Whole-genome sequencing, de novo assembly, and bioinformatic analysis of either pure cultures (genomics) or microbial communities (metagenomics) not only provide a detailed blueprint of the metabolic potential (genes and metabolic pathways) but is also often a prerequisite for studying gene expression patterns (transcriptomics or proteomics) and essential for high-resolution strain typing and comparative genomics.
The team behind DNASense has extensive experience within the fields of (meta)genomics, and our active involvement in state-of-the-art methods and sequencing platforms (read about it in Nature Methods) ensures that customers obtain valuable insight from our tailored bioinformatic analyses.
We offer access to both short-read Illumina (MiSeq, HiSeq, and NovaSeq) and long-read (Oxford Nanopore) DNA sequencing platforms, allowing us to tailor sequencing and bioinformatic workflows according to your specific requirements.
For reference-grade prokaryotic assemblies and metagenomic binning of prokaryotic MAGs (metagenome-assembled genomes), we currently recommend using the current Oxford Nanopore long-read chemistry (R10.4.1). This greatly improves the retrieval of high-quality, contiguous MAGs and eliminates GC-, amplification-, and loading biases (accurate abundance estimates). We do not recommend using a short read-only approach (e.g., Illumina). However, for sequencing of eukaryotes or if targeting retrieval of eukaryotic MAGs, we recommend including short read data (30-50x) for polishing of the retrieved genomes (hybrid sequencing).
If you are considering doing (meta)genomics, we encourage you to contact DNASense already during the experimental planning and design, setting the foundation for the most optimal result outcome for your project.
Our standard package includes: Optional pre- and post-project meeting with a DNASense specialist, DNA extraction, library preparation, sequencing, pre- and post-sequencing quality control, de novo assembly, taxonomic profiling, gene annotation, online-access to raw data and result files and a detailed project report.
Add-on services (non-exhaustive list): Tailored DNA extraction and purification, genome binning, SNP-calling, Functional annotation (KO, GO and KEGG), functional enrichment analysis, manual curation of metabolic pathways, gene mining, core-genome SNP analysis, multi-locus sequencing typing (MLST), custom annotation, epigenetic analysis, data submission.
For de novo assembly of prokaryotic genomes (pure culture genomics), we recommend targeting a sequencing depth corresponding to 100x assembly coverage (500 Mbp for a 5 mbp genome). For eukaryotic genomes, we recommend combining short-read Illumina data (50x) with long-read Nanopore sequencing data (50-100x). Short-read (2×150 bp) DNA sequencing will provide a high-quality but fragmented assembly (several contigs).
Depending on the question asked, we recommend a sequencing depth of 100x. If you are interested in studying a microorganism (5 Mbp genome) present at a 1 % abundance, you would need 50 Gbp data.
While it is possible and the less-biased approach, you would need a relative high sequencing depth. Instead, consider using an amplicon-based approach. It is more sensitive, and you would need less data.
If your metagenome is relatively enriched (2-10 microorganisms) we can usually bin genomes from a combination of GC content, coverage and using more advanced tSNE plots. For more diverse metagenomes, we need additional sample dimensions to separate the genome bins. This could reflect different sample timepoints or samples extracted using different methods.
To be statistical meaningful, we recommend a 50-fold read depth.
We use the Qubit high-sensitivity dsDNA assay, which is specific for double-stranded DNA. Standard spectrophotometers based on absorbance at 260 nm is generally not suitable for estimating the concentration of DNA or RNA.
For Illumina paired-end sequencing (2×150 bps) we recommend concentrations above 2 ng/µL (20 µL) but less might possible. For long-read sequencing, it depends heavily on the details. Typically, 100-2000 ng.
For low input DNA samples, we always recommend including a DNA extraction negative to assess the impact of potential kit contaminants.
It varies. For thin water-samples, we can filter large sample volumes to concentrate the biomass. For high-load biomass samples, Eppendorf-tube pellets often suffices. Whenever possible, we generally prefer to have or make a backup in case of unforeseen obstacles or challenges.
For relatively complete prokaryotic genomes with little or no contamination, we use the Genome Taxonomy Database (GTDB), which potentially provides species-level resolution. Our standard service also includes rDNA extraction and classification against the Silva SSU database (genus level for both prokaryotes and eukaryotes). Custom databases can be included (add-on service).
Our standard library preparation protocol involves sequencing native DNA. There is no amplification or tagmentation involved.
Absolutely. We recommend Nanopore as there is minimal compositional biases associated with this sequencing platform.
Nanopore sequencing yield depends on many factors pertaining to the nature of the (native) DNA being sequenced. Therefore, we cannot offer any guarantee, but we regularly generate 20-30 Gbp on a single MinION run and 100+ Gbp on PromethION flow cells.
Unless agreed otherwise, we follow a thorough community-adopted bead-beating protocol to reduce the (potentially large) DNA extraction bias (see publication). This often results in extended DNA shearing but is still compatible with the generation of very contiguous prokaryotic assemblies from long-read sequencing platforms.
It depends on the aim of your analysis. If you wish to produce closed genomes, your DNA read length distribution should be compatible with spanning the longest repeat element in your target genome. For bacteria, this is often the rRNA operon, i.e., reads should be able to span a length of 5000-7000 bp.
The raw read accuracy of Nanopore sequencing is slightly lower than Illumina but we use state-of-the-art Q20+ chemistry which achieves comparable consensus accuracies and handles homopolymers found in prokaryotes (see Nature Methods).
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For more details please check out our metagenomics / genomics product sheet