Evidence map›Paper›PMID 42389176›Full record

ArticleData in brief2026

Long-read whole-genome sequencing dataset of microbial communities from industrially and municipally impacted freshwater wetlands in South Africa.

Onyedikachi Ubani, Veronica M Ngole-Jeme

Abstract read
In one paragraph

Article in Data in brief, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Onyedikachi UbaniDepartment of Environmental Sciences, College of Agricultural and Environmental Sciences, University of South Africa, Roodeport, 1709, South Africa.
Veronica M Ngole-JemeDepartment of Environmental Sciences, College of Agricultural and Environmental Sciences, University of South Africa, Roodeport, 1709, South Africa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article describes a long-read whole-genome shotgun sequencing dataset generated from microbial communities inhabiting industrially and municipally impacted freshwater wetlands in South Africa. Surface water samples were collected from five strategically selected sites exposed to distinct anthropogenic pressures, including industrial effluent discharge, sewage overflow, greywater inputs, informal settlement runoff, and landfill leachate to generate a unique microbial genomic data. Environmental DNA was extracted and sequenced using the PacBio Sequel IIe platform, producing high-fidelity long reads suitable for improved assembly contiguity and functional reconstruction. Post-quality control processing yielded 4.9 × 10⁴ to 1.6 × 10⁵ HiFi reads per sample, corresponding to 0.34-1.02 Gb of high-accuracy sequence data per site. Long-read assemblies generated between 16,080 and 54,670 predicted protein-coding genes per sample. Taxonomic classification using Kaiju assigned 94.1-99.8% of assembled sequences to reference taxa. Domain-level profiles were exclusively bacterial dominated, with few rare or undetected (0.000-0.001%) archaeal, eukaryotic, or viral representation. Phylum-level composition was strongly dominated by

Indexed as

Environmental genomicsFreshwater wetlandsGreywater dischargeIndustrial effluent impactKaiju and DRAM pipelineLandfill leachateSewage contaminationUrban water microbiome

Identifiers

PMID42389176
PMCPMC13320488

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.