The two most commonly used methods for microbial identification and genotyping are targeted marker gene (amplicon) sequencing (e.g., prokaryotic 16S rRNA gene, eukaryotic 18S rRNA gene, and fungal ITS region) and shotgun metagenomic sequencing. The most used target gene for bacterial identification is the highly conserved 16S rRNA (or 16S rDNA), which is the gold standard in microbial genotyping [1; 2], and has been successfully used in characterizing microbial communities associated with various milieus including soil, water sources and the human gut [3].
The Bioinformatics Core Research Facility provides a 16S rRNA sequencing data analysis pipeline facilitated by snakemake workflow management system [4]. The pipeline, which is centered at DADA2 [5] and phyloseq [6] R packages in conjunction with figaro [7], mafft [8] and fasttree [9; 10] packages, can deliver
In combination with various custom R scripts, this pipeline is highly versatile, and custom graphs and statistical analysis, such as univariate and multivariate analyses for single or selected taxa, canonical correspondence analysis, table and heatmap of differentially abundant taxa from interesting contrasts, can also be provided.
In addition to the above, we also assist in the writing of methods section and addressing follow-up questions regarding the analysis. If our work contributes sufficiently to warrant co-authorships, we help prepare figures of publication-quality for manuscripts.
Some example figures are shown below from analyzing publicly available 16S sequencing data previously published by MartÃnez et al. [11] from Dr. Amanda Ramer-Tait lab at UNL’s Department of Food Science and Technology.
Relative abundance of the top 500 most abundant taxa in samples is shown below. Relative abundance is more suited to draw comparison between samples, conditions, even time points, than absolute abundance. More detailed ranks, such as order, family or species, can also be plotted if needed.