.ncbi.nlm.nih.gov/bioproject/974836).
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Registered trials
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