Dataset Information

MTAGs: taxonomic profiling using degenerate consensus reference sequences of ribosomal RNA genes.

ABSTRACT:

Summary

Profiling the taxonomic composition of microbial communities commonly involves the classification of ribosomal RNA gene fragments. As a trade-off to maintain high classification accuracy, existing tools are typically limited to the genus level. Here, we present mTAGs, a taxonomic profiling tool that implements the alignment of metagenomic sequencing reads to degenerate consensus reference sequences of small subunit ribosomal RNA genes. It uses DNA fragments, that is, paired-end sequencing reads, as count units and provides relative abundance profiles at multiple taxonomic ranks, including operational taxonomic units (OTUs) based on a 97% sequence identity cutoff. At the genus rank, mTAGs outperformed other tools across several metrics, such as the F1 score by > 11% across data from different environments, and achieved competitive (F1 score) or better results (Bray-Curtis dissimilarity) at the sub-genus level.

Availability and implementation

The software tool mTAGs is implemented in Python. The source code and binaries are freely available (https://github.com/SushiLab/mTAGs).

Supplementary information

Supplementary information is available at Bioinformatics online. The data and analysis scripts used in this article are available at https://doi.org/10.5281/zenodo.4352762.

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Salazar G

PROVIDER: S-EPMC8696115 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Nematodes are representative soil metazoans with diverged species that play crucial roles in nutrient recycling in the pedosphere. Qualitative and quantitative information on nematode communities is useful for assessing soil quality, and DNA barcode-mediated taxonomic analysis is a powerful tool to investigate taxonomic compositions and changes in nematode communities. Here, we investigated four regions (regions 1-4) of the 18S small subunit ribosomal RNA (SSU) gene as PCR targets of deep amplicon sequencing for the taxonomic profiling of individual soil nematodes. We determined the sequence variants (SVs) of 4 SSU regions for 96 nematodes (total 384 amplicons) isolated from copse soils and assigned their taxonomy using the QIIME2 software with dada2 or deblur algorithm and the SILVA database. Dada2 detected approximately 2-fold more nematode-derived SVs than deblur, and a larger number of SVs were obtained in regions 1 and 4 than those in other regions. These results and sufficient reference sequence coverage in region 4 indicated that DNA barcoding using a primer set for region 4 followed by dada2-based analysis would be most suitable for soil nematode taxonomic analysis. Eighteen SSU-derived operational taxonomic units (rOTUs) were obtained from 68 isolates, and their orders were determined based on the phylogenetic trees built by four regional sequences of rOTUs and 116 nematode reference species as well as the BLASTN search. The majority of the isolates were derived from three major orders Dorylaimida (6 rOTUs, 51.5% in 68 isolates), Rhabditida (4 rOTUs, 29.4%), and Triplonchida (7 rOTUs, 17.6%). The predicted feeding types of the isolates were fungivores (38.2% in total nematodes), plant feeders (32.4%), and 14.7% for both bacterivores and omnivores/predators. Additionally, we attempted to improve the branch structure of phylogenetic trees by using long nucleotide sequences artificially prepared by connecting regional sequences, but the effect was limited.

Dataset Information

MTAGs: taxonomic profiling using degenerate consensus reference sequences of ribosomal RNA genes.

Summary

Availability and implementation

Supplementary information

Supplementary information

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