INTRODUCTION:
Metagenomic analysis studies genetic material collected directly from the environment. Amplicon-based sequencing targets specific marker genes (e.g., 16S rRNA) to profile community composition, while shotgun sequencing captures all genomic content, providing a broader view of taxonomic and functional diversity. Metagenomics provides deep insights into ecological diversity, community structure, and functional potential by capturing and analyzing genetic material from complex ecosystems, such as the human gut, soil, and aquatic microbiomes.
ANALYSIS METHODS:
We use a variety of methods for analyzing shotgun metagenomic data. Our reproducible workflows can accommodate unique client needs using paired-end Illumina, PacBio, or Nanopore data. Our typical workflow steps may include:
- Quality Control:
- Assess the sequence read quality of each library
- Trimming to remove adapter sequences, primers, low-quality bases, and truncated reads
- Removal of potential contaminating host read sequences by alignment
- Taxonomic classification:
- Assign taxonomy to reads using K-mer and marker-based methods
- Assess alpha and beta diversity
- Functional profiling:
- Antimicrobial resistance (AMR) gene prediction
- Metabolic pathway and gene prediction
- Metagenome-assembled genomes (MAGs)
- De novo assembly
- Assignment of contigs to bins and refinement
- Quality evaluation and taxonomic classification of MAGs
We typically use QIIME2 as the preferred method for analyzing amplicon-based microbiome data. Our workflows can use single/paired-end Illumina or PacBio sequencing data. Our typical workflow steps include:
- Quality Control:
- Insert size and read quality of each library are assessed to determine potential outliers that may need to be discarded.
- Error-correction:
- Read trimming to remove sequence adapters and low-quality bases.
- Sequencing errors are removed using probabilistic model error correction.
- Dereplication to avoid redundancy sequences are collapsed to Amplicon Sequence Variants (ASVs).
- Chimera detection and removal using a consensus-based approach.
- Taxonomy classification:
- Taxonomy is assigned to ASVs using a Naive Bayes classifier previously trained using an appropriate reference database.
- Visualization of taxa abundance using boxplots and heatmaps.
- Diversity analysis:
- Alpha diversity is calculated (Chao1, Shannon, and Simpson) to assess diversity within samples and visualized as boxplots.
- Beta diversity is calculated (Bray-Curtis) to assess diversity between samples and visualized using PCoA ordination scatterplots.
- Phylogeny-based analysis is used to reconstruct phylogenetic trees.
- Rarefaction:
- Species diversity is assessed across different sequence depths using observed features and alpha diversity metrics (Chao1, Shannon, and Simpson).
- Data is visualized using rarefaction curves.
EXAMPLE OUTPUT REPORT:
Click the link to be redirected to our: Example shotgun metagenomics report and Example 16S report
SEQUENCING AND ANALYSIS GUIDELINES
Please consult with BRC staff before starting your experiments brc@biotech.wisc.edu
Free Design Consultation
We offer free consultations as part of the initial experimental design. We want to ensure that you have thought about all the necessary design components before you conduct your experiment. This way BRC has high-quality data when it comes time for us to analyze the data. We offer this service at no charge because it is more cost-effective to catch design errors before we start the analysis.
Data Analysis and General Consultation ($/hr)
We will offer custom analysis or training at our hourly rate.
Grant Support (% effort)
We can provide project-specific analysis beyond our standard pipeline services when we are written into grants. This may be a cheaper option for labs requiring a lot of analysis time as we dedicate a percent of our effort to the project.