ArticleArchives of microbiology2021
A comprehensive evaluation of single-end sequencing data analyses for environmental microbiome research.
Article in Archives of microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Comparative analysis of soil prokaryotic community structure and function in Ethiopian Church Forests and adjacent habitats.Scientific reports · 2026Article
- Comparative Amplicon and Shotgun Metagenome Profiling of Soil Microbial Communities in Kauri Forests Affected by Phytophthora agathidicida.Environmental microbiology reports · 2026Article
- Microbes Under Climate Refugia: Equable Subcommunity Rank Dynamics in Large-River Deltaic Estuaries.Ecology and evolution · 2025Article
- Don't let valuable microbiome data go to waste: combined usage of merging and direct-joining of sequencing reads for low-quality paired-end amplicon data.Biotechnology letters · 2024Article
- Existence of rare actinobacterial forms in the Indian sector of Southern Ocean: 16 S rRNA based metabarcoding study.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2024Article
- Searching for bacterial plastitrophs in modified Winogradsky columns.Frontiers in microbiomes · 2024Article
- A quantitative sequencing method using synthetic internal standards including functional and phylogenetic marker genes.Environmental microbiology reports · 2023Article
- Editing efficiencies with Cas9 orthologs, Cas12a endonucleases, and temperature in rice.Frontiers in genome editing · 2023Article
- Influence of 16S rRNA reference databases in amplicon-based environmental microbiome research.Biotechnology letters · 2022Article
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1 author.
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Abstract
Illumina sequencing platforms have been widely used for amplicon-based environmental microbiome research. Analyses of amplicon data of environmental samples, generated from Illumina MiSeq platform illustrate the reverse (R2) reads in the PE datasets to have low quality towards the 3' end of the reads which affect the sequencing depth of samples and ultimately impact the sample size which may possibly lead to an altered outcome. This study evaluates the usefulness of single-end (SE) sequencing data in microbiome research when the Illumina MiSeq PE dataset shows significantly high number of low-quality reverse reads. In this study, the amplicon data (V1V3, V3V4, V4V5 and V6V8) from 128 environmental (soil) samples, downloaded from SRA, demonstrate the efficiency of single-end (SE) sequencing data analyses in microbiome research. The SE datasets were found to infer the core microbiome structure as comparable to the PE dataset. Conspicuously, the forward (R1) datasets inferred a higher number of taxa as compared to PE datasets for most of the amplicon regions, except V3V4. Thus, analyses of SE sequencing data, especially R1 reads, in environmental microbiome studies could ameliorate the problems arising on sample size of the study due to low quality reverse reads in the dataset. However, care must be taken while interpreting the microbiome structure as few taxa observed in the PE datasets were absent in the SE datasets. In conclusion, this study demonstrates the availability of choices in analyzing the amplicon data without having the need to remove samples with low quality reverse reads.
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