ArticleBMC bioinformatics2020
Joining Illumina paired-end reads for classifying phylogenetic marker sequences.
Article in BMC bioinformatics, 2020. 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.
- Refining microbiome diversity analysis by concatenating and integrating dual 16S rRNA amplicon reads.NPJ biofilms and microbiomes · 2025Article
- Untrimmed ITS2 metabarcode sequences cause artificially reduced abundances of specific fungal taxa.Applied and environmental microbiology · 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
- Improved high throughput protocol for targeting eukaryotic symbionts in metazoan and eDNA samples.Molecular ecology resources · 2022Article
- Concatenation of paired-end reads improves taxonomic classification of amplicons for profiling microbial communities.BMC bioinformatics · 2021Article
- 16S rRNA of Mucosal Colon Microbiome and CCL2 Circulating Levels Are Potential Biomarkers in Colorectal Cancer.International journal of molecular sciences · 2021Article
- 16S rRNA Gene Amplicon Sequencing Data of Tailing and Nontailing Rhizosphere Soils of Mimosa pudica from a Heavy Metal-Contaminated Ex-Tin Mining Area.Microbiology resource announcements · 2020Article
- High-Throughput Sequencing and Unsupervised Analysis of Formyltetrahydrofolate Synthetase (FTHFS) Gene Amplicons to Estimate Acetogenic Community Structure.Frontiers in microbiology · 2020Article
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Authors and funding
7 authors.
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Abstract
backgroundIllumina sequencing of a marker gene is popular in metagenomic studies. However, Illumina paired-end (PE) reads sometimes cannot be merged into single reads for subsequent analysis. When mergeable PE reads are limited, one can simply use only first reads for taxonomy annotation, but that wastes information in the second reads. Presumably, including second reads should improve taxonomy annotation. However, a rigorous investigation of how best to do this and how much can be gained has not been reported.
resultsWe evaluated two methods of joining as opposed to merging PE reads into single reads for taxonomy annotation using simulated data with sequencing errors. Our rigorous evaluation involved several top classifiers (RDP classifier, SINTAX, and two alignment-based methods) and realistic benchmark datasets. For most classifiers, read joining ameliorated the impact of sequencing errors and improved the accuracy of taxonomy predictions. For alignment-based top-hit classifiers, rearranging the reference sequences is recommended to avoid improper alignments of joined reads. For word-counting classifiers, joined reads could be compared to the original reference for classification. We also applied read joining to our own real MiSeq PE data of nasal microbiota of asthmatic children. Before joining, trimming low quality bases was necessary for optimizing taxonomy annotation and sequence clustering. We then showed that read joining increased the amount of effective data for taxonomy annotation. Using these joined trimmed reads, we were able to identify two promising bacterial genera that might be associated with asthma exacerbation.
conclusionsWhen mergeable PE reads are limited, joining them into single reads for taxonomy annotation is always recommended. Reference sequences may need to be rearranged accordingly depending on the classifier. Read joining also relaxes the constraint on primer selection, and thus may unleash the full capacity of Illumina PE data for taxonomy annotation. Our work provides guidance for fully utilizing PE data of a marker gene when mergeable reads are limited.
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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.